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Predicting the mutational drivers of future SARS-CoV-2 variants of concern

Maher, M. Cyrus
Bartha, Istvan
di Iulio, Julia
Ferri, Elena
Soriaga, Leah
Lempp, Florian A.
Hie, Brian L.
Bryson, Bryan
Berger, Bonnie
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Pre-print
Date
2021-06-22
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Biology
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https://doi.org/10.1101/2021.06.21.21259286
Abstract
SARS-CoV-2 evolution threatens vaccine- and natural infection-derived immunity, and the efficacy of therapeutic antibodies. Herein we sought to predict Spike amino acid changes that could contribute to future variants of concern. We tested the importance of features comprising epidemiology, evolution, immunology, and neural network-based protein sequence modeling. This resulted in identification of the primary biological drivers of SARS-CoV-2 intra-pandemic evolution. We found evidence that resistance to population-level host immunity has increasingly shaped SARS-CoV-2 evolution over time. We identified with high accuracy mutations that will spread, at up to four months in advance, across different phases of the pandemic. Behavior of the model was consistent with a plausible causal structure wherein epidemiological variables integrate the effects of diverse and shifting drivers of viral fitness. We applied our model to forecast mutations that will spread in the future, and characterize how these mutations affect the binding of therapeutic antibodies. These findings demonstrate that it is possible to forecast the driver mutations that could appear in emerging SARS-CoV-2 variants of concern. This modeling approach may be applied to any pathogen with genomic surveillance data, and so may address other rapidly evolving pathogens such as influenza, and unknown future pandemic viruses.
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M. Cyrus Maher, Istvan Bartha, Steven Weaver, Julia di Iulio, Elena Ferri, Leah Soriaga, Florian A. Lempp, Brian L. Hie, Bryan Bryson, Bonnie Berger, David L. Robertson, Gyorgy Snell, Davide Corti, Herbert W. Virgin, Sergei L. Kosakovsky Pond, Amalio Telenti. Predicting the mutational drivers of future SARS-CoV-2 variants of concern. medRxiv 2021.06.21.21259286; doi: https://doi.org/10.1101/2021.06.21.21259286
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