Hepatitis C Virus Entry: Protein Interactions and Fusion Determinants Governing Productive Hepatocyte Invasion

Abstract

Hepatitis C virus (HCV) entry is among the best-studied uptake processes for human pathogenic viruses. Uptake follows a spatially and temporally tightly controlled program. Numerous host factors including proteins, lipids, and glycans promote productive uptake of HCV particles into human liver cells. The virus initially attaches to surface proteoglycans, lipid receptors such as the scavenger receptor BI (SR-BI), and to the tetraspanin CD81. After lateral translocation of virions to tight junctions, claudin-1 (CLDN1) and occludin (OCLN) are essential for entry. Clathrin-mediated endocytosis engulfs HCV particles, which fuse with endosomal membranes after pH drop. Uncoating of the viral RNA genome in the cytoplasm completes the entry process. Here we systematically review and classify HCV entry factors by their mechanistic role, relevance, and level of evidence. Finally, we report on more recent knowledge on determinants of membrane fusion and close with an outlook on future implications of HCV entry research.

Figure 1.

Model of time-dependent hepatitis C virus (HCV) cell-binding, uptake, and membrane fusion. Selected attachment factors, entry factors, and entry cofactors are shown. A comprehensive list of host factors implicated in HCV cell entry is presented in Table 1. GAG, Glycosaminoglycans; LDLR, low-density lipoprotein receptor; SR-BI, scavenger receptor BI; EGFR, epidermal growth factor receptor; CLDN1, claudin-1; OCLN, occludin.

Figure 2.

Interaction network of hepatitis C virus (HCV) attachment factors, entry factors, and entry cofactors. Reported STRING interactions (all levels of evidence, confidence of 0.4) are depicted and the interaction strength is indicated (yellow, orange, and red edges). Additional reported interactions not yet annotated in STRING (Zona et al. 2013; Gerold et al. 2015; Bruening et al. 2018) are shown (black dotted edges). Proteins are assigned to their highest scoring DAVID cluster as indicated. Analysis performed using DAVID with high-classification stringency settings (Huang et al. 2009), STRING (Szklarczyk et al. 2015), a published Matlab algorithm (Mercer et al. 2012), and illustrated in Cytoscape (Smoot et al. 2011).