SMDP: SARS-CoV-2 Mutation Distribution Profiler for rapid estimation of mutational histories of unusual lineages

TL;DR

SMDP is an open-source web tool that rapidly estimates the mutational history of SARS-CoV-2 lineages by comparing user-submitted mutations with known distributions, aiding public health decision-making.

Contribution

The paper introduces SMDP, a novel web application that quickly infers SARS-CoV-2 lineage histories using mutation distribution comparisons and mutation pattern analysis.

Findings

Accurately classifies mutation distributions for various SARS-CoV-2 lineages.

Detects signs of drug-induced mutagenesis such as molnupiravir exposure.

Provides rapid insights into lineage evolution and mutation rates.

Abstract

SARS-CoV-2 usually evolves at a relatively constant rate over time. Occasionally, however, lineages arise with higher-than-expected numbers of mutations given the date of sampling. Such lineages can arise for a variety of reasons, including selection pressures imposed by evolution during a chronic infection or exposure to mutation-inducing drugs like molnupiravir. We have developed an open-source web-based application (SMDP: SARS-CoV-2 Mutation Distribution Profiler; https://eringill.shinyapps.io/covid_mutation_distributions) that compares a list of user-submitted lineage-defining mutations or a FASTA file containing a single genome (from which lineage-defining mutations are calculated) with established mutation distributions including those observed during (1) the first nine months of the pandemic, (2) during the global transmission of Omicron, (3) during the chronic infection of immunocompromised patients, and (4) during zoonotic spillover from humans to deer. The application calculates the most likely distribution for the user's mutation list and displays log likelihoods for all distributions. In addition, the transition:transversion ratio of the user's list is calculated to determine whether there is evidence of exposure to a mutation-inducing drug such as molnupiravir and indicates whether the list contains mutations in the proofreading domain of nsp14 which could lead to a higher-than-expected mutation rate in the lineage. This tool will be useful for public health and researchers seeking to rapidly infer evolutionary histories of SARS-CoV-2 variants, which can aid risk assessment and public health responses.