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Systematic metabolic profiling and bioactivity assays for bioconversion of Aceraceae family

  • Jinyong Park,

    Roles Writing – original draft

    Affiliation Department of Bioscience and Biotechnology, Konkuk University, Seoul, Republic of Korea

  • Dong Ho Suh,

    Roles Data curation, Methodology, Writing – review & editing

    Affiliation Department of Bioscience and Biotechnology, Konkuk University, Seoul, Republic of Korea

  • Digar Singh,

    Roles Writing – review & editing

    Affiliation Department of Bioscience and Biotechnology, Konkuk University, Seoul, Republic of Korea

  • Sarah Lee,

    Roles Conceptualization, Resources

    Affiliation National Institute of Biological Resources, Environmental Research Complex, Incheon, Republic of Korea

  • Jong Seok Lee,

    Roles Conceptualization, Resources

    Affiliation National Institute of Biological Resources, Environmental Research Complex, Incheon, Republic of Korea

  • Choong Hwan Lee

    Roles Project administration, Supervision, Writing – review & editing

    Affiliation Department of Bioscience and Biotechnology, Konkuk University, Seoul, Republic of Korea

Systematic metabolic profiling and bioactivity assays for bioconversion of Aceraceae family

  • Jinyong Park, 
  • Dong Ho Suh, 
  • Digar Singh, 
  • Sarah Lee, 
  • Jong Seok Lee, 
  • Choong Hwan Lee


Plants are an important and inexhaustible source of bioactive molecules in food, medicine, agriculture, and industry. In this study, we performed systematic liquid chromatography–mass spectrometry (LC-MS)-based metabolic profiling coupled with antioxidant assays for indigenous plant family extracts. Partial least-squares discriminant analysis of LC-MS datasets for the extracts of 34 plant species belonging to the families Aceraceae, Asteraceae, and Rosaceae showed that these species were clustered according to their respective phylogenies. In particular, seven Aceraceae species were clearly demarcated with higher average antioxidant activities, rationalizing their application for bioconversion studies. On the basis of further evaluation of the interspecies variability of metabolic profiles and antioxidant activities among Aceraceae family plants, we found that Acer tataricum (TA) extracts were clearly distinguished from those of other species, with a higher relative abundance of tannin derivatives. Further, we detected a strong positive correlation between most tannin derivatives and the observed higher antioxidant activities. Following Aspergillus oryzae-mediated fermentative bioconversion of Acer plant extracts, we observed a time-correlated (0–8 days) linear increase in antioxidant phenotypes for all species, with TA having the highest activity. Temporal analysis of the MS data revealed tannin bioconversion mechanisms with a relatively higher abundance of gallic acid (m/z 169) accumulated at the end of 8 days, particularly in TA. Similarly, quercetin precursor (glycoside) metabolites were also transformed to quercetin aglycones (m/z 301) in most Acer plant extracts. The present study underscores the efficacy of fermentative bioconversion strategies aimed at enhancing the quality and availability of bioactive metabolites from plant extracts.


Bioconversion of renewable plant biomass with the aim of tapping their high-end value-added pool of molecules for use as bioactives and food additives and inclusion in cosmetics and pharmaceuticals has attracted considerable attention in recent years. In general, this myriad of valuable plant-derived molecules includes antibiotics, alkaloids, antimicrobials, food-grade pigments, and phenolics [1]. In particular, plant-derived polyphenols and flavonoids have numerous health-related effects, including antioxidant, anticancer, and anti-obesity activities [2]. Hence, the inclusion of plant-derived functional bioactives as dietary supplements has increasingly been realized owing to their higher efficacies coupled with lower toxicity compared with conventional medicines [3]. Ushered by the soaring demands for plant-derived bioactive ingredients, microbial biotransformation and biovalorization of agro-waste and plant biomass through microbial fermentation have emerged as sustainable and environment-friendly alternatives. Given that plant biomass is a potentially inexhaustible source of valuable products, the enhanced production and bioconversion of natural products, e.g., bioactive secondary metabolites, using microbial fermentation have gained widespread interest [4, 5].

