Waters / Wittmann Quantitative Imaging in Cell Biology

1. Auflage 2014
ISBN: 978-0-12-420201-6
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, Band 123, 588 Seiten

Reihe: Methods in Cell Biology

This new volume, number 123, of Methods in Cell Biology looks at methods for quantitative imaging in cell biology. It covers both theoretical and practical aspects of using optical fluorescence microscopy and image analysis techniques for quantitative applications.  The introductory chapters cover fundamental concepts and techniques important for obtaining accurate and precise quantitative data from imaging systems. These chapters address how choice of microscope, fluorophores, and digital detector impact the quality of quantitative data, and include step-by-step protocols for capturing and analyzing quantitative images. Common quantitative applications, including co-localization, ratiometric imaging, and counting molecules, are covered in detail. Practical chapters cover topics critical to getting the most out of your imaging system, from microscope maintenance to creating standardized samples for measuring resolution. Later chapters cover recent advances in quantitative imaging techniques, including super-resolution and light sheet microscopy. With cutting-edge material, this comprehensive collection is intended to guide researchers for years to come. - Covers sections on model systems and functional studies, imaging-based approaches and emerging studies - Chapters are written by experts in the field - Cutting-edge material

Autoren/Hrsg.

Waters, Jennifer

Wittmann, Torsten

Inhaltsverzeichnis

1;Front Cover;1
2;Quantitative Imaging in Cell Biology;4
3;Copyright;5
4;Contents;6
5;Contributors;14
6;Preface;20
7;Chapter 1: Concepts in quantitative fluorescence microscopy;22
7.1;1.1. Accurate and Precise Quantitation;23
7.2;1.2. Signal, Background, and Noise;24
7.3;1.3. Optical Resolution: The Point Spread Function;28
7.4;1.4. Choice of Imaging Modality;28
7.5;1.5. Sampling: Spatial and Temporal;29
7.5.1;1.5.1. 2D sampling;31
7.5.2;1.5.2. 3D sampling;32
7.5.3;1.5.3. Temporal sampling;33
7.6;1.6. Postacquisition Corrections;33
7.6.1;1.6.1. Background subtraction;33
7.6.2;1.6.2. Flat-field correction;34
7.6.3;1.6.3. Photobleaching;35
7.6.4;1.6.4. Storing and processing images for quantitation;35
7.7;1.7. Making Compromises;36
7.8;1.8. Communicating Your Results;37
7.9;Acknowledgment;37
7.10;References;37
8;Chapter 2: Practical considerations of objective lenses for application in cell biology;40
8.1;Introduction;41
8.2;2.1. Optical Aberrations;41
8.2.1;2.1.1. On-axis aberrations;43
8.2.2;2.1.2. Off-axis aberrations;43
8.3;2.2. Types of Objective Lenses;43
8.3.1;2.2.1. Optical corrections;44
8.3.2;2.2.2. Numerical aperture;46
8.4;2.3. Objective Lens Nomenclature;46
8.5;2.4. Optical Transmission and Image Intensity;46
8.6;2.5. Coverslips, Immersion Media, and Induced Aberration;48
8.6.1;2.5.1. Optical path length;48
8.6.2;2.5.2. Correction collars;49
8.6.3;2.5.3. Cover glass;50
8.6.4;2.5.4. Immersion media;51
8.7;2.6. Considerations for Specialized Techniques;52
8.8;2.7. Care and Cleaning of Optics;53
8.9;Conclusions;55
8.10;References;55
9;Chapter 3: Assessing camera performance for quantitative microscopy;56
9.1;3.1. Introduction to Digital Cameras for Quantitative Fluorescence Microscopy;57
9.2;3.2. Camera Parameters;58
9.2.1;3.2.1. Quantum efficiency;58
9.2.2;3.2.2. Noise;58
9.2.3;3.2.3. Poisson noise;58
9.2.4;3.2.4. Camera noise;60
9.2.5;3.2.5. Fixed-Pattern noise;60
9.2.6;3.2.6. Digitization, bit depth, and dynamic range;61
9.2.7;3.2.7. Amplification;62
9.2.8;3.2.8. sCMOS considerations;64
9.3;3.3. Testing Camera Performance: The Photon Transfer Curve;65
9.3.1;3.3.1. Photon transfer theory;65
9.3.2;3.3.2. PTC collection protocol;67
9.4;References;73
10;Chapter 4: A Practical guide to microscope care and maintenance;76
10.1;Introduction;77
10.2;4.1. Cleaning;79
10.2.1;4.1.1. Before cleaning;79
10.2.2;4.1.2. Objectives;80
10.2.2.1;4.1.2.1. Proper use of objective lenses;80
10.2.2.2;4.1.2.2. Objective lens inspection and cleaning;81
10.2.2.3;4.1.2.3. Temperature;83
10.2.3;4.1.3. Fluorescence filters;83
10.2.3.1;4.1.3.1. Excitation and emission filters;84
10.2.3.2;4.1.3.2. Mirrors;85
10.2.4;4.1.4. Camera;85
10.2.5;4.1.5. The dust is still there!;86
10.3;4.2. Maintenance and Testing;87
