In a recent study published on the preprint server medRxiv*, researchers presented a new framework for genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on case studies from New York (NY) , the United States (US) and the United Kingdom (UK).
Study: Rapid detection of threats in SARS-CoV-2. Image credit: SWKStock/Shutterstock
SARS-CoV-2 has shown significantly higher transmissibility due to the continuous evolution of the SARS-CoV-2 spike (S) protein that mediates the binding interactions between SARS-CoV-2 S and hACE2 (enzyme human angiotensin converter 2) and, therefore, the efficiency of host invasion by SARS-CoV-2. Mutations in SARS-CoV-2 S not only affect viral transmission, but also increase the chances of reinfections, raising concerns about the effectiveness of vaccines against coronavirus disease 2019 (COVID-19).
About the study
In the present study, researchers developed a SARS-CoV-2 genomic surveillance framework based on case studies from New York, the UK, and the US and data obtained from the Global Initiative to Share All Data from influenza (GISAID).
The framework was based on sites of genomic coevolution as building blocks rather than genomic sequences and considered relationships between multiple sequence alignment (MSA) columns where each column represented a genetic site or loci. MSA was considered to be irreducible and display a motif complex representative of coevolutionary relationships between different genomic loci, such that if multiple loci were linked, concomitant mutations would occur at all loci; however, the binding would be preserved.
The linkage between the motif-based variant of Omicron (M) (OmicronM) with BA.1M mutations and the phylogeny-based variant Omicron (P) (OmicronP) with BA.1P mutations in SARS-CoV-2 S was assessed when the frame was activated. an alert (the initial week of December 2021). In addition, site links to DeltaM, BA.2M, BA.4M, and BA.5M were evaluated when corresponding reason-based alerts were evaluated.
Complex differentials of motifs (D) were analyzed to improve the understanding of the relational structures of MSA evolution. Alerts were only issued in case of sufficiently large D values and the presence of critical clusters (persistent clusters with entropy increases >0.35), and a variant was considered a key variant if the variant constituted >50% of the population in a given place. .
The surveillance framework was applied prospectively and retrospectively. The retrospective analysis was based on SARS-CoV-2 sequence data obtained from the UK (during the emergence of the Delta and Alpha variants) and the USA (during the emergence of the Omicron and Omicron BA.2 variants ). For the analysis, the prevalence of SARS-CoV-2 was known and threats could be mapped.
For the prospective analysis, data from New York on the occurrence of Omicron BA.2.12/Omicron BA.2.12.1 and Omicron BA.4/BA.5 were analyzed and not all threats could be mapped SARS-CoV-2 and therefore considered unknown. Surveillance was validated by testing SARS-CoV-2 populations at various temporal and spatial scales: city, state, country, and three-day, weekly, and monthly.
results
The framework issued alerts based on GISAID data and reasons on 16 May 2022 related to a cluster of coevolving sites consisting of several genomic sites (n = 7) that were mapped to Omicron BA.5, of which, one site encoded the D3N mutation in the SARS-CoV-2 (M) membrane protein, three sites encoded the ORF6:D61L mutation, and three sites encoded A27259C, C27889T, and C26858T mutations.
When newly visualized and projected as sequences, the cluster separated into two mutually exclusive blocks (nuc:C27889T, m:D3N) comprising coevolving regions linked to inverse amino acid substitutions such as ORF6:D61L ,nuc:A27259C, nuc:C26858T. The framework issued timely alerts based on the emergence and disappearance of SARS-CoV-2 variants with accuracies of 99%, 89%, and 100% for the New York, UK, and US case studies, respectively , and >85% overall accuracy.
In the case studies, the team observed that coevolutionary sites contained in critical clusters almost always had reverse mutations or exclusive mutations. OmicronM represented a unique critical group of 55 coevolving loci harboring OmicronP mutations (n = 30), BA.1P mutations (n = 13), and DeltaP reverse mutations (n = 13). The cluster was expanded the following week to contain 68 co-evolving loci comprising all loci harboring BA.1P mutations.
SARS-CoV-2 variants that triggered alerts showed linked and reverse mutations in their underlying critical groups, except for BA.2.12. Furthermore, BA.5 did not differ from BA.4 in SARS-CoV-2 S mutations, although BA.5 exhibited a critical cluster independent of any SARS-CoV-2 S mutation and involved a SARS-CoV- 2 M different. . Alerts issued by the surveillance system were specific but consistent across multiple geographic regions and robust to multiple parameter choices.
Overall, the study’s findings highlighted the accuracy of the new framework for SARS-CoV-2 surveillance in issuing real-time, reason-based alerts on the emergence and disappearance of variants key to SARS-CoV-2. Critical groups that trigger alerts could detect variant mutations, and the variants were characterized by linking mutations that deviate from the wild-type (WT) SARS-CoV-2 strain and reverse mutations.
*Important news
medRxiv publishes preliminary scientific reports that are not peer-reviewed and therefore should not be considered conclusive, guide clinical practice/health-related behavior, or be treated as established information.