GEO series

Mycobacterium tuberculosis resisters despite HIV exhibit activated T cells and macrophages in their pulmonary alveoli [scRNA-seq]

GSE273373 Homo sapiens (human) Single-cell RNA-seq 51 samples Submitted 2025/02/09 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 51 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 51 samples: 51 samples, each with a distinct title — no replicated groupsGroups 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: Mycobacterium tuberculosis resisters despite HIV exhibit activated T cells and macrophages in their pulmonary alveoliThe Journal of clinical investigation · 2025

Summary (written by the submitters)

Natural resistance to Mycobacterium tuberculosis (Mtb) infection in some people living with HIV (PLWH) is unexplained. We performed single cell RNA-sequencing of bronchoalveolar lavage cells, unstimulated or ex vivo stimulated with Mtb, for 7 PLWH who were Tuberculin skin test (TST) & Interferon Gamma Release Assay (IGRA) positive (called LTBI) and 6 who were persistently TST & IGRA negative (called resisters).

Read the full summary ↓

Alveolar macrophages (AM) from resisters displayed a stronger baseline M1 phenotype than LTBI AM. Resisters displayed alveolar lymphocytosis (10%-60%), with enrichment of all T cell subpopulations including CD4+ and CD8+ IFNG-expressing cells. Alveolar lymphocytosis was strongly associated with most of the AM transcriptomic features of resisters. In both groups, mycobactericidal granulysin was expressed almost exclusively by a CD8+ T cell subtype that co-expressed granzyme B, perforin and NK cell receptors. These poly-cytotoxic T lymphocytes (CTL) over-expressed activating NK cell receptors and were increased in resisters. Following challenge with Mtb, only a subpopulation of Intraepithelial Lymphocytes (IEL)-like cells in LTBI participants responded with increased transcription of IFNG. AM from resisters responded with stronger TNF signature at 6h post-infection (p.i.) while at 24h p.i. AM from LTBI displayed stronger IFN-γ signature. Conversely, at 24h p.i. only AM from resisters displayed a significant upregulation of MICA transcripts which encode an activating ligand for the CD8+ poly-CTL. These results suggest that CD8+ CTL and AM mediate the resister phenotype in PLWH.

Published in

Mycobacterium tuberculosis resisters despite HIV exhibit activated T cells and macrophages in their pulmonary alveoli

Dallmann-Sauer M, Fava VM, Malherbe ST et al. · The Journal of clinical investigation 2025 · PMID 39836471 · doi:10.1172/JCI188016

This dataset

Open GSE273373 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 GSE273373_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 PRJNA1141503 and SRA study SRP522958. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39836471) ↗

Study design

51 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 51 sample titles: 51 distinct titles with little repetition. 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

GSM8427114 2RTB0014, LTBI, MtbINF, 7h, BAL, scRNA-seq
GSM8427115 2RTB0014, LTBI, MtbINF, 30h, BAL, scRNA-seq
GSM8427116 2RTB0014, LTBI, MtbNEG, 30h, BAL, scRNA-seq
GSM8427117 2RTB0014, LTBI, MtbNEG, 7h, BAL, scRNA-seq
GSM8427118 2RTB0058, Resister, MtbINF, 6h, BAL, scRNA-seq
GSM8427119 2RTB0058, Resister, MtbINF, 23h, BAL, scRNA-seq
GSM8427120 2RTB0058, Resister, MtbNEG, 23h, BAL, scRNA-seq
GSM8427121 2RTB0058, Resister, MtbNEG, 6h, BAL, scRNA-seq
GSM8427122 2RTB0062, Resister, MtbINF, 16h, BAL, scRNA-seq
GSM8427123 2RTB0062, Resister, MtbNEG, 16h, BAL, scRNA-seq
GSM8427124 2RTB0062, Resister, MtbINF, 6h, BAL, scRNA-seq
GSM8427125 2RTB0062, Resister, MtbNEG, 6h, BAL, scRNA-seq
GSM8427126 2RTB0092, LTBI, MtbINF, 22h, BAL, scRNA-seq
GSM8427127 2RTB0092, LTBI, MtbNEG, 22h, BAL, scRNA-seq
GSM8427128 2RTB0092, LTBI, MtbINF, 6h, BAL, scRNA-seq
GSM8427129 2RTB0092, LTBI, MtbNEG, 6h, BAL, scRNA-seq
GSM8427130 2RTB0113, LTBI, MtbINF, 24h, BAL, scRNA-seq
GSM8427131 2RTB0113, LTBI, MtbNEG, 24h, BAL, scRNA-seq
GSM8427132 2RTB0113, LTBI, MtbINF, 6h, BAL, scRNA-seq
GSM8427133 2RTB0113, LTBI, MtbNEG, 6h, BAL, scRNA-seq
GSM8427134 2RTB0148, LTBI, MtbINF, 22h, BAL, scRNA-seq
GSM8427135 2RTB0148, LTBI, MtbNEG, 22h, BAL, scRNA-seq
GSM8427136 2RTB0148, LTBI, MtbINF, 6h, BAL, scRNA-seq
GSM8427137 2RTB0148, LTBI, MtbNEG, 6h, BAL, scRNA-seq
GSM8427138 2RTB0183, Resister, MtbINF, 24h, BAL, scRNA-seq
GSM8427139 2RTB0183, Resister, MtbNEG, 24h, BAL, scRNA-seq
GSM8427140 2RTB0183, Resister, MtbINF, 6h, BAL, scRNA-seq
GSM8427141 2RTB0183, Resister, MtbNEG, 6h, BAL, scRNA-seq
GSM8427142 2RTB0196, LTBI, MtbINF, 25h, BAL, scRNA-seq
GSM8427143 2RTB0196, LTBI, MtbINF, 6h, BAL, scRNA-seq
GSM8427144 2RTB0196, LTBI, MtbNEG, 25h, BAL, scRNA-seq
GSM8427145 2RTB0196, LTBI, MtbNEG, 6h, BAL, scRNA-seq
GSM8427146 2RTB0205, LTBI, MtbINF, 22h, BAL, scRNA-seq
GSM8427147 2RTB0205, LTBI, MtbINF, 6h, BAL, scRNA-seq
GSM8427148 2RTB0205, LTBI, MtbNEG, 22h, BAL, scRNA-seq
GSM8427149 2RTB0209, Resister, MtbINF, 22h, BAL, scRNA-seq
GSM8427150 2RTB0209, Resister, MtbNEG, 22h, BAL, scRNA-seq
GSM8427151 2RTB0209, Resister, MtbINF, 6h, BAL, scRNA-seq
GSM8427152 2RTB0209, Resister, MtbNEG, 6h, BAL, scRNA-seq
GSM8427153 2RTB0215, LTBI, MtbINF, 24h, BAL, scRNA-seq

+ 11 more — browse all 51 samples with per-sample file links →

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