10.3.1;4.2.1. Computer maintenance;87
10.3.2;4.2.2. Check the transmitted light pathway;87
10.3.3;4.2.3. Measure intensity of fluorescence light sources;88
10.3.4;4.2.4. Flatness of fluorescence illumination;92
10.3.5;4.2.5. Color registration;92
10.3.6;4.2.6. Vibration;93
10.3.7;4.2.7. Measure the point spread function;94
10.3.8;4.2.8. Test performance of motorized components and software;94
10.4;4.3. Considerations for New System Installation;95
10.5;Acknowledgments;96
10.6;References;96
11;Chapter 5: Fluorescence live cell imaging;98
11.1;5.1. Fluorescence Microscopy Basics;99
11.2;5.2. The Live Cell Imaging Microscope;100
11.3;5.3. Microscope Environmental Control;104
11.3.1;5.3.1. Temperature;104
11.3.2;5.3.2. Media composition and pH;105
11.3.3;5.3.3. Imaging chambers;106
11.4;5.4. Fluorescent Proteins;108
11.4.1;5.4.1. Protocol for analyzing FP photobleaching;111
11.5;5.5. Other Fluorescent Probes;113
11.6;Conclusion;114
11.7;Acknowledgments;114
11.8;References;114
12;Chapter 6: Fluorescent proteins for quantitative microscopy: Important properties and practical evaluation;116
12.1;6.1. Optical and Physical Properties Important for Quantitative Imaging;117
12.1.1;6.1.1. Color and brightness;117
12.1.2;6.1.2. Photostability;119
12.1.3;6.1.3. Other properties;119
12.2;6.2. Physical Basis for Fluorescent Protein Properties;120
12.2.1;6.2.1. Determinants of wavelength;120
12.2.2;6.2.2. Determinants of brightness;121
12.3;6.3. The Complexities of Photostability;122
12.3.1;6.3.1. Multiple photobleaching pathways;123
12.3.2;6.3.2. Photobleaching behaviors;123
12.3.3;6.3.3. Reporting standards for FP photostability;127
12.4;6.4. Evaluation of Fluorescent Protein Performance in Vivo;127
12.4.1;6.4.1. Cell-line-specific photostability and contrast evaluation;128
12.4.1.1;Protocol;128
12.4.2;6.4.2. Fusion Protein-specific FP evaluation;129
12.5;Conclusion;129
12.6;References;130
13;Chapter 7: Quantitative confocal microscopy: Beyond a pretty picture;134
13.1;7.1. The Classic Confocal: Blocking Out the Blur;135
13.2;7.2. You Call that quantitative?;139
13.2.1;7.2.1. Quantitative imaging toolkit;139
13.2.2;7.2.2. Localization and morphology;140
13.2.3;7.2.3. Quantifying intensity;141
13.2.3.1;7.2.3.1. Aspects of the microscope;141
13.2.3.2;7.2.3.2. Aspects of the sample;142
13.2.3.2.1;7.2.3.2.1. Mounting media;142
13.2.3.2.2;7.2.3.2.2. Coverslips;144
13.2.3.2.3;7.2.3.2.3. Sample labeling;144
13.3;7.3. Interaction and Dynamics;144
13.3.1;7.3.1. Cross talk;144
13.3.2;7.3.2. Time-lapse imaging;145
13.3.3;7.3.3. Spectral imaging;146
13.4;7.4. Controls: Who Needs Them?;146
13.4.1;7.4.1. Unlabeled sample;146
13.4.2;7.4.2. Nonspecific binding controls;146
13.4.3;7.4.3. Antibody titration curves;146
13.4.4;7.4.4. Isotype controls;147
13.4.5;7.4.5. Blind imaging;148
13.4.6;7.4.6. Fluorescent proteins;148
13.4.7;7.4.7. Flat-field images;148
13.4.8;7.4.8. Biological control samples;148
13.5;7.5. Protocols;148
13.5.1;7.5.1. Protocol 1: Measuring instrument PSF (Resolution and objective Lens Quality);148
13.5.1.1;Imaging;148
13.5.2;7.5.2. Protocol 2: Testing short-term and long-term laser power stability;150
13.5.2.1;Slide;150
13.5.2.2;Data Collection;150
13.5.2.3;Data Analysis;150
13.5.3;7.5.3. Protocol 3: Correct nonuniform field illumination;150
13.5.3.1;Slide;150
13.5.3.2;Data Collection;150
13.5.3.3;Data Analysis;150
13.5.4;7.5.4. Protocol 4: Coregistration of TetraSpeck beads;151
13.5.4.1;Slide;151
13.5.4.2;Data Collection;151
13.5.4.3;Data Analysis;151
13.5.5;7.5.5. Protocol 5: Spectral accuracy;151
13.5.5.1;Slides;151
13.5.5.2;Data Collection;151
13.5.5.3;Data Analysis;152
13.5.6;7.5.6. Protocol 6: Spectral Unmixing algorithm accuracy;152
13.5.6.1;Slide;152
13.5.6.2;7.5.6.1. Channel (Multi-PMT) method;152
13.5.6.3;7.5.6.2. Separation (Unmixing);153
13.5.6.4;7.5.6.3. Spectral detection method;153
13.6;Conclusions;154
13.7;References;154
14;Chapter 8: Assessing and benchmarking multiphoton microscopes for biologists;156
14.1;Introduction: Practical Quantitative 2P Benchmarking;157
14.2;8.1. Part I: Benchmarking Inputs;157
14.2.1;8.1.1. Laser power at the sample;158
14.2.2;8.1.2. Photomultiplier settings;159
14.2.2.1;8.1.2.1. Method 1—Fixed PMT voltage;160
14.2.2.2;8.1.2.2. Method 2—PMT voltage range;161
14.2.3;8.1.3. Standard samples;161
14.2.3.1;8.1.3.1. A standard three-dimensional sample set with variable dispersive properties;162
