TY - JOUR
T1 - Characterizing Transcriptional Dynamics of HIV-1 in T-cells and Macrophages Using a Three-State LTR Model
AU - Phan, Tin
AU - Demarino, Catherine
AU - Kashanchi, Fatah
AU - Kuang, Yang
AU - Anderson, Daniel M.
AU - Emelianenko, Maria
N1 - Funding Information:
We would like to acknowledge the Intercollegiate Biomathematics Alliance for its funding to support this article.
Publisher Copyright:
© 2021, Intercollegiate Biomathematics Alliance. All rights reserved.
PY - 2021/2/17
Y1 - 2021/2/17
N2 - 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.
AB - 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.
KW - F07#13
KW - HIV-1 transcription
KW - mathematical modeling
KW - transcriptional feedback loop
KW - transcriptional inhibitor
KW - treatment combination
UR - http://www.scopus.com/inward/record.url?scp=85127716634&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85127716634&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:85127716634
SN - 2373-7867
VL - 8
SP - 133
EP - 150
JO - Letters in Biomathematics
JF - Letters in Biomathematics
IS - 1
ER -