Among angiosperms, plants belonging to the families Aceraceae, Asteraceae, and Rosaceae have virtually ubiquitous distribution, and are renowned for their food, herbal medicine, and ornamental applications. The Aceraceae (maple) family comprises 129 species, most of which are trees and shrubs distributed widely in temperate regions of the northern hemisphere, including North-Eastern America, Europe, and East Asia [6]. Aceraceae contains two commercially important genera, i.e., Diptesonia and Acer, the latter of which has been harnessed for commercial purposes, such as the preparation of traditional medicines in East Asia (owing to their high antioxidant, antitumor, and anti-inflammatory activities) and production of Maple syrup in the West [7]. Plants in the Asteraceae (daisy) family, of which there are over 25,000 species, have traditionally been used as sources of rubber, edible oils, and vegetables with associated antioxidant functions [8]. Quintessentially, species of Asteraceae contain a high abundance of sesquiterpenoids that have a myriad of pharmacological applications as growth regulators and antifungal and antitumor compounds [9]. Similarly, the Rosaceae family represents another dominant group of flowering plants containing an abundance of bioactive metabolites with antioxidant, estrogenic, and anti-proliferative activities [10].

Recently, the fermentative bioconversion of agro-industrial and plant biomass has attracted renewed interest with a view toward exploiting the bioavailability of valuable natural products. Analogous to food fermentative bioprocesses, in which secretion of hydrolytic enzymes promotes the release of flavor and functional metabolites, the fermentative bioconversion of plant biomass or its crude extracts typically produces valuable phytochemicals from plant matrices [11, 12]. Previously, a number of studies have highlighted the bioconversion and biovalorization of agro-industrial products, including capsaicin hydrolysates [13], kaempferol from cauliflower outer leaves [14], soy isoflavones in soy extracts [15], and pine polyphenols [16]. Since most of these studies have focused on selected groups of molecules or their targeted bioconversion, we conjecture that a comprehensive high-throughput and high-fidelity MS-analysis of the intermediate metabolic entities would make a valuable contribution toward attaining the mechanistic understanding if the bioconversion processes. Under current perspectives, metabolomic analysis, which can provide an unbiased snapshot of the quantitative and quantitative trends of low molecular weight metabolites, can be used to generate a holistic picture of the overall metabolic events concomitant with a bioconversion event.

In this study, we performed comprehensive metabolite profiling of different plant species (34) belonging to three commercially important plant families (Aceraceae, Asteraceae, and Rosaceae) abundant throughout the Korean Peninsula. The plant extracts with significantly higher antioxidant activities were screened and subjected to fermentative bioconversion using Aspergillus oryzae to examine time-correlated alterations in corresponding antioxidant potentials.

Materials and methods

Chemicals and reagents

Analytical grade ethanol, methanol, acetonitrile, and water were purchased from Fisher Scientific (Pittsburgh, PA, USA). 2,2'-Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS), 2,2-diphenyl-1-picrylhydrazyl (DPPH), 6-hydroxy-2,5,7,8-tetramethylchromane-2-carboxylic acid (Trolox), 2,4,6-Tris(2-pyridyl)-s-triazine (TPTZ), acetic acid, formic acid, glycerol, iron (III) chloride, potassium persulfate, sodium hydroxide, sodium acetate, and standard compounds were obtained from Sigma-Aldrich (St. Louis, MO).

Plant materials

Overall, 34 native Korean plant species from the families Aceraceae (7), Asteraceae (9), and Rosaceae (18) were examined in this study. The plant samples were procured from the National Institute of Biological Resources (NIBR, Incheon, Republic of Korea). Detailed information on the respective plant species, including their harvest zones and collection dates, and NIBR sample accession numbers is listed in Table 1. The plant samples were collected between May and October 2014 from two megalopolises, seven provinces, and one special self-governing province in the Republic of Korea. The field studies by NIBR and harvested samples did not involve any endangered or protected species.

Table 1. Information on the 34 native Korean plant species used in this study.

