Biosensors for Environmental Monitoring

Title : Biosensors for Environmental Monitoring author : Bilitewski, Ursula.; Turner, Anthony P. F. publisher : Taylor & Francis Routledge isbn10 | asin : print isbn13 : 9780203352939 ebook isbn13 : 9780203303856 language : English subject Environmental monitoring, Biosensors, ram--Environnement--Surveillance, ram-Biocapteurs. publication date : 2000 lcc : QH541.15.M64B58 2000eb ddc : 628.5/028/7 subject : Environmental monitoring, Biosensors, ram--Environnement--Surveillance, ram-Biocapteurs.

BIOSENSORS FOR ENVIRONMENTAL MONITORING

BIOSENSORS FOR ENVIRONMENTAL MONITORING Edited by Ursula Bilitewski Gesellschaft für Biotechnologishe Forschung mbH Braunschweig, Germany and Anthony P.F.Turner Cranfield Biotechnology Centre Cranfield University UK

harwood academic publishers Australia • Canada • France • Germany • India • Japan • Luxembourg Malaysia • The Netherlands • Russia • Singapore • Switzerland

This edition published in the Taylor & Francis e-Library, 2004. Copyright © 2000 OPA (Overseas Publishers Association) N.V. Published by license under the Harwood Academic Publishers imprint, part of The Gordon and Breach Publishing Group. All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying and recording, or by any information storage or retrieval system, without permission in writing from the publisher. Printed in Singapore. Amsteldijk 166 1st Floor 1079 LH Amsterdam The Netherlands

British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library. ISBN 0-203-30385-7 Master e-book ISBN ISBN 0-203-35293-9 (OEB Format) ISBN: 90-5702-449-7 (Print Edition)

CONTENTS Contributors 1. Introduction U.Bilitewski and A.P.F.Turner 2. Technical Principles U.Bilitewski 2.1. Electrodes F.Lisdat and F.W.Scheller 2.1.1. Introduction

ix 1 5 5 5

2.1.2. Potentiometric Transducers

6

2.1.3. Amperometric Transducers

12

2.1.4. Impedance Measurements

20

2.1.5. Concluding Remarks

24

2.2. Optical Sensors G.Gauglitz 2.2.1. Introduction

28

2.2.2. Classification of Optical and Transduction Principles

30

2.2.3. Trends

45

2.3. Flow Injection Analysis U.Bilitewski 2.3.1. Introduction

51

2.3.2. Selected Components of FIA-Manifolds

52

2.3.3. Dispersion

57

2.3.4. Conclusion—Focussing on Biochemical Applications

58

3. Biochemical Principles U.Bilitewski 3.1. Enzyme Assays 3.1.1. Enzyme Substrate Determination A.Warsinke 3.1.2. Enzyme Inhibitors B.Leca, T.Noguer and J.-L.Marty 3.2. Microbial Sensors K.Riedel, G.Kunze, M.Lehmann and A.König

28

51

61 61 61 76 87

3.2.1. Introduction

87

3.2.2. Design and Function

87

3.2.3. Improvement of Selectivity of Microbial Sensors

93

3.2.4. General Considerations of Application

99

Page vi 3.3. Immunoassays B.Hock 3.3.1. Antibody Structure 3.3.2. Polyclonal Antibodies 3.3.3. Monoclonal Antibodies 3.3.4. Recombinant Antibodies 3.3.5. Binding Properties of Antibodies 3.3.6. Immunoassays 3.3.7. Data Processing and Statistics 3.3.8. Cross-Reactivities 3.3.9. Conclusions 3.4. DNA Based Biosensors J.Wang 3.4.1. Introduction 3.4.2. DNA Structure 3.4.3. Sequence Specific Hybridization Biosensors 3.4.4. Detection of Small Analytes Interacting with DNA 3.4.5. Conclusions 4. Water Analysis I.Katakis, M.Campàs and E.Domínguez 4.1. Pesticides U.Bilitewski 4.1.1. Enzymatic Systems T.Noguer, B.Leca and J.-L.Marty 4.1.2. Affinity Sensor Systems G.Gauglitz, J.Piehler and U.Bilitewski 4.2. Biochemical Oxygen Demand (BOD) K.Riedel, M.Lehmann and G.Kunze 4.2.1. Introduction 4.2.2. Structure and Function of the BOD Sensor System 4.2.3. Problems of Practical Use and Comparison of Sensor-BOD and BOD5 4.2.4. Conclusion 4.3. Other Organic Pollutants 4.3.1. Enzymatic Biosensors I.Katakis, M.Campàs and E.Domínguez 4.3.2. Microbial Sensors for Determination of Aromatics and their Halogenated Derivatives

105 105 108 110 112 115 116 120 122 122 124 124 124 126 132 133 137 140 141 150 165 165 165 168 179 182 182 192

K.Riedel, T.Bachmann and R.D.Schmid 4.3.3. Other Types of Sensors for Organic Pollutants I.Katakis, M.Campàs and E.Domínguez 4.3.4. Conclusion I.Katakis, M.Campàs, E.Domínguez and K.Riedel 4.4. Heavy Metals R.E.Williams, P.-J.Holt, N.C.Bruce and C.R.Lowe 4.4.1. Introduction

4.4.2. Current Analytical Methods 4.4.3. Bioassays Using Whole Cells/Organisms 4.4.4. Engineered Microorganisms as Sensors 4.4.5. Sensors Using Biological Molecules 4.4.6. Concluding Comments 4.5. Phosphate A.Warsinke 4.5.1. Introduction 4.5.2. Phosphate as Inhibitor 4.5.3. Phosphate as a Second Substrate 4.6. Nitrate A.Warsinke 4.6.1. Introduction 4.6.2. Enzyme Sensors for Nitrate Determination 5. Analysis of Soil S.Kröger and A.P.F.Turner 5.1. Sampling K.Cammann and W.Kleiböhmer 5.1.1. Introduction 5.1.2. Sampling Strategies 5.1.3. Sampling Protocol 5.1.4. Sampling Depth 5.1.5. Collection of Samples and Sample Transport 5.1.6. Sample Homogenization, Drying, Partition 5.1.7. Sampling Documentation 5.1.8. Summary 5.2. Biosensors for Pesticides and Organic Pollutants in Soil S.Kröger and A.P.F.Turner 5.2.1. Introduction 5.2.2. Detection Methods 5.2.3. Sample Preparation 5.2.4. Pesticides 5.2.5. Organic Pollutants 5.2.6. Biosensors and Organic Solvents 5.2.7. Unconventional Detection Methods

203 211 213 213

216 218 218 219 222 226 226 227 228 235 235 235 239 239 239 241 243 243 245 246 247 247 248 248 250 251 254 265 268 274

5.2.8. Concluding Remarks 6. Gas-Phase Enzyme Electrodes M.J.Dennison and A.P.F.Turner 6.1. Background 6.2. Gas-Phase Biosensors 6.3. Phenol 6.3.1. Sources of Phenol Pollution 6.3.2. Phenols and Air Pollution 6.3.3. Health Effects 6.3.4. Polyphenol Oxidase

6.3.5. Biosensors for Phenol Monitoring 6.3.6. Phenol-Vapour Biosensors 6.4. Formaldehyde 6.4.1. Health Effects of Formaldehyde 6.4.2. Formaldehyde Dehydrogenase 6.4.3. Enzymatic Assays for Formaldehyde 6.4.4. Biosensors for Formaldehyde Vapour 6.5. Ethanol-Vapour Sensing 6.5.1. Biological Elements for Sensing Ethanol 6.5.2. Biosensors for Monitoring Liquid-Phase Ethanol 6.5.3. Biosensors for Monitoring Ethanol Vapour 6.6. Conclusions 7. Chemical Analysis 7.1. Sample Handling and Analysis of Organic Pollutants in Water Matrices S.Lacorte, D.Puig and D.Barceló 7.1.1. Introduction 7.1.2. Strategies for Sample Handling 7.1.3. Chromatographic Techniques 7.1.4. Biological Techniques 7.1.5. Quality Assurance 7.1.6. Conclusions 7.2. Inorganic Compounds 7.2.1. Heavy Metals K.Cammann, W.Buscher, C.B.Breer, H.G.Riepe, B.Rosenkranz and T.Twiehaus 7.2.2. Determination of Nitrate in Waste Water with Chemical Sensors and Modern Separation Techniques K.Cammann, U.Krismann, B.Ross and W.Kleiböhmer 8. Conclusion A.P.F.Turner and U.Bilitewski

277 285 285 286 287 287 287 288 288

290 291 292 293 293 294 294 295 296 297 300 302 309 309 309 311 324 347 351 357 368 368 392

405

Page 1

1. INTRODUCTION URSULA BILITEWSKI and ANTHONY P.F.TURNER The area of Biosensors has been an active field of research for over 30 years. Initially mainly stimulated by the needs of medical analysis to determine well-defined compounds, such as glucose, in complex media, such as whole blood, biosensors have now found wide applications in fields such as bioprocess monitoring, food and environmental analysis. The development and application of biosensor systems is attractive because of specific features of biochemical reactions, which are well-known and utilized in analysis already since several decades, namely as enzyme assays, immunoassays or bioassays. Generally the recognition of an analyte by a suitable biological molecule is rather specific, which means that only a limited number of compounds will be recognised and specific quantification is often possible even in the presence of chemically related compounds. In addition the affinity of the receptor to the analyte and, in the case of a catalytic system, its chemical turnover are so high that a rather sensitive determination is possible. When combined with a transducer, the biochemical reaction is transformed into an electrical signal, allowing its immediate use for documentation and control. Transduction is not limited to optical methods, which are the classical methods of detection in biochemical analytical assays and which may be prone to interference from the sample matrix, but can also be achieved by using electrochemical, thermometric or piezoelectric principles, thus avoiding separation from particles often required in biochemical assays. Because in biosensors enzymes, whole cells, antibodies, receptors or nucleic acids used as receptors are immobilized, they can be re-used and the resulting biosensors can be applied to a number of samples. There is already a huge number of publications in the biosensor field, ranging from books describing the fundamentals of biosensors (e.g. Turner, Karube, Wilson, 1987; Scheller, Schubert, 1989; Hall, 1990; Buerk, 1993; Kress-Rogers, 1997), proceedings of biosensor meetings (e.g. GBF-workshops on biosensors or EC Climate+Environment), scientific journals (e.g. Biosensors and Bioelectronics, Elsevier) and series (e.g. Advances in Biosensors, JAI Press) entirely devoted to biosensortopics to monographs aimed at the description of the state of the art for a specialist field of application, e.g. food analysis (Wagner, Guilbault, 1994) and bioprocess analysis (e.g. Freitag, 1996) and scientific publications in analytical journals (e.g. Analytica Chimica Acta, Electroanalysis, Analytical Chemistry, Analyst) or application-oriented journals (e.g. J. of Biotechnology, J. Food and Agric. Chem.). These numerous publications reflect the flexibility in the design of biosensor systems, which allow to deal with requirements of the different fields of application. As mentioned above biosensor research was stimulated by the needs of medical analysis and has expanded to field such as bioprocess, food and environmental analysis. Each of these fields of application has its own unique requirements with respect to the analytes to be determined, the concentration ranges of analytes, sample matrices and the desired speed and frequency of analysis. Moreover, in each field there exist different regulations, either legal or just by convention, which analytical procedures have to meet. As a consequence, analytical protocols and in particular biosensors

which have been established for one application are often useless in other surroundings. The simplest biosensors are those where the biochemical element is immobilized directly on the transducer and the resulting sensor can be placed directly in the untreated sample giving near immediate results. However, such simple systems are rather rare in practice and limited to some glucose sensors developed for blood analysis. The reason is that the development of such sensors requires fundamental research on the different steps involved in biosensor development and these basic investigations are to be repeated for each biosensor for each application. Among others the parameters to be investigated include: • the biological element to obtain the desired specificity of the sensor; • the immobilization of the biological element to keep it active and stable for a sufficiently long time; • the process of immobilization to facilitate industrial fabrication of the sensor; • the interface between the transducer and the immobilized biological element to achieve reproducible monitoring of the biochemical reaction; • the performance of the transducer, as its specificity and stability should be sufficient not to counteract the specificity and stability of the biochemical element; • the constant accessibility of the biochemical element in its immobilization matrix to the analyte, as constituents of the sample matrix may form an impermeable membrane on top of the sensor with increasing use; • the analytical range of the sensor to meet the requirements of the samples to be investigated. Moreover, not all biosensors can be as simple as glucose sensors based on glucose oxidase. This is particularly relevant for sensors based on bioaffinity interactions, as only some years ago transduction principles were established allowing the determination of the affinity reaction by simple assay formats (see Chap. 2.2.). Usually not-catalyic biochemical reactions require complex assay principles to result in a signal which can be electrically recorded (see Chap. 3.3, 3.4.). In addition, to reduce the research efforts on the sensor itself with respect to adaption to special requirements of samples, manipulations of the samples are tolerated, such as dilution, filtration, extraction and enrichment of analytes. However, strategies were established to achieve automation of these sample pretreatment protocols thus minimizing the manual laboratory work during analysis (see Chap. 2.3.). Thus, the sensors are often integrated in more complex devices and the idea of a biosensor as a device, which is simply placed into the sample and delivers the analytical information, has only been realised, to date, for a few applications. As a consequence of the various achievements and aspects in biosensor research it is impossible to cover all within one book. Therefore, we present here an overview on the current state of the art of the use of Biosensors for Environmental Monitoring, as this area is at present a rather active area of research for example stimulated by national and European research programs.

Among the various fields of application biosensors have attracted special attention in environmental analysis as there is an increasing concern about pollution of the environment with toxic chemicals. Although conventional chemical analytical procedures have also been improved during recent years with respect to sensitivity, reliability, automation, etc. they often require sophisticated, expensive instruments operated by skilled personnel (see Chap. 7.). Biosensor systems promised to allow analysis of samples by simpler and cheaper methods resulting in a more frequent, perhaps even quasi-continuous analysis, thus reducing the risk for hazardous accidents or criminal poisoning of the environment. However, the total analysis of a sample is increasingly less feasible, independent on the method of analysis, as the list of compounds found in environmental samples expands and information about the toxicity of samples is still demanded. Summing parameters have been defined to avoid the necessity of determining each single compound (e.g. total organic carbon, chemical and biochemical oxygen demand) and biological methods are already well-established in environmental analysis, using bacteria or whole animals (daphnia, fish) to evaluate the toxicity of samples. However, there is also increasing ethical concern about the use of animals as indicators of toxicity, and investigations with respect to the utilization of less complex biological elements are a logical consequence. Thus, work was initiated on the applicability of well-defined microbiological strains, isolated enzymes, antibodies and, more recently, isolated receptors and nucleic acids. Based on this a variety of biosensor systems designed for application in environmental analysis can now be found in the literature and some of these (especially the whole-cell systems) have been commercialized. The following chapters describe first technical fundamentals, i.e. the principles of electrochemical and optical transduction (Chap. 2.1, 2.2.), as these are the most wide-spread and important transduction principles, and of principles used for the design of automated analytical instruments (Chap. 2.3.). Due to the diversity of biochemical principles used in biosensor systems for environmental monitoring an explanation of the fundamentals of the different biochemical approaches follows (Chap. 3.). The second part of the book is devoted to examples of biosensor systems from the different environmental compartments, i.e. water (Chap. 4.), soil (Chap. 5.) and air (Chap. 6.); the analyis of water is the most often cited field of application due to its prominence in legislation and the preference for an aqueous phase in biochemical analysis. The analysis of soil and air is of increasing importance and mainly for soil analysis often the same systems as in water analysis are used in combination with sample pretreatment procedures, such as extraction. Thus, some comments on sampling strategies (Chap. 5.1.) and the use of organic solvents are also included as these are of special relevance in soil analysis due to the heterogeneity of soil. Finally, methods of chemical analysis are described (Chap. 7.) to allow a comparative assessment of the possibilities and limitations of chemical and biochemical analytical approaches.

REFERENCES

Buerk, D.G. (1993) Biosensors Theory and Applications. Lancaster, USA: Technomic Publishing Comp. Inc. Freitag, R. (1996) Biosensors in Analytical Biotechnology. London, UK: Academic Press. Hall, E.A.H. (1990) Biosensors. In Biotechnol. Ser., Milton Keynes, UK: Open University Press. Kress-Rogers, E. (1997) Handbook of Biosensors and Electronic Noses, Boca Raton, USA: CRC Press. Scheller, F. and Schmid, R.D. (1992) Biosensors: Fundamentals, Technologies and Applications. GBF-Monographs Vol. 17, Weinheim, Germany: VCH. Scheller, F. and Schubert, F. (1989) Biosensoren. Germany: Birkhäuser-Verlag. Schmid, R.D. and Scheller F. (1989) Biosensors Applications in Medicine, Environmental Protection and Process Control. GBF-Monographs Vol. 13, Weinheim, Germany: VCH. Turner, A.P.P., Karube, I. and Wilson, G. (1987) Biosensors Fundamentals and Applications. Oxford, UK: Oxford Science Publications, Oxford University Press. Wagner, G. and Guilbault, G.G. (1994) Food Biosensor Analysis. New York, USA: Marcel Dekker, Inc.

Page 5

2. TECHNICAL PRINCIPLES URSULA BILITEWSKI Characteristic features of biosensor systems, such as sensitivity, specificity, influence of sample matrix, measuring frequency, are strongly influenced by technical details of the total system. These include the transduction principle, the fabrication technology of the transducer, the degree of automation, etc. Therefore in this chapter the fundamentals of the most wide-spread transduction principles and some aspects leading to automated analytical devices will be mentioned. The first biosensors described were enzyme electrodes being a combination of glucose oxidase with an oxygen or a hydrogen peroxide electrode and still today electrochemical transduction is of major relevance when developing enzyme sensors. That is why the electrochemical fundamentals are described here. In biochemical assays photometry is the major transduction principle, and optical transduction has developed into a major principle also in the field of biosensors. This was mainly due to the availability of optical fibres and decreasing prices for lasers, laserdiodes and optical detectors. Moreover, besides the classical optical principles of fluorescence and absorbance new principles were established based on the evanescent field moving optical detection from volume-based to surface-sensitive measurements. This made them ideally suited as transducers in affinity sensor systems, where they have found major application. Thus, in Chap. 2.2. optical transduction principles are described, focussing however on those being used in affinity sensor systems. As final part (Chap. 2.3.) the principles of flow injection analysis will be described, as they form the basis of most automated biosensor systems. 2.1. ELECTRODES

FRED LISDAT and FRIEDER W.SCHELLER 2.1.1. INTRODUCTION

Considering the number of published papers on biosensors as well as the types of commercialised sensors, electrochemical systems appear to be the most favoured transducers. Electrochemical transduction means that the biological recognition or conversion event is transferred to an electrical signal, which might be a current or a potential. Thus, two types of electrode systems can be distinguished: amperometric and potentiometric. A third group are impedimetric transducers, which detect impedance changes resulting from the analyte interaction with the receptor molecule. In the simplest case these are changes in the conductivity within the medium. Electrochemical methods provide a direct relation between the electrical signal measured and the concentration of charged or uncharged species in solution. In most cases equipment is not sophisticated, but precise and versatile measurements are provided. Furthermore, electrodes are well suited to sensor miniaturisation and by means of semiconductor industry techniques, systems can be mass produced in a defined way.

Analytical information can be transferred from the biomolecule to the transducer by secondary chemical signals (substances produced or consumed by the receptor molecule and detected with an electrochemical system) or by direct electron transfer between the biomolecule and the electrode (Turner et al., 1987; Scheller and Schubert, 1992). The latter approach (direct protein electrochemistry) has gained considerable interest in the literature (e.g. Tarasevich, 1985; Guo and Hill, 1991; Gilmanshin, 1993; Schmidt et al., 1991; Ikeda, 1997) but application for environmental control is rather limited. Therefore, this chapter will concentrate on the first approach. Alternatively to the detection of secondary chemical signals, the direct observation of analyte interaction with a biomolecule is accessible by means of impedance spectroscopy, the basics of which will be described in the last section of this chapter. Application of electrochemical transducers in biosensors for environmental analysis can be seen mainly in two directions: First, enzymes are combined with electrodes to detect phenolic compounds (the phenolic content of a sample is one of the key parameters for the assessment of an environmental situation) or inhibitors of enzymatic activity are determined. Second, for highly toxic substances such as pesticides or herbicides, which have to be determined in very low concentrations (subnanomolar), immunoassays using enzyme or redox labels are used. 2.1.2. POTENTIOMETRIC TRANSDUCERS 2.1.2.1. Fundamentals

Potentiometry is based on the formation of an electrochemical equilibrium at an electrode under the condition of zero current (Kissinger and Heineman, 1984a; Bard and Faulkner, 1980). The equilibrium reaction is characterised by a charge transfer across the phase interface with the same exchange current density for both directions of the electrode reaction. Depending on the type of charge carrier ion electrodes (anions, cations) and redox electrodes (electrons) can be distinguished. In both cases the electrode potential depends in a defined way on the concentration (or better activity) of the substances involved in the electrode reaction. This dependence is given by the Nernst equation: (2.1.1)

where E is the equilibrium potential of the electrode, E0 the standard potential, ai, the activity product of substances taking part in the electrode reaction, vi is the stoichiometric factor of the individual substances according to the reaction equation, n the number of exchanged charges (electrons, ion charge) and R, T and F are Gas constant, temperature and Faraday constant, respectively. The concentration is correlated to the activity by an activity factor taking into account the deviation from the ideal behaviour by interactions of the particles in solution ( ). Constant activity factors can be reached by using supporting electrolytes or buffer systems. Because of the logarithmic potential dependence on concentration, a large concentration range can be covered by potentiometric sensors (several orders of magnitude). The electrode potential is measured versus a reference electrode. This electrode provides a constant potential in different electrolytes with variable composition so that all changes in the

potential measurement are attributed only to processes at the working or sensing electrode (Ives and Janz, 1961; Lisdat et al., 1990; Sawyer et al., 1995). The most frequently used reference systems are calomel and silver/silver chloride electrodes. According to the electrode reactions for both systems, constant chloride concentration has to be ensured in order to provide a reference potential:

This requirement is fulfilled by establishing a constant chloride ion concentration in solution or by separating the reference half cell using a diaphragm from the electrolyte under investigation. It shall be mentioned that the separation of both electrolytes causes a diffusion potential, which results in a potential error if pH and composition are extremely different in both solutions. Ways to minimize the influence of this “liquid junction” on the potential measurement are discussed in the literature (Sawyer et al., 1995; Kortüm, 1962; Bagg, 1990). They are mainly based on the use of “bridging electrolytes” with the same ionic conductivity for an- and cation. For practical measurements, sensing and reference electrode are connected to a digital voltmeter with high input resistance ( ) and the voltage difference is measured. Standard electrode potentials are defined versus the standard hydrogen electrode, but since this electrode is not used for practical measurements the electrode potentials of the most commonly used reference electrodes vs. the standard hydrogen electrode have been collected in Table 2.1. Among potentiometric transducers ion-selective electrodes and the derived gas-sensitive electrodes are used virtually exclusively for analytical applications in biosensors. This is because the lack of selectivity of redox electrodes, which results in Table 2.1. Potential of several reference electrodes vs. the standard hydrogen electrode. electrode system

potential vs. SHE (V)

Ag/AgCl, KCl(sa)

+0.197

Ag/AgCl, KCl(1 mol/l)

+0.236

Hg/Hg2Cl2, KCl(sa)

+0.241

Hg/Hg2Cl2, KCl(1 mol/l)

+0.280

Hg/Hg2SO4, H2SO4(0,5 mol/l)

+0.679

interference of the electrode potential by other electro-active substances. Reduction of electrode dimensions is not a simple task for potentiomeric sensors but with the use of semiconductor devices miniaturised potentiometric sensor elements can be provided (see ISFET section below). The combination of potentiometric transducers with the biocomponent is based on the detection of products of the biocatalytic analyte conversion. The products might be NH3, CO2 or protons. In the latter case actual pH changes caused by the enzyme reaction near the pH electrode are

detected. However, sensitivity is influenced by the buffer capacity of the solution. Combinations of biocatalysis with subsequent chemical reactions allow the introduction of other ion-selective electrodes as transducers in biosensors (e.g. fluoride-sensitive electrodes for enzymes producing H2O2, which subsequently reacts with a fluororganic compound liberating fluoride ions). 2.1.2.2. Ion-selective electrodes (ISE)

These electrodes make use of a solid-state membrane electrolyte showing an exchange equilibrium for the preferred ion and thus establishing a membrane potential across the membrane-solution interface (Morf, 1981; Camman, 1996; Fry, 1991). The most commonly used ISE is the pH glass electrode. It consists of a glass membrane which on one side is in contact with an outer solution and on the other side with an internal filling solution of known pH. In both electrolytes (internal, external) reference electrodes are inserted (Figure 2.1). The ion-conducting glass forms a surface silicic acid/silicate buffer layer which is in equilibrium with hydrogen ions in solution. Thus a membrane potential is formed on both sides of the glass. Because the internal pH is constant, the electrode potential is only dependent on the pH of the outer solution. (2.1.2)

(2.1.3) Due to the high reaction rate of protons, the pH-glass electrode responds fast to concentration changes in solution and, in addition, covers the largest concentration range among ISEs (10−14– 100 mol/l). As an alternative to the pH-glass electrode, metal oxide electrodes can be used for pH determination. These electrodes are based on the combination of a heterogeneous electron transfer reaction with a chemical reaction. Besides antimony oxide, palladium or iridium oxide electrodes can serve as the basic transducer in biosensors. The electrodes are well suited to miniaturisation, however, their potential is influenced by other redox-active substances. Analogous to the pH-glass membrane, other solid membrane electrolytes (such as ion-conducting polymers, solid electrolytes or liquid electrolytes held in a supporting matrix) can be used for ion-selective electrodes (Morf, 1981). Glasses modified in their composition compared to the pH electrodes give access to the determination of several metal ions such as Na+, Li+, Ca2+, Mg2+, Ag+ a.o. With LaF3 single crystals, doped with EuF2 for ionic conductivity, fluoride ions can be detected. Other examples of ion conductors used as sensing material are silver halides (halide detection) and

Figure 2.1. Cross section of a pH-glass electrode incorporating the external reference electrode into the electrode body. NASICON (Na+ detection). A large group of electrodes uses polymer membranes incorporating ionophores—compounds with binding specificity for a certain ion (by complexation). Based on these membranes, ISEs for several an- and cations can be obtained. For biosensor construction —sensitive electrodes are particularly relevant (because of the use of NH3 forming enzymes). 2.1.2.3. Gas-selective electrodes

Two main kinds of these ISEs can be distinguished with only one having importance in the biosensor field. Solid electrolyte cells (Möbius, 1991) using, for example, ZrO2 as ion conductor between two metal electrodes can be applied to gas detection at higher temperatures (e.g. system O2 (ref.), Pt/ZrO2/Pt, O2 for oxygen sensing). For measurements in solution membrane electrodes are used. These electrodes are derived from the pH-glass electrode; the pH-sensitive glass is covered by a thin liquid electrolyte film and a gas permeable membrane. Gases in the test solution can permeate this membrane, change the pH of the electrolyte film and therefore the electrode potential.

For the detection of gas-forming ions such as or (produced by an enzymatic reaction) the pH of the solution is decisive. To convert these weak electrolytes into the non-ionic form which can pass the gas permeable membrane, pH values of > 10 (for NH3) and < 5 (for CO2) have to be aimed at. These values are often far from the optimum condition of the biocomponent, so that compromises have to be found (lowering the sensitivity of the electrode) or the biocatalytic conversion has to be separated from the potentiometric detection. Such an arrangement can be termed a reactor electrode. 2.1.2.4. Ion-sensitive field-effect transistor (ISFET)

For the miniaturisation of potentiometric sensors chemically-sensitive semiconductor devices (CSSD) are particularly suited. In addition to their small size they have the potential for standardised mass fabrication using techniques from the semiconductor industry. The ISFET is the most extensively investigated representative of this group, which has already found commercial application (Janata and Huber, 1979; Bergveld and Sibbald, 1988; Lundström et al., 1991). The structure is derived from the transistor device MOSFET (metal-oxide semiconductor field-effect transistor). In ISFETs, the metal gate of the MOSFET is replaced by the ion-sensitive membrane in contact with the solution and the reference electrode (Figure 2.2). As for all potentiometric sensors an electrochemical potential is established at the solution/ion-sensitive membrane interface. This potential, which is dependent on the concentration of the potentialdetermining ion, affects via the field effect the current flowing in the inversion layer between source and drain. Two modes of operation can be used for the device. In the first version, the drain-source current (IDS) is held constant by compensating changes of the interfacial potential at the sensitive membrane applying an external voltage via the reference electrode (gate voltage VG). For this mode the output of the device is correlated to the concentration via the Nernst equation as usual for potentiometric sensors. In the second mode, the gate voltage is held constant and changes of the drain-source current due to concentration changes are monitored. The semiconductor device provides the advantage of in-situ impedance transduction. The signal coming from the high impedance line between the bulk of the semiconductor and the reference electrode where no current flows, is transferred to the low impedance line between source and drain where current flow is possible in the interfacial inversion layer of the semiconductor. The dependence of the drain-source current from substances in solution as well as from the design of the device is given by the following equation for the unsaturated region where the source-drain current IDS is a function of the applied voltage VDS: (2.1 A)

µ is the electron mobility, COx the capacitance of the gate insulator, W and L represent the width and length of the channel between source and drain (gate region), is the threshold voltage which includes the standard potential of the electro-

Figure 2.2. Schematic view of an ion-sensitive field-effect transistor (ISFET). 1 is the semiconductor bulk (e.g. p-region), 2 and 3 are source and drain (e.g. n-regions), 4 is the insulator layer (typically SiO2), 5 and 6 are the sensitive layer and reference electrode which are in contact with solution, 7 represents the encapsulation of the device, VG and VDS are the gate and drain-source voltage. chemical reaction. VDS and VG represent the voltage applied between source and drain and the gate voltage, respectively, ai is the activity of the electrochemically active substance in solution and Eref is the potential of the reference electrode. Si3N4, Al2O3 or Ta2O5 are the prefered sensitive layers on the gate region of ISFETs for pHdetermination. Fluoride-sensitive ISFETs are obtained by evaporation of LaF3 on top of the gate insulator and metal ion-sensitive devices use chalkogenide glasses (Pb2+, Cu2+, Cd2+ a.o.), silicate layers (Na+ a.o.) or thin polymer membranes with ionophores (K+, Ca2+, Mg2+ a.o.). ISFETs in combination with a biocomponent are referred to as ENFETs (enzyme FETs) or IMFETs (immunochemically sensitive FETs). From the basic MOSFET structure devices can be also derived for gas measurements (Lundström et al., 1991). The gate metal of the field effect transistor serves as the sensing layer and different metals and mixtures are used for different gases to be detected. For example, palladium gas-FETs which are sensitive to hydrogen can be modified by iridium to become a NH3 sensor. Besides the ISFET, there are other semiconductor devices, like diodes and capacitive elements, which can transform the electrochemical potential, according to the device characteristics, to a current, voltage or capacity (Lundström et al., 1991). However, for biosensor construction they are at the moment of minor importance.

2.1.3. AMPEROMETRIC TRANSDUCERS 2.1.3.1. Fundamentals

Amperometry belongs to the group of voltammetric measurements recording an electrode current as a function of applied potential. For amperometric detection, the electrode is held at a potential for electrocatalytic conversion of the redox-active substance in solution and the resulting steadystate current is measured. At the electrode interface heterogeneous electron transfer occurs between the substance and the electrode (oxidation, reduction). The current measured is not only determined by this redox reaction, but with increasing overpotential (deviation from the redox potential of the substance) mass transport phenomena and concentration polarisation become important (Kissinger and Heineman, 1984b; Bockris and Khan, 1993). At a high overpotential, where the electron transfer reaction is accelerated so that the surface concentration of the substance becomes zero (because all particles transported to the electrode are immediately converted), electrode current is limited by diffusion of the substance through the diffusion layer in front of the electrode (Figure 2.3). Using Fick’s first law of diffusion, the current can be described as follows: (2.1.5)

where n, F and D are number of exchanged electrons, Faraday constant and diffusion coefficient of the redox active substance. A is the electrode area, δ denotes the thickness of the diffusion layer and cS the concentration of the substance in the bulk solution. The formula is only valid if the total conductivity is much higher than the conductivity contribution of the species to be detected so that migration effects can

Figure 2.3. Schematic view of the concentration course in front of an amperometric electrode for the case of diffusion limitation (cEl denotes the surface concentration of the electrochemically active substance, cS the bulk concentration in solution and δ the thickness of diffusion layer). be neglected (i.e. in solutions with supporting electrolyte). The proportionality of the current to the concentration gradient in front of the electrode results in a linear current-concentration

relationship under the condition of constant convection (δ=const.). Therefore, diffusion limitation is the case of choice for most applications. In biosensor application this situation is often achieved by use of a membrane in front of the electrode (e.g. for biomolecule immobilisation) and thus membrane thickness may correspond to the diffusion layer thickness avoiding stirring influences on the electrochemical detection. Amperometric measurements are very sensitive; concentrations from the milli-molar concentration range down to the submicromolar level can be determined. If the electrode reaction is well defined fast response of the electrode can be obtained. The high sensitivity in combination with the high response rate are two of the main advantages of amperometric transducers. There are two different electrode configurations that are suitable for practical measurements. Figure 2.4 shows both the two- and three-electrode arrangements. In general, the use of the threeelectrode system is more advantageous because no current flows through the reference electrode and precise measurements at well defined potentials are possible. However, at low current densities two electrode measurement can be used without any significant disturbance. Reference and counter electrode have to be combined and a large electrode surface and low resistance have to be ensured to avoid electrode polarization and serious potential changes, (see, for example, oxygen electrode below). In amperometry the reference electrode is not as critical for the

Figure 2.4. Electrode arrangements for amperometric detection, A—three electrode measurement, B—two electrode measurement (WE working or sensing electrode, RE reference electrode, CE counter electrode).

measurement as in potentiometry, but because it serves as a basis for the definition of the working electrode potential, the reader is referred to section 2.1.2.1. for more details. Due to the different redox potentials of substances present in the sample, the applied potential at the working electrode is of decisive importance for the selectivity in amperometric detection. If the redox potentials of the analyte and interfering substances are very close to each other, the current measured can no longer be correlated to the analyte concentration alone. Different ways can be adopted to solve this interference problem. By use of an electrode material for which the interferant shows high overpotential, the current-analyte concentration calibration can be reestablished (increase the relation between the analyte determined current and interference current). Another possibility is the introduction of protecting or repelling films which allow the analyte to pass the film (or even to enrich within the film) but strictly limit the access of interferants to the electrode surface (e.g. NAFION as anion exchanger can reject acids such as ascorbic or uric acid). For the same purpose, interference removal by means of an enzyme can be effectively used. Interferants are enzymatically converted into substances which are no longer electro-active at the chosen electrode potential and thus do not disturb analyte detection. Another approach avoids the detection of substrates or products of the biocatalytic conversion and uses redox mediators acting as an electron shuttle between the biomolecule and the electrode. The redox potential of such a mediator is low compared to the interferant so that only the mediator contributes to the measured current. On the other hand, the mediator has to show enough redox potential to transfer redox equivalents from or to the biomolecule in solution (see section mediator modified electrodes below). Oxidases are often used as biochemical receptor elements. Their action during analyte conversion can be followed by measuring oxygen or hydrogen peroxide, which is either consumed or produced in the enzymatic catalysis. Basic transducers for their electrochemical detection will be described in more detail in the following sections. 2.1.3.2. Oxygen electrode (Clark cell)

The principal scheme of an oxygen cell (named after its inventor L.C.Clark) is shown in Figure 2.5. The cell consists of a working electrode (noble metal—Pt, Au) which is insulated and then surrounded by a silver electrode operating as reference and counter electrode. Therefore, the silver is covered at the surface by silver chloride. The electrode compartment is separated from the test medium by a gas-permeable membrane and filled with a chloride containing electrolyte. The working electrode is poised at a potential of −0,6V versus the surrounding Ag/AgCl electrode. If oxygen is present in the test medium it can pass the permeable membrane, diffuse through the electrolyte and is then reduced at the noble metal electrode. The following reactions take place at both electrodes of the cell:

It is obvious that during the amperometric detection of oxygen silver is consumed. Therefore, a small working electrode area is advantageous and a sufficient reservoir of

Figure 2.5. Example of a Clark-type oxygen electrode. silver has to be ensured. This applies especially to miniaturised versions of the Clark cell. The main advantage of the oxygen electrode is that it is free from electrochemical interference effects because the gas-permeable membrane rejects all other constituents in the solution which might interfere with the electrochemical oxygen detection at the electrode. The problem of varying oxygen content in different samples to be analysed can be circumvented e.g. by sample dilution with air-saturated buffer or elegantly by mixing the sample solution with a larger volume of air, thus passing the electrode as an aerosol or by introduction of an additional electrode within the oxygen consuming biolayer producing the same amount of oxygen which is consumed during the biocatalytic conversion. 2.1.3.3. H2O2-measurement

Two or three electrode arrangements can be used as detection systems for hydrogen peroxide. In both cases the working electrode is biased at +0.4 −1 V vs. a Ag/AgCl electrode (depending on electrode material and pretreatment) to force H2O2 oxidation:

For the measurement, the electrode is covered with a dialysis membrane to avoid influence from high molecular weight compounds (e.g. electrode fouling by proteins). The main disadvantage of H2O2 detection results from interference by other electrochemically oxidizable species in solution. Besides the described use of repelling films, differential measurements between enzyme-loaded and enzyme-free electrodes are feasible. Despite the principal problem inherent in these measurements, enzyme electrodes based on H2O2 detection have found widespread application being evidence of the high standard in membrane optimisation (design) used for enzyme immobilisation and interference protection. 2.1.3.4. Mediator modified electrodes

Another way to reduce the interference problem is to reduce the potential at the working electrode. The natural electron acceptor (e.g. O2, cytochrome c) of many oxidoreductases can be replaced by redox dyes or other reversible redox systems transferring redox equivalents from the enzyme to the electrode (Figure 2.6). Examples of typical substance classes for these redox mediators are collected in Table 2.2. For practical use redox mediators have not only to be electrochemically reversible but should also have a well defined electrochemical stoichiometry and a high electron transfer rate (to the electrode and to the biomolecule). They

Figure 2.6. Schematic diagram of the mediated electron transfer from the analyte molecule to the electrode (EOX and MOX denotes the oxidised form of enzyme and mediator and Ered, Mred the reduced form).

