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Pandemics originating from non-human animals highlight the need to understand how natural hosts have evolved in response to emerging human pathogens and which groups may be susceptible to infection and/or potential reservoirs to mitigate public health and conservation concerns. Multiple zoonotic coronaviruses, such as severe acute respiratory syndrome-associated coronavirus (SARS-CoV), SARS-CoV-2 and Middle Eastern respiratory syndrome-associated coronavirus (MERS-CoV), are hypothesized to have evolved in bats. We investigate angiotensin-converting enzyme 2 (ACE2), the host protein bound by SARS-CoV and SARS-CoV-2, and dipeptidyl-peptidase 4 (DPP4 or CD26), the host protein bound by MERS-CoV, in the largest bat datasets to date. Both the ACE2 and DPP4 genes are under strong selection pressure in bats, more so than in other mammals, and in residues that contact viruses. Additionally, mammalian groups vary in their similarity to humans in residues that contact SARS-CoV, SARS-CoV-2 and MERS-CoV, and increased similarity to humans in binding residues is broadly predictive of susceptibility to SARS-CoV-2. This work augments our understanding of the relationship between coronaviruses and mammals, particularly bats, provides taxonomically diverse data for studies of how host proteins are bound by coronaviruses and can inform surveillance, conservation and public health efforts.
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Timing the SARS-CoV-2 index case in Hubei province
Understanding when SARS-CoV-2 emerged is critical to evaluating our current approach to monitoring novel zoonotic pathogens and understanding the failure of early containment and mitigation efforts for COVID-19. We employed a coalescent framework to combine retrospective molecular clock inference with forward epidemiological simulations to determine how long SARS-CoV-2 could have circulated prior to the time of the most recent common ancestor. Our results define the period between mid-October and mid-November 2019 as the plausible interval when the first case of SARS-CoV-2 emerged in Hubei province. By characterizing the likely dynamics of the virus before it was discovered, we show that over two-thirds of SARS-CoV-2-like zoonotic events would be self-limited, dying out without igniting a pandemic. Our findings highlight the shortcomings of zoonosis surveillance approaches for detecting highly contagious pathogens with moderate mortality rates.
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- Award ID(s):
- 2028040
- PAR ID:
- 10219867
- Date Published:
- Journal Name:
- Science
- ISSN:
- 0036-8075
- Page Range / eLocation ID:
- eabf8003
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1126/science.abf8003
