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The antioxidant activity, α-glucosidase and acetylcholinesterase inhibition activity, and chemical composition of Paeonia delavayi petal

The antioxidant activity, α-glucosidase and acetylcholinesterase inhibition activity, and... Objectives: This study aimed to evaluate the functional activity and phytochemical composition in the flower petals of Paeonia delavayi (P. delavayi) in different colors. Materials and Methods: P. delavayi petal extracts were prepared by maceration in methanol, including purple petal extract (PPE), red petal extract (RPE), and yellow petal extract (YPE), and their antioxidant activity and α-glucosidase and acetylcholinesterase inhibition activities were evaluated. To correlate these measured activities to phytochemicals in the petals, an ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS)-based metabolomics method was applied to profile the compositions in the petals of different colors. Finally, the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways database was used to identify the related metabolic pathways that are responsible for the production of these polyphenolic phytochemicals in the petals. Results: The results showed that PPE had the highest total phenolic content, total flavonoid content, and the strongest 2,2ʹ-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) radical scavenging ability, ferric reducing antioxidant power, and acetylcholin- esterase inhibition ability in all three samples, while YPE showed the strongest 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activity and α-glucosidase inhibition ability. A total of 232 metabolites were detected in the metabolomic analysis, 198 of which were flavonoids, chalcones, a fl vonols, and anthocyanins. Correlation analysis indicated that peonidin-3- O-arabinoside and cyanidin-3-O-arabinoside were the major contribu- tors to the antioxidant activity. Principal component analysis showed a clear separation among these three petals. In addition, a total of 38, 98, and 96 differential metabolites were identified in PPE, RPE, and YPE, respectively. Pathway enrichment revealed 6 KEGG pathways that displayed significant enrichment differences, of which the anthocyanin biosynthesis, flavone and flavonol biosynthesis were the most enriched signaling pathways, revealing a potential reason for the differences in metabolic and functional levels among different colors of P. delavayi petal. Conclusions: P . delavayi petals in different colors have different metabolite contents and functional activities, of which the anthocyanin, flavone, and flavonol metabolites are critical in its functional activities, suggesting the anthocyanin biosynthesis, flavone and flavonol biosynthesis path - ways are the key pathways responsible for both petal color and bioactive phytochemicals in P. delavayi flowers. Keywords: Paeonia delavayi; antioxidant activity; α-glucosidase; acetylcholinesterase; metabolomics; Kyoto Encyclopedia of Genes and Genomes pathway. Introduction inhibit α-glucosidase, a key enzyme that is a therapeutic target in the management of diabetes (Zhang et al., 2019; Liu Paeonia delavayi (P. delavayi) Franch. is a perennial woody et al., 2021). Similar effects were observed for the root, stem, plant species that belongs to tree peony species (Cheng et al., and leaves of P. delavayi (Huang et al., 2021; Chen et al., 1998; Hong and Pan, 1999; Pękal and Pyrzynska, 2014). The 2022). Thus, P. delavayi may also play a role in glycemic con- tree peony has been well known over thousands of years for trol. However, previous studies mostly focused on particular its various floral colors, nutritional benefits, and edible and peony species. As an endemic species, P. delavayi is a widely medicinal properties (Li, 2013; Zhang et al., 2017). It has available germplasm resource in the Southwest of China. been reported that tree peony flowers are abundant in bio - Plants of P. delavayi species show distinct variations in their active compounds such as polyphenolics and exert therapeutic flower colors, showing yellow, red, or purple. These flower effects against various diseases, such as aging, neurological color attributions strongly indicate that the polyphenolic diseases, and coronary heart disease (Finkel and Holbrook, compounds, especially flavonoids and anthocyanins, may be 2000; Barnham et al., 2004; Wang et al., 2005; Zhao et al., differentially accumulated in their flower petals of different 2012; Seifried et al., 2017). In addition, tree peony seed coat colored flower petals (Yan et al., 2020; Wang et al., 2021). extracts have been reported to effectively and competitively Received 28 December 2021; Revised 23 February 2022; Editorial decision 8 March 2022 © The Author(s) 2022. Published by Oxford University Press on behalf of Zhejiang University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. 2 J. Song et al. The petal is one of the most important organs of a 10 min. The supernatants were collected and filtered through flowering plant, which is involved in plant growth and devel - Millipore filters (0.5 µm) and each of the extracts of the opment, and primary and secondary metabolite regulations. purple, red, and yellow flower petals was aliquoted into a set The different components and contents of the chemical com- of tubes and stored at –20 °C until further analysis. position of petals, especially flavonoids and anthocyanins, confer the various colors and functions. Many studies have Total phenolic content investigated flavonoids and anthocyanins in plants and The total phenolic content (TPC) in the flower petal extracts was their relationships with flower color, for example, chalcone, determined by the Folin–Ciocalteau (FC) method ( Wang ZX et dihydroflavonoid, and flavone mainly yield yellow flowers al., 2020) with some modifications. In a 96-well microplate, (Mol et al., 1998; Harborne and Williams, 2000; Ferreyra 40 µL of diluted extract or reference sample, 125 µL of Folin– et al., 2012; Deguchi et al., 2013). For tree peony flowers, Ciocalteu reagent (0.5  mol/L), and 100 µL of Na CO were 2 3 flavonoids and anthocyanidins have been reported to be the added, mixed and incubated for 30  min in the dark at room main substances, which have proven to be excellent anti- temperature for colorimetric development to complete in the re- oxidants and antidiabetic resources (Wang et al., 2001a, action solution. Absorbance of the reaction solution was meas- 2001b; Li et al., 2009). Previous literature demonstrated ured at 760 nm wavelength using a microplate reader (Biotek, that tree peony flowers in different colors showed different Winooski, VT, USA). The standard calibration curve of gallic antioxidant capacities (Fan et al., 2012; Zhang et al., 2017; acid was obtained using a series of concentrations by dilutions Xiang et al., 2019). Interestingly, yellow P. delavayi exhibited (10, 20, 40, 60, 80, and 100 µg/mL) for calculating TPC, and stronger ferric reducing antioxidant power and 2,2ʹ-azino-bis TPC results for flower petals were expressed as µg of gallic acid (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt equivalents (GAE)/g dry extract (DE). (ABTS) radical scavenging activity than other yellow peonies (Li et al., 2009). Although there has been more and more Total Flavonoid Content researches on the edible and medicinal values of tree peony A modified method by Wang ZX et al. (2020) was used to flowers, the relationship between its flower colors and func - quantify the total flavonoid content (TFC). In a 96-well tions is poorly investigated. microplate, reaction solution was prepared in each well, 20 µL Therefore, this study aimed to evaluate the functional of NaNO (3%, mass concentration) was mixed with 40 µL activity and chemical composition of P. delavayi petals in of properly diluted extract or reference sample followed by different colors. Liquid chromatography (LC)/mass spectrom- a 6-min incubation. Subsequently, 20 µL of Al (NO ) (6%, 3 3 etry (MS)-based metabonomic technology was further used to mass concentration) was added to the reaction solution and elucidate the chemical basis of its function and the potential the solution was incubated for an additional 6 min. At the end mechanism of flower color formation. This research could in - of the incubation, 140 µL of NaOH (4%, mass concentra- crease the commercial value of P. delavayi. tion) and 70% methanol (containing 1% hydrochloric acid) were added to each well followed by 15  min incubation at room temperature. Absorbance of the obtained reaction so- Materials and Methods lutions was measured at 510 nm wavelength. Rutin solutions Chemical reagents (200, 400, 600, 800, and 1000 µg/mL) were used to make a standard reference curve and the flavonoid contents are pre - Analytical-grade formic acid, methanol, Folin–Ciocalteu sented as µg of rutin equivalents (RE)/g DE. reagent, gallic acid, rutin, quercetin, 2,2-diphenyl-1- picrylhydrazyl radical (DPPH), ABTS, 2,4,6-tri(2-pyridyl)- 1,3,5-triazine (TPTZ), iron chloride (FeCl ·6H O), ascorbic DPPH radical scavenging assay 3 2 acid (Vc), butylated hydroxytoluene (BHT), and other DPPH assay was used to determine the antioxidant potential chemicals were purchased from Aladdin (Shanghai, China). of the flower petal extracts, following the previously reported Chromatographic acetonitrile, acarbose, α-glucosidase method (Ghane et al., 2018), with some modifications. In from Saccharomyces cerevisiae (G5003), 5,5ʹ-dithiobis each well of a 96-well microplate, diluted extract or reference 2-nitrobenzoic acid (DTNB), acetyl-chymotrypsin sample (100 µL) of various concentrations was mixed with acetylthiocholine iodide (ATCI) were purchased from Sigma- 100 µL DPPH reagent (Zhang et al., 2014) and the mixed Aldrich (St. Louis, MO, USA). reaction solution was then subjected to a 30-min incubation at room temperature in darkness. Absorbance of the colori- Preparation of extracts metric development of the reaction solution in the microplate was measured at 517  nm using a plate reader. The blank Purple, red, and yellow flower petals of P. delavayi plants in control was prepared by mixing equal volumes of methanol natural habitats were harvested from Shangri-La (Yunnan, and DPPH. Vc and BHT were used as positive controls. The China). All the petals were sampled on April 20, 2021 and DPPH radical scavenging activity was presented as IC value stored at –80 °C until analysis. (the concentration providing 50% inhibition, µg/mL) and Antioxidant extractions from the P. delavayi flower petals was calculated using the following Equation (1): were carried out according to the previous developed method (Hua et al., 2018), with a slight modification. Briefly, 0.5 g of Control absorbance − Sample absorbance Inhibitory percentage = × 100% purple, red, or yellow flower petals were ground in liquid ni - Control absorbance (1) trogen to powder, and the powder was extracted with 10 mL of 70% methanol aqueous solution (containing 1% hydro- ABTS radical scavenging assay chloric acid) at 4 °C in the dark and overnight. Subsequently the samples were ultrasonicated for 30  min in an ice bath The ABTS assay was also employed for determination of anti- (parameters) prior to