UGT93s, Plant UGTs Generating Prenylated Phenolic Glycosides

UGT93s, Plant UGTs Generating Prenylated Phenolic Glycosides | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article UGT93s, Plant UGTs Generating Prenylated Phenolic Glycosides Hongye Li, Jianlin Zou, Bao Nie, Zilong Wang, Meng Zhang, Chunxue Zhao, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7134866/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract • Prenylated phenolic glycosides, such as nodakenin, represent a class of natural products with diverse bioactivities. The metabolic engineering production of these compounds remains largely unexplored, primarily due to the scarcity of efficient UDP-glycosyltransferases (UGTs) capable of catalyzing prenylated phenolic substrates. • Through UGT classification and functional characterization, 14 UGT93s from Angelica decursiva were identified to generate nodakenin utilizing nodakenetin. • Six UGT93s showed catalytic preference toward prenylated phenolics. Through functional characterization of more UGT93s and ancestral sequence reconstruction, this catalytic characteristic was found in most UGT93s. • Two hydrophobic clusters wrapping around the substrates are probably the structural basis for the catalytic activities toward prenylated phenolics. • Functionally characterizing the novel UGT93s provided valuable biosynthetic modules for biomanufacturing. And finding the catalytic preference highlight the UGT93 family as a promising source of biocatalysts for the biosynthesis of prenylated phenolic glycosides, offering new opportunities for their scalable production. Natural Product Chemistry Angelica decursiva biosynthesis glycosyltransferase nodakenin prenylated phenolic glycoside UGT93 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Prenylated phenolics demonstrate impressive bioactivities and health benefits including antioxidation, anti-diabetic activity, obesity prevention, cardioprotection, immunomodulation, neuroprotection and osteoprotection. They show better bioactivities than their phenolic precursors. However, prenylation also lead to lower intestinal absorption and decrease the bioavailability (Chang et al, 2021 ). Prenylated phenolic glycosides, natural products that retain the bioactivities of prenylated phenolics and possess better bioavailability, hold broader prospects for drug development. Furocoumarin glycosides like nodakenin, furochromone glycosides like Prim- O -Glucosylcimifugin (POG) and 5- O -Methylvisamminoside (5- O -MVG) and prenylated flavone glycosides like icariin are typical prenylated phenolic glycosides. They demonstrate prominent anti-dementia (Kim et al, 2007 ), anti-aging (Wang et al, 2023 ), hepatoprotective (Zhang et al, 2024 ) and anticancer activities (He et al, 2025 ), respectively. Natural glycosides are usually biosynthesized through glycosylation reactions catalyzed by uridine diphosphate (UDP)-dependent glycosyltransferases (UGTs; Ross et al, 2001 ). However, glycosylation reactions of prenylated compounds have rarely been realized through biosynthetic approaches. To date, only SdUGT1/2 from Saposhnikovia divaricate (Zou et al, 2025 ), Sb7GT from Scutellaria baicalensis (An et al, 2023 ), Ep7GT and EpGT60 from Epimedium pseudowushanense were reported to glycosylate furochromones or prenylated flavonols (Feng et al, 2019 ; Yao et al, 2022 ). No UGT was reported to glycosylate furocoumarins and other prenylated phenolics yet. This limited the biomanufacturing of many prenylated phenolic glycosides and molecular breeding aim to regulate the content of these compounds in medicinal plants. In this work, we characterized 14 UDP-glycosyltransferases (UGTs) in Angelica decursiva catalyzing O -glucosylation reaction to generate nodakenin. All these UGTs belong to UGT93 family. Moreover, we also found that UGTs in this family showed preference for prenylated phenolics, as two hydrophobic clusters wrap the substrates. Plant UGT93 is therefore recognized as an important source of natural catalysts for glycosylation of prenylated phenolic compounds. Materials and methods Materials and Reagents The fresh plants of Angelica decursiva were collected from Yunnan, China. We sampled leaves, petioles, and roots of Angelica decursiva for both metabolic and RNA-Seq analyses. The chemical reference standards and sugar donors used in this study were purchased from YuanYe Biotechnology Co., Ltd. (Shanghai, China). Methanol and acetonitrile (Thermo Fisher Scientific, USA) were of HPLC grade. The conversion rates were determined by HPLC/UV analysis on an Agilent HPLC 1260 instrument. Samples were separated on a Zorbax SB-C18 column (4.6×250 mm, 5 µm, Agilent, USA). The column temperature was 30°C. To calculate the conversion rates, peak areas of both substrate and product were integrated by Chromeleon® at a certain wavelength. LC/MS analysis was performed on a Q-Exactive quadrupole Orbitrap mass spectrometer (Thermo Fisher Scientific, USA). Total RNA isolation, RNA-Seq, and gene expression quantification The total RNA was extracted with the TranZol™ kit (Transgen Biotech, China) and was used to synthesize the first-stranded complementary DNA (cDNA) with TransScript one-step genomic DNA (gDNA) removal and cDNA synthesis SuperMix (Transgen Biotech, China). The transcriptome data of different tissues of A. decursiva were sequenced at Tsingke Biotechnology Co., Ltd. (Beijing, China). The counts of reads mapping to exons of each gene were calculated by featureCounts (Liao et al, 2014 ). The FPKM value of each gene was calculated in R. Phylogenetic analyses and ancestral sequence reconstruction Amino acid sequences of UGTs in the transcriptome of Angelica decursiva were acquired by Simple HMM Search and Text Block Extract supported by TBtools-II (Chen et al, 2023 ). The phylogenetic tree was constructed using MEGA 11 Software with the Neighbor-Joining method based on ClustalW multiple alignments (Tamura et al, 2021 ). The families of UGTs from A. decursiva were identified by incorporating them with 100 reported UGTs of pUGTdb database representing 22 different plant UGT families (Liu et al, 2023 ). The UGT93s used in phylogeny analysis were acquired from the genome of different apiaceous plants and pUGTdb (Zou et al, 2025 ; Liu et al, 2023 ). Molecular phylogenetic analysis of UGT93s were conducted following the same method mentioned above. The ancestral sequence of UGT93 was reconstructed by GRASP according to the sequence alignment result and the phylogenetic tree (Foley et al, 2022 ). Molecular cloning The full-length candidate genes were amplified from cDNA with TransStart FastPfu DNA Polymerase (Transgen, China). Candidate genes were subcloned into the pET-28a (+) vector (Invitrogen, USA) at BamH I site. Sequences of the primers used in this study are listed in Table S1. Expression of candidate biosynthetic genes The recombinant plasmids for candidate UGTs were chemically transformed into E. coli BL21 (DE3) (Transgen Biotech, China) for heterologous expression. The E. coli cells were grown in 500 mL Luria-Bertani medium (JS0666, JSENB, China) containing kanamycin (50 µg/mL) at 37°C. When OD 600 reached 0.4–0.6, the cells were induced with 0.1 mM IPTG at 18°C. After 16–24 h, the cell pellets were harvested by centrifugation (5,632 × g, 3 min at 4°C), and then resuspended in 10 mL lysis buffer (50 mM NaH 2 PO 4 pH 8.0, 300 mM NaCl, 30 mM imidazole, pH 8.0). Then cells were disrupted by sonication on ice, and the cell debris was removed by centrifugation at 5,632 × g for 45 min at 4°C. The supernatant was collected and loaded onto a pre-equilibrated column (His Trap™ HP, 5 mL, GE Healthcare), and eluted with different concentrations of elution buffer (50 mM NaH 2 PO 4 , pH 8.0, 300 mM NaCl, 30/300 mM imidazole). The purified protein solution was added with approximately 0.5 mL glycerol (25%) and stored at -80°C. Enzyme activity assay The purified proteins were used for functional characterization of UGTs by in vitro enzymatic reactions. The reactions were conducted in 100 µL Tris-HCl buffer (50 mM, pH 8.0) containing 20 µg purified enzymes. The reaction mixtures also include substrates (0.1 mM), and sugar donor (UDP-Glc/Gal/Rha/Ara/Xyl/GlcA/GlcN, 0.5 mM). The reactions continued in a shaking incubator for 2 hours under 37°C. Reactions were terminated by adding 100 µL MeOH. The mixtures were then centrifuged at 21,130 × g for 20 min. The supernatants were analyzed by HPLC and LC/MS. When testing the substrate promiscuities of UGTs, all enzymatic reactions (100 µL reaction mixtures, the same as those used for enzyme activity assay) were conducted in three parallel experiments ( n = 3). The reactions were terminated and centrifuged at 21,130 × g for 20 min for HPLC analysis as described above. The conversion rates in percentage were calculated from peak areas of products and substrates in HPLC/UV chromatograms (Agilent 1260, USA) (The peak area of product divided by the total peak area of product and substrate). Samples were separated on a Zorbax SB-C18 column (4.6×75 mm, 3.5 µm, Agilent, USA). LC/MS analysis was performed on a Q-Exactive hybrid quadrupole-Orbitrap mass spectrometer equipped with a heated ESI source (Thermo Fisher Scientific, USA). The HPLC and LC/MS methods are shown in Table S2. The MS parameters were as follows: sheath gas pressure 45 arb, aux gas pressure 10 arb, discharge voltage 4.5 kV, capillary temperature 350°C. MS 1 resolution was set as 70,000 FWHM, AGC target 1*E 6 , maximum injection time 50 ms, and scan range m / z 100–1,000. MS 2 resolution was set as 17,500 FWHM, AGC target 1*E5, maximum injection time 100 ms, NCE 35. Scaled-up enzymatic reactions To prepare the glucosylated product of 12 , the reaction mixtures contained 10 mL buffer (10 mM PBS, pH 7.4), 0.2 mM 12 , 1.0 mM UDPG and 200 µg purified enzyme of g12439_i0. A total of 25 parallel tube reactions were conducted. The reactions were performed at 30°C overnight and terminated by extraction with 4-fold volume of ethyl acetate. The organic solvent was removed under reduced pressure. The residue was then dissolved in 5.0 mL of methanol. The products were then purified by reversed-phase semi-preparative HPLC. The structures were characterized by HRMS and extensive 1D and 2D NMR analyses. To prepare the glucosylated product of 14 , the reaction mixtures contained 20 mL buffer (10 mM PBS, pH 7.4), 0.1 mM 14 , 0.5 mM UDPG and 125 µg purified enzyme of g12439_i0. A total of 25 parallel tube reactions were conducted. The reactions were performed at 30°C overnight and terminated by extraction with 4-fold volume of ethyl acetate. The extract was treated as described above. Structure analysis of N0 The structures of N0 in complex with different substrates were stimulated by Helixfold (Furui et al , 2025) according to the structure of substrates and the amino acid sequence of N0. The structure rank 1st in each project was used for further analysis. The modelled structures were further used for hydrophobic cluster analysis in ProteinTools (Ferruz et al, 2021 ). The stimulated structures as well as the hydrophobic clusters were analyzed using Pymol (Seeliger et al , 2010). Results Candidate Genes Mining for UGTs Involved in Nodakenin Biosynthesis To study the biosynthesis of nodakenin in Angelica decursiva , we analyzed the distribution of this compound in different organs through HPLC/UV. The