Recent Advances in Cytometry, Part B, Volume 103, Fifth Edition: Advances in Applications (Methods in Cell Biology)

Methods in Cell Biology VOLUME 103 Recent Advances in Cytometry, Part B: Advances in Applications Series Editors Lesl...

Author: Zbigniew Darzynkiewicz | Elena Holden | William Telford | Donald Wlodkowic

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Methods in Cell Biology VOLUME 103 Recent Advances in Cytometry, Part B: Advances in Applications

Series Editors Leslie Wilson Department of Molecular, Cellular and Developmental Biology University of California Santa Barbara, California

Paul Matsudaira Department of Biological Sciences National University of Singapore Singapore

Methods in Cell Biology VOLUME 103 Recent Advances in Cytometry, Part B: Advances in Applications Edited by

Zbigniew Darzynkiewicz Brander Cancer Research Institute, Department of Pathology, New York Medical College, Valhalla, NY, USA

Elena Holden CompuCyte Corporation, Westwood, MA, USA

Alberto Orfao Cancer Research Center (CSIC/USAL) University of Salamanca Salamanca (Spain)

William Telford National Cancer Institute, Bethesda, MD, USA

Donald Wlodkowic The BioMEMS Research Group Department of Chemistry University of Auckland Auckland, New Zealand

AMSTERDAM BOSTON HEIDELBERG LONDON NEW YORK OXFORD PARIS SAN DIEGO SAN FRANCISCO SINGAPORE SYDNEY TOKYO Academic Press is an imprint of Elsevier

Academic Press is an imprint of Elsevier 225 Wyman Street, Waltham, MA 02451, USA 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA 32, Jamestown Road, London NW1 7BY, UK Linacre House, Jordan Hill, Oxford OX2 8DP, UK Fifth edition 2011 Copyright # 2011 Elsevier Inc. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: [email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made ISBN: 978-0-12-385493-3 ISSN: 0091-679X

For information on all Academic Press publications visit our website at elsevierdirect.com

Printed and bound in USA 11 12 13 14

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CONTRIBUTORS

Numbers in parentheses indicate the pages on which the authors’ contributions begin.

Markus J. Barten (267), Department of Cardiac Surgery, Heart Center, University of Leipzig, Leipzig, Germany Hartmuth B. Bittner (267), Department of Cardiac Surgery, Heart Center, University of Leipzig, Leipzig, Germany Wojtek Blogowski (31), Department of Gastroenterology, Pomeranian Medical University, Szczecin, Poland Robert A. Bray (285), Department of Pathology, Emory University, Atlanta, Georgia, USA Maurizio Carbonari (189), Clinical Medicine Department, University Sapienza, viale dell’Universita, Roma, Italy Angela Catizone (189), Histology and Medical Embryology Department, University Sapienza, via Scarpa, Roma, Italy Alden Chesney (311), Department of Laboratory Medicine and Pathobiology, University of Toronto, Department of Clinical Pathology, Sunnybrook Health Sciences Centre, Toronto, Canada Sohee Cho (149), Department of Life Science, University of Seoul, Seoul, Republic of Korea Sue Chow (205), Ontario Cancer Institute/Princess Margaret Hospital, Toronto, Ontario Canada Marina Cibati (189), Clinical Medicine Department, University Sapienza, viale dell’Universita, Roma, Italy William Cronin (221), Genzyme Genetics (New York Laboratory), New York, New York, USA Zbigniew Darzynkiewicz (55, 115), Brander Cancer Research Institute and Department of Pathology, New York Medical College, Valhalla, New York, USA Maja-Theresa Dieterlen (267), Department of Cardiac Surgery, Heart Center, University of Leipzig, Leipzig, Germany Katja Eberhardt (267), Department of Cardiac Surgery, Heart Center, University of Leipzig, Leipzig, Germany Luis Escribano (333), Instituto de Estudios de Mastocitosis de Castilla La Mancha, Hospital Virgen del Valle, Toledo, Spain Massimo Fiorilli (189), Clinical Medicine Department, University Sapienza, viale dell’Universita, Roma, Italy Howard M. Gebel (285), Department of Pathology, Emory University, Atlanta, Georgia, USA

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Contributors

David Good (311), Department of Laboratory Medicine and Pathobiology, University of Toronto; Department of Clinical Pathology, Sunnybrook Health Sciences Centre, Toronto, Canada Magaret A. Goodell (21), Stem Cell and Regenerative Medicine Center; Center for Cell and Gene Therapy; Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA Wojciech Gorczyca (221), Genzyme Genetics (New York Laboratory), New York, New York, USA H. Dorota Halicka (115), Brander Cancer Research Institute and Department of Pathology, New York Medical College, Valhalla, New York, USA David W. Hedley (205), Ontario Cancer Institute/Princess Margaret Hospital, Toronto, Ontario Canada Eun Seong Hwang (149), Department of Life Science, University of Seoul, Seoul, Republic of Korea Jar-How Lee (285), Research Department, One Lambda, Inc., Canoga Park, California, USA Soo Fern Lee (99), Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore Xiaoyu Li (221), Genzyme Genetics (New York Laboratory), New York, New York, USA Kuanyin K. Lin (21), Stem Cell and Regenerative Medicine Center; Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, Texas, USA Rui Liu (31), Stem Cell Biology Institute, James Graham Brown Cancer Center, University of Louisville, Louisville, Kentucky, USA Wojtek Marlicz (31), Department of Gastroenterology, Pomeranian Medical University, Szczecin, Poland Sophal Mau (221), Genzyme Genetics (New York Laboratory), New York, New York, USA Anja Mittag (1), Department of Pediatric Cardiology, Heart Centre; Translational Centre for Regenerative Medicine (TRM), University of Leipzig, Leipzig, Germany Jos e M. Morgado (333), Instituto de Estudios de Mastocitosis de Castilla La Mancha, Hospital Virgen del Valle, Toledo, Spain Shazib Pervaiz (99), Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore; NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore; Cancer and Stem Cell Biology Program, Duke-NUS Graduate Medical School, Singapore; Singapore-MIT Alliance, Singapore Mariusz Z. Ratajczak (31), Stem Cell Biology Institute, James Graham Brown Cancer Center, University of Louisville, Louisville, Kentucky, USA Marciano Reis (311), Department of Laboratory Medicine and Pathobiology, University of Toronto; Department of Clinical Pathology, Sunnybrook Health Sciences Centre, Toronto, Canada Laura S anchez-Muñoz (333), Instituto de Estudios de Mastocitosis de Castilla La Mancha, Hospital Virgen del Valle, Toledo, Spain

Contributors

xiii Nicla Sette (189), Clinical Medicine Department, University Sapienza, viale dell’Universita, Roma, Italy T. Vincent Shankey (205), Systems Research/Cellular Analysis Business Group, Beckman Coulter, Inc., Miami, Florida, USA Joanna Skommer (55, 115), School of Biological Sciences, University of Auckland, Auckland, New Zealand Teresa Starzynska (31), Department of Gastroenterology, Pomeranian Medical University, Szczecin, Poland Zhong-Yi Sun (221), Genzyme Genetics (New York Laboratory), New York, New York, USA Attila Tarnok (1, 267), Department of Pediatric Cardiology, Heart Centre; Translational Centre for Regenerative Medicine (TRM), University of Leipzig, Leipzig, Germany Christine Tarsitani (285), Research Department, One Lambda, Inc., Canoga Park, California, USA William Telford (55), Experimental Transplantation and Immunology Branch, Center for Cancer Research, NCI, NIH, Bethesda, Maryland, USA Cristina Teodósio (333), Servicio General de Citometrıa, Instituto de Biologıa Molecular y Celular del Cancer, Centro de Investigación del Cancer/IBMCC (CSIC-USAL) and Departamento de Medicina, Universidad de Salamanca, Salamanca, Spain Frank Traganos (115), Brander Cancer Research Institute and Department of Pathology, New York Medical College, Valhalla, New York, USA Sorina Tugulea (221), Genzyme Genetics (New York Laboratory), New York, New York, USA Donald Wlodkowic (55, 115), The BioMEMS Research Group, Department of Chemistry, University of Auckland, Auckland, New Zealand Wojtek Wojakowski (31), Third Division of Cardiology, Medical University of Silesia, Katowice, Poland Hong Zhao (115), Brander Cancer Research Institute and Department of Pathology, New York Medical College, Valhalla, New York, USA Ewa Zuba-Surma (31), Department of Medical Biotechnology, Faculty of Biochemistry, Biophysics and Biotechnology, Jagiellonian University, Krakow, Poland

PREFACE TO FIFTH EDITION

Two hundred sixteen chapters presenting different cytometric methodologies and instrumentation consisting of six volumes (33, 41 & 42, 63 & 64, and 75) were published in the four editions (1990, 1994, 2001, and 2004) of the series of Methods in Cell Biology (MCB) dedicated to cytometry. The chapters presented the most widely used methods of flow- and quantitative image-cytometry, outlining their principles, applications, advantages, alternative approaches, and potential pitfalls in their use. These volumes received wide readership, high citation rates, and were valuable in promoting cytometric techniques across different fields of cell biology. Thirty-nine chapters from these volumes, selected based on high frequency of citations and relevance of methodology, were updated and recently published by Elsevier within the framework of the new series defined ‘‘Reliable Lab Solutions’’ as a special edition of the ‘‘Essential Cytometry Methods.’’ Collectively, these volumes contain the most inclusive assortment of articles on different cytometric methods and the associated instrumentation. The development in instrumentation and new methods as well as novel applications of cytometry continued at an accelerating pace since the last edition. This progress and the success of the earlier CYTOMETRY MCB editions, which become the proverbial ‘‘bible’’ for researchers utilizing these methods in a variety of fields of biology and medicine, prompted us to prepare the fifth edition. The topics of all chapters in the present edition (Volumes A and B) are novel, covering the instrumentation, methods, and applications that were not included in the earlier editions. The present volumes thus complement and not update the earlier editions. There is an abundance of the methodology books presenting particular methods in a form of technical protocols such as ‘‘Current Protocols’’ by Wiley-Liss, ‘‘Practical Approach’’ series by Oxford Press, ‘‘Methods of Molecular Biology’’ series by Humana Press, and Springer or Nature Protocols. The commercially available reagent kits also provide protocols describing the use of these reagents. Because of the proprietary nature of some reagents the latter are often cryptic and do not inform about chemistry of the components or mechanistic principles of the kit. While the protocols provide the guidance to reproduce a particular assay their standard ‘‘cook-book’’ format is restrictive and does not allow one to explain in detail the principles of the methodology, discuss its limitations and possible pitfalls. Likewise the discussion on optimal choice of the assay for a particular task or cell system, or review of the method applications, is limited. Yet such knowledge is of importance for rational use of the methodology and for extraction of maximal relevant information from the experiment. Compared to the protocol-format series the chapters in CYTOMETRY MCB volumes provide more comprehensive and often

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complementary to protocols description of particular methods. The authors were invited to review and discuss the aspects of the methodology that cannot be included in the typical protocols, explain theoretical foundations of the methods, their applicability in experimental laboratory and clinical setting, outline common traps and pitfalls, discuss problems with data interpretation, and compare with alternative assays. While authors of some chapters did include specific protocols, a large number of chapters can be defined as critical reviews of methodology and applications. The 35 chapters presented in CYTOMETRY Fifth Edition cover a wide range of diverse topics. Several chapters describe different approaches to downsizing cytometry instrumentation to the microfluidic and lab-on-a-chip dimension. Application of these miniaturized cytometric platforms in high-throughput analysis, as reported in these chapters, opens new possibilities in drug discovery studies. It also offers the means for real time, dynamic clinical assays that may be customized to individual patients, which could be a significant asset in targeted therapy. The microfluidic cytometry platforms are expected to play a major role in the era of the introduction of micro- and nanodimensional tools to modern biology and medicine, which we currently witness. Imaging cytometry, by providing morphometric analytical capabilities, makes it possible to measure cellular attributes that cannot be assessed by flow cytometry. Different approaches and applications of imaging cytometry are addressed in several other chapters of this edition. Capturing intercellular interactions during the immune response in situ, quantifying, and imaging the blood-circulating tumor cells as well as measuring apoptosis in fine-needle biopsy aspirates are the chapters describing highly relevant applications of imaging cytometry with a potential for use in the clinical setting. Also of interest and of importance is the chapter addressing the assessment of mutagenicity by buccal micronucleus cytome assay. The use of imaging cytometry was also instrumental for dissecting consecutive mitotic stages and states, revealed by highly choreographed molecular and morphological changes, as presented in yet another chapter. Further chapters describe advances in development of flow cytometry instrumentation, new probes, and methods. Among them are reviews on new lasers that are applicable to flow cytometry, applications of quantum dots, progress in development of red fluorescent proteins and biosensors, application of lanthanide elements to eliminate the autofluorescence background, surface-enhanced Raman scattering cytometry (SERC), and recent advances in cell sorting. The novel use of cytometry in analysis of bacteriological samples maintained on hollow fibers is also presented. Reviews of new applications of cytometry in cell biology are presented in several other chapters. Two chapters of this genre are focused on the use of cytometry for identification and isolation of stem cells. Other chapters present the advances in use of cytometry in studies of cell necrobiology, in assessment of oxidative DNA damage, in DNA damage response, and in analysis of cell senescence.

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Still another group of chapters present reviews on preclinical and clinical applications of cytometry. Of particular interest is the chapter addressing the use of cytometry in monitoring the intracellular signaling, which outlines the possibilities of assessing the effectiveness of the protein kinases-targeted therapies. The chapter describing advances in immunophenotyping of myeloid cell populations is very comprehensive, being illustrated by as many as 33 figures. Other chapters of interest for pathologists and clinicians describe the cytometry advances in monitoring transplantation patients, progress in HLA antibody detection, in erythropoiesis and nonclonal red cell disorders, as well as in mast cells disorders. The latter received recognition of the World Health Organization (WHO) as an example of the clinical utility of flow cytometry immunophenotyping in the diagnosis of mastocytosis. Both volumes contain the introductory chapters from the laboratory of Dr. Attila Tarnok, the Editor-in-Chief of the Cytometry A, outlining in more general terms the advances in development in cytometry instrumentation, probes, and methods (Part A), as well as in applications of flow and image-assisted cytometry in different fields of biology and medicine (Part B). In tradition with the earlier CYTOMETRY MCB editions, the chapters were prepared by the colleagues who either developed the described methods, contributed to their modification, or found new applications and have extensive experience in their use. The list of authors, thus, is a continuation of ‘‘Who’s Who’’directory in the field of cytometry. We are thankful to all contributing authors for the time they devoted to share their knowledge and experience. Applications of cytometric methods have had a tremendous impact on research in various fields of cell and molecular biology, immunology, microbiology, and medicine. We hope that these volumes of MCB will be of help to many researchers who need these methods in their investigation, stimulate application of the methodology in new areas, and promote further progress in science. Zbigniew Darzynkiewicz, Elena Holden, Alberto Orfao, William G. Telford and Donald Wlodkowic

Note to the readers: For interpretation of the references to color in the figure legends, please refer to the web version of this book. Also, note that all the color figures will appear in color in online version.

SECTION I

New applications in cell biology

CHAPTER 1

Recent Advances in Cytometry Applications: Preclinical, Clinical, and Cell Biology Anja Mittag*,y and Attila Tarnok*,y *

Department of Pediatric Cardiology, Heart Centre, University of Leipzig, Leipzig, Germany y Translational Centre for Regenerative Medicine (TRM), University of Leipzig, Leipzig, Germany

Abstract I. Preclinical and Clinical Applications II. Cell Biology and Cell Transplantation Therapy Acknowledgment References

Abstract The acceptance of flow cytometry (FCM) in clinical laboratory medicine is a major stepping stone towards development new cell analyses, improvement of accuracy, and finally a new range of diagnostic tests. Applications range from differential blood count determination to the identification of fluorescence-labeled subpopulations of disease-specific cell types in cell suspensions. Even new disease patterns can be identified by FCM. However, FCM is not only applicable for making a diagnosis but also for disease monitoring and routine check-ups. It is often used in oncology-related analyses, such as for leukemia and lymphoma patients. Here, not only cell numbers are relevant but also the degree of antigen expression which can be determined in a standardized way. Next to FCM also image cytometry has entered clinical applications although manual review by pathologists is still standard. In general, the multicolor approach and hence the ability for multiparametric analyses has led FCM to a central cornerstone in cell biology research. This review is intended METHODS IN CELL BIOLOGY, VOL 103 Copyright 2011, Elsevier Inc. All rights reserved.

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0091-679X/10 $35.00 DOI 10.1016/B978-0-12-385493-3.00001-2

Mittag A. et al.

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to present an overview of cytometric applications which have entered clinical practice and led to deeper understanding in biological processes.

I. Preclinical and Clinical Applications The Coulter principle, founded by Wallace H. Coulter, is the reference method for counting and sizing microscopic particles in suspension. It led to automation in blood cell analysis and became a cornerstone of modern laboratory hematology and diagnostic industry. Considering the labor-intensive process of counting and testing blood cells in the past, the acceptance of flow cytometry (FCM) in clinical laboratory medicine was a major stepping stone in the development of analytical capabilities. By entering the field of differential blood count determination (Miller, 1981), automated flow analysis drastically reduced the analysis time in hematology. It is probably the main application of clinical flow analysis to date. However, even today, in 10–50% of the instances, the results of automated cell counters need to be confirmed by a visual screening of blood smears [‘‘manual white blood count (WBC) differential’’] (Roussel et al., 2010). Criteria for deciding whether the result of an automated analyzer needs visual verification or yields sufficient and reliable information are not defined as general rules. There is little uniformity among different laboratories (Barnes et al., 2005). As a reference WBC differential, a cell count of 400 is recommended by The Clinical and Laboratory Standards Institute (CSLI, 2007). The analyzed cell count of automated flow analyzers is far beyond this number but the analytical capabilities of nonfluorescent blood cell analyses based on measurement of scattered and absorbed light are restricted. This leads to confines in the identification of abnormal or diagnostic relevant cells such as activated lymphocytes or nucleated red blood cells. In such cases, the manual analysis of blood smears allowing for a detailed morphological cell assessment is necessary. However, a good portion of microscopic reviews in routine blood analysis is due to misclassification, that is, false positively flagged events in hematology instruments (Barnes et al., 2005). Fluorescence labeling of cells allows for identification of cell types usually determined in the blood count and also subpopulations of lymphocytes, blasts, etc. in a standardized way. Although several working groups have proposed convenient antibody combinations (Bj€ ornsson et al., 2008; Faucher et al., 2007), thus far there is no consensus protocol for a WBC differential using fluorescence-labeled antibodies. An initial investigation on the use of FCM as part of the diagnostic process for an automated validation of samples with suspect cells resulted in the conclusion that it is a robust tool in supplementing the automated hematology analyzer but cannot fully replace the manual blood differential analysis (Roussel et al., 2010). It is a highthroughput tool in which all processes (from sample preparation to gating and data management software) can be automated. Although multicolor FCM is not a substitution for a manual review, it reduces the need for time-consuming blood smear analyses to detect morphological abnormalities of blood cells. Most protocols used

1. Recent Advances in Cytometry Applications: Preclinical, Clinical, and Cell Biology

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for blood assays are not suitable for a full differential blood count as they focus on single-cell type identification, such as immature granulocytes (Fujimoto et al., 2000), lymphocytes (Finn et al., 2004), monocytes (H€ ubl et al., 1996), or dendritic cells (Della Bella et al., 2008; Giannelli et al., 2008). Such protocols can be used to confirm specific diagnoses or disease monitoring. For specific clinical questions, FCM is frequently used for diagnosis, subsequent to histopathological tissue analysis. Friese et al. (2010) came up with the provocative finding that chronic lymphocytic leukemia (CLL) patients who had FCM performed early in their diagnosis experience an overall survival benefit. There may be several reasons for that finding, but nevertheless, FCM is a valuable tool for clinical cell analyses. Even new disease patterns were identified by FCM such as monoclonal B-cell lymphocytosis (MBL). MBL is rather ‘‘accidentally’’detected and diagnosed in the blood by an elevated lymphocyte count of asymptomatic individuals, but its significance is still unknown. It may be associated with an autoimmune abnormality or may be related to aging (immunosenescence) (Nieto et al., 2010). MBL is considered to be the precursor of CLL (Landgren et al., 2009; Marti et al., 2007; Rawstron et al., 2008) or to be associated with non-Hodgkin’s lymphoma (NHL) (Marti et al., 2005). At present, MBL is defined by its distinction from CLL and NHL by FCM characteristics (Marti et al., 2005; Nieto et al., 2010; Shanafelt et al., 2010). Original protocols were based on two or three colors. However, evolution in FCM instrumentation led to more complex and precise identification of MBL but global consensus guidelines have not been yet generally accepted. The diversity in reagents, instruments, and methods of analysis needs to be aligned (Nieto et al., 2010). One important example of successful unbiased leukemia diagnosis approach comes from EuroFlow Consortium. The approach based on eight-color protocols seems to unify the analytical principles for all laboratories involved in leukemia diagnostics according to EuroFlow standard and there is a hope that even more diseases will be diagnosed based on similar approach (Pedreira et al., 2008a). Severe combined immunodeficiency (SCID) is a combination of different congenital immunodeficiency syndromes that have in common a malfunction or reduced number of T-lymphocytes. However, also B- and NK-cells may be affected. The occurrence of SCID is estimated for around 1:100,000 of life births. The most successful treatment method for SCID is bone marrow transplantation (BMT) or hematopoietic stem cell transplantation (HSCT). Transplantation can be performed within the first 3 months of life and offers a 95% survival rate (Buckley et al., 1999). Children with untreated SCID rarely pass the age of two. The earlier the diagnosis of SCID is done, including prenatally, the better, as immune reconstitution must be monitored closely following transplantation. Delayed or incomplete reconstitution can put patients at risk for lethal infections and complications from autoimmunity (Gennery et al., 2010; Puck and SCID Newborn Screening Working Group, 2007). FCM assays performing T- and B-cell subset enumeration are a powerful tool to assess immune reconstitution immediately following transplantation and for longterm follow-up postsurgery to ensure that lymphocyte counts reach and remain at normal levels (Curtis et al., 2010).

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Essential for the use of FCM in clinical analysis is also the standardization of measurements and results. Next to ‘‘simple’’ immunophenotyping and cell counting, the determination of the degree of antigen expression is of practical utility in diagnosis of, for example, leukemia and lymphomas (Atra et al., 1997; D’Arena et al., 2000; Jasper et al., 2010; Ginaldi et al., 1998). It should be clear that terms such as ‘‘dim’’ or ‘‘bright’’ are not useful in this context. Also, the measured mean fluorescence intensity (MFI) value of a cell population provides no reliable information for making a profound diagnosis. In order to avoid changes due to variations in particular antibody batches or instrument performance, data must be standardized by quality control measures such as a comparison with standard beads fluorescence intensity. If the mean fluorescence is set off against the value of standard particles concurrently measured, standardized results are obtained, which allows monitoring over time and can be compared between specimen and laboratories (McLaughlin et al., 2008). One example for such quantitative FCM is the analysis of the CD22 antigen. An abnormally bright CD22 expression is a characteristic of hairy cell leukemia. In contrast, typical for CLL is an abnormally dim expression of CD22 (Jasper et al., 2010). The quantitative analysis of CD22 is considered as very precise if a sufficient number of cells are analyzed, making it an appropriate test for longitudinal studies (Jasper et al., 2010). Also, the absolute quantification of other antigens is clinically relevant; for example, CD38 is useful in the prognosis of CLL patients (Hsi et al., 2003). Likewise, the determination of CD52 expression can be applied to patients with T/NK-cell malignancies being considered for Alemtuzumab therapy (Jiang et al., 2009). FCM enters more and more classical fields of pathology. For example, traditionally, the diagnosis of classical Hodgkin’s lymphoma (CHL) is based on morphological evaluation of hematoxylin and eosin (H&E) stained tissue sections. Fromm et al. demonstrated recently that Hodgkin and Reed–Sternberg cells can be identified and hence CHL diagnosed by an appropriate antibody panel by FCM. With 89% sensitivity and a specificity of 100%, immunophenotyping by FCM could be used for routine diagnosis or supplementing the immunohistochemical analysis (Fromm et al., 2009). Also, the assessment of CD123 may be useful in supporting the diagnosis of CHL (Fromm, 2010). Furthermore, an unequivocal discrimination between low-grade NHL and reactive lymphoid hyperplasias is problematic, but a combined approach of fine needle aspiration cytology and FCM has a high diagnostic value. With this combination, it is possible to distinguish between benign and malignant lymphoid infiltrates (Bangerter et al., 2007). Moreover, it enables discrimination between reactive hyperplasias and neoplastic proliferations and the classification of low-grade B-cell NHL on cytological samples by FCM with high reliability (Schmid et al., 2010). The subclassification of NHL by FCM is avoiding the need for invasive surgical biopsies in many cases (Demurtas et al., 2010). Another focus of FCM in oncology is on the detection of circulating cells in the peripheral blood with the characteristics of tumor cells, known as circulating tumor cells (CTC). They are found not only in patients with metastatic disease but also in


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patients with apparently localized tumors (Ring et al., 2004). Hu et al. (2010) presented a multiparameter FCM analysis for effectively detecting CTC in breast cancer as a valuable tool for prognosis assessment among breast cancer patients. Their results demonstrated that the overall survival was closely correlated both with CTC levels and with metastasis and age, but was independent of clinical pathology and tumor size. Hence, monitoring of CTC values in the clinical course of metastatic breast cancer patients is believed to be of great importance and becomes a valuable tool in clinic (Li, 2010). Moreover, this approach is proposed as a possibly better prognostic tool than functional imaging (De Giorgi et al., 2009; Hayes et al., 2006; Hu et al., 2010) provided that a standardized approach for CTC level assessment is developed (De Mattos-Arruda et al., 2010). The determination of the level of circulating endothelial lineage cells (ELC) might also be of clinical relevance. Their presence in blood could serve as a biomarker of tumor neovascularization in patients with pancreatic ductal adenocarcinoma (PDCA) as increasing ELC levels after PDAC resection seem to be associated with cancer recurrence (Sabbaghian et al., 2010). Another prognostic tool and potential therapeutic target may be expression of CD157 as it plays a pivotal role in the control of ovarian cancer cell migration (Ortolan et al., 2010). The quantification of vascular circulating endothelial cells (CEC) in the peripheral blood can be used for assessing endothelial damage (Lampka et al., 2010). CECs share several surface antigens with other stem and progenitor cells but have a unique pattern of them (Adams et al., 2009). CEC counts correlate with disease activity across a broad variety of diseases (Erdbruegger et al., 2006). Lampka et al. (2010) evaluated the flow cytometric assessment of CEC in peripheral blood by CD31, CD146, and CD45 in patients with coronary artery disease. They found a significant higher CEC count in patients with acute myocardial infarction compared to healthy controls, whereas CEC numbers in stable angina patients remained inconspicuous. Estes et al. (2010) further refined the assay and developed a polychromatic panel for the detection and discrimination of circulating angiogenic and nonangiogenic stem and progenitor cells. These methods may in future be used to improve diagnosis of an acute coronary syndrome. In majority of flow cytometric tests, analysis of cell populations is based on identification of markers or marker combinations in or on the surface of cells. In contrast to that, diagnosis of paroxysmal nocturnal hemoglobinuria (PNH) is based on the demonstration of antigen absence. Common markers are CD55 and CD59. However, several studies discuss that PNH testing by FCM has significant problems with regard to false-positive and false-negative results (Rachidi et al., 2010; Richards et al., 2008). As for almost all flow cytometric assays for diagnostic purposes, also in this case there is an urgent need for standardized protocols (Richards et al., 2008). While certain authors state that the use of CD59 and/or CD55 combined with careful gating analysis is reliable and reproducible for PNH diagnosis (Kim et al., 2010; Parker et al., 2005; Tembhare et al., 2010) and may even be useful in differentiating PNH from patients with aplastic anemia (Kim et al., 2010), other markers have also been proposed for a reliable diagnosis. Furthermore,

