Method for Measuring the Content of COX-2 Metabolites in the Arachidonic Acid Metabolic Pathway in an Inflammatory Model

Abstract

The present invention relates to a method for determining the content of COX-2 metabolites in the arachidonic acid metabolic pathway in an inflammation model, comprising the following steps: (1) Pretreating the sample: Pretreating the cell supernatant sample and / or serum sample, and adding an internal standard working solution during the pretreatment process, wherein the internal standard working solution is a PGA2-D4 solution; (2) Detecting the pretreated sample using an Agilent 6495 triple quadrupole mass spectrometer. The method provided by the present invention can simultaneously detect the content of 11 metabolites in the AA metabolic pathway, and has the advantages of rapidity, high sensitivity, good stability, etc.

Description

Technical Field

[0001] The present invention belongs to the technical field of detection, and particularly relates to a method for determining the content of COX-2 metabolites in the arachidonic acid metabolic pathway in an inflammation model. Background Art

[0002] Arachidonic acid (AA) is an ω-6 polyunsaturated fatty acid and is the most widely distributed endogenous active substance in the body, playing an important role in maintaining the structure and function of the body's cell membranes. AA is not only an essential phospholipid in various tissues and organs of the body, but also an important precursor for the synthesis of prostaglandins (PGs) in the human body. In the AA metabolic network, AA generates a series of metabolites such as prostaglandins (PGs), thromboxanes (TXs), leukotrienes (LTs), or hydroxy fatty acids through three metabolic pathways of cyclooxygenases (COXs), lipoxygenase (LOXs), and cytochrome P450 (CYP450) enzymes respectively, triggering different inflammatory responses. Prostaglandins include prostaglandin F 2β (PGF 2β ), prostaglandin E2 (PGE2), prostaglandin E1 (PGE1), prostaglandin D1 (PGD1), prostaglandin D2 (PGD2), prostaglandin A1 (PGA1), prostaglandin A2 (PGA2), prostaglandin J2 (PGJ2), prostaglandin B2 (PGB2), etc. Thromboxanes include thromboxane B1 (TXB1), thromboxane B2 (TXB2), etc. These AA metabolites are collectively referred to as eicosanoids, which are effective autocrine and paracrine bioactive mediators, important inflammatory factors in the body, participating in the body's immune and inflammatory response processes, and playing an important role in the pathophysiological processes of many diseases. Inflammation is an important pathological basis of arthritis and is a process closely related to the occurrence of arthritis. Taking PGE2 as an example, PGE2 has the strongest effect in promoting bone resorption among prostaglandin-like substances. There are PGE2 receptors in the arthritis tissue, which bind to PGE2 to play a role. The histopathology of joint tissues in animals with PGE2 receptors reveals cartilage degeneration and proteoglycan loss, resulting in the destruction of type II collagen. Therefore, it plays an important role in the pathological mechanism of arthritis.

[0003] Based on the COX metabolic pathway, which has two subtypes, COX-1 and COX-2, COX-1 is used for basic prostaglandin synthesis and belongs to constitutive enzymes; COX-2 plays an important role in many inflammations, is produced upon stimulation, and belongs to inducible enzymes. The arachidonic acid (AA) metabolic pathway plays an important role in the inflammatory response. However, the overall metabolic profile of AA in the inflammatory model remains elusive.

[0004] Currently, the detection of the content of inflammatory factors in the AA metabolic pathway still uses techniques such as enzyme-linked immunosorbent assay, flow cytometry, and Western blot for single-index detection, which have problems such as instability of different batches of samples, high detection costs, and high requirements for technical personnel. Pang et al. established a method for quantitatively analyzing PGE2 and LTB4 in spinal cord tissues at 4 h, 24 h, and 48 h after spinal cord contusion in rats (Reference: Pang Y, Liu X, Zhao C, et al. LC-MS / MS-based arachidonic acid metabolomics in acute spinal cord injury reveals the upregulation of 5-LOX and COX-2 products. Free Radic Biol Med. 2022; 193(Pt1): 363-372.). Lin et al. established an LC-MS method for determining the content of leukotriene B4 in human plasma samples (Reference: LIN W, HUANG MQ, XUE X, et al. A highly sensitive and selective method for the determination of leukotriene B4 (LTB4) in ex vivo stimulated human plasma by ultra fast liquid chromatography tandem mass spectrometry [J]. J Chromatogr B Analyt Technol Biomed Life Sci, 2013, 925: 54.). Existing methods can only detect 1-2 AA metabolites, but the detection of 1-2 AA metabolites cannot clearly understand the overall metabolism of AA in the inflammatory model. Summary of the Invention

[0005] In view of the problems existing in the prior art, the present invention provides a method for determining the content of COX-2 metabolites in the arachidonic acid metabolic pathway in an inflammation model. The method provided by the present invention can simultaneously detect the contents of 11 metabolites in the AA metabolic pathway, and has the advantages of rapidity, high sensitivity, good stability, etc.

[0006] The technical solution of the present invention to solve the above technical problems is as follows:

[0007] The present invention provides a method for determining the content of COX-2 metabolites in the arachidonic acid metabolic pathway in an inflammation model, comprising the following steps:

[0008] (1) Pretreatment of the sample: Pretreat the cell supernatant sample and / or serum sample, and add an internal standard working solution during the pretreatment process. The internal standard working solution is a solution of the internal standard PGA2-D4.

[0009] (2) Detect the treated sample using an Agilent 6495 triple quadrupole mass spectrometer.

[0010] The beneficial effects of adopting the above solution include: The method provided by the present invention can determine the qualitative and quantitative analysis of components such as AA metabolites and their structural analogs, and expands the application of LC-MS in detecting inflammatory factors such as PGE2. The present invention establishes a detection method for 11 metabolites with rapidity, high sensitivity, and good stability through the UHPLC-QQQ-MS / MS method, realizing a large number of samples, a large amount of information, and a small requirement for the amount of a single sample.

