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8 March 2026

18 Pages

Comparative Metabolomic Analysis of Shoot Apices and Leaves of Idesia polycarpa and Quantitative Determination of Leaf Flavonoids

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Henan Province Engineering Technology Research Center for Idesia, Zhengzhou 450046, China
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National Forestry and Grassland Administration Key Laboratory for Central Plains Forest Resources Cultivation, Zhengzhou 450046, China
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College of Forestry, Henan Agricultural University, Zhengzhou 450046, China
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Henan Academy of Forestry Sciences, Zhengzhou 450008, China
Forests2026, 17(3), 336;https://doi.org/10.3390/f17030336
This article belongs to the Section Forest Ecophysiology and Biology
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Abstract

Idesia polycarpa is a multipurpose tree species valued for both fruit production and timber and is often referred to as a “beautiful oil reservoir on trees”. However, research has largely focused on fruits, whereas the metabolic composition and potential value of other tissues, such as leaves and shoot tips, remain insufficiently characterized. Here, we employed UPLC–MS/MS-based untargeted metabolomics to compare metabolite profiles and functional components between the leaves and shoot tips of I. polycarpa. In total, 378 differential metabolites were identified, with 105 significantly upregulated in leaves and 273 significantly upregulated in shoot tips. Among these, 32 metabolites were detected exclusively in shoot tips, and 22 were unique to leaves. Leaves were enriched in secondary metabolites, particularly flavonoids and phenolic acids, with scutellarin and catechol as representative compounds. In contrast, shoot tips exhibited higher levels of primary metabolites, including nucleotides and their derivatives as well as amino acids, with catechin and epicatechin being representative compounds. In addition, targeted metabolomics was performed to quantify 53 flavonoids in leaves; scutellarin (2088.1350 μg/g) and apigenin-7-O-glucuronide (1020.9085 μg/g) showed the highest concentrations. Collectively, these results reveal tissue-specific metabolic characteristics in I. polycarpa and provide a data basis for future functional studies and the comprehensive utilization of leaves and shoot tips.