root of Angelica decursiva accumulate abundant nodakenin (Fig. 1 a), which indicate UGTs participating in nodakenin biosynthesis should have higher expression levels in it. To screen for the UGTs generating nodakenin, we acquired the transcriptome data of the root, leaf and stem by RNA-seq (NGDC BioProject: PRJCA040560). Then, we characterized 145 UGTs using HMM Search based on HMMER profile PF00201 supported by TBtools II (Chen et al, 2023 ). These UGTs were further classified into 18 families through phylogeny analysis. The family classification follows that in pUGTdb. We found genes in UGT93 family have a relatively higher expression abundance in root (Fig. 1 b; Table S3). Therefore, we paid our attention on the expression and characterization of candidate UGTs in this family. Functional Characterization of UGTs Catalyzing Nodakenetin To find the exact UGT converting nodakenetin ( 1 ) to nodakenin ( 1b ) (Fig. 2 a), we successfully cloned 15 candidate UGT93s out of 18 genes in this family and sub-cloned these genes into pET28a (+) expression vector. By heterogenous expression in Escherichia coli strain BL21 (DE3) and in vitro enzymatic reactions using the purified proteins, we characterized the catalytic functions of these UGTs. Through HPLC/UV analysis, we found that when incubating one of the 14 UGT93s (g18838_i0, g22322_i0, g19500_i1, g18160_i0, g12439_i1, g20190_i0, g16606_i0, g10426_i0, g10426_i1, g15793_i1, g15793_i0, g16556_i0, g19098_i0 and g19098_i1) with 1 and UDP-Glc, a new product can be detected (Fig. 2 b). In LC/MS analysis, the product exhibited a [M + H] + peak at m/z 409 (Fig. 2 c). In the MS/MS spectra, the [M + H] + ion further fragment into a [M-Glc + H] + ion at m/z 247 (Fig. 2 d). This indicate that the product was generated by the glucosylation reaction of 1 . Comparing with standard reference, we identified the product as nodakenin ( 1b ). UGT93s Showed Catalytic Preference for Prenylated Phenolics Given typical furocoumarins and furochromones have similar benzofuran structure, we added SdUGT1 and SdUGT2, the reported UGT93 catalyzing furochromones, in our study to investigate the substrate promiscuities of these UGTs. Four UGT93s with high catalytic efficiency toward 1 were also involved in our study (g12439_i0, g10426_i0, g16556_i0 and g19098_i1). We tested and compared the catalytic abilities of these enzymes using different sugar acceptors and sugar donors (Figs. 3 a, S1 ). Since prenyl substitution is fundamental in the generation of benzofuran structure, we tested more substrates with prenyl group. We noticed that these UGTs showed moderate or high catalytic efficiency toward prenylated substrates or substrates with alkyl groups. However, when catalyzing substrates without alkyl groups, the catalytic abilities drop remarkably. Specifically, when umbelliferone ( 17 ) was fed as substrate, the catalytic activities of the six UGTs were very low. While all these enzymes show increased catalytic efficiencies when catalyzing 7-demethylsuberosin ( 9 ), substrate with an extra prenyl group link to C -6 of umbelliferone. Also, 12 and 13 , with hydroxyl group substituted on alkyl group, are also highly preferred by all six UGT93s comparing with 19 , a compound without alkyl substitution (Figs. 3 a, b, S2 –21). This indicate that the preference toward prenylated phenolic compounds might be a characteristic of UGT93s. These UGTs also showed catalytic abilities to utilize several sugar donors including UDP-Glc/Gal/Rha/Ara/Xyl, while UDP-Glc is highly preferred (Figs S22–31). Since UGTs with catalytic abilities toward prenylated phenolic substrates have rarely been reported, these UGTs can be important source of tool enzymes for glycosylation of alkylated, especially prenylated compounds. Utilizing g12439_i0, we prepared the glucosylated products of 12 and 14 through scaled-up enzymatic reactions and determined the structure of these two new compounds by NMR (Figs S32–39, Table S4, S5). This demonstrates the great potential of these UGTs in expanding the structural diversity of prenylated phenolic glycosides as important biocatalyst. They can also be suitable elements in metabolic engineering to produce various prenylated phenolic glycosides. Catalytic Activities toward Prenylated Phenolics are Shared by Apiaceous UGT93 Since all tested UGT93 showed preference toward prenylated phenolic compounds, we wonder whether the catalytic abilities toward prenylated phenolic compounds are shared by UGT93s in a boarder range of plants. We collected 3136 UGT93s from pUGTdb database. Most of them are from dicots. Among them, apiaceous plants have more UGT93s in average than other species (Fig. S40). We therefore retrieved all annotated UGT93s in nine apiaceous plants ( A . decursiva , Saposhnikovia divaricata (Zou et al, 2025 ), Ligusticum sinense ' Chuanxiong ' (Nie et al, 2024 ), Angelica sinensis (Han et al, 2022 ), Apium graveolens (Song et al, 2021 ), Coriandrum sativum (Song et al, 2020 ), Daucus carota (Iorizzo et al, 2016 ), Bupleurum chinense (Zhang et al, 2022 ) and Centella asiatica (Nawae et al, 2021 )) and constructed a maximum likelihood (ML) phylogeny tree. Six relatively ancestral UGT93s were also included (Liu et al, 2023 ). In this tree, a total of 31 UGTs were selected and expressed in apiaceous plants including those already expressed in A . decursiva . Their catalytic activities toward substrates 1 , 9 and 12 were analyzed. All of these enzymes recognize at least one substrate and generate related glycosylated products. Most of them catalyze all three substrates (Figs. 4 a, 2 b, S41 –48). This indicate the catalytic abilities toward prenylated phenolic compounds are likely to be shared by most UGT93s in apiaceae. We further reconstructed the ancestral sequence of all UGTs in the tree (N0) using Graphical Representation of Ancestral Sequence Predictions (GRASP) and expressed it for further characterization (Foley et al, 2022 ). In enzymatic assay, this ancestral enzyme catalyzes substrate 1 , 9 and 12 efficiently (Fig. 4 b). We therefore postulate that the catalytic activity toward prenylated phenolic compounds may represent a characteristic of UGT93s across apiaceous species, and possibly throughout the plant kingdom. Structural Basis for the Catalytic Abilities toward Prenylated Phenolics Through structural stimulation supported by Helixfold3 (Furui et al , 2025), the structure of N0 in complex with substrate 1 , 9 and 12 were modeled. We further found 11 hydrophobic clusters in N0 using ProteinTools (HC0–10, Fig. 5 a, Table S6; Ferruz et al, 2021 ). Among them, HC3 and HC4 wrap around the prenylated substrates in different dimensions (Fig. 5 a). Considering the hydrophobicity of prenyl group, the hydrophobic environment between HC3 and HC4 could probably enhance the binding stability of prenylated substrates, leading to the catalytic efficiency of UGT93s toward these substrates. To verify the assumption, we mutate residues facing substrates in the hydrophobic cluster to serine, a hydrophilic residue and compared the catalytic activities of mutants and N0. Mutant L140S, V162S, L201S and I204S significantly reduce the catalytic activities of N0 toward prenylated phenolics, especially I204S, which almost lost the catalytic abilities totally (Fig. 5 b, Table S7–9). This informed us that the hydrophobic clusters composed of these residues significantly contribute to the catalytic activities of UGT93s toward prenylated phenolics. Discussion Prenylated phenolic glycosides exhibit remarkable bioactivities derived from their prenylated phenolic moieties while benefiting from the enhanced bioavailability conferred by glycosylation (Brezani et al, 2018 ; Azietaku et al, 2017 ; Abu-Hashem et al , 2014). These properties make them promising candidates for drug development. However, large-scale extraction from natural sources remains economically and environmentally unsustainable (Lv et al, 2019 ). Consequently, significant efforts have been directed toward the biosynthesis of these compounds to circumvent reliance on natural extraction. A critical bottleneck in this endeavor is the limited availability of efficient glycosyltransferases (UGTs) capable of glycosylating diverse prenylated phenolics. Although a few UGTs have been characterized for synthesizing furochromone glucosides and icariin, their substrate scope remains narrow. (Zou et al, 2025 ; Feng et al, 2019 ; Yao et al, 2022 ). In this study, we identified multiple UGT93 family members that efficiently glycosylate furocoumarins and exhibit broad substrate promiscuity toward various prenylated phenolics. Notably, our findings suggest that prenylated phenolic glycosylation activity may be a conserved feature among UGT93s, providing a valuable framework for future enzyme discovery in the biosynthesis of prenylated phenolic glycosides. Despite the impressive bioactivities, natural prenylated phenolic glycosides were not widely found, with few cases including furocoumarins, furochromones and icariin (Chen et al, 2025 ). Naturally, phenolic compounds are unlikely to be substituted by both prenyl and glycosyl, this constrains structural diversity of prenylated phenolic glycosides and impedes medicinal exploration. With the rapid development of combinatorial biosynthesis, this problem can be solved (Zhao et al , 2024). The UGT93s characterized here not only enable the synthesis of known natural products but also serve as modular tools for engineering novel prenylated phenolic glycosides when combined with other biocatalysts. This approach holds great promise for expanding the structural repertoire of these compounds and accelerating drug discovery. Over the past decade, extensive research has characterized UGTs catalyzing various substrates like phenolics, terpenoids and alkaloids from different plants (Sirirungruang et al, 2023 ). Recent efforts have focused on deciphering UGT functional patterns and developing bioinformatic tools for rapid enzyme discovery (Liu et al, 2023 ; Chen et al, 2025 ; Yao et al , 2025). While plant UGTs can be divided into different families according to their evolutionary relationship (Mackenzie et al, 2005 ), the correlation between evolution and enzymatic characteristics remain elusive. In this work, we found the catalytic activities toward prenylated phenolics shared by UGT93s. This indicate that UGTs from the same family likely possess similar catalytic functions and might serve as a new aspect to summarize the function of UGTs. For instance, UGT94s, a sister clade to UGT93s, are frequently associated with triterpene glycosylation (Cui et al, 2024 ; Jiang et al, 2025 ), another prenyl-derived metabolite. Investigating the functional and evolutionary interplay between these families could yield deeper insights into UGT diversification. Furthermore, systematic exploration of UGT family functions may facilitate the discovery or engineering of more efficient and novel biocatalysts. Collectively, we have identified a panel of UGT93s capable of glycosylating prenylated phenolics, including furocoumarins, and demonstrated that this activity is a conserved feature within the family through ancestral sequence reconstruction and structural analysis. These enzymes represent valuable biocatalytic modules for the sustainable production of prenylated phenolic glycosides. Moreover, our family-scale functional and