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antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers
Microbial secondary metabolites are a potent source of antibiotics and other pharmaceuticals. Genome mining of their biosynthetic gene clusters has become a key method to accelerate their identification and characterization. In 2011, we developed antiSMASH, a web-based analysis platform that automat...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3692088/ https://www.ncbi.nlm.nih.gov/pubmed/23737449 http://dx.doi.org/10.1093/nar/gkt449 |
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author | Blin, Kai Medema, Marnix H. Kazempour, Daniyal Fischbach, Michael A. Breitling, Rainer Takano, Eriko Weber, Tilmann |
author_facet | Blin, Kai Medema, Marnix H. Kazempour, Daniyal Fischbach, Michael A. Breitling, Rainer Takano, Eriko Weber, Tilmann |
author_sort | Blin, Kai |
collection | PubMed |
description | Microbial secondary metabolites are a potent source of antibiotics and other pharmaceuticals. Genome mining of their biosynthetic gene clusters has become a key method to accelerate their identification and characterization. In 2011, we developed antiSMASH, a web-based analysis platform that automates this process. Here, we present the highly improved antiSMASH 2.0 release, available at http://antismash.secondarymetabolites.org/. For the new version, antiSMASH was entirely re-designed using a plug-and-play concept that allows easy integration of novel predictor or output modules. antiSMASH 2.0 now supports input of multiple related sequences simultaneously (multi-FASTA/GenBank/EMBL), which allows the analysis of draft genomes comprising multiple contigs. Moreover, direct analysis of protein sequences is now possible. antiSMASH 2.0 has also been equipped with the capacity to detect additional classes of secondary metabolites, including oligosaccharide antibiotics, phenazines, thiopeptides, homo-serine lactones, phosphonates and furans. The algorithm for predicting the core structure of the cluster end product is now also covering lantipeptides, in addition to polyketides and non-ribosomal peptides. The antiSMASH ClusterBlast functionality has been extended to identify sub-clusters involved in the biosynthesis of specific chemical building blocks. The new features currently make antiSMASH 2.0 the most comprehensive resource for identifying and analyzing novel secondary metabolite biosynthetic pathways in microorganisms. |
format | Online Article Text |
id | pubmed-3692088 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-36920882013-06-25 antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers Blin, Kai Medema, Marnix H. Kazempour, Daniyal Fischbach, Michael A. Breitling, Rainer Takano, Eriko Weber, Tilmann Nucleic Acids Res Articles Microbial secondary metabolites are a potent source of antibiotics and other pharmaceuticals. Genome mining of their biosynthetic gene clusters has become a key method to accelerate their identification and characterization. In 2011, we developed antiSMASH, a web-based analysis platform that automates this process. Here, we present the highly improved antiSMASH 2.0 release, available at http://antismash.secondarymetabolites.org/. For the new version, antiSMASH was entirely re-designed using a plug-and-play concept that allows easy integration of novel predictor or output modules. antiSMASH 2.0 now supports input of multiple related sequences simultaneously (multi-FASTA/GenBank/EMBL), which allows the analysis of draft genomes comprising multiple contigs. Moreover, direct analysis of protein sequences is now possible. antiSMASH 2.0 has also been equipped with the capacity to detect additional classes of secondary metabolites, including oligosaccharide antibiotics, phenazines, thiopeptides, homo-serine lactones, phosphonates and furans. The algorithm for predicting the core structure of the cluster end product is now also covering lantipeptides, in addition to polyketides and non-ribosomal peptides. The antiSMASH ClusterBlast functionality has been extended to identify sub-clusters involved in the biosynthesis of specific chemical building blocks. The new features currently make antiSMASH 2.0 the most comprehensive resource for identifying and analyzing novel secondary metabolite biosynthetic pathways in microorganisms. Oxford University Press 2013-07 2013-05-21 /pmc/articles/PMC3692088/ /pubmed/23737449 http://dx.doi.org/10.1093/nar/gkt449 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Articles Blin, Kai Medema, Marnix H. Kazempour, Daniyal Fischbach, Michael A. Breitling, Rainer Takano, Eriko Weber, Tilmann antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers |
title | antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers |
title_full | antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers |
title_fullStr | antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers |
title_full_unstemmed | antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers |
title_short | antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers |
title_sort | antismash 2.0—a versatile platform for genome mining of secondary metabolite producers |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3692088/ https://www.ncbi.nlm.nih.gov/pubmed/23737449 http://dx.doi.org/10.1093/nar/gkt449 |
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