1. Introduction

Idesia polycarpa Maxim. is a deciduous tree species in the genus Idesia (family Flacourtiaceae) that is widely distributed across warm-temperate and subtropical regions of East Asia [1,2]. It is characterized by a straight trunk, a layered canopy, and abundant red fruits in autumn. Its wood has a clear and attractive grain and moderate hardness, making the species valuable for timber production and urban landscaping [3,4]. The fruits contain more than 30% oil, which is rich in unsaturated fatty acids; linoleic acid can account for up to 80% of the total fatty acids. Accordingly, I. polycarpa is considered an important woody edible oil crop and is often referred to as a “beautiful oil reservoir on trees” [5,6]. Given its multifunctional value, almost all parts of I. polycarpa have potential for utilization. To date, studies have primarily focused on fruit yield and production traits [7,8,9,10,11,12,13,14,15,16,17], optimization of oil extraction and refining processes [18,19,20,21,22], and high-value applications of fruit oil and oil residues [23,24,25,26,27,28]. In addition, branch extracts have been reported to exhibit anti-leukemic activity by regulating glucocorticoid receptor expression and modulating the mTOR and MAPK signaling pathways in CCRF-SB cells [29]. Despite these advances, the chemical composition and metabolic characteristics of vegetative organs, such as leaves and shoot tips, remain insufficiently explored, which limits the comprehensive utilization of whole-plant resources.
In many woody plant species, leaves and actively growing tissues are enriched in secondary metabolites (e.g., polyphenols, flavonoids, and terpenoids) that are closely associated with diverse biological activities. For instance, olive (Olea europaea L.) leaf extracts have been reported to significantly reduce systolic and diastolic blood pressure, as well as triglyceride levels, in subjects with stage I hypertension [30,31,32]. In Ginkgo biloba L., terpene lactones, ginkgolic acids, and flavonoids display dynamic changes during leaf development, indicating that metabolite composition is strongly influenced by developmental processes [33]. Similarly, tea (Camellia sinensis (L.) O. Kuntze) shoot tips and leaves contain abundant polyphenols, L-theanine, caffeine, and volatile compounds, underscoring the value of these tissues for linking chemical composition with biological functions [34,35]. Together, these studies suggest that leaves and shoot tips of woody plants can serve as important reservoirs of bioactive metabolites and that Idesia polycarpa may likewise harbor distinctive and potentially valuable compounds in these tissues. Accordingly, preliminary work has begun to characterize the chemical composition and bioactivities of I. polycarpa leaves. Huang [36,37] isolated four compounds using high-speed counter-current chromatography (HSCCC) coupled with preparative high-performance liquid chromatography (prep-HPLC) and demonstrated their antioxidant activity and cytotoxicity against tumor cells. Feistel et al. [38] reported that I. polycarpa leaf extracts were toxic to larvae of Lymantria dispar and Cerura vinula. From a metabolomics perspective, Zhang et al. [39] further indicated that differential metabolites between leaves and soil were mainly associated with sugars and phenolic acids. Despite these advances, current studies have largely focused on a limited set of compounds and do not yet provide a systematic view of leaf metabolite profiles; moreover, the composition and characteristics of metabolites in I. polycarpa shoot tips have rarely been reported.
However, leaves and shoot tips differ markedly in tissue structure and physiological function. Leaves primarily support photosynthesis and stress responses and are often enriched in secondary metabolites, such as phenolic acids and flavonoids, that are associated with antioxidant capacity and defensive functions [40]. In contrast, shoot tips represent meristematic growth centers and are more closely linked to metabolic processes underlying growth and developmental regulation, signal transduction, and the biosynthesis of structural components [41].
Therefore, we employed UPLC–MS/MS-based untargeted metabolomics to compare the metabolic profiles of Idesia polycarpa leaves and shoot tips and screened and annotated differential metabolites to elucidate tissue-specific metabolic characteristics. On this basis, flavonoids in leaves were quantified to validate key functional components, thereby providing a basis for the development and utilization of I. polycarpa leaf and shoot-tip resources.

2. Materials and Methods

2.1. Sample Collection

In July 2020, the leaves and shoot apices of Idesia polycarpa were collected concurrently at the Forestry Experimental Station of Henan Agricultural University (Zhengzhou, China) to minimize temporal variation during sampling. Fully expanded leaves were excised from the mid-canopy region of the main stem across multiple trees. In contrast, shoot apices were collected from the terminal portions of lateral branches at mid-canopy height, and any attached young leaves were carefully removed prior to processing. To reduce positional bias, samples were taken from branches with different orientations, and three independent biological replicates were prepared for each tissue type. Immediately after collection, all samples were cryopreserved in liquid nitrogen for 3 min and then stored at −80 °C until analysis. The frozen tissues were subsequently freeze-dried under vacuum using a Scientz-100F lyophilizer (Scientz, Ningbo, China) and ground to a uniform fine powder with a mixer mill (MM 400, Retsch) at 30 Hz for 1.5 min to ensure homogeneity. For subsequent analyses, mature leaves were designated as group A and shoot tips as group B.

2.2. Chemical Reagents and Materials

LC–MS-grade methanol, acetonitrile, and formic acid were purchased from Thermo Fisher Scientific (Fair Lawn, NJ, USA). Ultrapure water was produced using a Milli-Q purification system (Millipore, Bedford, MA, USA). Authentic reference standards were obtained from BioBioPha (Kunming, China) and Sigma-Aldrich (St. Louis, MO, USA). Prior to instrumental analysis, all sample solutions were filtered through a 0.22 μm nylon membrane (Jinteng, Tianjin, China) to remove particulate matter.

