A standardized workflow for submitting data to the Minimum Information about a Biosynthetic Gene cluster (MIBiG) repository: prospects for research-based educational experiences

Abstract

Microorganisms utilize complex enzymatic pathways to biosynthesize structurally complex and pharmacologically relevant molecules. These pathways are encoded by gene clusters and are found in a diverse set of organisms. The Minimum Information about a Biosynthetic Gene cluster repository facilitates standardized and centralized storage of experimental data on these gene clusters and their molecular products, by utilizing user-submitted data to translate scientific discoveries into a format that can be analyzed computationally. This accelerates the processes of connecting genes to chemical structures, understanding biosynthetic gene clusters in the context of environmental diversity, and performing computer-assisted design of synthetic gene clusters. Here, we present a Standard Operating Procedure, Excel templates, a tutorial video, and a collection of relevant review literature to support scientists in their efforts to submit data into MiBIG. Further, we provide tools to integrate gene cluster annotation projects into the classroom environment, including workflows and assessment materials.Electronic supplementary materialThe online version of this article (10.1186/s40793-018-0318-y) contains supplementary material, which is available to authorized users.

Uncovering the biosynthetic potential of rare metagenomic DNA using co-occurrence network analysis of targeted sequences

“…Next, we sought to determine the proportion of domain networks that do not correspond to previously described BGCs, and therefore potentially encode novel secondary metabolites. We compared all of the predicted domain networks in this sample to sequences of NRPS and PKS gene clusters reported in publicly available databases (antiSMASH 7 , 10733 sequences) and to a curated collection of functionally characterized BGCs (MIBiG 8 , 1067 sequences). We considered a domain network to be affiliated with a reference BGC if half or more of its domains matched those of a reference with 75% or greater amino acid identity (Fig.…”

Novel bioactive natural products from bacteria via bioprospecting, genome mining and metabolic engineering

“…Our knowledge on the biosynthesis of secondary metabolites by bacteria is constantly expanding, thereby adding new information that connects biosynthetic genes with metabolites of particular chemical classes. In this respect, recently developed standardized database of BGCs, MIBiG, represents an important resource allowing identification of both already characterized BGCs and those that may encode enzymes for assembly of novel secondary metabolites (Epstein et al ., ). Supported by the abovementioned bioinformatics tools and databases, a new concept of so‐called ‘genome mining’ based on analysing bacterial genomes for the presence of various BGCs has been established.…”

Table_4.DOCX

“…KS domains and A domains from predicted PKS and NRPS clusters, respectively, were extracted and translated using the bacterial translation table. For comparison to known NRPS or PKS clusters, the MIBiG database (Epstein et al, 2018) (accessed 06/14/2019, version 1.4) was used to obtain a wellcurated database of KS and A-domains. Prior to comparison, the KS and A domains database was clustered using MMseqs2 (Steinegger and Soding, 2017) to clusters of 75% amino acid similarity to decrease computational requirements for multiple alignment.…”