The Molecular and Physiological Basis of Nutrient Use Efficiency in Crops

The Molecular and Physiological Basis of Nutrient Use Efficiency in Crops The Molecular and Physiological Basis of Nut...

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The Molecular and Physiological Basis of Nutrient Use Efficiency in Crops

The Molecular and Physiological Basis of Nutrient Use Efficiency in Crops Edited by

Malcolm J. Hawkesford Peter Barraclough

A John Wiley & Sons, Inc., Publication

This edition first published 2011 © 2011 by John Wiley & Sons, Inc. Wiley-Blackwell is an imprint of John Wiley & Sons, formed by the merger of Wiley’s global Scientific, Technical and Medical business with Blackwell Publishing. Registered office: John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK Editorial offices: 2121 State Avenue, Ames, Iowa 50014-8300, USA The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK 9600 Garsington Road, Oxford, OX4 2DQ, UK For details of our global editorial offices, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com/wiley-blackwell. Authorization to photocopy items for internal or personal use, or the internal or personal use of specific clients, is granted by Blackwell Publishing, provided that the base fee is paid directly to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923. For those organizations that have been granted a photocopy license by CCC, a separate system of payments has been arranged. The fee codes for users of the Transactional Reporting Service are ISBN-13: 978-0-8138-1992-1/2011. Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher is not associated with any product or vendor mentioned in this book. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold on the understanding that the publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought. Disclaimer The publisher and the author make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation warranties of fitness for a particular purpose. No warranty may be created or extended by sales or promotional materials. The advice and strategies contained herein may not be suitable for every situation. This work is sold with the understanding that the publisher is not engaged in rendering legal, accounting, or other professional services. If professional assistance is required, the services of a competent professional person should be sought. Neither the publisher nor the author shall be liable for damages arising herefrom. The fact that an organization or Website is referred to in this work as a citation and/or a potential source of further information does not mean that the author or the publisher endorses the information the organization or Website may provide or recommendations it may make. Further, readers should be aware that Internet Websites listed in this work may have changed or disappeared between when this work was written and when it is read. Library of Congress Cataloging-in-Publication Data The molecular and physiological basis of nutrient use efficiency in crops / edited by Malcolm J. Hawkesford, Peter Barraclough. p. cm. Includes bibliographical references and index. ISBN-13: 978-0-8138-1992-1 (hard cover : alk. paper) ISBN-10: 0-8138-1992-X (hard cover : alk. paper) 1. Crops—Nutrition. 2. Crops—Nutrition—Molecular aspects. 3. Crops—Nutrition—Physiology. 4. Plant nutrients. 5. Crop yields. I. Hawkesford, Malcolm J. II. Barraclough, Peter (Peter B.) SB112.5.M65 2011 631.8–dc23 2011019195 A catalogue record for this book is available from the British Library. This book is published in the following electronic formats: ePDF 9780470960677; Wiley Online Library 9780470960707; ePub 9780470960684; Mobi 9780470960691 Set in 10/12 pt Times by Toppan Best-set Premedia Limited The cover includes a photograph of the Broadbalk field at Rothamsted Experimental Station in southern England in 2003. The Broadbalk wheat experiment was established in 1842 and is the oldest continuous agricultural experiment in the world. The aim was to compare the efficacy of new synthetic inorganic fertilisers with organic manures and to rank plant nutrients for their effects on yield. The effects of nutrient deficiencies can clearly be seen in the photograph. Yields and soil and plant analyses have been recorded and samples archived since the start. The experiment is continually updated to reflect modern farming practice. Short-straw wheat is now grown continuously and in rotation, with and without crop protection chemicals, on plots having no nutrient inputs, plots with established mineral deficiencies, and plots testing rates and forms N including organic and inorganic sources. It has been used to quantify nitrogen balances in crop production including losses by leaching and de-nitrification. More recently it has been used to examine the impact of nutrition on wheat grain quality (Godfrey et al., 2010, Journal of Agricultural Food Chemistry 58, 3012–3021), and for the identification of nutrient-related genes through grain transcriptome analysis (for examples, Lu et al., 2005 Proceedings of the Royal Society, Series B 272, 1901–1908). Photograph taken by Richard F. Wallis Photography and used by permission of Rothamsted Research. 1

2011

Contents

Preface

vii

Contributors

ix

Part I:

3

Chapter 1

Generic Aspects of Crop Nutrition An Overview of Nutrient Use Efficiency and Strategies for Crop Improvement Malcolm J. Hawkesford

5

Chapter 2

Crop Root Systems and Nutrient Uptake from Soils Peter J. Gregory

21

Chapter 3

The Role of the Rhizosphere in Nutrient Use Efficiency in Crops Petra Marschner

47

Chapter 4

Optimizing Canopy Physiology Traits to Improve the Nutrient Utilization Efficiency of Crops M. John Foulkes and Erik H. Murchie

Chapter 5

Senescence and Nutrient Remobilization in Crop Plants Per L. Gregersen

Chapter 6

Effects of Nitrogen and Sulfur Nutrition on Grain Composition and Properties of Wheat and Related Cereals Peter R. Shewry

Part II:

Nitrogen as a Key Driver of Production

65 83

103

121

Chapter 7

Genetic Improvement of Nutrient Use Efficiency in Wheat Jacques Le Gouis

123

Chapter 8

The Molecular Genetics of Nitrogen Use Efficiency in Crops Bertrand Hirel and Peter J. Lea

139 v

vi

CONTENTS

Chapter 9

Biotechnological Approaches to Improving Nitrogen Use Efficiency in Plants: Alanine Aminotransferase as a Case Study Allen G. Good and Perrin H. Beatty

Chapter 10

Transporters Involved in Nitrogen Uptake and Movement Anthony J. Miller and Nick Chapman

Chapter 11

Crop Improvement for Nitrogen Use Efficiency in Irrigated Lowland Rice Shaobing Peng

Part III:

Other Critical Macro- and Micronutrients

Chapter 12

Phosphorus as a Critical Macronutrient Carroll P. Vance

Chapter 13

Uptake, Distribution, and Physiological Functions of Potassium, Calcium, and Magnesium Frans J.M. Maathuis and Dorina Podar

Chapter 14

Sulfur Nutrition in Crop Plants Luit J. De Kok, Ineke Stulen, and Malcolm J. Hawkesford

Chapter 15

Iron Nutrition and Implications for Biomass Production and the Nutritional Quality of Plant Products Jean-François Briat

Chapter 16

Zinc in Soils and Crop Nutrition Behzad Sadeghzadeh and Zed Rengel

Chapter 17

Overview of the Acquisition and Utilization of Boron, Chlorine, Copper, Manganese, Molybdenum, and Nickel by Plants and Prospects for Improvement of Micronutrient Use Efficiency Patrick H. Brown and Elias Bassil

Part IV:

Specialized Case Studies

165 193

211

227 229

265 295

311 335

377

429

Chapter 18

Drought and Implications for Nutrition Eric Ober and Martin A.J. Parry

Chapter 19

Salt Resistance of Crop Plants: Physiological Characterization of a Multigenic Trait Sven Schubert

443

Legumes and Nitrogen Fixation: Physiological, Molecular, Evolutionary Perspectives, and Applications Muthusubramanian Venkateshwaran and Jean-Michel Ané

457

Chapter 20

Index

431

491

Preface

Achieving global food security is a major challenge for plant biology. Crop improvement including efficient nutrient use is required to meet increasing demands to feed the world population with sustainable agricultural systems. This volume both summarizes the current state of knowledge and anticipates directions of future research and prospects for crop improvement in the area of efficient use of nutrients. An overview describing the principles and scope of the problems relating to efficient nutrient use is provided, with invited experts contributing specialist chapters. These are divided into four sections, covering generic aspects of crop nutrition, a focus on nitrogen as the key driver of production, contributions on all the other major nutrients, and finally a section containing specialist topics including abiotic stresses and legume nitrogen fixation. Substantial advances have been made recently at the molecular and genetic levels in terms of understanding plant function. In parallel, increases in nutrient use efficiency have arisen through successful breeding for yield and through better agronomic prac-

tices. The aim of this volume is to place current molecular studies in the context of the important agronomic trait of efficient nutrient use, bridging academic advances to practical application. Understanding the molecular basis of nutrient use efficiency is fundamental for targeting improvements in this complex trait. Selecting for yield has improved nitrogen use efficiency specifically, but in recent years selection has mostly been at high inputs. There is increasing pressure to decrease inputs while maintaining or improving productivity. In addition, in many agricultural systems, inputs are low or nonexistent and require germplasm quite different from intensively managed systems. There is a real concern that alleles for efficient scavenging of nutrients may have been lost in breeding programs for some crops. Worldwide there are many plant nutrition issues that impact on yield and food security, and in all cases, increased basic knowledge will contribute to solutions. It is essential to consider the problem at all levels, and place molecular knowledge, often detailed at the cellular level, into the context of whole-plant physiology and even in terms of crops in the vii

viii

PREFACE

agro-ecosystem. This volume attempts to synthesize the complexity of the underpinning mechanisms, alongside an appreciation of the systems in which they operate. As such, it is hoped that it will be useful to scientists and students involved in plant nutrition research as well as to plant breeders and biotechnologists

who are responsible for delivery of new germplasm. Malcolm J. Hawkesford Peter Barraclough Rothamsted Research May 2011

Contributors

Jean-Michel Ané Department of Agronomy University of Wisconsin Madison Madison, WI

Patrick H. Brown Department of Plant Sciences University of California-Davis Davis, CA

Peter Barraclough Rothamsted Research Harpenden, Hertfordshire UK

Nick Chapman Rothamsted Research Harpenden, Hertfordshire UK

Elias Bassil Department of Plant Sciences University of California-Davis Davis, CA

Luit J. De Kok Centre for Ecological and Evolutionary Studies University of Groningen Groningen The Netherlands

Perrin H. Beatty Department of Biological Sciences University of Alberta Edmonton, Alberta Canada Jean-François Briat Centre National de la Recherche Scientifique Université Montpellier 2 Montpellier France

M. John Foulkes Division of Plant and Crop Sciences University of Nottingham School of Biosciences Leicestershire UK Allen G. Good Department of Biological Sciences University of Alberta Edmonton, Alberta Canada ix

x

CONTRIBUTORS

Per L. Gregersen Department of Genetics and Biotechnology Aarhus University Denmark Peter J. Gregory East Malling Research East Malling, Kent UK and Centre for Food Security University of Reading Reading UK Malcolm J. Hawkesford Rothamsted Research Harpenden Hertfordshire UK Bertrand Hirel Département Adaptation des Plantes à leur Environnement Institut National de la Recherche Agronomique Route de Saint-Cyr Versailles France Jacques Le Gouis INRA / UBP UMR 1095 Génétique, Diversité et Ecophysiologie des Céréales Clermont-Ferrand France and Diversité et Ecophysiologie des Céréales Université Blaise Pascal Aubière France

Peter J. Lea Lancaster Environment Centre Lancaster University Lancaster UK Frans J.M. Maathuis Biology Department Area 9 University of York York UK Petra Marschner School of Agriculture, Food and Wine The University of Adelaide Adelaide Australia Anthony J. Miller Department of Disease and Stress Biology John Innes Centre Norwich Research Park Colney, Norwich UK Erik H. Murchie Division of Plant and Crop Sciences University of Nottingham Leicestershire UK Eric Ober Rothamsted Research Harpenden Hertfordshire UK Martin A.J. Parry Rothamsted Research Harpenden Hertfordshire UK

CONTRIBUTORS

Shaobing Peng Crop Physiology and Production Center College of Plant Science and Technology Huazhong Agricultural University Wuhan, Hubei P.R. China

Peter R. Shewry Rothamsted Research Harpenden Hertfordshire UK

Dorina Podar Department of Experimental Biology Faculty of Biology-Geology Babes-Bolyai University Cluj-Napoca Romania

Ineke Stulen Laboratory of Plant Physiology Centre for Ecological and Evolutionary Studies (CEES) University of Groningen Groningen The Netherlands

Zed Rengel Soil Science and Plant Nutrition School of Earth and Environment, University of Western Australia Crawley WA Australia

Carroll P. Vance USDA/Agricultural Research Service Plant Science Research Unit Agronomy and Plant Genetics University of Minnesota St. Paul, MN

Behzad Sadeghzadeh Dryland Agricultural Research Institute (DARI) Maragheh Iran

Muthusubramanian Venkateshwaran Department of Agronomy University of Wisconsin Madison Madison, WI

Sven Schubert Institute of Plant Nutrition Interdisciplinary Research Center for Environmental Research, (IFZ) Justus-Liebig-Universität Giessen Germany

xi

Part I

Generic Aspects of Crop Nutrition

Chapter 1

An Overview of Nutrient Use Efficiency and Strategies for Crop Improvement Malcolm J. Hawkesford

Abstract

Introduction

Understanding the molecular basis of crop nutrient use efficiency is a prerequisite for genetic improvement aimed at maximizing yield and minimizing inputs. Plant breeding has been hugely successful at developing high yielding varieties, albeit often with high nutrient requirements. In addition, substantial progress has been made in improving nutrient use efficiency in terms of agronomic practice. Recent developments in genetic and genomic resources, combined with existing physiological and biochemical knowledge, should facilitate substantial further genetic improvements targeted at yield increase and efficient resource utilization. However, this is not a trivial task, given the complexity of the plant systems involved: The traits need to be defined and resolved into specific processes, and appropriate genetic targets need to be identified. This overview considers some issues relating to likely traits, the potential molecular basis of the traits, and potential routes for improvement.

The major challenge facing plant biology is to improve crop production to feed an expanding world population. This is against a background of pressure on agricultural land use and climate change having negative impacts on growing conditions and limiting geographic regions for agriculture (Parry and Hawkesford, 2010). The adverse effects of agriculture, and specifically fertilizer use, include damage to the environment, a large carbon footprint for the manufacture and use of agrochemicals, and the utilization of nonrenewable resources. One solution is to increase the area of land for agriculture, as well as increasing production while maintaining the current rate of inputs; however, this is predicted to have substantial negative impacts on the environment (Tilman et al., 2001; Tilman et al., 2002), is unsustainable in terms of phosphate use, and would have a huge economic footprint in terms of energy demands for nitrogenous fertilizer production. The challenge is to increase yield, decrease inputs, and improve resistance to

The Molecular and Physiological Basis of Nutrient Use Efficiency in Crops, First Edition. Edited by Malcolm J. Hawkesford, Peter Barraclough. © 2011 John Wiley & Sons, Inc. Published 2011 by John Wiley & Sons, Inc. 5

6

NUTRIENT USE EFFICIENCY IN CROPS

abiotic and biotic stresses. Improving crop nutrient use efficiency ideally requires an understanding of the whole system, from the macro- (agro-ecosystem) to the molecular level. While acknowledging the critical contribution of agronomy to improving efficient nutrient use, particularly in classically inefficient systems, there is a point at which crop genetic improvement becomes essential for further improvement. This may be achieved by conventional breeding, as indeed has been the case to the present day with ever increasing yields, albeit often in parallel with increased nutrient demands, with marker-assisted breeding utilizing genetic information derived from basic plant science, and by the utilization of this same information to produce genetically modified crops. Nutrients, along with light, temperature, and water, are critical determinants of crop production, but fertilizers are costly inputs and inappropriate overuse can have many ecologically damaging effects, making efficient use of fertilizers a major issue for agriculture. For example, excessive nitrogen use results in a major fraction of anthropogenic nitrous oxide and methane emissions, which contribute substantially to climate change, and inefficient nutrient uptake may result in pollution of inland and coastal waters by leaching and runoff. Worldwide, it has been estimated that nitrogen use efficiency (NUE) for cereal production is only 33% (nitrogen removed in grain as a percentage of that applied) (Raun and Johnson, 1999). Both agronomic practice and plant breeding have a responsibility to optimize efficient nutrient use, particularly nitrogen, in crop systems. Furthermore, crop improvements to anticipate changing patterns of rainfall and temperature must include an anticipation of nutritional demands influenced by changing cropping systems and crop ideotypes. Optimal plant growth demands a balanced nutrient supply, with a deficiency of any individual essential nutrient having a

detrimental effect on production (law of the minimum). Some nutrients are required at high levels (the macronutrients nitrogen, phosphorus, potassium, and sulfur; see Chapters 8–14), while others are only required at low levels (the micronutrients: iron, zinc, magnesium, etc., see Chapters 15, 16, and 17). In some cases, excess or luxury accumulation of nutrients in plant organs is an issue, negatively impacting on crop growth or quality for the consumer. Agricultural production systems have a range of demands for nutrients; low input as compared with intensive highly managed systems will have different issues and the solutions will be specific for each system. Solutions for efficient fertilizer capture and conversion to biomass or yield in high-input agriculture will be quite different from targets in extensive, organic, or low-input agriculture. In recent years, the emphasis has alternated from a primary objective of improving yields (a target that has always been present in all but the most productive environments) to minimizing impacts on the environment (especially in intensively cropped systems), and back to yield in order to achieve global food security. In the 21st century, sustainable food production has become a major issue with a growing world population, negative impacts of climate change, and demands on land use. To optimize progress on crop improvement, an understanding of nutrient use efficiency from the agronomic or agro-ecosystem level down to the molecular level (the genes involved and their regulation) is required. Substantial progress is being made on the functions and regulation of genes and proteins; molecular data are usually interpreted at the cellular level; however, it is essential that this understanding is placed at the organ, plant, and whole-crop levels. Targets for improvement need to take into account the different agricultural systems, crop physiology and yield components, and the demands

AN OVERVIEW OF NUTRIENT USE EFFICIENCY

of the consumer. Safe, sustainable, and secure food, feed, fiber, and fuel production will demand optimized genetic material including the trait of nutrient use efficiency. Yield and fertilizers: the need for crop improvement

7

in more recent years, there have been incrementally smaller improvements in theoretically achievable yields. In some cases, theoretical yields may not be achievable due to limiting fertilizer application. Theoretical, record, and average (wheat) yields are approximately 18, 16, 8 (in the United Kingdom), and 3 t ha−1 (worldwide), respectively.

Meeting the yield potential Plant breeding has resulted in considerable increases in yield for many crops (for example: maize [Evans and Fischer, 1999], wheat [Ortiz-Monasterio et al., 1997; Brancourt-Hulmel et al., 2003], sugar cane [Robinson et al., 2007]), with the principal target being resistance to biotic and abiotic stresses, as well as for yield itself. Yield is a good measure of nutrient use efficiency, especially as related to nitrogen (Barraclough et al., 2010): The definition of NUE is grain or total biomass (depending on crop) yield divided by available nutrient (see Table 1.1). Theoretical or best yields are seldom achieved in practice as production field conditions are seldom as ideal as breeding plots, which have optimum inputs and agronomy (Fig. 1.1A). This discrepancy is inevitable as the “yield gap” is usually reported on a national level and will encompass growth of varieties in a range of conditions and environments (Austin, 1999; Fischer and Edmeades, 2010). Including traits for resistance to as many stress factors as possible, for example, drought (Chapter 18) and salinity stress (Chapter 19) in breeding programs, will narrow this gap but is unlikely ever to close it. Breeding for resistance to stress, as well as yield, is a key target for crop improvement (Araus et al., 2008). A greater issue is the observed plateau of yield improvements, probably due to abiotic and biotic stress. Initial large improvements in wheat yields were brought about by introduction of dwarfing genes and the consequent improvement in (grain) harvest index (HI). However,

Nutrient response curves As already stated, most plant breeding is performed under “ideal” conditions, which usually include high fertilizer inputs. Nutrient use efficiency has seldom been a key target; however, yield and NUE are closely related at a given fertilizer input. Nutrient use efficiency is the product of both uptake and utilization efficiencies (see the next sections for fuller descriptions), and therefore selecting for yield effectively selects for the combination of these two very separate traits. Small improvements, or even negative trends in one trait (most likely acquisition or uptake), may be hidden by gains in the other (in this case, utilization efficiency). Therefore, selecting for yield alone may not select for optimal nutrient acquisition characteristics, especially at reduced inputs or in environments with specific nutrient deficiencies. It is obvious that maximum acquisition is determined by availability; however, the efficiency of scavenging mechanisms will have a substantial impact on acquisition, although this may not be sustainable in the long term in any single location if nutrients are being mined and not replaced. Traits that will contribute to efficient acquisition are mainly root-associated properties for which there are immense practical difficulties for assessment. A simple approach is to determine overall nutrient capture (nutrient uptake), which integrates the separate features of root architecture and function contributing to this trait (see below for details on the dissection of this trait),

8 Term Fertilizer use efficiency Nutrient (usually nitrogen) use efficiency Nutrient (usually nitrogen) uptake efficiency Nutrient (usually nitrogen) utilization efficiency Harvest index

Nutrient (usually nitrogen) harvest index

Nitrogenagronomic efficiency Apparent recovery efficiency

Abbreviation

FUE

NUE

NUpE

NUtE

HI

NHI

NAE

ARE

kg kg−1

NUp/nitrogen applied as fertilizer

Yield with fertilizer minus yield without nitrogen applied

Fraction of nutrient harvested fraction (e.g., grain)/nutrient in total aboveground biomass (e.g., grain + straw)

Mass of harvested fraction (e.g., grain)/ total aboveground biomass (e.g., grain + straw)

Improvement in yield for fertilizer applied

kg kg−1 kg kg−1

Measure of partitioning of nutrient to harvested fraction of biomass

fraction

Measure of partitioning of yield to harvested fraction of biomass

Also NAPE (agrophysiological efficiency)

kg kg−1

NUp/Nav (soil + fertilizer)

fraction

Also NPE (physiological efficiency)

kg kg−1

NUpE × NUtE = yield/N available

Yield/NUp

% of applied fertilizer recovered by crop NUE is closely related to yield at a given nutrient input

%

(NUp/N applied) × 100

Notes

Unit

Formula

Table 1.1. Some definitions of NUE, mostly used with respect to nitrogen


A yield

theoretical achieved

year to present B

Variety 1

yield

Variety 2

9

tilization with any limiting nutrient will improve yield. The tendency for yields to reach a plateau as shown for nitrogen in Figure 1.1B are indicative of secondary limiting factors being present, which may be other nutrients, or may be due to constraints with conversion to harvestable biomass (limiting photosynthesis). A consequence of this plateauing is decreased NUE, specifically attributable to the nitrogen utilization efficiency component (see below). Yield quality conundrum

increasing nitrogen fertilizer

protein content

C

high medium

fertilizer application

low

yield Schematic yield trends and relationships with nutrient inputs. (A) Yield improvements in recent years (second half of the 20th century onward), showing theoretical yield improvements delivered by breeders under ideal growing conditions and those typically achieved on farms. (B) Possible theoretical nitrogen response curves for two varieties, where variety 1 outperforms variety 2 (increasing nitrogen inputs further often results in a down trend of this curve) at all nitrogen inputs. (C) The inverse relationship between yield and nutrient content, in this case nitrogen content expressed as protein content, at three fertilizer levels. Fig. 1.1.

but this is not ideal as selection for the component traits is not achieved. There is little data to indicate whether best uptake performance as selected at high inputs equates to best performance at low inputs. Increasing inputs of nitrogen fertilizer will, in the absence of other limiting nutrients or environmental constraints, result in increasing yield (Fig. 1.1B). Similarly, fer-

In many crops, including grain crops, yield is determined by photosynthetic carbohydrate production and storage. As a consequence, as yield is increased, other nutritional components are often diluted as is seen for the protein content in grain (Fig. 1.1C; Monaghan et al., 2001). Similarly, reduced micronutrient concentrations in grain will occur as a result of dilution with starch. Outliers to the regression relationship between yield and quality shown in Figure 1.1C at any defined nutrient (nitrogen in this case) input must have particularly efficient acquisition and/or partitioning mechanisms. It has been suggested that postanthesis nitrogen uptake is an important contributory mechanism (Monaghan et al., 2001; Kichey et al., 2007; Bogard et al., 2010), although the molecular and genetic basis for this has not been determined. It may be assumed that deep rooting systems, which have access to untapped nutrient reserves at depth in the soil profile, may be important, along with mechanisms to ensure that such nutrients that are taken up are preferentially allocated to the harvested sink material. The diversity of inputs to cropping systems Agricultural systems span a wide range of inputs from none (organic), through extensive (low input), to intensively farmed (high-input)

10


systems. These different situations present quite different challenges in terms of the ideal germplasm required. Targeting improvement of nutrient use efficiency needs to take into account these contrasting agro-ecosystems, the associated agronomic practices, and end-product requirements (e.g., bread vs. feed wheat). In some cases, it is clear that substantial improvements in NUE can be achieved through improved agronomic practice alone. Genetic improvements are likely to be small and incremental by comparison. In low and no input systems, with ever more nutrient capture-efficient varieties, there is a danger of “mining” reserves, leaving land completely unproductive; here the target for genetic improvement needs to be low-nutrient-requiring genotypes combined with improved agronomy to supply minimal nutrition. In many extensive systems, where fertilizers are applied at seed sowing, improved early capture is a critical phenotype. In intensive, high-input systems, conversion to biomass is the principal concern, along with minimization of losses from the system from overfertilization or inappropriate application. Nutrient use efficiency: critical processes, definitions, mechanisms, and targets for improvement Within the broad concept of nutrient use efficiency and depending on the nutrient in question, many definitions of efficiency are possible (see Table 1.1). In this work, depending on the nutrient involved, authors use their own definitions, but in all cases these are clearly stated. Table 1.1 lists many of the common definitions of efficient nutrient and fertilizer use. As already indicated, efficient use of any nutrient comprises two fundamental aspects: acquisition efficiency and utilization efficiency (see also Fig. 1.2). For the target of improving crop nutrient use

efficiency, it is important to separate the individual processes and identify the respective genes involved, monitoring improvements with the appropriate physiological measures. Resolving NUE into two component traits, nitrogen uptake efficiency (NUpE) and nitrogen utilization efficiency (NUtE), is a first step to resolving the complexity, and subsequently each of these traits can be subdivided into many specific physiology traits, each of which are complex traits in itself, the result of networks of biochemical pathways, encoded by multiple genes and subject to complex regulatory processes (Figs. 1.2 and 1.3; Nikiforova et al., 2005; Gojon et al., 2009). Acquisition efficiency and root architecture Nutrient capture (NUpE) is essentially a root trait, although to be fully expressed, it also requires adequate sinks for temporary storage or final deposition of the nutrients. Efficient acquisition will depend first on root architecture (see Chapter 2), root functions in terms of transporters and exudates(Chapter 10), and often the presence of symbiotic associations such as mycorrhiza (Chapters 3 and 12). As indicated in Figure 1.2, early root establishment is essential for scavenging soil nutrients prior to the application of fertilizer, or alternatively to capture fertilizer applied at the time of sowing. Nutrients will be immediately available in the soil solution, and further availability will be depend on mineralization of organic matter and release from sparingly soluble soil minerals (oxides, clays, etc.). High activity of the high-affinity transporter systems required for uptake into root cells, expressed in the plasma membranes of cells of roots, root tips, root hairs, or in associated organisms (mycorrizha), will be important in this situation as diffusion of nutrients through soil is the rate-limiting factor. In addition, a


11

Yield: photosynth etic activity, canopy architecture, canopy longevity, and senescence

Canopy establishment and photosynthesis in seedling

Canopy development and setting of yield potential

Nutrient export, patritioning, HI, and NHI

Early root establishment

Nutrients and water

Architecture/ proliferation/activity: •shallow roots for intercepting fertilizers •deep roots for accessing deep resources

Parameters influencing components of nutrient use efficiency at the crop plant level. Both nutrients and water acquisition depend on root architecture and function. The developing canopy will determine yield; however, for grain crops, nutrient (particularly nitrogen) redistribution from the canopy to the grain (essential for efficient nutrient use and for quality attributes) will negatively affect photosynthesis and limit yield.

Fig. 1.2.

well-developed shallow root system will be ideal for intercepting further applications of fertilizer. Deeper roots assume importance with the depletion of surface nutrients, as water near the surface becomes limiting and restricts uptake of nutrients, or in the case of high water supply, for the interception of nutrients that would be potentially leached from the soil profile. In some cases, local proliferation of roots in response to nutrient supply is observed (Drew and Saker, 1978), controlled by specific transcription factors (Zhang and Forde, 1998; Forde 2002). An alternative approach to enhancing capture mechanisms (root architecture and

function) to improve acquisition is to enhance mechanisms for increasing bioavailability of nutrients (e.g., for phosphorus by acid secretions, see Chapters 3 and 12), or to inhibit nitrification losses by the secretion of bio-inhibitors of this process (Subbarao et al., 2007a,b). Acquisition efficiency and nutrient transporter systems A key step in mineral nutrient acquisition is the initial transmembrane transport step. In many cases, for any individual nutrient, there are gene families encoding multiple

12


nutritional availability/ demand

allosteric effectors

ions/metabolites

pathways

metabolism

sensors

posttranscriptional/ posttranslational regulation

gene expression for structural components: transporters, assimilatory pathway, root architecture

transcriptional regulators Fig. 1.3. Simple pathway linking supply and demand of nutrients to regulation of gene expression, as envisioned

at the cellular level. Complex pathways with multiple components link demands for and availability of nutrients for plant growth, mediated by changes in metabolism, usually as a result of changes in gene expression, but in some cases at the level of enzyme/pathway activity (allosteric regulation).

homologs. In Arabidopsis, for example, there are two gene families for nitrate transporters, NRT1 and NRT2, with 53 and 7 members, respectively (see Chapter 10), a gene family of 14 sulfate transporters (Chapter 14 and Hawkesford, 2003) and 9 members of the phosphate transporter family pht1 (Chapter 12 and Smith et al., 2003). While in most cases there are families specific for a single nutrient, there are instances of nonspecificity: Sulfate transporters effectively transport selenate (Shinmachi et al., 2010) and molybdate (Tomatsu et al., 2007; Baxter et al., 2008; Fitzpatrick et al., 2008; Shinmachi et al., 2010). While there is some potential redundancy of function with these large gene families, it has become apparent that there is tissue, developmental, and even membrane specificity with regard to expression patterns. Functionally, there are usually both high and low affinities for the substrate ions, depending on functional requirements: In relation to primary uptake into root cells, the most common functionality is for high-affinity uptake, as required for effec-

tive acquisition from soil solutions with low concentrations of ions. Patterns of expression within the root are often complex to effectively transfer the respective ions from the soil solution to the vasculature for transfer to the shoot material. In some instances, vacuolar storage may also play an important part (Kataoka et al., 2004). Many studies have focused on the impacts of nutrient limitation on patterns of transporter expression and the contribution to overall nutrient use efficiency strategies of plants in limiting nutrient availability (Buchner et al., 2004, 2010). For phosphate and sulfate, there is an apparent de-repression system controlling gene expression, facilitating increased expression when nutrient demand exceeds availability (Smith, 2002; Hawkesford and De Kok, 2006). For nitrate, the pattern is more complex, with some transporters induced and others repressed, depending on the presence of nitrate and the nutritional status of the plant (see Chapter 10). The transporters play essential roles, contributing to nutrient use efficiency, for the


most part extremely effectively scavenging nutrients from the soil (potentially present at low concentrations), and particularly in conjunction with effective root proliferation. As targets for improvement of NUE, sophisticated strategies are likely to be important. Modifications to the selectivity (Rogers et al., 2000) may enhance preferential uptake of beneficial ions and exclude toxic ions. Overriding negative feedback mechanisms may facilitate luxury uptake, but appropriate sinks or temporary storage would also be required (see below). One approach that apparently overrides limits on nitrogen uptake is the overexpression of alanine amino transferase in root exodermal tissues, thus channeling nitrogen away from metabolites involved in negative feedback (see Chapter 9). In some instances, enhancing remobilization and optimizing partitioning to harvested organs may require optimization of transporter expression. Metabolic responses to nutrient availability Plant responses to nutrient availability are complex and involve changes in pathway fluxes, in activity of pathway enzymes mediated by posttranslation modifications and/or changes in substrate/inhibitor ratios (allosteric effects), as well as changes in expression of genes encoding the pathway enzymes and many additional proteins (Fig. 1.3). The challenge for the plant is to optimize growth and development given the available nutrient inputs. Matching availability to demand may entail many regulatory steps and sensory mechanisms. It is essential to understand these networks before intervention through transgenesis or molecular breeding. For the most part, our knowledge of these regulatory loops is restricted in plants (Gojon et al., 2009). Nutrient use efficiency, although simply divided into uptake and utilization, encompasses all processes of plant growth and

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development, and all aspects of metabolism. Potential targets for nutrient use efficiency improvement are therefore diverse. Obvious targets in, for example, nitrogen metabolism (see Chapters 8 and 9) include genes of the assimilatory pathway. Glutamine synthetase has been a specific target for transgenic approaches (Chapter 8), as it is not only involved in primary assimilation but also has a role in efficient recycling of ammonia during senescence processes (Kichey et al., 2006). Generally, results of single-gene manipulation have been disappointing, in part because metabolic pathways form networks that have a great plasticity in responding to perturbations, whether due to gene targeting or environmental fluctuations, for example, in nutrient supply (Wasaki et al., 2003; Palenchar et al., 2004; Nikiforova et al., 2005). Typically, nutrient uptake is balanced by nutritional requirement for growth, and a coordination of pathway expression and activity is seen (Prosser et al., 2001; Hawkesford and De Kok, 2006; Howarth et al., 2008; Gojon et al., 2009) and excess uptake of nutrient is avoided. Excess accumulation of some ions does occur but only to the point at which available storage pools are saturated (for example, nitrate accumulation in vacuoles); this is a strategy to aid with fluctuating supplies of nutrients but is not helpful when one nutrient becomes permanently limiting. Utilization efficiency Efficiency of utilization may be defined as biomass production (predominantly fixed carbon) as a function of nutrient taken up (see Table 1.1). This is most often applied for nitrogen, as total canopy nitrogen content reflects the extent of photosynthetically active biomass, as the greatest proportion of the total nitrogen content in this tissue is a major component of proteins involved in photosynthesis. The effectiveness of this capacity in producing

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harvestable biomass is defined by NUtE. The key attributes that will enhance NUtE are photosynthetic activity, canopy size, longevity, and sink organ capacity (Fig. 1.2). Photosynthetic activity includes the ability to intercept light, which is clearly linked to canopy architecture and the light harvesting complex density, as well as the biochemistry of the carbon fixation processes, particularly Rubisco, for efficient fixation of carbon dioxide (Parry et al., 2003). An alternative and radical solution is to engineer C4 photosynthesis, which is up to 50% more efficient than C3 photosynthesis, into C3 plants such as rice (Hibberd et al., 2008). Attributes of canopy development and architecture include rapid establishment, followed by proliferation and eventual canopy closure (full coverage of the ground), and then effective architecture to intercept radiant light. Depending on the harvestable product, which may be the canopy itself, or it may be biomass derived from this, for example, woody stem or generative material such as seed, the canopy must be photosynthetically active for as long as possible. Delaying senescence and prolonging the period of photosynthesis results in increased carbon fixation (see Chapters 4 and 5). However, the complexity of processes involved in leaf senescence is highlighted by transcriptome analysis, emphasizing the difficulty in manipulating this process to enhance yield (Gregersen and Holm, 2007). As a target, this process has huge potential for crop improvement, as by definition for a fixed amount of nutrient (nitrogen) taken up, the more carbon that is fixed, the better the NUtE (for a full discussion on the physiology associated with these traits, see Chapter 4). Sinks An important attribute for uptake efficiency is having adequate sinks to store acquired

nutrients, whether nitrogen or minor but important nutritional components including Fe, Zn, and Se. Adequate sinks will prevent negative feedback regulation on the initial acquisition/assimilatory processes and should provide important remobilizable storage that can be accessed should supply be limiting as well as during production of harvested organs such as seed. Sinks may be subcellular, for example, vacuoles, may be chemical such as nitrogen stores in protein, or may be defined at the organ level, for example, stems (see Chapter 4). Attempts have been made to engineer both metabolism and (Zhu and Galili, 2003) protein sinks to enhance nutritional quality with high methionine, cysteine, or lysine content (Tabe and Higgins, 1998; Nikiforova et al., 2002; see also Chapter 6). As already indicated, one explanation for the remarkable improvement in NUE seen by the overexpression of alanine aminotransferase is that alanine is a local metabolic sink for nitrogen that does not have negative feedback effects on uptake, unlike glutamate (Chapter 9). HI and partitioning of nutrients By definition, measures of nutrient use efficiency will be optimum if HI is high and nutrients are partitioned to the harvested material. This ignores the impact at the whole ecosystem level, and there may be merit in not harvesting some nutrients but allowing them to be recycled within the field; this might particularly apply to phosphorus; it does, however, assume that leaching losses will be minimal between crops. In many instances, partitioning to the cropped organ is preferable, for example, nitrogen in the case of grain protein (Chapter 6) and minerals for human nutrition (Chapters 14, 16, and 17). As indicated, a major improvement in yields and NUE was obtained with the introduction of dwarfing genes (into wheat and rice), minimizing the nonhar-


vested fraction of wheat and rice. Although there are efforts to extend the repertoire of dwarfing genes, which may have additional benefits (Ellis et al., 2005), overall, as the HI for many crops has already been optimized, there is likely little benefit from further manipulation of the HI. For those crops for which this is not the case, improving the HI is a high priority. While nutrient harvest index (NHI) for nitrogen is usually high in cereals, this is not the case for all minerals in all crops. Even in wheat, different minerals are partitioned with varied efficiency: selenium and molybdenum were shown to be differentially partitioned to grain (Shinmachi et al., 2010). In Brassica napus (oil seed rape, Colza), sulfur is very inefficiently partitioned to the seed (Blake-Kalff et al., 1998). Manipulating senescence to produce stay-green phenotypes, thus enhancing yield may have a detrimental effect on the HI and NHI. In this case, additional selection for late but rapid nutrient remobilization would be required. Conversely, enhancing the rate of senescence by the introduction of a NAC transcription factor increased remobilization and enhanced grain protein as well as zinc and iron content (Uauy et al., 2006; Waters et al., 2009). However, increasing the onset and rate of senescence may have a negative effect on yield. Many nutrient deficiencies lead to changes in biomass allocation between roots and shoots, generally increasing the root : shoot ratio (Hermans et al., 2006). This is an adaptive strategy, facilitating the ability to scavenge for nutrients. In nutrientpoor environments, this would be an advantageous trait; however, this does need to be balanced with production of harvestable material. Little is known about the signaling pathways involved; however, the signals may be linked to imbalances in nutrient accumulation in shoot tissues. Signals from the shoots to the roots (Forde, 2002) may be

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hormonal (Signora et al., 2001) or may be metabolites, for example, carbohydrates (Hermans et al., 2006). Ultimately, partitioning to the cropped organ is of most importance in agricultural production. Strategies and approaches for the genetic improvement of NUE traits There is considerable pressure to improve fertilizer use efficiency (see above: economic, environmental, nonrenewable resource use), and this has been traditionally achieved by agronomic practice and breeding for yield in specific environments and agronomic systems. In the case of nitrogen, breeding for yield is equivalent to breeding for nitrogen utilization efficiency at any given nitrogen input, and there has been considerable progress in improving yields and, therefore, the NUtE component of NUE. Generally, wheat varieties responding well at high inputs also respond well at low inputs (Ortiz-Monasterio et al., 1997; Barraclough et al., 2010). However, there is a strong case for selection at varied inputs and for seeking new and untested germplasm to find new alleles for greater NUtE efficiency. However, acquisition efficiency has been much less specifically selected for, in part due to the difficulties of phenotyping roots. Here, selection at low inputs is vital. Additionally, it will certainly be necessary to introduce wider germplasm pools (landraces, wild relatives) into screening programs, as alleles for high efficiency of acquisition will have almost certainly been lost from the gene pool without the selection pressure for high acquisition efficiency. Many new technologies for gene discovery (microarrays, deep sequencing tilling transformation SNP detection) are now available and may be combined with established breeding approaches (breeding, quantitative trait loci [QTLs], germplasm

16


screening). In combination with the identification of new traits, technologies for introducing these into modern breeding lines are required (synthetic polyploids, alien introgression, gene transformation; Able et al., 2007). As already mentioned and cautioned by others, single-gene introductions, perhaps through crop transgenesis, are often not successful, particularly when gene selection is from only preexisting biochemical knowledge (Sinclair et al., 2004), almost certainly due to a lack of appreciation of the complexity of the systems being manipulated. Figure 1.4 outlines an approach for genetic improvement, beginning with a statement of the need to precisely define the trait of interest. Ideally, in order to effectively target the trait, this needs to be resolved to the smallest subcomponent, encoded by just a few genes. After trait prioritization, assessment of variation is required. This may be either natural variation, or variation induced by mutation or by crossing an examination of mapping populations, and will provide material directly for commercial breeding. Variation may also be used to aid in the identification of the target genes. Transcriptome approaches will indicate genes coexpressed with traits of interest; however, these candidates are usually very numerous (Wang et al., 2000, 2001, 2003, 2004; Lu et al., 2005; Gregersen and Holm, 2007). Examination of occurrence across diverse germplasm and expression patterns under multiple conditions will narrow these candidate lists to a few key genes worth further investigation. Definitive implication in crop improvement with respect to NUE may require transgenesis in the crop of interest. Such genetically modified crops may be the end product, or the genes may be used as “perfect” markers for screening other natural populations, avoiding the need for transgenesis. Critically, genes identified by such a route may be

•

Trait de convolution and prioritization

•

Assessment of variation

•

•

–

Provision of materials for breeding

–

Aid gene discovery

Identification of genes/markers –

Target appropriate tissues

–

Correlation with traits

–

Mapping populations

Breeding or biotechnology

Approaches to finding novel target genes and crop improvement. Germplasm identified with appropriate traits is of direct value for crop improvement. Identified genes will facilitate breeding either as markers or in transgenic approaches. Fig. 1.4.

more robust than selection based on biochemical pathways alone. Prospects The main targets for improving NUE have been outlined and a case for a thorough understanding of the underlying molecular process has been made. The major targets are improving nutrient capture and interception to avoid losses, modifying requirements (reducing if possible) and enhancing utilization efficiency by generally improving carbon fixation and yield. An ideotype of an idealized set of traits for nutrient use efficiency can be defined and will be crop specific (Foulkes et al., 2009). Furthermore, such ideotypes will be specific to different environments and cropping systems.


Nutrient use efficiency in its broadest sense indicates how effectively a plant is able to capture and utilize nutrients to produce biomass. It is most usually specified for nitrogen as this is a main driver for production. However, healthy and productive crop growth requires a balanced nutrition including several macronutrients and many micronutrients. Irrespective of the quantity needed, all are essential and any limitation will impact on plant growth and crop yields. In almost all cases, the nutrient in question must be obtained from the pedosphere and therefore uptake processes dependent on architecture and functioning of the roots are critical. Subsequent to this, partitioning within the plant is a vital prerequisite to efficient utilization of the element as part of the plant’s growth and developmental cycle. Independent but simultaneous selection for both of these traits must be performed. A radical and alternative solution to providing nitrogen fertilizer would be the transfer of nitrogen fixation capacity, or the ability to form the required symbioses, to nonlegume crops (see Chapter 20). NUE is an essential component of crop production, and irrespective of the agronomic system, low-input or intense, efficient utilization of valuable resources will be essential for future sustainable food production. NUE is a complex trait that can be broken down into subtraits, all of which are also complex in nature. Few instances can be expected where single genes or a single locus will have a huge benefit; dwarfing genes were an exception. Modern tools and resources available to plant scientists and the agronomy and breeding communities should aid further improvements in NUE and hence crop production. Great variability exists in the extent to which individual crops have been optimized in relation to NUE, and while large improvements may be anticipated for some crops, for the major world grain crops such as wheat maize and rice,

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smaller incremental improvements are likely. The prospect of step changes in primary production by engineering the photosynthetic process itself will require additional concomitant improvements in nutrient acquisition efficiency. Acknowledgments Rothamsted Research is an institute of the Biotechnology and Biological Sciences Research Council of the United Kingdom. The author ’s research is also supported by the Biotechnology and Biological Sciences Research Council (BB/G022437/1 and BB/ C514066/1) and the Department of Environment, Food and Rural Affairs (WGIN project IF0146). References Able, J.A., Langridge, P., & Milligan, A.S. (2007) Capturing diversity in the cereals: many options but little promiscuity. Trends in Plant Science 12, 71–79. Araus, J.L., Slafer, G.A., Royo, C., et al. (2008) Breeding for yield potential and stress adaptation in cereals. Critical Reviews in Plant Sciences 27, 377–412. Austin, R.B. (1999) Yield of wheat in the United Kingdom: recent advances and prospects. Crop Science 39, 1604–1610. Barraclough, P.B., Howarth, J.R., Jones, J., et al. (2010) Nitrogen efficiency of wheat: genotypic and environmental variation and prospects for improvement. European Journal of Agronomy 33, 1–11. Baxter, I., Muthukumar, B., Park, H.C., et al. (2008) Variation in molybdenum content across broadly distributed populations of Arabidopsis thaliana is controlled by a mitochondrial molybdenum transporter (MOT1). PLoS Genetics 4, e1000004. Blake-Kalff, M.M.A., Harrison, K.R., Hawkesford, M.J., et al. (1998) Distribution of sulfur within oilseed rape leaves in response to sulfur deficiency during vegetative growth. Plant Physiology 118, 1337–1344. Bogard, M., Allard, V., Brancourt-Hulmel, M., et al. (2010) Deviation from the grain protein concentration–grain yield negative relationship is highly correlated to post-anthesis N uptake in

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Hermans, C., Hammond, J.P., White, P.J., et al. (2006) How do plants respond to nutrient shortage by biomass allocation? Trends in Plant Science 11, 610–617. Hibberd, J.M., Sheehy, J.E., & Langdale, J.A. (2008) Using C-4 photosynthesis to increase the yield of rice—rationale and feasibility. Current Opinion in Plant Biology 11, 228–231. Howarth, J.R., Parmar, S., Jones, J., et al. (2008) Coordinated expression of amino acid metabolism in response to N and S deficiency during wheat grain filling. Journal of Experimental Botany 59, 3675–3689. Kataoka, T., Watanabe-Takahashi, A., Hayashi, N., et al. (2004) Vacuolar sulfate transporters are essential determinants controlling internal distribution of sulfate in Arabidopsis. The Plant Cell 16, 2693–2704. Kichey, T., Heumez, E., Pocholle, D., et al. (2006) Combined agronomic and physiological aspects of nitrogen management in wheat highlight a central role for glutamine synthetase. The New Phytologist 169, 265–278. Kichey, T., Hirel, B., Heumez, E., et al. (2007) In winter wheat (Triticum aestivum L.), post-anthesis nitrogen uptake and remobilisation to the grain correlates with agronomic traits and nitrogen physiological markers. Field Crops Research 102, 22–32. Lu, C.G., Hawkesford, M.J., Barraclough, P.B., et al. (2005) Markedly different gene expression in wheat grown with organic or inorganic fertilizer. Proceedings of the Royal Society B-Biological Sciences 272, 1901–1908. Monaghan, J.M., Snape, J.W., Chojecki, A.J.S., et al. (2001) The use of grain protein deviation for identifying wheat cultivars with high grain protein concentration and yield. Euphytica 122, 309–317. Nikiforova, V., Kempa, S., Zeh, M., et al. (2002) Engineering of cysteine and methionine biosynthesis in potato. Amino Acids 22, 259–278. Nikiforova, V.J., Kopka, J., Tolstikov, V., et al. (2005) Systems rebalancing of metabolism in response to sulfur deprivation, as revealed by metabolome analysis of Arabidopsis plants. Plant Physiology 138, 304–318. Ortiz-Monasterio, J.I., Sayre, K.D., Rajaram, S., et al. (1997) Genetic progress in wheat yield and nitrogen use efficiency under four nitrogen rates. Crop Science 37, 898–904. Palenchar, P.M., Kouranov, A., Lejay, L.V., et al. (2004) Genome-wide patterns of carbon and nitrogen regulation of gene expression validate the combined carbon and nitrogen (CN)-signaling hypothesis in plants. Genome Biology 5, R91.


Parry, M.A.J. & Hawkesford, M.J. (2010) Genetic approaches to reduce greenhouse gas emissions: increasing carbon capture and decreasing environmental impact. In: Climate Change and Crop Production (ed. M.P. Reynolds), pp. 139–150. CABI, Wallingford, U.K. Parry, M.A.J., Andralojc, P.J., Mitchell, R.A.C., et al. (2003) Manipulation of Rubisco: the amount, activity, function and regulation. Journal of Experimental Botany 54, 1321–1333. Prosser, I.M., Purves, J.V., Saker, L.R., et al. (2001) Rapid disruption of nitrogen metabolism and nitrate transport in spinach plants deprived of sulphate. Journal of Experimental Botany 52, 113–121. Raun, W.R. & Johnson, G.V. (1999) Improving nitrogen use efficiency for cereal production. Agronomy Journal 91, 357–363. Robinson, N., Fletcher, A., Whan, A., et al. (2007) Sugarcane genotypes differ in internal nitrogen use efficiency. Functional Plant Biology 34, 1122–1129. Rogers, E.E., Eide, D.J., & Guerinot, M.L. (2000) Altered selectivity in an Arabidopsis metal transporter. Proceedings of the National Academy of Sciences of the United States of America 97, 12356–12360. Shinmachi, F., Buchner, P., Stroud, J.L., et al. (2010) Influence of sulfur deficiency on the expression of specific sulfate transporters and the distribution of sulfur, selenium, and molybdenum in wheat. Plant Physiology 153, 327–336. Signora, L., De Smet, I., Foyer, C.H., et al. (2001) ABA plays a central role in mediating the regulatory effects of nitrate on root branching in Arabidopsis. The Plant Journal 28, 655–662. Sinclair, T.R., Purcell, L.C., & Sneller, C.H. (2004) Crop transformation and the challenge to increase yield potential. Trends in Plant Science 9, 70–75. Smith, F.W. (2002) The phosphate uptake mechanism. Plant and Soil 245, 105–114. Smith, F.W., Mudge, S.R., Rae, A.L., et al. (2003) Phosphate transport in plants. Plant and Soil 248, 71–83. Subbarao, G.V., Rondon, M., Ito, O., et al. (2007a) Biological nitrification inhibition (BNI)—is it a widespread phenomenon? Plant and Soil 294, 5–18. Subbarao, G.V., Tomohiro, B., Masahiro, K., et al. (2007b) Can biological nitrification inhibition (BNI) genes from perennial Leymus racemosus (Triticeae) combat nitrification in wheat farming? Plant and Soil 299, 55–64. Tabe, L. & Higgins, T.J.V. (1998) Engineering plant protein composition for improved nutrition. Trends in Plant Science 3, 282–286.

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Tilman, D., Fargione, J., Wolff, B., et al. (2001) Forecasting agriculturally driven global environmental change. Science 292, 281–284. Tilman, D., Cassman, K.G., Matson, P.A., et al. (2002) Agricultural sustainability and intensive production practices. Nature 418, 671–677. Tomatsu, H., Takano, J., Takahashi, H., et al. (2007) An Arabidopsis thaliana high-affinity molybdate transporter required for efficient uptake of molybdate from soil. Proceedings of the National Academy of Sciences of the United States of America 104, 18807–18812. Uauy, C., Distelfeld, A., Fahima, T., et al. (2006) A NAC gene regulating senescence improves grain protein, zinc, and iron content in wheat. Science 314, 1298–1301. Wang, Y.H., Garvin, D.F., & Kochian, L.V. (2001) Nitrate-induced genes in tomato roots. Array analysis reveals novel genes that may play a role in nitrogen nutrition. Plant Physiology 127, 345–359. Wang, R.C., Guegler, K., LaBrie, S.T., et al. (2000) Genomic analysis of a nutrient response in Arabidopsis reveals diverse expression patterns and novel metabolic and potential regulatory genes induced by nitrate. Plant Cell 12, 1491–1509. Wang, R.C., Okamoto, M., Xing, X.J., et al. (2003) Microarray analysis of the nitrate response in Arabidopsis roots and shoots reveals over 1000 rapidly responding genes and new linkages to glucose, trehalose-6-phosphate, iron, and sulfate metabolism. Plant Physiology 132, 556–567. Wang, R.C., Tischner, R., Gutierrez, R.A., et al. (2004) Genomic analysis of the nitrate response using a nitrate reductase-null mutant of Arabidopsis. Plant Physiology 136, 2512–2522. Wasaki, J., Yonetani, R., Kuroda, S., et al. (2003) Transcriptomic analysis of metabolic changes by phosphorus stress in rice plant roots. Plant, Cell & Environment 26, 1515–1523. Waters, B.M., Uauy, C., Dubcovsky, J., et al. (2009) Wheat (Triticum aestivum) NAM proteins regulate the translocation of iron, zinc, and nitrogen compounds from vegetative tissues to grain. Journal of Experimental Botany 60, 4263–4274. Zhang, H. & Forde, B.G. (1998) An Arabidopsis MADS box gene that controls nutrient-induced changes in root architecture. Science 279, 407–409. Zhu, X.H. & Galili, G. (2003) Increased lysine synthesis coupled with a knockout of its catabolism synergistically boosts lysine content and also transregulates the metabolism of other amino acids in Arabidopsis seeds. Plant Cell 15, 845–853.

