Increasingly, it is becoming apparent that understanding, predicting, and diagnosing disease states is confounded by the inherent heterogeneity of in situ cell populations. This variation in cell fate can be dramatic, for instance, one cell living while an adjacent cell dies. Thus, in order to understand fundamental pathways involved in disease states, it is necessary to link preexisting cell state to cell fate in the disease process at the individual cell level. The Microscale Life Sciences Center (MLSC) at the University of Washington is focused on solving this problem, by developing cutting-edge microscale technology for high throughput genomic-level and multi-parameter single-cell analysis, and applying that technology to fundamental problems of biology and health. Our vision is to address pathways to disease states directly at the individual cell level, at increasing levels of complexity that progressively move to an in vivo understanding of disease. We propose to apply MLSC technological innovations to questions that focus on the balance between cell proliferation and cell death. The top three killers in the US, cancer, heart disease and stroke, all involve an imbalance in this cellular decision-making process. Because of intrinsic cellular heterogeneity in the live/die decision, this fundamental cellular biology problem is an example of one for which analysis of individual cells is essential for developing the link between genomics, cell function, and disease. The specific systems to be studied are proinflammatory cell death (pyroptosis) in a mouse macrophage model, and neoplastic ? progression in the Barrett's Esophagus (BE) precancerous model. In each case, diagnostic signatures for specific cell states will be determined by measuring both physiological (cell cycle, ploidy, respiration rate, membrane potential) and genomic (gene expression profiles by single-cell proteomics, qRT-PCR and transcriptomics; LOH by LATE-PCR) parameters. These will then be correlated with cell fate via the same sets of measurements after a challenge is administered, for instance, a cell death stimulus for pyroptosis or a predisposing risk factor challenge (acid reflux) for BE. Ultimately, time series will be taken to map out the pathways that underlie the live/die decision. Finally, this information will be used ? ? ? as a platform to define cell-cell interactions at the single-cell level, to move information on disease pathways towards greater in vivo relevance. New technology will be developed and integrated into the existing MLSC Living Cell Analysis cassette system to support these ambitious biological goals including 1) automated systems for cell placement, off-chip device interconnects, and high throughput data analysis with user friendly interfaces; 2) new optical and electronic sensors based on a new detection platform, new dyes and nanowires; and 3) new micromodules for single-cell qRT-PCR, LATE-PCR for LOH including single-cell pyrosequencing, on-chip single-cell proteomics, and single-cell transcriptomics using barcoded nanobeads. ? ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Specialized Center (P50)
Project #
2P50HG002360-06
Application #
7158163
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Schloss, Jeffery
Project Start
2001-08-01
Project End
2006-12-31
Budget Start
2006-08-15
Budget End
2006-12-31
Support Year
6
Fiscal Year
2006
Total Cost
$1,792,012
Indirect Cost
Name
University of Washington
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
605799469
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

Showing the most recent 10 out of 97 publications