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Remdesivir has previously unknown anti-viral immunomodulatory properties through the Adenosine A2A Receptor pathway

GSE236563 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2024/09/11 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 4 × Vehicle_day4 vs 4 × Vehicle_day7 vs 4 × REM_day4 vs 4 × REM_day7Groups 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
Novel immunomodulatory properties of adenosine analogs promote their antiviral activity against SARS-CoV-2EMBO reports · 2024
Summary (written by the submitters)
The COVID-19 pandemic has unveiled an urgent need for new anti-virals to control emerging infectious diseases and potential future pandemics. Classic anti-virals are currently designed to directly interfere with pathogens. However, anti-virals are often insufficient to rapidly clear infections in the absence of an effective immune response.
Read the full summary ↓
Immunotherapy could complement the use of anti-virals, however its application to infectious diseases remains largely unexplored. In this work, we found that the anti-viral drug remdesivir has previously unknown immunomodulatory properties which contribute to its therapeutic effect against SARS-CoV-2. These properties are due to remdesivir metabolite, GS-441524, acting as an Adenosine A2A Receptor antagonist, a function that is distinct from its intrinsic anti-viral activity. Our findings support a new rationale for the design of next-generation anti-viral agents with dual – immunomodulatory and intrinsic - anti-viral properties. These compounds could represent game-changing therapies to control emerging viral diseases and future pandemics.
Published in
Novel immunomodulatory properties of adenosine analogs promote their antiviral activity against SARS-CoV-2
Monticone G, Huang Z, Hewins P et al. · EMBO reports 2024 · PMID 39009832 · doi:10.1038/s44319-024-00189-4
This dataset
Open GSE236563 in finder → Find more mouse 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 GSE236563_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 PRJNA991577 and SRA study SRP447456. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39009832) ↗
Study design
4 × Vehicle_day4 vs 4 × Vehicle_day7 vs 4 × REM_day4 vs 4 × REM_day7

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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
Datasets on a similar topic

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