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

  1. Juan Ángel Patiño-Galindo
  2. Ioan Filip
  3. Ratul Chowdhury
  4. Costas D. Maranas
  5. Peter K. Sorger
  6. Mohammed AlQuraishi
  7. Raul Rabadan

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Abstract

The emergence of SARS-CoV-2 underscores the need to better understand the evolutionary processes that drive the emergence and adaptation of zoonotic viruses in humans. In the betacoronavirus genus, which also includes SARS-CoV and MERS-CoV, recombination frequently encompasses the Receptor Binding Domain (RBD) of the Spike protein, which, in turn, is responsible for viral binding to host cell receptors. Here, we find evidence of a recombination event in the RBD involving ancestral linages to both SARS-CoV and SARS-CoV-2. Although we cannot specify the recombinant nor the parental strains, likely due to the ancestry of the event and potential undersampling, our statistical analyses in the space of phylogenetic trees support such an ancestral recombination. Consequently, SARS-CoV and SARS-CoV-2 share an RBD sequence that includes two insertions (positions 432-436 and 460-472), as well as the variants 427N and 436Y. Both 427N and 436Y belong to a helix that interacts directly with the human ACE2 (hACE2) receptor. Reconstruction of ancestral states, combined with protein-binding affinity analyses using the physics-based trRosetta algorithm, reveal that the recombination event involving ancestral strains of SARS-CoV and SARS-CoV-2 led to an increased affinity for hACE2 binding, and that alleles 427N and 436Y significantly enhanced affinity as well. Structural modeling indicates that ancestors of SARS-CoV-2 may have acquired the ability to infect humans decades ago. The binding affinity with the human receptor was subsequently boosted in SARS-CoV and SARS-CoV-2 through further mutations in RBD. In sum, we report an ancestral recombination event affecting the RBD of both SARS-CoV and SARS-CoV-2 that was associated with an increased binding affinity to hACE2.

Importance

This paper addresses critical questions about the origin of the SARS-CoV-2 virus: what are the evolutionary mechanisms that led to the emergence of the virus, and how can we leverage such knowledge to assess the potential of SARS-like viruses to become pandemic strains? In this work, we demonstrate common mechanisms involved in the emergence of human-infecting SARS-like viruses: first, by acquiring a common haplotype in the RBD through recombination, and further, through increased specificity to the human ACE2 receptor through lineage specific mutations. We also show that the ancestors of SARS-CoV-2 already had the potential to infect humans at least a decade ago, suggesting that SARS-like viruses currently circulating in wild animal species constitute a source of potential pandemic re-emergence.

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  1. Version published to 10.1101/2020.02.10.942748v3 on bioRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.02.10.942748: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Sample collection: Phylogenetic analysis: The evolutionary relationships between SARS-CoV-2 and other SARS/SARS-like CoVs was inferred from genome alignment using PhyML (GTR + GAMMA 4CAT)31.
    PhyML
    suggested: (PhyML, RRID:SCR_014629)
    GAMMA
    suggested: (GAMMA, RRID:SCR_009484)
    Dated phylogeny of the RBD was obtained with BEAST v1.8.4 (Supplementary Table 8), after assessing the molecular clock signal of the selected sequences with TempEst32.
    BEAST
    suggested: (BEAST, RRID:SCR_010228)
    Convergence of the estimated parameters was confirmed with Tracer http://tree.bio.ed.ac.uk/software/tracer/.
    Tracer
    suggested: (Tracer, RRID:SCR_019121)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. ScreenIT

    SciScore for 10.1101/2020.02.10.942748: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Using the RPDv4 package12 to identify recombination breakpoints, we identified 103 recombination events (Figure 1a, Methods).
    RPDv4
    suggested: None

    Results from OddPub: Thank you for sharing your data.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, please follow this link.

  4. Version published to 10.1101/2020.02.10.942748v2 on bioRxiv
  5. Version published to 10.1101/2020.02.10.942748v1 on bioRxiv