Table 2.2. Typical classes of compounds used as mediators in amperometric biosensors. anthraquinones benzoamines benzoquinones ferrocene+derivatives hexacyanoferrate (III) indophenols naphtoquinones phenazines Ru, Os complexes viologenes (e.g. methylviologen MV) charge transfer complexes (e.g. tetracyano-p-chinone dimethane TCNQ—tetrathiafulvalene TTF) should show no non-specific interaction with the biomolecule and have to be stable in both redox states—prerequisites limiting the applicability of some redox dyes. The use of mediators brings an additional advantage into the measurement with oxygen-dependent enzymes; the problem of oxygen fluctuations in the solution under investigation can be overcome and even measurements in oxygen-free solution are possible. In order to minimize problems of mediator solubility and stability as well as avoid mediator addition to the solution, the concept of mediator-modified electrodes was developed. The mediator can be adsorbed onto the electrode surface, enclosed together with the enzyme in a conducting polymer on top of the electrode, covalently attached to the electrode surface or mixed into a carbon paste electrode. In all cases communication with the enzyme has to be ensured and leaching out of the mediator has to be avoided. For further discussions see e.g. Bartlett et al. 1991. The principle of mediated electron transfer to the electrode has also importance for the analytical determination of the coenzyme NAD(P)H. This pyridine nucleotide is the coenzyme for more than 300 enzymes providing access to a large number of analytes. However, the electrochemistry of NADH at metal electrodes is not sufficiently reversible resulting in high overpotentials for its oxidation (~1V). Therefore, interference by other redox active substances occurs and in addition, electrode poisoning by products of the two step oxidation process is observed. In contrast, mediated NADH oxidation allows low electrode potentials and leads to well defined electrochemistry. For the mediator modification of electrodes charge-transfer complexes can be effectively used (“organic salt electrodes” [Bartlett, 1990]). 2.1.3.5. Enzyme modified electrodes

Starting from the concept of mediator fixation, the enzyme itself can be covalently immobilised on the electrode leading to enzyme chemically modified electrodes. This

method provides short diffusion distances and thus achieves high mediation efficiency. A more advantageous method is the combined immobilisation of both the mediator and enzyme onto the same detecting electrode. For analyte determination no additives to the solution are required, resulting in a reagentless measuring system. The efficiency of electron transfer can be further improved by “wiring” the enzyme to the electrode. As “wires” mediator-like molecules can be used which are covalently attached to both the electrode and the enzyme molecule and thus, transferring electrons like a “molecular wire” (Heller, 1992). Redox polymers are also suitable for the construction of this kind of enzyme sensors. With these electrodes one comes to the borderline of direct electron transfer between the enzyme and the electrode avoiding any redox shuttle between the partners. Because of the limited application in the environmental field, the interested reader is referred to extensive presentations in the literature (e.g. Tarasevich, 1985; Guo and Hill, 1991; Gilmanshin, 1993; Schmidt et al., 1991; Ikeda, 1997). The surface immobilisation of enzymes can be effectively used for another type of biosensors. The basic idea can be seen in analogy to redox mediation in enzyme sensors. In contrast, however, the analyte itself is here a redox-reversible substance which can be oxidised or reduced by the electrode and subsequently enzymatically re-reduced or re-oxidised to the original form. Therefore, a redox cycle is formed and the amperometric electrode current can be accelerated by several orders of magnitude resulting in an ultrasensitive detection system (see Figure 2.7). Compared with

Figure 2.7. Scheme of a bioelectrocatalytic amplification system. The analyte is electrochemically oxidised and subsequently enzymatically recycled to be again available for electro-oxidation. This analyte shuttling results in an amplification of anodic electrode current giving access to lower concentration ranges compared to the non-amplified electrode reaction. It should be mentioned that in the redox cycle the partners may be arranged vice versa, i.e. combination of enzymatic oxidation and electrochemical reduction.

conventional amperometric electrodes, the concentration range below 10−7 M down to nanomolar or even subnanomolar concentrations is accessible with these bioelectrocatalytic amplification systems (Wollenberger et al., 1997). This is relevant, for example, for the detection of phenolic compounds in environmental analysis. The application of this type of sensors is limited to analytes which show rather reversible redox behaviour at the chosen electrode material and to systems in which the redox intermediates are not poisoning the electrode. 2.1.3.6. (Ultra)-Microelectrodes

The impetus for miniaturisation of electrodes has come particularly from the medical area and is now a general trend in the field of sensors. The reduction in electrode dimension does not simply lead to decreased signals and problems of reliable measurements, but results in a qualitatively new behaviour compared to measurements with “macroscopic” electrodes (Montenegro, 1994; Heinze, 1993; Aoki, 1993). The term “microelectrodes” (or ultramicroelectrodes) is used when electrode dimensions become smaller than the characteristic diffusion layer thickness. In general this applies to planar electrodes with diameters 0. That means that not all substrate molecules are consumed by the enzyme within the layer. If we apply this model to an enzyme sensor (solid phase=transducer), the sensor works under kinetic control. Small changes of the enzyme activity will influence the sensor signal. If the concentration of the enzyme in the layer is increased (represented by Vmax in Figure 3.5b) the substrate concentration within the enzyme layer decreases rapidly. All substrate molecules are consumed by the enzyme. The enzyme sensor works then under diffusion control. Small changes of the enzyme activity will not influence the sensor signal. Under these conditions a relatively stable enzyme sensor can be constructed, because decreases in enzyme activity can be tolerated for a period. Another possibility to generate a diffusion controlled sensor is to decrease the diffusion of the substrate (Figure 3.5c). Although the enzyme concentration is the same as in Figure 5a the concentration of the substrate decreases to 0 within the enzyme layer. The sensor works under diffusion control. Both methods to reach diffusion control are often realized in membrane enzyme sensors. That is the reason for the extraordinary stability of this type of biosensor. A useful mathematical term which describes whether the velocity of an immobilized enzyme is kinetic or diffusion limited is given by the enzyme loading factor, fe, which is the quadrate of the Thiele module, lα (equation 3.1.23). As an example, in Figure 3.5a

, but in Figure 3.5b and 3.5c

(3.1.23)

Figure 3.5. (A) Substrate concentration profile within an enzyme layer under kinetic controlled conditions; (B) under diffusion controlled conditions by high enzyme loading; (C) under diffusion controlled conditions by restricted diffusion. If the substrate concentration is very high in comparison to the Km value, the velocity of the reaction approximates Vmax. This means that under these conditions the diffusion has no influence. Whether the inner diffusion of the substrate has or has not influence becomes clear, if the linearisation of the Michaelis-Menten equation (e.g. Lineweaver-Burk-Diagram) does not produce straight lines. Sometimes it is difficult to detect such differences. Another possibility exists if the enzymatic reaction is investigated under different temperatures. At low temperatures the enzymatic reaction controls the reaction rate and the Arrhenius plot will give the true energy of activation. If the temperature increases, the velocity of the enzymatic reaction increases faster than the diffusion rate. Then, diffusion controls partly the velocity of the reaction and the energy of activation decreases apparently. Nevertheless, for such experiments control experiments are very important, because differences in the energy of activation can also be caused by other effects (e.g. conformation changes of the enzyme).

3.1.1.6. Substrate measurement with enzyme sensors

Enzymes can be used in enzyme sensors in various configurations. They can be immobilized to a transducer surface in different manner (e.g. by gel entrapment, membrane fixation, covalent linkage, adsorption). Often more than one enzyme are used in enzyme sensors (multienzyme sensors). For instance, if the product or the substrate are not directly transducable, the analyte converting enzyme is often combined with one or more additional enzymes to produce finally a transducable compound. Therefore the enzyme reactions are connected in linear sequences (Figure 3.6a) or competition reactions (Figure 3.6b). Another possibility to make the enzyme

Figure 3.6. A-E Different types of enzyme sensors (see text).

reaction transducable is to use a mediator or to use the direct communication of the enzyme with the transducer, e.g. by optical methods or by “molecular wires” (Figure 3.6c). Other examples for using more than one enzyme are, to trap an interfering substance by an additional enzyme reaction, shift the measuring range to lower concentrations by substrate recycling (Figure 3.6d) or shift the measuring range to higher concentrations by part elimination of the product. For a kinetically controlled enzyme sensor, if the cosubstrate concentration is not limited, the signal depends linear on the substrate concentration below . For this type of enzyme sensor a very thin enzyme layer can be used. The sensor response (described by I2/DPeffective) is very fast (with amperometric transducer the stationary signal can be reached within 5 s), but also very sensitive to changes in enzyme activity, e.g. by pH, denaturation or inhibition. To increase the sensitivity of the sensor it is necessary to increase by using another enzyme with higher , or by immobilization of a higher amount of enzyme (E0). The sensitivity rises until the sensor becomes diffusion limited. A further increase in enzyme loading will not provide a further increase in sensitivity (Figure 3.7), but due to the additional “enzyme reservoir” the sensor becomes insensitive to changes in enzyme activity. In that way, high stability of the enzyme sensor can be reached. The pH optimum is normally broader as for kinetic controlled sensors. Normally a further increase of enzyme loading is accompanied with a thicker enzyme layer and thereby with a decrease in sensitivity and increase in response time. In practice a compromise is used, where the enzyme loading is high enough to reach diffusion control but low enough to have a fast and sensitive sensor. In general, the linear measuring range of enzyme sensors depends on the transducer and the properties of the enzyme layer. Potentiometric sensors normally have detection limits of 10−4M, whereas the detection limits of amperometric sensors are around 10−7 M. The linear measuring ranges of amperometric enzyme sensors are

Figure 3.7. Influence of the glucose oxidase (GOD) loading in a gelatine layer to the sensor response.

usually 10−6–10−2 M. A reason for a reduced linear range can be the diffusion limitation of a cosubstrate, e.g. oxygen in the case of oxidase based sensors. Nevertheless, for many applications (e.g. amino acid, sugar, fat determination in diluted media) the linear ranges fulfil the requirements. To shift the linear measuring range to higher concentrations (e.g. for measurements in undiluted media like whole blood) additional diffusion barriers (e.g. membranes or polymers) can be used. If the linear range has to be shifted to lower concentrations (e.g. for determination of toxic compounds or hormones) substrate recycling can be used. Two enzymes (Figure 3.6d) as well as one enzyme and a transducer (Figure 3.6e) are normally used for substrate recycling. In an initial reaction the analyte is converted to a product, which is then converted back to the analyte by the second reaction. The consumption or production of a cosubstrate is measured. In that way the detection limit can be shifted to 10−9 M. But you must pay for what you get. The linear range is much smaller than for the nonamplified sensor and if the sensor works with the highest amplification, a decrease in stability is normally observed due to the conversion of a diffusion-controlled sensor into a kinetic-controlled sensor. 3.1.1.7. Conclusions

Enzymes have found widespread application for substrate determination. With the development of better enzymes (with respect to stability, kcat, Km, specificity) by screening or by design of artificial enzymes, the potential for bioanalytical techniques has increased enormously. For bioanalytical application, the kinetic constants of an enzyme as well as the reaction to be catalyzed indicates which experimental setup should be used. For high sensitivity and fast response of a biosensor a high and a thin enzyme layer should be used. To reach a high stability the sensor should work under diffusion control. REFERENCES

Farber, G.K. (1995) Laue crystallography. It’s show time. Curr-Biol., 5(10), 1088–90. Highbarger, L., Gerit, J.A. and Kenyon, G.L. (1996) Mechanism of the reaction catalyzed by acetoacetate decarboxylase. Importance of lysine 116 in determining the pKa of activesite lysine 115. Biochem., 35, 41–46. Jencks, W.P. (1997) From chemistry to biochemistry to catalysis to movement. Annu. Rev. Biochem., 66, 1–18. Kirby, A.J. (1996) Enzyme mechanisms, models and mimics. Angew. Chem. Int. Ed., 35(7), 707–724. Pauling, L. (1948) Nature of forces between large molecules of biological interest. Nature, 161, 707–709. Purich, D.L., Abelson, J.N. and Simon, M.I. (1995) Enzyme kinetics and mechanism. Methods in Enzymology, 249, Pt.D., Academic Press.

Radzicka, A. and Wolfenden, R. (1995) A proficient enzyme. Science, 267, 90–93. Segel, I.H. (1975) Enzyme kinetics: behavior and analysis of rapid equilibrium and steady state enzyme systems. John Wiley & Sons, Inc.

3.1.2. ENZYME INHIBITORS

BÉATRICE LECA, THIERRY NOGUER AND JEAN-LOUIS MARTY 3.1.2.1. Introduction

A large percentage of environmental pollutants are known to act as enzyme inhibitors, resulting in the development of numerous pollutant-detection tests based on the measurement of this property. Environmental pollutants are widely dispersed in waterways, air and soil as a consequence of industrial, agricultural and domestic wastes. Among the large number of enzyme inhibitors spread throughout the environment, pesticides and heavy metals are considered to be particularly hazardous compounds, especially in terms of their effects on human health and ecosystem function. These inhibitors, as well as their corresponding target enzymes are listed in Table 3.1. As one would expect, numerous studies have been devoted to the detection of cholinesterase inhibitors made up of organophosphorus and carbamate insecticides (Durand and Thomas, 1984; Mionetto et al., 1992; Palleschi et al., 1992; Sklàdal and Mascini, 1992; La Rosa et al., 1994; Cremisini et al., 1995; Kumaran and Morita, Table 3.1. Principal Inhibitor Families and their Target Enzymes. Inhibitor

Enzyme

Pesticides: insecticides (organophosphorus and carbamate)

cholinesterase, alkaline phosphatase, acid phosphatase, acylase, lipase, chymotrypsin

herbicides (sulfonylureas, triazines)

tyrosinase, acetolactate synthase, peroxidase

fungicides (dithiocarbamates)

aldehyde dehydrogenase, tyrosinase

Heavy metal salts: beryllium

alkaline phosphatase

cadmium

cholinesterase, G-3-PDH, L-LDH, LAP

chromium

L-LDH, G-6-PDH, cholinesterase, pyruvate kinase, hexokinase

cobalt

urease

copper

L-LDH, urease, GOD, cholinesterase, acid phosphatase

lead

alkaline phosphatase, L-LDH

mercury

urease, L-glycerophosphate oxidase, pyruvate oxidase, LLDH, GOD, invertase, cholinesterase, acid phosphatase

silver

L-LDH, GOD, urease

zinc

L-LDH

G-3-PDH: glycerol- 3 -phosphate dehydrogenase; L-LDH: L-lactate dehydrogenase; LAP: leucine aminopeptidase; G-6-PDH: glucose-6-phosphate dehydrogenase; GOD: glucose oxidase.

1995). Cholinesterase has been shown to be sensitive to a variety of heavy metals (Tran-Minh, 1985; Cokugras and Tezcan, 1993; Sklàdal et al., 1996) which have also been reported to inhibit many oxidases and dehydrogenases (Gayet et al., 1993). Spectrophotometry is currently the most widely used method to detect enzyme inhibitors. Nevertheless, this method often involves the use of enzymes in solution, so that the biocatalyst has to be renewed with each assay, thus increasing the cost of performing such measurements. One of the advantages of the biosensor technique of detection, however, is the use of enzymes in an immobilized state, thus allowing for the continuous use of the same enzyme loading. 3.1.2.2. Inhibition of enzymes in solution

In the first part of this review, we will focus on the inhibition of enzymes in solution. For this purpose, will be taken as our primary reference the theoretical aspects of enzyme inhibition described by Segel (1975). Main (1969) described more specifically the kinetics concerning inhibition of cholinesterase by organophosphorus and carbamate insecticides in solution, while Tran-Minh (1985) presented a kinetic analysis for the inhibition of enzymes in both soluble and immobilized states. Depending on their chemical mode of action, inhibitors can be divided into two groups: reversible or irreversible inhibitors. It must be stressed that substrate is required in all cases for the enzymatic determination of an inhibitor. Usually, the amount of substrate is sufficiently abundant so that the rate of the non-inhibited reaction can be considered unchanged and used as a point of reference. Among the different important parameters influencing the inhibition process, pH must be carefully selected as the interaction of the enzyme with the inhibitor is pHdependent. The main characteristics of the different types of inhibition are summarized in Table 3.2. 3.1.2.2.1. Reversible inhibition

Reversible inhibition is characterized by an equilibrium between the enzyme and the inhibitor, defined by the equilibrium constant Ki (dissociation constant of the enzyme-inhibitor complex, , with [E] and [I] representing respectively the concentrations of enzyme and inhibitor) which reflects the affinity of the enzyme for the inhibitor. The reversibility of inhibition implies that there is no need for incubation of the enzyme with the inhibitor. It is possible to distinguish three main types of inhibition depending on the behaviour of the inhibitor in relation to the active site of the enzyme: competitive, uncompetitive and non-competitive. When inhibition occurs, the expression of the enzymatic reaction rate is modified by a term (1+[I]/Ki) which affects either the maximum velocity Vm (non-competitive inhibition) or the affinity constant Km (competitive inhibition) or both of them (uncompetitive inhibition) (Table 3.2). Considering the classical and more commonly used Lineweaver-Burk plot (1/v=f(1/[S])), each type of inhibition can be determined according to modifications in the slope (Km/Vm), the 1/[S] axis intercept (−1/Km), and/or the 1/v axis intercept (1/Vm). Other linear plots such as Hanes ([S]/v=f ([S]) or Woolf-Hofster (v=f(v/[S])) representations can also be used.

Table 3.2. Principal Characteristics of Reversible and Irreversible Inhibitions. Reversible

Irreversible

dissociation (equilibrium) constant Ki

bimolecular rate constant k;

Inhibitor binding mode

non covalent (ionic, Van der Waals…)

covalent

Change in the inhibitor molecule after dissociation

No

Yes

Reactions Inhibition parameter Equations

(hydrolysis, oxidation…) Need of pre-incubation

No

Yes

Reactivation

rapid by washing out the inhibitor

need of special reactivators

Competitive inhibition (Figure 3.8) This type of inhibition occurs when the inhibitor and the substrate are mutually exclusive; the binding of one species prevents the binding of the other. The simplest and more common feature is encountered when the inhibitor sufficiently resembles the substrate to compete for the same active site of the enzyme. More complex models fit the same type of inhibition, as shown in Figure 3.8. In all of the cases, the degree of inhibition decreases when the substrate concentration increases; inhibition can thus be reversed by using very high concentrations of substrate. The equilibria describing competitive inhibition are given below, showing clearly the mutual exclusion of substrate (S) and inhibitor (I) (with E representing the enzyme, Ks=[E][S]/[ES], the dissociation constant of the complex enzyme-substrate, and k, the rate constant for the breakdown of ES to E and P):

Figure 3.8. Models of Competitive Inhibition according to Segel (1975): a) S and I compete for the same binding site; b) steric hindrance prevents the mutual fixation of I and S; c) I and S share a common binding site; d) I and S binding sites are differents but overlapping; e) the binding of one ligand modifies the conformation of the binding site of the other ligand. Kinetically, competitive inhibition affects the slope of the Lineweaver-Burk plots without modifying the maximal velocity ( ), so that the apparent affinity constant (K′m) of the enzyme for the substrate increases when the concentration of inhibitor increases. The inhibition of urease by thiourea can be cited as an example of competitive inhibition that is of interest in environmental monitoring (Tran-Minh, 1985), with thiourea being a degradation product of dithiocarbamate fungicides. Non-competitive inhibition (Figure 3.9) A non-competitive inhibitor binds to the enzyme independently of the substrate, without modifying the affinity of the enzyme for the substrate. The inhibition in this case is thus independent of the substrate concentration. The main mechanisms of non-competitive inhibition are presented in Figure 3.9. The equilibria describing non-competitive inhibition clearly show that I can bind both to E and ES, leading to inactive EI and ESI complexes:

Figure 3.9. Models of Non-competitive Inhibition according to Segel (1975): a) the binding of I does not prevent the binding of S but induces a conformation change of the catalytic center (C); b) the binding of I prevents sterically the binding of S; c) if I binds first, the catalytic site can not align with the substrate, on the other hand if S binds first, it prevents sterically the binding of I. Even at high substrate concentrations, not all of the enzyme can be driven to the ES form. Consequently, a non-competitive inhibitor acts by decreasing the apparent value of Vm, the apparent Km remaining unchanged. Inhibition of acetylcholinesterase (Tran-Minh, 1985) and L-glycerophosphate oxidase (Gayet et al., 1993) by mercury (Hg2+) constitute two examples of non-competitive inhibition that are of environmental concern.

Uncompetitive inhibition (Figure 3.10) In the case of uncompetitive inhibition, the inhibitor does not bind to the free enzyme but to the ES complex, yielding an inactive ESI complex. This type of inhibition generally occurs only when using monosubstrate systems. Contrary to competitive inhibition, the degree of inhibition increases as the substrate

Figure 3.10. Model of Uncompetitive Inhibition according to Segel (1975). I binds only to the complex ES. concentration increases. The equilibria describing uncompetitive inhibition are provided in the diagram below:

The equilibria show that some ESI complex will always be formed, even at very high substrate concentrations. Uncompetitive inhibition does not modify the slope of the 1/v=f(1/[S]) plots but only increases the value of the intercept on the 1/v axis. This results in a decrease in the apparent values of Vm and Km. Examples of uncompetitive inhibition are the inhibition of urease (Tran-Minh and Beaux, 1979) and acetylcholinesterase (Tran-Minh, 1985; Kambam et al., 1990) by fluoride.

Mixed-type inhibitions These inhibitions are derived from the three types of inhibitions previously described. In all cases, mixed-type inhibitions modify both the Km and the Vm values. A simple mixed system is encountered for alkaline phosphatase inhibition by paraoxon, an organophosphorus insecticide (Ayyagari et al., 1995), where the EI complex has a higher affinity for S than for E ( ) and the ESI complex is inactive:

3.1.2.2.2. Irreversible inhibition Due to the irreversible nature of inhibition, the reaction cannot be expressed in terms of an equilibrium situation, but in terms of initial velocity. The main parameter is thus the bimolecular rate constant ki (Table 3.2). The equation of Aldridge is valid when the concentration of inhibitor is much higher than that of the active sites of the enzyme. Contrary to reversible inhibitors, irreversible inhibitors generally act by covalent binding to the enzyme. When the inhibitor binds to the enzyme, the transient complex EI rapidly evolves towards a new irreversible EI′ complex as a result of chemical modifications. For instance, the binding of organophosphorus insecticides to cholinesterases leads to the phosphorylation of the serine residue at the enzyme catalytic center:

Enzyme activity cannot be restored by lowering the inhibitor concentration, and so the enzyme has to be regenerated and reactivated using special agents. Phosphorylated cholinesterases can be reactivated in this way using a powerful nucleophilic compound such as 2-PAM (2pyridinealdoxime methiodide) or TMB-4 ({1,1′-trimethylenebis-4-(hydroxyimino-methyl)pyridinium bromide}):

Heavy metals ions (Table 3.1) can sometimes be considered as irreversible inhibitors due to the very slow reversibility of inhibition. These compounds act by the binding of the metal salt to protein thiol groups (Webb, 1966). Consequently, the main targets of heavy metals are dehydrogenases and oxidases due to the presence of cysteine residues near the active site:

In some cases, enzymes that have been inhibited by heavy metals can be reactivated using complexing agents such as EDTA or thiols (dithiothreitol) (Gayet et al., 1993). Another difference when compared to reversible inhibition is the need to perform a preliminary incubation between the enzyme and the inhibitor, due to the rather slow rate of the inhibition process. For this reason, the degree of inhibition and the sensitivity of the system are directly related to the incubation time. 3.1.2.3. Inhibition of immobilized enzymes in biosensors

Some new problems arise in the use of immobilized enzymes instead of soluble enzymes to detect inhibitors. First of all, the immobilization of an enzyme generally induces conformational modifications that may affect its activity and its sensitivity towards inhibition. Gayet et al. (1993) reported that the inhibition of L-glycero-phosphate oxidase by mercury salts was reversible and non-competitive in solution, and irreversible after immobilization on either a gelatin film or on the surface of an affinity membrane. Moreover, many reports point out that immobilization induces a decrease in the sensitivity of enzymes towards inhibitors (Tran-Minh, 1985; Campanella et al., 1991; Bernabei et al., 1991; Roda et al., 1994; Cremisini et al., 1995). The theoretical aspects of the use of inhibited enzyme electrodes have been discussed by many authors such as Tran-Minh (1985) and Albery et al. (1990a-c). When using biosensors, the inhibition process is influenced by various new parameters such as microenvironmental effects, diffusion limitations and possible interactions between the substrate and/or the inhibitor and the membrane. This sorption effect can be suppressed by the addition of surfactants, thereby increasing the sensitivity of the biosensor towards organophosphorus pesticides (Evtugyn et al., 1996).

Unlike biosensors devoted to the determination of substrates, the detection of inhibitors requires the use of low enzyme loadings in order to detect very low inhibitor concentrations. Consequently, enzyme electrodes used in such assays must work under kinetic control. This concept is not usual in the design of biosensors for substrate determination where high enzyme loadings are used, so that the responses are governed by diffusional constraints. Generally, the detection of inhibitors proceeds in three steps (Figure 3.11a): — the first step is the determination of the initial response (I1) of the biosensor to a sufficiently high concentration of substrate, — the second step consists of the incubation of the biosensor with the inhibitor for a defined period, — the last step is the determination of the residual response (I2) of the biosensor using the same concentration of substrate as in the first step. The degree of

Figure 3.11. Schematic representation of the two possible methods of determination of inhibitors using a biosensor, a) indirect determination: the responses to substrate are measured before (I1) and after (I2) incubation with the inhibitor during a given time, b) direct determination: the inhibitor is added in the medium once the steady state response (I1 to substrate is reached. inhibition (I %) is then calculated by comparing the responses before and after inhibition according to the relation:

This method has been principally reported by Palleschi et al. (1992) and Marty et al. (1992). The main drawback of the procedure is that it is time consuming because it involves two separate measurements of activity as well as an additional incubation step with the inhibitor. Nevertheless, very low concentrations of inhibitor can be detected using this method. Another approach has been described by Sklàdal and colleagues (Sklàdal, 1991; Sklàdal, 1992; Sklàdal and Mascini, 1992). In a first step, an appropriate concentration of substrate is added in the medium. When a steady-state current is reached, a defined concentration of inhibitor is

injected (Figure 3.11b) inducing a decrease in the intensity of the current as function of time (dI/dt). The relative inhibition (RI) is then determined according to the following relation:

In spite of its relative rapidity, this method suffers from a low sensitivity towards inhibitors. This drawback can be related to the fact that the contact time of the enzyme probe with the inhibitor is too short to bring about a noticeable inhibition in the presence of very low inhibitor concentrations. 3.1.2.4. Conclusion

Many enzymes are inhibited by various substances that are known to have an effect on the environment, such as pesticides or heavy metals (Table 3.1). Enzyme electrodes for the detection of various families of environmental pollutants have been widely reported in literature. Such devices are based on the immobilization of the target enzyme, leading to possible modifications in the inhibition process. Among the various reports, cholinesterases have been widely used in the detection of organophosphorus insecticides. These insecticides correspond to irreversible inhibitors, making it necessary to find a way to reactivate the enzyme after inhibition. This has been successfully achieved by using nucleophilic agents such as 2-PAM (Tran-Minh et al., 1990; Mionetto et al., 1994; Marty et al., 1995). Another important family of toxic compounds is represented by heavy metal salts. These are generally detected using immobilized oxidases or dehydrogenases. The restoration of activity of the immobilized enzyme is generally performed by removal of the metallic ions from the enzyme, by complexation with EDTA or dithiotreitol, or by precipitation using an appropriate counter-ion (Tran-Minh, 1985). It must be stressed that, on occasions, some heavy metals may also act as enzyme activators or cofactors, thereby causing an increased activity in the presence of the pollutant. For instance, carbonic anhydrase binds specifically to its cofactor Zn2+ to form the active holoenzyme. A fiber optic sensor using this enzyme is capable of detecting nanomolar concentrations of zinc (Thompson and Jones, 1993). Contrary to chemical methods of detection, enzyme-based methods appear simple and sensitive. However, such devices often suffer from a lack of specificity as various compounds are likely to inhibit enzyme activity. Nevertheless, this poor specificity could be used to advantage in evaluating a global index of toxicity. REFERENCES

Albery, W.J., Cass, A.E.G. and Shu, Z.X. (1990a) Inhibited enzyme electrodes. Part 1: theorical model. Biosensors and Bioelectronics, 5, 367–378. Albery, W.J., Cass, A.E.G. and Shu, Z.X. (1990b) Inhibited enzyme electrodes. Part 2: the kinetics of the cytochrome oxidase system. Biosensors and Bioelectronics, 5, 379–395.

Albery, W.J., Cass, A.E.G. and Shu, Z.X. (1990c) Inhibited enzyme electrodes. Part 3: A sensor for low levels of H2S and HCN. Biosensors and Bioelectronics, 5, 397–413. Ayyagari, M.S., Kamtekar, S., Pande, R., Marx, K.A., Kumar, J., Tripathy, S.K., Akhara, J. and Kaplan, D.L. (1995) Chemiluminescence-based inhibition kinetics of alkaline phosphatase in the development of a pesticide biosensor. Biotechnol. Prog., 11, 699–703. Bernabei, M., Cremisini, C., Mascini, M. and Palleschi, G. (1991) Determination of organophosphorus and carbamic pesticides with a choline and acetylcholine electrochemical biosensor. Anal. Lett., 24, 1317–1331. Campanella, L., Achilli, M., Sammartino, M.P and Tomassetti, M. (1991) Butyrylcholine enzyme sensor for determining organophosphorus inhibitors. Bioelectrochem. Bioenerg., 26, 237–249. Cokugras, A.N. and Tezcan, E.F. (1993) Inhibition kinetics of brain butyrylcholinesterase by Cd2+ and Zn2+, Ca2+ or Mg2+ reactivates the inhibited enzyme. Int. J. Biochem., 25, 1115–1120. Cremisini, C., Di Sario, S., Mela, J., Pilloton, R. and Palleschi, G. (1995) Evaluation of the use of free and immobilised acetylcholinesterase for paraoxon detection with an amperometric choline oxidase based biosensor. Anal. Chim. Acta, 311, 273–280. Durand, P. and Thomas, D. (1984) Use of immobilized enzyme coupled with an electrochemical sensor for the detection of organophosphates and carbamates pesticides. J. Environ. Pathol. Toxicol. Oncol., 5, 51–57. Evtugyn, G.A., Budnikov, H.C. and Nokolskaya, E.B. (1996) Influence of surface-active compounds on the response and sensitivity of cholinesterase biosensors for inhibitor determination. Analyst, 121, 1911–1915. Gayet, J.-C., Haouz, A., Geloso-Meyer, A. and Burstein, C. (1993) Detection of heavy metals salts with biosensors built with an oxygen electrode coupled to various immobilized oxidases and dehydrogenases. Biosensors and Bioelectronics, 8, 177–183. Kambam, J.R., Parris, W.C.V., Naukam, R.J., Franks, J.J. and Rama Sastry, B.V. (1990) In vitro effects of fluoride and bromide on pseudoacetylcholinesterase and acetylcholinesterase activities. Can. J. Anaesth., 37, 916–919. Kumaran, S. and Morita, M. (1995) Application of a cholinesterase biosensor to screen for organophosphorus pesticides extracted from soil . Talanta, 42, 649–655. La Rosa, C., Pariente, F., Hernandez, L. and Lorenzo, E. (1994) Determination of organophosphorus and carbamic pesticides with an acetylcholinesterase amperometric biosensor using 4-aminophenyl acetate as substrate. Anal. Chim. Acta, 295, 273–282.

Main, A.R. (1969) Kinetics of cholinesterase inhibition by organophosphate and carbamate insecticides. Canadian Medical Association Journal, 100, 161–167. Marty, J.-L., Mionetto, N., Lacorte, S. and Barcelo, D. (1995) Validation of an enzymatic biosensor with various liquid chromatographic techniques for determining organophosphorus pesticides and carbaryl in freeze-dried waters. Anal. Chim. Acta, 311, 265–271. Marty, J.-L., Sode, K. and Karube, I. (1992) Biosensor for detection of organophosphate and carbamate insecticides. Electroanal., 4, 249–252. Mionetto, N., Marty, J.-L. and Karube, I. (1994) Acetylcholinesterase in organic solvents for the detection of pesticides: biosensor application. Biosensors and Bioelectronics, 9, 463–470. Mionetto, N., Rouillon, R. and Marty, J.-L. (1992) Inhibition of acetylcholinesterase by organophosphorus and carbamates compounds. Studies on free and immobilized enzymes. Z.Wasser-Abwasser-Forsch., 25, 171–174. Palleschi, G., Berbabei, M., Cremisini, C. and Mascini, M. (1992) Determination of organophosphorus insecticides with a choline electrochemical biosensor. Sensors and Actuators B, 7, 513–517. Roda, A., Rauch, P., Ferri, E., Girotti, S., Ghini, S., Carrea, G. and Bovara, R. (1994) Chemiluminescent flow sensor for the determination of paraoxon and aldicarb pesticides. Anal. Chim. Acta, 294, 35–42. Segel, I.H. (1975) Simple inhibition systems (Chapter 3). In Enzyme kinetics. Behavior and analysis of rapid equilibrium and steady-state enzyme systems, (eds). pp. 100–159. New York: John Wiley & Sons. Sklàdal, P. (1991) Determination of organophosphate and carbamate pesticides using a cobalt phtalocyanine-modified carbon paste electrode and a cholinesterase enzyme membrane. Anal. Chim. Acta, 252, 11–15. Sklàdal, P. (1992) Detection of organophosphate and carbamate pesticides using disposable biosensors based on chemically modified electrodes and immobilized cholinesterase. Anal. Chim. Acta, 269, 281–287. Sklàdal, P., Fiala, M. and Krejci, J. (1996) Detection of pesticides in the environment using biosensors based on cholinesterases. Intern. J. Environ. Anal. Chem., 65, 139–148. Sklàdal, P. and Mascini, M. (1992) Sensitive detection of pesticides using amperometric sensors based on cobalt phtalocyanine-modified composite electrodes and immobilized cholinesterases. Biosensors and Bioelectronics, 7, 335–343. Thompson, R.B. and Jones, E.R. (1993) Enzyme based fiber optic zinc biosensor. Anal. Chem., 65, 730–734.

Tran-Minh, C. (1985) Immobilized enzyme probes for determining inhibitors. Ion-Selective Electrode Rev., 7, 41–75. Tran-Minh, C. and Beaux, J. (1979). Enzyme electrode for inhibitors determination: ureasefluoride system. Anal. Chem., 51, 91–95. Tran-Minh, C., Pandey, P.C. and Kumaran, S. (1990) Studies on acetylcholine sensor and its analytical application based on the inhibition of cholinesterase. Biosensors and Bioelectronics, 5, 461–471. Webb, J.L. (1966) Enzyme and metabolic inhibitors. II, pp. 635–653. New York: Academic Press.

3.2. MICROBIAL SENSORS

KLAUS RIEDEL, GOTTHARD KUNZE, MATTHIAS LEHMANN and ANDREAS KÖNIG 3.2.1. INTRODUCTION

Microbial sensors consisting of microorganisms in intimate contact with a transducer allow the sensitive determination of a large spectrum of substances and are especially suitable for environmental monitoring because of the following characteristics: • multistep transformations, which are difficult or impossible to achieve with single enzymes or enzyme chains; • ability to recognize a group of substances simultanously, designated as multi-receptor behaviour; • inexhaustible reserve of microorganisms with a wide spectrum of metabolic types; • wide repertoire of specifities; • variability that allows adaptation to the specific conditions; • physiological response to toxic products; • independency from cofactors; • increased stability due to the enzyme environment “optimized by evolution” and well suited for recovery and sense; • inexpensive preparation because enzyme extraction and purification steps are not necessary and the cultivation of microorganisms is simple. Microbial sensors are particularly well suited for environmental control because they are physically robust and stable, easy to handle and cheap to prepare. Especially, the ability to recognize a group of substances is interesting for environmental control. This multireceptor behaviour has been exploited for the determination of complex variables, such as the sum of biodegradable compounds in waste water (BOD), toxicity and mutagenicity (see 4.2.1.). Certainly this multireceptor behaviour causes rather poor selectivity. Therefore, microbial sensors are less suitable for the determination of individual analytes. 3.2.2. DESIGN AND FUNCTION

The design of the microbial biosensor is, in principle, identical to an enzyme sensor. The scheme in Figure 3.12 shows the structure of microbial sensors. The biosensor

Figure 3.12. Schematic design of microbial sensor. consists of immobilized intact cells in intimate contact with a transducer unit, which converts the biochemical signal into an electrical one. 3.2.2.1. Microbial basis

Microbial sensors show important differences to enzyme sensors. Sensing by enzyme sensors is achieved by selective molecular binding of a chemical analyte to the enzyme including the alteration of analyte, whereas the microbial sensor employs physiological responses of living cells as the sensing component. Figure 3.13 demonstrates the flow of the physiological response which includes:

Figure 3.13. Physiological response of microbial sensor.

• substrate uptake through the cell membrane; • intracellular modification or degradation of the substrate by metabolic sequences of the enzyme network; • secretion or separation of metabolic products and by-products; • respiration; • luminescence by photobacteria. This behaviour of microorganisms is related to their physiological state, which is characterized under biosensor conditions by extreme nutrient limitation. Their metabolism is in a stand-by state to guarantee the survival of the cell (Riedel, 1991). The first and critical step of formation of the signal by a microbial sensor is substrate uptake. Solutes can pass into the cells only via specific translocation systems, either by an active transport system or by facilitated diffusion; passive transport events by diffusion are of minor importance. Active transport allows accumulation of substrates up a concentration gradient. This requires carrier proteins with high specificity and it consumes metabolic energy. However, the coupling to the cell energy transducing systems, especially to the respiratory chain is an important aspect of active transport, which is crucial for the formation of the signal from the sensor, for example using glucose, maltose, sucrose and various oligopeptides (Riedel, 1991; Riedel et al., 1989, 1990a). After the uptake of substrate it is degraded specifically by the metabolic sequences of the enzyme networks of the immobilized cells. Under aerobic conditions this is connected with oxygen consumption. Organic acids such as lactate and pyruvate, CO2, ammonium ions and H2S are secreted as by-products. Moreover, the metabolic response to the analytical substrate can cause luminescence by photobacteria. In general, the microbial species chosen for biosensor development must fulfil at least one of the following criteria: • oxygen consumption in the respiratory process for assimilation of substrate; • electrode-active products liberated from reactions of microbial metabolism, e.g. protons, CO2, ammonium ions and H2S; • photoluminescence.