centrifugation at 10  000 r/min for oxidant capacity in the flower petal extracts. The assay was Functional activity and phytochemical composition in Paeonia delavayi petals 3 performed in 96-well microplates and carried out according Metabolomic analysis to a method reported in the literature (Ghane et al., 2018). The metabolomics analysis was performed by Wuhan For each well, 50 µL of diluted extract or reference sample in Metware Biotechnology Co., Ltd. (www.metware.cn). a range of concentrations was mixed with 200 µL of diluted Briefly, the sample extracts were analyzed using an ultra ABTS (7 mmol/L) working solution. The absorbance of the performance liquid chromatography-electrospray-tandem reaction was recorded at 734 nm by a plate reader after 6-min mass spectrometry (UPLC-ESI-MS/MS) system (UPLC, incubation at room temperature in the dark. Methanol was SHIMADZU NexeraX2, Kyoto, Japan; MS, Applied used as negative control, Vc and BHT were used as positive Biosystems 4500 Q TRAP, Foster City, CA, USA) . The ana- controls. The results of ABTS radical scavenging assays were lytical conditions were as follows: column, Agilent SB-C18 presented as shown in Equation (1). (1.8 µm, 2.1 mm×100 mm); Agilent Technologies, Palo Alto, CA, USA). The mobile phase consisted of solvent A—pure water with 0.1% formic acid, and solvent B—acetonitrile Ferric reducing antioxidant power assay with 0.1% formic acid. Sample measurements were per- The ferric reducing antioxidant power (FRAP) was quantified formed with a gradient program that employed the starting by the reported method (Liao and Banbury, 2015). The FRAP conditions of 95% A, 5% B. Within 9 min, a linear gradient solution made up of 1  mL TPTZ (10 mmol/L), 1  mL FeCl 3 to 5% A, 95% B was programmed, and a composition of (20 mmol/L) and 10 mL acetate buffer (pH 3.6) was kept at 5% A, 95% B was kept for 1 min. Subsequently, a compos- 37 °C. In each well of a 96-well microplate, 50 µL of diluted ition of 95% A, 5% B was adjusted within 1.10  min and sample was mixed with 250 µL of freshly prepared FRAP kept for 2.9 min. The flow velocity was set at 0.35 mL/min. working solution. The absorbance was measured at 593 nm The column oven was set to 40 °C. The injection volume after incubation for 10 min in the dark at 37 °C. The standard was 4 μL. The effluent was alternatively connected to an calibration curve of FeSO was obtained using dilutions 4 ESI–triple quadrupole–linear ion trap (LIT)–MS. LIT and (20, 40, 60, 80, and 100 µg/mL), and results were expressed triple quadrupole (QQQ) scans were acquired on a triple as µg of FeSO equivalents/mg DE. Vc and BHT were used as 4 quadrupole–LIT mass spectrometer (Q-TRAP), equipped positive controls. with an ESI Turbo Ion-Spray interface, operating in posi- tive and negative ion mode and controlled by Analyst 1.6.3 software (https://sciex.com/products/software/analyst- α-Glucosidase inhibition assay software). The ESI source operation parameters were as fol- The α-glucosidase inhibition assay was performed according lows: ion source, turbo spray; source temperature 550 °C; to a previously developed protocol (Liao and Banbury, 2015) ion spray voltage (IS) 5500 V (positive ion mode)/–4500 V with slight modifications. The enzyme reaction in each well of (negative ion mode); ion source gas I, gas II, and curtain a 96-well microplate was set up by adding 50 µL of sample of gas were set at 50.0, 60.0, and 25.0 MPa, respectively. The various concentrations and 25 µL α-glucosidase (0.1 U/mL) collision-activated dissociation was high. Instrument tuning in phosphate buffer. The reactions in the microplate were and mass calibration were performed with 10 μmoL/L and mixed prior to an incubation at 25 °C for 10  min; 25 µL 100 μmoL/L polypropylene glycol solutions in QQQ and of p-nitrophenyl-ɑ-d-glucopyranoside (5 mmol/L) was LIT modes, respectively. QQQ scans were acquired at mul- added subsequently and the mixture was incubated for an - tiple reaction monitoring (MRM) mode with collision gas other 15 min at 25 °C. One hundred microliters of Na CO 2 3 (nitrogen) set to medium. (0.2 mol/L) was added to stop the enzymatic reactions. The In the MRM mode, the quadrupole first screens the pre - absorbance was recorded with a plate reader at 412  nm cursor ions of the target substances and excludes the ions of wavelength. Methanol and acarbose were, respectively, used other molecular-weight substances in order to preliminarily as negative and positive controls. The α-glucosidase inhib- eliminate interference. Then the precursor ions are induced ition ability was expressed as IC (mg/mL). Inhibitory per- to ionize by the collision cell and break up to form many centage of the enzyme activity was calculated according to fragment ions. To eliminate nontarget ion interference, Equation (1). these fragment ions are filtered by triple quadrupole, and the fragment ions with the desired characteristic were finally -6 Acetylcholinesterase inhibition assay selected. By comparing the accurate mass (error<2×10 ), -6 The acetylcholinesterase (AChE) inhibitory ability was de- MS2 fragments (error<5×10 ), secondary mass spectrom- termined according to the published procedure ( Luo et al., etry (MS2) fragment isotope distribution, and retention time 2019) with some modifications. A 50-µL diluted sample with the standards database (MetWare Database, https:// at various concentrations was mixed with 30 µL ATCI sourceforge.net/projects/metware/), the substances were (15 mmol/L) and 75 µL DTNB (3 μmol/L) in a 96-well identified. For the metabolites not matched to standard sub- microplate and incubated at 30 °C for 10 min in the dark; stances, they were matched to public databases or manu- 20 µL of 0.1 U/mL AChE was added and mixed; then, ally identified based on their mass spectral cleavage rules. 50 µL of phosphate buffer was added to initiate the reaction. The peak areas of ion chromatograms for typical ions of At the same time, the absorbance was measured at 405 nm. the metabolites were integrated and calibrated by using After 5 min of incubation in darkness at room temperature, MultiQuant software (v.3.0.3; https://sciex.com/products/ the absorbance was measured again at 405  nm. Methanol software/multiquant-software), and were used to represent and galantamine were, respectively, used as negative and the relative content of the corresponding substance (Fraga positive controls. The AChE inhibitory ability was expressed et al., 2010; Jiang et al., 2020). Finally, corresponding dif- as the IC value (mg/mL). The AChE inhibition assay was ference analysis and Spearman correlation analysis were recorded using Equation (1). performed. 4 J. Song et al. Statistical analysis antioxidants beside phenolic compounds also react with the FC reagent (Everette et al., 2010). All data were presented as mean±standard deviation (SD) of As measured with the aluminum complexation reaction three parallel measurements, analyzed by analysis of variance method, the TFCs displayed a significant difference among and Tukey’s multiple comparison test (P<0.05). Statistical the three petal extracts. The purple flower petals showed the analysis was performed with SPSS 26.0 software (IBM, highest TFC ((133.15±0.87) mg RE/g DE), followed by red Armonk, NY, USA) and ORIGIN 2018 software (https:// flower petals ((101.69±3.03) mg RE/g DE) and yellow flower www.originlab.com/). The correlations efficient between petals ((86.79±2.23) mg RE/g DE; Figure 1B). This may be each variable were calculated by the two-tailed Pearson directly related to the types of flavonoids and the genetic char- test. Principal component analysis (PCA), Spearmen correl- acteristics of P. delavayi (Wang ZX et al., 2020). Flavonoids ation clustering heatmap, associated network diagram, the are a class of very important plant secondary metabolites, and Venn diagram and the volcano plots were performed within plants usually accumulate high levels of flavonoids in their R (v4.0.3). All data used unit variance scaling (UV) nor - tissues. Flavonoids also provide strong antioxidant proper - malization. The formula for UV normalization is z=(x–μ)/σ ties that contribute toward human health. Our previous study (where x is a specific score, μ is the mean, σ is the standard revealed that flower petals accumulated a wide range of fla - deviation), and orthogonal partial least squares discriminant vonoids apart from anthocyanins (Wang et al., 2021). While analysis (OPLS-DA) is logarithmically transformed and then the aluminum complexation method has been regarded as the centrally processed. Significantly regulated metabolites among standard to measure total flavonoids in food and beverages, a groups were determined by variable importance in projection detailed study (Pękal and Pyrzynska, 2014) revealed that this (VIP)≥1 and absolute log fold change (FC)≥1. By using the method was highly biased toward rutin, luteolin, and catechin R package MetaboAnalystR, VIP values were extracted from phytochemicals. Given the wide range of flavonoids present the OPLS-DA result, which also contained score plots and in the flower petals of P. delavayi, the TFC determined with permutation plots. The data were log transformed (log ) and this method may not be a true representation of the TFC in mean centered before OPLS-DA. In order to avoid overfitting, the petals, but rather a correlation of the total flavonoids in a permutation test (200 permutations) was performed. the petals. Results Antioxidant properties Both DPPH and ABTS assays have been widely used for the Total phenolic content and total flavonoid content measurements of the antioxidant capacities, and the prin- The FC colorimetric assay has been widely used for phenolic ciples of both methods are on the quenching of colored rad - and polyphenolic antioxidant quantification in food and bev - icals DPPH or ABTS. The color reductions of DPPH or ABTS erage industries (Wang ZX et al., 2020). In our study, a sig- radicals are negatively correlated with the capacities of anti- nificant difference in the TPC was demonstrated in the flower oxidants present in the natural products. Previous studies petals among the different colors (P<0.05). Purple petal ex- have indicated that the petals from tree peony species have tract (PPE) gave the highest TPC value ((469.48±6.88) mg strong antioxidant activity, in correlation with the abundance GAE/g DE), yellow petal extract (YPE) had the lowest value of bioactive compounds (Li et al., 2009; Su et al., 2017; Wang ((377.17±1.26) mg GAE/g DE), and red petal extract (RPE) ZX et al., 2020). In this work, apart from DPPH and ABTS showed TFC of (388.35±9.84) mg GAE/g DE (Figure 1A). assays, FRAP assays, based on the conversion of colorless Clearly, the purple flower petals accumulated much higher ferric complex into intense blue when antioxidants are pre- total phenolic compounds as determined with the FC method. sent in the reaction solution, was also used to estimate the Similar results were observed in the P. delavayi seeds (Yan et antioxidant activity of tree peony petals. al., 2020). The FC method is based on the reaction of the re- ducing power of phenolic compounds; a detailed study on the DPPH radical scavenging assay FC reagent toward various classes