The availability of genome sequences for both prokaryotes and eukaryotes is laying the foundation for a revolution that will ultimately transform biology from a largely descriptive and reductionist predictive science. The growing ability to analyze whole biological systems based on genomic information is creating snapshots of cells at the transcriptional and translational level, which are providing preliminary insights into cellular complexity. However, to understand complex molecular outcomes such as cell proliferation, differentiation, apoptosis, and pathogenesis, it will be necessary to determine how the parts are integrated in time and space to form complex, dynamic cellular functions, and how cellular interactions create higher-order functions. Such analyses require the simultaneous measurement of many variable sin real-time, and due to heterogeneity in cellular populations, these analyses need to be carried out for individual cells. Therefore, a major barrier to achieving this objective is the lack of available technology for carrying out highly multi-variant, dynamic analyses at the level of individual cells, based on genomic information. A second major barrier is the lack of available technology for processing individual cells, based on genomic information. A second major barrier is the lack of available technology for processing microsamples for genome-based expression analysis, to allow comparative initiative is to meet these challenges with an interdisciplinary team of experts from genomic sciences, microanalytical chemistry, and microsystems engineering who will develop and apply enabling technology for analysis and processing of individual cells. We propose to design and build fully integrated and automated microsystems for the interrogation of individual cells. This core technology will then be converted into modules designed for specific applications, which will push the limits of detection to the minium, in some cases, to single molecule levels This enabling technology will be directed towards specific research problems in two main areas: 1) automated detection of rare cells in cell populations, and 2) real-time analysis of metabolism in individual cells. Both areas are applicable to eukaryotes and prokaryotes, and depend on availability of genome sequence data, but not necessary complete genomes. The integrated biologically-active microsystems we develop 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.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Specialized Center (P50)
Project #
3P50HG002360-01S1
Application #
6594528
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Schloss, Jeffery
Project Start
2001-08-01
Project End
2006-07-31
Budget Start
2002-06-17
Budget End
2002-07-31
Support Year
1
Fiscal Year
2002
Total Cost
$46,988
Indirect Cost
Name
University of Washington
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
135646524
City
Seattle
State
WA
Country
United States
Zip Code
98195
Kelbauskas, Laimonas; Ashili, Shashaanka P; Lee, Kristen B et al. (2018) Simultaneous Multiparameter Cellular Energy Metabolism Profiling of Small Populations of Cells. Sci Rep 8:4359
Kelbauskas, Laimonas; Glenn, Honor; Anderson, Clifford et al. (2017) A platform for high-throughput bioenergy production phenotype characterization in single cells. Sci Rep 7:45399
Cheng, Yichen; Dai, James Y; Paulson, Thomas G et al. (2017) Quantification of Multiple Tumor Clones Using Gene Array and Sequencing Data. Ann Appl Stat 11:967-991
Kelbauskas, L; Ashili, S; Zeng, J et al. (2017) Platform for combined analysis of functional and biomolecular phenotypes of the same cell. Sci Rep 7:44636
Lee, Kristen B; Kelbauskas, Laimonas; Brunner, Alan et al. (2017) A versatile method for dynamically controlled patterning of small populations of epithelial cells on substrates via non-contact piezoelectric inkjet printing. PLoS One 12:e0176079
Yaron, Jordan R; Rao, Mounica Y; Gangaraju, Sandhya et al. (2016) The oxindole Syk inhibitor OXSI-2 blocks nigericin-induced inflammasome signaling and pyroptosis independent of potassium efflux. Biochem Biophys Res Commun 472:545-50
Zeng, Jia; Kelbauskas, Laimonas; Rezaie, Aida et al. (2016) Transcriptional regulation by normal epithelium of premalignant to malignant progression in Barrett's esophagus. Sci Rep 6:35227
Zhang, Liqiang; Su, Fengyu; Kong, Xiangxing et al. (2016) Ratiometric fluorescent pH-sensitive polymers for high-throughput monitoring of extracellular pH. RSC Adv 6:46134-46142
Zhang, Liqiang; Su, Fengyu; Kong, Xiangxing et al. (2016) 1,8-Naphthalimide Derivative Dyes with Large Stokes Shifts for Targeting Live-Cell Mitochondria. Chembiochem 17:1719-24
Yaron, J R; Gangaraju, S; Rao, M Y et al. (2015) K(+) regulates Ca(2+) to drive inflammasome signaling: dynamic visualization of ion flux in live cells. Cell Death Dis 6:e1954

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