3.2.2.2. Physical basis of the transducer

Transducers are potentiometric or amperometric electrodes, optoelectronic detectors, thermistors, field-effect transistors and piezoelectric crystal systems (Figure 3.12). The selection of a transducer depends on the physiological response such as respiration or photoluminescence as well as on the product formed from the biological layer of the biosensor. A particular advantage of the sensor is the ability to measure the respiratory activity of microorganisms and its alteration caused by the presence of a tested substance. This allows a relatively simple transduction of the analyte response of microorganisms by an oxygen electrode. Therefore, amperometric oxygen electrodes dominate among the transducers used in microbial sensors. However, the application of an optical oxygen electrode was described too (Preininger et al., 1994).

Figure 3.14. Schematic function of microbial sensor with mediators (modified to Kaláb and Skládal, 1994). Metabolic products such as lactate and pyruvate, CO2, ammonium ions and H2S are determined with gas-sensitive, potentiometric electrodes and ion selective electrodes (ISE) (Table 3.5). The direct combination of microorganisms on a gate of a field effect transistor have been developed for the estimation of glucose (Hanazato and Shio, 1983), for alcohol with Acetobacter aceti (Kitagawa et al., 1987) and xylose based on Gluconobacter oxydans cells (Reshetilov et al., 1996). Furthermore, soluble redox mediators, such as phenazine ethosulphate (Turner et al., 1983), ferricyanide (Richardson et al., 1991), or ferricyanide in combination with benzoquinone (Turner et al., 1986) enable the direct measurement of electrons following the metabolic activity of cells. Recently, the use of insoluble mediators was described, such as ferrocene, tetrathiafulvalene and tetracyanoquinodimethane, which were incorporated in carbon paste in connection with Paracoccus denitrificans (Kaláb and Skládal, 1994). The schematic function of this biosensor type is shown in Figure 3.14. These amperometric microbial sensors are not based on oxygen dependency which is advantageous.

Another interesting technique was created by luminescent photobacteria in connected to an optical detector. Such microbial sensors have been described for the determination of metal ions (Guzzo et al., 1992; Holmes et al., 1993) and aromatics (Heitzer et al., 1994). By genetic engineering the lux or light-emitting genes from the photobacteria Vibrio were fused to genetic regulatory or structural genes from Escherichia coli and Serratia marcescens (see 3.2.4.). If microorganisms are combined with a thermistor it is possible to measure the metabolic heat caused by cell reaction to analyte. Such biosensors were described by Mattiasson et al. (1977) as well as Henrysson and Mattiasson (1991, 1993). Further transducers of biosensors are piezoelectric crystals. However, these do not play a role in microbial sensors. 3.2.2.3. Immobilization of microorganisms

The intimate contact between biocatalyst and transducer element by immobilization of the microorganisms is a prerequisite for the constant function of a biosensor. In general, immobilization of the microorganisms for analytical purposes should cause the following effects: • impediment of washout of microorganisms with a increased working stability of the organisms and the biosensor; • reusability of the organisms because of their increased storage stability; • due to the long, predictable, half-life of the activity of the immobilized organisms they become an integrated constituent of the analytical device. Immobilization procedures are limited by the sensitivity of microorganisms. That is why chemical methods, to the best of our knowledge, have been unsuccessful and resulted in decreased biological activity. The preferred immobilization methods are: • entrapment of microorganisms in polymers forming gel membranes such as agar, gelatine, collagen, polyacrylamide, polyvinylalcohol (Riedel et al., 1988a; Matsunaga et al., 1978) and socalled prepolymers (Fukui and Tanaka 1984); • physical methods, like adsorption onto a membrane or sheet of acetylcellulose (Matsunaga et al., 1980), filter paper (Matsunaga et al., 1980; Riedel et al., 1985, 1990b) or nylon (Kulys and Kadziauskiene, 1980) by centrifugation or filtration of a microbial suspension. A very promising approach is the use of socalled prepolymers of ENT (poly(ethyleneglycol)) and ENTP type (poly(propyleneglycol)) or modified polyvinylalcohols for entrapment of microbial cells (Fukui and Tanaka, 1984). This prepolymer method allows defined adjustment of hydrophobicity by alteration of the relation of the hydrophilic ENT and the hydrophobic ENTP. This is important for the determination of polar compounds, such as biphenyl (BeyersdorfRadeck et al., 1992). Moreover, oxygen permeability and substrate diffusion through the immobilized microorganism membrane must be efficient. Although the gel membrane is also influenced by diffusion of substrates, the diffusional resistance is mostly caused by the biomass concentration on the membrane. As shown in Figure 3.15 the signal is strictly related to the cell

loading of the sensor. Mostly a relatively high concentration of biomass and thick membranes are used. Due to the diffusional resistance imposed by the microbial cell membranes the response times for microbial sensors are higher than for enzyme electrodes. Response times comparable in magnitude to enzyme sensors are achieved with very low microbe loadings and suitable immobilization of microorganisms (Riedel et al., 1985, 1988b). The sensitivity of these kinetically controlled sensors is mostly determined by the cell activity, but not by diffusional limitation. 3.2.2.4. Signal formation and measuring principle

Formation of the signal is described for the example of an amperometric sensor based on the respiration of microorganisms. This aerobic process consists of the following steps (Figure 3.16):

Figure 3.15. Influence of cell loading on the signal for glucose (0.15 mmol) (modified to Riedel, 1994).

Figure 3.16. Principle of measurement with microbial sensor (modified to Riedel, 1994). (i) Oxygen diffuses from the air-satured solution through the dialysis membrane, the membrane containing the microorganisms, as well as the teflon membrane and then reduced at the cathode. A small proportion of the oxygen is consumed by the microorganisms. The steady state current represents the oxygen diffusion through the composite membrane and reflects the endogenous respiration of the microorganisms. (ii) If an analyte as assimilable substrate is added to the measuring solution the substrate permeates through the dialysis membrane, subsequently, it is taken up by the microbial cells and then degraded. These processes are caused by an increase of respiration rate resulting in a decrease in the “dissolved” oxygen concentration. The current decreases until a new steadystate is reached. In principle, there are two possibilities for measurement: (i) end-point measurement (steady-state mode), the differences in current I reflect the respiration rate of the substrates Rs, and (ii) kinetic measurement (first derivative of the current-time curve corresponding to the acceleration of respiration A). 3.2.3. IMPROVEMENT OF SELECTIVITY OF MICROBIAL SENSORS

One critical disadvantage of microbial sensors for substrate determination is their low selectivity. Nevertheless biochemical knowledge in connection with gene manipulation enables the alteration of the selectivity and sensitivity of microbial sensors. Approaches for enhancing the selectivity and sensitivity are:

• induction of desired transport and/or metabolic systems; • inhibition or suppression of undesired transport mechanisms and/or metabolic pathways; • construction of species modified by gene manipulation methods; • coupling of enzymes with immobilized microbial cells to form hybrid sensors for elimination of interfering substances or formation of specific products; • combination of various microbial species with supplementary specific metabolic capacities; • exclusion of undesired substrates by dialysis membranes. 3.2.3.1. Influence of selectivity by induction of desired metabolic activity of microorganisms

The induction of desired activity can be achieved by two different methods: • by cultivation of microorganisms with the appropriate substrate; • by incubation of the sensor with the appropriate substrate. The knowledge of the genotype of microorganisms is a prerequisite to influence their sensitivity. The cultivation mode is a widespread procedure and has been used to develop sensors for example for histidine by Pseudomonas sp. (Walters et al., 1980), Table 3.3. Influence of incubation (3h) with inductor (2 mM) on the response of a Bacillus subtilis biosensor to various sugars (Riedel et al., 1990a). Substrate

Increase of biosensorsignal after Incubation [%] Sucrose

Maltose

Lactose

Maltose+ Chloramphenicol

Sucrose

2322

83

168

96

Maltose

83

1905

147

90

Lactose

–

–

2680

–

Glucose

96

118

117

114

Glycerol

82

130

200

63

tyrosine by Aeromonas phenologenes (Di Palantonio and Rechnitz, 1982), maltose by B. subtilis (Riedel et al., 1988b), lactate by Hansenula anomala (Vincke et al., 1985a), ascorbic acid by Enterobacter agglomerant (Vincke et al., 1985b), glutamate (Riedel and Scheller, 1987), and phenols or benzoate by Rhodococcm P1 (Riedel et al., 1991a).

It is also possible to improve the specificity and sensitivity of the microbial sensor to the desired substrate by direct induction. The signal for the induced substrate was increased by a factor of up to 26, as demonstrated for Bacillus subtilis or Trichosporon cutaneum (Table 3.3) (Riedel et al., 1990a). The biosensor can thus be adapted to the desired analytical conditions. Under these conditions the alteration of specificity and sensitivity is highly specific. This was demonstrated for sucrose and maltose by a Bacillus subtilis-containing sensor (Riedel et al., 1990a). Sucrose and maltose gave a low signal in comparison to glucose. The incubation of the sensor with sucrose for 3h caused a drastic increase of sensor response only for this sugar because the response for glucose and maltose was not changed. In each case incubation with the given substrate caused a specific increase of sensitivity for this substance only. Therefore the adequate genotypical potency of the microoganisms is a prerequisite. The achieved activity is constant during incubation. Moreover, the desired uptake systems as well as metabolic pathways were formed by a de novo protein synthesis. This was concluded from the effect of chloramphenicol, because preincubation in the presence of chloramphenicol did not alter the signal (Riedel et al., 1990a). Furthermore, evalution of the Michaelis-Menten kinetics demonstrates that the apparent KM is not influenced by preincubation (Table 3.4), whereas Vmax increases for all substrates tested and achieves similar values (Riedel et al., 1991). It might be assumed that an identical limiting step exists for all substrates tested: the respiration capacity. 3.2.3.2. Influence of selectivity by elimination of undesired activities

The principle of increase of selectivity by elimination of undesired activities have been used repeatedly. Corcoran and Kobos (1983) achieved the selective determination of arginine with an Streptococcus faecium sensor by treatment with sodium azide, which eliminated the reaction of sensor to glutamine and asparagine. A Streptococcus faecium sensor also allows the sensitive determination of pyruvate, because the Table 3.4. Alteration of the Michaelis-Menten apparent KM- and Vmax-values by incubation of a Bacillus subtilis sensor with these substrates (Riedel, 1991). Substrate

app. KM[1/mmol] control

Vmax[nA/mmol]

incubation

control

incubation

Sucrose

1.25

1.25

142

5000

Maltose

2.00

2.00

400

5000

Glycerol

1.25

1.25

1000

5000

interfering reaction of tyrosine decarboxylase is inhibited by thyramine and glycolysis by iodoacetamide (Di Paolantonio and Rechnitz, 1983). Furthermore, the inhibition of undesired metabolic reaction of a B. subtilis biosensor has been used or the determination of glutamic acid (Riedel and Scheller, 1987). In general determination of glutamic acid in the presence of glucose is not possible, because the signal caused by glucose is higher than the signal caused by glutamic acid. The glucose activity can be reduced by inhibition of the glucose uptake system with chloromercuribenzoate (CMB) (Riedel et al., 1988b). CMB is a thiol reagent and irreversibly inhibits the glucose carrier. Additional inhibition of the glucose signal is achieved by reversible inhibition of glycolysis using NaF. An analogous strategy was used by Corcoran and Kobos

(1987) for the elimination of undesired reactions. By treatment of the biosensor consisting of E. coli cells with the enzyme inhibitor 6-diazo-5-oxo-L-norleucin as well as the transport inhibitor gamma-L-glutamylhydrazide, the glutamine response of the cells was strongly reduced. Sometimes the metabolism of the products which should be detected, such as ammonium ions may decrease the sensitivity of the biosensor. By adding isoicotinic acid hydrazide, a competitive inhibitor of transaminases, this process could be selectively eliminated resulting in increased sensitivity (Walters et al., 1980; di Palantonio et al., 1981; Kobos et al., 1979). Inhibitors must be used in relatively low but efficient concentrations achieving partial inhibition, because high concentrations could possibly abolish metabolism. 3.2.3.3. Genetically manipulated species

Microorganisms modified by genetic engineering can be used in biosensor technology in such a manner that they can be utilized for specific tasks in the environmental protection field. For this aim plasmids are constructed containing fusions of regulatory elements with genes encoding products which are easy to detect, for example the lux gene producing a luminescent gene product. Optical biosensors (optrodes) have been developed: • for the determination of benzene a fusion construct is used which contains the TOL plasmid responsible for the degradation of benzene and the gene encoding firefly luciferase which breeds a luminescent E. coli (Ikariyama et al., 1993); • for the determination of naphthalene and salicylate. The bioluminescence reporter bacterium, Pseudomonas fluorescent HK44, carries a transcriptional fusion of the gene nahG derived from the salicylate operon from Pseudomonas fluorescens and the gene casette luxCDABE from Vibrio fischeri (Heitzer et al., 1994); • for the detection of aluminium an E. coli strain is used, which expresses a transcriptional fusion of the genes luxAB of Vibrio harvey (encoding bacterial luciferase) and the genes FliC of E. coli (Guzzo et al., 1992); • for the detection of copper as well as zinc, cadmium, and lead ions with Alcaligenes eutrophus harbouring constructs consisting of the heavy metal resistant gene and the bioluminescence gene (Corbisier et al., 1996). New possibilities are opened by the combination of regulatory genes with structural genes, as demonstrated for example for the determination of Cu2+ with an Saccharomyces cervisiae strain (Lehmann et al., 1997). Plasmids were constructed containing the CUP1 promoter of S. cerevisiae, which is induced by copper ions, fused to the LacZ gene of E. coli. Transformants with these plasmids cannot utilize lactose as a carbon source. The fusion construct is therefore only transcribed and translated in solutions containing Cu2+ ions. When lactose is used as the measuring solution the transformant cells are able to utilize this substance as carbon source only in presence of Cu2+ ions. Therefore changes in oxygen consumption depend on the concentration of Cu2+ ions. These concentrations can be measured by amperometric detection (Figure 3.17).

Figure 3.17. Schematic design of measuring cell and genetically manipulated yeast cell for the detection of Cu2+ ion concentrations. 3.2.3.4. Hybrid sensor

By combination of microorganisms with enzymes it is possible to improve selectivity. Furthermore these combinations enable determinations of polymers, such as starch, proteins and lipids, which cannot be taken up by the microorganisms. For this the microorganisms are combined with hydrolases (Renneberg et al., 1984). Additionally, amperometric hybrid sensors have been developed for the determination of NAD+ on the basis of E. coli and NADase (Riechel and Rechnitz, 1978), urea and creatinine by use a combination of nitrifying bacteria and urease (Kubo et al., 1983) or creatinase (Okada et al, 1982). 3.2.3.5. Combination of various microorganisms

Combination of various species was developed with the aim of achieving a broad substrate spectrum such as for the determination of BOD (see Chap. 4.2.3.2.1.). An other typical example for a biosensor containing a mixed population of species with supplementary specifical metabolic capacity is the biosensor with nitrifiers (König et al., 1997a, b). This sensor, which especially was developed for waste water investigations, contains a mixed culture of Nitrosomonas sp. and Nitrobacter sp. and allows the amperometric determination of ammonia according the following scheme of nitrification:

The oxygen demand by the nitrifying bacteria is therefore a measure for the ammonia concentration in the sample. For this rapid determination method a detection limit for ammonium in the ppb-range was observed. Because this biosensor reacts also to nitrite and urea, it is further suitable for the summary quantitation of nitrifiable N-compounds, the so-called N-BOD (Wagner, 1990; Deai et al., 1991). This parameter can be useful for waste water control. Furthermore, it is possible to estimate compounds, which are inhibitors of nitrification. When starting such investigations the sensor is principally exposed to a surplus of substrate (ammonium or urea). The basic current becomes stable at a low level, because under these conditions the oxygen consumption by the immobilisate increases to the maximum rate, and therefore the oxygen molecules diffuse through the bacterial immobilisate in relatively small amounts. The addition of an inhibitor leads to a rapidly decreased bacterial oxygen consumption. By this time the oxygen diffusion to the probe again takes place normally and becomes noticeable in the increasing currents registered by the Clark electrode until the new steady-state is reached (Figure 3.18). Performing investigations with waste water-relevant inhibitors and nitrification-inhibiting waste waters, for the relation between the inhibitor concentration and the sensor signal a sigmoidal function was found, as usual for toxicological investigations. This is shown in Figure 3.19, when allyl thiourea was used as the nitrification

Figure 3.18. Principle of nitrification inhibition with a microbial sensor containing nitrifiers.

inhibiting agent. A complete concentration series of an inhibitor for quantitation of its inhibitory effect could be recorded within one day, if the inhibitor was a reversible agent. This is a very short time compared with the time required for other tests for measuring the inhibition of nitrification. Finally, the biosensor for nitrifiers also was integrated in a field testing plant for online-monitoring of the sewerage system for nitrification inhibiting effects directly in the waste water stream (König et al., 1997b). 3.2.3.6. Exclusion of undesired substrates by dialysis membranes

An elegant possibility to improve the selectivity of microbial sensors offers the exclusion of undesired substrates by specific membranes. If the microbial sensor was

Figure 3.19. Influence of concentration of allyl thiourea on the signal of a nitrification sensor (König et al., 1997b). covered with a gas-permeable membrane instead of a dialysis membrane, only volatile compounds can penetrate through the membrane and the permeation of nonvolatile components such as carbohydrates, amino acids and ions was hindered. Such microbial sensors were used for the determination of alcohol with Trichosporon brassicae (Karube et al., 1980) and ammonia with nitrifying bacteria (Karube et al., 1981).

3.2.4. GENERAL CONSIDERATIONS OF APPLICATION

Many kinds of microbial biosensor have been developed and described for environmental monitoring. Table 3.5 gives an overview of these biosensors. The determination of complex parameters such as BOD (see 4.2.1.) and toxicity are major application fields of microbial sensors in environmental control because of their multireceptor behaviour. On the other hand is this behaviour a disadvantage for the determination of individual analytes. However, modification of microorganisms by use of genetic engineering as well as biochemical and physiological knowledges should enable an improvement of selectivity and too of sensitivity and stability. Microbial sensors will be of practical relevance in the near future and promise to be of great importance for the sensitive detection of compounds of environmental significance. Table 3.5. Microbial sensors for determination of compounds of environmental relevance (an overview). Analyte

Microorganisms

Transducer

Detection limit [mg/l]

Response time [min]

References

Ammonium ions

Nitrosomonas europaea

amp. Oxygen sensor

0.04

8

Hikuma et al., 1980

Bacillus subtilis

amp. Oxygen sensor

0.2

0.1

Riedel et al., 1990b

Ammonia

nitrifying bacteria

amp. Oxygen sensor

0.09

4

Karube et al., 1981

Nitrate

Azotobacter vinielandii

pot. Ammonium sens.

0.6

7

Kobos et al., 1979

Nitrite

Nitrobacter sp.

amp. Oxygen sensor

2.3

10

Karube et al., 1982

Urea

nitrifying bacteria +urease

amp. Oxygen sensor

125

7

Okada et al., 1982

Proteus vulgaris

pot. Ammonium sens.

0.04

Sulfur dioxide

Thiobacillus thiooxydans

pot. pHelectrode

5

20

Nakamura et al., 1993

Sulfide

Thiobacillus thiooxydans

pot. pHelectrode

1

20

Kurosawa et al., 1994

Sulfite

Thiobacillus thiooxydans

amp. Oxygen sensor

0.3

Ihn et al., 1988

Suzuki et al., 1992

Sulfate

Desulfovibrio desulfuricum

pot. Sulfide sensor

3.8

8–15

Kobos, 1986

Phosphate

Chlorella vulgaris

amp. Oxygen sensor

72

1

Matsunaga et al., 1984

Fe (II)/

Thiobacillus

amp. Oxygen

3

0.5–5

Mandl and

Fe (III)

ferrooxydans

sensor

Macholan, 1990

Cu (II)

E. coli recombinante

Optrode

0.06

Holmes et al., 1993

Hg (II)

E. coli recombinante

Optrode

0.002

Holmes et al., 1993

Al (III)

E. coli recombinante

Optrode

0.001

Guzzo et al., 1992

Phenol

Trichosporon cutaneum

amp. Oxygen sensor

2

0.25

(beigelii)

Neujahr et al., 1979 Riedel et al., 1995

Rhodococus P1

amp. Oxygen sensor

2

0.25

Riedel et al., 1991a

Rhodotorula spec.

amp. Oxygen sensor

1

0.2

Ciucu et al., 1991

Page 101 Analyte

Microorganisms

Chlorophenols

amp. Oxygen 0.3 Trichosporon cutaneum (beigelii) sensor

0.25

Riedel et al., 1995

Rhodococus P1

amp. Oxygen 2 sensor

0.25

Riedel et al., 1993

Rhodococus P1

amp. Oxygen 2.8 sensor

0.25

Riedel et al., 1993

Pseudomonas putida

amp. Oxygen 0.5 sensor

0.25

Riedel et al., 1991b

Chlorobenzoate

Pseudomonas putida

amp. Oxygen 7 sensor

0.25

Riedel et al., 1991b

Biphenyl

Alcaligenes eutrophus

amp. Oxygen >100 sensor

0.25

BeyersdorfRadeck et al., 1991, 1993

PCB

Pseudomonas

amp. Oxygen >100

0.25

Beyersdorf-

Benzoate

Transducer

Detection Response References limit [mg/l] time [min]

putida

sensor

2,4-D

Alcaligenes eutrophus

amp. Oxygen 40 sensor

0.25

BeyersdorfRadeck et al., 1991

Benzene

Pseudomonas putida

amp. Oxygen 5 sensor

2–10

Tan et al., 1994

E. coli recombinante

Optrode

1

Pseudomonas fluorescence

Optrode

1.5

Naphthaline

Radeck et al., 1992, 1993, 1998

8–15

Heitzer et al., 1994

amp. Oxygen 0.1 sensor

2

König et al., 1996

10

Matsunaga et al., 1980

1–2

Okada et al., 1981

Formic acid

Pseudomonas oxalalitus

pot. CO2 sensor

Methane

Methylomonas flagellata

amp. Oxygen 0.4 sensor

Dichloromethane Hyphomicrobium spec.

Ikariyama et al., 1993

Thermistor

5

0.008

Nitrilotriacetic acid

Pseudomonas spec. pot. Ammonium sens.

Cyanide

Pseudomonas fluorescence

Surfactants

not defined bacteria amp. Oxygen 2 sensor

Henrysson et al., 1993

90

5

Kobos and Pyon, 1981

amp. Oxygen 0.1 sensor

2

Lee and Karube, 1995 Nomura et al., 1994

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3.3. IMMUNOASSAYS

BERTOLD HOCK 3.3.1. ANTIBODY STRUCTURE

Antibodies (=immunoglobulins, Ig) are multifunctional binding proteins. They are produced by the immune system of vertebrates and form an essential part of the defense reactions. Antibodies (abs) are responsible for specific recognition of pathogens, toxins and xenobiotics. The huge repertoire of abs covers practically any ligand. High molecular mass ligands function as antigens, low molecular ones as haptens. Any foreign substance, which induces specific ab synthesis after its injection into the body, is an antigen (antibody generator). Antigens are principally macromolecules, e.g. proteins, polysaccharides or nucleic acids. Even synthetic polymers can serve as antigens. The part of an antigen, which binds an ab, is called an antigenic determinant or epitope. An antigen usually displays several different epitopes. The protective function of abs is related to their ability to form specific antigen-ab complexes, which subsequently activate defined effector mechanisms of the immunosystem, followed by neutralisation, destruction and elimination of antigens. The basic structural unit of all abs is the same, independent of their specificity and class. Each basic unit consists of four polypeptide chains, which belong to two different types. Two identical heavy chains (H) and two identical light chains (L) are joined to an immunoglobulin monomer. Figure 3.20 shows the domain structure of an ab of the IgG class, which is usually applied for immunochemical methods. The two symmetrical halves of the molecule are held together by two disulfide bridges between the H chains as well as by noncovalent bonds. Each of the two halves consists of a H and L chain, which again are joined together by a disulfide bridge and by noncovalent interactions. Each chain is subdivided into domains of ca. 110 amino acid residues and displays the same structural motif, the immunoglobulin fold. Each domain contains two highly conserved cystein residues, which form an intradomain disulfide bridge. Abs of the IgG class consist of two domains per L chain and four domains per H chain.

Figure 3.20. Domain structure of the IgG molecule with the flexibilities of the Fab and Fc region. After Clark (1994). •—• Disulfide bridges.

The antigen binding sites are formed by pairs of VL and VH domains. These variable (V) regions display a considerable diversity in a natural ab population whereas the other regions of the chains are relatively constant. H and L chains are therefore divided in two different regions, the variable (V) region, which is responsible for antigen binding, and the constant (C) region, which enables secondary biological functions such as complement binding and macrophage binding. Distinct sequences within the variable regions are characterized by a remarkable diversity, the three hypervariable regions (complementary-determining regions, CDRs), found on each chain and embedded between four frame regions. Immunoglobulin monomers can be digested by proteases into ab fragments. Three fragments are obtained by papain. Two of them are identical Fab fragments (Fragments with antigen binding sites) and consist of the entire L chain and the H chain fragment with the domain .A third fragment does not have an antigen binding site. But it can be crystallized because of its homogeneity in contrast to the Fab fragment. The Fc part has binding sites for the bacterial proteins Protein A and Protein G. This can be used for purifying abs, but also for uniform alignment, e.g. on immunosensor surfaces. Abs can be grouped according to the structure of their H chains into different classes (Table 3.6) and subclasses. In addition, there are two types of L chains, κ (kappa) and λ (lambda), independent from division into classes and subclasses. It is Table 3.6. Properties of the most relevant human immunoglobulins. Property

IgG

IgM

IgA

IgD

IgE

Molecular mass

150,000

900,000

160,000 (and dimer)

185,000

200,000

Number of immunglobulin monomers

1

5

1 (2)

1

1

Heavy chains

γ

µ

α

δ

ε

Light chains

κ and λ

κ and λ

κ and λ

κ and λ

κ and λ

Number of antibody binding sites

2

5

2 (4)

2

2

Average serum concentration 8–16 mg/ml

0.5–2 mg/ml

1.4–4 mg/ml

0–0.4 mg/ml

17–450 ng/ml

Carbohydrate (in %)

12

8

13

12

3

possible to produce abs against already existing abs, e.g. anti-rabbit abs from goat, anti-mouse IgG from rabbit etc. In this case species- or class-specific epitopes serve as antigens. They are usually located on the Fc part. Such anti-abs or anti-Ig are of great importance for the detection and alignment of abs. For more details, the reader is referred to text books of immunology, e.g. Klein (1991); Roitt (1991); Austyn and Wood (1993). 3.3.2. POLYCLONAL ANTIBODIES

Abs are produced and secreted by vertebrate plasma cells, found especially in secondary lymphoid tissues such as spleen, lymph nodes and tonsils. Although each plasma cell produces only a single type of abs of the same affinity and selectivity, vertebrates have a huge genetic repertoire of 108 to 1010 different abs. If an immune response is triggered by the presence of an antigen, the precursors of plasma cells, the B lymphocytes, are activated. Since an enormous amount of different B lymphocytes circulate between blood and lymphatic organs, chances are high for a contacting the antigen. Foreign antigens are recognized by specific membrane-bound receptors on the surface of B lymphocytes. These antigen receptors are related to the subsequently secreted abs with respect to their structure and their specificity. The antigen receptors of a B lymphocyte only recognize a single epitope of an antigen. The activation of a B lymphocyte is a highly complex sequence, involving additional factors as well as T lymphocytes. Optimal immunization schedules are available for strong immune responses with high ab titers (Huber and Hock, 1986). The time periods required for polyclonal antibody (pab) production are normally at least two or three months depending on the immunogenicity of the antigen. An important practical aspect of B cell activation is the impossibility of low molecular weight substances such as pesticides and endocrine substances to trigger ab production. The first step in the signal transduction chain involves cross-linking of membrane-bound receptors by multivalent antigens, aggregation and endocytosis. Since low molecular weight substances do not expose several epitopes, cross-linking by surface receptors can not take place and ab production is prevented. However, this shortcoming of ab production can be circumvented: if low molecular substances are coupled to a suitable antigen, the immunogen, the former ones are recognized by the B lymphocytes as antigenic determinants. Consequently, there are also abs being produced against these determinants during the immune response. Some of these abs may bind to the free low molecular substances, which are then called haptens. Figure 3.21 shows a few possibilities of immunoconjugate synthesis if abs are to be produced against PCP, TCDD, and estradiol. The strategy of hapten derivatization for immunoconjugate synthesis and coupling essentially determines the properties of the produced abs. Before 1975 immunochemical methods were exclusively based on pabs. They are raised by immunizing vertebrates, usually mammals (such as rabbits, sheep or goat) or birds (chicken), and prepared from the blood or the eggs, respectively. Although each B cell and its descendants (a clone of plasma cells) produces only a single type of abs, the injection of an antigen into an

organism triggers the production of different ab species that are directed against different antigenic determinants on the immuno-

Figure 3.21. Immunoconjugate synthesis for antibody production against TCDD, PCP and estradiol. Suitable hapten derivatives are coupled to bovine serum albumin (BSA). conjugate. The expression “polyclonal” points to the fact that these abs are derived from a multitude of plasma cells and therefore represent a heterogeneous mixture of abs. Among this heterogeneous population of abs there are selective ones that may be directed against different antigenic determinants on the antigen. The other abs originate from earlier contacts with other foreign antigens present in the organism. This has to be kept in mind if pabs are used for immunoassay development or immunosensing. It may be more critical for medical applications, e.g. identification and quantification of viruses, than for the environmental field. Antiserum production is relatively simple. Rabbits for instance require usually four to five immunizations, the first three in weekly periods and later, if required, within longer intervals. The first blood drawing can take place approximately six weeks after starting immunization. Up to 30 ml blood can be drawn from the ear vein per session and c. 15ml antiserum can be obtained after blood clotting and centrifugation of the supernatant. Depending on the ab concentration (=titer) the antiserum can be diluted at least 1:10,000 to 1:50,000. Since a microwell plate with 96 cavities requires ca. 30ml ab solution, a single blood drawing is sufficient for coating between 5,000 and 25,000 microwell plates. In spite of these impressive numbers it should not be

overlooked that each antiserum is unique because of its polyclonality and can even change for the same animal if different blood samples are compaired. 3.3.3. MONOCLONAL ANTIBODIES

The efforts to produce abs with uniform properties, e.g. for standardized assays, were only successful when a strategy was found to immortalize B lymphocytes, which can be kept alive at most for 10–14 days, but do not undergo cell divisions. This has been achieved by Köhler and Milstein (1975). They fused B lymphocytes producing abs against red blood cells of sheep with suitable myeloma cells, cancerous cells of the immune system. Selected hybrid cells, the hybridomas, developed abs with uniform affinity and specifities against red blood cells of sheep. In 1984 Georges J.F.Köhler and César Milstein together with Niels K.Jerne received the Nobel prize for medicine for their pioneering work. Table 3.7 summarizes and compares the properties of pabs and mabs. The production of mabs by the hybridoma technology (Figure 3.22) involves five basic steps, immunization of mice or rats (recently also rabbits), fusion of their spleen cells with myeloma cells, HAT selection, screening and cloning. It is followed by mass production of mabs. A suitable immunoconjugate is injected into mice, using an appropriate immunization schedule in order to obtain enough B lymphocytes, which secrete abs directed against the required antigenic determinant. Then the B lymphocytes are taken from the spleen and fused with myeloma cells in the presence of poly-ethyleneglycol (PEG). A mixture of unfused cells, multiple-fused cells and the Table 3.7. Properties of polyclonal and monoclonal antibodies. Properties

Polyclonal Antibodies

Monoclonal Antibodies

supply

limited and variable

unlimited production possible

uniformity

changing properties with different sera and bleedings

constant properties of a given mAb

affinity

mixture of abs with different affinities

uniformly high or low, can be selected by testing

cross-reactivity occurs as a result of different selectivities and low affinity interactions

depends upon the individual ab

classes and subclasses

one defined isotype

typical spectrum

demands on the high purity required for specific antigen antisera

impure antigens or mixtures of antigen can be used, high purity required for screening

Figure 3.22. Production of monoclonal antibodies. See colour plate 1. desired hybridomas is obtained and seeded into the cavities of microtiter plates. The unfused B lymphocytes and the multiple-fused cells die within a short time. As the unfused myeloma cells grow vigorously in contrast to the hybridomas and tend to overgrow the hybridomas, myeloma cell lines are used, which lack the enzyme HGPRT (hypoxanthine-guanine-phosphoribosyltransferase) in the nucleic acid pathway and therefore cannot survive in a culture medium containing aminopterin. Only the hybridoma cells can survive this selection because in the presence of hypoxanthine and thymidine they use a salvage pathway and therefore complement the genetic defect due to the B lymphocyte genome.

The next step involves screening of the growing hybridoma cell colonies for their ability to produce the desired ab. For this purpose a competitive immunoassay (cf. below) is usually applied. This strategy allows the presence of “positive” hybridoma cells to be detected. But alternatives are now available, e.g. optical sensors applying the SPR technique. This more sophisticated approach provides instant information on the affinity and kinetic constants of the abs and therefore simplifies selection of mabs required for specific purposes such as immunochromatography. Subsequently, it is necessary to isolate and multiply (=clone) single positive cells that are still mixed at this stage with other hybridomas (cf. Figure 3.22). Different methods can be used for the cloning, e.g. limiting dilution. After cloning it is necessary to test the clones to see whether they still produce the desired antibody since not all hybridomas are stable. Then the clones are cultivated in a suitable environment. If a stable cell line is available, it can be expanded to larger volumes. For instance, cultures are conveniently grown in roller bottles with 500mL culture medium and mab concentrations up to 50mg/L are obtained. Larger amounts are raised in fermenters. Plants are reported operating in the gram range. 3.3.4. RECOMBINANT ANTIBODIES

Since it is not possible to alter the properties of existing abs, alternatives are required. The necessity of new immunizations should be circumvented, for instance to obtain mabs with altered cross-reactivities. This is achieved at the DNA level by generating and expressing mutant ab genes. This recombinant technology has considerable consequences. It will bridge the gap between artificial peptide receptors and abs. In addition, gene technology offers the option to express ab genes in bacteria, insect cells, yeast or plants. The basic technology for the production of recombinant antibodies (rabs) was developed in the biochemical and medical field in order to produce humanized abs and circumvent allergic reactions during therapy. Today the main emphasis is still laid upon medical applications including HIV and cancer research. In addition there are first applications in the field of environmental (Karu et al., 1994; Kamps-Holtzapple and Stanker, 1996; Kramer and Hock, 1996). Figure 3.23 shows a generalized scheme for the production of rabs. It permits several options, for instance the production of fusion proteins (e.g. enzyme-coupled abs, abs with tags for affinity purification or directed orientation on a sensor surface) or the generation of rab libraries. A proved strategy takes advantage of the natural diversity of the immune system. In this case mRNA is isolated from spleen lymphocytes. cDNA synthesis is followed by the amplification of desired immunoglobulin sequences, e.g. the variable regions of abs, with the aid of the polymerase chain reaction (PCR) with universal primers. After introducing restriction sites at the 3′ and 5′ end, the PCR amplificates are introduced into a suitable vector, followed by transformation of bacterial cells, usually E. coli. Each individual transformed bacterium contains an ab coding DNA sequence, which is multiplied and transferred by cell division to the descendants. They represent a recombinant bacterial clone.

Since B lymphocytes represent a heterogeneous cell population, the entire repertoire of the ab coding DNA sequences is distributed to different clones, which therefore contain a simple gene library.

Figure 3.23. Production of recombinant antibodies and establishment of an H and L chains, which are linked by a synthetic petide linker. Fab: cf. Figure 3.24, in this case, the CH1 and CL domaines are amplified together with the variable regions by means of suitable primers.

Further diversification and refinement of the ab library can be obtained by (1) chain shuffling. The individual H and L chain fragments can be joined by random combination (Marks et al., 1992). The heterodimers can then be expressed as functional rab. (2) Random variation of the variable regions by error-prone PCR followed by selection of suitable rabs. (3) Randomization of CDRs, followed by selection, or (4) a combination of any of these strategies. The potential size of an rab library exceeds far beyond the number of bacterial clones which can usually be handled and screened. They form a huge repertoire for the selection of new ab properties. It is obvious that evolutionary strategies will contribute to simplify the screening problem. An elegant form of expressing and selecting positive clones represents the phage display system for rabs (Barbas et al., 1994; Winter et al., 1994). Single chain fragments of the variable region (scFv), which are stabilized by covalently bound peptide linkers (cf. Figure 3.24), are expressed as fusion proteins with the p III-coat protein of a M13 phage. In this case the phage particle not only displays the expressed rab fragment, but also carries the genetic information. Screening of large libraries can be carried out by panning, magnetic bead separation or immunochromatography in hapten-coated gels. It is obvious that there is a gradual transition from rabs to synthetic binding peptides, which may finally replace abs in analytics. If comparable stabilities, affinities and selectivities can be obtained with synthetic peptides, it appears to be feasable to replace time-consuming ab production in the laboratory of specialists by the much faster selection of recombinant binding proteins from commercially available peptide libraries by application laboratories. Performance of assays will not be affected by the substitution of abs by binding peptides.

Figure 3.24. Architecture of IgG antibodies and their fragments.