[0011] Further, in step (2), the detection conditions include: chromatographic separation is carried out on a Waters Acquity UPLC C18 column; the mobile phase is 0.1% formic acid A and acetonitrile B, with gradient elution: 40% B for 0 - 3 minutes, 40% - 80% B for 3 - 8 minutes, 40% B for 8.01 - 10 minutes; inject an equal amount of 5 μL, the FLOW rate is 300 μL / min; use MRM and ESI source to detect metabolites in the negative ion mode; the drying gas flow rate is 11.0 L / min, the drying gas temperature is 300 °C, the nebulizer is 15 psig, and the capillary voltage is 4000 V.

[0012] Further, in step (1), the method for pretreating the cell supernatant sample includes the following steps: Take 200 μL of the supernatant, add 50 μL of the internal standard working solution, add 800 μL of acetonitrile, vortex for 3 min; centrifuge at 4 °C and 14000 rpm for 10 min, and take the supernatant; vacuum concentrate; add 100 μL of chromatographic methanol to redissolve, let stand and then ultrasonicate, vortex for 3 min; centrifuge at 4 °C and 14000 rpm for 10 min, and take the supernatant.

[0013] Further, the cell supernatant is the supernatant of an LPS-induced RAW264.7 cell inflammation model.

[0014] Further, in step (1), the method for preprocessing the serum sample includes the following steps: Take 200 μL of serum, add 50 μL of internal standard working solution, then add 800 μL of acetonitrile, and vortex for 3 min; centrifuge at 14,000 rpm at 4 °C for 10 min, and take the supernatant; vacuum concentrate; add 100 μL of chromatographic methanol to redissolve, let stand and then ultrasonicate, and vortex for 3 min; centrifuge at 14,000 rpm at 4 °C for 10 min, and take the supernatant.

[0015] Further, the serum sample is a serum sample of an adjuvant-induced arthritis (AIA) model or a type II collagen-induced arthritis (CIA) model.

[0016] The beneficial effects of adopting the above scheme include: The present invention uses high-performance liquid chromatography tandem mass spectrometry (LC-MS method) to simultaneously perform rapid quantitative analysis on 11 AA metabolite contents in cell supernatants and animal sera, and has the advantages of rapidity, high efficiency, high sensitivity, good stability, large amount of information, and small requirement for a single sample. This method is a suitable method for determining the content of COX-2 metabolites in the construction of various different inflammation models.

[0017] Further, in step (2), the content of the metabolite is calculated according to the detected peak area and the standard curve formula.

[0018] When detecting the cell supernatant sample, the standard curve of TXB1 is y = 0.196x - 0.0572, and the standard curve of PGF 2β is y = 1.98x - 0.0400, the standard curve of TXB2 is y = 0.928x - 0.0335, the standard curve of PGE2 is y = 21.2x - 0.259, the standard curve of PGE1 is y = 49.1x - 0.500, the standard curve of PGD1 is y = 4.09x - 0.0314, the standard curve of PGD2 is y = 4.03x - 0.232, the standard curve of PGA2 is y = 48.5x - 0.00965, the standard curve of PGJ2 is y = 34.8x - 0.315, the standard curve of PGB2 is y = 10.5x - 0.0443, and the standard curve of PGA1 is y = 4.86x - 0.0330; herein, x is the concentration of the target substance, with the unit of ng / mL, and y is the peak area ratio of the target substance to the internal standard substance.

[0019] When detecting the serum sample, the standard curve of TXB1 is y = 0.298x + 0.0378, and the standard curve of PGF 2βThe standard curve of [substance name] is y = 12.5x + 0.131, the standard curve of TXB2 is y = 8.84x + 0.259, the standard curve of PGE2 is y = 110.4x + 3.21, the standard curve of PGE1 is y = 243.8x + 5.23, the standard curve of PGD1 is y = 76.0x + 1.68, the standard curve of PGD2 is y = 646.23X + 0.457, the standard curve of PGA2 is y = 6051.63x + 0.565, the standard curve of PGJ2 is y = 136.94x + 14.5, the standard curve of PGB2 is y = 62.8x + 1.50, and the standard curve of PGA1 is y = 24.7x + 0.574; herein, x is the concentration of the target substance in ng / mL, and y is the peak area ratio of the target substance to the internal standard substance.

[0020] Furthermore, in step (1), in the internal standard working solution, the concentration of PGA2-D4 is 0.1 μg / mL.

[0021] The beneficial effects of adopting the above solution include: PGA2-D4 as the internal standard has better benefits, being in the middle of the chromatographic peaks of several measured components and not co-eluting, while the other internal standard, Arachidonic Acid-d8, was not successfully detected after sample reconstitution. Description of the Drawings

[0022] Figure 1 It is the experimental result of the LPS-induced RAW264.7 cell inflammation model.

[0023] Figure 2 It is the apparent observation result diagram of the rat CIA model and AIA model.

[0024] Figure 3 It is the 3D construction diagram of Micro-CT, where (a) the articular surface and bone ends are intact and smooth, the joint space shows no widening or narrowing, and the surrounding soft tissues are normal; (b) there is bone defect on the articular surface, showing a brush-like change, the cartilage edge is irregular, the articular surface is blurred, and the joint space shows irregular narrowing.

[0025] Figure 4 It is the detection result of 11 metabolites contained in the mixed reference substance.

[0026] Figure 5 It is the content change of metabolites in the supernatant of RAW264.7 cells.

[0027] Figure 6 It is the detection result (bar chart) of 5 metabolites in the supernatant of RAW264.7 cells.

[0028] Figure 7Detection results (bar graph) of three metabolites in the sera of AIA model and CIA model rats.

[0029] Figure 8 For the changes in the contents of metabolites in the sera of CIA model and AIA model rats. Specific implementation manner

[0030] The principles and features of the present invention will be described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0031] In the present invention, the supernatant of RAW264.7 macrophages and the sera of SD rat arthritis disease models were selected as the research objects, and a rapid, sensitive and reliable LC-MS method was established to explore the influence on the cyclooxygenase pathway in AA metabolism of cells and whole animals during the occurrence of inflammation. Eleven metabolites produced by arachidonic acid through the COX metabolic pathway were selected in the present invention, and quantitative detection of 11 inflammatory factors was achieved simultaneously in a short time with a simple pretreatment process using fewer samples (200 μL of biological samples), having the advantages of rapidity, high sensitivity and good stability.

