Sample Data: High Dimensional Flow Cytometry

Introduction
The key to the power of flow cytometry is its ability to measure several independent properties on each cell and to use complex combinations of these quantitative measurements to classify and isolate cells of interest. Multidimensional analysis often reveals clearly what is invisible when fewer colors are employed or must be inferred indirectly from multiple separate samples. Even going from one color immunofluorescence to two colors made a profound difference in the work of immunologists. This was enabled once fluorescence compensation equipment has been devised to obtain independent measurements of dyes with overlapping spectra. With the use of multiple laser excitations and the development of more dyes and fluorescent probes, the variety of biological applications has risen dramatically.

As we have increased the number of properties measured for each cell, the amount of information available and our ability to make fine distinctions among cell populations has also increased dramatically. Several years ago, it was recognized that 3- or 4-color FACS technology would be inadequate to analyze the phenotypic and functional hereogeneity in lymphoid cells. Investigators undertook an ongoing effort that combined the development of novel fluorescent dyes, new software analysis tools, and hardware. Currently, at Stanford University we have the ability to simultaneously measure 11 different fluorescent markers to each cell. Each of the fluorescent dyes is conjugated to monoclonal antibodies for use in immunophenotyping. New dye systems have become available, most notably the Alexa dye series available from Molecular probes that have been synthesized and chosen based on this tight fluorescence excitation and emission spectra as well as their excitability at wavelength commonly attainable by standard laser systems. These technological advances give us an unprecedented and unique ability to resolve heterogeneity within the cell compartments such as the lymphoid system. It also has important practical benefits in conserving reagents and obtaining the maximum amount of information when cell numbers are limiting.

An important advantage of high dimensional FACS technology is the ability to combine high-resolution immunophenotyping with single-cell functional analyses. In order to identify specific subsets of T cells, we often need 5(or more) colors. For example, to uniquely identify CD-4-SP naïve T cells, cells must be simultaneously stained with CD3, CD4, and CD8(to identify the CD4-SP lineage,) and then CD45RA and CD62L(to identify the differentiation stage). With up to 11 colors high dimensional FACS, we can carry out comprehensive immunophenotyping and still devote several additional colors to functional assays. Such assays include intracellular cytokines(e.g, simultaneous determination of IL2 and IL4), apoptosis(using Annexin V binding, the combination of Hoechst and propidium, MC540 staining, or other FACS-identifiable markers of the apoptotic response), and CTL activity(by quantitating intracellular perforin or granzyme expression), specific phosphoprotein levels.

 
Multidimensional analysis of naive CD4+ T cells. Magnetic cell sorting, 13-parameter flow cytometry, transcription factor profiling and cytokine bead arrays were 'combined' to determine the effect of stimulation on immunophenotyped naive CD4+ T cells(CD3+CD4+CD8-CD45RA+CD62L+ CD11adimCD27+CD28+). (a) Intracellular IL-2 and phosphorylated Erk1/2(Phospho-Erk1/2) were correlated with surface phenotype and activation markers CD69 and CD25. Numbers in quadrants indicate percentages of each population. (b) Cell cycle analysis of CD4+ T cells stimulated with CD3, CD3 plus CD28, or CD3 and LFA-1 ligand. Cells in the G0, G1, and S + G2/M phases of the cell cycle were determined by double staining for expression of Ki-67 and DNA content(propidium iodide; PI). Low Ki-67- were considered cells in G0; Ki-67+ signals with 2n DNA, cells in G1; and Ki-67+ signals with >2n DNA, cells in S or G2/M.

Perez, OD, Mitchell, D., Jager, G., South,S., Murriel, C., McBride, J., Herzenberg, LA., Kinoshita, S. and Nolan, GP. Leukocyte functional antigen 1 lowers T cell activation thresholds and signaling through cytohesin-1 and Jun-activating binding protein 1. Nature Immunology 2003 4:1083-92

 

 
Ligation of ICAM-2 and Interaction with LFA-1 Induces AKT Activity and Protects Primary B Cells from Apoptosis. ( A) Multiparameter FACS analysis illustrates ICAM-2-induced AKT activity in CD4+ and CD19+ populations protects from apoptosis. (B) PBMC were crosslinked for ICAM-1,-2,-3, CD43, or CD44(10ug/ml, 45 min) and subjected to phosphatidylinositol detection of phosphatidylinositol 3,4,5 triphosphate(PIP3)and phosphatidylinositol 4,5 bisphosphate(PIP2).

Perez OD, Kinoshita, S., Hitoshi, Y., Payan, DG, Kitamura, T., Nolan, GP and Lorens, JB. Activation of the PKB/AKT Pathway by ICAM-2 Immunity 2002 16:51-65.

 
Multivariate analysis of complex populations. 1 x 106 PBMCs (nondepleted) were left untreated or treated with indicated TNF-a (200 ng/mL, 15 min) and stained for CD14-FITC (clone MoP9), CD19-cychrome (clone HIB19), phospho-STAT3 (Y705)-PE (clone 4), and phospho-STAT5 (Y694)-AX647. Multivariate analysis was performed using clustering algorithms developed by Dr. Mario Roederer in FlowJo 4.2 (Tree Star, San Carlos, CA).
 
Figure courtesy of Omar Perez, Nolan Lab, 2004