2515340
Cooperative Agreement
Overview
Grant Description
BII: Predicting the global host-virus network from molecular foundations - The Viral Emergence Research Initiative Biology Integration Institute (VERENA BII) will integrate data and biological theory across the fields of microbiology, immunology, ecology, evolution, and global change biology, working towards a unified understanding that improves our ability to predict viral emergence.
The COVID-19 pandemic highlights a pressing need to understand the ecology and evolution of emerging viruses.
These global dynamics are determined first and foremost by the genetic code of both viruses and their hosts, and by microscopic interactions between the two at the level of proteins and cells.
However, biologists frequently struggle to connect theory across these scales.
At the heart of this research effort is an open clearinghouse of big data, creating new opportunities to apply artificial intelligence to real-world problems.
To foster a core set of data fluency and interdisciplinary research skills, the Lighthouse Learning Community will train participants at every career stage in the boundary-spanning science of the host-virus network, including more than 100 early career scientists.
Undergraduates will be introduced to both biology and data science through a course-based undergraduate research experience in “The Fundamentals of Disease Surveillance,” while graduate students and postdoctoral fellows will explore these methods deeper through a Biology Integration Workshop series, including a new Summer in the Capitol program in Washington, D.C.
This cohort of emerging scholars will use open source materials, K-12 outreach, and digital media to harness public interest in emerging diseases like COVID-19, raising awareness about key issues while sharing the importance of basic biological research to save lives and protect ecosystems.
To identify the mechanistic and molecular rules of life that govern host-virus dynamics at planetary scales, the VERENA BII will leverage a unique mix of data synthesis, computational innovation, field sampling, and laboratory experiments to identify the molecular underpinnings of host-virus interactions.
An unprecedented comparative study of the chiropteran within-host environment will generate and test hypotheses about the immunological adaptations that allow bats to tolerate deadly viruses.
In parallel, model-guided experiments will measure the features of the invertebrate immune system that play the greatest role in mosquitoes’ competence as arboviral vectors.
Together, these model systems will illuminate the hard-coded basis of host-virus compatibility, supporting new machine learning methods to predict ecological and evolutionary networks and anticipate global risks of viral emergence in a changing climate.
More broadly, the VERENA BII will expand an existing role as a hub of open data, software, and cyberinfrastructure for host-virus interactions, experimental virology, and wildlife disease surveillance.
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.
Subawards are not planned for this award.
The COVID-19 pandemic highlights a pressing need to understand the ecology and evolution of emerging viruses.
These global dynamics are determined first and foremost by the genetic code of both viruses and their hosts, and by microscopic interactions between the two at the level of proteins and cells.
However, biologists frequently struggle to connect theory across these scales.
At the heart of this research effort is an open clearinghouse of big data, creating new opportunities to apply artificial intelligence to real-world problems.
To foster a core set of data fluency and interdisciplinary research skills, the Lighthouse Learning Community will train participants at every career stage in the boundary-spanning science of the host-virus network, including more than 100 early career scientists.
Undergraduates will be introduced to both biology and data science through a course-based undergraduate research experience in “The Fundamentals of Disease Surveillance,” while graduate students and postdoctoral fellows will explore these methods deeper through a Biology Integration Workshop series, including a new Summer in the Capitol program in Washington, D.C.
This cohort of emerging scholars will use open source materials, K-12 outreach, and digital media to harness public interest in emerging diseases like COVID-19, raising awareness about key issues while sharing the importance of basic biological research to save lives and protect ecosystems.
To identify the mechanistic and molecular rules of life that govern host-virus dynamics at planetary scales, the VERENA BII will leverage a unique mix of data synthesis, computational innovation, field sampling, and laboratory experiments to identify the molecular underpinnings of host-virus interactions.
An unprecedented comparative study of the chiropteran within-host environment will generate and test hypotheses about the immunological adaptations that allow bats to tolerate deadly viruses.
In parallel, model-guided experiments will measure the features of the invertebrate immune system that play the greatest role in mosquitoes’ competence as arboviral vectors.
Together, these model systems will illuminate the hard-coded basis of host-virus compatibility, supporting new machine learning methods to predict ecological and evolutionary networks and anticipate global risks of viral emergence in a changing climate.
More broadly, the VERENA BII will expand an existing role as a hub of open data, software, and cyberinfrastructure for host-virus interactions, experimental virology, and wildlife disease surveillance.
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.
Subawards are not planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "BIOLOGY INTEGRATION INSTITUTES", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF21619
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
New Haven,
Connecticut
06511-3572
United States
Geographic Scope
Single Zip Code
Related Opportunity
Yale Univ was awarded
Global Host-Virus Network Prediction Initiative - VERENA BII
Cooperative Agreement 2515340
worth $4,772,318
from the Division of Biological Infrastructure in October 2024 with work to be completed primarily in New Haven Connecticut United States.
The grant
has a duration of 2 years 10 months and
was awarded through assistance program 47.074 Biological Sciences.
The Cooperative Agreement was awarded through grant opportunity Biology Integration Institutes.
Status
(Ongoing)
Last Modified 5/19/25
Period of Performance
10/1/24
Start Date
8/31/27
End Date
Funding Split
$4.8M
Federal Obligation
$0.0
Non-Federal Obligation
$4.8M
Total Obligated
Activity Timeline
Transaction History
Modifications to 2515340
Additional Detail
Award ID FAIN
2515340
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Private Institution Of Higher Education
Awarding Office
490808 DIV OF BIOLOGICAL INFRASTRUCTURE
Funding Office
490808 DIV OF BIOLOGICAL INFRASTRUCTURE
Awardee UEI
FL6GV84CKN57
Awardee CAGE
4B992
Performance District
CT-03
Senators
Richard Blumenthal
Christopher Murphy
Christopher Murphy
Modified: 5/19/25