High-content and high-throughput analysis of single cell protein signatures is a long-sought but elusive goal in cell biology. Such analysis is crucial to understanding how non-genetic cell-to-cell variability impacts behavior, as well as to reconstruct intracellular signaling networks at the systems level, both of which have significant implications in human health and disease. Currently, there is no high dimensional, robust single cell analysis technology platform that meets all three ofthe following requirements, (i) Single cell sensitivity: proteins can be isolated and sensitively measured from a single cell, (ii) High multiplicity: a large panel of proteins can be simultaneously measured from a single cell, (iii) High content: thousands of single cells can be analyzed in parallel in order to reveal cellular heterogeneity in response to perturbations. Herein we propose to develop and fully validate a high content and high-throughput single cell technology that integrates microfluidic cell handling and an ultra-high density protein microarray. The integrated microchip will allow analysis of 1000 single cells for each of which levels of up to 60 proteins will be measured. The device will enable detection of intracellular proteins in single cells following cell lysis in the chip, with simultaneous measurement of secreted cytokines. We will validate the integrated microchip in multiple cell lines and benchmark its performance against comparable technologies. Finally, we will collect a systematic single cell data set of protein signals and secreted cytokines in the HT-29 cell line in response to TNF, EGF, and insulin stimulation to demonstrate the utility ofthe integrated microchip for revealing how proteomic heterogeneity impacts signal transduction and cell behavior. Responsiveness: This project addresses a major goal of this U01 program: to substantially adapt a technology to improve the scope and throughput of perturbation-induced cellular signature data generation. The ability to do multiplexed analysis of protein levels in single cells is complementary to other LINCS efforts that focus on population-based analyses. This technology is transferrable to a broad range of human cell lines, and has the potential to mature into a standardized, integrated and robust platform within two years.
Non-genetic heterogeneity is emerging as a significant challenge in therapeutic responses to drugs, such as fractional killing in cancer therapy. The single cell proteomics technology described in this proposal has great potential to become a pharmacological tool to evaluate treatment efficacy, as well as a clinical tool for informative diagnosis and stratification of patients to enable individualized treatment.
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