Genomics analysis on the responses of E. coli cells to varying environmental conditions

Abstract

The natural living environments of E. coli cells are diverse, varying from mammalian gastrointestinal tracts and soil. Each environment might require distinct metabolic pathways and transporter systems, and long-term evolution has established elaborate regulatory system for E. coli cells to quickly adapt to the changing conditions. Sensing outside stresses and then adopting a different phenotype enable them to take advantage of any possible nutrients and defend against hostile environment. A lot of regulatory mechanisms have been identified by genetic, biochemical and molecular biology methods, and our study aim to build a systematic view on the response of the whole genome to four different environmental conditions. We used statistical tests including Pearson’s tests and Spearman’s tests and multiple testing adjustments to identify feature genes that are induced or repressed significantly across treatment levels. The feature genes identified were partially supported by previous literatures, and some of the novel genes not found in any previous studies may infer a potential research blind spot. Additionally, we compared the correlation tests to the implementation of machine learning algorithms, and discussed the advantage and drawbacks of each method.