Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes

Evan W Newell, Natalia Sigal, Sean C Bendall, Garry P Nolan, Mark M Davis, Evan W Newell, Natalia Sigal, Sean C Bendall, Garry P Nolan, Mark M Davis

Abstract

Cytotoxic CD8(+) T lymphocytes directly kill infected or aberrant cells and secrete proinflammatory cytokines. By using metal-labeled probes and mass spectrometric analysis (cytometry by time-of-flight, or CyTOF) of human CD8(+) T cells, we analyzed the expression of many more proteins than previously possible with fluorescent labels, including surface markers, cytokines, and antigen specificity with modified peptide-MHC tetramers. With 3-dimensional principal component analysis (3D-PCA) to display phenotypic diversity, we observed a relatively uniform pattern of variation in all subjects tested, highlighting the interrelatedness of previously described subsets and the continuous nature of CD8(+) T cell differentiation. These data also showed much greater complexity in the CD8(+) T cell compartment than previously appreciated, including a nearly combinatorial pattern of cytokine expression, with distinct niches occupied by virus-specific cells. This large degree of functional diversity even between cells with the same specificity gives CD8(+) T cells a remarkable degree of flexibility in responding to pathogens.

Figures

Figure 1. Representative Analysis of Antibody and…
Figure 1. Representative Analysis of Antibody and pMHC Tetramer-Stained Cells via CyTOF
(A) Without light scatter to identify individual cells as in fluorescence flow cytomety, DNA content stained by an iridium-191/193 interchelator is used to identify individual cells. (B) The cells are also gated for uniformity in the length of signal received by the ion detector and by exclusion of a live-dead viability stain (see Experimental Procedures). (C and D) CD8+ T cells are distinguished from negative-control mouse cells stained with mouse CD45 (C), and two example surface stains (CD45RA versus CD62L) are shown (D). (E and F) For the same donor sample, influenza-MP58-66-HLA-A2 pMHC tetramer staining versus CD45RA staining are shown before (E) and after (F) tetramer enrichment via anti-c-myc magnetic particles (see Experimental Procedures). The sample plotted here and in all figures is representative of six samples analyzed in this study. See also Figure S1
Figure 2. Boolean Gating for Functional Determination…
Figure 2. Boolean Gating for Functional Determination of Functional Capacity of Stimulated Live CD8+T Cells
Boolean gates were set for each measureto define the multifunctional capacity of each stimulated cell. (A) For inducible functions, not including perforin or granzyme B, the cut-off between positive and negative defined by the 99th percentile (1%+ cells) for unstimulated cells. (B) PMA+ionomycin-stimulated cells are plotted for each of these functions. (C and D) Spiked-in negative control mouse cells (C) were used to define the threshold of positivity for granzyme B and perforin of human CD8+ T cells (D).
Figure 3. 36-Parameter Mass Cytometry Staining Experimental…
Figure 3. 36-Parameter Mass Cytometry Staining Experimental Setup and Principal Component Analysis
(A) A table of cellular markers and the atomic masses of each antibody or pMHC tetramer label are shown. To distill the information from 25 of these parameters, principal component analysis was used on live CD8+ T cells (gated as in Figure 1). *CD69 probed intracellularly, **anti-CD107a and -CD107b added at time of stimulation, ***anti-mouse CD45 used to distinguish negative control cells) (see Experimental Procedures). (B) The percent variation explained are plotted for each component (bars) and cumulatively (line). (C–E) The principle component analysis parameter loadings (weighting coefficients) for the first three components are plotted. See also Figure S2
Figure 4. 3D-PCA Representation of CD8 +…
Figure 4. 3D-PCA Representation of CD8+T Cell Data and Memory Cell Phenotypic and Functional Progression
(A) One cytometry data set is plotted on the first three principal component axes (a representative PMA+ ionomycin-stimulated CD8+ T cell sample) and shown from three different perspectives (rotated around the PC2-axis). After gating by surface marker phenotype, naive (green), central memory (Tcm, yellow), effector memory (Tem, blue), and short lived effector (Tslec, red) cell populations are overlaid to identify the main phenotypic clusters. (B and C) To analyze only memory cells, cells in the principal components PC1 versus PC2 plot in(A) were gated to exclude the naive compartment (cells with low value for PC1) and subjected to further analysis. To determine the average expression for a number of different phenotypic markers and functional capacities across the entire range of PC2 values, small bins of cells with similar PC2 values were pooled and the average intensity of each marker was determined. These average expression for each phenotypic (B) and functional (C) parameters were normalized and plotted as a function of normalized PC2 values. In this way, the phenotypic progression of CD8+ memory T cells are represented by the x axis and the y axis represents the average expression of each marker. See also Figure S3
Figure 5. Functional and Phenotypic Analysis of…
Figure 5. Functional and Phenotypic Analysis of CD8+T Cells Stimulated by Various Means
(A–C) The combinatorial diversity of nine T cell functions were assessed in response to (A) PMA+ionomycin, (B) anti-CD3, or (C) anti-CD3+anti-CD28. 512 =29 possible functional phenotypes are each represented in a16×32grid, where the heat of each block represents the log scale frequency of cells displaying each combination of functional capacity (white represents frequencies below 0.1% cutoff). (D–F) Psuedo-colored density-dot plots of the first two principal components after PCA loading with all 25 surface and intracellular parameters of PMA+ ionomycin-stimulated cells (see Figure 3) are shown for cells stimulated with (D) PMA+ionomycin, (E) anti-CD3, and (F) anti-CD3+anti-CD28. See also Figure S4
Figure 6. Diverse Combinatorial Functional Capacities of…
Figure 6. Diverse Combinatorial Functional Capacities of Stringently Defined CD8+T Cell Subsets
As described for Figure 3, the combinatorial makeup of functional capcities are plotted on a 16×32 grid as a heat plot. PMA+ionomycin-stimulated live cells were further segregated based on stringent criteria: (A) naive (CD45RA+ CD27+CD62L+CCR7+), (B) central memory (Tcm, CD45RA−CD27+CD62L+ CCR7+), (C) effector memory (Tem, CD45RA−CD27−CD62L−CCR7−), and (D) short-lived effector (Tsle, CD45RA+CD27−CD62L−CD28−KLRG1+CD57+) cells before plotting frequencies of each the frequencies of cells expressing each combination of functional capacities. See also Figure S5
Figure 7. Functional and Phenotypic Analysis of…
Figure 7. Functional and Phenotypic Analysis of Antigen-Specific CD8+T Cells
(A–C) Examples of the combinatorial diversity in functional capacities of pMHC tetramer-stained cells are shown (as in Figure 2) for cells specific for CMV-pp65482-490-HLA-A2 (A), EBV-BRLF109-117-HLA-A2 (B), and influenza-MP58-65-HLA-A2 (C). (D–F) Density plots of the first two PCA components of total live PMA+- ionomycin-stimulated CD8+ T cells are overlaid with contour density plots of pMHC tetramer-positive cells in red for CMV- (D), EBV- (E), and influenza (F)-specific cells. See also Figure S6

Source: PubMed

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