Chemical Physics Seminar

Abstract

High-resolution, high-content measurements have greatly advanced our understanding of heterogeneous populations in biology. My group focuses on developing advanced tools and conceptual frameworks to facilitate the next phase: comprehension and prediction of system-level behavior. We aim to achieve this by uncovering the molecular architecture of complex biological systems. We take a unique information-centric perspective: we study biological insights that emerge exclusively from high-resolution, high-content measurements. We study natural systems that are amenable to reductionist analysis using high-precision datasets, utilizing both non-spatial (droplet microfluidics) and spatial (imaging) measurements. On the non-spatial measurement front, we are pioneering 'single virus genomics' for quantitative profiling of influenza evolution. I will present our technical innovations that enable direct, high-throughput measurement of individual viral genomes, as well as the first quantitative assessment of genome mixing probabilities among circulating influenza A virus (IAV) strains from natural reservoirs - an essential step in predicting potential pandemic strains. On the spatial measurement front, we are working toward "whole-brain, genome-scale, 3D molecular mapping across individuals" to integrate circuit-based and molecular-based understandings of brain functions that have remained disparate. We have studied the honeybee brain to take advantage of its small size, simple circuits, and well-defined social behaviors. I will discuss new biological insights revealed by our comprehensive brain mapping efforts and present the tools we have developed for next-generation molecular neuroimaging.