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Specific CD4+ T cell phenotypes associate with bacterial control in people who ‘resist’ infection with Mycobacterium tuberculosis

GSE267774 Homo sapiens (human) Single-cell RNA-seq 3076 samples Submitted 2024/06/01 Platform GPL16791
At a glance

Single-cell RNA-seq · human · 3076 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
3076 samples: 97 conditions, mostly with about 4 replicates eachGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Specific CD4(+) T cell phenotypes associate with bacterial control in people who 'resist' infection with Mycobacterium tuberculosisNature immunology · 2024
Summary (written by the submitters)
A subset of individuals with a high probability of exposure to M. tuberculosis (M.tb) appears to ‘resist’ established M.tb infection, as demonstrated by serially negative tuberculin skin test (TST) or IFN-γ release assay (IGRA) results. While these ‘resisters’ (RSTR) display IFN-γ-independent T cell responses to the M.tb-specific antigens ESAT-6 and CFP-10, it is currently unknown whether unique T cell functional programs are associated with this clinical outcome.
Read the full summary ↓
We used multi-modal single-cell RNA, TCR sequencing, multi-parameter flow cytometry, and cytokine analysis in a discovery and validation format to compare the phenotypes and functions of M.tb-specific T cells between RSTRs and matched controls with ‘latent’ M.tb infection (LTBI). M.tb-specific T cells were clonally expanded in both RSTRs and LTBIs, confirming the priming of adaptive immune responses after M.tb exposure. However, M.tb-specific T cells derived from RSTRs showed enrichment of T regulatory as well as Th17-like functional programs compared to LTBIs, which were characterized by Th1*-like effector programs. Th17-like functional programs were also associated with a lack of progression to active TB among South African adolescents with LTBI, as well as bacterial control in published non-human primate studies. Together, these data suggest that ‘resisters’ may successfully control M.tb after exposure and immune priming and establish a set of T cell biomarkers to facilitate further study of this important clinical phenotype.
Published in
Specific CD4(+) T cell phenotypes associate with bacterial control in people who 'resist' infection with Mycobacterium tuberculosis
Sun M, Phan JM, Kieswetter NS et al. · Nature immunology 2024 · PMID 38997431 · doi:10.1038/s41590-024-01897-8
This dataset
Open GSE267774 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE267774_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1112843 and SRA study SRP508438. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38997431) ↗
Study design
97 conditions, mostly with about 4 replicates each
D05_S41_L ×4 F08_S68_L ×4 H06_S90_L ×4 H07_S91_L ×4 A10_S10_L ×4 B04_S16_L ×4 D04_S40_L ×4 E10_S58_L ×4 +101 more

Supports a between-group comparison across 388 samples.

How we read this: 97 replicated groups read from the first 400 of 3076 sample titles; they account for 388 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 3036 more — browse all 3076 samples with per-sample file links →

Datasets on a similar topic

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