Seasonal effects decouple SARS-CoV-2 haplotypes worldwide

Abstract

Background: Variants of concern (VOCs) have been replacing each other during the still rampant COVID-19 pandemic. As a result, SARS-CoV-2 populations have evolved increasingly intricate constellations of mutations that often enhance transmissibility, disease severity, and other epidemiological characteristics. The origin and evolution of these constellations remain puzzling. Methods: Here we study the evolution of VOCs at the proteome level by analyzing about 12 million genomic sequences retrieved from GISAID on July 23, 2022. A total 183,276 mutations were identified and filtered with a relevancy heuristic. The prevalence of haplotypes and free-standing mutations was then tracked monthly in various latitude corridors of the world. Results: A chronology of 22 haplotypes defined three phases driven by protein flexibility-rigidity, environmental sensing, and immune escape. A network of haplotypes illustrated the recruitment and coalescence of mutations into major VOC constellations and seasonal effects of decoupling and loss. Protein interaction networks mediated by haplotypes predicted communications impacting the structure and function of proteins, showing the increasingly central role of molecular interactions involving the spike (S), nucleocapsid (N), and membrane (M) proteins. Haplotype markers either affected fusogenic regions while spreading along the sequence of the S-protein or clustered around binding domains. Modeling of protein structure with AlphaFold2 showed that VOC Omicron and one of its haplotypes were major contributors to the distortion of the M-protein endodomain, which behaves as a receptor of other structural proteins during virion assembly. Remarkably, VOC constellations acted cooperatively to balance the more extreme effects of individual haplotypes. Conclusions: Our study uncovers seasonal patterns of emergence and diversification occurring amid a highly dynamic evolutionary landscape of bursts and waves. The mapping of genetically-linked mutations to structures that sense environmental change with powerful ab initio modeling tools demonstrates the potential of deep-learning for COVID-19 predictive intelligence and therapeutic intervention.

AlphaFold2 Reveals Structural Patterns of Seasonal Haplotype Diversification in SARS-CoV-2 Spike Protein Variants

“…The Wuhan reference fasta sequence (EPI_ISL_402124) was obtained from the online web service GISAID [ 28 ]. VOC and haplotype definitions were retrieved from the data curated by Tomaszewski et al [ 14 ]. Table S1 describes the order of progression of VOCs and haplotypes and their associated mutations.…”

“…Three VOCs, Alpha, Delta, and Omicron, were the most widespread across the globe, with later variants completely replacing earlier variants in a very dynamic evolutionary landscape of mutation accumulations [ 14 ]. Each of these variants brought about their own sets of mutations, with VOC Omicron being increasingly concerning as mutations tended to be inherited across variants.…”

“…This presents a problem of combinatorics. In this regard, the work of Tomaszewski et al [ 14 ] lays the foundation for modeling the most relevant sets of mutations associated with virus seasonal behavior making up VOC constellations in the form of haplotypes. Haplotypes are sets of mutations (genetic signatures) that tend to be linked (inherited) together in viral variants.…”

“…The available AlphaFold2 models used in the previously mentioned studies [ 19 ] only model the SARS-CoV-2 proteins with variant definitions (VOC constellations). However, this approach loses information on the patterns and trends of haplotype coalescence and decoupling that occurred during the course of the COVID-19 pandemic [ 14 ]. Haplotypes can originate independently but are later recruited into variants to become larger stable haplotypes in a process of coalescence.…”

“…Haplotypes can originate independently but are later recruited into variants to become larger stable haplotypes in a process of coalescence. However, they can also recruit prior haplotypes or develop sets of mutations that distinguish themselves by their global accumulation patterns, causing mutations to decouple from their originating variant [ 14 ]. Since the different haplotypes have mutations located in different regions of the S-protein, each haplotype will impact molecular structure differently.…”