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Sepsis-induced changes in hepatic cell communication in mice: RNA-seq on purified cells

GSE311736 Mus musculus (mouse) RNA-seq (gene expression) 39 samples Submitted 2025/12/31 Platform GPL34475
At a glance

RNA-seq (gene expression) · mouse · 39 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
39 samples
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)
Sepsis, which affects 49 million people yearly, killing 11 million of them, involves activation of inflammation, as well as significant metabolic reprogramming. The liver is affected by these changes and is confronted with pathogens and is a key organ in restoring homeostasis. We addressed the question to what extent cell-cell communication between hepatic cell types is affected in sepsis, using the CLP model of sepsis in mice.
Read the full summary ↓
We sorted the four major hepatic cell types, hepatocytes (HEPs), hepatic stellate cells (HSCs), liver sinusoidal endothelial cells (LSECs) and Kupffer cells (KCs) as well as non-KC CD45+ cells and performed bulk deep RNAseq. Cell-specific pathways were studied, and we focused on cell-cell interactions between the cell types. We found that HSCs, which in control (Sham) animals are not significantly communicative, in sepsis behave as the major signal-spreading cell type, primarily stimulated by LSECs. The impact of the HSC signals on the other cell types was investigated by NicheNet and reveals interesting new insights into the initiation of diverse hepatic responses in sepsis, such as pathogen clearance, ECM remodeling, chemotaxis and metabolic reprogramming. HSCs may therefore be considered as primary cells to targets in sepsis.
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 GSE311736_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: 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 PRJNA1370845 and SRA study SRP649664. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 39 more — browse all 39 samples with per-sample file links →

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