Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases

Abstract Background Fungi are prolific producers of secondary metabolites (SMs), which are bioactive small molecules with important applications in medicine, agriculture and other industries. The backbones of a large proportion of fungal SMs are generated through the action of large, multi-domain me...

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Autores principales:	Cameron L. M. Gilchrist, Yit-Heng Chooi
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Secondary metabolism Domain architecture Polyketide synthase Nonribosomal peptide synthetase Bioinformatics software Biotechnology TP248.13-248.65
Acceso en línea:	https://doaj.org/article/1deb786e1d244213a3f9018d948bdbe3
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spelling	oai:doaj.org-article:1deb786e1d244213a3f9018d948bdbe32021-11-14T12:29:03ZSynthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases10.1186/s40694-021-00120-92054-3085https://doaj.org/article/1deb786e1d244213a3f9018d948bdbe32021-11-01T00:00:00Zhttps://doi.org/10.1186/s40694-021-00120-9https://doaj.org/toc/2054-3085Abstract Background Fungi are prolific producers of secondary metabolites (SMs), which are bioactive small molecules with important applications in medicine, agriculture and other industries. The backbones of a large proportion of fungal SMs are generated through the action of large, multi-domain megasynth(et)ases such as polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs). The structure of these backbones is determined by the domain architecture of the corresponding megasynth(et)ase, and thus accurate annotation and classification of these architectures is an important step in linking SMs to their biosynthetic origins in the genome. Results Here we report synthaser, a Python package leveraging the NCBI’s conserved domain search tool for remote prediction and classification of fungal megasynth(et)ase domain architectures. Synthaser is capable of batch sequence analysis, and produces rich textual output and interactive visualisations which allow for quick assessment of the megasynth(et)ase diversity of a fungal genome. Synthaser uses a hierarchical rule-based classification system, which can be extensively customised by the user through a web application ( http://gamcil.github.io/synthaser ). We show that synthaser provides more accurate domain architecture predictions than comparable tools which rely on curated profile hidden Markov model (pHMM)-based approaches; the utilisation of the NCBI conserved domain database also allows for significantly greater flexibility compared to pHMM approaches. In addition, we demonstrate how synthaser can be applied to large scale genome mining pipelines through the construction of an Aspergillus PKS similarity network. Conclusions Synthaser is an easy to use tool that represents a significant upgrade to previous domain architecture analysis tools. It is freely available under a MIT license from PyPI ( https://pypi.org/project/synthaser ) and GitHub ( https://github.com/gamcil/synthaser ).Cameron L. M. GilchristYit-Heng ChooiBMCarticleSecondary metabolismDomain architecturePolyketide synthaseNonribosomal peptide synthetaseBioinformaticssoftwareBiotechnologyTP248.13-248.65ENFungal Biology and Biotechnology, Vol 8, Iss 1, Pp 1-19 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Secondary metabolism Domain architecture Polyketide synthase Nonribosomal peptide synthetase Bioinformatics software Biotechnology TP248.13-248.65
spellingShingle	Secondary metabolism Domain architecture Polyketide synthase Nonribosomal peptide synthetase Bioinformatics software Biotechnology TP248.13-248.65 Cameron L. M. Gilchrist Yit-Heng Chooi Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases
description	Abstract Background Fungi are prolific producers of secondary metabolites (SMs), which are bioactive small molecules with important applications in medicine, agriculture and other industries. The backbones of a large proportion of fungal SMs are generated through the action of large, multi-domain megasynth(et)ases such as polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs). The structure of these backbones is determined by the domain architecture of the corresponding megasynth(et)ase, and thus accurate annotation and classification of these architectures is an important step in linking SMs to their biosynthetic origins in the genome. Results Here we report synthaser, a Python package leveraging the NCBI’s conserved domain search tool for remote prediction and classification of fungal megasynth(et)ase domain architectures. Synthaser is capable of batch sequence analysis, and produces rich textual output and interactive visualisations which allow for quick assessment of the megasynth(et)ase diversity of a fungal genome. Synthaser uses a hierarchical rule-based classification system, which can be extensively customised by the user through a web application ( http://gamcil.github.io/synthaser ). We show that synthaser provides more accurate domain architecture predictions than comparable tools which rely on curated profile hidden Markov model (pHMM)-based approaches; the utilisation of the NCBI conserved domain database also allows for significantly greater flexibility compared to pHMM approaches. In addition, we demonstrate how synthaser can be applied to large scale genome mining pipelines through the construction of an Aspergillus PKS similarity network. Conclusions Synthaser is an easy to use tool that represents a significant upgrade to previous domain architecture analysis tools. It is freely available under a MIT license from PyPI ( https://pypi.org/project/synthaser ) and GitHub ( https://github.com/gamcil/synthaser ).
format	article
author	Cameron L. M. Gilchrist Yit-Heng Chooi
author_facet	Cameron L. M. Gilchrist Yit-Heng Chooi
author_sort	Cameron L. M. Gilchrist
title	Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases
title_short	Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases
title_full	Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases
title_fullStr	Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases
title_full_unstemmed	Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases
title_sort	synthaser: a cd-search enabled python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases
publisher	BMC
publishDate	2021
url	https://doaj.org/article/1deb786e1d244213a3f9018d948bdbe3
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Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases

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