Simultaneous quantitative detection method of multiple metabolites in biological samples

Abstract

This invention discloses a method for the simultaneous quantitative detection of multiple metabolites in biological samples. The method employs chromatographic tandem mass spectrometry (GC-MS) to detect the biological samples, comprising the following steps: (1) optimizing mass spectrometry detection parameters to obtain the optimal mass spectrometry detection parameters for each metabolite; (2) applying the optimal mass spectrometry detection parameters to detect the biological samples and classifying each metabolite; (3) optimizing and obtaining the final CE value for each metabolite; (4) using the final CE value corresponding to each metabolite to detect the biological sample to be tested, and using the internal standard method to perform quantitative analysis of each metabolite in the biological sample to be tested, thereby obtaining the content of each metabolite in the biological sample to be tested. Furthermore, an absolute quantitative analysis method based on eliminating interference from natural isotopes in metabolites is also provided. The method of this invention has high throughput, high accuracy, simple operation, high experimental reproducibility and operability, and can be applied to clinical pathophysiological research and biomarker discovery.

Description

Technical Field

[0001] This invention relates to a method for the simultaneous quantitative detection of multiple metabolites in biological samples. Background Technology

[0002] In quantitative methods based on UHPLC-MS / MS detection systems, internal standards are often added to biological samples to eliminate random errors and matrix effects that may exist during sample pretreatment and detection, thereby improving detection accuracy. Furthermore, an internal standard of known concentration is essential for achieving absolute quantification. Compared to structurally similar internal standards, stable isotope internal standards (SIL-IS) and isotope probe-labeled internal standards (CIL-IS) possess chemical and physical properties extremely similar to the analyte, ensuring similar chromatographic behavior and ionization efficiency.

[0003] However, achieving high-throughput absolute quantitative analysis of metabolites in biological samples currently faces the following two challenges:

[0004] On the one hand, the concentrations of some metabolites (such as amino metabolites) vary greatly, and some high-concentration metabolites are prone to detector saturation, hindering the simultaneous quantitative analysis of multiple metabolites in a sample and reducing the analytical throughput of the method. Current technologies generally use sample dilution to address detector saturation caused by high-concentration metabolites. However, when the number of samples to be analyzed is large, this operation is time-consuming and labor-intensive. Furthermore, at the same dilution factor, some low-concentration metabolites in the sample may be difficult to detect simultaneously due to their extremely low concentration. Therefore, general analytical methods are only suitable for the detection of one specific metabolite or a few to dozens of metabolites, resulting in low analytical throughput.

[0005] On the other hand, internal standards are susceptible to interference from natural isotopes in metabolites, leading to a shortened quantitative linear range. Therefore, most current methods only perform qualitative or relative quantitative detection, making absolute quantitative detection difficult. Some studies use quadratic regression to expand the dynamic range, but due to the weak predictive power of parabolic curves, quantitative accuracy cannot be guaranteed. Furthermore, some studies have considered the interference of analytes on internal standards and vice versa, proposing two equations to correct for interference and calculate sample concentrations using these equations. Similarly, some studies have constructed new quantitative linear curves through data transformation. However, these methods are only applicable to a few analytes, making them difficult to apply to multiple analytes, and are often incompatible with data analysis software, significantly increasing the complexity of data analysis when analyzing large batches of samples. Summary of the Invention

[0006] The technical problem this invention aims to solve is to overcome the shortcomings of existing technologies in the quantitative analysis of metabolites in biological samples, such as low throughput or difficulty in analyzing multiple types of biological samples, and to provide a method for the simultaneous quantitative detection of multiple metabolites in biological samples. The detection method of this invention features high throughput and high accuracy.

[0007] The present invention solves the above-mentioned technical problems through the following technical solution:

[0008] A method for simultaneous quantitative detection of multiple metabolites in biological samples, which employs chromatography-tandem mass spectrometry (GC-MS) for the detection of biological samples, wherein the mass spectrometry detection includes the following steps:

[0009] (1) Determine the characteristic ion pairs of each metabolite, optimize the mass spectrometry detection parameters, and obtain the best mass spectrometry detection parameters for each metabolite, including the best collision energy, i.e. the best CE value.

[0010] (2) Apply the optimal mass spectrometry detection parameters obtained in step (1) to detect the biological sample and obtain the chromatographic peak intensity of each metabolite in the biological sample;

[0011] Then, using a threshold A of 0.05-0.5 times the upper limit of the detection intensity of the chromatography-tandem mass spectrometry system, the metabolites were classified according to their chromatographic peak intensities:

[0012] The first category of metabolites are low-concentration metabolites, which are defined as metabolites whose chromatographic peak intensity is lower than or equal to threshold A;

[0013] The second category of metabolites are high-concentration metabolites, which are defined as metabolites whose chromatographic peak intensity is higher than the threshold A.

[0014] (3) Determine the final CE value:

[0015] For the first type of metabolite, the CE value of its mass spectrometry detection is not optimized, and the best CE value in step (1) is still used as the final CE value;

[0016] For the second type of metabolite, the CE value is optimized as follows: different CE values ​​are used to detect the same metabolite in the biological sample to obtain a chromatographic peak intensity-CE value curve, and the CE value with the chromatographic peak intensity closest to the threshold A is taken as the final CE value.

[0017] (4) Using the final CE value corresponding to each metabolite, the biological sample to be tested is injected into the liquid chromatography-tandem mass spectrometry system, and the internal standard method is used to quantitatively analyze each metabolite in the biological sample to be tested, so as to obtain the content of each metabolite in the biological sample to be tested.

[0018] In this invention, the number of metabolites can be one or more, and the types can be expanded according to the upper limit of ion pairs that the liquid chromatography-tandem mass spectrometry system used can cover. Preferably, it can reach more than 120 types, such as 121 types.

[0019] In this invention, the metabolites can be metabolites from conventional biological samples in the art. Preferably, the metabolites include amino metabolites, such as those selected from norepinephrine, octanamine, 1,2-diaminopropane, 1,3-diaminopropane, 1-deoxynojirimycin, 1-methyl-histidine, 2,4-diaminobutyric acid, 2-amino-2-methyl-1-propanol, 2-aminoisobutyric acid, 3-aminobenzoic acid, 4-aminobenzoic acid, transtriiodothyronine, triiodothyronine, 3,4-dihydroxy-DL-phenylalanine, 3-aminosalicylic acid, 3-hydroxy-2-aminobenzoic acid, 3-iodothyronine, 3-methoxytyramine, 3-methyl-histidine, 4-aminophenol, and 4-hydroxy-L-isoleucine. 4-Hydroxy-L-proline, 5-aminovaleric acid, 5-hydroxydopamine, 5-hydroxy-L-tryptophan, 6-aminohexanoic acid, guanidinobutylamine, alanylleucine, alanyltryptophan, argininosuccinic acid, asymmetric dimethylarginine, cadaverine, cystathionine, cysteine ​​& cystamine, D-(-)-α-phenylglycine, dextromethorphanine, D-homoserine, quinoline, DL-2,6-diaminopimelic acid, DL-3-aminoisobutyric acid, DL-5-hydroxylysine, DL-ethionine, DL-dialanine sulfoxide, DL-methionine sulfoxide, DL-norepinephrine, dopamine, D-serine, adrenaline, glycine, glutathione 1, glutathione 2, histamine, taurine L-aminohexanoic acid, L-2-aminoadipic acid, L-2-aminobutyric acid, L-alanine, L-carnosine, L-arginine, L-asparagine, L-aspartic acid, L-carnosine, L-citrulline, L-sulfoalanine, L-cysteine ​​& L-cysteine, leucylproline, L-glutamic acid, L-glutamine, histidine, L-homocysteine, L-homocysteine ​​& L-homocysteine, L-isoleucine, L-kynurenine, L-leucine, L-lysine, L-methionine, L-valine, L-ornithine, L-piperidinic acid, proline, L-serine, L-threonine, L-thyroxine, L-tryptophan, L-tryptophanamide, L-tyrosine, L-valine, adrenal cortex The following are included in the following groups: adenosine, N-methylphenylethylamine, N-methyltyramine, Nα-acetyl-L-lysine, Nε,Nε,Nε-trimethyllysine, L-serine acetyl ester, L-serine phosphate ester, L-threonine phosphate ester, L-tyrosine phosphate ester, ethanolamine phosphate 1, ethanolamine phosphate 2, p-aminohippuric acid, phenylethylamine, phenylalanine, procaine, proline, putrescine, S-(2-aminoethyl)-L-cysteine, S-adenosyl-L-homocysteine, S-adenosylmethionine, yeast amino acid, decarboxylated S-adenosylmethionine, sarcosine, serotonin, spermine, spermine, deoxyepinephrine, taurine, tryptamine, tyramine, β-alanine, γ-aminobutyric acid, γ-glutamylcysteine, and creatinine.

[0020] In this invention, generally, the biological sample to be tested in step (4) and the biological sample in step (2) can be of the same type, as long as their composition is not significantly different. For example, if the biological sample is urine, then the biological sample to be tested can be urine from different sources.

[0021] In this invention, preferably, the biological sample to be tested in step (4) is the same as the biological sample.

[0022] In this invention, the biological sample can be of 1-3 types, thus enabling the method to be applicable to the detection of various metabolites in 1-3 types of samples. For example, the biological sample is selected from one or more of serum, urine, cell, and tissue samples, such as 1, 2, or 3 types. As another example, when the biological sample is urine, serum, or tissue, and these three types of samples contain the same metabolite 1-methyl-histidine, the detection method of this invention can be used to detect 1-methyl-histidine in these three types of samples.

[0023] When there is only one biological sample, the final CE value of the metabolite is determined as in steps (1)-(3) above.

[0024] When the biological sample contains two types of metabolites of the same kind, preferably, the metabolites are classified according to the following three conditions, and a final CE value for detecting the metabolites is obtained:

[0025] i. In two biological samples, metabolites of the same type are all Class I metabolites (i.e., the chromatographic peak intensity of the same metabolite in different biological samples is lower than or equal to the threshold A).

[0026] At this point, the CE value for the mass spectrometry detection of this metabolite will not be optimized, and the optimal CE value will still be used as the final CE value for the detection of this metabolite.

[0027] ii. In two biological samples, metabolites of the same type are all Class II metabolites (i.e., the chromatographic peak intensity of the same metabolite in different biological samples is higher than the threshold A);

[0028] At this point, the final CE value of the metabolite is obtained through the following steps:

[0029] a. For each biological sample, the same metabolite in the biological sample is detected using different CE values ​​according to step (3) to obtain a chromatographic peak intensity-CE value curve, that is, two chromatographic peak intensity-CE value curves of the same metabolite are obtained.

[0030] b. In the two chromatographic peak intensity-CE value curves of the same metabolite, take several (e.g., 3) CE values ​​of chromatographic peak intensities that are closest to threshold A (e.g., take three CE values ​​close to threshold A from the curves, and sum up to a total of six CE values). Use this to test the chromatographic peak intensity of the same metabolite in two biological samples. When the chromatographic peak intensity of the same metabolite in both biological samples does not exceed 0.5 times the upper limit of mass spectrometry detection intensity, the CE value is the final CE value of the metabolite.

[0031] iii. In two biological samples, metabolites of the same type are classified as Class III metabolites. Class III metabolites refer to low-concentration metabolites in some samples where the chromatographic peak intensity is lower than or equal to threshold A, and high-concentration metabolites in others where the chromatographic peak intensity is higher than threshold A.

[0032] At this point, for the CE values ​​of low-concentration metabolites in the third category of metabolites, the CE values ​​detected by mass spectrometry are not optimized, and the best CE value in step (1) is still used as the final CE value.

[0033] For the CE values ​​of high-concentration metabolites in the third category of metabolites, the final CE value of each metabolite is obtained by step (3).