3.3.5. BINDING PROPERTIES OF ANTIBODIES

The interaction between an ab and its ligand is based on spacial complementarity but not on covalent bondings. The forces contributing to the binding are (1) electrostatic forces, they are due to the attraction between oppositely charged ionic groups, for example an ionized amino group on a lysine of one protein and an ionized carboxylic group on the other; (2) hydrogen bonding between hydrophilic group such as—OH,—NH2 and—COOH; (3) hydrophobic forces between non-polar, hydrophobic group such as the side-chains of valine, leucine and phenylalanine, which tend to associate in an aqueous environment; (4) Van der Waals forces, which depend upon the interaction between the external electron clouds of molecules. These intermolecular bonds are all weak physical bonds, which require a short distance between ab and antigen (or hapten) to reach sufficient strength of the binding. The primary reaction is predominantly electrostatic bonding and partly Van der Waals bonding, which takes place within seconds to minutes (Jefferis and Deverill, 1991). The primary bond energy may constitute only a small percentage of the total bond energy. However, secondary bonding occurs over longer time periods and may continue to increase for many hours and even several days. As the ab binding site and the ligand are drawn together, hydrogen bonds may be formed. Strengthening of the bonds decreases reversibility of the binding reaction. This should be kept in mind if antigen (or hapten) binding has to be reversed. This situation occurs in tracer displacement assays as well as in immunoaffinity chromatography. In this case, reversal should take place as early as possible. The affinity of the ab bonding is defined by the difference in free energy (∆G) between the ab and its ligand in the free state on the one hand and in the complexed form on the other. The following equations are given for haptens (H) as ligands. (3.3.1) where R=universal gas constant T=absolute temperature K=affinity constant [M−1] of the reaction ab+H=abH The affinity constant is defined as (3.3.2) where k+1=association constant [M−1 s−1] k−1=dissociation constant [s−1]

[abH]=concentration of bound hapten at the equilibrium point [ab]=concentration of free ab binding sites at the equilibrium point [H]=concentration of free hapten at the equilibrium point The high degree of complementarity can provide strong affinities of abs for their ligand. They usually fall into the range between 105 to 1011 M−1 at a mature immune response. For many analyte systems the association constants are found within a range of 10−7 to 10−8 M−1 s−1. Differences in the affinity are mainly related to differences in the dissociation constants. For practical applications the free hapten concentration is of interest where half of the ab sites are bound [H0.5]. In this case (3.3.3) This means that the affinity constant is equal to the reciprocal of the concentration of free hapten at the equilibrium point where half the ab sites are in the bound form. High affinity constants require only low hapten concentrations for half saturation of abs. Abs of this property enable highly sensitive assays. The term avidity applies to antisera and pabs; it describes the tendency of the ab to bind antigens with several epitopes. The avidity is not only influenced by the heterogeneity of abs in a antiserum and the heterogeneity of the epitopes, but also by the fact that two antigen molecules with different epitopes can be simultaneously be bound by an IgG. It should be noted that avidity is less precisely defined as affinity, which characterizes the strength of binding between a monovalent antigen or hapten and a monovalent ab (antigen binding site). The selectivity of an ab towards a defined ligand is usually not an absolute one. It should be considered a rule rather than an exception that an given ab can also recognize similar ligands although with a lower affinity. As the bonding strength is given by the affinity, selectivity of an ab is the relative affinity towards another substance. Relative affinities are usually displayed by the cross-reactivity pattern of an ab. A skilful design of immunoconjugate synthesis can help to avoid unwanted cross-reactivities. On the other hand, ab arrays can be employed to take advantage of abs with different cross reactivities. Chemometrics combined with neuronal networks are more recent approaches in the field of immunosensors for multianalyte analysis. 3.3.6. IMMUNOASSAYS

Since the introduction of immunoassay technology by Berson and Yalow (1959) and in the more general form of saturation analysis, by Ekins (1960), a vast amount of literature has appeared on theoretical aspects of immunoassays and their practical application in medicine and other fields. The reader is referred to extensive reviews for further details, e.g. Chan and Perlstein (1987); Tijssen (1985); Pal (1988); Kemeny and Challacombe (1988); Butler (1991); Van der Laan et al. (1991); Beier and Stanker (1996); Price and Newman (1991). Since the same principles apply to

immunoassays and immunosensors in terms of binding characteristics, the basic aspect and classification principles are summarized below. The most fundamental criterium for classifying immunoassays depends on the measurement of fractional occupancy of ab binding sites (Ekins, 1991) as the occupancy of ab binding sites by the analyte depends on the analyte concentration in the sample. Analyte binding by the ab does not generate a signal, which can be easily measured. Therefore immunoassays and indirect immunosensors (Chap. 4.1.2.) require a tracer as helper reagent, which allows the estimation of ab occupancy by measuring the tracer signal. Figure 3.25 explains the two alternatives: noncompetitive immunoassays and competitive immunoassays. Non-competitive immunoassays measure directly the occupied binding sites. Maximal sensitivity is obtained with an excess of abs. Signal production is usually provided by tracer abs, for instance enzyme-coupled abs. Competitive immunoassays measure unoccupied ab binding sites. Maximal sensitivity is obtained at minimal ab concentrations. Labelled analytes or labelled abs, respectively, can be used as tracers in different formats (cf. below). In spite of the advantages of non-competitive assays such as lower detection limits, higher robustness and at least in some cases faster performance, they cannot be applied for the analysis of dissolved haptens since non-competitive assays require multivalent antigens as analytes, which display more than one epitope.

Figure 3.25. Comparison of non-competitive (a) and competitive immunoassays (b). See colour plate 2.

3.3.6.1. Heterogeneous and homogeneous immunoassays

Heterogeneous immunoassays are characterized by the requirement for separating the free from the solid phase-bound fraction. Either the bound fraction is used for signal generation, as it is the case for solid phase enzyme immunoassays (EIAs), or the unbound fraction as it is practised with radioimmunoassays (RIAs). In contrast, homogeneous immunoassays do not require any phase separation, i.e. the physical separation of free and ab-bound components. Ab-ligand binding as well as its detection by means of a tracer takes place in a homogeneous solution. The detection principle is based on the fact that the ab does not only bind the tracer but also influences the subsequent reaction of the tracer. One of the numerous possibilities is the interference of the ab with the substrate binding of an enzyme tracer. If the analyte concentration is increased, the tracer is displaced from the ab binding sites and is available for the subsequent enzyme reaction with a conversion of a substrate. The omission of a separation step simplifies the assay compared to the heterogeneous approach. However, interferences by matrix effects play a significant role whereas phase separation in heterogeneous assays also removes a significant part of interfering substances. Therefore heterogeneous immunoassays are much more common than homogeneous assays, for instance they are used in practically all commercial immunoassays as well as immunosensors. However, flow injection systems would benefit from the homogeneous approach although even in this case the heterogeneous variant is normally applied (Chap. 4.1.2.). 3.3.6.2. The heterogeneous competitive immunoassay

The most frequently applied format in the immunoassay and immunosensor field is the heterogeneous competitive immunoassay where the amount of bound tracer is related to the analyte concentration in the sample. As the tracer produces the signal, its strength is inversely related to the analyte concentration. Figure 3.26 summarizes the two possibilities approaches for phase separation, binding of the ab to the solid phase (Figure 3.26a) or binding of a coating conjugate with a hapten-derivative to the solid phase (Figure 3.26b). The variant with the immobilized ab uses a labelled analyte as tracer, the variant with the coating conjugate a labelled ab, which has the function of the tracer and simultaneously the reaction partner during the immune reaction. The terminology of these two variants can cause confusion. Variant b with enzyme-labelled abs is designated as Enzyme-Linked Immunosorbent Assay (ELISA) although this term is now often applied to variant a, too. Moreover variant a is sometimes called direct immunoassay and variant b indirect immunoassay. Since these terms can be confused with the same ones applied in the immunosensor field but with different meanings, they should be avoided. Indirect immunosensors are those which require tracers, whereas direct sensors are label-free procedures. In addition, distinctions are made between direct labelling (use of labelled primary abs) and indirect labelling (use of labelled second abs).

Both variant a and b exhibit an inverse relation between signal height and analyte concentrations. The variant with the immobilized coat conjugate (Figure 3.26b)

Figure 3.26. Variants of the competitive immunoassay. See colour plate 3. is frequently used in immunosensor technology because even the application of unlabelled abs provides measurable signals, e.g. by changes of the mass or the refraction index during the immune reaction. An example is direct immunosensing which does not require labelled abs. The mass increase at the sensor surface due to ab binding is sufficient to generate a signal (Chapts. 2.2 and 4.1.2.). The principle used for instance by a SPR sensor relies on the heterogeneous immunoassay although phase separation is not employed. This is described in more detail in Chapter 2.2.2.3.2.). A more simple alternative with unlabelled first abs is indirect labelling, e.g. with labelled second abs. A common practice is the application of peroxidase-labelled anti-mouse abs from rabbit or

goat, which recognize the Fc part of the primary mouse abs. In this case the labelling is independent from the individual ab applied for the immunoassay.

Figure 3.27. Immunosensor based upon the evanescent field principle. Antibodies with free binding sites bind to an immunoconjugate at the sensor surface increasing its thickness. 3.3.7. DATA PROCESSING AND STATISTICS

Although data processing is automated in immunosensors and therefore hidden from the user, it appears to be helpful to get acquainted with the basics in order to deal with problems arising during measurements of samples. As the immune response shows a non-linear relationship to the analyte concentration, curve fitting procedures must be applied. This subject is treated in detail by Rodgers (1984); Dudley et al. (1985); Raggatt (1991). The basic approaches do not differ between immunoassays and immunosensors. A linearization of calibration curves is of advantage for the direct comparison of different calibration curves, for instance for judging cross-reactivities of matrix effects. This is carried out in two steps: (1) curve fitting and (2) linear transformation. Curve fitting is required for computing the curve from which the unknowns will be calculated. The most frequently applied procedure is based on the logit-log model (Rodbard and Cooper, 1970). The logit function is a continuous sigmoidal function with a single point of inflexion. An appropriate compromise between the quality of curve fitting and cost of calculation can be met by the 4-parameter model. It relates the signal y (e.g. the absorption A) to the concentration of the analyte x (3.3.4)

where a, b, c, d=const.

The constants a and d in equation (4) correspond to the upper and lower asymptotes, respectively, of the curve, c to the analyte concentration at the middle of the test and b to the slope of the curve at the middle of the test. Linearization is carried out by transforming equation 3.3.4: (3.3.5)

If log (

) is equated with Y (logit-log transformation), (3.3.6)

is obtained. Equation 3.3.6 represents a straight line with the slope -b and the segment b • log c on the Y axis if Y is plotted against log (x). A simplified model sets a=1 (or 100%) and d=0 and is therefore called the 2-parameter model. Equation (3.3.4) is simplified to (3.3.7) which can be transformed to (3.3.8) Equation 3.3.8 is a straight line if Y is plotted against log (x). The 2-parameter fit is carried out in two steps. First the response (e.g. absorption) is transformed into % B/B0 values, which represent the occupancy of the ab binding sites by the tracer and therefore represent the ratio (3.3.9)

The %B/B0 values lie in between 100 % (=A0, the upper asymptote of the curve) and 0% (=Aexcess, the lower asymptote). They are calculated according to (3.3.10)

Aexcess is the absorption of a sample with an excess of the analyte, A0 the absorption of the control. 50% B/B0 represents the middle of the test. Here half of the ab binding sites are occupied by the tracer. A linearization is obtained after the logit-log transformation

(3.3.11)

by plotting the logit values against the logarithm of the concentration. 3.3.8. CROSS-REACTIVITIES

The affinity of an ab or a mixture of abs is expressed as cross-reactivity. Therefore crossreactivity determines the extent to which an ab or an antiserum reacts with compounds related to the analyte or, even worse, with entirely different compounds. Cross-reactivity can be due to the existence of a heterogeneous ab mixture as it is usually the case with pabs, where individual ab molecules react with different analytes. But even a homogeneous population of ab, such as mab, does not exclude cross-reactivities because it is an intrinsic property of almost all abs, especially those which are directed against haptens, to bind related compounds, usually with different affinities. Cross reactivity is calculated according to the formula (3.3.12) where A=concentration of the analyte at 50 % B/B0 (=logit 0), C=concentration of the cross reacting compound at 50% B/B0. A selective assay does not show significant cross-reactions, whereas a group-selective assay measures a sum parameter. In this case the affinity of all cross-reacting analytes would be the same. However, these two cases are only extremes of a spectrum of assays with different ab affinities. Sensor arrays are expected to deal with different cross-reactivities by using chemometric approaches and neuronal networks for data analysis. 3.3.9. CONCLUSIONS

Antibodies as highly selective binding proteins are used for a great variety of antigens and haptens. At present time immunoassays are the most widely used analytical procedures in the immunochemical field because many test kits are available that fulfill defined quality requirements. Future applications will make extended use of immunochromatography, immunosensors and flow injection immunoanalysis. Therefore it is essential to extend the selectivities of abs to other analytes, especially in the environmental field. Since the classical procedures of ab production are too slow and cumbersome, recombinant techniques are expected to replace eventually the technologies of polyclonal and monoclonal ab production. The most significant breakthrough is expected from evolutionary strategies that are used to select and subsequently modify abs or fragments from ab libraries.

REFERENCES

Austyn, J.M. and Wood, K.J. (1993) Principles of cellular and molecular immunology. Oxford: Oxford University Press. Barbas III, C.F., Hu, D., Dunlop, N., Sawyer, L., Cababa, D., Hendry, R.M., Nara, P.L. and Burton, D.R. (1994) In vitro evolution of a neutralizing human antibody to HIV-1 to enhance affinity and broaden strain cross reactivity. Proc. Natl. Acad. Sci. USA, 91, 3809–3813. Beier, R.C. and Stanker, L.H. (1996) Immunoassays for residue analysis. Food safety. ACS Symposium Series, 621. Berson, S.A. and Yalow, R.S. (1959) Recent studies on insulin-binding antibodies. Ann. N.Y. Acad. Set., 82, 338–344. Butler, J.E. (1991) Immunochemistry of solid-phase immunoassay. Boca Raton, Ann Arbor, Boston, London: CRC Press. Chan, W.D. and Perlstein, M.T. (eds.) (1987) Immunoassay. A practical guide. Orlando (Florida), London: Academic Press, Inc. Clark, M. (1994) Internet (http://www.path.cam.ac.uk/~mrc7/igs/mikeimages.html). Dudley, R.A., Edwards, P., Ekins, R.P., Finney, D.J., McKenzie, I.G.M., Raab, G.M., Rodbard, D. and Rodgers, R.P.C. (1985) Guidelines for immunoassay data processing. Clin. Chem., 31, 1264–1271. Ekins, R. (1991) Immunoassay design and optimisation. In Principles and practice of immunoassays, Price, C.P. and Newman, D.J. (eds.) pp. 96–153, New York, USA: Stockton Press. Ekins, R.P. (1970) Theoretical aspects of saturation analysis. In In vitro procedures with radioisotopes in medicine. International Atomic Energy Agency. Printed by the IAEA, Wien, Austria. Huber, S.J. and Hock, B. (1986) Atrazine in water. In Methods of enzymatic analysis, Bergmeyer, H.U. (ed.) 12, 3rd edn. Weinheim: VCH Verlagsgesellschaft mbH. Jefferis, R. and Deverill, I. (1991) The antigen antibody reaction. In Principles and practice of immunoassay, Price, C.P. and Newman, D.J. (eds.) New York: Stockton Press. Kamps-Holtzapple, C. and Stanker, L.H. (1995) Development of recombinant single-chain variable portion recognizing potato glycoalkaloids. In Immunoassays for residue analysis. Food Safety, 209th ACS Meeting and Exposition, Beier, R.C. and Stanker, L.H. (eds.) pp. 485–499. California: Anaheim.

Karu, A.E., Scholthof, K.-B.G., Zhang, G. and Bell, C.W. (1994) Recombinant antibodies to small analytes and prospects for deriving them from synthetic combinatorial libraries. Food and Agricult. Immunol., 6, 277–286. Kemeny, D.M. and Challacombe, S.J. (1988) ELISA and other solid phase immunoassays. Theoretical and practical aspects. Chichester, New York, Brisbane, Toronto, Singapore: John Wiley & Sons. Klein, J. (1991) Immunologie. Weinheim: VCH Verlagsgesellschaft mbH. Köhler, G. and Milstein, C. (1975) Continuous cultures of fused cells secreting antibody of defined specificity. Nature, 256, 495–497. Kramer, K. and Hock, B. (1996) Recombinant single-chain antibodies against s-triazines. Food and Agricultural Immunology, 2, 97–109. Marks, J.D., Griffiths, A.D., Malmqvist, M., Clackson, T.P., Bye, J.M. and Winter, G. (1992) By-passing immunization: building high affinity human antibodies by chain shuffling. Bio/Technol., 10, 779–783. Price, C.P. and Newman, D.J. (1991) Principles and practice of immunoassays. New York, USA: Stockton Press. Raggatt, P. (1991) Data processing. In Principles and practice of immunoassays, Price, C.P. and Newman, D.J. (eds.) pp. 190–218, New York, USA: Stockton Press. Rodbard, D. and Cooper, J.A. (1970) A model for the prediction of confidence limits in radioimmunoassay and competitive protein binding assays. In In vitro procedures with radioisotopes in medicine. International Atomic Energy Agency, Vienna, 659–673. Rodgers, R.P.C. (1984) Data analysis and quality control of assays: A practical primer. In Clinical Immunoassay: The State of the Art, Butt, W.R. (ed.) New York: Marcel Dekker. Roitt, I. (1991) Essential immunology. 7th edn, London: Blackwell Scientific Publications. Tijssen, P. (1985) Practise and theory of enzyme immunoassays. In Laboratory techniques in biochemistry and molecular biology, Bordon, R.H. and van Knippenberg, P.H. (eds.) 15, p. 549. Amsterdam, New York: Elsevier. Van der Laan, M., Stanker, L.H., Watkins, B.E. and Roberts, D.W. (1991) Immunoassays for trace chemical analysis. Monitoring toxic chemicals in humans, food and the environment. ACS Symposium Series, 451. Winter, G., Griffiths, A.D., Hawkins, R.E. and Hoogenboom, H.R. (1994) Making antibodies by phage display technology. Annual Rev. Immunol., 12, 433–455.

3.4. DNA BASED BIOSENSORS

JOSEPH WANG 3.4.1. INTRODUCTION

The aim of the present chapter is to review new strategies for environmental monitoring based on DNA biosensors. The use of DNA as a selective recognition layer in biosensor design represents a new and exciting area in analytical chemistry. Unlike enzyme or antibodies, nucleic acid recognition layers are very stable, and can be readily synthesized for repeated use. Such recognition layers add new and unique dimensions to our arsenal of environmental biosensors, and should play a major role in future environmental analysis. Various strategies for environmental DNA biosensors will be examined in the following sections, including hybridization detection of nucleic acid from infectious microorganisms, as well as monitoring of small pollutants interacting with the immobilized DNA layer. While the field of DNA biosensors is still in infancy, there is no doubt that such devices will play a major role in future environmental analysis. 3.4.2. DNA STRUCTURE

DNA (deoxyribonucleic acid) is a very long molecule comprising of two very long strands wrapped around each other to form a helix. Each strand is comprised of a large number of monomeric units known as nucleotides (Figure 3.28). An individual nucleotide consists of three parts—a nitrogen-containing heterocyclic base, a sugar and a phosphoric acid residue—all of which are covalently bonded together. The order of the bases specifies the genetic code, while the phosphate and sugar groups have only a structural role. Among the four bases, two (adenine (A) and thymine (T)) are pyrimidines, while the other two (guanine (G) and cytosine)) are purines. The two strands are connected through hydrogen bonding. Only certain pairs of bases form these bonds (Figure 3.29); G always pairs with C (with 3 such bonds) and T always pairs with A (via 2 hydrogen bonds). Such paired DNA strands are said to be complementary. Knowledge of the nucleobase order in one strand is sufficient for defining the primary sequence of the other.

Figure 3.28. DNA structure: the double helix (top) along with the chemical composition of one of the strands (bottom). When DNA is denaturated, the double helix structure is broken down and the two complementary strands separate. Usually heat is needed to break the hydrogen bonds between the bases and disrupt the stacking interactions. Such heat denaturation of DNA is called melting. The binding of two complementary DNA strands together (reassociation of the hydrogen bonding) to reform the double helix is called hybridization. A complete turn of the helix spans ten base pairs, covering a distance

Figure 3.29. The structure of Watson-Crick base pairs. of 3.4 nm. The overall structure creates two distinct helical grooves, a minor one and a major one, which spiral around the surface of the duplex. The grooves create unique microenvironments for the binding of various molecules. The recognition of various pollutants by an immobilized DNA layer often relies on their binding within these grooves or by their intercalation between the base pairs of the double helix. Similar intercalative association has been used also for incorporating a (redox or optical) marker within DNA duplexes in connection with the detection of DNA hybridization. Intercalation is the insertion of a molecule (or its planar part) between two stacked base pairs (Figure 3.30). While it is not affecting the primary or secondary structures of DNA, it induces a partial lengthening (unwinding) of the helix. 3.4.3. SEQUENCE SPECIFIC HYBRIDIZATION BIOSENSORS

Detection of individual DNA sequences provides the basis for detecting a wide variety of microbial and viral pathogens. The basis for such DNA biosensing of specific DNA fragments is base pairing. Namely, such devices rely on the immob-

Figure 3.30. Intercalation association of a small molecule within the DNA. ilization of a single-stranded DNA sequence (the “probe”) on a transducer surface, which upon hybridization to its complementary strand (the “target”) gives rise to an electrical signal (Figure 3.31). The probes are typically short sequences (15–40 mer) that are capable of hybridizing with specific and unique regions of the target

Figure 3.31. Steps in sequence-specific biosensing of DNA hybridization.

Figure 3.32. Top: idealized signal development during the different steps of the hybridization biosensing cycle. Bottom: two assay cycles, in which the regeneration was performed thermally or chemically. (From Abel et al., 1996, with permission.) nucleotide sequence. The inherent specificity of these DNA recognition reactions has been coupled with the high sensitivity of piezoelectric (Okahata, 1992), electrochemical (Mikkelsen, 1996) and optical (Piunno et al., 1995) transducers. Proper surface immobilization is essential to assure high reactivity, accessibility and stability of the surface-bound probe, as well as for minimizing non-specific binding/adsorption events. Several probe immobilization schemes can be employed, depending often on the nature of the physical transducer. These include self-assembly of organized monolayers of thiol functionalized probes, carbodiimide covalent binding to an activated surface, attachment of biotinfunctionalized probes to avidin-coated surfaces, as well as adsorptive accumulation. The performance of such DNA biosensors depends on experimental variables affecting the hybridization event. These include the temperature, salt concentration, presence of accelerating/condensing agents, viscosity, contacting time, base composition (% G+C), and length of probe sequence. Careful control of the hybridization event is thus required. The

stability of duplexes formed between strands with mismatched bases is decreased according to the number and location of the mismatches. Recent studies have demonstrated that significantly enhanced selectivity can be achieved by the use of peptide nucleic acid (PNA) probes (Wang et al., 1996a). PNA is a structural DNA analog, with an uncharged pseudopeptide backbone (instead of the charged phosphate-sugar one). Because of their neutral backbone, PNA probes offer greater affinity in binding to complementary DNA, and improved distinction between closely related sequences. Such mismatch discrimination is of particular importance in the detection of disease-related mutations, in connection to genetic screening and therapy. Attention should be given also to the reusability of the DNA biosensors (i.e. to the regeneration of the surface-bound single-stranded probe after each assay). Both thermal and chemical (urea, sodium hydroxide) regeneration schemes have been shown useful for “removing” the bound target in connection with different DNA biosensor formats. Figure 3.32(bottom) illustrates two assays cycles, in which the regeneration is performed by either thermal or chemical regeneration. The top figure displays the idealized development of the signal during the various steps of the biosensor operation. Depending on the hybridization time, DNA biosensors commonly offer detection limits at the picomolar to nanomolar concentration range. Such levels are not low enough to allow most relevant environmental assays without PCR amplification. Miniaturized, silicon-based PCR units, developed in recent years, may be readily integrated with the new DNA biosensors for facilitating on-site environmental analysis. By further optimizing the probe immobilization, hybridization step, and detection process, DNA biosensors would allow direct detection without the need for a separate amplification step. 3.4.3.1. Electrochemical DNA biosensors

Several recent studies (Millan and Mikkelson, 1993; Wang et al., 1996b) demonstrated the utility of electroactive indicators for detection the hybridization between the surface-confined probe and its target sequence. Such indicator is a small redoxactive DNA intercalating or groove binding substance. Such compound has a much higher affinity for the resulting duplex compared to the single-stranded probe. Accordingly, the concentration of the indicator at the electrode surface increases when hybridization occurs, resulting in increased electrochemical response. For example, Figure 3.33 displays signals for 1 mg/1 of the pathogenic protozoan Cryptosporidium target DNA following different hybridization times (a–f, 1–7 min). Dashed and solid lines are the indicator (Co(phen) ) peaks at the Cryptosporidium-probe coated carbon-paste electrode in the absence and presence of the Cryptosporidium target, respectively. The difference between these peaks thus serves as the hybridization signal. A similar principle has been employed for the detection of DNA fragments from the Escherichia Coli pathogen at disposable carbon strip electrodes (Wang et al., 1997b). As desired for on-site environmental analysis, the operation of these screen-printed devices can

Figure 3.33. Chronopotentiograms for 1 mg/l of the Cryptosporidium DNA target, following different hybridization times(1(a), 2(b), 3(c), 4(d), 5(e) and 7(f) min (From Wang et al., 1997a, with permission). be readily integrated with hand-held analyzers. Both linear-scan or square-wave voltammetric modes (Millan and Mikkelsen, 1993) or constant-current chronopotentiometry (Wang et al., 1996b) can be used to detect the association of the redox indicator with the surface duplex. In addition to carbon paste or strip electrodes, such electrochemical scheme has been carried out in connection to gold and glassy-carbon electrodes. This strategy has been shown useful for the detection of common mutations, associated with diseases such as cancer (Wang et al., 1997c) or cystic fibrosis (Millan et al, 1994). Sequence specific electrochemical biosensors based on other detection strategies have been developed recently. These include electrochemical measurements of the solvent accessibility of nucleobases using electron transfer between DNA and metal complexes (Lumely-Woodyear et al., 1996), and the use of enzyme amplification in connection with an enzyme-intercalant conjugate (Kolakowski et al., 1996) or through proper electrical wiring of the enzyme (Johnston et al., 1995). 3.4.3.2. Optical DNA biosensors

Fiber optic transducers have been used successfully for the detection of DNA hybridization (Piunno et al., 1995; Abel et al., 1996). In a manner analogous to electrochemical hybridization biosensors, such devices commonly rely on the use of fluorescent indicators or labels for detecting the duplex formation. In the first study, the ssDNA probe was immobilized onto a quartz optical fiber activated with a long-chain aliphatic spacer arm. The covalently immobilized oligomers were found to hybridize to complementary ssDNA or ssRNA. The duplex formation at the fiber surface was monitored with the aid of an ethidium-cation fluorescent intercalating agent. The attractive features of this optical sensor include a low detection limit (of 86 ng/ml), reusability (at least 5 cycles) and high storage stability. The device of Abel et al. offered even lower detection limits down to 24 fmol (2×10−13 M) and an efficient chemical regeneration for multiple use (Figure 3.32).

Several hundreds assay cycles were thus performed with the same optical fiber. A biotinylated capture probe was immobilized onto the surface (via avidin), and a fluorescein-labeled complementary strand was used for the evanescent wave fluorescent detection of the hybridization event. The biotin-avidin interaction was used also in connection with a reusable DNA optical biosensor, based on real-rime resonant mirror detection of the duplex formation (Watts et al., 1995). High density DNA chips, described below, also rely on optical transduction of hybridization events. 3.4.3.3. Mass-based DNA biosensors

Mass-sensitive devices, particularly quartz crystal microbalance (QCM), have been used successfully for transducing hybridization events (Okahata et al., 1992). The QCM is a goldplated oscillating quartz crystal device suitable for measuring weight changes on the surface. When placed in an electronic oscillator circuit, an oscillating electrical field is applied to the crystal, resulting in an oscillating mechanical vibration. The fundamental principle of QCMDNA biosensors involves the frequency change (∆f) due to the mass increase on the QCM associated with the duplex formation: (1) where f0 is the resonant basic frequency, ∆m is the weight change on the surface of the crystal, and A is the coated area. Equation 1 is known as the Sauberbrey equation. The decreased resonant frequency upon the increase of mass on the QCM can thus be used for monitoring molecular binding processes. Such piezoelectric transduction mode offers direct in-situ detection of hybridization event, without any (redox or optical) indicator or label, and allows measurements of minutes mass changes (as low 10−12 g). Nonspecific adsorption effects can be addressed using a reference (uncoated) crystal. Additional mass-sensitive transducers, including surface-acoustic wave (SAW) or thickness-shear mode (TSM) devices, have also been used for the detection of hybridization reactions. 3.4.3.4. High-density DNA chips

The discriminative power of nucleic acid hybridization tests can be dramatically enhanced by using more than one oligonucleotide probe. Recent advances in photolitography and combinatorial chemical synthesis have led to the development of high-throughput “DNA chips” (Borman, 1996; Noble, 1995). The high precision and resolution of such thin-film microfabrication technology allows for the generation of high density arrays of immobilized probes (in the range of 105–106 probes per cm2). Using these microfabricated surfaces, multiple sequences can be assayed in a single experiment. Different fragments from the organism, or several microorganisms may thus be determined simultaneously. The multiple hybridization events are commonly detected optically (using fluorescent tags) to produce a readable pattern, based on quantifying the label in each site. The fluorescent intensity data, captured from the scanner, are used with computer files to provide DNA profiling of the test sample. These chips,

pioneered by Affymetrix Inc (Santa Clara, CA), will eventually be incorporated into micromachined analyzers that will integrate the sample handling and amplification step with the detection process. DNA biosensor arrays have been developed also in connection with a bundle of optical fibers, with each fiber carrying a different oligonucleotide probe (Ferguson et al., 1996). Hybridization of fluorescently labeled complementary strands was accomplished by observing the increase in fluorescence that accompanied the binding event. This resulted in a fast (3 −1 Demand (BOD) (mgL O2)

>3

>5

>7

—Determination of the dissolved oxygen before and after incubation of 5 days on the dark

Chemical Oxygen Demand – (COD) (mg L−1 O2)

–

–

30

—Potassium dichromate method

Nitrogen (mg L−1 N)

1

1

2

3

—Mineralization, destination by Kjeldahl method and Molecular Absorption Spectrophotometry

Substances Extractable in Chloroform (µg L−1 dry residue)

100

100 200 500

10** Dissolved or Emulsified Hydrocarbons; Mineral Oil (µg L−1)

—Extraction with purified chloroform, evaporation and dry weight verification

50* 200* 500/ —IR Spectroscopy after extraction 1000* with CCl4 —Gravimetry after extraction with petroleum ether

Phenols (Phenol Index) (µg 0.5** L−1)

1*

1/5* 10/ 100*

—Molecular Absorption Spectrophotometry —4-Aminoantipyrine method —Paranitroaniline method

Surfactants (Reacting with Methylene Blue) (µg L−1)

200**

200 200 500

—Molecular Absorption Spectrophotometry

Polycyclic Aromatic Hydrocarbons (µg L−1)

0.2**

0.2* 0.2* 1*

—UV Fluorescence after TLC —Comparison with a mixture of 6 standard substances with the same concentration

Organochlorinated Compounds (µg L−1)

1

–

–

–

—Gas chromatography after extraction with appropriate solvents and purification

A1: Simple physical treatment and disinfection; A2: Normal physic treatment, chemical treatment and disinfection; A3: Intensive physical and chemical treatments, refining and

desinfection * Mandatory level ** MAC Values Data extracted from Bulletin of the European Communities, No. L 194/33, 07.25.75 and from Boletín Oficial del Estado (Spain), No. 53, 03.02.88 techniques. Such an approach defies the legislative confines or even aspires to redefine them. It is possible that such technological advances will enlarge the existing range of uses confined by legislation. Above all, they point to the possibility of the unravelling of new markets composed of non-expert users that could make the Table 4.2. Major Legislated Limits for Organic Pollutants in Waste Water. Compound

Industrial Sector

Value per month mgL

Chloroform

a) Production of chloromethanes from methanol or a 1 mixture of methanol and methane b) Production of chloromethanes by chloration of methane

1

c) Production of chlorofluorocarbon (CFC)

–

1,2-Dichloroethane (DCE) a) Production of DCE (without transformation or use 1.25 at the same site) b) Production of DCE and transformation or use at the same site, except for e)

2.5

c) Transformation of DCE into substances other than 1 vinyl chloride d) Use of DCE for metal degreasing (out of the industrial sites mentioned in b)

0.1

e) Use of DCE in the production of ion exchangers

0.1

Hexachlorobenzene (HCB) a) Production and transformation of HCB

Hexachlorobutadiene (HCBD) Hexachlorocyclohexane (HCH)

1

b) Production of PCE and CCl4 by perchloration

1.9

c) Production of PCE and/or trichloroethylene by another process

–

a) Production of PCE and CCl4 by perchloration

1.5

b) Production of PCE and CCl4 by another process

–

a) Production of HCH

2

b) Extraction of lindane

2

c) Production of HCH and extraction of lindane

2

d) Other sectors

2

Pentachlorophenol (PCP)

a) Production of PCP-Na by hydrolysis of HCB

1*

Perchloroethylene (PCE)

a) Production of TCE and PCE (procedures TCEPCE)

0.5

b) Production of CCl4 and PCE (procedures CCl4PCE)

1.25

c) Use of PCE for metal degreasing

0.1

d) Production of chlorofluorocarbon

–

a) Production of TCB by dehydrochloration and/or transformation of TCB

1

b) Production and/or transformation of chlorobenzene by chloration of benzene

0.05

a) Production of TCE and PCE

0.5

b) Use of TCE for metal degreasing

0.1

Trichlorobenzene (TCB)

Trichloroethylene (TCE)

Limit values per day will be twice the mentioned concentration The reference method for determination is Gas Chromatography * The reference method for determination is Gas or Liquid Chromatography Data extracted from Boletín Oficial del Estado, No. 2475, 11.23.87, No. 613, 03.13.89, No. 2425, 10.31.89, No. 1244, 05.09.91, No. 1719, 06.28.91 investment in product development worthwhile. Such an outcome of the present activity in biosensor research would be desirable. The difficulties involved in all analytical situations mentioned above explain why the involvement of the private sector in the development of environmental biosensors is generally low. They also point to the directions of most efficient use of resources for the development of commercially important biosensors for environmental analysis that should be based on generic technologies and multianalyte sensors. This explains the fact that at present most of the commercial efforts are centered on microbial sensors and on the development of immunoassays since for the latter exist generally trouble-free methods for the development of antibodies and a well established format (ELISA) to use them (Chap. 3.3.). As a result, many kits have been made commercially available in the last few years that with more or less success have met new analytical challenges and have even started legislation reform processes in some cases. On the other hand, work on enzymatic sensors appears to have centered on the more traditionalist approach of meeting legislative requirements either as disposable sensors or as modular detectors in sample pretreatment flow systems. Having to compete with the well established analytical

methods, these types of biosensors are still in the validation stage. The enzymatic sensors involving the catalytic transformation of the pollutant (Chap. 4.3.1, 4.6.), such as the phenolics sensors based on tyrosinase, are by far the most advanced in this process. The inhibition or enzymatic activity modulation sensors find application mainly in the pesticide (Chap. 4.1.1.), heavy metals (Chap. 4.4.) and phosphate (Chap. 4.5.) monitoring and are treated separately.

4.1. PESTICIDES

URSULA BILITEWSKI More than 300 compounds are used in agriculture for plant protection. They differ in chemical nature and accordingly in their mode of action and application area. Most of the active ingredients are herbicides and among them the organic compounds are the major group. They are organophosphorous compounds (e.g. glyphosat), carbamates, thiocarbamates, urea derivatives (e.g. diuron), triazines (e.g. atrazine) and others. Another important group of pesticides are the insecticides to control animal pests. Again different chemical classes are used: the organophosphorous compounds and carbamates are also active as insecticides, another wellknown group are the chlorinated hydrocarbons (e.g. DDT, aldrin), but also some “natural insecticides” and derived synthetic compounds are known, such as pyrethroides and pyrethrins. Of some groups the biological mode of action is known, for example some herbicides (e.g. atrazine, diuron) block photosynthesis by binding to the photosynthetic reaction centre in plants, and organophosphorous compounds and carbamates are very effective inhibitors of the acetylcholinesterase. However, from a large number of pesticides the site of action is not known, and also toxic effects on animal and men can often not totally be excluded. Due to their different chemical nature these compounds also differ strongly in their natural degradation rate, which may be due to microbial metabolism or chemical turnover, e.g. hydrolysis or photochemical degradation. For example the first generation of insecticides, the chlorinated hydrocarbons, were rather stable, thus remained on the plants and reached water ways and the food chain. To minimize the risk for continuous intoxination in a lot of countries the use of pesticides is regulated and it is aimed at the maintainance of a pesticide-free drinking water. Therefore, upper allowable concentrations were set, for example, in Europe 0.1 µg/L for a single pesticide independent on the toxicity of the compound. This concentration level was defined according to the lower detection limits of standard analytical methods and has stimulated research to improve existing methods and establish new ones. Thus, next to HPLC and GC (see Chap. 7) biochemical methods were established and among them a variety of biosensor systems, aiming at the determination of herbicides, insecticides and fungicides in the relevant concentration range without the necessity of enrichment procedures. They utilize mainly the inhibitory power of pesticides on enzymes (Chap. 3.1.2, 4.1.1.) or the binding of analytes by antibodies (Chap. 3.3, 4.1.2.). 4.1.1. ENZYMATIC SYSTEMS

THIERRY NOGUER, BÉATRICE LECA AND JEAN-LOUIS MARTY 4.1.1.1. Introduction

Biosensors have been found to be simple, cost-effective and easy-to-handle tools that could be extremely useful for environmental monitoring. The detection of pesticides is based, in some cases, on the catalytic transformation of the pesticides by a selected enzyme, i.e. organophosphorus hydrolase for organophosphorus insecticides. Nevertheless, pesticides are toxic compounds that usually act by inhibiting one or several enzyme(s). Therefore, the detection of such compounds is primarily based on the inhibitory properties of the pesticide. Since the

specificity of enzymes for inhibitors is quite wide, the measured response can be related to a family of pesticides rather than to a specific compound. Contrary to immunosensors, enzymebased sensors can be considered as early-warning devices because they are sensitive to a relatively large spectrum of compounds. 4.1.1.2. Organophosphorus and Carbamate pesticides

Organophosphorus and carbamic compounds represent a large percentage of currently used pesticides (insecticides, fungicides, herbicides…). These pesticides have harmful consequences as they act as inhibitors of cholinesterases which are involved in neuronal transmission. It is therefore not surprising to note that cholinesterase-based electrodes form the basis of the detection methods most frequently described in the literature. Acetyl- or butyryl-cholinesterases (AChE, E.C. 3.1.1.7 or BuChE, E.C 3.1.1.8), which are enzymes that catalyze the hydrolysis of acetyl- or butyrylcholine into choline and acetate or butyrate, have been purified and are now commercially available. The development of electrochemical biosensors, based on the potentiometric or amperometric detection of compounds has been evaluated in recent review of this topic by Trojanowicz and Hitchman (1996). The use of cholinesterase as a sensing element does not allow for the selective detection of a particular pesticide, but rather provides an estimation of the total anticholinesterase activity present in a sample. This activity represents the “toxicological index”, which is defined as the quantity of compounds that induce a percentage of cholinesterase inhibition equivalent to that produced by a known amount of a reference pesticide. In this report, paraoxon has been chosen as the reference compound as this pesticide is stable, commercially available, and known to have a strong inhibitory effect on cholinesterases. Each cholinesterase has been characterized by its own affinity for organophosphorus and carbamate pesticides. The activity and stability of cholinesterases, as well as their sensitivity towards a given inhibitor, depend on the type and the source of cholinesterase. Therefore, the selection of a suitable cholinesterase is a key step in the design of a pesticide biosensor. In this paper, we will focus on potentiometric and amperometric biosensors. Potentiometric biosensors have been designed based on the measurement of pH change, electrode potential change or more sophisticated methods such as ISFET (ion-selective fieldeffect transistor) or LAPS (light-addressable potentiometric sensors). The change in pH is induced by the formation of an organic acid during the hydrolysis of the choline ester by an appropriate esterase, with detection based on the use of pH electrodes (Durand and Thomas, 1984; Tran-Minh et al., 1990; El Yamani et al., 1987; El Yamani et al., 1988; Tran-Minh, 1993; Kumaran and Morita, 1995; Budnikov and Evtugyn, 1996).

