Global analysis of adenylate-forming enzymes reveals β-lactone biosynthesis pathway in pathogenic Nocardia

Serina L. Robinson, Barbara R. Terlouw, Megan D. Smith, Sacha J. Pidot, Timothy P. Stinear, Marnix H. Medema, Lawrence P. Wackett

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Enzymes that cleave ATP to activate carboxylic acids play essential roles in primary and secondary metabolism in all domains of life. Class I adenylate-forming enzymes share a conserved structural fold but act on a wide range of substrates to catalyze reactions involved in bioluminescence, nonribosomal peptide biosynthesis, fatty acid activation, and β-lactone formation. Despite their metabolic importance, the substrates and functions of the vast majority of adenylate-forming enzymes are unknown without tools available to accurately predict them. Given the crucial roles of adenylate-forming enzymes in biosynthesis, this also severely limits our ability to predict natural product structures from biosynthetic gene clusters. Here we used machine learning to predict adenylate-forming enzyme function and substrate specificity from protein sequences. We built a web-based predictive tool and used it to comprehensively map the biochemical diversity of adenylate-forming enzymes across >50,000 candidate biosynthetic gene clusters in bacterial, fungal, and plant genomes. Ancestral phylogenetic reconstruction and sequence similarity networking of enzymes from these clusters suggested divergent evolution of the adenylate-forming superfamily from a core enzyme scaffold most related to contemporary CoA ligases toward more specialized functions including β-lactone synthetases. Our classifier predicted β-lactone synthetases in uncharacterized biosynthetic gene clusters conserved in >90 different strains of Nocardia. To test our prediction, we purified a candidate β-lactone synthetase from Nocardia brasiliensis and reconstituted the biosynthetic pathway in vitro to link the gene cluster to the β-lactone natural product, nocardiolactone. We anticipate that our machine learning approach will aid in functional classification of enzymes and advance natural product discovery.

Original languageEnglish
Pages (from-to)14826-14839
Number of pages14
JournalThe Journal of biological chemistry
Volume295
Issue number44
DOIs
Publication statusPublished - 30 Oct 2020

Keywords

  • acetyl-CoA synthetase
  • adenylate-forming enzymes
  • bioinformatics
  • coenzyme A (CoA)
  • enzyme catalysis
  • machine learning
  • natural product biosynthesis
  • Nocardia
  • substrate specificity
  • β-lactone synthetases

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