[0034] When the biological sample contains three types of metabolites of the same kind, preferably, the metabolites are classified according to the following three conditions, and a CE value for detecting the metabolite is obtained:

[0035] i. In the three biological samples, the metabolites of the same type are all Class I metabolites (i.e., the chromatographic peak intensity of the same metabolite in different biological samples is lower than or equal to the threshold A).

[0036] At this time, the method for determining the final CE value of the metabolite is the same as that for case i when there are two biological samples, that is, the CE value of the mass spectrometry detection of the metabolite is not optimized, and the optimal CE value is still used as the final CE value for detecting the metabolite.

[0037] ii. In the three biological samples, the metabolites of the same type are all Class II metabolites (i.e., the chromatographic peak intensity of the same metabolite in different biological samples is higher than the threshold A);

[0038] At this point, referring to the method described in case ii when there are two types of biological samples, the final CE value of the metabolite is obtained;

[0039] Preferably, the final CE value of the metabolite is obtained through the following steps: For each biological sample, the same metabolite in the biological sample is detected using different CE values ​​according to step (3) to obtain a chromatographic peak intensity-CE value curve, that is, three chromatographic peak intensity-CE value curves of the same metabolite are obtained; in the three chromatographic peak intensity-CE value curves of the same metabolite, the CE values ​​of the three chromatographic peak intensities closest to the threshold A are taken respectively, for a total of 9 CE values, and the 9 CE values ​​are sorted from smallest to largest, and the median value is taken as the final CE value of the metabolite;

[0040] iii. Among the three biological samples, metabolites of the same type are classified as Class III metabolites. Class III metabolites refer to low-concentration metabolites in some samples where the chromatographic peak intensity is lower than or equal to threshold A, and high-concentration metabolites in others where the chromatographic peak intensity is higher than threshold A.

[0041] For the CE values ​​of low-concentration metabolites in the third category of metabolites, the CE values ​​detected by mass spectrometry are not optimized, and the best CE value in step (1) is still used as the final CE value.

[0042] For high-concentration metabolites in the third category of metabolites, the final CE value of the metabolite is obtained using the following method:

[0043] If only one biological sample has a high concentration of the same metabolite, then the CE optimized according to step (3) is the final CE value of the metabolite in that biological sample. The CE values ​​of the same metabolite in other samples are not optimized.

[0044] If two biological samples have the same metabolite at a high concentration, the final CE value of the metabolite is obtained according to the method described in case ii when there are two biological samples. The CE values ​​of the same metabolite in other samples are not optimized.

[0045] In this invention, in step (1), the method for determining the characteristic ion pairs of each metabolite can be a conventional method for determining characteristic ion pairs during mass spectrometry detection in the art. For example, after the metabolite standard solution has been derivatized (or not derivatized), the mass-to-charge ratio of the parent ion is determined by direct injection of the mass spectrometer in the parent ion scanning mode. Then, the daughter ion corresponding to the parent ion is obtained by the daughter ion scanning mode. Finally, based on the selected parent ion and daughter ion, a multiple reaction monitoring ion pair is constructed.

[0046] The derivatization process can be a conventional derivatization method in the art, such as adding a derivatization reagent to a derivatization reaction buffer containing the metabolite standard solution, reacting for a certain period of time, centrifuging, and taking the supernatant.

[0047] The derivatization reaction buffer can be a conventional solution used for derivatization reactions in the art, such as a methanol-water phosphate buffer. Preferably, the methanol-water phosphate buffer has a concentration of 0.4 M, a pH of 5.8, and a methanol-to-water volume ratio of 1:1.

[0048] The solvent in the metabolite standard solution is a suitable solvent that can dissolve the metabolite. For example, glycine can be dissolved in 50% methanol-water solvent, and yeast amino acids can be dissolved in dimethyl sulfoxide solvent.

[0049] The derivatizing reagent can be a conventional derivatizing reagent in the art, such as those selected from methyl esters, succinimidyl esters, N-alkylates, pentafluorobenzene activated esters, or dansyl chlorides, for example, NaBH3CN or NaBD3CN. The derivatizing reagent can be prepared using conventional methods in the art, such as mixing the derivatizing reagent with a methanol solution to prepare a 2M derivatizing reagent solution.

[0050] In this invention, in step (1), the method for optimizing the mass spectrometry detection parameters can be carried out in accordance with conventional methods in the art, for example: after determining the characteristic ion pair, the response value of the metabolite standard under different mass spectrometry detection parameters (CE value) is measured to achieve the best sensitivity, and the CE value with the highest response is taken as the best CE value.

[0051] The optimized mass spectrometry detection parameters also include optimized declustering voltage (DP), and the method for optimizing the declustering voltage can be a conventional method for optimizing the declustering voltage in the art.

[0052] In this invention, in step (2), preferably, the threshold A is 0.05 times the upper limit of the detection intensity of the chromatography-tandem mass spectrometry system.

[0053] In this invention, in step (3), the CE value is optimized so that the chromatographic peak intensity of the metabolite does not exceed 0.5 times the upper limit of mass spectrometry detection intensity; preferably, it does not exceed 0.2 times the upper limit of mass spectrometry detection intensity. By optimizing the CE value, the sensitivity of this type of metabolite is suppressed, ensuring that samples with high levels of this type of metabolite can be accurately quantified.

[0054] In this invention, in step (3), the use of different CE values ​​means taking a number of points on the left and right sides of the optimal CE value (for example, taking 10 points on the left and 20 points on the right), with a certain value between each point, preferably 1 to 3, for example 2.

[0055] In this invention, in step (3), the CE value of the chromatographic peak intensity closest to the threshold A can generally be obtained by taking the three CE values ​​of the chromatographic peak intensity closest to the threshold A from the chromatographic peak intensity-CE value curve, and then taking the median value of the three CE values ​​as the CE value of the chromatographic peak intensity closest to the threshold A.

[0056] In this invention, the biological sample or the biological sample to be tested may be pretreated in accordance with conventional practices in the art before detection.

[0057] The pretreatment method can be a conventional pretreatment method for biological samples in the art. For example, the pretreatment includes the following steps: sample extraction and derivatization.

[0058] The sample extraction method can be a conventional sample extraction method in the art, such as the following steps: adding a precipitant to the sample for precipitation, sonication, centrifugation, and extraction of the supernatant.

[0059] The derivatization process can be a conventional derivatization process in the art, for example, including the following steps: adding a derivatization reagent to a derivatization reaction buffer containing the biological sample, reacting for a certain time, centrifuging, and taking the supernatant.

[0060] The derivatization reaction buffer solution can be a solution conventional for derivatization reactions in the art, such as the derivatization reaction buffer solution described above.

[0061] The derivatizing reagent may be a conventional derivatizing reagent in the art, such as the derivatizing reagent used in the derivatization treatment of metabolite standard solutions as described above.

[0062] In this invention, the chromatographic tandem mass spectrometry method can be HPLC-MS / MS, UHPLC-MS / MS, or UPLC-MS / MS.

[0063] In this invention, the instrument used in the chromatographic tandem mass spectrometry method can be a conventional chromatographic tandem mass spectrometry system in the art, such as the Waters ACQUITY UPLC chromatographic tandem Xevo G2-XS QTOF mass spectrometry system (Waters, Milford, USA) or the Shimadzu Nexera UHPLC chromatographic system (Shimadzu, Columbia, MD) tandem AB Sciex 6500QTRAP triple quadrupole mass spectrometry system (AB Sciex, Foster City, CA).

[0064] In this invention, the chromatographic conditions for the chromatographic tandem mass spectrometry method can be conventional chromatographic conditions in the art.

[0065] The mobile phases used in the chromatography are preferably mobile phase A and mobile phase B, wherein mobile phase A is an aqueous solution containing 1.0% (volume percentage) formic acid and mobile phase B is an acetonitrile solution containing 1.0% (volume percentage) formic acid.

[0066] Preferably, the elution gradient of the chromatography is as follows:

[0067]

[0068]

[0069] The percentages mentioned above represent the volume percentage of mobile phase A or B relative to the total volume of "mobile phase A and mobile phase B".

[0070] As is known from common knowledge in this field, during gradient elution, the sum of the volume fractions of mobile phase A and mobile phase B is 100% at any given time.

[0071] The chromatographic injection volume can be a conventional chromatographic injection volume in the field, such as 2 μL.

[0072] The column temperature setting for chromatography can be a conventional column temperature in the field, such as 40°C.

[0073] The flow rate of the chromatographic mobile phase can be a conventional chromatographic mobile phase flow rate in the art, for example, 0.5 mL / min.

[0074] Preferably, the chromatographic column used is a Waters ACQUITY UPLC HSS T3 (2.1×100mm, 1.8μm).

[0075] Preferably, the chromatographic guard column is a Waters ACQUITY UPLC HSS T3 VanGuard Pre-Column (2.1mm × 5mm, 1.8μm).

[0076] In this invention, in step (4), the internal standard method can be a conventional internal standard method in the art.

[0077] In this invention, step (4) preferably includes the following steps:

[0078] A. Preparation of standard solutions:

[0079] Prepare an initial standard solution of a certain concentration using standards of the metabolites.

[0080] The initial standard solution is serially diluted n times to obtain n+1 groups of linear standard solutions with different concentrations. An appropriate amount of the corresponding isotope internal standard of the metabolite with known concentration is added to each solution to obtain n+1 groups of linear standard solutions containing internal standards, where n is an integer.

[0081] In the n+1 group of linear standard solutions containing internal standards, the concentration of the metabolite is denoted as C. li , where i is an integer, taking the value 1, 2, 3, ..., n+1;

[0082] B. Correction of isotope internal standard concentration:

[0083] B1. Calculation of the natural isotope interference ratio (R) of the metabolite: The initial standard solution was analyzed by multiple reaction monitoring (MRM) mode of a liquid chromatography-tandem mass spectrometry system, and the natural isotope interference ratio R of the metabolite was calculated as R = P. l+x / P l ;in,

[0084] P l+x The peak area of ​​the natural isotope of the metabolite in the standard solution;

[0085] P l The peak area of ​​the metabolite in the standard solution;

[0086] B2. Calculate the isotopic internal standard corrected concentration of metabolites (C H ):

[0087] The n+1 groups of linear standard solutions containing internal standards were analyzed by multiple reaction monitoring (MRM) of a liquid chromatography-tandem mass spectrometry (LC-MS) system, and the corrected concentration C of the isotopic internal standard for each metabolite in each group of linear standard solutions was calculated. Hi =C hi P Hi / (P Hi -RP li );

[0088] Where i is an integer, taking the value 1, 2, 3, ..., n+1;

[0089] C Hi To correct for the concentration of the internal standard isotope, i.e., the concentrations of the added internal standard isotope and the natural isotopes of the metabolites, C is obtained for the n+1 groups of linear standard solutions containing the internal standard using the above formula. H1 C H2 C H3 …,C Hn+1 The unit is μM;

[0090] C hi To determine the concentration of the corresponding isotopic internal standard for the added metabolite, C was obtained for each of the n+1 groups of linear standard solutions containing the internal standard. h1 C h2 C h3 …,C hn+1 The unit is μM;

[0091] P Hi To determine the peak areas of the added isotopic internal standard and the natural isotopes of the metabolites, P was obtained for each of the n+1 groups of linear standard solutions containing the internal standard. H1 ,P H2 ,P H3…,P Hn+1 ;

[0092] P li For the peak area of ​​the metabolite, P is obtained for each of the n+1 groups of linear standard solutions containing an internal standard. l1 ,P H2 ,P H3 …,P Hn+1 ;

[0093] C. Establish a standard curve:

[0094] The ratio P is the peak area of ​​the metabolite to that of the added isotopic internal standard and the natural isotope of the metabolite. li / P Hi The vertical axis represents the ratio C between the concentrations of metabolites and the corrected isotopic internal standard. li / C Hi Using the x-axis as the horizontal axis, construct a linear equation and plot a standard curve;

[0095] D. Calculate the concentration of metabolites in the biological sample: Based on the peak area of ​​metabolites in the biological sample to be tested, the peak area of ​​the added isotope internal standard and the natural isotope internal standard, and the isotope internal standard correction concentration, substitute them into the standard curve to calculate the concentration of each metabolite in the biological sample to be tested.