Chapter 2

Crop Root Systems and Nutrient Uptake from Soils Peter J. Gregory

Abstract Root systems have evolved to allow thorough exploration of the soil for water and nutrients, and to modify soil properties so that scarce nutrients can be acquired. The maximum depth of rooting of crops (average 2.1 m) is less than that of other types of vegetation and influenced by genetic, cultural, and environmental factors. Downward progression of the rooting front follows a sigmoidal pattern with time, and roots are frequently distributed logarithmically in the soil, with the highest concentrations at the surface (typically 5–10 cm root cm−3 soil for temperate cereals and 1–2 cm cm−3 for other crops at 0–0.1 m). Acquisition of nutrients, especially immobile nutrients such as phosphorus, is dependent on root architecture (especially branching), associations with microorganisms (especially mycorrhizal fungi), and modifications to the bioavailability of the nutrient in the rhizosphere (see, for example, Chapters 3 and 12). Several studies have demonstrated the importance of root architecture for phosphorus acquisition in low-

phosphorus soils, and markers associated with quantitative trait locus (QTL) are emerging that should facilitate breeding of improved genotypes. Suitable placement of fertilizers to complement root architecture and the ontology of the crop is already widely practiced, and the ability to manipulate and engineer rhizosphere properties to exploit nutrients more effectively is emerging rapidly as an area of essential research endeavor if the challenge of increasing production while using resources more efficiently is to be realized. Introduction This chapter is about root systems growing in soil. Much useful information has been learned from the model plant Arabidopsis about the genes and regulation of individual root growth (e.g., Ubeda-Tomás et al., 2008; Péret et al., 2009; Brun et al., 2010), but for crops it is the functioning of the whole system that is important. Measurements of such systems are difficult and timeconsuming, with a variety of approaches used to gain basic information about depth,

The Molecular and Physiological Basis of Nutrient Use Efficiency in Crops, First Edition. Edited by Malcolm J. Hawkesford, Peter Barraclough. © 2011 John Wiley & Sons, Inc. Published 2011 by John Wiley & Sons, Inc. 21

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distribution, and various architectural features (see Smit et al., 1994 and Gregory, 2006b for examples). This brief overview focuses on the features of crop root systems contributing to the ability to acquire nutrients. It draws on plant science as well as agricultural and ecological studies to demonstrate how our improved understanding of root interactions with soils to facilitate nutrient acquisition is paving the way for improved genotypes and management techniques to use nutrients more efficiently in crop production. Exploration of the soil Roots have evolved to explore the soil for water and nutrients; roots both respond to the edaphic environment and modify its properties to secure resources. The depth to which roots are able to grow has many implications for the hydrological balance and biogeochemical cycling of ecosystems by extracting nutrients for growth and preventing the leaching of nutrients to water courses. Depth and distribution of crop root systems The depth of rooting and the distribution of roots in the soil profile are affected by genetic and environmental factors. On deep soils, the maximum depth of rooting of crops is typically less than that of forests or grasslands. For example, Canadell et al. (1996) summarized 290 observations of maximum rooting depth of 253 woody and herbaceous species (23 crop studies) from the major terrestrial biomes and found that while the average maximum rooting depth for crops was 2.1 ± 0.2 m, those for temperate deciduous and tropical evergreen forests were 2.6 ± 0.2 m and 7.3 ± 2.8 m, respectively, and those for temperate and tropical grasslands were 2.6 ± 0.2 m and 15.0 ± 5.4 m, respectively. Only tundra and

boreal forests had shallower maximum rooting depths (0.5 ± 0.1 m and 2.0 ± 0.3 m, respectively). Comparisons of crops grown on the same sites with deep soils demonstrate that the maximum depth of rooting is genetically determined and differs between species grown under identical conditions. For example, lupin (Lupinus spp.), pea, and wheat grown on deep sands (entisols) at different sites in Western Australia had significantly different (P < 0.001) maximum rooting depths (Hamblin and Hamblin, 1985). Rooting depths averaged 0.65 m for peas, 1.13 m for wheats, and 1.9 m for lupins. Similarly, Greenwood et al. (1982) grew a range of vegetables on a sandy loam at Wellesbourne, United Kingdom, and found that while onion and lettuce roots were confined to the upper 0.65 m, pea rooted to 0.75 m, broadbean to 0.85 m, and turnip, parsnip, and cauliflower to >0.85 m. Merrill et al. (2002) also found differences between eight crops grown at different sites (soil predominantly a silt loam) over three seasons in North Dakota, USA, with average maximum rooting depths of 1.0 m in common bean, soybean, and pea; about 1.15 m in crambe (Crambe abysinnica); 1.3 m in spring wheat and canola (Brassica rapa); 1.45 m in sunflower; and 1.6 m in safflower. In practice, however, both cultural and environmental conditions often play an important role in determining rooting depth. Comparison of autumn- and spring-sown wheat crops on a sandy loam in Denmark over three seasons showed that autumn sowing gave consistently deeper root systems (2.2 m) than spring sowing (1.1 m; Thorup-Kristensen et al., 2009). This occurred because the downward extension of the rooting front of the winter and spring wheat varieties used was similar (1.3 mm °C day−1), but the period of root growth was longer for the winter crop. In

CROP ROOT SYSTEMS AND NUTRIENT UPTAKE FROM SOILS

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rapid downward extension depending on the crop and growing conditions. Gregory et al. (1978) found that the rate of downward growth of a winter wheat crop grown in the United Kingdom averaged 6 mm day−1 during the winter and 18 mm d−1 between early April and early June, when temperatures were much warmer. The rate of downward progression of the rooting front differs between crops with crops such as leeks and common velvet grass extending at 0.07 cm °C day−1, while others such as cereals and fodder radish were much faster (0.18– 0.26 cm °C day−1; Smit and Groenwold, 2005). For a temperature of 15°C, this corresponds to a root front extending downward at about 1–4 cm day−1. The Borg and Grimes (1986) analysis of data from 48 crop species in 135 field studies found that while the increase in rooting depth with time followed a sigmoidal pattern, the final depth achieved, as well as the time required to achieve it, depended on the crop species and environmental conditions. The rooting depth (RD) could be estimated from RDmax (the maximum

regions with a Mediterranean climate, the depth of rooting is frequently determined by the annual depth of rewetting by rainfall and varies with both site and season. For example, on a deep vertisol at Jindiress, northern Syria, the depths of rooting and of water extraction of barley and chickpea crops were similar at 1.2 m (Gregory and Brown, 1989). Similarly, lupin (Lupinus angustifolius) and wheat crops planted on a duplex (sand over clay) soil in Western Australia both rooted to 0.8 m because of physical impediments to growth in both the sand and clay layers, and because of the limited depth of wetting by rain (Dracup et al., 1992). Rates of downward progression of the rooting front typically vary during the growing season and the front often shows a sigmoidal pattern (Borg and Grimes, 1986). Figure 2.1 gives some examples of the change of rooting depth with time for soybean, sunflower, and winter wheat crops. Downward rates of root extension are typically 10–40 mm day−1 during the phase of

0 20 40 60

Root depth (cm)

80 100 120 140 160 180 200 220 240 260 280 0

20

40

60

80

100

120

140

160

180

200

220

240

Days after sowing Change in rooting depth with time for soybean (•), sunflower (䊏, data for two crops), and winter wheat (䉱). See Gregory (2006b) for details of origin of the data. Reproduced with permission from P.J. Gregory, Plant Roots: Growth, Activity and Interaction with Soils; Wiley-Blackwell Publishing, 2006. Fig. 2.1.

24


Root length (cm cm–3) 0.01 0

0.1

1

10

20 40

Depth (cm)

60 80 100 120 140 160 180

Distribution of root length with depth in the soil profile for maturing crops of cauliflower (•), oilseed rape (䊏), winter wheat (䉱), and sugar beet (䊊). Linear regressions have been drawn for the distributions of cauliflower and winter wheat roots. See Gregory (2006b) for details of origin of the data. Reproduced with permission from Gregory, Plant Roots: Growth, Activity and Interaction with Soils; Wiley-Blackwell Publishing, 2006. Fig. 2.2.

rooting depth) and tr (the relative time elapsed between sowing and maturity) using: RD = RDmax [0.5 + 0.5 sin(3.03 t r − 1.47)]. (2.1) In practice, while the length of the cropping cycle is usually easy to estimate, selecting RDmax requires some local knowledge. Roots are not distributed evenly throughout the soil profile, and the length in layers within the soil profile is normally expressed in terms of a root length per unit volume of soil (Lv often with units of cm root cm−3 soil), sometimes referred to as a root length density. Typical values of Lv in the upper 0.1 m of soil are about 20 cm cm−3 in grasses, 5–10 cm cm−3 in temperate cereal crops, and 1–2 cm cm−3 in other crops (Gregory, 2006a). In many, but not all, studies, it has been found that roots are distributed in the soil

such that their length and mass decrease exponentially with depth (Gerwitz and Page, 1974; Schenk and Jackson, 2002). Figure 2.2 shows that the distribution of roots of some crops (e.g., cauliflower and winter wheat) is well described by such a relation, but for others (e.g., rape and sugar beet), while this relation can be found in the surface layers, there is a tendency for values of Lv in deeper soil layers to be almost constant (see also Smit and Groenwold, 2005 for fodder radish). Whether this is strictly a property of the crop or a result of an interaction between the crop and soil properties remains to be established. Typically the gradient of the relationship between Ln Lv and depth changes rapidly during the early part of the growing season as the crop is establishing (see Gregory 1994 for examples). For example, in a winter wheat crop grown at Sutton Bonington in the United Kingdom, the gradient decreased from 0.077 cm−1 in


mid-January to 0.038 cm−1 shortly before anthesis in June (Gregory, 1994). King et al. (2003) found that after early season changes in the relationship, the gradient was fairly stable during the main phase of growth, suggesting that during the major period of growth, the relative extension of roots proceeds at a similar rate at all depths. Major soil limitations to growth As indicated in the previous section, the development and growth of a crop’s root system is profoundly affected by the properties of the soil and especially by its strength and chemical properties (see Gregory, 2006b for a fuller account). Soils must have sufficient mechanical strength to provide anchorage for the plant but also contain a system of pores containing water and air, which are essential for plant growth. Dense regions of the soil may limit root growth because they offer a large mechanical resistance to root growth and/or restrict the supply of oxygen to roots. Almost all roots growing through soil experience some degree of mechanical impedance, and if continuous pores of appropriate size do not already exist, then the root tip region must exert sufficient force to deform the soil. Typically, the elongation rate of individual roots decreases almost linearly with increase in mechanical strength over a range of about 0.05–0.2 MPa to 2–2.5 MPa (Taylor and Ratliff, 1969; Kirkegaard et al., 1992; Bengough et al., 2006). The ability of a root to deform soil during elongation influences the mechanical resistance to root penetration and results in changes to soil porosity close to the root. Young (1998) summarized results from several studies showing changes in bulk density up to 4–5 mm away from the root surface, while Bruand et al. (1996) found that bulk density increased to 1.8 Mg m−3 at the root–soil interface compared with 1.54 Mg m−3 at distances of greater than

25

about 0.8 mm. Analysis of the displacement of individual particles close to a maize root grown in sand found density increases of up to 30% adjacent to growing root tips, with an approximately exponential variation in particle displacement as a function of distance from the root surface (Vollsnes et al., 2010). Local variation in sand density was associated with the frictional properties of the root cap, and capless mutant roots that shed neither mucilage nor border cells had zones of greater density in front of the root tip, whereas intact wild-type roots deformed the soil more radially, with density increases generally confined to the flanks of the root. Bengough et al. (1997) suggested that cell wall properties were more important than turgor in regulating the elongation rate of roots and that both properties were influenced by stress history. Relatively little is known about the properties of cell walls of roots compared with those of leaves and stems, but Croser et al. (2000) demonstrated that reduced cell extension in mechanically impeded pea roots was associated with a loosening of cell walls in the radial direction and a stiffening of walls in the axial direction, although there was no change in turgor pressure. There are two clear responses of roots to mechanical impedance: slowing of the rate of extension and an increase in root diameter immediately behind the root tip. The strength of most soils increases as they dry, so that shortage of soil water and hard soils are commonly interlinked. Whalley et al. (2007) determined that the strength (Q) of a number of UK and Canadian soils could be described using the product of matric potential (ψ) and degree of saturation (S) together with bulk density (ρ) by: log10 Q = 0.35 log10 ( I ψ S I ) + 0.93 ρ + 1.26. (2.2) This relation demonstrates that even wet soils can be strong and that dense soils can

26


become too strong for roots to penetrate at quite high matric potentials. For example, for a silt, Whitmore and Whalley (2009) showed that a penetrometer pressure of 2 MPa was achieved at a matric potential of about −2000 kPa when the soil was loosely packed at a bulk density of 1.2 Mg m−3, but that the same strength was achieved at only about −60 kPa when more densely packed to a bulk density of 1.6 Mg m−3. Roots also respond to their chemical environment, especially to pH, aluminum, and salinity (see Chapters 3 and 19); responses to localized enhanced nutrient supplies will be covered in the next section. Almost 50% of all nonirrigated soils are acidic and are very common in the tropics where high rainfall has leached soluble bases. As pH falls to less than 5–5.5, aluminum materials become soluble and root growth responds negatively to both increased H+ and Al3+ concentrations. In saline soils, both Na+ and Cl− can inhibit growth. The effects of acidity and salinity on the growth of root systems have been extensively studied in Australia, where both soil conditions are common. For example, in southeastern Australia, varying combinations of salinity, sodicity, alkalinity, and boron toxicity in subsoils restrict the depth of rooting and thereby limit the access to water, a crucial yield-determining resource (Sadras et al., 2003; Adcock et al., 2007). Root system architecture Root architecture, the spatial configuration of a root system in the soil, results from the production of new root apical meristems and a combination of extension and initiation of lateral branches in the proximity of root apices. Most dicotyledons have an allorhizic system consisting of a primary (tap) root and lateral roots, whereas monocotyledons have a secondary homorhizic system consisting of multiple axes and associated lateral roots.

Studies of root architecture do not usually include fine details such as root hairs, but describe the entire root system of an individual plant (Lynch, 1995) and encapsulate both the topology (a description of how individual roots are connected through branching) and the distribution (the presence of roots in a spatial framework) of roots. Root system architecture is complex and varies between and within plant species, but drawings of excavated root systems (e.g., Kutschera, 1960) allow some broad generalizations to be made about the shape of the system and the spatial orientation and distribution of roots. Nearly all such drawings show that, with the exception of the taproot, which grows almost vertically throughout, most other root axes grow initially at some angle relative to the vertical but gradually become more vertically orientated. A large number of signals, both within and outside the plant, affect the root system and its final architecture, particularly via the initiation and development of lateral roots (Nibau et al., 2008). Recent studies with Arabidopsis have elucidated some of the processes and genes controlling the production and growth of primary and lateral roots (Osmont et al., 2007). Nibau et al. (2008) identify four key stages in lateral root formation: (1) stimulation and de-differentiation of pericycle founder cells; (2) cell cycle reentry and asymmetrical cell division to give a lateral root primordium (LRP); (3) LRP emergence through the outer layers of the primary root via cell expansion; and (4) activation of the lateral root meristem and elongation of the new lateral root. Lateral root development is very dependent on auxin and auxin transport (Reed et al., 1998; Casimiro et al., 2003) and constitutes a common signal that integrates all stages of the developmental process (Péret et al., 2009). Other hormones such as ethylene and abscisic acid, together with nutrients such as nitrate and phosphate, also affect lateral development,


27

Fig. 2.3. Geometric simulation modeling of bean root systems that vary in basal root angle but are otherwise identical in length and branching. The variation illustrated is present among different genotypes of Phaseolus vulgaris and has been shown to be influenced by soil phosphorus availability. The scale on the right is from 0 to 40 cm. Reproduced with permission from Ge et al., Plant and Soil; Springer-Verlag, 2000.

but there is still some way to go in understanding the integration of these multiple signals. In contrast to auxin control of root development, root elongation is primarily regulated via gibberellins (GAs; Swarup et al., 2005). Ubeda-Tomás et al. (2008) demonstrated that the endodermis was the main GA-responsive tissue regulating root growth, and that the rate of elongation of the endodermis limited the rates of elongation of other tissues, and hence of the whole root. Root architecture is important because it influences the ability of plants to access nutrients and water (Lynch, 1995). This has been demonstrated in a program of work undertaken with beans (Phaseolus vulgaris). Bonser et al. (1996) found that in soils low in phosphorus the gravitropic sensitivity of both the taproot and the basal roots was decreased, resulting in a shallower root system. They hypothesized that the shallower root system was a positive adaptive response to low soil phosphorus availability,

which concentrated roots in the surface soil layers, where soil phosphorus availability was highest, and also reduced the spatial competition for phosphorus among roots of the same plant. Ge et al. (2000) tested this hypothesis by modeling root growth and phosphorus acquisition by plants with nine contrasting root systems in which the root angle of the basal roots was varied but the root length and degree of branching were kept constant (Fig. 2.3). Irrespective of the distribution of phosphorus in the soil, shallower root systems acquired more phosphorus per unit of carbon than deeper root systems, and in soils with higher phosphorus availability in the surface layers, the hypothesis was substantiated with shallower root systems acquiring more phosphorus than deeper root systems (Ge et al., 2000). Subsequent simulation studies have demonstrated that roots borne by the underground stem (termed adventitious roots) are also important in phosphorus acquisition, especially when phosphorus is preferentially located in the upper soil,

28


despite the accompanying reduction in growth of the tap and lateral roots (Walk et al., 2006). The effects of root architecture extend beyond phosphorus acquisition and also influence losses from soil erosion (Henry et al., 2010). In a field study on a low-phosphorus soil in Costa Rica, Henry et al. (2010) found that genotypes of common bean with a shallow roots trait acquired more phosphorus, had greater shoot biomass, and thereby lost less phosphorus via soil erosion. They concluded that selection of root traits such as shallowness, when combined with integrated nutrient management, was a promising strategy for increasing both productivity and sustainability. The structure and dynamics of root system architecture are complex, and architectural models have been developed to take account of space and the biophysical interactions between roots and their environment. Simple spatial models of root distribution have been available for many years (e.g., Gerwitz and Page, 1974; Fig. 2.2), but more recently more complex architectural models (Dunbabin et al., 2003; Pagès et al., 2004; Pierret et al., 2007) have emerged that reproduce the developmental processes of root apical meristems to construct virtual root architectures. Single roots are assembled incrementally through the growth of a set of virtual apical meristems whose activity is determined at each time step of the simulation. Usually, the same morphogenetic rules are used to define the behavior of sets of meristems, and complex architectures arise as emergent properties of these simple rules (Prusinkiewicz, 2004). Other mathematical approaches, however, offer alternatives to architectural models and may more easily interact with soil mechanics and transport models that use partial differential equations to describe soil strength, and diffusion and mass flow of nutrients in soil (Dupuy et al., 2010a).

Analytical models incorporating exact or approximate solutions to growth equations can be obtained in the form of mathematical functions that provide insight into the development of the root system as a whole. They also have the added advantage in that they can be parameterized relatively easily from field data. For example, Dupuy et al. (2010b) observed barley roots in large soil bins and found that root meristems propagated like waves through the soil and that the morphology of the waves was a function of specific root developmental processes linked to properties such as gravitropism and frequency of branching. The use of continuous variables to aggregate root morphological properties also facilitates the coupling of growth with environmental and physical properties such as soil heterogeneity (de Willigen et al., 2002). Finally, representing root systems as continua allows more efficient computational models to be developed (Dupuy et al., 2010a). Accessing and capturing nutrients Capture of mobile and immobile nutrients Even in root systems with complex architecture, roots are only in direct contact with a small proportion of the nutrients in the soil solution. This means that for a plant to access nutrients, either the nutrients must move from the bulk soil to the root surface or the plant must extend its influence into the soil. There is an extensive literature on the movement of nutrients to roots growing in soils via the processes of mass flow and diffusion (Tinker and Nye, 2000; Gregory, 2006b). Mass flow (convection) occurs as a result of transpiration, and dissolved ions are carried to the root surface. Because the


membranes of the root are highly selective about what they allow to enter, concentration gradients of different strengths and directions are established around roots; ions will diffuse toward the root if they are taken up faster than they are carried to the root surface by mass flow and away from the root if the converse pertains. A consequence of this differential movement of ions in the soil solution is that the zones of competition for different ions around roots vary (Bray, 1954). The concentration of ions in the soil solution varies widely, but in soils used for crops it is typically about 1 mM for Ca2+, 0.1–1 mM for Mg2+, K+, and Na+, and 0.01–0.001 mM for phosphate. Phosphate is strongly adsorbed by many soils, ensuring that its concentration in solution is low, while nitrate concentration, although generally higher than that of phosphate, is very dependent on microbial and root activities. The supply of nutrients to several crops by mass flow has been estimated from the product of the quantity of water taken up and the concentration of ions in the soil solution and shows that, in general, mass flow will transport more than sufficient sulfur, calcium, sodium, and magnesium to the root surface, significant but insufficient quantities of potassium and nitrogen, and insufficient phosphorus (maize, Barber et al., 1963; leek, Brewster and Tinker, 1970; winter wheat, Gregory et al., 1979). The concentration of micronutrients in solution is highly dependent on pH and there are few experimental results, so generalizations are impossible. Such measurements demonstrate that unadsorbed nutrients such as nitrate can be regarded as mobile, while adsorbed nutrients with low concentrations in solution supplied principally to the root surface by diffusion are immobile. It follows that the zone of competition between roots for a mobile nutrient such as nitrate will be much larger than

29

that for an immobile nutrient such as phosphate. The more strongly the ion is adsorbed by the soil and the drier the soil, the slower the diffusion of the ion to the root surface. Typically, in moist soil, an ion such as nitrate will move 4 mm in 1 day, while potassium will move 1.3 mm, but phosphate only 0.04 mm. These distances are reduced substantially as the soil dries so that nitrate, for example, will move by only 0.2 mm in a soil at a permanent wilting point and movement of phosphate will effectively cease. These distances give some indication of the quantities of nutrients that are potentially available to plants by diffusion and of the difficulty of acquiring phosphorus relative to other nutrients. In contrast, a molecule of gas will move about 800 mm in a day in air and about 8 mm in solution (Tinker and Nye, 2000). While much attention has been paid to the ability of root systems to capture nutrients in pursuit of crop production, there is increasing emphasis on the role of root system architecture in capturing nutrients, such as nitrate, that might otherwise leach from the soil profile into water courses. Dunbabin et al. (2003) have shown the role that root architecture may play in this regard and the importance of quickly producing a high density of roots in the top soil on the sandy Australian soils that they studied. Similarly, the growth of deep rooting arable and cover crops over winter has been shown to reduce nitrate leaching on deep soils in northern Europe (ThorupKristensen et al., 2009; Pedersen et al., 2010). In many parts of the world mixed cropping, intercropping, and agroforestry associations rely on differences in root architecture to overcome spatial competition and ensure spatial complementarity of root systems in their quest for nutrients (van Noordwijk et al., 1996).

30


Response of roots to localized nutrient supplies Nutrients are rarely, if ever, uniformly distributed in soils, and the response of roots to the heterogeneity of their distribution has been of considerable interest. A common, though not universal, response of roots to a nutrient-rich patch is root proliferation with suppression elsewhere. For example, Drew and coworkers undertook a series of experiments with barley grown in solution culture and sand irrigated with nutrient solution, with part of seminal axis 1 exposed to either higher or lower concentrations of nutrients than the remainder of the axis (Drew et al., 1973; Drew, 1975; Drew and Saker, 1975 and 1978). When exposed to a localized high concentration of nutrient, the root responded by increasing the number and length of firstand second-order laterals with phosphate, NH4+, and NO3−, but not K+. The reason for the lack of response to localized potassium is uncertain (see Drew, 1975 for possible explanations). In other plants, different responses are obtained, and in a review by Robinson (1994) one third of the studies showed little or no response of roots to localized nutrient supply. Hodge (2009) concluded that roots are very adaptable and plastic in their response to their environment so that “rules of response” and variation in strategy among plant species that can be applied in different environments are still absent. Studies with Arabidopsis seedlings are starting to reveal the mechanisms by which nutrient availability affects root architecture. For NO3−, increased elongation rates of laterals in the zone of enhanced concentration were due to enhanced meristematic activity and appeared to arise from a direct signal from the NO3− ion rather than from a product of NO3− metabolism (a mutant with low nitrate reductase activity showed a similar response to NO3−-rich zones; Zhang and

Forde, 1998). Zhang and Forde (1998) suggested that cells in the lateral root tips have a NO3− sensor and a signal transduction pathway to convert the NO3− signal into a growth response. Remans et al. (2006) concluded that the nitrate transporter NRT1.1, expressed in root tips, is a key component of this nitrate-sensing system, enabling the plant to detect and exploit nitrate-rich patches. Two genes have been identified as playing a role in the signal transduction pathway: (1) ANR1 is a NO3−-regulated member of the MADS-box family of transcription factors (Zhang and Forde, 1998); (2) AXR4 is an auxin-sensitive gene that may be involved because of the failure of an axr4 mutant to respond to localized NO3− (Zhang et al., 1999; Forde, 2002). More recently, studies have demonstrated an intricate N regulatory network at the root tip that coordinates changes in root growth rate and architecture to external and internal supplies of nitrogen (Forde and Walch-Liu, 2009). In Arabidopsis grown on agar, distinct mechanisms for sensing and responding to nitrate and glutamate (an amino acid representative of the major form of soluble organic nitrogen in soils) have been identified. The major effect of nitrate is to stimulate the growth of lateral roots, while that of glutamate is to slow growth of the primary root and stimulate branching near the root tip. Whether such responses to soluble organic nitrogen are replicated in soil is still to be determined. While a role for auxin in plant development and in lateral root development is undisputed, its role in nutrient signal transduction pathways is still to be established unequivocally. For example, while Williamson et al. (2001) demonstrated that responses to localized phosphate indicated a response to internal phosphate concentration, there was no indication from the auxin mutants axr1, aux1, and axr4 that auxin played any role in the response. In contrast, Al-Ghazi et al. (2003) concluded that auxin


signaling was involved in the response of the root system architecture of Arabidopsis to phosphate deprivation, and López-Bucio et al. (2003) concluded that the responses of root architecture to nutrients can be modified by several plant growth regulators such as auxins, cytokinins, and ethylene, so that nutritional effects on root development may be mediated by changes in hormone synthesis, transport, or sensitivity. Many effects of nutrients on root growth may also be linked to changes in carbon supply, a feature that is only now being quantitatively modeled (Brun et al., 2010). Several workers have attempted to assess the significance of root proliferation for nutrient acquisition. Robinson (1996) used Drew’s (1975) results to calculate the potential exploitation of individual nutrients and showed that the production of additional lateral roots was highly beneficial in the exploitation of locally available phosphorus, principally because of its low diffusion coefficient. For nitrate, however, the necessity for lateral roots, let alone proliferation of laterals, was not demonstrated, and their growth appeared to be superfluous for effecting nitrate capture. Indeed, it has frequently been difficult to link quantitatively the proliferation response directly to strategies for nutrient acquisition (Hodge, 2009). Hodge (2004) reviewed three experiments in which root proliferation of wheat and two grass species were measured in response to nitrogen-enriched organic patches. A relationship between root proliferation in, and nitrogen capture from, the patches was not found in any experiment, but in experiments where two different plant species were grown together and allowed to explore a common enriched patch, there was a direct relation between root proliferation in, and nitrogen capture from, the patch. Hodge et al. (1999) and Robinson et al. (1999) concluded that root proliferation was important for nitrogen capture when plants are in inter-

31

specific competition for organic patches containing a finite supply of mixed nitrogen sources, but when any one of these factors was not present, then the importance of root proliferation for nitrogen capture was less obvious. Whether roots proliferate depends on the plant demand for the nutrient, the mobility of the nutrient within the plant, and the concentration in the patch relative to background (Hodge, 2004). The substantial plasticity of plant responses to heterogenous nutrient supplies opens the possibility of developing crops with enhanced capacity to capture nutrients. Dunbabin et al. (2001a,b) examined growth responses of Lupinus angustifolius (dominant tap root and lateral system) and Lupinus pilosis (minor tap root and well-developed laterals) to nitrate supplied either uniformly or split between the upper and lower root system. In both species, increased root proliferation in the high nitrate zone was accompanied by decreased root growth in the low nitrate zone to give about the same total growth as the uniform low nitrate treatment. However, while L. angustifolius increased its rate of nitrate uptake from parts of the root system supplied locally with high nitrate, L. pilosis did not and only used its increased root growth to exploit nitrate patches. From this range of responses, it may be possible to select a lupin type with an enhanced ability to capture nitrate from the soil profile. In practice, of course, plants have multiple resource constraints to contend with (e.g., heterogeneously distributed phosphorus and soil water) and will try to optimize their investment in roots. Modeling of these responses is at an early stage. Ho et al. (2004) investigated this possible optimization for beans grown under different combinations of water and phosphorus availability and found that the basal root angle was shallower for localized shallow phosphorus, and deeper for localized deep water than that

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obtained in the case of uniformly distributed water and phosphorus. When phosphorus was concentrated in the surface and water located deep, the optimal basal root angle depended on the relative rates of change with depth in the values ascribed to the available resources. Root-microbe–soil interactions that influence nutrient availability Roots and their associated microorganisms play a crucial role in modifying soils and in the availability of nutrients (see also Chapter 3). About 80% of all higher plant species form mycorrhizal symbioses, with the arbuscular mycorrhizal (AM) association being the most common among the seven different types of mycorrhizal symbioses (Smith and Read, 2008; Brundrett, 2009). The symbiosis evolved early in the evolution of land plants and facilitated the uptake of poorly soluble ions such as phosphate and zinc. Plants benefit from the AM fungi because these acquire nutrients that would otherwise be inaccessible for reasons of distance from the root, location in pores that are too small for roots to enter, or occurrence in forms unavailable to plants but not fungi; in return, the fungi benefit from a supply of C from photosynthesis (Lambers et al., 2009). The AM hyphae may also be more effective than roots in competing with other soil microbes for phosphorus and may also have a higher affinity for phosphorus than roots (Smith and Read, 2008). The nutritional benefits of AM fungi to plants grown on soils low in phosphorus are well documented (Smith and Read, 2008), although many questions about their functioning remain. For example, Hodge (2009) identifies the importance of AM fungal foraging, the nutrients captured, the differences that occur among AM fungal species, and the consequences for different plants linked together in a common network as unresolved

questions. Transfer of nutrients between the fungus and the host is also still not well understood (Tinker and Nye, 2000; Smith and Read, 2008). Ryan et al. (2003) measured the concentrations of phosphorus, potassium, and magnesium in the hyphae and young arbuscules of indigenous AM of field- and glasshouse-grown plants of subterranean clover, white clover, leek, and pea, and concluded that nutrient transfer to the host and carbon transfer to the fungus occurred in both young arbuscules and intercellular hyphae. They suggested that magnesium and potassium ions are probably the balancing cations for phosphorus transfer. Different mycorrhizal fungi do not all behave in identical manner (for example, some fungi grow only close to a root while others extend to considerable distance), with the result that different fungal–plant combinations are functionally diverse. Smith et al. (2003, 2004) grew combinations of flax, medic, and tomato with the AM fungi Glomus caledonium, Glomus intraradices, and Gigaspora rosea in pots of equal mixtures of sand and irradiated soil with root + hyphal, and hyphal-only compartments. After 6 weeks, the dry weight of flax was increased by all fungi relative to a nonmycorrhizal control, while medic increased with the two Glomus spp. but not Gigaspora rosea, and tomato showed no positive responses with any species. There was no simple relation between plant growth and external hyphal growth in the soil, and the contributions of the AM fungi to phosphorus content of the plants varied significantly (Table 2.1). After 6 weeks of growth, G. intraradices contributed almost 100% of the phosphorus taken up by flax, 80% by tomato, and only 60% by medic. The contribution of G. caledonium was 25–40% across all plants, with only small contributions of Gi. rosea throughout. Smith et al. (2004) concluded that mycorrhizal uptake of phosphorus could replace uptake by roots and root


Table 2.1. Contribution (%) of the mycorrhizal pathway to phosphorus uptake in plants of flax, medic, and tomato after 6 weeks when colonized by either Glomus caledonium or Glomus intraradices. The standard error is in brackets

Flax Medic Tomato

G. caledonium

G. intraradices

42 (3) 38 (5) 25 (8)

94 (15) 62 (5) 83 (12)

Data from Smith et al. (2004).

hairs even in plants such as tomato, which showed no growth response to AM colonization; therefore, lack of a growth response to an AM fungus does not mean that the fungus makes no contribution to phosphorus uptake. Much work with AM fungi has been performed with young plants grown in media that are not natural soils, where nutrients may be in uncommon forms and without the microbes that would normally be part of the mineralization processes, raising questions as to the transferability of results to fieldgrown plants. In managed production systems where fertilizers and manures are applied, the carbon cost of maintaining the fungus may exceed the benefits of its activities in phosphorus uptake, and there has been little evidence to date for a beneficial role of AM fungi in improving productivity (Ryan et al., 2002). Ryan and Graham (2002) reviewed literature of field-based studies and found that even when phosphorus availability was low, and AM colonization levels were high (as on some long-term organic farms), there was no obvious net benefit from the symbiosis. They concluded that AM fungi “do not play a vital role in the nutrition and growth of plants in many production-orientated agricultural systems” (p. 263). Rhizodeposition of carbon compounds from roots provides a source of energy to a wide variety of soil microorganisms and results in rhizosphere soil having different chemical, physical, and biological properties

33

to the bulk soil (Jones et al., 2009). These deposits affect nutrient availability in multiple ways. For example, surfactants present in root mucilage can affect phosphorus adsorption to increase the amount of phosphorus in solution and thereby increase availability to the plant; they also reduced net rates of ammonium consumption and nitrate production in soil (Read et al., 2003). Rhizodeposits may also stimulate microbial growth, promoting a wide range of effects beneficial to plant growth (Lambers et al., 2009). Exploiting genotypic variation in root properties to improve nutrient capture Case studies with genotypes As detailed throughout this book, there is much interest in exploiting genotypic differences in the uptake of nutrients (especially of nitrogen and phosphorus), and particularly in improving the efficiency with which resources are used. Kirk et al. (1998) summarized the root factors contributing to phosphorus uptake efficiency as: 1. Root geometry—differences in root length and its distribution in soils, root hair length, and density, root diameter, and so on. 2. Mycorrhizal effects—differences in the extent or rate of infection, or species of mycorrhizal fungus. 3. Solubilization effects—differences in phosphorus solubility close to the root surface arising from changed soil chemical conditions. This is a complex set of properties that produce interrelated effects on internal, physiological efficiency and the efficiency of recovery (see Ladha et al., 2005 for definitions). The interactions arise mainly

34


Table 2.2. Root growth parameters for four genotypes of common bean grown in containers of an oxisol for 14 days. Values are the mean of four replicates with the standard error shown in brackets

Genotype −1

Total root dry weight (g plant ) Total root length (m plant−1) Number of basal roots Relative total root growth rate (day−1) Relative total root elongation rate (day−1)

Tostado

Porrillo Sintetico

Carioca

HAB 229

0.38 (0.03) 65.9 (23.9) 252 (14) 0.20 (0.01) 0.48 (0.03)

0.23 (0.05) 23.9 (2.6) 171 (22) 0.20 (0.04) 0.38 (0.03)

0.27 (0.04) 35.1 (5.0) 271 (39) 0.18 (0.01) 0.40 (0.03)

0.28 (0.01) 49.6 (15.6) 216 (44) 0.25 (0.01) 0.42 (0.02)

Data from Lynch and van Beem (1993).

because any additional nutrients provided by externally efficient roots may also stimulate root growth. For example, model simulations of rice by Wissuwa (2003) showed that small changes (22%) in root diameter or internal efficiency had large effects (threefold) on phosphorus uptake. The same result could be achieved by a 33% increase in root external efficiency, but only 10% of the threefold increase in phosphorus uptake was directly attributable to the direct effect of increased external root efficiency, with 90% due to enhanced root growth as a consequence of higher phosphorus uptake per unit of root. Wissuwa (2003) concluded that large genotypic differences in phosphorus uptake from phosphorus-deficient soils can result from small differences in tolerance mechanisms and that these small changes will be difficult to detect as changes in recovery efficiency because they are likely to be overshadowed by the effects on root growth. The importance of different root architecture in response to soil conditions, or as a consequence of genotypic differences in root growth, for nutrient uptake is starting to emerge. Lynch and van Beem (1993) grew four genotypes of common bean representing distinct shoot growth habits (erect determinate, erect indeterminate, prostrate indeterminate, and climbing) in containers of an oxisol and measured a range of root

parameters up to 14 days after planting. Table 2.2 shows that there were significant differences between the genotypes after 14 days in root length and mass, number of roots arising from the base of the hypocotyls (basal roots), and root growth and root elongation rates. The phosphorus-efficient genotype Tostado, which grows well in highly acidic, infertile soils in Rwanda, had the most vigorous seedling root system, which was highly branched and had numerous basal roots, whereas the landrace Porrillo sintetico, which grows well on fertile soils in South America, had a smaller, less branched root system. Such results demonstrate that substantial genetic variability exists for root traits that determine the relative distribution of roots in different soil layers, and thereby influence the acquisition of resources. Liao et al. (2004) exploited this variation by crossing deep-rooted and shallow-rooted genotypes of bean to obtain recombinant inbred lines, and found that lines with the highest phosphorus acquisition efficiency had shallower root systems. At least two factors are believed to contribute to this greater phosphorus efficiency of shallower root systems compared with deeper root systems: first, spatial coincidence of root and resource; and second, lower intra-plant inter-root competition. The latter is an important consideration because at typical planting densities of crops, inter-


root competition has been found to be more important in determining the efficiency of phosphorus uptake than root competition between plants (Rubio et al., 2001). Significant correlations between root architectural features and phosphorus uptake and phosphorus use efficiency have also been found in a range of other dicotyledonous species. For example, Hammond et al. (2009) found that in a wide range (355) of Brassica oleracea L. accessions, many measures of phosphorus use efficiency were correlated with root development and architecture, especially with lateral root number, length, and growth rate. Physiological phosphorus use efficiency varied four- to fivefold in a range of commercial genotypes, suggesting that there is potential to breed more efficient cultivars. Similarly Ao et al. (2010) employed two soybean genotypes together with their 88 recombinant inbred lines and found that phosphorus use efficiency was significantly correlated with root length, surface area, root width, and root depth. These correlations together with the high broad-sense heritability values of the root traits suggest the feasibility of screening phosphorusefficient genotypes through selection of simple root traits in the field. In cereals, there is also ample evidence of genetic variation in root architecture (e.g., Chloupek et al., 2006; Manschadi, 2008; Hargreaves et al., 2009), although there has been relatively little work so far to relate these features to nutrient use. Wojciechowski et al. (2009) explored the effects of semidwarfing and dwarfing alleles on root growth of young wheat seedling grown in a range of media. No significant differences in root length were found between semi-dwarfing lines and the control lines, but the dwarfing lines had significant effects on early root growth although no effect on early shoot growth. These results suggest a direct effect of dwarfing genes on root growth during

35

seedling establishment, although the mechanism for this is uncertain but probably involving the gibberellic acid pathway (Wojciechowski et al., 2009). This study also found that root length of the dwarf lines was significantly increased relative to the control lines when grown in gel but decreased when grown in soil, thereby raising questions about the relationship between results obtained in gel-based experiments and field performance in soils. Similar concerns were evident in the studies of Hargreaves et al. (2009) with genotypes of barley. Quantitative Trait Locus (QTL) studies The development of DNA-based molecular markers has opened up opportunities for identifying the genetic factors (QTL) underpinning root traits influencing nutrient acquisition and efficiency. For example, the tolerance of rice to phosphorus deficiency was investigated by Wissuwa et al. (1998) using 98 backcross inbred lines derived from a cross of the traditional Indian indica variety Kasalath, which is tolerant of phosphorus deficiency with the modern Japanese japonica variety Nipponbare, which does not yield well under low phosphorus conditions. Three QTL explained 45% of the variation in dry weight and four QTL explained 55% of the variation in phosphorus uptake. For both traits, the QTL linked to marker C443 on chromosome 12 had a major effect, and this was confirmed in a complementary study of tiller numbers under conditions of phosphorus deficiency. One of the minor QTL associated with tolerance to phosphorus deficiency coincided with a locus found in another study to account for 10% of the variation in total root number. Subsequent transference of the major QTL linked to marker C443 on chromosome 12 into Nipponbare by three backcrosses resulted in an improved line that

36


increased phosphorus uptake by 170% and grain yield by 230% compared with Nipponbare when grown in the field on a low-phosphorus andosol (Wissuwa and Ae, 2001). This approach meant that it was possible to combine the high phosphorus uptake of the traditional variety Kasalath with the high harvest index of the modern variety to produce a plant that yielded 21% more grain under low phosphorus conditions, even though it produced only 58% of the shoot weight and 68% of the root weight of Kasalath. As described, earlier, shoot-borne (adventitious) roots play a significant role in the phosphorus nutrition of bean. Ochoa et al. (2006) screened a population of recombinant inbred lines of P. vulgaris L. under high and low phosphorus conditions in glasshouse and field conditions, and found that 19 QTLs accounted for 19–61% of the total phenotypic variation for adventitious root traits in the field and 128–39% under glasshouse conditions. Under low phosphorus conditions in the field, two major QTL located on linkage groups B2 and B9 accounted for 61% of the observed phenotypic variation. The identification of such QTL suggests that the use of markers for specific adventitious root traits might be possible to assist in breeding beans for lowphosphorus soils (Ochoa et al., 2006). Identifying appropriate traits and markers to assist the breeding of nutrient-efficient genotypes is emerging as a major challenge in the development of more sustainable cropping systems (Foulkes et al., 2009). However, it is important that the screening for such markers is undertaken in a number of conditions because there may be a large interaction between the genes/markers identified and the environment. George et al. (2011) found significant variation in the phosphorus nutrition of spring and winter barley genotypes, but the variation was different between crops grown with conventional

plow and minimum tillage. Results of an association mapping exercise showed that the associations between phosphorus use and specific markers were different in the two cultivation systems, implying that for multimechanistic traits such as phosphorus use efficiency, robust markers will emerge only after tests under different climatic and agronomic conditions. Management to optimize capture by root systems A major means of achieving efficient nutrient use is to ensure that the availability of individual nutrients is matched to crop demand in time and space. Management options that can increase the efficiency of nutrient use from fertilizers focus on a combination of increasing fertilizer use during the growing season when the fertilizer is applied, and decreasing fertilizer losses so that the recovery of any residual fertilizer by subsequent crops can be maximized. Placement of fertilizers For mobile nutrients such as nitrate, proximity to a root is less crucial for uptake by the plant than that of an immobile nutrient such as phosphate, so that placement techniques for phosphorus fertilizers have generally been more widely investigated than those for nitrogen. Field experiments on fertilizer placement have typically compared applications as a band in, or near, the row at planting with applications broadcast on the soil surface and then incorporated. While phosphorus applications may be drilled with the seed in the same row, there is much work that demonstrates that nitrogen and potassium fertilizers applied in this manner will damage the seed and/or seedling and reduce germination (Cooke, 1982). The advantages of fertilizer placement vary depending on the fertilizer, crop, soil,


and climate factors, so that prediction of effects is imprecise at present. Banded phosphorus typically gives higher yields than broadcast phosphorus on soils low in phosphorus at low rates of application, with the yield advantage decreasing and eventually reversing as both native soil phosphorus and/or amount of phosphorus applied increase. For example, Welch et al. (1966) found that banded phosphorus gave greater yields of maize than broadcast phosphorus at application rates 90%) is present as cysteine and methionine residues in proteins (De Kok et al., 2002a; Haneklaus et al., 2007a,b; Zhao et al., 2008). On a molar basis, the organic N : S ratio of the vegetative part of crop plants is generally around 20:1. The sulfur residues of cysteine and methionine in proteins are of great significance for their structure, conformation, and physiological functioning. For instance, the thiol group of the cysteine residue in proteins is involved in redox/disulfide exchange reactions, which have significance in DNA and protein synthesis and activation/deactivation of enzymes (De Kok et al., 2002a; Haneklaus et al., 2007b; Zhao et al., 2008). Protein thiols are also imported in substrate binding and in metal-sulfur clusters. Seed storage proteins may contain high levels of cysteine and methionine residues, which are utilized as a sulfur source during germination. Plants contain a wide variety of other organic sulfur compounds, for example, glu-

tathione, sulfolipids, and secondary sulfur metabolites, which are of great significance in plant functioning and its tolerance to biotic and abiotic stresses, and protection against herbivory (De Kok et al., 2002a; Bloem et al., 2007; Haneklaus et al., 2007a,b; Hell and Kruse, 2007; Zhao et al., 2008). Glutathione, the predominant water-soluble nonprotein thiol compound present in plant tissue, functions in the reduction of sulfate as an electron donor and metabolic regulator, as the transported form of reduced sulfur, as the precursor of metal-binding phytochelatins, and in the enzymatic detoxification of xenobiotics via conjugation, catalyzed by glutathione S-transferases (North and Kopriva, 2007; Sirko and Gotor, 2007). Moreover, via thiol/disulfide exchange, glutathione is involved in the enzymatic and direct detoxification of reactive oxygen species (De Kok and Stulen, 1993; North and Kopriva, 2007). Sulfoquinovosyl diacylglycerol is a prominent anionic lipid in chloroplast membrane and its content may account for 3–8% of the total organic sulfur content (Stulen and De Kok 1993; Benning, 1998; Benning et al., 2008). Some plant species contain high levels of secondary sulfur metabolites, for example, glucosinolates in Brassica and alliins in Allium, which may have significance in plant–herbivore and plant–pathogen interactions (De Kok et al., 2002a; Haneklaus et al., 2007b; Zhao et al., 2008). Humans and animals rely on plants as source of reduced sulfur, and balanced sulfur nutrition of crops is essential for optimal food quality and security (Zhao et al., 1999, 2008). Crop sulfur status combined with levels of sulfur fertilizer will also have effects on selenate and molybdate accumulation (Shinmachi et al., 2010). Crop sulfur nutrition Adequate and balanced sulfur nutrition is essential for optimal crop yield and quality.

SULFUR NUTRITION IN CROP PLANTS

The overall sulfur demand for optimal crop yield and quality varies strongly between species and ranges from 0.3 kg S t−1(sugarcane) to 17 kg S t−1 (oilseed rape, mustard). The total uptake of sulfur by crops, the crop sulfur content times its yield per hectare, ranges from 10–40 kg S ha−1 for grasses and cereals to 50–100 kg S ha−1 for high sulfur-demanding crops such as Brassica (Haneklaus et al., 2003, 2007a,b, Zhao et al., 2008). Groundwater contains generally 0.08–1.6 mM sulfate and is of great significance in crop sulfur nutrition at sites where roots have direct access or are irrigated with it (Haneklaus et al., 2007b). In some regions, dry and wet deposition of atmospheric sulfur from salt spray and sulfurous air pollutants may also contribute to the crop sulfur supply since atmospheric sulfur deposition may range from 20 kg S ha−1 in heavily polluted areas (Haneklaus et al., 2003). In different regions of the world, incidences of sulfur deficiency in agricultural crops and grassland have been reported, which can be corrected by sulfur fertilizer application. The dose of sulfur fertilizer (rate of application) depends on the crop sulfur demand, soil type, and management, and on atmospheric sulfur deposition. Sulfur fertilizer recommendation rates vary between countries and range, for example, for cereals from 10–50 kg S ha−1 and for oilseed rape from 20–100 kg S ha−1 (Walker, 2002; Haneklaus et al., 2007a,b). Balanced sulfur fertilization is also essential for optimal nitrogen use efficiency and for preventing negative environmental side effects such as nitrogen leaching (Haneklaus et al., 2007b; Zhao et al., 2008). A fertilizer rate of approximately 0.17 kg kgN−1 (oilseed plants) or 0.1 kg kgN−1 (cereals and seeded grass) appears to be advisable (Walker, 2002). The timing and form of sulfur fertilizer is also of great importance for optimal crop sulfur nutrition. In contrast to nitrogen (and

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several other minerals), the rate of remobilization of sulfur from older to young tissue appears often to be low in crops. Consequently, a sufficient soil sulfur supply to the root may be required during the entire vegetative and generative growth period for optimal crop production and quality. If crops are fertilized with either elemental or organic sulfur, the rate of mineralization may hinder the sulfur availability required for optimal crop production since generally plants rely on sulfate taken up by the root as the primary sulfur source for growth (Eriksen, 2002; Haneklaus et al., 2007a,b). Sulfate is highly water-soluble and is carried through the soil toward the root surface by mass/bulk flow. The transfer of sulfate from the soil water into the root cells across the plasma-membrane is an active process. Upon its uptake, sulfate may be transported symplastically through plasmodesmata from cell to cell radially through the cortex and endodermis into the root stele (Hawkesford and De Kok 2006). If sulfate is absorbed by the root apoplastic water, then the endodermis will be the selective cell layer for the active uptake of sulfate. In the stele, the sulfate is transferred into the xylem (xylem loading) and transported by the transpiration stream to the shoot (by mass/bulk flow). Distribution of sulfate from the xylem to sink tissue (vascular transport) occurs via active loading/ modulated transfer of the sulfate from the xylem into the phloem via phloem companion/transfer cells (Anderson, 2005). In most crop species, the major proportion of the sulfate taken up is reduced in the plastids (roots) and chloroplasts (shoot), and subsequently further assimilated into organic sulfur compounds (De Kok et al., 2002a; Hawkesford and De Kok, 2006). The remaining sulfate—in some species a substantial proportion of the sulfate taken up—is transferred into the vacuoles of root and shoots cells.

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In contrast to nitrate, the remobilization and redistribution of the vacuolar sulfate is rather slow, and it may be even too slow to keep pace with the growth of the plant under temporary sulfur-limitations and sulfurdeficient plants may still contain detectable levels of sulfate (Cram, 1990; Hawkesford, 2000). Sulfurous air pollutants may act as both toxin and nutrient for plants, and in addition to sulfate taken up by the roots, plants are also able to utilize sulfur gases, namely SO2, H2S, taken up by shoot as sulfur source for growth (De Kok et al., 2007, 2009). The stomatal opening is generally the limiting factor for the uptake of SO2 by the shoot, since SO2 is highly soluble in the water of the mesophyll cells wherein it is rapidly dissociated upon liberation of H+ ions. The (bi) sulfite formed may be directly assimilated into organic sulfur compounds or enzymatically or nonenzymatically oxidized to sulfate and subsequently transferred into the vacuoles (De Kok et al., 2007, 2009). In contrast to SO2, the uptake of H2S by the shoot appears to be determined by the rate of its metabolism into cysteine in the mesophyll cells rather than stomatal opening (De Kok and Tausz, 2001; De Kok et al., 2002b, 2007, 2009). Evidently, atmospheric levels of ≥0.05 μl L−1 SO2 and H2S may substantially contribute to plant sulfur nutrition (De Kok et al., 2007, 2009). Nevertheless, it is unclear as to what extent metabolism contributes to the detoxification of the absorbed sulfur gases since there is no clear-cut transition in the level/rate of metabolism of the absorbed sulfur gases and their phytotoxicity (De Kok et al., 2009). Sulfate uptake, distribution, and assimilation in plants The uptake of sulfate by the root, its transport from root to shoot, and the subcellular distribution of sulfate in plants is mediated

by sulfate transporters, generally acting as SO42-/H+ symporters, driven by a proton gradient generated by ATPases (Cram, 1990; Clarkson et al., 1993). Sulfate transporters (see also Chapter 1) are transmembrane proteins containing 12 hydrophobic membrane-spanning domains (MSDs) and a sulfate transport/antisigma-factor antagonists domain (STAS domain) at their C-terminal region (Hawkesford and Smith, 1997; Hawkesford, 2003). The STAS domain possesses a conserved loop with a potentially phosphorylated-conserved serine residue, which may be involved in regulation of the sulfate transporters (Fourcroy et al., 2005). Distinct sulfate transporters are involved in the uptake, transport, and distribution of sulfate in the plant. For instance, Arabidopsis, Brassica, rice, and wheat contain 10–14 different sulfate transporter genes. The sulfate transporters have been classified in up to five different groups according to their cellular and subcellular expression and possible functioning in the plant (Hawkesford, 2003, 2007, 2008; Buchner et al., 2004a,b, 2010; Hawkesford and De Kok, 2006; Parmar et al., 2007). The uptake of sulfate by the root plasma membrane is mediated by so-called highaffinity Group 1 sulfate transporters, which have an apparent Km for sulfate around 1.5– 10 μM (Clarkson et al., 1993; Smith et al., 1995, 1997; Davidian et al., 2000; Hawkesford and Wray, 2000; Hawkesford, 2003, 2007, 2008; Smith and Diatloff, 2005; Hawkesford and De Kok 2006). Within Group 1 in Arabidopsis, three different sulfate transporters have been characterized. The sulfate transporters Sultr1;1 and Sultr1;2 are responsible for primary sulfate uptake by the roots and are localized in the epidermis, cortex, and root hairs (Takahashi et al., 2000; Shibagaki et al., 2002; Buchner et al., 2004a,b, 2010; Takahashi, 2005; Yoshimoto et al., 2002, 2007). Sultr1;2 appeared also to


be particularly important for the uptake of selenate in Arabidopsis (El Kassis et al., 2007). Sultr1;3 is presumably involved in phloem loading of sulfate (Yoshimoto et al., 2003). The abundance and expression of the Group 1 sulfate transporters in roots is species specific. For instance, in roots of dicotyledons (e.g., Arabidopsis, Brassica), Sultr1;2 was the sole constitutively expressed sulfate transporter present, whereas Sultr1;1 was only expressed upon sulfate deprivation (Buchner et al., 2004a,b; Koralewska et al., 2007, 2008, 2009a,b; Parmar et al., 2007). In the monocotyledon wheat, however, the Sultr1;2-type transporter appeared to be absent in the roots, and here the Sultr1;- type sulfate transporter was expressed (Buchner et al., 2010). Group 2 sulfate transporters are so-called low-affinity transporters with an apparent Km for sulfate > 100 μM and are involved in the distribution (vascular transport) of sulfate in the plant (Hawkesford, 2003; Hawkesford et al., 2003a,b). Sultr2;1 is localized in the xylem parenchyma and pericycle cells of roots and in the xylem and parenchyma cells of shoot, whereas Sultr2;2 is localized in the root phloem and leaf vascular bundle sheath cells (Takahashi et al., 2000). Five sulfate transporters (in rice six) belong to the less well-characterized Group 3 (Hawkesford et al., 2003a,b; Buchner et al., 2004a,b, 2010). In Arabidopsis, the Sultr3;1, Sultr3;2, and Sultr3;3 sulfate transporters are localized in the leaves (Takahashi et al., 2000; Hawkesford et al., 2003a,b), whereas in Brassica, the Sultr3;2 appeared exclusively to be present in the root, and Sultr3;3 in leaves, stem, and roots (Buchner et al., 2004a,b). In Brassica, Sultr3;4 appeared only to be present in the stem and Sultr3;5 in the roots (Buchner et al., 2004a). In wheat, however, Sultr3;2 was not expressed, whereas Sultr3;1, Sultr3;3 Sultr3;4, and Sultr3;5 appeared to be present in both root and shoot, although their level

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of expression was relatively low (Buchner et al., 2010). Until now the role of the Group 3 sulfate transporters is poorly understood, but an enhanced activity of Sultr2;1 and increased sulfate uptake capacity were demonstrated for Sultr3;5 coexpressed with Sultr2;1 in Arabidopis (Kataoka et al., 2004a; Takahashi, 2005). Two Group 4 sulfate transporters have been identified in roots and shoots of Arabidopsis and Brassica, and only one in rice and wheat (Hawkesford, 2008; Buchner et al., 2010). These transporters are localized in the tonoplast and appear to function in the vacuolar unloading of sulfate (Kataoka et al., 2004b; Takahashi, 2005; Hawkesford, 2007, 2008). The Group 5 transporters are quite distinct from the other sulfate transporter groups since they do not posses the STAS domain (Hawkesford, 2003). Two Group 5 transporters have been identified in Arabidopsis and rice, and one in Brassica (Hawkesford, 2003, 2008). In Brassica napus, Sultr5;1 is present in the root, stem, and leaves and is localized in the tonoplast (Hawkesford et al., 2003b; Parmar et al., 2007). In Arabidopsis, transporter AtSultr5;2, appears to be a high-affinity molybdenum transporter and has been renamed MOT1 (molybdenum transporter 1; Tomatsu et al., 2007; Baxter et al., 2008). It is evident that sulfate may also be transferred across membranes via so-called rapid activated depolarization-activated R-type anion channels, and sulfate-selective anion channels have been characterized in hypocotyls, the root epidermis, and guard cells (Roberts, 2006). The physiological role of the sulfate selective anion channels in sulfate transport and distribution still needs to be assessed, but they may be involved in sulfate homeostasis and may have significance in sulfate efflux from cells and roots preventing toxic accumulation of cytosolic levels within the cells (Roberts, 2006).

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Moreover, sulfate-selective anion channels may also play a role in the radial movement of sulfate from the epidermis to the xylem (Hawkesford, 2007). Sulfate needs to be transported into the stroma of the plastids in roots and chloroplasts in the shoots, where it is reduced to sulfide. The transfer of sulfate over the plastid/chloroplast membrane is yet unresolved, but may be mediated by the triose-

phosphate/phosphate translocator and/or an ABC-type transporter (membrane pore proteins; Hawkesford, 2008). Sulfate is first activated to adenosine 5′ phosphosulfate (APS) by adenosine triphosphate (ATP)sulfurylase prior to its reduction to sulfite by APS reductase (Hell, 1997; De Kok et al., 2002a; Kopriva and Koprivova, 2003, 2004; Saito, 2004; Kopriva et al., 2008; Fig. 14.1). APS may also be further phosphorylated by

Glutathione ADP + Pi glutathione synthetase glycine + ATP g-Glutamyl-cysteine ADP + Pi

g-glutamyl-cysteine synthetase

glutamate + ATP Methionine

Cysteine

Proteins

acetate O-acethlserine (thiol)lyase O-acetylserine H2S

Sulfide 6Fdox sulfite reductase 6Fdred Sulfite

SO2

SQDG

AMP+GSSG OXIDATION

APS reductase 2GSH APS kinase APS

PAPS ATP

SSM

ADP

PPi ATP sulfurylase ATP Sulfate

Sulfur metabolism in plants. APS, adenosine 5′-phosphosulfate; Fdred, Fdox, reduced and oxidized ferredoxin; GSH, GSSH, reduced and oxidized glutathione; PAPS, adenosine 3′-phosphate 5′-phosphosulfate; SQDG, sulfoquinovosyl diacylglycerol; SSM, secondary sulfur metabolites; AMP, adenosine monophosphate; GSSG, oxidized glutathione; PPi, pyrophosphate.

