Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance
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...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-09-01
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| Series: | Cell Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211124723011166 |
| _version_ | 1797685290944430080 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Kevin Rychel |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T00:42:04Z |
| format | Article |
| id | doaj.art-3fa5f4f1b24a41dda13d125aac6d22b6 |
| institution | Directory Open Access Journal |
| issn | 2211-1247 |
| language | English |
| last_indexed | 2024-03-12T00:42:04Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cell Reports |
| spelling | doaj.art-3fa5f4f1b24a41dda13d125aac6d22b62023-09-15T04:39:29ZengElsevierCell Reports2211-12472023-09-01429113105Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat toleranceKevin Rychel0Justin Tan1Arjun Patel2Cameron Lamoureux3Ying Hefner4Richard Szubin5Josefin Johnsen6Elsayed Tharwat Tolba Mohamed7Patrick V. Phaneuf8Amitesh Anand9Connor A. Olson10Joon Ho Park11Anand V. Sastry12Laurence Yang13Adam M. Feist14Bernhard O. Palsson15Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USADepartment of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USADepartment of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USADepartment of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USADepartment of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USADepartment of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USANovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kgs. Lyngby, DenmarkNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kgs. Lyngby, DenmarkNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kgs. Lyngby, DenmarkTata Institute of Fundamental Research, Homi Bhabha Road, Colaba, Mumbai, Maharashtra, IndiaDepartment of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USADepartment of Chemical Engineering, Massachusetts Institute of Technology, 500 Main Street, Building 76, Cambridge, MA 02139, USADepartment of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USADepartment of Chemical Engineering, Queen’s University, Kingston, ON K7L 3N6, CanadaDepartment 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, DenmarkDepartment 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 authorSummary: 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.http://www.sciencedirect.com/science/article/pii/S2211124723011166CP: Microbiology |
| spellingShingle | 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 Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance Cell Reports CP: Microbiology |
| title | Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance |
| title_full | Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance |
| title_fullStr | Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance |
| title_full_unstemmed | Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance |
| title_short | Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance |
| title_sort | laboratory evolution transcriptomics and modeling reveal mechanisms of paraquat tolerance |
| topic | CP: Microbiology |
| url | http://www.sciencedirect.com/science/article/pii/S2211124723011166 |
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