(265g) Phenome to Genome Enabled By Microfluidics and High-Throughput Quantitative Microscopy

Lu, H., Georgia Institute of Technology
Biological systems are complex. Often the observables are a result of gene and environmental interactions, sometimes influenced by stochasticity. To accelerate our understanding in order to cure diseases or to engineer solutions to industrial problems, mapping the relationships between phenome and genome is crucial. My lab is interested in developing and using a set of automation, microfluidics, and image-based data mining technologies to address questions in quantitative biology. I will show how we take advantage of simple hydrodynamics to design microfluidic systems for large throughput and spatially and temporally well-controlled experiments in Drosophila embryonic development as well as in immunology. In another example, I will show how we combine the power of experimental tools and computational tools to study problems in development neurobiology and behavior in C. elegans. The power of these engineered systems lies in that the throughput that can be achieved by using automation and microfluidics is 100-1,000 times that of conventional methods; furthermore, we can obtain information unattainable by conventional tools and “invisible” to human vision to discover new genes and gene functions.