Hybrid spreading mechanisms and T cell activation shape the dynamics of HIV-1 infection
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
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2015
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| _version_ | 1866913181196091392 |
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| author | Zhang, Changwang Zhou, Shi Groppelli, Elisabetta Pellegrino, Pierre Williams, Ian Borrow, Persephone Chain, Benjamin M. Jolly, Clare |
| author_facet | Zhang, Changwang Zhou, Shi Groppelli, Elisabetta Pellegrino, Pierre Williams, Ian Borrow, Persephone Chain, Benjamin M. Jolly, Clare |
| contents | HIV-1 can disseminate between susceptible cells by two mechanisms: cell-free infection following fluid-phase diffusion of virions and by highly-efficient direct cell-to-cell transmission at immune cell contacts. The contribution of this hybrid spreading mechanism, which is also a characteristic of some important computer worm outbreaks, to HIV-1 progression in vivo remains unknown. Here we present a new mathematical model that explicitly incorporates the ability of HIV-1 to use hybrid spreading mechanisms and evaluate the consequences for HIV-1 pathogenenesis. The model captures the major phases of the HIV-1 infection course of a cohort of treatment naive patients and also accurately predicts the results of the Short Pulse Anti-Retroviral Therapy at Seroconversion (SPARTAC) trial. Using this model we find that hybrid spreading is critical to seed and establish infection, and that cell-to-cell spread and increased CD4+ T cell activation are important for HIV-1 progression. Notably, the model predicts that cell-to-cell spread becomes increasingly effective as infection progresses and thus may present a considerable treatment barrier. Deriving predictions of various treatments' influence on HIV-1 progression highlights the importance of earlier intervention and suggests that treatments effectively targeting cell-to-cell HIV-1 spread can delay progression to AIDS. This study suggests that hybrid spreading is a fundamental feature of HIV infection, and provides the mathematical framework incorporating this feature with which to evaluate future therapeutic strategies. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_1503_08992 |
| institution | arXiv |
| publishDate | 2015 |
| record_format | arxiv |
| spellingShingle | Hybrid spreading mechanisms and T cell activation shape the dynamics of HIV-1 infection Zhang, Changwang Zhou, Shi Groppelli, Elisabetta Pellegrino, Pierre Williams, Ian Borrow, Persephone Chain, Benjamin M. Jolly, Clare Populations and Evolution Artificial Intelligence Computational Engineering, Finance, and Science Biological Physics Cell Behavior HIV-1 can disseminate between susceptible cells by two mechanisms: cell-free infection following fluid-phase diffusion of virions and by highly-efficient direct cell-to-cell transmission at immune cell contacts. The contribution of this hybrid spreading mechanism, which is also a characteristic of some important computer worm outbreaks, to HIV-1 progression in vivo remains unknown. Here we present a new mathematical model that explicitly incorporates the ability of HIV-1 to use hybrid spreading mechanisms and evaluate the consequences for HIV-1 pathogenenesis. The model captures the major phases of the HIV-1 infection course of a cohort of treatment naive patients and also accurately predicts the results of the Short Pulse Anti-Retroviral Therapy at Seroconversion (SPARTAC) trial. Using this model we find that hybrid spreading is critical to seed and establish infection, and that cell-to-cell spread and increased CD4+ T cell activation are important for HIV-1 progression. Notably, the model predicts that cell-to-cell spread becomes increasingly effective as infection progresses and thus may present a considerable treatment barrier. Deriving predictions of various treatments' influence on HIV-1 progression highlights the importance of earlier intervention and suggests that treatments effectively targeting cell-to-cell HIV-1 spread can delay progression to AIDS. This study suggests that hybrid spreading is a fundamental feature of HIV infection, and provides the mathematical framework incorporating this feature with which to evaluate future therapeutic strategies. |
| title | Hybrid spreading mechanisms and T cell activation shape the dynamics of HIV-1 infection |
| topic | Populations and Evolution Artificial Intelligence Computational Engineering, Finance, and Science Biological Physics Cell Behavior |
| url | https://arxiv.org/abs/1503.08992 |