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

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.Despite these observations, it remains unclear as to why subtype 1b infections may lead to more severe disease outcomes. This may be attributed to various reasons, including differences in viral phenotype, host-specific immune factors, demographics, transmission route (injectable drug use in the case of 1a

Inference of annealed protein fitness landscapes with AnnealDCA

“…In an undersampled regime, these correlations are expected to be weak and multiple rounds can be treated as independent samples. The approach shares similarities with various studies where a Potts model is inferred from a Multiple Sequence Alignment (MSA) of observed mutated viruses [44][45][46][47][48]. This inference is typically used to establish a prevalence landscape, often considered a surrogate for the intrinsic fitness landscape.…”