of compounds in plants suggested that the FC assay should be treated as a measure DPPH radical scavenging assay is frequently used to deter - of total antioxidant capacity of plant extract, because other mine the free radical scavenging capacity of target compounds Figure 1. Total phoenolic content (TPC; A) and total flavonoid content (TFC; B) of Paeonia delavayi petals extraction. For the same determination, bars with different lowercase letters suggest significant difference (P<0.05). GAE, gallic acid equivalents; DE, dry extract; RE, rutin equivalents; PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract. Functional activity and phytochemical composition in Paeonia delavayi petals 5 Figure 2. The antioxidant activity of the petal extracts of Paeonia delavayi. (A) DPPH radical scavenging ability, (B) ABTS radical scavenging ability, (C) ferric reducing antioxidant power. Bars with different lowercase letters indicate insignificant difference (P<0.05). DE, dry extract; PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract; Vc, ascorbic acid (as positive control); BHT, butylated hydroxytoluene (as positive control). or extracts (Nascimento et al., 2020). As shown in Figure 2A, the purple and yellow flower petals had very similar levels of radical scavenging capacities, (324.24±0.98) μg Trolox/mg DE and (336.08±4.02) μg Trolox/mg DE, re- spectively. The scavenging capacity measured with the DPPH method was marginally lower despite being significant stat - istically ((290.12±2.11) µg Trolox/mg DE). Although below the positive control Vc, the DPPH radical scavenging capaci- ties derived from the flower petals of all colors were signifi - cantly higher than the control BHT at the concentration used (P<0.05). Vc is popularly acclaimed as a potent antioxidant and free radical scavenger (Li et al., 2021) , while BHT is a commonly used antioxidant, recognized as safe for use in foods containing fats, and in the pharmaceutical, petroleum products, rubber, and oil industries (Yehye et al., 2015). ABTS radical scavenging assay Figure 2B shows the results of the ABTS radical scavenging activity, the ABTS assay results being inconsistent with the DPPH assay. PPE had the highest scavenging activity, which amounted to (631.68±7.32) µg Trolox/mg DE, followed by RPE ((517.19±7.12) µg Trolox/mg DE), whereas YPE was Figure 3. Pearson correlation heatmap among bioactivities in the petal (447.24±9.67) µg Trolox/mg DE. From Figure 3, ABTS radical extracts of Paeonia delavayi. α-Glu, the IC value for α-glucosidase scavenging ability was observed to exhibit a high correlation inhibitory activity; AChE, acetylcholinesterase; TPC, total phoenolic content; TFC, total flavonoid content; FRAP, ferric reducing antioxidant with TPC and TFC (r=0.944 and 0.989, P<0.01), which meant power. that phenolics and flavonoids were the main components scav - enging ABTS radicals. Compared with the controls, the scav- enging ability of PPE and RPE was significantly higher than indices, respectively. Considering that ‘antioxidant capacity’ that of BHT ((536.1±14.33) µg Trolox/mg DE) but lower than is a comprehensive assessment using different methods and that of Vc ((1754.52±48.85) µg Trolox/mg DE). principles, we considered the phenolic and flavonoid com - pounds both to be major contributors to the antioxidant ac- Ferric reducing antioxidant power assay tivities of P. delavayi (Wang ZX et al., 2020). The FRAP assay is usually applied to evaluate the reducing The radical scavenging capacities were clearly different capacity of plant extracts (Wang SL et al., 2020). As demon- when the DPPH method was used in comparison with the strated in Figure 2C, the FRAP values of samples from the lar- other two methods (Figure 2). Both ABTS and ferric reduc- gest to the smallest were as follows: PPE ((941.23±30.46) µg tion methods gave the purple flower petals the highest scav - FeSO /mg DE), RPE ((738.64±21.74) µg FeSO /mg DE), and enging capacity, followed by red and yellow petals ( Figure 2), 4 4 YPE ((694.72±23.76) µg FeSO /mg DE). Although the level but this was not the trend measured with the DPPH method was not as high as Vc, PPE was comparable to BHT, while RPE (Figure 2A). The DPPH method might not be reflecting the and YPE were lower than Vc and BHT (P<0.01). In addition, true value in the colored petals of purple and red flowers the high correlation of FRAP with TPC and TFC (r=0.960 and due to the fact that the detecting wavelength (517  nm) is 0.968, P<0.01) indicated that the phenolic and flavonoid com- also around the maximum absorption from anthocyanins 3+ ponents also contributed to the Fe reducing activity. (500–530  nm). This interference to the detection may have From the present results, the phenolic and flavonoid con- underestimated the scavenging power in the highly colored tents significantly contributed to the different antioxidant peony petals. 6 J. Song et al. addition, there was a high and significant negative correl- α-Glucosidase inhibitory ability ation between α-glucosidase inhibitory ability with DPPH, It is well known that active phytoconstituents such as fla- ABTS, and FRAP (r=–0.964, –0.885, and –0.895, P<0.01), vonoids and polyphenols could decrease postprandial hyper - respectively. This indicated that these various compounds in glycemia by inhibiting the activity of α-glucosidase, thus P. delavayi petals with a different mechanism of antioxidant having important health benefits in treating/preventing type-2 action also played an important role in α-glucosidase inhibi- diabetes (Shim et al., 2003). In this work, we assessed the tory effect. hypoglycemic potential of P. delavayi by investigating their α-glucosidase inhibitory abilities. Acetylcholinesterase inhibitory ability As shown in Figure 4A, all samples and the positive con- trol (acarbose) inhibited α-glucosidase in a concentration- Alzheimer’s disease (AD) is a chronic syndrome that causes dependent manner. The orders of inhibition activities from progressive deterioration of the central nervous system. strong to weak were as follows: acarbose (IC value was According to the cholinergic hypothesis, the reduction in (9.46±0.13) µg/mL), YPE (IC (1.64±0.26) mg/mL), RPE (IC acetylcholine synthesis is the main cause of AD, and increasing 50 50 (1.73±0.14) mg/mL), and PPE (IC (2.027±0.16) mg/mL). the cholinergic levels in the brain by inhibiting the AChE is a The result denoted that all samples had certain ability to potential therapeutic strategy (Bartus et al., 1982; Sharma, inhibit α-glucosidase but significantly lower than control 2019). Natural products are considered to be beneficial AChE (Figure 4B). The reason may be that these three extracts inhibitors, and gain considerable research interest, because were a mixture of many substances, and the active com- they are economical, safe, effective, and have low side effects. pounds with α-glucosidase inhibitory ability were only a From Figure 5B, PPE, RPE, and YPE inhibited AChE with IC small part of the total mixture (Wang ZX et al., 2020). In value of (2.77±0.45), (6.06±0.18), and (4.32±0.33) mg/mL, Figure 4. The α-glucosidase inhibitory activity of the petal extracts of Paeonia delavayi. Bars with different lowercase letters indicate insignificant difference (P<0.05). PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract; IC , the concentration providing 50% inhibition. Figure 5. The AChE inhibitory activity of the petal extracts of Paeonia delavayi. Bars with different lowercase letters indicate insignificant difference (P<0.05). AChE, acetylcholinesterase; PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract; IC , the concentration providing 50% inhibition. Functional activity and phytochemical composition in Paeonia delavayi petals 7 respectively, where the RPE value was more than twice that 7-O-neohesperidoside, and chrysoeriol 7-O-glucoside (Zhao of PPE. Although the three samples were lower in inhibition et al., 2016; Hua et al., 2018; Shi et al., 2018). Additionally, of AChE than control galantamine (IC (1.9±0.11) µg/mL), 5 anthocyanins of these 197 flavonoids were first found in they also showed some inhibition capacity as concentra- P. delavayi petals. They were cyanidin-3-O-(6ʹʹ-O-malonyl) tion increased (Figure 5A). Correlation analysis (Figure 3) glucoside-5-O-glucoside, cyanidin-3-O -arabinoside, peonidin- showed that both phenolic and flavonoid compounds had 3-O-arabinoside, peonidin-3-O-sambubioside, and peonidin- a great inhibitory effect on AChE; the high degree of correl- 3-O-sophoroside-5-O-glucoside. ation between AChE inhibitory ability with DPPH radical To assess the relationship between these metabolites scavenging ability, ABTS radical scavenging ability, FRAP, and the biological activities of samples, we conducted a and α-glucosidase inhibitory ability (r=–0.87, –0.89, –0.89, Spearman association analysis between the relative content and 0.75, P<0.01), respectively, also demonstrated this point. of the metabolites of all samples and their functional activ- ities. The top 20 metabolites with the highest association coefficients are shown in Figure 6. According to Figure 6A, Metabolomic Analysis peonidin-3-O-arabinoside and cyanidin-3- O-arabinoside Metabolome analysis were strongly associated with TPC, TFC, DPPH radical Our results presented above appeared to attribute the dif - scavenging activity, ABTS radical scavenging ability, and ferent functional activities to the color difference of the petals FRAP. These associations were also clearly exemplified by from which the extracts were derived. In general, flower the network diagram of association in Figure 6B. Peonidin- color is an evolutionary result caused by the accumulation of 3-O-arabinoside and cyanidin-3- O-arabinoside belong to pigments such as flavonoids (anthocyanins). Diverse flower anthocyanins, which play the major role in the purple, blue colors play a critical role in pollination biology and the me- and red color presentation of plant tissues, and exhibited tabolites also have physiological functions in plants (Ren et strong antioxidant activity (Chuntakaruk et al., 2021). al., 2017; Wu et al., 2018). Therefore, to further elucidate the In our study, although a strong correlation between the phytochemical basis of these functional differences, metabolic anthocyanin-3-O-arabinosides and antioxidant activities analysis was carried out with UPLC-MS/MS, particularly to was revealed, the fact that these anthocyanins are posi- target the flavonoids in the petals. tively correlated with the total polyphenolic compounds A total of 232 metabolites were detected, including 197 and TFCs points to the collective effect of polyphenolic flavonoids and 35 tannins. Specifically, the 197 flavonoids compounds and anthocyanins attributing to antioxidant were classified into 9 categories, including 75 flavonols, activities. From previous work, we showed that antho- 9 anthocyanins, 13 flavonoid C-glycosides, 5 flavanols, 4 cyanin glucoside in red flower petals was at a much higher di-hydroflavonols, 9 dihydroflavones, 5 chalcones, and 3 level than anthocyanin arabinosides (Wang et al., 2021). In isoflavones. The details about these metabolites are shown a recent study, peonidin-3-O-arabinoside and cyanidin-3- in Table S1, many of which have previously been reported O-arabinoside were discovered as potent pancreatic lipase to be associated with flower colors, such as cyanidin-3, inhibitors (Xie et al., 2020). No other metabolite was 5-di-O-glucoside, peonidin-3-O-glucoside, apigenin found to be significantly associated with AChE inhibitory Figure 6. (A) The top 20 Spearmen correlation clustering heatmap between biological activity and the content of the metabolites in the petal extracts of Paeonia delavayi. **P<0.01, *P<0.05. (B) Associated network diagram. The red line represents positive correlation, and the green line represents negative correlation, the thickness of the line represents the level of the correlation coefficient (P<0.05). α-Glu, the IC value for α-glucosidase inhibitory activity; AChE, acetylcholinesterase; TPC, total phoenolic content; TFC, total flavonoid content; FRAP, ferric reducing antioxidant power. 