Qualitative metabolomics-based characterization of a phenolic UDP-xylosyltransferase with a broad substrate spectrum from Lentinus brumalis.

Wood-decaying fungi are the major decomposers of plant litter. Heavy sequencing efforts on genomes of wood-decaying fungi have recently been made due to the interest in their lignocellulolytic enzymes; however, most parts of their proteomes remain uncharted. We hypothesized that wood-decaying fungi would possess promiscuous enzymes for detoxifying antifungal phytochemicals remaining in the dead plant bodies, which can be useful biocatalysts. We designed a computational mass spectrometry-based untargeted metabolomics pipeline for the phenotyping of biotransformation and applied it to 264 fungal cultures supplemented with antifungal plant phenolics. The analysis identified the occurrence of diverse reactivities by the tested fungal species. Among those, we focused on O-xylosylation of multiple phenolics by one of the species tested, Lentinus brumalis. By integrating the metabolic phenotyping results with publicly available genome sequences and transcriptome analysis, a UDP-glycosyltransferase designated UGT66A1 was identified and validated as an enzyme catalyzing O-xylosylation with broad substrate specificity. We anticipate that our analytical workflow will accelerate the further characterization of fungal enzymes as promising biocatalysts.

Mass spectrometry data on specialized metabolome of medicinal plants used in East Asian traditional medicine.

Traditional East Asian medicine not only serves as a potential source of drug discovery, but also plays an important role in the healthcare systems of Korea, China, and Japan. Tandem mass spectrometry (MS/MS)-based untargeted metabolomics is a key methodology for high-throughput analysis of the complex chemical compositions of medicinal plants used in traditional East Asian medicine. This Data Descriptor documents the deposition to a public repository of a re-analyzable raw LC-MS/MS dataset of 337 medicinal plants listed in the Korean Pharmacopeia, in addition to a reference spectral library of 223 phytochemicals isolated from medicinal plants. Enhanced by recently developed repository-level data analysis pipelines, this information can serve as a reference dataset for MS/MS-based untargeted metabolomic analysis of plant specialized metabolites.