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Series GSE209537 Query DataSets for GSE209537
Status Public on Jul 29, 2022
Title Profiling of lung SARS-CoV-2 and influenza virus infection dissects virus-specific host responses and gene signatures
Organism Homo sapiens
Experiment type Other
Summary The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in late 2019 has spread globally, causing a pandemic of respiratory illness designated coronavirus disease 2019 (COVID-19). A better definition of the pulmonary host response to SARS-CoV-2 infection is required to understand viral pathogenesis and to validate putative COVID-19 biomarkers that have been proposed in clinical studies. Here, we use targeted transcriptomics of FFPE tissue using the Nanostring GeoMX™ platform to generate an in-depth picture of the pulmonary transcriptional landscape of COVID-19, pandemic H1N1 influenza and uninfected control patients. Host transcriptomics showed a significant upregulation of genes associated with inflammation, type I interferon production, coagulation and angiogenesis in the lungs of COVID-19 patients compared to non-infected controls. SARS-CoV-2 was non-uniformly distributed in lungs (emphasising the advantages of spatial transcriptomics) with the areas of high viral load associated with an increased type I interferon response. Once the dominant cell type present in the sample, within patient correlations and patient-patient variation had been controlled for, only a very limited number of genes were differentially expressed between the lungs of fatal influenza and COVID-19 patients. Strikingly, the interferon-associated gene IFI27, previously identified as a useful blood biomarker to differentiate bacterial and viral lung infections, was significantly upregulated in the lungs of COVID-19 patients compared to patients with influenza. Collectively, these data demonstrate that spatial transcriptomics is a powerful tool to identify novel gene signatures within tissues, offering new insights into the pathogenesis of SARS-COV-2 to aid in patient triage and treatment
 
Overall design In this dataset, we capture GeoMx DSP RNA profiles of lung tissue from SARS-CoV2 infected patients aswell as pH1N1 and control specimens
 
Contributor(s) Kulasinghe AK, Tan CW
Citation(s) 34675048
Submission date Jul 22, 2022
Last update date Jul 31, 2022
Contact name Arutha Kulasinghe
E-mail(s) arutha.kulasinghe@uq.edu.au
Organization name University of Queensland
Street address 37 kent st
City brisbane
ZIP/Postal code 4102
Country Australia
 
Platforms (1)
GPL24676 Illumina NovaSeq 6000 (Homo sapiens)
Samples (61)
GSM6373981 1_Covid(6) DSP-1012340008710-A03
GSM6373982 1_Covid(6) DSP-1012340008710-A02
GSM6373983 1_Covid(6) DSP-1012340008710-B01
Relations
BioProject PRJNA861390

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE209537_Hs_R_NGS_CTA_v1.0.pkc.gz 558.1 Kb (ftp)(http) PKC
GSE209537_Initial.csv.gz 6.6 Kb (ftp)(http) CSV
GSE209537_RAW.tar 1.9 Mb (http)(custom) TAR (of DCC)
GSE209537_q3.csv.gz 251.3 Kb (ftp)(http) CSV
GSE209537_qc.csv.gz 589.2 Kb (ftp)(http) CSV
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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