Rheum tanguticum tissue specific metabolite detection method and Rheum tanguticum comprehensive development and utilization method

Abstract

The invention belongs to the technical field of metabonomics, and particularly relates to a detection method of rheum tanguticum tissue specific metabolites and a comprehensive development and utilization method of rheum tanguticum, the detection method comprises the following steps: grinding roots, stems, leaves and seeds of rheum tanguticum to obtain powder samples of each tissue; mixing the powder sample with the extracting solution, extracting by adopting an ultrasonic-assisted method, and standing, centrifuging and filtering the obtained extract to obtain supernate; and carrying out liquid chromatography-tandem mass spectrometry analysis on the supernate, collecting data, and screening differential metabolites in combination with multivariate statistics and metabolic pathway enrichment analysis. According to the invention, a non-targeted metabonomics technology is adopted, composition differences of metabolites in various tissues of rheum tanguticum are systematically analyzed, and tissue-specific marker metabolites are screened out. The tissue distribution rule of the secondary metabolite on the metabolome level is disclosed, and a scientific basis is provided for medicine part selection, non-medicine tissue utilization, molecular breeding and the like.

Description

Technical Field

[0001] The present invention belongs to the technical field of metabolomics, and specifically relates to a method for detecting tissue-specific metabolites of Rheum tanguticum and a method for comprehensive development and utilization of Rheum tanguticum. Background Art

[0002] Rheum tanguticum Maxim. ex Balf. is a perennial herbaceous plant in the genus Rheum, Polygonaceae. Its dried roots and rhizomes are listed as medicinal parts in the Chinese Pharmacopoeia, making it one of the primary basal species of the traditional Chinese medicinal herb "rhubarb." Modern pharmacological studies have shown that the active ingredients contained in this plant, such as anthraquinones, tannins, and stilbenes, possess significant anti-inflammatory, antioxidant, and anti-tumor properties. In recent years, with the advancement of natural product research, anthraquinones in Rheum tanguticum have attracted considerable attention due to their multiple biological activities, such as antioxidant, anti-inflammatory, and anti-tumor properties, demonstrating potential for application in food additives and functional health products. Notably, the synthesis and accumulation of plant secondary metabolites are often tissue-specific. For example, anthraquinones in Rheum tanguticum are primarily concentrated in the roots, while leaves, stems, and seeds may contain other potentially valuable metabolites. Current research focuses on the chemical composition analysis of medicinal parts, and there is a lack of systematic research on the metabolic characteristics of non-medicinal tissues (such as leaves, stems, and seeds) and their relationship with the root system, resulting in the aboveground parts, which account for more than 50% of the biomass, being often discarded.

[0003] In recent years, the development of metabolomics technology (such as liquid chromatography-mass spectrometry, LC-MS) has provided a powerful tool for the comprehensive analysis of plant metabolic networks. By combining non-targeted metabolomics with multivariate statistical analysis (such as PCA, OPLS-DA), researchers have successfully revealed the distribution patterns of metabolites and their biosynthetic regulatory mechanisms in different tissues of a variety of medicinal plants. Although certain progress has been made in the study of the metabolism of Rheum officinale, existing work mainly focuses on the analysis of single tissues or specific components, and the tissue-specific distribution patterns of full-spectrum metabolites and their regulatory mechanisms are still unclear. In addition, wild Rheum tanguticum resources are on the verge of depletion due to over-exploitation. If the medicinal value of the aboveground parts or the regulatory targets of key metabolites are explored through metabolomics, the efficiency of resource utilization will be significantly improved, and a theoretical basis will be provided for the optimization of metabolic engineering. Summary of the Invention

[0004] The present invention aims to provide a method for detecting tissue-specific metabolites of Rheum tanguticum and a method for its comprehensive development and utilization. Using non-targeted metabolomics technology, the present invention systematically analyzes the compositional differences of metabolites in various Rheum tanguticum tissues and screens for tissue-specific marker metabolites. This method reveals the tissue distribution patterns of secondary metabolites at the metabolomic level, providing a scientific basis for drug site selection, non-drug tissue utilization, and molecular breeding.

[0005] The present invention provides a method for detecting tissue-specific metabolites of Rheum tanguticum, comprising the following steps:

[0006] The roots, stems, leaves and seeds of Rheum tanguticum were ground to obtain powder samples of each tissue;

[0007] After mixing the powder sample with the extracting solution, the extraction is performed using an ultrasound-assisted method, and the obtained extract is allowed to stand, centrifuged, and filtered to obtain a supernatant;

[0008] The supernatant was subjected to liquid chromatography-tandem mass spectrometry analysis. After data collection, differential metabolites were screened by combining multivariate statistics and metabolic pathway enrichment analysis.

[0009] As a preferred embodiment, the Rhubarb Tangut includes Rhubarb Tangut of the same growth cycle, and the same growth cycle includes five years.

[0010] As a preferred solution, the extracting solution is methanol and water, the volume ratio of methanol to water is 4:1, and the mass volume ratio of the powder sample to the extracting solution is 0.1-0.2 g:500 μL.

[0011] As a preferred solution, the frequency of the ultrasonic assistance is 40 to 50 Hz, and the time of the ultrasonic assistance is 50 to 70 minutes.

