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Comparative Overview of Flow and Image Cytometry

J. Paul Robinson¹

¹Purdue University, West Lafayette, Indiana

Publication Name:

Current Protocols in Cytometry

Unit Number:

Unit 12.1

DOI:

10.1002/0471142956.cy1201s31

Online Posting Date:

February, 2005

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Abstract

This unit considers the issues of which tool to use—flow cytometry or imaging—and under what conditions. In particular, it compares the advantages and disadvantages of flow and image cytometry and provides examples illustrating the proper choice of each technology. The result is a better understanding of why the two technologies are complementary in many applications. It is clear that many scientists use the tools that are familiar to them, often in preference to the best tool. In cases where very advanced and rather expensive technologies are concerned, this is not surprising. However, there are clearly times when one form of cytometry is definitely superior to another. What then constitute the criteria for a decision when both flow cytometry and imaging are available This unit addresses some of these concerns.

Keywords: flow cytometry; image cytometry; fluorescence measurement

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Unit Introduction
Introduction to Flow Cytometry
Introduction to Imaging
Introduction to Scanning Laser Cytometry
Advantages of Flow Cytometry
Advantages of Imaging
Comparison of Traditional Imaging and Flow Cytometry
Combination Studies with Flow and Imaging
Imaging Cytometry
Conclusion
Literature Cited
Figures

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Figures

Figure 12.1.1

Typical flow chamber in which fluorochrome-labeled cells are injected into a flowing sheath of saline and directed through the laser beam. Left: typical fluorescence histograms. Right: forward-scatter histogram. Diagram is not drawn to scale.

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Figure 12.1.2

The Medimachine automated mechanical disaggregation system is a very useful device that allows disaggregation of biopsy materials, providing single-cell suspensions of excellent quality and making it possible to do high-quality flow cytometry on tissue specimens. The principle of this instrument is the high-speed cutting tool that spins within the small sampling unit. Single cells pass through the holes in the blades and into a reservoir below, where they can be rescued using a pipet from a side port. Once cells are removed from the vessel they can be stained, e.g., for cell-cycle analysis or for specific antigens of interest, using traditional flow cytometry staining techniques.

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Figure 12.1.3

Typical images from image systems. (A) Bright-field image of tongue histology. (B) Brightest pixel reconstruction of pine tree pollen. (C) Standard fluorescence image of a human neutrophil. (D) A human neutrophil which has phagocytosed yeast. (E) Reconstruction of bacteria growing in a biofilm. B and D are confocal images. All of these are typical images where the spatial relationship of components is crucial for understanding the processes of interest.

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Figure 12.1.4

(A) Cells organized in an ordered matrix. The abnormal cell (x) is in a specific position. From a pathology perspective, the location of this cell and the relationship to others provide important information. (B) Cells as they might be in suspension, totally randomly arranged.

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Figure 12.1.5

A comparison of information from traditional imaging and flow cytometry. Cartoons represent side-scatter histograms of the cell populations in the images. In the center of the middle image is a lymphocyte. The side-scatter histogram for this cell is in the top right corner and reflects the homogeneity and low granularity of this cell type. Note that some cells, such as macrophages (top center, right center), have significant variation in shape and granule composition. This increases the CV of the histogram. All images were collected on a COSMIC digital microscope.

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Figure 12.1.6

Flow histograms demonstrating mitochondrial membrane transitions. Numbers above each histogram represent median channel number. Mitochondrial populations in panels (A) to (D) show decrease in membrane potential, while those in panels (E) to (H) show very little change. Abbreviation: TMRM, tetramethylrhodamine methyl ester.

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Figure 12.1.7

Cell images demonstrating the ability of imaging to evaluate the presence of certain fluorescence probes and their location within organelles in the cell environment.

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Figure 12.1.8

For a bacterial study, a composite of flow cytometry and image analysis is required both to evaluate how many microorganisms are present and to differentiate between live and dead organisms. A live-dead stain was used so that both image and flow systems were able to make identical measurements under completely different circumstances. Image data were collected from a biofilm, while the flow data were collected from individual organisms in suspension.

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Figure 12.1.9

An example of LSC data in which each cell has been segmented using image-processing algorithms. A large number of parameters have been collected into a correlated listmode file that can be further analyzed by comparing the positional information on histograms and dual-parameter dot plots with actual images of cells and with their location on a tissue array. By collecting multiple tissue sections, it is even possible to identify 3-D relationships of cells within the organ or part of organ evaluated. Data from Gerstner et al. (2004).

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Figure 12.1.10

Layout of the imaging cytometer. This system allows for basic flow cytometry measurements as well as the ability to make a reasonably good image of each cell. While the images are not at a resolution that allows detailed analysis, they are nevertheless particularly useful since they do provide sufficient information to identify morphological differences in cells. Figure courtesy of Amnis Corp.

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Figure 12.1.11

Automated segmentation algorithms allow critical analysis of single cells from image-based systems. Once a cell area has been classified, a number of analyses can be performed.

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Literature Cited

Literature Cited
	De Rosa, S.C. and Roederer, M. 2001. Eleven-color flow cytometry. A powerful tool for elucidation of the complex immune system. Clin. Lab. Med. 21:697-712.
	Gerstner, A.O.H., Trumpfheller, C., Racz, P., Osmancik, P., Tenner-Racz, K., and Tárnok, A. 2004. Quantitative histology by multicolor slide-based cytometry. Cytometry 59A:210-219.
	Lenz, D., Gerstner, A., Laffers, W., Steinbrecher, M., Bootz, F., and Tárnok, A. 2003. Six and more color immunophenotyping on the slide by Laser Scanning Cytometry (LCS). Proc. SPIE 4962:364-374.
	Salvioli, S., Ardizzoni, A., Franceschi, C., and Cossarizza, A. 1997. JC-1, but not DiOC6(3) or rhodamine, is a reliable fluorescent probe to assess delta psi changes in intact cells: Implications for studies on mitochondrial functionality during apoptosis. FEBS Lett. 411:77-82.