CN114894949A - Lipid fine structure analysis process and control processing system - Google Patents
Lipid fine structure analysis process and control processing system Download PDFInfo
- Publication number
- CN114894949A CN114894949A CN202210380764.2A CN202210380764A CN114894949A CN 114894949 A CN114894949 A CN 114894949A CN 202210380764 A CN202210380764 A CN 202210380764A CN 114894949 A CN114894949 A CN 114894949A
- Authority
- CN
- China
- Prior art keywords
- lipid
- photochemical
- sample
- fine structure
- mass
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 150000002632 lipids Chemical class 0.000 title claims abstract description 226
- 238000000034 method Methods 0.000 title claims abstract description 139
- 238000004458 analytical method Methods 0.000 title claims abstract description 107
- 230000008569 process Effects 0.000 title claims abstract description 65
- 238000012545 processing Methods 0.000 title claims abstract description 22
- 238000001819 mass spectrum Methods 0.000 claims abstract description 83
- 239000011203 carbon fibre reinforced carbon Substances 0.000 claims abstract description 47
- 238000004949 mass spectrometry Methods 0.000 claims abstract description 46
- 125000005313 fatty acid group Chemical group 0.000 claims abstract description 32
- 239000007788 liquid Substances 0.000 claims abstract description 31
- 238000004895 liquid chromatography mass spectrometry Methods 0.000 claims abstract description 31
- 239000000203 mixture Substances 0.000 claims abstract description 31
- 230000013190 lipid storage Effects 0.000 claims abstract description 17
- 239000012634 fragment Substances 0.000 claims abstract description 6
- 238000001514 detection method Methods 0.000 claims description 24
- 238000006243 chemical reaction Methods 0.000 claims description 17
- 238000009795 derivation Methods 0.000 claims description 16
- 239000003153 chemical reaction reagent Substances 0.000 claims description 9
- 238000007405 data analysis Methods 0.000 claims description 6
- 241001465754 Metazoa Species 0.000 claims description 4
- 125000002915 carbonyl group Chemical group [*:2]C([*:1])=O 0.000 claims description 4
- 239000003814 drug Substances 0.000 claims description 4
- 235000013305 food Nutrition 0.000 claims description 4
- 241000894007 species Species 0.000 claims description 4
- 238000000338 in vitro Methods 0.000 claims description 2
- 238000004811 liquid chromatography Methods 0.000 abstract description 9
- 150000002500 ions Chemical class 0.000 description 66
- 230000014759 maintenance of location Effects 0.000 description 29
- 239000000047 product Substances 0.000 description 19
- CSCPPACGZOOCGX-UHFFFAOYSA-N Acetone Chemical compound CC(C)=O CSCPPACGZOOCGX-UHFFFAOYSA-N 0.000 description 18
- WEVYAHXRMPXWCK-UHFFFAOYSA-N Acetonitrile Chemical compound CC#N WEVYAHXRMPXWCK-UHFFFAOYSA-N 0.000 description 18
- JZNWSCPGTDBMEW-UHFFFAOYSA-N Glycerophosphorylethanolamin Natural products NCCOP(O)(=O)OCC(O)CO JZNWSCPGTDBMEW-UHFFFAOYSA-N 0.000 description 17
- 150000008104 phosphatidylethanolamines Chemical class 0.000 description 17
- 238000001212 derivatisation Methods 0.000 description 15
- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 description 12
- 238000002347 injection Methods 0.000 description 12
- 239000007924 injection Substances 0.000 description 12
- WTJKGGKOPKCXLL-RRHRGVEJSA-N phosphatidylcholine Chemical compound CCCCCCCCCCCCCCCC(=O)OC[C@H](COP([O-])(=O)OCC[N+](C)(C)C)OC(=O)CCCCCCCC=CCCCCCCCC WTJKGGKOPKCXLL-RRHRGVEJSA-N 0.000 description 12
- 239000000243 solution Substances 0.000 description 12
- 241000251468 Actinopterygii Species 0.000 description 11
- 210000002966 serum Anatomy 0.000 description 9
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 8
- 241000283690 Bos taurus Species 0.000 description 8
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 description 8
- 238000002013 hydrophilic interaction chromatography Methods 0.000 description 8
- 210000004185 liver Anatomy 0.000 description 8
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 8
- 239000012071 phase Substances 0.000 description 7
- 238000011002 quantification Methods 0.000 description 7
- 210000001519 tissue Anatomy 0.000 description 7
- 101100348341 Caenorhabditis elegans gas-1 gene Proteins 0.000 description 6
