NSF Award
2032774
Bats appear to have co-evolved with coronaviruses (CoVs) for millennia. The CoVs that bats carry include the closest relatives of SARS-COV-2, the causative agent of COVID-19. The relationship between the bat host and CoV virus appears to have selected for immune tolerance that enables bats to control CoV replication and yet avoid immune damage. Although some novel CoV hosts (humans) are able to manage and clear the virus without significant consequence, many do not, falling victim instead to a pathological inflammatory response that results from overly-exuberant immune signaling. Understanding how bats avoid this deleterious path may provide insight into new disease mitigation strategies. The researchers supported by this award will leverage a large existing set of bat samples to better understand how bats respond to infection with CoVs. Beyond these direct COVID-19 societal benefits, this project will benefit society by training young scientists in disease ecology and in bioinformatics, preparing them for future careers in the transdisciplinary STEM workforce. Data from this study will be published in peer-reviewed journals, presented at scientific meetings, and shared through public data repositories.<br/><br/>The purpose of this study is to identify immune mechanisms associated with tolerance of Coronavirus (CoV) infections in bats. Gaining information on bat responses to CoV infections will shed light on the mechanisms of effective immune control. Parallel study of (1) the CoV virome, and (2) the accompanying gene up- or down-regulation in response to infection will reveal immune system signatures of viral tolerance and advance fundamental understandings of antiviral immunity. By comparing responses in the African little epauletted fruit bat (Epomophorus labiatus), which host beta-CoVs, and the North American little brown myotis (Myotis lucifugus), which host alpha-CoVs, the common mechanisms of tolerance to both alpha- and beta-CoVs will be determined. A powerful dual RNA sequencing approach will be deployed to simultaneously sequence the virome and the host transcriptome. Using weighted gene correlation network analysis, gene expression counts will be used to determine gene networks in the host that are most tightly correlated to each CoV infection. These correlated gene networks will be analyzed functionally to determine which immune pathways are associated with CoV tolerance by either blocking inflammation and immune activation or by dampening tissue damage. Finally, the functions of these co-regulated genes will be compared to those documented in novel hosts (human and other animals). This RAPID award is made by the Physiological and Structural Systems Cluster in the BIO Division of Integrative Organismal Systems, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.<br/><br/>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.
