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Comparative Metabologenomics Analysis of Polar Actinomycetes
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7916644/ https://www.ncbi.nlm.nih.gov/pubmed/33578887 http://dx.doi.org/10.3390/md19020103 |
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author | Soldatou, Sylvia Eldjárn, Grímur Hjörleifsson Ramsay, Andrew van der Hooft, Justin J. J. Hughes, Alison H. Rogers, Simon Duncan, Katherine R. |
author_facet | Soldatou, Sylvia Eldjárn, Grímur Hjörleifsson Ramsay, Andrew van der Hooft, Justin J. J. Hughes, Alison H. Rogers, Simon Duncan, Katherine R. |
author_sort | Soldatou, Sylvia |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7916644 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79166442021-03-01 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. Mar Drugs Article 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. MDPI 2021-02-10 /pmc/articles/PMC7916644/ /pubmed/33578887 http://dx.doi.org/10.3390/md19020103 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Soldatou, Sylvia Eldjárn, Grímur Hjörleifsson Ramsay, Andrew van der Hooft, Justin J. J. Hughes, Alison H. Rogers, Simon Duncan, Katherine R. Comparative Metabologenomics Analysis of Polar Actinomycetes |
title | Comparative Metabologenomics Analysis of Polar Actinomycetes |
title_full | Comparative Metabologenomics Analysis of Polar Actinomycetes |
title_fullStr | Comparative Metabologenomics Analysis of Polar Actinomycetes |
title_full_unstemmed | Comparative Metabologenomics Analysis of Polar Actinomycetes |
title_short | Comparative Metabologenomics Analysis of Polar Actinomycetes |
title_sort | comparative metabologenomics analysis of polar actinomycetes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7916644/ https://www.ncbi.nlm.nih.gov/pubmed/33578887 http://dx.doi.org/10.3390/md19020103 |
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