[0012] As a preferred solution, the standing time is 50 to 70 minutes, the standing temperature is -40°C, the centrifugal speed is 12000 rpm, and the centrifugal time is 10 to 20 minutes.

[0013] As a preferred embodiment, the chromatographic conditions in the liquid chromatography-tandem mass spectrometry analysis are as follows: a Waters UPLC BEHC18 chromatographic column is selected, the column temperature is 35° C., the flow rate is 0.4 mL / min, and the injection volume is 2 μL; the mobile phase consists of 0.1% A acid aqueous solution and 0.1% A acid B nitrile solution.

[0014] As a preferred embodiment, the cleanup gradient program in the liquid chromatography-tandem mass spectrometry analysis is: 0-3.5 min, 95-85% A; 3.5-6 min, 85-70% A; 6-6.5 min, 70% A; 6.5-12 min, 70-30% A; 12-12.5 min, 30% A; 12.5-18 min, 30-0% A; 18-25 min, 0% A; 25-26 min, 0-95% A; 26-30 min, 95% A.

[0015] As a preferred embodiment, the mass spectrometry conditions in the liquid chromatography-tandem mass spectrometry analysis are as follows: the mass spectrometry analysis uses an Orbitrap Exploris 120 mass spectrometer, and in information-dependent acquisition mode, MS and MS / MS data are obtained under the control of XCalibur software; the mass range of each acquisition cycle is 100-1500 m / z, and the first four ions in each cycle are selected for further MS / MS scanning.

[0016] As a preferred embodiment, the specific parameters of the mass spectrometry in the liquid chromatography-tandem mass spectrometry analysis are: sheath gas flow rate: 30Arb; auxiliary air flow rate: 10Arb; ion transfer tube temperature: 350°C; evaporator temperature: 350°C; full scan mass spectrometry resolution: 60,000; MS / MS mass spectrometry resolution: 15,000; collision energy: 16, 32 and 48 respectively in normalized collision energy mode; spray voltage: 5.5kV in positive ion mode and -4kV in negative ion mode.

[0017] The present invention also provides a comprehensive development and utilization method of Tangut rhubarb, comprising any one or more of the following:

[0018] (a) The roots are used to prepare anthraquinone medicinal preparations;

[0019] (b) Extraction of proanthocyanidins from seeds for use in antioxidant products;

[0020] (c) Processing of the stems as flavor food additives;

[0021] (d) Flavonoids extracted from leaves are used as daily chemical raw materials.

[0022] Beneficial effects: The present invention provides a method for detecting tissue-specific metabolites of Rheum tanguticum, comprising the following steps: grinding the roots, stems, leaves and seeds of Rheum tanguticum to obtain powder samples of each tissue; mixing the powder samples with the extract, extracting them by an ultrasound-assisted method, and obtaining a supernatant by standing, centrifuging and filtering the obtained extract; subjecting the supernatant to liquid chromatography-tandem mass spectrometry analysis, and after data collection, combining multivariate statistics and metabolic pathway enrichment analysis to screen differential metabolites. The present invention adopts non-targeted metabolomics technology to systematically analyze the compositional differences of metabolites in various tissues of Rheum tanguticum, and screen out tissue-specific marker metabolites. The present invention reveals the tissue distribution patterns of secondary metabolites at the metabolome level, providing a scientific basis for aspects such as drug site selection, non-drug tissue utilization and molecular breeding.

[0023] This study used untargeted metabolomics with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS / MS) to systematically analyze the metabolite profiles of four tissues: roots, stems, leaves, and seeds, from five-year-old plants of Rheum tanguticum Maxim. ex Balf., a species endemic to the Qinghai-Tibet Plateau. Multivariate statistical analysis (PCA, OPLS-DA) and KEGG pathway enrichment analysis identified 1,339 secondary metabolites, including flavonoids (20.88%), terpenes (16.9%), phenylpropanoids (12.4%), alkaloids (8.0%), and anthraquinones (quinones, 1.42%) as major active ingredients. The study found that the roots, a traditional medicinal part, are rich in anthraquinones (such as emodin and chrysophanol), phenolic acids, and phenylpropanoids; the leaves are primarily flavonoid-rich; and the seeds specifically accumulate procyanidins (such as procyanidin A1 / A2) and alkaloids. KEGG pathway enrichment analysis showed that flavonoid synthesis in leaves was significantly enriched in the phenylpropanoid metabolic pathway (involving key enzymes such as PAL and 4CL); in the root-stem / leaf comparison, α-linolenic acid metabolism and unsaturated fatty acid biosynthesis pathways were significantly enriched, which may be related to secondary metabolite storage and stress resistance. This invention is the first to elucidate the high-value metabolite potential of non-medicinal tissues of Rheum tanguticum from the metabolic network level. Based on the tissue distribution characteristics of metabolites, a full resource utilization model of "roots (anthraquinones) medicinal - seeds (proanthocyanidins) antioxidant - stems (malic acid) food processing - leaves (flavonoids) daily chemical raw materials" is proposed, providing a theoretical basis for the sustainable development of endangered medicinal plant resources and molecular breeding.