14.2.3.1.1;8.1.3.1.1. Support protocol: Preparation of PSF beads in a dispersive or nondispersive support;162
14.2.3.2;8.1.3.2. Standard biological samples;164
14.2.4;8.1.4. Sample-Driven parameters: How fast/How long;164
14.3;8.2. Part II: Benchmarking Outputs;165
14.3.1;8.2.1. The point spread function;165
14.3.2;8.2.2. SNR and total intensity;167
14.3.3;8.2.3. Maximal depth of acquisition;169
14.4;8.3. Troubleshooting/Optimizing;171
14.5;8.4. A Recipe for Purchasing Decisions;171
14.6;Conclusion;172
14.7;Acknowledgments;172
14.8;References;172
15;Chapter 9: Spinning-disk confocal microscopy: present technology and future trends;174
15.1;9.1. Principle of Operation;174
15.2;9.2. Strengths and Weaknesses;176
15.3;9.3. Improvements in Light Sources;178
15.4;9.4. Improvements in Illumination;178
15.5;9.5. Improvements in Optical Sectioning and FOV;183
15.6;9.6. New Detectors;187
15.7;9.7. A Look into the Future;188
15.8;References;192
16;Chapter 10: Quantitative deconvolution microscopy;198
16.1;Introduction;199
16.2;10.1. The Point-spread Function;201
16.3;10.2. Deconvolution Microscopy;203
16.3.1;10.2.1. Deblurring;204
16.3.2;10.2.2. Image restoration;205
16.3.3;10.2.3. Fourier transforms;205
16.3.4;10.2.4. Iterative methods;206
16.3.5;10.2.5. The importance of image quality;207
16.3.5.1;10.2.5.1. Factors that affect image restoration;207
16.4;10.3. Results;208
16.4.1;10.3.1. Assessing linearity;210
16.4.2;10.3.2. Applications of deconvolution microscopy;211
16.5;Conclusion;212
16.6;References;212
17;Chapter 11: Light sheet microscopy;214
17.1;Introduction;215
17.2;11.1. Principle of Light Sheet Microscopy;216
17.2.1;11.1.1. Light sheet illumination;216
17.2.2;11.1.2. Wide-Field detection;217
17.2.3;11.1.3. Large samples;219
17.3;11.2. Implementations of Light Sheet Microscopy;219
17.3.1;11.2.1. Light sheet properties;219
17.3.2;11.2.2. How to generate a light sheet;220
17.3.3;11.2.3. Vertical versus horizontal arrangements;222
17.3.4;11.2.4. Microscope built around the sample;222
17.3.5;11.2.5. Objective lenses;224
17.4;11.3. Mounting a Specimen for Light Sheet Microscopy;224
17.4.1;11.3.1. Solid gel cylinder;224
17.4.2;11.3.2. Tube embedding;226
17.5;11.4. Acquiring Data;226
17.5.1;11.4.1. Orienting the specimen;228
17.5.2;11.4.2. Light sheet alignment;228
17.5.2.1;11.4.2.1. Adjusting the light sheet height;228
17.5.2.2;11.4.2.2. Adjusting the light sheet thickness;229
17.5.2.3;11.4.2.3. Correct position of the beam waist;229
17.5.2.4;11.4.2.4. Moving the sheet in focus;230
17.5.2.5;11.4.2.5. Eliminating tilt;230
17.5.3;11.4.3. Choosing the right imaging parameters;230
17.6;11.5. Handling of Light Sheet Microscopy Data;231
17.6.1;11.5.1. Coping with high-Speed and large data;231
17.6.2;11.5.2. Image enhancements;232
17.6.3;11.5.3. Multiview fusion;232
17.6.4;11.5.4. Image Analysis;233
17.7;References;233
18;Chapter 12: DNA curtains: Novel tools for imaging protein–nucleic acid interactions at the single-molecule level;238
18.1;Introduction;239
18.2;12.1. Overview of TIRFM;240
18.3;12.2. Flow Cell Assembly;241
18.4;12.3. Importance of the Lipid Bilayer;242
18.5;12.4. Barriers to Lipid Diffusion;243
18.6;12.5. Different Types of DNA Curtains;244
18.6.1;12.5.1. Single-Tethered curtains;244
18.6.2;12.5.2. Double-Tethered DNA curtains;244
18.6.3;12.5.3. Parallel array of double-Tethered isolated patterns and crisscrossed DNA curtains;246
18.6.4;12.5.4. ssDNA curtains;246
18.7;12.6. Using DNA Curtains to Visualize Protein-DNA Interactions;247
18.7.1;12.6.1. Binding site preferences;247
18.7.2;12.6.2. Target search mechanisms;248
18.7.3;12.6.3. Protein–Protein colocalization;252
18.7.4;12.6.4. ATP hydrolysis-Driven DNA translocation;252
18.7.5;12.6.5. Beyond nucleic acids;252
18.8;12.7. Future Perspectives;253
18.9;Acknowledgments;253
18.10;References;253
19;Chapter 13: Nanoscale cellular imaging with scanning angle interference microscopy;256
19.1;Introduction;257
19.1.1;Superresolution optical imaging;257
19.1.2;Theory of SAIM;259
19.2;13.1. Experimental Methods and Instrumentation;262
19.2.1;13.1.1. Microscope and instrumentation;262
19.2.2;13.1.2. Preparation of reflective substrates;263
19.2.3;13.1.3. Selection of fluorescent probes;263
19.2.4;13.1.4. Cell culture and transfection;264
19.2.5;13.1.5. Immunolabeling of samples;265