Fig. 14.1.


APS kinase to adenosine 3′ phosphate 5′ phosphosulfate (PAPS), which is the precursor of secondary sulfur metabolites (e.g., glucosinolates). Sulfite is also the sulfur donor for sulfoquinovosyl diacylglycerol (SQDG) biosynthesis, the major sulfolipid present in plants tissue. Sulfite is reduced to sulfide by sulfite reductase and is incorporated into cysteine by cysteine synthase, an enzyme complex consisting of serine acetyltransferase (catalyzes the synthesis of Oacetyl-L-serine) and O-acetyl-L-serine (thiol)lyase (catalyzes the synthesis of cysteine. The synthesis of cysteine is one of the major direct links between sulfur and nitrogen assimilation in plants. Cysteine serves as the sulfur donor for the synthesis of methionine, and both amino acids are incorporated into proteins (Hoefgen and Hesse, 2007). Cysteine is also the precursor for several other sulfur compounds including glutathione (De Kok et al., 2002a, 2005). From localization and genomic organization studies it has become evident that plants may contain different isoforms of the enzymes involved in the sulfate reduction pathway (Kopriva and Koprivova, 2003, 2004; Kopriva et al., 2008). It is evident that APS reductase and sulfite reductase are exclusively present in the chloroplasts/plastids, whereas ATP sulfurylase may also be present in the cytosol and mitochondria, and APS kinase also in the cytosol. The biosynthesis of cysteine occurs in the chloroplast, cytosol, and mitochondria; however, the abundance of serine acetyltransferase and O-acetyl-L-serine (thiol)lyase may strongly vary between cellular compartments (Kopriva and Koprivova, 2003; Kopriva et al., 2008). Regulation of uptake, distribution, and assimilation of sulfate in plants The uptake and assimilation of sulfate is controlled by the plant sulfur demand for

301

growth (plant sulfur content times growth rate), which ranges from 10 to 100 μmol g−1 dry weight day−1 for different crop species (Haneklaus et al., 2003, 2007a,b; Hawkesford and De Kok, 2006; Zhao et al., 2008). The sulfate concentration in soil water around the root may be quite variable and ranges from 0.2 to 1600 μM, and crop plants need the ability to regulate the overall sulfate uptake and assimilation efficiency in order to keep up with the sulfur demand for growth (Cram, 1990; Clarkson et al., 1993; Haneklaus et al., 2003, 2007a,b: Hawkesford and De Kok 2006; Zhao et al., 2008). The uptake and assimilation of sulfate may be modulated by changing of the activity of the sulfate transporters and the enzymes involved in the sulfur reduction pathway. Evidently, the primary controlling factor in sulfur utilization is the uptake of sulfate by the root. The Group 1 sulfate transporters, which are responsible for the primary uptake of sulfate by the roots, not only have a very high affinity for sulfate, but also their activity is rapidly affected and adjusted to variation in sulfate supply to the roots and the overall sulfur status of the plant. For instance, the uptake of sulfate in Brassica, a species characterized by its high sulfur content and growth, was adjusted to the sulfur demand for growth, even at sulfate concentrations close to the Km of the Group 1 high-affinity sulfate transporters, by an upregulation of sulfate transporter activity of the roots (Koralewska et al., 2007). Plants were able to maintain their growth rate and high sulfur content when grown at 5 and 10 μM sulfate in the root environment (Koralewska et al., 2007). Moreover, if plants were able to utilize foliarly absorbed H2S as a sulfur source, this resulted not only in a downregulation of expression and activity of APS reductase (sulfate reduction) in the shoot but also in a decrease in expression and activity of the sulfate transporters in the root (Westerman et al., 2000, 2001a,b;

302


Koralewska et al., 2008). Sulfate deprivation generally results in a rapid upregulation of the expression of the high-affinity Group 1 sulfate transporters in the roots and, upon prolonged deprivation, also in the shoot (Buchner et al., 2004a,b, 2010; Koralewska et al., 2007, 2008, 2009a; Parmar et al., 2007; Stuiver et al., 2009; Shinmachi et al., 2010). Furthermore, the Group 2 (vascular transport) and Group 4 transporters (vacuolar efflux) are highly upregulated in the root and that of Group 4 transporters also in the shoot (Parmar et al., 2007; Stuiver et al., 2009; Koralewska et al., 2007, 2008, 2009a; Buchner et al., 2004a, 2010; Shinmachi et al., 2010). Apparently upon the occurrence of sulfur deficiency plants try to remobilize and redistribute all possible available sulfate from, for instance, vacuoles and other resources. The expression of Groups 3 and 5, however, was hardly affected by sulfate deprivation. Evidently, an altered expression and activity of sulfate transporters not only may be the consequence of a changed plant sulfur status and/or demand, but also the consequence of an altered root morphology (e.g., the formation of multiple undeveloped lateral roots) upon prolonged exposure to physiological stress conditions, for example, sulfate deprivation (Koralewska et al., 2009a,b) or elevated copper levels in the root environment (Shahbaz et al., 2010). In general, sulfate deprivation also results in a shift in shoot to root biomass partitioning during growth in favor of that of the root (Hawkesford and De Kok, 2006; Haneklaus et al., 2007a,b; Zhao et al., 2008). However, both an altered shoot to root biomass partitioning and the upregulated expression and activity of the Group 1 sulfate transporters upon sulfate deprivation was determined by the absence of sulfate in the root environment rather than by the sulfur status of the plant itself (Koralewska et al., 2008). For instance, if Brassica was simultaneously exposed to sulfate deprivation and to either

SO2 or H2S, at levels sufficient to maintain normal overall biomass production with time, both the decrease in shoot to root biomass partitioning and the enhanced activity of the sulfate transporters were still quite similar to that of sulfate-deprived nonexposed plants (Yang et al., 2006a,b; Koralewska et al., 2008). The signal transduction pathway involved in the regulation of the uptake, transport, and distribution of sulfate is still largely unsolved. It is presumed that the regulation of expression (transcriptional) and/or activity (translational and/or posttranslational) of the sulfate transporters might be signaled or mediated by sulfate itself or by products of the assimilatory sulfate reduction pathway (e.g., sulfide, cysteine and/or glutathione; Hawkesford and De Kok 2006). Furthermore, it has been proposed that the level of the cysteine precursor O-acetylserine would have significance in the regulatory control of the sulfate transporters. On the basis of the current knowledge and commonly applied research approaches, it is still unclear as to what extent measuring changes in concentrations of potential signal compounds and expression of the sulfate transporters, both determined at the wholeorgan level, provides sufficient insight into the actual regulatory control of sulfate uptake at the root cellular level. For instance, in Brassica there was generally no clear relation between the overall tissue levels of sulfate, thiols, and O-acetylserine in the root or shoot and the expression and activity of the sulfate transporters upon variation in sulfate supply (Buchner et al., 2004a; Koralewska et al., 2007, 2008, 2009a,b; Stuiver et al., 2009; Shahbaz et al., 2010). First, the fast upregulation of expression and activity of the sulfate transporters in Brassica upon sulfate deprivation usually already occurs without substantial changes in the overall tissue sulfate and/or thiol (viz. glutathione) levels (Buchner et al., 2006;


Koralewska et al., 2009b), whereas an enhanced level of O-acetylserine in sulfurdeficient plants only reflected a resulting imbalance in sulfur and nitrogen assimilation (Buchner et al., 2004a; Hawkesford and De Kok, 2006). Second, exposure of Brassica to elevated and growth-reducing copper levels in the root environment resulted in an upregulated expression and activity of the sulfate transporters in the root and even occurred at normal and enhanced thiol levels (root, shoot) and normal or enhanced sulfate levels (Shahbaz et al., 2010). The reduction of sulfate in the chloroplast (plastid) is also regulated by the sulfur status of the plant. The affinity of ATP sulfurylase appears to be rather low (Km values range from 0.5–3.1 mM; Stulen and De Kok 1993) and the in situ sulfate concentration may be one of the limiting/regulating steps in sulfate reduction (De Kok et al., 2005). Both the gene expression and measured activity of APS reductase change rapidly in response to variation in sulfur nutrition (Kopriva and Koprivova, 2003; Durenkamp et al., 2007). It is presumably the primary regulation points in sulfate reduction since this enzyme has a fast turnover rate and its activity is the lowest of all enzymes of the sulfate reduction pathway. Sulfide, O-acetylserine, cysteine, or glutathione are likely regulators of APS reductase and may occur both by allosteric inhibition and by metabolite activation or repression of expression of the genes encoding the APS reductase (Hell, 1997; Leustek and Saito, 1999; Kopriva and Koprivova, 2003). The majority of plant cells, including root cells, have the capacity to reduce and assimilate sulfate in their plastids, presumably facilitating local signaling of sulfate uptake as well as distribution and reduction/ assimilation at the cellular level; it is difficult to distinguish local signaling at the cellular level from that at the integrated tissue

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level, namely shoot to root interactions (Hawkesford and De Kok, 2006). A key unresolved issue is the signal transduction pathway in the crosstalk between the sulfate reduction pathway in the chloroplasts/ plastids and the transcription of sulfate transporters/sulfate reducing enzymes in the nucleus. Another key issue is the extent to which H2S, the first product of the sulfate reduction pathway, may function as an endogenous gaseous transmitter in this crosstalk. It is evident that at the cellular pH, H2S is largely undissociated, and in this form it may easily pass through membranes (De Kok et al., 1998, 2007, 2009). Plants grown under normal conditions may produce (and even emit) minute levels of H2S, which has been presumed to be a regulatory step in the homeostasis of the sulfur pools in plants (Schröder, 1993; Bloem et al., 2007). In prokaryotes, a role of sulfide in transcriptional regulation of the cys-operon (for genes involved in sulfur uptake and assimilation) is well documented (Kredich, 1993). Interactions between nitrogen and selenium with sulfur metabolism in plants Similarly to sulfur, plants are able to accomplish the same relative growth rate and plant nitrogen content over a wide range of external nitrate concentrations when grown in nutrient solution (Clement et al., 1978). The net nitrate uptake rate is under the control of an internal regulating mechanism, which adjusts the net nitrate uptake rate to the nitrogen need of the plant, as determined by plant growth and total plant nitrogen content (Ter Steege et al., 1998, 1999). Plants maintain their overall nitrogen and sulfur content within a certain range (Stulen and De Kok, 1993) and this might implicate a mutual regulation of the uptake of nitrogen and sulfur by the root. Upon sulfate deprivation of Brassica, the nitrate uptake rate was

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decreased (Stuiver et al., 1997; Westerman et al., 2000). When sulfate-deprived plants were exposed to atmospheric H2S, an increase in both biomass production and nitrate uptake was observed. However, when Brassica plants, which had access to sulfate in the root environment, were fumigated with atmospheric H2S, both nitrate uptake rate and relative growth rate were unaffected, while sulfate uptake was decreased (Westerman et al., 2000, 2001a). From these data the conclusion can be drawn that changes in nitrate uptake rate are related to changes in growth rate and that there is no direct linkage between the uptake of nitrate and sulfate. Protein synthesis requires inorganic carbon, and reduced nitrogen and sulfur. Coordination of the assimilatory reduction pathways of nitrate and sulfate is therefore necessary, so that appropriate proportions of both sulfur-containing and other amino acids are available for protein synthesis (Brunold et al., 2003; Hoefgen and Hesse, 2007). For the synthesis of sulfur-containing amino acids such as cysteine and methionine for protein synthesis, sufficient reduced sulfate and nitrogen compounds must be available. Evidently, both the expression and activity of APS reductase and nitrate reductase are affected by either sulfur or nitrogen deficiency (Leustek and Saito, 1999). Several compounds might act as signal molecules in the mutual regulation of both pathways. Amino acids and amides such as asparagine and arginine, and also O-acetyl-L-serine, which for instance accumulate under sulfur deficiency, may be related to the decrease in nitrate reductase activity (Migge et al., (2000). Selenium is not an essential plant nutrient and high levels are even phytotoxic. However, the uptake and metabolism of selenium and sulfate are strongly interrelated (Anderson, 1993; Hawkesford and Zhao, 2007; Zhu et al., 2009). Selenate is

an analog of sulfate and its uptake and distribution on plants is facilitated by sulfate transporters (and compete with sulfate), and it may be reduced in the chloroplasts/plastid by sulfate-reducing enzymes in yield in the formation of seleno-cysteine and selenomethionine (Anderson, 1993; Hawkesford and Zhao, 2007; Zhu et al., 2009; Shinmachi et al., 2010; Stroud et al., 2010). The selenometabolites are potentially phytotoxic and strongly enhanced levels of selenate or selenite in the root environment may negatively affect production of crop plants. Selenium is an essential micronutrient for humans and animals, which rely on plants as source for their diet (Hawkesford and Zhao, 2007; Zhu et al., 2009). A controlled uptake of selenium is essential in the biofortification of crops, though may strongly be affected by the sulfur nutritional status (Hawkesford and Zhao, 2007; Zhu et al., 2009; Shinmachi et al., 2010; Stroud et al., 2010). Targets for crop breeding Sulfur use efficiency has seldom been an important target for crop improvement; however, with the widespread appearance of sulfur deficiency symptoms in Europe and elsewhere at the end of the 20th century, the importance of sulfur nutrition has been rerecognized. Legislation controlling pollution has led to substantial reductions in the aerial deposition of sulfur, which was previously at levels to fulfill many crop requirements. Together with the use of high analysis fertilizer containing no sulfur, this led to deficiencies being apparent in crops as evidenced by yield penalties and quality issues (Zhao et al., 1999). Targets for crop improvement either focus on acquisition efficiency and/or conversion into protein, or nutritional issues related to specific sulfur-containing end products. While readily available and relatively cheap fertilizer application can effectively


Fig. 14.2.

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Are there targets to improve sulfur use efficiency in crop plants: the central role of the sulfate

transporters.

correct for sulfur deficiencies, solutions aimed at optimizing acquisition also have merits. Not least, as already noted (Shinmachi et al., 2010), the interaction between sulfate and selenate (and molybdate) can either result in overaccumulation of potentially toxic levels of selenate under deficient conditions, or conversely, sulfur fertilization can result in nutritionally suboptimal levels. The central role of the transporters is evident from Figure 14.2 (see also Hawkesford, 2000). One target may be to select for transporters with altered discrimination between the anions. For improving sulfate acquisition, logical targets may be enhanced by root architectural characteristics and the spatial expression of the high-affinity transporters involved in uptake. The repression of expression of these transporters due to high availability or low demand might be target to encourage luxury uptake. Subsequent to uptake, storage and remobilization patterns will depend on transporter expression. Both the temporary storage and the final sinks may need to be manipulated (see Chapter 1). In the latter cases particularly this may have

advantageous consequences for either resistance to stress or nutritional value. The breeding for low glucosinolate Brassica species was to specifically enhance nutritional quality (Schnug, 1990). Acknowledgments Rothamsted Research is an institute of the Biotechnology and Biological Sciences Research Council of the United Kingdom. Research (MJH) is also supported by the Biotechnology and Biological Sciences Research Council (BB/G022437/1 and BB/ C514066/1) and the Department of Environment, Food and Rural Affairs (WGIN project IF0146). The authors thank Dick Visser for drawing Figure 14.1. References Anderson, J.W. (1993) Selenium interactions in sulfur metabolism. In: Sulfur Nutrition and Assimilation in Higher Plants; Regulatory, Agricultural and Environmental Aspects (eds. L.J. De Kok, I. Stulen, H. Rennenberg, et al.), pp. 49–60. SPB Academic Publishing, The Hague.

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Chapter 15

Iron Nutrition and Implications for Biomass Production and the Nutritional Quality of Plant Products Jean-François Briat

Abstract Iron homeostasis is required to avoid deficiency or toxicity of this metal, which would be deleterious for the physiology and the growth of the plant. Basic knowledge of the molecular and cellular mechanisms establishing iron homeostasis concerns iron uptake from the soil, long-distance trafficking, and subcellular compartmentation and storage. These various aspects and the integration of these mechanisms at the wholeplant level have been studied in detail in the last decade. A direct output of this knowledge will be the development of new breeding strategies and new biotechnological approaches to improve (1) the plant resistance to iron deficiency, and as a consequence, biomass production, and (2) the nutritional quality of plant products, in particular the increase of iron content and bioavailability.

Introduction Agriculture will have to face tremendous changes in the near future. The major chal-

lenges will be increasing biomass productivity, while simultaneously improving plant product quality, and achieving this in a sustainable way within the perspective of a global climate modification involving CO2 concentration and temperature increases (Pretty, 2008). Mineral nutrients are key components of these challenges as they are essential for both plant productivity and quality, and they can, through fertilization, impact the environment. Among minerals, metals such as magnesium, manganese, and iron are essential because of their role in CO2 fixation by the photosynthesis process, iron being a key element in ensuring the electron flow through the Photosystem (PS) II-b6f/Rieske–PSI complex. It is well documented that iron is a limiting factor for biomass production since phytoplankton primary productivity in 30–40% of the world’s oceans is limited by availability of the micronutrient iron (Martin and Fitzwater, 1988). More recently, it was shown that iron was a limiting factor for biomass production by the model higher plant Arabidopsis thaliana (Ravet et al., 2009a). In both cases, the iron storage


312


IRON UTILIZATION IRON STORAGE

BIOMASS PRODUCTION QUALITY OF PRODUCTS

IRON ALLOCATION

IRON UPTAKE

Sensing

Nongrass plants Grass plants

GENOTYPE Iron efficient Iron inefficient

IRON STATUS

AIR : Light, Temperature, CO2

ENVIRONMENT SOIL : pH, Water, N/P, Organic matter

Fig. 15.1. Biomass production and plant product quality as an output of iron homeostasis. The iron status of a plant is not only defined by the quantity of the metal at a given moment. It also includes the redox state of the metal, its speciation with chelating molecules, and its tissular, cellular, and subcellular compartmentalization. It is dependent of the interactions between a given genotype and the various parameters of the environment. This iron status is sensed by the plant and transduced to regulate iron uptake, its distribution throughout the plant, and ultimately its utilization for physiological purposes, or its storage. The output of this iron homeostasis process will directly impact plant biomass and the quality of plant products.

protein ferritin was shown to be necessary to buffer transiently the iron in a safe form (Marchetti et al., 2009; Ravet et al., 2009a), revealing that iron-dependent biomass production requires the control of iron homeostasis. It is also well established that plant product quality in the future must include an improvement of nutritional content and availability. Among the micronutrients, iron is of primary importance because it is the most commonly deficient micronutrient in the human diet, and iron deficiency affects an estimated 2 billion people. In this context, it was proposed that feeding humans safely with enough iron directly within their diet could become possible by using iron-fortified transgenic plants overexpressing ferritin (Newell-McGloughlin, 2008). Reaching

such a goal requires an integrated knowledge of the establishment and control of iron homeostasis in plants, which will be reviewed in the first part of this chapter. The second part of this chapter will address the relationship between iron homeostasis and plant productivity and plant product quality (Fig. 15.1). Iron uptake by the roots Molecular components involved in iron uptake Iron enters the plant via the roots from where it is distributed inside the plant. According to the plant family considered—that is, graminacea plants versus other plants—two

IRON NUTRITION

mechanisms prevail for mining iron from the soil solution. They involve respectively chelation of the ferric iron (Fe3+) by small organic molecules, or its reduction in its ferrous form (Fe2+) prior to transport across the plasmalemma of root epidermal cells. These processes were recently reviewed in detail (Morrissey and Guerinot, 2009), and they will be briefly summarized here prior to considering lesser known aspects of iron fertilization and apoplasmic occurrence of iron. The iron chelation mechanism occurring in graminacea plants relies on the synthesis of methionine derivatives known as phytosiderophores and belonging to the mugineic acid family (Mori and Nishizawa, 1987). Methionine is converted to Sadenosylmethionine (SAM) by SAM synthetase (Shojima et al., 1989), and this enzyme activity shows no difference in irondeficient and iron-sufficient barley roots (Takizawa et al., 1996). Therefore, constitutive SAM synthase activity is likely to be sufficient for mugineic acid (MA) synthesis. Then, nicotianamine synthase (NAS) combines three molecules of SAM to form one molecule of nicotianamine (NA) (Shojima et al., 1989). Barley, rice, or corn NASs are induced in roots at a transcriptional level in response to low iron supply (Herbik et al., 1999; Higuchi et al., 1999, 2001; Inoue et al., 2003; Mizuno et al., 2003). Although NA is produced by both monocotyledons and dicotyledons, the subsequent steps leading to mugineic acid synthesis are specific to grasses. The critical enzymes in this specific pathway are nicotianamine aminotransferase (NAAT) (Takahashi et al., 2001) followed by deoxymugineic acid synthase (DMAS) (Bashir et al., 2006), which catalyze the removal of an amino residue from NA, resulting in the production of 2′-deoxymugineic acid, the precursor of all other mugineic acids. NAAT and DMAS activity are strongly induced by

313

iron deficiency in roots and represent a limiting step in the production of mugineic acids. Subsequent hydroxylation of 2′deoxymugineic acid results in the formation of other members of the mugineic acid family. Two barley cDNAs specifically expressed in iron-deficient roots, HvIDS2 and HvIDS3 (IRON DEFICIENCY SPECIFIC), were shown to encode dioxygenases involved in the production of 3epihydroxy-2′-deoxymugineic acid and 3epihydroxy–mugineic acid (Nakanishi et al., 2000; Kobayashi et al., 2001). In contrast to the biosynthetic pathway of mugineic acids, the molecular mechanisms of phytosiderophore secretion in the rhizosphere remain poorly understood. It has been suggested that vesicular transport may be involved since the appearance of swollen vesicles in iron-deficient barley roots correlates with phytosiderophore release. The production of phytosiderophores is increased in response to iron deficiency, and tolerance to iron deficiency is correlated to the quantity and the type of phytosiderophores secreted (Negishi et al., 2002). The yellow stripe 3 (ys3) maize mutant shows interveinal chlorosis characteristic of iron deficiency, due to a defect in MA secretion, and can be rescued by exogenous application of MAs or cocultivation with wild-type plants (Lanfranchi et al., 2002). The uptake of Fe(III)–PS complexes in grasses occurs through a specialized transporter. The gene encoding this transporter was discovered by investigating the yellow stripe 1 (ys1) mutant of maize, which is unable to respond to iron deficiency due to a defect in the uptake of Fe(III)–PS complexes. The ZmYS1 gene encodes a plasma membrane protein belonging to the oligopeptide transporter (OPT) family (Curie et al., 2001). ZmYS1 mRNA and protein are upregulated by iron deficiency in roots and shoots, where ZmYS1 functions as a proton-coupled symporter to transport Fe(III)-PS and Fe(III)-NA (Curie


SHOOT

YSLs Fe(III)-ITP Fe(II)-NA

FRD3 FPN1

? FPN2

I Iron

AHA2 FRO2 IRT1

PHLOEM

FRO3 FRO6 IRTs Fe(III)-citrate

et al., 2001; Roberts et al., 2004; Schaaf et al., 2004). Nongrass plants respond to iron deficiency with both morphological and physiological changes. Adaptative morphogenesis of roots in response to iron deficiency includes root hair formation, swelling of root tips, as well as enhanced lateral root development and reduced lateral root growth (Schmidt, 1999). +H-ATPases are involved in these processes, and it was recently reported that, in A. thaliana, two out of 12 + H-ATPase isoforms participate to establish the root responses to iron deficiency. The + H-ATPase encoded by the AHA2 gene is required to acidify the rhizosphere, whereas the one encoded by the AHA7 gene promotes root hair development (Santi and Schmidt, 2009). In addition to acidification, the second physiological response to iron deficiency in nongrass plants is an enhanced Fe3+ reduction capacity of the roots (Yi and Guerinot, 1996). Ferric reduction takes place at the plasma membrane of root epidermal cells. It catalyzes transmembrane (TM) electron transport from cytosolic reduced pyridine nucleotides to extracellular iron compounds serving as electron acceptors. The characterization of Arabidopsis mutants (frd1 mutants) lacking induction of Fe3+-chelate reductase under iron-deficient conditions confirms that iron must be reduced prior to its transport and that Fe3+ reduction can be uncoupled from proton release (Yi and Guerinot, 1996). The Arabidopsis Fe3+chelate reductase gene FRO2 has been cloned, based on sequence similarity to the yeast FRE genes (Robinson et al., 1999). FRO2-like genes were identified from other plant species such as pea and tomato (Waters et al., 2002; Li et al., 2004). After its reduction, iron is then transported across the root plasma membrane as the ferrous (Fe2+) form via a divalent metal transporter (Fig. 15.2). In Arabidopsis, the IRT1 gene encodes the founding member of this class of eukary-

XYLEM

314

Va

IRT2 Ve

ROOT

Fig. 15.2. Schematic representation of iron uptake by

Arabidospsis roots and of its long-distance trafficking throughout the plant. Iron from the soil is solubilized by acidification of the rhizosphere, which is mediated by the AHA2 H+-ATPase. Fe(III)-chelates are then reduced by the FRO2 ferric-chelate reductase (belonging to the NADPH oxidase family). The resulting Fe(II) is then transported across the plasmalemma of root epidermal cells by the IRT1 transporter. This rapid intake of iron within cortex root cells being potentially toxic, the metal can be transiently stored (1) in vacuoles (Va), where it is uploaded by the FPN2 transporter belonging to the ferroportin family, or (2) in uncharacterized vesicles (Ve) via the activity of the IRT2 transporter. Iron unloading within the xylem sap requires citrate, which chelates Fe(III) for long-distance circulation; the FRD3 transporter, belonging to the MATE family, has been characterized as a citrate effluxer important for iron translocation from root to shoot by the xylem sap. The ferroportin FPN1 is also involved in iron transport into the xylem vessels. Reduction of Fe(III)-chelates and transport within the shoots requires reductases, likely encoded by the FRO3 and/or FRO6 genes, and transporters of the IRT and YSL families. These latter transporters are important for long-distance transport of iron chelated to nicotianamine, a S-adenosylmethionine derivative, in the phloem sap, where Fe(III) can also be found complexed with small peptides, such as the ITP protein. YSLs are also important for iron cycling between the xylem and the phloem streams.

IRON NUTRITION

otic metal ion transporters (Eide et al., 1996), referred to as the ZIP (ZRT, IRT-like transporters) gene family (Guerinot, 2000), with related sequences in plants, yeast, animals, and humans. IRT1 is a protein with eight TM domains; IRT1 mediates uptake of manganese, zinc, and cadmium in yeast cells (Korshunova et al., 1999). In plants, IRT1 mediates transport of manganese, zinc, cadmium, and cobalt (Vert et al., 2002). Determinants for this broad substrate specificity of IRT1 have been investigated by sitedirected mutagenesis (Rogers et al., 2000). Mutant plants of irt1 are chlorotic and have a severe growth defect in soil, which can be rescued by foliar application of iron (Henriques et al., 2002; Varotto et al., 2002; Vert et al., 2002). IRT1 homologs have also been characterized in pea, tomato, and other plants (Cohen et al., 1998; Eckhardt et al., 2001). Rice has a unique behavior since in addition to the Fe3+-chelate uptake shared by all grass plants, it is also able to acquire iron through the uptake of Fe2+ through an IRT1 ortholog, as observed for nongrass plants (Ishimaru et al., 2006). Moreover, yeast ferric chelate reductase, when expressed in transgenic rice plants, increases the iron efficiency of these plants under iron-limiting conditions, compared with untransformed plants (Ishimaru et al., 2007). Additional factors should be considered in addition to this classical view of the molecular actors of iron uptake by roots. The first concerns the biology of the plant. In addition to the already characterized components of iron uptake, the roles of many other genes are likely to be discovered. This claim is documented by a recent report showing that in A. thaliana, up to 85% of the genes expressed in a particular region of the root are differentially regulated (Dinneny et al., 2008). Indeed, the ability to study iron metabolism in the various cell layers of a root is necessary and will be

315

required to improve our knowledge of these processes. From an agronomical point of view, upstream of the plant processes described above, it is important to consider that iron uptake by crops in the field will depend on the iron status, which can be defined by the availability of this metal being itself dependent of the interaction between a given genotype and the soil conditions (for review see Robin et al., 2008, Fig. 15.1). The solubility of soil iron is in particular considerably affected by the complexation or chelation of Fe3+ by organic ligands. Some of these organic ligands are produced by soil microorganisms (e.g., bacterial siderophores) or secreted by plant roots (organic acids such as citrate, or phenolic compounds). The amount and composition of humic acids of a soil also influence the iron status. The role of humic acids on the availability of micronutrients, including iron, is still a matter of debate that can be explained by their complex action. In the case of iron, humic substances not only contribute to increasing iron bioavailability through their chelating properties, but also have redox properties (Weber et al., 2006). These properties are related to phenolic groups contributing to Fe(III) reduction (Szilâgyi, 1971; Deiana et al., 1995; Chen et al., 2003). The chemical reduction of Fe(III) by humic substances is strongly pH dependent, the highest reduction capacities occurring at pH = 3 (Chen et al., 2003). As pH increases, humic substances are more frequently bound to metal cations and therefore have a decreased reducing ability (Chen et al., 2003). In addition to organic matter, nitrogen fertilization could contribute to determining the fate of iron availability since it has been reported that NO3 nutrition can promote iron deficiency chlorosis of sunflower leaves by inhibiting iron acquisition by roots due to high pH at the root surface (Nikolic and Römheld, 2003).

316


Regulation of iron uptake The iron uptake systems described above are upregulated transcriptionally in response to iron deficiency, both in grass and in nongrass plants (Walker and Connolly, 2008; Fig. 15.3). The orthologous genes of the Arabidopsis AtIRT1 and AtFRO2 genes are not expressed in response to iron deficiency in the tomato fer mutant, suggesting that this gene controls the expression of the uptake system, directly or indirectly (Bereczky et al.,

(A)

(B) Barley/Rice

Arabidopsis

XXX

2003; Li et al., 2004). The corresponding gene was cloned, revealing that it encodes a transcription factor belonging to the basic helix–loop–helix (bHLH) family (Ling et al., 2002). A FER gene ortholog is present in the Arabidopsis genome (Jakoby et al., 2004), able to complement the fer mutation when expressed in this tomato genetic background (Yuan et al., 2005). This gene was independently characterized by Colangelo and Guerinot (2004) and named FIT1 for iron deficiencyinduced transcription factor 1 (Fig. 15.3A).

FRO2 IDE2

IDE1

IDS2

IRT1

IRT1 mRNA RNA

K146

bHLH38

IDEF2

IDEF1

IRO2 RegTFs

IRO2

bHLH39 K171

FIT1

IRT1 protein XXXXXX

XXX

CACGTG

X

FeDRG

FeDRG

Degradation

Transcription factor networks for the regulation of iron uptake and homeostasis in grass and nongrass plants. (A) In Arabidopsis, FIT1 belongs to the bHLH family of transcription factors. It interacts with two other bHLHs (bHLH38 and 39) to regulate the increase in transcript abundance of the FRO2 reductase, and to control the expression of an uncharacterized gene (X) involved in the repression of the IRT1 protein degradation. The ciselement(s) recognized by FIT1 (XXX) are so far uncharacterized. The posttranslational regulation of the IRT1 protein stability requires two lysine residues (K146 and K171), suggesting that ubiquitination and proteasome-mediated degradation could participate in the turnover of this metal transporter. (B) In grass plants, the IDE1 and IDE2 ciselements were initially described within the promoter sequence of the barley IDS2 gene, which encodes a 2-oxoglutarate-dependent dioxygenase required for deoxymugineic acid synthesis. The trans-acting factors IDEF1 and IDEF2 able to bind these regulatory elements have been characterized. IDEF1 also regulates the expression of another transcription factor (IRO2) in response to iron deficiency. The IRO2 transcription factor is either (1) involved in the direct transactivation of some FeDRG (Fe-deficiency-response-genes) by binding to a CACGTG core sequence within FeDRG promoters, or (2) by controlling the expression of IRO2-regulated-transcription-factors (IRO2RegTFs) that will recognize as yet uncharacterized cis-elements (XXXX) within the promoter sequence of some FeDRG. Fig. 15.3.

IRON NUTRITION

FIT1 is required for regulating the FRO2/IRT1 iron uptake system at two different levels. It transcriptionally controls Fe(III)-chelate reductase FRO2 mRNA abundance, and posttranscriptionally controls the amount of the Fe(II) transporter protein IRT1. However, real-time polymerase chain reaction (RT–PCR) indicated that IRT1 and FRO2 transcript levels were reduced in fit-1 mutants grown in sufficient iron. The IRT1 protein, which was reported to be drastically less abundant in –Fe treated fit-1 (Colangelo and Guerinot, 2004), was also accumulated several fold less in fit-1 mutants grown in iron-replete conditions (Séguéla et al., 2008). Therefore, IRT1 and FRO2 are less expressed in fit-1 than in wild type, but they are still regulated by iron availability. Although, FIT1 is important to control the iron uptake machinery, it seems to do so by contributing to the general level of gene expression rather than by controlling the iron starvationinduced response. The specificity of the iron regulation of the uptake system in nongrass plants could therefore be provided by the interaction of FIT with other transcription factors. Indeed, the FIT gene is itself controlled by the iron status of the plant (Colangelo and Guerinot, 2004; Brumbarova and Bauer, 2005), consistent with the hypothesis that regulators could act upstream or interact with FIT to regulate the plant response to iron deficiency. Such a hypothesis is reinforced by the observation that four other bHLH transcription factors participate in the regulation of the iron deficiency response of nongrass plants (Yuan et al., 2005; Wang et al., 2007; Yuan et al., 2008); Two (bHLH38 and bHLH39) physically interact with FIT (Fig. 15.3A), and transgenic plants that constitutively coexpress either bHLH38 or bHLH39 with FIT show iron-independent high-level expression of FRO2 and IRT1 (Yuan et al., 2008).

317

In addition to the transcriptional control of the iron uptake system of roots of nongrass plants described above, a posttranscriptional control of IRT1 and FRO2 has been proposed (Connolly et al., 2002; Connolly et al., 2003). It is based on the observation that transgenic Arabidopsis plants transformed with a p35SCAMV::IRT1 or a p35SCAMV::FRO2 construct overexpress IRT1 and FRO2 transcripts regardless of the iron nutrition status of the plant, whereas the corresponding proteins are accumulated only under iron deficiency conditions. An iron-dependent control of the IRT1 and FRO2 protein stability was suggested, which recently received experimental support (Kerkeb et al., 2008). IRT1 contains an intracellular loop composed of a histidine, which might bind metals, and of two lysine residues (K146 or K171) that could serve as ubiquitination sites, known to be involved in the degradation of protein through the proteasome pathway. Mutation of the histidine or lysine residues did not eliminate the ability of IRT1 to transport iron or zinc. Expression of these variants in transgenic A. thaliana plants revealed that either K146 or K171 is required for ironinduced protein turnover. It was therefore hypothesized by these authors, that iron may signal modification and turnover of the A. thaliana IRT1 protein through K146 or K171 ubiquitination, resulting in the targeting of the protein to proteasome degradation (Kerkeb et al., 2008; Fig. 15.3A). In grass plants, the regulation of the iron uptake system has been studied at the transcriptional level in barley and rice (Fig. 15.3B). The barley IDS2 gene encodes a 2-oxoglutarate-dependent dioxygenase required for deoxymugineic acid synthesis, and is upregulated in response to iron deficiency (Nakanishi et al., 2000). Two cisacting elements of its promoter, named iron deficiency-responsive elements 1 and 2 (IDE1 and IDE2), act synergistically to

318


induce iron deficiency-specific expression of a reporter gene in transgenic plants (Kobayashi et al., 2003). Bioinformatic analysis indicated that many promoters of genes regulated in response to iron deficiency harbor sequences homologous to IDE1 and IDE2. Trans-acting factors interacting with the IDE1 and IDE2 cis-elements have been characterized (Kobayashi et al., 2007; Ogo et al., 2008). The rice IDEF1 protein belongs to the ABI3/VP1 family of transcription factors; in rice, IDEF1 knockdown plants grown under iron deficiency conditions are susceptible to early-stage iron deficiency. This is consistent with the observation that the IDEF1 expression level is positively correlated to the level of induction of known iron-regulated genes, just after the onset of iron starvation. However, this overall IDEF1 trans-activation became less evident in subsequent, later developmental stages. In fact, genes positively regulated by IDEF1 at this early stage all contain the IDE1 cis-element (CATGC) within their proximal promoter regions. These regions are also enriched in RY elements (CATGCA), known to regulate gene expression during seed maturation (Kobayashi et al., 2009). Indeed, expression of several iron deficiency-induced genes encoding late embryogenesis abundant proteins is increasingly regulated by IDEF1 at subsequent, later stages. A dual function of IDEF1 in the iron deficiency response in grass plants was therefore proposed (Kobayashi et al., 2010). This transcription factor would transactivate iron-regulated genes by interacting with IDE1 cis-elements at early stages. Transcriptional transactivation of seed maturation-related genes occurs later on, during the subsequent stages of iron deficiency, via RY elements. In rice, IDEF1 overexpression causes upregulation of OsIRO2, which encodes a bHLH transcription factor (Ogo et al., 2006; Fig. 15.3B). OsIRO2 is strongly expressed in both roots and shoots, specifically in response to iron

deficiency stress, and it has numerous homologs among graminaceous plants. The cisacting sequence bound by IRO2 was determined, and is found upstream of several genes involved in iron acquisition by grasses. The IDEF1 regulation of IRO2 reveals a potential network of transcription factors for the regulation of the iron responses in grass plants. Less information has been reported concerning the IDEF2 protein, which binds to the IDE2 cis-element; it is, however, known that it belongs to the NAC family of transcription factors (Kobayashi et al., 2007; Ogo et al., 2008). Iron distribution and compartmentation throughout the plant Long-distance trafficking of iron Once taken up by root epidermal cells, iron has to move through the symplast of cortical cells prior to reaching the pericycle and being loaded within the xylem vasculature to be transported to the aerial part of the plant via the sap (Fig. 15.2). Due to its reactivity with oxygen, iron will not diffuse freely in the cytoplasm. In A. thaliana, it could be safely stored within the vacuoles of root periphery cells as a consequence of the activity of one of the two ferroportin (FPN2) effluxers (Morrissey et al., 2009), or may reach the pericycle through various mechanisms; one of these mechanisms would require chelation of iron by still uncharacterized chaperones. Alternatively, iron compartmentalization within intracellular vesicles loaded by the IRT2 transporter (a close homolog of IRT1), and acting as a shuttle, has recently been proposed (Vert et al., 2009; Fig. 15.2). Organic acids, and especially citrate, have been suggested to be the main metal chelators in the xylem (Cataldo et al., 1988). It is, however, only very recently that it has

IRON NUTRITION

been unambiguously demonstrated that a triFe(III), tri-citrate complex (Fe(3)Cit(3)) was found in the xylem sap of iron-deficient tomato resupplied with iron. A second complex, a di-Fe(III), di-citrate complex was also detected along with Fe(3)Cit(3), with the allocation of iron between the two complexes depending on the iron to citrate ratio (Rellan-Alvarez et al., 2010). These reports suggest that active root transporters must load iron from the root cortex cells to the xylem and that citrate could play a role in this process. Such efflux iron transporters have recently been characterized at the molecular level in A. thaliana. The FRD3 gene is involved in citrate efflux into the xylem (Rogers and Guerinot, 2002; Fig. 15.2). It is a member of the multidrug and toxic compound extrusion (MATE) family, expressed in the root vasculature, and upregulated twofold in response to iron starvation. Genes involved in the iron deficiency response are constitutively expressed in an frd3 null mutant, consistent with its chlorotic phenotype. However, citrate (at 60% of wild type levels) is still measured in the xylem sap of this mutant, suggesting a role for other effluxers. Indeed, it has been recently proposed that the ferroportin FPN1 effluxer could also participate in the loading of iron into the root vasculature (Fig. 15.2). Yet fpn1 plants show no change in the iron deficiency response (Morrissey et al., 2009). Once in the leaves, Fe(III)-citrate is likely to be the substrate of leaf ferric chelate reductase since such an enzymatic activity has been described in leaf mesophyll cells (Bruggemann et al., 1993). In A. thaliana, some of the FRO genes could be involved in this process (Fig. 15.2), the best candidate being FRO3, and perhaps FRO2, which is also expressed in leaves in addition to roots, although to a much lower level (Mukherjee et al., 2006). Although presenting a low reductase activity when expressed in yeast, FRO6 has expression restricted to green

319

tissues and is regulated by light in a tissueor cell differentiation-specific manner (Feng et al., 2006). In pea, the fact that FRO1 is also expressed in leaves (Waters et al., 2002) makes it a good candidate for the function of leaf ferric reduction. Iron is not only trafficking through the xylem sap; mobility of iron from source to sink tissues via the phloem sap has also been reported (Stephan et al., 1994; Grusak, 1995). One of the molecules identified as a potential phloem metal transporter is NA (Stephan and Scholz, 1993). It is a ubiquitous molecule in the plant kingdom, used specifically in grass plants as a precursor for the synthesis of the siderophores of the mugineic acid family (see the “Molecular components involved in iron uptake” section). The three amino and three carboxy groups in the molecule enable the formation of hexadentate coordination, driving the formation of very stable octahedral chelates with a central metal ion. In vitro, NA is able to form stable complexes with manganese (Mn), Fe(II), and Fe(III), cobalt (Co), zinc (Zn), nickel (Ni), and copper (Cu) (reviewed by Curie et al., 2009). Long-distance transport of the Fe–NA complex, especially in the phloem, requires at least some of the yellow stripe-like (YSL) transporters (Fig. 15.2), a subclass of the OPT family, first identified by the characterization of the maize YS1 transporter of deoxymugineic acid (Curie et al., 2001; Curie et al., 2009). A common feature of the YSL genes is that their expression is limited to the vascular system. The precise localization of their expression to one type of vessel has not been systematically reported, except for A. thaliana AtYSL1 (xylem parenchyma) and Oryza sativa OsYSL2 (phloem companion cells). In other cases, the expression seems to be spread around or between the phloem and xylem, for example, Thlaspi caerulescens TcYSL3, and A. thaliana AtYSL3 or AtYSL5 (for review see Curie et al., 2009). Various

320


physiological roles of YSL proteins have been hypothesized (Curie et al., 2009). They could participate in the unloading of metals from the xylem sap through the uptake by xylem parenchyma cells, and in the loading of phloem sieve tubes via uptake by phloemassociated cells. In addition, their function in the xylem–phloem exchange (Fig. 15.2) could be important in all supporting tissues such as petioles and stems for the fine balance of NA–metal nutrition, and also in young organs or, where xylem is either not as yet differentiated or is interrupted, as for the seed coat and embryo. In A. thaliana seeds, AtYSL1 and AtYSL3 genes are required to maintain the amount of iron, zinc, and copper as well as NA (Le Jean et al., 2005; Waters et al., 2006) and could play important roles in circulating metals from the xylem to the phloem in this organ. In addition to NA, small peptides could also participate in the travel of iron in the phloem (Maas et al., 1988). Indeed, iron transport protein (ITP), a phloem protein of Ricinus communis, has been purified and shown to complex Fe(III) in vivo, but not Fe(II). ITP is a 96-amino acid protein belonging to the late embryogenesis abundant (LEA) family (Kruger et al., 2002). The preference of ITP for ferric iron is in agreement with the observation that only 4% of the total iron in the phloem exudate of R. communis seedlings is in the ferrous form (Schmidke et al., 1999). Although the stability constant (log K = [Fe-NA]/[Fe][NA]) of nicotianamine (NA) for Fe(III) is 20.6, and only 12.8 for Fe(II), the Fe(II)–NA complex possesses an unusual kinetic stability, explaining why NA is found complexed to Fe(II), and not to Fe(III), in the phloem sap (von Wiren et al., 1999). Since there is a low but significant steady-state concentration of ferrous iron in the phloem (Maas et al., 1988), and since the bulk of iron in the phloem is chelated in the Fe(III) form by ITP (Krueger et al., 2002), it is speculated that NA could

shuttle iron by chelating Fe(II) from ITPbound Fe(III) during loading and unloading of the phloem. Such a hypothesis would imply the existence of an as yet uncharacterized redox system within the phloem for ensuring Fe(III)/Fe(II) cycling. Intracellular compartmentation and cellular iron homeostasis Until recently, very little information was available concerning intracellular iron movement in plant cells. However, although still incomplete, our knowledge of the molecules involved in subcellular iron compartmentation has tremendously improved (for review see Morrissey and Guerinot, 2009; Fig. 15.4). For a long time is has been hypothesized that vacuoles were likely to play a major role in iron storage and homeostasis. Indeed, in Arabidopsis, two elegant pieces of work have demonstrated that three transporters were necessary for the efflux and influx of iron in and out seed vacuoles. Vacuolar iron transporter (VIT) 1 is required for delivery of iron into storage vacuoles of vascular cells in the embryo, whereas NRAMP3/ NRAMP4 divalent metal transporters remobilize this vacuolar iron upon germination (Lanquar et al., 2005; Kim et al., 2006; Fig. 15.4). Mutant plants altered in these transporters exhibit severe defects during germination. Mitochondria contain iron proteins important for respiration, and they host a universal iron–sulfur cluster biogenesis machinery (Briat et al., 2007); thus, iron needs to enter this organelle. So far no data have been reported on potential mechanisms. With respect to iron efflux from mitochondria, it has been reported that the STA1 gene from Arabidopsis encodes a homolog of the yeast ATM1p (Kushnir et al., 2001), an adenosine triphosphate binding cassette (ABC) transporter located at the mitochon-

IRON NUTRITION

YSL ?

N Fe(III)

321

VIT1

V

Fe-NA? Fe(II) PIC1?

FRO7

[Fe-S]

Fer Fe(III)

C

? ?

[Fe-S]

Fer Fe(III)

Frataxin

M

NRAMP3/4

ATM3 (STA1)

[Fe-S]

Fig. 15.4. Subcellular distribution of iron within plant cells. The distribution of iron between the various subcellular compartments is an important aspect of iron homeostasis. A reduction step of Fe(III) by the FRO7 reductase is required prior to Fe(II) uptake by the chloroplast (C). It has been suggested that PIC1 could be responsible for this transport activity. Inside the chloroplast, iron can be buffered within the iron storage protein ferritin (Fer) to avoid iron-mediated oxidative stress, or used for [Fe-S] cluster biogenesis, since these organelles are autonomous for this activity. The mitochondria (M) are also autonomous for their iron–sulfur cluster biosynthesis by a universal mitochondrial system conserved in all eukaryote cells, and the STA1/ATM3 ABC transporter is required for mitochondrial iron efflux. Such an iron efflux by the chloroplast has been hypothesized, but so far such a function has not been attributed to any transporter. Iron uptake by plant mitochondria is so far uncharacterized at the molecular level. Although ferritin could also be present in plant mitochondria of some specific cell types, the main form of iron storage in this organelle is achieved by the frataxin protein, as observed in yeast or animal and human mitochondria. The vacuole (V) also plays a major role in iron storage and homeostasis. Iron loading of vacuoles is performed by the VIT1 transporter and likely by some members of the YSL family of transporters. Iron efflux from the vacuole, in particular during seed germination, requires two members of the NRAMP family of transporters, namely NRAMP3 and NRAMP4. NA, nicotianamine; N, nucleus.

drial inner membrane (Fig. 15.4) and involved in the export of iron–sulfur clusters from the mitochondrial matrix to the cytoplasm (Kispal et al., 1999; Lill and Kispal, 2000). A subfamily of three A. thaliana halfmolecule adenosine triphosphate (ATP)binding cassette transporters, ATM1, 2 and 3, have been localized to the mitochondria when expressed in yeast; however, only ATM3 was able to rescue the Δatm1 yeast mutant (Chen et al., 2007). Consistent with this finding, the activity of cytosolic aconitase, an iron–sulfur-dependent enzyme, was strongly decreased across a range of atm3 alleles, whereas mitochondrial and plastid iron–sulfur enzymes were unaffected (Bernard et al., 2009). However, in contrast

to mutants in the yeast and mammalian orthologs, Arabidopsis atm3 mutants did not display a dramatic iron homeostasis defect and did not accumulate iron in mitochondria. The bulk of iron in leaves is found within the chloroplasts, where it is engaged in the photosynthetic process. Iron transport into the plastids is therefore of primary importance in plant physiology, and paradoxically this subcellular iron transport activity is poorly documented. Light was shown to be necessary for efficient iron transport from the leaf veins to the mesophyll cells. Iron uptake studies with isolated barley chloroplasts indicated that this process is also light dependent and requires a Fe(III)-chelate

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reductase activity (Bughio et al., 1997). In agreement with this result, an inwarddirected Fe(II) transport across the chloroplast inner membrane occurs by a potential-stimulated uniport mechanism, as shown by stopped flow spectrofluorometry using inner membrane vesicles (Shingles et al., 2002). At the molecular level, the localization of ferric reductase oxidase 7 (FRO7), one of the eight members of the A. thaliana FRO family, to the chloroplast, reinforces the previous physiological data evidencing the necessity of a reduction step in the iron uptake process by this organelle (Fig. 15.4). Chloroplasts from fro7 loss-offunction mutants have 75% less Fe(III)chelate reductase activity, contain 33% less iron per microgram of chlorophyll than wild-type chloroplasts, and are altered in photosynthetic electron transport. Hence, fro7 seedlings show severe chlorosis and die without setting seeds when germinated in alkaline soil, unless watered with high levels of soluble iron (Jeong et al., 2008). A potential chloroplast iron transporter could be encoded by the A. thaliana PIC1 gene (Duy et al., 2007), which displays homology with cyanobacterial permease-like proteins. Yeast complementation with PIC1 and studies of a pic-1 knockout allele suggest that PIC1 functions in iron transport across the inner envelope of chloroplasts (Fig. 15.4). Cellular iron homeostasis is not only dependent on transporter activities in charge of an adequate iron allocation within various subcellular compartments. At least two soluble proteins, the ferritins (for review see Briat et al., 2010) and frataxin (for review see Ramirez et al., 2010), play a key role in cellular iron metabolism, and in particular within the plastid and mitochondria compartments (Fig. 15.4). Both these proteins are involved in iron storage and buffering. Ferritins are mainly found within plastids, but they can also be detected in mitochondria, whereas frataxin is exclusively a mitochondria protein. The structure of ferritins

is highly conserved between plants and animals, but contol of ferritin gene expression in response to iron excess occurs at the transcriptional level in plants, in contrast to animals, which regulate ferritin expression at the translational level. Reverse genetic and physiological approaches revealed strong links between plant ferritins and protection against oxidative stress. In contrast, their putative iron-storage function to furnish iron during various developmental processes is unlikely to be essential. Ferritins, by buffering iron, exert a finetuning of the quantity of metal required for metabolic purposes and help plants to cope with adverse situations, the deleterious effects of which would be amplified if no system had evolved to take care of free reactive iron. Frataxin has been recently identified in plants where it plays an important role in mitochondria biogenesis and in maintaining mitochondrial iron homeostasis, likely through a role in iron–sulfur cluster biosynthesis. From an integrative point of view, these various subcellular compartments are likely to cooperate in order to establish iron homeostasis at the cell level. Such integration has been recently supported by studying iron homeostasis in Arabidopsis seeds (Ravet et al., 2009b). Analysis of the expression of the seed-specific AtFer2 ferritin gene in different genetic backgrounds modified in iron homeostasis of plastid or vacuolar compartments (fer, nramp, and vit knockout mutants, and NRAMP and VIT overexpressors) revealed that ferritin stability in seeds depends on a proper allocation of iron from vacuoles to plastids. It highlights a potential crosstalk between the vacuolar and plastidial seed compartments for iron store allocation. Iron and plant productivity: iron interactions with light and CO2 The best evidence that iron is a limiting factor for biomass production comes from

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mesoscale iron addition experiments launched more than 20 years ago, and which have unequivocally demonstrated that iron supply limits production in one third of the world’s ocean by controlling the dynamics of plankton blooms (Boyd et al., 2007). Iron, light, and photosynthesis Until recently, the physiological mechanisms driving biomass increase in oceanic phytoplankton in response to iron fertilization were not clearly identified. In one of these experiments, it was reported that iron supply was leading to a ninefold increase in chlorophyll concentration and that the maximum quantum yield of photosynthesis was doubled (Hiscock et al., 2008). The impact of iron on phytoplankton biomass was therefore attributed to its effect on lightlimited photosynthesis rates and not on light-saturated photosynthesis rates. This observation is consistent with the fact that iron deficiency decreases light-limited photosynthesis of phytoplankton by decreasing the synthesis of functional proteins for biogenesis or repair of reaction centers. The fact that photosynthetic reaction center core and electron transport chain proteins requiring iron are not synthesized or repaired under iron deficiency conditions is consistent with the observation of a reduced ability to process absorbed light energy into chemical energy. Furthermore, decrease in variable fluorescence, indicative of damaged photosystem II, and in reaction center turnover rate, revealing defects in the photosynthetic electron chain, are characteristics of iron limitation effects on photosynthesis by oceanic phytoplankton. From a molecular point of view, the more advanced characterization of the alterations of the structure and function of the photosynthetic apparatus in response to iron was obtained with the green unicellular algae Chamydomonas reinhardtii (Moseley et al., 2002; Busch et al., 2008; Petroutsos

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et al., 2009). The antenna protein complexes are differentially affected by iron deficiency. It leads to a pronounced degradation of PSI. The induction of ferritin synthesis (a chloroplast located iron storage protein) correlated with the degree of PSI degradation during iron deficiency, and with the observation that the PSI level can be restored to normal within 24 h after iron repletion at the expense of the accumulated ferritin (Busch et al., 2008). This indicates that the iron– ferritin is likely to participate in the fast adjustment of the photosynthetic apparatus with respect to iron availability. RNAi strains with a reduced ferritin amount exhibit a delay in the degradation of PSI under iron deficiency, and these Chlamydomonas strains are more sensitive to photo-oxidative stress under high-light conditions. In addition to iron-deficiency-mediated degradation of PSI, a remodeling of the PSI-associated light-harvesting antenna (LHCI) also occurs. This adaptation is a sequential process; it starts with uncoupling the antenna from the PSI core and is followed by specific degradation of LHCs and induction of new LHCs, prior to ending with assembly of new antenna complexes in Fe-deficient cells (Moseley et al., 2002). Quantitative proteomic analysis has shown that the proton gradient regulation L1 (PGRL1) protein has an increased abundance in C. reinhardtii cells deprived of iron, compared with unstarved cells. This protein is one of 90 members of a family absolutely conserved across all the organisms containing a photosynthetic plastid. PGRL1 participates in cyclic electron transfer (CEF), as do the two A. thaliana orthologs, and is likely to be involved in the switch between cyclic (CEF) and linear photosynthetic electron transfer (LEF) (DalCorso et al., 2008; Petroutsos et al., 2009). In C. reinhardtii, PGRL1 also plays a role in modulating acclimation to iron likely by binding, sensing, or distributing iron, by changing reaction center stoichiometries leading to remodeling