2.3. Metabolomics Sample Preparation

Approximately 100 mg of finely powdered leaf or shoot-tip tissue was accurately weighed and extracted with 1.2 mL of 70% (v/v) methanol (solvent-to-sample ratio: 12 mL·g−1). After thorough mixing, the suspension was incubated at 4 °C for 12 h to facilitate metabolite extraction, with intermittent vortexing (six times) to enhance solubilization. The extracts were then centrifuged at 12,000 rpm for 10 min at 4 °C, and the supernatants were collected and filtered through a 0.22 μm membrane to remove residual particulates. The clarified extracts were transferred to autosampler vials for subsequent UPLC–MS/MS analysis. Quality control (QC) samples were prepared by pooling equal aliquots of all leaf and shoot-tip extracts to obtain a representative matrix and were processed and analyzed under the same conditions as the test samples to monitor analytical stability and repeatability. To further assess instrument consistency, a pooled QC sample was injected after every six test samples throughout the sequence. Reproducibility of sample preparation and instrument performance was evaluated by comparing the total ion chromatograms across consecutive QC injections.

2.4. Metabolomic Analysis

Chromatographic separation was performed on a SHIMADZU Nexera X2 ultra-performance liquid chromatography (UPLC) system (Shimadzu Corporation, Kyoto, Japan) using an SB-C18 column (1.8 μm, 2.1 mm × 100 mm). The mobile phase consisted of solvent A (0.1% (v/v) formic acid in ultrapure water) and solvent B (0.1% (v/v) formic acid in acetonitrile). The gradient program was as follows: 5% B at 0 min, increased linearly to 95% B over 9.0 min, held at 95% B for 1.0 min, returned to 5% B from 10.0 to 11.1 min, and re-equilibrated at 5% B for 3.0 min. The flow rate was 0.35 mL·min−1, the column temperature was maintained at 40 °C, and the injection volume was 4 μL.
Prior to statistical analysis, the data were normalized and unit-variance (UV) scaled to reduce the influence of magnitude differences among variables. Principal component analysis (PCA) was then performed to visualize global metabolic variation among samples and to evaluate the clustering of biological replicates. To identify metabolites contributing to tissue discrimination, an orthogonal partial least squares discriminant analysis (OPLS-DA) model was constructed, and potential differential metabolites were selected based on variable importance in projection (VIP) scores. Metabolites with VIP ≥ 1, fold change (FC) ≥ 2 or ≤0.5, and p < 0.05 were considered significantly different. Model robustness and predictive performance were evaluated using a 200-permutation test. Metabolites meeting these criteria were further subjected to hierarchical clustering to assess within-group consistency and to characterize differences in metabolic profiles between tissue types.

2.5. Metabolomics Data Analysis

Metabolites were characterized based on MS/MS data acquired on the UPLC–MS/MS platform, and compound annotation was performed by matching spectra against the self-constructed MWDB library. During annotation, precursor m/z values, diagnostic fragment ions, and relative fragment-intensity patterns were jointly considered to improve confidence. Metabolites of particular interest were further verified using commercially available analytical standards (BioBioPha, Kunming, China; Sigma-Aldrich, St. Louis, MO, USA) analyzed under the same chromatographic and mass spectrometric conditions. Structural confirmation was achieved by matching both retention times and MS/MS fragmentation profiles between sample signals and authentic standards. Accordingly, the final metabolite list comprised compounds confirmed with standards and additional metabolites putatively annotated via spectral matching to the database.
After normalization and unit-variance (UV) scaling, multivariate statistical analyses were performed to explore metabolic variation among samples. Principal component analysis (PCA) was first applied to visualize overall metabolic differences and to evaluate the clustering consistency of biological replicates. To further discriminate between tissue types and identify metabolites contributing to classification, an orthogonal partial least squares discriminant analysis (OPLS-DA) model was constructed, and important variables were identified based on variable importance in projection (VIP) scores. Metabolites with VIP ≥ 1, fold change (FC) ≥ 2 or ≤0.5, and p < 0.05 were considered significantly differential. Model robustness and predictive performance were evaluated using a 200-permutation test. The selected differential metabolites were then subjected to hierarchical clustering to assess within-group consistency and to characterize tissue-specific metabolic patterns.