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the assessment of the percentage of abnormal cells based on erythrocyte analysis is affected by blood transfusion as the latter leads to an increase in proportion of cells with normal CD55 and CD59 expression. For an accurate diagnosis, at least two different monoclonal antibodies, directed against two different glycosylphosphatidylinositol (GPI)-anchored proteins, on at least two different cell lineages should be used to diagnose a patient with PNH (Rachidi et al., 2010). Hern andez-Campo et al. (2008) demonstrated that the best combination of markers for the diagnostic screening of PNH included evaluation of CD14 on monocytes and CD16 on neutrophils. Further analysis of CD55 and CD59 expression, however, may contain additional clinically useful information. The findings of Richards et al. (2008) suggest that the use of CD16 and CD66b provides more accurate results compared to CD55 and CD59, when testing granulocytes for GPI deficiency. Another FCM technique for PNH diagnosis uses a fluorescein-labeled proaerolysin variant (FLAER) as a ligand. As it directly binds GPI-anchor, it gives a more accurate assessment of this molecule’s deficit than does CD55 or CD59 on most cell lineages (Brodsky et al., 2000), with the exception of red cells and platelets (Brodsky, 2009). In conclusion, the multiparametric capabilities of FCM should be exploited in using several antibodies for a simultaneous analysis of different cell lines and a reliable PNH diagnosis. Since low volumes of blood are adequate for FCM analysis, this instrumentation is of practical utility for neonatal diagnosis (Michelson et al., 2000). In fact, FCM can be applied even for prenatal diagnosis as well. The sensitivity of detecting fetal cells within the maternal circulation has been improved. However, there are still several challenges that need to be overcome before application in prenatal diagnosis, mainly the lack of specific fetal cell markers and the paucity of fetal cell numbers, that range from 1 in 104 to 1 in 106 in the maternal blood (Curtis et al., 2010). However, when the fetal cells are enriched, which can be accomplished by magnetic or fluorescence activated cell sorting, FCM offers a promising alternative to the current methods of amniocentesis or chorionic villus sampling. Compared to FCM, the latter approaches for prenatal diagnosis are invasive, carry a risk of fetal injury, may result in pregnancy loss, and are expensive (Curtis et al., 2010). Curtis et al. (2010) provide an excellent review of FCM methods for prenatal and neonatal diagnoses of common immunological and hematological abnormalities. A clinical application where FCM has always been playing a crucial role is HIV diagnosis, monitoring, and research. It can be said that the history of these two fields is intimately linked (Chattopadhyay and Roederer, 2010). Determination of CD4+ T-cell count by FCM has been designated as the gold standard by the WHO (World Health Organization, 2007). The CD4+ T-cell counting technology has gradually evolved from a pure cellular research assay technique into a routine clinical diagnostic test (Arewa, 2010). This test has undergone several improvements and its evolution is still going on. Paradoxically, the last to benefit from the impact of the technology (or its technological improvements) are the ones who need it most but cannot afford it. That is why there are two major branches of developments in HIV diagnosis/monitoring by FCM. On the one side, there is the cellular research in order to understand mechanisms of infection and its influence


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on the immune system and the sophisticated (truly multiparametric) analysis in the Western World (Chattopadhyay and Roederer, 2010; Perfetto et al., 2004). But there is another side, namely, resource-poor countries with their inability to provide adequate HIV diagnosis and treatment. There are many attempts to simplify the technology to absolute necessary, reduce the costs with it, and make it easier to operate. Improvements in this directions are, for example, acoustic micromanipulating techniques to focus particles in a flow stream instead of the commonly used hydrodynamic focusing (Zaragosa, 2006), flow rate calibration (Nantakomol et al., 2010), or cost reduction in preparation with a no-lyse, no-wash technique (Cassens et al., 2004; Greve et al., 2003) or instrumentation in general (Pattanapanyasat et al., 2005; Zijenah et al., 2006). However, many approaches focus on image analysis for HIV diagnosis (Bae et al., 2009; Li et al., 2007a, 2007b, 2010; Moon et al., 2009; Rodriguez et al., 2005; Ymeti et al., 2007). Regardless whether CD4+ T-cell counting is based on imaging or flow analysis, there is still a great need for affordable and reliable HIV diagnostics. Malaria and tuberculosis have to be kept in mind, too. Also, for these patients essential healthcare is urgently needed (visit www.partec.com to see the great work Dr. Wolfgang G€ ohde is doing in this direction). It is not that only whole cells are relevant for diagnostic purposes in the peripheral blood. There are plenty of microparticles, that is, membranous vesicles, some of them apoptotic bodies, in the plasma of normal individuals, which express the surface markers from the parental cells and are therefore interesting subject for FCM analyses. By virtue of multiparametric and quantitative analyses, FCM offers a suitable method for clinical investigations of the microparticles. Orozco and Lewis (2010) review FCM analysis and applications of microparticles with the focus on fetal-derived microparticles found in maternal plasma. Elevated levels of microparticles, mainly derived from circulating blood cells, are associated with various diseases such as thrombosis, congestive heart failure, or breast cancer (Orozco and Lewis, 2010). The authors try to draw a roadmap for the assessment of microparticles as biomarkers for a variety of conditions, including an appeal for standardization of preanalytical and analytical procedures. Secretion of microparticles is one of the many ways cells can transfer information between one another. A related alternative method is the relatively recently observed trogocytosis where membrane fragments are transferred from one cell to another in direct cell–cell interaction. This may happen, for example, during antigen presentation (Daubeuf et al., 2006) and is considered responsible for immune modulation. Trogocytosis may be clinically relevant and was found to be related to HIV spread (Aucher et al., 2010) or transfer of antitumor activity from T- to NK-cells (Domaica et al., 2010), among others. Several FCM-based methods have been developed to detect specific trogocytosis (Daubeuf et al., 2009) so that these assays may become diagnostically relevant in future. Besides the hematology laboratories, diagnostic microbiology can also benefit from flow cytometric analyses. Pieretti et al. (2010) demonstrated that the determination of bacteria and leukocyte counts by a urine cytometer is acceptable for routine use and can considerably reduce the number of bacterial cultures needed.

10

Mittag A. et al.

Still, there are some limitations to using FCM as a diagnostic tool. FCM assays often require expensive reagents that may not be routinely available in a clinical setting and some analyses require highly skilled personnel to perform (Notarangelo and Sorensen, 2008). The ongoing development of new easier to operate instrument platforms capable of measuring multiple parameters, along with the advances in reagents and dye conjugations, will help this technology continue to make transition from the research setting to a key diagnostic tool in clinical medicine (Curtis et al., 2010). To make a long story short, FCM analyses have entered the field of clinical diagnosis in many different disease patterns. For example, FCM has proven to be useful in celiac disease by assessing diagnostic, prognostic, and disease activity biomarkers (Leon, 2010). Furthermore, it is known that basophils contribute to anaphylaxis and allergies. Hence, they are a suitable target for disease monitoring. Gernez et al. (2010) demonstrated the usefulness of determining the CD203c level on basophils for baseline diagnosis and therapeutic monitoring in subjects with nut allergy. Detection of inflammation is usually not problematic. However, in case of concomitant diseases such as rheumatoid arthritis (RA), it may be difficult to diagnose local musculoskeletal infections. Specific biomarkers would be of great use in that case. Nishino et al. (2010) reported that CD64 can provide a useful marker to discriminate local infection from RA-related inflammation. In general, identification of biomarkers specific to one disease pattern would improve diagnosis of many diseases. Due to its easy operability, FCM would be applicable for assessing diagnostically relevant levels of biomarkers, for example, activation markers on certain blood cell types. It would allow both diagnosis and monitoring disease progression and therapeutic effects. Likewise, specific biomarkers in tissue samples, for example, biopsy material, can also be identified by image cytometry. Image analysis is a well-known technique in clinical analysis. Optical inspection of blood smears or chromatically (e.g., H&E) stained tissue sections by a pathologist is the simplest form of image analysis and has been carried out for ages. Routine histomorphometric analysis and subjective scoring methods have traditionally been used to define, either in a quantitative or in a qualitative manner, morphologic endpoints in chromogenic immunohistochemistry (IHC) and routine histochemically stained sections. However, survey by pathologists of cellular samples of different origin, tissue sections, biopsies, swabs, etc., is not cytometry by definition. In most cases, they cannot be described as objective and quantitative analyses. There is a substantial interobserver variance in assessment of those samples that apparently cannot be diminished by training (Furness et al., 2003; LiVolsi, 2003). An objective quantitation would be preferable. This can be realized by image cytometry. Image cytometry is capable of extracting a multitude of parameters from cells. Cytometric slide-based assays are widely used in clinical and preclinical research but only rarely for clinical diagnosis (reviewed by Gerstner et al. (2009). Cytometric imaging techniques are available for analysis of solid tissue for many decades, but manual and hence subjective scoring of samples is still a common practice. However, automated high-content quantitative methods such as laser scanning cytometry


11

(LSC) offer more efficient unbiased data collection (Peterson et al., 2008). Application of fine-needle biopsies and swabs (Gerstner et al., 2003, 2004, 2005, 2006; Schwock et al., 2007) and of a variety of tissue specimens (Haider et al., 2003; Kayser et al., 2006; Mosch et al., 2007; Persohn et al., 2007) has been reported. Image cytometry provides insight into biological systems and their complex interactions such as the immune system (Harnett, 2007). Multiplexed analyses can thereby be performed with even very small samples such as FNAB or swabs. Concurrent multicolor analyses are possible or data can be obtained by sequential analyses of the same cells. Sequential analyses may be useful in drug screening assays. Holme et al. (2007) demonstrated that several classical parameters associated with apoptosis can be measured on the same cells in sequential analysis such as plasma membrane permeability changes, DNA integrity and hypodiploidy, chromatin condensation, loss of mitochondrial membrane potential, and cell cycle profile. Moreover, morphological features that cannot be assessed by FCM can be determined by image cytometry. For example, the efficacy of a drug to separate cell clusters into single cells might be an indication of inhibition of tumor colony formation and can be measured by LSC. In combination with the cell cycle profile of the treated cells, for example, the determination of G1 cell cycle arrest, one can conclude about the drug’s potential effectiveness (Holme et al., 2007). Main applications of image cytometry are DNA content and cell cycle analyses. DNA ploidy can be determined by quantitative fluorescence analysis of cells stained with DNA dyes. This proved to be useful in distinguishing malignant from benign lesions in breast cancer (Zhang et al., 2006). In addition, ploidy analysis was combined with determination of DNA copy number aberrations that was closely related to DNA aneuploidy in lung adenocarcinomas (Hayashi et al., 2005) or colorectal carcinoma (Liu et al., 2004). An increased hyperploidy in neurons in patients with Alzheimer’s disease compared to normal brain was found by LSC. Furthermore, the majority of those tetraploid neurons were found to express cyclin B1 indicating a reactivation of their cell cycle (Mosch et al., 2007).

II. Cell Biology and Cell Transplantation Therapy Both cell senescence and cell death are critical endpoint measurements for diagnosis, therapy monitoring, or cell-based drug discovery. Regarding cell senescence, it was shown that successful aging or longevity is correlated with reduced senescence of circulating NK-cells (Kaszubowska et al., 2008) and could be predictive for life expectancy. Furthermore, it can be useful in screening for tumor cells (Gancarcıkov a et al., 2010). Various FCM methods exist to determine cellular senescence. Senescence-associated beta-galactosidase (SA-beta-gal) activity is a widely used marker. SA-beta-gal activity is routinely detected cytochemically, manually discriminating negative from positive cells. This method is time consuming, subjective, and therefore prone to operator error. The FCM assays for SA-beta-gal show that under nonstressed conditions, fibroblasts from very old

12

Mittag A. et al.

subjects show higher SA-beta-gal activity than fibroblasts from young subjects as found by FCM. Under stress-induced conditions, a significantly higher SA-beta-gal activity in fibroblasts from very old compared to young subjects was reported (Noppe et al., 2009). An alternative assay is the determination of telomere length and telomerase activity by FCM (Carbonari et al., 2010) by in situ hybridization. Telomere length in NK-cells seems to be predictive for live expectancy in the elderly (2 years). The aging-dependent decrease of the pool and function of VSELs in BM may explain the decline of the regeneration potential during aging. This hypothesis has been further confirmed by looking for differences in the content of these cells among BM mononuclear cells (BMMNCs) in long- and short-lived mouse strains. The concentration of VSELs was much higher in the BM of long-lived (e.g., C57B6) as compared to short-lived (DBA/2J) mice (Kucia et al., 2006a).

1. Developmental Origin of VSELs An adult organism develops from the most primitive SC called a zygote, which is an oocyte fertilized by a sperm cell. This totipotent zygote, the ‘‘mother of all stem cells’’ in the developing body, first gives rise to morula that consists of PSCs and, subsequently, at blastocyst level a population of PSCs that is maintained in inner cell mass; the blastocyst will give rise to the epiblast, a part of the developing embryo, which is the origin of SCs committed to all the three germ layers (meso-, ecto-, and endoderm) (Tam and Loebel, 2007). Thus, the PSCs that form epiblast could be considered the origin for the TCSCs for all the organs and tissues in the developing embryo proper. PSCs in the epiblast undergo a sequel of specification events, first into multipotent and subsequently into versatile TCSCs, which play a role in the formation and rejuvenation of various organs (Tam and Loebel, 2007; Tam et al., 2007). The most important questions emerge of whether some of these primitive epiblast-forming PSCs can ‘‘escape’’ specification into more differentiated populations of SCs and retain their pluripotential character, thus surviving among differentiated daughter TCSCs. Conversely, would all of them undergo tissue-/organ-specific differentiation and then ‘‘disappear’’ after embryogenesis, not be found in the adult body. We envision that VSELs are epiblast-derived PSCs deposited early during embryonic development in developing organs as a potential reserve pool of precursors for TCSCs and thus this population has an important role in tissue rejuvenation and regeneration. We also hypothesize that VSELs originate or are closely related to a population of proximal epiblast migratory EpiSCs that approximately at embryonic day (E)7.25 in mice, become specified to PGCs, and egress from the epiblast into extra-embryonic tissues (extra-embryonic mesoderm) (Hayashi et al., 2007). These cells subsequently make a turn and through the primitive streak return to the embryo proper and migrate to genital ridges, where they ultimately give rise to precursors of sperm or oocytes. Accumulating evidence also indicates that PGCs could somehow be related to HSCs, another population of highly migratory SCs (Kritzenberger and Wrobel, 2004; Ohtaka et al., 1999; Rich, 1995). To support this notion, the first primitive HSCs appear in the extra-embryonic tissues in yolk sac blood islands at a time when proximal epiblast-specified PGCs enter the extra-embryonic mesoderm (Mikkola

3. Identification of Very Small Embryonic/Epiblast-Like Stem Cells (VSELs)/Tissue Injuries

37

and Orkin, 2006). Furthermore, the appearance of definitive HSCs in the aortagonad-mesonephros (AGM) region in the embryo proper corresponds in time with migration of PGCs to the genital ridges through the AGM. To support this hypothesis further PGCs isolated from murine embryos were described as being able to grow HSC colonies and robust hematopoietic differentiation was observed in some classical germ tumors (Ohtaka et al., 1999; Rich, 1995; Saito et al., 1998). Thus, all this collective evidence suggests developmental overlap between PGCs and HSCs. Our data indicate that VSELs share several characteristics with both PGCs and HSCs. To support this notion our recent molecular analysis data indicate that in fact VSELs share several markers characteristic for epiblast/germ line (Shin et al., 2010b). Furthermore, VSELs follow developmental route of HSCs colonizing together with HSCs first FL and subsequently BM (Zuba-Surma et al., 2009b). Furthermore, in appropriate culture conditions they could also be differentiated toward hematopoietic lineage (Zuba-Surma et al., 2009a). In the future, it will be important to evaluate the potential presence of VSELs in yolk sac blood islands and to determine whether VSELs are detectable in Ncx1/ embryos (Zuba-Surma et al., 2009c) that do not initiate a heart beat and thus lack definitive HSCs in embryonic tissues (Lux et al., 2008). Thus PGCs, HSCs, and VSELs form all together a unique highly migratory population of interrelated SCs that could be envisioned to be a kind of ‘‘fourth highly migratory germ layer.’’ Due to this unique developmental origin, VSELs not only show characteristic epigenetic reprogramming and gene expression in stemness-, germ line-, and imprinted-genes that maintain their pluripotency but also prevent their unleashed proliferation and teratoma formation (Shin et al., 2010a, 2010b).

2. VSELs and Their Unique Molecular Characteristics We employed several molecular strategies to evaluate molecular signature of VSELs. Highly purified Sca-1+LinCD45 VSELs from murine BM or FL were evaluated for expression of (i) ESCs, (ii) epiblast/germ line markers, and (iii) expression of developmentally crucial imprinted genes. We found that at mRNA and protein level VSELs express transcription factor Oct4 that is characteristic for ESCs (Shin et al., 2009, 2010b). However, recently some doubts were raised if cells isolated from adult tissues may express these embryonic genes and it has been postulated that positive PCR data showing Oct4 expression may be due to amplification of Oct4 pseudogenes (Lengner et al., 2008; Liedtke et al., 2007). Thus, to prove true expression of the Oct4 gene in VSELs we investigated the epigenetic status of Oct4 promoter in these cells. The Sca-1+LinCD45 VSELs were double purified and we examined the DNA methylation status of the Oct4 promoter in these cells by employing bisulfite sequencing. We noticed that the Oct4 promoter in VSELs, similar to cells isolated from ESCs-derived EBs, is hypomethylated (28 and 13.2%, respectively) (Shin et al., 2009). Next, to provide additional direct evidence that the Oct4 promoter in VSELs is in an active/open state, we

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Mariusz Z. Ratajczak et al.

performed the chromatin-immunoprecipitation (ChIP) assay to evaluate its association with acetylated-histone3 (H3Ac) and dimethylated-lysine-9 of histone-3 (H3K9me2), the molecular features for open- and closed-type chromatin, respectively. By employing Carrier-ChIP assay using human hematopoietic cell-line THP-1 as carrier, we found that Oct4 promoter chromatin is associated with H3Ac and its association with H3K9me2 is relatively very low (Shin et al., 2009). Since VSELs also express Nanog, we evaluated the epigenetic status of the Nanog promoter in these cells as well. We found that the Nanog promoter was methylated (50%); however, quantitative ChIP data confirmed that the H3Ac/H3K9me2 ratio supports the active status of the Nanog promoter in these cells (Shin et al., 2009). Based on these results, VSELs truly express Oct4 and Nanog. Of note we also reported that VSELs also express several other markers of PSCs such as SSEA-1 antigen as well as Sox2 and Klf4 transcription factors. While the expression levels of transcripts of Oct4 and Nanog in VSELs was around 50 and 20%, respectively, compared to ESC-D3 cells, VSELs express a similar level of Sox2 transcript and 3.5 times more Klf4 as compared to ESC-D3 cells (Shin et al., 2010a, 2010b). Next, since we hypothesized that VSELs could be epiblast-derived precursors of TCSCs, we focused on expression, in adult BM-derived VSELs, of genes that are characteristic for EpiSCs (Gbx2, Fgf5, and Nodal) and ESCs from inner cell mass of blastocyst (Rex1/Zfp42). It is known that Gbx2, Fgf5, and Nodal are upregulated in EpiSCs, but expressed at lower levels in ESCs isolated from the inner cell mass of blastocysts (Hayashi et al., 2008). In contrast, the level of Rex1/Zfp42 transcripts is highly expressed in inner cell mass cells. We found that VSELs highly express Gbx2, Fgf5, and Nodal, but express less Rex1/Zfp42 transcript as compared to ESC-D3s what suggests that VSELs are more differentiated than ICM-derived ESCs and share several markers with more differentiated EpiSCs (Shin et al., 2010a, 2010b). Next since we hypothesize that VSELs could be developmentally related to epiblast-derived PGCs we evaluated the expression of genes involved in the germ line specification of the epiblast (e.g., Stella, Prdm14, Fragilis, Blimp1, Nanos3, and Dnd1) (Hayashi et al., 2007). By employing RQ-PCR, we noticed that VSELs highly expressed all the genes involved in germ line specification from the epiblast. Subsequently, we confirmed the expression of Stella, Blimp1, and Mvh in purified VSELs at the protein level by immunostaining (Shin et al., 2010a, 2010b). Furthermore, our ChIP results show that the Stella promoter in VSELs displays transcriptionally active histone modifications [H3Ac and trimethylated-lysine-4 of histone3 (H3K4me3)] and was less enriched for transcriptionally repressive histone markers [H3K9me2 and trimethylated-lysine-27 of histone3 (H3K27me3)] (Shin et al., 2010a, 2010b). Thus, collectively, our results demonstrate that VSELs express specific genes and display a Stella promoter chromatin structure that is characteristic for germ line specification. VSELs also highly express Dppa2, Dppa4, and Mvh, which characterize late migratory PGCs. However, they do not express Sycp3, Dazl, and LINE1 genes that are highly expressed in postmigratory PGCs (Shin et al., 2010a, 2010b). In totality, thus, our results support a concept that VSELs deposited


39

into murine BM show some similarities in gene expression and epigenetic signatures to epiblast-derived migratory PGCs (E10.5–E11.5).

3. Epigenetic Changes of Imprinted Genes that Regulate VSELs Pluripotency The rapidly developing field of regenerative medicine is searching for safe and therapeutically efficient sources of PSCs. By definition, PSCs should (i) give rise to cells from all three germ layers; (ii) complete blastocyst development; and (iii) form teratomas after inoculation into experimental animals (Ratajczak et al., 2007a). Unfortunately, in contrast to immortalized embryonic ESC lines or inducible PSCs (iPSCs), these last two criteria have not been obtained thus far with any potential PSC candidates isolated from adult tissues. There are two potential explanations for this discrepancy. The first is that PSCs isolated from adult tissues are not fully pluripotent; the second is that there are some physiological mechanisms involved in keeping these cells quiescent in adult tissues to preclude their unleashed proliferation and risk of teratoma formation. We postulated that VSELs similarly as PGCs may modify methylation of imprinted genes that prevents them from unleashed proliferation and may explain their quiescent status in adult tissues. We noticed that Oct4+ VSELs do not proliferate in vitro if cultured alone and that the quiescence of these cells is epigenetically regulated by DNA methylation of genomic imprinting, which is an epigenetic program that ensures the parent-of-specific monoallelic transcription of imprinted genes (Shin et al., 2009). It is well known that the imprinted genes play a crucial role in embryogenesis, fetal growth, totipotential status of the zygote, and pluripotency of developmentally early stem cells (Reik and Walter, 2001). The expression of imprinted genes is regulated by DNA methylation on differential methylated regions (DMRs), which are CpG-rich cis-elements in their loci. We noticed that VSELs freshly isolated from murine BM erase the paternally methylated imprints (e.g., Igf2H19, Rasgrf1 loci); however, at the same time they hypermethylate the maternally methylated ones [e.g., Igf2 receptor (Igf2R), Kcnq1-p57KIP2, Peg1 loci]. Because paternally expressed imprinted genes (Igf2, Rasgrf1) enhance the embryo growth and maternally expressed genes (H19, p57KIP2, Igf2R) inhibit cell proliferation (Reik and Walter, 2001), the unique genomic imprinting pattern observed on VSELs demonstrates growth-repressive imprints in these cells. VSELs highly express growth-repressive genes (H19, p57KIP2, Igf2R) and downregulate growth-promoting genes (Igf2, Rasgrf1), which explains the quiescent status of VSELs (Shin et al., 2009). Importantly, the quiescent pattern of genomic imprinting was progressively recovered during the formation of VSEL-DSs, in which stem cells proliferate and differentiate. These results suggest that epigenetic reprogramming of genomic imprinting should maintain the quiescence of the most primitive pluripotent adult stem cells (e.g., Oct4+ VSELs) deposited in the adult body and protect them from premature aging and tumor formation. Therefore, it will be important to investigate whether this genomic imprinting pattern differs between VSELs isolated from young versus old mice and whether these potential epigenetic


40

changes could contribute to the previously mentioned decrease in the pool and function of VSELs during aging.

B. Mesenchymal Stem Cells (MSCs) Mesenchymal stem cells are a population of BM-derived adherent bone-/cartilageforming progenitor cells. It is known that BM-adherent cells grow colonies of fibroblastic-like cells, which have a high replating potential (colony-forming units of fibroblasts; CFU-F) (Pochampally et al., 2004; Prockop, 1997). It is now widely accepted that MSC cells contribute to the regeneration of mesenchymal tissues (e.g., bone, cartilage, muscle, ligament, tendon, adipose, and stroma). Because various inconsistencies have come to light in the field of MSC research, in particular if they truly represent a population of stem cells, the International Society for Cellular Therapy recently recommended avoiding the name of MSCs and changing it to multipotent mesenchymal stromal cells instead (Dominici et al., 2006). Of note recently it has been demonstrated that VSELs may give rise to population of MSCs (Taichman et al., 2010).

C. Endothelial Progenitor Cells (EPCs) It is postulated that the BM is endowed with neoangiogenetic activity and EPC, which is a rare and very primitive founder population of endothelial cells, may be released during stressed situations and circulate in PB (Asahara et al., 1999; Massa et al., 2005; Rafii and Lyden, 2003; Shintani et al., 2001). Furthermore, BM was also identified as a source of more differentiated circulating endothelial cells (CEC). BM-derived EPC and CEC subsequently circulate in PB at very low levels (0.0001 and 0.01%, respectively) and may play a role in the repair of damaged endothelium and contribute to postnatal neoangiogenesis (Asahara et al., 1999). While EPC are probably progeny of PSC or perhaps direct descendants of hemangioblasts, the more differentiated CEC originate in the myeloid compartment from a common myeloid progenitor (CMP). The level of contribution of BM-derived cells to organ/tissue vascularization, however, still requires further study.

