Trimodal single-cell profiling reveals a novel pediatric CD8αα+ T cell subset and broad age-related molecular reprogramming across the T cell compartment

Basic information
Cell
866,058
Sample
64

Technology
10X Genomics
Omics
scRNA-seq,TEA-seq,CITE-seq
Source
PBMCs

Dataset ID
37845489
Platform
Illumina NovaSeq 6000
Species
Human
Disease
Healthy
Age range
11 - 63
Update date
2023-10-16
Summary

Age-associated changes in the T cell compartment are well described. However, limitations of current single-modal or bimodal single-cell assays, including flow cytometry, RNA-seq (RNA sequencing) and CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing), have restricted our ability to deconvolve more complex cellular and molecular changes. Here, we profile >300,000 single T cells from healthy children (aged 11-13 years) and older adults (aged 55-65 years) by using the trimodal assay TEA-seq (single-cell analysis of mRNA transcripts, surface protein epitopes and chromatin accessibility), which revealed that molecular programming of T cell subsets shifts toward a more activated basal state with age. Naive CD4+ T cells, considered relatively resistant to aging, exhibited pronounced transcriptional and epigenetic reprogramming. Moreover, we discovered a novel CD8αα+ T cell subset lost with age that is epigenetically poised for rapid effector responses and has distinct inhibitory, costimulatory and tissue-homing properties. Together, these data reveal new insights into age-associated changes in the T cell compartment that may contribute to differential immune responses.

Overall design

scRNAseq was performed on 48 samples. In addition, TEA-seq (a novel method for simulaneous single-cell profiling of transcripts, epitopes, and chromatin accessiblity) was performed on 16 of those samples, as well as on 3 control samples (IMM19_435, IMM19_438, and IMM19_445). As part of TEA-seq testing we prepared CITE-seq, scATAC-seq, single-cell and single-nuclei 10x Multiome ATAC + Gene Expression, and TEA-seq libraries from the same PBMC sample in parallel.

Contributors

To be supplemented.

Contact

To be supplemented.

snRNA-Seq
Sample nameSample titleDiseaseGenderAgeSourceTreatmentTechnologyPlatformOmicsSample IDDataset IDAction
No data available