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A Novel Viral Assembly Inhibitor Blocks SARS-CoV-2 Replication in Airway Epithelial Cells

GSE261002 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2024/03/10 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 21 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
21 samples: 8 × DMSO vs 5 × SARS-CoV-2 infection vs 5 × PAV-104+SARS-CoV-2 infection vs 3 × PAV-104Groups 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
A viral assembly inhibitor blocks SARS-CoV-2 replication in airway epithelial cellsCommunications biology · 2024
Summary (written by the submitters)
The ongoing evolution of SARS-CoV-2 to evade vaccines and therapeutics underlines the need for novel therapies with high genetic barriers to resistance. The small molecule PAV-104, identified through a cell-free protein synthesis and assembly screen, was recently shown to target host protein assembly machinery in a manner specific to viral assembly.
Read the full summary ↓
Here, we investigated the capacity of PAV-104 to inhibit SARS-CoV-2 replication in human airway epithelial cells (AECs). Our data demonstrate that PAV-104 inhibited >99% of infection with diverse SARS-CoV-2 variants in primary and immortalized human AECs. PAV-104 suppressed SARS-CoV-2 production without affecting viral entry or protein synthesis. PAV-104 interacted with SARS-CoV-2 nucleocapsid (N) and interfered with its oligomerization, blocking particle assembly. Transcriptomic analysis revealed that PAV-104 reversed SARS-CoV-2 induction of the type-I interferon response and the maturation of nucleoprotein signaling pathway known to support coronavirus replication. Our findings suggest that PAV-104 is a promising therapeutic candidate for COVID-19.
Published in
A viral assembly inhibitor blocks SARS-CoV-2 replication in airway epithelial cells
Du L, Deiter F, Bouzidi MS et al. · Communications biology 2024 · PMID 38649430 · doi:10.1038/s42003-024-06130-8
This dataset
Open GSE261002 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 GSE261002_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 PRJNA1084811 and SRA study SRP493673. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38649430) ↗
Study design
8 × DMSO vs 5 × SARS-CoV-2 infection vs 5 × PAV-104+SARS-CoV-2 infection vs 3 × PAV-104

Supports a between-group comparison across 21 samples.

How we read this: 4 replicated groups read from 21 sample titles; they account for 21 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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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.