Rapid threat detection in SARS-CoV-2

ABSTRACT

This paper presents a novel virus surveillance framework, completely independent of phylogeny-based methods. The framework issues timely alerts with an accuracy exceeding 85% that are based on the co-evolutionary relations between sites of the viral multiple sequence array (MSA). This set of relations is formalized via a motif complex, whose dynamics contains key information about the emergence of viral threats without the referencing of strain prevalence. Our notion of threat is centered at the emergence of a certain type of critical cluster consisting of key co-evolving sites. We present three case studies, based on GISAID data from UK, US and New York, where we perform our surveillance. We alert on May 16, 2022, based on GISAID data from New York, to a critical cluster of co-evolving sites mapping to the Pango-designation, BA.5. The alert specifies a cluster of seven genomic sites, one of which exhibits D3N on the M (membrane) protein-the distinguishing mutation of BA.5, three encoding ORF6D61L and the remaining three exhibiting the synonymous mutations C26858T, C27889T and A27259C. New insight is obtained when projected onto sequences, this cluster splits into two, mutually exclusive blocks of co-evolving sites (mD3N,nucC27889T) linked to the five reverse mutations (nucC26858T,nucA27259C,ORF6D61L). We furthermore provide an in depth analysis of all major signaled threats, during which we discover a specific signature concerning linked reverse mutation in the critical cluster.