ArticleCell reports2023
Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance.
Article in Cell reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Meta-analysis Driven Strain Design for Mitigating Oxidative Stresses Important in Biomanufacturing.ACS synthetic biology · 2024Pooled it
- Transcriptional regulatory network differences between six industrialMetabolic engineering communications · 2026Article
- Selection favors cost-ordered adaptive mutational paths in a stress-magnitude-dependent manner.EMBO reports · 2026Article
- Dissecting host stress responses for predictable heterologous gene expression in E. coli.Nucleic acids research · 2026Article
- The transcriptional regulatory network of the Escherichia coli MG1655 reference strain.Nucleic acids research · 2026Article
- Laboratory Evolution Reveals Transcriptional Mechanisms Underlying Thermal Adaptation of Escherichia coli.Genome biology and evolution · 2025Article
- Article
- Reverse-Engineered Gas-Fermenting Acetogen Strains Recover Enhanced Phenotypes From Autotrophic Adaptive Laboratory Evolution.Microbial biotechnology · 2025Article
- Article
- Modulating bacterial function utilizing A knowledge base of transcriptional regulatory modules.Nucleic acids research · 2024Article
- Repeated glucose oscillations in high cell-density cultures influence stress-related functions ofPNAS nexus · 2024Article
- The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions.mSystems · 2024Article
- Review
- The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions.Research square · 2023Article
Corrections and comments
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Authors and funding
16 authors at 5 institutions in 5 countries.
Funding
Abstract
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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Registered trials
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