Sample preparation for metabolite profiling and antioxidant activity screening

Plant samples were dried under shade, and each sample (100 g) was extracted three times with 70% ethanol (1 L). The filtered sample extracts were dried using a rotary vacuum evaporator (Eyela, Tokyo, Japan), and were subsequently freeze-dried and stored under deep-freezing conditions (-70 °C) until further analyses. Each of the dried sample extracts (20 mg) was dissolved with 1 mL of 70% ethanol and filtered through a 0.2-μm polytetrafluoroethylene (PTFE) membrane prior to ultra-performance liquid chromatography–quadrupole–time of flight–mass spectrometry (UPLC-Q-TOF-MS) and ultrahigh-performance liquid chromatography–LTQ–linear ion trap–tandem mass spectrometry (UHPLC-LTQ-IT-MS/MS) analyses.


The Thermo Fischer Scientific LTQ XL linear ion trap mass spectrometry system used in the present study consisted of an electrospray interface (Thermo Fischer Scientific, San José, CA, USA) coupled with a DIONEX UltiMate 3000 RS Pump, RS Autosampler, RS Column Compartment, and RS Diode Array Detector (Dionex Corporation, Sunnyvale, CA, USA). The samples were separated on a Thermo Scientific Syncronis C18 UHPLC column with 1.7 μm particle size. The mobile phase consisted of solvent A [0.1% (v/v) formic acid in water] and solvent B [0.1% (v/v) formic acid in acetonitrile]. The gradient conditions were increased from 10% to 100% solvent B over 18 min, and re-equilibrated to the initial conditions for 4 min. The flow rate was 0.3 mL/min and the injection volume was 10 μL. The temperature of the column during measurement was maintained at 35 °C. The photodiode array was set at 200–600 nm for detection and managed by 3D field. Ion trap was performed in positive, negative, and full-scan ion modes within a range of 150–1000 m/z. The operating parameters were as follows: source voltage, ±5 kV, capillary voltage, 39 V; and capillary temperature, 275 °C. Tandem MS analysis was performed using scan-type turbo data-dependent scanning under the same conditions as those used for MS scanning. The samples were analyzed using three biological replicates for each sample. To circumvent systematic errors during analysis, the samples were analyzed in random blocks of 10 runs, followed by an intermittent quality control (QC) sample prepared from pooled blends of each sample extract.

UPLC-Q-TOF-MS analysis

UPLC-Q-TOF-MS analysis was performed using a Waters Micromass Q-TOF Premier mass spectrometer coupled to an UPLC Acquity system (Waters, Milford, MA) equipped with a binary solvent delivery system, an autosampler, and an ultraviolet (UV) detector. The samples were separated on an Acquity UPLC BEH C18 column (100 mm × 2.1 mm × 1.7 μm particle size; Waters Corp.). The sample injection volume was 5 μL with a mobile phase flow rate of 0.3 mL/min, and the column temperature was maintained at 37 °C. The binary mobile phase consisted of solvent A (0.1% formic acid in water) and solvent B (0.1% formic acid in acetonitrile). The mobile phase solvent gradient was programmed as follows: 5% solvent B for 1 min, gradually increased to 100% solvent B over 9 min, maintained as such for the next 1 min, and finally decreased to 5% Solvent B over 3 min, with a total run time of 13 min. The MS data were collected in the range of 100–1000 m/z, within negative and positive ion modes. The source temperature was 100 °C, the desolvation gas (nitrogen) was set to 600 L/h at a temperature of 200 °C, and the cone gas (nitrogen) was set to 50 L/h. The capillary voltage and cone voltage were set at 2.5 kV and 50 V, respectively. Data were collected with a scan accumulation time of 0.2 s in the centroid mode. Leucine enkephalin (10 ppm) was used as the reference lock mass [m/z 554.2615 (-) and 556.2771 (+)] at a flow rate of 10 μL/min. All samples were analyzed using three biological replicates and a random block of 10 samples with intermittent QC samples.

Data processing and multivariate analysis

The UHPLC-LTQ-IT-MS/MS data were acquired using Xcalibur software (version 2.00; Thermo Fisher Scientific), and raw data were subsequently converted to netCDF (*.cdf) format using Xcalibur software. The MS data files were then processed using MetAlign software (RIKILT-Institute of Food Safety, Wageningen, The Netherlands) to evaluate the retention times, normalized peak intensities, and accurate masses. The resulting data were exported to an Excel file (Microsoft, Redmond, WA, USA), and multivariate statistical analyses were performed using SIMCA-P+ software (version 12.0; Umetrics, Umea, Sweden). Principal component analysis (PCA) and loading plots were employed to compare metabolic variants among the plant sample extracts. The variables were selected based on the variable importance in the projection (VIP) value, whereas significant differences between experimental groups were determined by analysis of variance (ANOVA). PASW Statistics (version 18.0; SPSS, Inc., Chicago, IL) was used to calculate Pearson correlation coefficients between metabolites and bioactivity assays as well as imputing the missing values while data processing. Heat map and correlation maps were visualized using MEV software (version 4.8; Romania).

