Inglese Measuring Biological Responses with Automated Microscopy

1. Auflage 2006
ISBN: 978-0-08-046898-3
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, Band Volume 414, 736 Seiten

Reihe: Methods in Enzymology

The critically acclaimed laboratory standard for more than forty years, Methods in Enzymology is one of the most highly respected publications in the field of biochemistry. Since 1955, each volume has been eagerly awaited, frequently consulted, and praised by researchers and reviewers alike. Now with more than 300 volumes (all of them still in print), the series contains much material still relevant today-truly an essential publication for researchers in all fields of life sciences.

Autoren/Hrsg.

Inglese, James

Inhaltsverzeichnis

1;Front Cover;1
2;Measuring Biological Responses with Automated Microscopy;4
3;Copyright Page;5
4;Table of Contents;6
5;Contributors to Volume 414;12
6;Preface;18
7;Volumes in Series;22
8;Chapter 1: Dynamic Green Fluorescent Protein Sensors for High- Content Analysis of the Cell Cycle;46
8.1;Introduction;46
8.2;Design and Construction of Dynamic Cell Cycle Sensors;48
8.3;Validation of Sensors;50
8.4;Cell Cycle Analysis by Automated High-Throughput Imaging for Drug Profiling and Target Validation;54
8.5;Conclusions and Future Directions;62
8.6;Acknowledgments;62
8.7;References;63
9;Chapter 2: High-Content Fluorescence-Based Screening for Epigenetic Modulators;66
9.1;Introduction;67
9.2;Epigenetic Regulators of Gene Expression as Drug Targets;68
9.3;Rationale for the Development of Cell-Based Assays to Screen for Epigenetic Modulators;69
9.4;Methodological Considerations;70
9.5;General Conclusions and Perspectives;79
9.6;References;80
10;Chapter 3: Development of Assays for Nuclear Receptor Modulators Using Fluorescently Tagged Proteins;82
10.1;Introduction;82
10.2;Methods;84
10.3;Perspectives and Future Applications;93
10.4;References;94
11;Chapter 4: The Ligand-Independent Translocation Assay: An Enabling Technology for Screening Orphan G Protein-Coupled Receptors by Arrestin Recruitment;95
11.1;Introduction;96
11.2;Overview of the LITe Assay;98
11.3;Utility of the LITe Assay;100
11.4;Conclusion;107
11.5;Acknowledgments;107
11.6;References;107
12;Chapter 5: High-Content Screening of Known G Protein-Coupled Receptors by Arrestin Translocation;108
12.1;Introduction;109
12.2;Stable Expression of a Known GPCR for the ArrestinGFP Translocation Assay;112
12.3;Screening Known Receptors with Transfluor Technology;118
12.4;Conclusion;122
12.5;Acknowledgments;122
12.6;References;123
13;Chapter 6: Cell Imaging Assays for G Protein-Coupled Receptor Internalization: Application to High-Throughput Screening;124
13.1;Introduction;124
13.2;Monitoring GPCR Trafficking via Receptor-GFP;126
13.3;Monitoring GPCR Trafficking via Receptor-Arrestin-GFP;130
13.4;Case I: MRG-X1 Receptor;131
13.5;Case Study 2: NK1 Receptor Trafficking;136
13.6;Acknowledgments;142
13.7;References;143
14;Chapter 7: High-Throughput Confocal Microscopy for ß-Arrestin-Green Fluorescent Protein Translocation G Protein-coupled Receptor Assays Using the Evotec Opera;144
14.1;Choice of Orphans;144
14.2;Transfluor;147
14.3;Technology;147
14.4;Image Analysis Algorithm;150
14.5;EC50 Fitting and Scoring;153
14.6;Assay Methods;154
14.7;Screen Metrics and Results;161
14.8;Concluding Remarks;163
14.9;References;164
15;Chapter 8: G Protein-Coupled Receptor Internalization Assays in the High-Content Screening Format;166
15.1;Introduction;166
15.2;High-Throughput Confocal Cellular Imaging Systems;167
15.3;GPCR Internalization Assays;168
15.4;Internalization Assay and Image Analysis Protocols;171
15.5;Conclusions and Outlook;178