[0024] This study, through systematic metabolomics analysis, elucidates for the first time the metabolic characteristics and regulatory mechanisms of different tissues of Rheum tanguticum at the metabolic network level. This study not only confirms that the traditional medicinal part (root) is rich in pharmacologically active secondary metabolites, but more importantly, reveals that the aboveground parts (stems, leaves, and seeds), which account for over 50% of the plant's biomass, contain numerous high-value metabolites. Of particular note are flavonoids in the leaves and polyphenols in the seeds. These findings provide a scientific basis for the comprehensive development of Rheum tanguticum resources. Based on metabolomics data, the present invention proposes a gradient development model: "root medicinal use - seed antioxidant - stem food processing - leaf daily chemical raw material." This strategy can alleviate resource pressure on traditional medicinal parts while significantly improving comprehensive resource utilization, in line with the goal of sustainable utilization of endangered medicinal plants. Future research should combine multi-omics technologies to deeply analyze the regulatory networks of key metabolic pathways and verify the pharmacological activity of key metabolites through in vitro activity experiments. This will promote the transformation of Rheum tanguticum from a traditional medicinal plant into high-value-added functional products and promote the industrialization of high-altitude biological preparations. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments are briefly introduced below.

[0026] Figure 1 is the proportion of secondary metabolites detected in different tissues of Rheum tanguticum;

[0027] Figure 2 This is the PCA score scatter plot of all samples of Rheum tanguticum (including QC samples);

[0028] Figure 3 The differences in different metabolite categories among the roots, stems, leaves and seeds of Rheum tanguticum;

[0029] Figure 4 The differences in proanthocyanidins in the roots, stems, leaves and seeds of Rheum tanguticum;

[0030] Figure 5 To analyze the distribution of DAMs among different tissues of Rheum tanguticum;

[0031] Figure 6 To conduct intersection analysis of the six groups of DAMs comparisons through Venn diagrams, each dot in the figure represents a comparison group, and the Set Size corresponding to each dot represents the number of metabolites contained in the comparison group. The dots corresponding to the horizontal axis of the bar graph represent the comparison of each group, and the vertical axis represents the number of differential metabolites shared by each group.

[0032] Figure 7 KEGG enrichment analysis of root-stem differential metabolites was compared between groups;

[0033] Figure 8 KEGG enrichment analysis of differential metabolites between roots and leaves was compared between groups;

[0034] Figure 9 KEGG enrichment analysis of root-seed differential metabolites was compared between groups;

[0035] Figure 10 KEGG enrichment analysis of stem-leaf differential metabolites was compared between groups;

[0036] Figure 11 Comparison of KEGG enrichment analysis of stem-seed differential metabolites between groups;

[0037] Figure 12 KEGG enrichment analysis of leaf-seed differential metabolites was compared between groups;

[0038] Note: Figures 7-12 The horizontal axis represents the differential abundance score (DA Score), and the vertical axis represents the KEGG metabolic pathway name; the DA Score reflects the overall changes of all metabolites in the metabolic pathway. A score of 1 indicates that the expression trend of all annotated differential metabolites in the pathway is upregulated, and -1 indicates that the expression trend of all annotated differential metabolites in the pathway is downregulated. The length of the line segment represents the absolute value of the DA Score; the size of the dot represents the number of annotated differential metabolites in the pathway, and the larger the dot, the more differential metabolites in the pathway; the more the dots are distributed on the right side of the central axis and the longer the line segment, the more the overall expression of the pathway tends to be upregulated; the more the dots are distributed on the left side of the central axis and the longer the line segment, the more the overall expression of the pathway tends to be downregulated. DETAILED DESCRIPTION

[0039] The present invention provides a method for detecting tissue-specific metabolites of Rheum tanguticum, comprising the following steps:

[0040] The roots, stems, leaves and seeds of Rheum tanguticum were ground to obtain powder samples of each tissue;

[0041] After mixing the powder sample with the extracting solution, the extraction is performed using an ultrasound-assisted method, and the obtained extract is allowed to stand, centrifuged, and filtered to obtain a supernatant;

[0042] The supernatant was subjected to liquid chromatography-tandem mass spectrometry analysis. After data collection, differential metabolites were screened by combining multivariate statistics and metabolic pathway enrichment analysis.

[0043] The Rheum tanguticum described herein includes Rheum tanguticum plants of the same growth cycle. In the present embodiment, five Rheum tanguticum plants of the same growth cycle (five years old) and the same ecological environment were selected. These plants grew uniformly, were free of pests and diseases, and had mature seeds. Seeds, stems, leaves, and roots were sampled from each plant. The samples were first washed with clean water, then rinsed twice with PBS buffer, and then immediately frozen in liquid nitrogen and stored in a refrigerator for subsequent experimental use.

[0044] The extracting solution of the present invention is methanol and water, the volume ratio of methanol and water is 4:1, and the mass volume ratio of the powder sample to the extracting solution is 0.1-0.2 g:500 μL; as a specific embodiment, the mass volume ratio of the powder sample to the extracting solution can be 0.1 g:500 μL, 0.11 g:500 μL, 0.12 g:500 μL, 0.13 g:500 μL, 0.14 g:500 μL, 0.15 g:500 μL, 0.16 g:500 μL, 0.17 g:500 μL, 0.18 g:500 μL, 0.19 g:500 μL or 0.2 g:500 μL.

