Abstract

Chronic liver infection by hepatitis C virus (HCV) is a major public health concern. Despite partly successful treatment options, several aspects of intrahepatic HCV infection dynamics are still poorly understood, including the preferred mode of viral propagation, as well as the proportion of infected hepatocytes. Answers to these questions have important implications for the development of therapeutic interventions. In this study, we present methods to analyze the spatial distribution of infected hepatocytes obtained by single cell laser capture microdissection from liver biopsy samples of patients chronically infected with HCV. By characterizing the internal structure of clusters of infected cells, we are able to evaluate hypotheses about intrahepatic infection dynamics. We found that individual clusters on biopsy samples range in size from infected cells. In addition, the HCV RNA content in a cluster declines from the cell that presumably founded the cluster to cells at the maximal cluster extension. These observations support the idea that HCV infection in the liver is seeded randomly (e.g. from the blood) and then spreads locally. Assuming that the amount of intracellular HCV RNA is a proxy for how long a cell has been infected, we estimate based on models of intracellular HCV RNA replication and accumulation that cells in clusters have been infected on average for less than a week. Further, we do not find a relationship between the cluster size and the estimated cluster expansion time. Our method represents a novel approach to make inferences about infection dynamics in solid tissues from static spatial data.

Highlights

  • Around 170 million people worldwide are chronically infected with hepatitis C virus (HCV), representing a major public health problem [1]

  • Around 170 million people worldwide are chronically infected with the hepatitis C virus (HCV)

  • How many hepatocytes are infected during chronic HCV infection? How does the virus propagate, and how do innate immune responses interfere with the spread of the virus? We developed mathematical and computational methods to study liver biopsy samples of patients chronically infected with HCV that were analyzed by single cell laser capture microdissection, to infer the spatial distribution of infected cells

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Summary

Introduction

Around 170 million people worldwide are chronically infected with hepatitis C virus (HCV), representing a major public health problem [1]. Despite successful treatment options using mostly type I interferon-a (IFN-a) or newer direct-acting antiviral agents, several aspects of HCV infection dynamics are still unknown. As appropriate animal models for HCV infection are lacking, inferring in vivo infection dynamics from clinical data has relied on mathematical models that describe the interaction of hepatocytes with viral particles [3,4,5,6,7,8]. Mathematical modeling of viral load dynamics in combination with data on treatment with IFN-a and direct-acting antivirals has helped to reveal and quantify aspects of the infection process, such as the half-life of viral particles and the loss rate of infected hepatocytes under treatment [3,6,9,10]. Models have quantified the necessary treatment efficacy to clear the virus [5,11]

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