Proteomics typically involves the analysis of the protein components of large populations of cells. Nearlyall the of a cell's machinery are proteins, so many diseases and responses to stimuli and stressors aremanifested at the protein level. Proteomes are challenging to characterize fully for many reasons. Someof the key attributes of a proteome that make its characterization so challenging are: the large numberof proteins expressed in a single cell, the wide dynamic range of protein relative abundance, and thenumerous modifications that can switch proteins between active an inactive states. To further increasecomplexity, significant heterogeneity exists at the cellular level that is averaged out by bulk analyses. Tobetter understand biological and health implications of cellular heterogeneity, single cell proteomics hasemerged. However, improvements in the enabling analytical technologies are needed as single-cellproteomics adds the additional challenge of extremely small sample size. This application focuses on thedevelopment of a novel electrokinetic microfluidic/nanofluidic system for improved single-cell proteomeanalyses that is a significant deviation from the current ultra-performance liquid chromatography(UPLC)-mass spectrometry (MS) based approaches. The proposed electrokinetic microfluidic/nanofluidicsystem is expected to offer improved performance from: reduced sample loss, increased sampleconcentration eluted into the mass spectrometer, reduced peptide contamination, high efficiencyseparations, and rapid analyses. The Aims of this application focus on: 1) fabrication and optimization ofthe key functional modules, and 2) integration of these functional modules into a complete system andmeasurement of the performance of the complete system. The primary metrics for system performancewill be the speed of the analysis and the number of protein groups identified. If successful, thisapplication will provide a novel system for single-cell proteomics that will improve the analysis speedwithout sacrificing depth of proteome coverage.
Public Health Relevance Statement: This application seeks to develop an improved system for single cell proteomics to study the variability
of the protein machinery within individual cells. This system can be applied to determine how cells vary
within a tumor or how individual cells within a population respond differently to stimuli, such as an
environmental stressor or drug. Thus, a new rapid approach will be created to determine how cells
change with illness, disease, drug treatments, and environmental stressor and how the responses of
different cells effect health.
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