III. Materials In protocols described below in this chapter, we will focus on identification and enumeration of VSELs. Human PB-derived samples are collected from the patients into tubes with anticoagulant. To avoid the loss of small cells (e.g., VSELs) during separation of cells on Ficoll-Paque gradient we remove red blood cells by employing lysing buffer. Total nucleated cells are subsequently stained by using antibodies listed in Table II. For isolation of VSELs, we may use size-predefined beads, to define a sorting region containing small objects (2–10 mm), as indicated on the dotplot presenting FSC and SSC parameters of analyzed objects (Fig. 1, region P1). This

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Table II Antibodies employed in staining for identification and sorting of human PB-derived HSCs and VSELs by flow cytometry Antibody

Clone

Fluorochrome

Vendor

Anti-CD2 Anti-CD3 Anti-CD14 Anti-CD16 Anti-CD19 Anti-CD24 Anti-CD56 Anti-CD66b Anti-CD235a Anti-CD45 Anti-AC133 Anti-CD34 ANTI-CD184

RPA-2.10 UCHT1 M5E2 3G8 HIB19 ML5 NCAM16.2 G10F5 GA-R2 HI30 AC133 581/CD34 12G5

FITC FITC FITC FITC FITC FITC FITC FITC FITC PE-Cy7 APC APC APC

BD Biosciences BD Biosciences BD Biosciences BD Biosciences BD Biosciences BD Biosciences BD Biosciences BD Biosciences BD Biosciences BD Biosciences Miltenyi Biotec BD Biosciences BD Biosciences

FITC FITC FITC PE-Cy7 APC APC APC

BD Biosciences BD Biosciences BD Biosciences BD Biosciences Miltenyi Biotec BD Biosciences BD Biosciences

Mouse IgG1, k Mouse IgG2a, k Mouse IgG2b, k Mouse IgG1, k Mouse IgG1 Mouse IgG1, k Mouse IgG2a, k

Isotype controls MOPC-21 G155-178 27–35 MOPC-21 IS5-21F5 MOPC-21 G155-178

region not only contains mostly cellular debris but also includes rare nuclear cellular objects (Zuba-Surma et al., 2008a, 2010).

A. Preparation of Peripheral Blood (PB) for Analysis 1. Laboratory tubes containing anticoagulant or medium supplemented with anticoagulant. 2. Lysing buffer (BD PharmaLyse; BD Biosciences, cat. No. 555899). 3. RPMI 1640 medium with 2% fetal bovine serum (FBS; Invitrogen). 4. Fifty milliliters plastic tissue culture-grade tubes (BD Biosciences). 5. Centrifuge with 50 mL tube holders. 6. Hemocytometer to enumerate nucleated blood cells.

B. Staining of Total PB-Derived Nucleated Cells (TNCs) for Analysis 1. Medium used for staining RPMI 1640 with 2% fetal bovine serum (FBS; Invitrogen). 2. Flow Cytometry Size Calibration Kit microspheres (Invitrogen; Molecular Probes).


42

[(Fig._1)TD$IG]

Fig. 1 Gating strategy for analyzing/sorting human PB-VSELs by FACS. Panel A: PB-derived TNCs are visualized by dot-plot based on FSC versus SSC signals (region P3). Panels B–F: Cells from lymphocyte gate extended to the left region P1 are further analyzed for hematopoietic lineages marker expression and all the Lin events are included in region P2. Panel C: The Lin population from region P2 is subsequently analyzed based on CD133 and CD45 antigen expression and two populations of CD133+ cells are distinguished based on CD45 expression, that is, Lin/CD45/CD133+ (VSELs: region Q2) and Lin/CD45+/CD133+ (HSPCs: region Q4). Panel E: The Lin population from region P2 is analyzed based on CD34 and CD45 antigen expression and two populations of CD34+ cells are distinguished based on CD45 expression, that is, Lin/CD45/CD34+ (VSELs: region P5) and Lin/CD45+/CD34+ (HSPCs: region P4). Panel G: The Lin population from region P2 is subsequently analyzed based on CXCR4 and CD45 antigen expression and two populations of CXCR4+ cells are distinguished based on CD45 expression, that is, Lin/CD45/CXCR4+ (VSELs: region P5) and Lin/CD45+/CXCR4+ (HSPCs: region P4).

3. Fifty-milliliter plastic tissue-grade culture tubes (BD Biosciences) and 5 mL round-bottom tubes (BD Biosciences). 4. Seventy and 40 mm strainer/mesh filters (BD Biosciences). 5. Centrifuge with 50 and 5 mL tube holders. 6. Monoclonal antibodies used for staining human HSCs, VSELs, MSCs, and EPCs include mouse monoclonal antibodies against human epitopes, predominantly directly conjugated with fluorochromes – are listed in Table II. 7. Flow cytometer (LSR II; Becton Dickinson).


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IV. Methods A. Isolation of Total PB-Derived Nucleated Cells (TNCs) by Lysing Red Blood Cells (RBCs) 1. Collect patient PB into tubes containing anticoagulant (EDTA). 2. Distribute PB sample into 50 mL plastic tubes in amount of 10 mL of PB per tube, fill the tubes by adding 40 mL 1 PBS, and centrifuge samples for 10 min at 500g at room temperature (RT). 3. Discard supernatant and remove the RBCs by employing BD Pharm Lyse – lysing buffer. Add 40 mL of 1 lysing solution to each tube. Immediately after adding the lysing solution gently vortex each tube. Incubate at RT for 10 min and protect from light. 4. Centrifuge cells for 10 min at 500g at RT and remove supernatant carefully. 5. Repeat lysis of RBCs by resuspending the pellet of cells with 20 mL BD Pharm Lyse buffer. Incubate cells for 10 min in RT then spin the samples for 10 min at 500g at 4 ˚C. 6. Discard supernatant, resuspend remaining pellet in 50 mL of RPMI 1640 media with 2% FBS, and transfer cell suspension to a new 50 mL tube passing through a 70 mm strainer/mesh filter to remove cellular clumps, then spin down for 10 min at 500g at 4 C. 7. Resuspend cells in 1 mL of RPMI 1640 media with 2% FBS; count TNC cells with hemocytometer. 8. Separate the cell suspension into tubes (5 mL round-bottom tubes). The number of cells in each tube should be kept around 3–5 million/tube. Stain cells as described in the next section.

B. Staining of PB-Derived TNCs for Flow Cytometric Analysis 1. Stain PB-derived TNCs in RPMI 1640 media supplemented with 2% FBS with antibodies (for list of required antibodies, see Table II). Staining should be performed according to recommendations provided by vendor in 5 mL roundbottom tubes kept for 30 min on ice. 2. Wash all samples by adding 3 mL of RPMI 1640 medium with 2% FBS and centrifuge tubes for 10 min at 500g at 4 ˚C. 3. Resuspend cells for analysis in 0.5 mL RPMI 1640 medium with 2% FBS. Keep samples on ice until analysis by FACS. 4. Cells to be sorted have to be resuspended in RPMI 1640 medium supplemented with 2% FBS and transferred to new tubes (5 mL round-bottom tubes) after filtration through 40 mm strainer/mesh filter to remove cell clumps. Adjust volume of cell suspension to 4/tube and keep cells on ice until sorting.


44 C. Setting Up Instrument for FACS Analysis

1. Set up the forward- and side-scatter parameters (FSC and SSC, respectively) in logarithmic or linear scale and adjust the threshold on FSC parameter. 2. Run the mixture of the size-predefined beads (size calibration beads with standard diameters of 1, 2, 4, 6, 10, and 15 mm) and adjust the threshold of cytometer to be able to include for sort all objects that are bigger/equal 2 mm. 3. Set up minimal threshold to be able to see 2 mm beads on FSC versus SSC dotplot. 4. Set up the gate that will include all objects larger than 2 mm on dot-plot showing objects according to their FSC and SSC parameters. 5. Run the stained samples and adjust the gate to include agranular objects larger in size than 2 mm. 6. Perform compensation calculations and prepare the logical gating strategy resulting in identification. Analyze human VSELs by FACS (as shown in Fig. 1). 7. The phenotypes of VSELs are described below.

D. Identification of VSELs in Human PB and UCB 1. Human VSELs in PB (Fig. 1) or UCB (Fig. 2) are identified and enumerated as (i) Lin/CD45/CD133+, (ii) Lin/CD45/CD34+, and (iii) Lin/CD45/ CXCR4+. Lineage markers include CD2, CD3, CD14, CD16, CD19, CD24, CD56, CD66b, and CD235. 2. HSPCs in human PB (Fig. 1) or UCB (Fig. 2) are identified according to cell surface markers as (i) Lin/CD45+/CD133+, (ii) Lin/CD45+/CD34+ and Lin/ CD45+/CXCR4+ cells. Lineage markers include CD2, CD3, CD14, CD16, CD19, CD24, CD56, CD66b, and CD235.

E. Calculation of Absolute Numbers of Target Cells in 1 mL of PB 1. Calculate TNCs number in 1 mL of PB according to formula – TNCs number in 1 mL PB = amount of TNCs (by counting)/volume of PB (mL). 2. Calculate absolute numbers of target cells in 1 mL of PB by employing formula – absolute numbers of target cells in 1 mL of PB = (TNCs number/mL PB identified target cells number)/amount TNC cells recorded in each sample by FACs.

F. Sorting of Cells By employing the above-described gating strategies, VSELs can be sorted from BM, UCB, or PB.


45

[(Fig._2)TD$IG]

Fig. 2 Gating strategy for analyzing/sorting human UCB-VSELs by FACS. Panel A: UCB-derived TNCs are visualized by dot-plot based on FSC versus SSC signals. The TNCs events are shown in region P3. Panels B–F: Cells from region P1 are further analyzed for hematopoietic lineage marker expression and all the Lin events are included in region P2. Panel C: The Lin population from region P2 is subsequently analyzed based on CD133 and CD45 antigen expression and two populations of CD133+ cells are distinguished based on CD45 expression, that is, Lin/CD45/CD133+ (VSELs: region Q2) and Lin/CD45+/CD133+ (HSPCs: region Q4). Panel E: The Lin population from region P2 is subsequently analyzed based on CD34 and CD45 antigen expression and two populations of CD34+ cells are distinguished based on CD45 expression, that is, Lin/CD45/CD34+ (VSELs: region P5) and Lin/CD45+/ CD34+ (HSPCs: region P4). Panel G: The Lin population from region P2 is subsequently analyzed based on CXCR4 and CD45 antigen expression and two populations of CXCR4+ cells are distinguished based on CD45 expression, that is, Lin/CD45/CXCR4+(VSELs: region P5) and Lin/CD45+/CXCR4+ (HSPCs: region P4).

V. Results Our data indicated that VSELs are much smaller than their hematopoietic counterpart as well as mature erythrocytes (Ratajczak et al., 2009; Zuba-Surma and Ratajczak, 2010; Zuba-Surma et al., 2008a, 2010). Thus, the very small size of these stem cells may be considered as marker for their identification and isolation by FACS. We employed this novel size-based approach, controlled by the size-bead markers, for isolating rare and small VSELs from murine BM by FACS including the gating strategy with regions containing small size (2–10 mm) events. Such region

46


established on FSC versus SSC dot-plot contains predominantly cellular debris, but also rare nuclear cell events – VSELs, which may be further characterized based on specific phenotypic markers expression (Zuba-Surma et al., 2008a, 2010). In our opinion the fact that most of the sorting protocols exclude events smaller than erythrocytes (less than 6 mm in diameter) as debris or platelets may explain why exceptionally small VSELs were overlooked before among other sorted stem/progenitor cell populations. Fig. 1 shows the example of analysis of VSEL content in human PB following the lysis of RBCs and staining with antibodies for specific VSEL markers, as described above. The small events enclosed in region P1 (Panel A), including predominantly fraction of lymphocytes and primitive/stem cells, were further analyzed for the expression of hematopoietic lineage markers (Lin), and Lin events are included in region P2 on histogram (Panels B–F). Panel C: The Lin population from region P2 is subsequently analyzed based on CD133 and CD45 antigen expression, and two populations of CD133+ cells are distinguished based on CD45 expression, that is, Lin/CD45/CD133+ (VSELs: region Q2) and Lin/CD45+/CD133+ (HSPCs: region Q4). Panel E: The Lin population from region P2 is analyzed based on CD34 and CD45 antigen expression and two populations of CD34+ cells are distinguished based on CD45 expression, that is, Lin/CD45/CD34+ (VSELs: region P5) and Lin/CD45+/CD34+ (HSPCs: region P4). Panel G: The Lin population from region P2 is subsequently analyzed based on CXCR4 and CD45 antigen expression and two populations of CXCR4+ cells are distinguished based on CD45 expression, that is, Lin/CD45/CXCR4+ (VSELs: region P5) and Lin/CD45+/CXCR4+ (HSPCs: region P4). Such gating strategy occurred to be very successful for identification and isolation of PB-derived VSELs, as indicated by our further genetic analysis of expression of pluripotent/embryonic markers in the sorted cells (Ratajczak et al., 2008a, 2008c). Analogous analytical strategy has been employed for identification and isolation of human UCB-derived VSELs (Fig. 2) (Kucia et al., 2007a; Zuba-Surma and Ratajczak, 2010; Zuba-Surma et al., 2010). UCB-derived TNCs are visualized by dot-plot based on FSC versus SSC signals. The TNCs events are shown in region P3. Panels B–F: Cells from region P1 are further analyzed for hematopoietic lineage maker expression and all the Lin events are included in region P2. Panel C: The Lin population from region P2 is subsequently analyzed based on CD133 and CD45 antigen expression and two populations of CD133+ cells are distinguished based on CD45 expression, that is, Lin/CD45/CD133+ (VSELs: region Q2) and Lin/CD45+/CD133+ (HSPCs: region Q4). Panel E: The Lin population from region P2 is subsequently analyzed based on CD34 and CD45 antigen expression and two populations of CD34+ cells are distinguished based on CD45 expression, that is, Lin/CD45/CD34+ (VSELs: region P5) and Lin/CD45+/CD34+ (HSPCs: region P4). Panel G: The Lin population from region P2 is subsequently analyzed based on CXCR4 and CD45 antigen expression and two populations of CXCR4+ cells are distinguished based on CD45 expression, that is, Lin/CD45/ CXCR4+(VSELs: region P5) and Lin/CD45+/CXCR4+ (HSPCs: region P4).


47

Such gating strategy occurred to be very successful for identification and isolation of UCB-derived VSELs, as indicated by our further genetic analysis of expression of pluripotent/embryonic markers in the sorted cells (Ratajczak et al., 2008a, 2008c). Such optimized analytical strategy was successfully employed not only for identification of VSELs in human UCB (Kucia et al., 2007a; Zuba-Surma and Ratajczak, 2010; Zuba-Surma et al., 2010) but also for their detection in other human specimens including the investigation of VSELs circulating in PB of patients with several severe organ injuries such as myocardial infarction as well as inflammatory diseases (colitis) and in patients suffering with gastrointestinal tumors (Abdel-Latif et al., 2010; Paczkowska et al., 2009; Wojakowski et al., 2006, 2009). In such cases the very rare VSEL’s presence in PB was confirmed by several imaging technologies including imaging cytometry (ISS) (Abdel-Latif et al., 2010; Wojakowski et al., 2009; Zuba-Surma et al., 2008b). Such approach allowed for distinguishing VSELs from cellular debris and artifacts, thereby providing strong evidence for their existence and mobilization into blood due to tissue injury (Figs. 3 and 4). Based on the ability of the imaging cytometry, we confirmed that similarly to murine BM-derived VSELs, human VSELs are also smaller than mature erythrocytes and leukocytes (Fig. 3). The examples of ISS technology provided multicolor images of mobilized very small VSELs circulating in blood of patients are shown in figure 4. Both classical and imaging cytometry have become the major technology for VSEL identification, detailed characterization, and purification from multitude murine and human specimens, and the well-established flow cytometric protocols (Zuba-Surma and Ratajczak, 2010) provide vast and reliable material for further molecular and genetic analysis of these unique cells.

VI. Critical Aspects of the Methodology 1. Since VSEL, MSCs, and EPCs are exceptionally rare in PB, minimum 10 mL of PB is required to enumerate these cells – in particular in steady-state (nonpathological) conditions. 2. Similar protocol may be employed for enumeration of UCB-derived or human BM-derived cells. Since both UCB and BM contain more stem cells, the volume of the harvested samples may be decreased to 5 mL. 3. To remove efficient RBC, the 1 lysing solution should be warmed to RT. Lysing buffer prewarmed to RT works much better than the cold one. After adding the lysing solution, the cells should be very well resuspended. 4. Remember to use single-color stained samples to prepare proper compensation profile for flow cytometric analysis/sorting as well as samples stained with isotype controls only (for isotype control antibodies, see Table II). 5. In order to obtain valuable data record at least 1 million TNCs events from each sample.


48

[(Fig._3)TD$IG]

Fig. 3 Comparison of cellular size and morphology between human blood-derived VSELs and mature hematopoietic cells by imaging cytometry. Cells were isolated from peripheral blood of patients with acute myocardial infarction and were stained for specific markers to distinguish mature monocytes (CD14), granulocytes (CD66b), and erythrocytes (CD235a; glycophorin A). VSEL stem cell was identified as nucleated small cell negative for CD45 and hematopoietic lineages markers (FITC; green), which exhibits expression of Oct4 – pluripotent marker (PE; orange) and CXCR4 – receptor for SDF-1 (PE-Cy5; magenta). Nuclei were stained with 7-aminoactinomycin D (7-AAD; red). The specific size of each cell (shown in red) was calculated by ImageStream system software as a length of minor cellular axis and is expressed in micrometers. The scale bars indicate 10 mm. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of the chapter.)

6. The preferable concentration of cells resuspended for analysis/sort should be between 10 and 15 106 mL1. 7. While analyzing VSELs and HSCs, the cells are gated in extended to the left lymphocytic cells area. 8. During sorting, do not exceed the speed 20,000 of events/s to keep the recovery and purity of sorted cells high. Use typical high-purity sorting mode (e.g., purify 1 drop for MoFlo cell sorter). 9. ImageStream technology is a useful tool to verify if all the sorted events are truly cells (Fig. 4).


49

[(Fig._4)TD$IG]

Fig. 4 Representative images of VSEL and hematopoietic stem/progenitor cell (HSPC) circulating in blood of patients with acute myocardial infarction by imaging cytometry (ImageStreamX system). Human blood cells were stained for markers distinguishing VSELs such as (i) CD45 panleukocytic antigen (APCCy7, cyan), (ii) hematopoietic lineages markers (FITC, green), and (iii) stem cell antigens CD133 (PE, yellow) and CD34 (APC, violet). Nuclei were stained with Hoechst 33342 dye (red). The lower panel shows magnified combined images related to the expression of indicated antigens by the VSEL stem cell. The scale bars indicate 10 mm. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of the chapter.)

VII. Applications VSELs are detectable at extremely low level in steady-state conditions PB (150–300 mL1) (Zuba-Surma et al., 2010). However, there are several pathological situations (e.g., heart infarct or stroke) in which VSELs are mobilized into PB and circulate at a much higher level. They could be mobilized into PB in order to participate in tissue/organ repair. However, it is likely that if VSELs are released from the BM, even if they are able to home to the areas of tissue/organ injury, they may function only in the regeneration of minor tissue injuries. Heart infarct or stroke, on the other hand, may involve severe tissue damage beyond the effective repair capacity of these rare cells. We are also identifying crucial factors involved in mobilization of VSELs into PB, and our data indicate a crucial role of stromal-derived factor-1 (SDF-1), complement cascade cleavage fragments, and sphingosine-1-phosphate (S1P) in this process (Ratajczak et al., 2010). Further, the allocation of these cells to the damaged areas depends on homing signals that may be inefficient in the presence of proteolytic enzymes released from leukocytes and macrophages associated with damaged tissue. Thus, it may happen that VSELs may potentially circulate as a homeless population of SCs in PB and return to the BM or home to other organs. We envision that a level of these cells in PB not only could be of scientific value but also could be elaborated in the future as an important diagnostic tool. For example, since it is a link between these cells and tissue organ rejuvenation, changes in the level


50

of these cells circulating in PB could reflect overall ‘‘regeneration potential’’ of an adult organism. Next, we already noticed that the number of VSELs circulating in PB correlates with extend of heart infarct (Abdel-Latif et al., 2010; Wojakowski et al., 2006, 2009) and stroke (Paczkowska et al., 2009), and what is more important it possesses some prognostic value. An intriguing observation is also an increase in the number of circulating VSELs in PB of cancer patients. It is possible that VSELs are mobilized into growing tumor to participate in its better vascularization and provide precursors for cancer-associated fibroblasts. Thus, we encourage other investigators to study biological consequences of VSELs mobilization in all these above-mentioned situations. Finally, gating strategies described in this chapter could be employed in the future to gate these cells not only to enumerate their number in PB, UCB, and BM but also to sort these cells for research and potential clinical applications.

VIII. Future Directions VSELs isolated from adult tissues can be considered as an alternative, source of SCs for regenerative medicine, that is not ethically controversial, However, before VSELs can find their potential application in regenerative medicine there are missing answers to this timely issue, especially in view of the current and widely performed clinical trials with BM-derived SCs in cardiology and neurology. First, there is the obvious problem of isolating a sufficient number of VSELs from the BM, UCB, or mPB. The number of these cells among BM MNCs is very low. For example, VSELs represent 1 cell in 105 of BM MNCs (Kucia et al., 2006a; ZubaSurma et al., 2008a). Furthermore, our data show that these cells are enriched in the BM of young mammals and their number decreases with age (Ratajczak et al., 2008b; Zuba-Surma and Ratajczak, 2008). Our data also indicate that VSELs could potentially provide a therapeutic alternative to the controversial use of human ESCs and strategies based on therapeutic cloning. Hence, while the ethical debate on the application of ESCs in therapy continues, the potential of VSELs is ripe for exploration. The current work in our laboratory indicates that VSELs could be efficiently employed in the realm of regenerative medicine, and that they are physiologically more important than merely being potential developmental remnants. Finally, we believe that the controlled modulation of somatic imprint status in VSELs such as we hypothesized, a proper de novo methylation of somatic imprinted genes on maternal and paternal chromosomes, could increase a regenerative power of these cells. The coming years will bring important answers to these questions. Acknowledgments This work was supported by NIH R01 CA106281-01, NIH R01 DK074720, EU structural funds, Innovative Economy Operational Program POIG.01.01.01-00-109/09-01, KBN grant (No. N401 024536), and the Henry M. and Stella M. Hoenig Endowment to MZR.


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Mariusz Z. Ratajczak et al. Wojakowski, W., Tendera, M., Kucia, M., Zuba-Surma, E., Paczkowska, E., Ciosek, J., Halasa, M., Krol, M., Kazmierski, M., Buszman, P., Ochala, A., Ratajczak, J., Machalinski, B., Ratajczak, M. Z. (2009). Mobilization of bone marrow-derived Oct-4+ SSEA-4+ very small embryonic-like stem cells in patients with acute myocardial infarction. J. Am. Coll. Cardiol. 53, 1–9. Wojakowski, W., Tendera, M., Zebzda, A., Michalowska, A., Majka, M., Kucia, M., Maslankiewicz, K., Wyderka, R., Krol, M., Ochala, A., Kozakiewicz, K., Ratajczak, M. Z. (2006). Mobilization of CD34 (+), CD117(+), CXCR4(+), c-met(+) stem cells is correlated with left ventricular ejection fraction and plasma NT-proBNP levels in patients with acute myocardial infarction. Eur. Heart J. 27, 283–289. Zuba-Surma, E. K., Klich, I., Greco, N., Laughlin, M. J., Ratajczak, J., Ratajczak, M. Z. (2010). Optimization of isolation and further characterization of umbilical-cord-blood-derived very small embryonic/epiblast-like stem cells (VSELs). Eur. J. Haematol. 84, 34–46. Zuba-Surma, E., Klich, I., Wysoczynski, M., Greco, N., Laughlin, M., Ratajczak, M., Ratajczak, J. (2009a). In vitro and in vivo evidence that umbilical cord blood (UCB)-derived CD45-/SSEA-4 +/OCT-4+/CD133+/CXCR4+/Lin very small embryonic/epiblast like stem cells (VSELs) do not contain clonogenic hematopoietic progenitors but are highly enriched in more primitive stem cells – novel view on hierarchy of UCB stem cell compartment. Blood 114, 35. Zuba-Surma, E. K., Kucia, M., Abdel-Latif, A., Dawnn, B., Hall, B., Singh, R., Lillard, J. W., Ratajczak, M. Z. (2008a). Morphological characterization of very small embryonic-like stem cells (VSELs) by ImageStream system analysis. J. Cell. Mol. Med. 12, 292–303. Zuba-Surma, E. K., Kucia, M., Dawn, B., Guo, Y., Ratajczak, M. Z., Bolli, R. (2008b). Bone marrowderived pluripotent very small embryonic-like stem cells (VSELs) are mobilized after acute myocardial infarction. J. Mol. Cell. Cardiol. 44, 865–873. Zuba-Surma, E., Kucia, M., Liu, R., Klich, I., Ratajczak, M., Ratajczak, J. (2008c). CD45-/ALDH-low/ SSEA-4+/Oct-4+/CD133+/CXCR4+/Lin very small embryonic-like (VSEL) stem cells isolated from umbilical cord blood as potential long term repopulating hematopoietic stem cells. Blood 112, 850. Zuba-Surma, E. K., Kucia, M., Rui, L., Shin, D. M., Wojakowski, W., Ratajczak, J., Ratajczak, M. Z. (2009b). Fetal liver very small embryonic/epiblast like stem cells follow developmental migratory pathway of hematopoietic stem cells. Ann. N. Y. Acad. Sci. 1176, 205–218. Zuba-Surma, E. K., Kucia, M., Wu, W., Klich, I., Lillard Jr., J. W., Ratajczak, J., Ratajczak, M. Z. (2008d). Very small embryonic-like stem cells are present in adult murine organs: ImageStream-based morphological analysis and distribution studies. Cytometry A 73A, 1116–1127. Zuba-Surma, E. K., and Ratajczak, M. Z. (2008). Very small embryonic like stem cells – implications for aging. Mech. Ageing Dev. 1–2, 58–66. Zuba-Surma, E. K., and Ratajczak, M. Z. (2010). Overview of very small embryonic-like stem cells (VSELs) and methodology of their identification and isolation by flow cytometric methods. Curr. Protoc. Cytom. Chapter 9, Unit 9.29. Zuba-Surma, E., Yoshimoto, M., Kucia, M., Ratajczak, J., Yoder, M., Ratajczak, M. (2009c). An evidence that CD45-Lin-Sca-1+Oct-4+ VSEL stem cells are embryonic remnants and are present in embryonic tissues during development. Hum. Gene Ther. 20, 1493.

CHAPTER 4

Apoptosis and Beyond: Cytometry in Studies of Programmed Cell Death Donald Wlodkowic,* William Telford,y Joanna Skommerz and Zbigniew Darzynkiewiczx * The BioMEMS Research Group, Department of Chemistry, University of Auckland, Auckland, New Zealand y

Experimental Transplantation and Immunology Branch, Center for Cancer Research, NCI, NIH, Bethesda, Maryland, USA z School of Biological Sciences, University of Auckland, Auckland, New Zealand x

Brander Cancer Research Institute, New York Medical College, Valhalla, New York, USA

Abstract Introduction The Biology of Apoptosis Cytometry in Cell Necrobiology Cytometric Methods to Detect Apoptosis A. Light Scattering Changes in Apoptotic Cells B. Dissipation of Mitochondrial Transmembrane Potential (Dcm) C. Activation of Caspases D. Changes in the Plasma Membrane During Apoptosis E. Nuclear Hallmarks of Apoptosis F. SYTO-Based Detection of Apoptosis V. Time-Window in Measuring Incidence of Apoptosis VI. Multiparameter Detection of Apoptosis: Choosing the Right Method VII. Beyond Apoptosis – Analysis of Alternative Cell Death Modes A. Autophagy B. Necrosis C. Cell Senescence I. II. III. IV.