Bioactivity assays

A modified version of the method described by Re et al. [17] was used to perform the ABTS assay. Briefly, 7 mM ABTS was mixed in 2.45 mM potassium persulfate solution, and the mixture was stored for 12 h in the dark at room temperature. The solution was diluted with deionized water until the absorbance reached 0.7 ± 0.02 at 750 nm, as determined using a microplate reader (Spectronic Genesys 6; Thermo Electron, Madison, WI, USA). Sample extracts (10 μL) obtained from plants in each of the three plant families were mixed with 190 μL of diluted ABTS solution in the wells of a 96-well plate, and subsequently incubated at 37 °C in the dark for 6 min. Following incubation, the absorbance of the reacted samples was recorded at 750 nm using a microplate reader.

The DPPH assay was performed using the method described by Dietz et al. [18] with a few modifications. Plant extracts (20 μL) from each of the species from the three families were added to 0.2 mM DPPH ethanol solution (180 μL) in the wells of a 96-well plate, and then incubated for 20 min in the dark at room temperature. The absorbance was recorded at 515 nm using a microplate reader.

The ferric reducing ability of plasma (FRAP) assay was performed using a modified version of the procedure previously described by Benzie and Strain [19]. The FRAP reagent was mixed with 300 mM sodium acetate buffer (pH 3.6), 10 mM TPTZ, and 20 mM ferric chloride at a ratio of 10:1:1. Each plant sample (10 μL) was mixed with 300 μL of FRAP reagent in the wells of a 96-well plate and incubated in the dark at 37 °C for 6 min. The absorbance at 593 nm was then measured.

All bioactivity assays were conducted using three biological as well as analytical replicates for each sample and the results were expressed as the Trolox equivalents of antioxidant capacity, with a concentration range of 0.0156–1 mM.

Fungal strains and inoculum preparation

The Aspergillus oryzae KCCM 12698 strain used in the study was procured from the Korean Culture Center of Microorganisms (KCCM, Seoul, Republic of Korea). The strain was transferred from -80 °C frozen stocks to malt extract agar (MEA) plates for pre-culture prior to use as an inoculum. The frozen stocks were grown on MEA plates for 7 days at 28 °C in the dark and thereafter sub-cultured. The culture inoculum was prepared by harvesting the fresh spores from MEA cultures using 2 mL of sterile distilled water containing 0.1% Tween 80. The inoculum was dilution adjusted to 1.8 × 107 spores/mL.

Preparation of the Acer mixed broth and fermentative bioconversion

Acer plant extracts (0.25 g) were mixed with 50 mL of MEB (0.5%, w/v) prior to autoclave sterilization. One milliliter of A. oryzae inoculum was added to each culture flask and the cultures were incubated at 28 °C for 8 days. The broth samples (3 mL) for metabolite extraction were regularly harvested at an interval of 2 days, and the aliquots were stored immediately under deep-freezing (-20 °C) conditions until analyses.

The fermented samples were extracted by adding 6 mL of 70% ethanol to each aliquot sample, followed by vigorous mixing in a rotary shaker at 200 rpm for 2 h, and then centrifuged at 5,000 rpm and 4 °C for 10 min (Universal320; Hettich Zentrifugen, Germany). The supernatants were collected and dried in a speed vacuum concentrator (Biotron, Seoul, Republic of Korea). The extracted sample analytes were re-suspended in 70% ethanol to a fixed titer of 10 mg/mL and filtered using a disposable 0.45-μm PTFE filter membrane prior to further analyses. The bioconversion steps were performed for seven Acer species extracts using three biological replicates for each.


