We analyzed PBMC single-cell suspensions by CyTOF for the protein expression of several lineage-, activation- and trafficking-associated markers and converted them to barcoded scRNA-seq libraries using 10x Genomics for downstream scRNA-seq, scATAC-seq and scTCR/BCR-seq analysis. CellRanger software and the Seurat package were used for initial processing of the sequencing data. Quality metrics included numbers of unique molecular identifiers (UMIs), genes detected per cell, and reads aligned that were comparable across different research subjects. We identified red blood cells (RBCs), megakaryocytes (MEGAs) and five major immune cell lineages (TCs, NKs, BCs, MCs and DCs) based on the expression of canonical lineage markers and other genes specifically upregulated in each cluster (Figs. 1C, 1D and S1A–C). In accordance with the scRNA-seq results, we identified five immune cell lineages (TCs, NKs, BCs, MCs and DCs) in CyTOF using t-distributed stochastic neighbor embedding (t-SNE), an unbiased dimensionality reduction algorithm (See Table S2 for a list of antibodies) (Fig. S2A–D). Cell-type-specific marker genes were determined by differential gene expression values between clusters positioned and visualized in a t-SNE plot (Figs. S1 and S2). The definition of cell types in clusters in the t-SNE maps was comparable between old and young individuals (Figs. S1B and 2B) both by scRNA-seq and CyTOF, indicating that the cell type identity was not altered with age.
Figure 2 Changes in cell proportions during aging. (A) Bar chart of the relative percentage of immune cell types derived from scRNA-seq data in PBMCs. (B) Bar chart of the relative percentage of immune cell subsets derived from scRNA-seq data in PBMCs. The focused cell-subsets have been marked red. (C) Pie charts showing relative cluster abundances derived from mass cytometry data in the YA and AA groups. (D) Percentage of CD4 Naive cells in PBMCs from YA (n = 8) and AA (n = 8) groups. (E) Percentage of CD8 Naive cells in PBMCs from YA (n = 8) and AA (n = 8) groups. (F) Percentage of CD4 Naive cells in CD45+ cells from YA (n = 5) and AA (n = 5) groups. (G) Percentage of CD8 Naive cells in CD45+ cells from YA (n = 5) and AA (n = 5) groups. (H) Bar chart of the relative percentage of CD4+ T cell subsets derived from scRNA-seq data in PBMCs. (I) Bar chart of the relative percentage of CD8+ T cell subsets derived from scRNA-seq data in PBMCs. (J) Bar chart of the relative percentage of CD4+ T cell subsets derived from mass cytometry data in CD45+ cells. (K) Bar chart of the relative percentage of CD8+ T cell subsets derived from mass cytometry data in CD45+ cells. (L) Percentage of CD14 monocytes in PBMCs from YA (n = 8) and AA (n = 8) groups. (M) Percentage of CD14 monocytes in CD45+ cells from YA (n = 5) and AA (n = 5) groups. (N) Bar chart of the relative percentage of DC subsets derived from scRNA-seq data in PBMCs. (O) Bar chart of the relative percentage of DC subsets derived from mass cytometry data in CD45+ cells. P values are based on two-tailed Mann-Whitney-Wilcoxon tests between groups