Development of genetic and analytical tools for studying dose-dependent gene expression [electronic resource]
Keywords: Chemical Engineering

Studying the effects of gene expression in biological systems has traditionally been undertaken by measuring phenotypic response at a limited number of expression levels. Typically the effects of gene expression are assayed at a high level of overexpression and compared to physiological levels of expression; however, many examples exist in which the level of gene expression greatly affects the resulting cellular phenotypes. Of particular interest for our purposes is the interplay between oncogenes in driving tumorigenesis and cancer progression. For example, oncogene H-Ras is capable of both enhancing cellular proliferation at intermediate levels expression levels (doses) and causing cell cycle arrest and senescence at high expression levels. In order to more thoroughly investigate such behavior we have created a set of tools for measuring dose-dependent effects of gene expression. These tools consist of promoter library to drive wide range gene expression, single-cell proliferation measurements, and data analysis methods to calculate correlation curves between gene expression level and phenotype response. The system is designed for cell-by-cell measuring of both expression level and phenotype response by flow cytometry. This approach allows for full dose experiments to be performed in a single heterogeneous culture with individual cells accessing different expression levels for a given phenotype. Because we are interested in studying the cell biology and genetics of tumor cells, measuring the phenotype of proliferation rate was of particular interest. To aid in further investigation of proliferation rate response to gene overexpression a genetic proliferation reporter was developed. This reporter utilizes the cell cycle-dependent activity of the E2F class of transcription factors, which are active during the G1/S transition. The highly stable fluorescent proteins EGFP and mCherry are expressed from both an E2F-responsive and constitutive promoter, respectively. The ratio of fluorescence levels correlates to proliferation rate in a variety of cell lines, matching predictions made initially by computational model. Finally, given a culture containing expression of a gene or combination of genes by the promoter library and phenotype measurement, the data collected from those cells must be analyzed to determine a correlation curve representing the dose response of the phenotype to level of expression of the genes of interest. In order to calculate this curve from the flow cytometry data several empirical analysis methods were evaluated. We determined the locally weighted scatter plot smoothing (LOWESS) curve fitting method to be best for our purposes of fitting the dose-response curves. As the LOWESS fits of flow cytometry data represented a technical hurdle to performing the dose-response experiments a custom software package was created to allow for easy implementation of the constitutive promoter library for studying dose-dependent behavior. The result is a set of biological and computational tools that allow for high throughput evaluation of gene dose effects. Further effort has been undertaken to move the system to evaluate multiple genes simultaneously, with the ultimate goal of being able to measure genetic cooperation.