CN105301163A - Targeted metabo lomics analysis method for determining metabolites of living body - Google Patents
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Abstract
The invention provides a targeted metabo lomics analysis method for determining metabolites of a living body. The targeted metabo lomics analysis method can simultaneously determine 700 main metabolites of a living body based on series connection of ultra-high performance liquid chromatography and triple quadrupole and comprises the following steps: firstly, 700 main metabolites in a living body are screened; standard products of compounds are optimized to obtain optimal parent ions, daughter ions and mass spectrography conditions of the metabolites; the metabolites in samples are extracted by methanol, acetonitrile and water; liquid chromatograph conditions are optimized; a hydrophilic interaction is adopted to separate the metabolites; the separated metabolites enters a mass spectrum; the 700 main metabolites are determined at the same time by use of a real-time scheduled multi-reaction monitoring mode with quick positive and negative polarity switching function; the metabolite differences between all the samples are analyzed via partial least square analysis; changes of the metabolic pathway are found by pathway enrichment analysis. The targeted metabo lomics analysis method remarkably increases the number of detected compounds, and greatly shortens the analysis time.
Description
Technical field
The present invention relates to analytical chemistry field, especially a kind of target metabonomic analysis methods measuring biosome metabolic product.
Background technology
Metabolic product is the small molecular organic compounds (molecular weight <1500Da) realizing metabolic process in life entity, is under zymoprotein catalytic action, the final product of the gene expression of generation.Metabonomic technology (metabolomics) is the important research means of the systems biology that rear era gene grows up, and is intended to quantitatively detect metabolic product as much as possible in biosystem.Metabonomic technology is widely applied to multiple field, such as medical diagnosis on disease, drug research and development, nutraceutical evaluation, toxicological study, environmental monitoring, plant breeding etc.
Metabonomic technology, according to the metabolin whether presetting detection, is divided into non-targeted metabolism group (non-targetedmetabolomics) and target metabolism group (targetedmetabolomics).Non-targeted metabolism group does not set the compound of detection in advance, but the ion treating all metabolins in the sample of side carries out full scan analysis, then utilizes software database to compare qualification to scanned compound.Non-targeted metabolism group late time data process is complicated, consuming time.Especially the qualification of metabolic product, the biological interior metabolism product that energy precise Identification goes out is less.The structure of target metabolism group known metabolic product to be detected in advance, physicochemical property.Therefore the shortcoming of traditional non-targeted metabolism group is effectively overcome, simplify the process of data processing, improve precision of analysis, is the metabonomic technology of new generation (next-generationmetabolomics) just grown up in recent years.
The analysis platform of target metabolism group mainly contains based on nuclear magnetic resonance technique (NMR) with based on mass spectrum (MS) and serial connection technology (MS/MS) thereof. and with nuclear magnetic resonance technique phase, MS/MS has higher detection sensitivity and accuracy.MS/MS can be divided into again Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS), gas chromatography tandem mass spectrum (GC-MS/MS) and Capillary Electrophoresis tandem mass spectrum (CE-MS/MS) according to connected chromatograph.But GC-MS/MS is only suitable for analyzing Volatile Metabolites, and analyzing non-volatile metabolic product needs to carry out loaded down with trivial details metabolin derivatization.CE-MS/MS is only applicable to analysis part polar metabolites.LC-MS/MS sample pre-treatments is simple, can analyze polar compound, can analyze non-polar compound again, at utmost can meet the mensuration of metabolic product in complex sample.But traditional target metabolism group method based on LC-MS/MS has a great limitation to be exactly once can only measure a small amount of metabolic product (<50), has very large gap with the target of metabonomic analysis metabolic product as much as possible.In addition, traditional metabolism group stratographic analysis time is all more than 60 minutes.
Summary of the invention
Technical matters to be solved by this invention is to provide a kind of target metabonomic analysis methods measuring biosome metabolic product.The method is improved existing target metabolism group method, is a kind of target metabolism group method based on main metabolites in Simultaneously test 700 kinds of biosomes of LC-MS/MS.