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photosynthetic electron transfer, and/or by partitioning the electron flow between LEF, CEF, and respiration in order to adapt ATP synthesis capacity to the overall cellular demand (Petroutsos et al., 2009). Chlamydomonas cell responses to iron deficiency are comparable to those reported for vascular plants. A proteolytically induced loss of photosynthetic components including both photosystems and the cyt b6/f complex make the cells chlorotic. Iron deficiency therefore alters both structure and function of chloroplasts from higher plants (for review see Briat, 2008). It has been reported recently that iron nutrition was also a growth-limiting factor for the model plant A. thaliana (Ravet et al., 2009a). Under regular tap water irrigation, the biomass of the wild-type Col0 ecotype plants was found lower than under Fe(III)-ethylenediamineN-N′-bis(2-hydroxyphenylacetic acid) (EDDHA) fertilization. However, this irondependent gain of biomass requires the presence of ferritins in vegetative organs since “ferrirrigation” of the fer1-3-4 triple ferritin mutant line is reduced when compared to wild-type plants. The reduced growth of fer1-3-4 is likely due to a decrease in CO2 fixation. In mature leaves, photosynthesis is not affected by the absence of ferritin. The observation that the electron flux through PSII is not different in the mutant and in Col0 under iron or water irrigation suggests that the absence of ferritins in the triple mutant does not have a severe impact on the photosynthetic electron transfer machinery. However, the decrease in CO2 fixation observed suggests that the photosynthetic electron transfer chain is less efficiently used by the Calvin cycle enzymes in the absence of ferritins (Ravet et al., 2009a). Iron and CO2 interactions Global warming is in part correlated to substantial increases in carbon dioxide (CO2),

which is one of the most important greenhouse gases in the atmosphere. It is likely to have a major impact on plant growth since it is known that elevated CO2 increases net photosynthesis rate in C3 plants by suppressing ribulose-1,5-bisphosphate oxygenase activity, decreasing photorespiration, and increasing carbon assimilates for plant growth and development (Lawlor and Mitchell, 2000). Consequently, the biomass of C3 plants increases under elevated CO2 concentration (Dijkstra et al., 2002). As a consequence of such an enhancement of plant growth, the demand for nutrients also increases, and macronutrient limitation under elevated CO2 has generally been found to suppress the CO2-mediated gain of biomass. In this context, it is of particular interest to extend this knowledge to micronutriments, and in particular to iron because of its major role in the photosynthetic process. Iron content in soil regularly exceeds plant requirements, but its bioavailability to plants is often limited (Robin et al., 2008), particularly in calcareous soils, which represent one third of cultivated lands. Therefore, plant iron nutrition is likely to be affected by the continued elevation of atmospheric CO2, which, in turn, will affect crop production. Indeed, two recent studies have addressed this question in grass (barley) and nongrass (tomato) plants (Haase et al., 2008; Jin et al., 2009). In tomato, a relative increase in biomass at elevated CO2 was observed both under iron-limited or iron-sufficient conditions. However, the biomass increase was greater under iron deficiency, compared with the measurement performed with ironreplete plants (Jin et al., 2009). The increase in tomato plant biomass under elevated CO2 and restricted iron supply therefore cannot be attributed to increased photosynthesis alone; raising CO2 concentration also results in the improvement of iron nutrition of the plants. The same observation was reported with barley, a grass plant using chelation

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rather than reduction to take up iron from the soil. The stimulated biomass production in iron-sufficient and iron-deficient barley plants under elevated atmospheric CO2 treatments was observed both in hydroponics and in soil cultures (Haase et al., 2008). Iron biofortification and plant product quality General considerations: relationships between iron deficiency, sustainable agriculture, and public health Iron deficiency is one of the top 10 health challenges in modern society and is particularly prevalent in women of child-bearing age. It is the major cause of anemia, which affects at least 2 billion people worldwide. Symptoms associated with iron deficiency anemia can be severe, including increased susceptibility for infections and retardation of mental and psychomotor development, and of growth. More than half of the cases of iron deficiency anemia could be overcome by increasing the amount of iron in the diet. However, this goal is difficult to attain in developing countries where the population relies on plant products, including cereal grains, which contain very low levels of iron and antinutritional compounds such as phytate (Gomez-Galera et al., 2010). In Europe, cereals and their products provide 44% of the daily intake of iron, and there is increasing concern among public health authorities that the dietary supply of iron is below the lower recommended limit for some people. The “Green Revolution,” with the breeding of semi-dwarf, high-yielding crop cultivars that respond more to increased inputs of fertilizers, has markedly increased grain yield these last 50 years. This orientation of modern agriculture toward higher agronomic yield rather than the nutritional quality has raised the question of whether

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increased grain yield may have resulted in a lower density of minerals in grain. Measurements, over a period of 160 years, were made with archived wheat grain and soil samples from the Broadbalk Wheat Experiment, established in 1843 at Rothamsted, United Kingdom, in order to evaluate changes in the mineral concentration of wheat grain, including iron, and to establish whether trends are due to plant factors (e.g., cultivar, yield) or changes in soil nutrient concentration (Fan et al., 2008). Among the various analyses performed, it was observed that the iron concentrations of grain remained stable between 1845 and the mid-1960s, but subsequently has decreased significantly, which coincided with the introduction of semi-dwarf, high-yielding cultivars. In comparison, the concentrations in soil have either increased or remained stable. In conclusion, multiple regression analysis showed that both increasing yield and harvest index were highly significant factors that explained the downward trend in grain mineral concentration, including iron. Iron improvement of human diets can be achieved in different ways (Gomez-Galera et al., 2010). The Flour Fortification Initiative has created a network of governmental and private sectors in several developing countries in Latin America to promote the fortification of wheat flour. It enabled the increase of the use of iron-fortified wheat flour in these countries from 18% in 2004 to 27% in 2007, helping 540 million people avoid iron deficiency (Centers for Disease Control and Prevention, 2008). However, food fortification programs are not easy to implement, especially in developing countries, and biofortification has been proposed as an alternative long-term approach for improving mineral nutrition. It aims to improve the mineral nutritional qualities of crops, both by increasing the mineral content of the edible part of plants, seeds being a prime target, and by improving

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mineral bioavailability. Agronomical practices, plant breeding, and genetic engineering are used separately or in combination to reach these goals (Gomez-Galera et al., 2010). Iron biofortification and agronomical practices For iron, agronomical solutions to correct plant iron deficiency consist of using synthetic Fe(III)-chelates as fertilizers. Fe(III)chelates are generally derivatives from the family of ethylenediamine carboxylic acids. They are expensive and their use is therefore restricted to soil-less horticulture as well as to high added-value field-grown crops. Furthermore, these xenobiotics strongly impact metal availability and mobility in the soil because of their high persistence in the environment, raising questions about their sustainability in modern agriculture (Álvarez-Fernández et al., 2007). Alternatively to fertilization with iron chelates, it is well established that intercropping of grass and nongrass plants, especially on calcareous soils, where iron is poorly available, helps nongrass plants to resist iron deficiency (Zuo et al., 2000; Inal et al., 2007; Zuo and Zhang, 2009). Consequently, this agronomical practice can lead to 1.5 to 2.5 increases in iron content of shoots and seeds of the nongrass plant of such intercropping system. However, no advantage has been reported for the grass plant in this dual system. A simple explanation would be that phytosiderophores secreted by the grass plant help to solubilize iron, which is then actively reduced and taken up by the irondeficient nongrass partner. Molecular evidence to support this hypothesis has been recently reported for the peanut/maize couple (Ding et al., 2009). The Fe(III)chelate reductase activity of peanut and its transcript levels were higher in the maizeintercropped than in the monocropped

peanuts, and the maize roots secreted more phytosiderophore when intercropped with peanut. Iron biofortification and plant breeding Plant breeding offers the attractive possibility of increasing the iron content of crops. Indeed, natural variation for iron content of most plant species is well established. For example, the amount of iron in edible tissues varies between 6 and 22 mg kg−1 in rice, between 10 and 160 mg kg−1 in maize, and between 15 and 360 mg kg−1 in wheat (White and Broadley, 2005). Furthermore, including iron-enriched rice in nutrition trials of women in developing countries, where iron deficiency anemia is widespread, revealed that it has a positive impact on their health (Haas et al., 2005), validating the concept of biofortification. However, despite such genetic variation, cultivated varieties still have low iron levels, failing to provide the reference daily intake of this metal. Nevertheless, promising programs are still being developed. For example, the recent success in producing interspecific F1 hybrids between different iron-rich accessions of Aegilops longissima, and elite durum and bread wheat cultivars with low iron content have opened new possibilities for improved germplasm (Tiwari et al., 2008). As well as cereals, legume seeds are also of major importance for human diet, and they are therefore key targets for breeding with the aim of mineral biofortification, including iron. The model legume plants Lotus japonicus and Medicago truncatula were used to identify quantitative trait loci (QTLs), which determine the genetic basis for seed nutrient density, with the objective of facilitating the identification of synthenic regions in the legume genome, which will be of interest for the human diet, and to characterize beneficial alleles to assist

IRON NUTRITION

legume breeding programs (Klein and Grusak, 2009; Sankaran et al., 2009). Fiveseed iron QTLs were mapped on chromosome 1, 4, and 6 of L. japonicus (Klein and Grusak, 2009) and three-seed iron concentration QTLs, but no iron content QTL, were characterized in M. truncatula (Sankaran et al., 2009). Iron biofortification and transgenic approaches As an alternative to classical plant breeding methods, transgenic approaches for improving iron accumulation and bioavailability have been intensively developed in recent years. The most promising results with such a biotechnological strategy have been obtained by overexpressing the iron storage protein ferritin in transgenic plants, leading, on average, to a threefold increase in iron content. At the same time, it was reported that oral administration of plant ferritin (Beard et al., 1996), or a meal based on rice expressing high levels of ferritin (MurrayKolb et al., 2002), was suppressing rat anemia, demonstrating that plant ferritin constitutes an efficient iron source in the diet. Among the various significant trials performed, soybean ferritin has been expressed in several cereal crops under the control of an endosperm-specific promoter (Goto et al., 1999; Vasconcelos et al., 2003; Drakakaki et al., 2005; Qu et al., 2005), and pea ferritin has been constitutively expressed in rice (Hong-Xia et al., 2008). The impossibility of obtaining an improvement in iron content greater than threefold, although the amount of recombinant protein observed in western blots was often much higher, can be explained by bottlenecks existing upstream of iron sequestration within ferritins. Two such areas deserve attention: (1) iron unloading within the seeds is a critical control step, and NA and some of the YSL transporters play key roles in this process (Le Jean et al.,

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2005), and (2) iron loading of seed plastids is an important parameter for the posttranscriptional stabilization of the ferritin within these organelles (Ravet et al., 2009b). Consistent with these remarks, it has been recently reported that coexpression of NAS and of ferritin in rice endosperm led to a more than sixfold increase in seed iron content (Wirth et al., 2009), doubling what was currently obtained with single ferritin gene transformation. As well as the importance of an overall increase in iron content, the bioavailability of this iron is also a major point to be addressed because of the presence of antinutrients in plants, among which phytate is well known. To address this, the combined expression of ferritin and phytase has been achieved in rice and maize, resulting in an increase in iron levels and availability as assayed in simulated digestion/absorption trials (Lucca et al., 2002; Drakakaki et al., 2005). Although encouraging, these biotechnological approaches need to be integrated with physiological and agronomical knowledge, keeping in mind that metal benefit and metal toxicity can be “two sides of the same coin” (Guerinot and Salt, 2001; Zhao and McGrath, 2009). It is well known that iron uptake by plant roots results from complex interactions between plant and soil within the rhizosphere, and not only from the plant genotype. Solid phases controlling iron solubility in soils, chemical speciation of iron in solution, importance of redox in the solubilization of iron, and the role of synthetic and natural chelates in transport processes that occur near roots are among soil-dependent factors determining iron bioavailability (Lindsay, 1995). In addition, plant iron uptake mechanisms are intimately linked with loading processes of other metals, some of which are potentially toxic for humans. Ferritin overaccumulation in transgenic tobacco leaves leads to an unnatural iron

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sequestration. As a consequence, these transgenic plants behave as if iron deficient, and activate iron transport systems as revealed by an increase in root ferric reductase activity, explaining why these plants have an increased iron content (Van Wuytswinkel et al., 1999). This iron deficiency situation has been reported to be responsible for cadmium loading of plants, through activation of the IRT1 ferrous iron transporter (Vert et al., 2002). In grasses, phytosiderophores of the mugineic acid family are involved in root iron(III) uptake; this system, activated under iron deficiency conditions, is also able to transport zinc, copper, nickel, manganese, and cadmium (Schaaf et al., 2004). Indeed, the influence of various soil conditions on the increase in leaf iron content of various tobacco plant genotypes has been tested (Vansuyt et al., 2000). One control transgenic tobacco and two transgenic tobaccos overexpressing ferritin in the plastids or in the cytoplasm, respectively, were grown on five different soils, two of them being sewage sludge amended. Although a significant increase in leaf iron concentration was measured in transgenics overexpressing ferritin grown on three out of the five soils, this increase was not a general rule. On some soils, leaf iron concentration of control plants was as high as in transgenics grown on other soils. In addition, an increased phosphorus concentration in the two sewage sludge-amended soils correlated with a high leaf iron concentration in control plants, similar to the one measured in ferritin-transformed plants. Growing plants in vitro with various increasing phosphate concentrations revealed a direct phosphorous involvement in iron loading of control plants, at a similar level to the overexpressing ferritin plants. In addition, with one of the soils tested, not only iron but also manganese, zinc, and cadmium, and to a much lesser extent copper, nickel and lead, were found to be more abundant

in ferritin-transformed plants than in the control plants. These data indicate that the iron fortification of leaves, based on ferritin overexpression, could be limited in its biotechnological application because of its high soil dependence. Conclusion The molecular understanding of iron nutrition has tremendously increased in the last 10 years. Transporters and chelating molecules responsible for iron uptake, translocation, subcellular compartmentation, and storage have been described. More recently, the physiological integration of these molecular partners at the cell, organ, and even whole-plant levels has started to give promising results. A major challenge in the future concerns the regulation of these various targets, primarily driven by the iron status of the plant and its sensing. A major output of this molecular studies is to offer molecular markers for plant breeding or to propose alternative biotechnological transgenic approaches with aims of (1) remediating iron deficiency of plants on calcareous soils, and (2) increasing the iron content and bioavailability of edible parts of crops in order to improve the diet and to fight human iron deficiency anemia, a worldwide public health challenge. However, in order to be successful in the future, these applied science outputs will need to benefit of multidisciplinary programs promoting collaboration between molecular plant physiologists, soil scientists, agronomists, and plant, animal, and human nutritionists. References Álvarez-Fernández, A., Orera, I., Abadía, J., et al. (2007) Determination of synthetic ferric chelates used as fertilizers by liquid chromatographyelectrospray/mass spectrometry in agricultural matrices. Journal of the American Society of Mass Spectrometry 18, 37–47.

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Chapter 16

Zinc in Soils and Crop Nutrition Behzad Sadeghzadeh and Zed Rengel

Abstract As a micronutrient, zinc (Zn) is involved in enzyme activation (about 300 enzymes), gene expression, phytohormone activity, protein synthesis, photosynthesis and carbohydrate metabolism, fertility and seed production, and disease resistance. Zinc is taken up by root-cell membrane transporters of the zinc iron premeases (ZIP) family in all plant species, as well as by yellow stripe-like (YSL) proteins (Zn–phytosiderophore complexes) in grasses, and is loaded into the stele via heavy metal ATPases (HMA). About half of the arable soils in the world have low zinc availability, resulting in hampered crop growth, poor yields, and low zinc density in edible crop parts. There are commercially available cultivars with increased efficiency of zinc acquisition from soil as well as zinc utilization in tissues. Mechanisms underlying zinc efficiency are not completely understood. Given that 2–3 billion people have diets deficient in zinc, biofortification of staple crops is one of the global challenges being tackled at present. Soil and foliar fertilization with zinc (agronomic biofortification) as well as breeding genotypes

for increased zinc density in edible parts (genetic biofortification) are the options currently pursued for improving zinc intake in susceptible human populations.

Introduction Interest in plant micronutrients has risen in the last decades because poor availability of micronutrients in soil is widespread in agricultural lands and is becoming one of the major limiting factors for crop production. Not only crop yields, but also the quality of crop products, is impaired when the supply of plant-available micronutrients is insufficient. The essentiality of zinc for plant growth as a micronutrient was recognized only about 70 years ago. In some parts of the world, the existence of zinc deficiency in crops has only been established during the last 10 or 20 years. Zinc deficiency can be exacerbated by a change from traditional subsistence agriculture to growing modern varieties for commercial purposes using relatively large amounts of macronutrient fertilizers.


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Many of the high-yielding new varieties in intensively managed farming systems remove large amounts of zinc from soil at every harvest, thus depleting the soil and increasing the likelihood of zinc deficiency. For example, a harvest of 6.5 t grain ha−1 per year removed 416 g Zn ha−1 per year in soybean–wheat cropping system (Takkar, 1996). Furthermore, in intensively managed farming systems, increased use of macronutrient fertilizers, especially phosphorus as well as fertilizers containing little zinc impurities, can exacerbate zinc deficiency (Loneragan and Webb, 1993). Zinc deficiency causes yield losses in large areas under crop production. In developing countries, the need to maximize food production is crucial, and hence improving land productivity is necessary. Therefore, any factor (such as zinc deficiency) that prevents crops from reaching their potential yield needs to be addressed in these countries. However, zinc deficiency also occurs in many other technologically advanced countries such as Australia, most of the states in the United States, and in parts of Europe. In addition to staple crops such as wheat, maize, barley, and rice, the productivity of many other crops such as cotton, tea, fruit trees, grapes, and many vegetables can be significantly reduced by zinc deficiency. Fortunately, the occurrence and reason behind zinc deficiency in many crops growing in most farmlands on different soil types of the world are commonly known. Therefore, zinc deficiency problems can be solved if farmers are made aware of the condition and how to treat it. Zinc is essential for the normal healthy growth and reproduction of plants, animals, and humans. It is required as a structural component or regulatory cofactor of a large number of proteins and enzymes (such as metalloenzymes and transcription factors) involved in many important biochemical pathways (carbohydrate metabolism, protein

biosynthesis, growth regulator metabolism) and functions (e.g., maintenance and integrity of cell membranes, resistance to infection) (Vallee and Falchuk, 1993; Berg and Shi, 1996). If the available amount of zinc is insufficient (= Zn deficiency), plants suffer from physiological stresses caused by a failure of metabolic processes in which zinc plays a critical role. Among the essential trace elements for plants, zinc deficiency is the most widespread and most frequently encountered deficiency problem that has recently received global attention (Hotz and Brown, 2004). In cases of marginal or moderate deficiency, yield losses of 40% or more (without obvious visible symptoms on crops) can have a severe economic effect on farmers due to reduced income (Alloway, 2004). In addition to the yield losses, zinc deficiency can cause large reductions in crop quality by lowering zinc concentration in edible parts. Hence, increasing the zinc content of staple food crops is expected to enhance dietary intake of bioavailable zinc and improve zinc status of human populations (House et al., 2002). Applying zinc fertilizers does not always correct zinc deficiency due to factors such as subsoil constraints, topsoil drying, or disease interactions (Graham and Rengel, 1993). Where fertilizers are applied to correct zinc deficiency, the added zinc is likely to remain near the surface, especially in no-till farming systems, thus limiting its use by crops. In the semi-arid areas, applying the liquid form of nitrogen, phosphatic, and zinc fertilizers to the subsoil (up to 0.4 m deep) can increase zinc uptake and grain yield by crops more than applying granular fertilizers to the surface. However, the cost of the liquid form of fertilizers is relatively high in areas with extensive production (Holloway, 1996). Moreover, zinc fertilizers may be unavailable or unaffordable in developing countries.

ZINC IN SOILS AND CROP NUTRITION

Due to widespread zinc deficiency and difficulties in alleviating it by the use of fertilizers, development of crops that are efficient zinc accumulators (especially under low plant-available soil zinc) is an important approach for improving tolerance to zinc deficiency (= Zn efficiency) and consequently grain productivity and micronutrient quality of food. In addition, zinc-efficient genotypes could reduce land degradation by limiting the use of machinery and minimizing fertilizer inputs on agricultural lands. There are commercially available zincefficient cultivars of wheat, barley, and rice (Gregorio et al., 2000; Genc and McDonald, 2004; Sadeghzadeh et al., 2009a), which are grown quite widely in soils with a low plantavailable concentration of zinc. Tolerance of plant genotypes to zinc deficiency, as a genetic trait, is usually called zinc efficiency and defined as the ability of a cultivar to grow and yield well in soils too deficient in zinc for a standard cultivar (Graham, 1984). While physiological and molecular mechanisms of tolerance to zinc deficiency are partially known (Hacisalihoglu and Kochian, 2003), a better understanding of the physiological, morphological, and genetic bases of zinc efficiency is needed for developing fast, simple, and reliable screening procedures to be used in identifying and breeding genotypes for zinc efficiency. This chapter gives a broad review of the relevant aspects of soil–plant relationships: from the origins of zinc in soils, zinc deficiency distribution and the factors affecting zinc availability, to the interactions between zinc and other soil nutrients. Soil testing is then reviewed along with the lower critical concentrations of zinc in soil test extractions. The chapter also covers the importance of zinc in optimal growth and yield, followed by zinc uptake and transport in plants as well as physiological aspects and symptoms of zinc deficiency in cereals and the role of zinc in alleviating drought stress. Types of zinc

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compounds used as fertilizers and their application methods and rates are dealt with. Zinc concentration (density) in staple foods in relation to zinc deficiency problem in humans and improving this density by plant breeding are discussed, which leads to consideration of genotypic variation for seed zinc density, and mechanisms, screening, and genetics of zinc efficiency. Zinc in Soils Total zinc concentration of soils is related to the composition of the parent rock material and the nature and extent of weathering processes (Chesworth, 1991). The sedimentary rocks typically comprise 10–120 mg Zn kg−1, whereas the lithosphere contains 70–80 mg Zn kg−1 (Barak and Helmke, 1993; Alloway, 1995). Mean total zinc concentration in most agricultural soils is 10–300 mg Zn kg−1(Barber, 1995). Soils containing high amounts of zinc originated from parent rocks containing weathered zinc minerals (e.g., zinc sulfate, zinc carbonate, zinc oxide) (Barak and Helmke, 1993; Cappuyns et al., 2006). The range of total zinc concentrations in Australian soils that include many ancient, heavily weathered areas is 7) with moderate to high organic matter content (>15 g organic C per kg soil) are likely zincdeficient due to high HCO3− in the soil solution (Singh et al., 2005). In alkaline soil with low zinc supply, increasing zinc application increased zinc concentration in plants and reduced the deficiency symptoms, but only slightly improved plant growth. It is concluded that plant growth on alkaline soils was repressed more by soil alkalinity than zinc deficiency (Liu and Tang, 1999). Soil organic matter has a critical role in solubility and transport of zinc to roots (Marschner, 1993; Obrador et al., 2003) due

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to adsorption of zinc by organic ligands (Lindsay, 1972). Similarly, Catlett et al. (2002) reported a strong inverse relationship between the soil organic matter content and soluble zinc concentrations in 18 Colorado soils. However, an adequate level of organic matter increases solubility and zinc diffusion rate in soils (Sharma and Deb, 1988). The wheat experiment showed zinc content to be positively correlated with the soil organic matter content (Sillanpää, 1982; Hamilton et al., 1993). In the United States, one of the most frequent causes of zinc deficiency problems is removal of surface soil by land leveling (Alloway, 2004). The subsoil has lower organic matter and, in many cases, also a higher pH than the topsoil. Both the DTPA-extractable zinc and organic matter content decrease with depth in the soil profile (Alloway, 2004). Other factors that contribute to zinc deficiency are low soil moisture and low temperature (Moraghan and Mascagni, 1991; Marschner, 1993). Soil moisture affects nutrient supply via impaired diffusion to the root surface (Marschner, 1986). Given that zinc diffusion in soils is highly dependent on soil moisture, zinc nutrition of plants may be at risk in semi-arid and arid areas, where soils are usually deficient in water for long periods during the growing season. Accordingly, in zinc-deficient calcareous soils, wheat yield reductions are more severe under rain-fed than irrigated conditions (Ekiz et al., 1998). On the other hand, waterlogging alters zinc chemistry in the soil, whereby submerging the soil decreases water-soluble zinc concentration compared with well-drained soils (Amer et al., 1980). In addition, a decrease in zinc solubility and low zinc uptake in poorly drained soils may be due to the coprecipitation of zinc with soluble iron and aluminum (Singh and Abrol, 1986). Early in the growing season, zinc deficiency may occur when soil temperature is

still relatively low, and then diminishes as temperature rises (Brennan et al., 1993). Both incidence and severity of zinc deficiency symptoms are exacerbated by low soil temperature (Moraghan and Mascagni, 1991). It was suggested that colder root zone temperature decreases root colonization with arbuscular mycorrhizae, root growth, zinc uptake, and its translocation into the shoots (Schwartz et al., 1987; Moraghan and Mascagni, 1991). In barley, shoot zinc uptake was 82% higher in plants grown in solution at 20°C compared with 10°C (Schwartz et al., 1987). Finally, the interaction of zinc with other elements decreases zinc availability to plants, influencing its adsorption, distribution, and utilization in plants (Loneragan and Webb, 1993). Zinc interactions with phosphorus (P) and nitrogen (N) are most widespread in crop production on soils with limiting supplies of zinc and phosphorus or nitrogen. Interaction between Zinc and Other Soil Nutrients High amounts of applied nitrogen in the absence of zinc can cause zinc deficiency through a dilution effect brought about by promotion of plant growth, and to a lesser extent by changing soil pH (Table 16.1; Loneragan and Webb, 1993). Also, nitrogen application increases shoot-to-root ratio due to a stimulation of shoot growth to a greater extent than root growth. Promotion of plant growth without increasing root absorption rate or root size results in a decrease in zinc concentration in plants (Loneragan and Webb, 1993). High levels of phosphorus in soil can sometimes increase the symptoms of zinc deficiency (Foth and Ellis, 1997). Zinc and phosphorus coprecipitation in the soil may cause formation of insoluble ZnO3(PO4)2 that would decrease the soil solution zinc


Table 16.1.

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Interactions of zinc with other elements

Element

Zinc × Element Interactions

Reference

Nitrogen (N)

Increasing N fertilization may increase Zn requirement due to increased growth and/ or changing rhizosphere pH Higher level of P decreased Zn availability

Loneragan and Webb (1993); Hamlin et al. (2003)

Phosphorus (P)

High P may increase Zn deficiency symptoms P application depressed Zn concentration

Potassium (K)

Accumulation of Zn in plants may lead to a suppression of K accumulation

Calcium (Ca)

Ca decreased Zn availability

Manganese (Mn)

Increasing level of Zn inhibited uptake of Mn and vice versa in several plant species

Magnesium (Mg)

Cell Zn content was not influenced by Mn nutrition Toxic level of Zn suppressed accumulation of magnesium

Boron (B)

Nontoxic levels of Zn did not affect magnesium concentration Increasing Zn supplies may either increase, decrease, or have no effect on the Fe status High concentrations of Zn can induce iron chlorosis through reducing Fe availability in soil Zn absorption was suppressed by high concentration of Fe in nutrient solution culture Zinc can alleviate boron toxicity

Copper (Cu)

High level of Cu inhibited Zn uptake

Cesium (Cs)

Cesium application increased Zn concentration

Iron (Fe)

concentration to a deficiency level (Barrow, 1993). Moreover, phosphorus fertilization reduced the zinc absorption rate (Safaya, 1976). Under limiting or marginal supplies of zinc and phosphorus, application of phosphorus decreased zinc concentration to deficient levels due to the dilution of zinc concentration in the plant by growth stimulation (Sharma et al., 1968; Singh et al.,

Barrow (1993); Das et al. (2005) Foth and Ellis (1997) Wagar et al. (1986); Imtiaz et al. (2006); Agbim (2009) Kalyanaraman and Sivagurunathan (1994); Thalooth et al. (2006) Chaney (1993); Loneragan and Webb (1993) Galvez et al. (1989); de Varennes et al. (2001); Kaya et al. (2001); Xu et al. (2007b) Allen et al. (2007) Kalyanaraman and Sivagurunathan (1994); Bonnet et al. (2000) Gunes et al. (1998); Fontes et al. (1999) Loneragan and Webb (1993) Romheld and Marschner (1986) Alloway (2008)

Güne et al. (1999); Hosseini et al. (2007) Loneragan and Webb (1993); Arredondo et al. (2006) Isaure et al. (2006)

1988). Some studies, however, showed that a drop in shoot zinc concentration could be greater than what could be explained just by a dilution effect. In these cases, it was concluded that phosphorus-induced zinc deficiency depressed zinc uptake, first by curtailing its translocation from root to shoot, and second by lowering its rate of absorption (Sharma et al., 1968).

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High phosphorus supply can induce zinc deficiency in crops, for example, in wheat (Wagar et al., 1986). At a low zinc supply, zinc concentration in wheat shoots decreased with increased phosphorus applications, and severe zinc deficiency and lower yields were observed at 250 mg P kg−1 soil. Also, zinc deficiency was either induced or made more severe with increasing phosphorus concentration in the leaves (Cakmak and Marschner, 1987). Interestingly, increased application of phosphorus affected zinc concentration in the zinc-inefficient but not the zinc-efficient cultivars (Imtiaz et al., 2006). The zinc-efficient cultivars maintained phosphorus concentrations at a lower level, absorbed more zinc, and grew better. In zinc-inefficient cultivars, phosphorus may reduce the physiological activity of zinc (Leece, 1978), leading to higher zinc requirements (Boawn and Brown, 1968). Macronutrient cations such as calcium, potassium, and magnesium decrease the rate of zinc absorption by plants. Potassium, NH4, and magnesium cations strongly inhibit the rate of zinc absorption from solutions of low calcium concentration (Loneragan and Webb, 1993). In a study with wheat seedlings, tissue zinc concentration decreased as Ca(NO3) concentration was increased from 0 to 40 mM (Chaudhry and Loneragan, 1972). In addition, micronutrient cations, especially Cu2+, may diminish zinc uptake (Loneragan and Webb, 1993) due to competition between Cu2+ and Zn2+ for absorption sites on the root plasma membranes (Chaudhry et al., 1973). The iron and zinc interaction is complex, with conflicting results reported. With increasing iron supply, shoot zinc concentration was either decreased (Zhang et al., 1991), unchanged (Chaudhry and Loneragan, 1972), or increased (Giordano et al., 1974). Predicting Zinc Deficiency in Soil Soil analysis can be used as a tool for predicting nutrient deficiency in existing crops.

The results obtained can be compared with calculated critical zinc values in the soil types for the specific crop. Soil testing can be carried out at any time; therefore, it has an advantage over plant tissue analysis. Soil tests enable prediction of possible deficiencies in advance of growing the crop, so that appropriate fertilization or other treatments can be applied to avoid the yield and/or quality loss due to zinc deficiency. Several soil analytical procedures are available for predicting zinc availability in soils, including extractions with the chelating agents like DTPA, ethylenediamine tetraacetic acid (EDTA), hydrochloric acid and ammonium bicarbonate–DTPA, and Mehlich 1 test. The DTPA method is widely used for predicting plant-available zinc in soils (Lindsay and Norvell, 1978). Based on greenhouse and field experiments, about 0.6 mg kg−1 DTPA-extractable zinc has been suggested as a critical concentration for wheat grown in calcareous soils of arid regions in India (Bansal et al., 1990). In contrast, adding zinc fertilizer to soils containing 0.5 mg kg−1 soil of DTPA-extractable zinc had no significant effect on grain yield of barley and wheat grown in Saskatchewan (Singh et al., 1987). In Australia, the critical DTPA-extractable zinc concentration in acidic soils for wheat is 0.25 mg kg−1, and an application of zinc to soils containing more than 0.25 mg extractable Zn kg−1 is not effective in increasing yields (Brennan, 1996). Zinc in Plants The Functions of Zinc in Plants Zinc is required in small amounts to allow normal function of several key plant physiological pathways as well as in the structural and functional integrity of membranes. These functions have important roles in growth regulation, enzyme activation, gene expression and regulation, phytohormone activity, protein synthesis, photosynthesis


and carbohydrate metabolism, fertility and seed production, and defense against disease (Marschner, 1995). Zinc deficiency impairs these physiological functions, leading to severe reduction in growth, lower yields (or even crop failure), and poor quality crop products (Brown et al., 1993). Zinc is the only metal represented in all six enzyme classes (oxidoreductases, transferases, hydrolases, lyases, isomerases, and ligases) (Webb, 1992). The zinc requirement in a wide range of enzymes means that protein, carbohydrate, and auxin metabolism as well as reproductive processes are depressed under zinc deficiency (Römheld and Marschner, 1991; Brown et al., 1993). There are three primary Zn2+-ligand binding sites underpinning structural, catalytic, and cocatalytic function of zinc in enzymes (Auld, 2001; Maret, 2005). Structural zinc sites comprise four ligands for proper protein folding such as in protein kinases. At catalytic sites (e.g., carbonic anhydrase), Zn2+ is directly involved in the enzyme function by complexing with water and sulfur, nitrogen, or oxygen donors. At cocatalytic sites where two or three Zn2+ are bridged by amino acid residues (e.g., superoxide dismutases), Zn2+ is involved in catalytic, structural, and regulatory functions. Zinc is involved in carbohydrate metabolism through its effects on photosynthesis and sugar transformation (Salama et al., 2002). A decrease in photosynthesis by zinc deficiency can result from a decrease in (1) carbonic anhydrase (CA) activity (Sharma et al., 1982; Ohki, 2006), (2) the photochemical activity of chloroplasts (Tkachuk et al., 1994), (3) chlorophyll content, and (4) chloroplast structure. Low CA may inhibit photosynthetic electron transfer and consequently limit chlorophyll content (Römheld and Marschner, 1991). The activity of enzyme CA can be an indicator of the concentration of physiologically active zinc in leaves as well as the amount of zinc accumulation in leaves (Lazova et al., 2004).

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Zinc is essential in protein metabolism, being involved in the stability and functioning of genetic material. Zinc is essential in chromatin structure, DNA and RNA metabolism, and gene expression (Vallee and Falchuk, 1993; Ho, 2004). Zinc deficiency decreases protein synthesis (Marschner, 1995; Obata et al., 1999) due to RNA degradation (Ciais et al., 2004) and lower activity of RNA polymerase (Marschner, 1995) as well as deformation and reduction of ribosomes (Kitagishi et al., 1987; Brown et al., 1993). In zinc-deficient bean leaves compared with control plants, free amino acids concentration was increased by a factor of 6.5; following zinc resupply, this increase factor was 5.1 after 24 h, 2.7 after 48 h, and 1.4 after 72 h (Cakmak et al., 1989). Zinc has an important physiological effect in maintaining the integrity and function of cellular membranes (Pinton et al., 1994) by controlling generation and detoxification of reactive oxygen species (ROS; Cakmak and Marschner, 1988b; Cakmak, 2000). ROS can damage membrane lipids (Bettger and O’Dell, 1981) and sulfhydryl groups (Rengel, 1995b). When these compounds are damaged by oxidative stress, there is increased leakage of organic compounds (such as carbohydrates and amino acids) from zinc-deficient root cells (Cakmak and Marschner, 1988b). Due to the increased leakage of carbon-containing compounds into the rhizosphere, zinc-deficient plants may be susceptible to root diseases such as Fusarium graminearum (Sparrow and Graham, 1988; Grewal et al., 1996). Zinc Uptake and Movement in Plants Roots take up zinc from the soil solution as a divalent cation (Zn2+), and at high pH, zinc is absorbed as a monovalent ZnOH+ (Marschner, 1995). Zinc accumulation in roots has biphasic kinetics, with an initial rapid binding in the root cell walls, followed by a slower linear transport phase across the

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plasma membrane (Santa Maria and Cogliatti, 1988). The process of Zn2+ movement from the external solution to the root cell wall free space is via diffusion followed by zinc transport across the plasma membrane, via ion transport proteins such as zinc iron premeases (ZIP) family transport proteins (Guerinot, 2000). ZIP family genes appear to be the primary proteins responsible for zinc uptake from the rhizosphere (Grotz et al., 1998). The cytoplasm is negatively charged, and there is an electrical gradient drawing cations (including Zn2+) into the cell. Reid et al. (1996) reported that for zinc transport across the plasma membrane, it appears unnecessary to invoke an active transport system because zinc influx will be thermodynamically favored. Root zinc uptake is mediated by the high-velocity, low-affinity (Km = 2–5 μM) and low-velocity, highaffinity transport systems (Km = 0.6–2 nM), with the latter dominating under low soil zinc conditions (Hacisalihoglu et al., 2001; Hacisalihoglu, 2002). Zinc-inefficient plants have lower maximum rates of uptake and lower affinity values than zinc-efficient plants (Rengel and Wheal, 1997b; Hacisalihoglu et al., 2001). From the root surface, nutrients are transported into the root xylem through epidermis, cortex, and endodermis (Marschner, 1995). Zinc may pass through the root to the xylem either through the extracellular spaces between root cells (apoplast) or through the cytoplasmic continuum of root cells linked by plasmodesmata (symplast) (White et al., 2002; Broadley et al., 2007). The apoplastic flux is largely determined by the cation exchange properties of the cell wall, water flows, and the presence of the Casparian band, and contributes increasingly to zinc uptake and influx to the xylem as external zinc concentration increases (White et al., 2002). In Thlaspi caerulescens and Thlaspi arvense, the entry point for zinc accumula-

tion is across the plasma membrane of root cells, and zinc reaches the xylem via the symplastic pathway in both species (Lasat et al., 1996; Lasat and Kochian, 2000). Zinc can be taken up across the root-cell plasma membranes as Zn2+ or as a zinc– phytosiderophore (PS) complex (Grotz and Guerinot, 2006; Suzuki et al., 2006; Broadley et al., 2007). Most Zn2+ influx to the cytoplasm is mediated by ZIP family transport proteins such as ZIP1, ZIP3, and ZIP4 (Guerinot, 2000; Pence et al., 2000; Broadley et al., 2007), and the uptake of zinc–PS complexes is catalyzed by yellow stripe-like (YSL) proteins in Strategy II plants (the grasses) (Suzuki et al., 2006; Haydon and Cobbett, 2007b). The heavy metal ATPase (HMA) family appears to be the most likely candidate for loading zinc into the xylem for root-to-shoot transport (Eren and Arguello, 2004; Hussain et al., 2004). In xylem, zinc may be transferred as Zn2+ or complexed with the organic acids, histidine, or nicotianamine (Welch, 1995; Von Wirén et al., 1999; Broadley et al., 2007). Zinc in xylem has been measured in soluble form bound to small proteins and as insoluble complexes such as zinc–phytate (Tinker et al., 1981) or anionic complexes (White et al., 1981). ZIP family members appear to mediate Zn2+ influx to the phloem and leaf cells (Ishimaru et al., 2005). YSL proteins may also load zinc into the phloem (Haydon and Cobbett, 2007b; Waters and Grusak, 2008). For a large body of research on zinc transporters and the cellular trafficking of zinc, readers are referred to Eide (2006). Zinc Deficiency in Plants When the supply of zinc to plants is inadequate, physiological functions of zinc are impaired, and the growth is adversely affected. Zinc deficiency is a severe micronutrient disorder that threatens world food


production (Alloway, 2001; Welch and Graham, 2004). The main causes of zinc deficiency in crops are: low zinc availability (high pH, calcareous, and sodic soils), low total soil zinc concentration (especially in sandy, sodic, and calcareous soils), high levels of nitrogen and phosphate, and restricted root exploration due to soil compaction or high water table, particularly in soils of marginal zinc status (Alloway, 2004). Wheat and barley show a significant decrease in growth and grain yield under zinc-deficient conditions in the field (Graham et al., 1992; Cakmak et al., 1996c; McDonald et al., 2001). Zinc deficiency in soils also reduces zinc concentration and content in edible portions of staple food crops and diminishes their nutritional quality (Welch and Graham, 2004). About 40% of world’s human population suffers from micronutrient deficiencies, including zinc deficiency (the so-called hidden hunger) (Bouis, 1996; Graham and Welch, 1996). A high proportion of cereal-based foods with low zinc content in the diet is considered one of the major reasons for the widespread occurrence of zinc deficiency in humans, especially in developing countries (Welch and Graham, 1999; Graham et al., 2001).

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Diagnosing Zinc Deficiency in Plants Visible symptoms of zinc deficiency, such as small and distorted leaves, interveinal chlorosis in young leaves, and shortened internodes (Marschner, 1995), can be a quick and simple diagnostic tool for severe zinc deficiency in many crops. However, in some cases, visible symptoms are not easy to recognize. Climatic conditions can also affect symptom development. In some instances, visual diagnosis can be hampered by the simultaneous phoshphorus toxicity (Webb and Loneragan, 1988) and chlorosis induced by intense light (Cakmak et al., 1995). Perhaps most importantly, mild or even moderate cases of deficiency often do not give rise to clear diagnostic symptoms. Such hidden zinc deficiency can sometimes cause 20% yield loss or more. In barley, visual zinc deficiency symptoms are stunted plants and leaves, chlorotic areas on leaves, necrosis, and leaves collapsing around the middle (Fig. 16.1) (Genc et al., 2003; Lombnaes and Singh, 2003; Sadeghzadeh et al., 2009a). In wheat, symptoms of zinc deficiency are usually observed in young seedlings, later resulting in whitishbrown patches and then necrotic lesions on the leaf blades, with leaves collapsing in the

Zinc deficiency symptoms on barley leaves: development of necrotic lesions and collapsing leaves in the center (Sadeghzadeh, 2008).

Fig. 16.1.

346


middle (Rengel and Graham, 1995c; Cakmak and Braun, 2001). The appearance of these symptoms can vary with environmental conditions, plant age, deficiency stage and severity, as well as the supply of other nutrients (Brennan et al., 1993). In addition, the visual symptoms of zinc deficiency vary considerably among crop genotypes and may be significantly correlated with zinc efficiency and grain yield (Genc et al., 2002b; Sadeghzadeh, 2008). Given that individual varieties (or cultivars) can often vary considerably in their susceptibility to zinc deficiency, it is important to screen crop varieties and identify tolerant (or zinc-efficient) varieties to be grown on soils of low plant-available zinc. Genotypes can be screened for zinc efficiency based on expression and severity of visual zinc deficiency symptoms on leaves. By using a visual score of deficiency symptoms in barley, it was found that the greater tolerance to zinc deficiency in a zinc-efficient genotype compared with a zinc-inefficient genotype at the seedling stage was controlled by a single gene. Hence, visual zinc deficiency scores are useful for genetic analysis of tolerance to zinc deficiency (Genc et al., 2003). Critical (or threshold) concentration (usually defined as 90% of maximum yield) in tissues vary with plant species, cultivar, plant age, plant parts, and the environment. Whole shoot, root, young leaves, and grain are used for diagnosing zinc status, although leaves have been considered the most appropriate plant part to sample for determining nutrient status (Dang et al., 1993; Huang et al., 1996). The critical zinc concentrations in leaves vary between 20 mg Zn kg−1 in wheat, 15 mg Zn kg−1 in rice, and 22 mg Zn kg−1 in maize and groundnut. For the whole young plant, values reported include 8 mg Zn kg−1 for sorghum, 22 mg Zn kg−1 in rice and 25 mg Zn kg−1 in wheat and chickpea. However, differences can also occur between different varieties of these crops (Alloway, 2001).

It has been suggested that biochemical analysis can be an excellent indicator of nutrient status, particularly when plant tissues have a large amount of physiologically inactive nutrients (Table 16.2; Gibson and Leece, 1981). To diagnose zinc deficiency, the activity of CA was used in wheat (Rengel, 1995a), mustard (Chatterjee and Khurana, 2007), and maize (Gibson and Leece, 1981). Similarly, the activity of aldolase and ribonuclease appear to be reliable biological indicators of the zinc status in mustard (Chatterjee and Khurana, 2007). Correcting Zinc Deficiency in Plants Zinc deficiency in crop production can be ameliorated through agronomy and/or genetic improvement. Substantial crop responses to zinc fertilization were reported in Australia, India, and especially in Central Anatolia (Turkey), where wheat grain yields have increased by over 600% since the mid1990s (Cakmak, 2004). Fertilization is used to provide crops with the macronutrients nitrogen, phosphorus, and potassium (Constant and Sheldrick, 1991). These nutrients, by promoting root and shoot development, can increase the uptake of all nutrients, including zinc, required by the crop. In addition, the widespread use of macroelement fertilizers makes them a convenient vehicle, by adding zinc fertilizers during the manufacturing process, to supply crops with zinc as well. Alternatively, zinc-containing impurities in fertilizers may make a significant contribution to zinc supply to crops (Bolland et al., 1993). Fertilization could correct zinc deficiency and ensure optimum yields as well as increased zinc concentration in grain. However, fertilizer studies focusing specifically on increasing zinc concentration in edible crop parts (such as grain) have received much less attention compared with those on the role of soil and foliar zinc fertilization to correct zinc deficiency and


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Table 16.2. Enzyme activities as indicators of zinc nutrient stress used in screening plant genotypes for Zn

efficiency Enzyme Type

Plant Species

Reference

Carbonic anhydrase (CA) activity

Maize Cotton Mustard Rice Wheat

Alcohol dehydrogenase (ADH) activity Fructose 1,6 biphosphate aldolase (FBPAse) activity Total superoxide dismutase (SOD)

Rice

Gibson and Leece (1981) Ohki (2006) Chatterjee and Khurana (2007) Sasaki et al. (1998) Rengel (1995a); Hacisalihoglu et al. (2003a) Moore and Patrick (1988); Reddy (2006) Pandey et al. (2002)

Cu/Zn superoxide dismutase activity

Acid phosphatase (APase) activity Ribonuclease (RNAse) activity

Ascorbate peroxidase (APx) activity Production of superoxidegenerating NADPH-oxidases Nicotianamine synthase (NAS) activity Peroxidase (POD) activity

Black gram (Vigna mungo L.) Narrow-leaf lupin Tobacco Wheat, rye Maize Narrow-leaf lupin Rice Rye Wheat

Tobacco

Yu et al. (1998); Yu and Rengel (1999) Yu et al. (1998) Cakmak et al. (1998) Wang and Jin (2005) Yu and Rengel (1999) Obata et al. (1999) Cakmak et al. (1997c) Cakmak et al. (1998); Yu et al. (1999); Hacisalihoglu et al. (2003a) Chatterjee and Khurana (2007) Hayes et al. (1999) Kaya et al. (2000) Pandey et al. (2002) Brown et al. (1993); Azhar et al. (2005) Yu et al. (1998)

Bean, tomato

Cakmak and Marschner (1988a)

Wheat

Singh et al. (2002)

Mustard Wheat

Chatterjee and Khurana (2007) Salama and Fouly (2008)

Mustard Pasture species Tomato Black gram Wheat

increase plant growth and yield (Martens and Westermann, 1991; Mortvedt and Gilkes, 1993; Rengel et al., 1999). Zinc deficiency can be treated by applying fertilizers to soils and/or foliage, treating seeds with zinc (a technique called seed priming) as well as sowing zinc-dense seeds. Several different zinc sources, including ZnSO4, ZnCO3, ZnO, Zn(NO3)2, and ZnCl2, are being used as fertilizers (Shuman, 1998). Application rates of zinc fertilizers vary

depending on the crop, the zinc form, soil conditions, and the application method. Zinc can be applied to soil as organic and/ or inorganic zinc fertilizers. Zinc sulfate (ZnSO4) is the most commonly used inorganic source of zinc due to its high solubility in water, existence in both crystalline and granular, and low cost compared with synthetic zinc chelates such as zinc−ethylenedi aminetetraacetate (ZnEDTA; Martens and Westermann, 1991; Mortvedt and Gilkes,

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1993). For soil applications, the rates can range from 2.5–22 kg Zn ha−1 for inorganic forms such as ZnSO4 and 0.3–6 kg Zn ha−1 for chelated forms (Alloway, 2001). One application of zinc sulfate between 20 and 30 kg ha−1 can improve zinc status of the soil, which will last for around 5 years before another application is required (Alloway, 2004). However, the rates of zinc application can be affected by variations in soil DTPA-extractable zinc and the soil type; for example, the application rates of zinc fertilizer may have to be higher and more frequent in soils with a high content of calcium carbonate. Ekiz et al. (1998) reported that 7 kg broadcast applications of zinc sulfate per hectare on severely zinc-deficient calcareous soils significantly enhanced wheat yield, but that increasing the zinc rate from 7 to 21 kg did not result in an additional increase in grain yield. The agronomic effectiveness (e.g., magnitude of the crop response per unit of applied micronutrient) is higher with ZnEDTA than for inorganic zinc fertilizers. Inorganic zinc fertilizers (such as zinc sulfate) may become ineffective rapidly as the dissolved zinc reacts with soil minerals and organic matter, whereas synthetic zinc chelates have the advantage of keeping the applied zinc in solution in a less reactive form (Martens and Westermann, 1991; Mortvedt and Gilkes, 1993). In maize, it was reported that zinc sulfate was generally less effective than ZnEDTA in increasing zinc uptake on calcareous soils (Maftoun and Karimian, 1989). However, due to its high cost, the use of ZnEDTA in cereal farming is limited. There is also a leaching risk associated with zinc chelates application because the more mobile the chelate, or the less biodegradable the carrier, the greater the leaching risk (Gonzalez et al., 2007). Foliar application of zinc can be effective in alleviating zinc deficiency in plants, particularly in fruit and vegetable production.

