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

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 infect...

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Main Authors: Frederik Graw, Ashwin Balagopal, Abraham J Kandathil, Stuart C Ray, David L Thomas, Ruy M Ribeiro, Alan S Perelson
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-11-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC4230741?pdf=render
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author Frederik Graw
Ashwin Balagopal
Abraham J Kandathil
Stuart C Ray
David L Thomas
Ruy M Ribeiro
Alan S Perelson
author_facet Frederik Graw
Ashwin Balagopal
Abraham J Kandathil
Stuart C Ray
David L Thomas
Ruy M Ribeiro
Alan S Perelson
author_sort Frederik Graw
collection DOAJ
description 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 4-50 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.
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spelling doaj.art-9b5a240c26ee4b03a405adfcbf4b93b02022-12-21T23:51:40ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582014-11-011011e100393410.1371/journal.pcbi.1003934Inferring viral dynamics in chronically HCV infected patients from the spatial distribution of infected hepatocytes.Frederik GrawAshwin BalagopalAbraham J KandathilStuart C RayDavid L ThomasRuy M RibeiroAlan S PerelsonChronic 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 4-50 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.http://europepmc.org/articles/PMC4230741?pdf=render
spellingShingle Frederik Graw
Ashwin Balagopal
Abraham J Kandathil
Stuart C Ray
David L Thomas
Ruy M Ribeiro
Alan S Perelson
Inferring viral dynamics in chronically HCV infected patients from the spatial distribution of infected hepatocytes.
PLoS Computational Biology
title Inferring viral dynamics in chronically HCV infected patients from the spatial distribution of infected hepatocytes.
title_full Inferring viral dynamics in chronically HCV infected patients from the spatial distribution of infected hepatocytes.
title_fullStr Inferring viral dynamics in chronically HCV infected patients from the spatial distribution of infected hepatocytes.
title_full_unstemmed Inferring viral dynamics in chronically HCV infected patients from the spatial distribution of infected hepatocytes.
title_short Inferring viral dynamics in chronically HCV infected patients from the spatial distribution of infected hepatocytes.
title_sort inferring viral dynamics in chronically hcv infected patients from the spatial distribution of infected hepatocytes
url http://europepmc.org/articles/PMC4230741?pdf=render
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