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Number of infection events per cell during HIV-1 cell-free infection

HIV-1 accumulates changes in its genome through both recombination and mutation during the course of infection. For recombination to occur, a single cell must be infected by two HIV strains. These coinfection events were experimentally demonstrated to occur more frequently than would be expected for...

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Autores principales: Ito, Yusuke, Remion, Azaria, Tauzin, Alexandra, Ejima, Keisuke, Nakaoka, Shinji, Iwasa, Yoh, Iwami, Shingo, Mammano, Fabrizio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529392/
https://www.ncbi.nlm.nih.gov/pubmed/28747624
http://dx.doi.org/10.1038/s41598-017-03954-9
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author Ito, Yusuke
Remion, Azaria
Tauzin, Alexandra
Ejima, Keisuke
Nakaoka, Shinji
Iwasa, Yoh
Iwami, Shingo
Mammano, Fabrizio
author_facet Ito, Yusuke
Remion, Azaria
Tauzin, Alexandra
Ejima, Keisuke
Nakaoka, Shinji
Iwasa, Yoh
Iwami, Shingo
Mammano, Fabrizio
author_sort Ito, Yusuke
collection PubMed
description HIV-1 accumulates changes in its genome through both recombination and mutation during the course of infection. For recombination to occur, a single cell must be infected by two HIV strains. These coinfection events were experimentally demonstrated to occur more frequently than would be expected for independent infection events and do not follow a random distribution. Previous mathematical modeling approaches demonstrated that differences in target cell susceptibility can explain the non-randomness, both in the context of direct cell-to-cell transmission, and in the context of free virus transmission (Q. Dang et al., Proc. Natl. Acad. Sci. USA 101:632-7, 2004: K. M. Law et al., Cell reports 15:2711-83, 2016). Here, we build on these notions and provide a more detailed and extensive quantitative framework. We developed a novel mathematical model explicitly considering the heterogeneity of target cells and analysed datasets of cell-free HIV-1 single and double infection experiments in cell culture. Particularly, in contrast to the previous studies, we took into account the different susceptibility of the target cells as a continuous distribution. Interestingly, we showed that the number of infection events per cell during cell-free HIV-1 infection follows a negative-binomial distribution, and our model reproduces these datasets.
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spelling pubmed-55293922017-08-02 Number of infection events per cell during HIV-1 cell-free infection Ito, Yusuke Remion, Azaria Tauzin, Alexandra Ejima, Keisuke Nakaoka, Shinji Iwasa, Yoh Iwami, Shingo Mammano, Fabrizio Sci Rep Article HIV-1 accumulates changes in its genome through both recombination and mutation during the course of infection. For recombination to occur, a single cell must be infected by two HIV strains. These coinfection events were experimentally demonstrated to occur more frequently than would be expected for independent infection events and do not follow a random distribution. Previous mathematical modeling approaches demonstrated that differences in target cell susceptibility can explain the non-randomness, both in the context of direct cell-to-cell transmission, and in the context of free virus transmission (Q. Dang et al., Proc. Natl. Acad. Sci. USA 101:632-7, 2004: K. M. Law et al., Cell reports 15:2711-83, 2016). Here, we build on these notions and provide a more detailed and extensive quantitative framework. We developed a novel mathematical model explicitly considering the heterogeneity of target cells and analysed datasets of cell-free HIV-1 single and double infection experiments in cell culture. Particularly, in contrast to the previous studies, we took into account the different susceptibility of the target cells as a continuous distribution. Interestingly, we showed that the number of infection events per cell during cell-free HIV-1 infection follows a negative-binomial distribution, and our model reproduces these datasets. Nature Publishing Group UK 2017-07-26 /pmc/articles/PMC5529392/ /pubmed/28747624 http://dx.doi.org/10.1038/s41598-017-03954-9 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Ito, Yusuke
Remion, Azaria
Tauzin, Alexandra
Ejima, Keisuke
Nakaoka, Shinji
Iwasa, Yoh
Iwami, Shingo
Mammano, Fabrizio
Number of infection events per cell during HIV-1 cell-free infection
title Number of infection events per cell during HIV-1 cell-free infection
title_full Number of infection events per cell during HIV-1 cell-free infection
title_fullStr Number of infection events per cell during HIV-1 cell-free infection
title_full_unstemmed Number of infection events per cell during HIV-1 cell-free infection
title_short Number of infection events per cell during HIV-1 cell-free infection
title_sort number of infection events per cell during hiv-1 cell-free infection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529392/
https://www.ncbi.nlm.nih.gov/pubmed/28747624
http://dx.doi.org/10.1038/s41598-017-03954-9
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