[0032] In the present invention, the experimental methods used, unless otherwise specified, are all conventional experimental methods in the art. The materials, reagents and instruments used are all conventional materials, reagents and instruments in the art, and can be obtained through commercial channels or prepared by conventional methods.

[0033] TXB1 (purity ≥ 98%), PGF 2β (purity ≥ 98%), TXB2 (purity ≥ 98%), PGE2 (purity ≥ 98%), PGE1 (purity ≥ 98%), PGD1 (purity ≥ 98%), PGD2 (purity ≥ 98%), PGA2 (purity ≥ 98%), PGJ2 (purity ≥ 98%), PGB2 (purity ≥ 98%), PGA1 (purity ≥ 98%), PGA2-D4 were purchased from Cayman Chemical Company.

[0034] Formic acid was purchased from Macklin; acetonitrile and methanol were purchased from ACS (U.S.A.); ultrapure water was purchased from Watson; DMEM medium was purchased from Gibco, batch number: 8123318; fetal bovine serum was purchased from Gibco; lipopolysaccharide (LPS) was purchased from Sigma; PBS was purchased from Gibco; bovine type II collagen (CII) was purchased from Chondrex; complete Freund's adjuvant was purchased from Chondrex; inactivated Mycobacterium tuberculosis was purchased from BD, U.S.A.; RAW264.7 cells were purchased from Haixing Biology, product number: TCM-C766; SD rats, SPF grade, 180 - 220 g, female, were purchased from Guangdong Weitong Lihua Experimental Animal Technology Co., Ltd., license number: SCXK2022 - 0063.

[0035] The following is introduced through specific examples.

[0036] Example 1 Establishment of an LPS-induced RAW264.7 cell inflammation model

[0037] RAW264.7 cells in the logarithmic growth phase were seeded in 12-well plates, with 150,000 cells per well. After the cells adhered, drug administration began. A blank group (Blank), an LPS stimulation group (model group Model), and a positive drug (dexamethasone DEX) group were set up, with 3 replicates in each group. 1 mL of medium was added to each well. The medium (purchased from Gibco, model number C11995500BT) contained D-glucose (4.5 g / L), L-glutamine, sodium pyruvate (110 mg / L), and 10% fetal bovine serum. The final concentration of LPS in the LPS stimulation group was 100 ng / mL, and the final concentration of dexamethasone in the positive drug group was 0.5 μM. One hour after drug administration, the positive drug group was directly replaced with 1 mL of a new medium containing the positive drug and LPS (that is, the original medium containing only the positive drug was replaced with a medium containing both the positive drug and LPS, equivalent to adding LPS for stimulation one hour after the positive drug, with the concentration of the positive drug being 0.5 μM and the concentration of LPS being 100 ng / mL). After incubation for 24 h (the incubation time was calculated starting from 1 h after drug administration), the cell supernatants of each group were collected, and PBS (the addition amount of PBS was 500 μL for infiltration) was added for microscopic photography.

[0038] The microscopic observation results showed that: RAW264.7 cells were round in the normal state, with smooth cell edges and no pseudopodia, and no vacuoles in the cytoplasm. After 24 h of LPS stimulation, the cell surface area increased, pseudopodia extended, and the vacuoles in the cytoplasm also increased. Administration of the positive drug played a certain protective role against the stimulation received by the cells. It was shown that the LPS-induced RAW264.7 cell inflammation model was successfully constructed ( Figure 1 ).

[0039] Example 2

[0040] 2.1 Experimental methods

[0041] (1) Establish a rat model of type II collagen-induced arthritis (CIA)

[0042] The immunogen was prepared on the day of modeling (day 0), and the preparation process was ensured to be carried out in a laminar flow hood. In an ice bath environment, equal amounts of bovine type II collagen (CII) and complete Freund's adjuvant (CFA) were fully mixed at a volume ratio of 1:1. In the mixture, the concentration of bovine type II collagen was 2 mg / mL, and the concentration of CFA was 10 mg / mL. Stir and emulsify with a high-speed homogenizer for about 10 min until the final emulsification degree reached that it did not disperse when dropped into water, that is, a bovine type II collagen emulsion with a concentration of 1 mg / mL was prepared.

[0043] After one week of adaptive feeding of healthy female SD rats, 12 rats were randomly selected as the blank group (BLANK, the blank group was normally fed without drug injection), and 28 rats were in the CIA model group. The rats in the CIA group were subcutaneously injected with 0.2 mL of bovine type II collagen emulsion at the root of the right tail of the rats, and on the 7th day, the rats were boosted with the same volume (0.2 mL) of bovine type II collagen emulsion as the immunization procedure on day 0. On the 14th day, the establishment of the rat CIA model was completed. The blood of the rats was collected and samples were taken. After the blood samples were left standing at room temperature for 30 min, the supernatant was obtained by centrifugation and used as serum.

[0044] The swelling degree of the two feet of the rats in the above model was measured with a toe volume measuring instrument before and after modeling to judge whether the modeling was successful.

[0045] (2) Establish a rat model of adjuvant-induced arthritis (AIA)

[0046] Ten healthy female SD rats were selected. After one week of adaptive feeding, they were used for modeling. The emulsifier was prepared as follows: First, 100 mg of inactivated Mycobacterium tuberculosis was weighed and placed in a sterile glass mortar. It was slowly ground in the same direction on ice until it turned grayish white, and then 10 mL of mineral oil was slowly added dropwise and ground continuously to make the two mixed, resulting in a milky white viscous emulsifier. For the primary immunization, each rat was injected with 0.15 mL of the emulsifier; for the booster immunization, 7 days after the primary immunization, the above operation was repeated and 0.1 mL of Freund's complete adjuvant was injected at the root of the rat's tail. On the 14th day, the establishment of the rat AIA model was completed. The blood of the rats was collected and samples were taken. After the blood samples were left standing at room temperature for 30 min, the supernatant was obtained by centrifugation and used as serum.

[0047] The swelling degree of the two feet of the rats in the above model was measured with a toe volume measuring instrument before and after modeling to judge whether the modeling was successful.