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0091-679X/10 $35.00 DOI 10.1016/B978-0-12-385493-3.00004-8

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Abstract A cell undergoing apoptosis demonstrates multitude of characteristic morphological and biochemical features, which vary depending on the inducer of apoptosis, cell type and the ‘‘time window’’ at which the process of apoptosis is observed. Because the gross majority of apoptotic hallmarks can be revealed by flow and image cytometry, the cytometric methods become a technology of choice in diverse studies of cellular demise. Variety of cytometric methods designed to identify apoptotic cells, detect particular events of apoptosis and probe mechanisms associated with this mode of cell death have been developed during the past two decades. In the present review, we outline commonly used methods that are based on the assessment of mitochondrial transmembrane potential, activation of caspases, DNA fragmentation, and plasma membrane alterations. We also present novel developments in the field such as the use of cyanine SYTO and TO-PRO family of probes. Strategies of selecting the optimal multiparameter approaches, as well as potential difficulties in the experimental procedures, are thoroughly summarized.

I. Introduction During the past decade mechanisms underlying cell death have entered into a focus of interest of many researchers in diverse fields of biomedicine. These mechanisms include a wide range of signaling cascades that regulate initiation, execution, and postmortem cell disposal mechanisms (Darzynkiewicz et al., 1997, 2001b, 2004). The term cell necrobiology (biology of cell death) was introduced to collectively define all these cellular activities (Darzynkiewicz et al., 1997; see Cell Necrobiology in Wikipedia). Particular interest in cell necrobiology comes from the appreciation of the multitude of complex regulatory circuits that control the cellular demise. Considerable progress is currently being made in our understanding of a diversity of existing modes of programmed cell death (Blagosklonny, 2000; Leist and Jaattela, 2001; Zhivotovsky, 2004). Burgeoning data show that although the elimination of many cells relies heavily on classical apoptotic pathways, the alternative, quasiapoptotic, and nonapoptotic mechanisms, may also be involved in a plethora of biological processes (Kroemer and Martin, 2005; Leist and Jaattela, 2001). Undoubtedly, the cell propensity to undergo classical apoptosis still remains a key mechanism in the pathogenesis of many human diseases (Brown and Attardi, 2005; Danial and Korsmeyer, 2004). Genetic alterations that affect circuitry of the apoptotic machinery are reportedly linked to many disorders that are characterized by either diminished (cancer) or excessive (neurodegeneration) proclivity of cells to

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suicide. Thus, the in-depth understanding of different regulators of apoptosis at molecular level offers vast opportunities for innovative pharmacological intervention (Brown and Attardi, 2005; Green and Kroemer, 2005). In this context, there is an ever-increasing demand for convenient analytical tools to rapidly quantify and characterize diverse cell demise modes. Since cell death is a stochastic process, high-throughput single-cell analysis platforms are often of essence to deliver meaningful insights into intrinsically heterogeneous cell populations (Darzynkiewicz et al., 1997, 2004). Here, a gross majority of classical attributes of apoptosis can be quantitatively examined by flow and image cytometry, platforms that allow assessment of multiple cellular attributes on a single cell level (Darzynkiewicz et al., 1997, 2001a, 2001b, 2004; Telford et al., 2004). To date, diverse methods have been introduced that allow implementation of apoptotic assays on both live and/or fixed specimens (Darzynkiewicz et al., 2001a, 2001b, 2004). Some of them have evolved toward commercially available kits supplied by countless vendors. Although kits offer an advantage of simplicity and easy step-by-step protocols, the information accompanying is generally enigmatic. Adequate information about chemistry of the components or even mechanistic principles of the kit is often lacking because of the proprietary nature of patented reagents (Darzynkiewicz et al., 2004). Therefore, interpretation of the results and potential pitfalls may be particularly cumbersome for researchers unfamiliar with the biology of apoptosis. This chapter has been designed to complement the protocol-format literature by providing additional background information, methods’ comparison, and discussion about advantages and limitations of commonly used assays. Some steps of individual methods are discussed to emphasize their critical role and avoid the likelihood of artifacts. We update also some earlier reviews on the application of cytometry in analysis of cell death (Darzynkiewicz et al., 1992, 1994, 1997, 2001a, 2001b, 2004; Telford et al., 2004).

II. The Biology of Apoptosis Archetypically cells can disassemble in two morphologically and biochemically distinct processes: apoptosis and necrosis (Darzynkiewicz et al., 1997; Kerr et al., 1972; Lockshin and Zakeri, 2001). Both were initially identified based on characteristic changes in cell morphology (Kerr et al., 1972). Despite subsequent development of numerous molecular markers, the morphological changes still remain the ‘‘gold standard’’ to define the mode of cell death (Darzynkiewicz et al., 1997; Majno and Joris, 1995). Fig. 1 outlines major morphological and molecular changes occurring during apoptosis versus accidental cell death (herein termed necrosis). These were thoroughly discussed in some of our earlier reviews (Darzynkiewicz et al., 1997, 2001b, 2004). Alterations in cellular parameters, as presented in Fig. 1, become a basis to development of specific markers for microscopy, cytometry, and molecular techniques (Darzynkiewicz et al., 1997, 2001b, 2004). Importantly, however, constellation of apoptotic markers can vary depending on the stimuli and

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[(Fig._1)TD$IG]

Fig. 1

Simplified diagram of molecular pathways that regulate caspase-dependent apoptotic cell

death.

stress level, cell type, and unique cellular microenvironment that modulate cellular stress responses. In this context, some markers (such as oligonucleosomal DNA fragmentation) may not be detected in specimens challenged with divergent stimuli or microenvironmental conditions (e.g., cytokines, growth factor deprivation, heterotypic cell culture, etc.). It is, thus, always advisable to study several parameters at a time, which provide a multidimensional view of the advancing apoptotic cascade (Darzynkiewicz et al., 1997, 2001b, 2004). Noteworthy, recent reports have also provided closer insights into the mechanisms of cell death sentence and led to the characterization of several alternative demise modes (caspase-independent apoptosis-like PCD, autophagy, necrosis-like PCD, mitotic catastrophe) with serious connotations to disease pathogenesis and treatment (Edinger and Thompson, 2004; Leist and Jaattela, 2001; Lockshin and Zakeri, 2002; Okada and Mak, 2004). These important discoveries also initiated an ongoing debate aiming at the definition and classification of different modes of cell death that is of particular importance for the development of novel cytometric assays (Blagosklonny, 2000; Zhivotovsky, 2004). The general term apoptosis, exploited commonly in many research articles, tends sometimes to misinterpret the actual mechanisms underlying cell suicide program (Leist and Jaattela, 2001; Zhivotovsky, 2004). Therefore, it has been postulated to restrict the term apoptosis to only the traditional cell demise program featuring all ‘‘hallmarks of apoptotic cell death,’’ namely (i) activation of caspases as an absolute biomarker of cell death; (ii) condensation of chromatin; (iii) activation of endonucleases(s) causing internucleosomal DNA cleavage leading to extensive DNA fragmentation; (iv) appearance of


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[(Fig._2)TD$IG]

Fig. 2

Mitochondrial pathway of caspase-dependent apoptosis.

distinctive cellular morphology with preservation of organelles; (v) cell dehydration leading to its shrinkage; (vi) plasma membrane blebbing; and (vii) nuclear fragmentation and formation of apoptotic bodies (Figs. 1 and 2; Blagosklonny, 2000; Leist and Jaattela, 2001; Zhivotovsky, 2004; Ziegler and Groscurth, 2004). The use of the general term apoptosis should be always accompanied by listing the particular morphological and/or biochemical apoptosis-associated feature(s) that was (were) detected. It is also advisable to exploit a plethora of different assays to cross-analyze action of, for example, novel anticancer compounds and bear in mind that the characteristic changes in cell morphology revealed by cell imaging (light or electron microscopy) still remain the gold standard in the ultimate classification of the cell demise mode (Darzynkiewicz et al., 1997; King et al., 2000; Smolewski et al., 2003). Proper experimental approaches will help to avoid any potential misclassifications as the evidence accumulates that the roads to cellular disintegration represent a much more diverse and interconnected course than previously anticipated (Ferri and Kroemer, 2001; Leist and Jaattela, 2001). Not surprisingly the development of novel functional probes for cell death and thorough understanding of the mechanisms underlying properties of existing ones

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are of utmost importance for the future progress in cell necrobiology (Darzynkiewicz et al., 1997, 2001a, 2004). This is particularly relevant in view of the growing appreciation of the multitude of cell demise modes, and the need for sensitive and high-throughput cytometric assays capable to discriminate them.

III. Cytometry in Cell Necrobiology The major advantages of flow cytometry include the possibility of multiparameter measurements (correlation of different cellular events at a time), single cell analysis (avoidance of bulk analysis), and rapid analysis of cell populations (thousand of cells per second) (Bonetta, 2005; Melamed, 2001). Flow cytometry overcomes, thus, a frequent problem of traditional bulk techniques such as fluorimetry, spectrophotometry, or gel techniques (e.g., Western blot, WB). These are based on analysis of a total cell population that averages the results from every given cell (Darzynkiewicz et al., 1997, 2001a; Melamed, 2001). Moreover, by virtue of multiparameter analysis, cytometry allows correlative studies between many cell attributes based on both light scatter and fluorescence measurements (Darzynkiewicz et al., 1997; Melamed, 2001; Robinson, 2006). For example, when cellular DNA content, the parameter that reports the cell cycle position, is one of the measured attributes, an expression of other measured attribute(s) can be then directly related to the cell cycle position without a need for cell synchronization (Darzynkiewicz et al., 1997, 2004; Halicka et al., 1997). Furthermore, the change in expression of particular cell constituents, or coexpression of different events, if correlated within the same cell, may yield clues regarding a possible cause–effect relationship between the detected events (Darzynkiewicz et al., 1997, 2001b, 2004). It is why during the past two decades cytometric methodology has been applied in a gross majority of cell demise studies (Darzynkiewicz et al., 1997, 2004; Halicka et al., 1997; Huang et al., 2005). Novel technologies such as cell imaging in flow and laser scanning cytometry (LSC) deliver even more sophisticated features that combine superior statistical power of cytometric analysis coupled with low-resolution imaging capabilities (Darzynkiewicz et al., 1999; Deptala et al., 2001; George et al., 2004; Smolewski et al., 2001). Finally, high-speed sorting capabilities of newly designed bench-top equipment expand further cytometric applications by allowing detailed studies on the purified cell subpopulations of interest (Eisenstein, 2006; Melamed, 2001). Expectedly, the current pace in the development of novel cytometric technologies will open up new horizons for future research on cell demise (Bernas et al., 2006; Darzynkiewicz et al., 2004; Robinson, 2004). Applications of cytometry in cell necrobiology studies have archetypically two goals (thoroughly reviewed in Darzynkiewicz et al., 2001a, 2004). One aim is to elucidate molecular mechanisms associated with cell death. Here cytometric assays have been applied to quantify the expression of cell constituents involved in apoptotic circuitry [such as members of the Bcl-2 protein family (caspases), inhibitors of caspases, etc.]. Cytometric methods have been also developed to study many


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changes in metabolic attributes, such as mitochondrial metabolism, redox status, intracellular pH or calcium fluxes. The second goal of cytometry in cell necrobiology is to estimate the viability of individual cells in a given population. This includes identification and quantification of dead cells and discrimination between apoptotic versus necrotic mode of death. Such discrimination is generally based on the change in cell morphology and/or on the presence of characteristic biochemical or molecular markers (Fig. 1). Most of these changes serve as markers to identify and quantify apoptotic cells by cytometry. To stress it again, morphological criteria (examined by the light, fluorescent, and electron microscopy) are still the ‘‘gold standard’’ to define the mode of cell death and confirm flow cytometric results (Darzynkiewicz et al., 1997, 2004; Majno and Joris, 1995; Ziegler and Groscurth, 2004). Therefore, lack of microscopic examination may potentially lead to the misclassification and false-positive or -negative artifacts, and is a common drawback of the experimental design (Darzynkiewicz et al., 1997, 2001a, 2004). The striking example of such misclassification is identification by flow cytometry of phagocytes that engulfed apoptotic bodies as individual apoptotic cells (Bedner et al., 1999).

IV. Cytometric Methods to Detect Apoptosis A. Light Scattering Changes in Apoptotic Cells Flow cytometry allows quantitative measurements of laser light scatter characteristics that reflect morphological features of cells. Cell shrinkage due to the dehydration can be detected at early stages of apoptosis as a decrease in intensity of forward light scatter (FSC) signal (Ormerod et al., 1995; Swat et al., 1981). Either unchanged, or often increased side scatter signal (SSC, measured at 90 angle) is concomitantly observed as cell shrinkage; the condensation of nucleus and cytoplasm driven by cell dehydration leads to enhancement of light refraction and reflection (Fig. 3). When apoptotic cascade advances the cells become progressively smaller, and intensity of side scatter also decreases. Late apoptotic/secondary necrotic cells, therefore, are characterized by markedly diminished ability to scatter light in both, forward and right angle directions (Fig. 3). Necrosis, on the contrary, often proceeds through the simultaneous and rather drastic reduction in intensity of both light scatter parameters, which is believed to reflect rapid loss of the cell membrane integrity and leakage of cytoplasmic constituents. Primary necrotic cells fall, thus, into subpopulation similar to secondary necrotic cells and cannot be properly distinguished by light scattering measurements (Darzynkiewicz et al., 1997, 2004; Majno and Joris, 1995). It should be noted, however, that observable changes in light scattering are not a reliable marker of apoptosis or necrosis by themselves. Mechanically broken cells, isolated nuclei, cell debris, and individual apoptotic bodies all display reduced light scatter properties and may be mistakenly accounted for as apoptotic cells. Furthermore, activation of tissue transglutaminase 2 (TGase 2) has recently been

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[(Fig._3)TD$IG]

Fig. 3 Changes in light scattering properties during apoptosis. Human B-cell lymphoma cells were untreated (left panel) or treated with small molecule Bcl-2 inhibitor HA14-1 (right panel) as described (Skommer et al., 2006). Note that viable cell population (V) from the treated culture has similar light scattering properties as control cells. Apoptotic cells (A) have diminished forward scatter while their side scatter is enhanced. The late apoptotic/secondary necrotic cells (LA/N) have diminished both scatter parameters. Apoptotic bodies and cell debris exhibit extremely low light scatter values (D).

reported to influence light scattering properties detected by flow cytometry in some models of apoptosis (Darzynkiewicz et al., 2004; Grabarek et al., 2002). TGase 2 activity results here in protein crosslinking and enhancement of nuclear/cytoplasmic condensation. This is reflected by transient increase in intensity of the side scatter signal and moderate decrease in forward scatter signal. Conversely, apoptosis proceeding in absence of TGase 2 activation is reflected by the decrease in both forward and side scatter signals (Darzynkiewicz et al., 2004; Grabarek et al., 2002). It should be stressed that morphological features revealed by laser light scattering in flow cytometry should be considered as auxiliary parameters and be used only in conjunction with more specific markers of cell death. However, novel platforms such as LSC and multispectral imaging cytometry (cell imaging inflow), by providing low-resolution imaging of individual cells and expanding analytical capabilities to morphometric analysis deliver substantial improvements over classical flow cytometry in cell necrobiology studies (Bedner et al., 1999; Darzynkiewicz et al., 1999; George et al., 2004; Kamentsky, 2001; Pozarowski et al., 2006). B. Dissipation of Mitochondrial Transmembrane Potential (Dcm) The mitochondrion stands at the nexus of sensing and integrating diverse incoming stress signals, and mitochondrial disturbances often occur long before any marked morphological symptoms of apoptosis (Green, 2005; Skommer et al., 2007). In recent years multiple mechanisms have been revealed that explain


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mitochondrial function in apoptosis, including release of apoptogenic proteins into the cytosol upon mitochondrial outer membrane permeabilization (MOMP), loss of mitochondrial physiological processes indispensable for cell survival and generation of reactive oxygen species (ROS). The MOMP is a fundamental event leading to a release of holocytochrome c (cyt c) and an array of cell death modulating small proteins such as AIF, EndoG, Omi/HtrA2, Smac/DIABLO, Smac b, normally enclosed in the intermembrane space of the organelle (Saelens et al., 2004; van Gurp et al., 2003). Dissipation of mitochondrial inner transmembrane potential (Dcm) is frequently associated with MOMP (Kroemer, 1998; Zamzani et al., 1996, 1998). There are, however, examples of divergence where loss of Dcm can precede, coincide, or follow MOMP (Li et al., 2000; Skommer et al., 2007). Interestingly, as described by us and others, dissipation of mitochondrial inner transmembrane potential may not be an ultimate point of no return for cell commitment to die (Milella et al., 2002; Wlodkowic et al., 2006). The cytometric detection of Dcm loss is a sensitive marker of early apoptotic events. Procedures are based on lipofilic cationic probes that are readily taken up by live cells and accumulate in mitochondria according to the Nernst equation (Castedo et al., 2002). The extent of their uptake, as measured by intensity of cellular fluorescence, is proportional to Dcm status (Fig. 4). Majority of Dcm-sensitive probes are easily applicable for multiparameter detection with other apoptotic markers including caspase activation by fluorescently labelled inhibitors of caspases (FLICA), phosphatidylserine (PS) exposure by Annexin V and plasma membrane permeabilization by propidium iodide (PI) or YO-PRO 1 (Fig. 5; Castedo et al., 2002; Pozarowski et al., 2003; Wlodkowic et al., 2006, 2007a). In this context, lipophilic cationic fluorochromes rhodamine 123 (Rh123) or carboxycyanine dyes such as 3,30 -dihexiloxa-dicarbocyanine [DiOC6(3)] can serve as markers of Dcm loss (Darzynkiewicz et al., 1981, 1982; Johnson et al., 1980). Historically, a combination of Rh123 and PI was introduced as a viability assay that discriminates between live cells that stain with Rh123 but exclude PI versus early apoptotic cells that lost ability to accumulate Rh123 versus late apoptotic/necrotic cells that stain with PI only (Darzynkiewicz et al., 1982, 1994). The specificity of Rh123 and DiOC6(3) as selective Dcm-sensitive probes has been questioned (Salvioli et al., 1997). The apparent controversy may be due to the fact that to be a specific marker of Dcm Rh123 or DiOC6(3) has to be used at low concentration (1 mM), which was not the case in many studies. The alternative probes such as chloromethyltetramethylrosamine analogues or tetramethylrhodamine esters have became now more widely used to detect mitochondrial depolarization during apoptosis. MitoTrackerTM dyes (chloromethyltetramethylrosamine analogues) were introduced by Molecular Probes Inc. as new mitochondrial potential markers (Haughland, 2003). One of them is MitoTracker Red CMXRos, a probe considered to be highly sensitive and specific to Dcm and (Castedo et al., 2002; Pendergrass et al., 2004; Poot and Pierce, 1999). The previously reported retainability of CMXRos after fixation with formaldehyde was recently challenged by some authors (Ferlini et al., 1998; Macho et al., 1996; Poot and Pierce, 1999). It has been shown

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[(Fig._4)TD$IG]

Fig. 4 Dissipation of mitochondrial transmembrane potential (Dcm). (A) Analysis by staining with tetramethylrhodamine methyl ester (TMRM). Human B-cell lymphoma cells were either untreated (Ctrl) or treated with cycloheximide (CHX) to induce apoptosis and supravitally loaded with TMRM as described (Castedo et al., 2002; Wlodkowic et al., 2006). Cells with collapsed mitochondrial transmembrane potential (mito loss) have decreased intensity of orange TMRM fluorescence. (B) Analysis by staining with the Jaggregate dye JC-9. Human B-cell lymphoma cells were either untreated (Ctrl) or treated with crosslinking anti-CD95 antibody (anti-CD95) to induce apoptosis and loaded with JC-9 as described (Pritchard et al., 2001; Skommer et al., 2006). Cells with collapsed mitochondrial transmembrane potential (mito loss) have decreased intensity of red fluorescence (mitochondrial J-aggregates) and increased intensity of green fluorescence (cytoplasmic J-monomers). Note that by only employing the Dcm-sensitive probe there is no distinction between early, late apoptotic and necrotic cells. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of the chapter.)

that although uptake of CMXRos by live cells is a function of mitochondrial gradient, its retention following fixation depends rather on the availability of intramitochondrial thiols (Poot and Pierce, 1999). Thus, it is not advisable to apply CMXRos with measurements of another cell attributes that require subsequent cell


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fixation such as DNA fragmentation detected by the TDT-mediated dUTP-biotin nick-end labeling (TUNEL) assay or immunocytochemical detection of intracellular protein (see below). Other useful probes sensitive to Dcm changes are tetramethylrhodamine methyl ester perchlorate (TMRM) and tetramethylrhodamine ethyl ester perchlorate (TMRE). The application of TMRM combined with the marker of caspase activation (FLICA) and small cyanine cation YO-PRO 1 is illustrated in Fig. 5 (Pozarowski et al., 2003; Wlodkowic et al., 2006). Due to convenient spectral characteristics these probes are especially useful for multiparameter assays combining diverse apoptotic markers (Pozarowski et al., 2003; Wlodkowic et al., 2006, 2007a, 2007b). Major improvements have recently been made by implementing ratiometric J-aggregate forming cationic fluorochromes: JC-1 (5,50 ,6,60 -tetrachloro-1,10 , 3,30 -tetraethylbenzimidazolcarbocyanine iodide) and JC-9 (3,30 -dimethyl-aanaphthoxacarbocyanine iodide) (Cossarizza and Salvioli, 2001; Pritchard et al., 2001). Their uptake by energized mitochondria leads to formation of aggregates in the mitochondrial matrix and emission of orange/red fluorescence. Loss of Dcm leads to dissociation of the J-aggregates and transition to monomeric, cytoplasmic form that exhibits green fluorescence (Fig. 4). The major disadvantage of J-aggregate probes lies in occupation of crucial fluorescent channels that makes it difficult to multiplex on single 488 nm laser instrumentation. Furthermore, poor solubility of these probes in aqueous media may occasionally lead to staining artifacts. Nevertheless, when used concurrently with violet or red excitable fluorochromes they offer substantial improvements over traditional mitochondrial probes. Finally, probes such as 10-nonyl acridine orange (NAO), MitoFluor Green, and MitoTracker Green were previously advertised as markers of mitochondrial mass that are insensitive to Dcm changes (Pendergrass et al., 1997; Ratinaud et al., 1988). For increased sensitivity it was, thus, proposed to simultaneously measure both Dcm and mitochondrial mass with a combination of Dcm-sensitive and Dcm-insensitive probes (e.g., Petit et al., 1995). Disappointingly, further observations revealed that all three probes are dependent on changes in Dcm and cannot be used as mere markers of mitochondrial mass (Keij et al., 2000). NAO can be, however, conveniently applied to track peroxidation of mitochondrial cardiolipin by flow cytometry. This simple assay measures an early event that is a prerequisite for cytochrome c release during apoptosis (Castedo et al., 2002; Garcia Fernandez et al., 2004). Measurement of Dcm is particularly sensitive to changes in cellular environment. Therefore, samples assigned for comparison should be incubated and measured under identical temperature, pH, time elapsed between the onset of incubation and fluorescence measurement. Moreover, according to Nernst equation, the intracellular distribution of any cationic mitochondrial probe reflects the differences in the transmembrane potential across both the plasma membrane (i.e., between exterior vs. interior of the cell) and the outer mitochondrial membrane (Castedo et al., 2002; Shapiro, 2003). Thus, apart from mitochondria the probes can also accumulate in the cytosol. This is facilitated by both active and passive transport across the

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Fig. 5

Multiparameter analysis employing mitochondrial potential sensitive probes. (A) Concurrent analysis of collapse of

Dcm and early plasma membrane permeability during apoptosis. Cells were treated as in Fig. 4A and supravitally stained with

both YO-PRO 1 and TMRM probes (Wlodkowic et al., 2007a). Their green and orange fluorescence was measured by flow cytometry. Live cells (V) are both TMRMhigh and exclude YO-PRO 1. Early apoptotic cells (A) exhibit loss of Dcm (TMRMlow) and moderate uptake of YO-PRO 1. Late apoptotic/secondary necrotic cells (LA/N) are highly permeant to YO-PRO 1 probe. (B) Concurrent analysis of collapse of Dcm and caspase activation during apoptosis. Apoptosis of Jurkat cells was induced by oxidative stress (growth in the presence of 30 or 60 mM H2O2; Ctrl, untreated cells). The cells were then supravitally exposed to FAM-VAD-FMK and MitoTracker Red CMXRos, rinsed and their green and red fluorescence measured by flow cytometry (Pozarowski et al., 2003). Two subpopulations of apoptotic cells can be detected. Subpopulation B represents the cells that lost mitochondrial potential but did not activated caspases, while cells in subpopulation C are characterized by both, collapsed Dcm and caspase activation (FLICA binding). At 60 mM H2O2 caspase activation was accelerated as reflected by the increased proportion of cells in C compared to B. Note that multiparameter analysis of Dcm-sensitive probe with YO-PRO 1 or FLICA allows for excellent distinction between live, early, late apoptotic and necrotic cells. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of the chapter.)


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plasma membrane. To decrease the passive transport, mitochondrial probes should be used at their lowest possible concentration, that is, the minimal concentration that is still adequate to detect mitochondrial changes. This may, however, necessitate relatively high settings of the photomultiplier (photomultiplier voltage) and higher laser power outputs (Darzynkiewicz et al., 2004). Caution should be also taken, as cationic probes may be targeted to other organelles like endoplasmic reticulum (ER) or lysosomes. Moreover, accumulation of some probes may be influenced by the activity of multidrug efflux pumps (MDR). In each experiment it is advisable to assess probes’specificity by preincubation of cells for 20–30 min with 50–100 mM protonophores CCCP or FCCP. Both agents cause a collapse of the mitochondrial transmembrane potential and are used as positive controls (Castedo et al., 2002; Darzynkiewicz et al., 2004).

C. Activation of Caspases One of the hallmarks of classical apoptosis is the activation of unique cysteine aspartyl-specific proteases having a conserved QACXG consensus site containing active cysteine, called caspases (from cysteinyl aspartate-specific proteases; Fig. 2) (Alnemri et al., 1996; Kaufmann et al., 1993; Thornberry and Lazebnik, 1998). In mammals there are probably at least 14 members of the caspase family proteins that form a closely related family of proteases (Boyce et al., 2004; Zhivotovsky, 2003). Although individual caspases have specific functions, some degree of overlapping specificity and redundancy among them is apparent (Earnshaw et al., 1999). At present only eight caspases are known to participate in execution of apoptotic cell dismantling (caspase-2, -3, -6, -7, -8, -9, -10, -12). Remaining members of the caspase family participates in cytokine processing and inflammatory responses (Boyce et al., 2004; Lavrik et al., 2005; Zhivotovsky, 2003). Under normal physiological conditions caspases are constitutively expressed in the cytoplasm as zymogens with very low intrinsic activity. They become activated upon transcatalytic cleavage followed by dimerization. Specifically, cleaved molecules assemble to form a single heterotetramer with two active enzymatic sites in head-to-tail configuration (Earnshaw et al., 1999; Zhivotovsky, 2003). Once activated, caspases function in an orchestrated proteolytic cascade leading to self-amplification, cleavage of vital cell substrates, and ultimate cell disassembly (Fig. 2; Earnshaw et al., 1999; Zhivotovsky, 2003). Several methods were developed to detect activation of caspases by flow and laser scanning cytometry (thoroughly reviewed in Darzynkiewicz et al., 2001b, 2004; Telford et al., 2004). Here, we outline two commonly used techniques based on the affinity labeling of the caspase active centers and cleavage of the poly (ADP-ribose) polymerase (PARP).