evolutionary analysis provides a blueprint for future investigations into plant UGTs, offering a strategic approach to uncover new enzymes with desired catalytic properties. Declarations Acknowledgments This work was supported by the National Key Research and Development Program of China (No. 2023YFA0914100 to M. Y., and No. 2023YFA0915800 to L. W.), Beijing Natural Science Foundation (No. QY23076 to J.L. Z., and 83001Y0439 to C.X. Z.), National Natural Science Foundation of China (No. 32470245 to L. W., 32400192 to B. N., U24A20358 to B. N.), Shenzhen Science and Technology Program (No. JCYJ20241202130723030 to L. W.). Competing interests None declared. Author contributions MY, and LW planned and designed the research. HYL, JLZ ZLW, MZ, YFY and XRZ performed experiments, HYL, JLZ, BN and XYZ analysed data. HYL, JLZ, BN and MY wrote the manuscript. HYL, JLZ and BN contributed equally. Data availability RNA-Seq raw reads have been deposited in the Genome Sequence Archive at the National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation under BioProject number PRJCA040560 (https://ngdc.cncb.ac.cn/gsub/submit/bioproject/PRJCA040560). Gene sequences have been submitted to GenBase, the accession codes are: C_AA110113.1 (g18838_i0), C_AA110124.1 (g20190_i0), C_AA110135.1 (g16606_i0), C_AA110138.1 (g22322_i0), C_AA110139.1 (g19500_i0), C_AA110140.1 (g18160_i0), C_AA110141.1 (g12439_i0), C_AA110142.1 (g4726_i0), C_AA110143.1 (g10426_i0), C_AA110114.1 (g10426_i1), C_AA110115.1 (g15793_i0), C_AA110116.1 (g15793_i1), C_AA110117.1 (g16556_i0), C_AA110118.1 (g19098_i0), C_AA110119.1 (g19098_i1), C_AA110120.1 (DCAR_625897), C_AA110121.1 (DCAR_519424), C_AA110122.1 (LCX11BG002136), C_AA110123.1 (LCX10BG001765), C_AA110125.1 (LCX10BG001766), C_AA110126.1 (CAS03G001478), C_AA110127.1 (Cs08G01158), C_AA110128.1 (Ag2G01516), C_AA110129.1 (SaDchr08G000892), C_AA110130.1 (SaDchr04G001777_s2), C_AA110131.1 (SaDchr01G001897s1), C_AA110132.1 (SaDchr01G002295), C_AA110133.1 (SaDchr01G002295_s2), C_AA110134.1 (SaDchr01G002295_s3), C_AA110136.1 (SaDchr04G001012), C_AA110137.1 (SaDchr01G001897_s2). References Chang SK, Jiang YM, Yang B (2021) An update of prenylated phenolics: Food sources, chemistry and health benefits. Trends Food Sci Technol 108:197–213 Kim DH, Kim DY, Kim YC, Jung JW, Lee S et al (2007) Nodakenin, a coumarin compound, ameliorates scopolamine-induced memory disruption in mice. Life Sci 80:1944–1950 Wang Y, Jin SS, Luo D, He DQ, Yu M et al (2023) Prim- O -glucosylcimifugin ameliorates aging-impaired endogenous tendon regeneration by rejuvenating senescent tendon stem/progenitor cells. Bone Res 11:784–802 Zhang TW, Zhong Y, Shi Y, Feng CC, Xu L et al (2024) Multi-omics reveals that 5- O -methylvisammioside prevention acute liver injury in mice by regulating the TNF/MAPK/NF-κB/arachidonic acid pathway. Phytomedicine 128:155550 He D, Chen SL, Wang XY, Wen X, Gong CY et al (2025) Icaritin Represses Autophagy to Promote Colorectal Cancer Cell Apoptosis and Sensitized Low-Temperature Photothermal Therapy via Targeting HSP90-TXNDC9 Interactions. Adv Sci (Weinh) 12:e2412953 Ross J, Li Y, Lim E, Bowles DJ (2001) Higher plant glycosyltransferases. Genome Biol 2:REVIEWS3004 Zou JL, Li HY, Nie B, Wang ZL, Zhao CX et al (2025) Complete biosynthetic pathway of furochromones in Saposhnikovia divaricata and its evolutionary mechanism in Apiaceae plants. Nat Commun 16:3109 An T, Lin GY, Liu Y, Qin L, Xu YQ et al (2023) De novo biosynthesis of anticarcinogenic icariin in engineered yeast. Metab Eng 80:207–215 Feng KP, Chen RD, Xie KB, Chen DW, Liu JM et al (2019) Ep7GT, a glycosyltransferase with sugar donor flexibility from Epimedium pseudowushanense , catalyzes the 7- O -glycosylation of baohuoside. Org Biomol Chem 17:8106–8114 Yao Y, Gu JJ, Luo YJ, Wang YY, Pang YZ et al (2022) Genome-wide analysis of UGT gene family identified key gene for the biosynthesis of bioactive flavonol glycosides in Epimedium pubescens Maxim. Synth Syst Biotechnol 7:1095–1107 Liao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30:923–930 Chen CJ, Wu Y, Li JW, Wang X, Zeng ZH et al (2023) TBtools-II: A one for all, all for one bioinformatics platform for biological big-data mining. Mol Plant 16:1733–1742 Tamura K, Stecher G, Kumar S (2021) MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol Biol Evol 38:3022–3027 Liu YQ, Wang Q, Liu XN, Cheng J, Zhang L et al (2023) pUGTdb: A comprehensive database of plant UDP-dependent glycosyltransferases. Mol Plant 16:643–646 Foley G, Mora A, Ross CM, Bottoms S, Sützl L et al (2022) Engineering indel and substitution variants of diverse and ancient enzymes using Graphical Representation of Ancestral Sequence Predictions (GRASP). PLoS Comput Biol 18:e1010633 Furui K, Ohue M (2025) Benchmarking HelixFold3-Predicted Holo Structures for Relative Free Energy Perturbation Calculations. ACS Omega 10:11411–11420 Ferruz N, Schmidt S, Höcker B (2021) ProteinTools: a toolkit to analyze protein structures. Nucleic Acids Res 49:W559–W566 Seeliger D, de Groot BL (2010) Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J Comput Aided Mol Des 24:417–422 Nie B, Chen XQ, Hou ZW, Guo MX, Li C et al (2024) Haplotype-phased genome unveils the butylphthalide biosynthesis and homoploid hybrid origin of Ligusticum chuanxiong . Sci Adv 10:eadj6547 Song XM, Wang JP, Li N, Yu JG, Meng FB et al (2020) Deciphering the high-quality genome sequence of coriander that causes controversial feelings. Plant Biotechnol J 18:1444–1456 Song XM, Sun PC, Yuan JQ, Gong K, Li N et al (2021) The celery genome sequence reveals sequential paleo-polyploidizations, karyotype evolution and resistance gene reduction in apiales. Plant Biotechnol J 19:731–744 Han XX, Li C, Sun SC, Ji JJ, Nie B et al (2022) The chromosome-level genome of female ginseng ( Angelica sinensis ) provides insights into molecular mechanisms and evolution of coumarin biosynthesis. Plant J 112:1224–1237 Iorizzo M, Ellison S, Senalik D, Zeng P, Satapoomin P et al (2016) A high-quality carrot genome assembly provides new insights into carotenoid accumulation and asterid genome evolution. Nat Genet 48:657–666 Zhang QF, Li M, Chen XY, Liu GX, Zhang Z et al (2022) Chromosome-Level Genome Assembly of Bupleurum chinense DC Provides Insights into the Saikosaponin Biosynthesis. Front Genet 13:878431 Nawae W, Yoocha T, Narong N, Paemanee A, Ketngamkum Y et al (2021) Transcriptome sequencing revealed the influence of blue light on the expression levels of light-stress response genes in Centella asiatica . PLoS ONE 16:e0260468 Brezani V, Smejkal K, Hosek J, Tomasova V (2018) Anti-inflammatory Natural Prenylated Phenolic Compounds - Potential Lead Substances. Curr Med Chem 25:1094–1159 Azietaku JT, Ma H, Yu XA, Li J, Oppong MB et al (2017) A review of the ethnopharmacology, phytochemistry and pharmacology of Notopterygium incisum. J Ethnopharmacol 202:241–255 Abu-Hashem AA, El-Shazly M (2015) Synthesis, reactions and biological activities of furochromones: a review. Eur J Med Chem 90:633–665 Lv Y, Marsafari M, Koffas M, Zhou J, Xu P (2019) Optimizing Oleaginous Yeast Cell Factories for Flavonoids and Hydroxylated Flavonoids Biosynthesis. ACS Synth Biol 8:2514–2523 Chen W, Yu ZY, Leng L, Sun D, Liu H et al (2025) Artificial Intelligence-Curated repository of gene-encoded natural diverse components from herbal medicines. Innov. https://doi.org/10.1016/j.xinn.2025.101011 Zhao Y, Duan YT, Zang J, Raadam MH, Pateraki I et al (2025) Structure-Agnostic Bioactivity-Driven Combinatorial Biosynthesis Reveals New Antidiabetic and Anticancer Triterpenoids. Angew Chem Int Ed Engl 64:e202416218 Sirirungruang S, Barnum CR, Tang SN, Shih PM (2023) Plant glycosyltransferases for expanding bioactive glycoside diversity. Nat Prod Rep 40:1170–1180 Chen NH, Jiang ZN, Xie ZK, Zhou S, Zeng T et al (2025) An Effective Computational Strategy for UGTs Catalytic Function Prediction. ACS Synth Biol 14:2064–2080 Mackenzie PI, Bock KW, Burchell B, Guillemette C, Ikushiro S et al (2005) Nomenclature update for the mammalian UDP glycosyltransferase (UGT) gene superfamily. Pharmacogenet Genomics 15:677–685 Cui S, Zhang S, Wang N, Su XD, Luo ZL et al (2024) Structural insights into the catalytic selectivity of glycosyltransferase SgUGT94-289-3 towards mogrosides. Nat Commun 15:6423 Jiang Z, Chen N, Wang HT, Tian YG, Du XY et al (2025) Molecular characterization and structural basis of a promiscuous glycosyltransferase for β-(1,6) oligoglucoside chain glycosides biosynthesis. Plant Biotechnol J 23:2242–2253 Additional Declarations The authors declare no competing interests. Supplementary Files SupportingInformation.docx Supporting information Additional Supporting Information may be found online in the Supporting Information section at the end of the article. Fig. S1 Sugar donors used in this study. Fig. S2 Catalytic activities of UGT93s toward 1. Fig. S3 Catalytic activities of UGT93s toward 2. Fig. S4 Catalytic activities of UGT93s toward 3. Fig. S5 Catalytic activities of UGT93s toward 4. Fig. S6 Catalytic activities of UGT93s toward 5. Fig. S7 Catalytic activities of UGT93s toward 6. Fig. S8 Catalytic activities of UGT93s toward 7. Fig. S9 Catalytic activities of UGT93s toward 8. Fig. S10 Catalytic activities of UGT93s toward 9. Fig. S11 Catalytic activities of UGT93s toward 10. Fig. S12 Catalytic activities of UGT93s toward 11. Fig. S13 Catalytic activities of UGT93s toward 12. Fig. S14 Catalytic activities of UGT93s toward 13. Fig. S15 Catalytic activities of UGT93s toward 14. Fig. S16 Catalytic activities of UGT93s toward 15. Fig. S17 Catalytic activities of UGT93s toward 16. Fig. S18 Catalytic activities of UGT93s toward 17. Fig. S19 Catalytic activities of UGT93s toward 18. Fig. S20 Catalytic activities of UGT93s toward 19. Fig. S21 Catalytic activities of UGT93s toward 20. Fig. S22 Catalytic activities of g16556_i0 utilizing different sugar donors. Fig. S23 Catalytic activities of SdUGT1 utilizing different sugar donors. Fig. S24 Catalytic activities of g12439_i0 utilizing different sugar donors. Fig. S25 Catalytic activities of g10426_i0 utilizing different sugar donors. Fig. S26 Catalytic activities of g19098_i1 utilizing different sugar donors. Fig. S27 Catalytic activities of SdUGT2 utilizing different sugar donors. Fig. S28 MS spectra and MS/MS spectra of product 1c. Fig. S29 MS spectra and MS/MS spectra of product 1d. Fig. S30 MS spectra and MS/MS spectra of product 1e. Fig. S31 MS spectra and MS/MS spectra of product 1f. Fig. S32 1 H NMR spectrum of 12b in DMSO- d 6 (600 MHz). Fig. S33 13 C NMR spectrum of 12b in DMSO- d 6 (150 MHz). Fig. S34 HMBC spectrum of 12b in DMSO- d 6 (600 MHz). Fig. S35 HSQC spectrum of 12b in DMSO- d 6 (600 MHz). Fig. S36 1 H NMR spectrum of 14b in DMSO- d 6 (400 MHz). Fig. S37 13 C NMR spectrum of 14b in DMSO- d 6 (100 MHz). Fig. S38 HMBC spectrum of 14b in DMSO- d 6 (400 MHz). Fig. S39 HSQC spectrum of 14b in DMSO- d 6 (400 MHz). Fig. S40 Distribution of UGT93s in different families. Fig. S41 Catalytic activities of tested UGT93s in Apium graveolens , Coriandrum sativum , Daucus carota and Ligusticum sinense ' Chuanxiong ' toward 1. Fig. S42 Catalytic activities of tested UGT93s in Apium graveolens , Coriandrum sativum , Daucus carota and Ligusticum sinense ' Chuanxiong ' toward 9. Fig. S43 Catalytic activities of tested UGT93s in Apium graveolens , Coriandrum sativum , Daucus carota and Ligusticum sinense ' Chuanxiong ' toward 12. Fig. S44 Catalytic activities of tested UGT93s in Saposhnikovia divaricata toward 1. Fig. S45 Catalytic activities of tested UGT93s in Saposhnikovia divaricata toward 9. Fig. S46 Catalytic activities of tested UGT93s in Saposhnikovia divaricata toward 12. Fig. S47 Catalytic activities of tested UGT93s in Angelica decursiva toward 9. Fig. S48 Catalytic activities of tested UGT93s in Angelica decursiva toward 12. Table S1 PCR primers used in this study. Table S2 HPLC and LC/MS methods used in this study. Table S3 FPKM values of UGTs in Angelica decursiva. Table S4 1 H and 13 C NMR spectra data for 12b. Table S5 1 H and 13 C NMR spectra data for 14b. Table S6 Parameters of hydrophobic clusters in N0. Table S7 Catalytic activities of N0 and its mutants utilizing 1. Table S8 Catalytic activities of N0 and its mutants utilizing 9. Table S9 Catalytic activities of N0 and its mutants utilizing 12. