Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance
Kevin Rychel,
Justin Tan,
Arjun Patel,
Cameron Lamoureux,
Ying Hefner,
Richard Szubin,
Josefin Johnsen,
Elsayed Tharwat Tolba Mohamed,
Patrick V. Phaneuf,
Amitesh Anand,
Connor A. Olson,
Joon Ho Park,
Anand V. Sastry,
Laurence Yang,
Adam M. Feist,
Bernhard O. Palsson
Affiliations
Kevin Rychel
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
Justin Tan
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
Arjun Patel
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
Cameron Lamoureux
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
Ying Hefner
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
Richard Szubin
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
Josefin Johnsen
Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kgs. Lyngby, Denmark
Elsayed Tharwat Tolba Mohamed
Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kgs. Lyngby, Denmark
Patrick V. Phaneuf
Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kgs. Lyngby, Denmark
Amitesh Anand
Tata Institute of Fundamental Research, Homi Bhabha Road, Colaba, Mumbai, Maharashtra, India
Connor A. Olson
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
Joon Ho Park
Department of Chemical Engineering, Massachusetts Institute of Technology, 500 Main Street, Building 76, Cambridge, MA 02139, USA
Anand V. Sastry
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
Laurence Yang
Department of Chemical Engineering, Queen’s University, Kingston, ON K7L 3N6, Canada
Adam M. Feist
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kgs. Lyngby, Denmark
Bernhard O. Palsson
Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kgs. Lyngby, Denmark; Corresponding author
Summary: Relationships between the genome, transcriptome, and metabolome underlie all evolved phenotypes. However, it has proved difficult to elucidate these relationships because of the high number of variables measured. A recently developed data analytic method for characterizing the transcriptome can simplify interpretation by grouping genes into independently modulated sets (iModulons). Here, we demonstrate how iModulons reveal deep understanding of the effects of causal mutations and metabolic rewiring. We use adaptive laboratory evolution to generate E. coli strains that tolerate high levels of the redox cycling compound paraquat, which produces reactive oxygen species (ROS). We combine resequencing, iModulons, and metabolic models to elucidate six interacting stress-tolerance mechanisms: (1) modification of transport, (2) activation of ROS stress responses, (3) use of ROS-sensitive iron regulation, (4) motility, (5) broad transcriptional reallocation toward growth, and (6) metabolic rewiring to decrease NADH production. This work thus demonstrates the power of iModulon knowledge mapping for evolution analysis.