1. Fluorochrome-Labeled Inhibitors of Caspases (FLICA) Use of fluorochrome-labeled inhibitors of caspases (FLICA, recognized also under commercial names: CaspaTag, CaspACE, CaspGLOW, FLIVO) allows for a

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[(Fig._6)TD$IG]

Fig. 6

Activation of caspases. (A) Detection of caspases activation by fluorescently labeled inhibitors of caspases (FLICA) combined with plasma membrane permeability assessment (propidium iodide; PI).Human Bcell lymphoma cells were either untreated (Ctrl) or treated with Brefeldin A (BFA) to induce apoptosis as described (Wlodkowic et al., 2007a). Cells were subsequently supravitally stained with FAM-VAD-FMK (pan caspase marker; FLICA) and PI. Their logarithmically amplified green and red fluorescence signals were measured by flow cytometry. Live cells (V) are both FAM-VAD-FMK and PI negative. Early apoptotic cells (A) bind FAM-VAD-FMK but exclude PI. Late apoptotic/secondary necrotic cells (LA) are both FAM-VADFMK and PI positive. Primary necrotic and some very late apoptotic cells (N) stain with PI only. (B) Detection of PARP cleavage combined with DNA content (cell cycle) analysis. To induce apoptosis, HL-60 cells were treated with TNF-a in the presence of CHX for 30–360 min (Li and Darzynkiewicz, 2000). Upper panel shows immunoblots of the treated cells, stained with PARP plus PARP p89 (upper gel) or PARP p89 only (lower gel) Abs.Lower panelsshowbivariatedistributionsofPARPp89versusDNAcontent(stainedwithPI)oftheuntreated (Ctrl) and treated for 30 and 60 min cells. Note the appearance of the first PARP p89 positive cells already after 30 min of treatment, coinciding in time with the detection of PARP cleavage on gels. There is no evidence of cell cycle phase specificity of apoptosis induced by TNF-a. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of the chapter.)


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convenient estimation of apoptosis by both cytometry and fluorescence microscopy (Figs. 5B and 6A; Bedner et al., 2000; Smolewski et al., 2001). FLICAs were designed as affinity ligands to active centers of individual caspases (Bedner et al., 2000; Pozarowski et al., 2003; Smolewski et al., 2001). Each molecule has three functional domains: (i) the fluorochrome (carboxyfluorescein, FAM; fluorescein, FITC; or sulforhodamine, SR), (ii) the caspase recognition element comprising of a four amino-acid peptide, (iii) the chloro- or fluoromethyl ketone (CMK or FMK) binding moiety (Bedner et al., 2000; Pozarowski et al., 2003). The specificity toward individual caspases is provided by the recognition element. Currently, several FLICA kits are commercially available. The most common contains the valylalanyl-aspartic acid residue sequence (VAD). The VAD sequence allows binding to activated caspase-1, -3 -4, -5, -7, -8, and -9 providing a pan-caspase marker. Other inhibitors were subsequently developed and contain DVAD, DEVD, VEID, YVAD, LETD, LEHD, or AEVD peptide residues. They preferentially bind to activated caspase-2, -3, -6, -1, -8, -9, or -10, respectively. After docking of the FLICA molecule to the caspase active center, the FMK reacts with the active cysteine and forms a thiomethyl ketone (Thornberry et al., 1997; van Noorden, 2001). This irreversible, covalent reaction is deemed to inactivate the target enzyme. Presence of the fluorescent tag (FITC or SR) allows detection of FLICA–caspase complexes inside the cells. FLICAs are highly permeant to plasma membrane and relatively nontoxic. This provides a unique opportunity to detect caspase activation in living cells where uptake of these reagents is followed by covalent binding to activated caspases. To date, no interference resulting by MDR efflux pump activity has been reported for FLICA uptake. Unbound FLICAs are readily removed from the cells that lack caspase activity by rinsing with PBS buffer. When FLICAs are applied together with the plasma membrane permeability marker PI, several consecutive stages of apoptosis can be distinguished (Fig. 6A) (Pozarowski et al., 2003; Smolewski et al., 2001). Green fluorescent FLICAs (FAM, FITC) can also be used together with Dcm sensitive probes, such as MitoTracker Red CMXRos and TMRM as shown in Fig. 5B (Pozarowski et al., 2003; Wlodkowic et al., 2006). Moreover, other multiplexing combinations are compatible with both single and multilaser instrumentation. Because intracellular binding is covalent, FLICAs withstand cell fixation (with formaldehyde) and subsequent cell permeabilization with ethanol and methanol. As a result, this assay can be combined with the analysis of cell attributes that can require prior cell permeabilization such as DNA content measurement, DNA fragmentation (TUNEL assay), and so on. Recent reports shed, however, new light onto the FLICA binding mechanistic during apoptosis and cast doubts onto their absolute specificity toward caspase active centers (Kuzelova et al., 2007; Pozarowski et al., 2003). Namely, in apoptotic cells only a minor proportion of total FLICA binding was attributed to their FLICA–caspase interactions (Pozarowski et al., 2003). Likewise there is also no significant competition for the binding sites between FLICAs and unlabelled

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caspase inhibitors (e.g., z-VAD-fmk, z-DEVD-fmk) that are based on the same principle (Pozarowski et al., 2003). In the recent report, Kuzelova et al. (2007) confirmed that the overall fluorescence intensity of apoptotic cells labeled with FLICA does not reflect unique binding to caspase active centers. Moreover, FLICA appears to be incapable to arrest apoptosis a feature that initially formed the basis of ‘‘stathmo-apoptosis’’ assay (Pozarowski et al., 2003; Smolewski et al., 2002). These inconsistencies may be due to contamination of the early batches of FLICAs with the unlabelled caspase inhibitors. It remains evident, however, that other cellular constituents apart from caspase active centers contribute to FLICA staining. As FLICA reagents withstand fixation, this strongly suggests covalent interactions with the intracellular targets becoming accessible in the course of apoptosis (Darzynkiewicz and Pozarowski, 2007; Kuzelova et al., 2007; Pozarowski et al., 2003). The reactivity of FMK moiety with intracellular thiols may provide some explanation of these interactions. In this context, opening of the disulfide cysteine bridges (inter- and/or intramolecular) may provide as yet unidentified affinity sites (Darzynkiewicz and Pozarowski, 2007). Noncovalent hydrophobic interactions between fluorochrome domain and intracellular targets have also been postulated to play a role in FLICA retention (Pozarowski et al., 2003). It should be stressed that the covalent labeling of apoptotic cells with FLICA make these probes, called FLIVO, the markers of choice for detection of apoptosis in vivo, both in real time and after fixation of the tissue (Griffin et al., 2007). In any case FLICA reagents have proven to be reliable and sensitive markers of apoptotic cell death. Necrotic cells do not exhibit FLICA staining and caspase-3 activation assay correlates well with results obtained by FLICA. Recently published data suggest also their superior applicability in a plethora of multiparametric applications. Nevertheless, in light of recent reports one should be aware that staining with FLICA apparently does not represent affinity labeling of individual caspase active centers (Darzynkiewicz and Pozarowski, 2007; Pozarowski et al., 2003). The alternative approach for assessment of caspases activation involves the use of caspase substrates that upon cleavage generate fluorescent products (Lee et al., 2003; Telford et al., 2002). Another assay is based on the use of substrates consisting of two variants of fluorescent protein that differ in emission spectrum connected with a peptide linker whose cleavage by caspase leads to a loss of fluorescence resonance energy transfer (FRET) between the respective fluorescent proteins (He et al., 2004; Lee and Segal, 2004). It should be underscored that the use of labeled or unlabeled caspase inhibitors as well as caspase substrates poses uncertainty with respect to their specificity. The tetrapeptide moiety of these reagents is designed to confer their specificity. However, in studies of live cells they are used at four orders of magnitude higher concentration (20–50 mM) than their binding constants (0.2–2.2 nM) estimated on isolated caspases (Thornberry et al., 1997). Since their intracellular concentration and in situ accessibility to active caspase centers are unknown the published data


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on specificity of individual caspases detection should be in treated with a reservation. Immunocytochemical detection of activated (cleaved) caspases essentially has no problems with specificity provided that the antibody does not cross-react with other proteins. Antibodies to different activated caspases are available from variety of vendors. Flow cytometric analysis of immunocytochemically detected caspase-3 activation concurrently with DNA content (cell cycle analysis) has been reported most frequently (e.g., Pozarowski et al., 2003; Tanaka et al., 2007).

2. Detection of PARP Cleavage Another approach to study caspase activation is based on the analysis of the cleavage of specific caspase substrates. In this context, PARP is known as one of the characteristic endogenous ‘‘death substrates.’’ PARP is a nuclear enzyme involved in DNA repair that is activated in response to DNA damage (de Murcia and Menissier-de Murcia, 1994). Following initiation of proteolytic cascade, PARP is cleaved by executioner caspase-3 and -7, which is considered as hallmark of classical apoptosis (Alnemri et al., 1996; Kaufmann et al., 1993; Lazebnik et al., 1994). The specific cleavage results in generation of 89- and 24-kDa fragments that can be easily detected on Western blots. An antibody that recognizes the 89-kDa product of PARP cleavage has been adapted to label apoptotic cells for detection by both flow and laser scanning cytometry (Li and Darzynkiewicz, 2000). Since measurement of DNA content provides valuable information about the cell cycle position and DNA ploidy, attempts have been made to combine PARP cleavage assay with DNA labeling. Multiparameter analysis of the cells differentially stained for PARP p89 and DNA and correlating apoptosis with the cell cycle phase is shown in Fig. 6B (Li and Darzynkiewicz, 2000; Li et al., 2000). Because of the immunocytochemical detection principle, the assay requires prior cell fixation (with formaldehyde) and subsequent permeabilization (usually with ethanol). It should be stressed that the methanol-free formaldehyde obtained by hydrolysis of paraformaldehyde is often incorrectly named ‘‘paraformaldehyde.’’ Paraformaldehyde is the condensed, polymerized, solid state of formaldehyde. Since alcohol preserved samples may be stored for extended periods of time, this assay is particularly suitable for analysis of archive sample collections. Extensive kinetic studies are also straightforward as cells may be collected, fixed at the respective time intervals, and subsequently mass analyzed. Bias related to differential labeling conditions and/or progression of apoptotic cascade during the period of cell preparation is thus avoided. It should be noted that to enhance permeability of plasma membrane and to increase accessibility of the detected epitope (e.g., the cleaved 89kDa form of PARP) to the primary Ab (and also to secondary Ab, if needed) a nonionic detergent (e.g., Triton X-100) at final concentration 0.1% into the solution containing Ab is often included, together with the blocking reagent (1% w/v bovine serum albumin).

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To preserve physiological functions each cell strives to maintain an intact plasma membrane. The preservation plasma membrane integrity until late stages of cellular disintegration is also a distinctive feature of apoptosis that differentiate this process from accidental cell death, necrosis (Darzynkiewicz et al., 1997, 2004; Majno and Joris, 1995). Plasma membrane represents, thus, an active and dynamic organelle that plays an important part in the cascade of signaling events leading to a final removal of dying cell. However, alterations in both lipid composition and permeability to small cationic probes have been reported as relatively early signs of apoptotic cascade (Idziorek et al., 1995; Koopman et al., 1994; van Engeland et al., 1998). These usually follow Dcm collapse, caspase activation and chromatin condensation but precede nuclear disassembly and DNA laddering (van Engeland et al., 1998). Here, we describe common markers for both hallmarks that allow convenient analysis of live cells by flow cytometry.

1. Externalization of Phosphatidylserine A characteristic feature of healthy cell is the asymmetric distribution of plasma membrane phospholipids between inner and outer leaflets. Under physiological conditions, choline phospholipids (phosphatidylcholine, sphingomyelin) are exposed on the external leaflet while aminophospholipids (phosphatidylserine, phosphatidylethanolamine) are exclusively located on the cytoplasmic surface of the lipid bilayer. This asymmetry is scrambled during apoptosis when PS, constituting less than 10% of the total membrane phospholipids, becomes exposed on the outside leaflet of the membrane (Fadok et al., 1992; Koopman et al., 1994; van Engeland et al., 1998). Exposition of PS on cell surface provides signaling to macrophages, which then become attracted and initiate to phagocytize apoptotic cells and apoptotic bodies. The detection of exposed PS allows for a precise estimation of apoptotic incidence. The assay usually employs fluorochrome-tagged 36kDa anticoagulant protein Annexin V (van Engeland et al., 1998). This probe reversibly binds to PS residues in the presence of millimolar concentration of divalent calcium ions. Annexin V conjugated to fluorochromes of different absorption and emission wavelength has found many applications as a marker of apoptotic cells, in particular for their detection by flow cytometry and fluorescence microscopy (van Engeland et al., 1998; Van Genderen et al., 2006). Noteworthy, a C2A domain of Synaptotagmin I exhibits similar properties to Annexin V and was successfully used in cytometric applications (Jung et al., 2004). The cells become reactive with Annexin V prior to the loss of the plasma membrane’s ability to exclude cationic dyes such as PI or 7-aminoactinomycin D (7-AAD). Thus, when using Annexin V in conjunction with plasma membrane permeability marker a distinction can be made between live, apoptotic, and late apoptotic/secondary necrotic cells. Live cells stained with fluorochrome-tagged Annexin V and PI, have minimal Annexin V fluorescence and minimal PI fluorescence. At the early


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stages of apoptosis, cells stain brightly with Annexin V but still exclude PI. Finally, when apoptotic cascade advances to later stages, the secondary necrotic cells stain intensely with both probes. Of note the primary necrotic cells will also fall into the last group as Annexin V will penetrate cells with ruptured membrane and stain PS residues displayed on the inner leaflet of the plasma membrane. Moreover, cells with severely damaged membranes and very late apoptotic cells stain rapidly and strongly with PI and may not exhibit Annexin V staining. It should also be mentioned that even intact and live cells may become permeable to PI upon prolonged incubation times. Therefore, cytometric analysis should be performed shortly after addition of this dye. Our recent studies revealed also that the time-window of apoptosis detected by FLICA binding is much wider than by the Annexin V binding (Pozarowski et al., 2003). These data also suggest that activation of caspases is a prerequisite for externalization of PS since essentially no FLICA-negative cells that bind Annexin V are apparent (Pozarowski et al., 2003). Although commonly applied, the interpretation of results from Annexin V assay may be difficult after mechanical disaggregation of tissues to isolate individual cells, enzymatic (e.g., by trypsinization) or mechanic detachment (e.g., by ‘‘rubber policeman’’) of adherent cells from culture flasks, cell electroporation, chemical cell transfection, or high-titer retroviral infections. All these conditions have been reported to influence PS flipping and introduce substantial experimental bias. Interestingly, a high surface expression of PS has also been detected on some healthy cells such as differentiating monocytes, activated T cells, positively selected B lymphocytes, activated neutrophils, or myoblasts fusing into myotubes (Callahan et al., 2003; Elliott et al., 2005; van den Eijnde et al., 2001; Van Genderen et al., 2006). Furthermore, as PS serves as ‘‘eat me’’ signal for professional phagocytes, healthy macrophages/monocytes, become Annexin V positive upon ingestion of apoptotic bodies. In all these instances Annexin V binding may be mistakenly identified as a marker of apoptotic cells leading to false-positive identification of nonapoptotic cells (Marguet et al., 1999). Noteworthy, there are increasing examples of programmed cell death proceeding without exposure of PS, which may bring in false-negative bias when relying solely on Annexin V assay (King et al., 2000). Currently, a range of Annexin V conjugates with organic fluorescent probes is commercially available with the predominant popularity of FITC, PE, and APC conjugates. There is also a considerable interest in inorganic, semiconductor nanocrystals (Quantum Dots; QDs) conjugates (Dicker et al., 2005; Le Gac et al., 2006). Their significant advantages over currently available organic fluorochromes are rapidly attracting attention in both cytometric and imaging applications (Chattopadhyay et al., 2006; Jaiswal and Simon, 2004; Jaiswal et al., 2003). Moreover, a recent development from Alexis-Axxora introduced fluorescently labeled monoclonal antibodies against PS residues that can be used instead of Annexin V. This new class of reagents reportedly alleviates dependence on

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calcium-supplemented buffers without compromising sensitivity of detection. Progress is also being made in the field of inorganic zinc coordination complexes (fluorescent Zn2+–dipicolylamines, DPA) that under Ca2+-free conditions selectively bind to membranes enriched in anionic phospholipids (Hanshaw et al., 2005; Koulov et al., 2003). Finally, a small cationic molecule merocyanine 540 (MC540) can reportedly be used to detect apoptotic cells based on the altered phospholipids composition (Laakko et al., 2002).

2. Changes in Plasma Membrane Permeability Externalization of anionic phospholipids is not a sole hallmark occurring early during apoptosis at the cell surface. Structural integrity and most of the plasma membrane transport function are preserved during the early phase of apoptosis. However, the permeability to certain fluorochromes, such as 7-AAD, Hoechst 33342, or Hoechst 33258 is increased (Ormerod et al., 1993; Schmid et al., 1992, 2007). Recent work by Idziorek et al. (1995) also revealed that following initiation of apoptotic cascade plasma membrane becomes selectively permeable to small, cationic molecules such as cyanine dyes. At the same time it remains impermeable to larger cations such as PI or 7-AAD. Live, noninduced to apoptosis cells, exclude both classes of probes. As a result, a new assay has been developed based on green florescent YO-PRO 1 and more recently violet fluorescent PO-PRO 1 cyanine probes (Idziorek et al., 1995). Of note, violet excitable PO-PRO 1 probe features similar properties to YO-PRO 1 and can provide increased multiplexing capabilities on highend analyzers. The assay is rapid and only short incubation (20 min, at RT) is required to supravitally discriminate viable cells (YO-PRO 1neg/PIneg events) from early apoptotic cells characterized by initial cell membrane permeabilization (YOPRO 1+/PIneg events). Cells in late stages of apoptosis and primary necrotic cells are characterized by pronounced loss in cell membrane integrity, and are thus permeable to both YO-PRO 1 and PI probes (YO-PRO 1+/PI+ events) (Idziorek et al., 1995; Wlodkowic et al., 2007a). Some reports have recently postulated that entry of YO-PRO 1 cation (629 Da) into early apoptotic cell depends on the activation of P2X7 ion-gated channel, event concurrent with scramblase activation and PS externalization (Holme et al., 2007). Early changes in lipid composition, structural relaxation, and/or impaired active dye efflux cannot, however, be also excluded as similar hypotheses have previously been raised for bisbenzimide dye, Hoechst 33342 (Idziorek et al., 1995; Ormerod et al., 1993; Schmid et al., 2007). Interestingly, our recent studies revealed that the time-window of apoptosis detected by YO-PRO 1 when analyzed by multiparameter flow cytometry is substantially wider than assessed by Annexin V binding (Wlodkowic et al., 2007a; unpublished data). Comparable results are also often achieved when Dcm selective probe TMRM is used in conjunction with YO-PRO 1 (Wlodkowic et al., 2007a). These observations reinforce the notion that YO-PRO 1 is a convenient and sensitive marker of


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early apoptotic events. Caution should be, however, exercised as dye uptake and/ or efflux may vary between different cell types and some cells may not exhibit differential staining with YO-PRO 1 and PI. This holds to be especially true in cells of murine origin such as FL5.12, BaF3, and primary fetal-liver progenitors (Wlodkowic et al., unpublished data). Result achieved by means of YO-PRO 1 or PO-PRO 1 may, thus, introduce false-negative bias if not confirmed by other methods. Finally, similar to the Annexin V binding assay, the interpretation of results from YO-PRO 1 assay may be difficult after enzymatic (e.g., by trypsinization) or mechanic detachment (e.g., by ‘‘rubber policeman’’) of adherent cells from culture flasks, cell electroporation, chemical cell transfection, or high-titer retroviral infections. Furthermore, some drugs or culture conditions may distort lipid bilayer structure leading to enhanced permeability in the absence of apoptosis. It is always advisable to test selective uptake of cyanine dyes by apoptotic cells in every new experimental system. E. Nuclear Hallmarks of Apoptosis Upon initiation of executioner caspase-3 and -7, caspase-activated DNase (CAD/DFF40) becomes activated by the cleavage of its putative inhibitor (ICAD/DFF45) (Enari et al., 1996). CAD translocates then to the nucleus where its activity leads to characteristic DNA fragmentation (Arends et al., 1990; Kerr et al., 1972; Nagata, 2000). Although CAD is the best-characterized enzyme, DNase-I, DNase-II, DNase-X, and AIF are also postulated in the execution of DNA degradation (Barry and Eastman, 1993; Los et al., 2000; Peitsch et al., 1993; Sussin et al., 1999). Apoptotic DNA fragmentation proceeds in three consecutive steps: (i) type-I DNA fragmentation (high molecular weight fragmentation to 0.05–1 Mb sections); (ii) type-II DNA fragmentation (intermediate fragmentation to 300 kb sections); and (iii) type-III DNA fragmentation (internucleosomal fragmentation to mono- and oligonucleosomal sections). The latter is often detected by a characteristic pattern during agarose DNA electrophoresis (DNA-ladder) and considered as a hallmark of apoptosis (Nagata, 2000; Nagata et al., 2003). Of note, DNA fragmentation during classical apoptosis may be terminated at 50–300 kb fragments. As a result characteristic ‘‘DNA-ladder’’ is absent due to a lack of internucleosomal-sized fragments (Darzynkiewicz et al., 1997; Oberhammer et al., 1993). Not surprisingly DNA fragmentation provided basis for two commonly used cytometric assays that allow identification of apoptotic cells: (i) estimation of fractional DNA content (sub-G1 fraction; Gong et al., 1994; Nicoletti et al., 1991; Umansky et al., 1981) and (ii) labeling of DNA strand breaks (DSBs) with fluorochrome-tagged deoxynucleotides by exogenous terminal deoxynucleotidyltransferase, TdT (TUNEL; Gorczyca et al., 1992, 1993; Li and Darzynkiewicz, 1995; Li et al., 1996) (Fig. 7).

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Fig. 7 DNA fragmentation analysis. (A) Detection of fractional DNA content (‘‘sub-G1’’ peak). Apoptosis of human follicular lymphoma cells was induced with dexamethasone (Dex). Ethanol-fixed and propidium iodide (PI)-stained cells were analyzed on a flow cytometer. Red fluorescence of PI was collected using linear amplification scale. Debris were gated out electronically. Note distinctive sub-G1 peak. For further details refer to text. (B) Detection of DNA strand breaks (‘‘TUNEL’’ assay) using different deoxynucleotides. Apoptosis of HL-60 cells was induced by camptothecin, which selectively targets Sphase cells (Li and Darzynkiewicz, 1995). In the reaction catalyzed by terminal deoxynucleotidyl transferase, the DNA strand breaks were labeled (from right to left): directly with FITC and BODIPY-conjugated dUTP, or indirectly with biotinylated (biot) dUTP detected by FITC-avidin, digoxygenin-conjugated dUTP detected by digoxygenin-FITC Ab, and with BrdUTP detected by FITC-BrdU Ab. The highest resolution provides labeling with BrdUTP. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of the chapter.)

1. Assessment of Fractional DNA Content (Sub-G1 Fraction) The fragmented, low molecular weight DNA can be extracted from cells during the process of cell staining in aqueous solutions. Such extraction takes place when the cells are treated with detergent and/or hypotonic solution instead of fixation, to make them permeable to fluorochrome. Alternatively fixation in precipitating fixatives such as ethanol can be used for the same purpose. Fixation with crosslinking fixatives such as formaldehyde, on the other hand, results in the retention of low molecular weight DNA in the cell as they become crosslinked to intercellular proteins. Therefore, a formaldehyde fixation is incompatible with the ‘‘sub-G1’’


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assay. As a result of DNA extraction, apoptotic cells exhibit a deficit in DNA content. Following staining with a DNA-specific fluorochrome they can be recognized by cytometry as cells having fractional DNA content. On the DNA content frequency histograms it is often characterized by a distinctive ‘‘sub-G1’’ peak (Fig. 7A, Gong et al., 1994; Nicoletti et al., 1991; Umansky et al., 1981). Interestingly, apoptotic DNA fragmentation detected by several distinctive sub-G1 peaks has recently been reported as a discontinuous process, relaying on sequential activation of different deoxynucleases and also modulated by chromatin structure (Kajstura et al., 2007). Optimally, the ‘‘sub-G1’’ peak representing apoptotic cells should be separated with little or no overlapping from the G1 peak of the nonapoptotic cell population. However, the degree of low molecular weight DNA extraction varies markedly depending on the extent of DNA degradation (duration of apoptosis), the number of cell washings, pH, and molarity of the washing/staining buffers. Shedding of apoptotic bodies containing fragments of nuclear chromatin may also contribute to the loss of DNA from apoptotic cells. As a result, the separation of ‘‘sub-G1’’ is not always satisfactory. On the other hand, when DNA degradation does not proceed to internucleosomal regions but stops after generating 50–300 kb fragments (Oberhammer et al., 1993), little DNA can be extracted. This method fails, thus, to detect such atypical apoptotic cells. Furthermore, the loss of DNA from G2/M and late S-phase cells undergoing apoptosis, may be inadequate to generate clear ‘‘sub-G1’’ peak. In such situations cells often end up with DNA content equivalent to that of G1 or early S phase and are indistinguishable during cytometric analysis. Noteworthy, a reduced stainability with DNA fluorochromes, that resembles fractional DNA content, may be present during cell differentiation or even necrosis (Darzynkiewicz et al., 1984; Oberhammer et al., 1993). Unfortunately numerous investigators still apply sub-G1 analysis as the sole method for enumeration of apoptotic cells. Because without additional assays fractional DNA content cannot be used as decisive marker of cell death caution should be exercised interpreting such data. It is a common practice to use detergents or hypotonic solutions instead of fixation in DNA staining protocols (Nicoletti et al., 1991). This simple approach causes lysis of plasma membrane and nuclear isolation and yields excellent resolution for DNA content analysis. When used to quantify apoptotic cells, however, this method is poised to generate a significant bias. Namely, nuclei of apoptotic cells are often fragmented and upon cell lysis a multiplicity of chromatin fragments/nuclear bodies are released from a single cell. Lysis of mitotic cells additionally releases individual chromosomes and/or chromosome aggregates. Furthermore, after cell irradiation or treatment with clastogens the generated micronuclei are often released during hypotonic procedures. As a result, each nuclear fragment, chromosome or micronucleus is recorded by flow cytometer as an individual object with sub-G1 DNA content. Such objects are then erroneously classified as individual apoptotic cells. This bias is particularly pronounced when logarithmic scale is used to display DNA content on the histograms, which allows one to detect objects with minute DNA content such as 0.1% of that of G1 cells. These events certainly cannot be classified as individual apoptotic nuclei, and their percentage overestimates the actual percentage of apoptotic cells in the sample.