[0048] 2.2 Experimental results

[0049] The apparent observation results of the rat CIA and AIA models showed that compared with the normal control group (blank group), the signs of redness, swelling, pain, and stiffness in the joints of the rats in the CIA model group and the AIA model group were all in line with the characteristics of active arthritis( Figure 2 ).

[0050] The results of the 3D construction diagram of the rat CIA model showed that in the normal group (Control group), the joint surface and bone ends of the right hind limb of the rats were intact and smooth, the joint space was not widened or narrowed, and the surrounding soft tissues were normal; while in the CIA model group, the bone mass of the joint surface of the right hind limb of the rats was defective, showing a brush-like change, the cartilage edge was irregular, the joint surface was blurred, and the joint space showed irregular stenosis, indicating that the construction of the rat type II collagen-induced arthritis model was successful( Figure 3 ).

[0051] The results of the toe volume measurement of the rat type II collagen-induced arthritis (CIA) / adjuvant-induced arthritis (AIA) model showed that the toe volumes of the rats in each group were measured by a toe volume measuring instrument on the 0th day, 7th day, and 14th day. Compared with the normal control group (BLANK), the toe volumes of the CIA model group and the AIA model group were significantly increased, and the growth was rapid after the second booster immunization, and the difference was statistically significant( ** P<0.01)(see Table 1).

[0052] Table 1 Measurement of the toe volume of the rat arthritis model (cm 3 )

[0053]

[0054] ** P<0.01, vs BLANK group

[0055] Establishment of the methodology in Example 3

[0056] 3.1 Experimental method

[0057] (1) Preparation of standard solutions

[0058] Weigh appropriate amounts of TXB1, PGF 2β , TXB2, PGE2, PGE1, PGD1, PGD2, PGA1, PGA2, PGJ2, and PGB2 reference substances accurately, and prepare single reference substance stock solutions with methanol. The concentrations of the stock solutions are 100 μg / mL, 17.8 μg / mL, 18.1 μg / mL, 18.5 μg / mL, 15.7 μg / mL, 20 μg / mL, 112 μg / mL, 12.3 μg / mL, 10 μg / mL, 10 μg / mL, and 10 μg / mL in sequence.

[0059] Accurately pipette appropriate amounts of the stock solutions of each single reference substance to prepare a mixed reference substance. Each 1 mL of the mixed reference substance contains: TXB1 6.000 μg, PGF 2β 1.068 μg, TXB2 0.905 μg, PGE2 1.110 μg, PGE1 0.550 μg, PGD1 0.400 μg, PGD2 1.120 μg, PGA1 0.369 μg, PGA2 0.100 μg, PGJ2 0.150 μg, PGB2 0.200 μg.

[0060] (2) Prepare the internal standard solution

[0061] Take an appropriate amount of the PGA2-D4 reference substance, add methanol to prepare a stock solution of 0.1 mg / mL, and store it at 4°C. Before use, add methanol to dilute the stock solution to 0.1 μg / mL to obtain the internal standard working solution.

[0062] (3) Pretreatment of the cell supernatant sample

[0063] Take 200 μL of the supernatant, add 50 μL of the internal standard working solution (PGA2-D4 solution) prepared in step (2), then add 800 μL of acetonitrile, vortex for 3 min; centrifuge at 14000 rpm at 4°C for 10 min, take the supernatant; perform vacuum concentration using a nitrogen evaporator, store it at -80°C for later use; add 100 μL of chromatographic methanol, redissolve, ultrasonicate after standing, vortex for 3 min; centrifuge at 14000 rpm at 4°C for 10 min, take the supernatant and transfer it to an injection vial.

[0064] (4) Pretreatment of the rat serum sample

[0065] Take 200 μL of the serum, add 50 μL of the internal standard working solution (PGA2-D4 solution) prepared in step (2), then add 800 μL of acetonitrile, vortex for 3 min; centrifuge at 14000 rpm at 4°C for 10 min, take the supernatant; perform vacuum concentration using a nitrogen evaporator, store it at -80°C for later use; add 100 μL of chromatographic methanol, redissolve, ultrasonicate after standing, vortex for 3 min; centrifuge at 14000 rpm at 4°C for 10 min, take the supernatant and transfer it to an injection vial.

[0066] (5) The Agilent 6495 triple quadrupole mass spectrometer (QQQ-MS, Agilent Technologies, Santa Clara, CA, USA) was used to quantitatively detect inflammatory factors under the mass spectrometry conditions shown in Table 2. Chromatographic separation was performed on a Waters Acquity UPLC C18 column (1.7 μm, 2.1 mm × 100 mm, Waters, Milford). The mobile phase consisted of 0.1% formic acid (A) and acetonitrile (B), with gradient elution: 40% B from 0 - 3 minutes, 40% - 80% B from 3 - 8 minutes, and 40% B from 8.01 - 10 minutes. All percentages are by volume. An equal volume of 5 μL was injected, and the flow rate (FLOW) was 300 μL / min. The metabolites were detected using MRM and an ESI source in the negative ion mode. Other parameters were as follows: the flow rate of the drying gas (N2) was 11.0 L / min, the drying gas temperature was 300 °C; the nebulizer was at 15 psig; the capillary voltage was 4000 V.

[0067] Table 2 Mass Spectrometry Conditions

[0068]

[0069] 3.2 Experimental Results

[0070] (1) Specificity of the method

[0071] The following method was used to detect 11 metabolites in the mixed reference substance: The mixed reference substance was prepared according to the method in step (1) of Example 3.1. Take 200 μL of the mixed reference substance, add 50 μL of the internal standard working solution (PGA2 - D4 solution), then add 800 μL of acetonitrile, and vortex for 3 min; centrifuge at 14000 rpm at 4 °C for 10 min, and take the supernatant; perform vacuum concentration using a nitrogen blower and store it at -80 °C for later use; add 100 μL of chromatographic methanol to redissolve, let it stand, then ultrasonicate and vortex for 3 min; centrifuge at 14000 rpm at 4 °C for 10 min, and take the supernatant into the injection vial. Then, the 11 metabolites contained in the prepared mixed reference substance were detected under the conditions in (5) of Example 3.1.

[0072] The results showed that the 11 metabolites contained in the detected samples could be completely separated from the internal standard, with symmetric peak shapes and no interference from endogenous substances. See Figure 4 .