2.6. Quantitative Determination of Flavonoids in Leaves

2.6.1. Sample Preparation

Accurately weighed leaf powder (20 mg) was mixed with 10 μL of an internal standard mixed working solution (4000 nmol/L) and 500 μL of 70% (v/v) methanol. The mixture was ultrasonically extracted for 30 min and then centrifuged at 12,000 r/min for 5 min at 4 °C. The supernatant was collected and filtered through a 0.22 μm membrane to obtain the Idesia polycarpa leaf extract, which was transferred to autosampler vials for subsequent UPLC–MS/MS analysis.

2.6.2. Chromatographic and Mass Spectrometric Conditions

UPLC–MS/MS analysis was performed on a SHIMADZU Nexera X2 ultra-performance liquid chromatography (UPLC) system (Shimadzu, Kyoto, Japan) coupled to an Applied Biosystems 4500 QTRAP tandem mass spectrometer (AB Sciex LLC, Framingham, MA, USA).
(1)
Chromatographic conditions: Separation was performed on a Waters ACQUITY UPLC HSS T3 C18 column (1.8 μm, 100 mm × 2.1 mm i.d.; Waters, Milford, MA, USA). The mobile phase consisted of solvent A (0.05% formic acid in ultrapure water) and solvent B (0.05% formic acid in acetonitrile). The gradient program was as follows: 90:10 (A/B, v/v) at 0 min, 80:20 at 1 min, 30:70 at 9 min, and 5:95 at 12.5 min; 5:95 was maintained until 13.5 min, then returned to 90:10 at 13.6 min and re-equilibrated until 15 min. The flow rate was 0.35 mL·min−1; the column temperature was maintained at 40 °C, and the injection volume was 2 μL.
(2)
Mass spectrometric conditions: The electrospray ionization (ESI) source temperature was set to 550 °C. The ion spray voltage was 5500 V in positive ion mode and −4500 V in negative ion mode. The curtain gas (CUR) pressure was 25 psi, and collision-activated dissociation (CAD) was set to high. In the triple quadrupole (QQQ) mass analyzer (AB Sciex LLC, Framingham, MA, USA), each ion transition was monitored using the optimized declustering potential (DP) and collision energy (CE).

2.6.3. Calculation of Sample Contents

The integrated peak area ratio for each target compound was applied to the corresponding calibration curve to quantify its concentration in the extract. The calculated concentration was then used in the formula below to determine the absolute content of each compound in Idesia polycarpa leaves, expressed as nmol·g−1. For ease of interpretation and comparison, these values were subsequently converted to μg·g−1 and reported accordingly.
The flavonoid content in Idesia polycarpa leaves (nmol·g−1) was calculated using the following equation:
Flavonoid content (nmol/g) = c* × V/1,000,000m
where c is the analyte concentration (nmol·L−1) calculated by substituting the sample’s integrated peak area ratio into the calibration curve, V is the volume of extraction solvent (μL), and m is the mass of the weighed sample (g).

2.6.4. Construction of Calibration Curves

Standard working solutions were prepared at 0.5, 1, 5, 10, 20, 50, 100, 200, 500, 1000, and 2000 nmol·L−1. For each concentration level, the corresponding quantitative mass spectrometric responses were recorded. Calibration curves were constructed for each analyte by plotting the concentration ratio of the target compound to the internal standard (x-axis) against the corresponding peak area ratio (y-axis). The regression equations and correlation coefficients for all quantified metabolites are summarized in Table 1.
Table 1. Regression equations and corresponding correlation coefficients for the 53 quantified flavonoid compounds.

2.7. Data Processing

In this section, chromatographic peaks were integrated and manually inspected using MultiQuant software (version 3.0.3), while mass spectrometric data were processed with Analyst 1.6.3. The resulting tables were compiled in Microsoft Excel (2022 version). Multivariate analyses and graphical visualizations, including principal component analysis (PCA) score plots, hierarchical clustering heatmaps, and Venn diagrams, were generated in R (version 4.3.2).

