Experimental and Computational Tools for Single Cell Analysis in Cancer Diagnostics

Abstract

Substantial evidence shows that cellular heterogeneity commonly exists within an isogenic or clonal population. Whether in isolation or caused through a combination of the above events, cellular heterogeneity can dramatically influence cellular decision making and cell fate, however, this can be masked by the average response from a population. One approach to solve this issue is to analyze a population at the individual cell level. The goal of this work is to develop high-throughput experimental and computational platforms to screen and quantify single cancer cells for specific intracellular enzyme activities. An interdisciplinary approach was taken to 1) better understand the role of the ubiquitin-proteasome system (UPS) by characterizing a potential regulator and 2) to develop a set of bioanalytical tools to facilitate the direct quantification of intracellular enzyme activity in single intact cells by integrating a CPP-based fluorescent reporter into a droplet microfluidic platform coupled with automated single cell analysis and simulation techniques. The first part of this study focuses on the characterization of a deubiquitinating enzyme (DUB) regulator, PMI5011, derived from Artemisia dracunculus L. To design and develop CPP-based fluorescent reporters, a library of CPPs were first characterized to identify their potential as stable, cell-permeable bio vectors. Upon discovering the highly effective performance of the D-chirality CPPs and identifying their potential applications, the role of microfluidics in single cell analysis was explored. A droplet microfluidic device was incorporated with a previously developed peptide-based DUB reporter to quantify intracellular activity of DUBs in single multiple myeloma cells thus providing an insight on personalized medicine and drug development. The throughput of this experimental bioanalytical platform was increased by developing a Python algorithm called FluoroCellTrack, to quantify global microfluidic data. Finally, the utility of microfluidics in analyzing cellular heterogeneity was explored by screening algae cells for heterogeneous alkaline phosphatase (AP) activity using a microfluidic trapper device. Single algae cell analysis can provide information on harmful algal blooms and allelopathy. This thesis describes a holistic experimental and computational platform for single cell analysis which finds potential application in addressing healthcare and environmental issues.