[0045] The frequency of the ultrasonic assistance of the present invention is 40-50 Hz, and the time of the ultrasonic assistance is 50-70 min; as a specific embodiment, the frequency of the ultrasonic assistance may be 40 Hz, 41 Hz, 42 Hz, 43 Hz, 44 Hz, 45 Hz, 46 Hz, 47 Hz, 48 Hz, 49 Hz or 50 Hz; as a specific embodiment, the time of the ultrasonic assistance may be 50 min, 51 min, 52 min, 53 min, 54 min, 55 min, 56 min, 57 min, 58 min, 59 min, 60 min, 61 min, 62 min, 63 min, 64 min, 65 min, 66 min, 66 min, 67 min, 68 min, 69 min or 70 min.

[0046] The standing time of the present invention is 50 to 70 minutes, the standing temperature is -40°C, the centrifugal speed is 12000 rpm, and the centrifugal time is 10 to 20 minutes. As a specific embodiment, the standing time can be 50 minutes, 51 minutes, 52 minutes, 53 minutes, 54 minutes, 55 minutes, 56 minutes, 57 minutes, 58 minutes, 59 minutes, 60 minutes, 61 minutes, 62 minutes, 63 minutes, 64 minutes, 65 minutes, 66 minutes, 66 minutes, 67 minutes, 68 minutes, 69 minutes or 70 minutes; as a specific embodiment, the centrifugal time can be 10 minutes, 11 minutes, 12 minutes, 13 minutes, 14 minutes, 15 minutes, 16 minutes, 17 minutes, 18 minutes, 19 minutes or 20 minutes.

[0047] As a specific embodiment, the chromatographic conditions in the liquid chromatography-tandem mass spectrometry analysis are as follows: a Waters UPLC BEHC18 column is selected, the column temperature is 35°C, the flow rate is 0.4 mL / min, and the injection volume is 2 μL; the mobile phase consists of 0.1% aqueous acid A solution and 0.1% acid B nitrile solution. As a specific embodiment, the cleanup gradient program in the liquid chromatography-tandem mass spectrometry analysis is as follows: 0-3.5 min, 95-85% A; 3.5-6 min, 85-70% A; 6-6.5 min, 70% A; 6.5-12 min, 70-30% A; 12-12.5 min, 30% A; 12.5-18 min, 30-0% A; 18-25 min, 0% A; 25-26 min, 0-95% A; 26-30 min, 95% A. As a specific embodiment, the mass spectrometry conditions in the liquid chromatography-tandem mass spectrometry analysis are as follows: the mass spectrometry analysis uses an Orbitrap Exploris 120 mass spectrometer, and MS and MS / MS data are acquired under the control of XCalibur software in information-dependent acquisition mode; the mass range of each acquisition cycle is 100-1500 m / z, and the first four ions in each cycle are selected for further MS / MS scanning. As a specific embodiment, the specific mass spectrometry parameters in the liquid chromatography-tandem mass spectrometry analysis are as follows: sheath gas flow rate: 30 Arb; auxiliary air flow rate: 10 Arb; ion transfer tube temperature: 350°C; evaporator temperature: 350°C; full scan mass spectrometry resolution: 60,000; MS / MS mass spectrometry resolution: 15,000; collision energy: 16, 32, and 48, respectively, in normalized collision energy mode; spray voltage: 5.5 kV in positive ion mode and -4 kV in negative ion mode.

[0048] This study used untargeted metabolomics with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS / MS) to systematically analyze the metabolite profiles of four tissues: roots, stems, leaves, and seeds, from five-year-old plants of Rheum tanguticum Maxim. ex Balf., a species endemic to the Qinghai-Tibet Plateau. Multivariate statistical analysis (PCA, OPLS-DA) and KEGG pathway enrichment analysis identified 1,339 secondary metabolites, including flavonoids (20.88%), terpenes (16.9%), phenylpropanoids (12.4%), alkaloids (8.0%), and anthraquinones (quinones, 1.42%) as major active ingredients. The study found that the roots, a traditional medicinal part, are rich in anthraquinones (such as emodin and chrysophanol), phenolic acids, and phenylpropanoids; the leaves are primarily flavonoid-rich; and the seeds specifically accumulate procyanidins (such as procyanidin A1 / A2) and alkaloids. KEGG pathway enrichment analysis showed that flavonoid synthesis in leaves was significantly enriched in the phenylpropanoid metabolic pathway (involving key enzymes such as PAL and 4CL); in the root-stem / leaf comparison, α-linolenic acid metabolism and unsaturated fatty acid biosynthesis pathways were significantly enriched, which may be related to secondary metabolite storage and stress resistance.

[0049] The present invention also provides a comprehensive development and utilization method of Tangut rhubarb, comprising any one or more of the following:

[0050] (a) The roots are used to prepare anthraquinone medicinal preparations;

[0051] (b) Extraction of proanthocyanidins from seeds for use in antioxidant products;

[0052] (c) Processing of the stems as flavor food additives;

[0053] (d) Flavonoids extracted from leaves are used as daily chemical raw materials.

