Coordinated evolution at amino acid sites of SARS-CoV-2 spike
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Neverov and colleagues analyze patterns of correlated changes of amino acids in the SARS-CoV-2 spike protein to identify networks of interacting positions using an improved version of the previously validated method. Identifying such patterns of co-evolution is important for a better understanding of spike-protein evolution. The evidence for the identified co-evolving pairs is solid, though the degree of certainty varies among the different identified groups of potentially interacting positions.
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Abstract
SARS-CoV-2 has adapted in a stepwise manner, with multiple beneficial mutations accumulating in a rapid succession at origins of VOCs, and the reasons for this are unclear. Here, we searched for coordinated evolution of amino acid sites in the spike protein of SARS-CoV-2. Specifically, we searched for concordantly evolving site pairs (CSPs) for which changes at one site were rapidly followed by changes at the other site in the same lineage. We detected 46 sites which formed 45 CSP. Sites in CSP were closer to each other in the protein structure than random pairs, indicating that concordant evolution has a functional basis. Notably, site pairs carrying lineage defining mutations of the four VOCs that circulated before May 2021 are enriched in CSPs. For the Alpha VOC, the enrichment is detected even if Alpha sequences are removed from analysis, indicating that VOC origin could have been facilitated by positive epistasis. Additionally, we detected nine discordantly evolving pairs of sites where mutations at one site unexpectedly rarely occurred on the background of a specific allele at another site, for example on the background of wild-type D at site 614 (four pairs) or derived Y at site 501 (three pairs). Our findings hint that positive epistasis between accumulating mutations could have delayed the assembly of advantageous combinations of mutations comprising at least some of the VOCs.
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eLife assessment
Neverov and colleagues analyze patterns of correlated changes of amino acids in the SARS-CoV-2 spike protein to identify networks of interacting positions using an improved version of the previously validated method. Identifying such patterns of co-evolution is important for a better understanding of spike-protein evolution. The evidence for the identified co-evolving pairs is solid, though the degree of certainty varies among the different identified groups of potentially interacting positions.
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Reviewer #1 (Public Review):
Neverov and colleagues present a large-scale computational investigation of epistatic interactions between substitutions in the spike protein. The analysis is based on an improved version of their previous approach that has been applied to other organisms to the Influenza A virus. They find several sets of interacting sites that tend to change in concert.
The approach is sensible and the work seems well executed. A systematic investigation of epistatic interactions is important to better understand the constraints and drivers of future SC2 evolution. This work is hence an important contribution to the field and a nice complement to experimental work by Jesse Bloom's group and others.
The authors uncover several groups of residues that seem to change in concert. The identified groups make sense, but further …
Reviewer #1 (Public Review):
Neverov and colleagues present a large-scale computational investigation of epistatic interactions between substitutions in the spike protein. The analysis is based on an improved version of their previous approach that has been applied to other organisms to the Influenza A virus. They find several sets of interacting sites that tend to change in concert.
The approach is sensible and the work seems well executed. A systematic investigation of epistatic interactions is important to better understand the constraints and drivers of future SC2 evolution. This work is hence an important contribution to the field and a nice complement to experimental work by Jesse Bloom's group and others.
The authors uncover several groups of residues that seem to change in concert. The identified groups make sense, but further validation and comparison with experimental or other computational approaches would strengthen the conclusions.
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Reviewer #2 (Public Review):
The authors use the phylogeny of SARS-CoV-2 to find signals of functional interactions among the evolving amino acids of the spike protein. They do this by looking for pairs of substitutions that either tend to appear consecutively on branches, indicating positive interactions, or to appear on separate branches, indicating negative interactions. Although a massive number of SARS-CoV-2 sequences have been collected, many of these sequences have errors in them or are similar to each other. This affects the accuracy of the reconstructed phylogeny and the placement of mutations on it, creating difficulties for this approach. Still, the authors are able to identify several sets of sites with clear signals of interaction, and where the interaction makes sense given the structure of the protein. Some of these sites …
Reviewer #2 (Public Review):
The authors use the phylogeny of SARS-CoV-2 to find signals of functional interactions among the evolving amino acids of the spike protein. They do this by looking for pairs of substitutions that either tend to appear consecutively on branches, indicating positive interactions, or to appear on separate branches, indicating negative interactions. Although a massive number of SARS-CoV-2 sequences have been collected, many of these sequences have errors in them or are similar to each other. This affects the accuracy of the reconstructed phylogeny and the placement of mutations on it, creating difficulties for this approach. Still, the authors are able to identify several sets of sites with clear signals of interaction, and where the interaction makes sense given the structure of the protein. Some of these sites are carried by the Omicron variant, indicating that positive epistasis likely played a role in its evolution.
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Reviewer #3 (Public Review):
Neverov et al. conduct an analysis of the SARS-CoV-2 phylogeny to identify pairs of sites in the rapidly evolving spike protein that fix concordant mutations more or less frequently than expected, reflective of epistasis between spike mutations. The authors modify an existing method to this end, making some updates to their algorithm that I find logically intuitive. I find this to be an interesting question that is important for understanding the molecular forces that influence future SARS-CoV-2 evolution. I find the study uncovers some valuable examples of epistasis, but have some key questions about the Methods that make it unclear to me how efficiently the method is performing.
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