Sequence-based classification of type II polyketide synthase biosynthetic gene clusters for antiSMASH

Rasmus Villebro, Simon Shaw, Kai Blin, Tilmann Weber*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

The software antiSMASH examines microbial genome data to identify and analyze biosynthetic gene clusters for a wide range of natural products. So far, type II polyketide synthase (PKS) gene clusters could only be identified, but no detailed predictions for type II PKS gene clusters could be provided. In this study, an antiSMASH module for analyzing type II PKS gene clusters has been developed. The module detects genes/proteins in the type II PKS gene cluster involved with polyketide biosynthesis and is able to make predictions about the aromatic polyketide product. Predictions include the putative starter unit, the number of malonyl elongations during polyketide biosynthesis, the putative class and the molecular weight of the product. Furthermore, putative cyclization patterns are predicted. The accuracy of the predictions generated with the new PKSII antiSMASH module was evaluated using a leave-one-out cross validation. The prediction module is available in antiSMASH version 5 at https://antismash.secondarymetabolites.org .
Original languageEnglish
JournalJournal of Industrial Microbiology and Biotechnology
Volume46
Issue number3-4
Pages (from-to)469-475
ISSN1367-5435
DOIs
Publication statusPublished - 2019

Keywords

  • Aromatic polyketides
  • Genome mining
  • Natural product
  • PKS
  • Secondary metabolite
  • Type II polyketide synthases

Cite this

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title = "Sequence-based classification of type II polyketide synthase biosynthetic gene clusters for antiSMASH",
abstract = "The software antiSMASH examines microbial genome data to identify and analyze biosynthetic gene clusters for a wide range of natural products. So far, type II polyketide synthase (PKS) gene clusters could only be identified, but no detailed predictions for type II PKS gene clusters could be provided. In this study, an antiSMASH module for analyzing type II PKS gene clusters has been developed. The module detects genes/proteins in the type II PKS gene cluster involved with polyketide biosynthesis and is able to make predictions about the aromatic polyketide product. Predictions include the putative starter unit, the number of malonyl elongations during polyketide biosynthesis, the putative class and the molecular weight of the product. Furthermore, putative cyclization patterns are predicted. The accuracy of the predictions generated with the new PKSII antiSMASH module was evaluated using a leave-one-out cross validation. The prediction module is available in antiSMASH version 5 at https://antismash.secondarymetabolites.org .",
keywords = "Aromatic polyketides, Genome mining, Natural product, PKS, Secondary metabolite, Type II polyketide synthases",
author = "Rasmus Villebro and Simon Shaw and Kai Blin and Tilmann Weber",
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language = "English",
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pages = "469--475",
journal = "Journal of Industrial Microbiology and Biotechnology",
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Sequence-based classification of type II polyketide synthase biosynthetic gene clusters for antiSMASH. / Villebro, Rasmus; Shaw, Simon; Blin, Kai; Weber, Tilmann.

In: Journal of Industrial Microbiology and Biotechnology, Vol. 46, No. 3-4, 2019, p. 469-475.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Sequence-based classification of type II polyketide synthase biosynthetic gene clusters for antiSMASH

AU - Villebro, Rasmus

AU - Shaw, Simon

AU - Blin, Kai

AU - Weber, Tilmann

PY - 2019

Y1 - 2019

N2 - The software antiSMASH examines microbial genome data to identify and analyze biosynthetic gene clusters for a wide range of natural products. So far, type II polyketide synthase (PKS) gene clusters could only be identified, but no detailed predictions for type II PKS gene clusters could be provided. In this study, an antiSMASH module for analyzing type II PKS gene clusters has been developed. The module detects genes/proteins in the type II PKS gene cluster involved with polyketide biosynthesis and is able to make predictions about the aromatic polyketide product. Predictions include the putative starter unit, the number of malonyl elongations during polyketide biosynthesis, the putative class and the molecular weight of the product. Furthermore, putative cyclization patterns are predicted. The accuracy of the predictions generated with the new PKSII antiSMASH module was evaluated using a leave-one-out cross validation. The prediction module is available in antiSMASH version 5 at https://antismash.secondarymetabolites.org .

AB - The software antiSMASH examines microbial genome data to identify and analyze biosynthetic gene clusters for a wide range of natural products. So far, type II polyketide synthase (PKS) gene clusters could only be identified, but no detailed predictions for type II PKS gene clusters could be provided. In this study, an antiSMASH module for analyzing type II PKS gene clusters has been developed. The module detects genes/proteins in the type II PKS gene cluster involved with polyketide biosynthesis and is able to make predictions about the aromatic polyketide product. Predictions include the putative starter unit, the number of malonyl elongations during polyketide biosynthesis, the putative class and the molecular weight of the product. Furthermore, putative cyclization patterns are predicted. The accuracy of the predictions generated with the new PKSII antiSMASH module was evaluated using a leave-one-out cross validation. The prediction module is available in antiSMASH version 5 at https://antismash.secondarymetabolites.org .

KW - Aromatic polyketides

KW - Genome mining

KW - Natural product

KW - PKS

KW - Secondary metabolite

KW - Type II polyketide synthases

U2 - 10.1007/s10295-018-02131-9

DO - 10.1007/s10295-018-02131-9

M3 - Journal article

VL - 46

SP - 469

EP - 475

JO - Journal of Industrial Microbiology and Biotechnology

JF - Journal of Industrial Microbiology and Biotechnology

SN - 1367-5435

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