Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance Article Swipe
Kevin Rychel
,
Justin Tan
,
Arjun Patel
,
Cameron Lamoureux
,
Ying Hefner
,
Richard Szubin
,
Josefin Johnsen
,
Elsayed T. Mohamed
,
Patrick V. Phaneuf
,
Amitesh Anand
,
Connor A. Olson
,
Joon Ho Park
,
Anand V. Sastry
,
Laurence Yang
,
Adam M. Feist
,
Bernhard Ø. Palsson
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.celrep.2023.113105
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.celrep.2023.113105
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.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.celrep.2023.113105
- http://www.cell.com/article/S2211124723011166/pdf
- OA Status
- gold
- Cited By
- 20
- References
- 130
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386796053
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386796053Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.celrep.2023.113105Digital Object Identifier
- Title
-
Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat toleranceWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-09-01Full publication date if available
- Authors
-
Kevin Rychel, Justin Tan, Arjun Patel, Cameron Lamoureux, Ying Hefner, Richard Szubin, Josefin Johnsen, Elsayed T. Mohamed, Patrick V. Phaneuf, Amitesh Anand, Connor A. Olson, Joon Ho Park, Anand V. Sastry, Laurence Yang, Adam M. Feist, Bernhard Ø. PalssonList of authors in order
- Landing page
-
https://doi.org/10.1016/j.celrep.2023.113105Publisher landing page
- PDF URL
-
https://www.cell.com/article/S2211124723011166/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.cell.com/article/S2211124723011166/pdfDirect OA link when available
- Concepts
-
Transcriptome, Metabolome, Biology, Paraquat, Reactive oxygen species, Phenotype, Computational biology, Metabolic pathway, Negative selection, Metabolomics, Gene, Adaptation (eye), Genome, Experimental evolution, Genetics, Gene expression, Bioinformatics, Biochemistry, NeuroscienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
20Total citation count in OpenAlex
- Citations by year (recent)
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2025: 8, 2024: 11, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
130Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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