(151d) Using Mutual Information to Identify TAR-Tat Coevolution in HIV-1 and Its Implications for Viral Latency

After Human Immunodeficiency Virus (HIV-1) integrates into the host chromosome, the provirus displays two distinct gene expression states ? a transactivated state resulting in the formation of new viral particles or an inactive state resulting in the establishment of latency. The position of integration, the recruitment of activating and repressing factors by the viral promoter, and the viral protein Transactivator of Transcription (Tat) have been shown to be the most important factors in determining the gene expression state of the provirus. The few Tat molecules that are synthesized from weak viral gene expression shortly after integration bind to a stem-bulge-loop RNA structure called Transactivation Response Element (TAR) and recruit other cellular factors to promote the phosphorylation of RNA polymerase II and result in transcriptional activation, whereas the failure of these few Tat molecules to initiate the positive-feedback loop results in transcriptional silence and latency. The stochastic nature of this positive feedback loop thus gives rise to these two distinct gene expression modes with dynamics switching between them. Numerous studies that have examined the impact of the positive-feedback loop on viral gene expression and latency have primarily been limited to subtype B, the most prevalent subtype in the United States and Western Europe. In this paper, we have applied computational and experimental approaches to analyze the impact of TAR and Tat sequences from six different global isolates (A, A2, B, B/F, C and D) and the coevolution between different sites on viral gene expression and latency.

We constructed an open-loop system in which gene expression from the HIV-1 Long Terminal Repeat (LTR) with a particular TAR subtype was measured using Green Fluorescent protein (GFP) (called the LG vector(1)), and Tat was placed under the control of an ubiquitin promoter and its expression level quantified using the fluorescent protein mCherry (called the Ub-ChIT vector). Plots of gene expression vs. Tat concentration for certain TAR-Tat pairs were sigmoidal in nature, suggesting that large concentrations of these Tats are required to upregulate gene expression and that these Tats could potentially give rise to large populations of latent reservoirs. In contrast, some other pairs showed high levels of gene expression at even low concentrations of Tat. The impact of different TAR-Tat pairs on gene expression and latency was then studied in the context of the closed-loop system using the LTR-GFP-IRES-Tat (LGIT) lentiviral system(1). In agreement with the open-loop system, weaker TAR-Tat pairs had a significantly larger number of latent cells as compared to the stronger TAR-Tat pairs.

To understand the impact of sequence variation on expression dynamics and latency, we employed a statistical method called mutual information to identify positions that may be coevolving in TAR and Tat. An analysis of coevolving residues within Tat revealed that certain amino acids positions were strongly correlated. To test the in silico results, mutations introduced at these positions to give an evolutionarily non-conserved sequence resulted in a very weak Tat, with the majority of the provirus in an inactive gene expression state. Finally, a search for positions that are coevolving within TAR and Tat revealed that nucleotides in the bulge of TAR are coevolving with amino acids in the Arginine Rich Motif (ARM) of Tat.

Thus we have shown that TAR and Tat sequences from different subtypes display a wide array of gene expression levels, with certain TAR-Tat pairs having a very high propensity for latency. Furthermore, statistical analyses using mutual information has revealed that certain positions within TAR-Tat and in Tat alone are strongly correlated and coevolution within these positions are responsible for these unique gene expression phenotypes, yielding fundamental insights into mechanisms of viral evolution and behavior.

References:

(1) Weinberger, L. S., Burnett, J. C., Toettcher, J. E., Arkin, A. P. & Schaffer, D. V. (2005) Cell 122, 169-82.