Seminar Date: Tuesday, September 26, 2023
Time: 11:00 am
Location: 67-3111 & Zoom
Talk Title: Microfluidics for High-Throughput Biophysics, Biochemistry, and Single-Cell Biology
Zoom recording (available for 30 days Passcode: J&eD4u$8)
Polly Fordyce is an Associate Professor of Genetics and Bioengineering and fellow of the ChEM-H Institute at Stanford, where her laboratory focuses on developing and applying new microfluidic platforms for quantitative, high-throughput biophysics and biochemistry and single-cell genomics. She graduated from the University of Colorado at Boulder with undergraduate degrees in physics and biology before moving to Stanford University, where she earned a Ph.D. in physics for work with Professor Steve Block developing instrumentation and assays for single-molecule studies of kinesin motor proteins. For her postdoctoral research, she worked with Professor Joe DeRisi to develop a new microfluidic platform for understanding how transcription factors recognize and bind their DNA targets as well as a new technology for bead-based multiplexing. She is the recipient of a number of awards, including an NIH New Innovator Award, an NSF CAREER Award, the 2023 Eli Lilly Award in Biological Chemistry, and is a Chan Zuckerberg Biohub Investigator.
Cellular function and organismal homeostasis are governed by molecular interactions. Protein-DNA binding interactions are essential for regulating gene transcription and translation, dense networks of protein-protein and protein-peptide interactions further regulate cellular function, and enzymes make possible all of the chemical transformations essential to metabolism and signaling. Our goal is to understand, and eventually engineer, these complex processes by building and testing biophysical models of how the molecules that drive these processes work. To do so, an essential first step is to obtain the necessary quantitative measurements of the fundamental kinetic and thermodynamic constants of these molecular interactions and catalytic processes—the “universal language” needed to describe and ultimately predict function. In our lab, we use microfluidics and extensive hardware automation to perform these quantitative measurements at an unprecedented scale.