- 101100447658 Mus musculus Gas1 gene Proteins 0.000 description 6
- 101100447665 Mus musculus Gas2 gene Proteins 0.000 description 6
- 230000000052 comparative effect Effects 0.000 description 6
- 238000012937 correction Methods 0.000 description 6
- 239000007791 liquid phase Substances 0.000 description 6
- 241001248610 Ophiocordyceps sinensis Species 0.000 description 5
- 229910052799 carbon Inorganic materials 0.000 description 5
- 201000010099 disease Diseases 0.000 description 5
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 5
- 238000006552 photochemical reaction Methods 0.000 description 5
- 238000011160 research Methods 0.000 description 5
- 239000005695 Ammonium acetate Substances 0.000 description 4
- KFZMGEQAYNKOFK-UHFFFAOYSA-N Isopropanol Chemical compound CC(C)O KFZMGEQAYNKOFK-UHFFFAOYSA-N 0.000 description 4
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N Silicium dioxide Chemical compound O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 4
- FPWNQPQTICPCOM-UHFFFAOYSA-N acetonitrile;propan-2-ol Chemical compound CC#N.CC(C)O FPWNQPQTICPCOM-UHFFFAOYSA-N 0.000 description 4
- 229940043376 ammonium acetate Drugs 0.000 description 4
- 238000001360 collision-induced dissociation Methods 0.000 description 4
- 206010012601 diabetes mellitus Diseases 0.000 description 4
- 238000001035 drying Methods 0.000 description 4
- 238000010828 elution Methods 0.000 description 4
- 239000007789 gas Substances 0.000 description 4
- 238000002309 gasification Methods 0.000 description 4
- 239000012046 mixed solvent Substances 0.000 description 4
- 229910052757 nitrogen Inorganic materials 0.000 description 4
- 239000012074 organic phase Substances 0.000 description 4
- 238000002203 pretreatment Methods 0.000 description 4
- 238000000926 separation method Methods 0.000 description 4
- 238000001269 time-of-flight mass spectrometry Methods 0.000 description 4
- 238000004704 ultra performance liquid chromatography Methods 0.000 description 4
- 239000003643 water by type Substances 0.000 description 4
- 241000190633 Cordyceps Species 0.000 description 3
- 239000003795 chemical substances by application Substances 0.000 description 3
- 238000002514 liquid chromatography mass spectrum Methods 0.000 description 3
- 230000035484 reaction time Effects 0.000 description 3
- 230000035945 sensitivity Effects 0.000 description 3
- 108010022337 Leucine Enkephalin Proteins 0.000 description 2
- -1 PE lipids Chemical class 0.000 description 2
- 239000000337 buffer salt Substances 0.000 description 2
- 238000005119 centrifugation Methods 0.000 description 2
- 238000012512 characterization method Methods 0.000 description 2
- 239000007795 chemical reaction product Substances 0.000 description 2
- 238000010494 dissociation reaction Methods 0.000 description 2
- 230000005593 dissociations Effects 0.000 description 2
- 238000013467 fragmentation Methods 0.000 description 2
- 238000006062 fragmentation reaction Methods 0.000 description 2
- 230000008676 import Effects 0.000 description 2
- 150000007529 inorganic bases Chemical class 0.000 description 2
- 238000005040 ion trap Methods 0.000 description 2
- URLZCHNOLZSCCA-UHFFFAOYSA-N leu-enkephalin Chemical compound C=1C=C(O)C=CC=1CC(N)C(=O)NCC(=O)NCC(=O)NC(C(=O)NC(CC(C)C)C(O)=O)CC1=CC=CC=C1 URLZCHNOLZSCCA-UHFFFAOYSA-N 0.000 description 2
- 238000001294 liquid chromatography-tandem mass spectrometry Methods 0.000 description 2
- 150000007522 mineralic acids Chemical class 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 150000007524 organic acids Chemical class 0.000 description 2
- 150000007530 organic bases Chemical class 0.000 description 2
- 150000002921 oxetanes Chemical class 0.000 description 2
- 230000035790 physiological processes and functions Effects 0.000 description 2
- 239000002243 precursor Substances 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 239000000377 silicon dioxide Substances 0.000 description 2
- 239000002904 solvent Substances 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
- 239000007921 spray Substances 0.000 description 2
- 239000006228 supernatant Substances 0.000 description 2
- 238000009834 vaporization Methods 0.000 description 2
- 230000008016 vaporization Effects 0.000 description 2
