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.