15.6;Acknowledgment;182
15.7;References;182
16;Chapter 9: Screening for Activators of the Wingless Type/Frizzled Pathway by Automated Fluorescent Microscopy;185
16.1;Introduction;185
16.2;Use of Primary Human Preosteoblasts;187
16.3;Reagents and Materials;187
16.4;Preparation of L Cell Control- and Wnt3A-Conditioned Medium;188
16.5;Primary Preosteoblast Cell Culture and Compound Screening;188
16.6;Immunofluorescent Staining;189
16.7;Imaging and Quantitation of Nuclear Translocation;190
16.8;Data Analysis;193
16.9;Acknowledgments;193
16.10;References;193
17;Chapter 10: A Live Cell, Image-Based Approach to Understanding the Enzymology and Pharmacology of 2-Bromopalmitate and Palmitoylation;195
17.1;Introduction;196
17.2;Types of Protein Lipid Modifications;197
17.3;Palmitate Turnover;199
17.4;Enzymes for Depalmitoylation;200
17.5;Role of Palmitoylation in Development;201
17.6;Cysteines: Primary Sites of Palmitoylation;203
17.7;Palmitoyl Acyl Transferases (PATs);204
17.8;Links between Palmitoylation and Disease;205
17.9;Using Fluorescent Proteins to Study Protein Lipid Modifications;206
17.10;Monomeric Fluorescent Proteins: A Critical Feature for Studying Palmitoylation;206
17.11;High-Throughput Microscopy (HTM)/High-Content Screening (HCS) to Study Lipid-Modified Proteins;208
17.12;Morphometric Analysis of Palmitoylation with HCS;209
17.13;HCS Machine Vision Algorithms to Quantify Reporter Density on the Plasma Membrane;210
17.14;GAP43:YFP is Palmitoylated, Localized to the Plasma Membrane, and Is a Stereotypical Reporter of the Cellular Capacity for Palmitoylation;210
17.15;Determination of the Residence Half-Life of Palmitate on GAP43:YFP Using HCS;212
17.16;Thora Can Measure Precisely the Subcellular Distribution of GAP43:YFP: IC50 of 2BP;213
17.17;Determination of the Compatibility of the Cellular Reporter System with Dimethyl Sulfoxide (DMSO);216
17.18;Cytotoxic Effects of Antagonists of Palmitoylation;216
17.19;Considerations for Designing HCS, Cell-Based Assays with an Emphasis on Palmitoylation;219
17.20;Troubleshooting;221
17.21;System Error Identification;223
17.22;Data Tracking;223
17.23;Image Organization and Analysis;223
17.24;Conclusions;224
17.25;References;224
18;Chapter 11: High-Resolution, High-Throughput Microscopy Analyses of Nuclear Receptor and Coregulator Function;233
18.1;High-Throughput Microscopy (HTM);233
18.2;Steroid Nuclear Receptors and Coregulators;234
18.3;General Methods;236
18.4;Nuclear Receptor Coregulator SRC-3;240
18.5;Protein Expression Level Assay;241
18.6;Protein Translocation and Nuclear Variance Assays;245
18.7;Foci Identification and Chromatin Remodeling Assay;251
18.8;Conclusions;254
18.9;References;254
19;Chapter 12: Tracking Individual Proteins in Living Cells Using Single Quantum Dot Imaging;256
19.1;Introduction;256
19.2;Semiconductor Quantum Dots as Biological Probes;257
19.3;Single Molecule Imaging in Living Cells;258
19.4;Single Quantum Dot Tracking of Membrane Proteins;260
19.5;Solutions and Materials;261
19.6;Methods;262
19.7;Single Quantum Dot Tracking of Intracellular Proteins;262
19.8;Solutions and Materials;263
19.9;Methods;264
19.10;Imaging of Single Conjugated Quantum Dot in Living Cells;265
19.11;Analysis of Single QD trajectories;268
19.12;Image Processing and Extraction of Single QD Trajectories;268
19.13;Mean Square Displacement Function;270
19.14;Statistical Errors;271
19.15;Acknowledgments;271
19.16;References;271
20;Chapter 13: Development and Application of Automatic High-Resolution Light Microscopy for Cell-Based Screens;273
20.1;Introduction;274
20.2;Technical Description;275
20.3;Prospectives;290
20.4;Acknowledgments;290
20.5;References;291
