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A tissue-intrinsic mechanism sensitizes HIV-1 particles for TLR-triggered innate immune responses

GSE307977 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2026/03/31 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 18 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
18 samples: 18 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
A tissue-intrinsic mechanism sensitizes HIV-1 particles for TLR-triggered innate immune responsesNature communications · 2026
Summary (written by the submitters)
In vivo, HIV-1 replicates within tissues, yet the impact of three-dimensional (3D) environments on viral spread remains poorly understood. We previously showed that collagen-rich 3D extracellular matrix (ECM) imposes an Environmental Restriction to cell-free Virus Infectivity (ERVI). Here, we demonstrate that ERVI is mediated by adhesive ECM components assembled into tissue-like scaffolds.
Read the full summary ↓
Transient interactions with collagen fibers rapidly diminish virion infectivity across diverse primary strains by impairing virus fusogenicity. Notably, collagen-experienced particles also induce a distinct antiviral transcriptional program and strong pro-inflammatory cytokine secretion in monocyte-derived macrophages. Mechanistically, collagen contact induces conformational changes in the viral glycoprotein Env, enhances its interaction with toll-like receptor 2 (TLR2), and promotes trafficking into TLR8-positive endosomes, thereby amplifying innate immune sensing. Thus, ERVI acts through a dual mechanism: reducing virion fusogenicity while increasing innate immune detection. These findings identify the biophysical properties of the ECM as a tissue-intrinsic arm of antiviral innate immunity.
Published in
A tissue-intrinsic mechanism sensitizes HIV-1 particles for TLR-triggered innate immune responses
Sid Ahmed S, Zimmermann L, Imle A et al. · Nature communications 2026 · PMID 42106329 · doi:10.1038/s41467-026-72586-3
This dataset
Open GSE307977 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 GSE307977_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1327907 and SRA study SRP619883. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42106329) ↗
Study design
18 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 18 sample titles: 18 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
Datasets on a similar topic

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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.