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Comparative Genomics and Metabolomics in the Genus Nocardia

Using automated genome analysis tools, it is often unclear to what degree genetic variability in homologous biosynthetic pathways relates to structural variation. This hampers strain prioritization and compound identification and can lead to overinterpretation of chemical diversity. Here, we assesse...

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Autores principales: Männle, Daniel, McKinnie, Shaun M. K., Mantri, Shrikant S., Steinke, Katharina, Lu, Zeyin, Moore, Bradley S., Ziemert, Nadine, Kaysser, Leonard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7413640/
https://www.ncbi.nlm.nih.gov/pubmed/32487740
http://dx.doi.org/10.1128/mSystems.00125-20
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author Männle, Daniel
McKinnie, Shaun M. K.
Mantri, Shrikant S.
Steinke, Katharina
Lu, Zeyin
Moore, Bradley S.
Ziemert, Nadine
Kaysser, Leonard
author_facet Männle, Daniel
McKinnie, Shaun M. K.
Mantri, Shrikant S.
Steinke, Katharina
Lu, Zeyin
Moore, Bradley S.
Ziemert, Nadine
Kaysser, Leonard
author_sort Männle, Daniel
collection PubMed
description Using automated genome analysis tools, it is often unclear to what degree genetic variability in homologous biosynthetic pathways relates to structural variation. This hampers strain prioritization and compound identification and can lead to overinterpretation of chemical diversity. Here, we assessed the metabolic potential of Nocardia, an underinvestigated actinobacterial genus that is known to comprise opportunistic human pathogens. Our analysis revealed a plethora of putative biosynthetic gene clusters of various classes, including polyketide, nonribosomal peptide, and terpenoid pathways. Furthermore, we used the highly conserved biosynthetic pathway for nocobactin-like siderophores to investigate how gene cluster differences correlate to structural differences in the produced compounds. Sequence similarity networks generated by BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) showed the presence of several distinct gene cluster families. Metabolic profiling of selected Nocardia strains using liquid chromatography-mass spectrometry (LC-MS) metabolomics data, nuclear magnetic resonance (NMR) spectroscopy, and GNPS (Global Natural Product Social molecular networking) revealed that nocobactin-like biosynthetic gene cluster (BGC) families above a BiG-SCAPE threshold of 70% can be assigned to distinct structural types of nocobactin-like siderophores. IMPORTANCE Our work emphasizes that Nocardia represent a prolific source for natural products rivaling better-characterized genera such as Streptomyces or Amycolatopsis. Furthermore, we showed that large-scale analysis of biosynthetic gene clusters using similarity networks with high stringency allows the distinction and prediction of natural product structural variations. This will facilitate future genomics-driven drug discovery campaigns.
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spelling pubmed-74136402020-08-11 Comparative Genomics and Metabolomics in the Genus Nocardia Männle, Daniel McKinnie, Shaun M. K. Mantri, Shrikant S. Steinke, Katharina Lu, Zeyin Moore, Bradley S. Ziemert, Nadine Kaysser, Leonard mSystems Research Article Using automated genome analysis tools, it is often unclear to what degree genetic variability in homologous biosynthetic pathways relates to structural variation. This hampers strain prioritization and compound identification and can lead to overinterpretation of chemical diversity. Here, we assessed the metabolic potential of Nocardia, an underinvestigated actinobacterial genus that is known to comprise opportunistic human pathogens. Our analysis revealed a plethora of putative biosynthetic gene clusters of various classes, including polyketide, nonribosomal peptide, and terpenoid pathways. Furthermore, we used the highly conserved biosynthetic pathway for nocobactin-like siderophores to investigate how gene cluster differences correlate to structural differences in the produced compounds. Sequence similarity networks generated by BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) showed the presence of several distinct gene cluster families. Metabolic profiling of selected Nocardia strains using liquid chromatography-mass spectrometry (LC-MS) metabolomics data, nuclear magnetic resonance (NMR) spectroscopy, and GNPS (Global Natural Product Social molecular networking) revealed that nocobactin-like biosynthetic gene cluster (BGC) families above a BiG-SCAPE threshold of 70% can be assigned to distinct structural types of nocobactin-like siderophores. IMPORTANCE Our work emphasizes that Nocardia represent a prolific source for natural products rivaling better-characterized genera such as Streptomyces or Amycolatopsis. Furthermore, we showed that large-scale analysis of biosynthetic gene clusters using similarity networks with high stringency allows the distinction and prediction of natural product structural variations. This will facilitate future genomics-driven drug discovery campaigns. American Society for Microbiology 2020-06-02 /pmc/articles/PMC7413640/ /pubmed/32487740 http://dx.doi.org/10.1128/mSystems.00125-20 Text en Copyright © 2020 Männle et al. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Männle, Daniel
McKinnie, Shaun M. K.
Mantri, Shrikant S.
Steinke, Katharina
Lu, Zeyin
Moore, Bradley S.
Ziemert, Nadine
Kaysser, Leonard
Comparative Genomics and Metabolomics in the Genus Nocardia
title Comparative Genomics and Metabolomics in the Genus Nocardia
title_full Comparative Genomics and Metabolomics in the Genus Nocardia
title_fullStr Comparative Genomics and Metabolomics in the Genus Nocardia
title_full_unstemmed Comparative Genomics and Metabolomics in the Genus Nocardia
title_short Comparative Genomics and Metabolomics in the Genus Nocardia
title_sort comparative genomics and metabolomics in the genus nocardia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7413640/
https://www.ncbi.nlm.nih.gov/pubmed/32487740
http://dx.doi.org/10.1128/mSystems.00125-20
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