21;Chapter 14: Adenoviral Sensors for High-Content Cellular Analysis;292
21.1;Introduction;293
21.2;Design and Construction of Adenoviral Sensors for Cellular Assays;294
21.3;Validation of Adenoviral Sensors;299
21.4;Application of Adenoviral Sensors to High-Content Analysis;299
21.5;EGFP-Glucocorticoid Receptor (GR) Translocation Sensor;300
21.6;Reagent Preparation;302
21.7;Assay Procedure;302
21.8;Assay Analysis;303
21.9;Nuclear Factor of Activated T Cells (NFAT) Nitroreductase Reporter Gene Sensor;304
21.10;Reagent Preparation;305
21.11;Assay Procedure;305
21.12;Assay Analysis;306
21.13;Conclusions and Future Perspectives;307
21.14;Acknowledgments;308
21.15;References;308
22;Chapter 15: Cell-Based Assays Using Primary Endothelial Cells to Study Multiple Steps in Inflammation;311
22.1;Cellular Mechanism of the Inflammatory Response;312
22.2;Cell-Based Assays Used to Monitor the Effects of Proinflammatory Cytokines;312
22.3;Materials and Methods Common to All Three Assays;315
22.4;Image Analysis;318
22.5;Statistical Analysis;319
22.6;Assay Data;319
22.7;Concluding Remarks and Future Perspectives;326
22.8;Acknowledgments;327
22.9;References;327
23;Chapter 16: Development and Implementation of Multiplexed Cell-Based Imaging Assays;329
23.1;Introduction;329
23.2;General Considerations;330
23.3;Monitoring Cell Cycle Progression;332
23.4;Protocols for Cell Cycle Analysis;334
23.5;Visualizing Apoptosis by Fluorescence Microscopy;337
23.6;Multiplexing Cell Cycle and Apoptosis Assays;341
23.7;Conclusions;344
23.8;Acknowledgments;344
23.9;References;345
24;Chapter 17: High-Throughput Screening for Modulators of Stem Cell Differentiation;345
24.1;Introduction;345
24.2;Assay Design;346
24.3;Assay Development;350
24.4;Methods;352
24.5;Conclusion;358
24.6;Appendix;358
24.7;Acknowledgments;360
24.8;References;360
25;Chapter 18: High-Content Kinetic Calcium Imaging in Drug-Sensitive and Drug-Resistant Human Breast Cancer Cells;362
25.1;Introduction;362
25.2;High-Content Analysis of Ca2+ Dynamics by Fluorescence Microscopy;364
25.3;Conclusions from HCA and Rationale for High-Content Screening;370
25.4;High-Content Screening;371
25.5;Acknowledgments;377
25.6;References;378
26;Chapter 19: Measurement and Analysis of Calcium Signaling in Heterogeneous Cell Cultures;380
26.1;Introduction;380
26.2;Characterization of Calcium Signaling in Rat Cortical Cultures;381
26.3;Subpopulation Analysis of Calcium Signaling in Cocultures;388
26.4;Acknowledgments;392
26.5;References;392
27;Chapter 20: Multiplex Analysis of Inflammatory Signaling Pathways Using a High-Content Imaging System;393
27.1;Introduction;393
27.2;Assay Procedures;394
27.3;Concluding Remarks;407
27.4;Acknowledgments;407
27.5;References;407
28;Chapter 21: Generation and Characterization of a Stable MK2- EGFP Cell Line and Subsequent Development of a High-Content Imaging Assay on the Cellomics ArrayScan Platform to Screen for p38 Mitogen...;409
28.1;Introduction;409
28.2;Definition of the Cell Model;411
28.3;Generation and Characterization of MK2-EGFP HeLa Cell Line;412
28.4;Cellomics ArrayScan Automated Imaging Platform;414
28.5;Characterization of MK2-EGFP Clones via Imaging;417
28.6;Characterization of the p38 MAPK Signaling Pathway in HeLa-MK2-EGFP Cells;420
28.7;Assay Development on the ArrayScan 3.1 Imaging Platform;421
28.8;Standard Operating Procedure for the MK2-EGFP Translocation Assay;423
28.9;MK2-EGFP Translocation Assay Reproducibility and Signal Widow Evaluation;423
28.10;p38 Inhibitor Data;425
28.11;Secondary Analysis Parameters;425
28.12;Discussion;429
28.13;References;432
29;Chapter 22: Development and Implementation of Three Mitogen-Activated Protein Kinase (MAPK) Signaling Pathway Imaging Assays to Provide MAPK Module Selectivity Profiling for KInase Inhibitors: MK2...;434