Application of 0.5 to 1.0 kg Zn ha−1 as zinc sulfate or 0.2 kg Zn ha−1 as ZnEDTA can often correct zinc deficiency in plants (Martens and Westermann, 1991). The advantage of foliar fertilization is that the fertilizer is applied directly to the plant rather than to the soil. Thus, the absorption of zinc is not interfered by the soil–root transfer processes. Foliar application of zinc was more effective than soil application for increasing grain zinc density but not grain yield (Paterson et al., 1991). When high grain yield and grain zinc concentration are desired, a combined soil and leaf application of zinc was the most effective method. However, in the long term, soil application alone could be the most economical method because zinc applied to soil has a good residual effect and does not need to be reapplied every year (Martens and Westermann, 1991; Yilmaz et al., 1997). During early seed development, zinc transfer from shoots into wheat grains is particularly high, which suggests that the timing of foliar zinc application would be a critical factor for an effective increase in grain zinc density (= biofortification) (Ozturk et al., 2006). Depending on the growth stage of field-grown wheat, foliar applications of ZnEDTA and zinc sulfate at the rate of 400– 450 g Zn ha−1 were either equally effective or ZnEDTA was superior to zinc sulfate in correcting zinc deficiency (Brennan, 1991). Under zinc-deficient conditions, sowing seeds containing higher amounts of zinc can be a practical solution to increasing crop yield. In greenhouse experiments, wheat plants derived from seed low in zinc (250 ng Zn seed−1) had worse seedling vigor and grain yield compared with those arising from seed high in zinc (700 ng Zn seed−1) (Rengel and Graham, 1995b). Seed priming (applying zinc to seeds) is a simple and inexpensive technique, especially for resource-poor farmers. Improving seed zinc content by pretreating seeds in fer-


tilizer solutions can have high agronomic benefits due to accelerated seedling emergence and improved seedling vigor in soils with low zinc availability. However, seed priming alone was not found to increase the seed zinc density of the progeny in wheat (Yilmaz et al., (1997). Similarly, it was reported that zinc-primed rice grains produced larger seedlings, but seed priming had no effect on the zinc content of progeny seeds in rice, lentil, chickpea, and wheat (Johnson et al., 2005). Although seed priming may not substitute for soil or foliar fertilization in biofortifying staple food crops with zinc for human nutrition, it is obvious that seed with high zinc content is advantageous from the perspective of yield and thus food security. Furthermore, seed priming could provide a practical solution in soils with low zinc availability when farmers are not aware of zinc deficiency, and zinc applications are not practiced. There is increasing evidence that enhanced grain nutrient concentration may allow good crop establishment when such seeds were sown in soils with low plantavailable nutrients. In zinc-dense seeds, from an agronomic point of view, there may be enough seed reserves to last until a large root system is developed to compensate for the low nutrient supply in zinc-poor soils (Welch, 1999). Sowing seeds with high zinc concentration may be a practical solution for increasing yield under zinc deficiency (Cakmak and Braun, 2001). In glasshouse experiments, wheat plants grown from high zinc seed had better growth and grain yield than plants derived from the seed with low zinc content (Rengel and Graham, 1995a,b). In the zinc-deficient field, wheat plants derived from seed with high and medium zinc content had a significantly greater grain yield than plants grown from seed with low zinc content (Cakmak and Braun, 2001). In barley, Genc et al. (2000) reported that high seed zinc content reduced visual zinc defi-

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ciency symptoms and improved vegetative growth, especially when zinc supply from the rooting medium was deficient for plant growth. The use of seed with high zinc content could provide a practical approach to alleviating the zinc deficiency problem, especially where farmers are not aware of zinc deficiency, and zinc fertilization is not practical. An alternative approach to increasing crop yields on soils with low plant-available zinc is by exploiting genotypic differences in zinc uptake and tissue use efficiency that exist within crop species (Rengel, 2001; Cakmak, 2002; Hacisalihoglu and Kochian, 2003; Alloway, 2004). There are zincefficient cultivars of rice, wheat, and other crops that are grown widely in soils with low plant-available zinc. This approach is one of matching the plant to the soil rather than modifying the soil to suit the plant. Zinc Deficiency and Drought Tolerance Much of world cereal-growing areas suffer from drought stress and irregular distribution of precipitation during the growing season. Tolerance to environmental stresses is usually associated with a high requirement for zinc to regulate and maintain the expression of genes involved in protecting cells from the harmful effects of stress. Drought stress results in substantial yield losses, and a yield decrease becomes more severe in combination with zinc deficiency (Ekiz et al., 1998; Bagci et al., 2007). Low water availability under drought generally results in reduced total nutrient uptake and frequently causes reduced concentrations of zinc in plant tissues (Gunes et al., 2006). Under greenhouse conditions, drought stress reduced the accumulation of micronutrients, including zinc, in shoots of wheat and chickpea (Gunes et al., 2007). Limited water supply may reduce root

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growth and nutrient mobility in soil and uptake by plants (Fageria et al., 2002; Samarah et al., 2004). Decreased absorption of nutrients like zinc under drought results from an interference in nutrient uptake and unloading mechanisms, and in reduced transpiration flow (Marschner, 1995; Baligar et al., 2001). However, there is genotypic variation among species and genotypes within species in capacity to take up zinc under water stress (Abo-Hegazi et al., 1996; Zubaidi et al., 1999; Garg, 2003; Gunes et al., 2006; Bagci et al., 2007). Under drought stress, nutrient uptake in plants may have an important role in the tolerance (Samarah et al., 2004; Bagci et al., 2007). Water deficit causes oxidative stress by enhancing production of ROS, especially during photosynthesis (Sairam and Saxena, 2001; Li et al., 2004; Selote et al., 2004; Goodman and Newton, 2005). The ROS, including hydrogen peroxide (H2O2), superoxide (O2−), hydroxyl radicals (OH), and singlet oxygen (1O2), are unavoidable byproducts of cell metabolism. Under optimal physiological conditions, the production and destruction of ROS is successfully regulated by cell metabolism. However, under stress conditions, the formation of these radicals might be in excess of the amount present under optimal conditions, thus causing oxidative stress. ROS constitute a major threat to plants due to DNA strand breakage (Brawn and Fridovich, 1981), peroxidation of membrane lipids (Moran et al., 1994), enzyme inactivation (Hernandez-Ruiz et al., 2001), protein denaturation (Bowler et al., 1992), and inhibition of cell cycle progression (Reichheld et al., 1999). Such drought stress-induced production of ROS and increased sensitivity of plants to photoxidative damage in chloroplasts are exacerbated when plants are simultaneously under zinc-deficiency stress. Zinc deficiency can modulate the activities of antioxidative enzymes (Cakmak and

Marschner, 1988a; Wenzel and Mehlhorn, 1995); therefore, oxidative stress is a component of zinc deficiency stress. Cells have antioxidative systems that scavenge superoxide radicals and convert them to H2O2, while the resulting H2O2 can be detoxified in the ascorbate–glutathione cycle, which includes ascorbate peroxidase (APx) and glutathione reductase (Nakano and Asada, 1981). Adequate zinc nutrition may alleviate drought stress in different ways such as inhibition of photoxidative damage caused by ROS in chloroplasts (Cakmak, 2000; Wang and Jin, 2005). Zinc is involved in diminished production as well as detoxification of ROS by anti-oxidative enzymes such as copper/zinc superoxide dismutase (SOD) (Cakmak and Marschner, 1988b; Cakmak, 2000). Copper/zinc SOD is located mainly in the cytosol and/or chloroplasts (Fridovich, 1986). Many transcription factors are involved in tolerance to changes in environmental conditions (Chen et al., 2002), such as zinc finger proteins. More than 600 zinc finger proteins were found in Arabidopsis (Eulgem et al., 2000). However, only a few of these factors respond in a similar way to a variety of different stresses. One representative of the small group of genes that responds similarly to many stresses (e.g., cold, drought, and heat) is the zinc finger protein Zat12 (Fowler and Thomashow, 2002; Kreps et al., 2002; Rizhsky et al., 2004; Davletova et al., 2005). Zat12 was originally isolated as a light-stress-response cDNA (rhl41) by Iida et al. (2000), and was later identified by transcriptome analyses of plants subjected to different biotic and abiotic stress conditions. Zinc in Human Nutrition An emphasis on producing enough calories (and neglecting food quality) has resulted in unforeseen nutritional problems for nearly


50% of the world’s people, especially among the poor populations (UNACCSN, 1992). Around 30% of the world’s population has zinc-deficient diets (Alloway, 2008), emphasizing the importance of zinc content in staple foods, such as rice, wheat, and maize. Zinc deficiency in humans affects physical growth, the functioning of the immune system, reproductive health, and neurobehavioral development. Worldwide, zinc deficiency caused nearly half million deaths in children under 5 years of age in 2004 (Black et al., 2008). In humans, zinc deficiency can be caused by inadequate intake, increased requirements, malabsorption, increased losses, and impaired utilization. In most situations, inadequate dietary intake of absorbable zinc (low total dietary intake, heavy reliance on foods with low zinc content, and/or poorly absorbable zinc) is likely to be the primary cause of zinc malnutrition (Solomons and Cousins, 1984). Poor absorption of zinc may occur as a result of a number of different conditions, such as malabsorption syndromes and inflammatory diseases of the bowel (Bremner and Beattie, 2007; Cummings and Kovacic, 2007), whereas certain drugs that chelate zinc may cause impaired utilization of zinc in tissues (Moretti and Caprara, 2010). Enhancing nutrient content and nutritional quality of crops for human nutrition is currently a global challenge because it was mostly ignored in breeding in the past. Recently, there has been a growing research interest in increasing the micronutrient density in edible portions of crops (Rengel et al., 1999; Schachtman and Barker, 1999; Welch and Graham, 2004; Uauy et al., 2006; Distelfeld et al., 2007; Cakmak, 2008; Sadeghzadeh et al., 2009b), which will result in improved human health as well as better crop production. Micronutrient concentration in grains destined for human food is a more important

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parameter than the micronutrient content. Nutrient concentration in seed is dependent on parent plant growth conditions such as soil type, nutrient availability, crop species, and genotypes (Ascher et al., 1994; Rengel et al., 1999). There is a rapidly developing field of research on the biofortification of plant foods with zinc. This involves both the breeding of new varieties of cereal crops with the genetic potential to accumulate high concentration of zinc in grains (genetic biofortification) and the use of zinc fertilizers to increase grain zinc concentration (agronomic biofortification). Although the plant breeding route is likely to be the most costefficient approach in the long run, for the time being, the use of fertilizers is necessary to improve the zinc density in diets while the plant breeding programs are being carried out. However, it will be necessary to monitor both the zinc concentrations in the cereal grains and also the soil to ensure that the enrichment of the grains occurs without the accumulation of zinc in soils to possibly harmful levels. Breeding for Zinc Efficiency The primary objective of plant breeding has been to enhance farm productivity, usually by developing crops with higher yields. In contrast, improving micronutrient efficiencies and increasing nutrient concentrations in plants has rarely been a breeding objective. In fact, crop nutritional problems have been mostly ignored in breeding. Some nutritional problems cannot be easily resolved by altering soil fertility or chemistry, and application of modern breeding techniques to breed crops adapted to soils of poor nutritional status is required. With micronutrient deficiencies induced by high pH (in case of iron and maganese), agronomic solutions (fertilizers) are not always successful, and a genetic solution is

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necessary (Cakmak and Braun, 2001). Furthermore, correction of zinc deficiency induced by subsoil constraints, topsoil drying, and diseases is not effective via fertilization (Graham and Rengel, 1993). Hence, breeding and use of zinc-efficient plant genotypes that can more effectively function under zinc deficiency is an effective and sustainable solution to zinc deficiency limitations in crop production (Lynch and Steponkus, 1987). Some progress has been made relative to the first stage of breeding, which consists of screening for genetic variability in tissue concentration of trace minerals such as zinc. Most plants contain between 30 and 100 mg Zn kg−1 dry matter, and concentrations above 300 mg Zn/kg are generally toxic (Marschner, 1995). For example, in a glasshouse- and field-grown doubled-haploid barley population (150 genotypes), the range of shoot zinc concentrations were 22–61 mg kg−1 (Sadeghzadeh, 2008). In general, zincefficient genotypes have higher zinc concentration in the shoot than zinc-inefficient ones (Genc et al., 2002b; Sadeghzadeh, 2008). However, some studies do not recommend using zinc concentration as criteria to select for zinc efficiency due to the effect of dilution by growth (Cakmak and Braun, 2001). With the existence of large genotypic variations in zinc efficiency among crops (Cakmak et al., 1998), there is a need for targeted selection and/or breeding of plants with higher efficiency both in terms of higher grain yield and grain zinc concentration. In the past, a lack of a suitable screening procedure to allow screening of large numbers of genotypes in a short time hampered breeding for zinc efficiency. However, screening in the field at nutrient-responsive sites and comparing yields at limiting and nonlimiting rates of zinc has been used extensively to assess efficiency (Takkar et al., 1983; Graham et al., 1992). The results of such screening can be variable because

the severity of the nutrient deficiency varies between sites and years due to the effects of other growth-limiting factors like drought and diseases. Hence, reliable alternative methods are required. The use of controlled environments for screening is a common practice. Considerations of funding and time mean that the screening of large populations for development of molecular markers requires a pot culture screening system. Soil-based pot assays under controlled conditions allowed the relative efficiency of genotypes to be assessed (Cakmak et al., 1997b; Genc and McDonald, 2004), but these are generally based on seedling growth rather than grain yield. Finally, a major challenge will be to demonstrate the relevance of these screening methods under field conditions. Lombnaes and Singh (2003) chose four approaches to characterize tolerance to zinc deficiency in barley and wheat: (1) relative shoot weight at low compared with high zinc supply (zinc efficiency index), (2) relative shoot-to-root ratio at low compared with high zinc supply, (3) total shoot uptake of zinc under deficient conditions, and (4) shoot dry weight under deficient conditions. Evaluating severity of zinc deficiency symptoms on leaves together with the zinc efficiency ratio (yield at –Zn/yield at +Zn) appears to be a reasonable approach to reliably and quickly screen large numbers of genotypes for zinc efficiency in a short time (Cakmak and Braun, 2001; Genc et al., 2003). Mechanisms of Zinc Efficiency Various mechanisms have been proposed to explain zinc efficiency at the molecular, physiological, structural, and developmental levels, but the actual mechanisms involved are not clear. In general, zinc-efficient genotypes show increased zinc uptake efficiency by roots and/or more efficient utilization of


zinc within the cells. It was suggested that zinc-efficient plant species have the ability to mine zinc from soil by enhancing availability of zinc in the rhizosphere (Dong et al., 1995; Cakmak et al., 1996b; Rengel et al., 1998; Gao et al., 2005). Genc et al. (2006) reported that there are a number of different mechanisms contributing to zinc efficiency in barley, but uptake is the major one, and its effect is modified by the physiological efficiency within shoot. Increased zinc uptake might be dependent on root surface area, root colonization by mycorrhizae, pH decline in rhizosphere, release of zinc-chelating PS from roots, and induction of polypeptides involved in zinc uptake and transport across the plasma membranes (Rengel and Graham, 1995c; Cakmak and Braun, 2001). Zinc efficiency can be influenced by root size and morphology, which vary among plant species (Dong et al., 1995; Genc et al., 2007; Chen et al., 2009b) (see also Chapter 2). Longer and thinner roots with increased root surface area may influence availability of zinc and other nutrients such as copper, manganese, iron (Rengel and Graham, 1995c). Furthermore, soil biological activity such as root colonization by mycorrhizal fungi increases the uptake of diffusionlimited nutrients, including zinc, phosphorus, and copper (see Chapters 3, 12, and 17). Arbuscular mycorrhizae (AM) enables plants to increase zinc uptake by expanding the volume of soil explored by the root system (Gao et al., 2007; Subramanian et al., 2009). The fungal hyphae extend from the roots into the soil, and explore greater distance than root hairs. In maize, AM increased zinc uptake and shoot zinc content in soils with low plant-available zinc concentration (Faber et al., 1990). Roots alter rhizosphere chemistry by changing the rhizosphere pH (Fageria and Stone, 2006; Wang et al., 2006b) and/or releasing PS that could chelate soil zinc and

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increase its availability (Cakmak et al., 1994; Suzuki et al., 2006; Masuda et al., 2008). Root-mediated decline in pH increases zinc availability by solubilizing zinc from inorganic and organic soil complexes (Hacisalihoglu and Kochian, 2003). A number of studies have focused on the role of root exudates in zinc efficiency. PS are nonproteinogenic amino acids released from roots of graminaceous species under deficiency of iron (Marschner, 1995) or zinc (Zhang et al., 1991; Kochian, 1993). In the rhizosphere, root exudation plays an important role in increasing the mass and activity of soil microbes that can enhance decomposition of soil organic matter and nutrient cycling (Baudoin et al., 2003; Butler et al., 2003). PS released from roots can also change the solubility, adsorption/desorption, fractionation, and migration of metals in soils through dissolution, chelation, and oxidation/reduction (Clemens et al., 2002; Kuang et al., 2003; Xu et al., 2007a; RasouliSadaghiani et al., 2010). They are involved in mobilizing zinc from the apoplast of wheat roots (Zhang et al., 1991) and, possibly, in translocation and solubility of zinc within the plant (Welch, 1995). Root exudation is closely linked to plant nutritional status, with enhanced rates of exudation in response to nutrient deficiency (Ström et al., 2001; Dakora and Phillips, 2002; Rengel, 2002; Ryan et al., 2003; Shen et al., 2003; Xu et al., 2007a). Under zinc deficiency, release of PS is about 6–8 times lower in zinc-inefficient durum wheat than zincefficient bread wheat (Cakmak et al., 1996c, 1998). In rice grown in nutrient solution, zinc uptake efficiency correlated with exudation rates of low-molecular-weight organic anions (Hoffland et al., 2006). Under low soil zinc, the total concentration of organic acid anions in root exudates of barley genotypes was twofold and that of total amino acids 2.5-fold greater in Sahara

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(zinc-efficient) than Clipper (zinc-inefficient) (Rasouli-Sadaghiani et al., 2010). The results on the role of root PS release in zinc efficiency are both contradictory and somewhat controversial. Erenoglu et al. (1996) found that PS release under zinc deficiency did not correlate with differences in zinc efficiency of efficient and inefficient wheat genotypes. Zinc deficiency did not induce PS release in barley or in wheat cultivars that had previously been reported to exude more PS under zinc deficiency than zinc-inefficient genotypes (Gries et al., 1995; Pedler et al., 2000). Although root exudation of PS does not appear to have a major importance in zinc efficiency, it cannot be ruled out, and the final determination awaits the results of further studies (Rengel, 2001). In comparison, with zinc-inefficient genotypes, zinc-efficient ones may differentially affect the microbe populations in the rhizosphere (Rengel, 1997; Bais et al., 2006; Farinati et al., 2009; Xin-Xian et al., 2009). The rhizosphere is a biologically active zone of the soil surrounding the plant roots (Chapter 3). This zone is an important component of biogeochemical cycling of nitrogen, carbon, phosphorus, and other nutrients (Singh et al., 2004), which is essential for promoting plant growth (Morrissey et al., 2004). The number of pseudomonads increased significantly in the rhizosphere of zinc-efficient wheat genotypes under zinc deficiency (Rengel et al., 1996; Rengel, 1997). However, further research is needed to investigate a possible causal relationship between zinc efficiency and increased microbial populations in the rhizosphere. Zn-efficient genotypes can deliver more zinc from roots to shoots than zinc-inefficient genotypes under low but not under zincsufficient supply (Rengel and Graham, 1995c; Cakmak et al., 1996b). The high zinc efficiency of rye is mainly related to its capacity to take up and translocate zinc to

shoots at much higher rates than other cereals (Cakmak et al., 1997a). Khan et al. (1998) concluded that an efficient zinc uptake coupled with a better root-to-shoot transport could be important for zinc efficiency in chickpea genotypes. There are some reports suggesting that the zinc transport from the soil into the root and then to the shoot is not an important factor in differential zinc efficiency. There are no significant differences in shoot zinc concentration between inefficient and efficient genotypes grown in soils with low plant-available zinc, even when large differences in visual zinc deficiency symptoms can be observed in contrasting genotypes (Cakmak et al., 1999; Hacisalihoglu et al., 2003a). From these studies, the implication is that zinc efficiency might be a shootmediated trait. Most likely possibilities for a shoot-mediated mechanism for zinc efficiency would be: (1) changes in subcellular zinc compartmentation and homeostasis such that the efficient genotypes accumulate higher levels of zinc in the cytoplasm of leaf cells; and (2) more efficient biochemical use of cellular zinc such that zinc-requiring macromolecules can efficiently incorporate zinc as a cofactor under low zinc conditions (Hacisalihoglu and Kochian, 2003). However, both the efficient and inefficient cultivars had similar zinc content in the cytoplasm (9–11%) and vacuole (83–85%) (Hacisalihoglu et al., 2003a), suggesting that subcellular zinc compartmentation may not be involved in zinc efficiency. More studies are needed in this area. For zinc homeostasis, metal-responsive elements (MRE) may play a role by controlling gene expression in relation to changes in plant metal status. The metal response element-binding transcription factor-1 (MTF1) mediates the regulation of genes involved in zinc homeostasis, including responses to both zinc deficiency and toxicity. MTF1 appears to be involved in the


regulation of the free zinc concentration in the cell by allowing zinc to bind to MRE and initiate metallothionein gene transcription (Andrews, 2001). There is a positive correlation between biochemical utilization involving zincrequiring enzymes and zinc efficiency in wheat and bean (Hacisalihoglu et al., 2003a,b). Zinc-efficient genotypes might contain a higher amount of zinc that readily participates in metabolic reactions and binds to zinc-requiring enzymes. Zinc-efficient wheat genotypes showed higher activity of zinc-requiring enzymes (CA and copper/ zinc SOD) than zinc-inefficient genotypes under zinc-deficient conditions and at similar zinc concentrations in leaves (Rengel, 1995a; Cakmak et al., 1997c; Hacisalihoglu and Kochian, 2003). Internal utilization of zinc is considered an important potential zinc efficiency mechanism when zinc-efficient and zincinefficient plants have similar leaf zinc concentrations, and only zinc-inefficient plants show severe zinc deficiency symptoms (Rengel and Graham, 1995c). Genc et al. (2002a) indicated that the greater efficiency of barley genotypes may be attributed to more efficient utilization at the cellular level. Genotypic Variation for Seed Zinc Accumulation Some crops genotypes have a large capacity to take up trace minerals and accumulate them in grain even when grown in soils with low plant-available micronutrients (Graham and Welch, 1996); however, the physiological processes controlling micronutrient accumulation in seeds are not well understood (Welch and Graham, 2002). Nevertheless, micronutrient uptake and accumulation traits in plants are heritable and could therefore be improved by selective breeding. Screening for genetic variabil-

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ity in these traits is the first step in plant breeding (Ruel and Bouis, 1998). Similar to vegetative tissues, there is a significant genotypic variation for seed zinc accumulation in several staple crops including rice, wheat, maize, and bean (Graham et al., 1999; Moraghan and Grafton, 1999; Gregorio et al., 2000; Genc et al., 2002b; Mantovi et al., 2003). For example, the seed zinc concentration of wheat cultivars ranged from 25 to 64 mg kg−1 (Frossard et al., 2000), and field-grown barley seed zinc content varied from 0.7 to 2.9 μg seed−1 (Sadeghzadeh, 2008). It is desirable to combine the ability to load zinc into the grain with a high yield potential. The traits of zinc uptake efficiency from soil and loading into seed are achievable together with breeding for high yield. Farmers can be expected to adopt higher yielding genotypes with zinc-dense seeds to achieve higher profits. The grain zinc concentration of a genotype reflects its ability to take up zinc from the soil, mobilize zinc from different plant parts, and load it into the grain (Pearson et al., 1995; Genc et al., 2006). However, to obtain reliable information on genetic variation in grain nutrient concentrations, any possible dilution and concentration effects associated with differences in yield potential need to be taken into account (McDonald et al., 2008). Screening for Zinc Efficiency It is important to clearly define zinc efficiency before describing the screening methods. The definition proposed by Graham (1984) is useful in looking at genetic differences in zinc efficiency among plants. He defined zinc efficiency as the ability of a cultivar to grow and yield well in soils too deficient in zinc for a standard cultivar. Zinc efficiency can be calculated as the ratio of yield (shoot or grain dry matter) produced under zinc deficiency (–Zn) to yield

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Fig. 16.2. Genotypic variation in the expression of zinc deficiency symptoms and growth in barley genotypes Sahara (zinc-efficient) and Clipper (zinc-inefficient) grown for 50 days in Lancelin soil fertilized with 0.0 and 0.8 mg Zn kg−1 soil (Sadeghzadeh, 2008).

produced with supplied zinc fertilizer (+Zn). Zinc efficiency can be divided into two components: uptake, or the plant’s ability to acquire the nutrient from the soil, and utilization efficiency, or the ability to convert the absorbed nutrient into grain yield (see Chapter 1). Plant genotypes are widely different in their tolerance to zinc deficiency, both in zinc uptake and in zinc utilization. A wide range of wheat, barley, rice, bean, chickpea, and maize germplasm has been studied, indicating there is enough genotypic variation to allow breeding for nutritional improvement (Fig. 16.2, Table 16.3) (Khan et al., 1998; Genc et al., 1999; Banziger and Long, 2000; Beebe et al., 2000; Gregorio et al., 2000; Ortiz-Monasterio and Graham, 2000; Wissuwa et al., 2006; Sadeghzadeh et al., 2009a). Nutritional traits are generally stable across environments, despite some reported genotype × environment interactions; it is possible to combine high micronutrient traits with high yield (Gregorio, 2002). Rengel and Wheal (1997b) indicated that differences in zinc efficiency between wheat

cultivars are closely related to differences in zinc uptake capacity. Similarly, higher zinc efficiency of rye over wheat cultivars is accompanied by an increase in zinc concentration of shoots; rye has a higher genetic ability to absorb zinc from soils with low plant-available zinc (Cakmak et al., 1997a). In field experiments on zinc-deficient calcareous soils, zinc efficiency is positively correlated with total amount (uptake) of zinc in shoots (Graham et al., 1992; Cakmak et al., 1997b). Although zinc-efficient genotypes have greater zinc uptake ability, they do not necessarily have a higher zinc concentration (amount of zinc per unit of dry weight) in leaf or shoot tissue, or grain (Graham et al., 1992). Indeed, zinc-inefficient wheat genotypes may even have greater zinc concentrations in leaves or grains than zincefficient genotypes (Rengel and Graham, 1996; Cakmak et al., 1997b; Cakmak et al., 1998). Under zinc deficiency, increased zinc uptake by efficient genotypes improves dry matter production and results in corresponding decreases in zinc concentration similar to those present in zinc-inefficient

Table 16.3.

Plant traits used in screening plant genotypes for zinc efficiency

Plant Trait

Plant Type

Reference

Phytosiderophore release

Barley

Gries et al. (1995); Suzuki et al. (2006); RasouliSadaghiani et al. (2010) Cakmak et al. (1996a) Masuda et al. (2008) Hopkins et al. (1998) Cakmak et al. (1994); Walter et al. (1994) Cayton et al. (1985) Cakmak et al. (1996b) Grewal and Williams (1999) Norvell and Welch (1993) Fageria (2002) Yu et al. (1999) Rengel and Graham (1995c; Cakmak et al. (1996b); Rengel and Romheld (2000) Genc et al. (2002a); Sadeghzadeh et al. (2009a) Khan et al. (1998) Pearson and Rengel (1997) Genc et al. (2003); Sadeghzadeh et al. (2009a) Hacisalihoglu and Kochian (2003) Cakmak et al. (1996a); Yu et al. (1999) Jolley and Brown (1991) Cakmak et al. (1998) Cakmak et al. (1997b) Erenoglu et al. (1996) Genc et al. (2007) Gao et al. (2005) Cakmak et al. (1997b) Dong et al. (1995); Rengel and Wheal (1997a) Wu et al. (2003) Cakmak et al. (1996b) Chen et al. (2003) Gao et al. (2005) Pearson and Rengel (1997) Genc et al. (2002a); Sadeghzadeh (2008); Lonergan et al. (2009); Rasouli-Sadaghiani et al. (2010) Khan et al. (1998) Hopkins et al. (1998) Cakmak et al. (1996b) Cakmak et al. (1997b) Erenoglu et al. (1996) Norvell and Welch (1993); Sadeghzadeh et al. (2009a) Cakmak et al. (1996b) Rengel and Graham (1995d) Sadeghzadeh (2008); Birsin (2010) Ranjbar and Bahmaniar (2007) Harris and Taylor (2004) Cakmak et al. (1997c) Lasat et al. (1998) Kothari et al. (1991) Lynch and Whipps (1990)

Shoot/root ratio of Zn (translocation factor) Shoot/root dry weight

Root/shoot dry weight

Scoring Zn deficiency visual symptoms

Fine roots and root surface area

Zn translocation into shoot

Shoot Zn concentration and content

Root Zn concentration and content Flag leaf Zn concentration 65 Zn translocation into shoot Microbial growth in the rhizosphere

Durum Rice Sorghum Wheat Rice Wheat Lucerne Barley Bean Durum Wheat Barley Chickpea Wheat Barley Common bean Durum Navy bean Oat Triticale Wheat Barley Rice Rye Wheat Barley Durum Red clover Rice Wheat Barley Chickpea Maize Durum Rye Wheat Barley Durum Wheat Barley Wheat Durum Wheat Thlaspi Maize Wheat

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genotypes (dilution by growth) (cf. Marschner, 1995). A lack of a suitable screening procedure to allow screening of a large number of genotypes (e.g., doubled-haploid populations) in short time has hampered breeding for zinc efficiency. Different screening methods have been used to evaluate zinc efficiency: nutrient solution culture (Rengel and Graham, 1995c; Sadeghzadeh et al., 2009a), field evaluations (Bagci et al., 2007; Sadeghzadeh, 2008), and greenhouse soil bioassays (Genc et al., 2002b; Sadeghzadeh, 2008). Soil-free systems such as chelatorbuffered hydroponic system have been used commonly to study plant mineral nutrition at realistically low zinc concentrations (Parker, 1997; Rengel, 1999). Chelatorbuffered nutrition solutions simulate soil solution conditions with accurate control of micronutrient activity (Parker et al., 1995), so that zinc deficiency could be induced in a predictable and reproducible manner. Moreover, this system with appropriately low activities of zinc may be useful in ranking genotypes for differential tolerance to zinc deficiency that can be confirmed in the field (Rengel and Graham, 1995c; Rengel, 1999). In a study on differential zinc efficiency of two barley genotypes (Sahara = zinc-efficient; Clipper = zincinefficient) grown in soil and chelatorbuffered nutrient solution, Sadeghzadeh et al. (2009a) reported that the responses of the genotypes to zinc fertilization in chelatorbuffered nutrient solution were consistent with their response in soils in terms of visual zinc deficiency symptoms and shoot and root zinc concentration and content. Although zinc-efficient genotypes possess extensive root systems (Cakmak and Marschner, 1988b; Cakmak et al., 1989), they do not necessarily have bigger roots than inefficient genotypes when grown in nutrient solution. For example, Sahara had less root dry matter than Clipper in nutrient

solution with deficient zinc supply (Sadeghzadeh et al., 2009a). Similar results were reported by Rengel and Graham (1995c), where root growth of zincinefficient wheat genotypes increased in chelator-buffered nutrient solution with deficient zinc supply. In contrast, in chelatorbuffered nutrient solution, Rengel and Romheld (2000) observed a more severe decline in root growth of zinc-inefficient wheat Songlen than zinc-efficient Aroona as a consequence of zinc deficiency, which is consistent with other studies on wheat (Webb and Loneragan, 1990), as well as reports on unchanged root growth of barley grown in chelator-buffered nutrient solution at low zinc activity (Norvell and Welch, 1993; Welch and Norvell, 1993). Therefore, using root growth as a criterion to select for zinc-efficient genotypes when grown in nutrient solution is not recommended. Field-based techniques are more laborious than pot or solution culture ones. The results can be variable because the severity of the nutrient deficiency varies among sites and years due to the effects of other growthlimiting factors (such as drought and disease) as well as the irregular spatial distribution of zinc in soil. Screening under glasshouse condition in pots is generally easier than under field conditions because it is fast, cost-effective, and can overcome problems of soil heterogeneity. The growth containers should be big enough to eliminate root restriction, reduced sink strength at the whole plant level, and reduced photosynthetic enhancement (Arp, 1991). However, pot screening is less realistic than field conditions, especially for grain yield production. Nevertheless, using 150 barley doubled-haploid lines grown to maturity, a strong correlation between zinc efficiency in field and glasshouse conditions was shown (Sadeghzadeh, 2008). However, the suitability of pot screening can be affected when additional nutrient stress


exists. For example, the correlation between zinc efficiency in the field and glasshouse was weak in soils with both boron toxicity and zinc deficiency (Cakmak and Braun, 2001).

Genetics of Zinc Efficiency Most research related to zinc efficiency in crops has concentrated on the physiological aspects of zinc uptake, or has compared genotypes for their relative efficiency for growing in soils with low plant-available zinc. Although some physiological mechanisms involved in zinc efficiency have been documented, limited information is available on the genetic control of these mechanisms and the genes responsible for zinc efficiency. Genetic variability for zinc efficiency and its possibly simple inheritance should allow progress toward improving zinc efficiency in crops. A limited number of studies have yielded some preliminary evidence regarding the genetics of zinc efficiency in several crop species. Studies of chromosome addition lines in rye have shown that copper, zinc, and manganese efficiencies were independent traits located on different chromosomes (Graham, 1984). Results from a diallel analysis in rice suggested that the genes controlling zinc efficiency are additive and, to a lesser degree, dominant (Majumder et al., 1990). In maize, four additive genes were reported to affect zinc concentration in the ear leaf (El-Bendary et al., 1993). Several loci on chromosomes 1R, 2R, and 7R enhance zinc efficiency in rye, with genes on short arms of 1R and 7R being the most effective (Schlegel and Cakmak, 1997; Cakmak et al., 1997a). The distribution of F3 populations from the cross between zincefficient and zinc-inefficient genotypes showed that only a few genes control zinc efficiency in soybean based on measure-

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ments of foliar zinc concentrations (Hartwing et al., 1991). The results from a diallel experiment comparing seven wheat cultivars differing in zinc efficiency with their F1 derivatives showed that genes controlling zinc efficiency are dominant (Cakmak and Braun, 2001). The overexpression of zinc transporters in cereals may affect plant growth, seed mineral content, and zinc transport rates (Table 16.4). Lasat et al. (1996) found that enhanced expression of genes encoding zinc transporters can increase zinc uptake in T. caerulescens and T. arvense. Further studies in this system found a zinc transporter ZNT1 gene that was highly expressed in T. caerulescens, allowing enhanced zinc uptake (Lasat et al., 2000; Pence et al., 2000; Assunção et al., 2001). ZNT1 gene is a member of the ZIP family of metal transporters (Guerinot, 2000) that are known to transport a variety of divalent cations. Transgenic Arabidopsis that overexpressed a plasma membrane ion transporter, ZAT, exhibited enhanced zinc content in the roots of plants grown in a high-zinc environment (Van der Zaal et al., 1999). In barley, overexpression of an Arabidopsis zinc transporter increased short-term zinc uptake and seed cation content (Ramesh et al., 2004). Uauy et al. (2006) reported that a reduction in RNA levels of the T. aestivum, No Apical Meristem (TaNAM) gene, is associated with a decrease in wheat grain zinc and iron concentrations and an increase in residual nitrogen, zinc, and iron in the flag leaf. These results suggest that the reduced grain zinc and iron concentrations were the result of reduced translocation from leaves, rather than a dilution effect caused by larger grains. By using visual zinc deficiency symptoms, it was reported that a single dominant gene controls tolerance to zinc deficiency in common bean (Singh and Westermann, 2002). Similarly, using a visual score of deficiency symptoms in barley, Genc et al.

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Examples of up-regulated expression of genes encoding proteins responsible for Zn uptake, sequestration and redistribution within the plant during Zn deficiency

Table 16.4.

Gene

Encoded Protein

Plant Type

Reference

ZIPs

Zinc iron-like proteins (Zinc iron permeases)

Arabidopsis

HMAs

Heavy-metal ATPase family

Grotz et al. (1998); Wintz et al. (2003); Talke et al. (2006); Van De Mortel et al. (2006); Krämer et al. (2007) Ishimaru et al. (2005) Wintz et al. (2003); Papoyan and Kochian (2004); Verret et al. (2004); Van De Mortel et al. (2006) Suzuki et al. (2006) Wintz et al. (2003); Schaaf et al. (2005); Grotz and Guerinot (2006); Waters et al. (2006) Arrivault et al. (2006); Rout and Das (2009) Chen et al. (2009a)

Rice Arabidopsis

YSLs

Yellow stripe-like proteins Metal tolerance proteins

Barley Arabidopsis

MTPs

Zn-induced facilitator

Arabidopsis

Ferric reductase defective 3 Nicotianamine synthase

Medicago

ZIF

Thlaspi Arabidopsis

FRD3

Arabidopsis

NAS

Arabidopsis

Tobacco

Assunção et al. (2001) Hussain et al. (2004); Haydon and Cobbett (2007a) Delhaize (1996); Rogers and Guerinot (2002); Van De Mortel et al. (2006) Wintz et al. (2003); Becher et al. (2004); Weber et al. (2004); Talke et al. (2006) Takahashi et al. (2003)

FRD, ferric reductase defective.

(2003) reported that tolerance to zinc deficiency at the seedling stage is controlled by a single gene with no dominance. Concluding Remarks Low plant availability of soil zinc is a critical problem for crop production, causing severe reduction in yield and nutritional quality of the edible portion of field crops. High zinc efficiency in crops appears to be related to various morphological and physiological traits such as root surface area, zinc-mobilizing root exudates, and better utilization of zinc at the cellular level. Combining improved tolerance to zinc deficiency in soils and increased zinc concentra-

tion and content in seed is a highpriority research topic. This topic, however, requires a comprehensive exploration of potential genetic resources and an indepth understanding of zinc accumulation mechanisms. The processes and factors that control zinc transfer from soil to roots and shoots and then to the grain are far from being understood. More work is also needed on the effects of cultivation methods on phytate concentrations in food crops (phytate limits zinc absorption in the human digestive system) and the implications for human health. Research is also needed on the role of soil biota in zinc accumulation by plants.


With the growing awareness of the large numbers of people suffering from zinc deficiency, there is enough nutritional evidence to persuade plant breeders to consider zinc density traits as an important objective in the breeding programs targeted to the developing world. Currently, the application of zinc fertilizers appears to be a cheap, effective, and short-term means of increasing zinc concentration in grains. This increased zinc density in grain would have to be achieved without concomitant yield depression. However, increased application of zinc fertilization beyond a critical level can cause a vegetative and grain yield decrease because of zinc toxicity. The long-term solution is to develop new genotypes with higher concentration of zinc as well as nutritional enhancers that promote zinc bioavailability. Such biofortification would improve the health of people (especially susceptible populations) consuming these crops. There is significant genetic variation for zinc efficiency in cereals, suggesting that selection for improved zinc efficiency is possible. Evaluating the severity of zinc deficiency symptoms on leaves as well as monitoring shoot and seed zinc concentrations and content appear to be useful approaches for screening large populations for zinc efficiency. In view of the difficulty in developing fast and reliable methods of screening for efficiency (such as seedling selection in pots) or their limited applicability to field conditions, development of molecular markers for zinc efficiency is considered important for success in cereal breeding programs. The recent identification of DNA markers diagnostic of zinc efficiency should accelerate production of cultivars yielding well on soils with low plant-available zinc (Lonergan et al., 2009; Sadeghzadeh et al., 2009b), and may be the starting point for identifying the specific genes responsible for differences in the response of crops to zinc deficiency.

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Chapter 17

Overview of the Acquisition and Utilization of Boron, Chlorine, Copper, Manganese, Molybdenum, and Nickel by Plants and Prospects for Improvement of Micronutrient Use Efficiency Patrick H. Brown and Elias Bassil

Abstract The development of crops with improved micronutrient use efficiency requires an integrated consideration of the soil, plant, and environmental processes that determine nutrient acquisition and utilization. In the following, an overview of the extent of global deficiency, the chemistry of element behavior in soil, and the biological mechanisms of acquisition and utilization of boron, chlorine, copper, manganese, molybdenum, and nickel by plants is provided with emphasis on the molecular and physiological processes that hold most promise for optimizing the efficiency of use of these elements.

Introduction Agronomically important deficiencies of the essential micronutrients boron (B), chlorine (Cl), copper (Cu), manganese (Mn), molybdenum (Mo), and nickel (Ni) occur worldwide (Alloway, 2008). The scale and importance of these deficiencies, however,

varies greatly, boron deficiency occurs globally across a wide range of climates, cropping systems and soils; copper, manganese, and molybdenum deficiencies are of great importance in particular soil types and cropping systems, while nickel and chlorine deficiencies have been demonstrated in only isolated environments with limited crop species. The development of crops with improved micronutrient use efficiency requires consideration of the soil, plant, and environmental processes that determine nutrient acquisition and utilization. This chapter provides an overview of these processes with an emphasis on the physiological and molecular basis of micronutrient acquisition and an analysis of the prospects for improvement of micronutrient use efficiency. The micronutrients iron and zinc are dealt with in Chapters 15 and 16, respectively. Among the techniques used to predict crop response to micronutrients is the integration of data drawn from soil maps, tissue testing, and on-farm and off-farm testing.


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Sillanpää (1982, 1990) utilized field and laboratory trials, tissue sampling, and soil analysis and mapping to provide the first detailed maps of micronutrient-responsive soils for Africa, Europe, and parts of Asia. This approach has now been replicated in many countries and regions (see summaries in Alloway, 2008; Brown, 2008; Zou et al., 2008; Singh, 2008). The utility of these maps for micronutrient management is limited, however, since they generally lack sufficient resolution for farm-scale management and do not adequately integrate local environmental conditions, cropping system, and management practices. The occurrence of visual symptoms can also be used to identify micronutrient deficiencies but requires considerable expertise and is complicated by plant age, disease, and herbicide damage, and often varies with environment. Visual symptoms also do not appear until after plant growth has been reduced and yield has been substantially impacted. Conclusive diagnosis of micronutrient deficiency generally requires tissue analysis, which is expensive and difficult to perform effectively. Neither the visual analysis of symptoms nor tissue analysis provides any information on the cause of the deficiency or the approach required to correct the problem. The difficulties in assessments of micronutrient needs are exacerbated by the frequent ineffectiveness and high cost of micronutrient fertilizers and the oftenvariable crop response. Together these factors confound experimentation, make crop management decisions difficult, and add great complexity to the development of micronutrient-efficient cultivars. For the micronutrients discussed in this chapter, our understanding of the processes involved in soil acquisition and utilization of micronutrients is inadequate, and as a consequence most micronutrient management strategies are not based on well-established chemical or biological principles but are the result of

field experimentation and grower experience. Practices not based upon a clear physical or physiological understanding are frequently difficult to transfer to other locations or adapt to changing production practices. Micronutrient fertilization is often viewed as an uncertain, high-risk, and costprohibitive undertaking in low-input systems, while risk aversion in high-input systems has resulted in widespread application of micronutrients even in the absence of a predictable response (Brown, 2008). To achieve the goal of optimizing the efficiency of micronutrient use and maximizing crop productivity and quality, a better understanding of the processes involved in acquisition, and utilization of micronutrients by plants is required. Optimization of nutrient use efficiency cannot be achieved through improvements in understanding of fundamental processes alone but will require a sound understanding of soil supply processes, the environment, and agronomy of the cropping system of interest. Graham (1984) defined nutrient efficiency as the ability to produce a high plant yield in a soil, or other media, that would otherwise limit plant growth. While this definition is highly relevant in a crop improvement context for a given environment, it does not provide a mechanistic understanding of the processes involved and hence may not be transferable to new environments. This definition of efficiency, which was developed before the advent of low-cost molecular genetic techniques, may also fail to identify germplasm with unique efficiency traits if those traits are present in an otherwise unproductive background. Approaches for identifying and manipulating nutrient efficiency that focus solely on isolated mechanistic processes are equally constrained and can lead to the identification of germplasm of little agronomic relevance (for discussion see Gourley et al., 1994). Thus, a very highly nutrient-efficient

BORON, CHLORINE, COPPER, MANGANESE, MOLYBDENUM, AND NICKEL

germplasm may be of little agronomic value if maximal potential yield is low. Additionally, a cultivar that is inefficient at very low nutrient availability may have high nutrient utilization efficiency (yield per unit available nutrient) when nutrient availability is high. Nutrient use efficiency is ultimately determined by a complex of factors of varying importance including: (1) the amount, solubility, and distribution of the element in the soil, (2) the characteristics and regulation of nutrient acquisition from the soil by plant roots, (3) the function and demand for the element in the plant life cycle, and the (4) the mobility of the element within the cell and the plant. The relative contribution of each of these factors to overall nutrient use efficiency and the prospects for improvement in NUE differs widely among the nutrients. Boron, chlorine, copper, manganese, molybdenum, and nickel are extremely diverse in their chemical properties, which in turn influences soil reactions, the form of nutrient absorbed by roots and utilized in metabolism, and the function and mobility of the nutrient in plants. Available information on the molecular and physiological mechanisms of acquisition and utilization of boron, chlorine, copper, manganese, molybdenum, and nickel varies greatly in both quality and quantity. For the two most recently defined plant essential elements, chlorine (Broyer et al., 1954) and nickel (Brown et al., 1987), very little molecular and physiological information exists, while in contrast, the past decade has seen a tremendous increase in understanding of boron, copper, and manganese. The great diversity in chemistry, biology, and information available for the elements boron, chlorine, copper, manganese, molybdenum, and nickel precludes a unified discussion of the acquisition, utilization, and prospects for improvement of nutrient use

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efficiency of these elements. Collectively, boron, chlorine, copper, manganese, molybdenum, and nickel, however, do provide illustrative examples of each of the varied factors that determine nutrient efficiency and the diverse approaches that have been used to improve micronutrient use efficiency in crop plants. Optimized micronutrient status is essential not only for maximal productivity but also to ensure optimal crop quality, disease resistance, and the efficient use of both water and nitrogen by the crop. Boron, chlorine, copper, manganese, molybdenum, and nickel are beneficial for human health; however, there is very little data to suggest these elements are deficient in human populations and little rationale for explicit attempts to enhance the content of these nutrients in foods. In the following, an overview of the extent of global deficiency, the chemistry of element behavior in soil, and the biological mechanisms of acquisition and utilization of boron, chlorine, copper, manganese, molybdenum, and nickel by plants is provided with emphasis on the molecular and physiological processes that hold most promise for optimizing the efficiency of use of these elements. Boron Boron deficiency occurs widely and is considered the second most important micronutrient deficiency globally. It is a major constraint in cereal and brassica crops throughout south Asia and in forest and horticultural production in high rainfall zones worldwide. Reproductive growth is especially sensitive to boron deficiency and substantial crop losses can occur when no clear vegetative signs of deficiency are observed. Deficiencies are exacerbated by climate, temperature, and water stress, and are frequently erratic and transient in occurrence and hence difficult to detect or predict. Boron

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is among the least understood of all plant micronutrients and has only a single known essential function, as a component of the cell wall. While much progress has been made toward understanding the mechanisms of boron acquisition from soils and transport within the plant, our understanding is still far from adequate and many observed responses to boron deficiency cannot be explained. Species and genotypes vary significantly in their ability to grow in boron-deficient and toxic environments and success has been achieved in identifying and developing superior germplasm with greater efficiency of boron use and tolerance to toxicity. Boron in soils and plants and occurrence of global deficiencies Among the essential plant micronutrients, boron deficiency is the most widespread in agriculture (Loomis and Durst, 1992; Shorrocks, 1997) and impacts plant productivity by reducing not only quantity but also the quality of yield. One significant cause of boron deficiency that distinguishes it from other micronutrient deficiencies is that boron deficiency specifically inhibits growing tissues and especially reproductive structures, which represent more than 80% of the world’s agricultural product (Brown et al., 2002). Boron deficiency occurs in diverse cropping systems throughout the world and across a wide range of climates and is not restricted to specific soil types or crops. While boron deficiency is more prevalent on leached sandy, alkaline, and heavily limed soils, boron is easily leached from most soils and deficiencies often occur in areas with high rainfall (South East Asia, Japan, and Brazil) or in irrigated zones utilizing water with low boron content (2.0 g kg−1 DM) (Heckman, 2007). The best documented example of agricultural chlorine deficiency is in the wheatgrowing regions of the Great Plains of the United States (Fixen, 1993; Heckman, 2007). These rain-fed regions are typified by very low chlorine deposition in rain (98% of soluble copper in soils is complexed as Cu(II)-DOM (Sauve et al., 1997). It is estimated that a solution Cu2+ concentration of >5 × 10−9 M is required to support plant growth (Degryse et al., 2006; Bravin et al., 2010); soil solution Cu2+, however, is rarely present in noncontaminated soils in excess of 1 × 10−12 M, suggesting that free Cu2+ is not the sole source of copper for plants (Sauve et al., 1997; Nolan et al., 2005; Nolan et al., 2010). This suggestion is further supported by the observation that normal plant growth can also be attained in nutrientbuffered solutions in which free Cu2+ concentrations of 20%) with no vegetative symptoms. Typical concentrations of copper in plants is 2–50 μg g−1 DW with deficiencies occurring from 1 to 5 μg g−1 DW depending on plant species, plant organ, developmental, stage and nitrogen nutrition (Marschner, 1995). Function and deficiency symptoms Copper exists in two oxidation states, Cu+ and Cu2+, and readily participates in oxidation reduction reactions. In photosynthesis, copper is essential for plastocyanin-mediated electron transport, and in mitochondrion, copper occurs in cytochrome c oxidase in respiratory electron transport chains (Hänsch

and Mendel, 2009). More than half of the copper found in plants is found in chloroplasts and participates in photosynthesis. Copper has a high affinity for O2 and is a cofactor for a number of oxidases involved in cell wall metabolism and oxidative stress protection (Marschner, 1995; Burkhead et al., 2009; Yruela Guerrero, 2009). Copper may be essential for molybdenum (Mo) cofactor synthesis and hence may play an indirect role in nitrogen assimilation and abscisic acid (ABA) synthesis (Burkhead et al., 2009). Copper is also involved in the function of the ER-localized ethylene receptor, ETR1 (Rodriguez et al., 1999), and it was recently hypothesized that smallamplitude cytosolic copper oscillations may be involved in synchronization of cellular cycles (Penarrubia et al., 2010). Overexpression of the copper transporters COPT1 or COPT3 substantially reduces the expression of the nuclear circadian clock genes CCA1 and LHY (Andres-Colas et al., 2010). While the function of copper in plastocyanin, ethylene reception, and cytochrome c oxidase are well understood, the function of copper in the other known and putative copper proteins is uncertain. Typical symptoms of copper deficiency are stunted growth, apical necrosis, wilting, bleaching of young leaves, and deformation of growing organs including leaves, bark, stems, anthers, and pollen (Marschner, 1995). Reproductive tissues are much more sensitive than vegetative tissues and seed and fruit yield can be decreased significantly at copper supply levels that do not cause vegetative symptoms (Marschner, 1995). In addition to visual expressions of copper deficiency, low-copper plants show clear reductions in cell wall lignification as well as decreases in levels of soluble carbohydrates. Plant requirement for copper is also increased by nitrogen application, and copper deficiency inhibits nitrogen fixation.


While some of the symptoms of copper deficiency can be explained by known functions of copper in plants, others cannot. The deformation of organs, wilting, and impacts on pollen formation under copper deficiency occur as a consequence of the disruption of polyphenol oxidase, laccase, amine oxidase, and perhaps ascorbate oxidase, all of which function in cell wall synthesis. Apical necrosis, excessive tillering, and wilting also occur as a consequence of cell wall deformation, and bleaching of leaf tissue may be a consequence of decreased Cu/Zn SOD activity and degradation of chloroplasts (Henriques, 1989; Bernal et al., 2006). It is well demonstrated that dependence on nitrogen fixation and the application of nitrogen fertilizers increases copper demand, although an explanation for this effect has not previously been offered. The discovery that copper is essential for the synthesis of the molybdenum cofactors (Burkhead et al., 2009) may suggest that copper deficiency impairs nitrogen metabolism through a disruption of Mo-dependent nitrogenase and nitrate reductase activity. An interaction between copper status and the efficiency of molybdenum and nitrogen use in agriculture is likely. Copper is essential for plastocyanin function and more copper is present in plastocyanin that any other molecule. While copper deficiency is known to reduce tissue plastocyanin levels and PSI activity, these effects are generally not observed in the early stages of deficiency. The apparent insensitivity of plastocyanin to mild copper stress may be explained by recent findings that copper is preferentially allocated to plastocyanin during early deficiency onset. The mechanisms of allocation are discussed below.

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complex with polypeptides makes copper ions highly toxic. The Irving–Williams series specifies that Cu2+ and Zn2+ typically form more stable complexes than Fe2+ or Mn2+ (Lippard and Berg, 1994). To maintain the essential functions of copper while protecting cellular metabolism from the negative effects of copper ions, plants have developed an array of transport, complexation, and localization mechanisms. Copper, for example, has a greater affinity than manganese for the Mn-dependent periplasmic protein MncA in cyanobacteria such as Synechocystis PCC 6803 (Tottey et al., 2008), and copper incorporation into MncA renders the protein nonfunctional. To avoid substitution of manganese by copper in MncA, protein folding and metal incorporation occur external to the periplasm, where manganese is present at 104 greater molar ratios. Once in the folded conformation, the MncA is exported to the periplasm and copper can no longer replace the incorporated metal. Copper localization and homeostasis is thus tightly regulated and essential for metabolism. With the possible exception of iron, our understanding of the processes governing the transport and homeostasis of copper in plants is greater than for any other microelement. The mechanisms of uptake, transport, and homeostasis have been reviewed in great detail in a number of excellent recent publications and are summarized here (Colangelo and Guerinot, 2006; Pilon et al., 2006; Puig et al., 2007; Burkhead et al., 2009; Giehl et al., 2009; Palmer and Guerinot, 2009; Pilon et al., 2009; Puig and Penarrubia, 2009; Yruela Guerrero, 2009; Penarrubia et al., 2010). A summary of known and putative whole-plant and cellular copper transporters is provided in Figures 17.3 and 17.4.

Uptake, transport, and homeostasis The ability of copper to serve as a redox agent in metabolism, to react with molecular oxygen and generate oxygen radicals, and to

Uptake by roots Estimates of the kinetic parameters (KM, Vmax) of copper uptake derived from soil,

396 Cu+ CO OPT1 Cortex

Mn2+

Endodermis

NRAMP1

HMA5 CAX2 FRD3

Cu+ Mn2+ Citrate Pericycle

Shoot

Mesophyll

CAX2

YSL

IRT1 Mn2+

Mn2+

Mn2+,Cu2+ ,Ni2+ ?

Xylem

YSL?

Ni(II) – malate/citrate/h istidine

NA -Cu2+ NA –Mn2+

COPT1?

Guard Cell

Cu+

Companion cell

YSL 1, 3?

COPT1, COPT3, HMA5

FRO 6,7 ?

Reproductive Organs

Mn2+, Cu2+ ? 2 ? Ni2+

Cu+

Phloem

NA-Cu2+ NA -Mn2+

Ni(II) – malate/citrate/h l t / it t /h istidine

CCH-Cu

reduction is unknown though co-reduction by the ferric reductase FRO2 is possible. Expression analysis suggests that copper loading into leaves and reproductive structures may also utilize COPT transporters. HMA5 appears to be required for copper loading into the xylem, while the YSL transporter may be involved in NA–Cu uptake into leaf and reproductive tissues. The copper chaperone CCH appears to be required for copper movement to seeds during senescence. Manganese: Mn2+ is the sole ionic form of manganese known to be transported in plants and transport occurs through the ZIP, IRT, and NRAMP family transporters at both root surface and into leaf cells. Vascular loading and unloading is mediated by CAX2. Transport into reproductive tissue may involve the YSL transporters of the Mn(I)I-nicotianic acid (Mn–NA) complex. Nickel: Relatively little is known about nickel transport. Uptake likely occurs through the divalent cation transporters (ZIP/IRT/NRAMP). Nickel has a high affinity for histidine, malate, and citrate and is mobile in both the xylem and the phloem. The involvement of the YSL transporters has been proposed. Modified with permission from Palmer and Guerinot, 2009.

Fig. 17.3. Intercellular copper, manganese, and nickel transport in dicots. Copper: Copper uptake from soils occurs as the reduced Cu+ through COPT1; the mechanism of copper

NRAMP1 Epidermis Root

IRT1

ZIP?

?

F FRO2

Mn2+

?

Ni2+

Cu2+

Cu+


397

Cu2+ Cu+ Cu+

Mn2+ ?

NRAMP4

Ni

NRAMP3

Mn2+

CCS CuSOD2

PC

Cu+

CCS

ETR

RAN1 AT X

CuSOD2

IREG2

Ni

CAX2

Mn2+

COPT

Cu+

Mn2+

Chloroplast

Ni-ure?