Metabolite profiling and antioxidant activity screening for three plant families

In order to select the plant material extracts for bioconversion, we initially performed metabolite profiling coupled with multivariate statistical analysis for plants in three abundant and commercially important plant families in Korea (Aceraceae, Asteraceae, and Rosaceae). The partial least-square discrimination analysis (PLS-DA) score plot presented in Fig 1A shows that the 34 native Korean plant species were clustered depending on their phylogeny. The quality parameters of PLS-DA were signified using R2X (0.166), R2Y (0.999), Q2 (0.791), and p-value < 0.05, suggesting their high predictive accuracies. In addition, the bioactivity potentials of the three plant families were evaluated through examining the antioxidant activities of the extracts (Fig 1B). The average antioxidant activity (±SD) values for sample extracts from plants in each family were expressed as the Trolox equivalent antioxidant capacity. Although, observed differences in the antioxidant activities of plant extracts among the three different plant families were not statistically significant, the DPPH assay indicated that antioxidant activities were highest for Aceraceae family plant extracts, followed by Rosaceae and Asteraceae. Henceforth, we focused our next phase of study selectively on Aceraceae family plants owing to their relatively higher antioxidant activities as well as distinct metabolite compositions.

Fig 1.

(A) Partial least-square discriminant analysis score plot based on UHPLC–LTQ-IT-MS/MS datasets, and (B) average antioxidant activity (2,2-diphenyl-1-picrylhydrazyl: DPPH), for the metabolite extracts derived from plant species belonging to the families Aceraceae, Rosaceae, and Asteraceae. The different letters are indicative of statistically significant differences for observed bioactivities according to Duncan’s multiple-range test at p < 0.05.

Extracts obtained from seven different Acer species (Family: Aceraceae) were analyzed using UHPLC-LTQ-IT-MS/MS. A PLS-DA score plot indicated that the corresponding datasets for Acer species were clustered across PLS1 (16.0%) and PLS2 (17.4%), with model parameters R2X (0.449), R2Y (0.994), and Q2 (0.966), and p-value < 0.05 (Fig 2A). According to the PLS-DA score plot, the datasets for seven Acer species were clustered into three main groups. One group consisted of Acer triflorum (TR), Acer buergerianum (BU), Acer komarovii (KO), and Acer pseudosieboldianum (PS). The second group included Acer pictum subsp. mono (PM) and Acer pictum (PI), whereas the third group was represented by a single species, Acer tataricum (TA). On the basis of the PLS-DA model, 33 metabolites were selected as significantly discriminant among the seven different Acer species at a variable importance in the projection (VIP) value > 0.7 and p-value < 0.05. These metabolites were tentatively identified using measured mass spectra (m/z), retention times, mass fragment patterns, UV absorbance, elemental compositions, and i-FIT (theoretical isotope distribution) derived from the UHPLC-LTQ-IT-MS/MS and UPLC-Q-TOF-MS datasets, considering standard compounds, an in-house library, and published references (Table 2). Among the 33 significantly discriminant metabolites, we identified quinic acid derivatives (3), phenolic acid derivatives (7), flavonoid derivatives (14), miscellaneous (6), and non-identified (3) metabolites. A comparative analysis of the Acer species plant extracts based on DPPH (Fig 2B), ABTS, and FRAP (S1 Fig) assays indicated that TA had relatively higher antioxidant activities.

Table 2. Differences in the metabolites of seven Acer species identified using UHPLC-LTQ-IT-MS/MS and UPLC-Q-TOF-MS.

Fig 2.

(A) Partial least-square discriminant analysis (PLS-DA) score plot based on UHPLC–LTQ-IT-MS/MS datasets, (B) average antioxidant activity (2,2-diphenyl-1-picrylhydrazyl: DPPH) for seven Acer species plant extracts (different letters are indicative of statistically significant differences for observed bioactivities according to Duncan’s multiple-range test at p < 0.05), and (C) Heat map representation for the relative abundance of significantly discriminant metabolites based on the PLS-DA model (VIP > 0.7, p < 0.05). TR: Acer triflorum; PM: Acer pictum subsp. mono; BU: Acer buergerianum; KO: Acer komarovii; TA: Acer tataricum; PS: Acer pseudosieboldianum; PI: Acer pictum; PA: Acer palmatum.

