GEO series

Maternal and donor human milk support robust intestinal epithelial growth and differentiation in a fetal intestinal organoid model

GSE253501 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2024/07/01 Platform GPL24676

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: 24 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)

Necrotizing enterocolitis (NEC) is a severe gastrointestinal complication of prematurity. Using small intestinal organoids derived from fetal tissue of a gestational age similar to an extremely preterm infant, this study aims to assess the effect of diet on intestinal epithelial growth and differentiation to elucidate the role nutrition type plays in intestinal development and modifies the risk for NEC.

Read the full summary ↓

Organoids were cultured for 5 days in growth media and 5 days in differentiation media supplemented 1:40 with four different diets: maternal milk (MM), donor human milk (DHM), standard formula, or extensively hydrolyzed formula. Images were captured daily and organoids were quantified. Organoids were preserved for RNA sequencing and immunofluorescence staining with Ki67, cleaved caspase 3, and chromogranin-A. Media was saved for cytokine/chemokine and growth factor analysis.Human milk supplementation improved growth and differentiation of intestinal organoids generating larger organoids during the growth phase and organoids with longer and wider buds during differentiation compared to formula. Ki67 staining confirmed the proliferative nature of milk-supplemented organoids and chromogranin A staining proved that MM-supplemented organoids induced highest enteroendocrine differentiation. Human milk supplementation also upregulated genes involved in proliferation and promoted a homeostatic immune landscape while those supplemented with formula had a downregulation of cell-cycle-promoting genes and a more inflammatory immune signature. Our results show that MM, and to a lesser extent DHM, support robust intestinal epithelial proliferation and differentiation, suggesting a critical role for factors enriched in human milk in intestinal epithelial health.

This dataset

Open GSE253501 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 GSE253501_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 PRJNA1065907 and SRA study SRP484297. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

24 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 24 sample titles: 24 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

GSM8021752 1038-G-OGM
GSM8021753 1038-G-MM
GSM8021754 1038-G-DHM
GSM8021755 1038-G-SF
GSM8021756 1038-G-HF
GSM8021757 1042-G-OGM
GSM8021758 1042-G-DHM
GSM8021759 1042-G-HF
GSM8021760 1081-G-OGM
GSM8021761 1081-G-MM
GSM8021762 1081-G-DHM
GSM8021763 1081-G-HF
GSM8021764 1081-D-ODM
GSM8021765 1081-D-DHM
GSM8021766 1081-D-SF
GSM8021767 1081-D-HF
GSM8021768 1132-G-OGM
GSM8021769 1132-G-MM
GSM8021770 1132-G-DHM
GSM8021771 1132-G-SF
GSM8021772 1132-G-HF
GSM8021773 1132-D-ODM
GSM8021774 1132-D-DHM
GSM8021775 1132-D-HF

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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.