Anthocyanin non-target metabonomics detection method based on LC-HRMS

Abstract

The invention discloses an anthocyanin non-target metabonomics detection method based on LC-HRMS (Liquid Chromatography-High Resolution Mass Spectrometry), which comprises the following steps: respectively extracting effective components from samples, and detecting by adopting an ultra-high performance liquid chromatography-mass spectrometry combined method after extraction, the obtained original data is detected, the established anthocyanin database is used for screening, difference analysis is completed, and P value is screened out; 0.05 and VIPgt; 1 is taken as an anthocyanin differential metabolite. Based on a non-targeted metabonomics method, 34 anthocyanidin substances are identified by UPLC-MSMS, then the anthocyanidin differential metabolites are obtained by an OPLS-DA method, and an important basis can be provided for a molecular mechanism of anthocyanidin formation.

Description

Technical Field

[0001] This invention relates to the field of analytical chemistry, and in particular to a non-targeted metabolomics detection method for anthocyanin compounds based on UPLC-MSMS. Background Technology

[0002] Anthocyanins are a class of water-soluble plant pigments belonging to the polyphenol subclass of flavonoids. They are the main reason why plants exhibit vibrant colors such as red, purple, and blue. The core structure of anthocyanins is called anthocyanidin, or a glycoside. The most common anthocyanins in nature include cyanidin (Cy), delphinidin (Dp), peonidin (Pn), petunidin (Pt), pelargonidin (Pg), and malvidin (Mv). In nature, anthocyanins rarely exist in free form; the vast majority exist as glycosides, i.e., anthocyanins. The types of glycosyl groups that bind to anthocyanins are diverse, commonly including monosaccharides such as glucose, galactose, and arabinose, as well as disaccharides such as rutinose and sophorose. The location and number of glycosyl linkages, as well as further acylation modifications on the glycosyl groups, greatly increase the structural diversity of anthocyanins. It has been reported that over 600 different anthocyanins have been discovered in nature. This enormous structural diversity, along with the large number of isomers, poses a significant challenge to achieving comprehensive analytical characterization.

[0003] Despite their significant applications, anthocyanins' main drawback is their chemical instability. The stability and color of anthocyanins are influenced by various factors, including pH, temperature, light, oxygen, metal ions, enzymes, and their own structure. This instability places stringent demands on analytical methods. First, sample pretreatment processes, including extraction and purification, must be performed under conditions that minimize degradation. Second, chromatographic separation needs to be as rapid as possible to reduce the residence time of compounds in the column and mobile phase, thereby reducing the risk of online degradation. This makes rapid separation techniques such as UPLC-MS / MS more advantageous than traditional analytical methods.

[0004] Although existing LC-MS methods have made great progress in anthocyanin analysis, some limitations still exist, which constitute the technical problem that this invention aims to solve: 1. Most existing methods are essentially targeted or semi-targeted, primarily focusing on known, high-abundance anthocyanins. These methods may miss unknown, novel, or trace anthocyanin derivatives that may be present in the sample. Truly validated, non-targeted screening (NTS) workflows specifically for anthocyanins are relatively lacking.

[0005] 2. Sample pretreatment steps are cumbersome and time-consuming, and may introduce analytical errors or cause unstable anthocyanins to degrade. Meanwhile, the large amount of raw data generated by non-targeted screening requires sophisticated bioinformatics tools and specialized knowledge for processing and analysis.

[0006] 3. Differentiating structurally similar isomers (such as isomers of glycosides, acyl position isomers, anthocyanins and flavonol glycosides, etc.) remains a challenge in LC-MS / MS analysis. Standard LC-MS / MS methods may not provide sufficient information to definitively distinguish all isomers, requiring more refined chromatographic separation optimization, high-resolution mass spectrometry, and specific fragmentation experiments (such as multistage mass spectrometry). n (or in combination with other technologies.)

[0007] In summary, existing technologies still fall short in providing comprehensive and accurate analysis of anthocyanins in complex samples. In particular, there is a lack of an integrated and efficient UPLC-MS / MS method capable of comprehensive non-targeted screening of anthocyanins (covering both known and unknown compounds). This technological gap is precisely the problem this invention aims to solve: providing a more advanced and comprehensive method for anthocyanin analysis. Summary of the Invention

[0008] This invention provides a novel and improved method for non-targeted screening of anthocyanin compounds in complex samples (especially plant-derived samples such as fruits, vegetables, extracts, foods and beverages) based on ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS / MS).