19.2.6;13.1.6. Microscope calibration and configuration;267
19.2.7;13.1.7. Image acquisition;268
19.3;13.2. Image Analysis and Reconstruction;271
19.4;Conclusion;271
19.5;Acknowledgments;272
19.6;References;272
20;Chapter 14: Localization microscopy in yeast;274
20.1;Introduction;275
20.2;14.1. Preparing the Yeast Strain;277
20.3;14.2. Considerations for the Choice of a Labeling Strategy;278
20.4;14.3. Preparing the Sample;281
20.4.1;14.3.1. Immobilizing and fixing the yeast cells on coverslips;281
20.4.1.1;14.3.1.1. Materials and reagents;281
20.4.1.1.1;14.3.1.1.1. ConA-coated coverslips;281
20.4.1.1.2;14.3.1.1.2. ConA-cross-linked coverslips;282
20.4.1.2;14.3.1.2. Procedure;282
20.4.2;14.3.2. Labeling with organic dyes;283
20.4.2.1;14.3.2.1. Materials and reagents;283
20.4.2.1.1;14.3.2.1.1. Labeling of anti-GFP nanobodies with Alexa Fluor 647;284
20.4.2.1.2;14.3.2.1.2. Labeling of ConA with CF™ 680;284
20.4.2.2;14.3.2.2. Procedure: Nanobody or SNAP-tag staining;285
20.4.2.3;14.3.2.3. Procedure: ConA staining;285
20.5;14.4. Image Acquisition;285
20.5.1;14.4.1. Materials;285
20.6;14.5. Results;286
20.7;Summary;288
20.8;Acknowledgments;290
20.9;References;290
21;Chapter 15: Imaging cellular ultrastructure by PALM, iPALM, and correlative iPALM-EM;294
21.1;Introduction;295
21.2;15.1. Principles;296
21.2.1;15.1.1. 2D superresolution microscopy by Photoactivated Localization Microscopy (PALM);296
21.2.2;15.1.2. 3D superresolution by iPALM;296
21.3;15.2. Methods;298
21.3.1;15.2.1. Instrumentation for PALM;298
21.3.2;15.2.2. Fluorophore choice and sample preparation for PALM and iPALM;300
21.3.3;15.2.3. Fiducial-Based alignment: Drift correction and multichannel registration;304
21.3.4;15.2.4. Implementation of iPALM;307
21.3.5;15.2.5. Extending iPALM imaging depth with astigmatic defocusing;311
21.4;15.3. Future Directions;311
21.5;Acknowledgments;312
21.6;References;313
22;Chapter 16: Seeing more with structured illumination microscopy;316
22.1;Introduction;317
22.2;16.1. Theory of Structured Illumination;318
22.2.1;16.1.1. 2D image formation;318
22.2.2;16.1.2. Structured illumination;319
22.2.3;16.1.3. SIM combined with total internal reflection fluorescence Microscopy;322
22.3;16.2. 3D SIM;323
22.3.1;16.2.1. 3D image formation;323
22.3.2;16.2.2. 3D SIM theory;324
22.3.3;16.2.3. Practical implementations of 3D SIM;326
22.4;16.3. SIM Imaging Examples;328
22.4.1;16.3.1. TIRF SIM application;328
22.4.2;16.3.2. 3D SIM applications;328
22.5;16.4. Practical Considerations and Potential Pitfalls;331
22.6;16.5. Discussion;332
22.7;References;333
23;Chapter 17: Structured illumination superresolution imaging of the cytoskeleton;336
23.1;Introduction;337
23.1.1;Superresolution microscopy;337
23.1.2;SIM for imaging of the cytoskeleton;337
23.2;17.1. Instrumentation for SIM Imaging;337
23.2.1;17.1.1. Illumination pattern;338
23.2.2;17.1.2. Objective and camera;338
23.2.3;17.1.3. Reconstruction and judging of SIM images;342
23.3;17.2. Sample Preparation;343
23.3.1;17.2.1. Materials;343
23.3.1.1;Coverslip dishes;343
23.3.1.2;Fixative;343
23.3.1.3;Primary antibodies;343
23.3.1.4;Secondary antibodies;343
23.3.1.5;Fluorescent dyes;343
23.3.1.6;Mounting and index matching;343
23.3.1.7;Bead samples;343
23.3.2;17.2.2. Choice of fluorophore and staining;343
23.3.2.1;Indirect immunofluorescence;344
23.3.2.2;Genetically encoded fluorescence (fusion proteins with fluorescent proteins);344
23.3.3;17.2.3. Fixation;344
23.3.4;17.2.4. Index matching and embedding of sample;344
23.4;17.3. Minimizing Spherical Aberration;345
23.4.1;17.3.1. What is spherical aberration and when does it occur;345
23.4.2;17.3.2. Steps to minimize spherical aberration on the microscope;346
23.4.2.1;Prepare bead sample;346
23.4.2.2;Measure point spread function;347
23.4.2.3;Qualitative assessment of PSF;347
23.4.2.4;Quantitative assessment;347
23.5;17.4. Multichannel SIM;348
23.5.1;17.4.1. Setting up multicolor SIM;348
23.5.2;17.4.2. Correction for chromatic shift;349
23.5.3;17.4.3. Colocalization;349
23.5.4;17.4.4. Notes on quantitative analysis of intensity distribution;349
23.6;17.5. Live Imaging with SIM;351
23.7;Acknowledgments;352
23.8;References;352
24;Chapter 18: Analysis of focal adhesion turnover: A quantitative live-cell imaging example;356
24.1;Introduction to Focal Adhesion Dynamics;356
24.2;18.1. FA Turnover Analysis;358
