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Differential response of patient-derived intestinal organoids to site-specific mucosal bacteria in pediatric inflammatory bowel disease

GSE288179 Homo sapiens (human) RNA-seq (gene expression) 105 samples Submitted 2025/10/01 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 105 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
105 samples: 105 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.
Summary (written by the submitters)
Objective: Inflammatory bowel disease (IBD) is secondary to an abnormal immune response to the microbiota. There is evidence of impaired stem cell signatures in IBD contributing to impaired epithelial repair. We therefore aimed to study the role of the microbiome in the intestinal stem cell population in paediatric IBD cases, a group without confounding treatments or comorbidities, by directly studying the interaction between patient-isolated bacteria and the epithelium.
Read the full summary ↓
Design: We established a unique biobank with matched intestinal organoids and cultured mucosally adherent bacteria from 36 paediatric patients. To determine the bacterial effect on host epithelial cells, closely related bacterial isolates from control and IBD patients were selected for microinjection into their corresponding organoid line. Results: Whilst no differences were observed between control and IBD-derived organoids following injury, transcriptional profiling revealed differential gene expression between uninjured control and IBD- derived organoids. Furthermore, following microinjection of an isolate originating from a control patient, there was upregulation of inflammatory signalling pathways, whereas this was not observed with a closely related isolate originating from an IBD patient. Conclusion: This demonstrates the feasibility of isolating bacteria and generating organoids from the same biopsy tissue, to explore personalised host-microbe interactions. The microinjections show the individual nature of responses, with closely related bacteria inducing very different epithelial responses, with downstream implications for immune response. This highlights the importance of understanding host-microbe interactions in a strain and site-specific manner, and developing techniques for personalised microbiome-based therapeutics.
This dataset
Open GSE288179 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 GSE288179_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 PRJNA1216532. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
105 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 105 sample titles: 105 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

+ 65 more — browse all 105 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.