8 J. Song et al. activity, while α-glucosidase inhibitory activity was only cluster heatmap (Table S2, Figure 7A). The differences between significantly related to gallic acid ( r=0.83, P<0.01) and group YPE and groups PPE and RPE were significant, while peonidin-3-O-arabinoside (r=0.71, P<0.05). This indicated the difference between PPE and RPE was less pronounced, again that these two functional activities might be a re- indicating closer homogeneity between PPE and RPE. The flection of collective actions from multiple phytochemicals. Venn diagram (Figure 7B) demonstrated the shared and unique Furthermore, other phytochemicals that have not been differential metabolites between the three groups. Fewer differ - identified as significant variables in this study also need ential metabolites between PPE and RPE were observed, which attention. For example, tannins, as one of the other major also demonstrated the closeness between the two groups. components of P. delavayi petals, did not demonstrate a Among them, a total of 11 metabolites were differentially accu- significant correlation with biological activity in this study mulated between all the petal colors, including two flavonoids, in our correlation analysis, but there were many reports five anthocyanins, three flavonols, and one dihydroflavone. showing tannins have strong free radical scavenging ac- These observations were further supported by PCA that tivity and α-glucosidase inhibitory ability (Cardullo et al., can be used to identify relationships among variables. From 2018; Noorolahi et al., 2020). This reinforces the concept Figure 7C, these three groups were clustered separately from that polyphenols, flavonoids, and anthocyanins together each other, which indicated the distinctions of purple, red, and provide antioxidant activities and the inhibitory effect of yellow P. delavayi petals on a metabolite level. PC1 showed the enzymes observed in our study, while certain individual clear discrimination of YPE versus PPE and RPE, while PPE phytochemicals could be used as indexes at a practical and RPE could be discriminated at PC2. The two principal level for the screening of plant materials for healthy food components contributed 69.50% and 11.64%, respectively, supplements. which meant they could fully reflect the overall information. We further performed pairwise comparisons for the metab- olite data to identify further differences among three groups Differential metabolites analysis (Figure 8). Each file is filtered according to the fold change All 232 metabolites were normalized and then the top 30 me- values, which must be greater than or equal to 2 or less than tabolites were analyzed for differential accumulations by a 0.5, and the VIP scores greater than or equal to 1. The results Figure 7. (A) Top 30 differentially accumulated metabolites accumulation pattern of Paeonia delavayi petals. In the heatmap, differentially metabolites marked with red represent high content and blue were low content in Paeonia delavayi petals, respectively); (B) The Venn diagram shows the overlapping and cultivar-specific differential metabolites in the group PPE, RPE, and YPE; (C) Principal component analysis on the relationships among those variables. PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract. Functional activity and phytochemical composition in Paeonia delavayi petals 9 showed that there were 98 significant differential metabolites of anthocyanins and flavonoids in the functional activity of when comparing the PPE group with the YPE group, among P. delavayi petals, and was consistent with those previously which 44 were downregulated and 54 upregulated ( Figure 8A). reported (Zhao et al., 2016; Hua et al., 2018; Shi et al., 2018). For comparisons between RPE and YPE groups (Figure 8B), 96 differential metabolites were identified, of which 47 were KEGG enrichment analysis downregulated and 49 upregulated. When PPE was com - Diverse secondary metabolites are present in plants. These pared with RPE groups (Figure 8C), there were only 38 dif- secondary metabolites are mainly regulated by metabolic ferential metabolites (17 downregulated and 21 upregulated); pathways, which in turn affect their functional activity. In this the similar degree between PPE and RPE was also demon - study, the metabolic pathways associated with these differen - strated. The differential metabolites of each comparison tial metabolites were annotated using the Kyoto Encyclopedia group were also visualized with the corresponding volcano of Genes and Genomes (KEGG) database. plots (Figures 8D–8F). Overall, all groups were significantly KEGG pathway enrichment analysis indicated that the different from each other (all pairwise comparisons P<0.05), same six pathways were significantly enriched both be - and anthocyanins and flavonoids were the main difference me- tween PPE and YPE (Figure 9A) and RPE and YPE (Figure tabolites. From the figure, PPE contained more anthocyanins 9C), including flavonoid biosynthesis (ko00941), antho - when compared to RPE and YPE, while YPE has more fla - cyanin biosynthesis (ko00942), isoflavonoid biosynthesis vonoids than PPE and RPE. Combined with our functional (ko00943), flavone and flavonol biosynthesis (ko00944), activity results above, this result revealed the substantial roles biosynthesis of secondary metabolites (ko01110), and Figure 8. (A–C) Top 30 differentially accumulated metabolites accumulation pattern of Paeonia delavayi petals in different comparison groups. In the heatmap, differential metabolites marked with red represent high content and blue low content in Paeonia delavayi petals, respectively. (D–F) Volcano plots of differential metabolites. In the figure, green dots represent downregulated differentially expressed metabolites, red dots represent upregulated differentially expressed metabolites, and gray represents detected but not significantly different metabolites. Significantly different metabolites among groups were determined by VIP≥1 and an absolute log fold change (FC)≥1. PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract. Figure 9. Pathway enrichment analysis of differential metabolites for (A) PPE versus YPE, (B) PPE versus RPE, and (C) RPE versus YPE. The color of the point represents the P value, and the size of the point represents the number of differentially enriched metabolites. PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract. 10 J. Song et al. metabolic pathway (ko01100). Among them, anthocyanin anthocyanin and flavone of different colors' P. delavayi petals. biosynthesis was the most significant enrichment pathway. Changes in these pathways caused the difference in metabol- For the differential metabolites between PPE and RPE, only ites, finally leading to the difference in flower color and func - the flavonoid biosynthesis (ko00941), anthocyanin biosyn - tional activity of P. delavayi petals. thesis (ko00942), and flavone and flavonol biosynthesis In conclusion, our study characterized functional activities, (ko00944) pathways were significantly enriched ( Figure key active compounds, differential metabolites, and meta- 9B). Taken together, anthocyanin biosynthesis, flavone and bolic pathways of purple, red, and yellow P. delavayi petals, flavonol biosynthesis were the most enriched signaling path - which could provide a theoretical basis for further studies ways, and these pathways are presented in Figures S1 and and utilization of P. delavayi. Furthermore, more in-depth S2. It is well known that flavone and flavonol are early steps and comprehensive functional assessment, including the iso- of the flavonoid biosynthetic pathway, and the anthocyanins lation and preparation of the key active compounds and are late steps of the same flavonoid biosynthetic pathway. their mechanisms of action, should be considered in future During plant growth and development, flavonoids are re - research. sponsible for the coloration of fruits, flowers, and seeds, while the color changes are predominantly due to the result Author Contributions of anthocyanin accumulation (Sokół-Łętowska et al., 2018; Jing Song, Zhenxing Wang, and Juan Wang conceived and Xiao et al., 2019; Shen et al., 2021). Therefore, the activity designed the experiments; Jing Song performed the experi - of these metabolic pathways determines the content of the ment and wrote the manuscript; Jing Song, Zhenxing Wang, metabolites that lead to different colors and biological activ - and Huaibi Zhang analyzed the data, edited and reviewed the ities of P. delavayi petals. manuscript; Jing Song and Juan Wang contributed to mater- ials collection. All authors have read and agreed to the pub - lished version of the manuscript. Conclusions Flower color is an important horticultural trait of higher Funding plants. Owing to its diverse flower coloration, P. delavayi is an ideal model species to study the secondary metabolism This research was funded by the ‘High-level Foreign Experts’ of flowers. However, the bioactivity and the phytochemical Special Project of Yunnan Province Thousand Talents Plan compositions of P. delavayi petals in different colors are still and the ‘Yunling Industrial Technology Leading Talents’ poorly investigated. Special Project of Yunnan Province Ten Thousand Talents In this study, we compared the active phytochemical Plan (No. [2018]212), the Digitalization, Development and compositions, antioxidant activity, α-glucosidase inhib- Application of Biotic Resource of the Science and Technology ition ability, and acetylcholinesterase inhibition ability of Planning Project of Yunnan Province (No. 202002AA10007), P. delavayi petals in three distinct colors (purple, red, and and the Scientific Research Fund Project of Yunnan Provincial yellow), and found that phenolic compounds, including fla - Department of Education (No.2020Y0412), China. vonoids and anthocyanins, are the major contributors to anti- oxidant activities, while α-glucosidase inhibition ability and Conflict of Interest acetylcholinesterase inhibition ability might be the coaction The authors declare no conflict of interest. of multiple compounds. 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The antioxidant activity, α-glucosidase and acetylcholinesterase inhibition activity, and chemical composition of Paeonia delavayi petal