3. Results

3.1. UPLC–MS/MS Analysis and Multivariate Statistical Analysis

UPLC–MS/MS analysis was performed in both positive and negative electrospray ionization modes to characterize metabolic variation between the leaves and shoot tips of Idesia polycarpa. Representative total ion chromatograms for the two tissue types are shown in Figure 1A,B. To obtain an overview of metabolic differentiation and to evaluate sample consistency, principal component analysis (PCA) was conducted using data from leaf samples, shoot-tip samples, and quality control (QC) injections. As shown in Figure 1C, the first principal component (PC1) explained 48.13% of the total variance, while the second principal component (PC2) accounted for 24.28%, resulting in a cumulative explained variance of 72.41%. The PCA score plot showed a clear separation between leaves and shoot tips, indicating pronounced differences in metabolite profiles between the two tissues. In addition, biological replicates clustered tightly within each group, supporting strong analytical reproducibility and overall data reliability.
Figure 1. Total ion chromatograms and PCA score plot. (A) Positive ion mode; (B) Negative ion mode; (C) PCA score plot. Note: Mix is the quality control sample.

3.2. Comparative Analysis of Metabolites in Leaves and Shoot Tips of Idesia polycarpa

Database-based annotation identified 689 metabolites in Idesia polycarpa. Of these, 657 were detected in leaves and 667 in shoot tips, with 635 metabolites shared by both tissues. The annotated metabolites spanned diverse chemical classes, including phenolic acids, flavonoids, lipids, amino acids and related derivatives, organic acids, nucleotides and their derivatives, alkaloids, terpenoids, and other secondary metabolites. In terms of composition, flavonoids and phenolic acids were the predominant secondary-metabolite groups, whereas primary metabolites—such as lipids, amino acids and their derivatives, and organic acids—were also well represented (Figure 2A,B). Although leaves and shoot tips showed substantial overlap in metabolite identities, their relative abundances differed markedly.
Figure 2. Classification of metabolites in leaves and shoot tips of Idesia polycarpa. (A) Metabolite categories and numbers; (B) Venn diagram.

3.3. Screening of Differential Metabolites Between Leaves and Shoot Tips of Idesia polycarpa

Based on OPLS-DA screening (VIP ≥ 1 and fold change ≥ 2 or ≤0.5), 378 significantly differential metabolites were identified. Among these, 273 metabolites were downregulated in leaves (i.e., accumulated at higher levels in shoot tips), whereas 105 metabolites were upregulated in leaves. With respect to chemical classes, lipids comprised the largest fraction of metabolites enriched in shoot tips (63 compounds, including glycerides, lysophosphatidylcholines, lysophosphatidylethanolamines, and free fatty acids), followed by amino acids and their derivatives (36 compounds), flavonoids (44 compounds), and organic acids (24 compounds), indicating that lipid-related metabolites were relatively abundant in shoot tips. In contrast, metabolites enriched in leaves were mainly phenolic acids (28 compounds) and flavonoids (16 compounds), together with lignans and coumarins (11 compounds) and several terpenoids and alkaloids, suggesting a higher accumulation of secondary metabolites in leaves. Overall, shoot tips were characterized by elevated levels of lipids and other primary metabolites, whereas leaves were significantly enriched in phenolic acids and flavonoids, reflecting distinct tissue-specific metabolic differentiation (Figure 3).
Figure 3. Volcanic map of differential metabolites. Note: In the plot, each dot represents a metabolite showing differential accumulation. The x-axis indicates the fold change between the two groups; larger absolute values represent greater differences in abundance. The y-axis represents statistical significance, with higher values indicating stronger significance. Metabolites with significantly increased abundance are shown in red, whereas those with decreased abundance are shown in green; metabolites without significant differences are shown in gray. The horizontal dotted line indicates the threshold of VIP = 1, and the vertical dotted lines indicate the fold change thresholds (FC = 2 and FC = 0.5, corresponding to log2 FC = 1 and log2 FC = −1, respectively). Metabolites were considered significantly differential when they met the criteria of VIP ≥ 1, fold change ≥ 2 or ≤0.5, and p < 0.05.

