Real-time pandemic functional characterization of SARS-CoV-2
- Funded by Swiss National Science Foundation (SNSF)
- Total publications:18 publications
Grant number: 196644
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Key facts
Disease
COVID-19Start & end year
20202022Known Financial Commitments (USD)
$494,204.65Funder
Swiss National Science Foundation (SNSF)Principal Investigator
Thiel VolkerResearch Location
SwitzerlandLead Research Institution
Institut für Virologie und Immunologie Depart. Infektionskrankheiten und Pathologie Universität BernResearch Priority Alignment
N/A
Research Category
Pathogen: natural history, transmission and diagnostics
Research Subcategory
Pathogen morphology, shedding & natural history
Special Interest Tags
N/A
Study Type
Clinical
Clinical Trial Details
Not applicable
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Real-time pandemic functional characterization of SARS-CoV-2 Background. The outbreak of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) represents the third zoonotic transmission of a high pathogenic coronavirus (CoV) within only two decades. Compared to SARS-CoV and Middle East Respiratory Syndrome CoV (MERS-CoV), that emerged in 2002 and 2012, respectively, SARS-CoV-2 appears to have a lower case fatality rate but is much more able to transmit from human to human. While SARS-CoV-2 genome sequences from patient samples became available within the first two weeks of the outbreak, it took almost two months until virus isolates were made available for reference laboratories and the scientific community. Since phenotypic differences and similarities of SARS-CoV-2 to the high pathogenic SARS- and MERS-CoVs or the low pathogenic common cold human CoVs cannot be deduced from the virus genomes sequences, we urgently need to initiate phenotypic and functional studies on this novel CoV involving infectious virus. Working hypotheses and aims. Of particular importance during the time of the ongoing pandemic is to follow SARS-CoV-2 evolution and to use our established synthetic genomics platform and the established primary human airway epithelium (hAEC) culture system to link genotypes to phenotypes. On a global scale it will be important to carefully link genomic analyses with patient metadata in order to immediately recognize if SARS-CoV-2 variants that arise during the pandemic may have undergone a phenotypic change (aim 1). On the scale of the individual patient it will be important to monitor in-patient evolution of SARS-CoV-2 and host responses in order to identify virus- and host-specific molecular signatures that are associated with mild or severe disease outcome (aim 2). Finally, the obtained data resulting from virus variants will be compared to SARS-CoV and HCoV-NL63, two viruses that use the same cellular receptor (ACE2), and to a set of rationally designed SARS-CoV-2 mutants that lack individual or several accessory genes (aim 3). Importantly, we have complementary expertise and experimental systems that are unique worldwide. We will bridge clinical data, patient samples, coronavirus reverse genetics, and primary human airway epithelial systems, to translate observed virus evolution directly to functional studies.Expected significance. The anticipated results of this project will be highly significant in a number of areas. First, the rapid translation of SARS-CoV-2 genome sequences to functional studies using reconstructed virus variants for phenotypic analyses in primary human airway epithelial cultures will inform if global virus evolution will lead to changes of the SARS-CoV-2 phenotype in the human population. Second, we will determine if SARS-CoV-2 has to undergo an adaptation to be able to efficiently replicate in the lower respiratory tract of patients. This data is important to guide clinicians concerning patient prognosis and may have also a diagnostic value. Finally, we will determine the host response to SARS-CoV-2 and variants in the human airway epithelium in an unprecedented depth by transcriptomics including single cell analyses. This will provide a comprehensive map of host responses that will be particularly informative concerning molecular signatures that drive inflammation and signatures that are associated with disease severity.
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