[0073] (2) Standard curve, linear range, and lowest quantitative concentration

[0074] Take an appropriate amount of the mixed reference substance (for example, 200 μL). The preparation method of the mixed reference substance refers to Example 3.1(1), and the mixed reference substance was processed according to the method in Example 3.1(3).

[0075] Treat 200 μL of blank group culture medium using the method of Example 3.1(3).

[0076] Treat 200 μL of blank group rat serum using the method of Example 3.1(4).

[0077] The blank group rat serum is the rat serum from the blank control group in Example 2; the blank group culture medium refers to the cell culture medium from the blank control group during cell culture in Example 1 (i.e., the pure culture medium for RAW264.7 cell culture).

[0078] Detect the above - treated mixed reference substances, blank group culture medium, and blank group rat serum according to the method in Example 3.1(5).

[0079] Perform regression calculation on the peak area ratio Y of the target substance to the internal standard substance against the target substance concentration X (ng / mL) using the weighted least - squares method. The results are shown in Table 3 and Table 4. It can be seen from Table 3 and Table 4 that r is greater than 0.99, indicating that the linear relationships of the 11 metabolites are good in each range.

[0080] Table 3 Standard curve of blank group culture medium

[0081]

[0082]

[0083] Table 4 Standard curve of blank group rat serum

[0084]

[0085] (3) Accuracy, precision, extraction recovery

[0086] Add 11 metabolites with different concentrations to the blank group culture medium according to Table 5, mix them to prepare blank group culture medium samples with low, medium, and high concentrations; take 200 μL of the blank group culture medium sample and treat it according to the method of 3.1(3) as the quality control sample.

[0087] Table 5 Concentrations (ng / mL) of 11 substances contained in low, medium, and high samples of blank group culture medium

[0088] <![CDATA[TXB1]]> <![CDATA[PGF 2β > <![CDATA[TXB2]]> <![CDATA[PGE2]]> <![CDATA[PGE1]]> <![CDATA[PGD1]]> <![CDATA[PGD2]]> <![CDATA[PGA2]]> <![CDATA[PGJ2]]> <![CDATA[PGB2]]> <![CDATA[PGA1]]> Low 188 16.7 14.1 17.3 8.60 6.30 17.5 0.234 2.30 3.10 5.80 Medium 750 66.8 113 69.4 34.3 25.0 70.0 6.30 9.40 12.3 23.1 High 4800 427 724 444 220 160 448 40.0 120 160 148

[0089] Add 11 metabolites with different concentrations to the blank group rat serum according to Table 6, mix them to prepare blank group rat serum samples with low, medium, and high concentrations; take 200 μL of the blank group rat serum and treat it according to the method of 3.1(4) as the quality control sample.

[0090] Concentrations (ng / mL) of 11 substances contained in low, medium, and high samples of rat serum in the blank group

[0091] <![CDATA[TXB1]]> <![CDATA[PGF 2β > <![CDATA[TXB2]]> <![CDATA[PGE2]]> <![CDATA[PGE1]]> <![CDATA[PGD1]]> <![CDATA[PGD2]]> <![CDATA[PGA2]]> <![CDATA[PGJ2]]> <![CDATA[PGB2]]> <![CDATA[PGA1]]> Low 93.8 33.4 14.1 17.3 8.60 6.30 1.75 0.234 4.60 6.30 11.5 Medium 375 134 56.6 139 68.6 50.0 140 12.6 18.8 25.0 46.1 High 2400 854 362 888 440 180 896 80.0 120 160 295

[0092] The extraction recovery rate of the samples was investigated by the ratio of the peak area of the metabolite chromatogram after extraction to the peak area of the chromatogram of the 11 metabolite reference substance solutions. Three samples were analyzed for each concentration. The extraction recovery rates of the blank group culture medium samples at three concentrations were in the range of 97.7% - 111%, and the RSD range was 0.294% - 11.6%. The extraction recovery rates of the blank group rat serum samples at three concentrations were in the range of 88.4% - 108%, and the RSD range was 0.0384 - 4.74%. Therefore, the extraction recovery rates were all in the range of 85% - 115%, meeting the requirements. Using the same method, the concentrations of the samples were measured within 3 days respectively, and the inter-day accuracy and precision were calculated. The intra-day precision RSD of the blank culture medium samples was 0.535% - 6.48%, and the inter-day precision RSD was 0.111% - 10.2%. The intra-day precision RSD of the blank group rat serum samples was 0.225% - 3.95%, and the inter-day precision RSD was 0.174% - 8.79%. All RSD values were less than 15%. Therefore, the intra-day and inter-day precision and accuracy of this method met the requirements.

[0093] (4) Stability

[0094] Quality control samples: The low, medium, and high concentration blank group culture medium samples and low, medium, and high concentration blank group rat serum samples prepared in the above step (3) were used as quality control samples. The low, medium, and high concentration blank group culture medium samples were processed according to the method in 3.1(3), and the low, medium, and high concentration blank group rat serum samples were processed according to the method in 3.1(4).

[0095] The processed quality control samples were subjected to freeze-thaw under the following conditions: (a) placed at room temperature for 6 h, (b) placed at -20°C for 30 days, (c) freeze-thawed 3 times;

[0096] The processed samples were detected by the method in 3.1(5). The measurement results showed that the stability RSD of the blank group rat serum samples under the above storage conditions was 0.0161% - 5.95%, and the stability RSD of the blank group culture medium samples under the above storage conditions was 0.258% - 7.39%. The stability RSD values of all samples were less than 10%. Therefore, the samples were stable under the above storage conditions.

[0097] Example 4 Detection of changes in inflammatory factors in the LPS-stimulated RAW264.7 macrophage inflammation model

[0098] (1) Take 200 μL of the cell supernatant of the RAW264.7 cell inflammation model induced by LPS, add 50 μL of the internal standard working solution (PGA2-D4 solution), then add 800 μL of acetonitrile, and vortex for 3 min; centrifuge at 14,000 rpm at 4 °C for 10 min, and take the supernatant; perform vacuum concentration using a nitrogen evaporator, store at -80 °C for later use; add 100 μL of chromatographic methanol, redissolve, let stand and then sonicate, vortex for 3 min; centrifuge at 14,000 rpm at 4 °C for 10 min, and take the supernatant into a sample vial.

