Assessing the emergence time of SARS-CoV-2 zoonotic spillover

PLoS One. 2024 Apr 4;19(4):e0301195. doi: 10.1371/journal.pone.0301195. eCollection 2024.

Abstract

Understanding the evolution of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) and its relationship to other coronaviruses in the wild is crucial for preventing future virus outbreaks. While the origin of the SARS-CoV-2 pandemic remains uncertain, mounting evidence suggests the direct involvement of the bat and pangolin coronaviruses in the evolution of the SARS-CoV-2 genome. To unravel the early days of a probable zoonotic spillover event, we analyzed genomic data from various coronavirus strains from both human and wild hosts. Bayesian phylogenetic analysis was performed using multiple datasets, using strict and relaxed clock evolutionary models to estimate the occurrence times of key speciation, gene transfer, and recombination events affecting the evolution of SARS-CoV-2 and its closest relatives. We found strong evidence supporting the presence of temporal structure in datasets containing SARS-CoV-2 variants, enabling us to estimate the time of SARS-CoV-2 zoonotic spillover between August and early October 2019. In contrast, datasets without SARS-CoV-2 variants provided mixed results in terms of temporal structure. However, they allowed us to establish that the presence of a statistically robust clade in the phylogenies of gene S and its receptor-binding (RBD) domain, including two bat (BANAL) and two Guangdong pangolin coronaviruses (CoVs), is due to the horizontal gene transfer of this gene from the bat CoV to the pangolin CoV that occurred in the middle of 2018. Importantly, this clade is closely located to SARS-CoV-2 in both phylogenies. This phylogenetic proximity had been explained by an RBD gene transfer from the Guangdong pangolin CoV to a very recent ancestor of SARS-CoV-2 in some earlier works in the field before the BANAL coronaviruses were discovered. Overall, our study provides valuable insights into the timeline and evolutionary dynamics of the SARS-CoV-2 pandemic.

MeSH terms

  • Animals
  • Bayes Theorem
  • COVID-19* / epidemiology
  • Chiroptera*
  • Humans
  • Pangolins / genetics
  • Phylogeny
  • SARS-CoV-2 / genetics
  • Zoonoses / epidemiology

Supplementary concepts

  • SARS-CoV-2 variants

Grants and funding

1. Vladimir Makarenkov grant number: 173878 Le Fonds Québécois de la Recherche sur la Nature et les Technologies URL: https://frq.gouv.qc.ca/ The funder played no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript 2. Vladimir Makarenkov grant number: 249644 Natural Sciences and Engineering Research Council of Canada URL: https://www.nserc-crsng.gc.ca/index_eng.asp The funder played no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.