Single cell RNA sequencing provides a quantitative approach to study differences in the transcriptional profiles of cells in a heterogeneous sample. This technology has been transformative in many biological fields such cancer biology, developmental biology, and infectious disease. Often, however, the transcriptome alone is insufficient to address the biological research question at hand. For this reason, recent attention in the genomics field has turned towards developing multiomic technologies capable of simultaneously profiling multiple datasets simultaneously.

One critical technology gap is a sequencing technology that can provide both an optical phenotype and sequence data at single cell resolution. Existing technologies either are low throughput or incapable of identifying complex time varying phenotypes. Methods like fluorescent activated cell sorting, for example, can be used to perform targeted sequencing of cells by phenotype, but this approach is limited to low throughputs compatible with well plate formats. Importantly, it is also limited to simple phenotypes such as fluorescent antibodies against surface proteins or intracellular fluorescence values. It cannot process a time varying signal or an arbitrary phenotype like cell morphology changes.

In this proposed research, I develop a novel sequencing technology that leverages custom droplet microfluidic modules and a novel barcoding approach to simultaneously profile optical phenotypes and transcriptomes at the single cell level. After developing and validating the technology, I will then leverage it to perform parameter characterization of a synthetic genetic oscillator. I envision this technology as being broadly applicable to any biological question requiring an understanding of a cell’s sequence-phenotype relationship. I am particularly interested in applying my technology to accelerate the development of genetic circuits in the field of synthetic biology