Correlations between the discriminant metabolites and antioxidant activity in seven Acer species

The relative levels of significantly discriminant metabolites among the seven Acer species plant extracts were visualized using heat map representation (Fig 2C). Intriguingly, the levels of quercetin and its derivatives were relatively higher in PI, whereas quinic acid and its derivatives were abundant metabolites in PS. Further, acerogenin and acerogenin glycosides (aceroside) were selectively higher in TR, whereas those of tannin derivatives were higher in TA extracts compared with those of other Acer species.

Correlation analysis was performed to evaluate the individual contribution of metabolites toward the observed antioxidant activities (Fig 3). Accordingly, six tannin derivatives (ellagic acid, ethyl gallate and derivative, maplexin B, maplexin E, and maplexin J) exhibited a high positive correlation with antioxidant activity. Further, two quercetin derivatives (quercetin-(galloyl)rhamnoside and quercetin-(digalloyl)rhamnoside) and three acerogenin derivatives (acergenin, aceroside III, and aceroside VIII) showed positive but relatively weak correlations with antioxidant phenotypes.

Fig 3. Correlation map representation of the relative levels of significantly different metabolites and observed bioactivities [2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid), 2,2-diphenyl-1-picrylhydrazyl, and ferric reducing ability of plasma: ABTS, DPPH, and FRAP, respectively].

Each square indicates r, which is the Pearson correlation coefficient of a pair of metabolites and assayed activities. The red color indicates a positive (0 < r < 0.7) correlation and the blue color indicates a negative (-0.7 < r < 0) correlation.

Bioconversion affects metabolite profiles and antioxidant activities in Aceraceae family plant extracts

Following A. oryzae-mediated bioconversion of Aceraceae family plant extracts for 8 days, a time-correlated PCA was performed to evaluate the alterations in secondary metabolite profiles based on the UHPLC-LTQ-IT-MS/MS datasets. The PCA score plot showed variances of 6.24% and 5.94% along principal components PC1 and PC2, respectively (Fig 4A). The datasets for 0-day (▲) and 8-day (■) fermented extracts at the end of the bioconversion process were clearly separated along PC1, with each biological replicate representing a species clustered together. The discriminant metabolites that were significantly altered during the bioconversion process were selected at VIP value > 0.7 and p-value < 0.05 based on the corresponding PLS-DA model. A total of 36 metabolites were selected and divided into the following sub-groups: phenolic acid derivatives (12), flavonoid derivatives (12), miscellaneous (5), and non-identified (7) metabolites (Table 3). Considering the bioactivity phenotypes, we observed a concomitant increase in relative antioxidant activities for all Acer-extracts following the bioconversion process (Fig 4B). At 8 days after bioconversion, the order of the observed antioxidant activity was as follows: TA > TR > KO > BU > PS > PM > PI.

Fig 4.

(A) Principal component analysis score plot derived from UHPLC-LTQ-IT-MS/MS datasets displaying a variance between unfermented (0 day) and fermented (8 days) samples, and (B) antioxidant activity assays, where each of the five columns indicates average 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) activity for 0-, 2-, 4-, 6-, and 8-day fermented Acer extracts. TR: Acer triflorum; PM: Acer pictum subsp. mono; BU: Acer buergerianum; KO: Acer komarovii; TA: Acer tataricum; PS: Acer pseudosieboldianum; PI: Acer pictum; PA: Acer palmatum; C: control (only broth).

Table 3. Differential metabolites identified using UHPLC-LTQ-IT-MS/MS and UPLC-Q-TOF-MS in before/after bioconversion of Acer.

Further, we visualized variations in the relative levels and bioconversion mechanisms of selected sets of discriminant metabolites, including quercetin and tannin derivatives (Fig 5). As shown in Fig 5A, the relative levels of rutin, quercetin-(galloyl)arabinoside, and quercetin-O-glucoside were considerably decreased during the bioconversion process, whereas the remaining metabolites showed marginal changes. Intriguingly, the quercetin levels were steadily elevated from 0 to 4 days and decreased thereafter until the end of the bioconversion process. Similarly, a chain of bioconversion events involving the conversion of tannin derivatives (maplexin E, acalyphidin M1, tetragalloyl glucose, maplexin D, corilagin, trigalloyl glucose, and maplexin B) to gallic acid might have contributed to its elevated levels at the end of bioprocessing (Fig 5B). Notably, following bioconversion, the gallic acid levels were significantly higher in TA compared with the other Acer species.