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7134866","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":486047108,"identity":"ed7c4f94-ce8a-4fc9-89a4-ccb5354588c7","order_by":0,"name":"Hongye Li","email":"","orcid":"https://orcid.org/0009-0007-8462-6236","institution":"State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University","correspondingAuthor":false,"prefix":"","firstName":"Hongye","middleName":"","lastName":"Li","suffix":""},{"id":486047109,"identity":"baff3780-7248-4fef-b27b-dd90dfe981dd","order_by":1,"name":"Jianlin 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02:20:08","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-7134866/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7134866/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86929118,"identity":"11208719-1c6f-4ea8-b7fb-35d64517c6f3","added_by":"auto","created_at":"2025-07-17 09:18:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":6000525,"visible":true,"origin":"","legend":"\u003cp\u003eCandidate genes mining of target UGT. (a) Distribution of nodakenin in different organs of \u003cem\u003eAngelica decursiva\u003c/em\u003e. Shown are the picture of \u003cem\u003eAngelica decursiva\u003c/em\u003e and the HPLC/UV spectra of different organs; (b) Classification and expression abundances of UGTs in \u003cem\u003eAngelica decursiva\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7134866/v1/109cbb8608d5431964fb97cb.png"},{"id":86929116,"identity":"45ae8f3b-a1a7-4938-8a36-9132c9829509","added_by":"auto","created_at":"2025-07-17 09:18:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":305472,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional characterizations of UGT93s in \u003cem\u003eAngelica decursiva\u003c/em\u003e. (a) Reactions catalyzed by UGT93s; (b) HPLC/UV analysis of reaction mixtures of candidate UGTs (λ=280 nm); (c) MS spectra of the glucosylated product; (d) MS/MS spectra of the glucosylated product.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7134866/v1/127840b28a616edab120ebaf.png"},{"id":86930019,"identity":"13d48009-c3e4-447c-b13f-50ab95c36938","added_by":"auto","created_at":"2025-07-17 09:26:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":387531,"visible":true,"origin":"","legend":"\u003cp\u003eSubstrate promiscuities of four AdUGT93s and reported SdUGT1/2. (a) Substrates selected for testing the substrate promiscuities; (b) Catalytic activities of g16650_i0, g12439_i0, g10426_i0, g19098_i1, SdUGT1 and SdUGT2 toward different substrates (\u003cem\u003en=3\u003c/em\u003e independent biologically duplications were tested). Catalytic site verified by comparing with reference standards are labeled with blue circle. That verified by NMR are labeled with red circle.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7134866/v1/f19a34e0e325bbc39fafd374.png"},{"id":86929120,"identity":"88231399-0e29-43c5-acfe-eef1d97b1001","added_by":"auto","created_at":"2025-07-17 09:18:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":574267,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution and catalytic activities of UGT93s and ancestral enzyme. (a) ML tree of selected UGT93s. Catalytic activities of 31 enzymes were labeled; (b) Catalytic activities of the ancestral enzyme N0 toward substrate \u003cstrong\u003e1\u003c/strong\u003e, \u003cstrong\u003e9\u003c/strong\u003e and \u003cstrong\u003e12\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7134866/v1/0ff3d50b62f934f84283da2d.png"},{"id":86929127,"identity":"d5677561-46b9-4cd9-9fb9-7453fc269c41","added_by":"auto","created_at":"2025-07-17 09:18:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2935881,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStructural basis of the catalytic activities toward prenylated phenolics. \u003c/strong\u003e(a) Stimulated structure of the ancestral enzyme (N0) and hydrophobic cluster analysis; (b) Catalytic activities of N0 and its mutants toward three prenylated phenolics (Data are mean ± SD, \u003cem\u003en\u003c/em\u003e = 3, three biologically independent samples were tested). N. D.: Not detected. ****\u003cem\u003eP\u003c/em\u003e＜0.0001, ***\u003cem\u003eP\u003c/em\u003e＜0.001, **\u003cem\u003eP\u003c/em\u003e＜0.01 \u003cem\u003evs\u003c/em\u003e. Wild Type (WT).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7134866/v1/d7dcd7ad701ec7ca41d95956.png"},{"id":86930309,"identity":"6832a939-5f05-43c0-bfa0-4838b696e59d","added_by":"auto","created_at":"2025-07-17 09:34:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11977904,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7134866/v1/7a96c052-93be-4222-a6ff-c81a85f3c221.pdf"},{"id":86929124,"identity":"6833361d-134d-4ee0-bb6f-55df54532037","added_by":"auto","created_at":"2025-07-17 09:18:10","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3202512,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupporting information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdditional Supporting Information may be found online in the Supporting Information section at the end of the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S1\u003c/strong\u003e Sugar donors used in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S2\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S3\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e2\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S4\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e3\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S5\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e4\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S6\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e5\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S7\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e6\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S8\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e7\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S9\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e8\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S10\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e9\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S11\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e10\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S12\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e11\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S13\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e12\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S14\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e13\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S15\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e14\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S16\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e15\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S17\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e16\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S18\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e17\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S19\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e18\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S20\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e19\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S21\u003c/strong\u003e Catalytic activities of UGT93s toward \u003cstrong\u003e20\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S22\u003c/strong\u003e Catalytic activities of g16556_i0 utilizing different sugar donors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S23\u003c/strong\u003e Catalytic activities of SdUGT1 utilizing different sugar donors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S24\u003c/strong\u003e Catalytic activities of g12439_i0 utilizing different sugar donors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S25\u003c/strong\u003e Catalytic activities of g10426_i0 utilizing different sugar donors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S26\u003c/strong\u003e Catalytic activities of g19098_i1 utilizing different sugar donors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S27\u003c/strong\u003e Catalytic activities of SdUGT2 utilizing different sugar donors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S28\u003c/strong\u003e MS spectra and MS/MS spectra of product \u003cstrong\u003e1c\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S29\u003c/strong\u003e MS spectra and MS/MS spectra of product \u003cstrong\u003e1d\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S30\u003c/strong\u003e MS spectra and MS/MS spectra of product \u003cstrong\u003e1e\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S31\u003c/strong\u003e MS spectra and MS/MS spectra of product \u003cstrong\u003e1f\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S32\u003c/strong\u003e \u003csup\u003e1\u003c/sup\u003eH NMR spectrum of \u003cstrong\u003e12b\u003c/strong\u003e in DMSO-\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sub\u003e (600 MHz).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S33\u003c/strong\u003e \u003csup\u003e13\u003c/sup\u003eC NMR spectrum of \u003cstrong\u003e12b\u003c/strong\u003e in DMSO-\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sub\u003e (150 MHz).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S34\u003c/strong\u003e HMBC spectrum of \u003cstrong\u003e12b\u003c/strong\u003e in DMSO-\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sub\u003e (600 MHz).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S35\u003c/strong\u003e HSQC spectrum of \u003cstrong\u003e12b\u003c/strong\u003e in DMSO-\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sub\u003e (600 MHz).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S36\u003c/strong\u003e \u003csup\u003e1\u003c/sup\u003eH NMR spectrum of \u003cstrong\u003e14b\u003c/strong\u003e in DMSO-\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sub\u003e (400 MHz).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S37\u003c/strong\u003e \u003csup\u003e13\u003c/sup\u003eC NMR spectrum of \u003cstrong\u003e14b\u003c/strong\u003e in DMSO-\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sub\u003e (100 MHz).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S38\u003c/strong\u003e HMBC spectrum of \u003cstrong\u003e14b\u003c/strong\u003e in DMSO-\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sub\u003e (400 MHz).