| NSF Org: |
DBI Division of Biological Infrastructure |
| Recipient: |
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| Initial Amendment Date: | June 3, 2020 |
| Latest Amendment Date: | June 3, 2020 |
| Award Number: | 2033973 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Reed Beaman
DBI Division of Biological Infrastructure BIO Directorate for Biological Sciences |
| Start Date: | July 1, 2020 |
| End Date: | June 30, 2022 (Estimated) |
| Total Intended Award Amount: | $199,999.00 |
| Total Awarded Amount to Date: | $199,999.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
874 TRADITIONS WAY TALLAHASSEE FL US 32306-0001 (850)644-5260 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
319 Stadium Drive Tallahassee FL US 32306-4295 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | COVID-19 Research |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.074 |
ABSTRACT
The award to Florida State University will support research contributing to the development of georeferenced, vetted, and versioned data products of the world?s specimens of horseshoe bats and their relatives for use by researchers studying the origins and spread of SARS-like coronaviruses, including the causative agent of COVID-19. Horseshoe bats and other closely related species are reported to be reservoirs of several SARS-like coronaviruses. Species of these bats are primarily distributed in regions where these viruses have been introduced to populations of humans. Currently, data associated with specimens of these bats are housed in natural history collections that are widely distributed both nationally and globally. Additionally, information tying these specimens to localities are mostly vague, or in many instances missing. This decreases the utility of the specimens for understanding the source, emergence, and distribution of SARS-COV-2 and similar viruses. This project will provide quality georeferenced data products through the consolidation of ancillary information linked to each bat specimen, using the extended specimen model. The resulting product will serve as a model of how data in biodiversity collections might be used to address emerging diseases of zoonotic origin. Results from the project will be disseminated widely in opensource journals, at scientific meetings, and via websites associated with the participating organizations and institutions. Support of this project provides a quality resource optimized to inform research relevant to improving our understanding of the biology and spread of SARS-CoV-2. The overall objectives are to deliver versioned data products, in formats used by the wider research and biodiversity collections communities, through an open-access repository; project protocols and code via GitHub and described in a peer-reviewed paper, and; sustained engagement with biodiversity collections throughout the project for reintegration of improved data into their local specimen data management systems improving long-term curation.
This RAPID award will produce and deliver a georeferenced, vetted and consolidated data product for horseshoe bats and related species to facilitate understanding of the sources, distribution, and spread of SARS-CoV-2 and related viruses, a timely response to the ongoing global pandemic caused by SARS-CoV-2 and an important contribution to the global effort to consolidate and provide quality data that are relevant to understanding emergent and other properties the current pandemic. This RAPID award is made by the Division of Biological Infrastructure (DBI) using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The COVID-19 pandemic necessitated the mobilization of data about the diversity and distribution of horseshoe bats and relatives, a group documented to host close wild relatives to SARS-CoV-2 (the virus responsible for COVID-19). Our work accomplished two important things: (1) we produced a research-ready dataset about the nearly 90,000 specimens of in-scope bats from the world?s museums, and (2) we wrote and refined a set of rapid response protocols to enhance specimen data when the next crisis (e.g., an oil spill) arises. This involved assigning geospatial coordinates (i.e., longitude and latitude) to collecting locations for mapping and standardizing a set of high-value features of the dataset (taxonomic identifications, collector names, collection dates, and linkages to genomic data derived from the specimens). Our geocoding produced extensions of distributions for 40% of the bat species. Along the way we also enhanced a major tool for assigning geospatial coordinates to collection locations (GEOLocate) for the benefit of all of those using it. We shared versions of our dataset and protocols throughout the project on Zenodo, and the final version of the dataset has been downloaded over 3,250 times as of mid-2022. This attention to the dataset was partly driven by our outreach about our activities both within our domain (4 talks) and to the COVID Information Commons Community organized by Columbia University (1 talk). Results from the work were published in a pair of publications. The work engaged three early career professionals as well as trained a group of 34 people in methods that leverage two tools, Bionomia and Wikidata, to make references to people more precise in datasets of this type.
Last Modified: 10/28/2022
Modified by: Austin R Mast
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