[0099] In the above method, the construction method of the RAW264.7 cell inflammation model induced by LPS refers to Example 1. The preparation method of the internal standard working solution refers to Example 3.1(2).

[0100] (2) Use the method of Example 3.1(5) to detect the contents of 11 metabolites in the model. Substitute the detected peak areas into the formula in the standard curve (Table 3). The standard curve formula in Table 3 is obtained by performing a regression operation on the peak area ratio Y of the target substance and the internal standard substance to the target substance concentration X (ng / mL) using the weighted least squares method, and calculate the contents of the metabolites. Among them, the detection results of the contents of 5 metabolites are shown in Table 7.

[0101] Table 7 Contents of 5 metabolites in the RAW264.7 cell supernatant (ng / mL)

[0102] <![CDATA[PGE2]]> <![CDATA[PGD1]]> <![CDATA[PGD2]]> <![CDATA[PGA2]]> <![CDATA[PGJ2]]> BLANK 0.641±0.0172 0 2.99±0.0461 0 0.241±0.0136 LPS group 2.501±0.277 10.2±0.951 46.7±4.09 0.778±0.0561 21.5±1.90 DEX group 1.32±0.105 3.67±0.434 17.6±1.52 0.206±0.0554 11.3±1.04

[0103] According to LC-MS detection, 11 metabolites were detected ( Figure 5 ), among which the contents of 5 metabolites changed significantly ( Figure 6 ), and the contents of other metabolites did not change significantly, indicating that among the 11 metabolites detected simultaneously, the contents of PGE2, PGD1, PGD2, PGA2, and PGJ2 in the RAW264.7 inflammation model all increased significantly, suggesting that the comprehensive expression of these 5 metabolites can be selected as the detection index for the inflammation model.

[0104] According to the LC-MS detection results (see Figure 5 and Figure 6 ), it was found that the contents of inflammatory factors PGE2, PGD1, PGD2, PGA2, and PGJ2 in the supernatant of RAW264.7 macrophages all increased significantly, indicating that the contents of different inflammatory factors change significantly during the occurrence of the inflammatory response, and their functions are also different, and often multiple metabolites act together to produce an impact in the arachidonic acid metabolic pathway.

[0105] Studies have shown that inflammatory factors produced by the activation of RAW264.7 macrophages induced by lipopolysaccharide (LPS) play an important role in the occurrence and development of inflammation and metabolic disorders. Cytosolic phospholipase A2 (cPLA2), as a key pro-inflammatory enzyme, catalyzes the hydrolysis of membrane glycerophospholipids to release arachidonic acid (AA). LPS increases cPLA2 in inflammatory cells, thereby generating AA. Under the action of COX, AA can form prostaglandin endoperoxides PGH2 and PGG2, and these two prostaglandin endoperoxides are easily converted into PGs. Both PGH2 and PGG2 can be converted into PGD2, PGF2, PGE2, and PGI2 under the action of isomerase.

[0106] The results of the LC-MS method established in the present invention show that: while the contents of PGE2, PGD1, PGD2, PGA2, and PGJ2 in inflammatory cells increase, the positive drug (dexamethasone DEX) can inhibit the expression of cPLA2 and COX-2 in LPS-induced cells. After adding the positive drug (DEX) to inflammatory cells, the levels of inflammatory factors such as PGE2, PGA2, PGD2, and PGJ2 are all down-regulated, especially PGD2 and its metabolite PGJ2 are significantly down-regulated. At different stages of the onset of inflammation, arachidonic acid will be converted into different prostaglandins, from PGE2 in the acute phase to PGD2 in the resolution phase. This change is regulated by microsomal prostaglandin E synthase-1, which only increases in the acute phase of inflammation (at this time, the product of COX-2 is mainly PGE2), and then this synthase disappears, accompanied by an increase in the content of PGD2, indicating that the inflammation begins to subside. The research results of the method provided by the present invention show that the levels of PGD2 and PGJ2 increase significantly, indicating that it has entered the inflammation resolution stage. Therefore, it also suggests that when detecting the inflammatory indicators of LPS-induced inflammatory cells, in order to better explain the stage of inflammation occurrence, only selecting the single index of PGE2 is not comprehensive enough, and PGD2 and PGJ2 as precursors should be added, and the comprehensive expression of multiple indicators is more persuasive.

[0107] Example 5 Detection of changes in inflammatory factors in a rat arthritis model

[0108] (1) Take 200 μL of serum, add 50 μL of internal standard working solution (PGA2-D4 solution), then add 800 μL of acetonitrile, and vortex for 3 min; centrifuge at 14,000 rpm at 4 °C for 10 min, and take the supernatant; perform vacuum concentration using a nitrogen evaporator, store at -80 °C for later use; add 100 μL of chromatographic methanol, redissolve, let stand, sonicate, and vortex for 3 min; centrifuge at 14,000 rpm at 4 °C for 10 min, and take the supernatant into the injection vial.

[0109] The serum in the above method is the serum of the CIA model or the AIA model. The construction methods of the CIA model and the AIA model refer to Example 2. The preparation method of the internal standard working solution refers to Example 3.1(2).

[0110] (2) The contents of 11 metabolites in the model were detected by the method of Example 3.1(5). Substitute the peak areas obtained from the detection into the formula in the standard curve (Table 4). The formula of the standard curve in Table 4 was obtained by performing a regression operation on the peak area ratio Y of the target substance and the internal standard substance to the target substance concentration X (ng / mL) using the weighted least squares method, and the contents of the metabolites were calculated. The detection results of the contents of 3 of the metabolites are shown in Table 8.

