Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance

• DOI: 10.1016/j.celrep.2023.113105
• Publication Date: 2023-09-19T06:39:44Z
• Authors: Kevin Rychel; Justin Tan; Arjun Patel; Cameron Lamoureux; Ying Hefner; Richard Szubin; Josefin Johnsen; Elsayed Tharwat T...; Patrick V. Phaneuf; Amitesh Anand; Connor A. Olson; Joon Ho Park; Anand V. Sastry; Laurence Yang; Adam M. Feist; Bernhard O. Palsson
• Keywords: Metabolome; Metabolic pathway; Negative selection; Experimental Evolution

Relationships between the genome, transcriptome, and metabolome underlie all evolved phenotypes. However, it has proved difficult to elucidate these relationships because of high number variables measured. A recently developed data analytic method for characterizing transcriptome can simplify interpretation by grouping genes into independently modulated sets (iModulons). Here, we demonstrate how iModulons reveal deep understanding effects causal mutations metabolic rewiring. We use adaptive laboratory evolution generate E. coli strains that tolerate levels redox cycling compound paraquat, which produces reactive oxygen species (ROS). combine resequencing, iModulons, models six interacting stress-tolerance mechanisms: (1) modification transport, (2) activation ROS stress responses, (3) ROS-sensitive iron regulation, (4) motility, (5) broad transcriptional reallocation toward growth, (6) rewiring decrease NADH production. This work thus demonstrates power iModulon knowledge mapping analysis.