The Environment-Dependent Regulatory Landscape of the E. coli Genome

TL;DR

This study combines experimental and theoretical approaches to map the environment-dependent regulatory landscape of over 100 E. coli genes across diverse conditions, revealing new insights into gene regulation and function.

Contribution

It provides the first comprehensive, predictive models of E. coli gene regulation across multiple environments, integrating experimental data with information theory and statistical physics.

Findings

Discovered new regulatory binding sites and transcription factors.

Developed predictive models of gene regulatory behavior.

Gained biological insights into y-ome and toxin-antitoxin genes.

Abstract

All cells respond to changes in both their internal milieu and the environment around them through the regulation of their genes. Despite decades of effort, there remain huge gaps in our knowledge of both the function of many genes (the so-called y-ome) and how they adapt to changing environments via regulation. Here we describe a joint experimental and theoretical dissection of the regulation of a broad array of over 100 biologically interesting genes in E. coli across 39 diverse environments, permitting us to discover the binding sites and transcription factors that mediate regulatory control. Using a combination of mutagenesis, massively parallel reporter assays, mass spectrometry and tools from information theory and statistical physics, we go from complete ignorance of a promoter's environment-dependent regulatory architecture to predictive models of its behavior. As a proof of principle of the biological insights to be gained from such a study, we chose a combination of genes from the y-ome, toxin-antitoxin pairs, and genes hypothesized to be part of regulatory modules; in all cases, we discovered a host of new insights into their underlying regulatory landscape and resulting biological function.