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TNFSF13 insuffiency causes epithelial and immune disruption in the human colon I

GSE243443 Homo sapiens (human) Single-cell RNA-seq 14 samples Submitted 2024/11/05 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 14 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
14 samples: 14 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
TNFSF13 insufficiency disrupts human colonic epithelial cell-mediated B cell differentiationbioRxiv : the preprint server for biology · 2024
Summary (written by the submitters)
Objective: Cytokines produced by epithelial and immune cells can act upon one another to promote mucosal healing- a process that goes awry with chronic inflammation as in inflammatory bowel disease. TNFSF13 is a cytokine important for B cell function, but its role in epithelial cell behavior and contribution to inflammatory bowel disease is poorly understood.
Read the full summary ↓
Design: We performed histological and functional assays, single cell transcriptomics, and imaging mass cytometry on tissue-derived colonoids or biopsies from a patient with very early onset inflammatory bowel disease (VEO-IBD) harboring a novel TNFSF13 variant. To confirm causal, variant-driven phenotypes, parallel experiments were performed in induced pluripotent stem cell (iPSC)- derived colon organoids engineered with the same TNFSF13 variant. Results: TNFSF13 variant colonoids exhibited reduced TNFSF13 expression associated with increased proliferation and reduced apoptosis, which was confirmed in iPSC-derived colon organoids. Single cell RNA-sequencing and flow cytometry defined FAS as the predominant colonic epithelial receptor for TNFSF13. TNFSF13 variant colon biopsies demonstrated a shift in tissue B cell populations consistent with altered differentiation of memory B cells. Finally, imaging mass cytometry revealed an increase in epithelial-associated B cells in TNFSF13 variant colon tissue sections compared to healthy and non-monogenic VEO-IBD controls. Conclusions: The current study defines a previously unknown role for the cytokine TNFSF13 as a regulator of colonic epithelial proliferation and apoptosis. Furthermore, this study suggests that variant TNFSF13 can contribute to aberrant epithelial- B cell crosstalk in the human colon.
Published in
TNFSF13 insufficiency disrupts human colonic epithelial cell-mediated B cell differentiation
Ma X, Dawany N, Kondo A et al. · bioRxiv : the preprint server for biology 2024 · PMID 39386555 · doi:10.1101/2024.09.23.614260
This dataset
Open GSE243443 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 GSE243443_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1018512 and SRA study SRP461441. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39386555) ↗
Study design
14 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 14 sample titles: 14 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
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