Human memory CD4+ T cells recognize Mycobacterium tuberculosis-infected macrophages amid broader pathogen-specific responses [scRNA-seq]
Single-cell RNA-seq · human · 36 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
- 36 samples: 36 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
- Human CD4+ T cells recognize Mycobacterium tuberculosis-infected macrophages amid broader responsesThe Journal of experimental medicine · 2025
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE305300_RAW.tar (it can run to tens of gigabytes).
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.
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 PRJNA1305204 and SRA study SRP608586. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 36 sample titles: 36 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.
- GSM9168418 CL002 T-cells, Infected Macrophages, GEX
- GSM9168419 CL002 T-cells, Infected Macrophages, TCR
- GSM9168420 CL003 T-cells, Infected Macrophages, GEX
- GSM9168421 CL003 T-cells, Infected Macrophages, TCR
- GSM9168422 CL003 T-cells, Infected Macrophages and Mtb lysate, GEX
- GSM9168423 CL003 T-cells, Infected Macrophages and Mtb lysate, TCR
- GSM9168424 CL007 T-cells, Infected Macrophages, GEX
- GSM9168425 CL007 T-cells, Infected Macrophages, TCR
- GSM9168426 CL007 T-cells, Infected Macrophages and Mtb lysate, GEX
- GSM9168427 CL007 T-cells, Infected Macrophages and Mtb lysate, TCR
- GSM9168428 CL010 T-cells, Infected Macrophages, GEX
- GSM9168429 CL010 T-cells, Infected Macrophages, TCR
- GSM9168430 CL011 T-cells, Infected Macrophages, GEX
- GSM9168431 CL011 T-cells, Infected Macrophages, TCR
- GSM9168432 CL011 T-cells, Infected Macrophages and Mtb lysate, GEX
- GSM9168433 CL011 T-cells, Infected Macrophages and Mtb lysate, TCR
- GSM9168434 CL012 T-cells, Infected Macrophages, GEX
- GSM9168435 CL012 T-cells, Infected Macrophages, TCR
- GSM9168436 CL012 T-cells, Infected Macrophages and Mtb lysate, GEX
- GSM9168437 CL012 T-cells, Infected Macrophages and Mtb lysate, TCR
- GSM9168438 CL013 T-cells, Infected Macrophages, GEX
- GSM9168439 CL013 T-cells, Infected Macrophages, TCR
- GSM9168440 CL013 T-cells, Infected Macrophages and Mtb lysate, GEX
- GSM9168441 CL013 T-cells, Infected Macrophages and Mtb lysate, TCR
- GSM9168442 CL018 T-cells, Infected Macrophages, GEX
- GSM9168443 CL018 T-cells, Infected Macrophages, TCR
- GSM9168444 Leukopack 2 T-cells, Infected Macrophages, GEX
- GSM9168445 Leukopack 2 T-cells, Infected Macrophages, TCR
- GSM9168446 Leukopack 3 T-cells, Infected Macrophages, GEX
- GSM9168447 Leukopack 3 T-cells, Infected Macrophages, TCR
- GSM9168448 Leukopack 4 T-cells, Infected Macrophages, GEX
- GSM9168449 Leukopack 4 T-cells, Infected Macrophages, TCR
- GSM9168450 Leukopack 5 T-cells, Infected Macrophages, GEX
- GSM9168451 Leukopack 5 T-cells, Infected Macrophages, TCR
- GSM9168452 P079 T-cells, Infected Macrophages, GEX
- GSM9168453 P079 T-cells, Infected Macrophages, TCR
- GSE299662 scRNA-seq of Mycobacterium tuberculosis-specific CD4 T cells from Kenyan women with and wihtout HIV and before and after ART initiation following stimulation with Mtb WCL 14 samples shares cd4, mycobacterium, scrna-seq
- GSE267774 Specific CD4+ T cell phenotypes associate with bacterial control in people who ‘resist’ infection with Mycobacterium tuberculosis 3076 samples shares cd4, mycobacterium
- GSE189754 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - CD45 scRNA-Seq 15 samples shares cd4, scrna-seq
- GSE271543 UCPVax, a CD4 helper peptide vaccine induces polyfunctional Th1 cells, antibody response and epitope spreading to improve antitumor immunity [scRNA-seq] 5 samples shares cd4, scrna-seq
- GSE242232 Autoantigen-specific CD4+ T cells acquire an exhausted phenotype and persist in human antigen-specific autoimmune diseases 928 samples shares cd4
- GSE314342 Genome-scale perturb-seq in primary human CD4+ T cells reveals genes regulating T cell programs and human immune traits. 577 samples shares cd4
- GSE314188 Responders to low-dose ATG induce CD4+ T cell exhaustion in type 1 diabetes 514 samples shares cd4
- GSE303756 Loss of tolerance in cow milk allergic endotypes is linked to allergen-specific CD4+ T cell subset outgrowth and microbial dysbioses 114 samples shares cd4
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.