[0009] The method of the present invention overcomes the limitations of the prior art, and its key steps include: S1: Establish a database of anthocyanin compounds, including their primary and secondary precise mass-to-charge ratios, collision energies, and other information; S2: Extract the effective components from the obtained samples and analyze the extracts by high performance liquid chromatography-high resolution mass spectrometry. S3: The raw data obtained were analyzed using Progenesis QI software. Anthocyanin metabolites were screened based on the theoretical mass-to-charge ratio and secondary fragments, and the matching scores were combined with the analysis.

[0010] Furthermore, the method utilizes non-targeted metabolomics to establish a database containing 101 anthocyanin compounds, thereby enabling non-targeted screening of anthocyanin compounds in complex matrices.

[0011] Furthermore, the anthocyanin compounds in the database are shown in Table 1: Table 1: Further, the specific steps for extracting the effective components of the method are as follows: Weigh 50-100 mg of the sample after quick-freezing and grinding in liquid nitrogen into a 2 ml centrifuge tube, add 1 ml of 5% formic acid aqueous solution, vortex for 30 s, and extract on ice for 20 min. Then, centrifuge at 10000 rpm for 5 min in a 4℃ low-temperature centrifuge and transfer the supernatant. Add 1 ml of 5% formic acid to the precipitate and repeat the extraction step 2-3 times until the sample precipitate is nearly colorless. Combine the supernatants, centrifuge at 12000 rpm for 10 min in a 4℃ low-temperature centrifuge, transfer the supernatant, and enrich and purify it using an HLB (60 mg) solid-phase extraction column.

[0012] The specific steps of SPE are as follows: Activate the HLB column by adding 1 ml of methanol and water, and add all the sample supernatant to the activated column. Add 1 ml of water to rinse the column, replace with a new 15 ml centrifuge tube, add 1 ml of methanol (containing 5% formic acid) for elution, and collect the eluent. Remove the water from the collected liquid by nitrogen blowing and freeze drying. Then, add 0.2 ml of 50% methanol (containing 5% formic acid) to reconstitute the sample, centrifuge at 12000 rpm for 10 min at 4℃, transfer the supernatant to a 1.5 ml glass bottle, and wait for processing.

[0013] Furthermore, the chromatographic analysis conditions for the method are as follows: The liquid phase was produced using the Thermo Vanquish ultra-high efficiency liquid chromatography system. The chromatographic column was a Waters HSS T3 (100×2.1 mm, 1.8 μm), the flow rate was 0.3 mL / min, and the column temperature was 45℃. Mobile phase A is water containing 0.1% formic acid, and mobile phase B is acetonitrile containing 0.1% formic acid; The gradient elution conditions were: 0-4 min, 30% B; 4-22 min, 30% B-100% B; 22-22.1 min, 100% B-30% B; 22.1-26 min, 30% B. Furthermore, the mass spectrometry analysis conditions for the method are as follows: A Thermo Q Eactive HFX high-resolution mass spectrometer was used with a HESI source and positive ion mode. In positive ion mode, the spray voltage was 3.0 kV, the sheath gas was 60 kV, the auxiliary gas was 20 kV, and the ion transfer tube temperature was 285 °C. A first-stage full scan was performed at a resolution of 60,000 ions, with the primary precursor ion scan range being 80-1200 ions. Second-stage fragmentation was performed using an HCD collision cell with collision energies of 20 / 40 / 60 kV and a second-stage resolution of 15,000 ions. The first 10 ions acquired were fragmented, and dynamic exclusion was used to remove duplicate MS / MS data.

[0014] Collision Energy Optimization: For both DIA and DDA, setting the collision energy is crucial for obtaining meaningful MS / MS spectra. By experimentally performing direct injection analysis on representative anthocyanin standards, the optimal collision energy range was determined to obtain as much structural information as possible.