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Food Quality and Safety , Volume 6: 1 – Mar 18, 2022

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Abstract

Objectives: This study aimed to evaluate the functional activity and phytochemical composition in the flower petals of Paeonia delavayi (P. delavayi) in different colors. Materials and Methods: P. delavayi petal extracts were prepared by maceration in methanol, including purple petal extract (PPE), red petal extract (RPE), and yellow petal extract (YPE), and their antioxidant activity and α-glucosidase and acetylcholinesterase inhibition activities were evaluated. To correlate these measured activities to phytochemicals in the petals, an ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS)-based metabolomics method was applied to profile the compositions in the petals of different colors. Finally, the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways database was used to identify the related metabolic pathways that are responsible for the production of these polyphenolic phytochemicals in the petals. Results: The results showed that PPE had the highest total phenolic content, total flavonoid content, and the strongest 2,2ʹ-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) radical scavenging ability, ferric reducing antioxidant power, and acetylcholin- esterase inhibition ability in all three samples, while YPE showed the strongest 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activity and α-glucosidase inhibition ability. A total of 232 metabolites were detected in the metabolomic analysis, 198 of which were flavonoids, chalcones, a fl vonols, and anthocyanins. Correlation analysis indicated that peonidin-3- O-arabinoside and cyanidin-3-O-arabinoside were the major contribu- tors to the antioxidant activity. Principal component analysis showed a clear separation among these three petals. In addition, a total of 38, 98, and 96 differential metabolites were identified in PPE, RPE, and YPE, respectively. Pathway enrichment revealed 6 KEGG pathways that displayed significant enrichment differences, of which the anthocyanin biosynthesis, flavone and flavonol biosynthesis were the most enriched signaling pathways, revealing a potential reason for the differences in metabolic and functional levels among different colors of P. delavayi petal. Conclusions: P . delavayi petals in different colors have different metabolite contents and functional activities, of which the anthocyanin, flavone, and flavonol metabolites are critical in its functional activities, suggesting the anthocyanin biosynthesis, flavone and flavonol biosynthesis path - ways are the key pathways responsible for both petal color and bioactive phytochemicals in P. delavayi flowers. Keywords: Paeonia delavayi; antioxidant activity; α-glucosidase; acetylcholinesterase; metabolomics; Kyoto Encyclopedia of Genes and Genomes pathway. Introduction inhibit α-glucosidase, a key enzyme that is a therapeutic target in the management of diabetes (Zhang et al., 2019; Liu Paeonia delavayi (P. delavayi) Franch. is a perennial woody et al., 2021). Similar effects were observed for the root, stem, plant species that belongs to tree peony species (Cheng et al., and leaves of P. delavayi (Huang et al., 2021; Chen et al., 1998; Hong and Pan, 1999; Pękal and Pyrzynska, 2014). The 2022). Thus, P. delavayi may also play a role in glycemic con- tree peony has been well known over thousands of years for trol. However, previous studies mostly focused on particular its various floral colors, nutritional benefits, and edible and peony species. As an endemic species, P. delavayi is a widely medicinal properties (Li, 2013; Zhang et al., 2017). It has available germplasm resource in the Southwest of China. been reported that tree peony flowers are abundant in bio - Plants of P. delavayi species show distinct variations in their active compounds such as polyphenolics and exert therapeutic flower colors, showing yellow, red, or purple. These flower effects against various diseases, such as aging, neurological color attributions strongly indicate that the polyphenolic diseases, and coronary heart disease (Finkel and Holbrook, compounds, especially flavonoids and anthocyanins, may be 2000; Barnham et al., 2004; Wang et al., 2005; Zhao et al., differentially accumulated in their flower petals of different 2012; Seifried et al., 2017). In addition, tree peony seed coat colored flower petals (Yan et al., 2020; Wang et al., 2021). extracts have been reported to effectively and competitively Received 28 December 2021; Revised 23 February 2022; Editorial decision 8 March 2022 © The Author(s) 2022. Published by Oxford University Press on behalf of Zhejiang University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. 2 J. Song et al. The petal is one of the most important organs of a 10 min. The supernatants were collected and filtered through flowering plant, which is involved in plant growth and devel - Millipore filters (0.5 µm) and each of the extracts of the opment, and primary and secondary metabolite regulations. purple, red, and yellow flower petals was aliquoted into a set The different components and contents of the chemical com- of tubes and stored at –20 °C until further analysis. position of petals, especially flavonoids and anthocyanins, confer the various colors and functions. Many studies have Total phenolic content investigated flavonoids and anthocyanins in plants and The total phenolic content (TPC) in the flower petal extracts was their relationships with flower color, for example, chalcone, determined by the Folin–Ciocalteau (FC) method ( Wang ZX et dihydroflavonoid, and flavone mainly yield yellow flowers al., 2020) with some modifications. In a 96-well microplate, (Mol et al., 1998; Harborne and Williams, 2000; Ferreyra 40 µL of diluted extract or reference sample, 125 µL of Folin– et al., 2012; Deguchi et al., 2013). For tree peony flowers, Ciocalteu reagent (0.5  mol/L), and 100 µL of Na CO were 2 3 flavonoids and anthocyanidins have been reported to be the added, mixed and incubated for 30  min in the dark at room main substances, which have proven to be excellent anti- temperature for colorimetric development to complete in the re- oxidants and antidiabetic resources (Wang et al., 2001a, action solution. Absorbance of the reaction solution was meas- 2001b; Li et al., 2009). Previous literature demonstrated ured at 760 nm wavelength using a microplate reader (Biotek, that tree peony flowers in different colors showed different Winooski, VT, USA). The standard calibration curve of gallic antioxidant capacities (Fan et al., 2012; Zhang et al., 2017; acid was obtained using a series of concentrations by dilutions Xiang et al., 2019). Interestingly, yellow P. delavayi exhibited (10, 20, 40, 60, 80, and 100 µg/mL) for calculating TPC, and stronger ferric reducing antioxidant power and 2,2ʹ-azino-bis TPC results for flower petals were expressed as µg of gallic acid (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt equivalents (GAE)/g dry extract (DE). (ABTS) radical scavenging activity than other yellow peonies (Li et al., 2009). Although there has been more and more Total Flavonoid Content researches on the edible and medicinal values of tree peony A modified method by Wang ZX et al. (2020) was used to flowers, the relationship between its flower colors and func - quantify the total flavonoid content (TFC). In a 96-well tions is poorly investigated. microplate, reaction solution was prepared in each well, 20 µL Therefore, this study aimed to evaluate the functional of NaNO (3%, mass concentration) was mixed with 40 µL activity and chemical composition of P. delavayi petals in of properly diluted extract or reference sample followed by different colors. Liquid chromatography (LC)/mass spectrom- a 6-min incubation. Subsequently, 20 µL of Al (NO ) (6%, 3 3 etry (MS)-based metabonomic technology was further used to mass concentration) was added to the reaction solution and elucidate the chemical basis of its function and the potential the solution was incubated for an additional 6 min. At the end mechanism of flower color formation. This research could in - of the incubation, 140 µL of NaOH (4%, mass concentra- crease the commercial value of P. delavayi. tion) and 70% methanol (containing 1% hydrochloric acid) were added to each well followed by 15  min incubation at room temperature. Absorbance of the obtained reaction so- Materials and Methods lutions was measured at 510 nm wavelength. Rutin solutions Chemical reagents (200, 400, 600, 800, and 1000 µg/mL) were used to make a standard reference curve and the flavonoid contents are pre - Analytical-grade formic acid, methanol, Folin–Ciocalteu sented as µg of rutin equivalents (RE)/g DE. reagent, gallic acid, rutin, quercetin, 2,2-diphenyl-1- picrylhydrazyl radical (DPPH), ABTS, 2,4,6-tri(2-pyridyl)- 1,3,5-triazine (TPTZ), iron chloride (FeCl ·6H O), ascorbic DPPH radical scavenging assay 3 2 acid (Vc), butylated hydroxytoluene (BHT), and other DPPH assay was used to determine the antioxidant potential chemicals were purchased from Aladdin (Shanghai, China). of the flower petal extracts, following the previously reported Chromatographic acetonitrile, acarbose, α-glucosidase method (Ghane et al., 2018), with some modifications. In from Saccharomyces cerevisiae (G5003), 5,5ʹ-dithiobis each well of a 96-well microplate, diluted extract or reference 2-nitrobenzoic acid (DTNB), acetyl-chymotrypsin sample (100 µL) of various concentrations was mixed with acetylthiocholine iodide (ATCI) were purchased from Sigma- 100 µL DPPH reagent (Zhang et al., 2014) and the mixed Aldrich (St. Louis, MO, USA). reaction solution was then subjected to a 30-min incubation at room temperature in darkness. Absorbance of the colori- Preparation of extracts metric development of the reaction solution in the microplate was measured at 517  nm using a plate reader. The blank Purple, red, and yellow flower petals of P. delavayi plants in control was prepared by mixing equal volumes of methanol natural habitats were harvested from Shangri-La (Yunnan, and DPPH. Vc and BHT were used as positive controls. The China). All the petals were sampled on April 20, 2021 and DPPH radical scavenging activity was presented as IC value stored at –80 °C until analysis. (the concentration providing 50% inhibition, µg/mL) and Antioxidant extractions from the P. delavayi flower petals was calculated using the following Equation (1): were carried out according to the previous developed method (Hua et al., 2018), with a slight modification. Briefly, 0.5 g of Control absorbance − Sample absorbance Inhibitory percentage = × 100% purple, red, or yellow flower petals were ground in liquid ni - Control absorbance (1) trogen to powder, and the powder was extracted with 10 mL of 70% methanol aqueous solution (containing 1% hydro- ABTS radical scavenging assay chloric acid) at 4 °C in the dark and overnight. Subsequently the samples were ultrasonicated for 30  min in an ice bath The ABTS assay was also employed for determination of anti- (parameters) prior to centrifugation at 10  000 r/min for oxidant capacity in the flower petal extracts. The assay was Functional activity and