Liberator, P. A. | bioRxiv Science

bioRxiv2022

PfaSTer: A ML-powered serotype caller for Streptococcus pneumoniae genomes

Streptococcus pneumoniae (pneumococcus) is a leading cause of morbidity and mortality worldwide. Although multi-valent pneumococcal vaccines have curbed the incidence of disease, their introduction has resulted in shifted serotype distributions that must be monitored. Whole genome sequence (WGS) data provides a powerful surveillance tool for tracking isolate serotypes, which can be determined from nucleotide sequence of the capsular polysaccharide biosynthetic operon (cps). Although software exists to predict serotypes from WGS data, their use is constrained by the requirement of high-coverage Next Generation Sequencing (NGS) reads. This can present a challenge in so far as accessibility and data sharing. Here we present PfaSTer, a method to identify 65 prevalent serotypes from individual S. pneumoniae genome sequences rather than primary NGS data. PfaSTer combines dimensionality reduction from k-mer analysis with machine learning, allowing for rapid serotype prediction without the need for coverage-based assessments. We then demonstrate the robustness of this method, returning >97% concordance when compared to biochemical results and other in-silico serotypers. PfaSTer is open source and available at: https://github.com/pfizer-opensource/pfaster.

bioinformatics↗

bioRxiv2022

Genetic surveillance of SARS-CoV-2 Mpro reveals high sequence and structural conservation prior to the introduction of protease inhibitor Paxlovid

SARS-CoV-2 continues to represent a global health emergency as a highly transmissible, airborne virus. An important coronaviral drug target for treatment of COVID-19 is the conserved main protease (Mpro). Nirmatrelvir is a potent Mpro inhibitor and the antiviral component of Paxlovid. The significant viral sequencing effort during the ongoing COVID-19 pandemic represented a unique opportunity to assess potential nirmatrelvir escape mutations from emerging variants of SARS-CoV-2. To establish the baseline mutational landscape of Mpro prior to the introduction of Mpro inhibitors, Mpro sequences and its cleavage junction regions were retrieved from [~]4,892,000 high-quality SARS-CoV-2 genomes in GISAID. Any mutations identified from comparison to the reference sequence (Wuhan-hu-1) were cataloged and analyzed. Mutations at sites key to nirmatrelvir binding and protease functionality (e.g., dimerization sites) were still rare. Structural comparison of Mpro also showed conservation of key nirmatrelvir contact residues across the extended Coronaviridae family (alpha-, beta-, and gamma-coronaviruses). Additionally, we showed that over time the SARS-CoV-2 Mpro enzyme remained under purifying selection and was highly conserved relative to the spike protein. Now, with the EUA approval of Paxlovid and its expected widespread use across the globe, it is essential to continue large-scale genomic surveillance of SARS-CoV-2 Mpro evolution. This study establishes a robust analysis framework for monitoring emergent mutations in millions of virus isolates, with the goal of identifying potential resistance to present and future SARS-CoV-2 antivirals. ImportanceThe recent authorization of oral SARS-CoV-2 antivirals, such as Paxlovid, has ushered in a new era of the COVID-19 pandemic. Emergence of new variants, as well as selective pressure imposed by antiviral drugs themselves, raise concern for potential escape mutations in key drug binding motifs. To determine the potential emergence of antiviral resistance in globally circulating isolates and its implications for the clinical response to the COVID-19 pandemic, sequencing of SARS-CoV-2 viral isolates before, during, and after the introduction of new antiviral treatments is critical. The infrastructure built herein for active genetic surveillance of Mpro evolution and emergent mutations will play an important role in assessing potential antiviral resistance as the pandemic progresses and Mpro inhibitors are introduced. We anticipate our framework to be the starting point in a larger effort for global monitoring of the SARS-CoV-2 Mpro mutational landscape.

genomics↗