29.1;Introduction;435
29.2;Definition of the Cell Model;436
29.3;Cellomics ArrayScan Automated Imaging Platform;439
29.4;Development of the JNK MAPK Signaling Pathway Assay;440
29.5;c-Jun Activation Protocol;444
29.6;c-Jun Activation Signal Window and Reproducibility;445
29.7;Development of the ERK MAPK Signaling Pathway Assay;446
29.8;ERK1/2 Activation Protocol;451
29.9;ERK1/2 Activation Signal Window and Reproducibility;452
29.10;MAPK Pathway Inhibitor Test Cassette;453
29.11;p38 Inhibitor Hit Assessment;458
29.12;p38a Inhibitor Profiling;458
29.13;JNK Inhibitor Profiling;459
29.14;Discussion;462
29.15;References;462
30;Chapter 23: Assay Development and Case History of a 32K-Biased Library High-Content MK2-EGFP Translocation Screen to Identify p38 Mitogen-Activated Protein Kinase Inhibitors on the ArrayScan 3.1 Imaging Platform;464
30.1;Introduction;464
30.2;Cellomics ArrayScan Automated Imaging Platform;465
30.3;Conversion of the 96-Well MK2-EGFP Translocation Assay to a 384-Well Format Assay on the Arrayscanreg Imager;466
30.4;MK2-EGFP Translocation Assay Reproducibility and Signal Widow Evaluation;470
30.5;Standardized Operation Procedure for the MK2-EGFP Translocation Assay;474
30.6;MK2-EGFP Translocation HTS Assay for p38 Inhibitors;474
30.7;Discussion;480
30.8;References;483
31;Chapter 24: Compound Classification Using Image-Based Cellular Phenotypes;485
31.1;Introduction;485
31.2;Quantifying Cellular Morphology Changes;486
31.3;Cell Culture, Compound Addition, and Image Acquisition;487
31.4;Image and Data Reduction;489
31.5;Analysis of Quantitative Cellular Phenotypes across Cell Lines;492
31.6;Clustering and Classification of Compounds;503
31.7;Conclusions;506
31.8;Acknowledgments;511
31.9;References;511
32;Chapter 25: High-Content Screening: Emerging Hardware and Software Technologies;513
32.1;Introduction;513
32.2;Cellular Assay and Imaging Preparation;514
32.3;Image Acquisition;515
32.4;Image Analysis;521
32.5;Image Database and Data Visualization Tools;523
32.6;Conclusion;526
32.7;Protocols;526
32.8;References;528
33;Chapter 26: An Infrastructure for High-Throughput Microscopy: Instrumentation, Informatics, and Integration;529
33.1;Introduction;529
33.2;Assay Processing;532
33.3;Image Acquisition;540
33.4;Image and Data Analysis;544
33.5;Data Review and Quality Control;552
33.6;Summary;556
33.7;Acknowledgments;557
33.8;References;557
34;Chapter 27: Protein Translocation Assays: Key Tools for Accessing New Biological Information with High-Throughput Microscopy;558
34.1;Pathway Screening Using BioImage Redistribution Technology;558
34.2;p53-Hdm2 Protein-Protein Interaction Assay;561
34.3;Use of High-Content Assays in RNAi Studies;565
34.4;Use of siRNA-Mediated Knockdown to Validate Akt Isoform Dependency of a FKHR Redistribution Assay;567
34.5;Assay-Specific Cell-to-Cell Heterogeneity Plays a Role in Assay Quality;571
34.6;Future Developments;573
34.7;References;574
35;Chapter 28: High-Content Screening of Functional Genomic Libraries;575
35.1;Introduction;576
35.2;Development of Large-Scale Genomic Libraries;577
35.3;Maintaining Large Arrayed-Well Plasmid cDNA or shRNA Clone Libraries;581
35.4;Collection Replication;583
35.5;Growth of Bacterial Cultures in High-Throughput Format for DNA Preparation;584
35.6;Preparing DNA from 96-Well Deep-Well Block Cultures;585
35.7;Normalization of Plasmid DNA;587
35.8;Arraying Collections into High-Throughput Assay Plates;588
35.9;High-Throughput Transfections;590
35.10;High-Throughput Retroviral/Lentivial Packaging;592
35.11;Instrumentation Required for Functional Genomics Screening;594