Mn2+

CCH

Golgi/ER

Mitochondrion COX17 COX11

PVC

Mn2+

Cytc Ox

MTP1 1

MnSOD2

Vacuole

Mn2+ CuSOD3

Peroxisome

Mn2+

Chaperone

Enzyme

Transporter

HMA1

Fig. 17.4. Intracellular metal transport: Copper: Transport into the chloroplast is best characterized for copper, which is transported into the chloroplast by HMA1 and PAA1. PAA2 transports copper across the thylakoid membrane, a mechanism for transport into the chloroplast, and mitochondria are unknown. Cu-chaperones regulating metal insertion into CuSOD (CCS), the ethylene receptor (ATX, CCH), and mitochondrial Cyt C Oxidase (COX11, COX17) have been identified. Very little is known about transport of copper in and out of the mitochondria. COPT family transporters function at the root plasma membrane, in vascular tissue, cell surface, and tonoplast. Manganese: Mechanisms for transport of Mn2+ have been identified for mitochondrial transport (MTM1), vacuole (NRAMP3/4) and CAX2, and per-vacuolar and endosomal vesicles (ECAC1, MTP11). Mechanisms for manganese transport into the chloroplast have not been defined but may involve direct tonoplast/chloroplast interaction. Nickel: Nickel transport occurs through divalent metal ion transporters (NRAMP and IREG2). Ni-ure is a nickel urease accessory protein (chaperone) and has been cloned in bacteria with homologs present in plants. Modified with permission from Palmer and Guerinot (2009).

solution culture, and nutrient-buffered solution culture experiments are highly varied. Reported KM values for copper uptake range from 0.2 to 90 nM, while Vmax varies from 40 to 40,000 ng Cu m−2 s−1 (discussed in Bravin et al., 2010). The inconsistencies in reported values can be attributed to the copper concentrations used and the use of

free Cu2+ as the source and measure of the copper treatment. The majority of copper in soil solutions is present as Cu(II) complexes with dissolved organic matter (Cu(II)DOM); the presence and composition of metal ligands influences Cu2+ uptake by plants (Degryse et al., 2006; Amery et al., 2010); and free Cu2+ is not present in

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adequate amounts to support growth (see discussion above). It is estimated from nutrient-buffered solution culture experiments (Bell et al., 1991; Parker and Norvell, 1999) that an available copper concentration (all forms) of about 1 × 10−10 M is required to support plant growth (Degryse et al., 2006; Bravin et al., 2010) and normal plant growth can be maintained in nutrientbuffered solutions with free Cu2+ concentrations of 6.5, on soils with low total manganese content (sandy soils and weathered tropical soils) and in high organic matter soils (Alloway, 2008). Manganese deficiency is the most important micronutrient problem in large areas of cereal production on light-textured, alkaline, high-carbonate soils of southern Australia (Holloway et al., 2008) and in cool growing regions of Denmark (Hebbern et al., 2005),


and is also the most important micronutrient deficiency in arable crops in the United Kingdom grown on predominantly neutral high organic matter soils (Sinclair and Edwards, 2008). Although species and cultivars vary dramatically in their ability to grow on low-manganese soils, the critical tissue manganese requirement for most plant species is remarkably uniform (10–20 mg Mn kg−1). Species that are most sensitive to manganese deficiency include barley (H. vulgare L.), oat (Avena sativa, L.), wheat (T. aestivum, L.), apple (Malus domestica Borkh.), cherry (Prunus avium L.), raspberry (Rubus spp. L.), pea (Pisum sativum L.), bean (Phaseolus vulgaris L.), sugar beet (B. vulgaris L.), soybean (Glycine max Merr.), and potatoes (Solanum tuberosum L.) (Marschner, 1995; Alloway, 2008). Recent evidence suggests that the C4 NAD malic enzyme species, pearl millet (Pennisetum glaucum (L.) R. Br.) and purple amaranth (Amaranthus hypochondriacus (L.) cv. Plainsman), have a 10–30-fold higher tissue requirement for manganese for optimum growth and photosynthesis than corn (Z. mays (L.) cv. FR 697), grain sorghum (Sorghum bicolor (L.) Moench), wheat (T. aestivum (L.) cv. Ernie), and squash (Cucurbita pepo L. cv. Straighneck) (Kering et al., 2009). Function and deficiency symptoms In biological systems, manganese occurs in oxidation states II, III, and IV, and functions in redox reactions and as an activator of a diverse number of enzymes (Marschner, 1995; Hänsch and Mendel, 2009). Manganese functions as a redox element in the catalytic site of (1) the chloroplast-localized oxygenevolving complex of PSII; (2) mitochondrial superoxide dismutase MnSOD; (3) apoplastic oxalate oxidase (OxO), which catalyzes the conversion of oxalate (from Ca oxalate and oxalic acid) and dioxygen to CO2 and

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H2O2 (Requena and Bornemann, 1999); and (4) ER-localized allantoate amidohydrolase (AAH), which metabolizes allantoate in the ureide pathway (Serventi et al., 2010). Manganese is also essential for malic enzyme activity in bundle sheath chloroplasts of NAD-dependent C4 species (Marschner, 1995; Kering et al., 2009). Manganese is an activator of a large number of different enzymes, such as isocitrate dehydrogenase, PEP carboxykinase, and phenylalanine ammonia lyase, decarboxylases, and dehydrogenases in the tricarboxylic acid cycle and in several glycosyltransferases in the Golgi apparatus. Manganese deficiency disrupts the shikimic acid pathway, lignin synthesis, flavanoids, fructans, and indole acetic acid (IAA) metabolism (Marschner, 1995; Bai et al., 2006; Hänsch and Mendel, 2009). Most of the studies demonstrating an effect of Mn2+ on enzyme activation have been conducted in vitro, and in most instances Mg2+ is more effective; given that Mg2+ is present at up to 100 times the concentration of manganese in plants, the relevance of many of these observations to in vivo enzyme activity is unknown. Manganese deficiency causes interveinal chlorosis of younger leaves in dicots and gray specks on the basal leaves in cereals. The first effect of manganese deficiency is a reduction in photosynthesis (Husted et al., 2009), followed by a reduction in soluble carbohydrates and changes in lignin and phenol content and composition. Manganesedeficient plants are more susceptible to pathogen infections (Datnoff et al., 2007), and manganese deficiency has been reported to influence plant response to light, heat, and water stress, and to alter cell wall and root development (Graham et al., 1988; Moraghan and Mascagni, 1991; Tong et al., 1997; Marschner et al., 2003; Yang et al., 2008; Hebbern et al., 2009; Kaur and Sadana, 2010). With the exception of manganese function in PSII, the specific mechanism underlying these

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frequently observed deficiency effects is unclear in part because our understanding of the metabolic function of the Mn-dependent enzymes, Mn-SOD, OxO, and AAH, is incomplete. The Mn-dependent enzymes in plants, Mn-SOD, OxO, and AAH, are all members of the germin group of proteins. Germin-likeproteins (GLP) are implicated in a wide variety of plant processes including germination, development, pollen formation, cell wall formation, disease resistance, and response to abiotic and biotic stress, which reflect the symptoms of manganese deficiency (Woo et al., 2000; Dunwell et al., 2004; Dunwell et al., 2008; Davidson et al., 2009; Manosalva et al., 2009). Further consideration of the functions of GLPs in general and Mn-dependent GLPs in particular is warranted. Uptake, transport, and homeostasis Manganese uptake has long been considered poorly regulated (Clarkson, 1988). This conclusion was based on kinetic studies that found manganese uptake rates orders of magnitude greater than required for growth, field observation that tissue manganese concentrations vary greatly with environment, soil type, and iron deficiency, and the observation that there is a 50–100× range between the critical manganese requirement (10– 20 μg g−1 DW) and toxicity (>1000 μg g−1 DW) in most species (Graham et al., 1988). The occurrence of manganese toxicity in acid and low-eH soils suggests inability of many plant species to regulate uptake under conditions of high Mn(II) solubility. Manganese uptake is strongly enhanced by iron deficiency, and several well-described iron and zinc transporters (ZIP and NRAMP family) have been shown to transport manganese, which suggests that much manganese uptake is simply coincident with iron and zinc uptake processes. The relative paucity of manganese uptake studies (in contrast with

iron, zinc, and copper) is perhaps a consequence of these assumptions and, until quite recently, our understanding of the molecular basis of manganese uptake and homeostasis in plants has been quite poor. The observation that manganese uptake is often poorly regulated was incorrectly interpreted as evidence that specific and highly regulated transport systems do not exist. This conclusion is at odds with knowledge from other organisms and is incompatible with the known functions of manganese in plants. Evidence from bacteria, yeast, and animal systems demonstrate that organelle specific and highly regulated delivery of manganese is required to support essential manganese functions. An equivalent degree of organelle-specific and highly regulated delivery of manganese can be expected in plants, as it would be required to support the function of manganese in chloroplasts (PSII), the ER (AAH), mitochondria (MnSOD), and the cell wall (OxO). Observations that species and cultivars growing in the same environment can vary greatly in manganese uptake also imply that mechanisms for the regulation of manganese uptake must exist (Graham et al., 1988; Saberi et al., 1999; KhabazSaberi et al., 2002; Hebbern et al., 2005; Pedas et al., 2005; Jiang, 2006; SayyariZahan et al., 2009). While it has been known since the mid1990s that manganese can be transported through a variety of metal transporter families in plants (NRAMP, cation diffusion facilitator [CDF], ZIP, and cation/H+ antiporters; Williams et al., 2000; Hall and Williams, 2003), evidence for the presence of transporters specifically responsive to plant manganese status (under nontoxic conditions) has only emerged since 2005 (Pedas et al., 2005; Delhaize et al., 2007; Mills et al., 2008; Pedas et al., 2008). The identification of a first intercellular Mn2+ transporter (ECA3, a Golgi-localized P2A-type


ATPase) essential for plant growth under low manganese supply was identified in 2008 (Mills et al., 2008; Pedas et al., 2008), and the first transporters required for soil manganese uptake under low manganese (AtNRAMP1 and HvIRT1) were not identified until 2010 (Cailliatte et al., 2010; Lanquar et al., 2010). A summary of known and putative whole-plant and cellular Mn2+ transporters is provided in Figures 17.3 and 17.4. Uptake by roots In their elegant comparison of two barley genotypes differing significantly in ability to grow under low manganese supply, Pedas et al. (2005) demonstrated that uptake of manganese under low manganese supply was facilitated by a high-affinity uptake system operating in the low nM concentration range. Subsequently, it was shown that manganese uptake in barley was mediated by HvIRT1, a root-epidermal plasma membranelocalized high-affinity manganese transporter. HvIRT1 was upregulated by both iron and manganese deficiency and expression levels and uptake were significantly higher in the manganese deficiency-tolerant genotype (Pedas et al., 2008). A Km for HvIRT was estimated at 2.7 to 5.4 nM. AtIRT1 transports iron and manganese and is the major high-affinity transporter for Fe2+ and Mn2+ acquisition in iron-limited conditions. However, the irt1-1 mutant can be rescued only by supplying iron and not manganese (Vert et al., 2002). Multiple ZIP transporters with a capacity to transport Mn2+ have also been identified (MtZIP4 and MtZIP7 from Medicago truncatula; LeIRT1 and LeIRT2 from tomato, and PsIRT1 from pea (see Pittman, 2005; Pedas et al., 2008), but only AtIRT1 and HvIRT1 have been shown to transport manganese in plants. NRAMP transporters are evolutionarily conserved proton/metal symporters with

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broad capacity to transport divalent metal ions including Fe2+, Mn2+, Zn2+, Cd2+, Co2+, Cu2+, Ni2+, and Pb2+ in many species (Hall and Williams, 2003; Pilon et al., 2009). In Arabidopsis, AtNRAMP1 has been shown to be essential for manganese uptake under low manganese supply (Cailliatte et al., 2010). AtNRAMP1 is a plasma membrane localized high-affinity manganese transporter, with an apparent Km of 28 nM. Expression is restricted to the root and is regulated by manganese availability, and overexpression of NRAMP1 enhances plant growth and tissue manganese concentrations in Mn-limiting conditions. AtNRAMP1 activity is also upregulated by iron deficiency and stimulates Co2+, Fe2+, and Zn2+. AtNRAMP1 activity is present throughout the root and is not localized to epidermal layers, suggesting that it functions in manganese uptake from root apoplast. NRAMPs are widely distributed throughout plant species and structural and experimental data suggest many can behave as Mn2+ transporters (Hall and Williams, 2003; Krämer et al., 2007), and it is likely that IRT1 transporters will be found to be important for Mn2+ uptake in other species. The identification of distinct high-affinity manganese transporters (HvIRT1 and AtNRAMP1) in barley and Arabidopsis may suggest that multiple coordinated systems of high-affinity manganese uptake exist in plants. Cailliatte et al. (2010) hypothesize that IRT1 and NRAMP1 work in a coordinated fashion with IRT1 functioning at the epidermal layer and NRAMP1 functioning in the apoplast, regulating the storage and utilization of manganese in the cell wall. Inter- and intracellular manganese transport and homeostasis Manganese is an essential component of four enzymes each of which is localized in specific plant organelles: PSII in chloro-

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plasts, AAH in the ER, MnSOD in the mitochondria, and OxO in the cell wall. Manganese also has an affinity for a wide array of organic ligands, although it forms far less stable complexes than Cu2+ and Zn2+ (Lippard and Berg, 1994). These characteristics and the evidence of tight regulation of manganese activity in bacterial, animal, and fungal systems suggest that intracellular manganese will be tightly regulated in plants. Transport of manganese into mitochondria to support MnSOD2 activation appears to occur through AtMTM1 a member of the mitochondrial substrate carrier family, and evidence suggests that AtMTM1 activity is regulated directly by the superoxide anion O2− (Su et al., 2007). In Saccharomyces cerevisiae, manganese insertion into SOD2 is only possible with a newly synthesized polypeptide and is closely coupled to Sod2p import. In this context, MTM1 functions in a chaperone-like manner. Given the fundamental role of manganese in photosynthesis, it is surprising that mechanism of Mn2+ delivery to chloroplasts has not been identified. Lanquar et al. (2010) have recently hypothesized that chloroplastic manganese delivery may be mediated by tonoplast-localized AtNRAMP3/AtNRAMP4 Mn2+ export. The double mutant Atnramp3/ Atnramp4 exhibits strongly increased vacuolar Mn2+ and a decrease in PSII activity with no coincident decrease in MnSOD activity. These results were interpreted as evidence that the vacuole serves a critical function as a site for the cycling and transit of cellular Mn2+ and that NRAMP3/ NRAMP4 are redundant manganese transporters involved in intercellular and probable chloroplastic manganese transport (Lanquar et al., 2010). The role of the vacuole, prevacuolar compartments, and endosomal/Golgi in manganese homeostasis has been highlighted in several recent publications (Delhaize et al.,

2007; Peiter et al., 2007; Li et al., 2008; Mills et al., 2008; Lanquar et al., 2010). In the Mn-tolerant species Stylosanthes hamata, vacuolar manganese transport is mediated by SmMTP1 a member of the CDF family under high manganese supply. SmMTP1 is likely a H+/Mn2+ cotransporter localized to the prevacuolar compartments that function in protein transport through Golgi, endosomal, and vacuolar networks, and functions to sequester cytoplasmic Mn2+ to vacuoles or extracellular spaces to maintain functional cytosolic Mn2+ levels (Delhaize et al., 2007; Peiter et al., 2007). In the mutant Atmtp11, Mn2+ accumulates in the cytosol in toxic concentrations. AtMTP11 functions as a proton antiporter (Delhaize et al., 2007; Peiter et al., 2007). There are four P2A-type ATPases in Arabidopsis, AtECA1, AtECA2, AtECA3, and AtECA4 (ER-localized Ca2+-ATPase); of these, AtECA1 and AtECA3 have been shown to function at the ER in the transport of Ca2+ and Mn2+ (Pittman, 2005; Li et al., 2008). Golgi-localized AtECA3 is involved in the loading of Ca2+ and Mn2+ into a subpopulation of post-Golgi compartments and is critical for highly regulated endosomal trafficking, exocytosis, and secretion under conditions of excess Mn2+. AtECA3 has also been shown to be essential for plant survival under conditions of manganese deficiency, and the mutant eca3, but not eca2, exhibited chlorosis and dramatic growth inhibition (Mills et al., 2008). Application of Mn2+ at low but adequate levels recovered the phenotype, indicating that compensatory mechanisms of Mn2+ uptake operate in Arabidopsis (Mills et al., 2008). The failure of eca3 to grow under low Mn2+ was interpreted as evidence that other genes involved in Mn2+ transport (AtMTP11, AtECA1, CAX2) cannot compensate for loss of function of AtECA3 (Mills et al., 2008). While this suggestion is clearly true, it does not imply that the other identified


Mn2+ transporters (NRAMP1, NRAMP3, NRAMP4) do not play essential roles in the uptake and delivery of Mn2+ to essential sites of function.

Within-plant transport Manganese is generally considered phloem immobile, and remobilization is generally very low, except during senescence in a few species (Graham et al., 1988). The mechanism of Mn2+ loading into and Mn(II) transport within the vascular system is unknown. The oligopeptide transporter AtOPT3 is upregulated in root vascular tissue by manganese deficiency and rescues the smfl Mnsensitive yeast mutant, although a direct role in manganese transport has not been shown (Wintz et al., 2003). YSL NA divalent cation tranporters from a number of species can transport Mn(II)-NA and exhibit vascular expression patterns; a direct role of OsYSL2 in phloem Mn(II)–NA loading has been demonstrated in rice (Koike et al., 2004). Arabidopsis also has a multigene family of CAX genes including the tonoplast-localized cation/H+ antiporter CAX2 (Pittman, 2005). CAX2 GUS reporter gene fusions are strongly expressed in vascular tissue throughout the plant, indicating a possible role of CAX2 in regulating loading or unloading of manganese from the vasculature (Pittman, 2005). CAX-like transporters, however, are low-affinity and hence may only be relevant under conditions of excess manganese. While the past 5 years has seen a remarkable increase in our understanding of manganese transport in plants with new details emerging rapidly, gaps in our knowledge still exist. Our understanding of Mn2+ uptake from soils, manganese delivery and incorporation of Mn2+ into the PSII, delivery of Mn2+ to OxO in the apoplast, the possible function of manganese chaperones, and the

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mechanisms of manganese signaling and transporter regulation remain inadequate. Prospects for optimizing manganese use efficiency There is considerable variability among species and genotypes in tolerance to Mndeficient soils (Graham et al., 1988; Bansal et al., 1991; Tong et al., 1997; Saberi et al., 1999; Khabaz-Saberi et al., 2002; Hebbern et al., 2005; Jiang, 2006; Pedas et al., 2008; Kering et al., 2009). The factors that may contribute to differential manganese efficiency include manganese content in the germinating seed; exudation of Mn-chelating and/or Mn-reducing compounds from roots (Marschner et al., 2003; Rengel and Marschner, 2005); manganese uptake kinetics (Hebbern et al., 2005); manganese requirement of Mn-dependent key enzymes (Kering et al., 2009); subcellular compartmentation of Mn; and, finally, the populations of Mn-oxidizing and Mn-reducing microorganisms in the rhizosphere (Graham et al., 1988; Huang et al., 1996; Saberi et al., 1999; Marschner et al., 2003; Sayyari-Zahan et al., 2009) In some instances, the physiological basis for differences in plant uptake is clear; thus, in the barley varieties Vanessa (efficient) and Antonia (inefficient), differences in tolerance to Mn-deplete soils is a consequence of enhanced activity of a high-affinity Mn2+ transporter, HvIRT1 (Pedas et al., 2005). In a series of experiments conducted in wheat in Australia, it was generally observed that manganese efficiency was associated with higher absorption of manganese from lowmanganese soils (reviewed in (Graham et al., 1988). In a comparison of C3 and C4 species, the higher demand for Mn2+ for PSII activity was responsible for the 10 × higher Mn2+ requirement in NAD-malic enzyme C4 species (Kering et al., 2009). Increased internal utilization efficiency (specifically

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Mn-dependent PSII activity) was also the suggested mechanism for the increased efficiency of the wheat variety Maris Butler (Jiang, 2006, 2008). In a comparison of raya (Brassica juncea), wheat (T. aestivum), and oat (A. sativa), differences in efficiency were expressed in soil but not in solution culture and were ascribed to enhanced solubility of manganese in the rhizosphere of raya (Sayyari-Zahan et al., 2009). The role of rhizophere processes in manganese availability is, however, ambiguous and inconsistent. The ability of a species to effectively alter Mn2+ by causing rhizosphere changes is highly dependent on the prevailing pH and buffering capacity of the soil. Thus, in the high-pH, high-carbonate soils in which manganese deficiency is significant in parts of Australia and Europe, changes in rhizosphere pH (Tong et al., 1997) or microbial populations (Rengel and Marschner, 2005) are unlikely to influence soil manganese availability. The determination that differences in Mn2+ uptake in two cultivars of barley (Pedas et al., 2008) were the consequence of differential expression of the high-affinity Mn2+ transporter HvIRT1 are consistent with long-term experimentation in wheat in Australia that similarly ascribed efficiency to enhanced uptake under low Mn. The limited available information also suggests that manganese efficiency is a simply heritable characteristic (Graham et al., 1995; Saberi et al., 1999; Khabaz-Saberi et al., 2002). Thus, it appears (at least in cereals) that selection or genetic manipulation activity of IRT1 (but perhaps also NRAMP1) may result in enhanced tolerance to lowmanganese soils. Possible additional targets for manganese transport manipulation include the AtECA3 transporter, which may be involved in manganese storage and trafficking within the cell. The mechanism of manganese storage and remobilization in cell wall, vascular loading, and manganese

remobilization to reproductive structures is not adequately understood. Finally, manganese deficiency is frequently expressed transiently during cold wet springs, reflecting changes in soil chemical and microbial processes as well as changes in activity of manganese transporters. Spring manganese deficiencies can be extremely damaging to productivity; hence, an enhanced understanding of manganese transporter activity during this period may be fruitful. Molybdenum Chronic molybdenum (Mo) deficiency has been described in relatively few (though often extensive) regions of the world on acid-leached and iron oxide-rich soils (pH 4.0–5.0). There are large regions of the globe (especially in Africa) in which the need for molybdenum has not been adequately assessed. Molybdenum is essential for the function of bacterial nitrogenase, and four plant enzymes including nitrate reductase. Plants supplied with nitrate as well as nitrogen-fixing legumes are more sensitive to deficiencies of molybdenum and have reduced nitrogen use efficiency. Moderate deficiencies of molybdenum may limit yield as a consequence of impaired nitrogen nutrition and can be hard to identify as molybdenum deficiency. Molybdenum uptake occurs through at least two members of the sulfate transport family, although additional transporters likely exist. The mechanisms of within-plant mobility are unknown. Molybdenum is required in only low amounts and fertilizer rates of 50 g ha−1 provided long-term correction of molybdenum deficiency in southeastern Australia. Given the low cost, high solubility, longevity, and low toxicity of molybdenum fertilizers, the addition of molybdenum as a seed treatment, or selection of plants with higher seed molybdenum content is a sound strategy. Given the potential impact of molybdenum


on productivity and efficiency of nitrogen use, preventative molybdenum treatments may be prudent, especially in lowmolybdenum soils and in crops with high molybdenum demand. Molybdenum in soils and plants and occurrence of global deficiencies Plants take up molybdenum as the anion molybdate (MoO42–), and molybdenum speciation in soils is pH dependent. Molybdenum is generally available in neutral to alkaline soils and deficiencies are more prevalent in acid soils. At pH >5, molybdenum exists primarily as MoO42–, while at lower pH the plant unavailable ions HMoO4− and HMoO40 become dominant. Several excellent reviews on the chemistry and bioavailability of molybdenum are available (Vlek and Lindsay, 1977; Gupta and Lipsett, 1981; Barber, 1984; Barrow, 1985; Kaiser et al., 2005; Hamlin, 2007; Wichard et al., 2008). As an anion, MoO42– forms ionic complexes with positively charged minerals including iron, manganese, and aluminum oxides. Under acidic conditions, these reactions involve ligand formation and are most favorable at pH 4–5. With every increase in pH unit above 4.0, MoO42– availability increases 10- to 100-fold, depending on predominant soil mineralogy (Vlek and Lindsay, 1977). The application of agricultural lime to increase soil pH is commonly used to increase molybdenum availability in acid soils. Organic matter can either increase or decrease soil molybdenum content and availability depending on the specific form of the organic matter, soil mineralogy, and the prevailing soil pH (Hamlin, 2007). Molybdate forms only weak complexes with most organic ligands with the exception of catechols (Bellenger et al., 2008). The catechol groups of organic matter are able to bind molybdate over a wide pH range, retaining molybdenum in the top layer of the

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soil (Wichard et al., 2008). Catecholcontaining siderophores are essential for molybdenum acquisition in many bacteria (Wichard et al., 2008). The role of catechol molybdenum complexation in plant uptake is unknown. The average molybdenum content of soils is ∼2.0 mg kg−1 and ranges from 0.013 to 17.0 mg kg−1, although values as high as 300 mg kg−1 may be present in organic rich shales and soils contaminated with sewage sludge or industrial waste (Hamlin, 2007). Soluble molybdenum in the soil ranged from 10−8 to 10−6 M (0.96–96 μg L−1) (Vlek and Lindsay, 1977), although it is usually small (6.7, most nickel exists as insoluble hydroxides, whereas at pH 10 mg Ni kg−1 DW, which is an extremely wide range as compared with other elements (Gerendas et al., 1999). The critical nickel concentration required for seed germination in barley, shoot growth in oat, barley and wheat, and shoot growth of urea-fed tomato, rice, and zucchini has been estimated independently by two groups to be approximately 100 μg Ni kg−1 (Brown et al., 1987; Gerendas and Sattelmacher, 1997a,b). Function and deficiency symptoms Interest in the role of nickel in plant biology was stimulated by the discovery that nickel is a component of the plant enzyme urease

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in 1975 (Dixon et al., 1975) and subsequent demonstration that tissue-cultured soybean, rice, and tobacco cells could not grow in the absence of nickel when provided with urea as the sole nitrogen source (Polacco, 1977). Eskew et al. (1983) concluded that nickel was an essential element for leguminous plants, although they did not demonstrate a failure of nickel-deficient plants to complete their life cycle. Gerendas et al. (Gerendas et al., 1998; Gerendas and Sattelmacher, 1997a,b; Gerendas et al., 1999) demonstrated a profound effect of nickel deficiency on growth of urea-fed tobacco, zucchini, rice, and canola. Brown et al. (1987) demonstrated that barley (H. vulgare L.) seeds from nickel-deprived plants were incapable of germination even when grown on a nonurea nitrogen source and showed a significant reduction in shoot growth of barley, wheat, and oats under nickel-deficient conditions when plants where supplied with mineral nitrogen sources. The existence of field-level nickel deficiency in crops was discovered in pecan (Carya illinoiensis (Wangh.) K. Koch) trees growing in sandy poor draining and low cation exchange soils of southeastern United States (Wood et al., 2004). Responses to foliar and soil applications have been observed in a number of containerized crops, particularly, though not exclusively, when provided with a urea nitrogen source (Ruter, 2005a; Bai et al., 2006; Gheibi et al., 2009) and in species that utilize the ureides as a prominent nitrogen form. Examples of ureide transporting crop genera are Annona, Carya, Diospyros, Juglans, and Vitis (Brown, 2008). Additionally, tropical legumes (e.g., soybean, phaseolus beans, mungbean, and cowpeas) are also relatively sensitive to nickel deficiency (Brown, 2008). Nickel is known to be involved in the function of at least nine proteins including methyl-coenzyme M reductase, superoxide dismutase, nickel-dependent

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glyoxylase, aci-reductone dioxygenase, NiFehydrogenase, carbon monoxide dehydrogenase, acetyl-CoA decarbonylase synthase, and methyleneurease, of which two (urease EC 3.5.1.5; urea amidohydrolase) and the nickel-metallochaperone have identified roles in plants (Bai et al., 2006; Hänsch and Mendel, 2009). While a function of nickel in urease remains, the only definitive role for nickel in plants, many observations of plant growth under nickel deficiency suggest that additional functions are likely (Brown et al., 1987; Brown et al., 1990; Bai et al., 2006). The review by Li and Zamble (2009) provides an exceptional summary of function and homeostasis of nickel in biology. In legumes and other dicots, nickel deficiency results in decreased activity of urease and subsequently results in urea toxicity, exhibited as leaflet tip necrosis (Eskew et al., 1983). In graminaceous species, deficiency symptoms include chlorosis similar to that induced by iron deficiency (Brown et al., 1987), including interveinal chlorosis and patchy necrosis in the youngest leaves. Nickel deficiency also results in a marked enhancement in plant senescence and a reduction in tissue iron concentrations. In both monocots and dicots, the accumulation of urea in leaf tips is diagnostic of nickel deficiency (Eskew et al., 1983). In early or incipient stages of nickel toxicity, there are no clear symptoms, although shoot and root growth may be reduced. Acute nickel toxicity results in symptoms that have variously been likened to iron deficiency (interveinal chlorosis in monocots, mottling in dicots) or zinc deficiency (chlorosis and reduced leaf expansion). The clearest agronomic responses to nickel have been observed when nitrogen is supplied as urea or by nitrogen fixation. The most illustrative example of the relationship between nickel and urea metabolism is provided from studies with foliar urea application and tissue culture growth of plants.

Plants without a supply of nickel have low urease activity in the leaves, and foliar application of urea leads to a large accumulation of urea and severe necrosis of the leaf tips (Eskew et al., 1983). Nicoulaud and Bloom (1998) observed that tomato seedlings growing with foliar urea as the only nitrogen source exhibited significantly enhanced growth when nickel was added to the nutrient solution. The authors speculated that the effect of nickel was more consistent with its role in urea translocation than as a direct effect on urease activity. This result is in agreement with the findings of Brown et al. (1987), who suggest that nickel has a role in the transport of nitrogen to the seed, thereby influencing plant senescence and seed viability. Uptake, transport, and homeostasis In plant systems, most studies have been conducted at high soil nickel concentrations, well above the levels at which deficiency might occur. Cataldo et al. (1978), using 63 Ni, indicated that a high affinity Ni2+ carrier functioned at 0.075 and 0.25 μM with a Km of 0.5 μM, which approaches the nickel concentration in uncontaminated soils. Both Cu2+ and Zn2+ competitively inhibit Ni2+ uptake, an observation that is reflected in field occurrence of nickel deficiency in zincand copper -contaminated soils (Wood et al., 2004; Bai et al., 2006). Information on nickel uptake and cellular homeostasis is largely derived from research in bacteria, hyperaccumulating species, and genetic manipulation of metal transport gene families (Li and Zamble, 2009; TejadaJiménez et al., 2009). Three families of transporters, ZIP (ZRT/IRT-like protein; zinc-regulated transporters/iron regulated transporters), NRAMP, and YSL, participate in nickel transport and homeostasis (TejadaJiménez et al., 2009). Transformation of yeast with Thlapsi japonicum ZNT1 or


ZNT2 reduced nickel uptake, likely as a result of a competitive increase in zinc influx (Mizuno et al., 2007). Overexpression of the IRT-like membrane protein, AtIREG2, increased tolerance of Arabidopsis to nickel exposure possibly by enhancing vacuolar transport (Colangelo and Guerinot, 2006; Mizuno et al., 2007). The central role of the vacuole in nickel homeostasis is supported by the observation that NRAMP4 overexpression increases nickel sensitivity in yeast by enhancing nickel efflux from the vacuole (Mizuno et al., 2005; Colangelo and Guerinot, 2006). A summary of known and putative whole-plant and cellular nickel transporters is provided in Figures 17.3 and 17.4. The bacterial metallochaperone genes (UREd, UREf, and UREg) play a critical role in the activation of the nickel-dependent urease (Witte et al., 2001; Witte et al., 2005). Three putative urease accessory genes (AtUREd, AtUREf, and AtUREg) are required for competent incorporation of nickel into urease (Witte et al., 2005; Li and Zamble, 2009). Nickel, unlike other divalent cations, is readily retranslocated within the plant, likely as a complex with organic acids and amino acids (Tiffin, 1971; Tiffin and Thompson, 1975; Riesen and Feller, 2005; Krämer et al., 2007). Indeed, up to 70% of nickel in the shoots was transported to the seed of soybean (Tiffin, 1971). Nickel forms complexes with malate, citrate, histidine, and nicotianiamine (Ouerdane et al., 2006), which influences both within-plant nickel mobility and tolerance to nickel excess (Tiffin and Thompson, 1975; Mari et al., 2006; Ouerdane et al., 2006). Overexpression of NAS conferred nickel tolerance in Arabidopsis (Pianelli et al., 2005). Prospects for optimizing nickel use efficiency There have been no reports of selection, breeding, or molecular manipulation to

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enhance plant resistance to nickel deficiency or increase efficiency of nickel use. Given the diversity of functions of nickel in bacterial systems and the lack of systematic examination of the effects of nickel on cropping productivity, there remains a possibility that nickel deficiency is a more significant problem than currently recognized. The chemistry of nickel and the known functions suggest that deficiencies are most likely to occur in leached soils or high-pH soils in which nickel availability is low. Species that utilize ureides and those dependent on urea fertilization or nitrogen fixation will be more susceptible. Knowledge from bacterial and hyperaccumulating species suggests that opportunities exist to manipulate plant nickel uptake, within cell distribution and remobilization. The known plant nickel uptake mechanisms, however, are not nickelspecific and hence manipulations will influence the uptake of other essential and nonessential elements, making targeted manipulations impractical. Nickel forms a unique complex with histidine in plants, and manipulation of histidine levels in plants has been shown to alter within-plant distribution and tolerance to high nickel in the environment. The role of histidine metabolism in efficiency of nickel use in nickel-limiting environments is unknown. References Alhendawi, R.A., Kirkby, E.A., Pilbeam, D.J. (2005) Evidence that sulfur deficiency enhances molybdenum transport in xylem sap of tomato plants. Journal of Plant Nutrition 28, 1347–1353. Alloway, B.J. ed. (2008) Micronutrient Deficiencies in Global Crop Production. Springer, Dordrecht. Amery F, Degryse F, Degeling W, Smolders E, & Merckx R (2007) The copper-mobilizing-potential of dissolved organic matter in soils varies 10-fold depending on soil incubation and extraction procedures. Environmental Science & Technology 41, 2277–2281. Amery F, Degryse F, Van Moorleghem C, Duyck M, & Smolders E (2010) The dissociation kinetics of Cu-

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Part IV

Specialized Case Studies

Chapter 18

Drought and Implications for Nutrition Eric Ober and Martin A.J. Parry

Abstract The uptake of mineral nutrients by plants depends on the dissociation of ions in the soil solution and movement to the root surface. Therefore, sufficient soil water is critical for adequate plant nutrition. Although in many regions crops are grown under water-limited conditions and drought frequently causes yield losses, nutrient uptake usually keeps pace with the dry matter, which stabilizes the mineral nutrient concentrations in plant tissues. However, there are conditions when this homeostasis is disturbed. These situations provide insight into the regulation of nutrient balance and the role of nutrients in maintaining plant function, particularly under stress. There are new and exciting developments in the area of root-to-shoot communication involving nitrate, regulation of hydraulic conductivity, and stomatal function via abscisic acid (ABA) and K+, and genetic control of root system architecture. Further examination of how nutrient concentrations, growth, and water use are governed and regulated at the molecular level may provide avenues for further crop improvement.

Drought and global food production Plant productivity is primarily limited by the availability of resources (light, CO2, nutrients, and water) and by biotic and abiotic stresses. In agricultural systems, nutrients are supplied to the plants, but in natural systems, availability depends on their abundance in soils, water, and the atmosphere. The uptake of mineral nutrients by plants depends on the dissociation of ions in the soil solution and movement to the root surface. Therefore, sufficient soil water is critical for adequate plant nutrition. The availability of water is a major determinant of plant productivity; this is relevant to food security because a significant proportion of crop production worldwide takes place under water-limited conditions (Baldocchi and Valentini, 2004; Eriyagama et al., 2009). Drought causes more yield losses than any other single biotic or abiotic factor (Boyer, 1982). Therefore, plants that are subjected to water deficit can be also nutrient deficient, and nutrient deficient plants often can be more susceptible to drought. However, as the degree of drought stress is not constant


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and both the occurrence and severity can vary considerably over the life of a plant, the interactions with nutrition are complex and are affected both by environment and agronomic practice (Parry et al., 2005). For example, when growing cereals where water is limited, the addition of too much early nitrogen can lead to the establishment of a large canopy that cannot be supported by the available water and thus will lead to total crop failure, whereas with the same amount of available water, a later nitrogen application can secure quality and yield. Addressing the challenge of water availability to food production today and for a future world, which in many parts will be warmer and drier (Gornall et al., 2010), is a key research priority for disciplines ranging from agronomy to biotechnology. In this chapter the interactions between drought and plant nutrition are examined, emphasizing the situation for arable crops. Rather than a comprehensive review of the literature, which has been done elsewhere (Viets, 1972; Alam, 1999; Hu and Schmidhalter, 2005; Fleury et al., 2010), a general overview and highlight of certain areas that may provide avenues for crop improvement is provided. Interactions between water and ion fluxes in soils and roots Nutrient uptake depends on soil processes that occur in the rhizosphere and plant processes that occur within the root and shoot. In addition to soil moisture, the availability of mineral nutrients for uptake by roots depends on a wide range of soil conditions including pH, cation exchange capacity, redox potential, soil depth, organic matter content, microflora, type and proportion of clay content, and fertilizer application (Marschner, 1995). The rhizosphere is a heterogeneous environment in time and space:

Soil texture and physical structure varies, particularly with depth; the spatial distribution of nutrients and nutrient concentrations can vary enormously; and the occurrence of soil organisms, from earthworms to bacteria, is also variable. Not surprisingly, the excavation of root systems in this subterranean environment often reveals a complex and heterogeneous pattern, the result of root growth responses to local soil conditions and the physiology of the plant itself. Nutrient uptake is related to root biomass (Ehdaie et al., 2010). Roots must arrive where nutrients are located, and nutrients must be able to move into the root. Root growth is affected by supply of assimilates from the shoot and soil physical conditions such as moisture supply, pH, temperature, aeration, and penetration resistance (Waisel et al., 2002; Gregory, 2006). Soils also harden as they dry, so these constraints to root growth interact (Whalley et al., 2006; Whitmore and Whalley, 2009). However, useful variation in the ability of roots to penetrate hard soils has been identified (Clark et al., 2008). Root growth can also be inhibited in saline soils or soils high in aluminum or other toxic elements, and certain allelopathic organic compounds also restrict growth (Waisel et al., 2002). Mineral nutrients move to the root surface by a combination of mass flow and diffusion (Kramer and Boyer, 1995). Mass flow in fully drained soil occurs when soil water is taken up by roots as plants transpire. This process transports nutrients dissolved in soil solution regardless of concentration gradients present at the root–soil interface. However, when transpiration rates are low, concentration gradient-driven diffusion dominates movement of nutrients in the root–soil interface. Diffusion is slow compared with mass flow, so the flux of water from soil through the plant into the atmosphere in the transpiration stream has a large influence on nutrient delivery to the root

DROUGHT AND IMPLICATIONS FOR NUTRITION

surface. Water and ion uptake by roots depends on root anatomy, age, and type, and is affected by suberin deposition, and the density and activity of ion transporters (Baxter et al., 2009). Work using seedling roots or excised root segments show that fluxes of ion and water uptake vary with distance from the root apex, but because of technical difficulties there is comparatively little data on ion and water uptake in relation to root structure in mature, intact root systems (Varney and Canny, 1993; McCully, 1995; Peterson et al., 1999; Steudle, 2004). Processes governing the uptake and transport of nutrients by roots are covered elsewhere in this volume (see Chapters 2, 10, and 12). Nutrient-limited plants can exhibit decreased rates of photosynthesis, respiration, and growth. With less assimilate translocated from shoots to roots, the low energy status of roots limits the ability of the roots to supply nutrients to the shoot. Cell expansion and ion uptake that occurs against electrical and/or concentration gradients are processes that require energy. Thus, plants with nutrient deficiencies of any element, not surprisingly, are often more susceptible to drought because of shallow or weak root systems. In addition, nutrient-starved plants (a rare occurrence in most agricultural systems) show decreased rates of water uptake due to decreased solute potentials in root cells (Clarkson et al., 2000). However, it is interesting that comparisons of tissues of plants subjected to water deficit or irrigated conditions often show small differences in nutrient concentrations. This is because nutrient delivery to the shoot is coupled to dry matter production: decreased demand due to reduced biomass production slows nutrient uptake (Kramer and Boyer, 1995). Under optimum conditions, bulk flow is capable of supplying the demand for nitrogen, calcium, and magnesium, whereas diffusion supplies phosphorus. The sufficiency of bulk flow for

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potassium delivery may depend on soil availability. Therefore, due to this coupling of nutrient delivery with demand resulting from prevailing rates of dry matter accumulation, water deficit has not been observed to have drastic effects on mineral nutrient concentrations in plant tissues. An example of one exception to this general observation is the occurrence of pale green leaves of cereals during water deficits in the spring in the United Kingdom (Fig. 18.1). The low nitrogen status of the crop is most likely due to pellets of NH4NO3 that remain on the dry soil surface and do not become solubilized. However, plant growth continues because roots can access moisture deeper in the soil profile, and plants already have taken up much of the available nitrogen. Thus, tissue expansion outpaces nitrogen uptake and dilutes tissue nitrogen levels, resulting in the pale appearance. Another example is magnesium deficiency symptoms that appear in leaves of sugar beet subjected to long-term water deficit (Fig. 18.2). Lower magnesium concentrations were also observed in water-limited wheat plants (Hu et al., 2006). It is probable that water uptake from deep in the soil profile, where nutrient concentrations are very low, sustains some leaf growth while magnesium uptake in fertilized upper soil layers is minimal because of low water content and fewer living roots. However, foliar applications of nutrients, at least in part, may overcome these deficiencies. At high transpiration rates, sustained by open stomata and sufficient soil water availability, water flux into roots may exceed rates of ion uptake. This can result in accumulation of ions outside the root surface and dilution of ions in the xylem stream. This is because ion transport at the root cell membrane is governed by energy-dependent processes that are independent of water movement across the membrane. When transpiration rates are low because stomata close in response to water deficit, ion concentrations

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A

B

Fig. 18.1. (A) Poor nitrogen uptake in rain-fed, water-limited plots of winter wheat (foreground) compared with

darker green irrigated plots (background) during early growth in spring. (B) Plot strips of winter wheat showing differential nitrogen uptake under irrigated (darker green outer strips with drip tape) compared with rain-fed, waterlimited plants in the center of the tunnel structures.

can be depleted at the root–soil interface because ion transport continues unabated even though water flux is diminished. This steepens the concentration gradient, driving increased diffusion from the outer soil solution to the root surface. Another result is that ion concentrations in the xylem can increase considerably because of decreased dilution by water in the transpiration stream.

Aquaporins play an important role in water transport into and out of roots, but their contribution to ion uptake and plant nutrition remains uncertain. However, there is evidence that water channels can mediate uptake of boron and silicon in the form of silicic acid (Clarkson et al., 2000; Maurel et al., 2008). Root hydraulic conductivity, perhaps influenced by aquaporins, appeared


A

B

(A) Magnesium deficiency symptoms in drought-stressed sugar beet. (B) Note the more advanced necrosis and scorching in older leaves. Irrigated plants in nearby plots did not show symptoms.

Fig. 18.2.

to be greater when nitrogen was supplied in the form of NO3− compared with NH4+ (Guo et al., 2002). Root growth under dry conditions Roots continue growing at water potentials that are completely inhibitory to shoot growth (Sharp et al., 2004). The regulation of this phenomenon involves complex interactions between abscisic acid (ABA), ethylene, and cell-wall loosening enzymes sensitive to the redox potential of the apoplast. The net result is that biomass is partitioned in favor of roots over shoots, increasing the shoot to root ratio, limiting water loss to the atmosphere, and maintaining the exploration of soil. This adaptive

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response helps maintain plant water and nutrient status in challenging environments. Soil drying also causes soils to harden: Increased ability of roots to penetrate hard and compact soils would provide greater access to soil that contains unexploited moisture and nutrients (Whitmore and Whalley, 2009; White and Kirkegaard, 2010). The spatial arrangements of roots, or root system architecture, results from the differential growth of roots in response to local soil conditions. Nutrients and water are often distributed unevenly in the soil profile, and roots exhibit “plastic” behavior that allows plants to exploit these resource-rich patches surrounded by soil relatively depleted in nutrients or water (Ho et al., 2005; Hodge, 2006; Walk et al., 2006). The ability of roots to forage local patches high in nitrogen or phosphorus is well documented, and there is some evidence that roots may exhibit hydrotropism (Ober and Sharp, 2007). There is comparatively less information on how root architecture interacts with multiple conditions, such as patches of moisture and nutrients that are not necessarily colocated. A comparison of two maize cultivars showed different strategies of root placement and investment under combined nitrogen-limiting and waterdeficit conditions (Vamerali et al., 2003). Despite differences in plasticity of root growth, both cultivars showed similar yields. One study of oilseed rape, employing a compartmentalized pot system that permitted application of nutrients and water to isolated sections of the root system, found some unexpected results (Wang et al., 2007). Root growth was greater in sectors given more water or nutrients. However, application of fertilizer in patches resulted in greater soil water extraction from the nonfertilized sectors than from the fertilized sectors, even though root density was greatest in the fertilized sectors. One explanation is that nutrient

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uptake was high in fertilized sectors but water uptake was relatively low, forcing the balance of water demand to be sourced from the nonfertilized sectors. This again illustrates the predominance of active uptake of ions at the membrane level irrespective of mass flow rates of soil water. These results suggest that foraging for water by roots is stronger than nutrient foraging and that this level of water deficit did not impair the ability to obtain nutrients. In certain cases, partial root zone drying (PRD) or deficit irrigation could be a practical management technique to optimize water and nutrient use efficiencies and quality characteristics of harvested parts (Sadras, 2009). Nitrate as a root signal controlling water use

ABA ↑ Cytokinins ↓

ABA ↓ Cytokinins ↑

ABA ↑ Cytokinins ↓?

Xylem/apoplastic sap pH

Leaf growth rate and stomatal conductance

One of the key elements of PRD is that roots in drying soils produce chemical signals that enter the transpiration stream and affect

shoot growth and stomatal behavior (Davies et al., 2005). ABA is synthesized in roots at low water potentials and translocated to shoots where it causes stomata to close, decreasing transpiration and photosynthetic rates. Alkalization of xylem pH under waterdeficit conditions also alters the compartmentation of ABA in leaf tissues, allowing more ABA to be partitioned to the apoplast around stomatal guard cells. Cytokinins also play a role in root-to-shoot signaling (Davies et al., 2005). A fourth root-sourced signal that interacts with ABA, cytokinins, and pH is nitrate (Wilkinson et al., 2007; Fig. 18.3). Uptake of nitrate from the apoplast requires H+ cotransport, which effectively increases xylem pH. This mechanism can begin to explain observations that nitrogen deficiency can cause stomatal closure (McDonald and Davies, 1996). The effect of drying soil on xylem nitrate concentrations depends not only on the rate of uptake of nitrate from the soil but also on the degree to which nitrate

DEFICIENT

OPTIMAL

SUPRA-OPTIMAL

Xylem sap nitrate concentration Schematic representation of the interactions between xylem nitrate and other root-sourced signals in the regulation of shoot transpiration and growth. Reprinted with permission from Wilkinson et al. (2007).

Fig. 18.3.


in the xylem is diluted by flux of water into the root and the activity of the assimilatory pathway, specifically nitrate reductase. Nitrate reductase reduces nitrate to nitrite, which is then converted to NH3 for assimilation into glutamine. Transcriptional and posttranscriptional control of nitrate reductase expression and activity in response to a range of internal and external cues is complex. It is relevant that decreased activity is associated with low tissue water potentials, most likely in response to decreased adenosine triphosphate/ adenosine monophosphate (ATP/AMP) ratios resulting from decreased rates of photosynthesis under stress conditions (Fresneau et al., 2007). In summary, recent evidence demonstrates molecular control points governing the interplay between growth, transpiration, plant nutritional, and water status. Further research may elucidate how these targets could be manipulated to improve crop performance under nutrient- and water-limited conditions.

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may be indirect effects related to better phosphorus status of plants, and greater water extraction from soil could be due to greater leaf area of phosphorus-improved plants. There is increasing evidence that VAM association with roots can alter expression and activity of water channels (aquaporins) in root cell membranes that modulate the hydraulic conductivity of roots (Maurel et al., 2008). A study of southern beech tree seedlings showed that two species of ectomycorrhyzae contributed marginal improvements to dry matter accumulation under well-watered conditions, but provided a significant advantage under water deficit compared with noninoculated plants (Alvarez et al., 2009). The beneficial effect appeared to be through enhanced activity of assimilative enzymes in the infected roots. This is a complex area that needs further research, but there appears to be potential to improve both nutrition and drought tolerance simultaneously through root–fungi associations.

Mycorrhiza There is a substantial volume of literature that records the beneficial effects of root associations with endotrophic (vesicular arbuscular mycorrhizae [VAM], predominantly Glomus spp.) and ectotrophic fungi (Smith and Read, 2008) (Chapter 3). Hyphae extend into the soil and increase solubilization, particularly of phosphorus, and the surface area for absorption (Chapter 12). However, the evidence that mycorrhizal fungi make a positive contribution to the water economy of plants is mixed (Augé, 2001). For example, drought tolerance in pot-grown maize was improved in VAM plants over non-VAM plants (Boomsma and Vyn, 2008), but there were negative interactions between VAM and Rhizobia in Phaseolus under drought conditions (Franzini et al., 2010). The delayed effects of water deficit in VAM-colonized plants

Individual nutrients and plant water relations All the essential nutrients play important roles in maintaining productivity during periods of water deficit. Potassium is a key solute used in the stomatal complex for guard cell opening and closing (MacRobbie, 2006), and for osmotic adjustment in the growing zone of roots at low water potentials (Sharp et al., 1990). Many processes from photonastic leaf movements to phloem loading require K+ as a counterion and for osmotic balance (Marschner, 1995). The potassium concentration in roots affects tissue sensitivity to ABA, which is necessary for root growth maintenance (Sharp et al., 2004), the hyperpolarization response of root cells to decreasing water potentials (Ober and Sharp, 2003), and regulation of root hydraulic conductivity (Quintero et al.,

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1998). These processes are important during drought conditions but are probably compromised only under extreme conditions of potassium deficiency. Nevertheless, high potassium status has been shown to maintain photosynthetic rates during water deficits (Pier and Berkowitz, 1987), probably related to maintenance of high stromal pH in the chloroplast (Gupta et al., 1989). When electron transfer through photosystem II is inhibited during stress conditions, the ability of leaf tissues to handle excess energy and the production of reactive oxygen species is necessary to avoid tissue damage. Under these conditions, the potassium status of leaf tissue was shown to be an important part of the protection mechanism (Cakmak, 2005). Magnesium also affects ion balance and K+ transport across the stromal membrane (Gupta et al., 1989; Berkowitz and Wu, 1993). High magnesium concentrations in chloroplasts can inhibit photophosphorylation via ATPase (Younis et al., 1983; Lawlor and Tezara, 2009). Phosphorous nutrition influenced photosynthetic rates in moth bean (Garg et al., 2004) and improved growth in soybean under water-limited conditions (Jin et al., 2006). A potential difficulty with drought and phosphorus interactions is that root architecture for better drought tolerance (e.g., deep roots) is at odds with the best spatial arrangement for phosphorus acquisition (high density of shallow roots). Plants must balance these trade-offs to optimize biomass allocation to realize the best performance (Walk et al., 2006), which is measured in terms of yield in agricultural settings, or overall fitness in the wild.

there is considerable natural variation in how plants and even cultivars respond to the availability of nutrients and use water, which can be exploited in crop improvement (Barraclough et al., 2010). Both nutrient and water use efficiency are complex, quantitative traits that involve multiple genes. However, considerable progress has already been made in deconvoluting these complex traits and also in identifying variation in components traits (e.g., root traits—Clark et al., 2008; Courtois et al., 2009; leaf traits—Khowaja et al., 2009; Xu et al., 2009). Important component traits may have direct effects on the uptake and use of water or nutrients, or affect these processes indirectly, for example, by altering phenology: In some environments, a shorter life cycle may enable a crop to avoid water limitation entirely. Thus, such traits may contribute to yield increases if strategically targeted and effectively selected for (Richards et al., 2010). For example, carbon isotope discrimination by leaves is negatively correlated with transpiration efficiency, and low carbon isotope discrimination is being used to identify high water use efficiency and yield in rain-fed environments. This has led to the release of commercial wheat cultivars such as “Drysdale.” The individual component traits may be not be determined by multiple but by single genes, which by themselves can be used in marker-assisted breeding strategies (Kuchel et al., 2007) or used to identify novel alleles by TILLING (Parry et al., 2009) or exploited in transgenic approaches (Shrawat et al. 2008; Bi et al. 2009; Saad et al. 2010.

Crop improvement

Conclusion

There is no perfect crop ideotype for all environments; thus, for crop improvement it is necessary to identify specific ideotypes for specific crops and environments. Fortunately,

The acquisition of mineral nutrients and water from the soil are intimately interconnected. There have been numerous studies examining the interactions between the


nutritional status of plants and their relative susceptibility to drought conditions, but many of these have compared plants grown under extreme deficiency, which may not reflect realistic situations in most field environments. In general, within the normal range of soil nutrient availability, nutrient uptake keeps pace with the dry matter accumulation of plants, governed by the supply of water, which stabilizes the mineral nutrient concentrations in plant tissues. However, there are conditions when this homeostasis is disturbed. These situations provide insight into the regulation of nutrient balance and the role of nutrients in maintaining plant function, particularly under stress. There are new and exciting developments in the area of root-to-shoot communication involving nitrate, regulation of hydraulic conductivity and stomatal function via ABA and K+, and genetic control of root system architecture. Further examination of how nutrient concentrations, growth, and water use are governed and regulated at the molecular level may provide avenues for further crop improvement. Acknowledgments Rothamsted Research is an institute of the Biotechnology and Biological Sciences Research Council of the United Kingdom. The authors’ research is also supported by DEFRA (An integrated approach to increasing water use efficiency and drought tolerance of wheat production in the UK), the European Commission (OPTIWHEAT— Improving the Yield Stability of Durum Wheat under Mediterranean Conditions (EC Contract Number: INCO-CT-2006015460), and the British Beet Research Organisation. References Alam, S.M. (1999) Nutrient uptake by plants under stress conditions. In: Handbook of Plant and Crop

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Hodge, A. (2006) Plastic plants and patchy soils. Journal of Experimental Botany 57, 401–411. Hu, Y. & Schmidhalter, U. (2005) Drought and salinity: a comparison of their effects on mineral nutrition of plants. Journal of Plant Nutrition and Soil Science 168, 541–549. Hu, Y., Burucs, Z., & Schmidhalter, U. (2006) Shortterm effect of drought and salinity on growth and mineral elements in wheat seedlings. Journal of Plant Nutrition 29, 2227–2243. Jin, J., Wang, G., Liu, X., et al. (2006) Interaction between phosphorus nutrition and drought on grain yield, and assimilation of phosphorus and nitrogen in two soybean cultivars differing in protein concentration in grains. Journal of Plant Nutrition 29, 1433–1449. Khowaja, F.S., Norton, N.J., Courtois, B., et al. (2009) Improved resolution in the position of droughtrelated QTLs in a single mapping population of rice by meta-analysis. BMC Genomics 10, 276. Kramer, P.J. & Boyer, J.S. (1995) Water Relations of Plants and Soils. Academic Press, London. Kuchel, H., Fox, R., Reinheimer, J., Mosionek, L., et al. (2007) The successful application of a markerassisted wheat breeding strategy. Molecular Breeding 20, 295–308. Lawlor, D.W. & Tezara, W. (2009) Causes of decreased photosynthetic rate and metabolic capacity in waterdeficient leaf cells: a critical evaluation of mechanisms and integration of processes. Annals of Botany 103, 561–579. MacRobbie, E.A.C. (2006) Osmotic effects on vacuolar ion release in guard cells. Proceedings of the National Academy of Sciences of the United States of America 103, 1135–1140. Marschner, H. (1995) Mineral Nutrition of Higher Plants. Academic Press, London. Maurel, C., Verdoucq, L., Luu, D.-T., et al. (2008) Plant aquaporins: membrane channels with multiple integrated functions. Annual Review of Plant Biology 59, 595–624. McCully, M.E. (1995) How do real roots work? Some new views of root structure. Plant Physiology 109, 1–6. McDonald, A.J.S. & Davies, W.J. (1996) Keeping in touch: responses of the whole plant to deficits in water and nitrogen supply. Advances in Botanical Research 22, 229–300. Ober, E.S. & Sharp, R.E. (2003) Electrophysiological responses of maize roots to low water potentials: relationship to growth and ABA accumulation. Journal of Experimental Botany 54, 813–824. Ober, E.S. & Sharp, R.E. (2007) Regulation of root growth responses to water deficit. In: Advances in Molecular-Breeding toward Drought and Salt


Tolerant Crops (eds. M.A. Jenks, P.M. Hasegawa & S.M. Jain), pp. 33–53. Springer, London. Parry, M.A.J., Flexas, J., & Medrano, H. (2005) Prospects for crop production under drought: research priorities and future directions. Annals of Applied Biology 147, 211–226. Parry, M.A.J., Madgwick, P.J., Bayon, C., et al. (2009) Mutation discovery for crop improvement. Journal of Experimental Bot 60, 2817–2825. Peterson, C., Enstone, D., & Taylor, J. (1999) Pine root structure and its potential significance for root function. Plant and Soil 217, 205–213. Pier, P.A. & Berkowitz, G.A. (1987) Modulation of water stress effects on photosynthesis by altered leaf K+. Plant Physiology. 85, 655–661. Quintero, J.M., Fournier, J.M., Ramos, J., et al. (1998) K+ status and ABA affect both exudation rate and hydraulic conductivity in sunflower roots. Physiologia Plantarum 102, 279–284. Richards, R.A., Rebetzke, G.J., Watt, M., et al. (2010) Breeding for improved water productivity in temperate cereals: phenotyping, quantitative trait loci, markers and the selection environment. Functional Plant Biology 37, 85–97. Saad, R.B., Zouari, N., Ramdhan, W.B., et al. (2010) Improved drought and salt stress tolerance in transgenic tobacco overexpressing a novel A20/AN1 zinc-finger “AlSAP” gene isolated from the halophyte grass Aeluropus littoralis. Plant Molecular Biology 72, 171–190. Sadras, V. (2009) Does partial root-zone drying improve irrigation water productivity in the field? A metaanalysis. Irrigation Science 27, 183–190. Sharp, R.E., Hsiao, T.C., & Silk, W.K. (1990) Growth of the maize primary root at low water potentials. II. Role of growth and deposition of hexose and potassium in osmotic adjustment. Plant Physiology 93, 1337–1346. Sharp, R.E., Poroyko, V., Hejlek, L.G., et al. (2004) Root growth maintenance during water deficits: physiology to functional genomics. Journal of Experimental Botany 55, 2343–2351. Shrawat, A.K., Carroll, R.T., DePauw, M., et al. (2008) Genetic engineering of improved nitrogen use efficiency in rice by the tissue-specific expression of alanine aminotransferase. Plant Biotechnology Journal 6, 722–732. Smith, S.E. & Read, D.J. (2008) Mycorrhizal Symbioses, 3rd ed. Elsevier, London.

