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Posted: comet.paws on  Apr 11 04:57:38 PM
Title: Exploring regulation of HIV latency with single-cell systems biology  
Associate Professor of Biomedical Engineering and Molecular,, Cellular and Developmental Biology, Yale University
Sponsor: Carnegie Mellon University  >  Graduate Education Interdisciplinary Programs  >  Ph.D. Program in Computational Biology
University of Pittsburgh  >  School of Arts and Sciences  >  Biological Sciences
Carnegie Mellon University  >  School of Computer Science
Carnegie Mellon University  >  School of Computer Science  >  Computational Biology Department
University of Pittsburgh  >  School of Medicine  >  Computational and Systems Biology
Series: Joint CMU-Pitt Ph.D. Program in Computational Biology Seminar
Date: Apr 13, 2018 11:00 AM - 12:30 PM
Location: Bellefield Science Tower, BST3 6014

My lab integrates experimental and computational approaches to study signaling networks regulating phenotypic heterogeneity in the immune system. In this seminar, I will discuss our recent work on the clinical problem of HIV latency, which is driven in part by gene expression noise and cell-to-cell heterogeneity. By combining single-cell measurements and stochastic computational models, we found that the transcription factor NF-?B and chromatin together regulate transcriptional noise at the HIV promoter to control heterogeneity of viral activation. Our results suggest that latent-but-inducible HIV may exploit mechanisms regulating transcriptional noise that are also present at endogenous NF-?B-target promoters. We are also using mass cytometry to look more broadly at how signaling networks are perturbed in latent HIV-infected T cells. Using data-driven statistical analysis of the single-cell data, we identified changes in signaling pathways regulating apoptosis that are associated with latent infection and that can be targeted therapeutically to specifically promote death in HIV-infected T cells. Our results demonstrate how combining systems biology approaches with single-cell measurements can advance our mechanistic understanding of HIV latency and uncover novel clinical eradication strategies.

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