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Author Notes:

Zabrina L. Brumme, zbrumme@sfu.ca

KB, FO, RL, CB, EH, and ZB conceived the study and analyzed the data. KB, BJ, JJ, and EH developed methods and/or contributed the data. RL implemented the mathematical models. HS contributed to data visualization. FO and ZB drafted the initial manuscript with all authors contributing to further editing. All authors approved the submitted version.

We thank Daniel Reeves for helpful correspondence. Additionally, we thank the participants of the Zambia-Emory HIV Research Project, as the current study uses sequence data generated from individuals in the ZEHRP cohort.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a past collaboration with the authors ZB and CB.

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Research Funding:

This work was supported in part by the Canadian Institutes of Health Research (CIHR) through a project grant (PJT-159625 to ZB and JJ) and a focused team grant (HB1-164063 to ZB). This work was supported in part by the National Institutes of Health (NIH) under award numbers R21A127029 (to ZB), R01 AI064060 (to EH), and the Martin Delaney “BELIEVE” Collaboratory (NIH grant 1UM1AI26617 to ZB), which is supported by the following NIH Co-Funding and Participating Institutes and Centers: NIAID, NCI, NICHD, NHLBI, NIDA, NIMH, NIA, FIC, and OAR. FO was supported by a Ph.D. fellowship from the Sub-Saharan African Network for TB/HIV Research Excellence (SANTHE), a DELTAS Africa Initiative (grant # DEL-15-006). The DELTAS Africa Initiative was an independent funding scheme of the African Academy of Sciences (AAS)’s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust (grant # 107752/Z/15/Z) and the UK government. The views expressed in this publication were those of the authors and not necessarily those of AAS, NEPAD Agency, Wellcome Trust, or the UK government. BJ was supported by a CIHR Doctoral Award. EH was a Georgia Research Alliance Eminent Scholar. ZB was supported by a Scholar Award from the Michael Smith Foundation for Health Research.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Microbiology
  • HIV
  • persistence
  • reservoir
  • within-host phylogenetic analysis
  • proviral half-life
  • LATENT RESERVOIR
  • AFRICA

Proviral Turnover During Untreated HIV Infection Is Dynamic and Variable Between Hosts, Impacting Reservoir Composition on ART

Tools:

Journal Title:

FRONTIERS IN MICROBIOLOGY

Volume:

Volume 12

Publisher:

, Pages 719153-719153

Type of Work:

Article | Final Publisher PDF

Abstract:

Human immunodeficiency virus (HIV) can persist as an integrated provirus, in a transcriptionally repressed state, within infected cells. This small yet enduring pool of cellular reservoirs that harbor replication-competent HIV is the main barrier to cure. Entry of viral sequences into cellular reservoirs begins shortly after infection, and cells containing integrated proviral DNA are extremely stable once suppressive antiretroviral therapy (ART) is initiated. During untreated HIV infection however, reservoir turnover is likely to be more dynamic. Understanding these dynamics is important because the longevity of the persisting proviral pool during untreated infection dictates reservoir composition at ART initiation. If the persisting proviral pool turns over slowly pre-ART, then HIV sequences seeded into it during early infection would have a high likelihood of persisting for long periods. However, if pre-ART turnover was rapid, the persisting proviral pool would rapidly shift toward recently circulating HIV sequences. One-way to estimate this turnover rate is from the age distributions of proviruses sampled shortly after therapy initiation: this is because, at the time of sampling, the majority of proviral turnover would have already occurred prior to ART. Recently, methods to estimate a provirus’ age from its sequence have made this possible. Using data from 12 individuals with HIV subtype C for whom proviral ages had been determined phylogenetically, we estimated that the average proviral half-life during untreated infection was 0.78 (range 0.45–2.38) years, which is >15 times faster than that of proviral DNA during suppressive ART. We further show that proviral turnover during untreated infection correlates with both viral setpoint and rate of CD4+ T-cell decline during this period. Overall, our results support dynamic proviral turnover pre-ART in most individuals, which helps explain why many individuals’ reservoirs are skewed toward younger HIV sequences. Broadly, our findings are consistent with the notion that active viral replication creates an environment less favorable to proviral persistence, while viral suppression creates conditions more favorable to persistence, where ART stabilizes the proviral pool by dramatically slowing its rate of decay. Strategies to inhibit this stabilizing effect and/or to enhance reservoir turnover during ART could represent additional strategies to reduce the HIV reservoir.

Copyright information:

© 2021 Brooks, Omondi, Liang, Sudderuddin, Jones, Joy, Brumme, Hunter and Brumme.

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/rdf).
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