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scRNA sequencing revealed HIV-associated inflammatory-mediated lung epithelial dysregulation and fibroblast remodeling

GSE319646 Homo sapiens (human) Single-cell RNA-seq 15 samples Submitted 2026/03/27 Platform GPL34284
At a glance

Single-cell RNA-seq · human · 15 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
15 samples: 13 × HU vs 2 × HuGroups 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
scRNA sequencing revealed HIV-associated inflammation-mediated lung epithelial dysregulation and fibroblast remodelingFrontiers in immunology · 2026
Summary (written by the submitters)
HIV infection is a well-recognized risk factor for a wide spectrum of pulmonary diseases, with incidence rates significantly higher in people living with HIV (PLWH). Despite antiretroviral therapy, persistent immune activation and recurrent injury continue to compromise lung integrity in this population. However, the mechanism through which HIV disrupts alveolar homeostasis and reshapes epithelial, immune, and stromal compartments in the lungs remain poorly defined.
Read the full summary ↓
To characterize the cellular and molecular landscape of HIV infection within the lungs upon tobacco smoking, we performed single cell RNA sequencing (scRNA-seq) on human lung tissues from HIV non-smokers and smokers compared them with HIV positive subjects with and without a smoking history. Integration and Uniform Manifold Approximation and Projection (UMAP) clustering of 54,320 cells from all experimental groups identified 29 transcriptionally distinct clusters upon scRNA seq analyses. HIV infection profoundly altered lung cellular composition, marked by expansion of CD4+, CD8+ T-cells, B cells, and non-classical monocytes, alongside reduced fibroblast abundance. Alveolar Type I and Type II epithelial cells displayed robust HIV-associated transcriptional reprogramming. In AT1 cells,. Fibroblast and smooth muscle cells showed enhanced proinflammatory and stress responsiveness with suppression of extracellular matrix and contractile programs. EMT marker analysis revealed cell type specific shifts with: (a) AT1 cells exhibiting reduced E-cadherin and increased vimentin gene expression, (b) AT2 cells adopting a hybrid epithelial mesenchymal phenotype, and (c) myofibroblast cluster displaying amplified mesenchymal activation. These findings reveal HIV as a potent driver of epithelial dysregulation in the human lung, and suggest that targeting epithelial stress programs and fibroblast remodeling may offer new therapeutic avenues, supporting future efforts to develop therapeutic interventions tailored for PLWH.
Published in
scRNA sequencing revealed HIV-associated inflammation-mediated lung epithelial dysregulation and fibroblast remodeling
Islam KU, Kaur G, Shaikh SB et al. · Frontiers in immunology 2026 · PMID 42079650 · doi:10.3389/fimmu.2026.1789140
This dataset
Open GSE319646 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 GSE319646_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 PRJNA1424902 and SRA study SRP677683. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42079650) ↗
Study design
13 × HU vs 2 × Hu

Supports a between-group comparison across 15 samples.

How we read this: 2 replicated groups read from 15 sample titles; they account for 15 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
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