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Insights on the mutational landscape of the SARS-CoV-2 Omicron variant

Nathaniel L. Miller, Thomas Clark, Rahul Raman, Ram Sasisekharan
doi: https://doi.org/10.1101/2021.12.06.471499
Nathaniel L. Miller
1Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
2Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
3Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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Thomas Clark
2Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
3Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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Rahul Raman
2Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
3Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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Ram Sasisekharan
2Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
3Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
4Singapore-MIT Alliance in Research and Technology (SMART), Singapore 138602, Singapore
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  • For correspondence: rams@mit.edu
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Abstract

The SARS-COV2 Omicron variant has sparked global concern due to the possibility of enhanced transmissibility and escape from vaccines and therapeutics. In this study, we describe the mutational landscape of the Omicron variant using amino acid interaction (AAI) networks. AAI network analysis is particularly well suited for interrogating the impact of constellations of mutations as occur on Omicron that may function in an epistatic manner. Our analyses suggest that as compared to previous variants of concern, the Omicron variant has increased antibody escape breadth due to mutations in class 3 and 4 antibody epitopes as well as increased escape depth due to accumulated mutations in class 1 antibody epitopes. We note certain RBD mutations that might further enhance Omicron’s escape, and in particular advise careful surveillance of two subclades bearing R346S/K mutations with relevance for certain therapeutic antibodies. Further, AAI network analysis suggests that the function of certain therapeutic monoclonal antibodies may be disrupted by Omicron mutations as a result of the cumulative indirect perturbations to the epitope surface properties, despite point-mutation analyses suggesting these antibodies are tolerant of the set of Omicron mutations in isolation. Finally, for several Omicron mutations that do not appear to contribute meaningfully to antibody escape, we find evidence for a plausible role in enhanced transmissibility via disruption of RBD-down conformational stability at the RBD-RBD interface.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 10, 2021.
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Insights on the mutational landscape of the SARS-CoV-2 Omicron variant
Nathaniel L. Miller, Thomas Clark, Rahul Raman, Ram Sasisekharan
bioRxiv 2021.12.06.471499; doi: https://doi.org/10.1101/2021.12.06.471499
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Insights on the mutational landscape of the SARS-CoV-2 Omicron variant
Nathaniel L. Miller, Thomas Clark, Rahul Raman, Ram Sasisekharan
bioRxiv 2021.12.06.471499; doi: https://doi.org/10.1101/2021.12.06.471499

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