A Computational Model of Inhibition of HIV-1 by Interferon-Alpha
Type 1 interferons such as interferon-alpha (IFNα) inhibit replication of Human immunodeficiency virus (HIV-1) by upregulating the expression of genes that interfere with specific steps in the viral life cycle. This pathway thus represents a potential target for immune-based therapies that can alter...
| Main Authors: | , , |
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| Format: | Article |
| Language: | en_US |
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Public Library of Science
2016
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| Online Access: | http://hdl.handle.net/1721.1/103599 |
| _version_ | 1811093493629583360 |
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| author | Browne, Edward P. Letham, Benjamin Rudin, Cynthia |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Browne, Edward P. Letham, Benjamin Rudin, Cynthia |
| author_sort | Browne, Edward P. |
| collection | MIT |
| description | Type 1 interferons such as interferon-alpha (IFNα) inhibit replication of Human immunodeficiency virus (HIV-1) by upregulating the expression of genes that interfere with specific steps in the viral life cycle. This pathway thus represents a potential target for immune-based therapies that can alter the dynamics of host-virus interactions to benefit the host. To obtain a deeper mechanistic understanding of how IFNα impacts spreading HIV-1 infection, we modeled the interaction of HIV-1 with CD4 T cells and IFNα as a dynamical system. This model was then tested using experimental data from a cell culture model of spreading HIV-1 infection. We found that a model in which IFNα induces reversible cellular states that block both early and late stages of HIV-1 infection, combined with a saturating rate of conversion to these states, was able to successfully fit the experimental dataset. Sensitivity analysis showed that the potency of inhibition by IFNα was particularly dependent on specific network parameters and rate constants. This model will be useful for designing new therapies targeting the IFNα network in HIV-1-infected individuals, as well as potentially serving as a template for understanding the interaction of IFNα with other viruses. |
| first_indexed | 2024-09-23T15:45:44Z |
| format | Article |
| id | mit-1721.1/103599 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:45:44Z |
| publishDate | 2016 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/1035992022-09-29T15:59:52Z A Computational Model of Inhibition of HIV-1 by Interferon-Alpha Browne, Edward P. Letham, Benjamin Rudin, Cynthia Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Operations Research Center Sloan School of Management Koch Institute for Integrative Cancer Research at MIT Browne, Edward P. Letham, Benjamin Rudin, Cynthia Type 1 interferons such as interferon-alpha (IFNα) inhibit replication of Human immunodeficiency virus (HIV-1) by upregulating the expression of genes that interfere with specific steps in the viral life cycle. This pathway thus represents a potential target for immune-based therapies that can alter the dynamics of host-virus interactions to benefit the host. To obtain a deeper mechanistic understanding of how IFNα impacts spreading HIV-1 infection, we modeled the interaction of HIV-1 with CD4 T cells and IFNα as a dynamical system. This model was then tested using experimental data from a cell culture model of spreading HIV-1 infection. We found that a model in which IFNα induces reversible cellular states that block both early and late stages of HIV-1 infection, combined with a saturating rate of conversion to these states, was able to successfully fit the experimental dataset. Sensitivity analysis showed that the potency of inhibition by IFNα was particularly dependent on specific network parameters and rate constants. This model will be useful for designing new therapies targeting the IFNα network in HIV-1-infected individuals, as well as potentially serving as a template for understanding the interaction of IFNα with other viruses. United States. Army Research Office (W911NF-15- 1-0155) 2016-07-14T14:28:54Z 2016-07-14T14:28:54Z 2016-03 2015-10 Article http://purl.org/eprint/type/JournalArticle 1932-6203 http://hdl.handle.net/1721.1/103599 Browne, Edward P., Benjamin Letham, and Cynthia Rudin. “A Computational Model of Inhibition of HIV-1 by Interferon-Alpha.” Edited by Hans A Kestler. PLoS ONE 11, no. 3 (March 24, 2016): e0152316. en_US http://dx.doi.org/10.1371/journal.pone.0152316 PLOS ONE Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ application/pdf Public Library of Science Public Library of Science |
| spellingShingle | Browne, Edward P. Letham, Benjamin Rudin, Cynthia A Computational Model of Inhibition of HIV-1 by Interferon-Alpha |
| title | A Computational Model of Inhibition of HIV-1 by Interferon-Alpha |
| title_full | A Computational Model of Inhibition of HIV-1 by Interferon-Alpha |
| title_fullStr | A Computational Model of Inhibition of HIV-1 by Interferon-Alpha |
| title_full_unstemmed | A Computational Model of Inhibition of HIV-1 by Interferon-Alpha |
| title_short | A Computational Model of Inhibition of HIV-1 by Interferon-Alpha |
| title_sort | computational model of inhibition of hiv 1 by interferon alpha |
| url | http://hdl.handle.net/1721.1/103599 |
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