[0096] In step A, the linear standard solution is used to establish a standard curve, and the concentration of metabolites in the biological sample to be tested can be calculated from the standard curve in step C.

[0097] Preferably, in step A, the concentration of the metabolite in the initial standard solution is 2-500 mM. The concentration of the initial standard solution should not be too low, but should not exceed the upper limit of the instrument's detection capability, preferably the upper limit of the quantitative capability of the analytical method.

[0098] Preferably, in step A, when there are two or more metabolites, the standard solution can be a mixed standard solution containing each metabolite.

[0099] The acquisition parameters for the natural isotope peaks of metabolites are the same as those for the corresponding internal standards of metabolites.

[0100] Preferably, the initial standard solution, the linear standard solution, and the biological sample to be tested can be processed in accordance with conventional methods in the art before injection and detection, including derivatization or non-derivatization.

[0101] The derivatization method can be a conventional derivatization method in the art, such as the derivatization method described above.

[0102] Preferably, in step A, the dilution solvent used for gradient dilution can be a conventional solvent in the art, such as a 50% methanol aqueous solution containing 10mM Vc and 10mM EDTA.

[0103] Preferably, in step A, n is 13 for the n-times of gradient dilution, that is, the initial standard solution is diluted 13 times to obtain 14 sets of linear standard solutions.

[0104] Preferably, the gradient dilution method involves progressive dilution at a ratio of 1:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2.

[0105] Preferably, in step A, the corresponding isotopic internal standard of the added metabolite can be prepared from the initial standard solution.

[0106] For example, it can be prepared by diluting the initial standard solution by 1 time.

[0107] The method of configuration can be a conventional method used in the art for configuring internal standard solutions, such as: mixing a standard solution diluted by 1 time with a buffer solution, and then performing derivatization to obtain the internal standard solution to be added.

[0108] In step B, the R value is calculated using a standard solution without an internal standard. It is a constant that is only related to metabolites and not to the sample.

[0109] In step B, the composition of the internal standard includes two cases: one is that each metabolite has its corresponding natural isotope internal standard, and the other is that only some metabolites have their corresponding natural isotope internal standards, while the rest of the metabolites do not have natural isotope internal standards. In both cases, this method can be used to correct the concentration of the internal standard of the metabolites containing the internal standard.

[0110] When the R value calculated in step B is less than 0.004, or the number of atoms labeled with the internal standard is greater than 2, the interference from the natural isotopes of the metabolite can be ignored.

[0111] Preferably, Analyst 1.7 software can be used to collect data obtained during the testing process.

[0112] In step C, the linear equation can be constructed using software, such as data processing software corresponding to different brands of chromatography-tandem mass spectrometry instruments, or professional plotting software such as Excel.

[0113] Preferably, the software included with the chromatography-tandem mass spectrometry instrument (e.g., Sciex OS 1.7 and RStudio software) is selected to analyze the data, construct the linear equation, and calculate the concentration of metabolites in the biological sample to be tested, thus simplifying the analysis steps.

[0114] Preferably, the calculation processes involved in steps B-D can all be performed in batches using code written in the R language.

[0115] This invention also provides an absolute quantitative analysis method for metabolites in biological samples based on eliminating interference from natural isotopes in metabolites, which includes the following steps:

[0116] A. Preparation of standard solutions:

[0117] Prepare an initial standard solution of a certain concentration using standards of the metabolites.

[0118] The initial standard solution was serially diluted n times to obtain n+1 groups of linear standard solutions with different concentrations. An appropriate amount of the corresponding isotope internal standard of the metabolite with known concentration was added to each solution to obtain n+1 groups of linear standard solutions containing internal standards (where n is an integer).

[0119] In the n+1 group of linear standard solutions containing internal standards, the concentration of the metabolite is denoted as C. li , where i is an integer, taking the value 1, 2, 3, ..., n+1;

[0120] B. Correction of isotope internal standard concentration:

[0121] B1. Calculation of the natural isotope interference ratio (R) of the metabolite: The initial standard solution was analyzed by multiple reaction monitoring (MRM) mode of a liquid chromatography-tandem mass spectrometry system, and the natural isotope interference ratio R of the metabolite was calculated as R = P. l+x / P l ;in,

[0122] P l+x The peak area of ​​the natural isotope of the metabolite in the standard solution;

[0123] P l The peak area of ​​the metabolite in the standard solution;

[0124] B2. Calculate the isotopic internal standard corrected concentration of metabolites (C H ):

[0125] The n+1 groups of linear standard solutions containing internal standards were analyzed by multiple reaction monitoring (MRM) of a liquid chromatography-tandem mass spectrometry (LC-MS) system, and the corrected concentration C of the isotopic internal standard for each metabolite in each group of linear standard solutions was calculated. Hi =C hi P Hi / (P Hi -RP li );

[0126] Where i is an integer, taking the value 1, 2, 3, ..., n+1;

[0127] C Hi To correct for the concentration of the internal standard isotope, i.e., the concentrations of the added internal standard isotope and the natural isotopes of the metabolites, C is obtained for the n+1 groups of linear standard solutions containing the internal standard using the above formula. H1 C H2 C H3 …,C Hn+1 The unit is μM;

[0128] C hi To determine the concentration of the corresponding isotopic internal standard for the added metabolite, C was obtained for each of the n+1 groups of linear standard solutions containing the internal standard. h1 C h2 C h3 …,C hn+1 The unit is μM;

[0129] P Hi To determine the peak areas of the added isotopic internal standard and the natural isotopes of the metabolites, P was obtained for each of the n+1 groups of linear standard solutions containing the internal standard. H1 ,P H2 ,P H3 …,P Hn+1 ;

[0130] P li For the peak area of ​​the metabolite, P is obtained for each of the n+1 groups of linear standard solutions containing an internal standard. l1 ,P H2 ,P H3 …,P Hn+1 ;

[0131] C. Establish a standard curve:

[0132] The ratio P is the peak area of ​​the metabolite to that of the added isotopic internal standard and the natural isotope of the metabolite. li / P Hi The vertical axis represents the ratio C between the concentrations of metabolites and the corrected isotopic internal standard. li / C Hi Using the x-axis as the horizontal axis, construct a linear equation and plot a standard curve;

[0133] D. Calculate the concentration of metabolites in the biological sample: Based on the peak area of ​​metabolites in the biological sample to be tested, the peak area of ​​the added isotope internal standard and the natural isotope internal standard, and the isotope internal standard correction concentration, substitute them into the standard curve to calculate the concentration of each metabolite in the biological sample to be tested.

[0134] In this invention, in step A, the linear standard solution is used to establish a subsequent standard curve, and the concentration of metabolites in the biological sample to be tested can be calculated from the standard curve in step C.

[0135] In this invention, preferably, in step A, the concentration of metabolites in the initial standard solution is 2-500 mM.

[0136] In this invention, preferably, in step A, when there are two or more metabolites, the standard solution can be a mixed standard solution containing each metabolite.

[0137] In this invention, preferably, in step A, the concentration of the initial standard solution should not be too low, but should not exceed the upper limit of the instrument's detection capacity, and more preferably the upper limit of the quantitative capacity of the analytical method.

[0138] In this invention, the acquisition parameters for the natural isotope peaks of metabolites are the same as those for the internal standards corresponding to the metabolites.

[0139] In this invention, preferably, the initial standard solution, the linear standard solution, and the biological sample to be tested can be processed in accordance with conventional methods in the art before injection and detection, including derivatization or non-derivatization.

[0140] The derivatization method can be a conventional derivatization method in the art, such as the derivatization method described above.

[0141] In this invention, preferably, in step A, the dilution solvent used for gradient dilution can be a conventional solvent in the art, such as a 50% methanol aqueous solution containing 10mM Vc and 10mM EDTA.

[0142] In this invention, preferably, in step A, n is 13 for the n-times of gradient dilution, that is, the initial standard solution is diluted 13 times to obtain 14 sets of linear standard solutions.

[0143] Preferably, the gradient dilution method involves progressive dilution at a ratio of 1:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2.

[0144] In this invention, preferably, in step A, the corresponding isotopic internal standard of the added metabolite can be prepared from the initial standard solution.

[0145] For example, it can be prepared by diluting the initial standard solution by 1 time.

[0146] The method of configuration can be a conventional method used in the art for configuring internal standard solutions, such as: mixing a standard solution diluted by 1 time with a buffer solution, and then performing derivatization to obtain the internal standard solution to be added.

[0147] In this invention, in step B, the R value is calculated using a standard solution without an internal standard. It is a constant that is only related to metabolites and not to the sample.

[0148] In this invention, in step B, the composition of the internal standard includes two cases: one is that each metabolite has its corresponding natural isotope internal standard, and the other is that only some metabolites have their corresponding natural isotope internal standards, while the remaining metabolites do not have natural isotope internal standards. In both cases, this method can be used to correct the concentration of the internal standard of the metabolites containing the internal standard.

[0149] In this invention, when the R value calculated in step B is less than 0.004, or the number of atoms marked by the internal standard is greater than 2, the interference of the natural isotopes of the metabolite can be ignored.

[0150] In this invention, preferably, Analyst 1.7 software can be used to collect the data obtained from the detection.

[0151] In this invention, in step C, the linear equation can be constructed using software. For example, the software can be data processing software corresponding to different brands of chromatography-tandem mass spectrometry instruments, or professional plotting software such as Excel.

[0152] Preferably, the software included with the chromatography-tandem mass spectrometry instrument (e.g., Sciex OS 1.7 and RStudio software) is selected to analyze the data, construct the linear equation, and calculate the concentration of metabolites in the biological sample to be tested, thus simplifying the analysis steps.

[0153] In this invention, preferably, the calculation processes involved in steps B-D can all be performed in batches using code written in the R language.

[0154] Based on common knowledge in the field, the above-mentioned preferred conditions can be combined arbitrarily to obtain various preferred embodiments of the present invention.

[0155] The reagents and raw materials used in this invention are all commercially available.

[0156] The positive and progressive effects of this invention are as follows:

[0157] 1. The present invention provides a method for the simultaneous quantitative detection of multiple metabolites in biological samples. By finely optimizing the mass spectrometry detection parameters (collision energy CE) of each metabolite, the sensitivity of metabolites is suppressed, thereby solving the problem of detector signal saturation caused by high concentrations of metabolites. It also eliminates the need for multiple sample dilutions, enabling simultaneous quantitative analysis of low- and high-concentration metabolites, increasing the throughput of the method (up to 120 or more metabolites can be analyzed), and simplifying the sample analysis steps. This invention solves the problem of difficulty in simultaneously detecting multiple metabolites in the same sample due to large differences in metabolite concentrations.

[0158] 2. Furthermore, the present invention can also detect multiple metabolites in 3-4 types of biological samples.

[0159] 3. To address the interference problem caused by natural isotopes, this invention further provides an isotope internal standard concentration correction (IIC) strategy. This eliminates the interference of natural isotopes in metabolites on the quantification of the internal standard, significantly increasing the linear range for metabolite quantification and expanding the application scope of the analytical method. While ensuring that the concentrations of all metabolites in different samples are within the linear range of the established method, it also solves the problem of incompatibility between analytical software often found in existing technologies, increasing the method's versatility and enabling absolute quantitative analysis of multiple metabolites in biological samples.

