Large variations in HIV-1 viral load explained by shifting-mosaic metapopulation dynamics
The viral population of HIV-1, like many pathogens that cause systemic infection, is structured and differentiated within the body. The dynamics of cellular immune trafficking through the blood and within compartments of the body has also received wide attention. Despite these advances, mathematical...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
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Public Library of Science
2016
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| _version_ | 1797100964212113408 |
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| author | Lythgoe, K Blanquart, F Pellis, L Fraser, C |
| author_facet | Lythgoe, K Blanquart, F Pellis, L Fraser, C |
| author_sort | Lythgoe, K |
| collection | OXFORD |
| description | The viral population of HIV-1, like many pathogens that cause systemic infection, is structured and differentiated within the body. The dynamics of cellular immune trafficking through the blood and within compartments of the body has also received wide attention. Despite these advances, mathematical models, which are widely used to interpret and predict viral and immune dynamics in infection, typically treat the infected host as a well-mixed homogeneous environment. Here, we present mathematical, analytical and computational results that demonstrate that consideration of the spatial structure of the viral population within the host radically alters predictions of previous models. We study the dynamics of virus replication and cytotoxic T lymphocytes (CTLs) within a metapopulation of spatially segregated patches, representing T cell areas connected by circulating blood and lymph. The dynamics of the system depend critically on the interaction between CTLs and infected cells at the within-patch level. We show that for a wide range of parameters, the system admits an unexpected outcome called the shifting-mosaic steady state. In this state, the whole body’s viral population is stable over time, but the equilibrium results from an underlying, highly dynamic process of local infection and clearance within T-cell centers. Notably, and in contrast to previous models, this new model can explain the large differences in set-point viral load observed between patients and their distribution, as well as the relatively low proportion of cells infected at any one time, and alters the predicted determinants of viral load variation. |
| first_indexed | 2024-03-07T05:45:13Z |
| format | Journal article |
| id | oxford-uuid:e7008e6c-ce56-41b2-a316-1914108b9be2 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:45:13Z |
| publishDate | 2016 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | oxford-uuid:e7008e6c-ce56-41b2-a316-1914108b9be22022-03-27T10:35:21ZLarge variations in HIV-1 viral load explained by shifting-mosaic metapopulation dynamicsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e7008e6c-ce56-41b2-a316-1914108b9be2EnglishSymplectic Elements at OxfordPublic Library of Science2016Lythgoe, KBlanquart, FPellis, LFraser, CThe viral population of HIV-1, like many pathogens that cause systemic infection, is structured and differentiated within the body. The dynamics of cellular immune trafficking through the blood and within compartments of the body has also received wide attention. Despite these advances, mathematical models, which are widely used to interpret and predict viral and immune dynamics in infection, typically treat the infected host as a well-mixed homogeneous environment. Here, we present mathematical, analytical and computational results that demonstrate that consideration of the spatial structure of the viral population within the host radically alters predictions of previous models. We study the dynamics of virus replication and cytotoxic T lymphocytes (CTLs) within a metapopulation of spatially segregated patches, representing T cell areas connected by circulating blood and lymph. The dynamics of the system depend critically on the interaction between CTLs and infected cells at the within-patch level. We show that for a wide range of parameters, the system admits an unexpected outcome called the shifting-mosaic steady state. In this state, the whole body’s viral population is stable over time, but the equilibrium results from an underlying, highly dynamic process of local infection and clearance within T-cell centers. Notably, and in contrast to previous models, this new model can explain the large differences in set-point viral load observed between patients and their distribution, as well as the relatively low proportion of cells infected at any one time, and alters the predicted determinants of viral load variation. |
| spellingShingle | Lythgoe, K Blanquart, F Pellis, L Fraser, C Large variations in HIV-1 viral load explained by shifting-mosaic metapopulation dynamics |
| title | Large variations in HIV-1 viral load explained by shifting-mosaic metapopulation dynamics |
| title_full | Large variations in HIV-1 viral load explained by shifting-mosaic metapopulation dynamics |
| title_fullStr | Large variations in HIV-1 viral load explained by shifting-mosaic metapopulation dynamics |
| title_full_unstemmed | Large variations in HIV-1 viral load explained by shifting-mosaic metapopulation dynamics |
| title_short | Large variations in HIV-1 viral load explained by shifting-mosaic metapopulation dynamics |
| title_sort | large variations in hiv 1 viral load explained by shifting mosaic metapopulation dynamics |
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