3.4. Cluster Analysis of Differential Metabolites in Idesia polycarpa Leaves and Shoot Tips

To further examine class-specific distribution patterns between the two tissues, hierarchical clustering was performed using all differential metabolites (Figure 4 and Figure 5). Overall, most metabolite classes showed higher abundance in shoot tips, whereas leaves were mainly enriched in specific secondary metabolites. Among differential flavonoids and phenolic acids, a relatively larger fraction accumulated in leaves (16/60 and 28/60, respectively), indicating a stronger enrichment of secondary metabolites in leaf tissue. In contrast, most differential metabolites classified as lipids (63/72), amino acids and their derivatives (36/40), organic acids (24/32), nucleotides and their derivatives (20/24), and terpenoids (15/19) were more abundant in shoot tips, suggesting more active primary metabolism and membrane lipid-associated processes in this tissue. In addition, alkaloid metabolites showed a slight enrichment in shoot tips (7/11), whereas coumarins and lignans were relatively enriched in leaves. Although only a few tannin-related differential metabolites were detected, they mainly accumulated in shoot tips. Only one quinone metabolite, 4,8-dihydroxynaphthol-1-O-glucoside, differed between the two tissues and was present at a higher level in shoot tips. Overall, shoot tips were enriched in lipids and a range of primary metabolism-related compounds, whereas leaves accumulated higher levels of phenolic acids, flavonoids, and other phenylpropanoid-derived secondary metabolites, further highlighting tissue-specific metabolic differentiation.
Figure 4. Hierarchical clustering analysis of differential metabolites. (A) Flavonoids; (B) phenolic acids; (C) lipids.
Figure 5. Hierarchical clustering analysis of differential metabolites. (A) Amino acids and their derivatives; (B) alkaloids; (C) coumarins and lignans; (D) others; (E) organic acids; (F) nucleotides and their derivatives; (G) tannins; (H) terpenoids.

3.5. Analysis of Unique and Key Bioactive Constituents in Different Parts of Idesia polycarpa

Among the detected metabolites, five representative compounds showing significant differences were selected for further analysis (Figure 6). Catechol, salidroside, and idesin accumulated at higher levels in leaves, whereas norconiferin and idesin salicylate were more abundant in shoot tips. In addition, 22 and 32 tissue-specific metabolites were identified in leaves and shoot tips, respectively (Table 2).
Figure 6. Content of Key Functional Components (* p < 0.05, ** p < 0.01).
Table 2. Characteristic Components of Different Parts of Idesia polycarpa.

3.6. Quantitative Determination of Flavonoid Contents in Leaves of Idesia polycarpa

In the classification of differential metabolites, flavonoids showed a pronounced enrichment in leaves and constituted an important class of secondary metabolites in Idesia polycarpa. Therefore, targeted quantitative analysis of leaf flavonoids was conducted. In total, 52 flavonoids were analyzed by UPLC–MS/MS (Table 3), and absolute quantification was obtained for 51 compounds, including flavones, flavonols, dihydroflavones, and chalcones. Overall, flavonoid contents varied substantially among compounds in leaves. Scutellarin (2088.1350 μg/g) and apigenin-7-O-glucuronide (1020.9085 μg/g) were the predominant constituents, followed by luteoloside and apigenin-7-O-glucoside. Among the flavonols, rutin showed the highest content (13.6801 μg/g). Aside from these major constituents, most other flavonoids occurred at relatively low levels, with the majority below 1 μg/g.
Table 3. Flavonoid compounds identified in Idesia polycarpa leaves.

