GEO series

Airway immune signatures of protection and disease progression in recent human tuberculosis household contacts [bulk RNA-seq]

GSE328391 Homo sapiens (human) Single-cell RNA-seq 125 samples Submitted 2026/05/01 Platform GPL34281

At a glance

Single-cell RNA-seq · human · 125 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: 125 samples: 125 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: Airway immune signatures of protection and disease progression in recent human tuberculosis household contactsNature immunology · 2026

Summary (written by the submitters)

The local early immune factors dictating whether individuals who have been infected with Mycobacterium tuberculosis remain healthy or progress to active TB have not been defined. We interrogated the airway immune response at single cell resolution in bronchoalveolar lavage (BAL) from PET-CT characterised recent TB household contacts, who either controlled the infection or progressed to TB disease, as well as of active TB patients at diagnosis.

Read the full summary ↓

Single cell RNA-sequencing revealed type I IFN-dependent and -independent neutrophil signatures in BAL from active TB patients and TB progressors. We report an inverse relationship between airway neutrophils and T cells, with T cells showing signatures of exhaustion, cytotoxicity and cell death in progressors and active TB patients with a neutrophil dominated airway profile. Conversely, we identified T cell signatures of protection in non-progressor contacts dominated by genes related to regulation, quiescence and a stem-like profile. Both the signature of TB progression and the stem-like T cell signature of non-progressors from human airways were recapitulated in scRNA-seq data from non-human primate (NHP) granulomas, associated with disease or immune protection, respectively. Our findings from early human airway responses in TB contacts reveal genes, pathways and cell states that may dictate infection outcome and inform strategies for developing effective host-directed therapies and vaccines.

Published in

Airway immune signatures of protection and disease progression in recent human tuberculosis household contacts

Branchett WJ, Kim JW, Shields J et al. · Nature immunology 2026 · PMID 42343006 · doi:10.1038/s41590-026-02544-0

This dataset

Open GSE328391 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 GSE328391_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 PRJNA1454893 and SRA study SRP692761. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42343006) ↗

Study design

125 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 125 sample titles: 125 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

GSM9681796 C011_B_BAL_IGRApos_PETneg
GSM9681797 C011_F_BAL_IGRApos_PETneg
GSM9681798 C012_B_BAL_IGRApos_PETneg
GSM9681799 C013_B_BAL_IGRApos_PETpos
GSM9681800 C018_B_BAL_IGRApos_PETpos
GSM9681801 C018_F_BAL_IGRApos_PETpos
GSM9681802 C026_B_BAL_IGRApos_PETpos
GSM9681803 C030_B_BAL_IGRAneg
GSM9681804 C031_B_BAL_IGRAneg
GSM9681805 C034_F_BAL_IGRAneg
GSM9681806 C036_B_BAL_IGRAneg_PETpos
GSM9681807 C037_B_BAL_IGRAneg
GSM9681808 C038_B_BAL_IGRAneg
GSM9681809 C039_B_BAL_IGRAneg_PETpos
GSM9681810 C039_F_BAL_IGRApos_PETpos
GSM9681811 C040_B_BAL_IGRApos_PETneg
GSM9681812 C042_B_BAL_IGRAneg
GSM9681813 C046_B_BAL_IGRAneg
GSM9681814 C047_B_BAL_IGRAneg
GSM9681815 C052_B_BAL_IGRApos_PETneg
GSM9681816 C052_F_BAL_IGRApos_PETneg
GSM9681817 C056_F_BAL_IGRApos_PETpos
GSM9681818 C058_B_BAL_IGRApos_PETneg
GSM9681819 C058_F_BAL_IGRApos_PETpos
GSM9681820 C068_B_BAL_IGRAneg
GSM9681821 C069_B_BAL_IGRApos_PETpos
GSM9681822 C070_B_BAL_IGRAneg_PETpos
GSM9681823 C070_F_BAL_IGRAneg_PETpos
GSM9681824 C071_B_BAL_IGRAneg
GSM9681825 C073_B_BAL_IGRAneg
GSM9681826 C074_B_BAL_IGRApos_PETpos
GSM9681827 C074_F_BAL_Progressor
GSM9681828 C075_B_BAL_IGRApos_PETpos
GSM9681829 C075_F_BAL_Progressor
GSM9681830 C075_P_BAL_Progressor
GSM9681831 C077_B_BAL_IGRApos_PETpos
GSM9681832 C077_F_BAL_IGRApos_PETpos
GSM9681833 C078_P_BAL_Progressor
GSM9681834 C079_B_BAL_IGRAneg_PETpos
GSM9681835 C079_F_BAL_IGRApos_PETpos

+ 85 more — browse all 125 samples with per-sample file links →

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Search all human RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.