- TZCPCKNHXULUIY-RGULYWFUSA-N 1,2-distearoyl-sn-glycero-3-phosphoserine Chemical compound CCCCCCCCCCCCCCCCCC(=O)OC[C@H](COP(O)(=O)OC[C@H](N)C(O)=O)OC(=O)CCCCCCCCCCCCCCCCC TZCPCKNHXULUIY-RGULYWFUSA-N 0.000 description 1
- 208000021959 Abnormal metabolism Diseases 0.000 description 1
- 206010010099 Combined immunodeficiency Diseases 0.000 description 1
- 241000252230 Ctenopharyngodon idella Species 0.000 description 1
- ZWZWYGMENQVNFU-UHFFFAOYSA-N Glycerophosphorylserin Natural products OC(=O)C(N)COP(O)(=O)OCC(O)CO ZWZWYGMENQVNFU-UHFFFAOYSA-N 0.000 description 1
- 206010028980 Neoplasm Diseases 0.000 description 1
- 206010033128 Ovarian cancer Diseases 0.000 description 1
- 206010061535 Ovarian neoplasm Diseases 0.000 description 1
- CBENFWSGALASAD-UHFFFAOYSA-N Ozone Chemical compound [O-][O+]=O CBENFWSGALASAD-UHFFFAOYSA-N 0.000 description 1
- ATBOMIWRCZXYSZ-XZBBILGWSA-N [1-[2,3-dihydroxypropoxy(hydroxy)phosphoryl]oxy-3-hexadecanoyloxypropan-2-yl] (9e,12e)-octadeca-9,12-dienoate Chemical compound CCCCCCCCCCCCCCCC(=O)OCC(COP(O)(=O)OCC(O)CO)OC(=O)CCCCCCC\C=C\C\C=C\CCCCC ATBOMIWRCZXYSZ-XZBBILGWSA-N 0.000 description 1
- 230000005856 abnormality Effects 0.000 description 1
- AWUCVROLDVIAJX-UHFFFAOYSA-N alpha-glycerophosphate Natural products OCC(O)COP(O)(O)=O AWUCVROLDVIAJX-UHFFFAOYSA-N 0.000 description 1
- 238000003556 assay Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000000090 biomarker Substances 0.000 description 1
- 201000011510 cancer Diseases 0.000 description 1
- 210000000170 cell membrane Anatomy 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- 238000006735 epoxidation reaction Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000004896 high resolution mass spectrometry Methods 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000011898 label-free detection Methods 0.000 description 1
- 230000006371 metabolic abnormality Effects 0.000 description 1
- 230000004060 metabolic process Effects 0.000 description 1
- 210000002241 neurite Anatomy 0.000 description 1
- 210000003463 organelle Anatomy 0.000 description 1
- 230000037361 pathway Effects 0.000 description 1
- 150000003905 phosphatidylinositols Chemical class 0.000 description 1
- 239000000843 powder Substances 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000010298 pulverizing process Methods 0.000 description 1
- 238000004451 qualitative analysis Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 230000003248 secreting effect Effects 0.000 description 1
- 238000007873 sieving Methods 0.000 description 1
- 230000019491 signal transduction Effects 0.000 description 1
- 239000002002 slurry Substances 0.000 description 1
- 210000000130 stem cell Anatomy 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000001544 ultraviolet photolysis digestion Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
- G01N2030/8804—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 automated systems
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
Abstract
The application relates to the technical field of analytical chemistry, and particularly discloses a lipid fine structure analysis process and a control processing system. The analysis process comprises the following steps: detecting a sample by using liquid chromatography-primary mass spectrometry, determining lipid subclass information by combining lipid retention time information, and determining a next liquid chromatography-mass spectrometry acquisition method; detecting a sample by using liquid chromatography-secondary mass spectrometry, determining the composition of fatty acid chains, and determining the next liquid chromatography-mass spectrometry acquisition method; detecting the photochemical derivative product by utilizing liquid chromatography separation-photochemical derivative-secondary mass spectrometry to determine the position of the carbon-carbon double bond in the lipid; and determining the relative quantitative information of the isomers at the position of the carbon-carbon double bond of the lipid according to the mass spectrum fragment intensity ratio or the intensity sum ratio of the unsaturated lipid photochemical derivative products. And the analysis process is executed by a human operation control processing system. The method can determine the position of the carbon-carbon double bond in the unsaturated lipid and relative quantitative information.