Fig 5. Proposed bioconversion pathways derived for the selected metabolites in UHPLC-LTQ-IT-MS/MS datasets relevant to the time-correlated production of (A) quercetin, and (B) gallic acid during the fermentative bioconversion process.

The inset graphs indicate the metabolite peak area plotted along the y-axis, whereas the incubation period (0, 4, and 8 days) during fermentation is plotted along the x-axis. The seven Acer species are indicated with different color codes in the inset graph.


Throughout human history, plant-derived natural products and metabolic intermediates have served as dietary supplements, nutraceuticals, and pharmacological agents, and more recently have been used as templates for drug discovery. In this study, we mainly employed metabolic profiling, bioactivity screening, and subsequent bioconversion to examine the antioxidant bioactivities of extracts derived from members of three regionally abundant plant families: Aceraceae, Asteraceae, and Rosaceae. In the present study we focused on altered antioxidant activities mainly as the higher plants and their constituents provide a rich source of natural antioxidants with umpteen pharmaceutical, health, and cosmetic applications. Especially, the natural phytochemicals in plants have been receiving increased interest from consumers for their beneficial health effects owing to their antioxidant metabolites. The bioconversion of plant natural products coupled with microbial production of bioactive compounds from renewable plant resources is recognized as a sustainable alternative to synthetic processes. Hence, fermentative bioprocesses used for the bioconversion of plant materials are considered advantageous owing to their low energy requirements, low waste emissions, and efficient recovery of end products [20].

On the basis of the initial screening studies that revealed higher antioxidant activities in Aceraceae family plant extracts, we selectively examined the metabolic profiles of Acer species extracts and evaluated the correlations between the significantly discriminant metabolites and related antioxidant activities. Metabolic profiling followed by multivariate statistical analysis indicated that UHPLC-LTQ-IT-MS/MS datasets for seven Acer species extracts were separated into three groups (Fig 2A), which showed marked metabolic disparity, pertaining to the flavonoid and tannin contents, among the Acer family plant extracts. Hence, we observed a marked variation in the levels of antioxidant activities, with Acer tataricum (TA) showing the highest relative levels of antioxidant metabolites (Fig 2B and 2C). Substantiating our results, interspecies variations in secondary metabolite compositions as well as related bioactivities have previously been described for plant species, including those in the genus Acer [7, 21]. Further, correlation analysis indicating the contribution of individual metabolites to bioactivities revealed that most tannins, abundant in TA, showed a strong positive correlation with antioxidant activity (Fig 3). Moreover, we conjecture that while the bioconversion process, there would be a large spectrum of metabolites that either remained undetected, uncharacterized, transiently produced, or not selected as discriminant at VIP>0.7 and p<0.5 from PLS-DA model, which might have contributed to the observed antioxidant activities. Further, it appears hard to conceive the perfect one-to-one relationship between metabolites and associated bioactivity, because the fermentation environment is extremely dynamic and has an overwhelming range of byproduct including the antioxidant phenolic compounds influencing the phenotypes. Overall, these results indicated that the observed metabolic disparity among the Aceraceae family extracts contribute to their different bioactivities. In congruence to our study, Choudhary and Swarnkar [22] have previously reported that a disparity in phenolic and flavonoid contents results in different antioxidant potentials among extracts from the same plant species.