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S39\u003c/strong\u003e HSQC spectrum of \u003cstrong\u003e14b\u003c/strong\u003e in DMSO-\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sub\u003e (400 MHz).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S40\u003c/strong\u003e Distribution of UGT93s in different families.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S41\u003c/strong\u003e Catalytic activities of tested UGT93s in \u003cem\u003eApium graveolens\u003c/em\u003e, \u003cem\u003eCoriandrum sativum\u003c/em\u003e, \u003cem\u003eDaucus carota\u003c/em\u003e and \u003cem\u003eLigusticum sinense \u003c/em\u003e'\u003cem\u003eChuanxiong\u003c/em\u003e' toward \u003cstrong\u003e1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S42\u003c/strong\u003e Catalytic activities of tested UGT93s in \u003cem\u003eApium graveolens\u003c/em\u003e, \u003cem\u003eCoriandrum sativum\u003c/em\u003e, \u003cem\u003eDaucus carota\u003c/em\u003e and \u003cem\u003eLigusticum sinense \u003c/em\u003e'\u003cem\u003eChuanxiong\u003c/em\u003e' toward \u003cstrong\u003e9\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S43\u003c/strong\u003e Catalytic activities of tested UGT93s in \u003cem\u003eApium graveolens\u003c/em\u003e, \u003cem\u003eCoriandrum sativum\u003c/em\u003e, \u003cem\u003eDaucus carota\u003c/em\u003e and \u003cem\u003eLigusticum sinense \u003c/em\u003e'\u003cem\u003eChuanxiong\u003c/em\u003e' toward \u003cstrong\u003e12\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S44\u003c/strong\u003e Catalytic activities of tested UGT93s in \u003cem\u003eSaposhnikovia divaricata\u003c/em\u003e toward \u003cstrong\u003e1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S45\u003c/strong\u003e Catalytic activities of tested UGT93s in \u003cem\u003eSaposhnikovia divaricata\u003c/em\u003e toward \u003cstrong\u003e9\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S46\u003c/strong\u003e Catalytic activities of tested UGT93s in \u003cem\u003eSaposhnikovia divaricata\u003c/em\u003e toward \u003cstrong\u003e12\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S47\u003c/strong\u003e Catalytic activities of tested UGT93s in \u003cem\u003eAngelica decursiva\u003c/em\u003e toward \u003cstrong\u003e9\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S48\u003c/strong\u003e Catalytic activities of tested UGT93s in \u003cem\u003eAngelica decursiva\u003c/em\u003e toward \u003cstrong\u003e12\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S1 \u003c/strong\u003ePCR primers used in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S2\u003c/strong\u003e HPLC and LC/MS methods used in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S3\u003c/strong\u003e FPKM values of UGTs in \u003cem\u003eAngelica decursiva.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S4\u003c/strong\u003e \u003csup\u003e1\u003c/sup\u003eH and \u003csup\u003e13\u003c/sup\u003eC NMR spectra data for \u003cstrong\u003e12b\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S5\u003c/strong\u003e \u003csup\u003e1\u003c/sup\u003eH and \u003csup\u003e13\u003c/sup\u003eC NMR spectra data for \u003cstrong\u003e14b\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S6\u003c/strong\u003e Parameters of hydrophobic clusters in N0.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S7\u003c/strong\u003e Catalytic activities of N0 and its mutants utilizing \u003cstrong\u003e1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S8\u003c/strong\u003e Catalytic activities of N0 and its mutants utilizing \u003cstrong\u003e9\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S9\u003c/strong\u003e Catalytic activities of N0 and its mutants utilizing \u003cstrong\u003e12\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"SupportingInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-7134866/v1/922fb46f8f0eca480e94fa44.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eUGT93s, Plant UGTs Generating Prenylated Phenolic Glycosides\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePrenylated phenolics demonstrate impressive bioactivities and health benefits including antioxidation, anti-diabetic activity, obesity prevention, cardioprotection, immunomodulation, neuroprotection and osteoprotection. They show better bioactivities than their phenolic precursors. However, prenylation also lead to lower intestinal absorption and decrease the bioavailability (Chang et al, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Prenylated phenolic glycosides, natural products that retain the bioactivities of prenylated phenolics and possess better bioavailability, hold broader prospects for drug development. Furocoumarin glycosides like nodakenin, furochromone glycosides like Prim-\u003cem\u003eO\u003c/em\u003e-Glucosylcimifugin (POG) and 5-\u003cem\u003eO\u003c/em\u003e-Methylvisamminoside (5-\u003cem\u003eO\u003c/em\u003e-MVG) and prenylated flavone glycosides like icariin are typical prenylated phenolic glycosides. They demonstrate prominent anti-dementia (Kim et al, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), anti-aging (Wang et al, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), hepatoprotective (Zhang et al, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and anticancer activities (He et al, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), respectively. Natural glycosides are usually biosynthesized through glycosylation reactions catalyzed by uridine diphosphate (UDP)-dependent glycosyltransferases (UGTs; Ross et al, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). However, glycosylation reactions of prenylated compounds have rarely been realized through biosynthetic approaches. To date, only SdUGT1/2 from \u003cem\u003eSaposhnikovia divaricate\u003c/em\u003e (Zou et al, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), Sb7GT from \u003cem\u003eScutellaria baicalensis\u003c/em\u003e (An et al, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Ep7GT and EpGT60 from \u003cem\u003eEpimedium pseudowushanense\u003c/em\u003e were reported to glycosylate furochromones or prenylated flavonols (Feng et al, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yao et al, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). No UGT was reported to glycosylate furocoumarins and other prenylated phenolics yet. This limited the biomanufacturing of many prenylated phenolic glycosides and molecular breeding aim to regulate the content of these compounds in medicinal plants. In this work, we characterized 14 UDP-glycosyltransferases (UGTs) in \u003cem\u003eAngelica decursiva\u003c/em\u003e catalyzing \u003cem\u003eO\u003c/em\u003e-glucosylation reaction to generate nodakenin. All these UGTs belong to UGT93 family. Moreover, we also found that UGTs in this family showed preference for prenylated phenolics, as two hydrophobic clusters wrap the substrates. Plant UGT93 is therefore recognized as an important source of natural catalysts for glycosylation of prenylated phenolic compounds.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cb\u003eMaterials and Reagents\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe fresh plants of \u003cem\u003eAngelica decursiva\u003c/em\u003e were collected from Yunnan, China. We sampled leaves, petioles, and roots of \u003cem\u003eAngelica decursiva\u003c/em\u003e for both metabolic and RNA-Seq analyses.\u003c/p\u003e\u003cp\u003eThe chemical reference standards and sugar donors used in this study were purchased from YuanYe Biotechnology Co., Ltd. (Shanghai, China). Methanol and acetonitrile (Thermo Fisher Scientific, USA) were of HPLC grade. The conversion rates were determined by HPLC/UV analysis on an Agilent HPLC 1260 instrument. Samples were separated on a Zorbax SB-C18 column (4.6\u0026times;250 mm, 5 \u0026micro;m, Agilent, USA). The column temperature was 30\u0026deg;C. To calculate the conversion rates, peak areas of both substrate and product were integrated by Chromeleon\u0026reg; at a certain wavelength. LC/MS analysis was performed on a Q-Exactive quadrupole Orbitrap mass spectrometer (Thermo Fisher Scientific, USA).\u003c/p\u003e\u003cp\u003e\u003cb\u003eTotal RNA isolation, RNA-Seq, and gene expression quantification\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe total RNA was extracted with the TranZol\u0026trade; kit (Transgen Biotech, China) and was used to synthesize the first-stranded complementary DNA (cDNA) with TransScript one-step genomic DNA (gDNA) removal and cDNA synthesis SuperMix (Transgen Biotech, China). The transcriptome data of different tissues of \u003cem\u003eA. decursiva\u003c/em\u003e were sequenced at Tsingke Biotechnology Co., Ltd. (Beijing, China). The counts of reads mapping to exons of each gene were calculated by featureCounts (Liao et al, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The FPKM value of each gene was calculated in R.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhylogenetic analyses and ancestral sequence reconstruction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmino acid sequences of UGTs in the transcriptome of \u003cem\u003eAngelica decursiva\u003c/em\u003e were acquired by Simple HMM Search and Text Block Extract supported by TBtools-II (Chen et al, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The phylogenetic tree was constructed using MEGA 11 Software with the Neighbor-Joining method based on ClustalW multiple alignments (Tamura et al, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The families of UGTs from \u003cem\u003eA. decursiva\u003c/em\u003e were identified by incorporating them with 100 reported UGTs of pUGTdb database representing 22 different plant UGT families (Liu et al, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe UGT93s used in phylogeny analysis were acquired from the genome of different apiaceous plants and pUGTdb (Zou et al, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Liu et al, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Molecular phylogenetic analysis of UGT93s were conducted following the same method mentioned above. The ancestral sequence of UGT93 was reconstructed by GRASP according to the sequence alignment result and the phylogenetic tree (Foley et al, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMolecular cloning\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe full-length candidate genes were amplified from cDNA with TransStart FastPfu DNA Polymerase (Transgen, China). Candidate genes were subcloned into the pET-28a (+) vector (Invitrogen, USA) at BamH I site. Sequences of the primers used in this study are listed in Table S1.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExpression of candidate biosynthetic genes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe recombinant plasmids for candidate UGTs were chemically transformed into \u003cem\u003eE. coli\u003c/em\u003e BL21 (DE3) (Transgen Biotech, China) for heterologous expression. The \u003cem\u003eE. coli\u003c/em\u003e cells were grown in 500 mL Luria-Bertani medium (JS0666, JSENB, China) containing kanamycin (50 \u0026micro;g/mL) at 37\u0026deg;C. When OD\u003csub\u003e600\u003c/sub\u003e reached 0.4\u0026ndash;0.6, the cells were induced with 0.1 mM IPTG at 18\u0026deg;C. After 16\u0026ndash;24 h, the cell pellets were harvested by centrifugation (5,632 \u0026times; g, 3 min at 4\u0026deg;C), and then resuspended in 10 mL lysis buffer (50 mM NaH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e pH 8.0, 300 mM NaCl, 30 mM imidazole, pH 8.0). Then cells were disrupted by sonication on ice, and the cell debris was removed by centrifugation at 5,632 \u0026times; g for 45 min at 4\u0026deg;C. The supernatant was collected and loaded onto a pre-equilibrated column (His Trap\u0026trade; HP, 5 mL, GE Healthcare), and eluted with different concentrations of elution buffer (50 mM NaH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, pH 8.0, 300 mM NaCl, 30/300 mM imidazole). The purified protein solution was added with approximately 0.5 mL glycerol (25%) and stored at -80\u0026deg;C.