SARS-CoV-2 rapidly evolves lineage-specific phenotypic differences when passaged repeatedly in immune-naïve mice
Julian Daniel Sunday Willett, Annie Gravel, Isabelle Dubuc, Leslie Gudimard, Ana Claudia Dos Santos Pereira Andrade, Émile Lacasse, Paul Fortin, Ju-Ling Liu, Jose Avila Cervantes, Jose Hector Galvez, Haig Hugo Vrej Djambazian, Melissa Zwaig, Anne-Marie Roy, Sally Lee, Shu-Huang Chen, Jiannis Ragoussis, Louis Flamand
Communications Biology, doi:10.1038/s42003-024-05878-3
The persistence of SARS-CoV-2 despite the development of vaccines and a degree of herd immunity is partly due to viral evolution reducing vaccine and treatment efficacy. Serial infections of wild-type (WT) SARS-CoV-2 in Balb/c mice yield mouse-adapted strains with greater infectivity and mortality. We investigate if passaging unmodified B.1.351 (Beta) and B.1.617.2 (Delta) 20 times in K18-ACE2 mice, expressing the human ACE2 receptor, in a BSL-3 laboratory without selective pressures, drives human health-relevant evolution and if evolution is lineage-dependent. Late-passage virus causes more severe disease, at organism and lung tissue scales, with late-passage Delta demonstrating antibody resistance and interferon suppression. This resistance co-occurs with a de novo spike S371F mutation, linked with both traits. S371F, an Omicron-characteristic mutation, is co-inherited at times with spike E1182G per Nanopore sequencing, existing in different within-sample viral variants at others. Both S371F and E1182G are linked to mammalian GOLGA7 and ZDHHC5 interactions, which mediate viral-cell entry and antiviral response. This study demonstrates SARS-CoV-2's tendency to evolve with phenotypic consequences, its evolution varying by lineage, and suggests non-dominant quasi-species contribution. Part of the difficulty in responding to the COVID-19 pandemic has been predicting viral evolution and its impact on clinically relevant traits, such as disease severity, infectivity, and treatment resistance 1 . The basic biology of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, is well understood 2 . However, knowledge of SARS-CoV-2 evolution is limited. Many RNA viruses, like SARS-CoV-2, exist as quasispecies, meaning viral populations contain a multitude of mutants subjected to continuous selection, competition, and genetic variation [3] [4] [5] [6] [7] [8] [9] . These alleles give plasticity to the viral population allowing for rapid adaptation/selection to a variety of circumstances 10 . Viral evolution is also complex and affected by several factors, including host genetic background 11 , host immune status 12 , the organs targeted by the virus 13 , and a population's collective immunity 14 . As a result, it has been difficult to predict the emergence of new variants with altered virulence. Several SARS-CoV-2 variants of concern (VOC) have emerged, each with mutations providing dissemination advantages 1 . The SARS-CoV-2 Alpha variant (B.1.1.7) gained a growth advantage and rapidly spread globally due to the spike protein N501Y mutation that enhanced affinity for
Reporting summary Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
Data availability The numerical source data behind the graphs in the Figs. 2-8 can be found in Supplementary Data 1. VCF files used to complete computational analyses are available at https://zenodo.org/records/10460318. Raw data file for Illumina and Nanopore sequencing can be found on the NCBI BioProject using accessing codes PRJNA1068670 and PRJNA1069731, respectively. All numerical source data for graphs/charts are provided in the supplementary material section.
Author contributions J.D.S.W. conceived of the computational analyses needed for this study, completed all computational analysis of viral sequencing data, and wrote the majority of the manuscript. L.F. and J.R. conceived of the study. L.F. contributed to manuscript revisions, wrote sections relevant to animal models and antibody neutralization studies and performed analysis of results. J.R. supervised sequencing data generation and analysis.
Competing interests All authors declare no competing interests.
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