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Frequency, kinetics and determinants of viable SARS-CoV-2 in bioaerosols from ambulatory COVID-19 patients infected with the β, δ or ο variants

GSE252508 Homo sapiens (human) RNA-seq (gene expression) 33 samples Submitted 2024/03/13 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 33 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
33 samples: 33 samples, each with a distinct title — no replicated groupsGroups 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
Frequency, kinetics and determinants of viable SARS-CoV-2 in bioaerosols from ambulatory COVID-19 patients infected with the Beta, Delta or Omicron variantsNature communications · 2024
Summary (written by the submitters)
Airborne transmission of SARS-CoV-2 aerosol remains contentious. Importantly, whether cough or breath-generated bioaerosols can harbor viable and replicating virus remains largely unclarified. We perform size-fractionated aerosol sampling (Andersen cascade impactor) and evaluate viral culturability in human cell lines (infectiousness), viral genetics, and host immunity in ambulatory participants with COVID-19.
Read the full summary ↓
Sixty-one percent (27/44) and 50% (22/44) of participants emitted variant-specific culture-positive aerosols <10μm and <5μm, respectively, for up to 9 days after symptom onset. Aerosol culturability is significantly associated with lower neutralizing antibody titers, and suppression of transcriptomic pathways related to innate immunity and the humoral response. A nasopharyngeal Ct <17 rules-in ~40% of aerosol culture-positives and identifies those who are probably highly infectious. A parsimonious three transcript blood-based biosignature is highly predictive of infectious aerosol generation (PPV> 95%). There is considerable heterogeneity in potential infectiousness i.e., only 29% of participants were probably highly infectious (produced culture-positive aerosols <5μm at ~6 days after symptom onset). These data, which comprehensively confirm variant-specific culturable SARS-CoV-2 in aerosol, inform the targeting of transmission-related interventions and public health containment strategies emphasizing improved ventilation.
Published in
Frequency, kinetics and determinants of viable SARS-CoV-2 in bioaerosols from ambulatory COVID-19 patients infected with the Beta, Delta or Omicron variants
Jaumdally S, Tomasicchio M, Pooran A et al. · Nature communications 2024 · PMID 38443359 · doi:10.1038/s41467-024-45400-1
This dataset
Open GSE252508 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 GSE252508_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 PRJNA1061045 and SRA study SRP481306. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38443359) ↗
Study design
33 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 33 sample titles: 33 distinct titles with little repetition. 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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