For solving the problems of the technologies described above, technical scheme of the present invention is:
Measure a target metabonomic analysis methods for biosome metabolic product, concrete steps are as follows:
(1) metabolic product feature parent ion, the optimization of fragment daughter ion: standard items are dissolved in methyl alcohol or water, be made into the standard solution of 0.1-1 μM, use triple quadrupole bar mass spectrum (MS/MS), determine the parent ion of metabolic product, fragmention and Mass Spectrometry Conditions, comprise and separate ionization voltage (Declusteringpotential, DP), bombarding voltage (Collisionenergy, CE), mouth exit potential (Collisionexitpotential, CXP) and retention time is on a column collided;
(2) extraction of metabolic product in sample: by sample and E. coli-Yeast bacterium
13the 10:1 mixing by volume of C stable isotope internal standard compound, Extraction solvent methanol-acetonitrile-water is added and vortex mixes in the ratio of homomixture and Extraction solvent volume ratio 1:4, described methyl alcohol: acetonitrile: the volume ratio 40:40:20 of water, leaving standstill 10min on ice, high-speed low temperature (16000g, 4 DEG C) centrifugal after, get supernatant and obtain sample introduction liquid;
(3) LC chromatographic resolution: adopt nh 2 column, by hydrophilic Interaction Chromatography (Hydrophilicinteraction, HILIC), the metabolic product in sample is separated;
(4) MS/MS detection method is set up: by feature parent ion, fragment daughter ion, the bombarding voltage of metabolic product optimized, collision mouth entrance potential, bombarding voltage, collision mouth exit potential, retention time information is input in Analyst software, the mass spectrum negative ions dipole inversion time is set as 50ms, carry out negative ions conversion by many reaction detection pattern (ScheduledMRM) to metabolic product to scan simultaneously, obtain corresponding chromatogram;
(5) Data Management Analysis: by Multiquant analysis software, gained chromatographic peak is scanned to MS/MS and carry out area integral, by marking the peak area of compound in interpolation, each sample is normalized (Normalization), utilize partial least squares analysis (Partialleastsquareanalysis, PLS-DA) somatotype is carried out to the difference in each sample, analyzed by VIP (Variableinfluenceontheprojection) and find out the compound having significant difference between each group, carry out metabolic pathway analysis (Pathwayenrichmentanalysis).
Preferably, the target metabonomic analysis methods of said determination biosome metabolic product, in described step (2), sample is soil, sewage, food, blood, cell, animal vegetable tissue or microbial cells.
Preferably, the target metabonomic analysis methods of said determination biosome metabolic product, in described step (3), the condition of LC is: chromatographic column LunaNH
2(250mm × 2mm, 5 μm, U.S. Phenomenex, company), mobile phase A is 95% water+20mM ammonium hydroxide (NH4OH)+15.3mM formic acid (HCOOH), pH9.44; Mobile phase B is the acetonitrile of 100%.
Preferably, the target metabonomic analysis methods of said determination biosome metabolic product, in described step (4), mass spectrographic condition is: negative ions switching rate is set as 50ms, and the residence time is set as 2ms; Negative ion electrospray is installed with and is decided to be-4500V, and positive ion electrospray is installed with and is decided to be 5500V; Ion source temperature is set as 500 DEG C; Gas1, Gas2, protection gas (Curtaingas) is set as 30psi, and assisted gas 1 (Gas1) is set as 35psi, and assisted gas 2 (Gas2) is set as 35psi.
Preferably, the target metabonomic analysis methods of said determination biosome metabolic product, carries out log2 conversion to the peak area of gained in described step (5), peak area after must transforming; Calculate the geometrical mean of peak area after mark converting compounds in each sample; Calculate the correction factor of each sample; Correction factor is utilized to be normalized each sample; Partial least squares analysis is utilized to carry out somatotype to the difference in each sample; Analyzed by VIP and find out the compound between each group with significant difference; To have the metabolic product of significant difference, input metabolic pathway analysis software carries out metabolic pathway analysis.
