Characterizing Transcriptional Dynamics of HIV-1 in T-cells and Macrophages Using a Three-State LTR Model

  • Tin Phan Arizona State University
  • Catherine DeMarino George Mason University
  • Fatah Kashanchi George Mason University
  • Yang Kuang Arizona State University
  • Daniel M. Anderson George Mason University
  • Maria Emelianenko George Mason University
Keywords: HIV-1 transcription, F07#13, Transcriptional inhibitor, Treatment combination, Transcriptional feedback loop, Mathematical modeling

Abstract

HIV-1 affects tens of millions of people worldwide. In this work, we extend a novel three-state model of HIV-1 transcription to study the differences in the transcription process of HIV-1 in T-cells and macrophages. In particular, we find that the activation of the HIV-1 promoter in macrophages appears to take place rapidly as the Tat protein approaches a critical threshold. In contrast, the same process occurs smoother in T-cells. By examining the self-feedback loop of Tat, we observe distinct characteristic differences of the transcriptional feedback loop between macrophages and T-cells. A systematic analysis shows the stability of the positive steady state in limiting cases, with the global stability in the general case remaining an open question. Moreover, our numerical simulations and analysis demonstrate that the transcription-inhibitor's effect can be enhanced by synchronizing with standard treatments, such as combination antiretroviral therapy, to reduce the total dosages and toxicity.

Published
2021-08-16
How to Cite
Phan, Tin, Catherine DeMarino, Fatah Kashanchi, Yang Kuang, Daniel Anderson, and Maria Emelianenko. 2021. “Characterizing Transcriptional Dynamics of HIV-1 in T-Cells and Macrophages Using a Three-State LTR Model”. Letters in Biomathematics 8 (1), 133–150. https://lettersinbiomath.journals.publicknowledgeproject.org/index.php/lib/article/view/445.
Section
Research