[0111] Table 8 Contents of 3 metabolites in rat serum (ng / mL)

[0112] <![CDATA[PGE2]]> <![CDATA[PGD2]]> <![CDATA[PGA2]]> BLANK 24.3±14.3 1.23±0.137 0.0522±0.00413 AIA 201±72.3 6.78±3.47 0.345±0.137 CIA 45.3±10.4 2.22±0.486 0.0382±0.0216

[0113] The experimental results showed that: for the CIA model, there were no obvious changes in all 11 metabolites, indicating that although the CIA model was successfully established, the mechanism of its model establishment was different from that of the AIA model, and the selection of detection indicators was also different from that of the AIA model. Therefore, these 11 metabolites were not suitable for reflecting the changes of the indicators of the CIA model. For the AIA model, obvious changes occurred in 3 of the 11 metabolites, namely PGE2, PGD2, and PGA2. Therefore, these 3 metabolites can be selected for comprehensive evaluation in the evaluation of the detection indicators for the establishment of the AIA model.

[0114] According to the LC-MS detection results, it was shown that the contents of PGE2 and its metabolites PGD2 and PGA2 in the animal serum of the AIA model were all significantly increased ( Figure 7 ), while the contents of each inflammatory factor in the animal serum of the CIA model showed no obvious changes ( Figure 8)。This experiment used rats with collagen-induced arthritis (CIA) and adjuvant-induced arthritis (AIA) as models. The two models simulate different etiologies. The CIA model is established by injecting an emulsion of type II collagen mixed with complete Freund's adjuvant twice at the base of the tail (in the emulsion, the volume ratio of bovine type II collagen to complete Freund's adjuvant is 1:1). The animals mainly show joint swelling, mainly involving the ankle joint, tarsal joint, and interphalangeal joint, and eventually leading to joint deformation. The AIA model is constructed by injecting complete Freund's adjuvant subcutaneously at the base of the tail once. A protein molecule of Mycobacterium tuberculosis is similar in structure to a glycoprotein molecule on the joint synovium and can be recognized by the same T cell clone, thus inducing an immune response against the joint. This model has obvious cellular immune abnormalities. The AIA model is used for the study of immune-inflammatory models caused by external factor stimulation, while the CIA model is suitable for research on treatment mechanisms and immunity-related aspects. At the same time, the test results show that the AIA model is more suitable than the CIA model for detecting the contents of the three indicators of PGE2, PGD2, and PGA2 in AA metabolism by the method established in the present invention.

[0115] Studies have shown that PGE2 is involved in joint inflammatory reactions, participates in the synthesis of matrix metalloproteinases and induces cartilage degradation. The upregulation of PGE2 accelerates the development of arthritis. TXA2 is a prostaglandin synthesized and released by platelets that can promote platelet aggregation and cause strong vasoconstriction. AA in platelets synthesizes intermediate products through COX-1 or COX-2, and then catalyzes the synthesis of TXA2 by TXA2 synthase. TXA2 is extremely unstable and decomposes into inactive TXB2 in water. The basic pathological manifestation of rheumatoid arthritis is synovial hyperplasia and pannus formation in the joint, and new blood vessels are an important part of the pannus. Existing studies have shown that COX-2 plays a key role in the formation of new blood vessels in the joint synovium. The catalytic products of COX-2, such as PGE2, PGF2, and TXA2, can directly or indirectly promote angiogenesis. PGE2 can regulate the expression of vascular endothelial growth factor, and its metabolites induce the synthesis of angiogenic factors, promoting the formation of new blood vessels. Therefore, the method for detecting the contents of multiple indicators of PGE2, PGD2, and PGA2 provided by the present invention can more comprehensively explain the occurrence and development of inflammation in the animal AIA model.

[0116] Comparative Example 1

[0117] Screen the proportion of the mobile phase in (5) of Example 3.1. On the basis of (5) in Example 3.1, the mobile phases are set as follows respectively, and other conditions are the same as those in (5) of Example 3.1 except for the mobile phase.

[0118] Group 1: 10%-90% B for 0-10 minutes;

[0119] Group 2: 25% - 90% of B is for 0 - 8 minutes, and 90% of B is for 8 - 10 minutes;

[0120] Group 3: 30% of B is for 0 - 10 minutes, and 30% - 90% of B is for 10 - 12 minutes;

[0121] Group 4: 50% of B is for 0 - 8 minutes, 50% - 90% of B is for 8 - 10 minutes, and 90% of B is for 10 - 12 minutes;

[0122] Group 5: 45% of B is for 0 - 8 minutes, and 45% - 90% of B is for 8 - 10 minutes;

[0123] Group 6: 40% of B is for 0 - 8 minutes, and 40% - 90% of B is for 8 - 10 minutes;

[0124] Group 7: 40% of B is for 0 - 4 minutes, and 40% - 60% of B is for 4 - 8 minutes;

[0125] Group 8: 35% - 40% of B is for 0 - 4 minutes, and 40% - 80% of B is for 4 - 8 minutes;

[0126] Group 9: 40% of B is for 0 - 3 minutes, 40% - 80% of B is for 3 - 8 minutes, and 40% of B is for 8.01 - 10 minutes (i.e., the mobile phase used in Example 3.1).

[0127] Take 200 μL of the mixed reference substance. The preparation method of the mixed reference substance refers to Example 3.1(1), and the mixed reference substance is processed by the method of Example 3.1(3). The mixed reference substance is detected under the conditions of each of the above groups respectively. The experimental results show that: the mobile phase conditions adopted in the present invention (i.e., Group 9) have the advantage of complete separation, and there are problems such as incomplete separation and superposition of isomers in Groups 1 to 8.

[0128] Comparative Example 2

[0129] Replace the internal standard working solution (PGA2 - D4 solution) in (3) of Example 3.1 with an equal amount and equal concentration of Arachidonic Acid - d8, and the others are the same as in (3) of Example 3.1. The blank group of the culture medium is detected by the above method. The results show that after detection with Arachidonic Acid - d8 as the internal standard, when 200 μL of the supernatant is taken and finally 100 μL of methanol is added for re - dissolution, it cannot be detected, and the detection effect is not good. The above results show that the selection of the internal standard is crucial for the detection method of the present invention, and the internal standard PGA2 - D4 selected in the present invention is applicable to the detection method of 11 metabolites in the cell supernatant sample.

