A transient heritable memory regulates HIV reactivation from latency

Yiyang Lu; Harpal Singh; Abhyudai Singh; Roy D Dar

doi:10.1016/j.isci.2021.102291

A transient heritable memory regulates HIV reactivation from latency

iScience. 2021 Mar 9;24(4):102291. doi: 10.1016/j.isci.2021.102291. eCollection 2021 Apr 23.

Authors

Yiyang Lu¹, Harpal Singh¹, Abhyudai Singh², Roy D Dar^{1

3

4}

Affiliations

¹ Department of Bioengineering, University of Illinois at Urbana-Champaign, 321 Everitt Laboratory, 1406 West Green Street, Urbana, IL 61801, USA.
² Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA.
³ Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, 1110 West Green Street, Urbana, IL 61801, USA.
⁴ Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, IL 61801, USA.

Abstract

Reactivation of human immunodeficiency virus 1 (HIV-1) from latently infected T cells is a critical barrier to cure patients. It remains unknown whether reactivation of individual latent cells occurs stochastically in response to latency reversal agents (LRAs) or is a deterministic outcome of an underlying cell state. To characterize these single-cell responses, we leverage the classical Luria-Delbrück fluctuation test where single cells are isolated from a clonal population and exposed to LRAs after colony expansion. Data show considerable colony-to-colony fluctuations with the fraction of reactivating cells following a skewed distribution. Modeling systematic measurements of fluctuations over time uncovers a transient heritable memory that regulates HIV-1 reactivation, where single cells are in an LRA-responsive state for a few weeks before switching back to an irresponsive state. These results have enormous implications for designing therapies to purge the latent reservoir and further utilize fluctuation-based assays to uncover hidden transient cellular states underlying phenotypic heterogeneity.

Keywords: Computational Molecular Modeling; Virology.

Abstract

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