Fitness effects of mutations to SARS-CoV-2 proteins

Abstract

Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino-acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.

Repeated Omicron exposures override ancestral SARS-CoV-2 immune imprinting

“…For codon constraint weights, mutations that cannot be accessed through single nucleotide mutation are first assigned a weight of zero. To address the intrinsic disparities in the frequency of distinct nucleotide substitutions in SARS-CoV-2, we assign different weights for mutations corresponding to various nucleotide substitutions 46 . Specifically, the weight of the most frequent substitution (C>T) is assigned a value of 0.1, while weights for G>T and G>A are 0.041 and 0.035, respectively.…”

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

“…Using the empirically estimated distribution of fitness effects from Ref. [46] (which are consistent with experimental measurements, see Refs. [85, 86, 87, 88]) and the clock rate of 31 substitutions per year (Nextstrain SARS-CoV-2 GISAID build on August 7, 2023), a generation time of 5.1 days [35], and a population size of 10 4 (order of magnitude of true population size), we estimate that the effective population size will be decreased by at most a factor of 2 at times far into the past, and less in more recent times (see Figure S34).…”

“…We simulated the lineage frequency dynamics using the empirically estimated distribution of deleterious fitness effects from Ref. [46] (Figure S19 and Methods) and found that the inferred effective population size is consistent with the true effective population size to within the error bars (Figure S20) and lower than the inferred effective population size in a simulation with only neutral mutations (Figure S21) by no more than a factor of 2 (Figure S22). Analytical estimates for the expected decrease in effective population size due to the empirical distribution of deleterious fitness effects also predict at most a factor of at most 2 decrease in effective population size that is not sufficient to explain the two orders of magnitude lower effective population size that we observe compared to the expectation (Supplementary Information).…”

“…The distribution of deleterious fitness effects from Ref. [46]. The orange vertical line indicates , which is the threshold in fitness above which selection dominates over genetic drift.…”

Contributions of hyperactive mutations in Mprofrom SARS-CoV-2 to drug resistance

“…Hyperactive mutations at L141 and N151 are present at low frequency (<0.1%) in sequenced isolates of SARS-CoV-2 (Figure S2). Of note, phylogenetic analyses of sequenced isolates suggest that mutations at positions 141 and 151 of M pro cause fitness defects 23 . We considered the possibility that hyperactive mutations are deleterious when drug is not present (as has been observed for L50F 16 ), but did not observe any meaningful differences in the frequency in sequenced isolates of mutations with WT-like from those with increased enzyme activity.…”