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Chapter 19

Salt Resistance of Crop Plants: Physiological Characterization of a Multigenic Trait Sven Schubert

Abstract Soil salinity is an increasing hazard for worldwide crop production. Since highquality water for leaching of salts in semiarid and arid areas is scarce, the possibilities for soil amelioration are limited. Thus, efforts are made to improve the salt resistance of crop plants genetically. This requires a profound understanding of the physiological processes that limit plant growth and yield formation. The development of a biphasic model of growth response under salt stress has allowed the separation of osmotic resistance in a first phase from ion toxicity in a second phase. Generally, osmotic resistance is not limited by osmotic adjustment and turgor maintenance but by low cell-wall extensibility. Various sodium exclusion strategies as well as sodium inclusion in vacuoles contribute to salt resistance in the second phase. In the generative phase of cereals, kernel set seems to be the key bottleneck for yield formation under salt stress. Introduction Soil salinity is an increasing hazard in many arid and semi-arid regions of the world. When evaporation exceeds precipitation,

dissolved salts move to the upper soil layers, where they accumulate and impair the growth of crop plants. Worldwide nearly 109 ha of land are affected (Szabolcs, 1994), and this situation is being aggravated by improper cultivation practices: Specifically irrigation may contribute to the import of salts. It is estimated that currently 20% of irrigated lands are affected by salinity problems (Qadir et al., 2006). Although excess irrigation may help to ameliorate soils via the leaching of salts, under poor drainage conditions inappropriate irrigation may also cause additional problems, known as secondary salinity (Szabolcs, 1994). Saline soils are defined as those soils that have an electrical conductivity of at least 4 dS m−1 in the saturation extract. Soils with an exchangeable sodium percentage of more than 15 are classified as sodic soils (Qadir et al., 2007). Saline–sodic soils suffer both problems and require proper amelioration measures to ensure optimal crop production (Qadir et al., 2001). Plant growth and development are directly affected by salt accumulation and also result from negative effects of salts on soil structure. Depending on the parent soil material, specific nutrient problems may result in addition: such examples


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are toxicities of boron in Turkey, selenium in Southern California, or arsenic in Bangladesh. Ions with a large hydration shell such as sodium, and to some extent also magnesium, may compete with calcium for binding sites on soil colloids when present at high concentrations. Displacement of calcium leads to peptization and impairment of soil structure and as a result rooting and root aerobic metabolism may be inhibited. This in turn inhibits the acquisition of water and nutrients (Qadir and Schubert, 2002), sodium exclusion particularly from shoots (Drew and Läuchli, 1985), and N2 fixation of legumes as a result of insufficient nodulation (Arrese-Igor et al., 1993). These problems are encountered particularly when stagnant moisture develops simultaneously, and require sophisticated soil-amelioration practices (Qadir et al., 2007) or combined salt and waterlogging resistance (Teakle et al., 2010). Amelioration of saline or saline–sodic soils depends on the application of huge amounts of good-quality water, which is scarce in the affected areas. Therefore, the need to improve the salt resistance of crop plants genetically was suggested long ago (Epstein et al., 1980). Despite tremendous scientific efforts to enhance salt resistance, only moderate progress has been achieved so far (Rozema and Flowers, 2008). This is due to the fact that salt resistance is a multigenic trait that is still poorly understood. In this chapter, important physiological characters are highlighted that contribute to salt resistance. It will be shown that a profound physiological understanding of salt stress is required to improve salt resistance of crop plants, either by means of classical breeding methods and/or by molecular techniques. Although in the international literature the term “salt tolerance” is predominantly used, following Levitt’s definition (Levitt, 1980), the more general term “salt resistance” is given preference here because avoidance

rather than true tolerance strategies allow glycophytic crop plants to overcome salt stress in most cases. The two-phase model of salt stress An important reason for negligible progress in the development of salt-resistant crops until the beginning of this century was a poor understanding of why salt stress inhibits plant growth. Although detrimental effects of ion toxicity on plant growth were generally assumed, it was difficult to find evidence of specific ion toxicity. For example, no correlation was found between sodium exclusion and salt resistance (Lessani and Marschner, 1978; Schubert and Läuchli, 1986) and the specific toxicity of sodium was questioned (Cramer et al., 1990). In addition, osmotic resistance and a lack of turgor apparently did not limit plant growth under salt stress (Termaat et al., 1985; Munns, 1988). A big breakthrough was achieved with the postulation of the biphasic model of growth response under salt stress (Munns, 1993). According to this model, salt stress in a first phase limits plant growth due to osmotic effects, whereas in a second phase, ions accumulate and lead to ion toxicity (Fig. 19.1). Although being simple, this model proved to be very helpful in identifying important physiological shortcomings during salt stress and formed a basis for progress in the development of salt-resistant wheat and maize genotypes (Xue et al., 2004; Munns et al., 2006; Schubert et al., 2009). Recently, genetically improved breeding lines of durum wheat were tested that demonstrated 25% outperformance in field trials under saline conditions (R. Munns, pers. comm.). The model originally developed for wheat was confirmed for maize by Fortmeier and Schubert (1995), who showed that

SALT RESISTANCE OF CROP PLANTS

NaCl Growthrate t

Resistant genotype

Sensitive genotype

Phase I

Phase II

Time Fig. 19.1. Model of the biphasic growth response of

plants under salt stress. Phase I is characterized by osmotic stress, and phase II by ion toxicity (modified scheme, based on Munns, 1993).

sodium and not chloride is the toxic ion in the second phase of salt stress. This seems to be a general phenomenon in grasses and probably also in other plants. One problem of the model is the differentiation of the two phases by means of the development of toxicity symptoms. In a detailed study, Sümer et al. (2004) showed that ion toxicity comes into play in the first phase of salt stress, although the quantitative effects are negligible. On the other hand, potassium deficiency as a result of sodium competition with potassium during uptake, translocation, and physiological action was ruled out in that study. In the original model, it was proposed that genotypic differences in salt resistance occur in the second phase of salt stress (Munns, 1993). Numerous experimental data support this statement (e.g., Lauter and Munns, 1986, Schachtman and Munns, 1992; Fortmeier and Schubert, 1995). On the other hand, it was suggested that no genotypic differentiation occurs in the first phase of salt stress (Fig. 19.1). Recently, evidence has been presented that, although the differ-

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ences are small, genotypic variation exists also in the first phase of salt stress and can be exploited in breeding programs (Schubert et al., 2009). The biphasic model excludes short-term effects that occur during the first several minutes or hours after the imposition of salt stress, that is, before the first phase of salt stress; these effects may thus be ascribed to a “phase 0.” This phase 0 comprises transient changes in turgor and growth (Thiel et al., 1988) as well as in membrane potential (Läuchli and Schubert, 1989), and stress during this phase apparently has a profound impact on the chloroplast proteome of saltsensitive plant species such as maize (Zörb et al., 2009). Although these effects may be quantitatively negligible for physiological parameters (in fact, a 25 mM NaCl treatment does not represent a measurable strain for maize growth), they may nevertheless have important implications for the following phases. The biphasic model must be recognized as a conceptual model that has not just a purely temporal dimension, but also takes into account stress intensity and genotypic and developmental differences. It is used to differentiate osmotic and ion effects on plant growth during salt stress. Whereas the model has been used to characterize salt effects during the vegetative phase, only few investigations have been carried out during reproductive growth and development. Osmotic resistance during salt stress: first phase Salinity decreases the solute potential of the soil solution and thus the water potential gradient into roots that establishes the driving force for water uptake. Under conditions of low matric potential and/or high water vapor deficit of the atmosphere (including windy conditions), this may contribute to insufficient water supply to the

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Fig. 19.2. Maize plants (Zea mays L. cv. Pioneer 3906) after 2-month growth in soil culture under control (left) and 11 dS m−1 salinity (right). Plants are still in the first phase of salt stress (Photo: Schubert).

plants as is observed under drought stress. Wilting symptoms for leaves of dicots and rolling of leaf blades of grasses may thus be observed under specific circumstances under salt stress. However, this does not represent the typical reaction of crop plants to saline stress. Rather, stunted growth and occasionally a dark-green color of leaves are observed in the first phase of salt stress (Fig. 19.2). In line with these observations, turgor is maintained and osmotic adjustment seems not to limit shoot growth (Termaat et al., 1985; Van Volkenburgh and Boyer, 1985; De Costa et al., 2007). It is generally accepted that roots are able to sense osmotic stress and release signals that control plant growth (Davies and Zhang, 1991). One of these signals may be abscisic acid that is released by root tips and transported via xylem into leaves, where it may

contribute to growth inhibition (Thomas et al., 1992; Montero et al., 1997). Depending on how many root tips sense low water availability, the abscisic acid concentration in the xylem sap may serve as an integrating signal that adjusts growth according to water availability in the rooting zone (Davies and Zhang, 1991). Apart from abscisic acid, xylem pH (Jia and Davies, 2007), hydraulic signals (Chazen and Neumann, 1994), nitrate, and combinations (Felle and Hanstein, 2002; Wilkinson and Davies, 2002) have been suggested as signals to control shoot growth under water stress. Whatever the signal, it is evident that this capability helps to adjust shoot growth under limited water availability of the soil. It has been shown previously that transpiration rates of maize plants, grown in nutrient solution under salt stress, are not necessarily reduced relative to control plants (Schubert, 2009). As shown in Figure 19.3, transpiration rates of two-month-old maize plants grown in soil culture (Fig. 19.2) were not reduced, but even increased under salt stress. This suggests not only that shoot growth is tightly controlled in the first phase of salt stress, but also that shoots do not apparently suffer from water deficit, since more than 90% of the water taken up are transpired. Apparently, the decrease in hydraulic conductivity in roots under salt stress (Evlagon et al., 1992) did not limit growth and photosynthetic rates in the maize plants. The fact that transpiration rates may be unchanged under salt stress suggests that photosynthetic rates are not limited by stomatal conductivity. Thus, cell division and cell extension are not limited by carbohydrate supply (Aspinall, 1986). The accumulation of sugars in leaf tissue suggests that the production of sugars in photosynthesis is not limited during the first phase of salt stress (De Costa et al., 2007; Hatzig et al., 2010b) and that osmotic adjustment is not a problem even for salt-sensitive plant


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Transpiration rate (mL cm–2 week–1) 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Across

Lector

Pioneer

SR 05

SR 08

SR 15

Transpiration rates of various maize genotypes under control (white columns) and 11 dS m−1 salinity (black columns). Genotypes were Across 8023, Lector, Pioneer 3906, and newly developed salt-resistant (SR) hybrids (Schubert et al., 2009). Plants were grown in soil culture in large containers at 60% of maximum waterholding capacity. Transpiration rates were determined as water lost during the vegetative phase (S. Schubert, unpublished results). Fig. 19.3.

species such as maize (Cramer, 1994). However, osmotic adjustment is related to the synthesis of glycinebetaine (Saneoka et al., 1995) and proline (Kuznetsov and Shevyakova, 1997), which may also serve as cytoplasmic osmoprotectants. Insufficient calcium nutrition and physiological calcium deficiency may present a problem for growth in the first phase of salt stress (Mizrahi and Pasternak, 1985; He and Cramer, 1992; Hu and Schmidhalter, 2005). It appears that species and cultivars that are more salt-sensitive tend to suffer more from calcium deficiency than salt-resistant genotypes (Lynch and Läuchli, 1985; Ehret et al., 1990). It is interesting that substitution of potassium by sodium in the nutrient solution resulted in calcium deficiency, and not in potassium deficiency of sugar beet (Wakeel et al., 2009). Since generally turgor does not limit shoot growth under salinity stress (see above), according to the Lockhart equation

(Equation 19.1, Lockhart, 1965), growth must be impaired either by cell-wall extensibility or by the growth-effective turgor. As the latter also depends on the cell-wall extensibility, it can be concluded that a more rigid cell wall is mainly responsible for shoot-growth reduction in the first phase of salt stress: dV/dt = m × (Ψ p − Y ),

(1)

where dV/dt = growth rate; m = cell wall extensibility; Ψp = turgor; Y = threshold turgor; and Ψp − Y = growth-effective turgor. Although calcium is essential for cellwall structure in its function to bridge carboxyl groups of pectinates, it is unlikely that calcium deficiency decreases cell-wall extensibility. Rather an increase of cell-wall extensibility is anticipated when calcium is replaced by monovalent ions such as protons. According to the acid-growth theory, apoplast acidification triggers cell extension

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by increasing the cell-wall extensibility (Hager, 2003). Recently, it has been shown that salt stress resulted in inhibition of in vitro H+ pumping by leaf plasma membrane H+ ATPase in the maize cultivar Pioneer 3906. Shoot-growth reduction in the first phase of salt stress was explained in terms of expression of inefficient H+ ATPase isoforms that are not able to sufficiently acidify the leaf cell-wall (Zörb et al., 2005). The in vitro results were corroborated in vivo using ratio-imaging techniques (Pitann et al., 2009). At the same time, it was shown that a more salt-resistant maize genotype, SR 03, maintained proton pumping and cell-wall acidification in the first phase of salt stress (Pitann et al., 2009). This is in line with results of Neves-Piestun and Bernstein (2001), who found no decrease in cell-wall acidification of the maize cultivar G.S. 46 under salt stress, and results of Wakeel et al. (2010), who found the same in vitro result for H+ pumping by H+ ATPase from leaves of salt-resistant sugar beet. In contrast, maize hybrid SR 12, which has a similar salt-resistance to SR 03, was not capable of maintaining in vitro proton pumping (Hatzig et al., 2010a). These results indicate that cell-wall acidification is an important, but not a sufficient, process to maintain extension growth of leaf cells in the first phase of salt stress. Other cell wallstiffening processes such as crosslinking of hemicelluloses by phenolics (N. Uddin, pers. comm..) may in the future explain in more detail genotypic differences of cell extension growth in the first phase of salt stress. Sodium exclusion strategies: second phase Testing the biphasic model of growth response to salt stress strictly, it was shown that sodium exclusion contributes to salt resistance in the second phase of salt stress (Fortmeier and Schubert, 1995). It was also

shown that although chloride may synergistically enhance sodium uptake and translocation, it does not directly cause ion toxicity in maize. This finding may be representative for grasses in general (Gorham et al., 1990). In contrast, chloride toxicity is the primary reason for growth impairment of sensitive crops such as potato, strawberry, citrus, and legumes such as soybean (Martínez Barrosos and Alvarez, 1997, White and Broadley, 2001; Luo et al., 2005). However, a generalization is not possible, as it was shown that the primary toxicity in faba bean is caused by sodium, although chloride toxicity also occurred (Slabu et al., 2009). Various problems of sodium toxicity have been described in the literature. The activation of many enzymes requires high cytoplasmic concentrations of potassium, and displacement of potassium by sodium may thus disturb metabolism (Anil et al., 2007). Hecht-Buchholz et al. (1971) showed that mitochondrial functioning in maize roots was affected by salt stress but respiration was maintained by increasing the number of mitochondria. Plant leaves are particularly sensitive to sodium (Munns, 2002) for two reasons. First, potassium plays an important role in stomatal regulation. Displacement of potassium by sodium can maintain the turgor of guard cells, but due to the poorer membrane mobility of the latter ion, stomatal closure is hampered. This results in uncontrolled water losses and desiccation of leaf tissue, which becomes visible as necrotic spots on the leaf tissues of faba bean (Slabu et al., 2009), and chlorotic and necrotic lesions of maize leaves (Fig. 19.4). Second, chloroplasts are particularly sensitive to sodium, which they readily accumulate when available in the cytosol (Zörb et al., 2009). This results not only in overwhelming changes of the chloroplast proteome at low sodium concentrations (Zörb et al., 2009) but also in chloroplast deformation at higher concentrations (Marschner and Mix, 1973).


449

Plasma membrane Cytosol

Rhizosphere

N + Na

1

H+

Na+

2

Sodium exclusion mechanisms at the plasma membrane. (1) Passive sodium influx of sodium is restricted by selective channels. Sodium influx is driven by the electrochemical gradient. (2) Active sodium efflux of sodium via Na+/H+ antiporters is driven by the proton motive force. Fig. 19.5.

Fig. 19.4. Sodium toxicity in maize (Photo: Schubert).

From this it follows that sodium exclusion from the cytoplasm, particularly of leaf cells, is essential. For a complicated organism such as a higher plant, sodium exclusion is realized by various strategies (Tester and Davenport, 2003; Munns and Tester, 2008). The first and most important strategy is sodium exclusion at the root surface, which basically restricts sodium entry into the plant and avoids sodium accumulation in the plant (Amtmann et al., 2005). Whereas active sodium efflux from cells via SOS1-type Na+/ H+ antiporters was demonstrated for Arabidopsis thaliana (Qiu et al., 2003; Guo et al., 2009) and rice (Matínez-Atienza et al., 2007), no such evidence was found for maize, although active efflux was demon-

strated (Schubert and Läuchli, 1988). Genotypic differences in sodium uptake were explained in terms of low passive influx via selective cation channels (Schubert and Läuchli, 1990; Xuan et al., 2010, Fig. 19.5). A second exclusion strategy restricts sodium translocation from roots to shoots. Sodium inclusion in root cell vacuoles via NHX-type Na+/H+ antiporters (Xue et al., 2004) eliminates sodium from transport into the xylem vessels (Fig. 19.6). These tonoplast-located Na+/H+ antiporters have a dual function. They not only contribute to sodium exclusion but also convey sodium tissue tolerance (Zhang and Blumwald, 2001; Queirós et al., 2009), particularly in leaf cells (Davenport et al., 2005; Munns and Tester, 2008). Thus, these antiporters enable sodium to act as a metabolically innocuous solute (Saqib et al., 2005). The overexpression of vacuolar Na+/H+ antiporters in different plant species resulted in higher salt resistance (Apse et al., 1999; Zhang and Blumwald, 2001; Xue et al., 2004).

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Endodermis

Cortex

Exodermis

K+ K+ Xylem

Rhizosphere

K+ Na+ Na+

Na+

Casparian strip Schematic representation of potassium and sodium uptake and translocation through root tissue to the xylem vessels. Depending on genotypic expression of NHX-type Na+/H+ antiporters, sodium may be actively sequestered into vacuoles and thereby excluded from root-to-shoot translocation. The Casparian strip forces ions to the symplastic way and allows for selectivity. Sodium may also be reabsorbed from xylem by xylem parenchyma cells.

Fig. 19.6.

Salt resistance during the reproductive stage In contrast to the vegetative phase, only a few physiological studies have been performed during the generative phase, which is particularly important for the yield formation of cereals. Ion toxicity in the second phase may directly inhibit photosynthesis and thus yield formation (Yeo et al., 1985). Genetically improved sodium exclusion may therefore enhance yield performance of wheat and maize (Xue et al., 2004; Schubert et al., 2009; R. Munns, pers. comm.). Although genetic variation in the first phase of salt stress is limited, some maize inbred lines have been identified that show slightly superior osmotic resistance. The crossing of these inbred lines yielded maize hybrids that show higher stress resistance in terms of yield formation (Schubert et al., 2009). Since under the experimental conditions used, no stress symptoms of the second phase of salt stress were observed in any of the genotypes tested, it can be concluded that genotypic differences in yield formation were caused by differences in osmotic resistance.

Although drought stress and salt stress in the first phase are not identical (see above), they both have in common the root sensing of low water availability and the release of stress signals to shoots. Therefore, some findings for drought stress may also be relevant for the first phase of salt stress, although a validation still is required. Comparable to findings for faba bean under drought stress (Amede et al., 1999), in the first phase of salt stress, kernel set of maize is more sensitive than kernel weight formation (Schubert et al., 2009). Three different hypotheses have been suggested to explain the decrease in kernel number under drought stress: first, abscisic acid that controls leaf growth and stomatal aperture may also be responsible for early flower or kernel abortion (Bano et al., 1993; Setter et al., 2001); second, although sugar production in photosynthesis seems not to be limiting under drought stress during vegetative growth and grain filling stage, the supply of sucrose during flowering may represent a critical factor to establish a high number of kernels (Boyle et al., 1991; Zinselmeier et al., 1999); third, there is strong evidence that a lack of acid invertase in sink organs restricts the


451

Fructose Sucrose

Acid Invertase

Hexose Carrier

Glucose

Phloem Apoplast Sink Cell Phloem unloading of sucrose and active uptake of glucose and fructose by hexose carriers. The sink activity is controlled by acid invertase activity.

Fig. 19.7.

determination of kernels in ovaries (Zinselmeier et al., 1995; Roitsch and González, 2004). It is generally accepted that phloem unloading in cereals occurs via an apoplastic route (Fig. 19.7). According to this model, sucrose leaked from phloem is not retrieved by sucrose/proton cotransport. Instead, acid invertase apoplastically hydrolyzes sucrose (Roitsch and González, 2004). The resultant hexoses cannot be transported into phloem but are imported by sink cells via protondriven specific hexose carriers. Under drought stress, acid invertase activity is reduced so that hexose import into sink cells is inhibited. There are indications that reduced sink activity due to insufficient acid invertase may also be caused by salt stress (Fukushima et al., 2001; Balibrea et al., 2003). Further experiments are necessary to understand the genotypic differences in salt resistance of cereals during the reproductive stage. Concluding remarks The biphasic model of growth response of crop plants to salt stress has proved to be a powerful theoretical basis to improve salt resistance in wheat and maize germplasm.

Sodium exclusion from shoots was a major step for this improvement. It is expected that this strategy will also be successful in other grasses. In addition, tissue tolerance of sodium may be further improved by increasing vacuolar Na+/H+ antiporter activity. On the other hand, osmotic resistance still has to be raised. A better understanding of the processes of cell elongation is required. It is clear now, however, that osmotic adjustment and production of assimilates are not the main bottleneck. This is apparently also true for the generative phase. In this stage, kernel set mainly limits yield formation, and a better understanding of this process may further add to the development of saltresistant crop plants. Acknowledgment The author is thankful for stimulating discussions with Sarah Hatzig and helpful comments by Dr. Britta Pitann on an early version of the manuscript. References Amede, T., Kittlitz, E.V., & Schubert, S. (1999) Differential drought responses of faba bean (Vicia

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Chapter 20

Legumes and Nitrogen Fixation: Physiological, Molecular, Evolutionary Perspectives, and Applications Muthusubramanian Venkateshwaran and Jean-Michel Ané

Abstract In order to meet the ever-growing food, feed, and biofuel demand, there has been an increasing dependence on intensive agriculture. These nonsustainable practices may lead to the deterioration of soil quality and require the production of nitrogen fertilizers at the expense of nonrenewable fossil fuels. Apart from increasing the cost of cultivation, the excessive use of fertilizers is also responsible for the damage to many ecosystems. Legumes have the ability to establish a mutualistic association with soil bacteria known as rhizobia, which form root nodules, inside of which atmospheric dinitrogen is reduced into assimilable forms and supplied to host plants. A high level of species specificity exists in rhizobia–legume interactions, which are initiated by a signal exchange between the two partners. The infection process and the development of root nodules require a set of highly coordinated events at the root epidermal and cortical cells. Over the past decades, elegant genetic and biochemical studies have been conducted on legume nodulation to decipher the intrica-

cies of this unique plant–microbe association. This chapter highlights the biochemical, physiological, molecular, and evolutionary features of legume nodulation, and explores the applications of nature’s unique gift toward the sustainability of our agriculture.

Introduction Soil fertility is a major limiting factor for crop production in developed and developing countries. Intensive agricultural practices to meet ever-growing food, feed, and biofuel demands are depleting soil quality at an alarming rate. The excessive use of fertilizers not only increases the cost of cultivation but also depletes nonrenewable energy sources and causes irreparable damage to the environment. Enriching soil nutrient levels by biological means seems to offer a much more sustainable solution. Among land plants, legumes are unique as they can enter into symbiotic association with nitrogenfixing bacteria known as rhizobia. This interaction results in the formation of new organs called nodules on legume roots, in


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which the rhizobia thrive and fix atmospheric nitrogen in a process known as biological nitrogen fixation (BNF). Hence, legumes have the ability to grow even in nitrogen-deprived soils. In agricultural ecosystems worldwide, legumes provide an amount of assimilable nitrogen roughly equivalent to that produced by the chemical fertilizer industries. Crop rotations and intercropping with legumes are practiced in many parts of the world to reduce the cost of nitrogen fertilizer applications. Being cultivated in arid and semi-arid tropics, legumes serve as a major source of protein in dietary supplements of developing countries. Worldwide, legumes are grown over 71 million hectares, with a total production of 61.5 million tonnes (FAOSTAT, 2010), with major contributions from Asian and African countries. In the United States, legumes are grown over 1 million hectares, with a total production of 2.2 million tonnes (FAOSTAT, 2010). Despite global industrialization, the area under legume cultivation is constantly growing (FAOSTAT, 2010) due to the importance of legumes as a food, fodder, and manure crop. The symbiosis between legumes and rhizobia is a sophisticated example of coordinated development between bacteria and eukaryotes culminating in the organogenesis of root nodules (Oldroyd and Downie, 2008). Being the third largest plant family, legumes display a huge diversity comprising trees, shrubs, herbs, and climbers. Likewise, rhizobia are a paraphyletic group comprising members of two classes, α- and βproteobacteria. Rhizobiales, which belong to the most studied α-proteobacteria group, have been grouped at the generic level into Azorhizobium, Bradyrhizobium, Devosia, Mesorhizobium, Methylobacterium, Ochrobactrum, Phyllobacterium, Shinella, Rhizobium, and Sinorhizobium (Ensifer), each of which have multiple species, biovars, and a plethora of strains. Members of the

β-proteobacteria group, such as Burkholderia, Cupriavidus (Ralstonia), and Herbaspirillum, are also potential symbionts of legumes (Amadou et al., 2008). Amidst this diversity, there exists a high level of species specificity among legume species and their symbiotic partners. Although root nodule symbiosis (RNS) is a unique association between legumes and rhizobia, one exception to this “rule” is the mutualistic interaction between the nonlegume Parasponia (Ulmaceae) and nitrogen-fixing rhizobia (Trinick, 1979). Apart from legumes (Fabales), members of the plant orders Fagales, Cucurbitales, and Rosales are able to establish symbiotic interaction with the nitrogen-fixing actinobacteria Frankia. This symbiotic interaction is referred to as actinorhizal symbiosis (ARS). This chapter focuses on biochemical, physiological, molecular, and evolutionary aspects of legume–rhizobial interaction, with special interest on its immediate and long-term field applicability. Biological nitrogen fixation and nitrogenase biology BNF is the reduction of inert atmospheric nitrogen (N2) into ammonia (NH3) through biological means. The general chemical reaction for the biological fixation of nitrogen is N 2 + 8e − + 16 MgATP + 8H + → 2 NH 3 + H 2 + 16 MgADP + 16 Pi , where Pi is inorganic phosphate. This reaction is catalyzed by nitrogenase, a molybdenum-dependent enzyme, which comprises two component proteins called the Fe protein and the MoFe protein (Burgess and Lowe, 1996). The role of Fe protein is to deliver electrons from its [4Fe-4S] cluster to the MoFe protein one at a time. This elec-

LEGUMES AND NITROGEN FIXATION

tron transfer is coupled to the hydrolysis of a minimum of two magnesium–adenosine triphosphate (Mg–ATP) molecules (Lanzilotta et al., 1998). The MoFe protein (an α2ß2 heterotetramer) consists of α- and β-subunits and two metal clusters called the P cluster and the MoFe cofactor (Chan et al., 1993). The P cluster, which in turn is made up of 8Fe-7S, is positioned at the interface of, and with, α and β-subunits on each side (Lanzilotta et al., 1998). The role of the P cluster is likely to be to accept electrons from the Fe protein and to deliver it to MoFe cofactor, which is deeply buried within each of the α-subunits. The molecular composition of MoFe cofactor is quite intriguing, as it is composed of 7Fe-9S-Mo-X-homocitrate and serves as the site of nitrogen reduction (Einsle et al., 2002). A water-filled substrate channel that extends from the solventexposed surface to a specific face of the MoFe cofactor provides a pathway for substrate to bind to the active site (Barney et al., 2009). Several genes are involved in the synthesis and assembly of functional nitrogenase in rhizobia, albeit with high level of variations among different species. Photosynthetic Bradyrhizobium and Azorhizobium caulinodans carry about 15 nif genes required for nitrogenase synthesis, while Rhizobium and Sinorhizobium possess eight and nine genes, respectively. Some of the core nif genes, which are conserved in majority of the rhizobia are nifH (nitrogenase reductase), nifDK (α-and β-subunits of nitrogenase), nifEN (scaffold for MoFe cofactor), nifB (P cluster), and the regulatory gene, nifA (Masson-Boivin et al., 2009). The high energy requirement (16 moles of ATP for each mole of N2 reduced) of nitrogenase in rhizobia demands high levels of photosynthates as fuel from the plants. The extreme sensitivity of the rhizobia nitrogenase enzyme to oxygen may seem surprising, rhizobia being mostly aerobic bacteria.

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Thus, legume plants synthesize leghemoglobin (Lb) to scavenge excess oxygen and provide a microaerobic environment (less than 10 nM of free O2) required for nitrogen fixation. Lb are hemoproteins that have a high affinity for oxygen due to their extremely low oxygen–dissociation constant (Garrocho-Villegas et al., 2007). Legumes contain several symbiotic Lb genes, which are essential for the formation of functional nodules but do not seem necessary for general plant growth and development (Ott et al., 2005; Ott et al., 2009). Wild-type nodules exhibit a steep oxygen gradient from the surface toward the center of the nodule. Legume plants silenced for Lb genes exhibit a very high level of oxygen (more than 4.5% of ambient O2) at the central and infected zone, in contrast to much lower levels in wild-type nodules (Ott et al., 2005). Thus, the high level of intricacy and sophistication in the functionality of nitrogenase and Lb in nitrogen fixation has enabled legumes to occupy a unique niche among land plants. Nodule development and physiology Preinfection and infection Nodule development may be divided into three overlapping stages: preinfection, nodule initiation, and nodule differentiation. The preinfection stage commences with the release, by the host plants, of flavonoids and isoflavonoids, which act as chemoattractants for the rhizobial symbionts (Peters et al., 1986). Flavonoids are polyphenolic compounds that constitute one of the most diverse classes of compounds in higher plants, with more than 4000 identified. Unlike flavonoids, the distribution of isoflavonoids is limited to few taxonomic groups including the Leguminosae. Flavonoids and isoflavonoids allow the rhizobia to

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recognize their potential host. For instance, Sinorhizobium meliloti specifically recognizes flavonoids such as luteolin and crysoeriol released by alfalfa (Maxwell et al., 1989; Hartwig et al., 1990a). Similarly, Bradyrhizobium japonicum specifically responds to isoflavonoids, daidzein, and genistein secreted by soybean (Kosslak et al., 1987; Zhang and Smith, 1995). Upon perception, flavonoids and isoflavonoids bind to NodD proteins, which are transcriptional regulators in rhizobia. This activates the expression of several nod genes (Hartwig et al., 1990b; Perret et al., 2000; D’Haeze and Holsters, 2002). Enzymes encoded by rhizobial genes such as nod, noe, and nol are required for the synthesis of nodulation factors, referred to as “Nod factors.” Chemically, Nod factors are lipochitooligosaccharide molecules with a backbone of β-1,4linked N-acetyl-D-glucosamine residues. They are N-acylated at the nonreducing terminal residue with acyl chains of different lengths and saturation levels (Dénarié et al., 1996). This chemical core of Nod factors is synthesized by enzymes encoded by genes of the nodABC operon. However, speciesspecific decorations such as the addition of fucosyl, suphuryl, acetyl, methyl, carbamoyl, and arabinosyl are encoded by enzymes encoded by other nod genes, as well as noe and nol genes (Perret et al., 2000; Oldroyd and Downie, 2008). These decorations provide great variation in the final chemical makeup not only between different species of rhizobia but also within the same species (Perret et al., 2000; Oldroyd and Downie, 2004; Oldroyd and Downie, 2008). Nod factors are required for rhizobial infection and nodule development, are active at very low concentrations (10−9–10−12 M), and able to initiate responses in host plants similar to those elicited by the rhizobia themselves. The earliest responses elicited by Nod factors are ion fluxes (Ca2+ influx; H+, K+, and Cl− efflux), which alter the plasma mem-

brane potential in the root hair cells (Ehrhardt et al., 1996; Felle et al., 1999). From 10 to 20 min after addition of Nod factors, oscillations of calcium concentration and calcium spiking occur around and inside of the nucleus (Ehrhardt et al., 1996; Wais et al., 2000; Shaw and Long, 2003; Sieberer et al., 2009). Purified Nod factors induce cytoskeleton rearrangements that lead to root hair deformations, such as root hair waving, swelling, and branching (Heidstra et al., 1994; Spaink, 1995; Dénarié et al., 1996; Stougaard, 2000). Localized application of Nod factors by the rhizobia induces a curling of root hairs that entraps the bacteria and results in the formation of a microcolony inside the “Shepherd’s crook,” from which an infection thread originates (Fig. 20.1A). Infection threads are thin tubules filled with proliferating rhizobia and matrix growing inside plant cells and always separating the rhizobia from the plant cytoplasm. Infection threads reach the root cortex and release the bacteria into dividing cortical cells. In coordination with infection thread formation, Nod factors stimulate root cortical cells to reenter mitosis, resulting in the formation of a nodule primordium. The freshly dividing cortical cells internalize the invading bacteria through an endocytosis-like process using a host-derived membrane called the peribacteroid membrane, which results in the formation of symbiosomes. This Nod factor-dependent nodulation strategy is used by the phylogenetically distant symbionts, Methylobacterium nodulans (Jourand et al., 2005; Renier et al., 2008) and Cupriavidus taiwanensis (Amadou et al., 2008), demonstrating its widespread occurrence. In Andrea and other woody legumes, internalization of the rhizobia is not observed, and nitrogen fixation takes place in suberized infection threads known as fixation threads (Hirsch, 1992; Sprent and James, 2007). These fixation threads are restricted to an individual host cell.


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Two different modes of entry and nodulation strategies in rhizobia. (A) Nod factor-dependent root hair entry involves root hair contact with rhizobia, root hair curling, entrapping rhizobia, proliferation and infection thread growth via root hair to reach the cortical cell, and release of rhizobia in the newly divided nodule meristem. (B) Crack entry mode of infection involves entry of rhizobia via wounds or cracks formed due to the emergence of lateral roots. This mode of entry can be either Nod factor dependent or Nod factor independent. Nod factor-dependent crack entry involves early signaling and nodule organogenesis. Nod factor-independent crack entry bypasses the early signaling and triggers nodule organogenesis by cytokinin-dependent pathway.

Fig. 20.1.

Along with Nod factors, rhizobial exopolysaccharides (EPSs), lipopolysaccharides (LPSs), capsular polysaccharides (CPSs), and cyclic β-glucans are often required for infection thread formation and successful plant infection, possibly by suppressing plant defense responses (Leigh and Coplin, 1992; D’Haeze and Holsters, 2004). Among the various EPSs, succinoglycan (EPS1), a polymer of octasaccharide with succinyl, acetyl, and pyruvyl modifications, and galactoglucan (EPSII), are the subjects of intense studies. The role of EPS in rhizobial infection and nodule development was reported by several groups in various Galegoid legumes, such as Medicago sativa, Medicago truncatula, Pisum sativum, Trifolium pretense, and Leucaena leucocephala (Leigh et al., 1985; Pellock et al., 2000; Mazur et al., 2002; Jones et al., 2007; Jones et al., 2008). In M. truncatula, succinoglycan-deficient (exo) mutants of S.

meliloti are symbiotically defective, resulting in the formation of small nodules that are devoid of bacteria (Leigh et al., 1985; Jones et al., 2008). The role of a type III secretion system in rhizobial infection and suppression of legume defense responses was proposed by several groups (Freiberg et al., 1997; Viprey et al., 1998; Kaneko et al., 2000; Gottfert et al., 2001; Marie et al., 2001; Zehner et al., 2008). Unlike Rhizobium NGR234, Mesorhizobium loti, or B. japonicum, the alfalfa partner S. meliloti lacks the type III secretion system (Marie et al., 2001). Therefore, the use of the type III secretion system to infect plant cells is not a common mechanism among rhizobia but instead may play a role in host specificity (Perret et al., 2000). Similarly, VirB/D4 type IV secretion system found in M. loti strain R7A is necessary for nodulation in Lotus carniculatus and enables this strain to nodulate a nonhost, Leucaena leucocephala (Hubber et al.,

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2004). Another mechanism utilized by rhizobia to invade the host root hair is by degrading the cellulose present in the cell wall. A cellulase-encoding gene celC2 in Rhizobium leguminosarum was found to be crucial for root hair penetration (Robledo et al., 2008). Nod factor-dependent nodulation is not a universal strategy in legume–rhizobia interactions. Certain rhizobial strains, such as Bradyrhizobium BTAi1 and ORS278, form root and stem nodules on restricted species of Aeschynomene, although they lack the core nodABC genes required for the synthesis of Nod factors (Giraud et al., 2007). Since many species of Bradyrhizobium produce cytokinins (or equivalent purine derivatives), the recent identification of cytokinin receptors in legumes has led to the hypothesis that these purine derivatives may play a key role in these Nod factorindependent symbiotic events (Chaintreuil et al., 2001; Gonzalez-Rizzo et al., 2006; Giraud et al., 2007; Murray et al., 2007). The role of cytokinins in nodule development is discussed later in this chapter. Entry through root hairs is not the only mechanism of invasion by rhizobia. In several legume species, rhizobia enter via cracks at lateral root bases, wounds, or natural openings on the epidermis (Fig. 20.1B). This method of intercellular invasion, also known as “crack entry,” is observed in several legumes, including Arachis, Sesbania, Andrea, and other woody legumes (Sprent, 2008). In Papilionoideae such as Arachis hypogaea, crack entry has been known for several years, but the molecular mechanisms involved in this mode of entry are still poorly understood. Sesbania rostrata, which usually grows in waterlogged conditions, displays both crack entry and Nod factor-dependent root hair entry of rhizobia. Hence, S. rostrata is an excellent system to dissect the molecular mechanism mediating “crack entry” invasion (Capoen et

al., 2005; Capoen et al., 2009). Apart from Nod factor-dependent infection thread formation, infection by crack entry also depends on rhizobial EPS. An EPS-defective mutant of rhizobia failed to form functional nodules in peanut, resulting in nodule-like structures that were devoid of bacteroids (Morgante et al., 2005; Morgante et al., 2007). Unlike in the Galegoids, the role of EPS in nodule organogenesis in Phaseoloids is still controversial (Hirsch, 1992; Parniske et al., 1994; Parveen et al., 1997; D’Haeze and Holsters, 2004). Nodule organogenesis Upon perception of Nod factors, along with rhizobial infection and invasion, cortical cell divisions mark the commencement of nodule organogenesis. Root cortical cells below the point of infection de-differentiate and reenter the cell cycle. The site of cell division (outer or inner cortex of the root depending on the host plant) determines the type of nodule that forms. Unlike the cell divisions involved in lateral root formation, the cell divisions that initiate nodule primordium are initially anticlinal (Hirsch, 1992). Some of the cortical cells are arrested in the G2 phase and allow passage of inward progressing infection threads. The rest of the cells that complete their cell cycle resume cell division to form the rest of the nodule where infection and nitrogen fixation will occur. The bacteria released from the inward progressing infection thread are endocytosed into a subset of cells where they differentiate into nitrogen-fixing bacteroids. The vascular bundles present in the nodule parenchyma of mature nodules are connected to the root vasculature. The different cells and tissue types within a mature nodule can be distinguished by their cytological, anatomical, and functional attributes, and, to some extent, with molecular markers (Hirsch, 1992; Stougaard, 2000).


A

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B

Fig. 20.2. The two major nodule types observed in legume plants. (A) Indeterminate nodules on the roots of M. truncatula. (B) Determinate nodules on the roots of L. japonicus. Scale bar: 2 mm.

Genetic analyses show that rhizobial infection and nodule development are two separable processes, although they are tightly synchronized and coordinated for the making of a functional nodule. Legumes display a huge diversity with respect to nodule organogenesis. Based on the origin, anatomy, histology, host, and shape, legume nodules can be grouped into four types: indeterminate, determinate, aeschynomenoid, and lupinoid nodules (Hirsch, 1992; Sprent, 2008; Guinel, 2009). Although the structural features of these nodule types are discrete, there are a few unifying patterns observed among them with respect to their vasculature. They all possess vascular bundles sheathed by a vascular endodermis running through the uninfected parenchymatous cells, which encircles the infected tissue (Guinel, 2009). Indeterminate nodules are characterized by a persistent meristem that arises from the root inner cortex. Anticlinal cell divisions occur opposite to the protoxylem pole, suggesting a role for the vascular stele in conducting hormones regulating this event (Hirsch, 1992). The long-lived meristem makes the nodule elongated or club shaped, as newly dividing cells are added consistently at its distal end. Members of the

legume tribes Trifoliae and Viciae, such as Medicago, Trifolium, Pisum, and Vicia, form such indeterminate nodules (Fig. 20.2A). Mature nodules comprise distinct zones, such as zone I (meristematic), zone II (prefixation), interzone II–III, zone III (fixation), and zone IV (senescence zone). The actively dividing meristematic cells are present in zone I, which gives rise to fully prepared cells with the ability to accommodate the invading infection thread and the released bacteria (zone II) and nitrogen-fixing bacteroids (zone III). Interzone II–III is characterized by the presence of a heterogeneous mixture of cells, which are rich in starch and Lb transcripts (Perlick et al., 1996). A senescence zone is observed in fully mature nodules, where both host cells and rhizobial symbionts degenerate. In fully mature indeterminate nodules, an additional saprophytic zone (zone V) is often observed (Timmers et al., 2000). This saprophytic zone is characterized by the presence of nondifferentiated rhizobia, termed rhizoboids, which are more saprophytic than mutualistic (Timmers et al., 2000; Guinel, 2009). Generally, indeterminate nodules transport assimilated nitrogen as amides, whereas determinate nodules transport both amides (Glycine, Phaseolus, Vigna) and ureides

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(Lotus) (Sprent and James, 2007). The bacteroids in indeterminate nodules are of three types: bacteroids in the invasion zone (zone I) are rod-shaped, still dividing and surrounded by a peribacteroid membrane (type 1), while more elongated and differentiated bacteroids (type 2) are present in the prefixation zone (zone II). The interzone II–III comprises type 3 bacteroids, which are fully elongated and display cytoplasmic heterogeneity (Vasse et al., 1990; Hirsch, 1992). These type 3 bacteroids are longer than freeliving rhizobia (5–10 μm), Y-shaped, and polynucleoid, with an average of 24C (C being the haploid DNA content). The symbiosomes are formed by a single bacteroid and are distributed perpendicular to the cell wall. Bacteroids in these types of nodules are terminally differentiated and are digested by plants during senescence and therefore cannot be subcultured from indeterminate nodules (Vasse et al., 1990; Mergaert et al., 2006; Den Herder and Parniske, 2009). This terminal differentiation of bacteria is mediated by nodule-specific cysteine-rich (NCR) peptides encoded by the host and processed by a recently identified signal peptidase complex (Van de Velde et al., 2010; Wang et al., 2010b). Determinate or desmodioid nodules lack a persistent meristem and are spherical in shape. Legumes such as Phaseolus, Glycine, Vigna, and Lotus form such determinate nodules that contain a central and a peripheral tissue (Fig. 20.2B). The peripheral tissue comprises the nodule cortex and the nodule parenchyma, which are separated by the nodule endodermis. Nodule parenchyma in determinate nodules encircles the central infected tissue and is embedded with vascular bundles. The first cell divisions in the formation of desmodioid nodules are anticlinal, which are confined to the outer cortex, but later extend to the pericycle and inner cortex of the root.

Cell division activity ceases 12–18 days after inoculation with rhizobia. Some cells in the central tissue are invaded by infection threads. Infected cells at the center are large and dense due to the presence of released bacteria and differentiating bacteroids (Hirsch, 1992). These infected cells are interspersed with highly vacuolated uninfected cells. Bacteroids in determinate nodules do not differ in their shape and size from free-living bacteria, being 1–2 μm in size, rod-shaped, and uninucleate or binucleate. Bacteroids in determinate nodules accumulate excess carbon obtained from the legume plants as poly-β-hydroxybutyrate (PHB), a polyester reserve of carbon. This highly reduced product is an important source of oxidizable substrates that help maintain the respiratory demand of the bacteroids and support nitrogen fixation when the supply of photosynthate from the host is reduced (Kim and Copeland, 1996). Interestingly, bacteroids of indeterminate nodules do not accumulate PHB (Povolo et al., 1994; Cevallos et al., 1996). The symbiosomes in determinate nodules comprise multiple bacteroids and are distributed randomly within the infection zone. Bacteroids in determinate nodules are not terminally differentiated and can therefore be isolated and subcultured from a mature nodule (Muller et al., 2001; Mergaert et al., 2006; Den Herder and Parniske, 2009). The other two types of nodules, aeschynomenoid and lupinoid, differ in the mode of infection, morphology, and anatomy. Aeschynomenoid nodules are observed in peanuts, while lupinoid nodules are present in Lupinus sp. In aeschynomenoid nodules, infection takes place by crack entry through wounds that arise from lateral root emergence or through tufted hairs that originate from the epidermis of the lateral root primordium. These nodules do not arise from the tissue of primary roots but from the axils


of lateral roots. In lupinoid nodules, rhizobia penetrate the root in a similar way through the interstices found between the base of a root hair and its adjacent epidermal cell (Gonzalez-Sama et al., 2006). Both nodules have infected cells at the center with no adjoining uninfected cells (Sprent, 2008). Although both nodule types have broad attachments to the root, the aeschynomenoid nodule has a narrow base compared with the lupinoid nodule, which is the largest of all types. These nodules do not have lenticels on their surface. Bacterial proliferation in these two nodule types occur by successive division of infected cells at the center. With respect to the meristem, aeschynomenoid nodules have a nonpersistent meristem and are therefore small and oblate in shape. Lupinoid nodules have several lateral meristems of indeterminate growth (Guinel, 2009). Molecular mechanism of rhizobia infection and nodule organogenesis Early symbiotic signaling Genetic and genomic analyses in model legumes such as M. truncatula and Lotus japonicus have identified many genes involved in bacterial infection and nodule organogenesis. The species specificity associated with legume–rhizobia interaction relies on the high level of specificity between the Nod factor structure and their receptors. Receptor-like kinases (RLKs) located on the plasma membrane, such as Nod factor receptor 1 (NFR1) and NFR5 in L. japonicus are required for all responses to Nod factors and can recognize specific substitutions on the Nod factors (Madsen et al., 2003; Radutoiu et al., 2003; Radutoiu et al., 2007). In M. truncatula, Nod factor perception (NFP) is a homolog of Lotus NFR5 and is a compo-

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nent of a signaling receptor required for all responses to Nod factors (Amor et al., 2003; Arrighi et al., 2006). In contrast, Medicago LYK3/HCL (homolog of NFR1) is required for infection thread formation, but not for cortical cell divisions, calcium spiking, or expression of some nodulin genes such as NIN, and is hypothesized to be part of an entry receptor (Wais et al., 2000; Catoira et al., 2001; Limpens et al., 2003; Smit et al., 2007). A similar system with a low stringency signaling receptor and a high stringency entry receptor probably exists in pea, but there is no evidence so far for different receptor complexes in L. japonicus (Ardourel et al., 1994; Limpens et al., 2003). Lectin ecto-apyrases (LNPs) are a group of proteins that bind to Nod factors with high affinity, and regulate early nodulation signaling and nodule organogenesis. The role of LNPs in nodulation was initially demonstrated in Dolichos biflorus and subsequently in soybean (GS52), Medicago (apy1 and apy4), and Lotus (Etzler et al., 1999; Day et al., 2000; Cohn et al., 2001; McAlvin and Stacey, 2005; Govindarajulu et al., 2009). Their specific role is to hydrolyze nucleoside triphosphates and nucleoside diphosphates to nucloside monophosphate and orthophosphates, suggesting a role for extracellular ATP in legume nodulation. Another RLK with leucine rich repeats (LRR), known as NORK or DMI2 in Medicago and SYMRK in L. japonicus, also resides on the plasma membrane and plays a critical role in symbiotic signal transduction (Endre et al., 2002; Stracke et al., 2002; Limpens et al., 2005). NORK is also involved in actinorhizal symbiosis, suggesting conserved genetic machinery between these two types of nodule symbioses (Gherbi et al., 2008). To date, three interactors of NORK/ SYMRK have been identified: 3-hydroxyl 3-methylglutaryl coenzyme A reductase

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(HMGR1), which interacts with NORK; a DNA-binding protein, SIP1, which interacts with SYMRK; and symbiotic remorin, SYMREM1, which interacts with NFP, LYK3, and NORK (Kevei et al., 2007; Zhu et al., 2008; Lefebvre et al., 2010). HMGR1 is required for nodule development, infection thread formation, and calcium spiking, indicating its role in the Nod factor signaling pathway at the same level as NORK (Kevei et al., 2007; J.M. Ané, unpublished data). SIP1 binds to the promoter region of the early nodulin gene NIN in L. japonicus, suggesting the existence of a calcium spikingindependent pathway for the activation of nodulin expression (Zhu et al., 2008). SymREM1 localizes on the host plasma membrane surrounding the bacteria and controls infection and release of rhizobia into the host cytoplasm (Lefebvre et al., 2010). The nucleus plays a central role in Nod factor signaling. Several nuclear proteins have been identified as required for calcium spiking initiation and transduction. Among them, two ion channels, DMI1/POLLUX and CASTOR, localized on the nuclear envelope mediate Nod factor-induced calcium spiking in root hair cells (Ané et al., 2004; Imaizumi-Anraku et al., 2005; Peiter et al., 2007; Riely et al., 2007; Charpentier et al., 2008). Mutants in two nucleoporins, NUP133 and NUP85, are also affected in calcium spiking, rhizobial infection, and nodule development (Kanamori et al., 2006; Saito et al., 2007). Although the precise role of these nucleoporins has not yet been resolved, they probably help trafficking symbiotic proteins or symbiotic signals across the nuclear envelope. The nuclear envelope is probably the calcium source for intra- and perinuclear calcium spiking. However, the perception and transduction of this signal seem to take place only inside of the nucleus. A calciumand calmodulin-dependent protein kinase, DMI3/CCaMK, and its interactor, IPD3/

CYCLOPS, which are required for Nod factor signaling and very likely calcium spiking sensing, are both localized inside of the nucleus (Lévy et al., 2004; Mitra et al., 2004; Tirichine et al., 2006a,b; Messinese et al., 2007; Yano et al., 2008). Constitutively active alleles of DMI3/CCaMK have shown that this protein is not only required but also sufficient for nodulin gene expression and nodule development (Tirichine et al., 2006a,b; Gleason et al., 2006). In addition, two GRAS (gibberellin-insensitive [GAI], repressor of gal-3 [RGA] and SCARECROW [SCR]) family transcriptional regulators, nodulation signaling pathway 1 (NSP1) and NSP2, are indispensable for Nod factorinduced activation of early nodulin genes (Kaló et al., 2005; Smit et al., 2005; Heckmann et al., 2006; Murakami et al., 2006). NSP2 interacts with DMI3, while NSP1 binds to the promoter region of ENOD11 and NIN and regulates their expression in a Nod factor-dependent manner (Oldroyd and Downie, 2008; Hirsch et al., 2009). Infection thread formation and nodule organogenesis Mutants affected in later events, such as infection thread formation and nodule development, have also been identified in model legumes. M. truncatula ERN1 (BIT1) and ERN2, which are AP2/ERF-like transcription factors, play a role downstream of DMI3 in Nod factor-induced transcriptional activation of ENOD11 (Andriankaja et al., 2007; Middleton et al., 2007). ERN3 acts as a negative regulator (repressor) of ERN1/ ERN2-mediated transcriptional activation. BIT1/ERN1 mutants undergo normal root hair curling upon contact with rhizobia, but form aberrant infection threads, which cannot penetrate through the epidermal layers into the dividing cortical cells (Andriankaja et al., 2007; Middleton et al.,


2007). A transmembrane-containing transcription factor, NIN, was identified initially in L. japonicus and later in M. truncatula as required for both infection thread formation and cortical cell division. However, nin mutants display normal responses for early Nod factor signaling, indicating a role after NSP1 and NSP2 (Schauser et al., 1999, 2005; Murakami et al., 2006; Marsh et al., 2007). Medicago flotillin-like genes, FLOT2 and FLOT4, which are localized to membrane microdomains, play a critical role in infection thread initiation and nodule formation (Haney and Long, 2010); specifically, FLOT4 seems to be involved in polar growth of the infection thread, as silencing of FLOT4 affects infection thread elongation (Haney and Long, 2010). M. truncatula LIN (lumpy infections) encodes an E3 ubiquitin ligase with U-box and WD40 repeat domains, and the corresponding mutants are characterized by a reduction in the number of infections, aborted infection threads, and nodule primordia (Kuppusamy et al., 2004; Kiss et al., 2009). In M. truncatula dnf1 mutants, bacterial release into the host cell takes place; however, subsequent differentiation of the bacteria into bacteroids is blocked (Wang et al., 2010b). The DNF1 complex is an important host determinant, involved in the processing of NCR peptides, which mediate symbiosome development and terminal differentiation of bacteria in indeterminate nodules (Van de Velde et al., 2010; Wang et al., 2010b). Several other M. truncatula mutants, such as nip (numerous infections and polyphenolics), latd (lateral root organ-defective), api, rit1, and rpg (rhizobium-directed polar growth); L. japonicus itd1 (infection thread deficient 1), sym7, itd3, itd4, and lot1 (low nodulation and trichome distortion) and crincke; and P. sativum mutants sym7, sym34, sym37, and sym38, all show arrested infection (Veereshlingam et al., 2004; Bright et al.,

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2005; Ooki et al., 2005; Lombardo et al., 2006; Starker et al., 2006; Jones et al., 2007; Arrighi et al., 2008; Oldroyd and Downie, 2008; Teillet et al., 2008). Nodule organogenesis commences with programmed mitotic cell divisions in cortical cells to accommodate the invading rhizobia. Cortical cell divisions leading to nodule primordium always occur across from protoxylem poles (Timmers et al., 1999). Hence, regulators of the cell cycle obviously play a crucial role in nodule development (Cebolla et al., 1999). Characterization of plant mutants showed that rhizobial infection and cortical cell division can be uncoupled. The transcriptional regulation and developmental processes that occur in the cortex are different from those that occur in the epidermis. Several nodulins, ENOD40, ENOD2, ENOD12, and ENOD20, are specifically expressed in the cortex during nodule organogenesis (Crespi et al., 1994; Journet et al., 1994, 2001; Charon et al., 1999). ENOD40 plays a direct role in cell dedifferentiation and division of cortical cells during nodule formation (Charon et al., 1999). The HAP2-1 transcription factor plays a pivotal role during nodule development by controlling meristem persistence and rhizobial release (Combier et al., 2006). The spatial and temporal expression of the HAP2-1 transcription factor is controlled by a microRNA, miR169, in M. truncatula (Combier et al., 2006). A schematic illustration of genetic components involved in the symbiotic signaling pathway and the entry pathway, leading to coordination of infection and cortical cell division as shown in Figure 20.3. Hormonal regulation of nodulation Plant hormones are not only master regulators of general plant growth and development, but

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also control nodule development in legumes. Different groups of hormones affect the nodulation process either by positively or by negatively regulating these events (Oldroyd and Downie, 2008; Mukherjee and Ané, 2011). Auxins and cytokinins Elegant studies demonstrate that the auxin transport and auxin/cytokinin ratio is crucial for successful nodule formation (Mathesius et al., 1998; Mathesius, 2008). Exogenous application of Nod factors results in a transient inhibition of auxin transport to the roots of Vicia sativa and Trifolium repens (Mathesius et al., 1998; Boot et al., 1999). Auxin reporter constructs were used to study auxin transport and accumulation during root nodule formation (Mathesius et al., 1998; Pacios-Bras et al., 2003). Similarly, application of auxin transport inhibitors (1-naphthylphthalamic acid [NPA]) induces pseudonodules and expression of early nodulin genes, such as ENOD2, ENOD12, and ENOD40, which are associated with the establishment of nodule primordia (Hirsch

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et al., 1989; Hirsch and Fang, 1994; Fang and Hirsch, 1998). Interestingly, auxin homeostasis during nodulation appears to differ between determinate and indeterminate nodule types (Subramanian et al., 2007). In the roots of indeterminate noduleforming plants, such as Medicago, auxin transport is arrested at the site of infection by rhizobia, which is mediated by flavonoids. Flavonoid-deficient roots in these plants failed to inhibit auxin transport at the site of rhizobial inoculation and were defective for nodule organogenesis, while control roots showed a clear inhibition in auxin transport (Wasson et al., 2006). In plants forming determinate nodules, such as Glycine or Lotus, auxin transport is not arrested at the site of rhizobial entry (PaciosBras et al., 2003; Subramanian et al., 2006). RNAi silencing of the isoflavone biosynthesis pathway resulted in increased auxin transport and defective nodule formation. However, exogenous application of isoflavones inhibited auxin transport but failed to restore nodules (Subramanian et al., 2006). This suggests that isoflavones modulate auxin transport in plants forming determinate-type

Schematic illustration of genetic components involved in the symbiotic signaling pathway and entry pathway leading to coordination of infection and cortical cell division. The genetic components are grouped based on their functional hierarchy and their site of residence at the subcellular level. Nod factors are perceived by Nod factor receptors NFR1 and NFR5 (or NFP), which reside on the plasma membrane. This leads to root hair deformations and early calcium influx. The signals are transduced to NORK/SYMRK. Interacting proteins, such as remorin (SymREM1), 3-hydroxyl 3-methylglutaryl coenzyme A reductase (HMGR1), and SYMRK interacting protein 1 (SIP1) may be involved in this early signal transduction from LysM receptor kinases to LRR receptor kinases. It is also hypothesized that these interacting proteins may connect the genetic components in the plasma membrane to components in the nucleus. The nucleus acts as a central player in the symbiotic signaling. M. truncatula DMI1 (Does not Make Infections 1) and nucleoporins NUP85 and NUP133 reside on the nuclear envelope and are required for Nod factor-induced calcium spiking. These signals are decoded by DMI3, a calcium- and calmodulin-dependent protein kinase (CCamK) and its interactor IPD3 (Interacting Protein of DMI3). A set of transcriptional regulators in the nucleus govern the expression of early nodulin genes and cortical cell division in coordination with rhizobial infection and proliferation. It is hypothesized that the entry pathway comprises M. truncatula LysM receptor kinase (LYK3), IPD3, and nodule inception (NIN), as mutants of these genes are affected for rhizobial infection, but not in the cortical cell division and meristem formation. Coordinated infection and cortical cell division is needed for successful nodule formation.