phytochemical composition in Paeonia delavayi petals 3 performed in 96-well microplates and carried out according Metabolomic analysis to a method reported in the literature (Ghane et al., 2018). The metabolomics analysis was performed by Wuhan For each well, 50 µL of diluted extract or reference sample in Metware Biotechnology Co., Ltd. (www.metware.cn). a range of concentrations was mixed with 200 µL of diluted Briefly, the sample extracts were analyzed using an ultra ABTS (7 mmol/L) working solution. The absorbance of the performance liquid chromatography-electrospray-tandem reaction was recorded at 734 nm by a plate reader after 6-min mass spectrometry (UPLC-ESI-MS/MS) system (UPLC, incubation at room temperature in the dark. Methanol was SHIMADZU NexeraX2, Kyoto, Japan; MS, Applied used as negative control, Vc and BHT were used as positive Biosystems 4500 Q TRAP, Foster City, CA, USA) . The ana- controls. The results of ABTS radical scavenging assays were lytical conditions were as follows: column, Agilent SB-C18 presented as shown in Equation (1). (1.8 µm, 2.1 mm×100 mm); Agilent Technologies, Palo Alto, CA, USA). The mobile phase consisted of solvent A—pure water with 0.1% formic acid, and solvent B—acetonitrile Ferric reducing antioxidant power assay with 0.1% formic acid. Sample measurements were per- The ferric reducing antioxidant power (FRAP) was quantified formed with a gradient program that employed the starting by the reported method (Liao and Banbury, 2015). The FRAP conditions of 95% A, 5% B. Within 9 min, a linear gradient solution made up of 1  mL TPTZ (10 mmol/L), 1  mL FeCl 3 to 5% A, 95% B was programmed, and a composition of (20 mmol/L) and 10 mL acetate buffer (pH 3.6) was kept at 5% A, 95% B was kept for 1 min. Subsequently, a compos- 37 °C. In each well of a 96-well microplate, 50 µL of diluted ition of 95% A, 5% B was adjusted within 1.10  min and sample was mixed with 250 µL of freshly prepared FRAP kept for 2.9 min. The flow velocity was set at 0.35 mL/min. working solution. The absorbance was measured at 593 nm The column oven was set to 40 °C. The injection volume after incubation for 10 min in the dark at 37 °C. The standard was 4 μL. The effluent was alternatively connected to an calibration curve of FeSO was obtained using dilutions 4 ESI–triple quadrupole–linear ion trap (LIT)–MS. LIT and (20, 40, 60, 80, and 100 µg/mL), and results were expressed triple quadrupole (QQQ) scans were acquired on a triple as µg of FeSO equivalents/mg DE. Vc and BHT were used as 4 quadrupole–LIT mass spectrometer (Q-TRAP), equipped positive controls. with an ESI Turbo Ion-Spray interface, operating in posi- tive and negative ion mode and controlled by Analyst 1.6.3 software (https://sciex.com/products/software/analyst- α-Glucosidase inhibition assay software). The ESI source operation parameters were as fol- The α-glucosidase inhibition assay was performed according lows: ion source, turbo spray; source temperature 550 °C; to a previously developed protocol (Liao and Banbury, 2015) ion spray voltage (IS) 5500 V (positive ion mode)/–4500 V with slight modifications. The enzyme reaction in each well of (negative ion mode); ion source gas I, gas II, and curtain a 96-well microplate was set up by adding 50 µL of sample of gas were set at 50.0, 60.0, and 25.0 MPa, respectively. The various concentrations and 25 µL α-glucosidase (0.1 U/mL) collision-activated dissociation was high. Instrument tuning in phosphate buffer. The reactions in the microplate were and mass calibration were performed with 10 μmoL/L and mixed prior to an incubation at 25 °C for 10  min; 25 µL 100 μmoL/L polypropylene glycol solutions in QQQ and of p-nitrophenyl-ɑ-d-glucopyranoside (5 mmol/L) was LIT modes, respectively. QQQ scans were acquired at mul- added subsequently and the mixture was incubated for an - tiple reaction monitoring (MRM) mode with collision gas other 15 min at 25 °C. One hundred microliters of Na CO 2 3 (nitrogen) set to medium. (0.2 mol/L) was added to stop the enzymatic reactions. The In the MRM mode, the quadrupole first screens the pre - absorbance was recorded with a plate reader at 412  nm cursor ions of the target substances and excludes the ions of wavelength. Methanol and acarbose were, respectively, used other molecular-weight substances in order to preliminarily as negative and positive controls. The α-glucosidase inhib- eliminate interference. Then the precursor ions are induced ition ability was expressed as IC (mg/mL). Inhibitory per- to ionize by the collision cell and break up to form many centage of the enzyme activity was calculated according to fragment ions. To eliminate nontarget ion interference, Equation (1). these fragment ions are filtered by triple quadrupole, and the fragment ions with the desired characteristic were finally -6 Acetylcholinesterase inhibition assay selected. By comparing the accurate mass (error<2×10 ), -6 The acetylcholinesterase (AChE) inhibitory ability was de- MS2 fragments (error<5×10 ), secondary mass spectrom- termined according to the published procedure ( Luo et al., etry (MS2) fragment isotope distribution, and retention time 2019) with some modifications. A 50-µL diluted sample with the standards database (MetWare Database, https:// at various concentrations was mixed with 30 µL ATCI sourceforge.net/projects/metware/), the substances were (15 mmol/L) and 75 µL DTNB (3 μmol/L) in a 96-well identified. For the metabolites not matched to standard sub- microplate and incubated at 30 °C for 10 min in the dark; stances, they were matched to public databases or manu- 20 µL of 0.1 U/mL AChE was added and mixed; then, ally identified based on their mass spectral cleavage rules. 50 µL of phosphate buffer was added to initiate the reaction. The peak areas of ion chromatograms for typical ions of At the same time, the absorbance was measured at 405 nm. the metabolites were integrated and calibrated by using After 5 min of incubation in darkness at room temperature, MultiQuant software (v.3.0.3; https://sciex.com/products/ the absorbance was measured again at 405  nm. Methanol software/multiquant-software), and were used to represent and galantamine were, respectively, used as negative and the relative content of the corresponding substance (Fraga positive controls. The AChE inhibitory ability was expressed et al., 2010; Jiang et al., 2020). Finally, corresponding dif- as the IC value (mg/mL). The AChE inhibition assay was ference analysis and Spearman correlation analysis were recorded using Equation (1). performed. 4 J. Song et al. Statistical analysis antioxidants beside phenolic compounds also react with the FC reagent (Everette et al., 2010). All data were presented as mean±standard deviation (SD) of As measured with the aluminum complexation reaction three parallel measurements, analyzed by analysis of variance method, the TFCs displayed a significant difference among and Tukey’s multiple comparison test (P<0.05). Statistical the three petal extracts. The purple flower petals showed the analysis was performed with SPSS 26.0 software (IBM, highest TFC ((133.15±0.87) mg RE/g DE), followed by red Armonk, NY, USA) and ORIGIN 2018 software (https:// flower petals ((101.69±3.03) mg RE/g DE) and yellow flower www.originlab.com/). The correlations efficient between petals ((86.79±2.23) mg RE/g DE; Figure 1B). This may be each variable were calculated by the two-tailed Pearson directly related to the types of flavonoids and the genetic char- test. Principal component analysis (PCA), Spearmen correl- acteristics of P. delavayi (Wang ZX et al., 2020). Flavonoids ation clustering heatmap, associated network diagram, the are a class of very important plant secondary metabolites, and Venn diagram and the volcano plots were performed within plants usually accumulate high levels of flavonoids in their R (v4.0.3). All data used unit variance scaling (UV) nor - tissues. Flavonoids also provide strong antioxidant proper - malization. The formula for UV normalization is z=(x–μ)/σ ties that contribute toward human health. Our previous study (where x is a specific score, μ is the mean, σ is the standard revealed that flower petals accumulated a wide range of fla - deviation), and orthogonal partial least squares discriminant vonoids apart from anthocyanins (Wang et al., 2021). While analysis (OPLS-DA) is logarithmically transformed and then the aluminum complexation method has been regarded as the centrally processed. Significantly regulated metabolites among standard to measure total flavonoids in food and beverages, a groups were determined by variable importance in projection detailed study (Pękal and Pyrzynska, 2014) revealed that this (VIP)≥1 and absolute log fold change (FC)≥1. By using the method was highly biased toward rutin, luteolin, and catechin R package MetaboAnalystR, VIP values were extracted from phytochemicals. Given the wide range of flavonoids present the OPLS-DA result, which also contained score plots and in the flower petals of P. delavayi, the TFC determined with permutation plots. The data were log transformed (log ) and this method may not be a true representation of the TFC in mean centered before OPLS-DA. In order to avoid overfitting, the petals, but rather a correlation of the total flavonoids in a permutation test (200 permutations) was performed. the petals. Results Antioxidant properties Both DPPH and ABTS assays have been widely used for the Total phenolic content and total flavonoid content measurements of the antioxidant capacities, and the prin- The FC colorimetric assay has been widely used for phenolic ciples of both methods are on the quenching of colored rad - and polyphenolic antioxidant quantification in food and bev - icals DPPH or ABTS. The color reductions of DPPH or ABTS erage industries (Wang ZX et al., 2020). In our study, a sig- radicals are negatively correlated with the capacities of anti- nificant difference in the TPC was demonstrated in the flower oxidants present in the natural products. Previous studies petals among the different colors (P<0.05). Purple petal ex- have indicated that the petals from tree peony species have tract (PPE) gave the highest TPC value ((469.48±6.88) mg strong antioxidant activity, in correlation with the abundance GAE/g DE), yellow petal extract (YPE) had the lowest value of bioactive compounds (Li et al., 2009; Su et al., 2017; Wang ((377.17±1.26) mg GAE/g DE), and red petal extract (RPE) ZX et al., 2020). In this work, apart from DPPH and ABTS showed TFC of (388.35±9.84) mg GAE/g DE (Figure 1A). assays, FRAP assays, based on the conversion of colorless Clearly, the purple flower petals accumulated much higher ferric complex into intense blue when antioxidants are pre- total phenolic compounds as determined with the FC method. sent in the reaction solution, was also used to estimate the Similar results were observed in the P. delavayi seeds (Yan et antioxidant activity of tree peony petals. al., 2020). The FC method is based on the reaction of the re- ducing power of phenolic compounds; a detailed study on the DPPH radical scavenging assay FC reagent toward various classes of compounds in plants suggested that the FC assay should be treated as a measure DPPH radical scavenging assay is