Minimum Information about a Biosynthetic Gene cluster

By Marnix H. Medema, R. Kottmann, Pelin Yilmaz, M. Cummings, J. Biggins, Kai Blin, Irene de Bruijn, Y. Chooi, J. Claesen, R. Coates and 144 more. Nature Chemical Biology, 2015

802 citations recorded by the source corpus.

A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.

Subfields: Molecular Biology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/aebb1191e44ffe450276a05c65a559d713d73798

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Citations in the corpus

A new genome-mining tool redefines the lasso peptide biosynthetic landscape (2016, methodology): “Reconciling the challenges of traditional NP discovery with the opportunities of modern genomics, computational methods represent a promising bridge between genes and molecules 3, 4 .”
antiSMASH 4.0—improvements in chemistry prediction and gene cluster boundary identification (2017, methodology): “…at acceptable levels with the much larger database, antiSMASH now uses the BLAST-compatible DIAMOND algorithm (29) to calculate results for ClusterBlast (against all ± 220,000 BGCs currently detected in NCBI GenBank) and KnownClusterBlast (against experimentally characterized BGCs from MIBiG (14).”
MIBiG 2.0: a repository for biosynthetic gene clusters of known function (2019, methodology): “In 2015, the MIBiG (Minimum Information about a Biosynthetic Gene Cluster) Data Standard and Repository was established, containing 1170 BGC entries that were manually curated through a community effort, the results of which could be accessed via a fairly simple web application (6).”
MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters (2022, methodology): “To this purpose, we developed the Minimum Information about a Biosynthetic Gene cluster (MIBiG) standard and built a database which contains standardised entries for experimentally validated BGCs of known function (7,8).”
BAGEL4: a user-friendly web server to thoroughly mine RiPPs and bacteriocins (2018, methodology): “Next to literature in general specific resources have been used to update our records such as RippMiner (11) and the MIBiG data repository (14).”
antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline (2019, methodology): “As already implemented in previous versions of the software, the KnownClusterBlast functionality searches each identified region against the manually curated MIBiG (38) repository.”
Bacteriocins of lactic acid bacteria: extending the family (2016, background): “The key signatures for an appropriate and systematic definition of novel members of this class have been recently suggested (Medema et al. 2015).”