[0160] 4. The detection method of the present invention has high throughput and accuracy, simple operation steps, high experimental reproducibility and operability, and can be applied to clinical pathophysiological research and biomarker discovery. Attached Figure Description

[0161] Figure 1 This is the absolute quantitative analysis procedure for metabolites in biological samples in Example 1 of the present invention.

[0162] Figure 2 The diagram shows the CE value optimization method in step (5) of Embodiment 1 of the present invention (classification of metabolites and obtaining the chromatographic peak intensity-CE value change diagram of metabolites), wherein the chromatographic peak intensity threshold A is represented by a dashed line and the ideal CE value is marked with an asterisk.

[0163] Figure 3 To obtain the peak height-collision energy diagram corresponding to the optimal CE value of the second type of metabolite 1-methyl-histidine in step (5) of Example 1 before optimizing the CE value.

[0164] Figure 4A The peak height as a function of CE value is obtained when optimizing the CE value of the second type of metabolite 1-methyl-histidine in step (5) of Example 1 (serum sample).

[0165] Figure 4BThe peak height as a function of CE value obtained when optimizing the CE value of the second type of metabolite 1-methyl-histidine in step (5) of Example 1 (tissue sample).

[0166] Figure 4C The peak height as a function of CE value obtained when optimizing the CE value of the second type of metabolite 1-methyl-histidine in step (5) of Example 1 (urine sample).

[0167] Figure 5A The peak height as a function of CE value is obtained when optimizing the CE value of the third type of metabolite, ethanolamine phosphate, in step (5) of Example 1 (urine sample).

[0168] Figure 5B The peak height as a function of CE value is obtained when optimizing the CE value of the third type of metabolite, ethanolamine phosphate, in step (5) of Example 1 (tissue sample).

[0169] Figure 6A Linear curves constructed using the conventional method (uncorrected) and a schematic diagram of the construction.

[0170] Figure 6B The linear curve constructed by the method of the present invention and a schematic diagram thereof.

[0171] Figure 7 This is the calibration effect of the amino quantitative linear curve of the present invention.

[0172] Figure 8 The linear curve for isotope interference correction obtained by the method in Comparative Example 1 is shown.

[0173] Figure 9 This is a schematic diagram of the correction method for Comparative Example 2. Detailed Implementation

[0174] The present invention will be further illustrated by way of embodiments below, but the present invention is not limited to the scope of the embodiments described herein.

[0175] Example 1

[0176] A high-throughput absolute quantification method for metabolites in biological samples was developed, employing N-butylated isotope labeling for the absolute quantitative analysis of amino acid metabolites in four biological samples (urine, serum, liver tissue, and cells).

[0177] I. Experimental Materials and Instruments

[0178] Experimental materials: 120 standard amino metabolites, creatinine (99%), indole-3-acetic acid (98%), 5-hydroxyindoleacetic acid (98%), 5-aminoisoquinoline (98.5%), N,N'-succinimidyl carbonate (98%) were purchased from Sigma-Aldrich Co., LLC (St. Louis, Missouri, USA), J&K Scientific Ltd. (Beijing, China), TCI Chemical Industry Development Co., Ltd. (Shanghai, China) and Aladdin Chemical Reagent Co., Ltd. (Shanghai, China), respectively. Sodium cyanoborohydride (NaBH3CN, 95%), acetaldehyde (≥99%), propionaldehyde (≥98%), butyraldehyde (≥99%), valeraldehyde (≥97%), hexanal (≥98%), formic acid (FA, ≥96%), acetonitrile (ACN, ≥99.9%), methyl tert-butyl ether (MTBE, ≥99.8%), L-ascorbic acid (Vc, ≥99.0%), tris(2-carboxyethyl)phosphine hydrochloride (TCEP, ≥98%), ethylenediaminetetraacetic acid (EDTA, ≥99%) and 2,6-di-tert-butyl-p-cresol (BHT, ≥99.0%) were all purchased from Sigma-Aldrich (St. Louis, Missouri, USA). Methanol (MeOH, ≥99.9%) was purchased from Thermo Fisher Scientific Co., Ltd. (Shanghai, China). Tryptophan-2,3,3-d3 (98%), indole-3-acetic acid-2,2-d2 (98%), 5-hydroxyindoleacetic acid-2,2-d2 (98%), 5-hydroxytryptophan-4,6,7-d3 (99%), sodium cyanoborodeuteride (NaBD3CN, 97%) were purchased from C / D / N Isotopes Inc. (Canada) and Cambridge Isotope Laboratories, Inc. (Andover, Massachusetts, USA). Potassium dihydrogen phosphate (KH2PO4, 99.8%) and disodium hydrogen phosphate (Na2HPO4, ≥99.5%) were purchased from Aladdin Chemical Reagent Co., Ltd. (Shanghai, China). Ultra-pure water was prepared using a Milli-Q instrument (Merck Millipore, Germany).

[0179] Human serum and urine samples were obtained by mixing 15 normal adult samples. The cell sample was K562 mammalian cells from the China Center for Type Culture Collection. The liver samples were selected from healthy male New Zealand rabbits provided by Songlian Laboratory Animal Farm in Songjiang District, Shanghai [Animal License No.: SYXK (Shanghai) 2017-0008]. The rat liver samples included 24 SPF-grade male Sprague-Dawley rats (6 weeks old, body weight 177.8 ± 18.6 g) from the Animal Experiment Center of Wuhan University (Wuhan, China).

[0180] Experimental Instruments: Small instruments used in the experiment included a Labstar thermostatic mixer (MHR23), a Thermo Fisher Scientific low-temperature high-speed centrifuge (Thermo X1R), a dry nitrogen blower (MD200-2A), a snow ice maker (IMS-70), a QIAGENTissueLyser II tissue homogenizer, an ultrasonic cleaner (Kunshan Shumei KQ-200VDE), a Mettler Toledo analytical balance (ME104), and a SevenCompact benchtop pH meter. Large instruments included a Waters ACQUITY UPLC tandem Xevo G2-XS QTOF mass spectrometry system (Waters, Milford, USA), a Shimadzu Nexera UHPLC tandem AB Sciex 6500QTRAP triple quadrupole mass spectrometry system (AB Sciex, Foster City, CA), and Waters ACQUITY UPLC HSS columns. T3 (2.1×100mm, 1.8μm), with a Waters ACQUITY UPLCHSS T3 VanGuard Pre-Column (2.1mm×5mm, 1.8μm).

[0181] II. Chromatographic and Mass Spectrometry Conditions

[0182] Chromatographic conditions: The mobile phase consisted of an ultrapure aqueous solution (A) containing 1.0% (v / v) formic acid and an acetonitrile solution (B) containing 1.0% (v / v) formic acid. The elution gradient was as follows: 0-1 min 1% B, 1-2 min 1-9.1% B, 2-4 min 9.1-22% B, 4-8 min 22-25% B, 8-9 min 25-60% B, 9-9.5 min 60% B, 9.5-9.5 1 min 60-80% B, 9.5 1-11 min 80-89% B, 11-11.1 min 89-95% B, 11.1-13 min 95% B, 13-13.1 min 95-1% B, 13.1-17 min 1% B. The injection volume was set to 2 μL, the column temperature to 40℃, and the flow rate to 0.5 mL / min.

[0183] Mass spectrometry conditions: The mass spectrometry detection time window was set to 0.5 min–13 min. The ion source was selected as electrospray ionization (ESI), positive ion mode, and multiple reaction monitoring (MRM) mode. The precursor and daughter ion parameters of the metabolites and their corresponding internal standards are detailed in Table 1. The ion source parameters were: curtain gas 40 psi, collision gas Medium, ionization voltage 5.5 kV, ion source temperature 400 °C, spray gas 55 psi, auxiliary heating gas 60 psi, inlet potential and collision unit outlet potential both set to 10 V. The chromatographic retention time, ion pair monitoring window, collision energy (CE), and declustering voltage (DP) parameters are detailed in Table 1. (The selection of precursor and daughter ions and parameter optimization for each metabolite are described below).

[0184] Table 1 Mass spectrometry detection parameters of metabolites

[0185]

[0186]

[0187]

[0188]

[0189]

[0190]

[0191]

[0192] III. Experimental Procedure

[0193] The analytical procedure for metabolites in biological samples is as follows: Figure 1 As shown, internal standards, serially diluted standards, and biological samples were first prepared. Then, equal amounts of internal standard were added to the standards and biological samples, and the samples were analyzed using liquid chromatography-tandem mass spectrometry. By optimizing the CE value, simultaneous detection of multiple metabolites was achieved. Furthermore, by correcting for isotopic interference, a corrected linear curve (the ratio of the peak area of ​​the metabolite to the peak area of ​​the added isotopic internal standard and the natural isotope of the metabolite, P) was obtained. li / P Hi The vertical axis represents the ratio C between the concentrations of metabolites and the corrected isotopic internal standard. li / C Hi (where x is the horizontal axis), and based on the corrected linear curve, the concentration of metabolites in the sample to be tested is finally obtained, as detailed below.

[0194] (1) Preparation of standards: Accurately weigh 120 metabolite standards and creatinine standards using an analytical balance. Add appropriate solvents (containing 10 mM vitamin C and 10 mM EDTA) according to the solubility of the metabolites to prepare single standard solutions with concentrations of 2-500 mM. According to experimental requirements, mix the 121 metabolite standards into mixed standard solutions of different concentrations (as shown in Table 2). Then, use 50% methanol aqueous solution (containing 10 mM vitamin C and 10 mM EDTA) to dilute the mixed standards stepwise in a ratio of 1:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2 to prepare 14 different concentration diluents (L01 is the highest point (i.e., the original mixed standard solution, undiluted), and L14 is the lowest point (i.e., the last diluted solution)). Store the single standards, mixed standards and their diluents in a -20℃ refrigerator for later use. If not used for a long time, they should be stored in a -80℃ refrigerator.

[0195] Table 2 shows the concentration of each metabolite in the mixed standard solution (L01).

[0196]

[0197]

[0198]

[0199]

[0200] (2) Preparation of labeled reaction reagents:

[0201] Preparation of derivatization reaction buffer: Accurately weigh 1.3 g KH₂PO₄ powder (136.09 g / mol), 0.9 g Na₂HPO₄ powder (141.96 g / mol), 0.14 g Vc (176.12 g / mol), 0.3 g EDTA (372.24 g / mol), and 0.458 g TCEP (286.65 g / mol) into a 50 mL blue-capped bottle using an analytical balance. Add 40 mL of ultrapure water, vortex for 30 s, and sonicate for 5 min to obtain 40 mL of phosphate buffer solution (0.4 M, pH approximately 5.8). Store this solution at 4°C. When using, dilute with an equal volume of methanol by half as the derivatization reaction buffer.

[0202] Preparation of derivatization reagent: Accurately weigh NaBH3CN or NaBD3CN powder into an EP tube using an analytical balance, add an appropriate amount of methanol solution (pure methanol), and prepare a 2M derivatization reagent. This process must be prepared and used immediately and carried out in a fume hood to prevent the release of toxic HCN gas during reagent deliquescence. Butyraldehyde reagent does not require preparation and can be used directly.