Among the biosensors based on the change in redox potential, Ghindilis et al. (1996) developed an original approach by coupling BuChE, ChOD and peroxidase. ISFET (Dumschat et al., 1991; Vlasov et al, 1991; Nyamsi Hendji et al., 1993) and LAPS (Rogers et al., 1991; Fernando et al., 1993; Dehlawi et al., 1994) biosensors have also been reported. As can be seen in table 4.3, the highest sensitivity (0.3ppb) was achieved by Tran-Minh et al. (1990) using AChE immobilized on a glass pH electrode by cross-linking with polyacrylamide. With the exception of this work, the detection limits reported are generally close to 3ppb (Table 4.3). The potentiometric methods

are fast and accurate, but they show quite high detection limits. Furthermore, the potentiometric detection of H+ ions lacks sensitivity due to the consumption of protons by the buffer following proton liberation during the enzyme reaction. The amperometric method of detection is generally more sensitive and allows one to obtain a signal that is directly proportional to the analyte concentration. Depending on the cholinesterase substrate, different amperometric approaches have been described using mono- or bi-enzymatic systems based on the detection of thiocholine, O2, H2O2 or 4-aminophenol. With acetyl- or butyryl-choline as the substrate, bienzyme electrodes coupling a cholinesterase with choline oxidase (ChOD) Table 4.3. Potentiometric cholinesterase-based electrodes. Enzyme (origin)

Immobilization mode

Detection limit of References paraoxon (ppb)

BuChE (ns)

cross-linking with BSA and glutaraldehyde

3

El Yamani et al., 1987

BuChE (hs)

immobilization on nylon with HSA and glutaraldehyde

3

El Yamani et al., 1988

AChE (ns)

cross-linking with polyacrylamide

0.3

Tran-Minh et al., 1990

AChE (ee) (biotinylated)

immobilization on biotinylated cellulose nitrate membrane via streptavidin crosslinking (LAPS)

2.8

Rogers et al., 1991; Fernando et al., 1993; Dehlawi et al., 1994

AChE: acetylcholinesterase; BSA: bovine serum albumin; BuChE: butyrylcholinesterase; ee: electric eel; hs: horse serum; HSA: human serum albumin; LAPS: light-addressable potentiometric sensor; ns: not specified. have been reported, with measurement based on the detection of oxygen or hydrogen peroxide, the latter being more sensitive (Table 4.4):

Table 4.4. Bienzymatic electrodes based on an amperometric detection (O2 or H2O2 detection). Enzymes/ Immobilization mode

Potential

Detection limit of paraoxon (ppb)

References

BuChE (hs)+ChOD/ two enzymes in a dialysis membrane

Clark oxygen electrode

300

Campanella et al., 1991

AChE (ns)+ChOD/ covalent linking on nylon with glutaraldehyde

650 mV vs. Ag/AgCl (Pt)

2

Bernabei et al., 1991

AChE (ns) or BuChE (ns)+ ChOD/covalent linking on nylon with glutaraldehyde

650 mV vs. Ag/AgCl (Pt)

2

Palleschi et al., 1992

AChE (ee)+ChOD/ immobilization in PVA-SbQ

650 mV vs. Ag/AgCl (Pt)

0.03

Mionetto et al., 1992

AChE (ee)+ChOD/ immobilization in PVA-SbQ

650 mV vs. Ag/AgCl (Pt)

2.8

Marty et al., 1992

AChE: acetylcholinesterase; BSA: bovine serum albumin; BuChE: butyrylcholinesterase; ChOD: choline oxidase; ee: electric eel; hs: horse serum; ns=not specified; PVA-SbQ: poly(vinylalcohol) bearing styrylpyridinium groups. It is possible to perform a preliminary hydrolysis of the substrate using cholinesterase in solution and then detect choline using a choline biosensor (Palleschi et al., 1992; Bernabei et al., 1993; Cagnini et al., 1995a; Cagnini et al., 1995b). In this way, the lowest measured detection limit was 0.5 ppb paraoxon, as reported by Bernabei et al. (1993). Cremisini et al. (1995) have also made use of a choline probe in which AChE was immobilized separately from ChOD, thus allowing the incubation and measurement steps to be performed independently. In this case, the detection limit was 1.3 ppb of paraoxon. Another approach consists of co-immobilizing the two enzymes at the electrode surface (Bernabei et al., 1991; Wollenberger et al., 1991; Marty et al., 1992; Mionetto et al., 1992) allowing greater sensitivities and higher responses to be obtained. When comparing the results reported in the literature (Table 4.4), the highest sensitivity was obtained by Mionetto et al. (1992) (0.03 ppb paraoxon) using poly(vinyl alcohol) bearing styrylpyridinium groups (PVA-SbQ) as an immobilization matrix. The design of the sensor and the optimization of its performance can be simplified using monoenzymatic systems based on the hydrolysis of acetyl- or butyrylthiocholine by a selected cholinesterase (AChE or BuChE). Using such a principle, detection is based on the oxidation of thiocholine produced on a platinum electrode (Table 4.5):

In this way, the detection potential is lower than that used for the previously described oxidation of hydrogen peroxide (410 mV instead of 650 mV vs. Ag/AgCl on platinum). It is also possible to achieve such a result using electronic mediators such as TCNQ (Martorell et al., 1996) or CoPC (Sklàdal, 1992; Sklàdal and Mascini, 1992). In 1992, Sklàdal reported the detection of 0.08 ppb paraoxon by cross-linking BuChE with glutaraldehyde on a carbon electrode modified with cobalt phthalocyanine (CoPC). Using AChE immobilized in a PVA-SbQ matrix, Marty et

al. (1995) succeeded in reaching a detection limit of 0.03 ppb for paraoxon. Some studies have been successfully validated using chromatographic methods (Marty et al., 1995; Barceló et al., 1995). Monoenzymatic devices using 4-aminophenyl acetate as a substrate have also been reported; in these cases detection was carried out by the oxidation of 4-aminophenol at 0.25 V vs. SCE on a glassy carbon electrode (La Rosa et al., 1994; La Rosa et al., 1995; Pariente et al., 1996). With these electrodes, a detection limit of 1.1 ppb paraoxon is possible. It should be noted that indoxyl acetate has also been used as a substrate by Razumas et al. (1981), with the amperometric detection based on the oxidation of indigo white at 0.3V vs. Ag/AgCl. In this case, butyrylcholinesterase was used in solution which, to our knowledge, is a method that has not been previously reported in a biosensor configuration. Finally, two different cholinesterases can be co-immobilized in the same biorecognition layer (Sklàdal et al., 1994). When compared to sensors using only one specific cholinesterase, such devices permit the detection of a greater number of pesticides, thus enlarging the range of detectable compounds. Table 4.5. Monoenzymatic electrodes based on an amperometric detection (thiocholine oxidation). Enzyme/ immobilization mode

Potential

Detection limit References of paraoxon (ppb)

BuChE (hs)/cross-linking with glutaraldehyde

250mV vs. Ag/AgCl (CoPC modified carbon electrode)

0.08

Sklàdal, 1992

AChE (ee) or BuChE (hs)/cross-linking 300 mV vs. Ag/AgCl with glutaraldehyde (CoPC modified carbon electrode)

1.5

Sklàdal and Mascini, 1992

AChE (ee) or/and BuChE (hs)/crosslinking with BSA and glutaraldehyde

250mV vs. Ag/AgCl (CoPC modified graphite electrode)

2.8

Sklàdal et al., 1994

AChE (ee)/immobilization in epoxygraphite

700 mV vs. Ag/AgCl

28

Martorell et al., 1994

AChE (ee)/immobilization in PVASbQ

410 mV vs. Ag/AgCl 0.03 (Pt)

Marty et al., 1995

AChE (ee or be) or BuChE 300 mV vs. Ag/AgCl (hs)/immobilization on aminated silica (TCNQ modified particles in epoxy-graphite graphite)

27.5

Martorell et al., 1996

AChE (ee)/immobilization in PVASbQ

0.3

Jeanty and Marty, 1997

410 mV vs. SCE (Pt)

AChE: acetylcholinesterase; be: bovine erythocytes; BSA: bovine serum albumin; BuChE: butyrylcholinesterase; CoPC: cobalt phthalocyanine; ee: electric eel; hs: horse serum; PVA-SbQ: poly (vinylalcohol) bearing styrylpyridinium groups; TCNQ: tetracyanoquinodimethane.

One of the main requirements when detecting inhibitors is the need to reactivate the inhibited enzyme in order to allow for continuous monitoring. In the case of irreversible inhibitors of cholinesterases such as organophosphorus insecticides, the reactivation of the enzyme is performed by using a powerful nucleophilic reagent such as 2-PAM (2-pyridinealdoxime methiodide) (Tran-Minh et al., 1990; Mionetto et al., 1994; Marty et al., 1995) or TMB-4 ({1,1′trimethylenebis-4-(hydroxyiminomethyl)-pyridinium bromide}) (Budnikov and Evtugyn, 1996). 4.1.1.3. Other pesticides

In addition to cholinesterase-based biosensors, the detection of pesticides has been carried out using aldehyde dehydrogenase, acetolactate synthase, tyrosinase or peroxidase, with each enzyme being inhibited by a specific family of pesticides. Dithiocarbamate fungicides form the most important class of pesticides for the broad spectrum control of a variety of fungal diseases in crops. They are mainly composed of ethylenebis(dithiocarbamate) (maneb, zineb, mancozeb…) and dimethyldithiocarbamate compounds (ziram, ferbam…). While the target of action of dithiocarbamate fungicides is unknown, these compounds have been detected using biosensors configured to measure the inhibition of aldehyde dehydrogenase (AlDH) or tyrosinase. With respect to aldehyde dehydrogenase, Marty and Noguer (1993) developed an amperometric bienzymic sensor for the detection of ethylenebis(dithiocarbamate) by coupling AlDH with diaphorase, with detection based on hexacyanoferrate (II) oxidation:

The optimization of enzyme loading and incubation time led to a detection limit as low as 1.5ppb maneb (Noguer and Marty, 1997). An alternative form of dithiocarbamate detection is to use tyrosinase as the target enzyme:

Besombes et al. (1995a) used a polypyrrole membrane to detect, among other compounds, diethyldithiocarbamate. Since many dithiocarbamates are hydrophobic compounds, Wang et al. (1993) described a sensor for diethyl-dithiocarbamates to be used in organic media. Another approach, based on reversed micelle systems, was reported by Pérez Pita et al. (1997) in which a detection limit of 22.6ppb ziram was obtained.

Triazine herbicides are photosynthesis inhibitors which are persistent and remain active in the environment for several years, causing continuous water pollution. The detection of these pesticides by sensors has been described by Rawson et al. (1989) using cyanobacteria, and by Rouillon et al. (1995) who used thylakoid membranes. The first enzyme sensor for the detection of these herbicides was that reported by McArdle and Persaud (1993), based on tyrosinase inhibition. Using this principle, McArdle and Persaud (1993) and Besombes et al. (1995a) achieved a detection limit of around 1 ppm atrazine. It must be stressed that tyrosinase has also been used for the detection of a wide range of pesticides and pollutants that can act as substrates or inhibitors (Besombes et al., 1995ab). This lack of specificity may be an advantage if the sensor is used as a warning system for general environmental pollution. Sulfonylurea and imidazolinone herbicides (e.g. sulfometuron methyl, thifensulfuron methyl) are used for the control of broad-leaved weeds and grasses in cereal crops. Based on the fact that these herbicides are powerful inhibitors of acetolactate synthase, Seki et al. (1996) reported the design of an amperometric biosensor the detection of herbicide concentrations as low as 10−6 M, with detection based on the monitoring of oxygenase side-activity of ALS:

4.1.1.4. Conclusion

The detection of environmental pollutants using enzyme-based biosensors has been widely described in literature and appears promising since these devices are simple, fast, portable and they can be used for on-line monitoring. For this purpose, many authors have coupled amperometric biosensors with continuous flow techniques (Wollenberger et al, 1991; La Rosa et al., 1995; Jeanty and Marty, 1997). Such systems could be used as early-warning devices in cases such as water pollution monitoring, for instance. Keeping in mind that pesticides are generally hydrophobic compounds that must be extracted and concentrated using organic solvents, organic phase enzyme electrodes (OPEEs) have been developed. These devices, mainly devoted to substrate determination, have had their use extended towards the determination of pesticide concentrations in organic media. Mionetto et al. (1994) demonstrated the possible use of an acetylcholinesterase-based biosensor for the detection of organophosphorus and carbamate pesticides in organic solvents. Other reports have been devoted to tyrosinase-based sensors used in organic media (Wang et al., 1993; Adeyoju et al., 1994; Adeyoju et al., 1995; Deng and Dong, 1996) or in reversed micellar systems (Reviejo et al., 1995; Stancik et al., 1995). Based on these considerations, biosensors will undoubtedly play an important role in future environmental monitoring. As highlighted by many authors (Evans et al., 1986; Bogue, 1993; Dennison and Turner, 1995; Rogers, 1995), several requirements must be taken into account before such devices can be accepted, used and commercialized. The main problem to be overcome is that linked to the stability of the target enzyme. In view of improving this parameter, investigations now focus on the isolation of enzymes, from natural or genetically engineered thermophilic micro-organisms, that show enhanced stability at high temperatures. The development of artificial enzymes bearing functional moities that mimic natural enzyme activity, named “synzymes”, is also particularly promising.

REFERENCES

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Jeanty, G. and Marty, J.-L. (1998) Detection of paraoxon by continuous flow system-based enzyme sensors. Biosensors and Bioelectronics, 13(2), 213–218. Kumaran, S. and Morita, M. (1995) Application of a cholinesterase biosensor to screen for organophosphorus pesticides extracted from soil. Talanta, 42, 649–655. La Rosa, C., Pariente, F., Hernandez, L. and Lorenzo, E. (1994) Determination of organophosphorus and carbamic pesticides with an acetylcholinesterase amperometric biosensor using 4-aminophenyl acetate as substrate. Anal. Chim. Acta, 295, 273–282. La Rosa, C., Pariente, F., Hernandez, L. and Lorenzo, E. (1995) Amperometric flow-through biosensor for the determination of pesticides. Anal. Chim. Acta, 308, 129–136. Martorell, D., Céspedes, F., Martìnez-Fàbregas, E. and Alegret, S. (1994) Amperometric determination of pesticides using a biosensor based on a polishable graphite-epoxy biocomposite. Anal. Chim. Acta, 290, 343–348. Martorell, D., Céspedes, F., Martìnez-Fàbregas, E. and Alegret, S. (1996) Determination of organophosphorus and carbamate pesticides using a biosensor based on a polishable 7,7,8,8tetracyanoquinodimethane-modified graphite-epoxy biocomposite. Anal. Chim. Acta, 17693, 1– 9. Marty, J.-L. and Noguer, T. (1993) Bi-enzyme amperometric sensor for the detection of dithiocarbamate fungicides. Analusis, 21, 231–233. Marty, J.-L., Mionetto, N., Lacorte, S. and Barceló, D. (1995) Validation of an enzymatic biosensor with various liquid chromatographic techniques for determining organophosphorus pesticides and carbaryl in freeze-dried waters. Anal. Chim. Acta, 311, 265–271. Marty, J.-L., Sode, K. and Karube, I. (1992) Biosensor for detection of organophosphate and carbamate insecticides. Electroanal., 4, 249–252. McArdle, F.A. and Persaud, K.C. (1993) Development of an enzyme-based biosensor for atrazine detection. Analyst, 118, 419–423. Mionetto, N., Marty, J.-L. and Karube, I. (1994) Acetylcholinesterase in organic solvents for the detection of pesticides: biosensor application. Biosensors andBioelectronics, 9, 463–470. Mionetto, N., Rouillon, R. and Marty, J.-L. (1992) Inhibition of acetylcholinesterase by organophosphorus and carbamates compounds. Studies on free and immobilized enzymes. Z.Wasser-Abwasser-Forsch., 25, 171–174. Noguer, T. and Marty, J.-L. (1997) High sensitive bienzymic sensor for the detection of dithiocarbamate fungicides. Anal. Chim. Acta, 347, 63–70.

Nyamsi Hendji, A.M., Jaffrezic-Renault, N., Martelet, C., Clechet, P., Shul’ga, A.A., Strikha, V.I., Netchiporuk, L.I., Soldatkin, A.P. and Wlodarski, W.B. (1993) Sensitive detection of pesticides using a differential ISFET-based system with immobilized cholinesterases. Anal. Chim. Acta, 281, 3–11. Palleschi, G., Bernabei, M., Cremisini, C. and Mascini, M. (1992) Determination of organophosphorus insecticides with a choline electrochemical biosensor. Sensors and Actuators B, 7, 513–517. Pariente, F., La Rosa, C., Galan, F, Hernandez, L. and Lorenzo, E. (1996) Enzyme support systems for biosensor applications based on gold-coated nylon meshes. Biosensors and Bioelectronics, 11, 1115–1128. Pérez Pita, M.T., Reviejo, A.J., Manuel de Villena, F.J. and Pingarron, J.M. (1997) Amperometric selective biosensing of dimethyl- and diethyldithiocarbamates based on inhibition processes in a medium of reversed micelles. Anal. Chim. Acta, 340, 89–97. Rawson, D.M., Willmer, A.J. and Turner, A.P.P. (1989) Whole-cell biosensors for environmental monitoring. Biosensors, 4, 299–311. Razumas, V.J., Kulys, J.J. and Malinauskas, A.A. (1981) High-sensitivity bioamperometric determination of organophosphate insecticides. Environ. Sci. Technol., 15, 360–361. Reviejo, A.J., Fernàndez, C., Liu, F., Pingarron, J.M. and Wang, J. (1995) Advances in amperometric enzyme electrodes in reversed micelles. Anal. Chim. Acta, 315, 93–99. Rogers, K.R. (1995) Biosensors for environmental applications. Biosensors and Bioelectronics, 10, 533–541. Rogers, K.R., Foley, M., Alter, S., Koga, P. and Eldefrawi, M. (1991) Light addressable potentiometric biosensor for the detection of anticholinesterases. Anal. Lett., 24, 191–198. Rouillon, R., Sole, M., Carpentier, R. and Marty, J.-L. (1995) Immobilization of thylakoids in poly(vinyl alcohol) for the detection of herbicides. Sensors and Actuators B, 26/27, 477–479. Seki, A., Ortéga, F. and Marty, J.-L. (1996) Enzyme sensor for the detection of herbicides inhibiting acetolactate synthase. Anal. Lett., 29, 1259–1271. Sklàdal, P. (1992) Detection of organophosphate and carbamate pesticides using disposable biosensors based on chemically modified electrodes and immobilized cholinesterase. Anal. Chim. Acta, 269, 281–287. Sklàdal, P. and Mascini, M. (1992) Sensitive detection of pesticides using amperometric sensors based on cobalt phthalocyanine-modified composite electrodes and immobilized cholinesterases. Biosensors and Bioelectronics, 7, 335–343.

Sklàdal, P., Pavlìk, M. and Fiala, M. (1994) Pesticide biosensor based on coimmobilized acetylcholinesterase and butyrylcholinesterase. Anal. Lett., 27, 29–40. Stancik, L., Macholàn, L. and Scheller, F. (1995) Biosensing of tyrosinase inhibitors in nonaqueous solvents. Electroanal., 7, 649–651. Tran-Minh, C. (1993) Biosensors for the analysis of pesticide residues. Anal. Proc., 30, 73–74. Tran-Minh, C., Pandey, P.C. and Kumaran, S. (1990) Studies on acetylcholine sensor and its analytical application based on the inhibition of cholinesterase. Biosensors and Bioelectronics, 5, 461–471. Trojanowicz, M. and Hitchman, M.L. (1996) Determination of pesticides using electrochemical biosensors. TrAC, 15, 38–45. Vlasov, Y., Bratov, A., Levichev, S. and Tarantov, Y. (1991) Enzyme semiconductor sensor based on butyrylcholinesterase. Sensors and Actuators B, 4, 283–286. Wang, J., Dempsey, E., Eremenko, A. and Smyth, M.R. (1993) Organic-phase biosensing of enzyme inhibitors. Anal. Chim. Acta, 279, 203–208. Wollenberger, U., Setz, K., Scheller, W., Löffler, U., Göpel, W. and Gruss, R. (1991) Biosensors for choline, choline esters and inhibitors of choline esterase. Sensors and Actuators B, 4, 257– 260.

4.1.2. AFFINITY SENSOR SYSTEMS

G.GAUGLITZ, J.PIEHLER AND U.BILITEWSKI 4.1.2.1. Introduction

Immunoassays are an attractive approach to environmental analysis providing simple, low-cost but sensitive and rugged detection. However, total assay times of conventional immunoassays based on microtiter plate format are in the range of several hours and these methods are not readily automated. Affinity sensor systems attempt to overcome this drawback. The most straightforward approach is to speed up conventional enzyme immunoassays by using flow systems as described in detail in Chap. 2.3. This has been successfully implemented reaching sensitivities comparable to the corresponding microtiter plate format immunoassay (Krämer et al., 1997b). The development of a variety of novel detection methods led to the concept of the immunoprobe: These techniques allow direct, time-resolved monitoring of the interaction of antibodies with the analyte at a transducer surface. An attractive approach for detecting antibody-analyte interaction is to avoid any labeling of the interacting compounds. A variety of transducers based on optical or acoustical interrogation that allow label-free detection of binding at interfaces have been investigated (Brecht, Gauglitz, 1995b, and Chapter 2.2.). This approach is particularly attractive for implementing immunoprobes and numerous applications with respect to pesticide detection have been reported (Minnuni, Mascini, 1993; Heideman et al., 1993; Bier et al., 1994; Brecht et al, 1995a; Tom-Moy et al, 1995; Horácek, Skládal, 1997; Mouvet et al., 1997; Schipper et al., 1997; Drapp et al., 1997). A combination of the sensitivity of label-based detection and the advantages of a direct assay is possible by using fluorescence labeled antibodies or tracers. Binding at the transducer surface is then detected by selective fluorescence excitation adjacent to the surface by total internal reflection (total internal reflection fluorescence, TIRF). This technique found interest for various analytical problems including environmental analysis (Bier et al., 1992; Zhao et al., 1995; Brecht et al., 1997b). All these methods are based on separation of bound and non-bound species by immobilizing one of the interacting compounds on the surface of a solid support. In addition fluorescence based detection allows rapid detection in homogeneous phase without separation being required. However, this chapter will focus on detection in heterogeneous phase. Some basic principles and requirements valid for all affinity sensor systems will be stated in the first part of this chapter. Later on, the application of different detection methods will be discussed in more detail, followed by a critical conclusion and an outlook to future developments in this field.

Figure 4.1. Typical immunoassay formats used for affinity sensor systems. I: pretreated surface; II: surface after the assay. 4.1.2.2. Assay format, surface modification and sample handling

The performance of affinity sensor systems based on interactions at the solid/liquid interface strongly depends on the assay format, the properties of the surface, and the material transport to the surface. Adjusting these parameters systematically to the detection system is therefore essential. 4.1.2.2.1. Assay formats

Heterogeneous phase immunoassay allows a variety of different test formats. Some typical examples used in affinity sensor systems are depicted in Figure 4.1. Most simple is a binding inhibition assay which is frequently used for immunoprobes. Antibody is incubated with the sample to allow the analyte to bind to the antibody binding sites according to the analyte concentration (law of mass action). The remaining free antibodies are determined by detecting antibody binding to an immobilized analyte derivative. Competitive assays are somewhat more sophisticated as both the analyte and the tracer or the immobilized derivatives simultaneously interact with the antibody. Therefore, the concentrations of the antibody and the tracer or immobilized derivative have to be thoroughly adjusted to reach an optimum performance. However, more parameters are available for tuning the sensitivity and the working range. Displacement assays are attractive for directly monitoring concentrations, but an optimum dissociation rate of tracer is required to get maximum sensitivity and still no “leaching”. 4.1.2.2.2. Immobilization strategies

In almost all sensor systems immobilization of one of the interacting compounds is required. For typical immunoassays in microtiter plate format, immobilization is achieved by adsorption of

proteins or protein conjugates at the surface of the wells and the plate is disposed after the assay. In contrast to this procedure, in automated systems the active surface should be reusable for many times since mounting of new reactors or transducers should be avoided. Either the surface has to be regenerated after the assay by selectively cleaving the analyte-antibody complex or the whole immobilization procedure has to be carried out repeatedly after removing the immobilized compound. Both strategies have been investigated and found applications. For regeneration of the surface by cleaving the analyte-antibody complex, the immobilized compound has to remain on the surface during a regeneration procedure. Typically, harsh conditions such as pH 7 days

Önnerfjord et al., 1995

Wang et al., 1994b

Hedenmo et al., 1997

stor. Screen Printed

−3

SteadyState

0.05–14

0.25 10

Flow through

21–149

0.03 (gas) 300–5000 60–600

250

2–5

Graphite NMP+

disposable Kotte et al., 1995 20 days stor.

mediator Gold Array/

5 days contin.

Dennison et al., 1995

Glycerol gel Chamber GC: glassy carbon CP: carbon paste

Figure 4.10. Proposed enzyme mechanism of Tyrosinase. Kotte et al., 1995; Kulys and Schmid, 1990). Such electrodes lowered substantially the detection limits and improved the operational stability of the biosensors. Other efforts using tyrosinase electrodes have centered on the use of these biosensors for detection of phenolic compounds in organic solvent and gas (Saini et al., 1995; Dennison et al., 1995). The analytical characteristics of the most representative efforts using tyrosinase as the biorecognition element for phenolics detection are included in Table 4.14. The most advanced of these sensors are currently at a preprototype stage developed by the Umweltforschungszentrum Leipzig-Halle/Senslab GmbH in

Germany consisting of a screen-printed electrode incorporating a zeolite impregnated with NMP+ that acts as a catalytic site for the reduction and recycling of the enzymatically produced quinones to catechol. The detection limits of these disposable sensors reached the sub nM level and were used in real samples without any pretreatment. These sensors were validated with the 4-aminoantipyrine method (Kotte et al., 1995) and the results were satisfactory due to the phenolic nature of about 90% of the signal of the phenol index (Narváez et al., 1997). It therefore appears that a product based on this or a similar technology may soon result from the almost twenty years of research efforts on tyrosinase sensors. In the same work it was noted however that the selectivity of tyrosinase for different phenolic compounds is quite distinct from that of the 4-aminoantipyrine method. The majority of the polychlorinated and nitro- and aminophenols are not oxidised by tyrosinase, although at least some of them give moderate to full signals with the 4-aminoantipyrine method. This fact does not necessarily mean that a biosensor based on tyrosinase is doomed to fail as a phenolics sensor. It is possible for example to develop a “biosensor phenol index” that could be used as a satisfying substitute in the thousands of possible phenolics determinations in industrial, regulatory and even household situations, though it may never acquire legislative relevance. However, even the best tyrosinase sensors have detection limits barely sufficient for the low detection limits required for drinking water analysis. An elegant solution to this problem was suggested by Markower et al. (1996) where the quinones produced by the tyrosinase enter an enzymatic amplification cascade mediating a dehydrogenase co-immobilized on the electrode surface in the presence of its cosubstrate. As the specificity of the biosensors for phenolic compounds remained as the major problem, furthermore as the most toxic phenols, the ortho- and polysubstituted phenols, are no substrates of the tyrosinase, other enzymatic systems were sought as biorecognition elements. Biosensors for phenolic compounds based on laccases and peroxidases were reported (Marko-Varga et al., 1995; Yaropolov et al., 1995) and one report by Ruzgas et al. (1995) showed the detection of even chlorophenols with peroxidase. It remains to be seen whether this configuration leads to a biosensor that yields results that correlate better with the 4-aminoantipyrine index. The mechanism of action of laccases is less known than that of tyrosinase, with a wide selectivity for p-diphenols, catechols and aromatic amines (Thurston, 1994). Peroxidases however, would accept almost any reductant as substrate and for this it is conceivable that a broad range of phenols could be detected by those sensors. On the other hand, the broad substrate specificty of the enzyme causes problems in the interpretation of the analytical signal if the sensor is used without a pretreatment step. Kinetic resolution of the response and signal processing may be useful in this respect. 4.3.1.2. Enzyme sensors for other organic compounds

From Table 4.2 and from the ATSDR list of hazardous compounds (see Appendix) (http:\www.epa.gov/) several single compounds of environmental relevance can be targeted for detection by biosensors. Such sensors would correspond to the first “niche” already mentioned above (p. 147). It should be noted that such sensors should meet the most stringent reliability and operability criteria if they are to be used routinely in waste water analysis. Organic acids, aldehydes, polycyclic aromatic hydrocarbons, etc. can be included in the list of such target compounds. In this line, some sensor configurations appeared in recent years in the literature. Although most of these works are limited to a proof of concept level, they are worth mentioning

here since they demonstrate the possibility for the development of enzymatic biosensors for a variety of environmental applications. In some cases, new enzymes (not commercially available) were isolated to transform catalytically the contaminant, a strategy that shows an alternative way to antibodies raised as biorecognition elements (Chap. 4.3.3.). Page 186 Table 4.15. Enzyme Sensors for Specific Compounds in Water. Analyte

Enzyme

Glucose and Lactic acid

Benzoic acid

Stability

Application

References

Glucose Ox 100 glucose and Lactate Ox 0.05 lactate

glucose: stable at least 1 day lactate: ↓ 50% in 1 day

Detection of silage effluent pollution in river water

Stephens et al., 1997

Tyrosinase

10

–

–

Smit and Rechnitz, 1993b

Phenol, Catechol, p- Tyrosinase Cresol, 2Chorophenol

5 (phenol)

1 month stor.

Identification Burestedt and et al., 1995 quantification of spiked river water samples

Phenol, p-Cresol, 4- Tyrosinase Chlorophenol Methoxyphenol

–

–

Identification Wang et and al., 1997a quantification of spiked river water samples

Chlorophenol

0.4

↓ 15%, 7 days

Monitoring of Besombes chlorophenols in et al., water 1995b

Tyrosinase

Detection Limit/µM

↓ 80%, 54 days Hydrogen Peroxide and 2-Butanone Peroxide

Peroxidase

10

–

Measurements Wang et in untreated al., 1996a river and ground water samples

Atrazine, Phenol, Pentachlorophenol, Cadmium and Chromium

23 enzymes

–

–

Identification of Cowell et metal and al., 1995 organic pollutants in potable water

Benzoic acid and Ammonia

Nitrilase

150

7 days at 25°C

Organonitrile Liu et al., determination in 1995 water

Aldehydes

Aldehyde DH 5 – benzaldehyde

–

Pariente et al., 1995

Formaldehyde vapour

Formaldehyde 0.3 DH

7h continuous

–

Hammerle et al., 1996

Formaldehyde and Formic acid

Formaldehyde – DH and Formate DH

–

Formaldehyde Ho, 1987 determination in water and biological samples

Purines

Xanthine Ox

–

–

–

Urea

Urease

1–100

1 month stor.

Analysis of Zhylyak et water pollution al., 1995 by heavy metals

Barbosa et al., 1995

Ox: oxidase DH: dehydrogenase Thus, Liu et al. (1995) demonstrated a benzonitrile biosensor using a Rhodococcus sp. nitrilase for the hydrolysis of the analyte to benzoic acid and ammonia. The benzoic acid was reduced on a glassy carbon microelectrode where the biotinylated nitrilase had been immobilized. Stable responses were obtained and the sensor could detect 0.15mM benzonitrile both in aqueous and organic solvents. Smit and Rechnitz (1993a) were the first to use tyrosinase in its inhibition mode to detect benzoic acid. Although the work was not more than a proof-of-concept effort, it suggested that the judicial use of electroactive diphenols as substrates for tyrosinase could provide a means to differentiate between different inhibitors of the enzyme without the need for signal processing. Besombes et al. (1995b) also used tyrosinase in an inhibition sensor for the measurement of chlorophenols, pesticides and cyanide, achieving µM detection limits in water samples in the presence of various tyrosinase substrates for the baseline current. The enzyme electrode was constructed by electropolymerisation of an amphiphilic pyrrole-tyrosinase sensing layer. A detailed study on the use of combinations of inhibited enzymes for the detection of five contaminants (among those pentachlorophenol and phenol) and signal processing with neural networks (Cowell et al., 1995) showed a way to improve the reliability of inhibition sensors. Wang et al. (1996a) showed that peroxidase-based electrodes can be used for remote sensing applications in natural water simulating conditions for the detection of organic peroxides (2butanone peroxide) at the µM level. An aldehyde sensor based on NADH-producing aldehyde dehydrogenase immobilised on an electrode surface modified with quinoid functionalities for the catalytic recycling of NADH to NAD+ (Pariente et al., 1995) was demonstrated, although the problem of NAD+ -immobilization

was not solved, but such sensor could be conceivable in a FIA environment. A similar enzyme was used by Hammerle et al. (1996) to produce a gas sensor for formaldehyde. The principle of the use of formate dehydrogenase for the detection of formic acid was also shown earlier (Ho, 1987). Finally, the action of xanthine oxidase on purines (Barbose et al., 1995) was studied, demonstrating that an exhaustive study of the action of new and existing enzymes on contaminants could lead to configurations that could be used in environmental applications. The potential of using in an innovative way known and well-developed biosensor technology to provide new environmental pollution indicators that are useful to specific industries when combined with the capacity to provide rapid and reliable measurements was demonstrated by Stephens et al. (1997). In this work the authors showed the opening of possible market niches using glucose and lactate biosensors in silage effluents at different maturation stages of stored silage. In this manner, water management can be rationally designed. The sensors were validated with effluent from silos showing a satisfactory reliability completing an analysis in less than a minute. The most representative efforts to develop enzyme sensors for specific organic compounds in water are summarized in Table 4.15. REFERENCES

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4.3.2. MICROBIAL SENSORS FOR DETERMINATION OF AROMATICS AND THEIR HALOGENATED DERIVATIVES

KLAUS RIEDEL, TILL BACHMANN AND ROLF D.SCHMID 4.3.2.1. Introduction

Aliphatic and aromatic hydrocarbons and their chlorinated derivatives as well as organophosphorus and carbamate insecticides play an important role in industry and agriculture as pesticides, fungicides, herbicides, detergents and pharmaceuticals etc. (see ATSDR-list in Appendix). Due to their possible toxicity and persistence in the biosphere they have a high impact on the environment. Therefore their monitoring is essential for environmental protection and waste control. Conventional analysis by chromatographic methods is expensive and timeconsuming with regard to sample preparation and sample throughput. However, biosensors based on microorganisms, enzymes or antibodies open new possibilities for rapid analysis. Microorganism-based biosensors have been described for following aromatics: phenol, benzoate, naphthalene, dibenzofuran, biphenyl and their chlorinated derivatives. All the microorganisms used for these biosensors, degraded aromatics with oxygen consumption. The utilisation of microorganisms in biosensors requires some microorganisms which have adapted their metabolism to these unnatural compounds or their metabolic enzymes to be are active towards these substances. In general, the aerobic degradation of aromatics shows a high similarity for all microbial species. The aerobic microbial degradation of aromatics is mainly performed by a common mechanism (Figure 4.11) (Dagley, 1987): The initial reactions are the formation of diols by dioxygenases. This diols (catechol) are the key intermediates of aerobic degradation of aromatics. The following step is the cleavage of catechol to muconic acid. Further cleavage and oxidation reactions may lead to complete mineralization. Due to the fact, that the aerobic degradation of the various aromatics leads to general intermediates, microbial biosensors are relatively unspecific. The key metabolite catechol or the adequate diol structure of an aromatic compound causes a very high signal with all microbial sensors. The first step of degradation is the most specific and the formation of adequate enzyme is induceable. This opens the possibility to improve the sensor’s selectivity and sensitivity. The induction of desired enzymes can be obtained by direct cultivation of the microorganisms being used for the sensor with the analyte as sole carbon source. On the other hand the microrganisms on the sensor can be directly induced with an adequate aromatic compound as demonstrated for example with the Rhodococcus-sensor for determination of phenol and benzoate (Riedel et al., 1991) (Table 4.16). The sensor was almost specific to phenol, when cultivated with phenol. The cultivation with benzoate caused a specificity for benzoate only. In case of the Rhodococcus sensor the specificity of the microbial sensor increased after incubation of the sensor itself with the desired substrate. Also the incubation of the sensor containing phenol-cultivated cells with benzoate leads to a drastical increase of signal for this compound. These investigations of the Rhodococcus sensor demonstrate both the advantage and disadvantage of cell- and enzyme-sensors (Table 4.17). Indeed the sensor with enzyme extract of phenol-cultivated cells had a high specificity to Page 193

Figure 4.11. General scheme of aerobic degradation of aromatics by microorganisms. phenol, but a need for a cofactor and very little stability. Furthermore, the aerobic degradation of aromatic compounds is an enzymatic multistage reaction and therefore difficult, if not impossible to achieve with enzyme sensors. Table 4.16. Improvement of specificity and sensitivity of an Rhodococcus containing biosensor by cultivation or incubation with phenol or benzoate (substrate concentration: 20 µmol/l) (Riedel et al., 1991). Analyte

Signal [na/min] Cultivation with phenol

Glucose Phenol Benzoate

Incubation of “benzoate”-cells with

benzoate

phenol

benzoate

0

0

36

0

166

0

206

0

0

427

560

677

Page 194 Table 4.17. Comparison of phenol sensors consisting of Rhodococcus cells or enzymes from Rhodococcus (Riedel et al., 1991). Cell sensor

Enzyme sensor

Measuring range [µmol/l]

2–80

2–10

Detection limit [µmol/l]

2

2

Stability [h]

336

12

Need of cofactors

no

NADPH

Interferences

catechol

m-cresol

o-cresol m-cresol chlorophenols 4.3.2.2. Phenol and non-chlorinated phenolderivates

The use of the following microorganisms in combination with oxygen electrodes has been described for the determination of phenol: Trichosporon cutaneum (recently reclassified as T. beigelii), Candida tropicalis, Rhodococcus, Bacillus subtilis, Pseudomonas sp. and Alcaligenes sp. Table 4.18 gives an overview of the characteristic parameters of Table 4.18. Microbial sensors for phenol detection with oxygen electrodes. Microorganisms Specificity

Detection limit [µmol/l]

Trichosporon cutaneum (beigelii)

phenol

20 (=2 mg/l) 5

0.25

5

Neujahr and Kjellen, 1979

Rhodococcus sp. phenol

2(=0.2mg/l) 5

0.25

14

4 (=0.5 mg/l)

5.5

0.25

21

Riedel et al., 1991, 1993

0.5

n.d.

