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

Tin Phan, Catherine Demarino, Fatah Kashanchi, Yang Kuang, Daniel M. Anderson, Maria Emelianenko

Research output: Contribution to journalArticlepeer-review


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 ob-serve 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 stan-dard treatments, such as combination antiretroviral therapy, to reduce the total dosages and toxicity.

Original languageEnglish (US)
Pages (from-to)133-150
Number of pages18
JournalLetters in Biomathematics
Issue number1
StatePublished - Feb 17 2021


  • F07#13
  • HIV-1 transcription
  • mathematical modeling
  • transcriptional feedback loop
  • transcriptional inhibitor
  • treatment combination

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Applied Mathematics


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