Fig. 20.3.

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nodules, but the role of isoflavones in auxin transport is not necessary for nodule formation. M. truncatula cell division cycle 16 (CDC16), a core component of the anaphasepromoting complex, plays a key role in auxin signaling. Partial silencing of CDC16 results in reduced sensitivity to auxin, leading to reduced lateral root formation and a fourfold increase in the number of nodules (Kuppusamy et al., 2009). Cytokinins play a crucial role in various phases of legume nodulation including infection thread formation, induction of early nodulin genes, and cortical cell divisions. The role of cytokinins in the crack entry mode of infection in Bradyrhizobium defective for Nod factor synthesis was discussed earlier. Nod factor-defective rhizobia gain the ability to form nodules when engineered to produce transzeatin (Cooper and Long, 1994). Cytokinins secreted by rhizobia like Bradyrhizobium are perceived by cytokinin receptors in legumes, leading to the onset of nodule organogenesis (Giraud et al., 2007). Cytokinins are expressed in the dividing cortical cells and periphery of the emerging and young nodules in L. japonicus. However, their presence is not detected in the mature nodule (Lohar et al., 2004). Mutation in the cytokinin receptor gene, Lotus histidine kinase 1 (LHK1), results in a failure to form nodule primordia, although these mutants are unaffected for rhizobial infection. Similar effects were observed when an LHK1 ortholog in M. truncatula, CRE1, was silenced by an RNAi-based gene knockdown strategy (Gonzalez-Rizzo et al., 2006). Mutation in LHK1 is strong enough to suppress the supernodulation phenotype observed in har1 mutants. Reciprocally, a gain-of-function mutation in LHK1 resulted in the spontaneous formation of pseudonodules in L. japonicus, even in the absence of rhizobia (Murray et al., 2007; Tirichine et al., 2007).

Gibberellic acid and brassinosteroids In addition to auxins and cytokinins, gibberellic acid (GA) and brassinosteroids (BR) positively regulate nodulation. Application of GA induced pseudonodule structure in a nitrogen-sensitive manner (0–5 mM NO3 permissible and more than 10 mM NO3 inhibitory) in L. japonicus (Kawaguchi et al., 1996). Pea mutants that are affected in the GA and BR regulatory pathways show a reduction in nodule organogenesis (Ferguson et al., 2005). Exogenous application of 10−6 M GA to deficient mutants completely restored nodulation comparable to wild-type plants, but not at higher concentrations (10−3 M). Grafting experiments suggested that both the shoot and the root control GA signaling, while only the shoot controls the BR level pertaining to nodulation (Ferguson et al., 2005). However, exogenous application of GA (10−6 to 10−9 M) blocked Nod factor-induced root hair deformations, nodulin gene expression, and nodule organogenesis in L. japonicus. This effect was counteracted by the application of a GA biosynthesis inhibitor, uniconazole-P. The number of spontaneous pseudonodules induced by gain-of-function mutations in DMI3/CCaMK and LHK1 was reduced on exogenous application of GA. Overexpression of the gain-offunction mutant, L. japonicus SLEEPY1 (sly1-d), a positive regulator of GA signaling, results in reduced nodule number, demonstrating a negative role of SLY1 in nodulation (Maekawa et al., 2009). Hence, GA acts as a positive regulator in Medicago and pea, while negative regulator in L. japonicus.

Ethylene In most legumes, ethylene acts as a negative regulator for the formation of nodules. Ethylene appears to regulate multiple steps,


such as Nod factor-induced calcium spiking, early nodulin gene expression, growth of the infection thread, nodule number, and nodule positioning. One possible mechanism of ethylene inhibition is by decreasing the sensitivity of epidermal cells to Nod factors, leading to the loss of ENOD11 expression and Nod factor-induced calcium spiking (Oldroyd et al., 2001b; Oldroyd and Downie, 2008). Therefore, it has been hypothesized that ethylene-sensitive components necessary for the perpetuation of symbiotic signaling are positioned either upstream or at the site of origin of nuclear calcium spiking. Application of 1 - aminocyclopropane - 1 - carboxylic - acid (ACC), an ethylene precursor, on Medicago and Lotus affects calcium spiking, ENOD11 expression, and polar growth of infection thread through the cortex, ultimately resulting in a reduced number of nodules (Oldroyd et al., 2001a). This suggests that ethylene regulates the function of a genetic component involved in the Nod factor signaling cascade upstream of calcium spiking (Oldroyd and Downie, 2008). In contrast, application of aminoethoxyvinylglycine (AVG), an ethylene synthesis inhibitor, promotes these symbiotic responses (Oldroyd et al., 2001b). The role of ethylene as a negative regulator of nodulation was demonstrated using the ethylene-insensitive skl mutant in M. truncatula (Penmetsa and Cook, 1997). Skl mutants are also affected in auxin transport; suggesting that cytokinin and auxin signaling are ethylene-dependent (Prayitno et al., 2006; Penmetsa et al., 2008). SKL is a homolog of ethylene-insensitive 2 (EIN2), a key member of the ethylene signal transduction pathway in Arabidopsis thaliana (Penmetsa et al., 2008). Medicago skl mutants showed an increased number of infection events with successful infection thread formation and a 10-fold increase in nodules (Penmetsa and Cook, 1997; Oldroyd et al., 2001b). A similar negative regulatory

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role of ethylene was observed in P. sativum and L. japonicus but not in soybean (Glycine max) (Schmidt et al., 1999; Guinel and Geil, 2002; Nukui et al., 2004). Interestingly, S. rostrata, which allows root hair entry under dry conditions and crack entry under waterlogged conditions, possesses a switching mechanism controlled by ethylene concentration. While root hair entry requires low ethylene concentration, the crack entry mode of infection is possible at high ethylene levels (Goormachtig et al., 2004). Jasmonic acid and methyl jasmonate Like ethylene, jasmonic acid (JA), or methyl jasmonate, is a negative regulator of nodulation that affects both early signaling and nodule organogenesis. JA induces Nod factor expression and secretion in rhizobia, such as R. leguminosarum and B. japonicum (Rosas et al., 1998; Mabood et al., 2006). However, JA decreases the responsiveness of root hair cells to Nod factors, and reduces the frequency of calcium spiking. JA also changes the expression pattern of early nodulin genes such as RIP1 and ENOD11 (Sun et al., 2006). JA inhibits nodulation in a dose-dependent manner when applied exogenously and complete inhibition occurs at a 10 μM concentration in M. truncatula. However, such a high concentration does not affect rhizobial growth or Nod factor production (Sun et al., 2006). Abscisic acid In legume nodulation, abscisic acid (ABA) acts at multiple levels by independently regulating both Nod factor signaling in the epidermis, cytokinin-induced cell division in the cortex and nitrogen fixation in mature nodules (Cho and Harper, 1993; Suzuki et al., 2004; Liang et al., 2007; Ding et al.,

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2008; Tominaga et al., 2009). Unlike JA, ABA inhibits Nod factor-induced calcium spiking and early nodulin genes, such as RIP1 and ENOD1, in an ethyleneindependent manner (Ding et al., 2008). ABA negatively regulates not only nodule formation but also nitrogen fixation. The L. japonicus mutant, enhanced nitrogen fixation 1 (enf1), displays low sensitivity to ABA, increased root nodule number, and also enhanced nitrogen fixation by decreasing the nitric oxide production in the nodules. This mutant also had a lower concentration of endogenous ABA than that of wild-type seedlings, indicating the negative role of ABA in nodule organogenesis and nitrogen

fixation (Tominaga et al., 2009). Similar effects were observed in wild-type plants which were suppressed for ABA signaling, either by the overexpression of the dominant negative allele abscisic acid insensitive 1 (abi1-1) from A. thaliana, or by treatment with abamine, an inhibitor of ABA biosynthesis (Ding et al., 2008; Tominaga et al., 2009). In Medicago, mutants of sensitivity to ABA (sta-1) show reduced sensitivity to ABA and are hypernodulators (Ding et al., 2008). A schematic illustration of hormonal regulation of Nod factor signaling, nodule organogenesis, and nitrogen fixation is presented in Figure 20.4.

Schematic illustration of hormonal regulation of Nod factor signaling, nodule organogenesis, and nitrogen fixation. Auxins, cytokinins, gibberellic acid (GA), and brassinosteroids (BR) act as positive regulators in nodule organogenesis. Ethylene, jasmonic acid (JA), abscissic acid (ABA), and salicylic acid (SA) act as negative regulators and affect early signaling, nodulin gene expression, meristem formation, and nitrogen fixation. In Lotus, GA is shown to negatively regulate nodulin gene expression and nodule meristem formation.

Fig. 20.4.


Evolutionary perspectives The diversity and high level of host specificity in legume–rhizobia interactions suggest that legumes exert a high selection pressure on rhizobia. The evolution of rhizobia might have involved different strategies. Horizontal gene transfer of nodulation and nitrogen fixation-clustered genes within a “nod-nif kit” is considered a prime factor in the emergence of rhizobia. One of the rhizobial traits that may have favored such an event is the facultative saprophytic nature of rhizobia, which allows the exchange of genetic material with other soil bacteria (Sullivan et al., 1995; Barcellos et al., 2007). The acquisition of nod-nif genes allows a soil bacterium to infect, nodulate, and fix nitrogen in legumes. The nod-nif kit may have been transferred to a diverse group of soil bacteria via plasmids, phages, or even naked DNA (Sullivan et al., 1995; Rogel et al., 2001; Barcellos et al., 2007). Long-term evolution optimized the symbiotic performances, host range, and competitiveness of rhizobia (Martinez-Romero, 2009). Some of the proposed molecular events leading to the evolution of rhizobia include (1) integration of newly acquired nod-nif genes to fit in the preexisting regulatory circuits of recipient bacteria (Dixon and Kahn, 2004); (2) recruitment of genes necessary for infection, such as, exo, bacA, eps, lps, and celC2, which show restricted distribution in soil bacteria communities (Amadou et al., 2008; Robledo et al., 2008); (3) mechanisms that suppress plant defense responses; (4) duplication and integration of glmS and cysD in nod-box to improve nodulation efficiency; (5) incorporation of allelic variation in nodABC genes for Nod factor length and acylation refinement; (6) recruitment of genes for new Nod factor decorations (nodZ for fucosylation) and a type III secretion system for host range modulation; and (7) replacement of incoming nif genes by their endogeneous counter-

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parts by the recipient bacteria (Masson-Boivin et al., 2009). The emergence of rhizobia from nonrhizobial soil bacteria is well supported by several observations. The phylogenetic tree based on 16S rDNA sequences from selected α-, β-, and γ-proteobacteria contains a mixed population of both rhizobia and nonrhizobia (Masson-Boivin et al., 2009). Essential nod and nif genes are located on symbiotic plasmids or genomic islands that are readily transferable, and, once transferred, these symbiotic genes confer the ability to nodulate legumes to the recipient bacteria both in field and laboratory conditions (Sullivan et al., 1995; Brom et al., 2004). Finally, the core symbiotic genes nodABC are monophylgenetic in origin (Laguerre et al., 2001; Chen et al., 2003). Several species of Burkholderia nodulate legumes with varying levels of host specificity (Sprent, 2007). Some are capable of fixing nitrogen ex planta (Elliott et al., 2007). Although all the early reports were from Mimosoid legumes, there is now evidence that Papilionoid legumes such as Cyclopia (Elliott et al., 2007) and Dalbergia (Rasolomampianina et al., 2005) can also be nodulated with Burkholderia sp. Legumes evolved to occupy a unique niche in the plant kingdom due to their ability to form RNS with rhizobia. Fossil and genetic evidence suggests that legumes evolved about 60 million years ago, possibly by hijacking preexisting mycorrhizal and phagocytosis machineries and exploiting them to infect legume roots. The key mechanisms that legumes may have seized and fine-tuned from their predecessors include (1) the ability to recognize their symbiotic partners; (2) the ability to turn off defense responses against invading symbionts; (3) pollen tube growth, which shares commonality with that of the rhizobia infection thread growth through root hairs in plants; (4) hormonal regulation of cell differentiation; and

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(5) acquiring genes for Lb. The current understanding of the infection mechanisms suggests that Nod factor-dependent root hair entry is evolutionarily younger than crack entry. Rhizobia and other bacteria can penetrate the roots of a variety of plants through cracks; for example, rhizobia are able to enter the cells of potato tissue (Spencer et al., 1994). Similar modes of entry into host tissue was demonstrated in the nonnodulating Caesalpinioid legume Gleditsia triacanthos (Bryan et al., 1996), where the invading bacteria were confined by a hostderived membrane compartment comparable to infection thread material, but failed to penetrate the cells. This infection process is considered the first stage in the evolution of nodulation. Mimosoid legumes, Neptunia plena and Mimosa scabrella, which lack root hair infection, showed intercellular infection threads. In these cases, the mode of entry is through wounds present at the emergence sites of lateral or adventitious roots (James et al., 1992; Sprent, 2007). As with legume nodulation, arbuscular mycorrhization (AM) is a root endosymbiotic association of land plants with glomeromycetous fungi. AM evolved about 400 million years ago and paved the way for the emergence of land plants (Kistner and Parniske, 2002; Wang et al., 2010a). Genetic dissection of AM events in the model legumes, M. truncatula and L. japonicas, indicates that at least seven genes are shared between legume nodulation and AM (Banba et al., 2008; Markmann et al., 2008; Markmann and Parniske, 2009). This set of genes, collectively termed the common symbiotic pathway (CSP) genes in L. japonicus, includes NORK/SYMRK, CASTOR, POLLUX, NUP133, NUP85, DMI3/CCaMK, and IPD3/CYCLOPS. Mutants of these genes in the model legumes are defective for both symbioses. Homologs of NORK/ SYMRK, CASTOR, POLLUX, DMI3/CCaMK, and IPD3/CYCLOPS are conserved in the

majority of land plants and show vertical inheritance (Zhu et al., 2006; Wang et al., 2010a). Among the CSP genes, the NORK/ SYMRK receptor-like kinase has striking structural and functional divergence with respect to its potential to confer symbiotic abilities. Three distinct version of NORK have been identified in angiosperms (Markmann et al., 2008). A full version of NORK in the Rosids lineage possesses a conserved protein kinase domain, a transmembrane domain, a leucine-rich repeat (LRR) domain, a conserved extracellular domain, and an N-terminal region of unknown function. Variations have been observed with respect to the length of the LRR domain and the presence or absence of an N-terminal region across the plant kingdom. Members of the Rosids lineage establish RNS, ARS, and AM associations, while those higher plants with shorter versions of NORK only undergo AM association. Nonleguminous orthologs of other CSP genes, such as the two-ion channels CASTOR and POLLUX, DMI3/CCaMK, and the RNS-specific GRAS domain transcription factor NSP1, were able to partially restore nodulation in rescue assays (Gleason et al., 2006; Godfroy et al., 2006; Heckmann et al., 2006; Banba et al., 2008; Chen et al., 2008, 2009). Similarly, DMI3 homologs from lower plants such as liverworts and hornworts could rescue the AM phenotype in a dmi3 mutant of M. truncatula, indicating a functional conservation of these vertically inherited genes (Wang et al., 2010a). In parallel, legumes probably modified the lateral root genetic program to invent nodule organogenesis. The role of cytokinins and the cytokinin receptor LHK1/ CRE1 in nodule organogenesis is discussed earlier in this chapter. Cytokinin receptors (LHK1–3) are conserved in higher plants and are involved in developmental processes, such as the emergence of the lateral root, root length, and root vasculature,


which structurally resemble actinorhizal nodules. It is hypothesized that legumes acquired the AM symbiosis machinery from their non-nodulating ancestors to mediate symbiont recognition and intracellular infection, and lateral root machinery to control nodule organogenesis, and finetuned it to form functional nodules (Markmann et al., 2008). Applied agricultural implications Rhizobia bioinoculants and Nod factors applications Application of rhizobia as bioinoculants to enhance nodulation in legume plants is a common practice across the world (Herridge et al., 2002). About 2000 tons of rhizobia inoculants worth $50 million are produced annually, and it is estimated to meet the requirement of 20 million hectares of legumes (Singleton et al., 1997). By far, the United States stands as the largest producer of rhizobial inoculant with an annual production of about 1000 tons (Singleton et al., 1997). Seed treatment is the most popular mode of rhizobia inoculation, but other methods such as soil application to seedbed or seedling application as root dip are also practiced (Dart, 1988; Jha et al., 1994). Although rhizobia are ubiquitous in legumegrowing regions, many soils used for legume cultivation lack adequate numbers of highly effective rhizobial strains. Absence of a symbiotically related legume in the recent history of the land, poor nodulation when the same crop was grown on the land previously, legume crop following a nonlegume in a rotation, and land undergoing reclamation are few factors that necessitate rhizobial inoculation (Allen and Allen, 1961). The general recommendation is to apply rhizobial inoculum to the fields with no history of legume cultivation in the past 3–5 years, a

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soil pH of less than 6.0, sandy texture, low organic matter, or flooded for more than a week (Abendroth and Elmore, 2006). Fields planted with soybean for the first time require inoculation of rhizobia to ensure nodulation and to enhance the rhizobial population in the soil (Nelson et al., 1978; Hiltbold et al., 1980). The ability of soybean to form nodules decreased with the length of time since the last cultivation with soybean (Larson and Siemann, 1998). In several instances, the application of rhizobial inoculants significantly increased the crop yield where legumes had never been produced (Schulz and Thelen, 2008; Ruiz Diaz et al., 2009). However, no significant increase in soybean yield was observed due to the application of rhizobia to the fields where soybean was grown in the previous season (Nelson et al., 1978; De Bruin et al., 2010). In addition to the direct applications of rhizobia as bioinoculants to improve legume nutrition, simple application of Nod factors (or lipophilic chitin oligosaccharides [LCOs]) has significant impacts on crop cultivation. In poor soil with a limited rhizobial population, treatments with Nod factors increase the number of nodules per plant (Macchiavelli and Brelles-Mariño, 2004). In the United States, LCO promoter technology®, which utilizes the beneficial effects of rhizobial Nod factor molecules, has been widely popularized by EMD Crop BioSciences (Milwaukee, WI) for promoting growth in economic crops, such as soybean (Optimize 400), peanuts (Optimize LIFT), forage crops (Optimize Gold, Nitragin), and other pulses (Optimize Pulse). Nod factors are capable of triggering responses in crop plants in amounts as low as picomolar concentrations (Spaink, 1995, 1996). Nod factor-induced lateral root formation, which results in root proliferation in the model legume M. truncatula, is dependent on the DMI1/DMI2-mediated signaling pathway (Oláh et al., 2005).

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Breeding legumes for enhanced nitrogen fixation Enhancing the efficiency of BNF in legumes through conventional breeding programs has been pursued over the past decades with some success (Phillips et al., 1971; Mytton, 1984; Nutman, 1984; Herridge and Rose, 2000). There are a few success stories in the breeding strategies for improving nitrogen fixation in legumes. As early as the 1980s, five common bean germplasm lines with superior nitrogen-fixing abilities were registered. The backcross inbred method of population development was utilized to develop superior varieties in common beans with enhanced nitrogen fixation (Bliss and Hardarson, 1993). In this approach, the inbred backcross families were developed by hybridization of an adapted cultivar with a superior nitrogen-fixing parent, with few initial backcrosses followed by successive single seed descent. Similarly, divergent selection for specific nodule enzymes, such as aspartate aminotransferase and asparagine synthetase, was attempted in alfalfa (Degenhart et al., 1992). Recurrent selection was used for improving seed yield and nitrogen fixation in the common bean (Barron et al., 1999). Although the ongoing genetic dissection of model legumes, economically important oilseeds, and grain legumes significantly enriches our knowledge of the molecular mechanism behind nitrogen fixation, their field applications seem to be in the distant future. A tremendous revival of legume breeding programs for the selection of agronomic traits favoring enhanced nitrogen fixation is an urgent need. The research areas that focus on identifying the agronomic traits and developing successful breeding strategies include (1) investigation of carbon and nitrogen allocation in plant tissues; (2) legume– rhizobium interactions and host specificity for superior rhizobial strains; (3) develop-

ment of a simple, rapid, nondestructive, field-based, and cost-effective assays for nitrogen fixation; (4) enhancing symbiotic nitrate tolerance, early nodulation, and delayed nodule senescence; (5) root colonization and saprophytic competence; and (6) stress tolerance and its impact on interactions between the partners (Herridge and Rose, 2000; Graham et al., 2004). In addition to selecting traits for enhanced nitrogen fixation, legume breeding programs must also incorporate other agronomic traits, such as yield attributes, crop stand, adaptability, and disease and insect resistance. Regional preferences for cultivars, cropping systems, day length, and seed characteristics must also be considered (Bliss and Hardarson, 1993). Several studies have investigated variations among species and cultivars regarding traits associated with nitrogen fixation. Legumes, such as soybean, common bean, clover, and alfalfa, show cultivar differences with respect to nitrogen fixation traits, such as nodule number and mass, speed of nodulation, lateral root formation, nodulation postflowering, nitrogen accumulation, acetylene reduction activity, allantoic acid production, and nodule enzymes (Hardy et al., 1973; Rennie and Kemp, 1983; Nutman, 1984; Jessen et al., 1988; Degenhart et al., 1992; Pazdernik et al., 1996; Graham et al., 2004). Of the several approaches, breeding in nitrogen-poor soils for improving symbiotic ability is considered a promising and practical one (Graham et al., 2004). Transfer of root nodule symbiosis to nonlegumes: a feasibility study For several decades, it has been the dream of scientists to develop transgenic cereals and other nonlegumes that can form root nodules with rhizobia. One of the long-term goals of deciphering the molecular mechanism of RNS is to reconstitute the symbiotic


signaling machinery in nonleguminous plants. Albeit extremely challenging, such a transfer of RNS machinery to nonleguminous crops could tremendously help minimize the exogenous application of energy-expensive nitrogen fertilizers. Apart from reducing the cost of cultivation for food, feed, and bioenergy, this strategy would also provide protection for the environment against pollution from chemical fertilizers. This task will be extremely challenging, but the availability of advanced molecular tools in rhizobia and host plants makes this goal more realistic now than ever before. Several approaches could help in reaching this goal. The commonalities between legume RNS and ARS should be considered to identify key components and missing links in non-nodulating plants (Markmann and Parniske, 2009). Likewise, the molecular dissection of dissimilarities between nodulating and non-nodulating legumes seems a promising approach to identify master regulators of RNS, which are missing in nonleguminous plants (Sprent and James, 2007). Molecular dissection of RNS machinery in the nonleguminous plant Parasponia could also provide clues as to the master players in the symbiotic signaling, which non-nodulating plants lack. Attempts to transfer RNS to nonleguminous plants, both mono- and dicotyledonous, have been made since the 1980s (Ridge et al., 1993). Artificial induction of nodulelike structures was obtained in partially macerated rice roots exposed to rhizobia, as well as in Brassica napus (Al-Mallah et al., 1989, 1990). Another attempt was made to transfer RNS to rice by transformation (Zhang et al., 2001). Genes encoding a pea lectin and Parasponia hemoglobin were cloned into a plant expression vector and introduced by particle bombardment into rice calli from immature embryos (Zhang et al., 2001). Although these early attempts to transfer the RNS pathway to cereals were unsuccess-

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ful, they provide a platform to explore further possibilities for successful transfer of root nodule symbiotic machinery to nonlegumes. The high specificity of legume–rhizobia interactions makes it difficult to nodulate one group of legumes with the symbiotic partner of other group. Most rhizobia have a very narrow host range, making studies across species difficult. However, the rhizobial strain NGR234, with a wide host range of 353 legume species representing 122 genera, seems an interesting candidate for the transfer of RNS to nonlegume crops (Pueppke and Broughton, 1999). To reconstitute RNS machinery in nonleguminous plants, the genetic makeup of the host needs to be fine-tuned, to allow major nodulation events such as infection thread formation, intracellular uptake, and the formation of root nodules (Markmann and Parniske, 2009). Prevalence of CSP genes in the majority of land plants suggests that they could be adjusted to accommodate RNS. The homolog of NORK/SYMRK is necessary for actinorhizal interaction in Casuarina glauca and in the cucurbit Datista glomerata (Gherbi et al., 2008; Markmann et al., 2008). Events leading to the intracellular accommodation of the symbiont in all three of these mutualistic interactions share remarkable similarities. Prior to the invasion by the respective endosymbiont, the host cell prepares to accommodate the invading partner by cytoskeletal and organellar rearrangements and nuclear movements (Genre et al., 2005, 2008). The formation of the prepenetration apparatus (PPA) in AM symbiosis, and preinfection threads (PIT) in RNS and ARS present major similarities. Since AM symbiosis is prevalent in the majority of land plants, the components necessary for intracellular accommodation of symbionts may exist in nonleguminous crops already. Therefore, in our opinion, engineering a receptor-mediated perception of nitrogen-fixing symbionts in

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nonleguminous plants is not just a dream and will be possible in the future. The recognition of symbiotic partners by the host is a key factor for the establishment of mutualistic interactions. Such symbiont recognition is mediated by receptor kinases in plants. LysM receptor kinases NFR1 and NFR5 in Lotus and NFP, and LYK3 in Medicago are proven Nod factor receptors. The introduction of Lotus Nod factor receptors into Medicago enables the latter to enter into a symbiotic association with the Lotus symbiont, M. loti. Such an extreme specificity of receptors toward Nod factors needs to be relaxed by genetic manipulations, which would enable the host plant to recognize a wide array of rhizobial species. Homologs of LysM receptor kinases are present in nonleguminous crop plants, such as A. thaliana and rice, where they trigger the defense reaction upon perception of chitin oligomers, a common elicitor of fungal pathogens. Utilizing such preexisting recognition machineries without compromising their defenserelated role presents additional challenges. Alternatively, Nod factor-independent infection strategies, like those observed in certain species of photosynthetic Bradyrhizobia, have also been considered as an avenue for nonleguminous plants. Although it is not clear that LysM receptor kinases might play a role in recognition of yet unknown actinorhizal factors, the dual infection in Parasponia (Ulmaceae) by both Frankia and Nod factor-dependent rhizobia suggests this possibility (Trinick, 1979). The occurrence of endophytic colonization of plants roots by rhizobia has been demonstrated several times over the past decade (GutierrezZamora and Martinez-Romero, 2001; Cocking, 2003; Chi et al., 2005; Singh et al., 2009). This suggests that rhizobia can utilize the preexisting infection machinery in nonlegume plants to colonize them as endophytes. Rhizobial infection and nodule organogenesis are two separable events in RNS.

Genes involved in the spatiotemporal synchronization of these two distinct events are mandatory for successful RNS. Further characterization of mutants such as IPD3/CYCLOPS or NIN might help in identifying the coordinators of epidermal (infection) and cortical (infection and nodule organogenesis) events. In addition to having the genes necessary for rhizobial infection, nodule organogenesis and their coordination, legumes possess symbiosis-specific Lb genes for the protection and function of nitrogenase activity. Homologs of Lb genes are present in the majority of land plants, including the evolutionarily older Bryophytes and Pteridophytes (Garrocho-Villegas et al., 2007). In nonleguminous plants, including rice and maize, homologs of Lb are present as nonsymbiotic hemoglobins (nsHbs). Such nsHbs from Parasponia are expressed in the nodules formed during rhizobial interaction and facilitate the diffusion of oxygen to bacteroids (Appleby et al., 1983; Gibson et al., 1989). The role of nsHbs in symbiosis in actinorhizal plants, such as Causarina glauca, Alnus glutinosa, and Myrica gale, is still unknown (Fleming et al., 1987; Pathirana and Tjepkema, 1995; Suharjo and Tjepkema, 1995). Similarly, Lb genes are induced during AM, but their role in this widespread ancestral symbiosis is unknown. These observations provide encouraging evidence that nsHbs can be utilized in the assembly of the nodulation pathway in nonlegume plants. Together these observations suggest that reconstitution of root nodule symbiotic machinery in nonlegume plants is a feasible yet distant goal. Perspectives With the ability to increase soil nitrogen levels, legumes are a key component in many agroecological environments. Their rich diversity and adaptability make them a


primary choice for crop rotations, intercropping, mixed cropping, or relay-cropping systems. The benefits of incorporating legumes in cropping systems rely heavily on their ability to establish efficient nitrogenfixing symbioses with rhizobia. However, under biotic and abiotic stresses, legumes struggle to develop efficient symbiotic associations. Increased knowledge on the mechanisms allowing the establishment of these symbioses will provide practical remedies to enhance the utility of legumes in suboptimal environments. Continued and focused efforts on developing improved rhizobial inoculums, and breeding methods for superior legume cultivars with enhanced nitrogen fixation, are urgent needs. The ongoing genetic and genomic approaches aiming at deciphering the mechanisms of symbiotic signaling are paving the way for transferring the symbiotic abilities of legumes to nonlegume crops, which will be a major venture for sustainable agriculture in the future. Acknowledgments The authors sincerely thank Kari Forshey and Maxime Magne for critically reviewing this manuscript and Ronald Crandall for his help with the preparation of figures. The financial support for this work was provided by Hatch grant and National Science Foundation grant to JMA. References Abendroth, L.J. & Elmore, R.W. (2006) Soybean Inoculation: Applying the facts to Your Fields, G1622 ed. University of Nebraska-Lincoln Ext., Lincoln. Allen, E.K. & Allen, O.N. (1961) The scope of Nodulation in the Leguminosae. In: Recent Advances in Botany. Vol I, Proceedings of the Ninth International Botanical Congress, pp. 585–588, University of Toronto Press, Toronto. Al-Mallah, M.K., Davey, M.R., & Cocking, E.C. (1989) Formation of nodular structures on rice seedlings by rhizobia. Journal of Experimental Botany 40, 473–478.

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Index

acquisition efficiency, 10–13 Aegilops tauschii, 132 Aegilops longissima, 326 AlaAT, see alanine aminotransferase alanine, 181–182, 184 alanine aminotransferase (AlaAT), 14, 144, 165–191 alkaline soil(s), 338 Allium spp., 296 alternative oxidase, 243 Amaranthus cruentus, 76 amino acid(s), 90, 106, 113 metabolism, 89, 141–143 transporter(s), 90, 205 ammonia-oxidizing bacteria, 52 ANR1, 30 Arabidopsis thaliana, 21, 21, 26, 30, 87–89, 93, 144, 150, 152–153, 170–182, 196, 201–204, 230–238, 244, 248–249, 252, 272, 279, 314, 317, 319, 385–387, 391, 406, 412, 449, 471–472 Arachis hypogaea, 76, 409, 413 462, 464 Arcadia Bioscience, 184 AS, see asparagine synthetase asparagine, 113–114 asparagine synthetase, 170 aspartate amino transferase (AspAT), 170 AspAT, see aspartate amino transferase Aspergillus nidulans, 176 auxin(s), 27, 245, 469, 470 -ethylene interactions, 236

AXR2, 235 AXR4, 30 Azorhizobium spp., 458. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis Azorhizobium caulinodans, 459 Azospirillum spp., 52 β-glucan(s), 113 β-oxidation, 88 Banksia grandis, 238 barley, 112, 183, 324. See also Hordeum vulgare iron uptake, 317 bioavailability of nutrients, 11 biofortification, 325, 327, 335, 351 biofuels, 140, 169 biological nitrification inhibitor, 132 biological nitrogen fixation (BNF), 458–459 nitrogenase, 458–459 nodulation factor(s) (Nod factor(s)), 460–462, 465 biomass, 68 boron, 377, 379–388 availability, 380 crop improvement, 387–388 deficiency symptoms, 380–382 efficiency, 387 function, 380–382 RGII, 382 rhizobium-legume symbiosis, 382 in soils, 380


492

INDEX

boron (continued) transport, 382–384 BOR1, 386 channel-mediated transport, 385–386 translocation, 386–387 uptake, 382–386 vacuolar, 385 Bradyrhizobium spp., 458–459, 462, 470, 478. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis Bradyrhizobium japonicum, 460–461 Brassica spp., 183, 296, 302, 410, 435 Brassica rapa, 22 Brassica napus, 183, 296, 302, 410, 435 Burkholderia spp., 458. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis C3, 14 C4, 14, 69 calcium, 265–280 disorders, 276 nutrition, 277, 285–277 occurrence and availability in soil, 274 physiological function(s), 274–275 salt (sodic) stress, 447–448 structural, 274–275 signaling, 275 transporter(s), 276 uptake and distribution, 275–280 cellular partitioning, 279–280 radial transport, 278 symplastic movement, 278 translocation and distribution, 278–279 uptake, 275–278 Calvin cycle, 76 canopy, 65–82 architecture, 71 fractional interception, 69 nitrogen, 67, 74 photosynthetic capacity, 67, 69 radiation capture, 68–76 radiation interception, 68 rubisco, 74 carbon dioxide, 134, 311, 322 Carex acutiformis, 75 Carya illinoiensis 415 Chamydomonas reinhardtii 323, 412 chelator(s)/chelation, 56, 313 metal, 318

chloride channels (CLCs), 193, 200 chlorine, 388–392 crop improvement, 391–392 deficiency and symptoms of, 388–390, 393–394 function, 389–390, 394 abscisis acid (ABA) synthesis, 394 homeostasis, 390 translocation, 390 antiporters (CLCs), 390 cation chlorine transporter (CCC), 390 zinc iron premeases (ZIP), 392 uptake, 390 chloroplast, 88 CIMMYT, 95, 124, 132–133 CIPK, 206 CKX, see cytokinin oxidase CKX2, 177 climate change, 134, 166, 324 comparative genomics, 150 convection, 28 copper, 392–400 circadian clock genes, 394 complexed with dissolved organic matter ((CuII)-DOM), 392 crop improvement, 400 deficiency, 392 efficiency, 400 ethylene, 394, 397 homeostasis, 395, 398–399 transport, 395, 397–399 transporter(s), 392 COPT, 392, 394, 396, 398 YSL, 400 uptake, 395–397 Crambe abysinnica, 22 crop breeding, 304 drought, 438; see also drought improvement, 5, 7, 6, 211, 326, 351, 387, 391, 400, 413–414, 417, 438, 451, 475 production, 6, 443, 457 Cupriavidus (Ralstonia) spp., 458. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis 458 Cupriavidus taiwanensis, 460 cysteine, 14, 301 cytokinin, 92, 177, 237, 245, 436, 469–471, 474 cytokinin oxidase (CKX), 237

INDEX

decision support systems, 212 MANAGE RICE, 212 MANAGE-N, 212 denitrification, 51, 212 Devosia spp., 458. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis diet, 106, 140, 325–326, 350 diffusion, 432 Dionaea muscipula, 268 dof1, 145, 178 doubled haploid line(s) (DHL), 141 dough extensibility, bread making and baking, 105, 108, 129 drought, 431–441; see also water crop improvement, 438 global food production, 431–432 mycorrhiza, 437 nitrate, 436–437 nutrition, 431–432 relationship between nutrients and plant water, 437–438 magnesium, 438 osmotic balance, 437–438 phosphorus, 438 root growth, 435–436 compaction, 435 partial root zone drying (PRD), 436 transport, 434 water-limited plots, 434 DuPont-Pioneer, 141 economic margin, 126 edaphic environment, 22. See also soil epistasis, 151 Escherichia coli, 176 essential trace elements, 114 ethylene, 92, 237, 245, 394, 397, 470–471 -auxin reactions, 236, 243 exudates, 51–53, 55, 57, 353 fatty acid degeneration, 88 fertilizer management, 168 placement, 36–37 use efficiency, 126, 212 flowering, 86 Flour Fortification Initiative, 325 fossil fuels, 65 Frankia spp., 458

493

Galderia partita, 74 GC-MS, 153 GDH, 176 genetics, 128–138 forward, 143 gene networks, 152 improvement, 15 reverse, 143 variability/variation, 33, 146, 354 Gigaspora rosea, 32 gibberellic acid (GA), 470 gibberellins, 27 gliadins, 108–109, 129 Glomus caledonium, 32 Glomus intraradices, 32 glutamine, 90, 202 synthetase (GS), 13, 142, 144, 147, 149, 156, 166, 179 glutamate synthetase, 142 glutathione S-transferases, 296 glutenins, 108 Glycine max, 76 glycolytic pathways, 242 GOGAT, 142, 144, 169–170, 184–185, 220 Gpc-B1, 73, 93, 131 grain, 103–120 nitrogen concentration (GNC), 128 protein concentration (GPC), 123–124, 128–129, 131 storage proteins, 106, 128; see also seed storage compounds yields, 9, 213 Green Revolution, 169, 325 Grevillea robusta, 238 Hakea serica, 241 harvest index (HI), 7, 14–15, 219 Herbaspirillum spp., 458. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis Hereward wheat, 109–110 heterosis, 129 hexose, 176 HI, see harvest index high molecular mass polymer(s), 110 Hordeum vulgare, 113, 183, 345, 386, 394, 415; see also barley malting, 212 hormone(s), 152, 177, 436, 472 human population, 140

494

INDEX

Illinois High Protein (IHP) maize, 128 Illinois Low Protein (ILP) maize, 128 indole-3-acetic acid (IAA), 236 inputs to organic cropping system(s), 9 iron, 14, 50, 311–334 biofortification, 325, 327 agronomic practice(s), 326 intercropping, 326 plant breeding, 326–327 chelation, 313 nicotinamine synthase (NAS), 313 compartmentation, 318, 320 distribution, 318 ferrirrigation, 324 homeostasis, 320 ferritin, 322 frataxin, 322 interaction(s) with CO2, 322, 324 interaction(s) with light, 322 nutrition, 311 photosynthesis, 323 production, 311 plant nutritional quality, 311 reduction, 314 transcription factor(s), 316 bHLH family, 316–317 FIT1, 316–317 IDEF1 and IDEF2, 316 IRO2, 318–319 transporter(s), 314, 321 FPN2, 318 IRT, 314–316 NRAMP, 320 YSL, 319 ZIP, 315 uptake, 312–315 barley, 317 regulation, 316 rice, 317 Strategy I, 55 Strategy II, 55 use efficiency, 55 Lactuca sativa, 170 landrace, 85 lateral root primordium (LRP), 26 leaf area index, 77 lamina, 72

legumes, 52, 104, 457, 458, 459, 560, 461–463 actinobacteria (Frankia), 458 crop improvement, 475–476 Leguminosae, 459 nitrogen fixation, 141, 182, 410, 457–489 nonlegumes, 476–478 Nod factor(s), 460–462, 470–472 Nod factor perception (NFP), 465, 468, 478 lectin ecto-apyrase(s) (LNPs), 465 nodule, 459, 464–465 aeschynomenoid, 464 determinate (or desmodioid), 464 development, 459–460 evolutionary perspectives, 473–475 indeterminate, 463 lupinoid, 464–465 organogenesis, 462, 465–467, 470, 478 abscisic acid (ABA), 471–472 brassinosteroids (BR), 470 gibberellic acid (GA), 470 hormonal regulation, 467–469 jasmonic acid (JA), 471 physiology, 459–460 nonlegume bacteria, 458, 476 rhizobial infection, 465, 476–477 entry pathway, 469, 478 ethylene, 471 flotillin-like genes, 467–468 infection thread formation, 466, 468, 471 symbiotic signaling, 465–466, 469 soil fertility, 457 symbiosis, 474 arbuscular mycorrhization (AM), 474–475 Leymus racemosus, 132 light extinction coefficient, 69, 71 lin1, 197 localized nutrient supply, 30 Lotus japonicas, 326 low phosphate root (LPR), 234, 249 LPR, see low phosphate root LRP, see lateral root primordium Lupinus spp., 22, 244 Lupinus angustifolius, 23, 31 Lycopersicon esculentum, 170 lysine, 14, 107 macronutrients, see calcium; magnesium; potassium magnesium, 265, 280–287 limitation, 282–283 nutrition, 285–287

INDEX

occurrence and availability in soil(s), 280 physiological functions, 280 cofactor, 281 photosynthesis, 280 transporter(s), 282–283 uptake, 281, 283–284 partitioning, 284–285 translocation, 284 maize, 69, 40, 145, 147, 409, 413, 446, 448, 450 Illinois High Protein (IHP), 128 Illinois Low Protein (ILP), 128 manganese, 49–50, 400–408 crop improvement, 407 deficiency and symptoms of, 401–403 efficiency and variation of, 403 function, 403 homeostasis, 404 in soils, 401–402 translocation, 405, 407 transport, 404 transporter(s), 396 MTM, 401 NRAMP, 401, 405–406 uptake, 404, 407 by roots, 405 use efficiency, 56, 407 vacuolar transport, 406 MapMan, 152 marker-assisted selection (MAS), 151 mass flow, 28–29, 338, 432 MCO, see multicopper oxidase gene Medicago spp., 465, 467, 471–472, 478 Medicago sativa 461 Medicago truncatula, 231, 326, 405, 461, 466–467 Mesorhizobium spp., 458, 461. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis Mesorhizobium loti, 461, 478 methionine, 14 Methylobacterium spp., 458. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis Methylobacterium nodulans, 460 micronutrients, 377; see also boron; chlorine; copper; manganese; molybdenum; nickel micronutrient use efficiency (MUE), 377–379 definition, 378 microorganisms, 52, 55

495

microRNA, 93, 251 milling, 114 miRNA399, 229 molecular markers, 154 molybdenum, 394, 408–414 crop improvement, 413–414 deficiency and symptoms of, 409–410 efficiency, 413 function, 410 ABA biosynthesis, 410 nitrogenase, 458 nitrogen metabolism, 410 sulphite oxidase, 410 xanthine dehydrogenase, 410 homeostasis, 411 in soils, 409–410 translocation, 413 transport, 411 transporter(s), 411 MOT1, 411–412 sulfate, 411–412 uptake, 411–413 variation, 412 Monsanto, 141, 184 multicopper oxidase gene (MCO), 234 mycorrizha, 10, 32–33, 53, 55, 205, 230, 437 15

N-labeling, 156 NADH-dependent GDH, 179 NADH-GOGAT, 220 NAM-B1, 73, 93, 131 NAR2 (NRT3), 198 NHI, see nutrient harvest index nickel, 414–417 crop improvement, 417 deficiency, 415–416 function, 415–416 urea metabolism, 416 homeostasis, 416–417 in soils, 414–415 transport, 416–417 transporter(s), 396, 416–417 NRAMP, 416 YSL, 416 ZIP, 416 uptake, 416–417 use efficiency, 417 nitrate, 12–13, 194 control of water use in roots, 436–437 efflux, 201 transporter(s), 193–210

496

INDEX

nitrate reductase (NR), 142, 147, 156, 180 nitrification, 11, 132 nitrogen; see also nitrogen uptake/capture efficiency; nitrogen use efficiency; nitrogen utilization efficiency canopy, 67 effect on functional properties of wheat, 108 on grain protein nutrition, 103–120 on grain quality, 103–120 on prolamin (hordein) composition, 112 on protein composition, 108 fertilization, 105, 109–110 fertilizer, 65, 105, 139, 166 fixation, 141, 182, 410, 457–489 biological nitrogen fixation (BNF), 458–459 legumes, 457–458 nodule development and physiology, 459–460 rhizobial bacteria, 458 form of, 50 harvest index, 219 high inputs, 131 late acquisition, 131 leaching, 124 leaf, 216 metabolism, 52, 141, 171, 410 mineralization, 171, 215 nutrition, 103 optimal distribution, 75 optimum, 133 partitioning, 71, 75 pools, 72 remobilization, 71, 77, 86–87, 179 storage, 179 sulfur interactions, 303 underlying physiological mechanisms, 215 nitrogen uptake/capture efficiency (NUpE), 10, 124–125, 141,166, 180, 184, 187 nitrogen use efficiency (NUE), 7, 10, 16, 47, 51, 65, 123, 128–129, 130, 141, 165, 211, 215 compensation, 211 crop improvement, 8, 212–214 definition of, 123, 139 genetic improvement in wheat, 125, 128 genetic progress, 166 genetic variation, 129, 218 heterosis, 139–164

molecular genetics, 168 partial factor productivity (PFPN), 10, 15, 124–125 nitrogen utilization efficiency (NUtE), 10, 15, 124–125, 130, 141, 180 Nitromonas spp., 132 nitrous oxide, 65, 166 NMR, 154 non-protein amino acids, 104 NR, see nitrate reductase NRT1, 12, 30, 180, 194, 200, 204 NRT2, 196–197, 200 NUE, see nitrogen use efficiency NUpE, see nitrogen uptake/capture efficiency NUtE, see nitrogen utilization efficiency nutrient(s) availability, 10,13, 32, 51 capture, 10–11, 28, 33, 36; see also nitrogen uptake/capture efficiency remobilization, 83–84, 86 response curve(s), 7 uptake from soils, 21, 29, 57, 432–434 utilization efficiency, 13 nutrient harvest index (NHI), 15 nutrient use efficiency, 5–19, 123–138 O-acetyl-L-serine (thiol)lyase, 301 Ochrobactrum spp., 458. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis “omics,” 139 proteomics, 152 transcription factors MYB, 248 PHR1, 248 transcriptomics, 152–154, 245 Oryza sativa, see rice OsENOD93–1, 145, 177 Panicum miliaceum, 182–183 Parasponia spp., 458, 478 partial factor productivity, 10, 15, 124–125, 168 partitioning dry matter, 72 nitrogen, 71 penetrometer, 26 PEPC, 176, 179–180 Phaseolus spp., 464 Phaseolus vulgaris, 411

INDEX

phosphorus, 11–12, 27, 29, 48, 205, 229–264 acquisition, 27 bioavailability, 11, 33, 39 deficiency, 230, 231, 232 233, 234, 237 fertilizer, 230 mobilization, 55 phosphorus limitation, 243, 245 stress miR399, 253 sugars and microRNA crosstalk, 251–253 ubiquitin-conjugating E2 enzyme (UBC24), 252 uptake, 39, 233 use efficiency, 53 zinc, 340 photosynthesis, 65, 71, 211, 216, 229, 311, 323, 433, 446 photosynthetic capacity, 69 photosynthetic rate, 70 Phyllobacterium spp., 458. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis phytochelatins, 296 PII, 180 plant(s) growth, 6 breeding, 7, 133, 326 plastid transport, 204, 300 pollution, 65, 166, 230 potassium, 48, 265–271 biochemical roles, 267–268 biophysical roles, 268–269 cytoplasmic charge balancing, 268 electrical signaling, 269 homeostasis, 268 efflux, 271 nutrition, 285–287 physiological functions, 267 occurrence and availability in soil, 265–267 translocation and distribution, 271 AKT2,3, 272 SKOR, 272 sub-cellular partitioning, 272 uptake from soil, 270–271 prolamin box, 115 promoter(s), 186 protease, 88 proteasome pathway, 94 proteolysis, 87

497

quantitative trait(s), 125 loci (QTL), 15, 21, 31, 133–135, 146–147, 149, 150–151, 248 low phosphate root, 234, 249 recombinant inbred line (RIL), 141 respiration, 77 rhizobial bacteria, 458–466, 475. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis Rhizobium spp., 458–459, 461. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis Rhizobium-legume symbiosis, 141, 382, 457–459, 465–466, 477 Rhizobium leguminosarum, 462 Rhizopus arrhizus, 56 Rhizosphere, 37–39, 47–61, 205, 239, 313, 353–354, 402 availability of carbon, 51 availability of water, 49 nutrient transport, 48 pH, 50 redox potential, 49 rice, 76, 89, 113, 140, 144, 170, 184, 195, 211–225, 315, 319, 353, 415 breeding, 219 genotypic variation, 217 harvest index, 219 hybrid rice, 217 ion uptake, 317 world production, 213 RNA antisense RNA, 144 interference RNA (RNAi), 144 root(s), 21–45, 47, 432, 435–436 architecture, 10–11, 33–34, 179, 187, 220, 231–232, 234, 237, 353, 435 cluster roots, 238–240, 244 depth, 22–23 extracellular phosphatases, 233 hairs, 55, 235, 238, 462 mutants, 235 lateral, 236, 238, 314, 470, 474 microbe-soil interactions, 32 nutrient uptake, 57, 278, 395, 397, 405 via mycorrizha, 10 via plasma membranes, 10, 385 response to localized nutrient supply, 30

498

INDEX

root(s) (continued) response to phosphorus deficiency, 230 response to salt (sodic) stress, 446 rubisco, 14, 67, 74, 77, 87, 144, 179, 211, 215–216, 220 salinity, 443–455 accumulation in soil, 443–444 crop improvement, 451 H+ATPase, 448 nutrient problems, 443–444 resistance, 451 during reproductive stage, 450 sodic soils, 443–444 two-phase model of salt stress, 444–445 osmotic resistance, 445–446 sodium exclusion strategies, 448–449 hexose, 450 NHX transporter(s), 449 seed storage compounds, 103–120 selenium, 14, 114, 303–304 agronomic fortification, 114 senescence, 83–102 abscisic acid (ABA), 91, 394, 450, 471 hormones, 91, 93 proteolysis, 87 proteosome pathway, 94 regulation of, 91, 93 Shinella spp., 458. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis shuttle breeding, 133 sinks, 14, 179 carbon, 243 iron, 14 selenium 14, zinc, 14 Sinorhizobium spp. (Ensifer), 458–459. See also legumes; nitrogen, fixation; Rhizobium-legume symbiosis Sinorhizobium meliloti, 460 SLN, see specific leaf nitrogen soil, 22, 47, 432; see also edaphic environment fertility, 457–458 limitations to growth, 25 nutrient availability, 10, 48 pH, 338, 402 structure, 48 Sorghum bicolour, 76 specific leaf nitrogen (SLN), 69–70, 74 stay-green, 72–73, 85, 177 stem, 72

storage proteins, 129 gene expression, 115 sulfur, 12, 103, 108, 110–111, 295–309 assimilatory pathways, 298, 300–301 availability in barley, 113 demand, 296 distribution, 298, 301 effect on prolamin (hordein) composition, 112 fertilizer, 296 in grain, 112 limitation, 302–303 nitrogen interaction, 303 nutrition, 103, 295–296 selenium, 303 sulfur-rich protein(s), 111 transporter(s), 12, 297–298 uptake, 298 regulation, 301 use efficiency, 305 Syngenta, 141 synteny, 150 systems biology, 151 TCA, see tricarboxylic cycle acid Thlaspi arvense, 344 Thlaspi caerulescens, 319 Thlaspi japonicum, 416 tillers, 217 transcription factors NAC, 94 SCARECROW, 238, 466 WRKY, 93 transcriptome, 16, 152 transgenic crops, 143, 172–176, 327 transport, 90, 176, 193 peribacteroid membrane, 203 plastid, 204, 300 transporter(s) amino acid, 90, 205 ammonia, 203 ammonium, 201 uptake by roots, 202 boron, 386 copper, 392 dicarboxylic acid, 194 iron, 314 FPN2, 318 IRT family, 314–316 phytosiderophore complexes, 313 yellow stripe 1 (YSL), 313, 319, 335 ZIP, 315

INDEX

MATE, 12, 30, 180, 194, 198, 200 molybdenum, 299, 411 MOT1, 416–417 nickel, 416 NRAMP, 416 YSL, 416 ZIP, 193–210 nitrate (NRTs), 193–210 NRT1, 12, 30, 180, 194–196, 200, 204 NRT2, 196–197 post-translational regulation, 199 two-component, 198 regulation, 198 vacuolar, 200 peptide, 194, 196 phosphate, 12, 90, 233, 241 sulfate, 12, 297–298 vacuolar antiporters, 279, 390 boron, 385 calcium, 279 potassium, 266, 269, 279 CHX, 272 NHX, 272 sulfate, 299 zinc phytosiderophore complexes, 344 zinc iron premeases (ZIP), 344 tricarboxylic acid (TCA), pathways, 176, 242 trichoblasts, 235 Triticum spp., see also wheat Triticum aestivum, 394 Triticum durum, 132 Triticum turgidum spp. durum, 73 Triticum turgidum var. dicoccoides, 131 vacuoles, 13, 200, 203 VfAAP1, 177 Vicia faba, 177 Vitis vinifera, 409, 411, 413 water, 49 drought, 431–441 hydraulic conductivity, 434 interaction with ion fluxes, 432–433 in soils, 432–434 in roots, 432–433 wheat, 71, 73, 103, 111, 123, 127, 131–132, 140, 345, 394; see also Triticum spp. breeding, 123 functional properties, 111

499

genetic improvement of NUE, 123 yields, 127 xenobiotics, 296 yield, 7 gap, 7 grain, 9, 213 potential, 7 quality in grain, 9, 212 YSL, 319, 327, 335, 345, 400, 416 zinc, 14, 335–375 availability, 339 biofortification, 351 crop improvement, 351, 360 deficiency, 345–346 correction of, 346 drought tolerance, 349–350 efficiency, 351–353, 355 genetics of, 359, 361 screening for, 356–358 upregulated genes, 360 enzymes, 347 fertilizers, 336, 346–349, 356 functions, 336, 342–343 genotypic variation in seeds, 355 heavy metal ATPase (HMA) family, 344 homeostasis, 354 metal response element-binding transcription factor-1 (MTF1), 354 interactions with other soil nutrients, 340–341 limitation, 335, 337, 344 nutrition, 350 phosphorus interactions, 340 phytate, 360 phytosiderophore complexes, 335, 344 reactive oxygen species (ROS), 343 in soils, 337 fractions, 337 organic matter, 339 pH, 338–339 predicting deficiency, 342 superoxide dismutase (SOD), 350 translocation, 343 uptake, 338, 343 yellow stripe 1 (YSL), 335 zinc iron permease (ZIP), 344

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