CBE 289 Seminar: Building of EvolvR, a Cell Diversity Generating Tool, and Demonstrating Its Applications in Therapeutics Development
Department of Bioengineering
Abstract: Directed evolution is a powerful strategy for improving biological traits of interest. In this talk, I will present EvolvR, a technology I co-developed with David Schaffer and talented former students Shakked Halperin, Juan Hurtado and Adam Schieferecke. EvolvR is a CRISPR-based, in-cell diversifier that combines a nicking Cas9 for guide RNA targeting with an error-prone, nick-translating DNA polymerase to introduce SNPs within the targeted window. I will first describe the design and functionality of EvolvR in its original E. coli host and then explain how we recently adapted it for application in mammalian cells. We found that much of the diversity that is generated is gaited by the specificity of the CRISPR nickase. Finally, I will discuss how we further adapted EvolvR for the engineering of an oncolytic virus for improved delivery of therapeutic cargos to solid tumors.
Bio: John Dueber is the Lloyd Distinguished Professor of Bioengineering at UC Berkeley. He received his bachelor's degree in biochemistry at University of Delaware in 1999 and earned his doctorate in 2005 in Wendell Lim’s lab at UCSF, where he developed an interest in forward-engineering cellular behaviors. As a QB3 Distinguished Fellow at UC Berkeley, mentored by Jay Keasling, he applied synthetic biology approaches to enhance engineered metabolic pathway performance. Since establishing his lab in 2010, he has focused on developing technologies that increase engineering control over cellular function for a wide range of engineering applications. He has been awarded an NSF CAREER, DOE Early Career, and the Bakar Fellow award. His trainees have gone on to found five companies spanning cellular therapeutics to the fermentation-based production of commodity chemicals.
Share
Related Content
| Attachment | Size |
|---|---|
| 317.84 KB |
Upcoming Events
-
MSE 298 Seminar: Electrocatalysis as Enabling Technology for Decarbonization
-
CEE Ph.D. Defense Announcement: Modeling the Spatiotemporal Heterogeneities of Electric Vehicle Adoption in the United States through Sentiment-Mediated Mechanisms - A Large Language Model-Assisted Data-Fusion Framework
-
EECS Seminar: Random Thoughts After More Than 60 years in the Trenches
-
MAE 298 Seminar: Machine Learning Acceleration of Turbulent Combustion and Nonequilibrium Flow Predictions
-
CBE 298: Green Steel: Design, Supply Chain, H2 Storage and Dispatch Strategies