[0015] The method of the present invention has significant advantages over the prior art, including: An optimized extraction and purification procedure was employed to efficiently extract the widest possible range of anthocyanins (including derivatives of different polarities and degrees of glycosylation and acylation). Simultaneously, controlled conditions (using acidified solvents, low temperature, light protection, and rapid processing) were used to minimize degradation loss of target analytes during processing and effectively remove interfering matrix components. Based on this, a non-targeted screening strategy was employed to detect and identify a wider variety of unknown, trace anthocyanin metabolites and their derivatives. Combined with HRMS, dual-ion model data, and advanced annotation strategies, anthocyanin metabolites could be identified more reliably, and isomers and interfering substances could be effectively distinguished.

[0016] Therefore, this invention provides a powerful analytical tool that can more comprehensively and accurately resolve anthocyanin metabolites in complex samples, solving key problems in coverage, quantitative accuracy, and structural analysis of existing technologies. It has broad application prospects in food science, nutrition, plant science, drug development, and quality control. Attached Figure Description

[0017] Figure 1 This is an overall flowchart of the method of the present invention.

[0018] Figure 2 This is a heatmap of differential metabolite clustering according to the present invention.

[0019] Figure 3 This is a volcano diagram of differential metabolites from the present invention.

[0020] Figure 4A metabolic pathway annotation diagram for the differential metabolites of this invention; Figure 5 This is the total ion current (TIC) chromatogram of the anthocyanin sample of the present invention. Detailed Implementation

[0021] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0022] The method of this invention is applicable to a variety of complex matrix samples, including but not limited to: fruits (such as blueberries, blackberries, strawberries, grapes, cherries), vegetables (such as purple sweet potatoes, red cabbage, purple corn), plant extracts, fruit juices, wines, functional foods, and nutritional supplements. Each step of the process has been carefully designed and optimized to address the unique challenges in anthocyanin analysis, such as the diversity and instability of compounds, the presence of isomers, and the requirements for quantitative accuracy.

[0023] like Figures 1 to 5 As shown: A non-targeted metabolomics detection method for anthocyanin compounds based on UPLC-MSMS includes the following steps: S1: Sample collection and preparation: Representative samples were taken according to the sample type (e.g., fruits, vegetables, plant tissues, extracts, food, beverages, etc.) and subjected to necessary preliminary processing, such as washing, pitting, cutting, freeze-drying, or homogenization. Ten fruits of uniform maturity were selected for each sample. First, the peel was washed with distilled water and dried with paper towels. Peel from the top, middle, and bottom sections of each fruit without spots or lesions was taken, chopped, mixed, and flash-frozen in liquid nitrogen for 1 minute. After taking the peel, the fruit was cut open from the middle, and the top, middle, and bottom sections of the pulp were taken, chopped, mixed, and flash-frozen in liquid nitrogen for 1 minute. Finally, the samples were placed in an ultra-low temperature freezer at -80℃. S2: Extraction of effective components from the sample: Weigh 50-100 mg of the sample, after quick-freezing and grinding in liquid nitrogen, into a 2 ml centrifuge tube. Add 1 ml of 5% formic acid aqueous solution, vortex for 30 seconds, and extract on ice for 20 minutes. Then, centrifuge at 10,000 rpm for 5 minutes at 4°C and collect the supernatant. Add 1 ml of 5% formic acid to the precipitate and repeat the extraction step 2-3 times until the sample precipitate is nearly colorless. Combine the supernatants and centrifuge at 12,000 rpm for 10 minutes at 4°C. Collect the supernatant and enrich and purify it using an HLB (60 mg) solid-phase extraction column. Remove the water from the collected liquid by nitrogen blowing and freeze-drying. Then, add 0.2 ml of 50% methanol (containing 5% formic acid) to reconstitute the sample, centrifuge at 12,000 rpm for 10 minutes at 4°C, and collect the supernatant in a 1.5 ml glass bottle, ready for instrumentation. The treatment process should be carried out under low temperature (such as ice bath) and light-protected conditions as much as possible to reduce anthocyanin degradation.

