Your browser doesn't support javascript.
loading
Phylogenetic classification of natural product biosynthetic gene clusters based on regulatory mechanisms.
Rodriguez-Sanchez, Alberto C; Gónzalez-Salazar, Luz A; Rodriguez-Orduña, Lorena; Cumsille, Ándres; Undabarrena, Agustina; Camara, Beatriz; Sélem-Mojica, Nelly; Licona-Cassani, Cuauhtemoc.
Afiliação
  • Rodriguez-Sanchez AC; Centro de Biotecnologia FEMSA, Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Monterrey, Mexico.
  • Gónzalez-Salazar LA; Centro de Biotecnologia FEMSA, Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Monterrey, Mexico.
  • Rodriguez-Orduña L; Centro de Biotecnologia FEMSA, Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Monterrey, Mexico.
  • Cumsille Á; Centro de Biotecnología Daniel Alkalay, Universidad Técnica Federico Santa María, Valparaíso, Chile.
  • Undabarrena A; Centro de Biotecnología Daniel Alkalay, Universidad Técnica Federico Santa María, Valparaíso, Chile.
  • Camara B; The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark.
  • Sélem-Mojica N; Centro de Biotecnología Daniel Alkalay, Universidad Técnica Federico Santa María, Valparaíso, Chile.
  • Licona-Cassani C; Centro de Ciencias Matemáticas, UNAM, Morelia, Mexico.
Front Microbiol ; 14: 1290473, 2023.
Article em En | MEDLINE | ID: mdl-38029100
The natural products (NPs) biosynthetic gene clusters (BGCs) represent the adapting biochemical toolkit for microorganisms to thrive different microenvironments. Despite their high diversity, particularly at the genomic level, detecting them in a shake-flask is challenging and remains the primary obstacle limiting our access to valuable chemicals. Studying the molecular mechanisms that regulate BGC expression is crucial to design of artificial conditions that derive on their expression. Here, we propose a phylogenetic analysis of regulatory elements linked to biosynthesis gene clusters, to classify BGCs to regulatory mechanisms based on protein domain information. We utilized Hidden Markov Models from the Pfam database to retrieve regulatory elements, such as histidine kinases and transcription factors, from BGCs in the MIBiG database, focusing on actinobacterial strains from three distinct environments: oligotrophic basins, rainforests, and marine environments. Despite the environmental variations, our isolated microorganisms share similar regulatory mechanisms, suggesting the potential to activate new BGCs using activators known to affect previously characterized BGCs.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Microbiol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: México País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Microbiol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: México País de publicação: Suíça