antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers

By Kai Blin, Marnix H. Medema, Daniyal Kazempour, Michael A. Fischbach, Rainer Breitling, Eriko Takano, Tilmann Weber. Nucleic Acids Res., 2013

826 citations recorded by the source corpus.

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.

Subfields: Molecular Biology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/e03291f3054e2b04f4d46d5f8a0b919173864250

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Citations in the corpus

Bacteriocins of lactic acid bacteria: extending the family (2016, methodology): “Diverse tools have been created that can be used for the automated screening of bacteriocin gene clusters (Blin et al. 2013; van Heel et al. 2013).”
An Overview on Marine Sponge-Symbiotic Bacteria as Unexhausted Sources for Natural Product Discovery (2017, methodology): “One widely used computational tool used to identify these cryptic biosynthetic gene clusters is antiSMASH (antibiotics and secondary metabolite analysis shell) [227] which allows the input of multiple related sequences, direct analysis of protein sequences, and detection of added classes of speciali”
Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. (2014, background): “…Institute of Biotechnology, Faculty of Life Sciences, University of Manchester, Manchester M1 7DN, UK 12Present address: Max Planck Institute for Marine Microbiology, Celsiusstraße 1, 28359 Bremen, Germany *Correspondence: fischbach@fischbachgroup.org http://dx.doi.org/10.1016/j.cell.2014.06.034”