Quantification of Hepatitis C Virus Cell-to-Cell Spread Using a Stochastic Modeling Approach

Area of Science:

• Virology
• Infectious Diseases
• Mathematical Biology

Background:

• Viral cell-to-cell transmission is crucial for establishing and maintaining chronic infections.
• Hepatitis C virus (HCV) exhibits significant cell-to-cell spread, contributing to its high chronicity rate (up to 80%).
• Existing mathematical models for HCV often overlook cell-to-cell transmission dynamics.

Purpose of the Study:

• To investigate and quantify the dynamics of HCV cell-to-cell spread in vitro.
• To assess the impact of blocking individual host factors on HCV transmission efficiency.
• To develop and apply stochastic models for analyzing viral focus expansion.

Main Methods:

• HCV spread assays were conducted in vitro.
• Stochastic models were employed to describe and analyze HCV focus expansion kinetics.
• Blocking antibodies and small-molecule inhibitors targeting host cell entry factors were used to evaluate their effect on transmission.
• Immunohistochemical staining identified HCV-positive cells, and focus size was measured.

Main Results:

• HCV focus expansion is best described by mathematical models incorporating focus size-dependent growth.
• A hierarchy of host factor efficacy in blocking HCV cell-to-cell spread was estimated (e.g., CLDN1 > NPC1L1 > TfR1).
• The developed approach effectively quantifies cell-to-cell transmission and the impact of blocking specific host factors.

Conclusions:

• Mathematical modeling of focus expansion provides a robust method for quantifying viral cell-to-cell transmission.
• Understanding the differential impact of host factors is essential for designing effective antiviral strategies against HCV.
• This approach can be adapted to evaluate various factors influencing viral spread and antiviral efficacy.