[0203] (3) Biological sample extraction:

[0204] a. Urine extraction: Accurately pipette 10 μL of urine into a 1.5 mL ep tube, add 40 μL of pre-cooled methanol solution (containing 10 mM BHT), vortex mix for 30 s, place in a -20 ℃ freezer for about 1 h, centrifuge in a low-temperature high-speed centrifuge (4 ℃, 14000 g) for 10 min, accurately pipette 25 μL of supernatant, evaporate to dryness with nitrogen, and store in a -20 ℃ freezer before labeling reaction;

[0205] b. Serum extraction: Accurately pipette 20 μL of serum into a 1.5 mL EP tube, add 225 μL of pre-cooled methanol solution (containing 10 mM BHT), vortex mix for 30 s, place in a -20℃ freezer for about 1 h, centrifuge in a low-temperature high-speed centrifuge (4℃, 14000g) for 10 min, accurately pipette 200 μL of supernatant into a 1.5 mL EP tube, add 750 μL of pre-cooled MTBE solution (containing 10 mM BHT), vortex mix for 30 s, add 168 μL of pre-cooled ultrapure water at 4℃, vortex mix again for 30 s, centrifuge in a low-temperature high-speed centrifuge (4℃, 14000g) for 5 min, obvious solution stratification can be observed, then use a pipette to separate the upper liquid by bubbling, take about 230 μL of the lower liquid into a 1.5 mL EP tube, evaporate to dryness by nitrogen, and store in a -20℃ freezer before labeling reaction;

[0206] c. Tissue Extraction: Weigh approximately 10 mg of rabbit or rat liver tissue into a 2 mL EP tube, add 400 μL of pre-cooled 80% methanol solution (containing 10 mM BHT) and one grinding bead, and place in a tissue homogenizer (20 Hz, 60 s) for three homogenizations. Then transfer to an ultrasonic cleaner and sonicate at low temperature for 10 min (with a 1 min pause). Centrifuge in a low-temperature high-speed centrifuge (4℃, 14000 g) for 10 min. Take 200 μL of the supernatant into a 1.5 mL EP tube, add 65 μL of pre-cooled methanol (containing 10 mM BHT) and 750 μL of MTBE (containing 10 mM BHT), vortex for 30 s, and then add 148 μL of [unclear - possibly a specific solution or preparation]. Ultrapure water pre-cooled at 4℃ was vortexed again for 30 seconds and centrifuged in a low-temperature high-speed centrifuge (4℃, 14000g) for 5 minutes. A clear solution stratification phenomenon could be observed. The upper liquid was then isolated by bubbling with a pipette, and about 230 μL of the lower liquid was taken into a 1.5 mL ep tube, evaporated to dryness by nitrogen, and stored in a -20℃ refrigerator before the labeling reaction.

[0207] d. Cell extraction: K562 mammalian cells were cultured in IMDM medium supplemented with 10% fetal bovine serum and collected at a density of approximately 3.0 × 10⁶ cells / mL (7 mL). Approximately 5 mg of wet K562 cells were weighed into a 2 mL ep tube, and 400 μL of pre-cooled 80% methanol solution (containing 10 mM BHT) was added. After vortexing for 30 s, the sample was subjected to five freeze-thaw cycles with liquid nitrogen and warm water, and then transferred to an ultrasonic cleaner for low-temperature sonication for 10 min (with a 1 min stop). After settling on ice for 30 min, the sample was centrifuged in a low-temperature high-speed centrifuge (4 °C, 14000 g) for 10 min. 350 μL of the supernatant was collected into a 1.5 mL ep tube. The extraction was repeated twice, and the supernatants were combined and evaporated to dryness with nitrogen. The sample was stored at -20 °C before the labeling reaction.

[0208] (4) Sample derivatization:

[0209] a. Preparation of internal standard: Take 80 μL of standard solution (L02) into a 1.5 mL ep tube, add 560 μL of phosphate buffer (i.e., the derivatization reaction buffer prepared as before), vortex mix for 1 min, then add 80 μL of NaBD3CN methanol solution (i.e., the derivatization reagent prepared as before), vortex mix for 1 min, add 80 μL of butyraldehyde, and place in a constant temperature mixer at 25℃ for 2 h (900 rpm). After the reaction is completed, add 16 μL of FA to quench the reaction, vortex mix for 5 min, and place in a low temperature high speed centrifuge (4℃, 14000g) for 10 min. Take 700 μL of the supernatant into a 1.5 mL ep tube. Before use, it should be stored in a -20℃ refrigerator to prepare the derivatized internal standard solution L02.

[0210] b. Preparation of linear standard solutions: Take 10 μL of standard solutions (L01-L14) into a 1.5 mL ep tube, add 70 μL of phosphate buffer (i.e., the derivatization reaction buffer prepared as before), vortex mix for 1 min, then add 10 μL of NaBH3CN (i.e., the derivatization reagent prepared as before), vortex mix for 1 min, add 10 μL of butyraldehyde, and place in a constant temperature mixer at 25℃ for 2 h (900 rpm). After the reaction is completed, add 2 μL of FA to quench the reaction, vortex mix for 5 min, and place in a low temperature high speed centrifuge (4℃, 14000g) for 10 min. Take 50 μL of the supernatant and add 5 μL of the derivatized internal standard solution L02, vortex mix for 30 s, and transfer to a 2 mL chromatographic bottle containing a 150 μL inner liner tube for the establishment of the linear curve of the subsequent method.

[0211] In addition, 30 μL of supernatant was taken from the remaining L01 sample (i.e., the L01 sample that was derivatized but without internal standard) and transferred to a 2 mL chromatographic vial containing a 150 μL inner liner, which was used as a sample for calculating the abundance (R) of natural isotopes (sample name "d").

[0212] All samples must be stored at -20°C before instrument analysis for later use.

[0213] c. Sample Preparation: Take the biological sample and evaporate it to dryness. Add 80 μL of phosphate buffer and vortex for 1 min. Then add 10 μL of NaBH3CN and vortex for 1 min. Add 10 μL of butyraldehyde and react at 25°C (900 rpm) for 2 h in a constant temperature mixer. After the reaction, add 2 μL of FA to quench the reaction and vortex for 5 min. Centrifuge at 4°C (14000g) for 10 min. Take 50 μL of the supernatant and add 5 μL of derivatized internal standard solution L02. Vortex for 30 s and transfer to a 2 mL chromatographic vial with a 150 μL liner. Liver, serum, and urine samples are used for subsequent CE value optimization. Liver, serum, urine, and cell samples are used for absolute quantitative analysis of metabolite concentrations. All samples should be stored at -20°C before instrument analysis.

[0214] (5) Steps for optimizing CE value

[0215] a. Optimize mass spectrometry detection parameters, the steps are as follows:

[0216] To determine the characteristic ion pairs for each metabolite: First, derivatize the amino metabolite standard. Then, using direct mass spectrometry injection, determine the mass-to-charge ratio of the parent ion in parent ion scanning mode to identify the corresponding parent ion of the metabolite, ensuring its response is between 1e5 and 1e7. Next, fix the parent ion and use daughter ion scanning, selecting various collision energies (typically 15, 25, and 35) to break the parent ion into fragments. Multiple daughter ion fragments can be observed, and the daughter ion with the strongest response is selected as the characteristic daughter ion of the metabolite. After optimizing the CE and DP values, select the parent ion and daughter ion with the highest detection sensitivity. Finally, construct multiple reaction monitoring (MRM) ion pairs based on the selected parent ion and daughter ion.

[0217] Optimize mass spectrometry parameters: Optimize the CE values ​​of the previously selected characteristic ion pairs by measuring the response of metabolite standards under different CE value detection conditions (10–50). The CE value with the highest response is taken as the optimal CE value for the metabolite (i.e., the CE value before optimization in Table 1). See Table 1 for details. Figure 3 Optimization diagram of CE value for 1-methyl-histidine standard.

[0218] Sample detection: Derivatized urine, serum and tissue samples were detected by chromatography-tandem mass spectrometry using optimized mass spectrometry parameters (optimal CE value). Specific chromatography-mass spectrometry detection conditions have been given above. The chromatographic peak heights of each metabolite in the three samples were obtained.

[0219] b. Classify metabolites according to their peak height. See [link to relevant documentation] Figure 2 Since the upper limit of detection for the mass spectrometer used is 2E7, the CE value was optimized. A peak height higher than 1E6 was used as the standard for judging a compound as a high-concentration compound. That is, 0.05 times the upper limit of detection of the mass spectrometer was used as the threshold, and each metabolite was classified according to its peak height.

[0220] Class I metabolites are low-concentration metabolites, which are metabolites whose chromatographic peak intensity is lower than or equal to threshold A.

[0221] The second category of metabolites are high-concentration metabolites, which are metabolites whose chromatographic peak intensity is higher than the threshold A.

[0222] The third category of metabolites refers to metabolites with chromatographic peak intensities below or equal to threshold A in some samples, i.e., low-concentration metabolites; and metabolites with chromatographic peak intensities above threshold A in other samples, i.e., high-concentration metabolites.

[0223] c. Optimize or determine the final CE value for different metabolites:

[0224] For Class I metabolites, the CE value detected by mass spectrometry is not optimized, and the optimal CE value is still used as the final CE value.

[0225] For the second type of metabolite, the CE value is optimized. The optimization method is as follows: the same metabolite in the biological sample is detected with different CE values ​​to obtain the chromatographic peak intensity-CE value change graph. The different CE values ​​are obtained by taking 10 points to the left of the optimal CE value and 20 points to the right of the optimal CE value. Each point is separated from the CE value by a value of 2. The CE value with the chromatographic peak intensity closest to the threshold A is taken as the final CE value.

[0226] For the third type of metabolites, two sets of ion pairs were set up. One set used the optimal CE value (ion pair 1) to detect biological samples with low levels of this type of metabolite. The other set used optimized CE values ​​(ion pair 2), with the optimization method being the same as for the second type of metabolites. That is, an optimized CE value was obtained for each type of biological sample, and then the median value was taken as the final CE value for the metabolite. By optimizing the CE value, the chromatographic peak intensity of the metabolite was ensured to not exceed 0.5 times the upper limit of the mass spectrometry detection intensity, thus suppressing the sensitivity of this type of metabolite and ensuring accurate quantification of samples with high levels of this type of metabolite.

[0227] The CE values ​​of each metabolite before and after optimization are shown in Table 1. Metabolites without optimized CE values ​​in Table 1 are classified as Class I metabolites, those with optimized CE values ​​are classified as Class II metabolites, and those with two ion pairs are classified as Class III metabolites.

[0228] For the first type of metabolite, taking (±)-norepinephrine as an example:

[0229] The peak heights of this metabolite in serum, tissue and urine samples were detected using the pre-optimized CE value (23) as 2.69E+03, 2.74E+04 and 1.70E+05, respectively, all of which were lower than 1E6. Therefore, (±)-norepinephrine was classified as a Class I metabolite, and thus there was no need to optimize the detection CE value of (±)-norepinephrine, i.e., the optimal CE value was maintained.

[0230] For the second type of metabolite, taking 1-methyl-histidine as an example:

[0231] First, using the pre-optimization CE value (24) in Table 1, the peak heights of this metabolite in serum, tissue, and urine samples were detected to be 1.34E+07, 4.69E+07, and 1.07E+08, respectively, all higher than 1E6. Therefore, 1-methyl-histidine was classified as a Class II metabolite. Then, different CE values ​​(starting from 24, 10 points on the left and 20 points on the right, with a value interval of 2) were used to perform multiple tests on the same sample, and a peak height variation graph with CE value was plotted (see Table 1). Figure 4A , Figure 4B , Figure 4C Then, for each type of sample (urine, serum, tissue), there is a CE value with the peak height closest to 1E6 (the figure shows the three CE values ​​closest to 1E6 for each sample). The CE values ​​of the three types of samples are compared, and the CE value in the middle is selected as the final CE value after method optimization (45). The peak heights of serum, tissue and urine samples are 3.52E+05, 9.69E+05 and 9.98E+06, respectively, so that the peak height of the sample with the highest metabolite concentration does not exceed 0.5 times the upper limit of mass spectrometry detection, so as to ensure that accurate quantitative results can still be obtained for each type of sample by this method while reducing the peak height.

