GEO series

Deciphering the initial steps of SARS-CoV2 infection in whole human lungs identifies macrophages as primary targets and reveals subset-specific responses.

GSE246128 Homo sapiens (human) Single-cell RNA-seq 10 samples Submitted 2024/07/04 Platform GPL21697

At a glance

Single-cell RNA-seq · human · 10 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 10 samples: 8 distinct titles, 1 of them repeatedGroups 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: SARS-CoV2 infection in whole lung primarily targets macrophages that display subset-specific responsesCellular and molecular life sciences : CMLS · 2024

Summary (written by the submitters)

Several in vitro models have been established to mimic the initial interaction between lung cell types and SARS-CoV-2, mainly using explant-based techniques that generated contrasted results about the cell types that were infected. These contrasting results could be due to biases in the various tissue-culture conditions. Furthermore, all these systems do not respect the spatial tissue architecture and the anatomic constraints that shape cell type interactions with viruses.

Read the full summary ↓

In this study, we used whole human lungs maintained alive ex vivo for 10 h, based on a technique used in lung transplantation (ex vivo lung perfusion or EVLP), to analyze the first steps of SARS-CoV-2 infection in the lung. Five human donor lungs declined for transplantation were perfused and ventilated at 37°C and three of them were infected with SARS-CoV-2 using nebulization of the Wuhan lineage and D614G variants. Single-cell RNA-sequencing (scRNA-seq) using 10x Genomics 3' (v3 Chemistry) has been performed on these samples.

Published in

SARS-CoV2 infection in whole lung primarily targets macrophages that display subset-specific responses

Vu Manh TP, Gouin C, De Wolf J et al. · Cellular and molecular life sciences : CMLS 2024 · PMID 39147987 · doi:10.1007/s00018-024-05322-z

This dataset

Open GSE246128 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 GSE246128_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1031610. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39147987) ↗

Study design

8 distinct titles, 1 of them repeated

Lung of Dono ×3

How we read this: Read from 10 sample titles: 8 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

GSM7856856 Lung of Donor 1
GSM7856857 Lung of Donor 1, EVLP + virus
GSM7856858 Lung of Donor 2
GSM7856859 Lung of Donor 2, EVLP + virus
GSM7856860 Lung of Donor 2, MHC2 enriched
GSM7856861 Lung of Donor 2, MHC2 enriched, EVLP + virus
GSM7856862 Lung of Donor 3
GSM7856863 Lung of Donor 3, EVLP + virus
GSM7856864 Lung of Donor 3, MHC2 enriched
GSM7856865 Lung of Donor 3, MHC2 enriched, EVLP + virus

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