4. Discussion

4.1. Metabolomic Analysis of Shoot Tips and Leaves of Idesia polycarpa

In this study, untargeted metabolomics was used to systematically profile metabolites in the shoot tips and leaves of Idesia polycarpa. A total of 635 metabolites were shared between the two tissues, and 378 were identified as significantly differential; moreover, 32 metabolites were detected exclusively in shoot tips, and 22 were specific to leaves. In shoot tips, 273 metabolites showed higher abundance, mainly comprising primary metabolites (e.g., nucleotides and their derivatives and amino acids), together with compounds such as catechin, epicatechin, caffeine, and anthocyanins. Catechins are major constituents of tea polyphenols and contribute substantially to their health-promoting effects [42], whereas caffeine and anthocyanins are important contributors to bitterness in tea infusions [43]. In tea, polyphenols (including catechins), L-theanine, caffeine, theobromine, and volatile organic compounds have been associated with potential roles in the prevention and management of cardiovascular disease, cancer, digestive disorders, and metabolic diseases (e.g., obesity and diabetes) [14,35,36,44]. Phenolic acid extracts from I. polycarpa fruits have also been reported to alleviate non-alcoholic fatty liver disease by regulating lipid metabolism in oleic acid-induced HepG2 cells and high-fat diet-induced mice. Notably, the shoot tips of I. polycarpa contained L-theanine and various free amino acids. Free amino acids are major contributors to the umami taste of tea; among them, L-theanine, a characteristic amino acid in tea, has been reported to exhibit health-promoting and anticancer activities and to exert neuroprotective effects [45]. The enrichment of catechin, epicatechin, caffeine, anthocyanins, and free amino acids in I. polycarpa shoot tips provides a rationale for exploring shoot tips as a raw material for tea-like products. In contrast, 105 metabolites were more abundant in leaves, and secondary metabolites—particularly phenolic acids and flavonoids—accounted for the largest proportion, including catechol, salicortin, and idesin. Flavonoids are key components of plant defense against herbivorous insects and are generally considered safe for human consumption; they play central roles in biotic stress responses (e.g., herbivory and microbial and nematode infection) and can enhance tolerance to abiotic stresses such as ultraviolet radiation [46]. For example, herbivore feeding activates flavonoid-related genes in tea plants, promoting flavonoid accumulation and defense responses against the tea green leafhopper (Empoasca onukii Matsuda) [47], and elevated flavonoid levels in cotton have been linked to resistance against Spodoptera frugiperda (J. E. Smith) and Aphis gossypii Glover [48]. Catechol exhibits antibacterial activity, and its incorporation into hydrogels can confer antimicrobial properties [49]; additionally, catechol supplementation has been reported to preserve nutritional quality and enhance antioxidant capacity during the ensiling of Chinese toon (Toona sinensis (A. Juss.) M. Roem.) leaves [50]. Both salicortin and idesin have been shown to inhibit lipopolysaccharide-induced nitric oxide production in BV2 microglial cells, suggesting anti-inflammatory potential [51]. Collectively, the enrichment of catechol, salidroside, and idesin in I. polycarpa leaves indicates that this tissue may serve as a promising source of antioxidant and anti-inflammatory compounds; nevertheless, these activities require further experimental validation.
In addition, norconiferin and idesin salicylate were detected in Idesia polycarpa shoot tips for the first time, and idesin salicylate was also identified in leaves for the first time, further expanding the metabolite information available for different tissues of I. polycarpa. These compounds have been reported to exhibit antioxidant and anti-inflammatory activities [52,53], suggesting that they may represent promising bioactive constituents in I. polycarpa shoot tips and leaves; however, their activities in this species require further experimental validation.

