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Pandemic-driven immune imprinting accelerates evolution of human coronavirus OC43
Shuiping Lu1, Qi Shen2, Huanru Wang3
1School of Public Health, Fudan University, Key Lab of Public Health Safety, Ministry of Education, Shanghai, China.
Global pandemic interventions accelerated human coronavirus OC43 (HCoV-OC43) evolution, particularly its spike gene. This accelerated evolution may be driven by immune imprinting, necessitating continued surveillance of endemic coronaviruses.
Area of Science:
- Virology
- Genomics
- Epidemiology
Background:
- Global pandemic interventions have significantly impacted host-virus dynamics.
- Endemic pathogens may experience altered evolutionary trajectories due to these shifts.
- Human coronavirus OC43 (HCoV-OC43), a betacoronavirus related to pandemic strains, is under investigation.
Purpose of the Study:
- To investigate the genomic evolution of HCoV-OC43 in light of recent epidemiological changes.
- To determine if HCoV-OC43 exhibits accelerated evolution post-2020.
- To explore the potential drivers of observed evolutionary changes, including immune selection.
Main Methods:
- Bayesian analysis of longitudinal surveillance data.
- Calculation of nucleotide substitution rates in the HCoV-OC43 spike gene.
- Identification of positively selected mutations using evolutionary analysis.
- Structural modeling to assess antibody binding to conserved epitopes.
Main Results:
- A 3.76-fold increase in the HCoV-OC43 spike gene substitution rate was observed post-2020.
- Positively selected mutations predominantly occurred in the spike protein, with some affecting antigenic epitopes.
- Structural modeling indicated cross-binding of broadly neutralizing antibodies to conserved HCoV-OC43 epitopes, suggesting immune-driven selection.
Conclusions:
- Recent epidemiological shifts have led to accelerated genomic evolution in HCoV-OC43.
- Immune imprinting at the population level may be a significant driver of mutations in key HCoV-OC43 spike protein domains.
- Sustained co-surveillance of HCoV-OC43 and other coronaviruses is crucial for predicting emergent variants with potentially altered pathogenicity.
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