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ACE2 knockout hinders SARS-CoV-2 propagation in iPS cell-derived airway and alveolar epithelial cells

GSE275240 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/08/21 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 16 distinct titles, 2 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
ACE2 knockout hinders SARS-CoV-2 propagation in iPS cell-derived airway and alveolar epithelial cellsFrontiers in cell and developmental biology · 2023
Summary (written by the submitters)
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, continues to spread around the world with serious cases and deaths. It has also been suggested that different genetic variants in the human genome affect both the susceptibility to infection and severity of disease in COVID-19 patients. Angiotensin-converting enzyme 2 (ACE2) has been identified as a cell surface receptor for SARS-CoV and SARS-CoV-2 entry into cells.
Read the full summary ↓
The construction of an experimental model system using human iPS cells would enable further studies of the association between viral characteristics and genetic variants. Airway and alveolar epithelial cells are cell types of the lung that express high levels of ACE2 and are suitable for in vitro infection experiments. Here, we show that human iPS cell-derived airway and alveolar epithelial cells are highly susceptible to viral infection of SARS-CoV-2. Using gene knockout with CRISPR-Cas9 in human iPS cells we demonstrate that ACE2 plays an essential role in the airway and alveolar epithelial cell entry of SARS-CoV-2 in vitro. Replication of SARS-CoV-2 was strongly suppressed in ACE2 knockout (KO) lung cells. Our model system based on human iPS cell-derived lung cells may be applied to understand the molecular biology regulating viral respiratory infection leading to potential therapeutic developments for COVID-19 and the prevention of future pandemics.
Published in
ACE2 knockout hinders SARS-CoV-2 propagation in iPS cell-derived airway and alveolar epithelial cells
Niwa R, Sakai K, Lung MSY et al. · Frontiers in cell and developmental biology 2023 · PMID 38149046 · doi:10.3389/fcell.2023.1290876
This dataset
Open GSE275240 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 GSE275240_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 PRJDB15620 and SRA study DRP011895. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38149046) ↗
Study design
16 distinct titles, 2 of them repeated
1-Alv_x ×2 1-Air_x ×2

How we read this: Read from 18 sample titles: 16 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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