Probabilistic control of HIV latency and transactivation by the Tat gene circuit
The reservoir of HIV latently infected cells is the major obstacle for eradication of HIV infection. The “shock-and-kill” strategy proposed earlier aims to reduce the reservoir by activating cells out of latency. While the intracellular HIV Tat gene circuit is known to play important roles in contro...
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creator | Cao, Youfang 曹又方 Lei, Xue 雷雪 Ribeiro, Ruy M. Perelson, Alan S. Liang, Jie 梁杰 |
description | The reservoir of HIV latently infected cells is the major obstacle for eradication of HIV infection. The “shock-and-kill” strategy proposed earlier aims to reduce the reservoir by activating cells out of latency. While the intracellular HIV Tat gene circuit is known to play important roles in controlling latency and its transactivation in HIV-infected cells, the detailed control mechanisms are not well understood. Here we study the mechanism of probabilistic control of the latent and the transactivated cell phenotypes of HIV-infected cells. We reconstructed the probability landscape, which is the probability distribution of the Tat gene circuit states, by directly computing the exact solution of the underlying chemical master equation. Results show that the Tat circuit exhibits a clear bimodal probability landscape (i.e., there are two distinct probability peaks, one associated with the latent cell phenotype and the other with the transactivated cell phenotype). We explore potential modifications to reactions in the Tat gene circuit for more effective transactivation of latent cells (i.e., the shock-and-kill strategy). Our results suggest that enhancing Tat acetylation can dramatically increase Tat and viral production, while increasing the Tat–transactivation response binding affinity can transactivate latent cells more rapidly than other manipulations. Our results further explored the “block and lock” strategy toward a functional cure for HIV. Overall, our study demonstrates a general approach toward discovery of effective therapeutic strategies and druggable targets by examining control mechanisms of cell phenotype switching via exactly computed probability landscapes of reaction networks. |
doi_str_mv | 10.1073/pnas.1811195115 |
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The “shock-and-kill” strategy proposed earlier aims to reduce the reservoir by activating cells out of latency. While the intracellular HIV Tat gene circuit is known to play important roles in controlling latency and its transactivation in HIV-infected cells, the detailed control mechanisms are not well understood. Here we study the mechanism of probabilistic control of the latent and the transactivated cell phenotypes of HIV-infected cells. We reconstructed the probability landscape, which is the probability distribution of the Tat gene circuit states, by directly computing the exact solution of the underlying chemical master equation. Results show that the Tat circuit exhibits a clear bimodal probability landscape (i.e., there are two distinct probability peaks, one associated with the latent cell phenotype and the other with the transactivated cell phenotype). We explore potential modifications to reactions in the Tat gene circuit for more effective transactivation of latent cells (i.e., the shock-and-kill strategy). Our results suggest that enhancing Tat acetylation can dramatically increase Tat and viral production, while increasing the Tat–transactivation response binding affinity can transactivate latent cells more rapidly than other manipulations. Our results further explored the “block and lock” strategy toward a functional cure for HIV. Overall, our study demonstrates a general approach toward discovery of effective therapeutic strategies and druggable targets by examining control mechanisms of cell phenotype switching via exactly computed probability landscapes of reaction networks.</description><identifier>ISSN: 0027-8424</identifier><identifier>EISSN: 1091-6490</identifier><identifier>DOI: 10.1073/pnas.1811195115</identifier><identifier>PMID: 30455316</identifier><language>eng</language><publisher>United States: National Academy of Sciences</publisher><subject>Acetylation ; Anti-HIV Agents - pharmacology ; Biological Sciences ; Cellular biology ; Circuits ; Gene Expression Regulation, Viral - physiology ; Gene regulation network ; Gene Regulatory Networks ; Genetics ; HIV ; HIV Infections - drug therapy ; HIV Infections - virology ; HIV-1 - genetics ; HIV-1 - physiology ; Human immunodeficiency virus ; Humans ; Latency ; Latency reversing ; Latent infection ; Organic chemistry ; Phenotypes ; Physical Sciences ; Probability ; Probability distribution ; Probability landscape ; Signal Transduction ; State (computer science) ; Statistical analysis ; Strategy ; Switching theory ; Tat circuit ; Tat gene ; tat Gene Products, Human Immunodeficiency Virus - genetics ; tat Gene Products, Human Immunodeficiency Virus - metabolism ; Tat protein ; Transcriptional Activation ; Virus Latency - physiology</subject><ispartof>Proceedings of the National Academy of Sciences - PNAS, 2018-12, Vol.115 (49), p.12453-12458</ispartof><rights>Volumes 1–89 and 106–115, copyright as a collective work only; author(s) retains