| Summary: | Methods for single-cell analysis are critical to revealing cell-to-cell variability in biological systems, such as during development or onset of disease, where the characteristics of heterogeneity and minority cell populations are obscured by population-averaged measurements. Analysis of individual cells has been limited due to challenges associated with small amounts of starting material, combined with the cost and throughput required to examine large numbers of cells. Microfluidic approaches are well suited to single-cell analysis, providing increased sensitivity, economy of scale, and automation. This thesis presents the development and application of microfluidic technology for single cell gene expression analysis. The foundational contribution of this work is an integrated microfluidic device capable of performing high-precision RT-qPCR measurements of gene expression from hundreds of single cells per run. This device executes all steps of single cell processing including cell capture, cell lysis, reverse transcription, and quantitative PCR. This device is further expanded upon by integrating the single cell and nucleic acid processing capabilities with final measurement of cDNA by high-density digital PCR. The direct quantification of single molecules by digital PCR has advantages over RT-qPCR in the measurement of low abundance transcripts, as well as obviating the need for relative abundance measurements or calibration standards. This technology is demonstrated in over 5,000 individual cell measurements of mRNA, microRNA, and single nucleotide variant detection in a variety of cell types. Finally, this technology is applied to study the performance of lipid nanoparticles in delivery of RNA, and manipulation of gene expression in cells. The microfluidic integration of cell and nucleic acid processing established in this thesis permits analysis of hundreds of single cells in parallel, while improving work flow and reducing technical variation compared to samples prepared in microliter volumes. Ultimately, this advances the tools available for precisely measuring transcripts in single cells, and has application in research and clinical settings. === Science, Faculty of === Graduate
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