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEnzyme activity assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe purified proteins were used for functional characterization of UGTs by \u003cem\u003ein vitro\u003c/em\u003e enzymatic reactions. The reactions were conducted in 100 \u0026micro;L Tris-HCl buffer (50 mM, pH 8.0) containing 20 \u0026micro;g purified enzymes. The reaction mixtures also include substrates (0.1 mM), and sugar donor (UDP-Glc/Gal/Rha/Ara/Xyl/GlcA/GlcN, 0.5 mM). The reactions continued in a shaking incubator for 2 hours under 37\u0026deg;C. Reactions were terminated by adding 100 \u0026micro;L MeOH. The mixtures were then centrifuged at 21,130 \u0026times; g for 20 min. The supernatants were analyzed by HPLC and LC/MS.\u003c/p\u003e\u003cp\u003eWhen testing the substrate promiscuities of UGTs, all enzymatic reactions (100 \u0026micro;L reaction mixtures, the same as those used for enzyme activity assay) were conducted in three parallel experiments (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3). The reactions were terminated and centrifuged at 21,130 \u0026times; g for 20 min for HPLC analysis as described above. The conversion rates in percentage were calculated from peak areas of products and substrates in HPLC/UV chromatograms (Agilent 1260, USA) (The peak area of product divided by the total peak area of product and substrate).\u003c/p\u003e\u003cp\u003eSamples were separated on a Zorbax SB-C18 column (4.6\u0026times;75 mm, 3.5 \u0026micro;m, Agilent, USA). LC/MS analysis was performed on a Q-Exactive hybrid quadrupole-Orbitrap mass spectrometer equipped with a heated ESI source (Thermo Fisher Scientific, USA). The HPLC and LC/MS methods are shown in Table S2. The MS parameters were as follows: sheath gas pressure 45 arb, aux gas pressure 10 arb, discharge voltage 4.5 kV, capillary temperature 350\u0026deg;C. MS\u003csup\u003e1\u003c/sup\u003e resolution was set as 70,000 FWHM, AGC target 1*E\u003csup\u003e6\u003c/sup\u003e, maximum injection time 50 ms, and scan range \u003cem\u003em\u003c/em\u003e/\u003cem\u003ez\u003c/em\u003e 100\u0026ndash;1,000. MS\u003csup\u003e2\u003c/sup\u003e resolution was set as 17,500 FWHM, AGC target 1*E5, maximum injection time 100 ms, NCE 35.\u003c/p\u003e\u003cp\u003e\u003cb\u003eScaled-up enzymatic reactions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo prepare the glucosylated product of \u003cb\u003e12\u003c/b\u003e, the reaction mixtures contained 10 mL buffer (10 mM PBS, pH 7.4), 0.2 mM \u003cb\u003e12\u003c/b\u003e, 1.0 mM UDPG and 200 \u0026micro;g purified enzyme of g12439_i0. A total of 25 parallel tube reactions were conducted. The reactions were performed at 30\u0026deg;C overnight and terminated by extraction with 4-fold volume of ethyl acetate. The organic solvent was removed under reduced pressure. The residue was then dissolved in 5.0 mL of methanol. The products were then purified by reversed-phase semi-preparative HPLC. The structures were characterized by HRMS and extensive 1D and 2D NMR analyses.\u003c/p\u003e\u003cp\u003eTo prepare the glucosylated product of \u003cb\u003e14\u003c/b\u003e, the reaction mixtures contained 20 mL buffer (10 mM PBS, pH 7.4), 0.1 mM \u003cb\u003e14\u003c/b\u003e, 0.5 mM UDPG and 125 \u0026micro;g purified enzyme of g12439_i0. A total of 25 parallel tube reactions were conducted. The reactions were performed at 30\u0026deg;C overnight and terminated by extraction with 4-fold volume of ethyl acetate. The extract was treated as described above.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStructure analysis of N0\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe structures of N0 in complex with different substrates were stimulated by Helixfold (Furui \u003cem\u003eet al\u003c/em\u003e, 2025) according to the structure of substrates and the amino acid sequence of N0. The structure rank 1st in each project was used for further analysis. The modelled structures were further used for hydrophobic cluster analysis in ProteinTools (Ferruz et al, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The stimulated structures as well as the hydrophobic clusters were analyzed using Pymol (Seeliger \u003cem\u003eet al\u003c/em\u003e, 2010).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eCandidate Genes Mining for UGTs Involved in Nodakenin Biosynthesis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo study the biosynthesis of nodakenin in \u003cem\u003eAngelica decursiva\u003c/em\u003e, we analyzed the distribution of this compound in different organs through HPLC/UV. The root of \u003cem\u003eAngelica decursiva\u003c/em\u003e accumulate abundant nodakenin (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea), which indicate UGTs participating in nodakenin biosynthesis should have higher expression levels in it. To screen for the UGTs generating nodakenin, we acquired the transcriptome data of the root, leaf and stem by RNA-seq (NGDC BioProject: PRJCA040560). Then, we characterized 145 UGTs using HMM Search based on HMMER profile PF00201 supported by TBtools II (Chen et al, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These UGTs were further classified into 18 families through phylogeny analysis. The family classification follows that in pUGTdb. We found genes in UGT93 family have a relatively higher expression abundance in root (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb; Table S3). Therefore, we paid our attention on the expression and characterization of candidate UGTs in this family.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFunctional Characterization of UGTs Catalyzing Nodakenetin\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo find the exact UGT converting nodakenetin (\u003cb\u003e1\u003c/b\u003e) to nodakenin (\u003cb\u003e1b\u003c/b\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea), we successfully cloned 15 candidate UGT93s out of 18 genes in this family and sub-cloned these genes into pET28a (+) expression vector. By heterogenous expression in \u003cem\u003eEscherichia coli\u003c/em\u003e strain BL21 (DE3) and \u003cem\u003ein vitro\u003c/em\u003e enzymatic reactions using the purified proteins, we characterized the catalytic functions of these UGTs. Through HPLC/UV analysis, we found that when incubating one of the 14 UGT93s (g18838_i0, g22322_i0, g19500_i1, g18160_i0, g12439_i1, g20190_i0, g16606_i0, g10426_i0, g10426_i1, g15793_i1, g15793_i0, g16556_i0, g19098_i0 and g19098_i1) with \u003cb\u003e1\u003c/b\u003e and UDP-Glc, a new product can be detected (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). In LC/MS analysis, the product exhibited a [M\u0026thinsp;+\u0026thinsp;H]\u003csup\u003e+\u003c/sup\u003e peak at \u003cem\u003em/z\u003c/em\u003e 409 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). In the MS/MS spectra, the [M\u0026thinsp;+\u0026thinsp;H]\u003csup\u003e+\u003c/sup\u003e ion further fragment into a [M-Glc\u0026thinsp;+\u0026thinsp;H]\u003csup\u003e+\u003c/sup\u003e ion at \u003cem\u003em/z\u003c/em\u003e 247 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). This indicate that the product was generated by the glucosylation reaction of \u003cb\u003e1\u003c/b\u003e. Comparing with standard reference, we identified the product as nodakenin (\u003cb\u003e1b\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eUGT93s Showed Catalytic Preference for Prenylated Phenolics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGiven typical furocoumarins and furochromones have similar benzofuran structure, we added SdUGT1 and SdUGT2, the reported UGT93 catalyzing furochromones, in our study to investigate the substrate promiscuities of these UGTs. Four UGT93s with high catalytic efficiency toward \u003cb\u003e1\u003c/b\u003e were also involved in our study (g12439_i0, g10426_i0, g16556_i0 and g19098_i1). We tested and compared the catalytic abilities of these enzymes using different sugar acceptors and sugar donors (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Since prenyl substitution is fundamental in the generation of benzofuran structure, we tested more substrates with prenyl group. We noticed that these UGTs showed moderate or high catalytic efficiency toward prenylated substrates or substrates with alkyl groups. However, when catalyzing substrates without alkyl groups, the catalytic abilities drop remarkably. Specifically, when umbelliferone (\u003cb\u003e17\u003c/b\u003e) was fed as substrate, the catalytic activities of the six UGTs were very low. While all these enzymes show increased catalytic efficiencies when catalyzing 7-demethylsuberosin (\u003cb\u003e9\u003c/b\u003e), substrate with an extra prenyl group link to \u003cem\u003eC\u003c/em\u003e-6 of umbelliferone. Also, \u003cb\u003e12\u003c/b\u003e and \u003cb\u003e13\u003c/b\u003e, with hydroxyl group substituted on alkyl group, are also highly preferred by all six UGT93s comparing with \u003cb\u003e19\u003c/b\u003e, a compound without alkyl substitution (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, b, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u0026ndash;21). This indicate that the preference toward prenylated phenolic compounds might be a characteristic of UGT93s. These UGTs also showed catalytic abilities to utilize several sugar donors including UDP-Glc/Gal/Rha/Ara/Xyl, while UDP-Glc is highly preferred (Figs S22\u0026ndash;31). Since UGTs with catalytic abilities toward prenylated phenolic substrates have rarely been reported, these UGTs can be important source of tool enzymes for glycosylation of alkylated, especially prenylated compounds. Utilizing g12439_i0, we prepared the glucosylated products of \u003cb\u003e12\u003c/b\u003e and \u003cb\u003e14\u003c/b\u003e through scaled-up enzymatic reactions and determined the structure of these two new compounds by NMR (Figs S32\u0026ndash;39, Table S4, S5). This demonstrates the great potential of these UGTs in expanding the structural diversity of prenylated phenolic glycosides as important biocatalyst. They can also be suitable elements in metabolic engineering to produce various prenylated phenolic glycosides.