A standardized workflow for submitting data to the Minimum Information about a Biosynthetic Gene cluster (MIBiG) repository : Prospects for research-based educational experiences
Epstein, Samuel C. ; Charkoudian, Louise K. ; Medema, Marnix H. - \ 2018
Standards in Genomic Sciences 13 (2018)1. - ISSN 1944-3277
Biosynthetic gene cluster - Course-based undergraduate research experience - MIBiG - Natural product - Specialized metabolism
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.
Computational genomics of specialized metabolism : From natural product discovery to microbiome ecology
Medema, Marnix H. - \ 2018
mSystems 3 (2018)2. - ISSN 2379-5077
Bioinformatics - Biosynthetic gene cluster - Microbiome - Natural products - Specialized metabolism
Microbial and plant specialized metabolites, also known as natural products, are key mediators of microbe-microbe and host-microbe interactions and constitute a rich resource for drug development. In the past decade, genome mining has emerged as a prominent strategy for natural product discovery. Initially, such mining was performed on the basis of individual microbial genome sequences. Now, these efforts are being scaled up to fully genome-sequenced strain collections, pan-genomes of bacterial genera, and large sets of metagenome-assembled genomes from microbial communities. The Medema research group aims to play a leading role in these developments by developing and applying computational approaches to identify, classify, and prioritize specialized metabolite biosynthetic gene clusters and pathways and to connect them to specific molecules and microbiome-associated phenotypes. Moreover, we are extending the scope of genome mining from microbes to plants, which will allow more comprehensive interpretation of the chemical language between hosts and microbes in a microbiome setting.
Genome-based exploration of the specialized metabolic capacities of the genus Rhodococcus
Ceniceros, Ana ; Dijkhuizen, Lubbert ; Petrusma, Mirjan ; Medema, Marnix H. - \ 2017
BMC Genomics 18 (2017)1. - ISSN 1471-2164
Biosynthetic gene clusters - Mycobacterium - Natural products - Rhodococcus - Specialized metabolism
Background: Bacteria of the genus Rhodococcus are well known for their ability to degrade a large range of organic compounds. Some rhodococci are free-living, saprophytic bacteria; others are animal and plant pathogens. Recently, several studies have shown that their genomes encode putative pathways for the synthesis of a large number of specialized metabolites that are likely to be involved in microbe-microbe and host-microbe interactions. To systematically explore the specialized metabolic potential of this genus, we here performed a comprehensive analysis of the biosynthetic coding capacity across publicly available rhododoccal genomes, and compared these with those of several Mycobacterium strains as well as that of their mutual close relative Amycolicicoccus subflavus. Results: Comparative genomic analysis shows that most predicted biosynthetic gene cluster families in these strains are clade-specific and lack any homology with gene clusters encoding the production of known natural products. Interestingly, many of these clusters appear to encode the biosynthesis of lipopeptides, which may play key roles in the diverse environments were rhodococci thrive, by acting as biosurfactants, pathogenicity factors or antimicrobials. We also identified several gene cluster families that are universally shared among all three genera, which therefore may have a more 'primary' role in their physiology. Inactivation of these clusters by mutagenesis might help to generate weaker strains that can be used as live vaccines. Conclusions: The genus Rhodococcus thus provides an interesting target for natural product discovery, in view of its large and mostly uncharacterized biosynthetic repertoire, its relatively fast growth and the availability of effective genetic tools for its genomic modification.