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An atlas of gene regulatory networks for T memory cells in youth and old age [ATAC-seq]

ABSTRACT: We previously identified a population of IL-10-producing, T follicular helper-like cells ("Tfh10"), linked to suppressed vaccine responses in aged mice. Here, we applied scRNA-seq and scATAC-seq to characterize Tfh10 – and the full CD4+ memory T cell (CD4+TM) compartment – in young and old mice. Unprecedented scRNA-seq coverage of the CD4+TM compartment and parallel chromatin accessibility measurements (scATAC-seq) enabled identification of 13 CD4+TM populations, which we validated as a reference through comprehensive cross-comparison to aging cell atlases and scRNA-seq studies reporting Tfh10 in other contexts. In addition, we compared sc-resolved populations to flow-sorted CD4+TM populations (Treg, Tfh10 and "nonTfh, non-Treg IL-10-") subjected to bulk RNA-seq and bulk ATAC-seq. Beyond robust characterization of age- and cell-type-dependent transcriptional landscapes, we used integrative computational modeling to predict the underlying regulatory mechanisms: We inferred gene regulatory networks (GRNs) that describe transcription-factor control of gene expression in each T-cell population and how these circuits change with age. Furthermore, we integrated our data with prior, pan-cell scRNA-seq studies to identify intercellular-signaling networks driving age-dependent changes in CD4+TM. Our atlas of finely resolved CD4+TM subsets, GRNs and cell-cell communication networks is a critical resource for analysis of biologic processes operative in memory T cells in youth and old age. The resource presents new opportunities to manipulate regulatory circuits in CD4+TM, which, long-term, could improve immune responses in the elderly.

ORGANISM(S): Mus musculus

PROVIDER: GSE228667 | GEO | 2023/08/07

REPOSITORIES: GEO

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An atlas of gene regulatory networks for T memory cells in youth and old age [RNA-seq]

Project description:We previously identified a population of IL-10-producing, T follicular helper-like cells ("Tfh10"), linked to suppressed vaccine responses in aged mice. Here, we applied scRNA-seq and scATAC-seq to characterize Tfh10 – and the full CD4+ memory T cell (CD4+TM) compartment – in young and old mice. Unprecedented scRNA-seq coverage of the CD4+TM compartment and parallel chromatin accessibility measurements (scATAC-seq) enabled identification of 13 CD4+TM populations, which we validated as a reference through comprehensive cross-comparison to aging cell atlases and scRNA-seq studies reporting Tfh10 in other contexts. In addition, we compared sc-resolved populations to flow-sorted CD4+TM populations (Treg, Tfh10 and "nonTfh, non-Treg IL-10-") subjected to bulk RNA-seq and bulk ATAC-seq. Beyond robust characterization of age- and cell-type-dependent transcriptional landscapes, we used integrative computational modeling to predict the underlying regulatory mechanisms: We inferred gene regulatory networks (GRNs) that describe transcription-factor control of gene expression in each T-cell population and how these circuits change with age. Furthermore, we integrated our data with prior, pan-cell scRNA-seq studies to identify intercellular-signaling networks driving age-dependent changes in CD4+TM. Our atlas of finely resolved CD4+TM subsets, GRNs and cell-cell communication networks is a critical resource for analysis of biologic processes operative in memory T cells in youth and old age. The resource presents new opportunities to manipulate regulatory circuits in CD4+TM, which, long-term, could improve immune responses in the elderly.

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