Fueled by the explosion of (meta)genomic data, genome mining of specialized metabolites has become a major technology for drug discovery and studying microbiome ecology. In these efforts, computational tools like antiSMASH have played a central role through the analysis of Biosynthetic Gene Clusters (BGCs). Thousands of candidate BGCs from microbial genomes have been identified and stored in public databases. Interpreting the function and novelty of these predicted BGCs requires comparison with a well-documented set of BGCs of known function. The MIBiG (Minimum Information about a Biosynthetic Gene Cluster) Data Standard and Repository was established in 2015 to enable curation and storage of known BGCs. Here, we present MIBiG 2.0, which encompasses major updates to the schema, the data, and the online repository itself. Over the past five years, 851 new BGCs have been added. Additionally, we performed extensive manual data curation of all entries to improve the annotation quality of our repository. We also redesigned the data schema to ensure the compliance of future annotations. Finally, we improved the user experience by adding new features such as query searches and a statistics page, and enabled direct link-outs to chemical structure databases. The repository is accessible online at https://mibig.secondarymetabolites.org/.
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.
Engineering microbial biosynthetic pathways represents a compelling route to gain access to expanded chemical diversity. Carrier proteins (CPs) play a central role in biosynthesis, but the fast motions of CPs make their conformational dynamics difficult to capture using traditional spectroscopic approaches. Here we present a low-resource method to directly reveal carrier protein-substrate interactions. Chemoenzymatic loading of commercially available, alkyne-containing substrates onto CPs enables rapid visualization of the molecular cargo’s local environment using Raman spectroscopy. This method could clarify the foundations of the chain sequestration mechanism, facilitate the rapid characterization of CPs, and enable visualization of the vectoral processing of natural products both in vitro and in vivo.
The strategic redesign of microbial biosynthetic pathways is a compelling route to access molecules of diverse structure and function in a potentially environmentally sustainable fashion. The promise of this approach hinges on an improved understanding of acyl carrier proteins (ACPs), which serve as central hubs in biosynthetic pathways. These small, flexible proteins mediate the transport of molecular building blocks and intermediates to enzymatic partners that extend and tailor the growing natural products. Past combinatorial biosynthesis efforts have failed due to incompatible ACP-enzyme pairings. Herein we report the design of chimeric ACPs with features of the actinorhodin polyketide synthase ACP (ACT) and of the E. coli fatty acid synthase (FAS) ACP (AcpP). We evaluate the ability of the chimeric ACPs to interact with the E. coli FAS ketosynthase FabF, which represents an interaction essential to building the carbon backbone of the synthase molecular output. Given that AcpP interacts with FabF but ACT does not, we sought to exchange modular features of ACT with AcpP to confer functionality with FabF. The interactions of chimeric ACPs with FabF were interrogated using sedimentation velocity experiments, surface plasmon resonance analyses, mechanism-based crosslinking assays, and molecular dynamics simulations. Results suggest that the residues guiding AcpP-FabF compatibility and ACT-FabF incompatibility may reside in the loop I, α-helix II region. These findings can inform the development of strategic secondary element swaps that expand the enzyme compatibility of ACPs across systems and therefore represent a critical step towards the strategic engineering of unnatural natural products.
Therapeutic agents play an increasingly large role in our daily lives, and it is important to study the source of these powerful chemical compounds. Biosynthetic gene clusters found in a diverse set of organisms are capable of manufacturing structurally complex organic compounds in a systematic way, by expressing suites of a enzymes to build the natural products. There is a growing need for a centralized database to connect data for related genes, enzymes, and compounds. This information is currently stored in a siloed fashion, across several repositories, creating an obstacle for modern researchers. The Minimum Information about a Biosynthetic Gene cluster (MIBiG) database aims to solve this problem by utilizing user‐inputted data to translate scientific discoveries into a format that can be analyzed computationally to connect genes to chemistry, understand biosynthetic gene clusters in the context of environmental diversity, and develop computer‐generated gene cluster engineering. As an effort to make MiBIG more accessible to an expanding scientific community, we developed a workflow, Excel templates, a tutorial video, a collection of review literature, and educational tools to facilitate the entry process have all been developed. To verify the effectiveness of the protocol and associated resources, MIBiG was deployed as a course‐based undergraduate research experience (CURE) in an upper‐level undergraduate course.Support or Funding InformationWe would like to acknowledge an NSF CAREER Award #R15GM120704 to Louise K. Charkoudian as a source of funding for this project.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
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