NSF
Award Abstract #2033695

RAPID: Building a visual consensus model of the SARS-CoV-2 life cycle

See grant description on NSF site

Program Manager:

Richard Cyr

Active Dates:

Awarded Amount:

$173,405

Investigator(s):

Janet Iwasa

Miriah Meyer

Awardee Organization:

University of Utah
Utah

Directorate

Biological Sciences (BIO)

Abstract:

The COVID-19 epidemic has motivated hundreds (if not thousands) of biological researchers around the globe to redirect their research efforts towards the understanding of SARS-CoV-2. This is leading to an explosion of data and it will be essential to find ways to rapidly digest and integrate new information into a context that facilitates consensus building in the research community. How do researchers and the broader community stay abreast of this flood of information? And how can we quickly move towards building a consensus model of the SARS-CoV-2 life cycle that builds on this explosive body of scientific data and expertise? This work proposes to take a novel and intuitive approach to facilitate scientific discourse and dissemination through the development of: (1) detailed molecular 3-D depictions that put a diverse dataset into the context of the SARS-CoV-2 life cycle, and; (2) provide for annotation tools to be used by researchers to explore and capture scientific discussions that will speed up consensus building to promote a mechanistic understanding of how this virus works. If successful, the work will reduce the time of consensus building from years to months. In addition, a graduate student and postdoc will receive training at the intersection of biological and computer sciences. Specifically, researchers will work with an international group of SARS-CoV-2 experts to develop detailed and accurate visualizations of all stages of the viral life cycle including cellular entry, RNA replication and transcription, and viral assembly and egress with known energy states, rates, and spatial accuracy. These 3-D visualizations, which will be made freely available online, will be used to stimulate discussions within the scientific community, and will be iteratively updated based on community feedback and new data. To facilitate consensus building, annotation tools will be developed to interactively describe the data used to generate the visualizations and will also mediate and capture scientific discourse surrounding the various molecular mechanisms involved in viral infection. This project will rapidly produce a rich and publicly accessible collection of knowledge about SARS-CoV-2 biology for the global community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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