HIV modeling project

This project will explore mathematical modeling questions related to the theory of stochastic gene expression and its role in developing novel HIV treatment strategies. 

A portion of the workshop will focus on the latest topics related to HIV/AIDS and transcriptional latency. This is in keeping with the clinical findings that HIV/AIDS patients who are under anti-retroviral treatment (cART) still harbor the HIV in their infected cells.  These infected immune cells normally hide in various tissues including lymph nodes, gut, lung and brain, and are activated once the cART is removed (non-adherence).  Although these cells by definition are called “latent”, they still show leaky and aberrant levels of RNA transcription which contribute to pathogenesis in tissues such as brain.  Therefore, understanding the mechanism of latency and control of gene expression in immune cells is significant.  

Normal cellular gene expression occurs either as an episodic process, characterized by pulsatile bursts, or as a constitutive process, characterized by a Poisson-like accumulation of gene products. Transcriptional bursting dominates across the human genome, both in burst frequency and burst size which vary by chromosomal location. Along these lines phenotypic heterogeneity that arises from cell fate decisions driven by stochastic gene expression is also emerging as a persistence mechanism in diverse mammalian diseases.

We will utilize HIV gene expression as a model of gene expression and define signals that allow RNA polymerase II activity (closely spaced polymerases, termed convoys) using noise inducing signals.  Noise in gene expression often results from promoter transitions between on and off states that generate episodic ‘bursts’ of transcription.  In a ‘two-state’ model, RNA polymerase II stalls on the HIV Long Terminal Repeat (LTR) promoter but when the elongation stall is relieved, multiple polymerases can read through resulting in a burst of transcripts and highly variable expression levels.  We will therefore perform calculations of the noise strength equation and stochastic kinetic constants using HIV promoter basal activity as well as mathematical modeling of HIV’s super activator Tat protein for a positive-feedback circuitry that enables persistence and strongly controls latency.

We will use experimental data that created noise on HIV promoter in both T-cells and macrophages (both with very different transcriptional kinetics).  The noise inducers will include exosomes from normal cells, low level irradiation, and epigenetic activators on HIV promoter.  We will define how the RNA polymerase II activity is altered using various noise inducers and whether signals that block noise induction will suppress HIV promoter into a permanent state of dormancy and latency.