24.2.1;18.1.1. Sample preparation;358
24.2.2;18.1.2. Imaging;360
24.2.3;18.1.3. Image analysis;361
24.2.4;18.1.4. Data analysis;362
24.3;Acknowledgments;367
24.4;References;367
25;Chapter 19: Determining absolute protein numbers by quantitative fluorescence microscopy;368
25.1;Introduction;369
25.2;19.1. Methods for Counting Molecules;369
25.2.1;19.1.1. Imaging and measurement considerations;369
25.2.2;19.1.2. Fluorescence correlation spectroscopy;370
25.2.3;19.1.3. Stepwise photobleaching;372
25.2.4;19.1.4. Ratiometric comparison of fluorescence intensity to known standards;373
25.2.5;19.1.5. Fluorescence standards;375
25.3;19.2. Protocol for Counting Molecules by Ratiometric Comparison of Fluorescence Intensity;377
25.3.1;19.2.1. Minimizing instrument error;377
25.3.2;19.2.2. Measuring instrument variation;378
25.3.3;19.2.3. Budding yeast imaging protocol;379
25.3.4;19.2.4. Measuring Background-Subtracted, integrated intensity;379
25.3.5;19.2.5. Depth correction;380
25.3.6;19.2.6. Calculating photobleaching correction factor;381
25.3.7;19.2.7. Gaussian fitting and ratiometric comparison to determine Protein count;381
25.4;Conclusions;382
25.5;References;382
26;Chapter 20: High-Resolution Traction Force Microscopy;388
26.1;Introduction;389
26.1.1;Basic principle of high-Resolution Traction Force Microscopy (TFM);391
26.1.2;Principles of traction reconstruction;393
26.1.3;Overview of methods for reconstruction of traction Forces;394
26.1.4;High resolution and regularization;395
26.2;20.1. Materials;395
26.2.1;20.1.1. Instrumentation for high-Resolution TFM;396
26.2.2;20.1.2. Polyacrylamide substrates with two colors of fiducial markers;398
26.2.2.1;20.1.2.1. Suggested equipment and materials;398
26.2.2.2;20.1.2.2. Protocol;399
26.2.3;20.1.3. Functionalization of polyacrylamide substrates with ECM proteins;401
26.2.3.1;20.1.3.1. Suggested equipment and materials;401
26.2.3.2;20.1.3.2. Protocol;402
26.3;20.2. Methods;402
26.3.1;20.2.1. Cell culture and preparation of samples for High-Resolution TFM;402
26.3.1.1;20.2.1.1. Suggested equipment and materials;403
26.3.1.2;20.2.1.2. Protocol;403
26.3.2;20.2.2. Setting up a perfusion chamber for TFM and acquiring TFM images;404
26.3.2.1;20.2.2.1. Suggested equipment and materials;404
26.3.2.2;20.2.2.2. Protocol;404
26.3.3;20.2.3. Quantifying deformation of the elastic substrate;406
26.3.4;20.2.4. Calculation of traction Forces with regularized Fourier–Transform Traction cytometry;408
26.3.4.1;20.2.4.1. Computational procedure;408
26.3.4.2;20.2.4.2. Choice of the regularization parameter;409
26.3.4.3;20.2.4.3. Alleviating spectral leakage due to the FFT;411
26.3.5;20.2.5. Representing and processing TFM data;411
26.3.5.1;20.2.5.1. Spatial maps of traction magnitude;411
26.3.5.2;20.2.5.2. Whole-cell traction;411
26.3.5.3;20.2.5.3. Traction along a predefined line;413
26.4;References;413
27;Chapter 21: Experimenters' guide to colocalization studies: finding a way through indicators and quantifiers, in practice;416
27.1;Introduction;417
27.2;21.1. An Overview of Colocalization Approaches;418
27.2.1;21.1.1. Two types of numerical values to extract: Colocalization Indicators and colocalization quantifiers;418
27.2.2;21.1.2. Two ways to work on colocalization evaluation: Taking the image as a whole and splitting it into objects;418
27.2.2.1;21.1.2.1. Working on image intensities;418
27.2.2.1.1;21.1.2.1.1. Legacy colocalization indicators and visualization methods;418
27.2.2.1.2;21.1.2.1.2. Legacy colocalization indicators and visualization methods, revisited;420
27.2.2.1.3;21.1.2.1.3. Which strategy to adopt?;422
27.2.2.2;21.1.2.2. Working on objects;424
27.2.2.2.1;21.1.2.2.1. Grouping pixels into objects: Image segmentation;424
27.2.2.2.2;21.1.2.2.2. Colocalization quantifiers based on object overlaps;425
27.2.2.2.3;21.1.2.2.3. Colocalization quantifiers based on object distances;426
27.2.2.2.4;21.1.2.2.4. Which strategy to adopt?;427
27.3;Conclusion;427
27.4;References;428
28;Chapter 22: User-friendly tools for quantifying the dynamics of cellular morphology and intracellular protein clusters;430
28.1;Introduction;431
28.2;22.1. Automated Classification of Cell Motion Types;432
28.3;22.2. GUI for Morphodynamics Classification and Ready Representation of Changes in Cell Behavior Over Time;436
28.4;22.3. Results of Morphodynamics Classification;438
