Microscale Instrument Development for Genomic Analysis

University Of Washington, Seattle WA

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Abstract

Revised Abstract: The broad, long-term goal of this research is to develop technology for carrying out highly multivariant, dynamic analyses at the level of individual cells, based on genomic information. Microscale instrument systems will be developed that include technologies for highly sensitive detection of metabolites and specific proteins, for combining and analyzing multiple sensor inputs, and for efficient and sensitive separations of cells, metabolites, and internal cell contents. These systems will be developed primarily for two applications: 1) Modular microscale interfaces to a commercially available benchtop mass spectrometer and a microscale mass spectrometer will be developed for highly selective and sensitive metabolomic analysis of prokaryotes. This system will be used to analyze metabolic shifts in single cells and in real time with the ultimate goal of correlating genetic expression with metabolic outcomes. 2) Develop an integrated microscale cell culture instrument system that performs microscopic and chemical processing for eukaryote analysis. The specific application for this system is dense, high-throughput, loss of heterozygosity (LOH) analysis of progeny colonies from single Saccharomyces Cerevisiae cells. This system will be used to study the budding process in yeast and how the frequency of chromosome abnormalities effects aging and cancer development. The goals of this research are complementary to and contribute to the long-term goals of an NIH NHGRI Center of Excellence in Genomic Science, the Microscale Life Sciences Center, 1 P50 HG002360. The microscale instrument systems developed under these programs will comprise a low-cost, flexible, reconfigurable, benchtop toolbox that will push the limits of detection, tackle the module-to-module interconnect problem that is ubiquitous in all integrated microsystems, emphasize overall systems integration, and enable the production of comprehensive data sets. Ultimately, these microsystems will have far-reaching applications for both basic and applied research in broad areas of biomedical systems biology.