4.2. Quantitative Analysis of Flavonoids in Idesia polycarpa Leaves

Flavonoids are a major class of plant secondary metabolites that are widely distributed across plant species and tissues. They exhibit anti-inflammatory, antibacterial, and antioxidant activities and have been implicated in the prevention and management of cancer, diabetes, and cardiovascular diseases [54,55,56]. In this study, UPLC–MS/MS was used to quantitatively analyze 53 flavonoids in Idesia polycarpa leaves. The most abundant compounds were scutellarin (2088.14 μg/g) and apigenin-7-O-glucuronide (1020.91 μg/g). Scutellarin has been reported to exert anti-inflammatory [57] and hypoglycemic activities [58], to provide protection against cerebrovascular diseases [59], and to induce apoptosis and inhibit the proliferation of human leukemia K562 cells [60]. Apigenin has been reported to inhibit pancreatic lipase activity [61], alleviate age-related aortic stiffness [62], and promote bone formation and fracture healing in vivo, suggesting potential value for managing obesity, vascular aging, and fracture repair [63]. In addition, I. polycarpa leaves contained other bioactive flavonoids, including luteolin-7-O-glucoside, sakuranetin, and chrysin. Although present at lower levels, these compounds have documented biological relevance. Luteolin-7-O-glucoside exhibits anticancer activity [64] and cardiovascular protective effects [65] and has been explored for respiratory diseases such as asthma [66]. Sakuranetin shows bioactivities comparable to those reported for idescarpin, including antioxidant effects and inhibition of melanogenesis, which may contribute to skin-whitening properties [67]. Chrysin isolated from hickory leaves has also shown antitumor activity against human hepatocellular carcinoma HepG2 cells, with an IC50 of approximately 53 μmol·L−1 [68]. Beyond flavones, I. polycarpa leaves were rich in flavonols, including rutin, quercitrin, isorhamnetin, and quercetin. Quercetin is widely recognized for its anti-inflammatory and antioxidant properties and has potential as an adjunct in the management of inflammatory diseases and oxidative stress-related disorders [69]. Overall, these results indicate that I. polycarpa leaves contain a diverse set of flavonoids with potential functional value, including scutellarin, apigenin derivatives, luteoloside, sakuranin, and chrysoeriol. Nevertheless, because functional assays were not performed in the present study, the bioactivities of these compounds in I. polycarpa leaves warrant further experimental validation.

5. Conclusions

This study systematically compared the metabolic characteristics of leaves and shoot tips of Idesia polycarpa, identifying 635 shared metabolites and 378 differential metabolites, including 32 and 22 tissue-specific metabolites in shoot tips and leaves, respectively. The results showed that shoot tips were relatively enriched in lipids and other primary metabolites, with catechin and epicatechin as representative compounds, whereas leaves accumulated higher levels of secondary metabolites, particularly phenolic acids and flavonoids, including scutellarin and catechol. Targeted quantification further indicated that scutellarin was the most abundant flavonoid in leaves. Collectively, these findings demonstrate pronounced tissue-specific metabolic differentiation in I. polycarpa and provide a data basis for the future development and utilization of its shoot tips and leaves.

Author Contributions

Conceptualization, Z.L. (Zhen Liu); methodology, Z.L. (Zhen Liu).; software, X.X. and G.L.; validation, F.L., Q.C. (Qi Cai) and Z.L. (Zhen Liu); formal analysis, F.L., X.X., Y.W., L.D., Z.L., X.G., C.L. and G.L.; investigation, G.L. and X.X.; resources, Q.C. (Qi Cai) and Z.L. (Zhen Liu); data curation, X.X. and G.L.; writing—original draft preparation, G.L. and Z.L. (Zhen Liu); writing—review and editing, G.L., Q.C. (Qi Cai) and Z.L. (Zhen Liu); visualization, Q.C. (Qi Cai), Z.L. (Zhen Liu), G.L., F.L., X.X., Y.W., L.D., Z.L., X.G. and C.L.; supervision, Q.C. (Qi Cai), Z.L. (Zhen Liu), F.L. and Y.W.; project administration, Q.C. (Qi Cai) and Z.L. (Zhen Liu); funding acquisition, Q.C. (Qi Cai) and Z.L. (Zhen Liu). All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Henan Provincial School–Enterprise Research and Development Center Project for Idesia polycarpa (25CY017).

Data Availability Statement

The data sets generated during and/or analyzed during the current study are available from the corresponding authors upon reasonable request.

Acknowledgments

We appreciate the reviewers’ insightful critique enhancing the caliber of the article.

Conflicts of Interest

All the authors declare that there is no conflict of interest.

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