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Comparative Metabologenomics Analysis of Polar Actinomycetes.
Soldatou, Sylvia; Eldjárn, Grímur Hjörleifsson; Ramsay, Andrew; van der Hooft, Justin J J; Hughes, Alison H; Rogers, Simon; Duncan, Katherine R.
Afiliación
  • Soldatou S; Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow G4 0RE, UK.
  • Eldjárn GH; School of Computing Science, University of Glasgow, Glasgow G12 8RZ, UK.
  • Ramsay A; School of Computing Science, University of Glasgow, Glasgow G12 8RZ, UK.
  • van der Hooft JJJ; Bioinformatics Group, Wageningen University, 6708 PB Wageningen, The Netherlands.
  • Hughes AH; Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow G4 0RE, UK.
  • Rogers S; School of Computing Science, University of Glasgow, Glasgow G12 8RZ, UK.
  • Duncan KR; Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow G4 0RE, UK.
Mar Drugs ; 19(2)2021 Feb 10.
Article en En | MEDLINE | ID: mdl-33578887
ABSTRACT
Biosynthetic and chemical datasets are the two major pillars for microbial drug discovery in the omics era. Despite the advancement of analysis tools and platforms for multi-strain metabolomics and genomics, linking these information sources remains a considerable bottleneck in strain prioritisation and natural product discovery. In this study, molecular networking of the 100 metabolite extracts derived from applying the OSMAC approach to 25 Polar bacterial strains, showed growth media specificity and potential chemical novelty was suggested. Moreover, the metabolite extracts were screened for antibacterial activity and promising selective bioactivity against drug-persistent pathogens such as Klebsiella pneumoniae and Acinetobacter baumannii was observed. Genome sequencing data were combined with metabolomics experiments in the recently developed computational approach, NPLinker, which was used to link BGC and molecular features to prioritise strains for further investigation based on biosynthetic and chemical information. Herein, we putatively identified the known metabolites ectoine and chrloramphenicol which, through NPLinker, were linked to their associated BGCs. The metabologenomics approach followed in this study can potentially be applied to any large microbial datasets for accelerating the discovery of new (bioactive) specialised metabolites.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Actinobacteria / Genómica / Metabolómica Idioma: En Revista: Mar Drugs Asunto de la revista: BIOLOGIA / FARMACOLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Actinobacteria / Genómica / Metabolómica Idioma: En Revista: Mar Drugs Asunto de la revista: BIOLOGIA / FARMACOLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Reino Unido