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Macrophage-exacerbated viral lung injury and mechanical overdistension-driven bacterial superinfection replicated in a human lung chip

GSE272710 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/12/07 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 6 conditions, mostly with about 4 replicates eachGroups 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.
Summary (written by the submitters)
Patients with severe influenza-induced lung injury exhibit disrupted alveolar barrier and persistent viral load, accompanied by hyperinflammation, immune cell recruitment, and risk of bacterial superinfection. These complications are often exacerbated in patients undergoing mechanical ventilation.
Read the full summary ↓
Leveraging an immune-competent human lung alveolus-on-a-chip (Lung Chip) lined by human pulmonary alveolar epithelium co-cultured with monocyte-derived macrophages and interfaced with lung microvascular endothelium, we show that monocyte-derived macrophages play a central role in driving key hallmarks of severe influenza, including activated cell death programs. Physiological strain mimicking breathing motions supported alveolar homeostasis, whereas pathological strain analogous to mechanical ventilator-induced lung overdistension promoted secondary Pseudomonas aeruginosa infection. Computational gene network analysis combined with experimental validation identified SIRT1 as a key modulator of inflammation and susceptibility to bacterial superinfection, which can be mitigated using pharmacological SIRT1 activators. Together, these findings underscore the importance of incorporating macrophages into preclinical models of viral lung injury and establish an integrated workflow combining human Organ Chips and computational approaches for gaining insights into biophysical and molecular disease drivers while facilitating the identification of therapeutic targets and candidate countermeasures.
This dataset
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.

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 GSE272710_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1138243. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly with about 4 replicates each
w Mac, mock, apical, ×4 wo Mac, H3N2, apical, ×4 w Mac, H3N2, apical, ×4 w Mac, mock, basal, ×4 wo Mac, H3N2, basal, ×4 w Mac, H3N2, bascal, ×4

Supports a between-group comparison across 24 samples.

How we read this: 6 replicated groups read from 24 sample titles; they account for 24 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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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.