frequently used to deter - of total antioxidant capacity of plant extract, because other mine the free radical scavenging capacity of target compounds Figure 1. Total phoenolic content (TPC; A) and total flavonoid content (TFC; B) of Paeonia delavayi petals extraction. For the same determination, bars with different lowercase letters suggest significant difference (P<0.05). GAE, gallic acid equivalents; DE, dry extract; RE, rutin equivalents; PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract. Functional activity and phytochemical composition in Paeonia delavayi petals 5 Figure 2. The antioxidant activity of the petal extracts of Paeonia delavayi. (A) DPPH radical scavenging ability, (B) ABTS radical scavenging ability, (C) ferric reducing antioxidant power. Bars with different lowercase letters indicate insignificant difference (P<0.05). DE, dry extract; PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract; Vc, ascorbic acid (as positive control); BHT, butylated hydroxytoluene (as positive control). or extracts (Nascimento et al., 2020). As shown in Figure 2A, the purple and yellow flower petals had very similar levels of radical scavenging capacities, (324.24±0.98) μg Trolox/mg DE and (336.08±4.02) μg Trolox/mg DE, re- spectively. The scavenging capacity measured with the DPPH method was marginally lower despite being significant stat - istically ((290.12±2.11) µg Trolox/mg DE). Although below the positive control Vc, the DPPH radical scavenging capaci- ties derived from the flower petals of all colors were signifi - cantly higher than the control BHT at the concentration used (P<0.05). Vc is popularly acclaimed as a potent antioxidant and free radical scavenger (Li et al., 2021) , while BHT is a commonly used antioxidant, recognized as safe for use in foods containing fats, and in the pharmaceutical, petroleum products, rubber, and oil industries (Yehye et al., 2015). ABTS radical scavenging assay Figure 2B shows the results of the ABTS radical scavenging activity, the ABTS assay results being inconsistent with the DPPH assay. PPE had the highest scavenging activity, which amounted to (631.68±7.32) µg Trolox/mg DE, followed by RPE ((517.19±7.12) µg Trolox/mg DE), whereas YPE was Figure 3. Pearson correlation heatmap among bioactivities in the petal (447.24±9.67) µg Trolox/mg DE. From Figure 3, ABTS radical extracts of Paeonia delavayi. α-Glu, the IC value for α-glucosidase scavenging ability was observed to exhibit a high correlation inhibitory activity; AChE, acetylcholinesterase; TPC, total phoenolic content; TFC, total flavonoid content; FRAP, ferric reducing antioxidant with TPC and TFC (r=0.944 and 0.989, P<0.01), which meant power. that phenolics and flavonoids were the main components scav - enging ABTS radicals. Compared with the controls, the scav- enging ability of PPE and RPE was significantly higher than indices, respectively. Considering that ‘antioxidant capacity’ that of BHT ((536.1±14.33) µg Trolox/mg DE) but lower than is a comprehensive assessment using different methods and that of Vc ((1754.52±48.85) µg Trolox/mg DE). principles, we considered the phenolic and flavonoid com - pounds both to be major contributors to the antioxidant ac- Ferric reducing antioxidant power assay tivities of P. delavayi (Wang ZX et al., 2020). The FRAP assay is usually applied to evaluate the reducing The radical scavenging capacities were clearly different capacity of plant extracts (Wang SL et al., 2020). As demon- when the DPPH method was used in comparison with the strated in Figure 2C, the FRAP values of samples from the lar- other two methods (Figure 2). Both ABTS and ferric reduc- gest to the smallest were as follows: PPE ((941.23±30.46) µg tion methods gave the purple flower petals the highest scav - FeSO /mg DE), RPE ((738.64±21.74) µg FeSO /mg DE), and enging capacity, followed by red and yellow petals ( Figure 2), 4 4 YPE ((694.72±23.76) µg FeSO /mg DE). Although the level but this was not the trend measured with the DPPH method was not as high as Vc, PPE was comparable to BHT, while RPE (Figure 2A). The DPPH method might not be reflecting the and YPE were lower than Vc and BHT (P<0.01). In addition, true value in the colored petals of purple and red flowers the high correlation of FRAP with TPC and TFC (r=0.960 and due to the fact that the detecting wavelength (517  nm) is 0.968, P<0.01) indicated that the phenolic and flavonoid com- also around the maximum absorption from anthocyanins 3+ ponents also contributed to the Fe reducing activity. (500–530  nm). This interference to the detection may have From the present results, the phenolic and flavonoid con- underestimated the scavenging power in the highly colored tents significantly contributed to the different antioxidant peony petals. 6 J. Song et al. addition, there was a high and significant negative correl- α-Glucosidase inhibitory ability ation between α-glucosidase inhibitory ability with DPPH, It is well known that active phytoconstituents such as fla- ABTS, and FRAP (r=–0.964, –0.885, and –0.895, P<0.01), vonoids and polyphenols could decrease postprandial hyper - respectively. This indicated that these various compounds in glycemia by inhibiting the activity of α-glucosidase, thus P. delavayi petals with a different mechanism of antioxidant having important health benefits in treating/preventing type-2 action also played an important role in α-glucosidase inhibi- diabetes (Shim et al., 2003). In this work, we assessed the tory effect. hypoglycemic potential of P. delavayi by investigating their α-glucosidase inhibitory abilities. Acetylcholinesterase inhibitory ability As shown in Figure 4A, all samples and the positive con- trol (acarbose) inhibited α-glucosidase in a concentration- Alzheimer’s disease (AD) is a chronic syndrome that causes dependent manner. The orders of inhibition activities from progressive deterioration of the central nervous system. strong to weak were as follows: acarbose (IC value was According to the cholinergic hypothesis, the reduction in (9.46±0.13) µg/mL), YPE (IC (1.64±0.26) mg/mL), RPE (IC acetylcholine synthesis is the main cause of AD, and increasing 50 50 (1.73±0.14) mg/mL), and PPE (IC (2.027±0.16) mg/mL). the cholinergic levels in the brain by inhibiting the AChE is a The result denoted that all samples had certain ability to potential therapeutic strategy (Bartus et al., 1982; Sharma, inhibit α-glucosidase but significantly lower than control 2019). Natural products are considered to be beneficial AChE (Figure 4B). The reason may be that these three extracts inhibitors, and gain considerable research interest, because were a mixture of many substances, and the active com- they are economical, safe, effective, and have low side effects. pounds with α-glucosidase inhibitory ability were only a From Figure 5B, PPE, RPE, and YPE inhibited AChE with IC small part of the total mixture (Wang ZX et al., 2020). In value of (2.77±0.45), (6.06±0.18), and (4.32±0.33) mg/mL, Figure 4. The α-glucosidase inhibitory activity of the petal extracts of Paeonia delavayi. Bars with different lowercase letters indicate insignificant difference (P<0.05). PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract; IC , the concentration providing 50% inhibition. Figure 5. The AChE inhibitory activity of the petal extracts of Paeonia delavayi. Bars with different lowercase letters indicate insignificant difference (P<0.05). AChE, acetylcholinesterase; PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract; IC , the concentration providing 50% inhibition. Functional activity and phytochemical composition in Paeonia delavayi petals 7 respectively, where the RPE value was more than twice that 7-O-neohesperidoside, and chrysoeriol 7-O-glucoside (Zhao of PPE. Although the three samples were lower in inhibition et al., 2016; Hua et al., 2018; Shi et al., 2018). Additionally, of AChE than control galantamine (IC (1.9±0.11) µg/mL), 5 anthocyanins of these 197 flavonoids were first found in they also showed some inhibition capacity as concentra- P. delavayi petals. They were cyanidin-3-O-(6ʹʹ-O-malonyl) tion increased (Figure 5A). Correlation analysis (Figure 3) glucoside-5-O-glucoside, cyanidin-3-O -arabinoside, peonidin- showed that both phenolic and flavonoid compounds had 3-O-arabinoside, peonidin-3-O-sambubioside, and peonidin- a great inhibitory effect on AChE; the high degree of correl- 3-O-sophoroside-5-O-glucoside. ation between AChE inhibitory ability with DPPH radical To assess the relationship between these metabolites scavenging ability, ABTS radical scavenging ability, FRAP, and the biological activities of samples, we conducted a and α-glucosidase inhibitory ability (r=–0.87, –0.89, –0.89, Spearman association analysis between the relative content and 0.75, P<0.01), respectively, also demonstrated this point. of the metabolites of all samples and their functional activ- ities. The top 20 metabolites with the highest association coefficients are shown in Figure 6. According to Figure 6A, Metabolomic Analysis peonidin-3-O-arabinoside and cyanidin-3- O-arabinoside Metabolome analysis were strongly associated with TPC, TFC, DPPH radical Our results presented above appeared to attribute the dif - scavenging activity, ABTS radical scavenging ability, and ferent functional activities to the color difference of the petals FRAP. These associations were also clearly exemplified by from which the extracts were derived. In general, flower the network diagram of association in Figure 6B. Peonidin- color is an evolutionary result caused by the accumulation of 3-O-arabinoside and cyanidin-3- O-arabinoside belong to pigments such as flavonoids (anthocyanins). Diverse flower anthocyanins, which play the major role in the purple, blue colors play a critical role in pollination biology and the me- and red color presentation of plant tissues, and exhibited tabolites also have physiological functions in plants (Ren et strong antioxidant activity (Chuntakaruk et al., 2021). al., 2017; Wu et al., 2018). Therefore, to further elucidate the In our study, although a strong correlation between the phytochemical basis of these functional differences, metabolic anthocyanin-3-O-arabinosides and antioxidant activities analysis was carried out with UPLC-MS/MS, particularly to was revealed, the fact that these anthocyanins are posi- target the flavonoids in the petals. tively correlated with the total polyphenolic compounds A total of 232 metabolites were detected, including 197 and TFCs points to the collective effect of polyphenolic flavonoids and 35 tannins. Specifically, the 197 flavonoids compounds and anthocyanins attributing to antioxidant were classified into 9 categories, including 75 flavonols, activities. From previous work, we showed that antho- 9 anthocyanins, 13 flavonoid C-glycosides, 5 flavanols, 4 cyanin glucoside in red flower petals was at a much higher di-hydroflavonols, 9 dihydroflavones, 5 chalcones, and 3 level than anthocyanin arabinosides (Wang et al., 2021). In isoflavones. The details about these metabolites are shown a recent study, peonidin-3-O-arabinoside and cyanidin-3- in Table S1, many of which have previously been reported O-arabinoside were discovered as potent pancreatic lipase to be associated with flower colors, such as cyanidin-3, inhibitors (Xie et al., 2020). No other metabolite was 5-di-O-glucoside, peonidin-3-O-glucoside, apigenin found to be significantly associated with AChE inhibitory Figure 6. (A) The top 20 Spearmen correlation clustering heatmap between biological activity and the content of the metabolites in the petal extracts of Paeonia delavayi. **P<0.01, *P<0.05. (B) Associated network diagram. The red line represents positive correlation, and the green line represents negative correlation, the thickness of the line represents the level of the correlation coefficient (P<0.05). α-Glu, the IC value for α-glucosidase inhibitory activity; AChE, acetylcholinesterase; TPC, total phoenolic content; TFC, total flavonoid content; FRAP, ferric reducing antioxidant power. 