30

n.d.

Gaisford et al., 1991

0.2

12

Ciucu et al., 1991

chlorophenols Escherichia coli phenol chlorophenols

Standard Response Stability References deviation time [d] [%] [min]

(=0.05 mg/l) pentachlorphenol Rhodotorula sp. phenol

10(=1 mg/l) 2

Pseudomonas putida

phenol nitrophenol 2 (=0.1 pyrocatechol mg/l) mesityl oxide aniline 17(1 mg/l)

Azotobacter sp.

phenol hydroquinone catechol chinhydrone

5

20 (=2 mg/l) n.d.

5

1

Ignatov et al., 1995, Rainina et al., 1996

4

n.d.

Reiss et al., 1995

20 (=2 mg/l)

microbial sensors for phenol determination. However, phenol derivates interfered with phenol signals. Catechol and resorcinol where most likely to cause trouble whereas cresols and chlorophenols had little effect. Moreover, common substrates, such as glucose and amino acids, caused small signals only. A Rhodococcus P1, which has been isolated from the sediment of river Saale, in particular had a very high sensitivity to phenol and benzoate, but scarcely reacted to glucose. Therefore, this species is especially suitable for phenol sensors. Pseudomonas putida GFS-8-containing biosensors enable the determination of aniline in addition to phenol (Rainina et al., 1996). The relative activity with aniline is 71% compared to phenol. Furthermore the use of microbial sensors for determination of 2-ethoxyphenol with a Rhodococcus rhodochorus 116-containing sensor has been described (Beyersdorf-Radeck et al., 1994). This microbial sensor reacted to 2-ethoxyphenol with an higher signal than with glucose. The chemically similar compound 2-methoxyphenol and the degradation product catechol as well as glucose and acetate also led to a detectable signal. However, the glucose signal was smaller than the one for 2-ethoxyphenol. As the detection limits reached with any of the described sensors were higher than the 0.5 µg/1 prescribed as the maximum permissible concentration by the EC Directive for Drinking Water, the practical use of microbial phenol sensors is presently not practicable. The WHO (World Health Organisation) recommends a maximum phenol concentration in water of 1 µg/1. 4.3.2.3. Benzene

An optical biosensor has been developed for the determination of benzene using a genetically modified bacterial strain by Ikariyama et al. (1993). The TOL plasmid, responsible for degradation of benzene, was fused with the gene of firefly luciferase to breed a luminescent E. coli. The detection limit for benzene was 10 ppm (10 mg/l) with an measuring time of 4 min. The specificity of this sensor allowed a complex determination of benzene derivates only. In comparison to this, an amperometric biosensor consisting of Pseudomonas putida ML2 was more suitable with regard to sensitivity and specificity, as shown in Table 4.19 (Tan et al., 1994). 4.3.2.4. Polycyclic aromatic hydrocarbons (PAH)

Microbial PAH sensors have been described for detection of naphthalene, dibenzofurane and biphenyl based on the ability to aerobically degrade PAH. A Pseudomonas sp. HH693containing biosensor showed response to dibenzofurane (Beyersorf-Radeck et al., 1998). This sensor was also highly sensitive to metabolic intermediates like 2,3-dihydroxybenzofurane and

catechol, but also similar compounds, led to even higher signals than dibenzofurane. Microbial sensors using Rhodococcus globerulus (old designation: Corynebacterium MB1) reacted to biphenyl, but the signal was smaller than for catechol, 2,3-dihydroxybiphenyl and phenol (Beyersdorf-Radeck et al., 1991, 1993). Therefore, it was possible to detect biphenyl and dibenzofurane in real samples. The sensitivity and specificity reached with sensors for determination of dibenzofurane and biphenyl has not yet allowed practical applications. Page 196 Table 4.19. Microbial sensors for benzene detection. Microorganism Transducer Detection limit (mg/l) Response time (min)

Recombinant Escherichia coli Optical Sensor (luminescence) (Ikariyama et al., 1993)

Pseuodmonas putida ML2 Amperometric Sensor (oxygen) (Tan et al., 1994) 10 5 5 2–10

Sensitivity (in relation to benzene) [%] Benzene [%]

100 100

Toluene

150 2.4

o-Xylene

52 0.3

p-Xylene

46 0.3

m-Xylene

120 0.3

Ethylbenzene

26 1.3

Ethyltoluene

24 n.d.

Chlorotoluene

73 n.d.

Moreover, the sensitivity of a biosensor containing Sphingomonas sp. or Pseudomonas fluorescent allowed the specific determination of naphthalene (König et al., 1996). Table 4.20 gives an overview of the characteristic parameters of these biosensors. Biosensors using Sphingomonas sp. B1 or Pseudomonas fluorescens WW4 reached a remarkably low detection limit of 10 µg/l naphthalene (König et al., 1996). However this sensitivity was not sufficient for drinking water monitoring. The upper limit for PAH concentrations in drinking water is prescribed to be 0.2 µg/1. Moreover, both biosensors showed relatively large responses to salicylate and acetate. The sensitivity and specificity of an optical biosensor based on a genetically engineered bioluminescent catabolic reporter bacterium was also not sufficient for practical use. This sensor was developed for the determination of naphthalene and salicylate by Heitzer et al. (1994). The bioluminescent bacterium, Pseudomonas fluorescens HK44, carried a transcriptional fusion of the nahG gene of the salicylate operon from Pseudomonas fluorescens and the luxCDABE gene cassette from Vibrio fischeri. The detection limit for salicylate and naphthalene was 0.5 mg/l and 1.55 mg/l respectively.

4.3.2.5. Chloroaromatics

Products derived from chloroaromatics or generally haloaromatic compounds are of great industrial importance. Furthermore, chloroaromatic compounds can also be formed as side products during drinking water preparation via the chlorination step. Due to the assumed high toxicity and persistence of these substances, they are suspected to cause considerable problems in the environment. On account of their toxicity the upper limit of these compounds is prescribed as 0.2 µl/l by the EC Directive for Drinking Water. The extremely restricted ability of animals to degrade haloaromatics causes among other things an enhanced persistence of chlorinated hydrocarbons in the environment. Fortunately, some microbial species are capable of Page 197 Table 4.20. Microbial sensors for detection of naphthalene and salicylate.

Transducer

Sphingomonas sp. B1 (König et al., (1996)*)

Pseudomonas fluorescent WW4*) (König et al., 1996)

Ps. fluorescens HK 44 (genetically engineered) (Heitzer et al, 1994)

amper. oxygen electrode

amper. oxygen electrode

optical sensor

Detection limit [mg/l] Naphthalene

3

3

1.55

1.5

4

0.5

3–5

3–5

8–15

20

20

9

5

5

10

100

100

100

60

25

32

Toluene

n.d.

n.d.

30

Benzoate

35

2

n.d.

Acetate

22

67

n.d.

Pyruvate

17

56

n.d.

Ethanol

15

160

n.d.

Salicylate Response time [min] Stability [d] Standard deviation [%] Sensitivity [%] (in relation to Naphthalene) Naphthalene Salicylate

* Upper limit of linear range. degrading such compounds (Westmeier and Rehm, 1985; Reineke, 1986; Reineke and Knackmus, 1988; Sangadkar et al, 1989; Häggblom, 1990; Neilson, 1990). It is suggested that two types of mechanism are operative. First, microorganisms may have evolved specific enzyme systems for the degradation and dehalogenation of halogenated compounds and second, the

haloaromatics may be metabolized and splitted without dehalogenation by enzymes that have to degrade the base compounds. The crucial point is the removal of halogen substituents from the organic base compound. Two distinct mechanisms for this are known: the halogen is removed from the aromatic ring either (i) at early stage of the degradation pathway with reductive, hydrolytic, or oxygenolytic elimination, or (ii) after ring cleavage from aliphatic intermediates by hydrolysis or hydrogen halide by βelimination spontaneously. This ability is used for the development of microbial chloroaromatic sensors. Table 4.21 gives an overview over these biosensors. In general, the specificity is very poor, Page 198 Table 4.21. Microbial sensors for the determination of chlorinated phenols and benzoates. Analyte

Chlorobenzoates

Microorganisms

Pseudomonas putida 87

Rhodococcus sp. P1 Trichosporon beigelii (cutaneum)

Reference

Riedel et al, 1991

Riedel et al., 1993

Main substrate

344-Monochlorophenol Monochlorobenzoate Monochlorophenol

Detection limit [mg/l]

Chlorophenols

Riedel et al., 1995

50

0.4

0.2

0.25

0.25

0.25

Standard deviation [%]

5.5

5.5

5.5

Stability [d]

n.d.

>21

>21

100

14

0

3Monochlorobenzoate

39

8

42

2Monochlorobenzoate

9

11

0

4Monochlorobenzoate

24

1

0

2,4-Dichlorobenzoate

6

2

n.d.

Phenol

0

100

100

2-Monochlorophenol

n.d.

43

373

3-Monochlorophenol

9

45

875

4-Monochlorophenol

4

53

1167

Response time [min]

Sensitivity [%]* Benzoate

2,3-Dichlorophenol

n.d.

36

538

2,4-Dichlorophenol

4

20

725

2,6-Dichlorophenol

n.d.

15

1077

3,4-Dichlorophenol

n.d.

20

n.d.

2,3,6-Trichlorophenol

n.d.

7

inhibition

2,4,6-Trichlorophenol

n.d.

8

inhibition

2,4,5 Trichlorophenol

n.d.

11

inhibition

2

3

Glucose

* In relation to the basic aromatic compounds benzoate and phenole, resp. caused by the degradation mechanism and the unspecific degradation enzymes. This property of microbial sensors opens the possibility of determination of sum parametrs of the desired halogenated aromatics. The microbial species mainly used for biosensors for the estimation of chlorinated aromatics are Pseudomonas, Rhodococcus, Trichosporon, Ralstonia (old name: Alcaligenes). Pseudomonas putida 87 was successfully used to determine 3-chlorobenzoate (Riedel et al., 1991). This biosensor was especially sensitive to 3-chlorobenzoate, although the signal for this compound was lower than for the non-chlorinated benzoate. The relative response of 3-chlorobenzoate was 39 % of the benzoate signal. The sensitivity against further mono- and dichlorobenzoates as well as chlorophenols was comparatively small. The relative response was under ge 199 10% in comparison to benzoate, with the exception of 4-chlorobenzoate (24%). Because detailed knowledge about the degradation mechanism of chloroaromatics by Pseudomonas exists, one is able to understand this observation. The degradation of 3-chlorobenzoate by Pseudomonas putida 87 starts with an decarboxylation producing 3-chlorophenol, which is transformed into chlorocatechol, which in turn is cleaved to chloromuconic acid and eventually dechlorinated (Grishenko et al., 1983). The determination of chorinated phenols was possible with biosensors containing Rhodococcus sp. P1 or Trichosporon beigelii (cutaneum). The Rhodococcus-sensor allowed an overall determination of mono- and dichlorophenols. The sensitivity for mono- and dichlorinated phenols was on an average 30–40 % of phenol. The chlorobenzoate was not degraded by this sensor. Moreover, an specific and sensitive determination of chlorophenols was possible with a Trichosporon beigelii (cutaneum)-containing sensor (Riedel et al., 1995). This sensor used strain Tr. beigelii E4 which had a high specificity to 4-monochloro-, 3-monochloro-, 2,4- and 2,5-dichlorophenol and showed no reaction to benzoate. All tested tri-, tetra- and pentachlorophenols where toxic for this organism. The signals for the mono- and dichlorinated phenols where markedly higher than for phenol itself. Notwithstanding this high specificity, the attained detection limit of 50 µg/l of chlorophenols means that this sensor is not yet suitable for practical application because the permissable concentration in drinking water is 0.5 µg/l phenols (EC Directive for Drinking Water, German Drinking Water Ordinance).

Microorganisms capable of degrading polychlorinated biphenyls (PCB) have been isolated and used in biosensors to determine these xenobiotics. The following three particularly interesting PCB-degrading species Ralstonia eutrophus H850 (new name of Alcaligenes eutrophus), Rhodococcus globerulus fold designation: Corynebacterium MB1, and Pseudomonas putida LB400 were used in biosensors (Beyersdorf-Radeck et al., 1992, 1993). A problem of measuring of these compounds is their hydrophobicity. Therefore PCB was disolved in dimethylsulfoxide. Table 4.22 shows, that the sensors Table 4.22. Relative specificity of microbial sensors to PCB (Beyersdorf-Radeck et al., 1992) (In relation to 3-PCB). Ralstonias eutrophus H850

Rhodococcus globerulus

Pseudomonas LB400

100

100

100

2,2′-PCB

50

40

50

2,3-PCB

130

100

138

3,3′,4,4′5,5′-PCB

205

35

120

3,3′,4,4′-PCB

115

100

200

PCB Mix

24

130

59

Biphenyl

156

44

308

Dibenzofuran

246

18

85

2,3Dihydroxybiphenyl

1568

304

1162

Catechol

1064

218

517

0

0

600

61

65

61

3-PCB

Phenol Benzoic acid

Figure 4.12. Metabolic route for the degradation of 1, 2-dichloroethane in Xanthobacter autotrophicus (Greer et al., 1989).

Page 201 reacted to PCB, but the sensitivity and specificity was not suifficient for the specific determination of PCB. Furthermore, the use of microbial sensors for the determination of 2,4-dichlorophenoxyacetic acid (2,4-D) has been described (Beyersdorf-Radeck et al., 1991, 1998). This Ralstonia eutrophus JMP134-containing sensor was very sensitive to 2,4-D and 2,4,5-T (2,4,5trichlorophenoxyacetic acid). Catechol, benzoic acid and salicylaldehyde caused higher signals, but no or very little signal was obtained for glucose, fructose, ethanol, acetate, biphenyl and phenol. 4.3.2.6. Haloaliphatic compounds

The ability of some microorganisms to dehalogenate haloaliphatic compounds was used to construct biosensors for the determination of dihalomethanes (Henrysson and Mattiasson, 1991, 1993) as well as ethyl bromide, 1,2-dibromopropane, isobutyl bromide, 1-chlorobutane and 1,3dibromobutane (Hutter et al., 1994, 1996). The most detailed knowledge of the degrative mechanisms for haloaliphatic compounds was derived from studies with Xanthobacter autotrophicus, a Gram-positive coryneform bacterium, which uses a large varity of organic compounds, especially 1,2-dichloroethane (Jansen et al., 1984, 1985, 1987). The degradation pathway of 1,2-dichloroethane involves two constitutive hydrolytic dehalogenating enzymes with a broad substrate specificity: dichloroethane dehalogenase and chloroacetic acid dehalogenase (Figure 4.12). Two possibilities to determine this microbial response to haloaliphatic compounds have been described: the halogene-sensitive electrode, and flowcalorimeter. Hutter et al. (1994) have developed a highly sensitive microbial sensor consisting of Rhodococcus sp. combined with bromide- or chloride-sensitive electrodes for determination of brominated and chorinated aliphatics in the ppb range. The detection limit for 1,3dibrompropane, was 4 µg/l and for 1-chlorobutane 50 µg/l, respectively. Relatively high specificity has been reached with a biosensor containing Hyphomicrobium DM2 with a combination of transducers consisting of a flow-calorimeter followed by a chloride-sensitive electrode (Henrysson and Mattiasson, 1991, 1993). The detection limit for this biosensor was 5 µg/l dichloromethane. Chloroforme and 1,2-dichloroethane caused no response. In contrast, the sensor showed higher sensitivity against dibromomethane. REFERENCES

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Beyersdorf-Radeck, B., Riedel, K., Neumann, B., Scheller, F. and Schmid, R.D. (1993) Entwicklung mikrobieller Sensoren zur Bestimmung von Xenobiotika. In Biochemische Methoden zur Schadstofferfassung im Wasser. pp. 141–154, Weinheim: Verlagsgesel-Ischaft mbH. Beyersdorf-Radeck, B., Karlson, U. and Schmid, R.D. (1994) A microbial sensor for 2ethoxyphenol. Anal. Lett., 27, 285–298. Beyersdorf-Radeck, B., Riedel, K., Karlson, U. Bachmann, T.T. and Schmid, R.D. (1998) Screening of xenobiotic compounds degradating microorganisms using biosensor techniques. Microbiol Res., 153, 239–245. Ciucu, A., Magearu, V., Fleschin, S., Lucaciu, L. and David, F. (1991) Biocatalytical membrane electrode for phenol. Anal. Lett., 24, 567–580. Gaisford, W.C., Richardson, N.J., Haggert, B.G.D. and Rawson, D.M. (1991) Microbial sensors for environmental monitoring. Biochem. Soc. Trans., 19, 15. Dagley, S. (1987) Microbial metabolism of aromatic compounds. In Comprehensive biotechnology, Cooney, C.L. and Humphrey, A.E. (eds.) pp. 483–505. Pergamon Press. Häggblom, M. (1990) Mechanisms of bacterial degradation and transformation of chlorinated monoaromatic compounds. J. Basic Microbiol., 30, 115–141. Heitzer, A., Malchowsky, K., Thonnard, J.E., Bienkowski, P.R., White, D.C. and Sayler, G.S., Optical biosensor for environmental on-line monitoring of naphthaline and salicylate bioavailability with an immobilized bioluminescent catabolic reporter bacterium. Appl. and Environment. Microbiol., 60, 1487–1494. Henrysson, T. and Mattiasson, B. (1991) A dichlorethane sensitive biosensor based on immobilized Hyphomicrobium DM2 cells . In Proc. Symp. Environm. Biotechnol., Verachtert, H. and Verstraete, W.F. (eds.) Oostende, 73–76. Henrysson, T. and Mattiasson, B. (1993) A microbial biosensor for dihalomethanes. Biodegradation, 4, 101–105. Hutter, W., Peter, J., Svoboda, H. and Hampel, W. (1994) Biosensorsystem für halogenierte Kohlenwasserstoffe. (in german) ECOINFORM, 5, 377–387. Hutter, J.P., Stöllnberger, W. and Hampel, W. (1996) Detection of halogenated hydrocarbons by a microbial sensorsystems using a stop-flow-techniques. Biotechnol. Techniques., 10, 183–188. Ignatov, O.V. and Kozel, A.B. (1995) The determination of aromatic compounds by microbial biosensors. In Environmental Biotechnology: Principles and Application, Moo-Young, M. et al. (eds.) pp. 66–74. Kluver Academic Publishers.

Ikariyama, Y, Nishiguchi, S., Kobatake, E., Aizawa, M., Tsuda, M. and Nakazawa, T. (1993) Luminescent biomonitoring of benzene derivates in the environment using recombinant Escherichia coli. Sensors and Actuators B, 13/14, 169–172. Janssen, D.B., Scheper, A. and Witholt, B. (1984) Biodegradation of 2-chloroethanol and 1, 2dichloroethane by pure bacterial cultures. In Innovations in Biotechnology, Houwink, E.H. and van der Meer, R.R. (eds.) pp. 169–178. Amsterdam: Elsevier Science Publishers B.V. Janssen, D.B., Scheper, A., Dijkhuizen, L. and Witholt, B. (1985) Degradation of halogenated aliphatic compounds by Xanthobacter autotrophicus GJ 10. J. Gen. Microbiol., 49, 673–677. Janssen, D.B., Keuning, S. and Witholt, B. (1985) Involvement of a quinoprotein alcohol dehydrogenase and an NAD-dependent aldehyde dehydrogenase in 2-chloroethanol metabolism in Xanthobacter autotrophicus GJ10. J. Gen. Microbiol., 133, 85–92. König, A., Zaborosch, C., Muscat, A., Vorlop, K.D. and Spener, F. (1996) Microbial sensors for naphthaline using Spingomonas sp. B1 or Pseudomonas fluorescens WW4. App. Microbiol. Biotechnol., 45, 844–550. Neilson, A.H. (1990) The biodegradation of haloaromatics. J. Appl. Bacteriol., 69, 445–470. Neujahr, H.Y and Kjellen, K.G. (1979) Bioprobe electrode for phenol. Biotechn. Bioeng., 21, 671–678. Rainina, E.I., Badalian, I.E., Ignatov, O.V., Federov, A.Yu., Simonian, A.L. and Varfolomeyev, S.D. (1996) Cell biosensor for detection of phenol in aqueous solution. Appl. Biochem. Biotechnol., 56, 117–127. Reineke, W. (1986) Construction of bacterial strains with novel degradative capabilities for chloroaromatics. J. Bacic Microbiol., 9, 551–567. Reineke, W. and Knackmus, H.-J. (1988) Microbial degradation of haloaromatics. Ann. Rev. Microbiol., 42, 263–287. Reiss, M., Metzger, J. and Hartmeier, W. (1995) An amperometric microbial sensor based on Azotobacter species for phenolic compounds. Med. Fac. Landbouw. Univ. Gent,, 60/4b, 2227– 2230. Riedel, K., Hensel, J. und Ebert, K. (1991) Biosensoren zur Bestimmung von Phenol und Benzoat auf der Basis von Rhodococcus Zellen und Enzymextrakten (in german). Zbl. Bakt., 146, 425–434. Riedel, K., Naumov, A.V., Boronin, L.A., Golovleva, L.A., Stein, J. and Scheller, F. (1991) Microbial sensors for determination of aromatics and their chloroderivates. Part I: Determination of 3chlorobenzoate using a Pseudomonas containing biosensors. Appl. Microbiol. Biotechnol., 35, 557–562.

Riedel, K., Hensel, J., Rothe, S., Neumann, B. and Scheller, F. (1993) Microbial sensors for determination of aromatics and their chloroderivates. Part II: Determination of chlorinated phenols using a Rhodococcus containing biosensors. Appl. Microbiol. Biotechnol., 38, 556–559. Riedel, K., Beyersdorf-Radeck, B., Neumann, B. and Scheller, F. (1995) Microbial sensors for determination of aromatics and their chloroderivates. Part III: Determination of chlorinated phenols using a biosensors containing Trichossporon beigelii (cutaneum). Appl. Microbiol. Biotechnol., 43, 7–9. Sangodkar, U.M.X., Aldrich, T.L., Hangland, R.A., Johnson, J., Rothmel, R.K., Chapman, P.J. and Chakrabaty, A.M. (1989) Molecular basis of biodegradation of chloroaromatic compounds. Acta Biotechnol., 9, 301–306. Tan, H.-M., Cheong, S.-P. and Tan, T.-C. (1994) An amperometric benzene sensor using whole cell Pseudomonas putida ML2. Biosens. Bioelectron., 9, 1–8. Westmeier, F. and Rehm, H.-J. (1985) Biodegradation of 4-chlorophenol be entrapped Alcaligenes sp. A7–2. Appl. Microbiol. Biotechnol., 22, 301–305.

4.3.3. OTHER TYPES OF SENSORS FOR ORGANIC POLLUTANTS

IOANIS KATAKIS, MÒNICA CAMPÀS and ELENA DOMÍNGUEZ 4.3.3.1. Immunosensors for organic compounds

The reports and activity on immunoassay development for environmental analysis including water analysis have been intense in the past few years. The reason for this growth is that immunoassays are ideal candidates for both the first and third “niche” opening strategies mentioned above. The activity is intensified because of the real need of the market for fast and reliable field analytical methods for difficult-to-detect single or group analytes. This need is created by the existence of increasing numbers of landfills and government decisions around the world for their remediation. The intense activity in this field has been evaluated in various recent works (Wittmann and Schmid, 1997; Marco and Barceló, 1996; Rogers and Poziomek, 1996; Dennison and Turner, 1995) and specific applications were recently reviewed (López-Avila and Hill, 1997; Clement et al., 1997). It should be noted, that although immunoassays based on ELISA and similar systems and on newly developed antibodies and immunoconjugates are abundant, the available immunosensor configurations reported are limited in number. Immunosensors use antibodies as biorecognition elements and the advances in hapten design and monoclonal antibody development, and the possibility of production of recombinant antibodies without the need to use small animals as hosts for raising the antibodies, raises new hopes for short turnover times and affinity modulation of the antibodies (Marco and Barceló, 1996). Although ELISA and immunomagnetic formats are readily developed once the appropriate antibodies have been raised, the development of immunosensors is far from straightforward. However, the existence of these alternatives guarantees a marketable product once a need is detected and this fact encourages private and pubic investment in the field. Several immunoassay methods have now been included in the EPA manuals and have been evaluated for reliability and compared to standard techniques (López-Avila and Hill, 1997). The transducing schemes for immunosensors are electrochemical where most of the detection processes are indirect (using competition affinity reactions of the analyte with labelled haptens) and optical or acoustic where the detection can be direct, without the need and complication of labelling chemistries. However, the acoustic sensors are usually unsuitable for detection in water samples due to water adsorption that interferes with the measurement yielding unreliable results. A major drawback in the development of immunosensors is the limited ability for regeneration of the sensors, resulting in disposable devices with little calibration capacity. The use of low affinity antibodies can overcome this problem if the detection limits are sufficiently low. Most immunosensors have been developed for pesticide detection and the interested reader is referred to chapter 4.1.2 for a detailed account. Below some of the recent efforts in immunosensor development for other organic contaminants in water are summarised including some interesting transduction approaches (ELISA-type approaches including immunomagnetic particles and microtiter plates are in general not considered biosensors, http://www.cranfield.ac.uk/biotech/disdoc.htm). By far the most widely publicised success story is the on-site detection of TNT with a portable fibre-optic evanescent wave immunosensor. The immunosensor is based on a competitive fluorescent assay on the surface of an optical fibre (Shriver-Lake et al., 1995). The device has

been used for mapping of contamination by TNT, and TNB in two US military depots. The results (Shriver-Lake et al., 1997) agreed well with the standard EPA method (reverse phase HPLC) and the advantages of performing on-site the analysis in less than 16 minutes and at a fraction of the standard method’s cost demonstrated the superiority of the biosensor. This immunosensor was regenerable, permitting calibration and increasing the reliability of the measurement. Water samples were directly analysed without any pretreatment. Another work by the same authors (Golden et al., 1997) describes the electronics and construction of the portable device that permits the simultaneous measurement from up to four fibres possibly opening the perspectives for multianalyte immunosensors. The application of the sensor for RDX detection has also been described (Bart et al., 1997). A generic immunocomposite amperometric sensor has been demonstrated at the proof of concept level by Santandreu et al. (1997) with long response times using an IgG. The competition with alkaline phosphatase-labelled anti-IgG was used to detect rabbit IgG with phenyl phosphate as substrate. The high detection potentials and irreversibility of the electrochemical reaction may limit the usefulness and life time of this sensor which is however regenerable when fresh surface of the composite is exposed. Another interesting and innovative approach for electrochemical immunosensors demonstrated in two preliminary studies uses bilayer lipid membranes for the construction of immunosensors. In one study by Nikolelis and Siontorou (1997) the incorporation of the biorecognition molecules in the BLMs resulted in enhanced stability and the electrochemical detection resulted to nM detection limits for various pesticides. In another approach Roberts and Durst (1995) reported on immunomigration sensors based on liposomes for the detection of 2.6 pmol PCBs in less than 23 minutes when inhibition of the immunospecific liposome aggregation is detected. A near-infrared fluorescence detection principle has been applied to allow the detection of nearIR-tagged small molecules with high sensitivity. The principle has been applied for ELISA miniaturisation and for bringing it one step closer to an immunosensor format with the use of miniature and inexpensive laser diodes (Wengatz et al., 1996). Along the same lines (miniaturisation) a microformat imaging ELISA has been demonstrated that can use a video detection system (Dzgoev et al., 1996). Such developments may in the next few years lead to hybrid devices between ELISA and sensors combining the advantages of both formats. A very interesting and innovative approach for the development of multianalyte fibre optic immunosensors has been described by Abuknesha and Brecht (1997), Piehler et al. (1995) where spatially resolved specific multiple auxiliary reagents have been used for the simultaneous determination of industrial pollutants and agrochemicals. This possibility has important commercial repercussions. The interesting amplification scheme for the detection of antigens amperometrically that has been introduced by Gleria et al. (1989) has been used for the detection of dinitrophenol (O’Daly et al., 1992) without however achieving the low detection limits expected for such an amplification scheme. It is possible that the problem is the fact that the immunoassay is based on the displacement of the ferrocene-labelled dinitrophenol by the analyte and its subsequent recycling on the electrode surface with a redox enzyme in the presence of its substrate.

PCB immunodetection in waters attracted most interest in the literature. Zhao et al. (1995) have demonstrated an immunosensor for the detection of 2, 4, 5-trichlorophenoxybutyrate (TCPB) with a 10 ppb detection limit. This is still higher than the 0.1 ppb required by legislation, but the sensor could be used multiple times, it had a 5 minute response time and water samples could be directly injected. Although real samples were not analysed, the device appears to be attractive for further development. It consists of a quartz fibre coated with anti-PCB antibodies that were saturated with fluorescein-labelled TCPB. The displacement of the labelled TCPB by the analyte could be detected in the evanescent field. A method for the synthesis of such fluorescently labelled antigens is described in Charles et al. (1995). Despite the microtiter assay format used for the detection of PCBs (Aroclor® 1260), the long assay time (2 h and 30 min), and the high detection limit (100 ppb) reported by Del Carlo and Mascini (1995), the incorporation of electrochemical transduction in this immunoassay is notable. An elegant and successful approach in electrochemical immunosensors for the detection of PCBs (Aroclor® 1016) in a field-portable instrument has been shown by Sadik and Van Emon (1996) using conducting electroactive polymers as an antibody immobilisation matrix and applying a pulsed waveform (pulse frequency of 120 and 480 ms) between 0.40 and −0.60 V. The oscillating potential allows the reversible transduction of molecular interactions and monitoring in real time with a limit of detection of 10 ppb. This technology may offer wider applications for real-time monitoring of pollutants in ground water (Riviello et al., 1994). Finally, although only used in ELIS A formats in water analysis, the development of some new antibodies against trichloroethylene by Hudak et al. (1995) should be mentioned. This test kit in its ELISA format had a detection limit of 1.5 ppm, still higher than the 0.5–0.1 ppm required by the legislation in waste waters. A PAH-immunoassay has been successfully used and validated with HPLC for the detection of poly cyclic aromatic hydrocarbons in 114 ground water samples fulfilling the maximum admissible values set by the German Drinking Water Act (Knopp et al., 1995). An extensive list of references of the evaluation of commercially available kits for immunoassays can be found in López-Avila and Hill (1997) and Sherry (1992). In general, it could be said that despite the numerous works describing generic immunosensors and ELIS As using new and commercially available kits, there are very few works describing immunosensors for environmental applications. The reason for this lag is probably due to the competitive advantage that ELISA enjoys for routine environmental testing (standard method, multiple samples, reliability) especially in its miniaturised or portable formats. 4.3.3.1.1. New types of sensors Some biosensing or chemical sensing schemes especially applied in environmental analysis are worth mentioning as potential technologically important developments for the future. For example, DNA intercalators can be detected with DNA-Cu(II) complexes electrochemically, and with such a molecular construct immobilised on an electrode surface the intercalating drug quinarcine has been detected (Hasebe et al., 1997). A review of this and other kinds of interactions with DNA and their use for the detection of environmental pollutants by electrochemical means has been recently presented by Wang et al. (1997b). In a specific application the detection of aromatic amines at nM levels has been reported (Wang et al., 1996b)

by stripping voltammetry of the accumulated intercalating species. The sensor was directly applied to river water samples and these detection limits were achieved after 10 minute accumulation of the intercalating species. Mecklenburg et al. (1997) have applied optical detection (fluorescence quenching) in sensors with similar principles to detect known mutagens such as bisbenzidine, and 1, 2, 4-benzetriamine. The assay is based on the reduced fluorescence of intercalated ToPro 3 at 661 nm in the presence of the organic compounds. Protein and genetic engineering can also be used to develop novel biorecognition chemistries. For example Marvin et al. (1997) report on the point mutations of sites that are known to allosterically control the binding of maltose to the maltose binding protein. The modification of such sites with fluorophores results in a co-operative change of fluorescence with the binding of maltose that permitted a sensor for maltose with a 5% accuracy and in a range of concentration spanning five orders of magnitude. In another development, Armengaud and Timmis (1997) reported on the isolation of the gene of a ferredoxin participating in the electron transfer mechanism of dioxin dioxygenase from Sphingomonas sp. Such electron transfer proteins could be used for the construction of enzymatic dioxin sensors. Finally, although there have not been any reports yet on their use for environmental monitoring, attention should be paid to the various flavin monooxygenases that with their broad specificity could be used as generic biorecognition elements in this field once appropriate transduction schemes are described. The same is true for the hydrolysing catalytic antibodies that could be raised against any relevant organic contaminant as antibodies would, but with the additional advantage of no need for regeneration once incorporated in a biosensor. One such case has been reported in the past (Blackburn et al., 1990). With the increasing blurring between chemical and bio sensors, it is expected that mixed techniques (combinatorial synthesis, libraries of catalytic DNAs or RNAs, etc.) will have significant input in new types of sensors for new applications in the near future. REFERENCES

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IOANIS KATAKIS, MÒNICA CAMPÀS, ELENA DOMÍNGUEZ and KLAUS RIEDEL The cleanup efforts of hazardous waste landfills, the need of detection of particularly hazardous compounds (see Appendix), and the increasing environmental awareness of the public are factors that point to the necessity for fast, easy to use, low cost field devices such as biosensors. However, such biosensors should be reliable and with a long shelf life even when they are disposable. These requirements are at least partly met by tyrosinase-based sensors for phenolic compounds and by microbial sensors. Microbial sensors in particular open promising possibilities for the detection of aromatics and their halogenated derivatives. Main advantages are their stability and simple preparation. The low specificity of these biosensors turns out to be an advantage, if the determination of sumparameters is considered. The big variety in biochemical and adaptation capabilities of microorganism species allows the selective determination of specific groups of aromatic compounds. However, in most cases the detection limits obtained with microbial sensors and also with tyrosinase-based sensors, which were the most investigated enzyme-based sensors in the last 15 years, are obviously too high to reach the low concentrations required for drinking water analysis

without sample pretreatment. In the case of microbial sensors future improvements are expected by genetic engineering, such as metabolic design, and by the use of analyte specific reporter systems. Usually a higher sensitivity is obtained by immunoanalytical techniques. In the absence of generic technologies for multianalyte immunosensors and of transduction schemes even for single analyte immunosensors, most of the activities in new single analytes or group-specific immunoassays centered on the development of ELISA-formats. As a result, the high initial R&D costs and the fragmented, small volume market for single analytes prohibited the participation of the private sector in environmental biosensor development. Nevertheless, there is a potential market for fast, low cost instruments, and as described above there exist even for immunosensors a conceptual basis for a number of commercially acceptable biosensors. The question is, how the costs associated with prototype and product development will be covered. The success story of the TNT evanescent wave biosensor possible shows a way, where public funds assume the majority of these costs when a well identified need is detected and addressed. It is however true that up to now the expensive transduction method used in this sensor and other such “biosensors” available in the market (e.g. from Biacore, Fisons instruments, etc., see Chap. 2.2.) has proven the only reliable technology with commercial potential, possible due to the simplicity of the detection procedure (direct assays). The high initial investment for the acquisition of such instruments limits the volume of the potential market. It appears therefore that a low cost alternative is required, and this can be either the direct optical or electrochemical detection. Reliable sensor configurations (especially for affinity sensors) with generic character are needed based on transduction schemes that could also take advantage of the new genetic engineering and combinatorial techniques for the development of recognition chemistries. The main part of efforts to launch such commercially viable alternatives seems to be falling to small start-up companies and Universities and Research Institutes. ATSDR. LIST OF HAZARDOUS COMPOUNDS 1. Acetone 2. Acrolein 3. Acrylonitrile 4. Aldrin/Dieldrin 5. Benzene 6. Benzidine 7. Benzo(A)anthracene 8. Benzo(A)pyrene

9. Benzo(B)fluoranthene 10. Bis(2-chloroethyl)ether 11. Bis(chloromethyl)ether 12. Bromodichloromethane 13. Bromoform/Chlorodibromomethane 14. Bromomethane 15. Butadiene 16. Butanone 17. Carbon Disulfide 18. Carbon Tetrachloride 19. Chlordane 20. Chlorobenzene 21. Chlorodibenzofurans 22. Chloroethane 23. Chloroform 24. Chloronaphthalene 25. Chrysene 26. Creosote 27. Creosote (Coal Tar and Wood), Coal Tar and Coal Tar Pitch 28. Cresols 29. DDT, DDE and DDD 30. Diazinon 31. Dibenz(A,H)anthracene

32. Dibenzofuran 33. Dibromochloropropane 34. Dibromoethane 35. Dichlorobenzene 36. Dichlorobenzidine 37. Dichloroethanes 38. Dichloroethenes 39. Dichlorophenol 40. Dichloropropane 41. Dichloropropene 42. Di(2-ethylhexyl) phthalate 43. Diethyl phthalate 44. Dimethylphenols or Xylenols 45. Di-N-butyl phthalate 46. Di-N-octyl phthalate 47. Dinitrobenzene 48. Dinitrocresols 49. Dinitrophenols 50. Dinitrotoluenes 51. Diphenylhydrazine 52. Disulfoton 53. Endosulfan 54. Endrin/Endrin Aldehyde

55. Ethylbenzene 56. Ethylene Glycol/Propylen Glycol 57. Ethylene Oxide (Oxirane) 58. Fluoranthene 59. Fuel Oil 60. Heptachlor/Heptachlor Epoxide 61. Hexachlorobenzene 62. Hexachlorobutadiene 63. Hexachlorocyclohexanes 64. Hexachloro cyclopentadiene 65. Hexachloroethane 66. Hexanone 67. HMX 68. Hydraulic Fluids 69. Hydrazines 70. Isophorone 71. Jet fuels 72. Methoxychlor 73. Methylenebis(2-chloroaniline) 74. Methylene Chloride 75. Methyl Mercaptan 76. Methyl Parathion 77. Methyl Terc-Butyl Ether

78. Mineral-based Crankcase Oil 79. Mirex and Chlordecone 80. Mustard Gas 81. Naphthalene and Methylnaphthalenes 82. Nitrobenzene 83. Nitrophenols 84. N-Nitrosodi-N-propylamine 85. N-Nitrosodimethylamine 86. N-Nitrosodiphenylamine 87. Otto Fuel II 88. PCBs 89. Pentachlorophenol (PCP) 90. Phenol 91. Polybrominated Biphenyls 92. Polycyclic Aromatic Hydrocarbons 93. Pyridine 94. RDX 95. Stoddard Solvent 96. Styrene 97. Tetrachlorodibenzo-p-dioxin 98. Tetrachloroethane 99. Tetrachloroethylene 100. Tetryl

101. Toluene 102. Toxaphene 103. Trichloroethanes 104. Trichloroethylene 105. Trichlorophenol 106. Trichloropropane 107. Trinitrobenzene 108. Trinitrotoluene 109. Vinyl Acetate 110. Vinyl Chloride 111. White Phosphorus and White Phosphorus Smoke 112. Xylenes

4.4. HEAVY METALS

RICHARD E.WILLIAMS, PETER-JOHN HOLT, NEIL C.BRUCE and CHRISTOPHER R.LOWE 4.4.1. INTRODUCTION

Many metals are naturally abundant and, as such, occur in forms largely inoffensive to the ecosystem. Extraction, processing and use by man often cause metals to be reintroduced to the environment in a manner potentially toxic to both man and that environment. Of these metals, some have received much attention from both environmental and sensor researchers, whereas others have been paid scant regard in the literature. This uneven interest broadly follows the differing toxicities and scales of pollution attributable to the respective elements, with the more toxic, e.g. mercury, and industrially prolific, e.g. copper and zinc, receiving most attention. These heavier metals often form a significant proportion of pollutants at sites where environmental damage has occurred. 4.4.1.1. Elements considered

“Heavy metals” has been used as a label for various, sometimes seemingly arbitrary, groups of the heavier elements. This text is no exception. Densities of the metallic elements range from 0.53 gcm−3 (lithium) to 22.6gcm−3 (osmium), with 50% having densities above 7.5 gcm−3. We have decided to consider metals above a density of 7.0 gcm−3 as “heavy”, thus adding zinc, chromium, tin, indium and manganese to the group. Although radioisotopes and scarce metals, e.g. the Lanthanides and Actinides, fall outside the scope of this text, some attention has been paid to the heavier metalloids selenium (4.79 gcm−3), arsenic (5.72 gcm−3) and tellurium (6.4 gcm−3). A list of “heavy metals” is given in Table 4.23. 4.4.1.2. Toxicity of heavy metals

A feature common to all heavy metals is a strong affinity for sulphur, and their interaction with biological systems is generally through the formation of bonds to thiol groups in proteins. Cysteinyl residues have essential roles in the function of many enzymes, particularly those involved in hydrolytic and redox catalysis, e.g. glutathione reductase. Therefore, metals interacting with the essential thiol groups of proteins can be highly detrimental, or even lethal, to a biological species. It must be noted also that some metals, e.g. copper and zinc, are essential to many organisms at trace levels, but toxic at elevated concentrations. This has significant bearing on the sensitivities and dynamic ranges required of tests for heavy metals. 4.4.1.3. Heavy metals in the environment—speciation and bioavailability

Myriad forms of the heavy metals, with greatly varying solubilities and toxicities, are known. The less soluble compounds can be found both in sediments and adsorbed to suspended particulates, e.g. methylmercurysulphide (Fergusson, 1990; Palinkas et al., 1995).