35.12;Automated Microscopy;594
35.13;High-Throughput HCS Equipment;596
35.14;Fluorescent Biomarkers for HCS Applications;599
35.15;Preparing Samples for Automated Microscopy;601
35.16;Determining Transfection or Transduction Efficiency;603
35.17;Quantitative Image Analysis;604
35.18;Summary;607
35.19;References;609
36;Chapter 29: Fluorescent Protein-Based Cellular Assays Analyzed by Laser-Scanning Microplate Cytometry in 1536-Well Plate Format;611
36.1;Introduction;611
36.2;The Principle of Laser-Scanning Microplate Cytometers;613
36.3;General Methods;614
36.4;GR-GFP Nuclear Translocation Assay;616
36.5;Locus Derepression Assay;621
36.6;ß-Arrestin:ß2-Adrenergic Receptor (ßARR:ß2AR) Protein Fragment Complementation Assay;625
36.7;Summary;631
36.8;Acknowledgments;632
36.9;References;632
37;Chapter 30: High-Throughput Measurements of Biochemical Responses Using the Plate::Vision Multimode 96 Minilens Array Reader;634
37.1;Introduction;634
37.2;Instrumentation;635
37.3;Measurements of Biochemical Responses;639
37.4;Acknowledgments;645
37.5;References;645
38;Chapter 31: Systems Cell Biology Based on High-Content Screening;646
38.1;Background;646
38.2;The Systems Cell Biology Toolbox;649
38.3;Example Systems Cell Biology Profile;655
38.4;Summary and Conclusions;658
38.5;Prospectus;659
38.6;Acknowledgments;661
38.7;References;661
39;Chapter 32: Digital Autofocus Methods for Automated Microscopy;665
39.1;Introduction;665
39.2;Hardware;666
39.3;Software;669
39.4;Viscoelasticity;672
39.5;Multiple-Field Scans;674
39.6;Conclusion;674
39.7;Appendix;675
39.8;References;677
40;Chapter 33: Fluorescence Lifetime Imaging Microscopy: Two-Dimensional Distribution Measurement of Fluorescence Lifetime;678
40.1;Introduction;678
40.2;Operating Principle of a Streak Camera;679
40.3;Configuration of the FLIM System;681
40.4;Streak Image;681
40.5;Measurement Principle of FLIM System;681
40.6;System Calibration;683
40.7;Lifetime Imaging in Cells;684
40.8;FRET Imaging in Cells;685
40.9;Acknowledgments;687
40.10;References;687
41;Author Index;688
42;Subject Index;724

Leseproben

[1] Dynamic Green Fluorescent Protein Sensors for High-Content Analysis of the Cell Cycle
Simon Stubbs; Nick Thomas Abstract
We have developed two dynamic sensors that report cell cycle position in living mammalian cells. The sensors use well-characterized components from proteins that are spatially and temporally regulated through the cell cycle. Coupling of these components to Enhanced Green Fluorescent Protein (EGFP) has been used to engineer fusion proteins that report G1/S and G2/M transitions during the cell cycle without perturbing cell cycle progression. Expression of these sensors in stable cell lines allows high content analysis of the effects of drugs and gene knockdown on the cell cycle using automated image analysis to determine cell cycle position and to abstract correlative data from multiplexed sensors and morphological analysis. Introduction
The cell cycle is one of the most fundamental and complex processes in biology and influences the development, life, and, in cases where it goes wrong, the death of all eukaryotes. Progression of a cell through four phases, G1, S, G2, and M, is exquisitely regulated by a series of checks and balances to ensure that DNA is correctly maintained, replicated, and segregated into daughter cells at division. The cell cycle and its control mechanisms have been studied extensively for over a century (Nurse, 2000), and significant advances have been made in identifying and describing the role of components and their regulatory mechanisms. Understanding of the cell cycle has progressed to a point where the basic circuitry