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/.

New antimicrobials need to be discovered to fight the advance of multidrug-resistant pathogens. A promising approach is the screening for antimicrobial agents naturally produced by living organisms. As an alternative to studying the native producer, it is possible to use genetically tractable microbes as heterologous hosts to aid the discovery process, facilitate product diversification through genetic engineering, and ultimately enable environmentally friendly production. In this mini-review, we summarize the literature from 2017 to 2022 on the application of Escherichia coli and E. coli-based platforms as versatile and powerful systems for the discovery, characterization, and sustainable production of antimicrobials. We highlight recent developments in high-throughput screening methods and genetic engineering approaches that build on the strengths of E. coli as an expression host and that led to the production of antimicrobial compounds. In the last section, we briefly discuss new techniques that have not been applied to discover or engineer antimicrobials yet, but that may be useful for this application in the future.

Table of contentsTwo promiscuous O-methyltransferases from bacteria were found to methylate a panel of catechol substrates towards high-value medicinal compounds. Surprisingly, the non-catechol substrates 5hydroxyflavonoids and o-hydroxybenzoic acids/aldehydes were also methylated at low conversion rates. The crystal structures reveal potential target sites for enzyme engineering for biocatalytic applications.

Oxygen-directed methylation is a ubiquitous tailoring reaction in natural product pathways catalysed by O-methyltransferases (OMTs). Promiscuous OMT biocatalysts are thus a valuable asset in the toolkit for sustainable synthesis and optimization of known bioactive scaffolds for drug development. Here, we characterized two bacterial OMTs fromDesulforomonas acetoxidansandStreptomyces avermitilisin terms of their enzymatic properties and substrate scope and determined their crystal structures. Both OMTs methylated a wide range of catechol-like substrates, including flavonoids, coumarins, hydroxybenzoic acids and their respective aldehydes, an anthraquinone and an indole. One enzyme also accepted a steroid. The product range included pharmaceutically relevant compounds such as (iso)fraxidin, iso(scopoletin), chrysoeriol, alizarin 1-methyl ether and 2-methoxyestradiol. Interestingly, certain non-catechol flavonoids and hydroxybenzoic acids were also methylated. This study expands the knowledge on substrate preference and structural diversity of bacterial catechol OMTs and paves the way for their use in (combinatorial) pathway engineering.