Organometallics usually exist at low overall levels, have low aqueous solubilities and tend to associate with suspended or precipitated matter (Filella et al., 1995). Since organometallics can be highly toxic, e.g. methylmercury, determination of these compounds can be necessary, despite the low soluble concentrations usually encountered. Solvent extraction of water samples is used to remove organic substances for analysis, which obtains organometallics from both association with solids and the Table 4.23. The heavy metals (Merlan, 1991). Metal and Density (g/cm3)

Main Soluble Metal Ions

Other Relevant forms

Most Toxic Forms

Selenium (4.8)

Se4+, Se6+

H2Se, (CH3)2Se

Elemental

—

AsH3, As3+

(CH3)2Te

Elemental

ZnS, ZnO

Low toxicity

3+

5+

Arsenic (5.7)

As , As

Tellurium (6.4)

Te4+, Te6+

Zinc (7.1)

2+

Zn

6+

3+

Chromium (7.2)

Cr > Cr

—

Cr6+

Tin (7.3)

Sn2+, Sn4+

Tri-organotins

CH3, Et3 derivatives

3+

Indium (7.3)

In

Little known

Little known

Manganese (7.4)

Mn2+

MnCl+, MnO4−

MnO2, Mn3O4

Little known

Little known

Sulphides

Low toxicity

Niobium (8.4) Iron (7.9) Nickel (8.9) Cobalt (8.9)

Nb

5+

3+

2+

Fe > Fe Ni

2+

2+

3+

2+

Co > Co

Elemental, Carbonyls

—

Elemental, carbonyls

Cadmium (8.7)

Cd only

—

Species dependent; Cd2+ low toxicity

Copper (9.0)

Cu2+ > Cu+

Organo complexes

Elemental, Cu2+

Polonium (9.0)

Little known

Little known

Little known

but very few soluble

Very few soluble Low toxicity

Bismuth (9.8)

2+

Ni(H2O6)

3+

5+

Bi , Bi mainly,

Molybdenum (10.2) Complex chemistry, but very Few soluble few soluble forms

Little known, low toxicity?

Silver (10.5)

Ag+

AgS, complexes Low toxicity

Lead (12.0)

Pb2+

Alkyls, carbonyls

Tetraethyl and methyl lead

Technetium (11.5)

Little known

Little known

Little known

+

3+

Thalium(11.9)

T1 > T1

Dialkyls

Tl+, notably Tl2SO4

Palladium (12.0)

Many

Many

Many, but low exposure risk

Ruthenium (12.2)

Many

Many

Many, but low exposure risk

Rhodium (12.4)

Many

Many

Many, but low exposure risk

Hafnium (13.1)

Little known

Little known

Little known

2+

Mercury (13.6)

Hg

Alkyls, phenyls

Methyl mercury

Tantalum (16.6)

Ta5+, but few soluble forms

Few soluble forms

Little known

Tungsten (19–3)

Complex chemistry, but few Few soluble soluble forms forms

Little known

Gold (19.3)

Au+, Au3+ but only soluble as complexes

Soluble as complexes

Low toxicity

Rhenium (21.0)

Probably Rh3+

Little known

Little known

Platinum (21.4)

Many

Many

Many, but low exposure risk

Indium (22.5)

Many

Many

Many, but low exposure risk

Osmium (22.6)

Many

Many

Many, but low exposure risk

aqueous phase (Stoeppler, 1991). Depending on the purpose of the analysis, distinguishing between solid phase, aqueous phase and the total metal component of a sample may be necessary (Antonovich and Bezlutskaya, 1996). Some work has focused on measuring “bioavailable” forms, rather than total metal concentrations (Selifonova et al., 1993; Virta et al., 1995), as a better indicator of sample toxicity. “Bioavailability” is, however, a poorly defined and misleading term. There is no such thing as universal “bioavailability”—interactions between a plethora of organisms and the many forms of heavy metals must be considered on individual sets of circumstances. For example, mercury exists mainly as mercuric ions in water systems (Burg and Greenwood, 1991). Since organisms as diverse as bacteria and man can ingest this water-soluble form, mercuric ions may be considered bioavailable. Whilst it can be a potent anti-bacterial, some bacterial strains convert mercuric ions to elemental mercury, which is excreted without harm to the organism (Hughes and Poole, 1989), and humans only absorb about 7% of ingested inorganic mercury (Clarkson, 1972). So whilst mercuric chloride could be classed as “bioavailable”, it is not necessarily a direct toxic threat. In contrast, methylmercury is only sparingly soluble and thus less available. Methylmercury is lethal to many bacteria, but some bacterial species are resistant to it. Humans, to whom methylmercury is highly toxic, absorb up to 95% of this compound following ingestion (Clarkson, 1972). Being lipid soluble, it also has a high bioconcentration factor, and has proved a serious toxin in the aquatic food chain (Fergusson, 1990; Alloway and Ayres, 1997). So, although less readily “available” than mercuric ions, methylmercury is a much greater toxic threat.

Sensor development for water sample analysis has inevitably focused on dissolved substances, but the purpose behind analysing a given sample type should govern the target analyte and sensor design. 4.4.1.4. Water analysis and the law

Legislation defining the permissible levels of heavy metals in drinking water, environmental waters, industrial and agricultural effluents exists in many countries. Such legislation rarely considers metal speciation, but uses parts per million or billion (ppm or ppb) etc. of total metal to define limits instead. Legal maxima for heavy metal concentrations guide the sensitivities required of methods used for water analysis, including sensors. Levels of mercury permissible by European law incorporated as the UK Water Act 1989 are given as an example (Table 4.24). These permissible levels change with some regularity, nearly always to lower concentrations, and these changes can either follow improved analytical sensitivity or drive analytical research (Wilder, 1995). 4.4.2. CURRENT ANALYTICAL METHODS

Water quality is currently screened in a number of ways, with the United Nations and Economic Commission for Europe (UN/ECE) recommended tests grouped to cover toxicity e.g. Microtox® and Toxkit; mutagenicity/carcinogenicity e.g. Mutatox® and Table 4.24. Examples of mercury levels permitted in British and European water systems. Source of Mercury

Permitted levels

Drinking water standard (Britain and Europe)

1 µg/l total Mercury

Mercury and its compounds discharged into waters, above background, in any 12 month period (Britain and Europe)

200g (expressed as metal)

Manufacture of organic and inorganic mercury compounds (Britain)

0.05 mg/l effluent 0.05 g/kg mercury processed

Manufacture of primary batteries containing mercury (Britain)

0.05 mg/l effluent 0.03 g/kg mercury processed

Mercury recovery plants, non-ferrous metal extraction and refining, plants treating toxic waste containing mercury (Britain)

0.05 mg/l effluent

Manufacture of mercury catalysts used in vinyl chloride production (Britain)

0.05 mg/l effluent 0.7 g/kg mercury processed

Industries using mercury catalysts (not vinyl chloride production) (Britain)

0.05 mg/l effluent

5 g/kg mercury processed Industries using mercury catalysts in vinyl chloride production (Britain)

0.05 mg/l effluent 0.1 g/t vinyl chloride production capacity

SOS Chromotest®; and persistence/biodegradation e.g. Biological Oxygen Demand/ Chemical Oxygen Demand (BOD/COD). None are specific for a single metal. When water samples fail the screening tests, analyses for individual metals may carried out. Tests for specific metals acceptable to both British Standards (BS) and the International Standards Organisation (ISO) are largely atomic absorption spectroscopic (AAS) methods, some with flame, e.g. ISO5961 for cadmium and ISO8288 for cobalt; some flameless, e.g. ISO5666 for mercury. BS 6068 covers such tests extensively. Determinations of certain metal species require fractionation prior to AAS, e.g. organometallics such as the alkylmercuries, tests for which use GC-AAS. Other methods include that for arsenic by a spectrophotometric assay of a silver diethyldithiocarbamate complex (ISO6595). Inductively coupled mass spectrometric methods with pre-concentration and chromatographic fractionation steps have been reported, with sensitivities as low as 100 pg Cr3+ and 200pg Cr4+ (Byrdy et al., 1995). Methods relevant to environmental analysis are reviewed comprehensively in Analytical Chemistry (Clement et al., 1997; Clement et al., 1995). The role of laboratory test methods such as the many subtle variations of AAS is not in doubt. There is, however, a growing need for rapid on site screening tests, which, for example, could enable judgement to be made about which samples require laboratory testing, or could rapidly assess the viability of an industrial waste water stream. The versatility and comparative speed of biological methods developed to date, and an increasing amount of research in environmental sensors, suggest that a biosensors approach may be productive in environmental water testing (Kong et al., 1995). The following text groups heavy metal biosensors according, roughly, to the nature of the biological entity concerned, i.e. whole organisms, whole cells or specific proteins. Metal species relevant to environmental water analysis have been summarised (Table 4.23), but we recommend “Metals and their compounds in the Environment” (Merian, 1991) as providing a comprehensive background to this subject. 4.4.3. BIOASSAYS USING WHOLE CELLS/ORGANISMS

Environmental monitoring using living organisms has ranged from exploiting particular pollution responses observed in ecosystems as early warning signs, to attempting to use specific organisms as indicators, either in the field or the laboratory. Zebra fish (Brachydanio rerio) and the crustacean Daphnia magna, amongst other species, are still widely used in static, semi-static and flow-through cells to test for general water toxicity (ISO7346/1/2/3). Such tests are, however, screening tests only, and are inadequate in themselves for defining water quality. Zebra fish tests presently remain part of the UN/ECE recommendations for water quality monitoring.

Experiments using transgenic strains of the nematode worm Caenorhabditis elegans have coupled control regions from stress-inducible genes to the lacZ reporter gene, yielding a colorimetric assay for stress on the organism. Mercury, lead, copper (II), zinc and cadmium ions all induced lacZ expression. The sensitivity of the assay to cadmium ions was shown to lie in the subtoxic region, at around a hundredth of the LC50. (Candido and Jones, 1996) Commercially available general toxicity assays employing luminescent bacteria, such as the Vibrio fischeri Microtox® system (Azur Environmental Ltd, Wokingham, UK) have been employed in studies of heavy-metal toxicity e.g. Sillanpaa and Oikari, 1996. 4.4.4. ENGINEERED MICROORGANISMS AS SENSORS

A wide variety of genes have been identified where the expression is modulated by the concentration of metal ions. By fusing the promoter region of these genes with a reporter gene whose expression is amenable to assay, it is possible to construct more specific whole-cell biosensors that are extremely sensitive. 4.4.4.1. Promoters as sensing elements

In considering the suitability of metal-inducible promoters for use in biosensors, it is worth noting that the dynamic range of their response can vary greatly. This reflects the relationships between living cells and the various metals—some metals are toxic even in trace amounts, whilst others are micronutrients, which can be toxic in excess. Rouch et al. (1995) demonstrated this in comparing mercury and copper dependent promoters. The mercury dependent PmerTPAD promoter from Tn501 is hypersensitive (Hill coefficient is around 2.6), giving a 10–90 % induction across a four-fold change in Hg2+ concentration, which permits full induction of resistance genes at subtoxic Table 4.25. Examples of whole cell luminescent biosensors for heavy metals. Analyte

Promoter Source

References

2+

Tn21 mer operon

(Virta et at., 1995)

2+

Hg

Serratia marescens

(Tescione and Belfort, 1993)

Hg2+

Tn21 mer operon (with transport system)

(Selifonova et al., 1993)

Hg

Cd2+, Zn2+, Cu2+, Hg2+, Co3+, Synechococcus metallothionein promoter, smt Ni2+

(Erbe et al., 1996)

Cu2+, Tl4+/Tl6+, As3+/As5+, Cd2+

(Collard et al., 1994)

Alcaligenes eutrophus Staphylococcus aureus

levels of mercury. In contrast, the copper sensitive promoter PpcoE is hyposensitive (Hill coefficient is around 0.6), giving a response spread over several orders of magnitude. The former

is more suited to the detection of a threshold level of mercury whilst the latter has more potential for use in a quantitative sensor. Induction of expression in the presence of the target analyte may require the interaction of protein regulatory factors with the promoter, as in the interaction between the MerR protein and the promoter region of the mer operon (Foster, 1987). Induction may be contingent on transport of the metal into the cell, which will be highly dependent on the speciation of the analyte (Foster, 1987; Silver and Misra, 1988; Silver, 1992). It is also worth noting that cell viability is needed for reporter gene expression, so analyte toxicity could restrict the dynamic range of the sensor. 4.4.4.2. Sources of promoters

As the molecular basis for heavy metal tolerance in environmental microorganisms is investigated, a growing number of metal-inducible promoters have been identified. These vary in their selectivity and sensitivity—for example, in the case of mercury, both narrow-spectrum induction by Hg2+ ions, and broad-spectrum induction by a range of organomercurial compounds in addition to Hg2+ ions, has been observed. In an alternative approach to the identification of novel promoters, a luciferase reporter gene was cloned into the Tn5 transposon and randomly inserted into the genome of Escherichia coli. This library of gene fusions was then screened to identify clones exhibiting luminescence dependent on concentration of the target metal ion. From this procedure aluminium, nickel and selenite dependent promoters were identified (Guzzo and DuBow, 1994). Examples of biosensors based on metal-inducible promoters linked with luminescence reporter systems are shown (Table 4.25). 4.4.5. SENSORS USING BIOLOGICAL MOLECULES

Heavy metals have a strong affinity for sulphur, and their effect on biological systems is mainly via interactions with thiol groups in proteins. Cysteinyl residues have essential roles in the function of many enzymes, particularly those involved in hydrolytic and redox catalysis. Inhibition of enzyme activity upon titration of active-site thiols with metal ions has formed the basis of heavy metal determination systems emerging from many groups. The metal-binding sites of many metalloproteins are extremely specific chelators for their respective targets, and monitoring the binding events, rather than any resulting catalysis, may enable the detection of metals with no known participation in enzymatic activity. Such heavy metal binding sites exist in metallothioneins and in various protein elements of bacterial heavy metal resistance mechanisms, despite having no apparent catalytic functions. In particular, a cysteine-rich heavy metal-associated (HMA) protein motif has been described in a range of proteins which specifically bind a number of different metals. With structural information becoming available for some of these (Steele and Opella, 1997), it is possible to envisage rational engineering of specificity and affinity (Hellinga, 1996). 4.4.5.1. Heavy metals as enzyme substrates

Many bacterial heavy metal resistance mechanisms are known, which may involve metal ion reductases or other proteins potentially useful in sensor research (Silver and Misra, 1988;

Cervantes and Silver, 1992; Kaur and Rosen, 1992; Nies, 1992; Silver, 1992; Lloyd et al., 1997). Mercuric reductase, involved in both “narrow” and “broad” range bacterial mercury resistance, is a well studied example. Mercuric reductase couples reduction of Hg2+ to oxidation of a nicotinamide cofactor, suggesting the possibility of a linked enzyme assay (Lowe et al., 1996). 4.4.5.2. Inhibition of enzyme activity

Heavy metals are potent inhibitors of the activity of various enzymes, and systems based on this principle have been developed. At present, however, most such systems exhibit low specificity, although they may be very effective general indicators of heavy metal or toxin presence in water samples (Wittekindt et al., 1996; Cowell et al., 1995). Exploiting enzyme inhibition in a biosensor for a specific metal species represents a considerable challenge. It appears possible to optimise specificity for Hg2+, one of the more toxic metal forms, but the specific assay of other species in complex mixtures, such as those encountered in the field, has yet to be proven. Sensitivities reported for various analytes broadly correlate with their toxicity—ranging from mercury at ng/ml through cadmium, zinc, and lead to copper at µg/ml. These methods have an intrinsic lack of specificity. Attempts to overcome this have investigated the possibility of using arrays of different enzymes to build up inhibition profiles for various inhibitors (Cowell et al., 1995; Danzer and Schwedt, 1996). Use of neural networks to perform profile crossmatching can enable identification of specific inhibitors, but it is questionable how applicable this approach could be to the complex mixtures of metals potentially present in field samples. The presence of species involved in the reaction catalysed by the enzyme may be an additional interference with inhibition-based assays, for example ammonia has given high blank readings with urease assays (Jung et al., 1995). Examples of enzyme inhibition biosensors are given (Table 4.26). Table 4.26. Examples of enzyme inhibition biosensors for heavy metals. Analyte

Enzyme

Transduction

References

Hg2+

urease

surface acoustic wave resonance

(Liu et al., 1995)

Cu2+

urease

ion-sensitive field-effect transistor

(Zuern and Mueller, 1993)

urease

calorimetric

(Mattiasson, 1978)

Hg , Cu , Cd , Co2+, Pb2+, Sr2+

urease

conductimetric

(Zhylyak et al., 1995)

Heavy metals

β-galactosidase

colorimetric, fluorometric

(Ayoub et al., 1995)

Heavy metals

oxidases

O2 electrode

(Gayet et al., 1993)

Hg

horse-radish peroxidase

chemiluminescence

(Shekhovtsova et al., 1996)

Heavy metals

urease

colorimetric

(Wittekindt et al., 1996)

Hg2+

invertase and glucose O2 electrode oxidase

Hg2+, Cu2+ 2+

2+

2+

2+

(Amine et al., 1995)

4.4.5.3. Activation of metalloenzyme function

Although a large number of enzymes require specific metal cofactors for activity, just a very few metals fill the majority of metal cofactor roles. Restoration of enzyme activity obtained in the presence of certain metal ions, which might be exploited in assaying those metal ions has, therefore, a narrow range of potential analytes. In some cases, it will be possible to use the reactivation of enzyme activity on addition of metal cofactor as the recognition process. This principle has been demonstrated in the detection of copper, which reconstituted activity in galactose oxidase and ascorbate oxidase activities, and of zinc, which reconstituted activity in carbonic anhydrase and alkaline phosphatase (Satoh, 1990). 4.4.5.4. Fluorescent probes of metal binding sites in metalloenzymes

In fluorescent probe metal assays, apoenzymes have been used as highly refined chelators of target analytes. Certain competitive inhibitors of carbonic anhydrase function by binding to the active-site zinc, preventing its participation in catalysis. The arylsulphonamide compound dansylamide has been shown to bind to enzyme-bound zinc with concomitant enhancement and blue shift of its fluorescence. Thus dansylamide can be used as a probe sensitive to zinc binding by the apoenzyme. Whilst other metals are bound by the enzyme to a certain extent, they do not interact with the sulphonamide, and a fibre-optic biosensor based on this principle has been demonstrated (Thompson and Jones, 1993; Thompson and Patchan, 1995). Furthermore, by detecting fluorescence energy transfer from a fluorescent tag to the bound metal ion, cobalt and copper binding could be detected (Thompson et al., 1996). For metals ions exhibiting d-d absorbance bands at appropriate wavelengths, this may be an alternative probe of active site occupancy. Tracking zinc concentrations by measuring fluorescence of an artificial antibody has been possible—the zinc binding site from carbonic anhydrase was grafted onto a IgG light-chain backbone—showing the potential utility of simple de-novo engineered proteins in biosensing (Wade et al, 1993; Satoh, 1993; Satoh and Iijima, 1995). 4.4.6. CONCLUDING COMMENTS

The purposes behind analysing water samples vary—i.e. is it the total load of a metal or metals in a given water system that needs to be determined, or is it just the presence above a threshold level of a single metal or single metal species? General water quality or toxicity screening will also target a number of non-metallic analytes. Is the purpose better served by a single, general screening test, or by a range of distinct methods for groups of similar analytes e.g. heavy metals, pesticides, nitrates? The form of a metal may be insoluble and largely inert upon introduction to the environment, but with time may well be altered to more soluble and toxic forms. This poses a significant analytical challenge. Is the measurement a one-off, one of a regular sequence, or even “in-line” and continuous? Is it necessary to take a sensor to the sample, or can the sample be brought to an analytical laboratory? Is the measurement for screening purposes, with any unusual results followed by more extensive laboratory analysis, or will it be relied upon alone? Although analysis tends to focus on the chemical composition of waters exiting a process or facility, it is worth remembering that the need to monitor water quality at point of intake exists, notably in the brewing industry. With a clearly understood purpose, it must then be determined that a biological sensor or system is the best option for the corresponding analytical role. UN/ECE

recommendations include integrating the assessment of water quality and effluent quality strategies, with rapid on-the-spot sample prescreening and thence stepwise testing of analyte groups from “coarse to fine”, to gather as much information as possible. Of the systems reported to date, some are commercially available and some are regularly used for environmental or water quality monitoring purposes e.g. the Microtox-® tests. The potential for effective biosensors in the environmental sphere, and the need for such systems, has been documented (Erbe et al., 1996). Of the systems in use, none is a novel biosensor in the format of e.g. the Medisense Exactech® glucose monitor; rather, they are biological systems that, with suitable instrumentation, are analytically useful. Instances of an established sensor being diverted from its intended role to measure a heavy metal have been recorded, such as mercuric ion detection with a glucose probe (Amine et al., 1995) and non-biological portable sensors for heavy metals are also being developed (Williams and D’silva, 1994). Although metals are difficult propositions for immunologists, immunoassays for some metals, including mercury, have been reported (Blake et al., 1997; Szurdoki et al., 1997). These techniques, however, do not yet appear suitable for true sensor development. Because of the wide variety of heavy metals that are of environmental relevance, technologies that can be applied to wide range of metals, both as general screening tests and in the form of metal-specific sensors, are of the most interest. We wait to see if promising research, such as that into arsenate and mercury detection (Khan et al., 1996; Lowe et al., 1996), and general toxicity screening with enzyme inhibition (Danzer and Schwedt, 1996) actually yield any commercially produced, probe or dip-stick type biosensors for a heavy metal or metals. REFERENCES

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4.5. PHOSPHATE

AXEL WARSINKE 4.5.1. INTRODUCTION

The determination of phosphate is not only important for environmental control, but also for clinical diagnostics. Various diseases are accompanied by higher or lower phosphate concentrations (e.g. chronic renal insufficiency, vitamin-D-intoxication, primary hypoparathyroididmus, raccharitis). For animals and plants inorganic phosphate and the related phosphoric acid esters have an important role in the energy status of the cell, glycolysis, mineral and nucleic acid metabolisms and for the constitution of the cell membrane. To increase the yields in agriculture phosphate rich fertilizers are frequently used. Nevertheless, only about 10 percent of the phosphate contamination in a river is due to the usage of fertilizers. The greatest part (80 %) is contributed by domestic waste water. For analysis three different kinds of phosphates can be distinguished: The soluble o-phosphates, the whole phosphates and the particle bound insoluble phosphates. In spring-water and rainwater the o-phosphate is less abundant whereas near the outflow of waste water it occurs in high concentrations. So, the concentration of o-phosphate can be used as an indicator for waste water entrance. An example is the increased load of a river, the Mosel near Koblenz, which was contaminated with 0.1–0.2 mg/1 (about 1–2 µM) in 1961 whereas in 1975 the river was contaminated with 2 mg/l (about 20 µM). Because phosphate is one of the essential nutrients for eutrophication, high concentrations of phosphates can cause accelerated growth of plankton becoming more and more serious in many parts of the world. To control drinking water, food products and body fluids methods are required for phosphorous analyses in samples from many different origins. The recommended maximum value in drinking water is 1 mg/l (10 µM.). Therefore, analytical methods should not only be highly specific but should also be very sensitive. Furthermore, for widespread application the developed method should be reliable and cost-effective. Bioanalytical methods, especially when the biocomponent is reusable, have the potential to fulfil these requirements. Routinely, inorganic phosphate (Pi) is determined by the molybdenum blue method of Fiske and Subbarow in original (1925) or modified forms (Martland and Robinson, 1926; Saheki et al., 1985). After adding molybdate with subsequent reduction, the resulting phosphor-molybdenumblue complex is determined colorimetrically. Recently, Masini et al. (1995) applied this method to sequential injection for on-line monitoring of phosphate during the production of biomass in aerobic fermentations of Saccharomyces cerevisaei. Other methods like ion-selective electrodes (Glazier and Arnold, 1988; Goediker and Cammann, 1989) or ion chromatography (Singh and Nancollas, 1988) have also been described in the past, but normally exhibit low sensitivities, specificities or are rather laborious. A breakthrough in phosphate determination was achieved by the introduction of biomolecules as highly specific analytical tool. To describe all bioanalytical methods for phosphate deter-

mination would be beyond the scope of this chapter. Therefore mainly biosensors will be described. Biosensors for the determination of phosphate are normally based on mono- or multienzymatic reactions and can be divided in two catagories: (1) where phosphate acts as inhibitor (2) where phosphate acts as a second substrate. 4.5.2. PHOSPHATE AS INHIBITOR

Weetall and Jacobson (1972) have reported a spectrophotometric assay based on an alkaline phosphatase (aP, EC 3.1.3.1) reaction which produces a coloured product and which is inhibited in proportion to the phosphate concentration in the sample. To apply this principle to a biosensor, Guilbault and Nanjo (1975) used aP and glucose oxidase (EC 1.1.3.4) in combination with an oxygen electrode (−600 mV, Pt vs. SCE) (Figure 4.13). Glucose-6-phosphate was converted by aP (Figure 4.13) phosphatase to glucose (ß-Glc) which was converted to gluconolactone under oxygen consumption and hydrogen peroxide production by glucose oxidase. The oxygen decrease was measured. After addition of phosphate an oxygen increase was observed due to the inhibition effect of phosphate to the aP. The detection limit for phosphate was found to be 100 µM and therefore not sensitive enough for assay of low concentrations of phosphate ion in river water. In addition to the inhibitory effect of phosphate, the

Figure 4.13. Scheme of an enzyme sensor for phosphate determination by inhibition of the phosphatase reaction.

inhibitory effect of other anions were investigated. The order of inhibition was found to be as follows: . However, it was argued that in an assay for phosphate in rivers, streams or lakes it is unlikely that any of these ions would be present to interfere. Other ions that exist in water solutions as chloride, nitrate and sulfate which gave serious interferences on non-enzymatic ion-selective electrodes, did not show any effect up to 0.1 M. As indicated in Figure 4.13 amperometric hydrogen peroxide detection would also be possible with this principle. Su and Mascini (1995) used a platinum working electrode modified with a poly(phenol) film for hydrogen peroxide measurements instead of a plain electrode and thereby reduced interferences (e.g. ascorbic acid, uric acid). Nevertheless, as with all biosensors based on measurements of the changes in enzymatic activity (kinetic controlled biosensors), this principle is very susceptible to a huge number of different factors (e.g. stability of the biomolecule, inhibition by unknown components, etc.). After each determination the biosensor has to be calibrated very carefully. With respect to stability, Schubert et al. (1984) have improved this principle by use of a potato (Solanum tuberosum) tissue slice instead of alkaline phosphatase. The potato acid phosphatase (EC 3.1.3.2) was stabilized by the native environment allowing several hundred samples to be determined with high sensitivity. The lower detection limit of this hybrid sensor was 50 µM which was not sufficient for measurements in river water or serum, but acceptable for fertilizers and urine samples. Instead of using glucose-6-phosphate as the substrate of aP other substrates have been applied with the same principle. Razumas et al. (1980) used, for instance, catechol phosphate. The catechol released by the aP reaction was detected amperometrically on a solid electrode (+200 mV). Katsu and Kayamoto (1992) used o-carboxyphenyl phosphate as a substrate of aP. The salicylate produced was detected potentiometrically by a salicylate-sensitive membrane electrode. The lower detection limit was found to be 50 µM. The advantage of using substrates other than glucose-6-phosphate is that the sensor is also applicable for phosphate determinations in samples where glucose is present, e.g. for phosphate determination in serum. 4.5.3. PHOSPHATE AS A SECOND SUBSTRATE

The advantage of determining phosphate as a substrate instead as an inhibitor of an enzymatic reaction is obvious. Because the sensor can operate under diffusion control the sensor will be much more reliable and precise than the phosphate sensors operating under kinetic control as described before. The selectivity should also be higher as phosphate acts directly as a reaction partner of a chemical reaction within the active site of an enzyme. Two approaches are used as the initial phosphate utilizing reaction: (1) the use of a phosphate-dependent pyruvate oxidase (EC 1.2.3.3) or (2) the use of phosphorylases.

Pyruvate oxidase catalyzes the oxidation of pyruvate in the presence of phosphate and oxygen, with the formation of acetylphosphate, carbon dioxide, and hydrogen peroxide (Figure 4.14). Mizutani (1980) used this enzyme for the determination of

Figure 4.14. Scheme of an enzyme sensor for phosphate determination by using pyruvate oxidase. pyruvate by using immobilized pyruvate oxidase and an oxygen electrode. Six years later Ngo used the enzyme pyruvate oxidase for the first time for phosphate determination (1986). After the electrode (YSI-Clark 2510 hydrogen peroxide probe (+700 mV)) was immersed in the stirred substrate solution (sample+pyruvate) the reaction was started by adding the pyruvate oxidase to the solution. After 4min signal registration the cell was washed thoroughly with buffer. The registered hydrogen peroxide concentration was proportional to the phosphate concentration within the sample. A range of 50–500 µM phosphate has been measured by this method with high specificity. Kubo et al. (1991) used the same principle, but with oxygen indication, for the development of a phosphate biosensor by immobilization of the enzyme in PVA-SbQ in front of an oxygen electrode (Figure 4.14). The determination time was 7 min with a linear range of 12– 80 µM phosphate. Although 0.8 mM TPP and 10 µM FAD were added to the buffer, after 7 days use the response decreased to 50% of the initial value. This fast inactivation of pyruvate oxidase was one of the main problems for applying this enzyme to bioanalytical problems. The maximum permissible phosphate concentration of the natural waters in Japan is 0.32 µM. To shift the detection limit to lower concentrations Ikebukuro et al. (1996a; 1996b) used pyruvate oxidase in combination with a subsequent luminol chemiluminescence reaction to detect the hydrogen peroxide produced much more sensitively. The enzyme was immobilized to aminoalkylated controlled pore glass by glutaraldehyde and used in a small column within a FIA system, After injection of phosphate into the column, equilibrated with pyruvate, TPP, FAD and MgCl2, hydrogen peroxide was produced. Thereafter, in a mixing cell luminol and p-iodophenol were added and pumped to a flow cell with immobilized peroxidases where the chemiluminescence reaction took place which was detected by a photomultiplier tube. In comparison to the work of Kubo et al. (1991) the linear response was shifted to 0.37–7.4 µM.

The detection limit was observed to be 0.074 µM. In that case the sensitivity was sufficient for water control. By using a column instead of a membrane the amount of immobilized enzyme was increased. Under optimized storage conditions it was possible to detect 7.4 µphosphate for 2 weeks. Besides the pyruvate oxidase-based assays various enzymatic assays have been developed based on an initial phosphorylase reaction. In clinical diagnostics a highly specific enzymatic method based on an phosphorylase reaction has found widespread application (Gawehn, 1985) and this can also be used for other matrices. In the presence of phosphate glycogen (glucosen) is converted by the enzyme phosphorylase a (EC 2.4.1.1) to glycogen (glucosen−1) and glucose-1phosphate. The enzyme phosphoglucomutase (EC 5.4.2.2) converts the produced glucose-1phosphate to glucose-6-phosphate, which is indicated in the presence of NAD or NADP by a glucose-6-phosphate dehydrogenase (EC 1.1.1.49) reaction. The produced NADH is measured spectrophotometrically and is directly proportional to the phosphate concentration in the sample. Based on the same phosphorylase (phosphorylase a) Wollenberger and Scheller (1993) have developed an interesting principle for a reagentless phosphate sensor (Figure 4.15). Glycogen (glucosen) is coimmobilized with phosphorylase a, phosphatase (i.e. alkaline phosphatase), mutarotase (EC 5.1.3–3) and glucose oxidase within a membrane layer. As shown in Figure 4.15, both hydrogen peroxide production or oxygen consumption can be measured with a hydrogen peroxide sensor (+600 mV; Pt vs Ag/AgCl) or with a Clark-type oxygen sensor (−600 mV; Pt vs Ag/ AgCl), respectively. Because phosphate is released during the phosphatase reaction, substrate recycling is achieved. The measuring range is described to be 50–1000 µM with a detection limit of 10 µM. Nevertheless, for practical use of this sensor further optimizations with respect to the coimmobilization within the membrane are necessary. A principle (de Groot, 1984) which is often used in biosensors is based on the combination of the enzymes nucleoside phosphorylase (EC 2.4.2.1) and xanthine oxidase (EC 1.1.3.22). Watanabe et al. (1988) immobilized nucleoside phosphorylase and xanthine oxidase on a triacetyl cellulose membrane and fixed the membrane on the tip of the Clark-type oxygen electrode (−600 mV, Pt vs Ag/AgCl). This enzyme electrode was incorporated into a FIA system. Tris-HCl buffer (0.1 M, pH 7.0) containing inosine (0.2 mg/ml) was pumped continuously to the sensor by a peristaltic pump at a flow rate of 1.4 ml/min. A 50 µl aliquot of the phosphate sample was injected into the flow channel and the oxygen decrease was recorded. Linearity of the phosphate dependency was obtained from 300–1000 µM. Optimizations have produced more stable and sensitive enzyme sensors (D’Urso and Coulet, 1993) with a linear response of 10–250 µM (Haemmerli et al., 1990) and with a lower detection limit of 1.25 µM (Male and Luong, 1991). In contrast to the measurement of the consumed oxygen, in these works both the detection of the hydrogen peroxide as well as the uric acid produced were used (+700 mV; Pt vs Ag/AgCl). A further type of measurement was realized by Kulys et al. (1992). Instead of the oxidation of the reduced xanthine oxidase by oxygen, the reduced enzyme was oxidized on a 7, 7, 8, 8tetracyanoquinodimethane (TCNQ)-modified graphite electrode. The oxidation of the reduced TCNQ (KTCNQ) lead to an anodic current generated by the biosensor at +100 mV.

Figure 4.15. Scheme of a reagentless enzyme sensor for phosphate determination by using coimmobilized glycogen (glucosen), phosphorylase a and phosphatase for substrate recycling. A further improvement in lowering the detection limit was achieved by Wollenberger et al. (1992). They introduced uricase to this principle to convert the produced uric acid to allantoin accompanied by additional oxygen consumption as well as additional hydrogen peroxide production. The coimmobilization of both oxidases resulted in a 130% enhanced response. The oxygen consumption was measured by a Clark-type electrode. To avoid inactivation of the xanthine oxidase by increased hydrogen peroxide concentrations catalase was introduced. The result was an increase of the working stability to at least 8 days with 300 measurements. A detection limit of 0.5 µM and a linear range of 0.5–100 µM have been described for this configuration. Furthermore, the detection limit was improved by application of substrate recycling. Alkaline phosphatase was introduced to release phosphate from the produced ribose-1phosphate due to the nucleoside phosphorylase reaction

Figure 4.16. Scheme of an enzyme sensor for phosphate determination by using nucleoside phosphorylase and phosphatase for substrate recycling. (Figure 4.16). The result was a 20-fold enhancement in sensitivity. Thus the detection limit of the phosphate electrode was shifted to 25 nM which is quite sufficient for water control. Another principle for phosphate determination with internal substrate recycling using an initial phosphorylase reaction is based on a maltose phosphorylase (EC 2.4.1.8) reaction in combination with a phosphatase, mutarotase and glucose oxidase reaction (Warsinke and Gründig, 1992). As shown in Figure 4.17 the maltose molecule is converted by the maltose phosphorylase reaction into β-glucose-l-phosphate and a-glucose with the consumption of one phosphate molecule. By the phosphatase reaction as well as by the mutarotase reaction two molecules β-glucose are produced which are detected within the glucose oxidase reaction by hydrogen peroxide or oxygen measurement. In this way two molecules β-glucose are produced per molecule phosphate. Due to the phosphatase reaction phosphate is liberated from β-glucose-1-phosphate and can be consumed again by the phosphorylase reaction. This internal

Figure 4.17. Scheme of an enzyme sensor for phosphate determination by using maltose phosphorylase and phosphatase for substrate recycling. substrate recycling led to an amplification factor of at least 15. No intermediates other than βglucose are produced during the overall reaction. After optimization a linear range of 0.1–1 µM with a detection limit of 10 nM was obtained, which is the lowest detection limit ever observed for a phosphate biosensor (Conrath et al., 1995). However, because the final product is glucose determined by the glucose oxidase reaction, the sensor is not suitable for serum measurements. The principle should be applicable for environmental control. REFERENCES

Conrath, N., Gründig, B., Hüwel, St. and Cammann, K. (1995) A novel enzyme sensor for the determination of inorganic phosphate. Anal. Chim. Acta, 309, 47–52. DeGroot (1984) Method for the enzymatic determination of inorganic phosphate and Ist application, European Patent EP, 147867.