[0054] This invention illustrates for the first time the potential for high-value metabolites in the non-medicinal tissues of Rheum tanguticum from the metabolic network level. Based on the tissue distribution characteristics of the metabolites, a full resource utilization model of "roots (anthraquinones) medicinal - seeds (proanthocyanidins) antioxidant - stems (malic acid) food processing - leaves (flavonoids) daily chemical raw materials" is proposed, providing a theoretical basis for the sustainable development of endangered medicinal plant resources and molecular breeding.

[0055] To further illustrate the present invention, a method for detecting tissue-specific metabolites of Rheum tanguticum and a method for comprehensive development and utilization of Rheum tanguticum provided by the present invention are described in detail below in conjunction with the examples, but they should not be understood as limiting the scope of protection of the present invention.

[0056] Unless otherwise specified, the present invention has no special requirements for the raw materials, and commercially available products known to those skilled in the art can be used.

[0057] Example

[0058] 1. Test Materials

[0059] The experimental materials for this study were collected in October 2024 from Hualong County, Qinghai Province (latitude and longitude: 102.185607E, 36.192991N). Five Rheum tanguticum plants with the same growth cycle (five years old) and the same ecological environment were selected. These plants grew uniformly, were free of pests and diseases, and their seeds were at maturity. Seeds, stems, leaves, and roots were sampled from each plant. The samples were first washed with clean water, then rinsed twice with PBS buffer, and then immediately frozen in liquid nitrogen and stored in a refrigerator at -80°C for subsequent experimental use.

[0060] 2. Test methods

[0061] 1. Metabolite Extraction and Detection

[0062] Five samples stored at -80°C were ground in a stirred mill for 60 seconds at 50 Hz. Approximately 0.1 g of sample was weighed from each sample, and 500 μL of extraction solution (methanol:water (volume ratio) = 4:1, internal standard concentration 10 μg / mL) was added. After vortex mixing for 30 seconds, the samples were stirred at 45 Hz for 4 minutes and sonicated in an ice-water bath for 1 hour. Subsequently, the samples were allowed to rest at -40°C for 1 hour and then centrifuged at 12,000 rpm (relative centrifugal force 13,800 × g, rotor radius 8.6 cm) for 15 minutes at 4°C. The supernatant was carefully collected and filtered through a 0.22 μm microporous filter membrane. A 20 μL aliquot of each sample was mixed to form a quality control (QC) sample and stored at -80°C until analysis by ultra-performance liquid chromatography-mass spectrometry.

[0063] 2. Liquid chromatography-mass spectrometry

[0064] Liquid chromatography-tandem mass spectrometry (LC-MS / MS) analysis was performed using an ultra-high performance liquid chromatography system (Vanquish, Thermo Fisher Scientific) equipped with a Waters UPLC BEH C18 column (1.7 μm, 2.1 × 100 mm). ① Chromatographic conditions: A Waters UPLC BEH C18 column (1.7 μm x 2.1 × 100 mm) was used; the column temperature was set at 35°C; the flow rate was set at 0.4 mL / min, and the injection volume was 2 μL. The mobile phase consisted of 0.1% aqueous acid (A) and 0.1% acid (B) nitrile (B). The cleanup gradient program was: 0-3.5 min, 95-85% A; 3.5-6 min, 85-70% A; 6-6.5 min, 70% A; 6.5-12 min, 70-30% A; 12-12.5 min, 30% A; 12.5-18 min, 30-0% A; 18-25 min, 0% A; 25-26 min, 0-95% A; 26-30 min, 95% A.

[0065] Mass spectrometry conditions: MS and MS / MS data were acquired using an Orbitrap Exploris 120 mass spectrometer in information-dependent acquisition (IDA) mode, controlled by XCalibur software. The mass range for each acquisition cycle was 100 to 1500 m / z, and the first four ions in each cycle were selected for further MS / MS scanning. The mass spectrometry conditions are as follows: the specific parameters are as follows: sheath gas flow rate: 30 Arb; auxiliary air flow rate: 10 Arb; ion transfer tube temperature: 350 ° C; vaporizer temperature: 350 ° C; full scan mass spectrometry resolution: 60,000; MS / MS mass spectrometry resolution: 15,000; collision energy (Collision Energy): 16, 32 and 48 respectively in normalized collision energy (NCE) mode; spray voltage (Spray Voltage): 5.5 kV in positive ion mode and -4 kV in negative ion mode.

[0066] 3. Comparison of differential metabolites between different tissues

[0067] Based on the chemical composition of Rheum tanguticum plants, this study systematically compared secondary metabolites between adjacent and proximal tissues (roots, stems, leaves, and seeds) from bottom to top, screening for metabolites between different tissues. Specifically, the following tissue pairs were compared: roots (DdG) and stems (DdJ), roots (DdG) and leaves (DdY), roots (DdG) and seeds (DdZ), stems (DdJ) and leaves (DdY), stems (DdJ) and seeds (DdZ), and leaves (DdY) and seeds (DdZ).

[0068] 4. Statistical methods

[0069] Raw data were corrected for batch effects using LOESS or PQN normalization. Missing values ​​were addressed using internal standard normalization and random forest imputation to ensure that the relative standard deviation (RSD) of QC samples was below 30%. SD samples were treated accordingly. Differential metabolite screening was performed using a combination of multivariate analysis (PLS-DA / VIP1) and univariate analysis (T-test / FDR correction, P < 0.05). Model stability was verified using volcano plots (LOG2 FC) and replacement tests (N ≥ 200). Enrichment analysis of the identified differential metabolites was performed using MBRole 2.022, the Kyoto Encyclopedia of Genes and Genomes (KEGG), and KEGG annotations were provided for the biological effects of these metabolites. Enrichment bubble plots were generated using the ggplot2 package in R to visually display the analysis results.