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCatalytic Activities toward Prenylated Phenolics are Shared by Apiaceous UGT93\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSince all tested UGT93 showed preference toward prenylated phenolic compounds, we wonder whether the catalytic abilities toward prenylated phenolic compounds are shared by UGT93s in a boarder range of plants. We collected 3136 UGT93s from pUGTdb database. Most of them are from dicots. Among them, apiaceous plants have more UGT93s in average than other species (Fig. S40). We therefore retrieved all annotated UGT93s in nine apiaceous plants (\u003cem\u003eA\u003c/em\u003e. \u003cem\u003edecursiva\u003c/em\u003e, \u003cem\u003eSaposhnikovia divaricata\u003c/em\u003e (Zou et al, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), \u003cem\u003eLigusticum sinense\u003c/em\u003e '\u003cem\u003eChuanxiong\u003c/em\u003e' (Nie et al, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), \u003cem\u003eAngelica sinensis\u003c/em\u003e (Han et al, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), \u003cem\u003eApium graveolens\u003c/em\u003e (Song et al, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), \u003cem\u003eCoriandrum sativum\u003c/em\u003e (Song et al, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), \u003cem\u003eDaucus carota\u003c/em\u003e (Iorizzo et al, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), \u003cem\u003eBupleurum chinense\u003c/em\u003e (Zhang et al, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and \u003cem\u003eCentella asiatica\u003c/em\u003e (Nawae et al, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)) and constructed a maximum likelihood (ML) phylogeny tree. Six relatively ancestral UGT93s were also included (Liu et al, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this tree, a total of 31 UGTs were selected and expressed in apiaceous plants including those already expressed in \u003cem\u003eA\u003c/em\u003e. \u003cem\u003edecursiva\u003c/em\u003e. Their catalytic activities toward substrates \u003cb\u003e1\u003c/b\u003e, \u003cb\u003e9\u003c/b\u003e and \u003cb\u003e12\u003c/b\u003e were analyzed. All of these enzymes recognize at least one substrate and generate related glycosylated products. Most of them catalyze all three substrates (Figs.\u0026nbsp;\u003cspan refid=\"Fig36\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, \u003cspan refid=\"Fig45\" class=\"InternalRef\"\u003eS41\u003c/span\u003e\u0026ndash;48). This indicate the catalytic abilities toward prenylated phenolic compounds are likely to be shared by most UGT93s in apiaceae. We further reconstructed the ancestral sequence of all UGTs in the tree (N0) using Graphical Representation of Ancestral Sequence Predictions (GRASP) and expressed it for further characterization (Foley et al, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In enzymatic assay, this ancestral enzyme catalyzes substrate \u003cb\u003e1\u003c/b\u003e, \u003cb\u003e9\u003c/b\u003e and \u003cb\u003e12\u003c/b\u003e efficiently (Fig.\u0026nbsp;\u003cspan refid=\"Fig36\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). We therefore postulate that the catalytic activity toward prenylated phenolic compounds may represent a characteristic of UGT93s across apiaceous species, and possibly throughout the plant kingdom.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eStructural Basis for the Catalytic Abilities toward Prenylated Phenolics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThrough structural stimulation supported by Helixfold3 (Furui \u003cem\u003eet al\u003c/em\u003e, 2025), the structure of N0 in complex with substrate \u003cb\u003e1\u003c/b\u003e, \u003cb\u003e9\u003c/b\u003e and \u003cb\u003e12\u003c/b\u003e were modeled. We further found 11 hydrophobic clusters in N0 using ProteinTools (HC0\u0026ndash;10, Fig.\u0026nbsp;\u003cspan refid=\"Fig46\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, Table S6; Ferruz et al, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Among them, HC3 and HC4 wrap around the prenylated substrates in different dimensions (Fig.\u0026nbsp;\u003cspan refid=\"Fig46\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Considering the hydrophobicity of prenyl group, the hydrophobic environment between HC3 and HC4 could probably enhance the binding stability of prenylated substrates, leading to the catalytic efficiency of UGT93s toward these substrates. To verify the assumption, we mutate residues facing substrates in the hydrophobic cluster to serine, a hydrophilic residue and compared the catalytic activities of mutants and N0. Mutant L140S, V162S, L201S and I204S significantly reduce the catalytic activities of N0 toward prenylated phenolics, especially I204S, which almost lost the catalytic abilities totally (Fig.\u0026nbsp;\u003cspan refid=\"Fig46\" class=\"InternalRef\"\u003e5\u003c/span\u003eb, Table S7\u0026ndash;9). This informed us that the hydrophobic clusters composed of these residues significantly contribute to the catalytic activities of UGT93s toward prenylated phenolics.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePrenylated phenolic glycosides exhibit remarkable bioactivities derived from their prenylated phenolic moieties while benefiting from the enhanced bioavailability conferred by glycosylation (Brezani et al, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Azietaku et al, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Abu-Hashem \u003cem\u003eet al\u003c/em\u003e, 2014). These properties make them promising candidates for drug development. However, large-scale extraction from natural sources remains economically and environmentally unsustainable (Lv et al, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Consequently, significant efforts have been directed toward the biosynthesis of these compounds to circumvent reliance on natural extraction. A critical bottleneck in this endeavor is the limited availability of efficient glycosyltransferases (UGTs) capable of glycosylating diverse prenylated phenolics. Although a few UGTs have been characterized for synthesizing furochromone glucosides and icariin, their substrate scope remains narrow. (Zou et al, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Feng et al, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yao et al, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In this study, we identified multiple UGT93 family members that efficiently glycosylate furocoumarins and exhibit broad substrate promiscuity toward various prenylated phenolics. Notably, our findings suggest that prenylated phenolic glycosylation activity may be a conserved feature among UGT93s, providing a valuable framework for future enzyme discovery in the biosynthesis of prenylated phenolic glycosides.\u003c/p\u003e\u003cp\u003eDespite the impressive bioactivities, natural prenylated phenolic glycosides were not widely found, with few cases including furocoumarins, furochromones and icariin (Chen et al, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Naturally, phenolic compounds are unlikely to be substituted by both prenyl and glycosyl, this constrains structural diversity of prenylated phenolic glycosides and impedes medicinal exploration. With the rapid development of combinatorial biosynthesis, this problem can be solved (Zhao \u003cem\u003eet al\u003c/em\u003e, 2024). The UGT93s characterized here not only enable the synthesis of known natural products but also serve as modular tools for engineering novel prenylated phenolic glycosides when combined with other biocatalysts. This approach holds great promise for expanding the structural repertoire of these compounds and accelerating drug discovery.\u003c/p\u003e\u003cp\u003eOver the past decade, extensive research has characterized UGTs catalyzing various substrates like phenolics, terpenoids and alkaloids from different plants (Sirirungruang et al, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Recent efforts have focused on deciphering UGT functional patterns and developing bioinformatic tools for rapid enzyme discovery (Liu et al, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Chen et al, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Yao \u003cem\u003eet al\u003c/em\u003e, 2025). While plant UGTs can be divided into different families according to their evolutionary relationship (Mackenzie et al, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), the correlation between evolution and enzymatic characteristics remain elusive. In this work, we found the catalytic activities toward prenylated phenolics shared by UGT93s. This indicate that UGTs from the same family likely possess similar catalytic functions and might serve as a new aspect to summarize the function of UGTs. For instance, UGT94s, a sister clade to UGT93s, are frequently associated with triterpene glycosylation (Cui et al, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Jiang et al, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), another prenyl-derived metabolite. Investigating the functional and evolutionary interplay between these families could yield deeper insights into UGT diversification. Furthermore, systematic exploration of UGT family functions may facilitate the discovery or engineering of more efficient and novel biocatalysts.\u003c/p\u003e\u003cp\u003eCollectively, we have identified a panel of UGT93s capable of glycosylating prenylated phenolics, including furocoumarins, and demonstrated that this activity is a conserved feature within the family through ancestral sequence reconstruction and structural analysis. These enzymes represent valuable biocatalytic modules for the sustainable production of prenylated phenolic glycosides. Moreover, our family-scale functional and evolutionary analysis provides a blueprint for future investigations into plant UGTs, offering a strategic approach to uncover new enzymes with desired catalytic properties.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Key Research and Development Program of China (No. 2023YFA0914100 to M. Y., and No. 2023YFA0915800 to L. W.), Beijing Natural Science Foundation (No. QY23076 to J.L. Z., and 83001Y0439 to C.X. Z.), National Natural Science Foundation of China (No. 32470245 to L. W., 32400192 to B. N., U24A20358 to B. N.), Shenzhen Science and Technology Program (No. JCYJ20241202130723030 to L. W.).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone declared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMY, and LW planned and designed the research. HYL, JLZ ZLW, MZ, YFY and XRZ performed experiments, HYL, JLZ, BN and XYZ analysed data. HYL, JLZ, BN and MY wrote the manuscript. HYL, JLZ and BN contributed equally.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA-Seq raw reads have been deposited in the Genome Sequence Archive at the National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation under BioProject number PRJCA040560 (https://ngdc.cncb.ac.cn/gsub/submit/bioproject/PRJCA040560). Gene sequences have been submitted to GenBase, the accession codes are: C_AA110113.1 (g18838_i0), C_AA110124.1 (g20190_i0), C_AA110135.1 (g16606_i0), C_AA110138.1 (g22322_i0), C_AA110139.1 (g19500_i0), C_AA110140.1 (g18160_i0), C_AA110141.1 (g12439_i0), C_AA110142.1 (g4726_i0), C_AA110143.1 (g10426_i0), C_AA110114.1 (g10426_i1), C_AA110115.1 (g15793_i0), C_AA110116.1 (g15793_i1), C_AA110117.1 (g16556_i0), C_AA110118.1 (g19098_i0), C_AA110119.1 (g19098_i1), C_AA110120.1 (DCAR_625897), C_AA110121.1 (DCAR_519424), C_AA110122.1 (LCX11BG002136), C_AA110123.1 (LCX10BG001765), C_AA110125.1 (LCX10BG001766), C_AA110126.1 (CAS03G001478), C_AA110127.1 (Cs08G01158), C_AA110128.1 (Ag2G01516), C_AA110129.1 (SaDchr08G000892), C_AA110130.1 (SaDchr04G001777_s2), C_AA110131.1 (SaDchr01G001897s1), C_AA110132.1 (SaDchr01G002295), C_AA110133.1 (SaDchr01G002295_s2), C_AA110134.1 (SaDchr01G002295_s3), C_AA110136.1 (SaDchr04G001012), C_AA110137.1 (SaDchr01G001897_s2).