Evolutionary modeling reveals enhanced mutational flexibility of HCV subtype 1b compared with 1a

Hang Zhang; Ahmed A Quadeer; Matthew R McKay

doi:10.1016/j.isci.2021.103569

Evolutionary modeling reveals enhanced mutational flexibility of HCV subtype 1b compared with 1a

iScience. 2021 Dec 8;25(1):103569. doi: 10.1016/j.isci.2021.103569. eCollection 2022 Jan 21.

Authors

Hang Zhang¹, Ahmed A Quadeer¹, Matthew R McKay^{1

2

3

4}

Affiliations

¹ Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, SAR, China.
² Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, SAR, China.
³ Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, VIC, Australia.
⁴ Department of Microbiology and Immunology, University of Melbourne, The Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia.

Abstract

Hepatitis C virus (HCV) is a leading cause of liver-associated disease and liver cancer. Of the major HCV subtypes, patients infected with subtype 1b have been associated with having a higher risk of developing chronic infection and hepatocellular carcinoma. However, underlying reasons for this increased disease severity remain unknown. Here, we provide an evolutionary rationale, based on a comparative study of fitness landscape and in-host evolutionary models of the E2 glycoprotein of HCV subtypes 1a and 1b. Our analysis demonstrates that a higher chronicity rate of 1b may be attributed to lower fitness constraints, enabling 1b viruses to more easily escape antibody responses. More generally, our results suggest that differences in evolutionary constraints between HCV subtypes may be an important factor in mediating distinct disease outcomes. Our analysis also identifies antibodies that appear escape-resistant against both subtypes 1a and 1b, providing directions for designing HCV vaccines having cross-subtype protection.

Keywords: Hepatology; In silico biology; Systems biology; Virology.