28.5;22.4. Geometry-based Segmentation of Cells in Clusters;439
28.6;22.5. GUI for Cell Segmentation and Quantification of Protein Clusters;442
28.6.1;22.5.1. GUI module for 2D analysis;442
28.6.2;22.5.2. GUI module for 3D analysis;444
28.7;22.6. Results for Quantifying Protein Clusters;445
28.8;22.7. Discussion;445
28.9;Acknowledgments;447
28.10;References;447
29;Chapter 23: Ratiometric Imaging of pH Probes;450
29.1;Introduction;451
29.2;23.1. Currently Used Ratiometric pH Probes;451
29.2.1;23.1.1. pH-Sensitive ratiometric dyes;452
29.2.1.1;23.1.1.1. Advantages, limitations, and caveats of using dyes;454
29.2.2;23.1.2. Genetically encoded pH sensors;454
29.2.2.1;23.1.2.1. Advantages, limitations, and caveats of using genetically encoded pH biosensors;455
29.3;23.2. Applications;456
29.3.1;23.2.1. Measuring pHi in single cells;456
29.3.1.1;23.2.1.1. General considerations;456
29.3.1.2;23.2.1.2. Subcellular pH Measurements;457
29.3.2;23.2.2. Measuring pHi in tissues;459
29.4;23.3. Protocols;459
29.4.1;23.3.1. Solutions;459
29.4.1.1;HEPES buffer;459
29.4.1.2;HCO3 buffer;460
29.4.1.3;NH4Cl buffer;460
29.4.1.4;Nigericin buffer;461
29.4.2;23.3.2. Preparation of cultured cells;461
29.4.2.1;23.3.2.1. Dye loading in cultured cells;461
29.4.2.1.1;Materials required;461
29.4.2.2;23.3.2.2. Expression of genetically encoded pH biosensors in cultured cells;462
29.4.2.2.1;Materials required;462
29.4.2.3;23.3.2.3. Dye loading of whole-mount tissue;463
29.4.2.3.1;Materials required;463
29.4.2.3.2;Dissection tools;463
29.4.2.4;23.3.2.4. Expression of genetically coded pH biosensors in genetically tractable organisms;463
29.4.3;23.3.3. Ratiometric imaging;463
29.4.4;23.3.4. Generating nigericin calibration curves;464
29.4.4.1;Protocol;465
29.4.5;23.3.5. Ratiometric Analysis;465
29.5;Acknowledgments;466
29.6;References;466
30;Chapter 24: Toward quantitative fluorescence microscopy with DNA origami nanorulers;470
30.1;Introduction;471
30.2;24.1. The Principle of DNA Origami;473
30.3;24.2. Functionalizing DNA Origami Structures;473
30.4;24.3. DNA Origami as Fluorescence Microscopy Nanorulers;476
30.5;24.4. Brightness References Based on DNA Origami;478
30.6;24.5. Applications of DNA Origami Nanorulers for Visualizing Resolution;479
30.6.1;24.5.1. Nanorulers with defined distances for superresolution Microscopy;479
30.6.2;24.5.2. DNA-PAINT on the DNA origami nanoruler;480
30.7;24.6. How to Choose an Appropriate Nanoruler for a Given Application;482
30.8;References;484
31;Chapter 25: Imaging and physically probing kinetochores in live dividing cells;488
31.1;Introduction;489
31.1.1;The kinetochore;489
31.1.2;Mammalian cells: Challenges;490
31.1.3;Chapter overview;490
31.2;25.1. Spindle Compression to Image and Perturb Kinetochores;490
31.2.1;25.1.1. Historical context;490
31.2.2;25.1.2. Motivation;491
31.2.3;25.1.3. Methods;492
31.2.3.1;25.1.3.1. Choice of cell line;492
31.2.3.2;25.1.3.2. Cell culture;492
31.2.3.3;25.1.3.3. Agarose pad preparation;492
31.2.3.4;25.1.3.4. Experimental setup;493
31.2.3.5;25.1.3.5. Before spindle compression;493
31.2.3.6;25.1.3.6. Spindle compression;495
31.2.3.7;25.1.3.7. Choice of compression levels;495
31.2.3.8;25.1.3.8. After spindle compression;497
31.2.3.9;25.1.3.9. Troubleshooting tips;497
31.3;25.2. Imaging Kinetochore Dynamics at Subpixel Resolution Via Two-Color Reporter Probes;498
31.3.1;25.2.1. Historical context;498
31.3.2;25.2.2. Motivation;498
31.3.3;25.2.3. Methods;499
31.3.3.1;25.2.3.1. Gaussian fitting for subpixel resolution;499
31.3.3.2;25.2.3.2. Choice of cell line and reporter probes;499
31.3.3.3;25.2.3.3. Expression of reporter probes;500
31.3.3.4;25.2.3.4. Experimental setup;502
31.3.3.5;25.2.3.5. Before live cell imaging: Two-color bead registration;502
31.3.3.6;25.2.3.6. Subpixel resolution kinetochore imaging via two-color reporter probes;503
31.3.3.7;25.2.3.7. Data analysis for subpixel resolution kinetochore imaging;503
31.3.3.8;25.2.3.8. Key considerations for interpretation of interprobe distances;504
31.4;Conclusion and Outlook;505
31.5;Acknowledgments;506
31.6;References;506
32;Chapter 26: Adaptive fluorescence microscopy by online feedback image analysis;510
32.1;Introduction;511
32.2;26.1. Requirements for Adaptive Feedback Microscopy;513
32.3;26.2. Selected Applications;514
32.3.1;26.2.1. Automated detection and imaging of Plasmodium-infected cells;514
