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 ORF6:D61L 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 (m:D3N,nuc:C27889T) linked to the five reverse mutations (nuc:C26858T,nuc:A27259C,ORF6:D61L). 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.
ABSTRACT
We present a novel framework facilitating the rapid detection of variants of interest (VOI) and concern (VOC) in a viral multiple sequence alignment (MSA). The framework is purely based on the genomic sequence data, without requiring prior established biological analysis. The frameworks building blocks are sets of co-evolving sites (motifs), identified via co-evolutionary signals within the MSA. Motifs form a weighted simplicial complex, whose vertices are sites that satisfy a certain nucleotide diversity. Higher dimensional simplices are constructed using distances quantifying the co-evolutionary coupling of pairs and in the context of our method maximal motifs manifest as clusters. The framework triggers an alert via a cluster with a significant fraction of newly emerging polymorphic sites. We apply our method to SARS-CoV-2, analyzing all alerts issued from November 2020 through August 2021 with weekly resolution for England, USA, India and South America. Within a week at most a handful of alerts, each of which involving on the order of 10 sites are triggered. Cross referencing alerts with a posteriori knowledge of VOI/VOC-designations and lineages, motif-induced alerts detect VOIs/VOCs rapidly, typically weeks earlier than current methods. We show how motifs provide insight into the organization of the characteristic mutations of a VOI/VOC, organizing them as co-evolving blocks. Finally we study the dependency of the motif reconstruction on metric and clustering method and provide the receiver operating characteristic (ROC) of our alert criterion.
