Inferring viral dynamics in chronically HCV infected patients from the spatial distribution of infected hepatocytes

Frederik Graw1, Ashwin Balagopal2, Abraham J Kandathil2

  • 1Los Alamos National Laboratory, Theoretical Biology and Biophysics, Los Alamos, New Mexico, United States of America; Center for Modeling and Simulation in the Biosciences, Heidelberg University, Heidelberg, Germany.

Plos Computational Biology
|November 14, 2014
PubMed

Insights

Hepatitis C virus (HCV) infection spreads locally in the liver, with infected cell clusters forming randomly. Our new method analyzes spatial data to understand HCV infection dynamics in patients.

Area of Science:

  • Hepatology
  • Virology
  • Computational Biology

Background:

  • Chronic hepatitis C virus (HCV) infection poses a significant public health challenge.
  • Understanding intrahepatic HCV infection dynamics, including viral spread and infected cell proportions, is crucial for developing effective treatments.

Purpose of the Study:

  • To develop and apply novel methods for analyzing the spatial distribution of HCV-infected hepatocytes in liver biopsies.
  • To investigate the dynamics of intrahepatic HCV infection and viral propagation modes.

Main Methods:

  • Utilizing single-cell laser capture microdissection from liver biopsy samples of chronically HCV-infected patients.
  • Analyzing the spatial distribution and internal structure of infected cell clusters.
  • Employing models of intracellular HCV RNA replication to estimate infection duration.

Main Results:

  • Identified clusters of infected hepatocytes ranging from 4 to 50 cells.
  • Observed a decline in HCV RNA content within clusters, suggesting local spread from a seeded source.
  • Estimated that cells within clusters were infected for less than a week on average.
  • Found no correlation between cluster size and estimated expansion time.

Conclusions:

  • HCV infection appears to be seeded randomly in the liver and spreads locally.
  • The developed method offers a novel approach to infer infection dynamics in solid tissues from static spatial data.
  • These findings provide insights into intrahepatic HCV infection dynamics, aiding therapeutic intervention development.

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