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2. Assessment of DNA Strand Breaks (TUNEL Assay) DNA fragmentation during apoptosis generates a multitude of DSBs in the nucleus (Arends et al., 1990; Oberhammer et al., 1993). The 30 -OH termini of the breaks may be marked by attaching a fluorochrome to them. This is generally done directly or indirectly (e.g., via biotin or digoxygenin) by using fluorochrome-labeled triphosphodeoxynucleotides in a reaction catalyzed preferably by exogenous terminal deoxynucleotidyltransferase (Gorczyca et al., 1992, 1993; Li and Darzynkiewicz, 1995; Li et al., 1996). The reaction is commonly known as TUNEL from ‘‘TDT-mediated dUTP-biotin nick-end labeling’’ (Gavrieli et al., 1992). This acronym is a misnomer since the double strand breaks are labeled rather than the single strand nicks. Furthermore, other than dUTP deoxynucleotides are often used in this assay. Of all the deoxynucleotides BrdUTP appears to be the most advantageous to label DSBs, in terms of high sensitivity, low cost and simplicity of the assay (Li and Darzynkiewicz, 1995; see Fig. 7B). BrdU attached to DSBs (as poly-BrdU) is detected with an FITC-conjugated anti-BrdU Ab; the very same Ab that is used to detect BrdU incorporated during DNA replication (Fig. 7B). PolyBrdU at the DSBs, however, is accessible to the Ab without acid- or heat-induced DNA denaturation, which otherwise is needed to detect the precursor incorporated during DNA replication. The detection of DSBs by this assay requires cell prefixation with a crosslinking reagent such as formaldehyde, which unlike ethanol, prevents the extraction of small DNA fragments. Labeling DSBs in this procedure, which utilizes fluorescein-conjugated anti-BrdU Ab, can be combined with staining of DNA with the fluorochrome of another color (PI, red fluorescence). Cytometry of cells that are differentially stained for DSBs and for DNA allows one to distinguish apoptotic from nonapoptotic cell subpopulations and reveal the cell cycle distribution in each of these subpopulations (Fig. 7B; Gorczyca et al., 1992, 1993). Since late apoptotic cells may have diminished DNA content because of prior shedding of apoptotic bodies or due to such extensive DNA fragmentation that small DNA fragments cannot be retained in the cell after fixation with formaldehyde such cells may have sub-G1 DNA content and be TUNEL-positive. Several types of kits are commercially available, which utilize either directly fluorochrome-tagged triphospho deoxynucleotides or BrdUTP and BrdU Ab. The extensive DNA fragmentation during apoptosis, similar to radiation-induced DNA breakage, leads to an early attempts by the cell to repair the damage that manifests by activation of Ataxia Telangiectasia mutated protein kinase (ATM) and phosphorylation of histone H2AX on Ser-139. Both ATM activation as well as H2AX phosphorylation can be detected immunocytochemically by phosphospecific antibodies (Huang et al., 2005; Kurose et al., 2005; Tanaka et al., 2007). The extent of H2AX phosphorylation in early apoptotic cells is extremely high, by an order of magnitude higher than the maximal level that can be induced by the DNA damaging drugs or radiation (Kurose et al., 2005). Multiparameter cytometric analysis of H2AX phosphorylated on Ser-139 concurrently with DNA content makes


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it thus possible to identify subpopulations of cells with primary DSBs induced by the drug or radiation versus the cells with secondary, apoptosis-associated DSBs, and characterize cells in each subpopulation with respect to cell cycle phase (Kurose et al., 2005). F. SYTO-Based Detection of Apoptosis Progress in the modern field of cell necrobiology necessitates exploitation of novel methods that support high-throughput and multivariate analysis of critical cellular parameters at a single cell level (Darzynkiewicz et al., 1997, 2001b, 2004). To this aim diverse cytometric assays have been introduced, as described in previous sections of this chapter. Some of them include cell permeant DNA selective stains, such as Hoechst 33342, DRAQ5, and, more recently, probes from Vybrant DyeCycle family (Haughland, 2005; Schmid et al., 2007; Smith et al., 2000). All allow staining of unfixed cells and restrict cumbersome procedures to a simple step. To date, however, live-cell assays based on cell permeant DNA selective probes suffered mostly from their unfavorable spectral characteristics that necessitate UV excitation source and dedicated optics. Excessive toxicity/phototoxicity precludes also long-term studies such as cell sorting with subsequent cell cultivation (Durand and Olive, 1982; Fried et al., 1982; Martin et al., 2005). Nevertheless, progress has recently been made by the development of cell permeant, cyanine SYTO stains. This novel class of probes spans a broad range of visible excitation and emission spectra: (1) SYTO blue (Ex/Em 419–452/445–484 nm); (2) SYTO green (Ex/Em 483–521/ 500–556 nm); (3) SYTO orange (Ex/Em 528–567/544–583 nm); and (4) SYTO red (Ex/Em 598–654/620–680 nm) (Frey, 1995; Haughland, 2005). Exploitation of SYTO probes to cytometric detection of apoptosis started in 1990s (Frey, 1995; Poot et al., 1997) and is slowly gaining appreciation as an easy to perform, live-cell assay (Poot et al., 1997; Schuurhuis et al., 2001). Although, the fundamental mechanism underlying differential staining of SYTO-labeled apoptotic versus viable cells still remains uncertain, several hypotheses have been raised in the recent years (reviewed in Wlodkowic and Skommer, 2007). Following initiation of caspase-dependent apoptosis cells loaded with selected SYTO stains exhibit gradual reduction in fluorescence signal intensity to dim values. This phenomenon substantially precedes plasma membrane permeability changes (Fig. 9) (Frey, 1995; Poot et al., 1997; Wlodkowic et al., 2007b). Evidence from recently published data indicate an overall higher sensitivity of SYTO probes in detection of early apoptotic events as compared to Annexin V-based assays (Eray et al., 2001; Schuurhuis et al., 2001; Sparrow and Tippett, 2005). When progression toward the terminal stages of cellular demise advances, loss of SYTO fluorescence intensifies, and this usually coincides with the increased plasma membrane permeability to PI and 7-AAD (Poot et al., 1997; Schuurhuis et al., 2001; Wlodkowic et al., 2007b). Fig. 8 illustrates results obtained from a green fluorescent SYTO 11 probe used in conjunction with plasma membrane permeability marker PI. Both probes are exited by 488 nm line permitting their concomitant application on

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Fig. 8 Detection of apoptosis by SYTO 11 probe. Human B-cell lymphoma cells were untreated (left panel) or treated with dexamethasone (right panel), as described (Wlodkowic et al., 2007b). Cells were subsequently supravitally stained with SYTO 11 and PI probes. Their logarithmically amplified green and red fluorescence signals were measured by flow cytometry. Live cells (V) are SYTO 11bright and PI negative. Early apoptotic cells (A) are SYTO 11dim but still exclude PI. Late apoptotic/secondary necrotic cells (N) are both SYTO 11low and PI positive. Primary necrotic cells do not exhibit SYTOdim staining pattern and rapidly take up propidium iodide while loosing SYTO to low values (not shown; Wlodkowic et al., 2007b). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of the chapter.)

single laser analyzers. The assay requires only a short incubation (20 min, at RT) to supravitally discriminate viable cells (SYTOhigh/PIneg events; V) and early apoptotic cells. The latter population is characterized by initial loss of SYTO 11 fluorescence and preservation of plasma membrane integrity (SYTOdim/PIneg events; A). Cells in later stages of apoptosis feature progressive loss of SYTO fluorescence and gain bright PI staining (SYTOneg/PI+ events; N) (Wlodkowic and Skommer, 2007; Wlodkowic et al., 2007b). Of note, the primary necrotic cells will also fall into the last group with minimal SYTO 11 and bright PI fluorescence. We have recently shown that yet another green fluorescent probe, SYTO 16 allows discrimination between primary and secondary necrotic cells (Wlodkowic et al., 2007b). Therefore, SYTO 16 provides substantial enhancement over the standard PI exclusion assay in discerning cell demise mode by flow cytometry (Wlodkowic et al., 2007b). Importantly, SYTO probes prove in many instances inert and safe for tracking cells over extended periods of time. This may open up new opportunities for single cell real-time analysis protocols by both fluorescent activated cell sorting (FACS) and Lab-on-a-Chip platforms. Recent noteworthy reports provided strong evidence that at least some SYTO probes can be substrates for MDR efflux pumps (e.g., P-glycoprotein; P-gp) (Schuurhuis et al., 2001; van der Pol et al., 2003). Caution should be, thus, exercised when using SYTO probes in cells with active ABC-class transporters. It is always advisable to confirm MDR status of studied cell population. In cells


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with active P-gp its inhibition (e.g., by verapamil hydrochloride, PSC833, cyclosporin A) is required to avoid masking of apoptotic SYTOdim subpopulation by SYTOdim subpopulation engendered by an active dye efflux (Schuurhuis et al., 2001; van der Pol et al., 2003). Truly apoptotic reduction of SYTO fluorescence to dim values is not affected by the presence of P-gp inhibitors (Schuurhuis et al., 2001). Moreover, one should always bear in mind that results obtained using SYTO-based assays may vary when compared to assays detecting different cellular processes. Results acquired with SYTO probes should, therefore, never be considered conclusive without verification by independent methods (Wlodkowic and Skommer, 2007; Wlodkowic et al., 2007b).

V. Time-Window in Measuring Incidence of Apoptosis Apoptosis is a stochastic event of a variable induction and execution kinetics. There is a short time-window when apoptotic cells display their characteristic features. Moreover, the induction and the onset of apoptosis vary strongly depending on the cell type. For instance HL-60 (human promyelocytic leukemia) and MCF-7 (human breast cancer) cells treated with the same DNA damaging agent can succumb to apoptosis between 2 and more than 24 h, respectively (Del Bino et al., 1999). In general, the induction time in cells of hematopoietic lineage is much shorter compared to other cell types, such as fibroblasts of cells of solid tumors lineage. This induction-to-execution interval profoundly varies depending on the stimulus applied (Li and Darzynkiewicz, 2000). Furthermore, the length of apoptosis (i.e., from the initiation to complete cell disintegration) is cell type dependent parameter. In vivo, under homeostatic conditions when cell death rate balances proliferation rate mitotic index (MI) is often seen to exceed apoptotic index (AI). This is an indication that duration of apoptosis is actually shorter than that of mitosis (the latter is about of 1 h duration) (Darzynkiewicz et al., 2004). In cell culture, however, apoptotic cells remain detectable for extended periods of time before complete disintegration. This reflects lack of phagocytic clearance that characterizes homotypic cell culture conditions. Identification of apoptotic cells generally relies on a specific marker that is detectable in variable time intervals. Knowledge of time-windows when specific markers are being detected is, thus, essential for the rational use of the methodology. In this context, loss of the mitochondrial transmembrane potential appears to be initially a transient event, followed by permanent collapse later during apoptotic cascade (Li et al., 2000). Depolarization of mitochondrial membrane is followed by activation of caspases while binding of fluorescently labeled inhibitors of caspases (FLICA) substantially precedes externalization of PS (Pozarowski et al., 2003; Wlodkowic et al., 2006). In HL-60 cells challenged with DNA damaging agents, for example, DNA fragmentation follows caspase activation indirectly detected by cleavage of PARP, by approximately 20 min (Li and Darzynkiewicz, 2000). Furthermore, at early stages of apoptosis cells negative for the fractional DNA

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content (sub-G1 fraction) may be positive in TUNEL assay and expose PS residues (Darzynkiewicz et al., 2001a). Common application of cytometry is a comparison made between incidences of apoptosis (AI) in different samples (Darzynkiewicz et al., 1997, 2001a, 2004). This task is particularly problematic in view of the above-discussed variability and the snapshot measurement of AI may fail to target comparable time-windows of apoptosis. Observed AI indices may, thus, not reflect the actual differences in apoptosis incidence between samples (Darzynkiewicz et al., 2004; Smolewski et al., 2002). Attempts have recently been made to obtain the cumulative AI, by measuring the rate (kinetics) of cell entrance into apoptosis and preventing disintegration of apoptotic cells (Smolewski et al., 2002). The alternative solution is to count the absolute number of cells in culture and account for cell loss while estimating the AI based on specific markers (Darzynkiewicz et al., 2004; Pozarowski et al., 2003).

VI. Multiparameter Detection of Apoptosis: Choosing the Right Method As discussed before, in view of recent seminal discoveries, the universal term ‘‘apoptosis,’’ has a propensity to misinterpret the actual phenotype of cell suicide program (Leist and Jaattela, 2001; Zhivotovsky, 2004). Nevertheless, single cytometric assays such as the estimation of sub-G1 fraction or Annexin V binding are still being exploited in many research articles. Moreover, data from such single assays are persistently referred to as ‘‘apoptotic cells.’’ One should remember, however, that positive identification of apoptotic cells is far from straightforward. Furthermore, the reliance on single cytometric readout without proper understanding of the underlying assay mechanistic may lead to profound artifacts. It was only recently proposed to define apoptosis as a ‘‘caspase-mediated cell death’’ (Blagosklonny, 2000). Logically, caspase activation would be the most specific marker of apoptosis (Shi, 2002). There are, however, many examples of cell death that resembles classical apoptosis yet there is no evidence of caspase activation (Joza et al., 2001; Leist and Jaattela, 2001; Lockshin and Zakeri, 2002). Extensive DNA fragmentation is also considered as a specific marker of apoptosis. The number of DSBs in apoptotic cells is usually so large that intensity of their labeling in the TUNEL assay ensures their discrimination from the cells that underwent primary necrosis (Gorczyca et al., 1992). As mentioned, the high degree of phosphorylation of histone H2AX on Ser139 in apoptotic cells makes it also possible to positively identify them (Kurose et al., 2005). There are, however, mushrooming examples where apoptotic or apoptotic-like cell death proceeds without extensive internucleosomal DNA degradation (Catchpoole and Stewart, 1993; Cohen et al., 1992; Collins et al., 1992; Knapp et al., 1999; Ormerod et al., 1994). In these instances, the intensity of cell labeling in TUNEL assay will be inadequate to positively identify apoptotic cells. Furthermore, estimation of the sub-G1 fraction fails when DNA degradation does not proceed to internucleosomal regions but stops after generating 50–300 kb


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fragments (Oberhammer et al., 1993). Little DNA can be extracted then from the cells and rigid reliance on this method provides false-negative results (Darzynkiewicz et al., 2001a, 2004). Noteworthy, if G2/M or even late S-phase cells undergo apoptosis, the loss of DNA from these cells may not produce the sub-G1 peak. These apoptotic cells often end up with DNA content equivalent to G1/early S phase and are, thus, indistinguishable (Darzynkiewicz et al., 2001a, 2004). Finally, while nuclear fragmentation is commonly observed during apoptosis of hematopoietic lineage cells, it may not occur in cells of epithelial- or fibroblast-lineage. Likewise, cell shrinkage, at least early during apoptosis, is not a universal marker of the apoptosis or necrosis, which has been discussed earlier in this chapter. There are many other difficulties and potential pitfalls in analysis of classical apoptosis by flow cytometry (thoroughly reviewed in Darzynkiewicz et al., 2001a, 2001b, 2004). Cell harvesting by trypsinization, mechanical or enzymatic cell disaggregation from tissues, extensive centrifugation steps, may all lead to preferential loss of apoptotic cells. On the other hand, some cell harvesting procedures interfere with apoptotic assays as discussed earlier in this chapter. Because of cell shrinkage the density of apoptotic cells is markedly increased while volume is diminished. This change should be taken under consideration, for example, when isolating cells by density (ficoll-hypaque, percoll) gradient centrifugations or elutriation. The most common problem, however, is the inability to distinguish late apoptotic cells (called also ‘‘necrotic phase of apoptosis’’ or ‘‘secondary necrosis’’) from the primary necrosis (accidental cell death). In both cases, the integrity of plasma membrane is lost and the cells cannot exclude cationic dyes such as propidium iodide or Trypan blue. The loss of cell surface antigens during apoptosis creates another problem in the studies aimed to identify the lineage of apoptotic cells by their immunophenotype (Philippe et al., 1997; Potter et al., 1999; Schmid et al., 1992). Antigen loss often occurs at early stages of apoptosis and selectively depends on the antigen and the inducer of apoptosis. Therefore, regardless of the apoptotic marker used, the attempts to identify lineage of apoptotic cells by immunophenotyping are prone to significant errors. All these potential pitfalls together with means to avoid them are discussed in extent elsewhere (Darzynkiewicz et al., 2001a, 2001b). Perhaps the most important feature of flow cytometry is the capability of multiparameter gating analysis, which allows one to quantitatively correlate, within the same cell, expression of several measured attributes. Divergent cellular processes can be, therefore, simultaneously assessed, which has profound practical implications in cell necrobiology studies. For instance, since DNA content is the most frequently measured attribute, the expression of other parameters can be then directly related to the position in the cell cycle phase and/or to DNA ploidy of the tumor cell population. Thus, flow cytometry overcomes a limitation of traditional bulk techniques based on analysis of total cell population (such as fluorimetry, spectrophotometry, Western blots, etc.) that average the results from heterogeneous samples. As discussed above, the preference of an optimal multiparametric method depends on the cell type, stimuli, desired information, and technical restrictions. For

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example, the need for sample transportation or prolonged storage prior to analysis requires cell fixation. This excludes the use of ‘‘supravital’’ methods such as the assays of plasma membrane integrity (exclusion of YO-PRO 1, PI, 7-AAD), PS exposure (Annexin V binding) or dissipation of mitochondrial membrane potential (JC-1, TMRM). At the same time, however, the cell fixation allows to obtain information on the cell cycle phase specificity of apoptosis by concurrent analysis of cellular DNA content. In this context considerable progress has recently been made by the introduction of amine reactive viability dyes (ViD) (InvitrogenMolecular Probes; Prefetto et al., 2006). These allow for a convenient discrimination of cells with intact and damaged plasma membrane in fixed specimens. Reportedly, ViD probes span a broad range of visible excitation and emission spectra. Their uptake by cells with permeabilized membranes is followed by covalent binding to cytoplasmic amine residues that withstand formaldehyde fixation and alcohol permeabilization procedures (Prefetto et al., 2006). Technical restrictions of the cytometer, such as a single laser excitation source, few fluorescence detectors may further limit number of multiplexing possibilities. Importantly, restricted number of organic fluorochromes that have nonoverlapping spectra hampers broader introduction of multiparameter approaches. This impasse has recently been superseded by the development of semiconductor nanocrystals (QDs). Their unrivalled specifications such as prolonged stability, reduced photobleaching, broad excitation with narrow emission spectra are poised to profoundly transform multicolor cell analysis (Jaiswal and Simon, 2004; Jaiswal et al., 2003). Successful attempts have already been made to implement semiconductor nanocrystals in multiparameter flow cytometry (Chattopadhyay et al., 2006). Undoubtedly, future applications of QDs in multiplexed cytometric detection of apoptosis are of substantial commercial interest (Dicker et al., 2005; Le Gac et al., 2006).

VII. Beyond Apoptosis – Analysis of Alternative Cell Death Modes Although detection of classical, caspase-dependent apoptosis is still the major ground for the advancement of cytometric techniques there is an increasing demand for novel analytical tools that can rapidly quantify noncanonical modes of cell death. Although still a matter of debate, these noncanonical pathways appear to have wide reaching connotations in pathogenesis and treatment of human diseases (Edinger and Thompson, 2004; Lockshin and Zakeri, 2001; Okada and Mak, 2004). Moreover, they present an increasingly complex network of molecular cross-talks reflecting in a diversity of phenotypes. A. Autophagy Autophagy is an intracellular bulk degradation system for long-lived proteins and whole organelles (Meijer and Codogno, 2009). Emerging evidence suggests that


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while autophagy may enhance survival of cancer cells exposed to nutrient deprivation, hypoxia or certain chemotherapeutics, it may also contribute to cell death when induced above an acceptable for cellular homeostasis threshold (EisenbergLerner et al., 2009). Accurate estimation of autophagosome formation and/or functional catabolic autophagy is, therefore, important for preclinical drug screening (Corcelle et al., 2009; Vousden and Ryan, 2009). To date only a handful of methods have been introduced to quantify autophagy, including electron and fluorescent microscopy to follow steady-state accumulation of autophagosomes, and long-lived protein degradation assay to access the catabolic autophagic activity (Gurusamy and Das, 2009; Swanlund et al., 2010). Fluorescent microscopy is generally used to follow autophagosome accumulation using markers such as LC3 protein tagged with fluorescent protein GFP. In this assay, after induction of autophagy, cytoplasmatically localized LC3-I is cleaved and lipidated to form LC3-II. The latter is associated with the formation of an isolation membrane (Gurusamy and Das, 2009). Using, for example, adenoviral delivery of LC3-GFP it is possible to follow the changes in LC3-GFP distribution from diffuse cytoplasmic into punctuate, the latter indicative of autophagosome accumulation with reasonable precision. Current methods designed to quantify autophagic activity using LC3 are, however, time consuming, labor intensive, and require substantial expertise in accurate data interpretation (Shvets and Elazar, 2009; Shvets et al., 2008). Several attempts have recently been made to quantify autophagy in cells stably expressing GFP-LC3 reporters using flow cytometry (Shvets and Elazar, 2009; Shvets et al., 2008). Flow cytometry collects, however, only integrated fluorescence over each cell. This in turn is generally not sensitive enough to detect subtle redistribution at a subcellular level. More recently, a successful attempt has been made to employ the multispectral imaging flow cytometry to quantify autophagosome formation (Lee et al., 2007). Authors utilized the ‘‘virtual sort’’ capability to enumerate cells exhibiting the bright, punctuate spots of GFP-LC3. The inflow imaging is the first example of an automated and unbiased detection of autophagy in rare subpopulations of cells (Lee et al., 2007). Surprisingly there have been no attempts to adapt Laser Scanning Cytometry (LSCTM , CompuCyte Corp, Cambridge, MA, USA) for multivariate quantification of autophagosome formation. LSC has many attributes of both flow cytometry and low-resolution image analysis that proved to be optimal for multiparameter studies of apoptotic cell death. We postulate that adaptation of LSC to detection of autophagy based on maximal pixel analysis of vesicular LC3-GFP protein might prove beneficial for high-throughput screening routines. By combining bivariate analysis of the DNA content and LC3-GFP redistribution one can potentially examine the cell cycle specificity of autophagosome formation, for example, in different tumor cell lines. Recently a new elegant solution has been proposed by Farkas et al. (2009) to measure the dynamics of autophagic flux. The design of a luciferase-based reporter assay (RLuc-LC3) allows to measure an autophagic flux in real time. Particular advantage of the RLuc-LC3 assay lies in a broad dynamic range and applicability to a dynamic analysis on cell population. This system has already been validated by

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screening a small-molecule kinase inhibitor library and results demonstrated its applicability for tracking of dose- and stimulus-dependent differences in autophagy kinetics (Farkas et al., 2009). B. Necrosis The recent discovery of alternative cell death modes such as necrosis-like PCD, necroptosis, and paraptosis calls for the development of new and robust markers to distinguish between molecularly divergent cell death processes (Br€ oker et al., 2005; Galluzzi and Kroemer, 2008; Hetz et al., 2005; Krysko et al., 2008). As discussed previously in this article, the cell impermeant DNA binding dyes such as PI, YOPRO 1, or SYTOX are very convenient markers for the detection of accidental cell death (primary necrosis) and late stages of apoptosis. They all fail, however, to distinguish whether the labeled population is of late apoptotic, primary necrotic, or necrosis-like PCD origin. Even in conjunction with other probes it is often a matter of speculation whether, for example, Annexin Vneg/PI+ or FLICAneg/PI+ population represents programmed necrotic phenomenon. This cannot be resolved by mere flow cytometric analysis. Recently, however, an innovative assay based on a high-mobility group B1 protein (HMGB1) has been proposed that can reportedly differentiate primary necrotic cells (Ito et al., 2006; Scaffidi et al., 2002). HMGB1 protein is an architectural chromatin-binding factor that bends DNA and promotes protein assembly on specific DNA targets (Scaffidi et al., 2002). It normally resides in the nucleus and is passively released when cells die during necrotic cell death. HMGB1 remains, however, tightly sequestered in cells undergoing caspase-dependent apoptosis or autophagic cell death (Fig. 9) (Ito et al., 2006; Scaffidi et al., 2002). Interestingly, even during secondary necrosis that follows caspase-dependent apoptosis cells do not release HMGB1 (Scaffidi et al., 2002). This unique process has been associated with the prevention of chromatin deacetylation during necrosis (Scaffidi et al., 2002). As such immunohistochemical detection of HMGB1 can be readily applied in both flow cytometry and imaging cytometry to detect and quantify cells undergoing primary and necrosis, necroptosis, and/or necrosis-like PCD (Fig. 9) (Ito et al., 2006; Krysko et al., 2008). C. Cell Senescence In many solid tumors the anticancer treatment instead of apoptosis induces irreversible impairment of cell reproductive capacity, which is defined either as ‘‘reproductive cell death,’’ ‘‘senescence-like growth arrest,’’ ‘‘accelerated senescence,’’ ‘‘premature senescence,’’ or ‘‘drug- or radiation-induced senescence’’ (Gerwitz et al., 2008; Ohtani et al., 2009). Overexpression of certain oncogenes and excessive mitogenic signaling can also lead to cell proliferation arrest characterized by senescence-like features. Both the induction of apoptosis as well as senescence play important role as the barriers to tumor development (Campisi, 2001). Normal cells become senescent in the course of organismal aging and also


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Fig. 9

Selective detection of necrosis using monoclonal antibody against a high-mobility group B1 protein (HMGB1). (A) Human osteosarcoma U2OS cells cultured on glass coverslips were induced to undergo necrosis (freeze/thawing cycle) or apoptosis (Tet-On p53). Cells were then fixed and stained with DAPI (blue) and anti-HMGB1 antibody (red). Note that HMGB1 normally resides in the nucleus and is passively released when cells die during primary necrosis. It remains, however, tightly sequestered in cells undergoing caspase-dependent apoptosis. Immunohistochemical detection of HMGB1 can be readily applied in both flow cytometry and imaging cytometry to detect and quantify cells undergoing primary and necrosis, necroptosis, and/or necrosis-like PCD. (B) Specific release of HMGB1 from necrotic cells can be detected using Western blot (WB) analysis. Necrotic cell death was induced in U2OS cells by repeated freeze/thawing cycle. Both cells and medium were then harvested and protein extracts analyzed using WB. Note that HMGB1 band is detected in the medium. (See plate no. 1 in the color plate section.)

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after completion of certain number of cell divisions in cultures as a result of telomere shortening (Hayflick, 1985). Several markers characterize senescent cells. The most characteristic are morphological alterations (Cristofalo and Pignolo, 1993). Senescent cells show low saturation density at the plateau phase of growth, ‘‘flattened’’ appearance, enlarged, often irregular nuclei and cytoplasmic granularities. Their increased overall size is paralleled by an increase in nuclear and nucleolar size. They have numerous vacuoles in the cytoplasm, increased number of cytoplasmic microfilaments, the presence of large lysosomal bodies, and prominent Golgi apparatus (Cristofalo and Pignolo, 1993; Funayama and Ishikawa, 2007). The prominent abnormality of nuclear chromatin of senescent cells is the presence of senescence-associated heterochromatic foci (SAHF) that are abundant in histone H3 modified at lysine 9 (K9M H3) and its binding partner heterochromatin protein 1 (HP1) (Li et al., 2007). Senescent cells are also characterized by expression of CDKs inhibitors p21WAF1, p16, and p27KIP1; the feature common but not specific to these cells (Shen and Maki, 2010). Among all biomarkers of cell senescence the most specific are the characteristic changes in cell morphology and the induction of senescence-associated b-galactosidase activity, the latter considered to be the hallmark of cell senescence (Dimri et al., 1995). An excellent review of the cytometric methods to identify senescent cells is provided by Hwang and Cho (Chapter 7). Most recently, the imaging analytical capabilities of LSC have been used to assess morphological features considered to be typical of the senescent phenotype (Zhao et al., 2010). The characteristic ‘‘flattening’’ of senescing cells was represented by the decrease in the density of staining (intensity of maximal pixel) of DNA-associated fluorescence (DAPI). This change was paralleled by an increase in nuclear size (area). The decline in ratio of maximal pixel to nuclear area was even more sensitive senescence biomarker than the change in maximal pixel or nuclear area, each alone (Fig. 10). Also, the saturation cell density at plateau phase of growth recorded by LSC was found to be dramatically decreased in cultures of senescent cells, thereby additionally serving as a convenient marker (Zhao et al., 2010). This morphometric approach utilizing LSC complements other cytometric methods to identify senescent cells reviewed by Hwang and Cho (Chapter 7).