[0024] S3: UPLC-MS / MS Analysis: Chromatographic conditions The liquid chromatography was performed using a Thermo Vanquish (Thermo Fisher Scientific, USA) ultra-high performance liquid chromatography system with a Waters HSS T3 (100×2.1 mm, 1.8 μm) column at 45 °C in positive ion mode. Mobile phase A was an aqueous solution containing 0.1% formic acid by volume, and mobile phase B was acetonitrile containing 0.1% formic acid. The flow rate was 0.3 mL / min, and the injection volume was 2 μL. The gradient elution conditions were: 0-4 min, 30% B; 4-22 min, 30% B-100% B; 22-22.1 min, 100% B + 30% B; 22.1-26 min, 30% B.

[0025] Mass spectrometry conditions A Thermo Q Eactive HFX high-resolution mass spectrometer (Thermo Fisher Scientific, USA) was used with an HESI source and positive ion mode. In positive ion mode, the spray voltage was 3.0 kV, the sheath gas was 60 kV, the auxiliary gas was 20 kV, and the ion transfer tube temperature was 285 °C. A first-stage full scan was performed at a resolution of 60,000 ions, with the first-stage precursor ion scan range being 80–1200 ions. Second-stage fragmentation was performed using an HCD collision cell with collision energies of 20 / 40 / 60 kV and a second-stage resolution of 15,000 ions. The first 10 ions acquired were fragmented, and dynamic exclusion was used to remove duplicate MS / MS data.

[0026] S4: Non-targeted screening data processing and analysis Composition of anthocyanins Processing the acquired complex UPLC-HRMS ( / MS) data to detect, align, and annotate anthocyanin compounds is a crucial step in this method. The raw data was processed using Progenesis QI software, including feature detection, peak alignment, deconvolution, and compound annotation (based on precise mass-to-charge ratio, retention time, MS / MS fragment spectra, database comparison, and structure inference). Peaks containing secondary mass spectrometry data were identified using a self-built anthocyanin metabolite secondary mass spectrometry database from Sanshu Biotechnology and corresponding fragmentation patterns. The matching of secondary mass spectrometry (MS2) is mainly reflected in the secondary fragment score, which has a total score of 1. A higher score indicates a more reliable identification result; generally, a score greater than 0.7 is considered relatively reliable. Compound identification is a complex process aimed at determining the chemical identity of each detected feature as accurately as possible. The confidence grading standard proposed by Schymanski et al. is typically used as a reference. Level 5 (Precise Quality Match): Only precise quality information is available; Level 4 (Molecular Formula Confirmation): Based on the exact mass number (HRMS) and isotopic distribution pattern, the possible elemental composition (molecular formula) is deduced. Level 3 (Candidate Structure Category): Preliminary classification based on the characteristic properties of anthocyanins; Level 2 (Database Matching): The MS / MS fragment spectrograms obtained from the experiment are compared with self-built databases and commercial databases. Commonly used databases include MassBank, mzCloud, and Metlin. Matching algorithms and thresholds (such as similarity scores, fragment matching scores, etc.) are set according to actual needs. Level 1 (Structure Confirmation): The structure is definitively confirmed by rigorously comparing the sample's RT and MS / MS spectra with pure standards analyzed under the same conditions. For many compounds in non-targeted screenings, Level 1 confirmation is often difficult to achieve due to the lack of standards.

[0027] A total of 34 anthocyanin metabolites were identified in the samples through non-targeted metabolomics analysis, as shown in Table 2: Table 2: Screening of anthocyanin differential metabolites Based on the identified anthocyanin metabolites, differential analysis was performed using the t-test combined with multivariate analysis (OPLS-DA). The selection criteria were: P-value < 0.05 and VIP > 1. Table 3 shows the specific types of differentially expressed metabolites and their Pubchem database numbers. The corresponding data results for heatmaps, volcano plots, and metabolic pathway diagrams are as follows: Figure 2-4 As shown.

[0028] Table 3: In summary, this invention discloses a novel non-targeted screening method for anthocyanin compounds in complex samples based on UPLC-MS / MS technology. This method effectively overcomes the limitations of existing technologies in terms of analytical coverage, quantitative accuracy, structural resolution reliability, and analytical efficiency by optimizing and integrating sample pretreatment, high-performance liquid chromatography separation, high-resolution mass spectrometry, and advanced data processing and quantification strategies. This method can more comprehensively and accurately identify and evaluate the anthocyanin spectrum in samples, including both known and unknown compounds, providing a powerful analytical tool for research and applications in food science, nutrition and health, plant science, and biomedicine.

