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Synteruptor: mining genomic islands for non-classical specialized metabolite gene clusters.

Drago HaasMatthieu BarbaCláudia M VicenteŠarká NezbedováAmélie GarénauxStéphanie Bury-MonéJean-Noël LorenziLaurence HôtelLuisa LauretiAnnabelle ThibessardGéraldine Le GoffJamal OuazzaniPierre LeblondBertrand AigleJean-Luc PernodetOlivier LespinetSylvie Lautru
Published in: NAR genomics and bioinformatics (2024)
Microbial specialized metabolite biosynthetic gene clusters (SMBGCs) are a formidable source of natural products of pharmaceutical interest. With the multiplication of genomic data available, very efficient bioinformatic tools for automatic SMBGC detection have been developed. Nevertheless, most of these tools identify SMBGCs based on sequence similarity with enzymes typically involved in specialised metabolism and thus may miss SMBGCs coding for undercharacterised enzymes. Here we present Synteruptor (https://bioi2.i2bc.paris-saclay.fr/synteruptor), a program that identifies genomic islands, known to be enriched in SMBGCs, in the genomes of closely related species. With this tool, we identified a SMBGC in the genome of Streptomyces ambofaciens ATCC23877, undetected by antiSMASH versions prior to antiSMASH 5, and experimentally demonstrated that it directs the biosynthesis of two metabolites, one of which was identified as sphydrofuran. Synteruptor is also a valuable resource for the delineation of individual SMBGCs within antiSMASH regions that may encompass multiple clusters, and for refining the boundaries of these SMBGCs.
Keyphrases
  • copy number
  • genome wide
  • palliative care
  • dna methylation
  • machine learning
  • microbial community
  • ms ms
  • quality improvement
  • genome wide identification
  • big data
  • neural network
  • genetic diversity