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChang SK, Jiang YM, Yang B (2021) An update of prenylated phenolics: Food sources, chemistry and health benefits. Trends Food Sci Technol 108:197\u0026ndash;213\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim DH, Kim DY, Kim YC, Jung JW, Lee S et al (2007) Nodakenin, a coumarin compound, ameliorates scopolamine-induced memory disruption in mice. Life Sci 80:1944\u0026ndash;1950\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Y, Jin SS, Luo D, He DQ, Yu M et al (2023) Prim-\u003cem\u003eO\u003c/em\u003e-glucosylcimifugin ameliorates aging-impaired endogenous tendon regeneration by rejuvenating senescent tendon stem/progenitor cells. Bone Res 11:784\u0026ndash;802\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang TW, Zhong Y, Shi Y, Feng CC, Xu L et al (2024) Multi-omics reveals that 5-\u003cem\u003eO\u003c/em\u003e-methylvisammioside prevention acute liver injury in mice by regulating the TNF/MAPK/NF-κB/arachidonic acid pathway. Phytomedicine 128:155550\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHe D, Chen SL, Wang XY, Wen X, Gong CY et al (2025) Icaritin Represses Autophagy to Promote Colorectal Cancer Cell Apoptosis and Sensitized Low-Temperature Photothermal Therapy via Targeting HSP90-TXNDC9 Interactions. Adv Sci (Weinh) 12:e2412953\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoss J, Li Y, Lim E, Bowles DJ (2001) Higher plant glycosyltransferases. Genome Biol 2:REVIEWS3004\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZou JL, Li HY, Nie B, Wang ZL, Zhao CX et al (2025) Complete biosynthetic pathway of furochromones in \u003cem\u003eSaposhnikovia divaricata\u003c/em\u003e and its evolutionary mechanism in Apiaceae plants. Nat Commun 16:3109\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAn T, Lin GY, Liu Y, Qin L, Xu YQ et al (2023) \u003cem\u003eDe novo\u003c/em\u003e biosynthesis of anticarcinogenic icariin in engineered yeast. Metab Eng 80:207\u0026ndash;215\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeng KP, Chen RD, Xie KB, Chen DW, Liu JM et al (2019) Ep7GT, a glycosyltransferase with sugar donor flexibility from \u003cem\u003eEpimedium pseudowushanense\u003c/em\u003e, catalyzes the 7-\u003cem\u003eO\u003c/em\u003e-glycosylation of baohuoside. Org Biomol Chem 17:8106\u0026ndash;8114\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYao Y, Gu JJ, Luo YJ, Wang YY, Pang YZ et al (2022) Genome-wide analysis of UGT gene family identified key gene for the biosynthesis of bioactive flavonol glycosides in \u003cem\u003eEpimedium pubescens\u003c/em\u003e Maxim. Synth Syst Biotechnol 7:1095\u0026ndash;1107\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30:923\u0026ndash;930\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen CJ, Wu Y, Li JW, Wang X, Zeng ZH et al (2023) TBtools-II: A one for all, all for one bioinformatics platform for biological big-data mining. Mol Plant 16:1733\u0026ndash;1742\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTamura K, Stecher G, Kumar S (2021) MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol Biol Evol 38:3022\u0026ndash;3027\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu YQ, Wang Q, Liu XN, Cheng J, Zhang L et al (2023) pUGTdb: A comprehensive database of plant UDP-dependent glycosyltransferases. Mol Plant 16:643\u0026ndash;646\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFoley G, Mora A, Ross CM, Bottoms S, S\u0026uuml;tzl L et al (2022) Engineering indel and substitution variants of diverse and ancient enzymes using Graphical Representation of Ancestral Sequence Predictions (GRASP). PLoS Comput Biol 18:e1010633\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFurui K, Ohue M (2025) Benchmarking HelixFold3-Predicted Holo Structures for Relative Free Energy Perturbation Calculations. ACS Omega 10:11411\u0026ndash;11420\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFerruz N, Schmidt S, H\u0026ouml;cker B (2021) ProteinTools: a toolkit to analyze protein structures. Nucleic Acids Res 49:W559\u0026ndash;W566\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeeliger D, de Groot BL (2010) Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J Comput Aided Mol Des 24:417\u0026ndash;422\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNie B, Chen XQ, Hou ZW, Guo MX, Li C et al (2024) Haplotype-phased genome unveils the butylphthalide biosynthesis and homoploid hybrid origin of \u003cem\u003eLigusticum chuanxiong\u003c/em\u003e. Sci Adv 10:eadj6547\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSong XM, Wang JP, Li N, Yu JG, Meng FB et al (2020) Deciphering the high-quality genome sequence of coriander that causes controversial feelings. Plant Biotechnol J 18:1444\u0026ndash;1456\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSong XM, Sun PC, Yuan JQ, Gong K, Li N et al (2021) The celery genome sequence reveals sequential paleo-polyploidizations, karyotype evolution and resistance gene reduction in apiales. Plant Biotechnol J 19:731\u0026ndash;744\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHan XX, Li C, Sun SC, Ji JJ, Nie B et al (2022) The chromosome-level genome of female ginseng (\u003cem\u003eAngelica sinensis\u003c/em\u003e) provides insights into molecular mechanisms and evolution of coumarin biosynthesis. Plant J 112:1224\u0026ndash;1237\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIorizzo M, Ellison S, Senalik D, Zeng P, Satapoomin P et al (2016) A high-quality carrot genome assembly provides new insights into carotenoid accumulation and asterid genome evolution. Nat Genet 48:657\u0026ndash;666\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang QF, Li M, Chen XY, Liu GX, Zhang Z et al (2022) Chromosome-Level Genome Assembly of \u003cem\u003eBupleurum chinense\u003c/em\u003e DC Provides Insights into the Saikosaponin Biosynthesis. Front Genet 13:878431\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNawae W, Yoocha T, Narong N, Paemanee A, Ketngamkum Y et al (2021) Transcriptome sequencing revealed the influence of blue light on the expression levels of light-stress response genes in \u003cem\u003eCentella asiatica\u003c/em\u003e. PLoS ONE 16:e0260468\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrezani V, Smejkal K, Hosek J, Tomasova V (2018) Anti-inflammatory Natural Prenylated Phenolic Compounds - Potential Lead Substances. Curr Med Chem 25:1094\u0026ndash;1159\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAzietaku JT, Ma H, Yu XA, Li J, Oppong MB et al (2017) A review of the ethnopharmacology, phytochemistry and pharmacology of Notopterygium incisum. J Ethnopharmacol 202:241\u0026ndash;255\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbu-Hashem AA, El-Shazly M (2015) Synthesis, reactions and biological activities of furochromones: a review. Eur J Med Chem 90:633\u0026ndash;665\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLv Y, Marsafari M, Koffas M, Zhou J, Xu P (2019) Optimizing Oleaginous Yeast Cell Factories for Flavonoids and Hydroxylated Flavonoids Biosynthesis. ACS Synth Biol 8:2514\u0026ndash;2523\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen W, Yu ZY, Leng L, Sun D, Liu H et al (2025) Artificial Intelligence-Curated repository of gene-encoded natural diverse components from herbal medicines. Innov. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.xinn.2025.101011\u003c/span\u003e\u003cspan address=\"10.1016/j.xinn.2025.101011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao Y, Duan YT, Zang J, Raadam MH, Pateraki I et al (2025) Structure-Agnostic Bioactivity-Driven Combinatorial Biosynthesis Reveals New Antidiabetic and Anticancer Triterpenoids. Angew Chem Int Ed Engl 64:e202416218\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSirirungruang S, Barnum CR, Tang SN, Shih PM (2023) Plant glycosyltransferases for expanding bioactive glycoside diversity. Nat Prod Rep 40:1170\u0026ndash;1180\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen NH, Jiang ZN, Xie ZK, Zhou S, Zeng T et al (2025) An Effective Computational Strategy for UGTs Catalytic Function Prediction. ACS Synth Biol 14:2064\u0026ndash;2080\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMackenzie PI, Bock KW, Burchell B, Guillemette C, Ikushiro S et al (2005) Nomenclature update for the mammalian UDP glycosyltransferase (UGT) gene superfamily. Pharmacogenet Genomics 15:677\u0026ndash;685\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCui S, Zhang S, Wang N, Su XD, Luo ZL et al (2024) Structural insights into the catalytic selectivity of glycosyltransferase SgUGT94-289-3 towards mogrosides. Nat Commun 15:6423\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJiang Z, Chen N, Wang HT, Tian YG, Du XY et al (2025) Molecular characterization and structural basis of a promiscuous glycosyltransferase for β-(1,6) oligoglucoside chain glycosides biosynthesis. Plant Biotechnol J 23:2242\u0026ndash;2253\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Peking University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Angelica decursiva, biosynthesis, glycosyltransferase, nodakenin, prenylated phenolic glycoside, UGT93","lastPublishedDoi":"10.21203/rs.3.rs-7134866/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7134866/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u0026bull; Prenylated phenolic glycosides, such as nodakenin, represent a class of natural products with diverse bioactivities. The metabolic engineering production of these compounds remains largely unexplored, primarily due to the scarcity of efficient UDP-glycosyltransferases (UGTs) capable of catalyzing prenylated phenolic substrates.\u003c/p\u003e\u003cp\u003e\u0026bull; Through UGT classification and functional characterization, 14 UGT93s from \u003cem\u003eAngelica decursiva\u003c/em\u003e were identified to generate nodakenin utilizing nodakenetin.\u003c/p\u003e\u003cp\u003e\u0026bull; Six UGT93s showed catalytic preference toward prenylated phenolics. Through functional characterization of more UGT93s and ancestral sequence reconstruction, this catalytic characteristic was found in most UGT93s.\u003c/p\u003e\u003cp\u003e\u0026bull; Two hydrophobic clusters wrapping around the substrates are probably the structural basis for the catalytic activities toward prenylated phenolics.\u003c/p\u003e\u003cp\u003e\u0026bull; Functionally characterizing the novel UGT93s provided valuable biosynthetic modules for biomanufacturing. And finding the catalytic preference highlight the UGT93 family as a promising source of biocatalysts for the biosynthesis of prenylated phenolic glycosides, offering new opportunities for their scalable production.\u003c/p\u003e","manuscriptTitle":"UGT93s, Plant UGTs Generating Prenylated Phenolic Glycosides","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-17 09:18:05","doi":"10.21203/rs.3.rs-7134866/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"228a45bf-96a6-4e65-aec2-71a5ad562702","owner":[],"postedDate":"July 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51596805,"name":"Natural Product Chemistry"}],"tags":[],"updatedAt":"2025-07-17T09:18:05+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-17 09:18:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7134866","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7134866","identity":"rs-7134866","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}