Human Lung Organoid Models of SARS-CoV-2 Infection
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 3U19AI116484-05S1
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$900,000Funder
National Institutes of Health (NIH)Principal Investigator
PendingResearch Location
United States of AmericaLead Research Institution
STANFORD UNIVERSITYResearch Priority Alignment
N/A
Research Category
Pathogen: natural history, transmission and diagnostics
Research Subcategory
Immunity
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
ABSTRACTPrimary human organoid models are an increasingly deployed platform for in vitro infectious disease modeling.The COVID-19 pandemic, engendered by the novel coronavirus SARS-CoV-2, represents a grave threat topublic health and physiologic in vitro infection models are therefore urgently needed. This supplement requestfor U19AI116484, Stanford Cooperative Center for Novel, Alternative Model Systems for Enteric Diseases(Stanford NAMSED), requests funding to create new models for SARS-CoV-2 infection using novel human lungorganoid technologies in collaboration with Dr. Ralph Baric at UNC, a recognized coronavirus authority. Thesestudies exploit SARS-CoV-2 infection of organoids using a feeder-free, chemically defined human lung organoidsystem (Calvin Kuo lab), lung organoids with integrated immune components (Calvin Kuo), methods for robustapical-basal inversion of lung organoid polarity (Manuel Amieva), BSL3 single cell RNA-seq (Catherine Blish)and SARS-CoV-2-GFP indicator strains and BSL3 facilities (Ralph Baric). The SARS-CoV-2 infection of lungorganoids will occur in BSL3 containment at both UNC and Stanford to compare apical versus basal infectionroutes, document how epithelial infection initiates secondary immune responses, and overall generate improved3D physiological models of SARS-CoV-2-GFP infection relevant to therapeutics screening.