Natural populations of pathogens and their hosts are engaged in an arms race in which the pathogens diversify to escape host immunity while the hosts evolve novel immunity. This co-evolutionary process poses a fundamental challenge to the development of broadly effective vaccines and diagnostics against a diversifying pathogen. Based on surveys of natural allele frequencies and experimental immunization of mice, we show high antigenic specificities of natural variants of the outer surface protein C (OspC), a dominant antigen of a Lyme Disease-causing bacterium (Borrelia burgdorferi). To overcome the challenge of OspC antigenic diversity to clinical development of preventive measures, we implemented a number of evolution-informed strategies to broaden OspC antigenic reactivity. In particular, the centroid algorithm—a genetic algorithm to generate sequences that minimize amino-acid differences with natural variants—generated synthetic OspC analogs with the greatest promise as diagnostic and vaccine candidates against diverse Lyme pathogen strains co-existing in the Northeast United States. Mechanistically, we propose a model of maximum antigen diversification (MAD) mediated by amino-acid variations distributed across the hypervariable regions on the OspC molecule. Under the MAD hypothesis, evolutionary centroids display broad cross-reactivity by occupying the central void in the antigenic space excavated by diversifying natural variants. In contrast to vaccine designs based on concatenated epitopes, the evolutionary algorithms generate analogs of natural antigens and are automated. The novel centroid algorithm and the evolutionary antigen designs based on consensus and ancestral sequences have broad implications for combating diversifying pathogens driven by pathogen–host co-evolution.
12 Summary: Genome sequences constitute the primary evidence on the origin and spread 13 of the 2019-2020 Covid-19 pandemic. Rapid comparative analysis of coronavirus SARS-CoV-2 14 genomes is critical for disease control, outbreak forecasting, and developing clinical interven-15 tions. CoV Genome Tracker is a web portal dedicated to trace Covid-19 outbreaks in real time 16 using a haplotype network, an accurate and scalable representation of genomic changes in a 17 rapidly evolving population. We resolve the direction of mutations by using a bat-associated 18 genome as outgroup. At a broader evolutionary time scale, a companion browser provides gene-19 by-gene and codon-by-codon evolutionary rates to facilitate the search for molecular targets of 20 clinical interventions.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has accumulated genomic mutations at an approximately linear rate since it first infected human populations in late 2019. Controversies remain regarding the identity, proportion, and effects of adaptive mutations as SARS-CoV-2 evolves from a bat- to a human-adapted virus. The potential for vaccine-escape mutations poses additional challenges in pandemic control. Despite being of great interest to therapeutic and vaccine development, human-adaptive mutations in SARS-CoV-2 are masked by a genome-wide linkage disequilibrium under which neutral and even deleterious mutations can reach fixation by chance or through hitchhiking. Furthermore, genome-wide linkage equilibrium imposes clonal interference by which multiple adaptive mutations compete against one another. Informed by insights from microbial experimental evolution, we analyzed close to one million SARS-CoV-2 genomes sequenced during the first year of the COVID-19 pandemic and identified putative human-adaptive mutations according to the rates of synonymous and missense mutations, temporal linkage, and mutation recurrence. Furthermore, we developed a forward-evolution simulator with the realistic SARS-CoV-2 genome structure and base substitution probabilities able to predict viral genome diversity under neutral, background selection, and adaptive evolutionary models. We conclude that adaptive mutations have emerged early, rapidly, and constantly to dominate SARS-CoV-2 populations despite clonal interference and purifying selection. Our analysis underscores a need for genomic surveillance of mutation trajectories at the local level for early detection of adaptive and immune-escape variants. Putative human-adaptive mutations are over-represented in viral proteins interfering host immunity and binding host-cell receptors and thus may serve as priority targets for designing therapeutics and vaccines against human-adapted forms of SARS-CoV-2.
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