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Cut&Tag of GMP from mice treated with DSS, HK-EF or its excipient.

GSE281375 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 18 samples Submitted 2025/01/22 Platform GPL17021
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 18 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
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
Microbiota translocation following intestinal barrier disruption promotes Mincle-mediated training of myeloid progenitors in the bone marrowImmunity · 2025
Summary (written by the submitters)
Inflammatory bowel disease induced by treatment with DSS induce destruction of gut barrier inducing massive bacterial translocation to distal tissue. Our findings suggest that gut microbiota translocation induces trained immunity in Granulocyte-monocyte progenitors that can underlie pathologies related to low-grade systemic inflammation.
Read the full summary ↓
The identification of E.faecalis translocation to the bone marrow as a main driver of this effect and its sensing by Mincle receptor in bone marrow progenitors offers potential targets for intervention in pathophysiological settings where gut permeability is altered. Moreover, intravenously and intranasal administration of HK-EF provided protection against systemic candidiasis in wild-type and Rag1-deficient mice lacking functional lymphocytes, indicative of innate immune-mediated protection.
Published in
Microbiota translocation following intestinal barrier disruption promotes Mincle-mediated training of myeloid progenitors in the bone marrow
Robles-Vera I, Jarit-Cabanillas A, Brandi P et al. · Immunity 2025 · PMID 39848243 · doi:10.1016/j.immuni.2024.12.012
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 GSE281375_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1183753 and SRA study SRP544029. Searching any of these in the dataset finder brings you back here.

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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