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Series GSE155241 Query DataSets for GSE155241
Status Public on Aug 11, 2020
Title Identification of Drugs Blocking SARS-CoV-2 Infection using hPSC-derived Lung and Colonic Organoids
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary The SARS-CoV-2 has already caused over twelve million COVID-19 cases and half a million deaths worldwide. There is an urgent need to create novel models using human disease-relevant cells to study SARS-CoV-2 biology and to facilitate drug screening. As SARS-CoV-2 primarily infects the respiratory tract, we developed a lung organoid model using human pluripotent stem cells (hPSC-LOs) that could be adapted for drug screening. The hPSC-LOs, particularly alveolar type II-like cells, express the viral entry receptor ACE2, are permissive to SARS-CoV-2 infection, and showed robust induction of chemokines and cytokines upon SARS-CoV-2 infection, similar to what is seen in COVID-19 patients. Nearly 25% of these patients have gastrointestinal manifestations, which are associated with worse COVID-19 outcomes1. We therefore also generated complementary hPSC-derived colonic organoids (hPSC-COs) to explore the response of colonic cells to SARS-CoV-2 infection. We found that multiple colonic cell types, especially enterocytes, express ACE2 and are permissive to SARS-CoV-2 infection. Using hPSC-LOs, we performed a high throughput screen of FDA-approved drugs and identified entry inhibitors of SARS-CoV-2, including imatinib, mycophenolic acid (MPA), and quinacrine dihydrochloride (QNHC). Pre- or post-infection treatment at physiologically relevant levels of these drugs significantly inhibited SARS-CoV-2 infection of both hPSC-LOs and hPSC-COs. Together, these data demonstrate that hPSC-LOs and hPSC-COs infected by SARS-CoV-2 can serve as disease models to study SARS-CoV-2 infection and provide a valuable resource for drug screening to identify candidate COVID-19 therapeutics.
 
Overall design COVID-19 lung biopsy and SARS-CoV-2 infected lung organoids
 
Contributor(s) Han Y, Yang L, Chen S, Nilsson-Payant BE, Bram Y, Schwartz RE, tenOever BR
Citation(s) 33116299
Submission date Jul 27, 2020
Last update date Jan 05, 2022
Contact name Shuibing Chen
E-mail(s) shuibing.chen@gmail.com
Phone 2127465431
Organization name Weill Cornell Medical College
Department Surgery
Street address A 827B, 1300 York Ave
City New York
State/province NY
ZIP/Postal code 10065
Country USA
 
Platforms (1)
GPL24676 Illumina NovaSeq 6000 (Homo sapiens)
Samples (18)
GSM4697982 Healthy Lung autopsy [Healthy-lung]
GSM4697983 Healthy Lung autopsy_1 [HealthyLungBiopsy_1]
GSM4697984 Healthy Lung autopsy_2 [HealthyLungBiopsy_2]
Relations
BioProject PRJNA649019
SRA SRP273808

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
GSE155241_Processed_gene_expression.2.xlsx 1.9 Mb (ftp)(http) XLSX
GSE155241_Processed_gene_expression.xlsx 2.9 Mb (ftp)(http) XLSX
SRA Run SelectorHelp
Raw data are available in SRA
Processed data are available on Series record

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