Stochastic gene expression as a molecular switch for viral latency

Abstract

Stochastic 'noise' arises from random thermal fluctuations in the concentration of protein, RNA, or other molecules within the cell and is an unavoidable aspect of life at the single-cell level. Evidence is accumulating that this biochemical noise crucially influences cellular auto-regulatory circuits and can 'flip' genetic switches to drive probabilistic fate decisions in bacteria, viruses, cancer, and stem cells. Here, we review how stochastic gene expression in key auto-regulatory proteins can control fate determination between latency and productive replication in both phage-lambda and HIV-1. We highlight important new studies that synthetically manipulate auto-regulatory circuitry and noise, to bias HIV-1's ability to enter proviral latency. We argue that an appreciation of noise in gene expression may shed light on the mystery of animal virus latency and that strategies to manipulate noise may have impact on anti-viral therapeutics.

Figure 1. A minimal HIV Tat positive-feedback circuit is sufficient to generate a ‘latency’ decision in the presence of noise

(A) The HIV-1 ‘proviral’ genome with Tat positive feedback displayed and the HIV-1 developmental bifurcation between active replication and proviral latency after infection of a CD4+ T lymphocyte. (B) Jurkat T cells infected with either a control LTR-GFP or feedback LTR-GFP-IRES-Tat lentiviral vector, were single-cell sorted by FACS, grown into clonal populations and subsequently analyzed by flow cytometry. (C) Single-cell Tat trajectories of an HIV-1 gene-circuit model. Each trajectory represents the level of Tat within a single-cell over time. Significant fluctuations in Tat levels exist and can drive a phenotypic bifurcation between two states.

Figure 2. Weakening HIV-1 Tat positive feedback biases HIV-1 towards latency and limits reactivation

(A) Schematics of full-length HIV-1 with nef replaced by a gfp reporter (blue) and the SirT1 over expression effect (red). (B) SirT1 over expression deacetylase Tat and reduces positive-feedback strength (red) as evidenced from gene expression noise analysis. (C) SirT1 over-expressing cells have a higher probability of entering latency and show decreased latent reactivation [26].