Fig. 2

Identification of memory CD4⁺ and CD8⁺ T cells, MBCs, monocyte and NK cell sub-populations in DENV-infected individuals. A–K PBMCs collected at first presentation from DENV-positive individuals progressing to DF (n = 6) or DHF (n = 6) were stained with a panel of metal-labelled antibodies and analysed by CyTOF. tSNE analysis was performed and FlowSOM clustering was used to identify individual cell sub-populations within gated: A T_H1 memory CD4⁺ T cells (CD19⁻CD3⁺CD4⁺CD45RA⁻CCR6⁻CXCR3⁺), B T_H2 memory CD4⁺ T cells (CD19⁻CD3⁺CD4⁺CD45RA⁻CCR6⁻CXCR3⁻), C T_H17 memory CD4⁺ T cells (CD19⁻CD3⁺CD4⁺CD45RA⁻CCR6⁺CXCR3⁻), D Circulating memory T_FH cells (CD19⁻CD3⁺CD4⁺CD45RA⁻CXCR5⁺), E Memory CD8⁺ T cells (CD19⁻CD3⁺CD8⁺CD45RA⁻). F MBCs (CD3⁻CD19⁺CD20⁺CD10⁻), G Monocytes (CD3⁻CD19⁻CD14⁺), H. NK cells (CD3⁻CD19⁻CD14⁻CD56⁺). The tSNE plots in the top panel display cell density and represent the pooled data for each group, while the lower panel shows a projection of the FlowSOM clusters on a tSNE plot. Heatmaps show the median marker expression for each FlowSOM cluster. I Unsupervised hierarchical clustering heatmap showing the frequency of all FlowSOM clusters across all clinical samples. J Unsupervised multi-dimensional scaling of all populations identified by FlowSOM clustering across all clinical samples. K Spearman correlation networks were used to examine the relationship between cell populations identified by FlowSOM clustering induced in response to infection. Blue lines represent positive correlations, and red lines represent negative correlations. The distance between variables is determined by multidimensional scaling and represents the strength of the correlation, where highly correlated variables are positioned closer together