Beneficial effect of the present invention:
The target metabonomic analysis methods of said determination biosome metabolic product, first the method for bioinformatics is used, add that document real example has screened the 700 kinds of metabolic products containing main metabolic pathway in biosome, feature parent ion and the fragment daughter ion of 700 kinds of metabolic products is determined by metabolic product standard items, separate ionization voltage (Declusteringpotential, DP), bombarding voltage (Collisionenergy, CE) and retention time on a column; Metabolic product in sample achieved the chromatographic resolution to metabolic product by chromatographic column in liquid chromatography in 30 minutes, then metabolic product is imported into triple quadrupole mass spectrometer (MS/MS), detected by multiple-reaction monitoring (ScheduledMRM) and negative ions polarity switching mode (Polarityswitch), compared with traditional metabolism group method, the method significantly improves analysis time and the metabolic product amount detection of metabolism group, has the comprehensive feature of metabolic pathway that detection compound quantity is many, analysis time is short, contain.
Utilize the method for the invention, single injected sampling, can Simultaneously test 700 kinds of metabolic products within the time of 30 minutes, and the quantity of detection compound is current conventional target to more than 10 times of metabolism group method; The method of the invention have employed negative ions conversion and scans simultaneously, makes the time shorten of analysis 700 compounds to 1/4 of classic method.In addition, compound measured by the present invention covers all main metabolic pathway of biosome, can meet the demand of metabonomic analysis, and overcomes non-targeted metabolism group data processing complex, the shortcoming of poor repeatability, chromatographic peak qualification difficulty.
Accompanying drawing explanation
Fig. 1: target metabolism group Establishing process figure of new generation;
Fig. 2: representative chromatogram and metabolic product;
Fig. 3: partial least squares analysis (PLS-DA) analysis heavy metal Lead sweet and control group corn root Difference of Metabolism;
Fig. 4: VIP (Variableinfluenceontheprojection) analyzes display heavy metal lead and coerces the metabolic product with control group corn root with significant difference;
Fig. 5: metabolic pathway analysis display heavy metal lead coerces the impact on corn root metabolism;
Fig. 6: utilize target metabonomic technology detection accuracy of new generation to investigate;
Fig. 7: utilize the linear investigation that target metabonomic technology of new generation is analyzed.
Embodiment
Below in conjunction with specific embodiment, technical scheme of the present invention is further described.
Embodiment 1
Following embodiment 1 is for corn root, but the method for the invention is equally applicable to the solid samples such as food, animal tissue, pedotheque.
Based on the foundation of the target metabonomic analysis methods of new generation of LC-MS/MS Simultaneously test corn root 700 kinds of metabolic products
The process flow diagram of a new generation's target metabolism group method establishment and application is shown in Fig. 1, and embodiment is as follows:
(1) metabolic product feature parent ion, the optimization of fragment daughter ion: by the standard items of 700 compounds, is dissolved in methyl alcohol or water respectively according to solubleness, is made into the solution of 1 μM.Get 1ml solution, be injected in triple quadrupole bar mass spectrum (ABSCIEX, Qtrap5500) by syringe flowing; Open mass spectrum workstation, by Q1, MS
2determine the best parent ion of metabolic product with MRM scanning, fragment daughter ion, solution ionization voltage, bombarding voltage and collision mouth exit potential, select the ion that Q1 sweep signal is the strongest to be the best parent ion of detection, MS
2the ion that sweep signal is the strongest is best fragment daughter ion, get the ion pair that best parent ion and daughter ion are many reaction detection, scanned by MRM, optimize and obtain most strong solution ionization voltage, bombarding voltage and collision mouth exit potential, the condition of the 700 kinds of metabolic products optimized is in table 1.
The optimal value of table 1LC-MS/MS Simultaneously test 700 kinds of metabolic products
(2) extraction of the metabolic product of metabolic product in corn root: get heavy metal lead and coerce 50mg each with control group corn root, after liquid nitrogen grinding, add 50 μ l E. coli-Yeast bacterium
13in C stable isotope, mark compound, after mixing, adds 450 μ l Extraction solvent methanol-acetonitrile-water (volume ratio 40:40:20); After vortex mixing, leaving standstill 10 minutes on ice.After high-speed low temperature centrifugal (16,000g, 4 DEG C), get supernatant and obtain LC-MS/MS analysis sample introduction liquid.
