Cellular responses to reactive oxygen species are predicted from molecular mechanisms

Research output: Contribution to journalJournal article – Annual report year: 2019Researchpeer-review

DOI

  • Author: Yang, Laurence

    University of California at San Diego, United States

  • Author: Mih, Nathan

    University of California at San Diego, United States

  • Author: Anand, Amitesh

    University of California at San Diego, United States

  • Author: Park, Joon Ho

    University of California at San Diego, United States

  • Author: Tan, Justin

    University of California at San Diego, United States

  • Author: Yurkovich, James T.

    University of California at San Diego, United States

  • Author: Monk, Jonathan M

    University of California at San Diego, United States

  • Author: Lloyd, Colton J.

    University of California at San Diego, United States

  • Author: Sandberg, Troy E.

    University of California at San Diego, United States

  • Author: Seo, Sang Woo

    University of California at San Diego, United States

  • Author: Kim, Donghyuk

    University of California at San Diego, United States

  • Author: Sastry, Anand V.

    University of California at San Diego, United States

  • Author: Phaneuf, Patrick V.

    University of California at San Diego, United States

  • Author: Gao, Ye

    University of California at San Diego, United States

  • Author: Broddrick, Jared T.

    University of California at San Diego, United States

  • Author: Chen, Ke

    University of California at San Diego, United States

  • Author: Heckmann, David

    University of California at San Diego, United States

  • Author: Szubin, Richard

    University of California at San Diego, United States

  • Author: Hefner, Ying

    University of California at San Diego, United States

  • Author: Feist, Adam M.

    ALE Technology & Software Development, Research Groups, Network Reconstruction in Silico Biology, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, 2800, Kgs. Lyngby, Denmark

  • Author: Palsson, Bernhard O.

    Network Reconstruction in Silico Biology, Big Data 2 Knowledge, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, 2800, Kgs. Lyngby, Denmark

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Catalysis using iron–sulfur clusters and transition metals can be traced back to the last universal common ancestor. The damage to metalloproteins caused by reactive oxygen species (ROS) can prevent cell growth and survival when unmanaged, thus eliciting an essential stress response that is universal and fundamental in biology. Here we develop a computable multiscale description of the ROS stress response in Escherichia coli, called OxidizeME. We use OxidizeME to explain four key responses to oxidative stress: 1) ROS-induced auxotrophy for branched-chain, aromatic, and sulfurous amino acids; 2) nutrient-dependent sensitivity of growth rate to ROS; 3) ROS-specific differential gene expression separate from global growth-associated differential expression; and 4) coordinated expression of iron–sulfur cluster (ISC) and sulfur assimilation (SUF) systems for iron–sulfur cluster biosynthesis. These results show that we can now develop fundamental and quantitative genotype–phenotype relationships for stress responses on a genome-wide basis.
Original languageEnglish
JournalProceedings of the National Academy of Sciences of the United States of America
Volume116
Issue number28
Pages (from-to)14368-14373
ISSN0027-8424
DOIs
Publication statusPublished - 2019
CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • Reactive oxygen species, Oxidative stress, Metabolism, Protein expression, Genome-scale model

ID: 186198267