32.3.1.1;26.2.1.1. Motivation;514
32.3.1.2;26.2.1.2. Sample preparation;516
32.3.1.3;26.2.1.3. Feedback microscopy implementation using CellProfiler and LASAF Matrix Screener;516
32.3.1.4;26.2.1.4. CellProfiler for adaptive feedback microscopy;516
32.3.1.5;26.2.1.5. Setting up and running the experiment;517
32.3.1.6;26.2.1.6. Results and discussion;518
32.3.2;26.2.2. Automated FRAP on ER exit sites;518
32.3.2.1;26.2.2.1. Motivation and automation workflow overview;518
32.3.2.2;26.2.2.2. Sample preparation;519
32.3.2.3;26.2.2.3. Workflow and implementation;519
32.3.2.4;26.2.2.4. Results and discussion;521
32.4;Acknowledgments;522
32.5;References;522
33;Chapter 27: Open-source solutions for SPIMage processing;526
33.1;Introduction;527
33.1.1;Brief overview of light sheet microscopy flavors;527
33.1.2;Applications of light sheet microscopy;529
33.2;27.1. Prerequisites;530
33.2.1;27.1.1. Parameters of example dataset;530
33.2.2;27.1.2. Fluorescent beads as fiducial markers for registration;531
33.2.3;27.1.3. Installation and configuration of Fiji;531
33.2.4;27.1.4. Hardware requirements;532
33.2.5;27.1.5. File formats preprocessing and naming conventions;532
33.3;27.2. Overview of the SPIM Image-Processing Pipeline;533
33.4;27.3. Bead-based Registration;534
33.4.1;27.3.1. Workflow;536
33.4.2;27.3.2. Results;538
33.5;27.4. Multiview Fusion;539
33.5.1;27.4.1. Content-Based Multiview Fusion;539
33.5.1.1;27.4.1.1. Workflow;539
33.5.1.2;27.4.1.2. Results;542
33.5.2;27.4.2. Multiview Deconvolution;542
33.5.2.1;27.4.2.1. Workflow;543
33.5.2.2;27.4.2.2. Results;544
33.6;27.5. Processing on a High-Performance Cluster;545
33.7;27.6. Future Applications;546
33.8;References;548
34;Chapter 28: Second-harmonic generation imaging of cancer;552
34.1;Introduction;553
34.2;28.1. SHG Physical and Chemical Background;553
34.3;28.2. SHG Instrumentation;554
34.4;28.3. Collagen Structure as a Biomarker;554
34.5;28.4. SHG in Cancer Research;556
34.5.1;28.4.1. Breast cancer;556
34.5.2;28.4.2. Ovarian cancer;558
34.5.3;28.4.3. Skin cancer;558
34.5.4;28.4.4. SHG research in other types of cancer;560
34.6;28.5. Quantitative Analysis of SHG Images;562
34.7;Conclusion;562
34.8;References;563
35;Index;568
36;Volumes in Series;578
37;Color Plate;590

Leseproben

Contributors
John R. Allen,     National High Magnetic Field Laboratory and Department of Biological Science, The Florida State University, Tallahassee, Florida, USA Diane L. Barber,     Department of Cell and Tissue Biology, University of California, San Francisco, California, USA Susanne Beater,     Braunschweig University of Technology, Institute for Physical & Theoretical Chemistry and Braunschweig Integrated Centre of Systems Biology, Braunschweig, Germany Peter Beemiller,     Department of Pathology, University of California, San Francisco, California, USA Richard Berman,     Spectral Applied Research, Richmond Hill, Ontario, Canada Kerry Bloom,     Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA Susanne Bolte,     Sorbonne Universités—UPMC Univ Paris 06, Institut de Biologie Paris—Seine– CNRS FR 3631, Cellular Imaging Facility, Paris Cedex, France Jeremy S. Bredfeldt,     Laboratory for Optical and Computational Instrumentation, University of Wisconsin at Madison, Madison, USA Claire M. Brown,     McGill University, Life Sciences Complex Advanced BioImaging Facility (ABIF), Montreal, Québec, Canada Mark Browne,     Andor Technology, Belfast, United Kingdom Hsin Chen,     Department of Pharmacology and Cancer Biology, Duke University, Durham, North Carolina, USA Pei-Hsuan Chu,     Department of Pharmacology, University of North Carolina, Chapel Hill, North Carolina, USA Richard W. Cole,     Wadsworth Center, New York State Department of Health, P.O. Box 509, and Department of Biomedical Sciences, School of Public Health State University of New York, Albany New York, USA Bridget E. Collins,     Department of Biological Sciences, Columbia University, New York, USA Kaitlin Corbin,     Biological Imaging Development Center and Department of Pathology, University of California, San Francisco, California, USA Fabrice P. Cordelières,     Bordeaux Imaging Center, UMS 3420 CNRS—Université Bordeaux Segalen—US4 INSERM, Pôle d'imagerie photonique, Institut François Magendie, Bordeaux Cedex, France Michael W. Davidson,     National High