(3) Ultra Performance Liquid Chromatography is separated: by automatic sampler, 10 μ l are analyzed sample introduction liquid and inject LunaNH
2in chromatographic column (250mm × 2mm, 5 μm, Phenomenex, CA), by hydrophilic Interaction Chromatography, the metabolic product in sample is separated; Concrete chromatographic condition is: mobile phase A is 95% water+20mM ammonium hydroxide (NH
4oH)+15.3mM formic acid (HCOOH), pH9.44; Mobile phase B is the acetonitrile of 100%; Flow velocity is 0.3ml/min, and column temperature is 25 DEG C.Condition of gradient elution is: 0-3min, 95%B; 3.1-6min, 80%B; 6.1-10min, 70%B; 10-18min, 2%B; 18-21min, 0%B, 21-27min0%B; 28-31min, 100%B; 31.1min, 95%B; 35min stops.
(4) triple quadrupole bar scanning of the mass spectrum detects 700 metabolic products: by feature parent ion, fragment daughter ion, the bombarding voltage of 700 metabolic products optimized, collision mouth entrance potential, bombarding voltage, collision mouth exit potential, retention time information is input in mass spectrum workstation Analyst software; Many reaction detection pattern of the real-time programming adopting negative ions to switch fast scans; Negative ions switching rate is set as 50ms; the residence time is set as 2ms; negative ion electrospray is installed with and is decided to be-4500V; positive ion electrospray is installed with and is decided to be 5500V, and ion source temperature is set as 500 DEG C, Gas1; Gas2; protection gas (Curtaingas) is set as 30psi, and assisted gas 1 (Gas1) is set as 35psi, and assisted gas 2 (Gas2) is set as 35psi.Fig. 2 is representative chromatogram.
(5) sample data analysis: by Multiquant analysis software, gained chromatographic peak is scanned to MS/MS and carry out integration, to the peak area of gained, carry out log2 conversion, rear peak area must be transformed, calculate the geometrical mean (Geomean) of peak area after mark converting compounds in each sample, the correction factor (Normalizationfactor) calculating each sample utilizes correction factor to be normalized each sample, utilize partial least squares analysis (Partialleastsquareanalysis, PLS-DA) (www.metaboanalyst.com) carries out somatotype (Fig. 3) to the difference in each sample.Analyzed by VIP (Variableinfluenceontheprojection) and find out the compound (Fig. 4) between each group with significant difference.To have the metabolic product of significant difference, input metabolic pathway analysis software (www.metaboanalyst.com), carries out metabolic pathway analysis (Fig. 5).
Embodiment 2
The method accuracy using target metabonomic analysis methods of new generation to measure metabolic product in serum investigates (for serum, being applicable to the fluid samples such as microbial inoculum, urine, sewage)
(1) metabolic product extracts: get human serum sample 95 μ l, add 5 μ l E. coli-Yeast bacterium
13in C stable isotope, mark compound, after mixing, adds 400 μ l Extraction solvent (methanol-acetonitrile-water 40:40:20, v/v/v), after vortex mixing, is leaving standstill 10 minutes on ice.After high-speed low temperature centrifugal (16000g, 4 DEG C), get supernatant and obtain LC-MS/MS analysis sample introduction liquid.Get same serum, parallelly do 10 repeated sample.
(2) method reappearance is investigated: get 10 μ l serum extract, use the analytical approach of above-mentioned foundation to measure 700 kinds of metabolic products in 10 sample blood serum samples.Select 70 representative chromatographic peaks, calculate the relative standard deviation (RSD) of peak area and the relative standard deviation (RSD) of retention time that measure for 10 times.As shown in Figure 6, in selected 70 metabolic chromatographic peaks, the RSD of its peak area of peak of 47% (33) is less than 5%, and the RSD value of its peak area of chromatographic peak of 25% (18) is less than 10%.The RSD of the retention time of all 70 chromatographic peaks is less than 5%.This shows that the reappearance of method is good.
