Genetic Selection for Context-Dependent Stochastic Phenotypes: Sp1 and TATA Mutations Increase Phenotypic Noise in HIV-1 Gene Expression

Abstract

The sequence of a promoter within a genome does not uniquely determine gene expression levels and their variability; rather, promoter sequence can additionally interact with its location in the genome, or genomic context, to shape eukaryotic gene expression. Retroviruses, such as human immunodeficiency virus-1 (HIV), integrate their genomes into those of their host and thereby provide a biomedically-relevant model system to quantitatively explore the relationship between promoter sequence, genomic context, and noise-driven variability on viral gene expression. Using an in vitro model of the HIV Tat-mediated positive-feedback loop, we previously demonstrated that fluctuations in viral Tat-transactivating protein levels generate integration-site-dependent, stochastically-driven phenotypes, in which infected cells randomly ‘switch’ between high and low expressing states in a manner that may be related to viral latency. Here we extended this model and designed a forward genetic screen to systematically identify genetic elements in the HIV LTR promoter that modulate the fraction of genomic integrations that specify ‘Switching’ phenotypes. Our screen identified mutations in core promoter regions, including Sp1 and TATA transcription factor binding sites, which increased the Switching fraction several fold. By integrating single-cell experiments with computational modeling, we further investigated the mechanism of Switching-fraction enhancement for a selected Sp1 mutation. Our experimental observations demonstrated that the Sp1 mutation both impaired Tat-transactivated expression and also altered basal expression in the absence of Tat. Computational analysis demonstrated that the observed change in basal expression could contribute significantly to the observed increase in viral integrations that specify a Switching phenotype, provided that the selected mutation affected Tat-mediated noise amplification differentially across genomic contexts. Our study thus demonstrates a methodology to identify and characterize promoter elements that affect the distribution of stochastic phenotypes over genomic contexts, and advances our understanding of how promoter mutations may control the frequency of latent HIV infection.

NF-κB-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise

“…A small fraction of cells from each clonal population exhibited viral activation in the basal state (0.1 to 6% GFP+; Figure S1D), and these were excluded from the study. Spontaneous activation of GFP− cells in the absence of TNF occurs on a slow timescale of days to weeks (Miller-Jensen et al, 2013), and thus by focusing our analysis on initially GFP− cells, we could specifically investigate TNF-induced activation (Figure 1A). …”

“…J65c 4.4 and 6.6 were created as described in Figure S1; pMSCV-mCherry-RelA was packaged into an amphotropic retrovirus in HEK293Ts via Ca 3 (PO 4 ) 2 transfection. psLTR-Tat-GFP lentivirus was packaged, harvested, and titered as described previously (Miller-Jensen et al, 2013). …”

“…HIV LTR-driven gene expression is bursty, and bursting kinetics vary with integration site (Singh et al, 2010; Skupsky et al, 2010). Furthermore, HIV encodes its own positive transcriptional transactivator, Tat (Nabel and Baltimore, 1987), and there is evidence that Tat-mediated amplification of basal HIV transcriptional noise establishes phenotypic diversity in which some viruses replicate while others remain latent (Miller-Jensen et al, 2013; Weinberger et al, 2005). …”

Quantitative Evaluation and Optimization of Co-drugging to Improve Anti-HIV Latency Therapy

“…Therefore, the requirement for co-drugging to activate these latent proviruses will depend on the degree of chromatin repression observed across the entire polyclonal population. To test the degree of repression observed in a polyclonal latent population, we infected Jurkat cells with a full-length HIV virus containing stop codons in all viral proteins except Tat [36] at a low multiplicity of infection (MOI < 0.1). After 7 days, we treated the polyclonal population with TSA and phorbol myristate acetate (PMA) to activate all infections, and estimated a total infection level of approximately 7% (Fig.…”

“…This therapy design assumes that activation of latent viruses is in part stochastic [36,39,40], such that a different subset of the latent population will be purged by each treatment. A recent study demonstrated the validity of this assumption in HIV-infected patients undergoing ART therapy [41].…”