[0232] For the third type of metabolites, taking ethanolamine phosphate as an example:

[0233] First, using the pre-optimization CE value (23) of ethanolamine phosphate in Table 1, the peak heights of this metabolite in serum, tissue, and urine samples were detected to be 5.66E+05, 1.05E+08, and 7.18E+07, respectively. The peak height in serum was below 1E6, indicating a low-concentration metabolite, while the peak heights in tissue and urine samples were above 1E6, indicating a high-concentration metabolite. Therefore, ethanolamine phosphate was classified as a Class III metabolite. At this point, the CE values ​​of tissue and urine samples needed to be optimized. Multiple tests were performed on the same sample using different CE values ​​(starting from 23, with 10 points on the left and 20 points on the right, with a value interval of 2 between each point). A peak height variation graph was plotted as the CE value changed (see [reference]). Figure 5A , Figure 5B For each biological sample in the figure, three CE values ​​close to 1E6 were taken (all marked in the figure; the three CE values ​​for tissue samples are 7, 43, and 45, and the three CE values ​​for urine samples are 49, 51, and 53), for a total of six CE values. The peak heights of the two samples were tested in ascending order, starting with the smallest value of 7. The peak heights for tissue and urine samples were 1.51E+07 and 8.37E+05, respectively. Since the chromatographic peak intensity of the metabolite in the former exceeded 0.5 times the upper limit of mass spectrometry detection intensity, the peak heights of the two samples were tested using 43. The peak heights for tissue and urine samples were 8.06E+06 and 1.18E+06, respectively. The chromatographic peak intensity of the metabolites in both samples was below 0.5 times the upper limit of mass spectrometry detection intensity. Therefore, 43 was selected as the optimized CE value for the detection of tissue and urine (ion pair: ethanolamine phosphate 2), and 23 was selected as the unoptimized CE value for the detection of serum (ion pair: ethanolamine phosphate 1).

[0234] (6) Data acquisition and processing:

[0235] Data Acquisition: The following samples were injected for UPLC-MS / MS analysis. The chromatographic and mass spectrometric detection conditions have been given previously. One standard solution sample without internal standard (i.e., sample "d" prepared in the linearization preparation step, derivatized but without internal standard) was used to calculate the abundance (R) of the natural isotope (i.e., the interference ratio R). Fourteen graded-dilution standard solutions containing internal standard (i.e., standard solutions L01-L14 prepared in the linearization preparation step) were used to plot the linear curve. Several biological samples to be analyzed (i.e., liver, serum, urine, and cell samples prepared in the sample preparation step) and a quality control sample (QC) (prepared by mixing all biological samples in equal volumes to test instrument stability) were also included. Analyst 1.7 software was used for data acquisition.

[0236] Data processing: The data processing software includes Sciex OS 1.7 and RStudio. The processing workflow is as follows:

[0237] 1) Import the raw data (i.e., data collected through Analyst 1.7 software) into the Sciex OS 1.7 Analytics module. When using the software, you need to create a new result table in the software as usual and establish a data processing method with the standard (L01 sample) to batch process the raw data and obtain the peak area data required for subsequent analysis.

[0238] 2) After batch processing the data (all sample data) using the software in the previous step, manually check whether the chromatographic peak retention times and integrals of metabolites in each sample are correct. After confirming that there are no errors, export the raw data as "oridata.csv" and delete the data of compounds without internal standards. The exported result table must include index, sample name, sample type, compound name, compound type, and peak area. See Table 3 for an example data format of the result table.

[0239] Table 3 Example Data Format

[0240]

[0241] 3) Calculate the natural isotopic interference ratio R (R = P) for each metabolite using standard solution samples without internal standards (samples "d" in Table 3) in Excel or RStudio. l+x / P l The peak area of ​​the quantitative ion pair is P l The peak area of ​​the internal standard ion pair is P. l+x This only needs to be calculated once, and the R value for each metabolite remains constant if the method is not changed thereafter.

[0242] 4) Using all standards containing internal standards (each standard solution in the linear preparation step) and the biological sample to be tested, in Excel or RStudio, according to formula C... H =C h P H / (P H -RP l ) Calculate the corrected isotope internal standard concentration (C) of the compound. H ), where the true concentration of the internal standard (i.e., the concentration of the added internal standard) is C. h The peak area of ​​the quantitative ion pair of the metabolite is P. l The peak area of ​​the internal standard ion pair (the peak area of ​​the added internal standard + the peak area of ​​the natural isotope) is P. H R is calculated from step 3) above;

[0243] 5) Re-import the data after correcting for the internal standard concentration into the results table of Sciex OS 1.7. In the internal standard concentration column, use the peak area ratio (P0) of the metabolite and its isotopic internal standard in the linear standard solution. l / P H ) and concentration ratio (C l / C H Construct a linear equation and plot a standard curve; based on the standard curve, calculate the corrected true concentration of the sample according to the peak area of ​​metabolites in the sample, the peak area of ​​the isotope internal standard, and the correction concentration of the isotope internal standard.

[0244] Comparison of the correction method of the present invention with conventional methods:

[0245] Using conventional methods: the internal standard concentration was not corrected. A linear curve was directly constructed using the measured internal standard peak area ratio (ordinate) and the peak area ratio (x-axis) and concentration ratio (horizontal axis) of the standard solution and the internal standard. The linear fitting coefficient R before correction was also obtained. 2 .like Figure 6A As shown, Figure 6A C in A The concentration of the added isotope internal standard (uncorrected), P A Peak area of ​​isotope internal standard, C l For the concentration of metabolites, P l This represents the peak area of ​​the metabolite.

[0246] The correction method employed was to establish a linear curve using the ratio of the peak areas of the standard solution and the internal standard (ordinate) and the ratio of the concentration of the standard solution to the correction concentration of the internal standard (bb) to obtain the corrected linear fitting coefficient R. 2 .

[0247] The linear curves obtained by the conventional method and the correction method of this invention are respectively as follows: Figure 6A and Figure 6B As shown. Among them, Figure 6B In this context, l+1 and l+2 refer to the first two interfering substances with relatively obvious distribution of natural isotopes detected by mass spectrometry, whose mass differs from the internal standard by only 1 or 2.

[0248] (7) Test results: Figure 7 The linear fit coefficient R before and after correction for each metabolite is used. 2 A point plot worth making. For example... Figure 7 As shown, after correcting the internal standard concentration in the original data using the above correction strategy, the fitting effect of the corrected linear curve was significantly improved within the same linear range. Before correction, 36% of the metabolite R... 2 <0.99, after correction, all metabolites R 2 A value >0.99 indicates that this method is suitable for the correction of this type of derivatized isotope labeling method.

[0249] Table 4 below shows the sensitivity (LOD) and linear fit coefficient (R²) of this method. 2 The linear range (LLOQ-HLOQ) and linear range of most metabolites (except for those with optimized CE values, see Table 1) show that the LOD of most metabolites is less than 1 fmol, verifying the high sensitivity of the method. The linear range of the method is 2-4 orders of magnitude, and within this range, the ROD of all metabolites can be guaranteed. 2 A value greater than 0.99 indicates that this method can be adapted to the analysis of various biological samples with large concentration differences.

[0250] Table 5 below shows the absolute concentrations of amino metabolites measured in four common biological samples. As shown in Table 5, this method can accurately quantify 117 amino metabolites in 5 μL of urine, 107 amino metabolites in 20 μL of serum, and 117 amino metabolites in 5 mg of rabbit liver. Cell samples were used to verify the accuracy of the method. The results showed that 101 amino metabolites could be quantified in 5 mg wet weight K562 mammalian cells, demonstrating the superior versatility of this method.

[0251] Table 4. Method sensitivity (LOD), linear fit coefficient (R²), and linear range (LLOQ-HLOQ)

[0252]

[0253]

[0254]

[0255] Table 5. Absolute concentrations of amino acid metabolites in four common biological samples.

[0256] *In the table below, N / A represents values ​​below the lower limit of quantification.

[0257]

[0258]

[0259]

[0260]

[0261] Comparison of proportional isotope interference correction methods

[0262] Comparative Example 1:

[0263] The data processing in step (6) of Example 1 was referenced in the following literature, and the other steps were the same as in Example 1. The reference, Development, Validation, and Application of a New Method To Correct the Nonlinearity Problem in LC-MS / MS Quantification Using Stable Isotope-Labeled Internal Standards. Anal. Chem. 2019, 91, 9616-9622, proposes a new correction scheme. This literature first mixes equal amounts of analyte and internal standard, and then calculates the response ratio (γ) obtained after detection by liquid chromatography-mass spectrometry.

[0264] γ=R a / R is

[0265] Then the analyte response (R) was established. a ), concentration (C a ), the response of the internal standard (R) is ) and concentration (C is The relational equation (as shown below) establishes R. a / (R a +γR is ) and C a / (C a +C is The standard curve is used for quantitative analysis of samples.

[0266]

[0267] See the calibration results. Figure 8 The linear fit coefficient of the method did not improve.

[0268] Comparative Example 2:

[0269] The data processing in step (6) of Example 1 was referenced in the following literature, and the other steps were the same as in Example 1. The reference "Correction for Isotopic Interferences between Analyte and Internal Standard in Quantitative Mass Spectrometry by a Nonlinear Calibration Function" (Anal. Chem. 2013, 85, 3879-3885) proposes a nonlinear equation for correcting isotopic interference. See [link to reference]. Figure 9The ratio of the measured response of the metabolite to the internal standard is defined as R, the ratio of the theoretical response of the metabolite to the internal standard is defined as A, and the ratio of the response of the internal standard to its interfering peak is defined as R0. ∞ The concentrations of metabolites and internal standards in the sample are defined as C. T and C I The relational equations were obtained (e.g.) Figure 9 The concentration of the sample can be calculated directly using the equation.

[0270] The calibration results are shown in Table 6 below. The results show that this method can only improve the detection accuracy of a few concentration points, but it is difficult to cover a wider quantitative range.

[0271] Table 6

[0272]

[0273] use Figure 6B The test data in the paper compares the isotope interference correction method of the present invention with Comparative Example 1 and Comparative Example 2, from which... Figure 8 It can be seen that after correcting the test data using Comparative Example 1, the linear fitting coefficient of the method did not improve, thus failing to eliminate the isotope interference problem; while Comparative Example 2 only improved the detection accuracy for a few concentration points, and was unable to cover a wider quantitative range. Figure 6B As can be seen, through the correction by the method of the present invention, the linear fitting coefficient of the method has increased from the initial 0.8905 to 1, indicating that the present method has an advantage in isotope interference correction effect compared with the methods of Comparative Examples 1 and 2.

