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Mitochondrial dysfunction enhances influenza pathogenesis by upregulating sialic acid biosynthesis

GSE281057 Mus musculus (mouse) RNA-seq (gene expression) 29 samples Submitted 2025/05/30 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 29 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
29 samples: 6 conditions, mostly with about 5 replicates eachGroups 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
Mitochondrial dysfunction enhances influenza pathogenesis by up-regulating de novo sialic acid biosynthesisScience advances · 2025
Summary (written by the submitters)
Viral infections are well-established triggers of disease progression in pediatric mitochondrial disease (MtD). Caregivers frequently report that these infections are not only more severe but also prolonged, a concern reflected in high adherence to infection prevention practices within the MtD community. Despite these observations, significant gaps remain in our understanding of host-pathogen interactions during viral infections in MtD.
Read the full summary ↓
We hypothesized that mitochondrial dysfunction in MtD exacerbates viral pathogenesis and morbidity through metabolic allostatic alterations in infected cells. Using the Ndufs4 knock out (KO) mouse model of MtD, we observed severe clinical outcomes following influenza A virus infection, including pronounced weight loss, elevated viral load, cytokine storm, and reduced post-infection survival. Metabolic profiling in Ndufs4 KO lung epithelial cells (LET1), indicated a shift towards glycolysis and suggested a diversion of glucose carbons into anabolic pathways. Based on this finding, we determined that the increased influenza-associated susceptibility and morbidity in Ndufs4 KO was related to elevated levels of sialic acid (SIA), a key influenza receptor, derived from glycolysis. Pharmacological manipulation of glycolysis reduced SIA levels, viral load, and morbidity in Ndufs4 KO mice. Our findings demonstrate that metabolic dysregulation in MtD exacerbates viral attachment and pathogenesis, contributing to worsened clinical outcomes.
Published in
Mitochondrial dysfunction enhances influenza pathogenesis by up-regulating de novo sialic acid biosynthesis
Fuchs AL, Singh B, Jetmore JW et al. · Science advances 2025 · PMID 40614187 · doi:10.1126/sciadv.adu3739
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 GSE281057_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 PRJNA1181897 and SRA study SRP543107. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly with about 5 replicates each
WT mouse lung, IAV (H3N2) infected, 4 days po… ×5 Ndufs4 KO mouse lung, IAV (H3N2) infected, 4 … ×5 WT LET1 cells, uninfected, 24 hours post-mock… ×5 WT LET1 cells, IAV (H3N2) infected, 24 hours … ×5 Ndufs4 KO LET1 cells, uninfected, 24 hours po… ×5 Ndufs4 KO LET1 cells, IAV (H3N2) infected, 24… ×4

Supports a between-group comparison across 29 samples.

How we read this: 6 replicated groups read from 29 sample titles; they account for 29 of them. 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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