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Events & Seminars

 
 
 

IEEE: Dr. Abhyudai SinghTalk on Consequences of Stochastic Gene Expression

 

 

IEEE Delhi Section organized “Dr. Abhyudai Singh Talk on Consequences of stochastic gene expression - a tale of two viruses” at IIT Delhi on 25th September 2014. Four students namely Surbhi Gupta (14103), Ruchika Khaitan (14084), Shubham Rathi (15101) and Sneha Gupta (16157) of CSE attended the lecture.

Dr. Abhyudai Singh, an Assistant Professor in the departments of Electrical and Computer Engineering, Biomedical Engineering, and Mathematical Sciences at the University of Delaware, Newark, Delaware, USA. Dr. Abhyudai Singh talked about the HIV promoter within the viral long terminal repeat (LTR) orchestrates many aspects of the viral life cycle, from the dynamics of viral gene expression and replication to the establishment of a latent state. In particular, after viral integration into the host genome, stochastic fluctuations in viral gene expression amplified by the Tat positive feedback loop can contribute to the formation of either a productive; trans activated state or an inactive state. In a significant fraction of cells harboring an integrated copy of the HIV-1 model provirus (LTR-GFP-IRES-Tat), this bimodal gene expression profile is dynamic, as cells spontaneously and continuously flip between active (Bright) and inactive (Off) expression modes. Furthermore, these switching dynamics may contribute to the establishment and maintenance of latency, because after viral integration long delays in gene expression can occur before viral transactivation. The HIV-1 promoter contains cis-acting Sp1 and NF-?B elements that regulate gene expression via the recruitment of both activating and repressing complexes. We hypothesized that interplay in the recruitment of such positive and negative factors could modulate the stability of the Bright and off modes and thereby alter the sensitivity of viral gene expression to stochastic fluctuations in the feedback loop

Dr. Abhyudai Singh said that using model lent virus variants with mutations introduced in the Sp1 and NF-?B elements, he employed flow cytometry, mRNA quantification, pharmacological perturbations, and chromatin immune precipitation to reveal significant functional differences in contributions of each site to viral gene regulation. Specifically, the Sp1 sites apparently stabilize both the Bright and the Off states, such that their mutation promotes noisy gene expression and reduction in the regulation of histone acetylation and deacetylation. Furthermore, the NF-?B sites exhibit distinct properties, with ?B site I serving a stronger activating role than ?B site II. Moreover, Sp1 site III plays a particularly important role in the recruitment of both p300 and RelA to the promoter. Finally, analysis of 362 clonal cell populations infected with the viral variants revealed that mutations in any of the Sp1 sites yield a 6-fold higher frequency of clonal bifurcation compared to that of the wild-type promoter. Thus, each Sp1 and NF-?B site differentially contributes to the regulation of viral gene expression, and Sp1 sites functionally “dampen” transcriptional noise and thereby modulate the frequency and maintenance of this model of viral latency. These results may have biomedical implications for the treatment of HIV latency.

At the end, Dr. Abhyudai Singh summarized that to evaluate the individual contributions of key transcription factor binding elements in gene expression dynamics, he employed model HIV viruses with mutations introduced into numerous promoter elements. Extensive analysis of gene expression dynamics and transcription factor recruitment to the viral promoter reveals that each site differentially contributes to viral gene expression and to the establishment of a low expression state that may contribute to viral latency. This systems-level approach elucidates the synergistic contributions of host and viral factors to the dynamics, magnitudes, and stochastic effects in viral gene expression, as well as provides insights into mechanisms that contribute to latency.

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