(3) method is linearly investigated: get serum, the physiological saline of 0.9%, dilutes 2,4,8,16 and 32 times respectively.Get the serum that 100 μ l dilute, add 400 μ l Extraction solvent methanol-acetonitrile-water (40:40:20, v/v/v), as stated above, metabolic product is extracted and stratographic analysis.Concentration and gained peak area are done correlation analysis, with regression coefficient (r
2) evaluate mass spectrum response and the linear relationship of serum-concentration.As shown in Figure 7, the regression coefficient of its mass spectra peak area of the chromatographic peak of 70% and concentration is greater than 0.99, and the peak area of chromatographic peak and the regression coefficient of concentration of 20% are greater than 0.98.The inventive method accuracy is better as can be seen from these data, the range of linearity is wider.
As can be seen from embodiment 1 and 2, a kind of target metabonomic analysis methods of new generation based on LC-MS/MS Simultaneously test 700 kinds of metabolic products disclosed by the invention, by optimizing the parent ion of metabolic product, daughter ion and chromatographic separation condition, many reaction detection pattern of the real-time programming adopting negative ions to switch fast, 700 metabolic products achieved in 30 minutes covering all main metabolic pathway of biosome have carried out Simultaneously test.The chromatogram obtained, carries out integration by quantitative analysis software and obtains peak area.The peak area of gained is normalized by interior mark compound, then respectively organizes the difference between sample by statistical analysis and metabolic pathway com-parison and analysis, sets up target metabolism group method of new generation.
Different from traditional target metabolism group, the inventive method is more more than traditional target metabolism group method detection compound, and analysis time is shorter, and the metabolic pathway covered is wider, can meet the demand of metabonomic analysis.In addition, present invention overcomes non-targeted metabolism group data processing complex, the shortcoming of poor repeatability, chromatographic peak qualification difficulty.
Above-mentioned detailed description of this kind of target metabonomic analysis methods measuring biosome metabolic product being carried out with reference to embodiment; illustrative instead of determinate; several embodiments can be listed according to institute's limited range; therefore in the change do not departed under general plotting of the present invention and amendment, should belong within protection scope of the present invention.
Claims (5)
1. measure a target metabonomic analysis methods for biosome metabolic product, it is characterized in that: concrete steps are as follows:
(1) metabolic product feature parent ion, the optimization of fragment daughter ion: standard items are dissolved in methyl alcohol or water, be made into the standard solution of 0.1-1 μM, use triple quadrupole bar mass spectrum, determine the parent ion of metabolic product, fragmention and Mass Spectrometry Conditions, comprise and separate ionization voltage, bombarding voltage, collision mouth exit potential and retention time on a column;
(2) extraction of metabolic product in sample: by sample and E. coli-Yeast bacterium
13the 10:1 mixing by volume of C stable isotope internal standard compound, Extraction solvent methanol-acetonitrile-water is added and vortex mixes in the ratio of homomixture and Extraction solvent volume ratio 1:4, described methyl alcohol: acetonitrile: the volume ratio 40:40:20 of water, leaving standstill 10min on ice, after high-speed low temperature is centrifugal, gets supernatant and obtain sample introduction liquid;
(3) LC chromatographic resolution: adopt nh 2 column, by hydrophilic Interaction Chromatography, the metabolic product in sample is separated;
(4) MS/MS detection method is set up: by feature parent ion, fragment daughter ion, the bombarding voltage of metabolic product optimized, collision mouth entrance potential, bombarding voltage, collision mouth exit potential, retention time information is input in Analyst software, the mass spectrum negative ions dipole inversion time is set as 50ms, carry out negative ions conversion by many reaction detection pattern to metabolic product to scan simultaneously, obtain corresponding chromatogram;
(5) Data Management Analysis: by Multiquant analysis software, gained chromatographic peak is scanned to MS/MS and carry out area integral, by marking the peak area of compound in interpolation, each sample is normalized, partial least squares analysis is utilized to carry out somatotype to the difference in each sample, analyzed by VIP and find out the compound having significant difference between each group, carry out metabolic pathway analysis.