8 J. Song et al. activity, while α-glucosidase inhibitory activity was only cluster heatmap (Table S2, Figure 7A). The differences between significantly related to gallic acid ( r=0.83, P<0.01) and group YPE and groups PPE and RPE were significant, while peonidin-3-O-arabinoside (r=0.71, P<0.05). This indicated the difference between PPE and RPE was less pronounced, again that these two functional activities might be a re- indicating closer homogeneity between PPE and RPE. The flection of collective actions from multiple phytochemicals. Venn diagram (Figure 7B) demonstrated the shared and unique Furthermore, other phytochemicals that have not been differential metabolites between the three groups. Fewer differ - identified as significant variables in this study also need ential metabolites between PPE and RPE were observed, which attention. For example, tannins, as one of the other major also demonstrated the closeness between the two groups. components of P. delavayi petals, did not demonstrate a Among them, a total of 11 metabolites were differentially accu- significant correlation with biological activity in this study mulated between all the petal colors, including two flavonoids, in our correlation analysis, but there were many reports five anthocyanins, three flavonols, and one dihydroflavone. showing tannins have strong free radical scavenging ac- These observations were further supported by PCA that tivity and α-glucosidase inhibitory ability (Cardullo et al., can be used to identify relationships among variables. From 2018; Noorolahi et al., 2020). This reinforces the concept Figure 7C, these three groups were clustered separately from that polyphenols, flavonoids, and anthocyanins together each other, which indicated the distinctions of purple, red, and provide antioxidant activities and the inhibitory effect of yellow P. delavayi petals on a metabolite level. PC1 showed the enzymes observed in our study, while certain individual clear discrimination of YPE versus PPE and RPE, while PPE phytochemicals could be used as indexes at a practical and RPE could be discriminated at PC2. The two principal level for the screening of plant materials for healthy food components contributed 69.50% and 11.64%, respectively, supplements. which meant they could fully reflect the overall information. We further performed pairwise comparisons for the metab- olite data to identify further differences among three groups Differential metabolites analysis (Figure 8). Each file is filtered according to the fold change All 232 metabolites were normalized and then the top 30 me- values, which must be greater than or equal to 2 or less than tabolites were analyzed for differential accumulations by a 0.5, and the VIP scores greater than or equal to 1. The results Figure 7. (A) Top 30 differentially accumulated metabolites accumulation pattern of Paeonia delavayi petals. In the heatmap, differentially metabolites marked with red represent high content and blue were low content in Paeonia delavayi petals, respectively); (B) The Venn diagram shows the overlapping and cultivar-specific differential metabolites in the group PPE, RPE, and YPE; (C) Principal component analysis on the relationships among those variables. PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract. Functional activity and phytochemical composition in Paeonia delavayi petals 9 showed that there were 98 significant differential metabolites of anthocyanins and flavonoids in the functional activity of when comparing the PPE group with the YPE group, among P. delavayi petals, and was consistent with those previously which 44 were downregulated and 54 upregulated ( Figure 8A). reported (Zhao et al., 2016; Hua et al., 2018; Shi et al., 2018). For comparisons between RPE and YPE groups (Figure 8B), 96 differential metabolites were identified, of which 47 were KEGG enrichment analysis downregulated and 49 upregulated. When PPE was com - Diverse secondary metabolites are present in plants. These pared with RPE groups (Figure 8C), there were only 38 dif- secondary metabolites are mainly regulated by metabolic ferential metabolites (17 downregulated and 21 upregulated); pathways, which in turn affect their functional activity. In this the similar degree between PPE and RPE was also demon - study, the metabolic pathways associated with these differen - strated. The differential metabolites of each comparison tial metabolites were annotated using the Kyoto Encyclopedia group were also visualized with the corresponding volcano of Genes and Genomes (KEGG) database. plots (Figures 8D–8F). Overall, all groups were significantly KEGG pathway enrichment analysis indicated that the different from each other (all pairwise comparisons P<0.05), same six pathways were significantly enriched both be - and anthocyanins and flavonoids were the main difference me- tween PPE and YPE (Figure 9A) and RPE and YPE (Figure tabolites. From the figure, PPE contained more anthocyanins 9C), including flavonoid biosynthesis (ko00941), antho - when compared to RPE and YPE, while YPE has more fla - cyanin biosynthesis (ko00942), isoflavonoid biosynthesis vonoids than PPE and RPE. Combined with our functional (ko00943), flavone and flavonol biosynthesis (ko00944), activity results above, this result revealed the substantial roles biosynthesis of secondary metabolites (ko01110), and Figure 8. (A–C) Top 30 differentially accumulated metabolites accumulation pattern of Paeonia delavayi petals in different comparison groups. In the heatmap, differential metabolites marked with red represent high content and blue low content in Paeonia delavayi petals, respectively. (D–F) Volcano plots of differential metabolites. In the figure, green dots represent downregulated differentially expressed metabolites, red dots represent upregulated differentially expressed metabolites, and gray represents detected but not significantly different metabolites. Significantly different metabolites among groups were determined by VIP≥1 and an absolute log fold change (FC)≥1. PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract. Figure 9. Pathway enrichment analysis of differential metabolites for (A) PPE versus YPE, (B) PPE versus RPE, and (C) RPE versus YPE. The color of the point represents the P value, and the size of the point represents the number of differentially enriched metabolites. PPE, purple petal extract; RPE, red petal extract; YPE, yellow petal extract. 10 J. Song et al. metabolic pathway (ko01100). Among them, anthocyanin anthocyanin and flavone of different colors' P. delavayi petals. biosynthesis was the most significant enrichment pathway. Changes in these pathways caused the difference in metabol- For the differential metabolites between PPE and RPE, only ites, finally leading to the difference in flower color and func - the flavonoid biosynthesis (ko00941), anthocyanin biosyn - tional activity of P. delavayi petals. thesis (ko00942), and flavone and flavonol biosynthesis In conclusion, our study characterized functional activities, (ko00944) pathways were significantly enriched ( Figure key active compounds, differential metabolites, and meta- 9B). Taken together, anthocyanin biosynthesis, flavone and bolic pathways of purple, red, and yellow P. delavayi petals, flavonol biosynthesis were the most enriched signaling path - which could provide a theoretical basis for further studies ways, and these pathways are presented in Figures S1 and and utilization of P. delavayi. Furthermore, more in-depth S2. It is well known that flavone and flavonol are early steps and comprehensive functional assessment, including the iso- of the flavonoid biosynthetic pathway, and the anthocyanins lation and preparation of the key active compounds and are late steps of the same flavonoid biosynthetic pathway. their mechanisms of action, should be considered in future During plant growth and development, flavonoids are re - research. sponsible for the coloration of fruits, flowers, and seeds, while the color changes are predominantly due to the result Author Contributions of anthocyanin accumulation (Sokół-Łętowska et al., 2018; Jing Song, Zhenxing Wang, and Juan Wang conceived and Xiao et al., 2019; Shen et al., 2021). Therefore, the activity designed the experiments; Jing Song performed the experi - of these metabolic pathways determines the content of the ment and wrote the manuscript; Jing Song, Zhenxing Wang, metabolites that lead to different colors and biological activ - and Huaibi Zhang analyzed the data, edited and reviewed the ities of P. delavayi petals. manuscript; Jing Song and Juan Wang contributed to mater- ials collection. All authors have read and agreed to the pub - lished version of the manuscript. Conclusions Flower color is an important horticultural trait of higher Funding plants. Owing to its diverse flower coloration, P. delavayi is an ideal model species to study the secondary metabolism This research was funded by the ‘High-level Foreign Experts’ of flowers. However, the bioactivity and the phytochemical Special Project of Yunnan Province Thousand Talents Plan compositions of P. delavayi petals in different colors are still and the ‘Yunling Industrial Technology Leading Talents’ poorly investigated. Special Project of Yunnan Province Ten Thousand Talents In this study, we compared the active phytochemical Plan (No. [2018]212), the Digitalization, Development and compositions, antioxidant activity, α-glucosidase inhib- Application of Biotic Resource of the Science and Technology ition ability, and acetylcholinesterase inhibition ability of Planning Project of Yunnan Province (No. 202002AA10007), P. delavayi petals in three distinct colors (purple, red, and and the Scientific Research Fund Project of Yunnan Provincial yellow), and found that phenolic compounds, including fla - Department of Education (No.2020Y0412), China. vonoids and anthocyanins, are the major contributors to anti- oxidant activities, while α-glucosidase inhibition ability and Conflict of Interest acetylcholinesterase inhibition ability might be the coaction The authors declare no conflict of interest. of multiple compounds. 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Journal

Food Quality and SafetyOxford University Press

Published: Mar 18, 2022

Keywords: Paeonia delavayi; antioxidant activity; α-glucosidase; acetylcholinesterase; metabolomics; Kyoto Encyclopedia of Genes and Genomes pathway

References