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Genome mining: Prediction of lipopeptides and polyketides from Bacillus and related Firmicutes

Bacillus and related genera in the Bacillales within the Firmicutes harbor a variety of secondary metabolite gene clusters encoding polyketide synthases and non-ribosomal peptide synthetases responsible for remarkable diverse number of polyketides (PKs) and lipopeptides (LPs). These compounds may be...

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Autores principales: Aleti, Gajender, Sessitsch, Angela, Brader, Günter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4397504/
https://www.ncbi.nlm.nih.gov/pubmed/25893081
http://dx.doi.org/10.1016/j.csbj.2015.03.003
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author Aleti, Gajender
Sessitsch, Angela
Brader, Günter
author_facet Aleti, Gajender
Sessitsch, Angela
Brader, Günter
author_sort Aleti, Gajender
collection PubMed
description Bacillus and related genera in the Bacillales within the Firmicutes harbor a variety of secondary metabolite gene clusters encoding polyketide synthases and non-ribosomal peptide synthetases responsible for remarkable diverse number of polyketides (PKs) and lipopeptides (LPs). These compounds may be utilized for medical and agricultural applications. Here, we summarize the knowledge on structural diversity and underlying gene clusters of LPs and PKs in the Bacillales. Moreover, we evaluate by using published prediction tools the potential metabolic capacity of these bacteria to produce type I PKs or LPs. The huge sequence repository of bacterial genomes and metagenomes provides the basis for such genome-mining to reveal the potential for novel structurally diverse secondary metabolites. The otherwise cumbersome task to isolate often unstable PKs and deduce their structure can be streamlined. Using web based prediction tools, we identified here several novel clusters of PKs and LPs from genomes deposited in the database. Our analysis suggests that a substantial fraction of predicted LPs and type I PKs are uncharacterized, and their functions remain to be studied. Known and predicted LPs and PKs occurred in the majority of the plant associated genera, predominantly in Bacillus and Paenibacillus. Surprisingly, many genera from other environments contain no or few of such compounds indicating the role of these secondary metabolites in plant-associated niches.
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spelling pubmed-43975042015-04-17 Genome mining: Prediction of lipopeptides and polyketides from Bacillus and related Firmicutes Aleti, Gajender Sessitsch, Angela Brader, Günter Comput Struct Biotechnol J Mini Review Bacillus and related genera in the Bacillales within the Firmicutes harbor a variety of secondary metabolite gene clusters encoding polyketide synthases and non-ribosomal peptide synthetases responsible for remarkable diverse number of polyketides (PKs) and lipopeptides (LPs). These compounds may be utilized for medical and agricultural applications. Here, we summarize the knowledge on structural diversity and underlying gene clusters of LPs and PKs in the Bacillales. Moreover, we evaluate by using published prediction tools the potential metabolic capacity of these bacteria to produce type I PKs or LPs. The huge sequence repository of bacterial genomes and metagenomes provides the basis for such genome-mining to reveal the potential for novel structurally diverse secondary metabolites. The otherwise cumbersome task to isolate often unstable PKs and deduce their structure can be streamlined. Using web based prediction tools, we identified here several novel clusters of PKs and LPs from genomes deposited in the database. Our analysis suggests that a substantial fraction of predicted LPs and type I PKs are uncharacterized, and their functions remain to be studied. Known and predicted LPs and PKs occurred in the majority of the plant associated genera, predominantly in Bacillus and Paenibacillus. Surprisingly, many genera from other environments contain no or few of such compounds indicating the role of these secondary metabolites in plant-associated niches. Research Network of Computational and Structural Biotechnology 2015-03-24 /pmc/articles/PMC4397504/ /pubmed/25893081 http://dx.doi.org/10.1016/j.csbj.2015.03.003 Text en © 2015 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Mini Review
Aleti, Gajender
Sessitsch, Angela
Brader, Günter
Genome mining: Prediction of lipopeptides and polyketides from Bacillus and related Firmicutes
title Genome mining: Prediction of lipopeptides and polyketides from Bacillus and related Firmicutes
title_full Genome mining: Prediction of lipopeptides and polyketides from Bacillus and related Firmicutes
title_fullStr Genome mining: Prediction of lipopeptides and polyketides from Bacillus and related Firmicutes
title_full_unstemmed Genome mining: Prediction of lipopeptides and polyketides from Bacillus and related Firmicutes
title_short Genome mining: Prediction of lipopeptides and polyketides from Bacillus and related Firmicutes
title_sort genome mining: prediction of lipopeptides and polyketides from bacillus and related firmicutes
topic Mini Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4397504/
https://www.ncbi.nlm.nih.gov/pubmed/25893081
http://dx.doi.org/10.1016/j.csbj.2015.03.003
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