2. the target metabonomic analysis methods of mensuration biosome metabolic product according to claim 1, is characterized in that: in described step (2), sample is soil, sewage, food, blood, cell, animal vegetable tissue or microbial cells.
3. the target metabonomic analysis methods of mensuration biosome metabolic product according to claim 1, is characterized in that: in described step (3), the condition of LC is: chromatographic column LunaNH
2250mm × 2mm, 5 μm, mobile phase A is 95% water+20mM ammonium hydroxide+15.3mM formic acid, pH9.44; Mobile phase B is the acetonitrile of 100%.
4. the target metabonomic analysis methods of mensuration biosome metabolic product according to claim 1, is characterized in that: in described step (4), mass spectrographic condition is: negative ions switching rate is set as 50ms, and the residence time is set as 2ms; Negative ion electrospray is installed with and is decided to be-4500V, and positive ion electrospray is installed with and is decided to be 5500V; Ion source temperature is set as 500 DEG C; Protection gas is set as 30psi, and the first assisted gas is set as 35psi, and the second assisted gas is set as 35psi.
5. the target metabonomic analysis methods of mensuration biosome metabolic product according to claim 1, is characterized in that: carry out log2 conversion to the peak area of gained in described step (5), peak area after must transforming; Calculate the geometrical mean of peak area after mark converting compounds in each sample; Calculate the correction factor of each sample; Correction factor is utilized to be normalized each sample; Partial least squares analysis is utilized to carry out somatotype to the difference in each sample; Analyzed by VIP and find out the compound between each group with significant difference; To have the metabolic product of significant difference, input metabolic pathway analysis software carries out metabolic pathway analysis.
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Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105759065A (en) * | 2016-02-26 | 2016-07-13 | 天津桑尼匹克生物科技有限公司 | Use of blood metabolism marker and depression detecting kit |
| CN106226448A (en) * | 2016-10-11 | 2016-12-14 | 岛津企业管理（中国）有限公司 | A kind of method of multiple compounds changes of contents in quick mensuration cell culture supernatant |
| CN107121517A (en) * | 2017-07-05 | 2017-09-01 | 赛思莱（厦门）生物科技有限公司 | A kind of sample preparation processing method studied for excrement and soil metabolism group |
| CN109752549A (en) * | 2019-03-04 | 2019-05-14 | 北京和合医学诊断技术股份有限公司 | Method for establishing model based on targeting metabolism group data analysis |
| CN109781916A (en) * | 2018-11-05 | 2019-05-21 | 苏州帕诺米克生物医药科技有限公司 | Target the quantitative automatic analysis method of metabolism group and device, electronic equipment |
| CN109844515A (en) * | 2016-10-04 | 2019-06-04 | Atonarp株式会社 | System and method for the accurately composition of quantified goal sample |
| CN109975455A (en) * | 2019-03-29 | 2019-07-05 | 东北大学 | A kind of underground sewage percolating system microbial metabolic products detection method |
| CN110392830A (en) * | 2017-02-24 | 2019-10-29 | 伊罗亚科技有限公司 | For improved precision, the IROA metabolism group workflow of identification and quantification |
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| CN111579665A (en) * | 2020-05-20 | 2020-08-25 | 苏州帕诺米克生物医药科技有限公司 | UPLC/HRMS-based metabonomics relative quantitative analysis method |
| CN112525631A (en) * | 2020-10-16 | 2021-03-19 | 华南农业大学 | Sample preparation method for non-targeted metabonomics and non-targeted lipidomics research of shrimp meat samples |
