Natural selection in the evolution of SARS-CoV-2 in bats created a generalist virus and highly capable human pathogen

MacLean, Oscar A; Lytras, Spyros; Weaver, Steven; Singer, Joshua B.; Boni, Maciej F.; Lemey, Philippe; Pond, Sergei L. Kosakovsky; Robertson, David L.

doi:10.1371/journal.pbio.3001115

Cited by 191 publications

(197 citation statements)

References 74 publications

(66 reference statements)

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“…Interestingly, RmYN02 lies far away from the SARS/SARS-CoV-2 cluster in the RBD, suggesting that this bat strain has undergone some further recombination event at Spike. This further recombination involving RmYN02 is in agreement with recent publications 39 .…”

Section: Discussionsupporting

confidence: 93%

“…Others, have suggested through dN/dS analyses that the lineage leading to SARS-CoV-2 and its closest strains (RaTG13, RmYN02, pangolin CoVs) would have undergone in mammals (e.g. bats) an adaptive process facilitating infection in humans 39 . However, no analyses were performed to trace and compare the evolution of the receptor binding affinity in ancestors that led to SARS-CoV-2.…”

Section: Discussionmentioning

confidence: 99%

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Recombination and lineage-specific mutations linked to the emergence of SARS-CoV-2

Patiño-Galindo

Filip

AlQuraishi

et al. 2020

Preprint

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The recent outbreak of a new coronavirus (SARS-CoV-2) in Wuhan, China, underscores the need for understanding the evolutionary processes that drive the emergence and adaptation of zoonotic viruses in humans. Here, we show that recombination in betacoronaviruses, including human-infecting viruses like SARS-CoV and MERS-CoV, frequently encompasses the Receptor Binding Domain (RBD) in the Spike gene. We find that this common process likely led to a recombination event at least 11 years ago in an ancestor of the SARS-CoV-2 involving the RBD. As a result of this recombination event, SARS-CoV and SARS-CoV-2 share a similar genotype in RBD, including two insertions (positions 432-436 and 460-472), and alleles 427N and 436Y. Both 427N and 436Y belong to a helix that interacts with the human ACE2 receptor. Ancestral state analyses revealed that SARS-CoV-2 differentiated from its most recent common ancestor with RaTG13 by accumulating a significant number of amino acid changes in the RBD. In sum, we propose a two-hit scenario in the emergence of the SARS-CoV-2 virus whereby the SARS-CoV-2 ancestors in bats first acquired genetic characteristics of SARS-CoV by incorporation of a SARS-like RBD through recombination before 2009, and subsequently, the lineage that led to SARS-CoV-2 accumulated further, unique changes specifically in the RBD.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Recombination and lineage-specific mutations linked to the emergence of SARS-CoV-2

Patiño-Galindo

Filip

AlQuraishi

et al. 2020

Preprint

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“…Although several mutations of SARS-CoV-2 are becoming fixed in the population, e.g. D614G in the spike protein [65], the virus has experienced only weak purifying selection [66] and sequences remain extremely similar over the course of the pandemic. As such, our approach cannot identify host adaptation "in real-time"; rather, we examine variation generated over much longer macroevolutionary histories.…”

Section: Model Predictions Of Human Coronavirusesmentioning

confidence: 99%

“…The methods used here are unable to identify intermediate hosts without sufficient sequence availability, and lack of such from pangolins (order Pholidota) preclude us from directly testing this hypothesis. However, selection analyses indicate SARS-CoV-2 could reasonably have exhibited efficient human infectivity and human-tohuman transmissibility following direct transmission from bats [66,73], i.e., without strict need for prolonged selection within an intermediate host.…”

Section: Model Predictions Of Human Coronavirusesmentioning

confidence: 99%

Predicting the animal hosts of coronaviruses from compositional biases of spike protein and whole genome sequences through machine learning

