(113e) Integrating Micro-Environmental Cues into Single-Cell Targeted Proteomics Tools | AIChE

(113e) Integrating Micro-Environmental Cues into Single-Cell Targeted Proteomics Tools

Authors 

Su, E. - Presenter, Graduate Program in Bioengineering, UC Berkeley - UCSF
Yamauchi, K. A., UC Berkeley - UCSF
Herr, A. E., UC Berkeley - UCSF
Variation among individual cells does not arise in isolation, with the local microenvironment understood to play an important role. Physiologic processes underpinning stem cell differentiation and maturation are impacted by a complex milieu of extracellular factors including paracrine signaling, proximity and characteristics of neighboring cells, and mechanical substrate properties. Direct measurement of protein-mediated signaling in individual cells sheds insight on cellular response to each environmental variable, including 3D culture. Concomitantly, our previous studies show that microfluidic electrophoresis deepens the protein profiling that is possible in cytometry (analysis of single cells). Here, we advance the design of single-cell resolution electrophoretic separations to now include analysis of cells that are not in isolation.

To accomplish this goal, we design, demonstrate, and characterize a microfluidic cell patterning technique that allows us to culture single cells and small cell clusters in controlled, tunable microenvironments and then directly analyze the lysate of each single cell in situ. Using short assay times, electrophoresis, and photo-activatable crosslinkers, we demonstrate separation, detection, and ratiometric analysis of protein targets from stem cells in diverse microenvironments. We describe our multi-layered (3D) microfluidic device, tunable polymer formulations (chemical, mechanical, geometric) and separations-related outcomes (dispersion, dilution, separation resolution, peak capacity). By integrating microenvironmental cues into a precision microanalytical instrument, we measure key morphometric and spatial information and correlate these physical data to protein expression patterns of each mammalian cell.

Looking forward, we view the combination of spatio-temporal information with targeted proteomic information as an important and, as of yet missing, axis of systems biology.

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