[0130] Comparative Example 3

[0131] Replace the internal standard working solution (PGA2-D4 solution) in (4) of Example 3.1 with an equal amount and concentration of Arachidonic Acid-d8, and the others are the same as in (4) of Example 3.1. The blank group of rat serum samples was detected by the above method. The results showed that after detection with Arachidonic Acid-d8 as the internal standard, 200 μL of the supernatant was taken, and finally 100 μL of methanol was added for reconstitution, but it could not be detected, and the detection effect was not good. The above results indicate that the selection of the internal standard is crucial for the detection method of the present invention, and the internal standard PGA2-D4 selected by the present invention is applicable to the detection method of 11 metabolites in rat serum samples.

[0132] In summary, the present invention has successfully established an LC-MS method for the rapid quantification of 11 inflammatory factors including TXB1, PGF 2β , TXB2, PGE2, PGE1, PGD1, PGD2, PGA2, PGJ2, PGB2, and PGA1, and verified its advantages of rapidity, sensitivity, and accuracy. Traditional detection methods are difficult to achieve accurate quantitative detection of multiple inflammatory indicators simultaneously, but the method provided by the present invention can quickly and accurately obtain the concentration of the analyte in an unknown biological sample within a wide detection range, with higher specificity and accuracy, and the established method has been successfully applied to the analysis of changes in relevant inflammatory factors in biological samples. The results show that there are obvious differences in the trends and contents of the analyzed metabolites, providing more information for the study of metabolic pathways in the construction of inflammation models. In addition, the method provided in the present invention can be applied to the detection method of inflammatory indicators in the metabolic pathways of various different inflammation model constructions.

[0133] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for determining the content of COX-2 metabolites in the arachidonic acid metabolic pathway in an inflammation model, characterized in that: The following steps are involved: (1) Sample pretreatment: pretreatment of cell supernatant samples and / or serum samples, adding internal standard working solution during the pretreatment process, the internal standard working solution is a solution of internal standard substance PGA2-D4; cell supernatant is the supernatant of LPS-induced RAW264.7 cell inflammation model; serum sample is the serum sample of adjuvant-induced arthritis model or type II collagen-induced arthritis model; (2) Agilent 6495 triple quadrupole mass spectrometer is used to detect the treated samples, and the detection conditions include: chromatographic separation on Waters Acquity UPLC C18 column; The mobile phase was 0.1% formic acid A and acetonitrile B, with gradient elution: 40% B for 0-3 minutes, 40%-80% B for 3-8 minutes, and 40% B for 8.01-10 minutes; 5 μL of equal volume was injected, and the FLOW speed was 300 μL / min; metabolites were detected using MRM and ESI sources in negative ion mode; the drying gas flow rate was 11.0 L / min, the drying gas temperature was 300°C, the nebulizer was 15 psig, and the capillary voltage was 4000 V; the COX-2 metabolites of the arachidonic acid metabolic pathway included TXB1, PGF 2β , TXB2, PGE2, PGE1, PGD1, PGD2, PGA1, PGA2, PGJ2 and PGB2; the content of metabolites was calculated based on the peak area obtained by detection and the standard curve formula.

2. The method for determining the content of COX-2 metabolites in the arachidonic acid metabolic pathway in an inflammation model according to claim 1, characterized in that: The concentration of PGA2-D4 in the internal standard working solution was 0.1 μg / mL.

3. The method for determining the content of COX-2 metabolites in the arachidonic acid metabolic pathway in an inflammation model according to claim 1 or 2, characterized in that: The method for pretreatment of cell supernatant samples includes the following steps: taking 200 μL of supernatant, adding 50 μL of internal standard working solution, adding 800 μL of acetonitrile, and vortexing for 3 min; centrifuging at 4°C, 14000 rpm for 10 min, and taking the supernatant; vacuum concentrating; adding 100 μL of chromatographic methanol to re-dissolve, standing and then ultrasonicating, vortexing for 3 min; centrifuging at 4°C, 14000 rpm for 10 min, and taking the supernatant.

4. The method for determining the content of COX-2 metabolites in the arachidonic acid metabolic pathway in an inflammation model according to claim 1 or 2, characterized in that: The pre-treatment of serum samples includes the following steps: Take 200 μL of serum, add 50 μL of internal standard working solution, add 800 μL of acetonitrile, vortex for 3 min; centrifuge at 4 °C, 14000 rpm for 10 min, take the supernatant; vacuum concentrate; add 100 μL of chromatographic methanol to re-dissolve, let stand, then sonicate, vortex for 3 min; centrifuge at 4 °C, 14000 rpm for 10 min, take the supernatant.

5. The method for determining the content of COX-2 metabolites in the arachidonic acid metabolic pathway in an inflammation model according to claim 1 or 2, characterized in that: When the cell supernatant samples were tested, the standard curve of TXB1 was y=0.196x-0.0572, PGF 2β The standard curve of is y=1.98x-0.0400, the standard curve of TXB2 is y=0.928x-0.0335, the standard curve of PGE2 is y=21.2x-0.259, the standard curve of PGE1 is y=49.1x-0.500, the standard curve of PGD1 is y=4.09x-0.0314, the standard curve of PGD2 is y=4.03x-0.232, the standard curve of PGA2 is y=48.5x-0.00965, the standard curve of PGJ2 is y=34.8x-0.315, the standard curve of PGB2 is y=10.5x-0.0443, and the standard curve of PGA1 is y=4.86x-0.0330; in the above, x is the concentration of the target, in ng / mL, and y is the peak area ratio of the target and the internal standard.

6. The method for determining the content of COX-2 metabolites in the arachidonic acid metabolic pathway in an inflammation model according to claim 1 or 2, characterized in that: When testing serum samples, the standard curve of TXB1 is y=0.298x+0.0378, PGF 2β The standard curve of is y=12.5x+0.131, the standard curve of TXB2 is y=8.84x+0.259, the standard curve of PGE2 is y=110.4x+3.21, the standard curve of PGE1 is y=243.8x+5.23, the standard curve of PGD1 is y=76.0x+1.68, the standard curve of PGD2 is y=646.23X+0.457, the standard curve of PGA2 is y=6051.63x+0.565, the standard curve of PGJ2 is y=136.94x+14.5, the standard curve of PGB2 is y=62.8x+1.50, and the standard curve of PGA1 is y=24.7x+0.574; in the above, x is the concentration of the target in ng / mL, and y is the peak area ratio of the target and the internal standard.

Images