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

Abstract 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 exp...

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Autores principales:	Yusuke Ito, Azaria Remion, Alexandra Tauzin, Keisuke Ejima, Shinji Nakaoka, Yoh Iwasa, Shingo Iwami, Fabrizio Mammano
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1efbb90ef94d4c9da6477f95ff08d205
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spelling	oai:doaj.org-article:1efbb90ef94d4c9da6477f95ff08d2052021-12-02T11:40:23ZNumber of infection events per cell during HIV-1 cell-free infection10.1038/s41598-017-03954-92045-2322https://doaj.org/article/1efbb90ef94d4c9da6477f95ff08d2052017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-03954-9https://doaj.org/toc/2045-2322Abstract 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.Yusuke ItoAzaria RemionAlexandra TauzinKeisuke EjimaShinji NakaokaYoh IwasaShingo IwamiFabrizio MammanoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yusuke Ito Azaria Remion Alexandra Tauzin Keisuke Ejima Shinji Nakaoka Yoh Iwasa Shingo Iwami Fabrizio Mammano Number of infection events per cell during HIV-1 cell-free infection
description	Abstract 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.
format	article
author	Yusuke Ito Azaria Remion Alexandra Tauzin Keisuke Ejima Shinji Nakaoka Yoh Iwasa Shingo Iwami Fabrizio Mammano
author_facet	Yusuke Ito Azaria Remion Alexandra Tauzin Keisuke Ejima Shinji Nakaoka Yoh Iwasa Shingo Iwami Fabrizio Mammano
author_sort	Yusuke Ito
title	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_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_sort	number of infection events per cell during hiv-1 cell-free infection
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/1efbb90ef94d4c9da6477f95ff08d205
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Number of infection events per cell during HIV-1 cell-free infection

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