This project will examine the risk of future coronavirus (CoV) emergence from wildlife using in-depth field investigations across the human-wildlife interface in China, molecular characterization of novel CoVs and host receptor binding domain genes, mathematical models of transmission and evolution, and in vitro and in vivo laboratory studies of host range. Zoonotic CoVs are a significant threat to global health, as demonstrated with the emergence of pandemic severe acute respiratory syndrome coronavirus (SARS-CoV) in China in 2002, and the recent and ongoing emergence of Middle East Respiratory Syndrome (MERS-CoV). Bats appear to be the natural reservoir of these viruses, and hundreds of novel bat-CoVs have been discovered in the last two decades. Bats, and other wildlife species, are hunted, traded, butchered and consumed across Asia, creating a large scale human-wildlife interface, and high risk of future emergence of novel CoVs. This project aims to understand what factors increase the risk of the next CoV emerging in people by studying CoV diversity in a critical zoonotic reservoir (bats), at sites of high risk for emergence (wildlife markets) in an emerging disease hotspot (China). The three specific aims of this project are to: 1. Assess CoV spillover potential at high risk human-wildlife interfaces in China. This will include quantifying he nature and frequency of contact people have with bats and other wildlife; serological and molecular screening of people working in wet markets and highly exposed to wildlife; screening wild-caught and market sampled bats from 30+ species for CoVs using molecular assays; and genomic characterization and isolation of novel CoVs. 2. Develop predictive models of bat CoV emergence risk and host range. A combined modeling approach will include phylogenetic analyses of host receptors and novel CoV genes (including functional receptor binding domains); a fused ecological and evolutionary model to predict host-range and viral sharing; and mathematical matrix models to examine evolutionary and transmission dynamics. 3. Test predictions of CoV inter-species transmission. Predictive models of host range (i.e. emergence potential) will be tested experimentally using reverse genetics, pseudovirus and receptor binding assays, and virus infection experiments across a range of cell cultures from different species and humanized mice.

Public Health Relevance

Most emerging human viruses come from wildlife, and these represent a significant threat to global public health and biosecurity - as demonstrated by the SARS coronavirus pandemic of 2002-03 and an ongoing SARS-like epidemic in the Middle East. This project seeks to understand what factors allow animal Coronaviruses to evolve and jump into the human population by studying virus diversity in a critical group of animals (bats), a sites of high risk for emergence (wildlife markets) in an emerging disease hotspot (China).

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI110964-03
Application #
9086286
Study Section
Clinical Research and Field Studies of Infectious Diseases Study Section (CRFS)
Program Officer
Stemmy, Erik J
Project Start
2014-06-01
Project End
2019-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
3
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Ecohealth Alliance, Inc.
Department
Type
DUNS #
077090066
City
New York
State
NY
Country
United States
Zip Code
10001
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Wang, Ning; Li, Shi-Yue; Yang, Xing-Lou et al. (2018) Serological Evidence of Bat SARS-Related Coronavirus Infection in Humans, China. Virol Sin 33:104-107
Eskew, Evan A; Olival, Kevin J (2018) De-urbanization and Zoonotic Disease Risk. Ecohealth 15:707-712
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Hu, Ben; Zeng, Lei-Ping; Yang, Xing-Lou et al. (2017) Discovery of a rich gene pool of bat SARS-related coronaviruses provides new insights into the origin of SARS coronavirus. PLoS Pathog 13:e1006698
Olival, Kevin J; Hosseini, Parviez R; Zambrana-Torrelio, Carlos et al. (2017) Host and viral traits predict zoonotic spillover from mammals. Nature 546:646-650
Olival, Kevin J; Willoughby, Anna R (2017) Prioritizing the 'Dormant' Flaviviruses. Ecohealth 14:1-2

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