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Metabolic regulation of host defense against influenza virus infection through sensing oxaloacetate

GSE297098 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/07/18 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × Vehicle vs 3 × Vehicle-H1N1 vs 3 × DEOAA vs 3 × DEOAA-H1N1Groups 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)
Metabolic pathways determine cellular fate and function, however, the exact roles of metabolites in host immune responses against virus infection remain undefined. Here, we report that the metabolic pathways of oxaloacetate (OAA) are integrated with antiviral responses and OAA serves as a fundamental “cornerstone” to prime effective host resistance to the infection of influenza virus.
Read the full summary ↓
MDH1 senses cellular OAA to undergo dimerization, thus functions as a scaffold to recruit the transcription factor ETS2 for phosphorylation by the kinase TAOK1 at serine 313. The phosphorylated ETS2 translocates into the nucleus and sustains the appropriate expression of TBK1 to provide broad-spectrum antiviral activity. OAA deficiency caused by ACLY genetic ablation decreases the antiviral immunity through MDH1–TAOK1–ETS2–TBK1 pathway in vivo, and makes mice more susceptible to lethal H1N1 virus infection. Our results uncover a previously unknown signaling pathway to maintain immune homeostasis by sensing cellular OAA, which links metabolism and antiviral innate immunity.
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 GSE297098_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 PRJNA1262515 and SRA study SRP585014. Searching any of these in the dataset finder brings you back here.

Study design
3 × Vehicle vs 3 × Vehicle-H1N1 vs 3 × DEOAA vs 3 × DEOAA-H1N1

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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