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/.

The bioprospecting of secondary metabolites from endophytic fungi received great attention in the 1990s and 2000s, when the controversy around taxol production from Taxus spp. endophytes was at its height. Since then, hundreds of reports have described the isolation and characterization of putative secondary metabolites from endophytic fungi. However, only very few studies also report the genetic basis for these phenotypic observations. With low sequencing cost and fast sample turnaround, genetics- and genomics-based approaches have risen to become comprehensive approaches to study natural products from a wide-range of organisms, especially to elucidate underlying biosynthetic pathways. However, in the field of fungal endophyte biology, elucidation of biosynthetic pathways is still a major challenge. As a relatively poorly investigated group of microorganisms, even in the light of recent efforts to sequence more fungal genomes, such as the 1000 Fungal Genomes Project at the Joint Genome Institute (JGI), the basis for bioprospecting of enzymes and pathways from endophytic fungi is still rather slim. In this review we want to discuss the current approaches and tools used to associate phenotype and genotype to elucidate biosynthetic pathways of secondary metabolites in endophytic fungi through the lens of bioprospecting. This review will point out the reported successes and shortcomings, and discuss future directions in sampling, and genetics and genomics of endophytic fungi. Identifying responsible biosynthetic genes for the numerous secondary metabolites isolated from endophytic fungi opens the opportunity to explore the genetic potential of producer strains to discover novel secondary metabolites and enhance secondary metabolite production by metabolic engineering resulting in novel and more affordable medicines and food additives.