The extensive and safe application of A. oryzae in fermentative bioprocesses owing to its abundant secretion of hydrolytic enzymes (α-galactosidase, β-glucosidase, xylosidase, and tannase) provide justification for its application in Acer extract fermentation for valuable chemicals. Following A. oryzae-mediated bioconversion, the metabolite compositions of the Acer family plant extracts changed considerably, thereby affecting the associated antioxidant activities. As indicated in the PCA score plot shown in Fig 4A, a clear metabolic disparity was evident, discriminating the 8-day fermented samples from the unfermented 0-day metabolic profiles. The tentative mechanism for the bioconversion pathway based on UHPLC-LTQ-IT-MS/MS analysis indicates that the relative levels of quercetin derivatives steadily decreased, whereas those of end-product quercetin increased, which can be attributed to the hydrolytic action of β-glucosidase enzymes breaking glucosidic bonds. For example, β-glucosidases from A. oryzae can hydrolyze the glucosidic bonds of piceid to release free resveratrol compounds [23]. Hence, we assume that A. oryzae-released enzymes convert rutin, quercetin-O-glucoside, and quercetin-O-arabinoside into the corresponding deglycoside compounds, and finally into end-product quercetin aglycones. Interestingly, the relative abundance of quercetin was increased up to 4 days and then decreased until the end of bioconversion process. We conjecture that the observed reduction in quercetin levels during the latter half of the bioconversion process could be associated with the release of quercetinases in the fermentation matrix. Quercetinases are extracellular enzymes produced by several Aspergillus species that promote the enzymatic oxygenation and cleavage of quercetin [24]. Another noteworthy point relates to gallic acid production following the successive bioconversion steps degrading tannin derivatives (Fig 5B). The reaction mechanism involves the loss of galloyl moieties from highly polymerized tannins, e.g., maplexin E, corilagin, and tetragalloyl glucose, converting these into smaller residues, mainly gallic acid. Hence, the successive bioconversion of precursor compounds and stable accumulation of gallic acid results in its higher abundance at the end of the bioconversion process. Tannase enzymes from A. oryzae have been reported to specifically catalyze the cleavage of a galloyl moiety from tannins, resulting in the release of gallic acid and glucose moieties [25]. By analogy, the aforementioned mechanisms are similar to those reported for tannic acid conversion to gallic acid mediated by A. awamori-secreted tannases [26]. Hence, the relatively higher abundance of gallic acid in TA end products compared with other Acer species might be affected by the relatively higher abundance of gallic acid precursor compounds, e.g., maplexin B, D, and E.

We accordingly propose that the observed trends of increasing antioxidant bioactivities during the bioconversion process for all Acer species plant extracts could be correlated with the enhanced release and stable accumulation of secondary metabolites with higher antioxidant potentials (Fig 4B). In particular, the initial titers of flavonoid glycosides and hydrolysable tannins were converted into quercetin and gallic acid derivatives with relatively higher antioxidant potentials compared with the precursors. Our assumptions are in agreement with previous studies describing the higher antioxidant bioactivities of aglycones or free-moiety compounds [27, 28]. Further, similar studies employing metabolomic approaches have confirmed enhanced bioactivities following the bioconversion process for green tea [29] and soybean [30] extracts.


In the present study, we adopted an integrated metabolomic approach involving MS-based analysis and bioactivity screening of various plant extracts followed by systematic delineation of their fermentative bioconversion to high value metabolites. The A. oryzae-mediated bioconversion of Acer species plant extracts revealed that the precursor metabolites including various flavanols (tannins) and flavonols (quercetin precursors) were converted to relatively stable derivatives, such as gallic acid and quercetins, respectively. Hence, a relatively stable accumulation of end-product derivative might affect the higher bioactivities of plant metabolite extracts following a bioconversion process. The methodology adopted in this work can accordingly serve as a platform toward enhanced recovery and economic production of plant derived natural products having high commercial value. However, in this regard, we propose that further detailed studies involving process optimization, pharmacological efficacies, and toxicity assessment of plant extract bioconversion products are needed.

Supporting information

S1 Fig. Antioxidant activity test, ABTS (A) and FRAP (B) for the seven Acer species.

Different letters are significantly different according to Duncan’s multiple-range test (p < 0.05).


S2 Fig. PLS-DA score plot of each Acer species derived from UHPLC-LTQ-IT-MS/MS datasets displaying variance between unfermented (0- day), 4- days and 8- days fermented.

Here, TR, Acer triflorum; PM, Acer pictum subsp.mono; BU, Acer buergerianum; KO, Acer komarovii; TA, Acer tataricum; PS, Acer pseudosieboldianum; PI, Acer pictum; PA, Acer palmatum.


S1 Table. Peak area and ANOVA of each significantly different metabolites replicates.


S2 Table. Anonymized data set afterward alignment.



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