[0070] 3. Results and Analysis

[0071] 1. Metabolite Analysis of Different Tissues of Rheum tanguticum

[0072] Secondary metabolomics analysis was performed on 4 Rheum tanguticum tissue samples, and a total of 1,339 secondary metabolites were identified based on non-targeted metabolomics technology. The test results showed that the main metabolite categories included 280 flavonoids, 185 terpenoids, 119 phenylpropanoids, 82 alkaloids, 81 fatty acyl compounds, 77 prenol ester compounds, 66 phenolic compounds, 36 carboxylic acids and their derivatives, 29 aromatic compounds, 25 steroids and their derivatives, 19 quinones, 18 carbonyl compounds, 16 sugar compounds and 308 other metabolites (benzopyrans, stilbenes, lactones, etc.). Figure 1As shown in the results, among the secondary metabolites of Rheum tanguticum tissues, flavonoids accounted for the highest proportion, reaching 20.88%, followed by terpenoids (16.9%) and phenylpropanoids (12.4%). Furthermore, prenol esters and alkaloids each accounted for 8.0%, fatty acyl compounds accounted for 7.6%, phenolic compounds accounted for 6.9%, and quinones accounted for a relatively low proportion, only 1.42%.

[0073] The present invention conducted principal component analysis (PCA) on 20 samples and systematically analyzed the metabolite accumulation characteristics of four tissues of Rheum tanguticum: roots (DdG), stems (DdJ), leaves (DdY) and seeds (DdZ). Figure 2 As shown in Figure 2, the first two principal components of the PCA model cumulatively explained 73.2% of the variance (PC1 = 46.9%, PC2 = 26.3%), indicating that the model has good data representation capabilities. Different geometric shapes in the score map correspond to different tissue types, and all samples are located in Hotelling's T 2 The 95% confidence interval of the ellipse (p < 0.05) indicates that the data contain no significant outliers and conform to a multivariate normal distribution. Within-group samples were tightly clustered, reflecting good consistency across biological replicates. Intergroup analysis revealed that root and stem tissue samples were completely separated within the PC1-PC2 space, while leaf and seed groups partially overlapped, indicating significant metabolic differences between roots, stems, and other tissues.

[0074] Comparative analysis of metabolite profiles revealed differences in the accumulation of major metabolites in the four tissues of Rheum tanguticum. Figure 3 As shown in the results, there are significant differences in the relative contents of phenols, quinones, aromatics, isopentanol esters, sugars, carbonyls, etc. in the roots, stems, leaves and seeds of Rheum tanguticum. Among them, quinone compounds, as the key active ingredients, have the highest accumulation in the roots, followed by seeds and leaves. In addition, the roots also show the highest relative levels of phenylpropanoids, phenols, carboxylic acids and their derivatives, aromatic compounds and carbonyl compounds. This study found that fatty acyl and alkaloid substances are preferentially accumulated in seeds. At the same time, seeds are also rich in important secondary metabolites such as flavonoids, quinones, carboxylic acids and their derivatives and terpenoids. The highest relative contents in leaves are flavonoids, terpenes, phenylpropanoids, steroids and their derivatives and sugars. In contrast, the content of most secondary metabolites in stem tissue is at the lowest level among all tissues, and only the organic acid components are slightly higher than the corresponding contents in seed tissue and root tissue. It is worth noting that the content of proanthocyanidins (especially ProcyanidinA1, A2 and B4) in seeds is significantly higher than that in other tissues ( Figure 4 ).

[0075] 2. Analysis of differential metabolite profiles in four tissues of Rheum tanguticum and its KEGG pathway enrichment analysis

[0076] To analyze the distribution characteristics of differentially accumulated metabolites (DAMs) between different tissues of Rheum tanguticum, this study used orthogonal partial least squares discriminant analysis (OPLS-DA) to analyze the differential metabolites between groups. As shown in Table 1, the OPLS-DA score plots of each tissue comparison group showed that the model parameters were excellent: Q 2 The values ​​were all >0.96, R 2 The X value is 0.62-0.76, R 2 The Y value approaches 1, indicating that the model has high predictive ability and good fit. Based on the screening criteria of variable importance projection (VIP)>1 and P<0.05, multiple groups of tissue-specific DAMs were identified. The distribution analysis of DAMs between tissues showed that the metabolic differences between stems and seeds were the most significant, with a total of 869 DAMs detected (861 upregulated and 8 downregulated in stems); in the comparison between roots and stems, there were 752 differential metabolites (83 upregulated and 669 downregulated in roots) ( Figure 5 ). The intersection analysis of the six groups of DAMs was performed using a Venn diagram ( Figure 6 ), 32 common metabolites with significant differences among all groups were screened out, suggesting that they may be involved in tissue-specific regulatory networks or serve as potential biomarkers.

