Intra-host IRES heterogeneity shapes hepatitis C virus translation through epistatic and population-level effects

Abstract

Hepatitis C virus (HCV) circulates within each patient as a diverse population of closely related genomes, yet RNA functional properties are commonly inferred from a single consensus or dominant genome. The contribution of non-coding intra-host variability, particularly within the internal ribosome entry site (IRES), to translational efficiency remains poorly defined. Here we investigated how naturally occurring HCV IRES variation influences viral RNA translation. Complete IRES sequences from chronically infected patients were analyzed using molecular cloning, bicistronic reporters, full-length replication-deficient viral RNAs and reconstructed intra-host populations. We found that natural IRES mutations displayed context-dependent effects, and combinations of mutations produced translational phenotypes that could not be predicted from the corresponding single mutations, consistent with intragenic epistasis. Moreover, several variants behaved differently in bicistronic reporters and full-length viral RNAs, demonstrating that both genomic and cellular context shape IRES function. Reconstructed genotype 1a populations largely reproduced the activity of their dominant haplotypes. In contrast, reconstructed genotype 3a populations translated substantially more efficiently than their corresponding dominant sequences, showing that low-frequency variants can collectively modulate translation at the population level. These findings demonstrate that the translational phenotype of HCV cannot always be inferred from the dominant sequence alone and identify epistasis, genomic context, and intra-host population composition as interacting determinants of viral RNA translation. Importance Hepatitis C virus (HCV) exists within each infected person as a diverse population of closely related viruses rather than as a single genetic sequence. This study shows that natural variation in a key RNA region controlling viral protein production can alter how efficiently the virus functions, and that these effects depend on combinations of mutations rather than on individual changes alone. By analyzing complete viral RNAs in addition to widely used reporter systems, we demonstrate that the full viral genome can substantially influence the activity of this regulatory region, providing a more realistic view of how translation occurs during natural infection. Our findings also reveal that rare viral variants can collectively shape the behavior of the viral population, challenging the common practice of relying on a single dominant sequence to represent an infection. These results provide new insight into how genetic diversity drives HCV evolution and adaptation.