| CN112630363A (en) * | 2020-12-31 | 2021-04-09 | 四川大学华西医院 | MXene biological response characteristic metabonomics analysis method |
| CN113671097A (en) * | 2021-07-19 | 2021-11-19 | 中国农业科学院油料作物研究所 | Based on13Full-lipid quantitative method of C metabolism full-position labeled lipid combined isotope dilution mass spectrometry |
| CN115015450A (en) * | 2022-05-26 | 2022-09-06 | 贵州省烟草科学研究院 | Method for analyzing metabolites in soil through microwave derivatization-quasi-target gas chromatography-mass spectrometry |
| CN118067908A (en) * | 2024-04-22 | 2024-05-24 | 长春中医药大学 | Targeted data analysis method for non-targeted metabonomics research |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103149280A (en) * | 2011-12-07 | 2013-06-12 | 中国农业大学 | Method for evaluating animal individual nutriture by metabonomics |
| CN103235073A (en) * | 2013-04-15 | 2013-08-07 | 湖南省食品药品检验研究院 | Metabonomics analysis method base on acute anaphylactic reaction |
| CN103278579A (en) * | 2013-05-22 | 2013-09-04 | 夏彦恺 | Plasma metabolism micromolecular marker related to human intestinal canal aganglionosis and application of plasma metabolism micromolecular marker |
| CN103616450A (en) * | 2013-11-29 | 2014-03-05 | 湖州市中心医院 | Serum specificity metabolite spectrum for patient with lung cancer, and building method thereof |
-
2015
- 2015-11-27 CN CN201510853787.0A patent/CN105301163A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103149280A (en) * | 2011-12-07 | 2013-06-12 | 中国农业大学 | Method for evaluating animal individual nutriture by metabonomics |
| CN103235073A (en) * | 2013-04-15 | 2013-08-07 | 湖南省食品药品检验研究院 | Metabonomics analysis method base on acute anaphylactic reaction |
| CN103278579A (en) * | 2013-05-22 | 2013-09-04 | 夏彦恺 | Plasma metabolism micromolecular marker related to human intestinal canal aganglionosis and application of plasma metabolism micromolecular marker |
| CN103616450A (en) * | 2013-11-29 | 2014-03-05 | 湖州市中心医院 | Serum specificity metabolite spectrum for patient with lung cancer, and building method thereof |
Non-Patent Citations (6)
| Title |
|---|
| LIANG WU 等: "Quantitative analysis of the microbial metabolome by isotope dilution mass spectrometry using uniformly 13C-labeled cell extracts as internal standards", 《ANALYTICAL BIOCHEMISTRY》 * |
| MIN YUAN 等: "A positive/negative ion–switching, targeted mass spectrometry–based metabolomics platform for bodily fluids, cells, and fresh and fixed tissue", 《NATURE PROTOCOLS》 * |
| RU WEI 等: "High-Throughput and Multiplexed LC/MS/MRM Method for Targeted Metabolomics", 《ANALYTICAL CHEMISTRY》 * |
| 孔宏伟 等: "基于液相色谱⁃质谱联用的代谢组学研究中代谢物的结构鉴定进展", 《色谱》 * |
| 李鹏飞 等: "高效液相色谱-串联质谱法测定人体内30种氨基酸", 《分析化学研究报告》 * |
| 王希越 等: "亲水作用色谱／ 质谱联用方法用于大肠杆菌代谢组分析", 《色谱》 * |
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| WO2020094013A1 (en) * | 2018-11-05 | 2020-05-14 | 苏州帕诺米克生物医药科技有限公司 | Targeted metabolomic automatic quantitative analysis method and device, and electronic device |
| CN109752549B (en) * | 2019-03-04 | 2021-11-09 | 北京和合医学诊断技术股份有限公司 | Model establishing method based on targeted metabonomics data analysis |
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| CN113671097A (en) * | 2021-07-19 | 2021-11-19 | 中国农业科学院油料作物研究所 | Based on13Full-lipid quantitative method of C metabolism full-position labeled lipid combined isotope dilution mass spectrometry |
| CN113671097B (en) * | 2021-07-19 | 2024-02-23 | 中国农业科学院油料作物研究所 | Based on 13 Full-lipid quantification method by combining C metabolism full-position marked lipid with isotope dilution mass spectrometry |
| CN115015450A (en) * | 2022-05-26 | 2022-09-06 | 贵州省烟草科学研究院 | Method for analyzing metabolites in soil through microwave derivatization-quasi-target gas chromatography-mass spectrometry |
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