[0077] Table 1 OPLS-DA scores of different tissues of Rheum tanguticum

[0078] Group <![CDATA[R 2 X(how)]]> <![CDATA[R 2 Y(cum)]]> <![CDATA[Q 2 (how)]]> Root v Leaf (DdG-DdY) 0.692 0.996 0.98 Leaf v Seed (DdY-DdZ) 0.674 0.999 0.973 Stem v Seed (DdJ-DdZ) 0.714 1.000 0.983 Stem v leaf (DdJ-DdY) 0.76 0.995 0.962 Root v Seed (DdG-DdZ) 0.625 1.000 0.986 Root v stem (DdG-DdJ) 0.681 1.000 0.981

[0079] Note: R 2 X represents the cumulative explanation rate of the model in the x-axis direction, R 2 Y represents the cumulative explanation rate of the model in the y-axis direction, Q 2 Represents the cumulative prediction rate of the model.

[0080] The metabolic pathways of differentially accumulated metabolites (DAMs) were further identified through KEGG pathway enrichment analysis, and the differential abundance (DA) score was calculated to reflect the overall fluctuation of all metabolites in the pathway ( Figures 7 to 12 In all comparison groups of DAMS, at least one KEGG pathway was enriched in the flavonoid biosynthesis pathway. Figure 8 As shown in Figure 2, the significant DAMs in roots and leaves were mainly involved in betalain biosynthesis and tyrosine metabolism. Similarly, DAMs in roots and seeds were mainly enriched in α-linolenic acid metabolism, unsaturated fatty acid biosynthesis, cutin, suberin and wax biosynthesis, and β-alanine metabolism ( Figure 9The significant DAMs between leaves and seeds are mainly involved in alanine, aspartate and glutamate metabolism, tryptophan metabolism, arginine biosynthesis, pantothenic acid and coenzyme A biosynthesis, and nucleotide metabolism ( Figure 12 ).

[0081] The present invention uses non-targeted metabolomics technology to conduct a systematic metabolome analysis of four tissues: roots, stems, leaves, and seeds of 5-year-old Rheum tanguticum plants, and a total of 1,339 secondary metabolites were identified. Root tissue, a traditional medicinal part, has significantly higher accumulation of quinones (especially anthraquinones), phenylpropanoids, phenols, carboxylic acids and their derivatives, aromatic compounds, and carbonyl compounds than other tissues. Seed tissue exhibits unique metabolic characteristics, enriched not only in proanthocyanidins but also in high levels of fatty acyl and alkaloid components. Proanthocyanidins, as potent antioxidants, may be associated with an adaptive protection mechanism under the strong ultraviolet radiation environment of the Qinghai-Tibet Plateau, providing a new chemical basis for the development and utilization of seed resources. The high content of malic acid in stem tissue reveals its potential as a source of flavor substances, suggesting the application prospects of stems in the development of functional foods. Flavonoids are significantly enriched in leaves, which is closely related to the long-term exposure of leaves to the strong ultraviolet radiation and pathogenic microbial environment of the Qinghai-Tibet Plateau. Flavonoids, key secondary metabolites that plants use to cope with environmental stress, possess antioxidant and anti-inflammatory properties that not only provide a defense mechanism for plants but also offer a potential resource for the development of functional foods and pharmaceuticals. These findings suggest that the non-medicinal parts of Rheum tanguticum (such as leaves and seeds) have underutilized economic value. Their comprehensive utilization could reduce resource waste and align with the concept of sustainable development.

[0082] Metabolic pathway enrichment analysis is an important method for revealing the tissue-specific distribution patterns and regulatory mechanisms of plant secondary metabolites. Based on KEGG pathway enrichment analysis, this study conducted in-depth analysis of non-targeted metabolomics data from four tissues of Rheum tanguticum: roots, stems, leaves, and seeds. The results showed that flavonoids, which are closely related to the tissue-specific expression of key enzymes in the phenylpropanoid metabolic pathway, showed significant accumulation in the leaves. As the rate-limiting enzymes in this pathway, phenylalanine ammonia lyase (PAL) and 4-coumarate-CoA ligase (4CL) play a core regulatory role in the phenylpropanoid metabolic pathway. The phenylpropanoid metabolic pathway is one of the important core pathways of plant secondary metabolism, and its expression level directly affects the efficiency of flavonoid synthesis. This phenomenon may be related to the fact that leaves, as the main organs of photosynthesis, need to cope with the environmental pressures of strong ultraviolet radiation and pathogenic microorganisms on the Qinghai-Tibet Plateau. In the root-stem / leaf comparison, α-linolenic acid metabolism (ko00592) and unsaturated fatty acid biosynthesis pathway (ko01040) were significantly enriched. α-linolenic acid (18:3n-3) is a precursor to the ω-3 polyunsaturated fatty acids. Its derivatives, such as jasmonic acid, can regulate secondary metabolism by activating the MYB transcription factor. Notably, membrane lipid unsaturation can indirectly promote the synthesis of medicinal compounds such as anthraquinones by affecting the activity of P450 enzymes (such as CYP84A1). These findings provide new insights into the metabolic basis for the "authenticity" of rhubarb.