VIII. Future Outlook Development of novel bioassays was the driving force for the immense progress in research in cell necrobiology field during the past two decades (Darzynkiewicz et al., 1997, 2001b, 2004). Paradoxically, despite all the advances in flow cytometry the morphological changes defined by light and electron microscopy back in 1972 are still being considered to be the ‘‘gold standard’’ for the identification of cellular demise mode. Although detection of classical, caspase-dependent apoptosis is still the major ground for the advancement of cytometric techniques there is an increasing demand for novel analytical tools to rapidly quantify noncanonical modes of cell death.


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Fig. 10 LSC-assisted morphometric analysis of nuclear changes of A549 cells in cultures treated with mitoxantrone (Mxt). The cells were untreated (Ctrl) or to induce cell senescence treated with 2 nM Mxt for 24, 48, or 72 h, their DNA was stained with DAPI. Intensity of maximal (max) pixel of DNA/DAPI reveals degree of chromatin condensation and in untreated cells has the highest value in mitotic (M) and immediately postmitotic (pM) cells (shown by the arrows). In the cells undergoing senescence while nuclear area increased, the intensity of maximal pixel decreased likely due to the ‘‘flattening’’ of the cell. The insets in the top left panels show DNA frequency histograms of cells from the respective cultures. The bar plots at the bottom panels show mean values (SD) of nuclear DNA/DAPI area, DNA/DAPI maximal pixel, and the ratio of maximal pixel to nuclear area. The ratio of maximal pixel/nuclear area of the Mxt-treated cells is expressed as a fraction of such ratio of the untreated cells (Ctrl = 1.0) (Zhao et al., 2010).

It can be expected that novel technologies and instrumentation like LSC and cell imaging in flow (multispectral imaging cytometry) are just a prelude to a major transformation that cytometric field will experience in the coming years (Darzynkiewicz et al., 1999; Deptala et al., 2001; George et al., 2004; Smolewski et al., 2001). Here especially the LSC by having many attributes of both flow cytometry and low-resolution image analysis appears to be an optimal instrumentation for multiparameter studies on cell demise (Bedner et al., 1999; Darzynkiewicz et al., 1999; Kamentsky, 2001; Zhao et al., 2010). Application of nanocrystal quantum dots (Qdots) as convenient multispectral markers (Alivisatos et al., 2005) will also contribute toward expansion of cytometric methods in necrobiology. Furthermore, we expect to witness soon the massive rise of microand nanotechnologies that form a cornerstone for Lab-on-a-Chip platforms. Although still in their infancy the latter technologies warrant a major ‘‘quantum leap’’ in studies of cell death at a single cell level (Chan et al., 2003; El-Ali et al., 2006; Huh et al., 2005; Qin et al., 2005).

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90 Acknowledgements

The views and opinions described in this chapter were not influenced by any conflicting commercial interests. The study is supported in part by NCI RO1 28 704.

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CHAPTER 5

Assessment of Oxidative Stress-Induced DNA Damage by Immunoflourescent Analysis of 8-OxodG Soo Fern Lee* and Shazib Pervaiz*,y,z,x *

Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore y NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore z Cancer and Stem Cell Biology Program, Duke-NUS Graduate Medical School, Singapore x Singapore-MIT Alliance, Singapore

Abstract I. Redox Regulation of Cell Fate Signaling II. 8-OxodG as a Marker of Oxidative DNA Damage A. 8-OxodG is a Highly Mutagenic DNA Lesion B. 8-OxodG as a Biomarker of Cellular Oxidative Damage and its Clinical Relevance III. Detection of Oxidative DNA Damage Involving 8-OxodG A. Chromatography-Based Direct Assessment of 8-OxodG B. The Indirect Assessment of OxodG Modification of DNA IV. Concluding Remarks References

Abstract Oxidative stress refers to the imbalance between the generation of reactive oxygen species (ROS) and their scavenging by the inherent antioxidant defenses of the cell. The abnormal accumulation of ROS is the underlying pathology in a variety of human diseases such as neurodegenerative phenomena, inflammatory diseases, METHODS IN CELL BIOLOGY, VOL 103 Copyright 2011, Elsevier Inc. All rights reserved.

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0091-679X/10 $35.00 DOI 10.1016/B978-0-12-385493-3.00005-X

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Soo Fern Lee and Shazib Pervaiz

metabolic disorders, and cancer. The mechanism by which abnormal accumulation of ROS contributes to pathological conditions involves damage or oxidative modification of biomolecules, such as nucleotides, lipids, and proteins. One of the most common targets of ROS is DNA, modifications of which have been associated with cellular transformation and genome instability. There are a number of experimental strategies to assess oxidative modification of DNA bases, such as chromatographybased assays and indirect immunofluorescence. While the former provide quantitative assessment of oxidative modification, the latter is a much simpler assay for qualitative determination of DNA base modification in very small sample sizes. Here, we present a brief background of the various methodologies for the assessment of a specific oxidative DNA modification, 8-oxodG, and present a more detailed account of the indirect immunofluorescence assay.

I. Redox Regulation of Cell Fate Signaling Growth homeostasis is a function of a tight balance between the rates of cell proliferation and cell loss, regulated by diverse processes and/or signaling networks, such as kinases and phosphatase, cyclins and cell cycle inhibitors, oncogenes and tumor suppressors, proteases and lysosomal factors, transcription enhancers and repressors, ion transporters, and DNA damage and repair sensing machinery. Although, these pathways are responsive to a myriad of extracellular and intracellular signals, evidence is accumulating to implicate altered cellular redox status as an important effector mechanism underlying cellular response to stress signals. The cellular redox status is a product of the rates at which intracellular reactive oxygen species (ROS) are generated and the efficiency with which they are scavenged or decomposed. There is now evidence that depending on their intracellular levels and the nature of the ROS, the effects could be as diverse as activation of gene transcription and proliferation, DNA damage, and cell death induction (Droge, 2002). Along these lines, a mild increase in intracellular ROS, in particular O 2 , promotes cell survival by inhibiting apoptotic execution and by activating prosurvival signaling (Ahmad et al., 2003; Clement et al., 2003; Clement and Stamenkovic, 1996; Pervaiz et al., 2001). Contrarily, an increase in intracellular hydrogen peroxide facilitated death execution by creating a permissive intracellular milieu for protease activation (Ahmad et al., 2004; Clement and Pervaiz, 2001; Clement et al., 1998; Hirpara et al., 2001). The link between a prooxidant state and cell survival was further corroborated by findings from oncogene-induced models of cell transformation, such as activated Rac, Bcl-2, and Akt/PKB (Clement et al., 2003; Lim and Clement, 2007; Pervaiz et al., 2001). As a result, an abnormal ROS accumulation has been implicated in the pathogenesis of various diseases, including cancer, atherosclerosis, diabetes mellitus, and neurodegenerative disorders, and in oxidative protein damage associated with age-related sarcopenia (muscle wasting, reviewed in Droge, 2002).

5. Assessment of Oxidative Stress-Induced DNA Damage by Immunoflourescent Analysis of 8-OxodG

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Although, the intracellular targets of ROS are varied and diverse, one of the most frequent modifications associated with oxidative stress is damage to DNA. Not only is DNA damage an invariable finding in cancer but also is strongly linked to genome instability, an acquired hallmark of cancer. One of the most common targets of oxidation-induced DNA modification is the guanine nucleotide resulting in the formation of 8-oxo-7,8-dihydroguanine (8-oxoG) or its nucleoside form 8-oxo7,8-dihydro-20 -deoxyguanosine (8-oxodG) (Steenken and Jovanovic, 1997; Kanvah et al., 2010; Steenken, 1989). Here, we will focus on this oxidative modification of DNA, its biology, and methods for its detection as an index of DNA damage.

II. 8-OxodG as a Marker of Oxidative DNA Damage Guanine has been shown to be the preferential target during oxidative DNA damage owing to its lowest oxidation potential at 1.29 V among the four bases (dA 1.42 V, dC 1.6 V, dT 1.7 V). Aside from this unique property conferred by the electron-rich purine structure, guanine also acts as a ‘‘hot spot’’ for electron migration. The oxidation of guanine as a result of exposure to OH radical, one-electron oxidants, and singlet oxygen (1O2) generally gives rise to the formation of 8-oxoG or its nucleoside form 8-oxodG (Steenken and Jovanovic, 1997; Kanvah et al., 2010; Steenken, 1989). As a matter of fact, mutational research of this modified nucleobase has led to the realization that approximately 0.5–5 lesions per 100,000 guanine residues in human cellular DNA are oxidized at C-8 (ESCODD, 2003; Loft et al., 2008; Ravanat et al., 2002). Furthermore, the presence of 8-oxodG within DNA has been shown to induce other base damages. Hence, the 8-oxoG lesions have to be removed by 8-oxoguanine glycosylase 1 (OGG1) rapidly in order to protect the integrity of neighboring bases (Radicella et al., 1997). Meanwhile, there is evidence showing that 8-oxodG is highly susceptible to further oxidation under physiological conditions and therefore serves as an excellent ‘‘electron sink’’ during oxidative damage. This is explained by the fact that upon oxidation to 8-oxodG, the oxidation potential is further lowered to 0.74 V, thereby making this species highly reactive toward various radical species compared to other unmodified bases and highly prone to oxidation (Cadet et al., 2008; Steenken et al., 2000). This further oxidation and other chemical transformations of 8-oxodG can lead to the formation of a variety of secondary DNA adducts. For instance, through 1 O2 or peroxynitrite (OONO)-mediated oxidation, 8-oxodG is further oxidized to yield lesions such as cyanuric acid, oxaluric acid, and oxazolone. In addition, 5-guanidinohydantoin and 2-imino-5,50 -spirohydantoin could also be generated from the one-electron oxidation of 8-oxoG or through direct oxidation and photooxidation of guanine. As these secondary lesions are significantly more mutagenic than the primary lesion, 8-oxodG (Duarte et al., 2001; Gasparutto et al., 1999; Henderson et al., 2002, 2003; Luo et al., 2000; Tretyakova et al., 1999), the chain reaction triggered upon oxidative stress-induced nucleotide modification could either facilitate transformation or severely impact the cell fate.

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A. 8-OxodG is a Highly Mutagenic DNA Lesion Normal homeostatic growth is maintained by efficient and elaborate DNA repair machinery that ensures error-free DNA delivery through the cell cycle. A defect and/ or deficiency in the repair pathways promotes DNA mutations such as base substitution, deletions, or strand fragmentation resulting in severe genomic instability, an acquired hallmark of most cancer cells. Therefore, the fact that 8-oxodG and its oxidative byproducts are highly mutagenic compared to the other oxidatively modified DNA adducts, 8-oxodG has been receiving heightened attention as a bonafide marker of oxidative stress-induced DNA damage. The mutagenic potential of 8-oxodG stems from its miscoding properties. By default, most of the DNA damage lesions stall or block the progression of DNA replication, yet such high-fidelity mechanism is not always fail-proof, especially in the case of 8-oxodG modification. Studies carried out using the primer extension method demonstrated that dAMP and dCMP could be incorporated opposite 8-oxodG in vitro (Cheng et al., 1992; Shibutani et al., 1991). Furthermore, a study based on the crystal structure revealed that 8-oxodG induced an inversion of the mismatch recognition mechanism that should normally proofread DNA; the 8-oxodG:dA base pairing resembles a Watson–Crick base pair and is thereby exempted from removal by the 30 –50 exonuclease activity during the DNA polymerase error detection process (Hsu et al., 2004). Therefore in living cells, if the 8-oxodG lesion remains unrepaired before replication, the lesion itself is very likely to result in G:C ! T:A transversion, a common somatic mutation observed in human cancers (Kamiya et al., 1995). In addition to the G:C ! T:A transversion promoted by 8-oxodG, there is also the potential risk of 8-oxodG causing A:T ! C:G transversion in the genome. More importantly, as mammalian DNA is constantly exposed to ROS, the dGTP of the entire dNTP pool could also be a potential target as the spontaneous oxidation of dGTP results in the formation of 8-oxodGTP. The presence of 8-oxodGTP in the dNTP pool is potentially disastrous as it can be incorporated by the DNA polymerases opposite the dC or dA residues of the template DNA with almost equal efficiency, which eventually results in the A:T ! C:G transversion during the subsequent round of replication (Cheng et al., 1992; Maki and Sekiguchi, 1992).

B. 8-OxodG as a Biomarker of Cellular Oxidative Damage and its Clinical Relevance Ever since the first discovery by Kasai and Nishimura in 1984 that deoxyguanosine could be readily oxidized to 8-oxodG, this pivotal finding has spurred research in the area of oxidation-induced DNA damage (Kasai et al., 1984). These efforts have yielded remarkable results with tremendous progress being made not only in unraveling the mechanism of 8-oxodG formation but also in the development of more sensitive and accurate assays to analyze modified nucleobases in biological samples. Of note, due to the high potential risk of promoting the G:C ! T:A


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transversion in cellular DNA, the 8-oxodG lesion is believed to contribute significantly to the spontaneous mutations in human cancers. Therefore, 8-oxodG has emerged as an important biomarker both for evaluating cellular oxidative damage and for assessing cancer risk associated with exposure to carcinogens or environmental pollutants. For instance, carcinogens such as aflatoxin B1, ethylbenzene, pentachlorophenol, and benzo(a)pyrene have been shown to induce the formation of 8-oxodG both in animal organs and in cell lines (Briede et al., 2004; Lin et al., 2002; Midorikawa et al., 2004; Shen et al., 1995; Umemura et al., 1999). In similar in vivo studies, cigarette smoking was shown to induce oxidative DNA damage to a variety of tissues, primarily the lungs (Izzotti et al., 1999; Park et al., 1998); cigarette smoking is known to induce excessive amount of ROS production. In agreement with that, higher levels of 8-oxodG have been reported in the lungs, as well as in leukocyte DNA and urine, of cigarette smokers (Asami et al., 1997) compared to non-smokers. Of note, there appears to be a positive correlation between the number of cigarettes smoked per day and the 8-oxodG content, which strongly implicates ROS as one of the major contributing factors in cigarette smoking-induced lung carcinogenesis (Lodovici et al., 2000; Malayappan et al., 2007; Vulimiri et al., 2000). Further support for the critical role of oxidative DNA damage in cellular transformation and carcinogenesis is provided by studies on workers exposed to the genotoxic carcinogen, asbestos (Kamp, 2009). Experimental studies in cell cultures had identified that asbestos-induced oxidative DNA injury by producing hydroxyl radicals and other ROS (Kamp et al., 1992; Shukla et al., 2003). This finding was supported by data from epidemiological studies showing that high levels of 8-oxodG lesions were detected both in the leukocyte DNA and in the urine of workers chronically exposed to asbestos (Takahashi et al., 1997; Yoshida et al., 2001). Collectively, these studies provide evidence that the presence of oxidative DNA damage, in particular 8-oxodG lesions, is strongly correlated with exposure to genotoxic and/or mutagenic agents. The aforementioned studies provide ample evidence that the presence of 8-oxodG is an indicator of oxidative stress-induced DNA damage upon exposure to carcinogenic agents. However, due to the close association between 8-oxodG DNA lesions and carcinogenesis, 8-oxodG has emerged as a potentially reliable biomarker for predicting an individual’s cancer risk associated with oxidative stress. This is supported by clinical data from patients with various malignancies that indicate significantly higher 8-oxodG levels than the healthy control counterparts. Similarly, biopsy specimens from patients with cervical intraepithelial neoplasia (CIN) with human papilloma virus (HPV) displayed higher levels of 8-oxodG, and more importantly, 8-oxodG immunoreactivity correlated significantly with the CIN grade. Interestingly, upregulation of inducible nitric oxide synthase (iNOS), the enzyme responsible for nitric oxide (NO) production, has also been reported in CIN specimens. These data indicate that oxidative DNA injury as a result of chronic inflammation induced by the high-risk HPV viral infection is one of the factors contributing to cervical dysplasia and carcinogenesis (Hiraku et al., 2007).

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Chronic inflammation is also associated with an increase in incidence of cancer development and invasion. For example, intrahepatic cholangiocarcinoma (ICC) is an adenocarcinoma originating from intrahepatic bile duct epithelium, primarily caused by Opisthorchis Viverrini (OV) infection. Interestingly, a significantly higher level of 8-oxodG was detected in the cancerous tissue compared to the noncancerous surrounding tissue in biopsy specimens from affected patients (Pinlaor et al., 2005). Similarly, oxidative DNA damage has also been associated with Helicobater pylori infection and in the hepatocytes of patients with chronic hepatitis C. Of note, H. pylori infection is strongly associated with gastric carcinoma, while chronic hepatitis predisposes to the development of hepatocellular carcinoma (Horiike et al., 2005; Ma et al., 2004). Oral lichen planus (OLP) is a chronic inflammatory mucosal disease. Of note, significantly higher accumulation of 8-oxodG was identified in the oral epithelium of OLP- and oral squamous cell carcinoma (OSCC)-affected individuals. In turn, this finding relates the pathogenesis of OLP to the initiation of oral cancer development, which strongly suggests that the chronic inflammatory state in OLP plays a key role in disease progression (Chaiyarit et al., 2005). A recent report demonstrated elevated levels of 8-oxodG in leukocytes of patients carrying BRCA1 mutation that are at high risk of breast and ovarian cancer. In the report, it was suggested that the elevated 8-oxodG level in the BRCA1 carrier resulted from the deficiency in DNA repair. Thereby, one of the key mechanisms responsible for the pathogenesis of cancer development in women with BRCA1 mutation could be likely attributed to the DNA repair deficiency-mediated 8-oxodG accumulation in the cellular genome, which in turn promotes tumor progression via a subsequent series of mutations (Dziaman et al., 2009). Similarly, analysis of leukocyte DNA isolated from patients suffering from upper digestive tract cancer and colon cancer, and tissues from breast cancer patients show significantly higher level of 8-oxodG compared to the healthy control groups. These data confirm the strong correlation between the extent of oxidative DNA damage and the onset of tumorigenesis (Breton et al., 2005; Li et al., 2001; Obtulowicz et al., 2010). As such, 8-oxodG could serve as an important biomarker for cancer risk assessment and in the early diagnosis of the disease.

III. Detection of Oxidative DNA Damage Involving 8-OxodG The methodology for analysis of oxidative DNA damage in the form of 8-oxodG is generally divided into two categories: the first type of assay is the more direct approach that uses both physical and chemical methods to single out the DNA lesion from cells and tissues followed by quantitative analysis performed by one of the three chromatographic methods, that is, gas chromatography-mass spectrometry (GC-MS) (Dizdaroglu, 1994), HPLC coupled with electrochemical detection (HPLC-EC) (Shigenaga et al., 1994), or HPLC electrospray tandem mass spectrometry (HPLC-MS/MS) (Ravanat et al., 1998a). It is worth mentioning that the GC-MS


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assay was first introduced more than 20 years ago to measure the level of oxidized bases. Since then, notable efforts have been made in the development of more sensitive and accurate methods for detection of oxidative DNA lesions. Subsequently, HPLC-EC was used to replace the skeptical GC-MS method, which was followed by the development of the more precise HPLC-MS/MS technique. The second type of assay uses mainly an indirect approach whereby the whole DNA structure is usually preserved during the process and DNA lesions are detected in situ. The measurement of DNA lesions is normally carried out by enzymatic assays, which require the use of DNA repair enzymes to reveal the formation of oxidized bases in the DNA. A. Chromatography-Based Direct Assessment of 8-OxodG Initial reports highlighted discrepancies in the results reported from direct analysis of 8-oxodG modification of DNA using the various chromatographic techniques. This was mainly attributed to variations in the experimental protocols and different isolation methodologies used among laboratories (Dizdaroglu, 1998; England et al., 1998; Jenner et al., 1998; Senturker and Dizdaroglu, 1999). Such inconsistency unavoidably resulted in the exaggeration of the background DNA oxidation level during measurements. Therefore, the European Standards Committee on Oxidative Damage was set up with the aim of establishing a standard guideline for the optimized conditions for DNA extraction and enzymatic hydrolysis (ESCODD, 2002; Lunec, 1998). Despite the formation of the committee, the GC-MS assay is becoming less favorable nowadays as this method requires a sample derivatization step, which has been shown to generate spurious oxidation on nucleobases resulting in an artifactual increase (almost two to three orders of magnitude) in the background oxidation levels (Cadet et al., 1997; Dizdaroglu, 1994; Ravanat et al., 1995). HPLC-EC is considered a sensitive and accurate assay, which can detect oxidized nucleobase with a sensitivity of 1 in 106 normal bases. However, this method requires a complicated setup and multiple runs per sample. In addition, this assay requires relatively large quantities of starting material for the analysis (Bogdanov et al., 1999; Germadnik et al., 1997; Ravanat et al., 1998b; Shigenaga et al., 1994), which limits the use of this method in clinical settings where the specimen size is usually a ratelimiting factor. The HPLC-MS/MS assay has been described as the best HPLC procedure among the few existing chromatographic approaches because of its high sensitivity and precision (Malayappan et al., 2007; Podmore et al., 2000; Ravanat et al., 1998a; Weimann et al., 2001). This is due to the fact that this procedure does not require the derivatization step or the extensive sample preparation that carry the risk of introducing artifactual oxidation. Although the equipment is much more expensive, compared to GC-MS and HPLC-EC, the HPLC-MS/MS is fast and easily automated. Besides, the greatest advantage of this technology is its ability to measure two and potentially more oxidative DNA products and at the same time provides

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unambiguous information on the identity of analytes, which makes it suitable for large-scale epidemiological studies. B. The Indirect Assessment of OxodG Modification of DNA The indirect approach for the measurement of oxidized nucleobases in cellular DNA requires the use of base excision DNA repair enzymes, such as the formamidopyrimidine DNA glycosylase, which converts the 8-oxodG lesions into strand breaks. The quantitative measurement of the strand breaks is subsequently determined by performing the comet assay, the alkaline elution technique, or the unwinding elution method (Collins et al., 1993, 1996; ESCODD, 2003; Hartwig et al., 1996; Pflaum et al., 1997). Compared to the chromatographic approaches, which generally involves lengthy DNA isolation and hydrolysis procedures that tend to give rise to oxidation artifact, this enzymatic in situ detection method gives an estimation of endogenous oxidative base damage at several fold lower than the estimation value from the HPLC techniques. Therefore, this assay is more suitable for detecting low level of oxidative base damage, which could be close to a few lesions per 107 bases in a sample.

1. Indirect Assessment of Oxidative DNA Damage by Immunofluorescence Compared to the various approaches discussed above, the simplest and easiest methodology for the qualitative assessment of 8-oxodG modification of DNA is based on an immunofluorescence detection method. This assay relies on the use of a monoclonal antibody raised against 8-oxodG lesions, and similar to the enzymatic assays, the immunofluorescence detection method does not give rise to artifactual background oxidation during the sample preparation step. Of note, it provides in situ assessment of oxidative stress-induced DNA damage, which alleviates the problem of sample destruction associated with chromatography-based approaches. Furthermore, the analysis could be performed on a very small sample material (unlike some other techniques requiring relatively large quantity of DNA) with an average confocal microscope, thereby obviating the need for highly sophisticated and expensive equipments. Therefore, the immunofluorescence-based assay is very suitable for clinical research where the quantity of the starting material for DNA extraction and analysis is usually a rate-limiting factor. Also, the relative simplicity of the assay has conferred on this approach broader applications in different fields of studies such as oxidant and antioxidant research. For example, this technique can be used to study genes associated with antioxidant defenses at the cellular level and to identify potential agents that can cause extensive oxidative DNA damage. Furthermore, since oxidative DNA damage is generally perceived as the leading cause in the initiation and promotion of tumorigenesis, this relatively simple and easy-to-use assay could be employed for screening individuals at high risk of oxidative stress-induced DNA insults, such as those exposed to industrial pollutants, cigarette smoke, and other potential mutagens.


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Materials 1. HCT116 human colorectal carcinoma cell line. 2. Culture medium: Mc Coy’s 5A (Invitrogen) supplemented with 10% FBS (Hyclone) and 5 mM glutamine solution. 3. Fixative: cold acetone stored at 20 C. 4. RNase stock solution: 10 mg/mL in 10 mM Tris-HCl (pH 7.5), 15 mM NaCl. 5. HCl solution: 2 N HCl in distilled water. 6. Washing solution: phosphate buffered saline (PBS). 7. Blocking buffer: 2% bovine serum albumin (BSA) + 10% FBS in 1 PBS. 8. Primary antibody: anti-8-oxodG monoclonal antibody (clone 2E2, Trevigen). 9. Secondary antibody: goat anti-mouse IgG Alexa 568 (Molecular Probes). 10. Nuclear staining solution: DAPI (Molecular Probes) diluted in antifade mounting media at 1:1000. 11. Antifade mounting media: Vectashield (Vector Lab).

Methodology 1. HCT116 cells were seeded on glass slides in a six-well plate until 80–90% confluency. 2. The culture medium was removed and replaced with fresh growth medium. 3. Cells were then treated with the ROS-producing agent, such as hydrogen peroxide (H2O2) for 2–4 h at 37 C. 4. Following incubation, the medium was removed and cells were washed once with 1 PBS. 5. Cells were then fixed with cold acetone at 20 C for 15 min. 6. The slides were transferred to new container and washed two times (5 min each with shaking) with 1 PBS at room temperature. 7. Cells were treated with the RNase solution (final concentration at 100 mg/ml) for 1 h at 37 C to get rid of the RNA. 8. Slides were washed three times (3 min each with shaking) with 1 PBS at room temperature. 9. To denature DNA, the slides were treated with 2 N HCl solution for 10 min at room temperature. 10. The slides were washed three times (5 min each with shaking) with 1 PBS at room temperature. 11. The slides were kept in the blocking buffer for at least 1 h with gentle shaking. (Slides can be kept in blocking buffer for overnight at 4 C with gentle shaking.) 12. Slides were then washed with 1 PBS for 5 min at room temperature with moderate shaking. 13. A working dilution (1:300) of the primary antibody (mouse monoclonal anti8-oxodG) was prepared in the blocking buffer. 14. The slides were incubated with the primary antibody for 2 h at room temperature with gentle shaking.

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15. Following incubation with the primary antibody, the slides were washed three times with 1 PBS (5 min each), at room temperature with moderate shaking. 16. A working dilution of the secondary antibody (1:500) was prepared in the blocking buffer. 17. The slides were incubated with the secondary antibody for 1 h at room temperature (in dark) with gentle shaking. 18. Following incubation with the secondary antibody, the slides were washed four times (5 min each) with 1 PBS, at room temperature with moderate shaking. 19. A working dilution of the DNA binding dye DAPI (1:1000) was prepared in the antifade mounting media. 20. The slides were mounted with the antifade mounting media (from step 19). 21. The edges of the slides were sealed with nail polish after the mounting media had completely dried. 22. The slides were stored in a humidified chamber at 4 C until analysis by confocal microscopy.

