Chemical-damage MINE: A database of curated and predicted spontaneous metabolic reactions

James G. Jeffryes, Claudia Lerma-Ortiz, Filipe Liu, Alexey Golubev, Thomas D. Niehaus, Mona Elbadawi-Sidhu, Oliver Fiehn, Andrew D. Hanson, Keith EJ Tyo, Christopher S. Henry*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Spontaneous reactions between metabolites are often neglected in favor of emphasizing enzyme-catalyzed chemistry because spontaneous reaction rates are assumed to be insignificant under physiological conditions. However, synthetic biology and engineering efforts can raise natural metabolites' levels or introduce unnatural ones, so that previously innocuous or nonexistent spontaneous reactions become an issue. Problems arise when spontaneous reaction rates exceed the capacity of a platform organism to dispose of toxic or chemically active reaction products. While various reliable sources list competing or toxic enzymatic pathways’ side-reactions, no corresponding compilation of spontaneous side-reactions exists, nor is it possible to predict their occurrence. We addressed this deficiency by creating the Chemical Damage (CD)-MINE resource. First, we used literature data to construct a comprehensive database of metabolite reactions that occur spontaneously in physiological conditions. We then leveraged this data to construct 148 reaction rules describing the known spontaneous chemistry in a substrate-generic way. We applied these rules to all compounds in the ModelSEED database, predicting 180,891 spontaneous reactions. The resulting (CD)-MINE is available at https://minedatabase.mcs.anl.gov/cdmine/#/home and through developer tools. We also demonstrate how damage-prone intermediates and end products are widely distributed among metabolic pathways, and how predicting spontaneous chemical damage helps rationalize toxicity and carbon loss using examples from published pathways to commercial products. We explain how analyzing damage-prone areas in metabolism helps design effective engineering strategies. Finally, we use the CD-MINE toolset to predict the formation of the novel damage product N-carbamoyl proline, and present mass spectrometric evidence for its presence in Escherichia coli.

Original languageEnglish (US)
Pages (from-to)302-312
Number of pages11
JournalMetabolic Engineering
Volume69
DOIs
StatePublished - Jan 2022

Keywords

  • Computational biochemistry
  • Metabolic engineering
  • Metabolite damage
  • Side-product
  • Spontaneous reaction
  • Synthetic biology

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology

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