can be mapped (Kohn, 1999), and ongoing research continues to refine our understanding of the interplay between the players in this game of life (Aleem et al., 2005; Cobrinik, 2005; Fu et al., 2004; Sherr and Roberts, 2004). Much work remains, and study of the basic molecular mechanisms followed by integration of these mechanisms into a full understanding of cell cycle control and regulation will engage researchers for many years to come (Nurse, 2000a). The aim of these studies has been twofold: to understand cell cycle control as a key biological process and to gain a greater understanding of the process as an aid in the selection of targets and development of effective drugs for use against the aberrant cell cycle in oncology (Carnero, 2002; Gillessen et al., 2002; Hamel and Covell, 2002; Sampath and Plunkett, 2001; Stewart et al., 2003; Vermeulen et al., 2003) and other fields, including cardiovascular (Bicknell et al., 2003), neurological (Arendt, 2002) and hepatic (Horie et al., 2003) disease, stroke (O'Hare et al., 2002), and HIV infection (Galati et al., 2002). Cancer is characterized by deregulated cell cycle control. In contrast to normal cells proliferating only in response to developmental or other mitogenic signals, tumor cell proliferation proceeds automatously. The cell cycle in a cancer cell is not necessarily different from that of a normal cycling cell, but in the cancer cell the accelerator and braking mechanisms that normally control cell cycle progression to give a cell time to repair damaged DNA and to respond to mitogenic stimuli or differentiative inhibition have become decoupled from the cell cycle engine. In oncology, opportunities for target identification and drug development exist at both G1/S and G2/M transitions as intervention points to target the cell cycle in tumor cells. The G2/M transition has traditionally been the focus of attention, resulting in the development of drugs such as taxol (Hadfield et al., 2003), which interfere with the mechanics of cell division. In more recent programs, new G2/M cell cycle control targets, such as histone deacetylase (Wong et al., 2005), aurora kinases (Mortlock et al., 2005), Polo-like kinases (PLK) (Blagden and de Bono, 2005), and the G2 checkpoint proteins CHK1 (Li and Zhu, 2002) and CHK2 (Kawabe, 2004), continue to be evaluated and targeted. At the G1/S transition, targets involved in DNA repair and replication, including DNA helicases (Sharma et al., 2005), poly(ADP-ribose) polymerase (Jagtap and Szabo, 2005), topoisomerases (Pommier et al., 2003), and the MCM complex (Lei, 2005), together with targets controlling G1–S progression, including CDKs (Owa et al., 2001), mTOR (Dutcher, 2004), and pRB/E2F (Seville et al., 2005), offer alternative approaches to selectively targeting the aberrant cell cycle in cancer cells. Despite advances in knowledge of the mechanics of the process, the techniques routinely used to study the cell cycle and related events have remained essentially unchanged for many years. Proliferation assays that measure cell numbers (Denizot and Lang, 1986) or radiolabeled thymidine (Graves et al., 1997) incorporation can be used to obtain a relatively crude population averaged response to an experimental condition, that is, whether cell growth is stimulated or inhibited, but in asynchronous cells these methods cannot give any indication of which part of the cell cycle is being affected. Higher-resolution methods, including flow cytometry (Smith et al., 2000), bromodeoxyuridine incorporation (Humbert et al., 1990), and other immunofluorescence techniques (Yuan et al., 2002), allow analysis of cell cycle status at the individual