[0029] The above description is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention fall within the protection and disclosure scope of the present invention.

Claims

1. A non-target metabolomics detection method for anthocyanins based on LC-HRMS, characterized in that, The steps of the method include: S1: Establish a database of anthocyanin compounds, including their primary and secondary accurate mass-to-charge ratios and collision energy information; S2: Extract the effective components from the obtained samples and analyze the extracts by high performance liquid chromatography-high resolution mass spectrometry. S3: The raw data obtained were analyzed using Progenesis QI. Anthocyanin metabolites were screened based on the theoretical mass-to-charge ratio and secondary fragments, and the matching scores were combined with the analysis. S4: The OPLS-DA method was used to perform differential anthocyanin analysis, and variables with P<0.05 and VIP>1.0 were selected as differential anthocyanin metabolites.

2. The method for detecting anthocyanins using LC-HRMS based on non-target metabolomics according to claim 1, characterized in that: A database containing 101 anthocyanin compounds was established, including their primary and secondary accurate mass-to-charge ratios and collision energies.

3. The non-target metabolomics detection method for anthocyanins based on LC-HRMS according to claim 1, characterized in that: The obtained samples were subjected to extraction of active ingredients, and the extracts were analyzed by high performance liquid chromatography-high resolution mass spectrometry. The raw data were analyzed using Progenesis QI, and 34 anthocyanin metabolites were identified based on the theoretical mass-to-charge ratio and secondary fragments, combined with the matching scores.

4. The non-target metabolomics detection method for anthocyanins based on LC-HRMS according to claim 1, characterized in that: The specific pretreatment method for extracting the effective components from the samples obtained in step S2 is as follows: Weigh 50-100 mg of the sample after quick-freezing and grinding in liquid nitrogen into a 2 ml centrifuge tube, add 1 ml of 5% formic acid aqueous solution, vortex for 30 s, and extract on ice for 20 min; then centrifuge at 10000 rpm for 5 min in a centrifuge at 4℃, and transfer the supernatant; add 1 ml of 5% formic acid to the precipitate, and repeat the extraction step 2-3 times until the sample precipitate is colorless; combine the supernatants, centrifuge at 12000 rpm for 10 min in a centrifuge at 4℃, transfer the supernatant, and enrich and purify it using an HLB 60 mg solid phase extraction column.

5. The non-target metabolomics detection method for anthocyanins based on LC-HRMS according to claim 1, characterized in that: The chromatographic analysis conditions for extracting the effective components from the samples obtained in step S2 are as follows: The liquid phase was achieved using the ThermoVanquish ultra-high efficiency liquid chromatography system. The chromatographic column was a Waters HSS T3, 100×2.1 mm, 1.8 μm, with a flow rate of 0.3 mL / min and a column temperature of 45℃; Mobile phase A is water containing 0.1% formic acid, and mobile phase B is acetonitrile containing 0.1% formic acid; The gradient elution conditions were: 0-4 min, 30% mobile phase B; 4-22 min, 30% mobile phase B-100% mobile phase B; 22-22.1 min, 100% mobile phase B-30% mobile phase B; 22.1-26 min, 30% mobile phase B.

6. The non-target metabolomics detection method for anthocyanins based on LC-HRMS according to claim 1, characterized in that: The mass spectrometry analysis conditions for extracting the effective components from the samples obtained in step S2 are as follows: a Thermo QEactive HFX high-resolution mass spectrometer is used, with an HESI ion source and positive ion mode. In positive mode, the spray voltage is 3.0 kV, the sheath gas is 60 kV, the auxiliary gas is 20 kV, the ion transfer tube temperature is 285 °C, and a first-stage full scan is performed at a resolution of 60,000 kΩ, with the first-stage precursor ion scan range being 80-1200 kΩ. Second-stage fragmentation is performed using an HCD collision cell with collision energies of 20 / 40 / 60 kΩ and a second-stage resolution of 15,000 kΩ. The first 10 ions acquired are fragmented, and dynamic exclusion is used to remove duplicate MS / MS information.

7. An application of LC-HRMS-based non-targeted screening of anthocyanin metabolites.

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