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Functional manipulation of biosynthetic enzymes such as cytochrome P450s (or P450s) has attracted great interest in metabolic engineering of plant natural products. Cucurbitacins and mogrosides are plant triterpenoids that share the same backbone but display contrasting bioactivities. This structural and functional diversity of the two metabolites can be manipulated by engineering P450s. However, the functional redesign of P450s through directed evolution (DE) or structure-guided protein engineering is time consuming and challenging, often because of a lack of high-throughput screening methods and crystal structures of P450s. In this study, we used an integrated approach combining computational protein design, evolutionary information, and experimental data-driven optimization to alter the substrate specificity of a multifunctional P450 (CYP87D20) from cucumber. After three rounds of iterative design and evaluation of 96 protein variants, CYP87D20, which is involved in the cucurbitacin C biosynthetic pathway, was successfully transformed into a P450 mono-oxygenase that performs a single specific hydroxylation at C11 of cucurbitadienol. This integrated P450-engineering approach can be further applied to create a de novo pathway to produce mogrol, the precursor of the natural sweetener mogroside, or to alter the structural diversity of plant triterpenoids by functionally manipulating other P450s.

Seed development plays an important role during the life cycle of plants. Linseed flax is an oil crop and the seed is a key organ for fatty acids synthesis and storage. So it is important to understand the molecular mechanism of fatty acid biosynthesis during seed development. In this study, four small RNA libraries from early seeds at 5, 10, 20 and 30 days after flowering (DAF) were constructed and used for high-throughput sequencing to identify microRNAs (miRNAs). A total of 235 miRNAs including 114 known conserved miRNAs and 121 novel miRNAs were identified. The expression patterns of these miRNAs in the four libraries were investigated by bioinformatics and quantitative real-time polymerase chain reaction (qPCR) analysis. It was found that several miRNAs, including Lus-miRNA156a was significantly correlated with seed development process. In order to confirm the actual biological function of Lus-miRNA156a, over-expression vector was constructed and transformed to Arabidopsis. The phenotypes of homozygous transgenic lines showed decreasing of oil content and most of the fatty acid content in seeds as well as late flowering time. The results provided a clue that miRNA156a participating the fatty acid biosynthesis pathway and the detailed molecular mechanism of how it regulates the pathway needs to be further investigated.

The discovery of antibiotics from microorganisms using classic bioactivity screens suffers from heavy labor and high re-discovery rate. Recently, largely uncovered biosynthetic potentials were unveiled by new approaches, such as genetic manipulation of "silent" biosynthetic gene clusters, innovative data acquisition, and processing methods. In this work, a fast and efficient antibiotic identification pipeline based on the MALDI-TOF imaging mass spectrometry was applied to study the antifungal metabolites during the confrontation of two fungal species, Penicillium polonicum and wilt-inducing fungus Fusarium oxysporum. By visualizing the spatial distribution of metabolites directly on the microbial colony and surrounding media, we predicted the antifungal candidates before isolating pure compounds and individually testing their bioactivity, which subsequently guided the identification of target molecules using classic chromatographic methods. Via this procedure, we successfully identified two antifungal metabolites, fructigenine A and B, which belong to indole alkaloid class and were not reported for antifungal activity. Our work assigned new bioactivity to previously reported compounds and more importantly showed the efficiency of this approach towards quick discovery of bioactive compounds, which can help study the vast unexploited synthetic potential of microbial secondary metabolites.

Glycosylation is a prominent strategy to optimize the pharmacokinetic and pharmacodynamic properties of drug-like small-molecule scaffolds by modulating their solubility, stability, bioavailability, and bioactivity. Glycosyltransferases applicable for “sugarcoating” various small-molecule acceptors have been isolated and characterized from plants and bacteria, but remained cryptic from filamentous fungi until recently, despite the frequent use of some fungi for whole-cell biocatalytic glycosylations. Here, we use bioinformatic and genomic tools combined with heterologous expression to identify a glycosyltransferase–methyltransferase (GT–MT) gene pair that encodes a methylglucosylation functional module in the ascomycetous fungus Beauveria bassiana. The GT is the founding member of a family nonorthologous to characterized fungal enzymes. Using combinatorial biosynthetic and biocatalytic platforms, we reveal that this GT is a promiscuous enzyme that efficiently modifies a broad range of drug-like substrates, including polyketides, anthraquinones, flavonoids, and naphthalenes. It yields both O- and N-glucosides with remarkable regio- and stereospecificity, a spectrum not demonstrated for other characterized fungal enzymes. These glucosides are faithfully processed by the dedicated MT to afford 4-O-methyl-glucosides. The resulting “unnatural products” show increased solubility, while representative polyketide methylglucosides also display increased stability against glycoside hydrolysis. Upon methylglucosi-dation, specific polyketides were found to attain cancer cell line-specific antiproliferative or matrix attachment inhibitory activities. These findings will guide genome mining for fungal GTs with novel substrate and product specificities, and empower the efficient combinatorial biosynthesis of a broad range of natural and unnatural glycosides in total biosynthetic or biocatalytic formats.