cell level and can be used to determine the distribution of a population of cells around the cell cycle. Despite their widespread use, all of the aforementioned methods lack the ability to provide a fully dynamic description of the cell cycle in individual cells. Recent developments in understanding of the control mechanisms of the cell cycle and methods for engineering genetically encoded fluorescent sensors (Tsien, 1998; Zhang et al., 2002) have made it possible to design novel cell cycle sensors based on key cell cycle control molecules. When coupled with advances in high-throughput cellular analysis instruments (Lundholt et al., 2005; Ramm and Thomas, 2003), these sensors enable high-content analysis of the cell cycle and a high-definition view of the effects of candidate drugs. Design and Construction of Dynamic Cell Cycle Sensors
Application of fluorescent proteins to cell cycle analysis has enabled significant advances to be made in understanding the timing of molecular events that control the cell cycle. While green fluorescent protein (GFP) fusions with key cell cycle control proteins (Arnaud et al., 1998; Huang and Raff, 1999; Raff et al., 2002; Weingartner et al., 2001; Zeng et al., 2000) and other proteins (Kanda et al., 1998; Reits et al., 1997; Tatebe et al., 2001) have provided very significant insights into the molecular mechanics of the cell cycle, expression of cell cycle protein fusions that retain enzyme or structural activity have the potential to perturb the cell cycle and are therefore not suitable as cell cycle sensors (Clute and Pines, 1999). To provide nonperturbing stealth cell cycle sensors we have developed constructs (Fig. 1) based on the fusion of EGFP to domains isolated from well-characterized cell cycle control and response proteins. The first of these sensors reports on the G1/S transition and the second reports on the G2/M transition. Fig. 1 EGFP cell cycle phase markers. Constitutive expression of the G1/S sensor (A) is achieved via a ubiquitin C (UbC) promoter driving production of a fusion protein between EGFP and the C-terminal region of human DNA helicase B containing a phosphorylation and subcellular localization domain (PSLD). The fluorescent fusion protein localizes to the nucleus in G1 cells (B) and undergoes translocation to the cytoplasm as cells progress through S phase and into G2. Expression of the G2/M sensor (C) is controlled by the cyclin B1 (CCNB1) promoter, which initiates production of the cyclin B1–EGFP fusion protein in late S phase. As cells progress through late S phase into G2, fluorescence increases in the cytoplasm (D) until phosphorylation of the cytoplasmic retention sequence (CRS) causes translocation of the sensor to the nucleus at prophase. At anaphase the sensor is degraded rapidly mediated by the cyclin B1 destruction box (D-box) producing two nonfluorescent daughter cells following mitosis. The G1/S cell cycle phase marker (Fig. 1A and B) is derived from the human homologue of helicase B (HELB), a protein that is essential for G1/S transition (Taneja et al., 2002). HELB has been demonstrated to be localized at nuclear foci induced by DNA damage (Gu et al., 2004), where the protein operates during G1 to process endogenous DNA damage prior to the G1/S transition. Consistent with the proposed action of HELB, the protein resides in the nucleus during G1 but is predominantly cytoplasmic in S and G2 phase cells. Cell cycle-coordinated nuclear and cytoplasmic residence is controlled by a 131 amino acid C-terminal phosphorylation-dependent subcellular localization control domain (PSLD) containing a nuclear localization sequence that retains the protein in...