copyright to individual articles</rights><rights>Copyright National Academy of Sciences Dec 4, 2018</rights><rights>2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c562t-78b82f1e17094d84091e0506b0c07769e0b3892bf869fdc545ff35b47b8de2cf3</citedby><cites>FETCH-LOGICAL-c562t-78b82f1e17094d84091e0506b0c07769e0b3892bf869fdc545ff35b47b8de2cf3</cites><orcidid>0000-0002-3988-8241 ; 0000-0002-2773-6427 ; 0000-0002-5880-0006 ; 0000000227736427 ; 0000000258800006 ; 0000000239888241</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26573682$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26573682$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,723,776,780,799,881,27901,27902,53766,53768,57992,58225</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30455316$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/biblio/1482776$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Cao, Youfang</creatorcontrib><creatorcontrib>曹又方</creatorcontrib><creatorcontrib>Lei, Xue</creatorcontrib><creatorcontrib>雷雪</creatorcontrib><creatorcontrib>Ribeiro, Ruy M.</creatorcontrib><creatorcontrib>Perelson, Alan S.</creatorcontrib><creatorcontrib>Liang, Jie</creatorcontrib><creatorcontrib>梁杰</creatorcontrib><title>Probabilistic control of HIV latency and transactivation by the Tat gene circuit</title><title>Proceedings of the National Academy of Sciences - PNAS</title><addtitle>Proc Natl Acad Sci U S A</addtitle><description>The reservoir of HIV latently infected cells is the major obstacle for eradication of HIV infection. The “shock-and-kill” strategy proposed earlier aims to reduce the reservoir by activating cells out of latency. While the intracellular HIV Tat gene circuit is known to play important roles in controlling latency and its transactivation in HIV-infected cells, the detailed control mechanisms are not well understood. Here we study the mechanism of probabilistic control of the latent and the transactivated cell phenotypes of HIV-infected cells. We reconstructed the probability landscape, which is the probability distribution of the Tat gene circuit states, by directly computing the exact solution of the underlying chemical master equation. Results show that the Tat circuit exhibits a clear bimodal probability landscape (i.e., there are two distinct probability peaks, one associated with the latent cell phenotype and the other with the transactivated cell phenotype). We explore potential modifications to reactions in the Tat gene circuit for more effective transactivation of latent cells (i.e., the shock-and-kill strategy). Our results suggest that enhancing Tat acetylation can dramatically increase Tat and viral production, while increasing the Tat–transactivation response binding affinity can transactivate latent cells more rapidly than other manipulations. Our results further explored the “block and lock” strategy toward a functional cure for HIV. 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The “shock-and-kill” strategy proposed earlier aims to reduce the reservoir by activating cells out of latency. While the intracellular HIV Tat gene circuit is known to play important roles in controlling latency and its transactivation in HIV-infected cells, the detailed control mechanisms are not well understood. Here we study the mechanism of probabilistic control of the latent and the transactivated cell phenotypes of HIV-infected cells. We reconstructed the probability landscape, which is the probability distribution of the Tat gene circuit states, by directly computing the exact solution of the underlying chemical master equation. Results show that the Tat circuit exhibits a clear bimodal probability landscape (i.e., there are two distinct probability peaks, one associated with the latent cell phenotype and the other with the transactivated cell phenotype). We explore potential modifications to reactions in the Tat gene circuit for more effective transactivation of latent cells (i.e., the shock-and-kill strategy). Our results suggest that enhancing Tat acetylation can dramatically increase Tat and viral production, while increasing the Tat–transactivation response binding affinity can transactivate latent cells more rapidly than other manipulations. Our results further explored the “block and lock” strategy toward a functional cure for HIV. 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subjects | Acetylation Anti-HIV Agents - pharmacology Biological Sciences Cellular biology Circuits Gene Expression Regulation, Viral - physiology Gene regulation network Gene Regulatory Networks Genetics HIV HIV Infections - drug therapy HIV Infections - virology HIV-1 - genetics HIV-1 - physiology Human immunodeficiency virus Humans Latency Latency reversing Latent infection Organic chemistry Phenotypes Physical Sciences Probability Probability distribution Probability landscape Signal Transduction State (computer science) Statistical analysis Strategy Switching theory Tat circuit Tat gene tat Gene Products, Human Immunodeficiency Virus - genetics tat Gene Products, Human Immunodeficiency Virus - metabolism Tat protein Transcriptional Activation Virus Latency - physiology |
title | Probabilistic control of HIV latency and transactivation by the Tat gene circuit |
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