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Mathematical Model of Viral Kinetics In Vitro Estimates the Number of E2-CD81 Complexes Necessary for Hepatitis C Virus Entry

Overview of attention for article published in PLoS Computational Biology, December 2011
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Title
Mathematical Model of Viral Kinetics In Vitro Estimates the Number of E2-CD81 Complexes Necessary for Hepatitis C Virus Entry
Published in
PLoS Computational Biology, December 2011
DOI 10.1371/journal.pcbi.1002307
Pubmed ID
Authors

Pranesh Padmanabhan, Narendra M. Dixit

Abstract

Interaction between the hepatitis C virus (HCV) envelope protein E2 and the host receptor CD81 is essential for HCV entry into target cells. The number of E2-CD81 complexes necessary for HCV entry has remained difficult to estimate experimentally. Using the recently developed cell culture systems that allow persistent HCV infection in vitro, the dependence of HCV entry and kinetics on CD81 expression has been measured. We reasoned that analysis of the latter experiments using a mathematical model of viral kinetics may yield estimates of the number of E2-CD81 complexes necessary for HCV entry. Here, we constructed a mathematical model of HCV viral kinetics in vitro, in which we accounted explicitly for the dependence of HCV entry on CD81 expression. Model predictions of viral kinetics are in quantitative agreement with experimental observations. Specifically, our model predicts triphasic viral kinetics in vitro, where the first phase is characterized by cell proliferation, the second by the infection of susceptible cells and the third by the growth of cells refractory to infection. By fitting model predictions to the above data, we were able to estimate the threshold number of E2-CD81 complexes necessary for HCV entry into human hepatoma-derived cells. We found that depending on the E2-CD81 binding affinity, between 1 and 13 E2-CD81 complexes are necessary for HCV entry. With this estimate, our model captured data from independent experiments that employed different HCV clones and cells with distinct CD81 expression levels, indicating that the estimate is robust. Our study thus quantifies the molecular requirements of HCV entry and suggests guidelines for intervention strategies that target the E2-CD81 interaction. Further, our model presents a framework for quantitative analyses of cell culture studies now extensively employed to investigate HCV infection.

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Mendeley readers

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Geographical breakdown

Country Count As %
Portugal 1 3%
Germany 1 3%
Netherlands 1 3%
China 1 3%
United States 1 3%
Unknown 25 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 30%
Researcher 7 23%
Student > Master 3 10%
Professor > Associate Professor 2 7%
Student > Doctoral Student 2 7%
Other 2 7%
Unknown 5 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 40%
Engineering 4 13%
Medicine and Dentistry 4 13%
Biochemistry, Genetics and Molecular Biology 3 10%
Philosophy 1 3%
Other 1 3%
Unknown 5 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 December 2011.
All research outputs
#17,236,404
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#7,471
of 8,960 outputs
Outputs of similar age
#171,621
of 246,969 outputs
Outputs of similar age from PLoS Computational Biology
#80
of 126 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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