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.

Catalases play a key role in the defense against oxidative stress in bacteria by catalyzing the decomposition of H₂O₂. In addition, catalases are also involved in multiple cellular processes, such as cell development and differentiation, as well as metabolite production. However, little is known about the abundance, diversity, and distribution of catalases in bacteria. In this study, we systematically surveyed and classified the homologs of three catalase families from 2,634 bacterial genomes. It was found that both of the typical catalase and Mn-catalase families could be divided into distinct groups, while the catalase-peroxidase homologs formed a tight family. The typical catalases are rich in all the analyzed bacterial phyla except Chlorobi, in which the catalase-peroxidases are dominant. Catalase-peroxidases are rich in many phyla, but lacking in Deinococcus-Thermus, Spirochetes, and Firmicutes. Mn-catalases are found mainly in Firmicutes and Deinococcus-Thermus, but are rare in many other phyla. Given the fact that catalases were reported to be involved in secondary metabolite biosynthesis in several Streptomyces strains, the distribution of catalases in the genus Streptomyces was given more attention herein. On average, there are 2.99 typical catalases and 0.99 catalase-peroxidases in each Streptomyces genome, while no Mn-catalases were identified. To understand detailed properties of catalases in Streptomyces, we characterized all the five typical catalases from S. rimosus ATCC 10970, the oxytetracycline-producing strain. The five catalases showed typical catalase activity, but possessed different catalytic properties. Our findings contribute to the more detailed classification of catalases and facilitate further studies about their physiological roles in secondary metabolite biosynthesis and other cellular processes, which might facilitate the yield improvement of valuable secondary metabolites in engineered bacteria.

With contributions from the global natural product (NP) research community, and continuing the Raw Data Initiative, this review collects a comprehensive demonstration of the immense scientific value of disseminating raw nuclear magnetic resonance (NMR) data, independently of, and in parallel with, classical publishing outlets.

Nature’s ability to generate diverse natural products from simple building blocks has inspired combinatorial biosynthesis. The knowledge-based approach to combinatorial biosynthesis has allowed the production of designer analogs by rational metabolic pathway engineering. While successful, structural alterations are limited, with designer analogs often produced in compromised titers. The discovery-based approach to combinatorial biosynthesis complements the knowledge-based approach by exploring the vast combinatorial biosynthesis repertoire found in Nature. Here we showcase the discovery-based approach to combinatorial biosynthesis by targeting the domain of unknown function and cysteine lyase domain (DUF–SH) didomain, specific for sulfur incorporation from the leinamycin (LNM) biosynthetic machinery, to discover the LNM family of natural products. By mining bacterial genomes from public databases and the actinomycetes strain collection at The Scripps Research Institute, we discovered 49 potential producers that could be grouped into 18 distinct clades based on phylogenetic analysis of the DUF–SH didomains. Further analysis of the representative genomes from each of the clades identified 28 lnm-type gene clusters. Structural diversities encoded by the LNM-type biosynthetic machineries were predicted based on bioinformatics and confirmed by in vitro characterization of selected adenylation proteins and isolation and structural elucidation of the guangnanmycins and weishanmycins. These findings demonstrate the power of the discovery-based approach to combinatorial biosynthesis for natural product discovery and structural diversity and highlight Nature’s rich biosynthetic repertoire. Comparative analysis of the LNM-type biosynthetic machineries provides outstanding opportunities to dissect Nature’s biosynthetic strategies and apply these findings to combinatorial biosynthesis for natural product discovery and structural diversity.

Significance: This work addresses the molecular basis for interspecies signaling effects of antibiotics, which have been a controversial but potentially significant emerging topic over the last few years. The “pseudo” gamma-butyrolactone (GBL) receptor (i.e., those GBL receptor homologues often found in Streptomyces genomes, but apparently not binding or responding to GBLs), ScbR2, was identified as the receptor of JdB. It has an extraordinary ability to bind and respond to exogenous angucyclines, as well as to be able to directly regulate the biosynthesis of different endogenous antibiotics and the morphological development of Streptomyces . Our findings significantly extend understanding of antibiotic-mediated signaling mechanisms and the ecological impact of antibiotics.