MIBiG 3.0 : a community-driven effort to annotate experimentally validated biosynthetic gene clusters

With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/

Compendium of specialized metabolite biosynthetic diversity encoded in bacterial genomes

Bacterial specialized metabolites are a proven source of antibiotics and cancer therapeutics, but whether we have sampled all the secondary metabolite chemical diversity of cultivated bacteria is not known. We analysed ~ 170,000 bacterial genomes and ~ 47,000 metagenome assembled genomes (MAGs) using a modified BiG-SLiCE and the new clust-o-matic algorithm. We found that only 3% of the natural products potentially encoded in bacterial genomes have been experimentally characterized. We show that the variation of secondary metabolite biosynthetic diversity drops significantly on a genus level, identifying it as an appropriate taxonomic rank for comparison. Equal comparison of genera based on Relative Evolutionary Distance revealed that Streptomyces bacteria encode the largest biosynthetic diversity by far, with Amycolatopsis, Kutzneria and Micromonospora also encoding substantial chemical diversity. Finally we find that several less-well-studied taxa such as Weeksellaceae (Bacteroidota), Myxococcaceae (Myxococcota), Pleurocapsa and Nostocaceae (Cyanobacteria) have potential to produce highly diverse secondary metabolites that warrant further investigation

Author Correction: Compendium of specialized metabolite biosynthetic diversity encoded in bacterial genomes

In the version of this article initially published, for author Satria A. Kaustar, a present address with the Chemistry Department, Scripps Research, was incorrectly included. The affiliation has now been removed from the HTML and PDF versions of the article

Mining Indonesian Microbial Biodiversity for Novel Natural Compounds by a Combined Genome Mining and Molecular Networking Approach

Indonesia is one of the most biodiverse countries in the world and a promising resource for novel natural compound producers. Actinomycetes produce about two thirds of all clinically used antibiotics. Thus, exploiting Indonesia’s microbial diversity for actinomycetes may lead to the discovery of novel antibiotics. A total of 422 actinomycete strains were isolated from three different unique areas in Indonesia and tested for their antimicrobial activity. Nine potent bioactive strains were prioritized for further drug screening approaches. The nine strains were cultivated in different solid and liquid media, and a combination of genome mining analysis and mass spectrometry (MS)-based molecular networking was employed to identify potential novel compounds. By correlating secondary metabolite gene cluster data with MS-based molecular networking results, we identified several gene cluster-encoded biosynthetic products from the nine strains, including naphthyridinomycin, amicetin, echinomycin, tirandamycin, antimycin, and desferrioxamine B. Moreover, 16 putative ion clusters and numerous gene clusters were detected that could not be associated with any known compound, indicating that the strains can produce novel secondary metabolites. Our results demonstrate that sampling of actinomycetes from unique and biodiversity-rich habitats, such as Indonesia, along with a combination of gene cluster networking and molecular networking approaches, accelerates natural product identification

Structures of a non-ribosomal peptide synthetase condensation domain suggest the basis of substrate selectivity

Non-ribosomal peptide synthetases are important enzymes for the assembly of complex peptide natural products. Within these multi-modular assembly lines, condensation domains perform the central function of chain assembly, typically by forming a peptide bond between two peptidyl carrier protein (PCP)-bound substrates. In this work, we report structural snapshots of a condensation domain in complex with an aminoacyl-PCP acceptor substrate. These structures allow the identification of a mechanism that controls access of acceptor substrates to the active site in condensation domains. The structures of this complex also allow us to demonstrate that condensation domain active sites do not contain a distinct pocket to select the side chain of the acceptor substrate during peptide assembly but that residues within the active site motif can instead serve to tune the selectivity of these central biosynthetic domains