Results HCT116 cells were treated with 2 mM H2O2 for 2 h and the cells were prepared and analyzed as described above. Results show that exposure to H2O2 resulted in the increased reactivity with anti-8-oxodG (Fig. 1B), shown as the increase in red

[(Fig._1)TD$IG]

Fig. 1

ROS-induced 8-oxodG lesion. HCT116 cells were incubated in the absence (A) or presence (B) of 2 mM H2O2 for 2 h. Modified DNA bases were detected by the use of antibody that specifically recognizes 8-oxodG. Goat anti-mouse IgG(H+L) Alexa Fluor 568 was used as the secondary antibody for detection by immunofluorescence.


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fluorescence (Alexa Fluor 568) compared to the untreated cells (Fig. 1A). These results highlighted the effect of oxidative stress on 8-oxodG modification of DNA and could be very useful as a screening assay.

Shortcomings of the Immunofluorescence Assay Although an easy and simple assay with potential for use as a screening tool, the immunofluorescence detection method does have its pitfalls. Unlike the chromatographic measurements or enzymatic assays whereby the amount of 8-oxodG lesions in the DNA is quantifiable at high sensitivity and accuracy, the immunofluorescence assay for 8-oxodG detection provides mainly a qualitative assessment of the oxidized bases. Despite this limitation, this method is a reliable and simple to use with cultured cell lines and/or clinical tissues for determining the presence of oxidative DNA injury.

IV. Concluding Remarks In conclusion, the chromatographic approaches, which comprise of HPLC-EC, HPLC-MS/MS, and GC-MS, are frequently used in experimental studies to detect any abnormal changes in nucleobases due to their extremely high sensitivity and specificity. This preference is especially reflected by the increasing popularity with the use of HPLC-MS/MS method, which is showing an additional advantage by giving unambiguous information on the identity of the analytes. However, the chromatographic approaches do have imperfections and therefore find limited application under certain circumstances. In general, these approaches are sample-destructive and issues associated with high background oxidation that always give rise to overestimations can be quite difficult to tackle. On the other hand, the enzymatic approaches do not have significant issues with the high background oxidation problem. Although these approaches are more suitable for the assessment of very low amount of inflicted base damage, there is still concern regarding the way the calibration is performed for the extent of DNA nicks, with the hope of developing a more feasible protocol in near future (Cadet et al., 2003). References Ahmad, K. A., Clement, M. V., and Pervaiz, S. (2003). Pro-oxidant activity of low doses of resveratrol inhibits hydrogen peroxide-induced apoptosis. Ann. N. Y. Acad. Sci. 1010, 365–373. Ahmad, K. A., Iskandar, K. B., Hirpara, J. L., Clement, M. V., and Pervaiz, S. (2004). Hydrogen peroxidemediated cytosolic acidification is a signal for mitochondrial translocation of Bax during drug-induced apoptosis of tumor cells. Cancer Res. 64, 7867–7878. Asami, S., Manabe, H., Miyake, J., Tsurudome, Y., Hirano, T., Yamaguchi, R., Itoh, H., Kasai, H. (1997). Cigarette smoking induces an increase in oxidative DNA damage, 8-hydroxydeoxyguanosine, in a central site of the human lung. Carcinogenesis 18, 1763–1766.

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CHAPTER 6

Analysis of Individual Molecular Events of DNA Damage Response by Flowand Image-Assisted Cytometry Zbigniew Darzynkiewicz*, Frank Traganos*, Hong Zhao*, H. Dorota Halicka*, Joanna Skommery and Donald Wlodkowicz * Brander Cancer Research Institute and Department of Pathology, New York Medical College, Valhalla, New York, USA y

School of Biological Sciences, University of Auckland, Auckland, New Zealand

z

The BioMEMS Research Group, Department of Chemistry, University of Auckland, Auckland, New Zealand

Abstract I. Introduction II. Events of the DDR A. Chromatin Decondensation (Relaxation) B. Activation of Phosphatidyl Inositol 30 -Kinase-Related Kinases (PIKKs) C. Activation of Checkpoint Kinases D. Histone H2AX Phosphorylation III. Detection of DDR Events by Cytometry A. Chromatin Relaxation (Decondensation) B. Recruitment of Mre11 C. Immunocytochemical Detection of DDR-Associated ATM, DNA-PKcs and Chk2 Activation, Phosphorylation of p53 and Histone H2AX IV. Application of Cytometry to Detect DDR Induced by Different Genotoxic Agents A. Assessment of DDR Induced by DNA Topoisomerase Inhibitors B. Induction of DDR by Ionizing Radiation and UV Light C. Induction of DDR by Cigarette Smoke (CS) and Other Environmental Mutagens D. Oxidative DNA Damage

METHODS IN CELL BIOLOGY, VOL 103 Copyright 2011, Elsevier Inc. All rights reserved.

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0091-679X/10 $35.00 DOI 10.1016/B978-0-12-385493-3.00006-1

Darzynkiewicz et al.

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V. Interpretation of Cytometric Data: Role of Image-Assisted Cytometry VI. Role of Microfluidic Lab-on-a-Chip Platforms for DDR Analysis References

Abstract This chapter describes molecular mechanisms of DNA damage response (DDR) and presents flow- and image-assisted cytometric approaches to assess these mechanisms and measure the extent of DDR in individual cells. DNA damage was induced by cell treatment with oxidizing agents, UV light, DNA topoisomerase I or II inhibitors, cisplatin, tobacco smoke, and by exogenous and endogenous oxidants. Chromatin relaxation (decondensation) is an early event of DDR chromatin that involves modification of high mobility group proteins (HMGs) and histone H1 and was detected by cytometry by analysis of the susceptibility of DNA in situ to denaturation using the metachromatic fluorochrome acridine orange. Translocation of the MRN complex consisting of Meiotic Recombination 11 Homolog A (Mre11), Rad50 homolog, and Nijmegen Breakage Syndrome 1 (NMR1) into DNA damage sites was assessed by laser scanning cytometry as the increase in the intensity of maximal pixel as well as integral value of Mre11 immunofluorescence. Examples of cytometric detection of activation of Ataxia telangiectasia mutated (ATM), and Check 2 (Chk2) protein kinases using phospho-specific Abs targeting Ser1981 and Thr68 of these proteins, respectively are also presented. We also discuss approaches to correlate activation of ATM and Chk2 with phosphorylation of p53 on Ser15 and histone H2AX on Ser139 as well as with cell cycle position and DNA replication. The capability of laser scanning cytometry to quantify individual foci of phosphorylated H2AX and/or ATM that provides more dependable assessment of the presence of DNA double-strand breaks is outlined. The new microfluidic Labon-a-Chip platforms for interrogation of individual cells offer a novel approach for DDR cytometric analysis.

I. Introduction Intricate and highly choreographed series of molecular events broadly defined as the DNA damage response (DDR) take place in the live cell upon induction of DNA damage. The events of DDR involve a multitude of posttranslational modifications of proteins that trigger interactions between intracellular molecules activating several signaling pathways. Activation of these pathways has four critical aims: (i) stopping cell cycle progression and division and thereby preventing transfer of damaged DNA to progeny cells; (ii) enhancing accessibility of the damage site to the DNA repair machinery; (iii) activating and engaging repair machinery; and (iv) triggering apoptosis or inducing cellular senescence (reproductive cell death) to eliminate cells whose damaged DNA cannot successfully be repaired (reviews,

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Bakkenist and Kastan, 2003, 2004; Bonner et al., 2008; Helt et al., 2005; Kastan, 2008; Lee and Paull, 2005; Nakamura et al., 2010). This review briefly describes the molecular mechanisms of DDR and outlines applications of cytometry in analysis of particular events and stages of DDR.

II. Events of the DDR A. Chromatin Decondensation (Relaxation) One of the early events of the DDR is remodeling of chromatin structure that involves its decondensation (Murga et al., 2007; Pandita and Richardson, 2009; Rouleau et al., 2004; Ziv et al., 2006). Chromatin decondensation appears to be triggered by decline of torsional strain of the DNA double helix occurring upon DNA damage, particularly when the damage involves formation of DNA double-strand breaks (DSBs) (Fig. 1). DNA torsional strain (topological stress) is otherwise maintained by its winding onto histone octamers of the nucleosome core and supercoiling to form the supra-nucleosomal chromatin structure (Marko, 2010). High mobility group proteins (HMGs) play a key role in providing a rapid dynamic response by local decondensation of chromatin triggered by DNA damage (Gerlitz and Bustin, 2009; Kim et al., 2009; Sinha and Peterson, 2009). HMGs and histone H1 are persistently moving along the chromatin fiber and interacting with each other and with internucleosomal DNA. Compared with other nuclear proteins, HMGs are the most extensively modified, being rapidly phosphorylated, acetylated, methylated, ribosylated, and/or sumoylated in response to changes in the physiological state of the cell, induction of stress, or cell cycle phase (Zhang and Wang, 2008). This network provides a continuous highly dynamic interplay between a variety of nuclear structural proteins, modulating their binding to each other and to nucleosomes (Lim et al., 2004; Misteli and Soutoglou, 2009). Of particular importance is the binding of the HMGN1 protein to the nucleosome, which alters the architecture of chromatin and affects the levels of posttranscriptional modifications of the tails of nucleosomal histones. Specifically, upon HMGN1 binding to nucleosomes, phosphorylation of histone H3 on Ser10 is reduced (Lim et al., 2004). Since histone H3 phosphorylation on Ser10 is required to maintain chromatin in a condensed state such as during mitosis (Juan et al., 1998) or premature chromosome condensation (Huang et al., 2006a) the reduction of its level of phosphorylation facilitates chromatin decondensation (relaxation). Thus, the DNA damage-induced activation of HMGN1 and its binding to nucleosomes preventing histone H3 phosphorylation may directly mediate chromatin decondensation. Histone acetyltransferase TIP60 also plays a role in modulation of chromatin dynamics. After damage to DNA, in addition to acetylation of histone H2AX, which is a prerequisite for its phosphorylation on Ser139, TIP60 regulates the ubiquitination of H2AX via the ubiquitin-conjugating enzyme UBC (Ikura et al., 2007; Kruhlak et al., 2006). Sequential acetylation and ubiquitination of H2AX by TIP60-UBC promotes enhanced histone dynamics, which in turn stimulates the


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[(Fig._1)TD$IG]

The ATM signaling pathway triggered by induction of DSBs [(Kitagawa et al., 2004, updated (Darzynkiewicz et al., 2009)]. Induction of DSB leads to lessening of torsional strain and unwinding of DNA superhelical structure that triggers local decondensation of chromatin and recruits the Mre11, Rad50, and NBS1 proteins (MRN complex), as well as BRCA1 to the DSB site (A, dashed arrows). These events activate ATM, which occurs by autophosphorylation of Ser1981 and leads to dissociation of the ATM dimer onto two monomers that are enzymatically active. Activated ATM is then recruited to the site of the DSB (B, dashed arrow) where it phosphorylates several substrates including NBS1, BRCA1, and SMC1 (C). NBS1 phosphorylation is required for targeting ATM to phosphorylate Chk1 and Chk2. Phosphorylation of SMC1 activates S-phase checkpoints whereas BRCA1 phosphorylation engages this protein in the DSB repair pathway. ATM also phosphorylates E2F-1, Chk1, p53, Mdm2, Chk2, and H2AX and several other substrates. Activated p53 (phosphorylated on Ser15) induces transcription of p21WAF1 and/or Bax genes whose protein products arrest cells in G1 or promote apoptosis, respectively.

Fig. 1

DDR. It should be noted that the presence of wt p53 appears to be critical for the induction of chromatin relaxation upon DNA damage (Murga et al., 2007; Rubi and Milner, 2003) perhaps through its effect on the tumor suppressor p33ING2 (Wang et al., 2006). Chromatin relaxation augments accessibility of the repair machinery to DNA damage sites and appears to also provide the signal for activation of Ataxia telangiectasia mutated (ATM) protein kinase. The MRN complex consisting of Meiotic Recombination 11 Homolog A (Mre11), Rad50 homolog and Nijmegen Breakage Syndrome 1 (NMR1) proteins undergoes translocation into the site of DNA damage at the time of chromatin decondensation


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and activation of the ATM protein kinase (Abraham and Tibbetts, 2005; Downs and Cote, 2005; Kitagawa and Kastan, 2005; Paull and Lee, 2005). It should be noted that ATM activation takes place at some distance from the DNA break site and the activated kinase moves then to the site. B. Activation of Phosphatidyl Inositol 30 -Kinase-Related Kinases (PIKKs) The DDR is regulated by three PIKKs: ATM, ATM and Rad3-related (ATR), and DNA-dependent protein kinase (DNA-PKcs) (Cuadrado et al., 2006; Helt et al., 2005; Hill and Lee, 2010; Lovejoy and Cortez, 2009). These kinases are primarily responsible for signaling the presence of DNA damage and phosphorylate hundreds of proteins whose function is to maintain the integrity of the genome. The substrates phosphorylated by these PIKKs are implicated in regulation of DNA damage repair, cell cycle progression, apoptosis, and cell senescence. In many instances these PIKKs can have redundant activities and backup each other in terms of phosphorylation of the same proteins. Among the PIKKs that are activated in response to DNA damage the most extensively studied was ATM, which is the key component of the signal transduction pathways mobilized by the induction of DSBs (Li and Zou, 2005; Shiloh, 2003). Activation of ATM occurs through its autophosphorylation on Ser1981 and requires its prior acetylation that is mediated by the Tip60 histone acetyltransferase (Sun et al., 2005). ATM phosphorylation leads to dissociation of the inactive ATM dimers onto monomers that have kinase catalytic activity (Bakkenist and Kastan, 2003, 2004) (Fig. 1). The MRN protein complex plays a critical role in the process of ATM activation as it detects DNA damage, recruits ATM to the damage site, and targets ATM to the respective substrates to initiate their phosphorylation (Lee and Paull, 2005). Whereas ATM phosphorylation on Ser1981 is a prerequisite for dissociation of the dimer, the catalytic domain of ATM is outside of the Ser1981 site and becomes accessible to the kinase substrates only when ATM is in its monomeric conformation (Bakkenist and Kastan, 2004). As schematically presented in Fig. 1, ATM phosphorylates several substrates at the site of the DSB, including NBS1, structural maintenance of chromosomes 1 (SMC1), and breast cancer 1 (BRCA1) proteins. Phosphorylated NBS1 targets ATM toward Chk1, phosphorylated SMC1 engages the S-phase checkpoints halting DNA replication (Kitagawa et al., 2004; Wakeman et al., 2004) and BRCA1 phosphorylation is required to activate this protein along the DNA repair pathway. The BRCA1 (E3-ubiquitin ligase) is involved in several biochemical processes related to DNA repair (Kastan, 2008; Kitagawa and Kastan, 2005). BRCA2 is essential for locating Rad51 to the sites of DNA damage and both BRCA proteins are involved in DNA repair by homologous recombination (HR) (Yuan et al., 1999). The mediator of DNA damage checkpoint 1 (MDC1) is also recruited to the DSB site (Stucki and Jackson, 2004). This nuclear protein activates the S-phase and G2/M-phase cell cycle checkpoints and interacts with phosphorylated histone H2AX near sites of DSB facilitating recruitment of the ATM and other repair factors to the damage foci.


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Other than ATM, PIKKs activated in response to DNA damage are ATR and DNAPKcs (Cuadrado et al., 2006; Helt et al., 2005; Hill and Lee, 2010; Lovejoy and Cortez, 2009). Activation of ATR occurs in response to replication stress Kurose et al., 2006a, 2006b; Ward et al., 2004) rather than to direct induction of DSBs such as caused by ionizing radiation, which triggers activation of ATM. However, activation of DNA-PKcs takes place during repair of DSBs where it is an essential factor for the nonhomologous end-joining (NHEJ) mechanism of DNA repair (Hill and Lee, 2010; Smith and Jackson, 1999). Because the NHEJ mechanism also operates during V(D)J recombination and is responsible for antibody diversity (Smith, 2004) DNA-PKcs is a critical element for normal immune development. DNA-PKcs is also strongly implicated in telomere maintenance (Samper et al., 2000). The process of activation and inactivation of DNA-PKcs is mediated by its extensive posttranslational modification (Hill and Lee, 2010). Among several sites of its phosphorylation Thr2609, which becomes autophosphorylated in response to DNA damage by ionizing radiation, has been the most studied (Chan et al., 2002). C. Activation of Checkpoint Kinases The most important downstream target substrates phosphorylated by PIKKs include p53 (TP53), checkpoint kinase 2 (Chk2), and histone H2AX (Bakkenist and Kastan, 2004; Wakeman et al., 2004). The main purpose of checkpoint pathways activation is to halt progression through the cell cycle until integrity of DNA is restored by the repair mechanisms (Ahn et al., 2002; Matsuoka et al., 2000; Zhou and Elledge, 2000). Chk2 plays a key role in response of the cell cycle progression machinery to DNA damage. Upon induction of DSBs ATM activates Chk2 by phosphorylating Thr68 of this protein (Fig. 2). This leads to dimerization of Chk2 and acquirement of the kinase catalytic activity (Ahn et al., 2002, 2004). It should be noted that phosphorylation of Chk2 on Thr68 may also be mediated by ATR; this occurs however in response to replication stress (Matsuoka et al., 2000). Intermolecular phosphorylation on Thr383, Thr387, and Ser516 takes place within the Chk dimers, which leads to dissociation of the dimers. Both the monomers and the multiphosphorylated dimers are enzymatically active (Fig. 2). The DNA damage-activated Chk2 undergoes dissociation from chromatin that facilitates further signal amplification and translocation to soluble substrates (Li and Stern, 2005). The enzymatically active monomers as well as dimers of Chk2 phosphorylate numerous downstream substrates including Cdc25A and Cdc25C phosphatases, which upon activation induce cell arrest at the G1 or at the transition from G2 to M, respectively (Fig. 2). In addition to cell cycle arrest Chk2 plays a role in mediating the response to DNA damage by promoting apoptosis. For example, after DNA damage induced by topo2 inhibitor etoposide, Chk2 phosphorylates and activates the E2F-1 transcription factor that activates apoptotic pathways (Stevens et al., 2003). Likewise, phosphorylation of p53 by Chk2 may lead to upregulation of Bax, an event promoting apoptosis. However, phosphorylation of p53 may also lead to upregulation of p21Waf1 providing an additional means to halt cell progression


121

[(Fig._2)TD$IG]

Fig. 2 Activation of Chk2 and Chk2’s major substrates. DNA damage (induction of DSBs) triggers activation of ATM (Fig. 1), which in turn phosphorylates Chk2 on Thr68 causing its dimerization. Phosphorylation of Chk2 can also be mediated by ATR but this occurs in response to replication stress rather than DSB. Within the dimer of Chk2 phosphorylation at Thr383, Thr387, and Ser516 takes place that leads to dissociation of the dimer onto monomers. Both multiphosphorylated dimers and monomers of Chk2 are enzymatically active and able to phosphorylate the downstream substrates. Among these substrates are the Cdc25C and Cdc25A phosphatases whose phosphorylation by Chk2 promotes binding to a 14-3-3 protein (Rudolph, 2007) thereby preventing translocation into the nucleus and dephosphorylation of inhibitory phosphorylations at Thr14 and Tyr15 on cyclin/CDK complexes. This halts cell cycle transitions from G2 to M (Cdc25C) and G1 to S (Cdc25A), respectively. Phosphorylation of Cdc25 phosphatases also accelerates their proteasomal degradation (Boutros et al., 2006). A redundant mechanism of cell arrest in G1 involves phosphorylation of p53 by Chk2 that may lead to upregulation of the cdk2 inhibitor p21CIP1/WAF1. Phosphorylation of p53 may also result in upregulation of the proapoptotic protein Bax. Apoptosis may additionally be promoted by phosphorylation of PML and E2F-1. Phosphorylation of BRCA1 engages it in the DNA repair pathway.

through G1 (Lin et al., 1996). BRCA1 and promyelocytic leukemia (PML) proteins may be phosphorylated by Chk2 as well (Lee et al., 2000; Yang et al., 2002). Phosphorylation of BRCA1 engages this protein in the DNA repair pathway whereas phosphorylation of PML increases cells proclivity to undergo apoptosis (Ahn et al., 2004). Activated Chk2 also stabilizes the FoxM1 transcription factor thereby enhancing expression of DNA repair genes (Tan et al., 2007). There is strong redundancy between Chk1 and Chk2 as well as among all three isoforms of Cdc25 (Cdc25A, Cdc25B, and Cdc25C) (Boutros et al., 2006, 2007; Rudolph,


122

2007) in their enzymatic activities of phosphorylation (Chk1, Chk2) or dephosphorylation (Cdc25A, Cdc25B, Cdc25C), respectively. D. Histone H2AX Phosphorylation Histone H2AX, one of the variants of histone H2A (Thatcher and Gorovsky, 1994), is one of the critical proteins responsible for surveillance of genome integrity (Bassing et al., 2003; Celeste et al., 2003). In response to DNA damage, particularly when the damage involves induction of DSBs, H2AX becomes phosphorylated on Ser139 (Rogakou et al., 1998; Sedelnikova et al., 2002). The phosphorylation can be mediated by ATM (Anderson et al., 2001; Burma et al., 2001), ATR (Furuta et al., 2003), and/or DNA-PKcs (Park et al., 2003) and takes place on nucleosomes on both sides flanking DSBs along a megabase domain of DNA (Rogakou et al., 1999). The Ser139-phosphorylated H2AX is defined as g H2AX. Of notice, H2AX is also phosphorylated during induction of DSBs in physiological processes such as DNA recombination in V(D)J class-switch during the process of immune system development and in meiosis (Modesti and Kanaar, 2001; Smith, 2004). DNA fragmentation in cells undergoing apoptosis also induces extensive H2AX phosphorylation (Huang et al., 2003, 2004, 2006a).

III. Detection of DDR Events by Cytometry A. Chromatin Relaxation (Decondensation) We have recently reported that the DNA damage-induced chromatin decondensation can be detected and measured by flow cytometry (Halicka et al., 2009b). The method is based on the use of the metachromatic fluorochrome acridine orange (AO) that differentially stains double-stranded (ds) versus single-stranded (ss) nucleic acids (Darzynkiewicz et al., 1975). Specifically, AO intercalates between the base pairs of the dsDNA and as a monomer fluoresces green (530 nm). However, when AO binds to ss nucleic acid sections it causes their condensation (transition of the AO–ssDNA complex to solid state) that manifests as red luminescence (>640 nm) that occurs as a result of intersystem crossing (triplet excitation) (Kapuscinski and Darzynkiewicz, 1984a, 1984b). The lifetime of the green fluorescence is 3 ns while the lifetime of the red luminescence is about 9 ns. The susceptibility of DNA to denaturation when stressed by heat or acid varies with the degree of chromatin condensation and the most susceptible is DNA in highly condensed chromatin of mitotic and apoptotic cells (Dobrucki and Darzynkiewicz, 2001). This propensity of AO to differentially stain DNA in condensed versus decondensed chromatin, assessed by cytometry, has been described by us in different cell systems including spermatogenesis, differentiation, G0 to G1 or G2 to M transition, and during apoptosis. In fact, this application of AO to detect


123

abnormal chromatin condensation during spermatogenesis (Evenson et al., 1980) that resembles apoptotic chromatin condensation (Gorczyca et al., 1993) has become a widely recognized male fertility assay, defined as the ‘‘sperm chromatin structure assay’’ (SCSA). As it is evident in Fig. 3, the treatment of cells with UV led to an increase in intensity of green and a decrease of red emission indicating that DNA in the UVtreated cells was more resistant to acid-driven denaturation. Thus, this simple approach, based on the use of AO, detects chromatin decondensation induced by DNA damage. A similar response was observed in other cell types including human lymphocytes, as well as following oxidative DNA damage by H2O2 (Halicka et al., 2009a, 2009b). The degree of DNA denaturation is presented as the at index, which represents the ratio of the mean value of red luminescence intensity of the cell subpopulations (reporting AO interactions with the denatured, ssDNA) to the mean total (red plus green) intensity of the emission. Of interest is the observation that while chromatin decondensation induced by DNA damage caused by UV was global, occurring more or less equally in all phases of the cell cycle, the subsequent events of DDR induced by UV (activation of ATM and induction of g H2AX) were limited to S-phase cells only (Zhao et al., 2010).

[(Fig._3)TD$IG]

Fig. 3 Relaxation of chromatin of TK6 cells treated with UV light detected as susceptibility of DNA to denaturation after staining with acridine orange (AO). The left panel shows schematically the principle of differential staining of double-stranded (ds) versus single-stranded (ss, denatured) DNA sections with the metachromatic fluorochrome AO. AO binding to ssDNA results in red luminescence (>640 nm) whereas its binding to dsDNA results in green fluorescence (530 nm) (Darzynkiewicz, 1990; Darzynkiewicz and Kapuscinski, 1990; Kapuscinski and Darzynkiewicz, 1984a, 1984b). The center panels show bivariate distributions of human leukemic TK6 cells untreated (Ctrl) or exposed to 100 J/m2 UV, then cultured for 30 min, fixed, treated with RNase A, subsequently with 0.1 M HCl to induce partial DNA denaturation, and then stained with AO at pH 2.6 (Halicka et al., 2009). The extent of DNA denaturation is assessed by flow cytometry as the intensity of red luminescence (ssDNA) and green fluorescence (dsDNA). Note a decrease of red luminescence and an increase of green AO fluorescence of the UV-treated cells compared to control, reporting decondensation of chromatin. DNA in mitotic cells (M) is much more susceptible to denaturation than in interphase cells and this is reflected by their high red and low green intensity of emission (Darzynkiewicz et al., 1977). The G1, S, G2, and M cell subpopulations thus can be identified and gated as shown by the dashed-line borders. The mean intensity of red luminescence (ssDNA) to total (red + green) intensity of emission (reporting ssDNA + dsDNA) was calculated for cells in each of these subpopulations. This DNA denaturation index (reporting approximate fraction of denatured DNA, at) is plotted (as at 100) in the right panel. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of the chapter.)


124 B. Recruitment of Mre11

As mentioned earlier in this chapter, the recruitment of MRN complex of proteins consisting of Mre11–Rad50–NBS1 to the DNA damage site is one of the earliest events of the DDR. This event is essential for activation of ATM. The MRN complex then targets ATM to initiate phosphorylation of the respective substrates (Fig. 1). We attempted to measure this event by cytometry expecting that the recruitment of these proteins to the damage site will be reflected by the increase in maximal pixel of Mre11 immunofluorescence (IF). This would be analogous to the recruitment of Bax to the mitochondrial membrane when this protein, normally diffusely distributed throughout the cell, becomes translocated and locally concentrated in mitochondria upon induction of apoptosis (Bedner et al., 2000). Our data presented in Fig. 4 indicate that the recruitment of MRN complex induced by DNA oxidative damage in A549 cells can be detected by cytometry as the increase in intensity of Mre11 IF (Zhao et al., 2008a). However, rather unexpectedly we observed that not only the intensity of maximal pixel increased but Mre11 IF integrated over the whole nucleus also increased. The latter could indicate that either (i) Mre11 was synthesized after induction of the damage; (ii) Mre11 was translocated from cytoplasm to the nucleus; or (iii) the accessibility of the Mre11 epitope to the Ab was increased when this protein was recruited to the site of DNA damage. The rapidity of the response (

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