[0083] This study, through systematic metabolomics analysis, elucidates for the first time the metabolic characteristics and regulatory mechanisms of different tissues of Rheum tanguticum at the metabolic network level. This study not only confirms that the traditional medicinal part (root) is rich in pharmacologically active secondary metabolites, but more importantly, reveals that the aboveground parts (stems, leaves, and seeds), which account for over 50% of the plant's biomass, contain numerous high-value metabolites. Of particular note are flavonoids in the leaves and polyphenols in the seeds. These findings provide a scientific basis for the comprehensive development of Rheum tanguticum resources. Based on metabolomics data, this study proposes a gradient development model: "root medicinal use - seed antioxidant - stem food processing - leaf daily chemical raw material." This strategy can alleviate resource pressure on traditional medicinal parts while significantly improving overall resource utilization, in line with the goal of sustainable utilization of endangered medicinal plants. Future research should combine multi-omics technologies to further dissect the regulatory networks of key metabolic pathways and validate the pharmacological activity of key metabolites through in vitro activity assays. This will promote the transformation of Rheum tanguticum from a traditional medicinal plant into high-value-added functional products and promote the industrialization of high-altitude biopharmaceuticals.

[0084] This study demonstrates that the present invention uses non-targeted metabolomics technology to systematically analyze metabolite composition differences across Rheum tanguticum tissues and screen for tissue-specific marker metabolites. This study reveals the tissue distribution patterns of secondary metabolites at the metabolomic level, providing a scientific basis for drug site selection, non-drug tissue utilization, and molecular breeding.

[0085] Although the above embodiment provides a detailed description of the present invention, it is only a part of the embodiments of the present invention, not all of the embodiments. People can also obtain other embodiments based on this embodiment without creativity, and these embodiments all fall within the scope of protection of the present invention.

Claims

1. A method for detecting tissue-specific metabolites of Rheum tanguticum, characterized in that: The following steps are involved: The roots, stems, leaves and seeds of Rheum tanguticum were ground to obtain powder samples of each tissue; After mixing the powder sample with the extracting solution, the extraction is performed using an ultrasound-assisted method, and the obtained extract is allowed to stand, centrifuged, and filtered to obtain a supernatant; The supernatant was subjected to liquid chromatography-tandem mass spectrometry analysis. After data collection, differential metabolites were screened by combining multivariate statistics and metabolic pathway enrichment analysis.

2. The detection method according to claim 1, wherein The Tangut rhubarb includes Tangut rhubarb of the same growth cycle, and the same growth cycle includes five years.

3. The detection method according to claim 1, wherein The extracting solution is methanol and water, the volume ratio of the methanol to water is 4:1, and the mass volume ratio of the powder sample to the extracting solution is 0.1-0.2 g:500 μL.

4. The detection method according to claim 1, wherein The frequency of the ultrasonic assistance is 40 to 50 Hz, and the time of the ultrasonic assistance is 50 to 70 minutes.

5. The detection method according to claim 1, wherein The standing time is 50 to 70 minutes, the standing temperature is -40°C, the centrifugal speed is 12000 rpm, and the centrifugal time is 10 to 20 minutes.

6. The detection method according to claim 1, characterized in that The chromatographic conditions in the liquid chromatography-tandem mass spectrometry analysis are as follows: a Waters UPLC BEHC18 column is selected as the chromatographic column, the column temperature is 35° C., the flow rate is 0.4 mL / min, and the injection volume is 2 μL; the mobile phase consists of 0.1% A acid aqueous solution and 0.1% A acid B nitrile solution.

7. The detection method according to claim 1, characterized in that The cleanup gradient program in the liquid chromatography-tandem mass spectrometry analysis is: 0-3.5 min, 95-85% A; 3.5-6 min, 85-70% A; 6-6.5 min, 70% A; 6.5-12 min, 70-30% A; 12-12.5 min, 30% A; 12.5-18 min, 30-0% A; 18-25 min, 0% A; 25-26 min, 0-95% A; 26-30 min, 95% A.

8. The detection method according to claim 1, wherein The mass spectrometry conditions in the liquid chromatography-tandem mass spectrometry analysis are as follows: the mass spectrometry analysis uses an Orbitrap Exploris 120 mass spectrometer, and MS and MS / MS data are obtained under the control of XCalibur software in information-dependent acquisition mode; the mass range of each acquisition cycle is 100-1500 m / z, and the first four ions in each cycle are selected for further MS / MS scanning.

9. The detection method according to claim 1, wherein The specific parameters of the mass spectrometry in the liquid chromatography-tandem mass spectrometry analysis are as follows: sheath gas flow rate: 30 Arb; auxiliary air flow rate: 10 Arb; ion transfer tube temperature: 350°C; evaporator temperature: 350°C; full scan mass spectrometry resolution: 60,000; MS / MS mass spectrometry resolution: 15,000; collision energy: 16, 32, and 48, respectively, in normalized collision energy mode; spray voltage: 5.5 kV in positive ion mode and -4 kV in negative ion mode.

10. A comprehensive development and utilization method of Tangut rhubarb, characterized in that: Includes any one or more of the following: (a) The roots are used to prepare anthraquinone medicinal preparations; (b) Extraction of proanthocyanidins from seeds for use in antioxidant products; (c) Processing of the stems as flavor food additives; (d) Flavonoids extracted from leaves are used as daily chemical raw materials.

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