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, 13 (8), e0200818
eCollection

Heterogeneity of Circulating CD8 T-cells Specific to Islet, Neo-Antigen and Virus in Patients With Type 1 Diabetes Mellitus

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Heterogeneity of Circulating CD8 T-cells Specific to Islet, Neo-Antigen and Virus in Patients With Type 1 Diabetes Mellitus

Sandra Laban et al. PLoS One.

Abstract

Auto-reactive CD8 T-cells play an important role in the destruction of pancreatic β-cells resulting in type 1 diabetes (T1D). However, the phenotype of these auto-reactive cytolytic CD8 T-cells has not yet been extensively described. We used high-dimensional mass cytometry to phenotype autoantigen- (pre-proinsulin), neoantigen- (insulin-DRIP) and virus- (cytomegalovirus) reactive CD8 T-cells in peripheral blood mononuclear cells (PBMCs) of T1D patients. A panel of 33 monoclonal antibodies was designed to further characterise these cells at the single-cell level. HLA-A2 class I tetramers were used for the detection of antigen-specific CD8 T-cells. Using a novel Hierarchical Stochastic Neighbor Embedding (HSNE) tool (implemented in Cytosplore), we identified 42 clusters within the CD8 T-cell compartment of three T1D patients and revealed profound heterogeneity between individuals, as each patient displayed a distinct cluster distribution. Single-cell analysis of pre-proinsulin, insulin-DRIP and cytomegalovirus-specific CD8 T-cells showed that the detected specificities were heterogeneous between and within patients. These findings emphasize the challenge to define the obscure nature of auto-reactive CD8 T-cells.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Dissection of the CD8 compartment of three T1D patients.
a) Overview HSNE of CD8 compartment, clustering was based on marker expression of 33 markers after hyperbolic Arcsin5 transformation. b) Density map including cluster number. A sigma value of 7 resulted in 42 clusters. c) Distribution of clusters per patient. d) Heat map view including variation in marker expression within a cluster (box fill–smaller box depicts higher variation).
Fig 2
Fig 2. Marker expression visualization.
a) t-SNE of CD8 compartment of three T1D patients. Markers CD8, CD3 and TCRgd used for gating, as well as the negative markers NKp44 and NKp46 are not displayed. b) Jensen-Shannon divergence plots of t-SNE maps comparing three patients. Higher values indicate more dissimilarity between a pair of t-SNE maps.
Fig 3
Fig 3. Single-cell heat map of CD8 T-cells of three T1D patients.
The first sidebar displays the specificity (red = PPI, blue = DRIP, green = CMV, grey = tetramer negative), the second bar is depicting the tetramer signal (not taken into account for clustering).
Fig 4
Fig 4. Single-cell heat map of INS-DRIP-specific CD8 T-cells.
The first sidebar displays patient origin (pink = patient 1, light-blue = patient 2, purple = patient 3), the second bar is depicting the tetramer signal.

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Publication types

Grant support

This work was supported by Diabetesfonds Nederland, Stichting Diabetes Onderzoek Nederland, The Wanek Family Project for Type 1 Diabetes (BOR).
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