AntiSMASH 6.0: Improving cluster detection and comparison capabilities

Kai Blin; Simon Shaw; Alexander M. Kloosterman; Zach Charlop-Powers; Gilles P. Van Wezel; Marnix H. Medema; Tilmann Weber

doi:10.1093/nar/gkab335

AntiSMASH 6.0: Improving cluster detection and comparison capabilities

Kai Blin^*, Simon Shaw, Alexander M. Kloosterman, Zach Charlop-Powers, Gilles P. Van Wezel, Marnix H. Medema^*, Tilmann Weber^*

^*Corresponding author for this work

Bioinformatics

Research output: Contribution to journal › Article › Academic › peer-review

1504 Citations (Scopus)

Abstract

Many microorganisms produce natural products that form the basis of antimicrobials, antivirals, and other drugs. Genome mining is routinely used to complement screening-based workflows to discover novel natural products. Since 2011, the "antibiotics and secondary metabolite analysis shell - antiSMASH"(https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free-to-use web server and as a standalone tool under an OSI-approved open-source license. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in bacteria and fungi. Here, we present the updated version 6 of antiSMASH. antiSMASH 6 increases the number of supported cluster types from 58 to 71, displays the modular structure of multi-modular BGCs, adds a new BGC comparison algorithm, allows for the integration of results from other prediction tools, and more effectively detects tailoring enzymes in RiPP clusters.

Original language	English
Pages (from-to)	W29-W35
Journal	Nucleic acids research
Volume	49
Issue number	W1
DOIs	https://doi.org/10.1093/nar/gkab335
Publication status	Published - 12 May 2021

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10.1093/nar/gkab335Licence: CC BY

https://edepot.wur.nl/551292Licence: CC BY

DECIPHER: A computational framework to interpret the chemical language of the microbiome
1/12/20 → 30/11/25
Project: EU research project

Cite this

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title = "AntiSMASH 6.0: Improving cluster detection and comparison capabilities",

abstract = "Many microorganisms produce natural products that form the basis of antimicrobials, antivirals, and other drugs. Genome mining is routinely used to complement screening-based workflows to discover novel natural products. Since 2011, the {"}antibiotics and secondary metabolite analysis shell - antiSMASH{"}(https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free-to-use web server and as a standalone tool under an OSI-approved open-source license. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in bacteria and fungi. Here, we present the updated version 6 of antiSMASH. antiSMASH 6 increases the number of supported cluster types from 58 to 71, displays the modular structure of multi-modular BGCs, adds a new BGC comparison algorithm, allows for the integration of results from other prediction tools, and more effectively detects tailoring enzymes in RiPP clusters.",

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doi = "10.1093/nar/gkab335",

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T2 - Improving cluster detection and comparison capabilities

AU - Blin, Kai

AU - Shaw, Simon

AU - Kloosterman, Alexander M.

AU - Charlop-Powers, Zach

AU - Van Wezel, Gilles P.

AU - Medema, Marnix H.

AU - Weber, Tilmann

PY - 2021/5/12

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AB - Many microorganisms produce natural products that form the basis of antimicrobials, antivirals, and other drugs. Genome mining is routinely used to complement screening-based workflows to discover novel natural products. Since 2011, the "antibiotics and secondary metabolite analysis shell - antiSMASH"(https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free-to-use web server and as a standalone tool under an OSI-approved open-source license. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in bacteria and fungi. Here, we present the updated version 6 of antiSMASH. antiSMASH 6 increases the number of supported cluster types from 58 to 71, displays the modular structure of multi-modular BGCs, adds a new BGC comparison algorithm, allows for the integration of results from other prediction tools, and more effectively detects tailoring enzymes in RiPP clusters.

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AntiSMASH 6.0: Improving cluster detection and comparison capabilities

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DECIPHER: A computational framework to interpret the chemical language of the microbiome

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