D’Urso, E.M. and Coulet, R.P. (1993) Effect of enzyme ratio and enzyme loading on the performance of a bienzymatic electrochemical phosphate biosensor. Anal. Chim. Acta, 281, 535– 542. Fiske, C.H. and Subbarow, Y. (1925) The colorimetric determination of phosphorous. J. Biol. Chem., 66, 375–400. Gawehn, K. (1985) Inorganic phosphate. In Methods of enzymatic analysis, Bergmeyer, H.U. (ed.) 7, pp. 552–558. Weinheim: VCH. Glazier, S.A. and Arnold, A. (1989) Phosphate-selective polymer membrane electrode. Anal. Lett., 22, 1075. Goediker, W. and Cammann, K. (1989) Properties of a phosphate sensitive solid state electrode based on cerium-IV-hydrogenphosphate mixed with PVC. Anal. Lett., 22, 1237. Guilbault, G.G. and Nanjo, M. (1975) A Phosphate-selective Electrode based on Immobilized Alakaline Phosphatase and Glucose Oxidase. Anal. Chim. Acta, 78, 69–80. Haemmerli, S.D., Suleimann, A.A. and Guilbault, G.G. (1990) Amperometric Determination of Phosphate by Use of a Nucleoside Phosphorylase-Xanthin Oxidase Enzyme Sensor Based on a dark-Type Hydrogen Peroxide or Oxygen Electrode. Anal. Biochem., 191, 106–109. Ikebukuro, K., Nishida, R., Yamamoto, H., Arikawa, Y., Nakamura, H., Suzuki, M., Kubo, I., Takeuchi, T. and Karube, I. (1996a) A novel biosensor system for the determination of phosphate. J. Biotech., 48, 67–72. Ikebukuro, K., Wakamura, H., Karube, I., Kubo, I., Inagawa, M., Sugawara, T., Arikawa, Y, Suzuki, M. and Takeuchi, T. (1996b) Phosphate sensing system using pyruvate oxidase and chemiluminescence detection. Biosens, and Bioelectr., 10/11, 959–965. Katsu, T. and Kayamoto, T. (1992) Potentiometric determination of inorganic phosphate using a salicylate-sensitive membrane electrode and an alkaline phosphatase enzyme. Anal. Chim. Acta, 265, 1–4. Kubo, I., Inagawa, M., Sugawara, T., Arikawa, Y and Karube, I. (1991) Phosphate sensor composed from immobilized pyruvate oxidase and an oxygen electrode. Anal. Lett., 24, 1711– 1727. Kulys, J., Higgins, I.J. and Bannister, J.V. (1992) Amperometric determination of phosphate ions by biosensor. Biosens, and Bioelectr., 7, 187–191. Male, K.B. and Luong, J.H.T. (1991) An FIA biosensor system for the determination of phosphate. Biosens, and Bioelectr., 6, 581–587.

Martland and Robinson (1926) CVI. Possible significance of hexose-phosphoric esters in ossification. Part VI. Phosphoric esters in blood-plasma. Biochem. J., 20, 847–855. Masini, J.C., Baxter, P.J., Detwiller, K.R. and Christian, G.D. (1995) online spectrophotometric determination of phosphate in bioprocesses by sequential injection. Analyst, 120, 1583–1587. Mizutani, F., Karube, I., Matsumoto, K., Suzuki, S. and Tsuda, K. (1980) Determination of glutamate pyruvate transaminase and pyruvate with an amperometric pyruvate oxidase sensor. Anal. Chim. Acta, 118, 65–71. Ngo, T.T. (1996) Single-Enzyme-Based Amperometric Assay for Phosphate Ion. Appl. Biochem. Biotechnol., 13, 127–131. Razumas, V.J., Kulys, J.J. and Malinauskas, A.A. (1980) Acceleration of the electrode process by biocatalysis. 3. Amperometric analytical systems based on alkaline phosphatase. Liet. TSR Mokslu Akad. Darb Sehr. B, 5, 19–26. Saheki, S., Takeda, A. and Shimazu, T. (1985) Assay of Inorganic Phosphate in the Mild pHrange, Suitable for Measurement of Glykogen Phosphorylase Activity. Anal. Biochem., 148, 277–281. Schubert, F., Renneberg, R., Scheller, F.W. and Kirstein, L. (1984) Plant Tissue Hybrid Electrode for Determination of Phosphate and Fluoride. Anal. Chem., 56, 1677–1682. Singh, R.P. and Nancollas, G.H. (1988) Determination of phosphate, sulfate and oxalate in urine by ion chromatography. J. Chromatogr. Bio. med. Appl., 77, 373–376. Su, Y. and Mascini, M. (1995) AP-GOD biosensor based on a modified poly(phenol)film electrode and its application in the determination of low-levels of phosphate. Anal. Lett., 28(8), 1359–1378. Warsinke, A. and Gründig, B. (1992) Verfahren zum empfindlichen enzymatischen Nachweis von anorganischem Phosphat, German Patent, DE 4227569. Watanabe, E., Endo, H. and Toyama, K. (1988) Determination of Phosphate Ions with an Enzyme Sensor System. Biosensors, 3, 297–306. Weetall, H.H. and Jacobson, M.A. (1972) Studies on phosphate inhibition and quantitation using immobilized bacterial alkaline phosphatase. In Ferment. Technol. Today, Terui, G. (ed.) Proc. IV., 361. Wollenberger, U., Schubert, F. and Scheller, F.W. (1992) Biosensor for Sensitive Phosphate Detection. Sensors and Actuators B, 7, 412–415. Wollenberger, U. and Scheller, F.W. (1993) Enzyme activation for activator and enzyme activity measurement. Biosens, and Bioelectr., 8, 291–297.

4.6. NITRATE

AXEL WARSINKE 4.6.1. INTRODUCTION

As in the case of phosphate, nitrate is a well-known contaminant of ground- and stream water. Nitrate can also contribute to algae blooms and eutrophication and can lead to serious environmental problems. It is generally accepted that nitrate itself is not toxic. However, the reduction of nitrate to the hazardous nitrite, which can form carcinogenic N-nitroso compounds and which can cause methemoglobinemia, occurs in the presence of microorganisms which are present in the saliva within the mouth. Therefore the determination of nitrate and nitrite concentrations is of great interest especially for the supervision of drinking water. The routine methods are photometric (DIN 38405 D9/D10) which require a careful pretreatment of the samples. Other methods are based on ion-selective chromatography (Fritz et al., 1982) and electrochemical methods such as polarographic, voltammetric, and potentiometric determination (Davenport and Johnson, 1973; Hussein and Guilbault, 1974; de Beer and Sweerts, 1989). Although biosensors or bioprobes based on microorganisms have been described for nitrate determination in the past (Larsen et al., 1996; Schramm et al., 1996; Prest et al., 1997), in this part only enzyme sensors will be considered. 4.6.2. ENZYME SENSORS FOR NITRATE DETERMINATION

Hussein and Guilbault (1974) have shown that a potentiometric ammonia electrode can be used for the determination of nitrate and nitrite reductases from Escherichia coli during the cultivation process. The different reductases responsible for nitrate respiration and assimilation can be summarized as: 1. Dissimilatory nitrate reductase (EC 1.9.6.1)

H-donor=formate, succinate, lactate 2. Assimilatory nitrate reductase (EC 1.6.6.2)

H-donor=NADH, NADPH 3. Nitrite reductase (EC 1.6.6.4)

H-donor=NADH, NADPH, flavin (FMN-reduced), viologen

Kiang et al. (1978) used the nitrite reductase from spinach leaves for the determination of nitrite and in combination with the dissimilatory nitrate reductase from E. coli K12 for the determination of nitrate. Thereby the enzymes were used in immobilized form (glutaraldehyde immobilization to glass beads) in a flow system. For column 1 only nitrite reductase was used, whereas in column 2 nitrate reductase and nitrite reductase in a 1:1 ratio were used. As electron donor the reduced form of methyl viologen (MVH) was used, obtained through the chemical reduction of its oxidized form by dithionite. Finally, the ammonia produced due to the nitrite reductase reaction was determined by an air-gap electrode (Ruzicka and Hansen, 1974). Although it was possible to determine nitrate and nitrite with this concept, the method was only reasonable good for the determination of concentration greater than 500 µM (about 3 ppm). Since the U.S. Public Health Service has announced that allowable limits for nitrate and nitrite in potable water are 10 and 0.06 ppm, respectively, the method was not sensitive enough for potable water control. Based on the principle described before Willner et al. (1990) have immobilized the enzyme nitrate reductase in a polyacrylamide gel functionalized by MVH. It was shown that after chemically or photochemically generation of the viologen radical cation MV+ the enzyme can reduce nitrate to nitrite. The same was shown with poly(thiophene viologen)—modified electrodes (Willner et al., 1992). Nevertheless, the reduction of the viologen group could not be obtained by the electrode itself. Because no catalytic cathodic current was observed, the principle could not be utilized for the development of an amperometric enzyme sensor. In 1994 the first amperometric enzyme sensors for nitrate and nitrite were developed by Strehlitz et al. and by Cosnier et al. Strehlitz et al. tested a huge number of artificial electron donors as mediators for nitrite and nitrate reductases which were reduced at different potentials on a graphite electrode. With benzyl viologen as mediator (polarization voltage of the graphite electrode: −800 mV) and nitrate reductase the nitrate response was linear from 2–300 µM, whereas with l-methoxy-NMP+ (polarization voltage of the graphite electrode: −200 mV) and nitrite reductase the nitrite response was linear from 3–45 µM. An improvement in detection limit for nitrite was achieved by using a phenosafranin-modified graphite electrode (applied potential for reduction:—600 mV) and poly(carbamoyl sulfonate) (PCS) hydrogel immobilized tetraheme cytochrome c nitrite reductase. The linear response was up to 250 µM nitrite with a detection limit of 1 µM (Strehlitz et al., 1996). By using electropolymerization of a nitrate reductase-amphiphilic pyrrole viologen mixture on a polypyrrole-viologen precoated carbon disk electrode an amperometric nitrate electrode (applied potential for reduction: −700 mV) has been produced with a lower detection limit of 0.4 µM (Cosnier et al., 1994).

Recently, an interesting optical biosensor for nitrate has been described by using sol-gel immobilized nitrate reductase (Aylott et al., 1997). The procedure is as follows: In a first step the periplasmic nitrate reductase is reduced by sodium dithionite. By adding nitrate to the sensor the enzyme is reoxidized due to the conversion of nitrate to nitrite. The oxidation of the enzyme is accompanied with a decrease in absorbance at 550nm which is used as transducable signal. In contrast to other enzyme sensors, the transducable signal is not obtained by the determination of the cosubstrate or product concentration, but by the determination of changes of the physicochemical properties of the enzyme due to the enzymatic reaction itself. A linear response to nitrate was observed over the range 0–1.5 µM with a detection limit of 0.125 µM which is better than the other sensors described. By using sol-gel entrapment the activity of the enzyme was not affected even after a storage period of up to six months. REFERENCES

Aylott, J.W., Richardson, D.J. and Russell, D.A. (1997) Optical biosensing of nitrate ions using a sol-gel immobilized nitrate reductase. Analyst, 122, 77–80. Cosnier, S., Innocent, C. and Jouanneau, Y. (1994) Amperometric Detection of Nitrate via a Nitrate Reductase Immobilized and Electrically Wired at the Electrode Surface. Anal. Chem., 66, 3198–3201. Davenport, R.J. and Johnson, D.C. (1973) Determination of nitrate and nitrite by forced-flow liquid chromatography with electrochemical detection. Anal. Chem., 46, 1971–1978. DeBeer, D. and Sweerts, J.-P.R.A. (1989) Measurement of nitrate gradients with an ionselective microelectrode. Anal. Chim. Acta, 219, 351–359. Fritz, J.S., Gjerde, D.T. and Pohlandt, C. (1982) Ion Chromatography, Hüthig Heidelberg. Hussein, W.R. and Guilbault, G.G. (1974) Nitrate and ammonium ion-selective electrodes as sensors. I. In bacterial growth curves for isolation of nitrate and nitrite reductases from Escherichia coli. Anal. Chim. Acta, 72, 381–390. Kiang, C.H., Kuan, S.S. and Guilbault, G.G. (1978) Enzymatic Determination of Nitrate: Electrochemical Detection after Reduction with Nitrate Reductase and Nitrite Reductase. Anal. Chem., 50, 1319–1322. Larsen, L.H., Revsbech, N.P. and Binnerup, S.J. (1996) A Microsensor for Nitrate Based on Immobilized Denitrifying Bacteria. Appl. Environ. Microbiol., 62, 1248–1251. Prest, A.G., Winson, M.K., Hammond, J.R.M. and Stewart, G.S.A.B. (1997) The construction and application of a lux-based nitrate sensor. Lett. Appl. Microbiol., 24, 355–360. Ruzicka, J. and Hansen, E.H. (1974) A new potentiometric gas sensor—The air gap electrode. Anal. Chim. Acta, 69, 129–141.

Schramm, A., Larsen, L.H., Revsbach, N.P., Ramsing, N.B., Amann, R. and Schleifer, K.H. (1996) Structure and Function of a Nitrifying Biofilm as Determined by In Situ Hybridization and the Use of Microelectrodes. Appl. Environ. Microbiol., 62, 4641–47. Strehlitz, B., Gründig, B., Vorlop, K.D., Bartholmes, P., Kotte, H., Stottmeister, U. (1994) Artificial electron-donors for nitrate and nitrite reductases usable as mediators in amperometric biosensors. Fres. J. Anal. Chem., 349, 676–678. Strehlitz, B., Gründig, B., Schumacher, W., Kroneck, P.M.H., Vorlop, K.D. and Kotte, H. (1996) Nitrite Sensor Based on a Highly Sensitive Nitrite Reductase Mediator-Coupled Amperometric Detection. Anal. Chem., 68, 807–816. Willner, I., Riklin, A. and Lapidot, N. (1990) Electron-Transfer Communication between Redox Polymer Matrix and an Immobilized Enzyme: Activity of Nitrate Reductase in a ViologenAcrylamide Copolymer. J. Am. Chem. Soc., 112, 6438–6439. Willner, I., Katz, E. and Lapidot, N. (1992) Bioelectrocatlysed reduction of nitrate utilizing polythiophene bipyrdinium enzyme electrodes. Bioelectrchem. Bioenerg., 29, 29–45.

5. ANALYSIS OF SOIL SILKE KRÖGER and ANTHONY P.F.TURNER Soil analysis is complex and challenging because soil is a natural product, alive with microorganisms and even small animals, constantly changing in consistency and composition. Metabolic processes as well as the influence of rain, sunshine and wind guarantee that soil samples do not only differ from place to place, but also samples from identical collection points change with time. A number of physical and chemical parameters, e.g. particle size, organic matter content, pH and water content, are commonly measured to allow a general characterisation of the soil type, but every soil sample will to some extent remain a unique mixture. When dealing with soil samples, the analyst has to be aware of the difficulties inherent in this matrix. Due to the heterogeneous nature of the matrix already the sampling, as the first step of the whole procedure is of importance and can influence the analytical result (Chap. 5.1.). The need to analyse soil samples for a range of pollutants has grown considerably with increasing environmental awareness by the public. Since conventional analysis such as HPLC or GC-MS requires specialist laboratories, highly trained personal, and is time consuming and therefore expensive, alternative analytical methods are being sought. Biosensors have demonstrated their advantages as analytical tools in the medical sector, for example in decentralised monitoring of blood glucose, and the idea of transferring the concept to soil analysis is very attractive. Thus, an overview will be given on biosensors for certain organic compounds (Chap. 5.2.). 5.1. SAMPLING

KARL CAMMANN and WOLFGANG KLEIBÖHMER 5.1.1. INTRODUCTION

Analytical investigations are performed for various reasons, such as in product quality control and with incoming raw products, with legal proceedings and in forensic medicine or in the field of food control and environmental monitoring. One of the most important steps in all these analytical investigations is sampling. After having decided on the problem to be solved by the onstanding investigation and having elaborated an appropriate analytical procedure every analysis starts with the sampling step. The importance of a correct sampling procedure cannot be emphasized enough as it is the decisive step in the whole analytical process to gain a true and reliable result. If the sample to be analysed is not a representative part of the subject of investigation the result of even the most elaborated and sophisticated analytical procedures is worthless. The reliability of an analytical result could depend on the analytical method applied but it always depends on an expert sampling procedure

carefully carried out. Samples either received inappropriately or characterized insufficiently should not be analysed as the results lead to wrong conclusions. It should be noted that errors are summed up according to the equation

The size of the error arising from incorrect sampling compared with the errors from incorrect sample preparation and incorrect measurements are shown in Figure 5.1. It can easily be seen that—due to low variances in the analytical measuring technique—the main sources for errors result from inappropriate and incorrect sampling and sample preparation. So an emphasis should lie on an improvement of these steps before analytical methods are further developed. It should be mentioned that a possible field blank should be taken into account thus regarding a possible contamination from the environment of the sample by dust and other micro particles not being part of the sample. Especially in trace analytical work it is good practice to take field blanks in containers cleaned in the same way as the sample containers in order to check those for impurities or carried over analytes. Taking a field blank consists of opening the container for the same time in the same environment and under similar conditions as the sample container. If stability enhancing solvents or reagents are used during the sampling procedure the same amount is also filled into the field blank containers. By this any interfering input of non-sample material (e.g. contaminated air with aerosols or blossom dust) can be corrected for. The ideal field blank consists of a sample containing all the matrix attributes of the sample under consideration but without the analyte of interest. In

Figure 5.1. Sources of errors in analysis (according to[6]).

the laboratory the field blank can be transferred into the typical reagent blank necessary in every case of trace analysis by treating it like the samples. Very often the standard deviation of these blanks determines the actual detection limit. 5.1.2. SAMPLING STRATEGIES

Sampling strategies and sampling technologies to receive representative samples are fixed in numerous instructions, orders and rules (Markert, 1994; Mason, 1993; Keith, 1991; Petersen and Calvin; Smyth 1996; VDLUFA, 1991). For environmental analysis some of these shall be elucidated in view of soil sampling. Analogous considerations for a strategic measurement planning can be made in other fields of instrumental analysis (material science, food quality control, forensic chemistry, clinical chemistry etc.). In contrast to air and water the solid soil consists of several components forming a heterogenious mixture and therefore demands special measures when samples are taken. Usually harmful substances are spread inhomogeneously in the soil of polluted areas according to type or concentration. Also the vicinity of polluted areas can be differently contaminated by mobilized pollutants. Spreading of substances is dependent on — the chemical properties of the pollutants; — the physico-chemical environment; — characteristics of the soil. In spite of these inhomogeneities samples must be representative for the entirety in view of the characteristics to be analysed. According to the homogeneity of the entirety various numbers of samples have to be taken on various places of the area to be investigated. At the start of every sampling protocol there is the question of which conclusions should be drawn from the final results. That means that the analysis strategy is directly dependent from the aim of the investigation and the desired information. The definition of the analytical aim of the investigation should be ruled by common sense. Too many analyses are performed with a shortage of a basic analytical knowledge. Of course the complexity of the information wanted and the historical knowledge of the sampling area determine the complexity of sampling and analysis. This will be shown with the following three examples. 5.1.2.1. Determination of mean values

For a determination of mean values various single or random samples are united to a mixed sample, and the desired parameters are then determined. This is of some importance in agriculture if the contents of heavy metals and plant nutrients available in soil (ammonia, nitrate, phosphate etc.) should be determined. These values are important to determine the pollutant endurance capacity of the soil for ground water protection reasons prior to a possible deposition

of sewage slurry on the area in question. In Figure 5.2 a possible distribution of the single samples is depicted.

Figure 5.2. Map of the sampling target. Per hectare a mixture is made from 20 single samples of an overall weight of 700 grams. The direction of sampling should be diagonally to the ploughing direction. To exclude a possible pollution from neighbouring fields or roads an edge of 10–15 m should be left free from sampling. 5.1.2.2. Determination of maximum values

For the determination of maximum values the single samples are not united but analysed separately. These maximum values are of interest in view of a critical exposure by skin contact or inhalation of vapours from a contaminated soil e.g. from a playground. In this case the demands are very high as from the sampling strategy it must be possible to localize and to judge the main source of contamination (e.g. in view of playing children).

5.1.2.3. Determination of distribution patterns

A careful and extensive sampling strategy is necessary if a hypothesis of emmission shall be verified according to the distribution and the concentration profile of the pollutant. An example for this is the examination of soil in industrial areas in view of a possible pollution by cadmium or by fluorine in the case of a near-by aluminium plant which can reach considerable high values especially during course of time. Cadmium can be introduced into the soil either from the atmosphere as part of the dust or from certain cadmium containing solid fertilizers, from sewage slurry deposited on the area or from industrial waste. The aim of these investigations could be judging the relative contribution of each source to the overall contamination. 5.1.3. SAMPLING PROTOCOL

The next step of establishing a sampling protocol is gaining knowledge of all sources and data available to evaluate the history of the area in question. These sources can be: — plans and maps; — photographs and drawings; — aerial photographs; — files and records, chronicals, registers; — official documents, approvals and permissions and; — statements and evidence of contemporary witnesses. Samplings schemes have been developed to assist fixing the various points of sampling in order to assure a correct determination of mean values or maximum values. By using additional information sources the final sampling grid is then established in view of the analytical information desired. Figure 5.3 shows how the choice of sample grid and the informations avaliable determine the distribution of samples. These sample grids must not be regarded as totally fixed but can be adopted to the local situation and to the aim of the investigation. The grids shown in Figure 5.4 are the commonly used one. Furthermore there are statistic-based grids available probably with a higher hit probability but also at higher costs for establishing the sample points. Normally the regular “bottle-rack” grid will be applied which can be complemented by additional sampling points when needed. Polar (Figure 5.5) grids are suited for point sources of contamination e.g. a tank leakage or for recording former industrial plant locations with only a few facilities. Additional sampling lines can be laid into that grid. The radius size is dependent from the estimated size of the contamination source.

5.1.4. SAMPLING DEPTH

The sampling depth is mainly determined by the environmental considerations taking into account the following influences and spreading mechanisms:

Figure 5.3. Selecting and adapting a fixed soil sampling plan according to previous information and to objectives (1). — direct intake (orally) by playing children; — intake by plant roots; — solution by precipitation water and material transport by ground water and surface water; — evaporation into ground near layers and into the air; — wash-out and blow-out into neighbouring sites (Table 5.1). These values are approximate values only, locally a change of sampling depths may be necessary according to the structure of soil layers.

Figure 5.4. Examples for various fixed grid plans Importance of representative sampling and divisions to follow (according to (1)) A: rectangular grid; B: random grid; C: bottle rack grid.

Figure 5.5. Example for a polar grid. Table 5.1. Dependence of sampling depth from environmental considerations. Environmental consideration

Sampling depth

soil surface—air

0–10 cm

soil—surface water (wash-out)

0–10 cm

soil—human uptake (oral incorporation)

0–35 cm

soil—plant

0–100 cm

soil—ground water

0–

5.1.5. COLLECTION OF SAMPLES AND SAMPLE TRANSPORT

After having fixed the sampling points and depths the appropriate sampling equipment must be chosen. Inappropriate devices can lead to large errors with respect to the analytical results especially when the contaminants of interest are present at low concentrations. The actual composition of a soil sample can change during sampling and transport for various reasons. The main points to take into account are the following:

— abrasion of sampling devices (in the ppb-range a short contact can falsify the analysis result); — analyte adsorption with sampling devices and transport containers; — analyte contamination by unsufficiently cleaned tools; — gaseous pollutants with a tendency to pass into the atmosphere; — photolytic and microbial decomposition of the analyte; — oxidation of the analyte by oxygen from air. These influences cannot be excluded in any case but an optimal sampling strategy must cover measures to minimize those influences. Apart from these basic selection criteria the selection of sampling tools is determined by the sampling depth and the characteristics of the soil. For taking samples near the surface scoops can be used, for sampling at shallow depths hand drills or push tubes can be used especially in soft soils for a depth of 20–30 cm. 5.1.6. SAMPLE HOMOGENIZATION, DRYING, PARTITION

Prior to further analytical processing in the laboratory the samples have to be devided into representative parts. Ideally the entire sample material ought to be analysed to gain the optimum information. This is practically impossible and thus, after several dividing operations, a minor part of the entire material is analysed. Figure 5.6 shows this mass decline. The final determination is made with a volume that represent much less than 1 % of the original soil sample only, in the chosen example only 5 mg or 1 µl taken from the soil sample are analysed finally.

Figure 5.6. Relation between total sample mass and the final analysed mass. Most analytical methods demand a multi-step sample preparation. In the case of solid samples mechanical steps such as drying and breaking prior to analytical steps such as digestions, or extractions an analyte containing solution can be prepared ready for analysis. An exception from this procedure is necessary only, if preparation steps lead to non-tolerable changes of the sample state or of the analyte concentration. This is valid e.g. for the determination of volatile compounds in soil. In this case the sample to be examined must be

transferred immediately into a gas-tight container suitable for the analysis steps to follow. A sample mix cannot be obtained in such cases. It is then necessary to dry the sample as on one hand most concentration values are referred to the dry mass and on the other hand for many analytical steps to follow it is essential to have dry material. An extraction of soil samples using unpolar eluents such as cyclohexane, toluene or hexane can only be performed with dry samples as otherwise a complete weting could not be possible. Various physical methods can be applied for drying samples: Drying at elevated temperature — infrared — drying oven — micro wave oven Drying at lower temperature — freeze-dried Drying by chemical water absorption — grinding with Na2SO4 None of these methods produces optimal results, for each analytical method a suitable drying method has to be selected, and the loss of analyte during drying has to be determined. Digestions and extraction methods are the more effective the smaller the sample grain size is. Therefore solid samples have to be broken up prior to analytical procedures. Analytical grinders made of porcelain or agate mortar are used for that purpose. A contamination of the sample by abrasion should be taken into account. 5.1.7. SAMPLING DOCUMENTATION

All data concerning the tools, devices, and containers used during sampling including their materials, concerning the weather conditions including the temperature, and soil-specific data concerning character of soil, colour, sensorial observations should be carefully recorded. 5.1.8. SUMMARY

In critical situations (high damage potential in case of false results) experts from the analytical laboratory should have an input into the sampling procedure since they have the background expertise and are aware of the limitations of the storage conditions and possible affect on the

sample by the sampling process, the used sampling tools, and the storage containers. It should be noted that in trace and speciation analysis extra experience is needed and for each analyte the optimum storage and transport conditions need to be considered individually based on a sound knowledge on the many specific problems possible. For environmental multi-analyte trace analysis it is good practice to take more than one sample in parallel and store them under different optimal conditions according to the specific analytes (pH, exclusion of light or oxygen, refrigeration) For organic trace analytes special care has to be devoted to prevent any microbiological activity from metabolising the analyte. Last but not least, when possible and appropriate, certain primary sample material to allow a second confirmatory analysis. REFERENCES

Keith, L.H. (1991) Environmental sampling and analysis: a practical guide. Lewis, Chelsa. Markert, B. (ed.) (1994) Environmental Sampling for Trace Analysis. Weinheim: VCH Verlagsgesellschaft. Mason, B.J. (1983) Preparation of soil sampling protocol: Techniques and strategy. EPA-600/4– 83–020, U.S. EPA, Las Vegas: Environmental Monitoring Systems Laboratory. Petersen, F.-G. and Calvin, L.-D., Sampling. In Methods of soil analysis, Klute, A. (ed.) Part 1, Madison: American Society of Agronomy Inc, Soil Society of America. Smyth, W.F. (1996) Analytical Chemistry of Complex Matrices. New York: Wiley. VDLUFA (1991) Die Untersuchung von Boden. Methodenbuch VDLUFA, Darmstadt VDLUFA-Verlag.

5.2. BIOSENSORS FOR PESTICIDES AND ORGANIC POLLUTANTS IN SOIL

SILKE KRÖGER and ANTHONY P.F.TURNER 5.2.1. INTRODUCTION

The previous chapter (5.1.) has illustrated the importance of the sampling procedure. Once a representative soil sample is collected, the next step is the extraction of the analyte of interest from the bulk, since most analytical methods rely on the analyte being in the liquid phase. Extraction methods are manifold and have to be carefully selected to suit the particular application. A second extraction procedure can simultaneously achieve the elimination of interferences and, if necessary, pre-concentration. Depending on the solubility of the analyte the extraction solvent can be aqueous, but is more commonly organic or a mixture of both. Figure 5.7 summarises the steps involved in soil analysis and standard methods can be found for example in US EPA publications, the “blue book” (HMSO) or are defined by the AOAC International. Biosensors can be integrated into the analytical procedure either after the initial extraction step or after the purification/pre-concentration, depending on the nature of the device, its robustness and the desired detection range. In this chapter, different methods will be introduced in combination with their analytical applications. The aim of this chapter is to review the potential of biosensors for the analysis of pesticides and organic pollutants in soil, describing existing approaches and highlighting areas which may be interesting for future developments. Even though the above mentioned considerations complicate the analytical procedure when compared to the more convenient matrix water, researchers developing biosensors and analysts wishing

Figure 5.7. Flow scheme for conventional soil analysis and biosensor measurements (the method examples given are not comprehensive).

to employ them should not be deterred. The difficulties are identical for all other methods of analysis, physical as well as chemical, and it is conceivable that for many applications biosensors will prove a valuable alternative or addition to the standard laboratory methods. Some recent reviews highlight the potential of biosensors for environmental analysis (Dennison and Turner, 1995; Gizeli and Lowe, 1996; McDonald, 1994; Rogers, 1995).

5.2.2. DETECTION METHODS

An overview of biochemical principles and transducers has been given in chapters 1 and 2 of this book. Broadly, the multifarious combinations of receptors and transducers can be divided into three main classes: metabolic sensors, inhibition sensors and affinity sensors, depending on the type of interaction between the analyte and the biological component. For the analysis of pesticides and organic pollutants, the later two are more important. 5.2.2.1. Metabolic sensors

Metabolic sensors commonly rely on the availability of an organism or enzyme capable of utilising the analyte as a substrate. This is not impossible for pesticides, but unusual, since pesticides by definition are designed to inhibit rather than be broken down. Of course microorganisms have a unique ability to adapt to metabolise almost any compound found in their environment and various strains have been isolated capable of degrading xenobiotics (see Microbial sensors, Chapter 3.2. etc.). Most biosensors for pesticides and organic pollutants such as PAH and PCB described in the literature, however, rely on the inhibition of a biological component (see also Chapter 3.1.2.) or the development of an immunoreagent for a specific compound or class of compounds (see also Chapter 4.1.2.). These two groups of devices are different in their recognition element, but can be combined with similar physical transducers. 5.2.2.2. Inhibition sensors

Inhibition sensors are generic in their detection mode, since for example an enzyme is usually not specifically inhibited only by one compound but rather by one or more groups of chemicals. The advantage of this non-selective approach is its ability to act as an early warning system. It can be especially useful to detect a broad range of analytes simultaneously. The fact that the chosen biological component acts as an indicator for the potential toxicity of the sample lends this approach its significance. The biological compounds employed range from tissue slices through whole cells to isolated enzymes. 5.2.2.3. Affinity sensors

Affinity sensors are based on a receptor molecule specifically recognising and binding an analyte. The receptor can be for example a plant lectin, a membrane receptor protein or, most commonly, an antibody. Biosensors using the antibody/antigen interaction for their analyte recognition are generally named immunosensors. In recent years immunoassays, particularly enzyme linked immuno-sorbent assays (ELISAs), have gained widespread recognition in environmental analysis (Aga and Thurman, 1997) and proven to be useful tools for pesticide detection (Kaufmann and Clower, 1991; Morgan et al., 1996; Watts and Hegarty, 1995). Their acceptance has increased markedly and the US Environmental Protection Agency (US EPA) has modified their standard methods for the evaluation of solid waste to include immunoassays for the detection of pesticides in soil (Telliard, 1996; US EPA SW846, 1995). Based on this change in attitude and legal frame work, the transfer of immunoassays to immunosensors appears desirable and promising.

Immunosensors are generally chosen for their high specificity. Polyclonal antibodies are usually less specific and yield more generic detection methods, while monoclonal antibodies can be raised and selected for remarkable affinity and specificity. Since most pesticides and organic pollutants are haptens, meaning they are too small to elicit immunoreactions, they have to be linked to a carrier. Great care has to be taken during the antibody production since the haptencarrier design crucially influences sensitivity and selectivity of the envisaged assay. An interesting description of antibody production and immunosensor development for environmental analysis was given by Marco et al. (1995 I.+II.) and antibody production specifically for pesticide analysis was reviewed by Hock et al. (1995). A more recent addition towards the design of the recognition element in immunoassays is the possibility of generating recombinant antibodies. Again the technique has so far mainly been applied in the medical field, but as Kramer and Hock (1995) indicate, it holds a lot of promise for environmental analysis. Even further away from the traditional methods of generating the recognition element is the relatively novel techniques of obtaining antibody mimics by molecular imprinting, rational design or combinatorial chemistry. Despite the fact that applying these techniques strictly means leaving the area of biosensors and entering bio-mimetic or chemosensors, it could be an important tool in the development of environmental sensors, in particular for analytes in soil extracts and will be discussed briefly in section 5.2.7. Depending on the envisaged application, the format for environmental biosensors can range from small, hand-held devices for decentralised measurements to sophisticated, automated flowinjection instrumentation combined with complex data handling systems or sensor arrays for multi-analyte detection. 5.2.3. SAMPLE PREPARATION

For a very large number of analytes that are of interest in soil analysis, biosensor or immunoassay based methods exist. It is therefore interesting to consider their adaptation to the more complex matrices. The main considerations to be made before transferring a method e.g. from water to soil analysis are: • How will the analyte be made accessible, i.e. extracted? • What concentration range is to be expected? • Which other interfering molecules could be present in the extract? These key-issues will be dealt with in the following, setting a frame in which the performance of biosensor devices can be evaluated with regard to the requirements of soil analysis. 5.2.3.1. Extraction

Depending on the nature of the analyte, the extraction often utilises organic solvents rather than water, particularly since a number of commonly used pesticides and many organic pollutants display very low water-solubility. Most biosensors have been developed for the aqueous phase,

leaving the soil analyst with the options of a) extracting with water, b) evaporating the solvent prior to re-suspending the analyte in water, c) diluting the extract until the organic solvent does not interfere with the measurement or d) adapting the sensor to the organic phase. All these approaches have been used and have their specific advantages and drawbacks: (a) Extracting with water is very convenient, avoids the problem of having to deal with an organic solvent during the analysis and also afterwards when disposing of the waste. Interesting in this context is the method of hot water percolation (HWP) (Füleky and Czinkota, 1993), based on the coffee percolator principle, representing a rapid and easy soil extraction method. Soilwater samples can also be prepared using a lysimeter, allowing some control over the extraction process to be exerted. Unfortunately the recovery rates for many quite polar pesticides are very low, but it can be argued that the extent to which the analyte is extracted using this method provides some information about its bioavailability. (b) Evaporating the organic solvent between extraction and measurement gives high recovery rates, allows pre-concentration of the sample and avoids disturbance of the assay by the solvent, but is time consuming and often requires specialist equipment (rotary evaporator). Furthermore the introduction of additional handling steps always increases sources of errors. (c) Diluting the extract, until the overall solvent concentration is low and therefore tolerated by the assay, is relatively easy, but introduces inaccuracies (dilution error) and decreases the overall assay sensitivity. (d) The last possibility—adaptation of biosensor measurements to the organic phase—is a relatively new concept, founded on the discovery that biological materials are capable of maintaining their activity in a range of organic solvents. The area of biosensor measurements in non-aqueous environment will be discussed in a separate section (5.2.6). 5.2.3.2. Concentration range

The concentration of an analyte in soil samples is very hard to predict. Pesticide levels in soil are generally of interest for two different reasons: undesired contamination of land (through e.g. accidents or spray-drift) or because of agricultural use. Knowledge about the concentrations of pesticides in farmland-soil is important for a number of reasons, including maintaining a controlled level of pesticide throughout the growing season (dosage) or checking that a herbicide used previously for the control of weeds is not present anymore at the time of sowing a sensitive crop. With regard to organic pollutants, soil samples are usually analysed when a contamination is suspected. If this contamination dates back to, for example, previous industrial use of the investigated site, the expected concentration will depend on the time span between the last use and the analysis, on the mobility of the analyte in soil and on the nature of the soil, as this influences binding of the analyte and microbial breakdown. Contaminations that occur as a consequence of an accident, i.e. spillages, will have very high concentrations in the immediate vicinity, but lower concentrations in the surroundings might have to be analysed to determine the size of the contaminated site. Generally the relevant detection range is considerably higher when dealing with soil samples than is to be expected in water analysis.

5.2.3.3. Interferences

The third aspect, interferences co-eluted from soil samples, is quite complex. As discussed in the introduction, the composition of soil is very variable, leading to a large number of possible interferents, the exact nature of which is difficult to predict. One group of compounds virtually omnipresent in soil samples, although a greater or lesser extent depending on the soil type, are humic substances, the major fraction of soil organic matter. For a comprehensive understanding of the subject the reader is referred to the corresponding literature such as “Humus chemistry” by F.J.Stevenson (1994) and herein especially the chapter on organic matter reactions involving pesticides in soil. Humic substances have been classified into three fractions according to their water solubility: humin is the fraction not soluble in water, humic acid is insoluble under acidic conditions (pH3 years) and their response is very reproducible (RSD