Magnetic Field Laboratory and Department of Biological Science, The Florida State University, Tallahassee, Florida, USA Christopher DuFort,     Department of Surgery, and Department of Orthopaedic Surgery, University of California, San Francisco, California, USA Sophie Dumont,     Department of Cell & Tissue Biology; Tetrad Graduate Program, and Department of Cellular & Molecular Pharmacology, University of California, San Francisco, California, USA Daniel Duzdevich,     Department of Biological Sciences, Columbia University, New York, USA Kevin W. Eliceiri,     Laboratory for Optical and Computational Instrumentation, University of Wisconsin at Madison, Madison, USA Timothy C. Elston,     Department of Pharmacology, University of North Carolina, Chapel Hill, North Carolina, USA Ulrike Engel,     Center for Organismal Studies and Nikon Imaging Center, Bioquant, University of Heidelberg, Heidelberg, Germany Andreas Ettinger,     Department of Cell and Tissue Biology, University of California, San Francisco, USA Reto Fiolka,     Department of Cell Biology, UT Southwestern Medical Center, Dallas, Texas, USA Wah Ing Goh,     Mechanobiology Institute, National University of Singapore, Singapore Paul C. Goodwin,     GE Healthcare, Issaquah, and Department of Comparative Medicine, University of Washington, Seattle, Washington, USA Eric C. Greene,     Department of Biochemistry and Molecular Biophysics, and Howard Hughes Medical Institute, Columbia University, New York, USA Bree K. Grillo-Hill,     Department of Cell and Tissue Biology, University of California, San Francisco, California, USA Klaus M. Hahn,     Department of Pharmacology, and Lineberger Cancer Center, University of North Carolina, Chapel Hill, North Carolina, USA Kirsten Hanson,     Instituto de Medicina Molecular, Lisboa, Portugal Harald F. Hess,     Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia, USA Volker Hilsenstein,     European Molecular Biology Laboratory, Heidelberg, Germany Jan Huisken,     Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), Dresden, Germany James Jonkman,     Advanced Optical Microscopy Facility (AOMF), University Health Network, Toronto, Ontario, Canada Pakorn Kanchanawong,     Mechanobiology Institute, and Department of Biomedical Engineering, National University of Singapore, Singapore Charlotte Kaplan,     Institute of Biochemistry, ETH Zurich, Switzerland Adib Keikhosravi,     Laboratory for Optical and Computational Instrumentation, University of Wisconsin at Madison, Madison, USA Matthew F. Krummel,     Biological Imaging Development Center and Department of Pathology, University of California, San Francisco, California, USA Jonathan Kuhn,     Department of Cell & Tissue Biology, and Tetrad Graduate Program, University of California, San Francisco, California, USA Talley J. Lambert,     Harvard Medical School, Boston, Massachusetts, USA Josh Lawrimore,     Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA Michaela Mickoleit,     Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), Dresden, Germany Markus Mund,     European Molecular Biology Laboratory, Cell Biology and Biophysics Unit, Heidelberg, Germany John Oreopoulos,     Spectral Applied Research, Richmond Hill, Ontario, Canada Matthew Paszek,     School of Chemical and Biomolecular Engineering, Cornell University, and Kavli Institute at Cornell for Nanoscale Science, Ithaca, New York, USA Sebastian Peck,     Biological Imaging Development Center and Department of Pathology, University of California, San Francisco, California, USA Rainer Pepperkok,     European Molecular Biology Laboratory, Heidelberg, Germany Lara J. Petrak,     Departments of Cell Biology, Departments of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA Henry Pinkard,     Biological Imaging Development Center and Department of Pathology, University of California, San Francisco, California, USA Sergey V. Plotnikov,     National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA Mario Raab,     Braunschweig University of Technology, Institute for Physical & Theoretical Chemistry and Braunschweig Integrated Centre of Systems Biology, Braunschweig, Germany Jonas Ries,     European Molecular Biology Laboratory, Cell Biology and Biophysics Unit, Heidelberg, Germany Stephen T. Ross,     Nikon Instruments, Inc., Melville, New York, USA Benedikt...