[0274] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. A method for simultaneous quantitative detection of metabolites in biological samples, characterized in that, The biological samples to be tested were detected using chromatographic tandem mass spectrometry, and the mass spectrometry detection included the following steps: (1) Determine the characteristic ion pairs of each metabolite, optimize the mass spectrometry detection parameters, and obtain the optimal mass spectrometry detection parameters for each metabolite, including the optimal collision energy, i.e. the optimal CE value. (2) Apply the optimal mass spectrometry detection parameters obtained in step (1) to detect biological samples of the same type or the same type as the biological sample to be tested, and obtain the chromatographic peak intensity of each metabolite in the biological sample. Then, using a threshold A of 0.05-0.5 times the upper limit of the detection intensity of the chromatography-tandem mass spectrometry system, the metabolites were classified according to their chromatographic peak intensities: The first category of metabolites are low-concentration metabolites, which are defined as metabolites whose chromatographic peak intensity is lower than or equal to threshold A; The second category of metabolites are high-concentration metabolites, which are defined as metabolites whose chromatographic peak intensity is higher than the threshold A. (3) Determine the final CE value: For the first type of metabolite, the CE value of its mass spectrometry detection is not optimized, and the best CE value in step (1) is still used as the final CE value; For the second type of metabolite, the CE value is optimized as follows: different CE values ​​are used to detect the same metabolite in the biological sample to obtain a chromatographic peak intensity-CE value curve, and the CE value with the chromatographic peak intensity closest to the threshold A is taken as the final CE value. (4) Using the final CE value corresponding to each metabolite, the biological sample to be tested is injected into the liquid chromatography-tandem mass spectrometry system, and the internal standard method is used to quantitatively analyze each metabolite in the biological sample to be tested, so as to obtain the content of each metabolite in the biological sample to be tested. The internal standard method includes the following steps: A. Preparation of standard solutions: Take the standards of the metabolites and prepare an initial standard solution of a certain concentration. The initial standard solution is serially diluted n times to obtain n+1 groups of linear standard solutions with different concentrations. An appropriate amount of the corresponding isotope internal standard of the metabolite with known concentration is added to each solution to obtain n+1 groups of linear standard solutions containing internal standards, where n is an integer. In the n+1 group of linear standard solutions containing internal standards, the concentration of the metabolite is denoted as C. li , where i is an integer, taking values ​​1, 2, 3, ..., n+1; B. Correction of isotope internal standard concentration: B1. Calculate the natural isotopic interference ratio of metabolites. R The initial standard solution was detected and analyzed using the multiple reaction monitoring mode of a liquid chromatography-tandem mass spectrometry system to calculate the natural isotope interference ratio of the metabolites. R=P l+x / P l ;in, P l+x The peak area of ​​the natural isotope of the metabolite in the standard solution; P l The peak area of ​​the metabolite in the standard solution; B2. Calculate the isotopic internal standard corrected concentration of the metabolite. C H : The n+1 groups of linear standard solutions containing internal standards were analyzed by multiple reaction monitoring (MRM) of a liquid chromatography-tandem mass spectrometry (LC-MS) system, and the corrected concentration of the isotopic internal standard for each metabolite in each group of linear standard solutions was calculated. C Hi =C hi P Hi / (P Hi -RP li ) ; Where i is an integer, taking the values ​​1, 2, 3, ..., n+1; C Hi To correct for the concentration of the internal standard isotope, i.e., the concentrations of the added internal standard and the natural isotopes of the metabolites, the concentrations of the n+1 groups of linear standard solutions containing the internal standard are obtained using the above formula. C H1, C H2, C H3…, C Hn+1 The unit is μM; C hi To determine the concentration of the corresponding isotopic internal standard for the added metabolite, for the n+1 groups of linear standard solutions containing the internal standard, the concentrations were respectively obtained. C h1, C h2, C h3…, C hn+1 The unit is μM; P Hi To obtain the peak areas of the added isotopic internal standard and the natural isotopes of the metabolites, for the n+1 groups of linear standard solutions containing internal standards, respectively... P H1, P H2, P H3…, P Hn+1 ; P li The peak area of ​​the metabolite was obtained for each of the n+1 groups of linear standard solutions containing an internal standard. P l1, P H2, P H3…, P Hn+1 ; C. Establish a standard curve: The ratio of the peak area of ​​the metabolite to that of the added isotopic internal standard and the natural isotope of the metabolite. P li / P Hi The vertical axis represents the ratio of the concentration of metabolites to the concentration of the corrected isotopic internal standard. C li / C Hi Using the x-axis as the horizontal axis, construct a linear equation and plot a standard curve; D. Calculate the concentration of metabolites in the biological sample: Based on the peak area of ​​metabolites in the biological sample to be tested, the peak area of ​​the added isotope internal standard and the natural isotope internal standard, and the isotope internal standard correction concentration, substitute them into the standard curve to calculate the concentration of each metabolite in the biological sample to be tested.

2. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 1, characterized in that, The number of the metabolites is one or more; And / or, the metabolites include amino metabolites.

3. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 2, characterized in that, The number of metabolites is more than 120; And / or, the amino metabolite is selected from norepinephrine, octanamine, 1,2-diaminopropane, 1,3-diaminopropane, 1-deoxynojirimycin, 1-methyl-histidine, 2,4-diaminobutyric acid, 2-amino-2-methyl-1-propanol, 2-aminoisobutyric acid, 3-aminobenzoic acid, 4-aminobenzoic acid, transtriiodothyronine, triiodothyronine, 3,4-dihydroxy-DL-phenylalanine, 3-aminosalicylic acid, 3-hydroxy-2-aminobenzoic acid, 3-iodothyronine, 3-methoxytyramine, 3-methyl-histidine, 4-aminophenol, 4-hydroxy-L-isoleucine, 4-hydroxy-L-proline, 5-aminovaleric acid, 5-hydroxydopamine, 5-Hydroxy-L-Tryptophan, 6-Aminohexanoic acid, Guanidylbutyramine, Alanylleucine, Alanyltryptophan, Arginaminosuccinic acid, Asymmetric dimethylarginine, Cadaverine, Cystine, Cysteine ​​& Cystamine, D-(-)-α-Phenylexic acid, Dextromethorphan, D-Homoserine, Responin, DL-2,6-Diaminopimelic acid, DL-3-Aminoisobutyric acid, DL-5-Hydroxylysine, DL-Ethioprine, DL-Diallanine Sulfate, DL-Methionine Sulfoxide, DL-Norepinephrine, Dopamine, D-Serine, Adrenaline, Glycine, Glutathione 1, Glutathione 2, Histamine, Taurine, Isoamylamine, L-2-Aminohexanoic acid, L- 2-Aminobutyric acid, L-alanine, L-carnosine, L-arginine, L-asparagine, L-aspartic acid, L-carnosine, L-citrulline, L-sulfoalanine, L-cysteine ​​& L-cysteine, leucylproline, L-glutamic acid, L-glutamine, histidine, L-homogeneous arginine, L-homogeneous citrulline, L-homocysteine ​​& L-homocysteine, L-isoleucine, L-kynurenine, L-leucine, L-lysine, L-methionine, L-valine, L-ornithine, L-piperidinic acid, proline, L-serine, L-threonine, L-thyroxine, L-tryptophan, L-tryptophanamide, L-tyrosine, L-valine, adrenaline, N-methylphenidate The following are included in the list of amines, N-methyltyramine, Nα-acetyl-L-lysine, Nε,Nε,Nε-trimethyllysine, L-serine acetyl ester, L-serine phosphate ester, L-threonine phosphate ester, L-tyrosine phosphate ester, ethanolamine phosphate 1, ethanolamine phosphate 2, p-aminohippuric acid, phenylethylamine, phenylalanine, procaine, proline, putrescine, S-(2-aminoethyl)-L-cysteine, S-adenosyl-L-homocysteine, S-adenosylmethionine, yeast amino acid, decarboxylated S-adenosylmethionine, sarcosine, serotonin, spermine, spermine, deoxyepinephrine, taurine, tryptamine, tyramine, β-alanine, γ-aminobutyric acid, γ-glutamylcysteine, and creatinine.

4. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 2, characterized in that, The number of metabolites is 121.

5. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 1, characterized in that, The number of biological samples mentioned in step (2) is 1-3; When there is only one biological sample, the final CE value of the metabolite is determined as in the previous steps (1)-(3); When the biological sample contains two types of metabolites of the same kind, the metabolites are classified according to the following three conditions, and the final CE value for detecting the metabolites is obtained: i. In both biological samples, the metabolites of the same type are both Class I metabolites; At this point, the CE value for the mass spectrometry detection of this metabolite will not be optimized, and the optimal CE value will still be used as the final CE value for the detection of this metabolite. ii. In both biological samples, the metabolites of the same type were both Class II metabolites; At this point, the final CE value of the metabolite is obtained through the following steps: a. For each biological sample, the same metabolite in the biological sample is detected using different CE values ​​according to step (3) to obtain a chromatographic peak intensity-CE value curve, that is, two chromatographic peak intensity-CE value curves of the same metabolite are obtained; b. In the two chromatographic peak intensity-CE value curves of the same metabolite, take the CE values ​​of several chromatographic peak intensities that are closest to the threshold A. Use this to test the chromatographic peak intensity of the same metabolite in two biological samples. When the chromatographic peak intensity of the same metabolite in both biological samples does not exceed 0.5 times the upper limit of mass spectrometry detection intensity, the CE value is the final CE value of the metabolite. iii. In two biological samples, metabolites of the same type are classified as Class III metabolites. Class III metabolites refer to metabolites in some samples where the chromatographic peak intensity is lower than or equal to threshold A, i.e., low-concentration metabolites; and in other samples where the chromatographic peak intensity is higher than threshold A, i.e., high-concentration metabolites. At this point, for the CE values ​​of low-concentration metabolites in the third category of metabolites, the CE values ​​detected by mass spectrometry are not optimized, and the best CE value in step (1) is still used as the final CE value. For the CE values ​​of high-concentration metabolites in the third category of metabolites, the final CE values ​​of each metabolite are obtained by step (3); When the biological sample contains three types of metabolites of the same kind, the metabolites are classified according to the following three conditions, and the CE value for detecting the metabolites is obtained: i. In all three biological samples, the metabolites of the same type were all Class I metabolites; At this point, the CE value for the mass spectrometry detection of this metabolite will not be optimized, and the optimal CE value will still be used as the final CE value for the detection of this metabolite. ii. In all three biological samples, metabolites of the same type were all Class II metabolites; At this point, the final CE value of the metabolite is obtained through the following steps: For each biological sample, the same metabolite in the biological sample is detected using different CE values ​​according to step (3) to obtain a chromatographic peak intensity-CE value curve, that is, three chromatographic peak intensity-CE value curves of the same metabolite are obtained; in the three chromatographic peak intensity-CE value curves of the same metabolite, the CE values ​​of the three chromatographic peak intensities closest to the threshold A are taken respectively, for a total of 9 CE values, and the median value of the 9 CE values ​​is taken as the final CE value of the metabolite; iii. Among the three biological samples, metabolites of the same type are classified as Class III metabolites. Class III metabolites refer to low-concentration metabolites in some samples where the chromatographic peak intensity is lower than or equal to threshold A, and high-concentration metabolites in others where the chromatographic peak intensity is higher than threshold A. For the CE values ​​of low-concentration metabolites in the third category of metabolites, the CE values ​​detected by mass spectrometry are not optimized, and the best CE value in step (1) is still used as the final CE value. For high-concentration metabolites in the third category of metabolites, the final CE value of the metabolite is obtained using the following method: If only one biological sample has a high concentration of the same metabolite, then the CE optimized according to step (3) is the final CE value of the metabolite in that biological sample. The CE values ​​of the same metabolite in other samples are not optimized. If two biological samples have the same metabolite at a high concentration, the final CE value of the metabolite is obtained according to the method described in case ii when there are two biological samples. The CE values ​​of the same metabolite in other samples are not optimized.

6. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 5, characterized in that, The biological samples mentioned in step (2) are selected from one, two or three of the following: serum, urine, cell and tissue samples.

7. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 5, characterized in that, The number of "several" refers to 3.

8. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 1, characterized in that, In step (1), the method for determining the characteristic ion pairs of each metabolite is as follows: First, after the metabolite standard solution has undergone derivatization or non-derivatization treatment, the mass-to-charge ratio of the parent ion is determined by direct injection of the mass-to-charge ratio of the parent ion in the parent ion scanning mode. Then, the daughter ion corresponding to the parent ion is obtained by the daughter ion scanning mode. Finally, based on the selected parent ion and daughter ion, a multiple reaction monitoring ion pair is constructed. And / or, in step (1), the method for optimizing mass spectrometry detection parameters includes the following steps: after determining the characteristic ion pair, measuring the response value of the metabolite standard under different mass spectrometry detection parameter CE values, so that the sensitivity reaches the best, and taking the CE value with the highest response as the best CE value; The optimized mass spectrometry detection parameters also include the optimized declustering voltage DP; And / or, in step (2), the threshold A is 0.05 times the upper limit of the detection intensity of the chromatography-tandem mass spectrometry system; And / or, in step (3), the CE value is optimized so that the chromatographic peak intensity of the metabolite does not exceed 0.5 times the upper limit of the mass spectrometry detection intensity; And / or, in step (3), using different CE values ​​means taking several points to the left and right of the optimal CE value respectively; with a certain value between each point; And / or, in step (3), the CE value of the chromatographic peak intensity closest to the threshold A is obtained by taking the three CE values ​​of the chromatographic peak intensity closest to the threshold A from the chromatographic peak intensity-CE value curve, and then taking the median value of the three CE values ​​as the CE value of the chromatographic peak intensity closest to the threshold A. And / or, the biological sample or the biological sample to be tested is pretreated before detection.

9. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 8, characterized in that, In step (1), the derivatization process includes the following steps: adding derivatization reagent to a derivatization reaction buffer containing the metabolite standard solution, reacting for a certain time, centrifuging, and taking the supernatant; And / or, in step (3), the CE value is optimized so that the chromatographic peak intensity of the metabolite does not exceed 0.2 times the upper limit of the mass spectrometry detection intensity; And / or, in step (3), using different CE values ​​means taking 10 points on the left and 20 points on the right; And / or, the pretreatment includes the following steps: sample extraction, derivatization.

10. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 9, characterized in that, In step (1), the derivatization reaction buffer is a phosphate buffer containing methanol and water; In step (1), the derivatizing reagent is selected from methyl esters, succinimide esters, N-alkylates, pentafluorobenzene activated esters, or dansyl chlorides; In step (1), the preparation of the derivatization reagent includes the following steps: mixing the derivatization reagent with a methanol solution to prepare a derivatization reagent solution with a concentration of 2M; And / or, in step (3), the interval between each point is 1 to 3; And / or, in the pretreatment, the sample extraction includes the following steps: adding a precipitant to the sample for precipitation, sonication, centrifugation, and extraction of the supernatant; In the pretreatment, the derivatization process includes the following steps: adding a derivatization reagent to a derivatization reaction buffer containing the biological sample, reacting for a certain time, centrifuging, and taking the supernatant.

11. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 10, characterized in that, In step (1), the concentration of the methanol-water phosphate buffer is 0.4M, the pH is 5.8, and the volume ratio of methanol to water is 1:

1. The derivatizing reagent is selected from NaBH3CN or NaBD3CN; And / or, in step (3), the interval between each point is a value of 2; And / or, in the pretreatment, the derivatization reaction buffer is a phosphate buffer containing methanol and water.

12. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 11, characterized in that, In the pretreatment, the concentration of the methanol-water phosphate buffer is 0.4M, the pH is 5.8, and the volume ratio of methanol to water is 1:

1.

13. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 1, characterized in that, The chromatographic tandem mass spectrometry method is HPLC-MS / MS or UHPLC-MS / MS; And / or, the chromatographic mobile phase of the chromatographic tandem mass spectrometry method is mobile phase A and mobile phase B, wherein mobile phase A is an aqueous solution containing 1.0% formic acid and mobile phase B is an acetonitrile solution containing 1.0% formic acid, where % is volume percentage; And / or, the chromatographic injection volume of the chromatographic tandem mass spectrometry is 2 μL; And / or, the column temperature of the chromatography in the chromatographic tandem mass spectrometry is set to 40°C; And / or, the chromatographic mobile phase flow rate of the chromatographic tandem mass spectrometry is 0.5 mL / min; And / or, the chromatographic column used in the chromatographic tandem mass spectrometry method is a Waters ACQUITY UPLC HSS T3 with a column size of 2.1 × 100 mm and 1.8 μm; And / or, the chromatographic guard column for the chromatographic tandem mass spectrometry is a Waters ACQUITY UPLC HSS T3 VanGuard Pre-Column with a column size of 2.1 mm × 5 mm and 1.8 μm.

14. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 13, characterized in that, The elution gradient for chromatography is as follows: The percentages mentioned above represent the volume percentage of mobile phase A or B relative to the total volume of "mobile phase A and mobile phase B".

15. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 1, characterized in that, In step A, the concentration of metabolites in the initial standard solution is 2-500 mM; And / or, in step A, when there are two or more metabolites, the standard solution is a mixed standard solution containing each metabolite; And / or, the initial standard solution, the linear standard solution, and the biological sample to be tested are subjected to derivatization or non-derivatization treatment before injection and detection; And / or, in step A, the dilution solvent used for the gradient dilution is a 50% methanol aqueous solution containing 10 mM Vc and 10 mM EDTA; And / or, in step A, n is 13 for n gradient dilutions, that is, the initial standard solution is diluted 13 times to obtain 14 sets of linear standard solutions; And / or, in step A, the corresponding isotopic internal standard of the added metabolite is prepared from the initial standard solution; And / or, use Analyst 1.7 software to collect data from the data obtained during the detection process; And / or, in step C, the linear equation is constructed using software; And / or, the calculations involved in steps B through D are all performed in batches using code written in R language.

16. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 15, characterized in that, In step A, the gradient dilution method is to perform stepwise dilutions in a ratio of 1:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2; And / or, in step A, the corresponding isotopic internal standard of the added metabolite is prepared by diluting the initial standard solution by 1 time; And / or, in step C, the software is the data processing software or plotting software that comes with the chromatography-tandem mass spectrometry detection instrument.

17. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 16, characterized in that, In step A, the preparation method includes the following steps: mixing the standard solution diluted by 1 time with the buffer solution, and then performing derivatization to obtain the internal standard solution to be added; And / or, in step C, the drawing software is Excel.

18. The method for simultaneous quantitative detection of metabolites in biological samples as described in claim 16, characterized in that, In step C, the software included with the chromatography-tandem mass spectrometry instrument, Sciex OS 1.7 software, and RStudio software are used to construct the linear equation and calculate the concentration of metabolites in the biological sample to be tested.

19. An absolute quantitative analysis method for metabolites in biological samples based on eliminating interference from natural isotopes in metabolites, characterized in that, It includes the following steps: A. Preparation of standard solutions: Take the standards of the metabolites and prepare an initial standard solution of a certain concentration. The initial standard solution is serially diluted n times to obtain n+1 groups of linear standard solutions with different concentrations. An appropriate amount of the corresponding isotope internal standard of the metabolite with known concentration is added to each solution to obtain n+1 groups of linear standard solutions containing internal standards, where n is an integer. In the n+1 group of linear standard solutions containing internal standards, the concentration of the metabolite is denoted as C. li , where i is an integer, taking values ​​1, 2, 3, ..., n+1; B. Correction of isotope internal standard concentration: B1. Calculate the natural isotopic interference ratio of metabolites. R The initial standard solution was detected and analyzed using the multiple reaction monitoring mode of a liquid chromatography-tandem mass spectrometry system to calculate the natural isotope interference ratio of the metabolites. R=P l+x / P l ;in, P l+x The peak area of ​​the natural isotope of the metabolite in the standard solution; P l The peak area of ​​the metabolite in the standard solution; B2. Calculate the isotopic internal standard corrected concentration of the metabolite. C H : The n+1 groups of linear standard solutions containing internal standards were analyzed by multiple reaction monitoring (MRM) of a liquid chromatography-tandem mass spectrometry (LC-MS) system, and the corrected concentration of the isotopic internal standard for each metabolite in each group of linear standard solutions was calculated. C Hi =C hi P Hi / (P Hi -RP li ) ; Where i is an integer, taking the values ​​1, 2, 3, ..., n+1; C Hi To correct for the concentration of the internal standard isotope, i.e., the concentrations of the added internal standard and the natural isotopes of the metabolites, the concentrations of the n+1 groups of linear standard solutions containing the internal standard are obtained using the above formula. C H1, C H2, C H3…, C Hn+1 The unit is μM; C hi To determine the concentration of the corresponding isotopic internal standard for the added metabolite, for the n+1 groups of linear standard solutions containing the internal standard, the concentrations were respectively obtained. C h1, C h2, C h3…, C hn+1 The unit is μM; P Hi To obtain the peak areas of the added isotopic internal standard and the natural isotopes of the metabolites, for the n+1 groups of linear standard solutions containing internal standards, respectively... P H1, P H2, P H3…, P Hn+1 ; P li The peak area of ​​the metabolite was obtained for each of the n+1 groups of linear standard solutions containing an internal standard. P l1, P H2, P H3…, P Hn+1 ; C. Establish a standard curve: The ratio of the peak area of ​​the metabolite to that of the added isotopic internal standard and the natural isotope of the metabolite. P li / P Hi The vertical axis represents the ratio of the concentration of metabolites to the concentration of the corrected isotopic internal standard. C li / C Hi Using the x-axis as the horizontal axis, construct a linear equation and plot a standard curve; D. Calculate the concentration of metabolites in the biological sample: Based on the peak area of ​​metabolites in the biological sample to be tested, the peak area of ​​the added isotope internal standard and the natural isotope internal standard, and the isotope internal standard correction concentration, substitute them into the standard curve to calculate the concentration of each metabolite in the biological sample to be tested.

20. The absolute quantitative analysis method for metabolites in biological samples based on eliminating interference from natural isotopes in metabolites as described in claim 19, characterized in that, In step A, the concentration of metabolites in the initial standard solution is 2-500 mM; And / or, in step A, when there are two or more metabolites, the standard solution is a mixed standard solution containing each metabolite; And / or, the initial standard solution, the linear standard solution, and the biological sample to be tested are subjected to derivatization or non-derivatization treatment before injection and detection; And / or, in step A, the dilution solvent used for the gradient dilution is a 50% methanol aqueous solution containing 10 mM Vc and 10 mM EDTA; And / or, in step A, n is 13 for n gradient dilutions, that is, the initial standard solution is diluted 13 times to obtain 14 sets of linear standard solutions; And / or, in step A, the corresponding isotopic internal standard of the added metabolite is prepared from the initial standard solution.

21. The absolute quantitative analysis method for metabolites in biological samples based on eliminating interference from natural isotopes in metabolites as described in claim 20, characterized in that, In step A, the gradient dilution method is to perform stepwise dilutions in a ratio of 1:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2:2.5:2; And / or, in step A, the corresponding isotopic internal standard of the added metabolite is prepared by diluting the initial standard solution by 1 time.

22. The absolute quantitative analysis method for metabolites in biological samples based on eliminating interference from natural isotopes in metabolites as described in claim 21, characterized in that, In step A, the preparation method includes the following steps: mixing the standard solution diluted by 1 time with the buffer solution, and then performing derivatization to obtain the internal standard solution to be added.

23. The absolute quantitative analysis method for metabolites in biological samples based on eliminating interference from natural isotopes in metabolites as described in claim 19, characterized in that, Analyst 1.7 software was used to collect data during the testing process; And / or, in step C, the linear equation is constructed using software; And / or, the calculations involved in steps B through D are all performed in batches using code written in R language.

24. The absolute quantitative analysis method for metabolites in biological samples based on eliminating interference from natural isotopes in metabolites as described in claim 23, characterized in that, In step C, the software is the data processing software or plotting software that comes with the chromatography-tandem mass spectrometry detection instrument.

25. The absolute quantitative analysis method for metabolites in biological samples based on eliminating interference from natural isotopes in metabolites as described in claim 24, characterized in that, In step C, the drawing software is Excel.

26. The absolute quantitative analysis method for metabolites in biological samples based on eliminating interference from natural isotopes in metabolites as described in claim 24, characterized in that, In step C, the software included with the chromatography-tandem mass spectrometry instrument, Sciex OS 1.7 software, and RStudio software are used to construct the linear equation and calculate the concentration of metabolites in the biological sample to be tested.

Images