Brierley

Fowler

2021

PLoS Pathog

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The COVID-19 pandemic has demonstrated the serious potential for novel zoonotic coronaviruses to emerge and cause major outbreaks. The immediate animal origin of the causative virus, SARS-CoV-2, remains unknown, a notoriously challenging task for emerging disease investigations. Coevolution with hosts leads to specific evolutionary signatures within viral genomes that can inform likely animal origins. We obtained a set of 650 spike protein and 511 whole genome nucleotide sequences from 222 and 185 viruses belonging to the family Coronaviridae, respectively. We then trained random forest models independently on genome composition biases of spike protein and whole genome sequences, including dinucleotide and codon usage biases in order to predict animal host (of nine possible categories, including human). In hold-one-out cross-validation, predictive accuracy on unseen coronaviruses consistently reached ~73%, indicating evolutionary signal in spike proteins to be just as informative as whole genome sequences. However, different composition biases were informative in each case. Applying optimised random forest models to classify human sequences of MERS-CoV and SARS-CoV revealed evolutionary signatures consistent with their recognised intermediate hosts (camelids, carnivores), while human sequences of SARS-CoV-2 were predicted as having bat hosts (suborder Yinpterochiroptera), supporting bats as the suspected origins of the current pandemic. In addition to phylogeny, variation in genome composition can act as an informative approach to predict emerging virus traits as soon as sequences are available. More widely, this work demonstrates the potential in combining genetic resources with machine learning algorithms to address long-standing challenges in emerging infectious diseases.

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“…Given that the animal reservoir for SARS-CoV-2 is yet to be identified, others propose the virus be classified an "emerging infectious disease (EID) of probable animal origin" rather than a zoonosis (2). Many, but not all, early cases of COVID-19 were associated with a market in Wuhan that traded in wildlife (11), and plausible scenarios have been put forth to explain the origin of SARS-CoV-2: evolution in bats or an intermediate animal host before zoonotic spillover to humans in the market or market trade chain (12,13); or natural evolution in humans following direct zoonotic transfer from bats (12), though purifying selection of SARS-CoV-2 in humans since the start of the pandemic has been weak compared with the significant positive diversifying selection that has occurred in bats since SARS-CoV-2 evolved from its closest known relative RmYN02 (13). SARS-CoV-2 shares some genetic similarity with SARS-CoV, and prevailing evidence suggests that SARS-CoV spilled over into humans via an intermediate host-likely masked palm civets (Paguma larvata)-at a wildlife market in southern China in 2002 (14)(15)(16)(17).…”

Section: Introductionmentioning

confidence: 99%

Implications of Zoonoses From Hunting and Use of Wildlife in North American Arctic and Boreal Biomes: Pandemic Potential, Monitoring, and Mitigation

Keatts

Robards

Olson

et al. 2021

Front. Public Health

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The COVID-19 pandemic has re-focused attention on mechanisms that lead to zoonotic disease spillover and spread. Commercial wildlife trade, and associated markets, are recognized mechanisms for zoonotic disease emergence, resulting in a growing global conversation around reducing human disease risks from spillover associated with hunting, trade, and consumption of wild animals. These discussions are especially relevant to people who rely on harvesting wildlife to meet nutritional, and cultural needs, including those in Arctic and boreal regions. Global policies around wildlife use and trade can impact food sovereignty and security, especially of Indigenous Peoples. We reviewed known zoonotic pathogens and current risks of transmission from wildlife (including fish) to humans in North American Arctic and boreal biomes, and evaluated the epidemic and pandemic potential of these zoonoses. We discuss future concerns, and consider monitoring and mitigation measures in these changing socio-ecological systems. While multiple zoonotic pathogens circulate in these systems, risks to humans are mostly limited to individual illness or local community outbreaks. These regions are relatively remote, subject to very cold temperatures, have relatively low wildlife, domestic animal, and pathogen diversity, and in many cases low density, including of humans. Hence, favorable conditions for emergence of novel diseases or major amplification of a spillover event are currently not present. The greatest risk to northern communities from pathogens of pandemic potential is via introduction with humans visiting from other areas. However, Arctic and boreal ecosystems are undergoing rapid changes through climate warming, habitat encroachment, and development; all of which can change host and pathogen relationships, thereby affecting the probability of the emergence of new (and re-emergence of old) zoonoses. Indigenous leadership and engagement in disease monitoring, prevention and response, is vital from the outset, and would increase the success of such efforts, as well as ensure the protection of Indigenous rights as outlined in the United Nations Declaration on the Rights of Indigenous Peoples. Partnering with northern communities and including Indigenous Knowledge Systems would improve the timeliness, and likelihood, of detecting emerging zoonotic risks, and contextualize risk assessments to the unique human-wildlife relationships present in northern biomes.

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Natural selection in the evolution of SARS-CoV-2 in bats created a generalist virus and highly capable human pathogen

Cited by 191 publications

References 74 publications

Recombination and lineage-specific mutations linked to the emergence of SARS-CoV-2

Recombination and lineage-specific mutations linked to the emergence of SARS-CoV-2

Predicting the animal hosts of coronaviruses from compositional biases of spike protein and whole genome sequences through machine learning

Implications of Zoonoses From Hunting and Use of Wildlife in North American Arctic and Boreal Biomes: Pandemic Potential, Monitoring, and Mitigation

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