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Antibiotics damage the colonic mucus barrier in a microbiota-independent manner I

GSE260592 Mus musculus (mouse) RNA-seq (gene expression) 28 samples Submitted 2024/03/19 Platform GPL21626
At a glance

RNA-seq (gene expression) · mouse · 28 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
Mus musculus (mouse)
Samples
28 samples: 7 × PBS_DONO vs 7 × VANCO_DONO vs 7 × PBS_RECIPIENT vs 7 × VANCO_RECIPIENTGroups 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
Antibiotics damage the colonic mucus barrier in a microbiota-independent mannerScience advances · 2024
Summary (written by the submitters)
Antibiotic use is a risk factor for development of inflammatory bowel diseases (IBDs). IBDs are characterized by a damaged mucus layer, which does not properly separate the host intestinal epithelium from the microbiota. Here, we hypothesized that antibiotics might affect the integrity of the mucus barrier. By systematically determining the effects of different antibiotics on mucus layer penetrability we found that oral antibiotic treatment led to breakdown of the mucus barrier and penetration of bacteria into the mucus layer.
Read the full summary ↓
Using fecal microbiota transplant, RNA sequencing followed by machine learning and ex vivo mucus secretion measurements, we determined that antibiotic treatment induces ER stress and inhibits colonic mucus secretion in a microbiota-independent manner. This mucus secretion flaw led to penetration of bacteria into the colonic mucus layer, translocation of microbial antigens into circulation and exacerbation of ulcerations in a mouse model of IBD. Thus, antibiotic use might predispose to development of intestinal inflammation by impeding mucus production.
Published in
Antibiotics damage the colonic mucus barrier in a microbiota-independent manner
Sawaed J, Zelik L, Levin Y et al. · Science advances 2024 · PMID 39259805 · doi:10.1126/sciadv.adp4119
This dataset
Open GSE260592 in finder → Find more mouse 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 GSE260592_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 PRJNA1082294 and SRA study SRP493675. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39259805) ↗
Study design
7 × PBS_DONO vs 7 × VANCO_DONO vs 7 × PBS_RECIPIENT vs 7 × VANCO_RECIPIENT

Supports a between-group comparison across 28 samples.

How we read this: 4 replicated groups read from 28 sample titles; they account for 28 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
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.