Engineering cellular transcriptional state with perturbations
Thomas Norman, PhD
Assistant Member
Computational & Systems Biology Program
Memorial Sloan Kettering Cancer Center
Abstract: Perturb-seq links CRISPR-mediated genetic perturbations to their effects on the transcriptome. Crucially, this readout is both quantitative and interpretable, meaning it is possible to reason about progress towards realizing a desired phenotype using computational modeling. As it scales, these features make Perturb-seq a promising tool for rationally engineering cellular transcriptional state. In this seminar, I will discuss our work towards achieving this goal, including our use of CRISPRa to recapitulate in vivo transcriptional states adopted by fibroblasts, such as those associated with disease, and our development of Multiome Perturb-seq, which enables the use of chromatin changes to predict effective perturbations. Finally, I will introduce a technique we are developing for conducting screens with millions of elements, enabling us to search vast spaces for desired phenotypes.
Short Bio: Thomas Norman is an Assistant Member in the Computational & Systems Biology Program at Memorial Sloan Kettering Cancer Center. Born in Canada, he has a bachelor’s degree in Mathematics and Engineering and a Master’s degree in Mathematics from Queen’s University in Kingston, Ontario. He did his Ph.D. in Systems Biology at Harvard University under the supervision of Richard Losick and Johan Paulsson, where he investigated how stochastic protein interactions can drive epigenetic, multi-generational phenotypes in genetically identical bacterial cells. Following his Ph.D., he worked as a Damon Runyon Fellow in Jonathan Weissman’s lab at UCSF, where he contributed to the development of the Perturb-seq approach and its application to understanding genetic interactions. He is a 2020 recipient of an NIH Director’s New Innovator Award and is currently a Josie Robertson Investigator at the Sloan Kettering Institute.