Description
Technical Field
The present application relates to the technical field of analytical chemistry, and more particularly, to a lipid fine structure analysis process and control processing system.
Background
Lipids are important components of cell membranes, which are involved in important physiological processes of the organism, such as energy storage, signal transduction, and the like. There are large differences in lipid composition between different organisms, and between different individuals of the same organism. Lipids can be classified into saturated lipids (containing no carbon-carbon double bonds) and unsaturated lipids (containing carbon-carbon double bonds) depending on whether the fatty acid chain composition of the lipid contains carbon-carbon double bonds.
Abnormal metabolism of lipids can cause various physiological diseases of the organism; likewise, physiological abnormalities and diseases of the organism can affect lipid composition and metabolism. Therefore, the identification of the lipid fine structure not only plays an important role in the research of the physiological process of a living body, but also can provide information and basis for the characterization of diseases. Related studies have shown that the distribution of unsaturated lipids varies regularly in the relevant organelles involved in the secretory pathway, as well as in some differentiated structures such as neurites; meanwhile, the increase of lipid unsaturation degree can be obviously seen in the ovarian cancer stem cells, so that the unsaturated lipid can be used as a target for cancer treatment; in addition, the ratio of carbon-carbon double bond position isomers has difference change in various disease tissues and normal tissues, and is also a potential disease biomarker index. Therefore, the identification of the lipid fine structure has important biological significance and clinical value.
Mass Spectrometry (MS) methods can provide label-free detection with high sensitivity and structural characterization capability, and their high selectivity and high throughput characteristics make their application in lipidomics of increasing interest. However, mass spectrometry generally only identifies lipid subclasses and fatty acid chains in terms of high-throughput analysis of lipid structures, and cannot deeply analyze fine structures (such as carbon-carbon double bond position isomerism).
Until now, various Mass Spectrometry (MS) and chemical derivatization methods have been developed, such as ozone induced dissociation (OzID), ultraviolet light dissociation (UVPD), epoxidation derivatization (exposition) -mass spectrometry Collision Induced Dissociation (CID), and the like. However, the method is not widely used in lipidomics because the modification of the instrument is complicated and the reaction time is long, so that the requirement of high-throughput detection is difficult to meet. Photochemical derivatization (Patern oa-B uchi reaction, PB reaction) can utilize double bond reagents containing carbonyl groups or their corresponding derivatives to derivatize the carbon-carbon double bond in lipids to chemically relatively stable oxetanes, and the structures can be easily fragmented selectively by low-energy CID, the resulting qualitative and quantitative ions have high relative abundance, which facilitates quantitative and qualitative analysis of lipids. However, the lipid fine structure analysis process based on the PB reaction has the problems of high professional degree, high difficulty, long time consumption and the like of method setting and data processing, and is difficult to be universally applied.
Therefore, there is a need to develop and establish a systematic, efficient and easy-to-use new tool for accurately and rapidly analyzing different lipid components in complex lipid systems.
Disclosure of Invention
In order to deeply analyze the lipid fine structure and further systematically and simply determine the position of a carbon-carbon double bond in unsaturated lipid and relative quantitative information, the application provides a lipid fine structure analysis flow and a control processing system.
The method for analyzing the lipid fine structure by utilizing the photochemical reaction and mass spectrometry technology establishes a corresponding analysis process and develops a matched control processing system by simplifying or intelligentizing instrument control or data conversion, data analysis and report output, and can reduce professional requirements on operators and simplify the analysis process. The analysis process provided by the application can be used for efficiently, quickly, systematically and simply carrying out accurate analysis on different lipid components in a complex lipid system, comprises the positioning of carbon-carbon double bond positions, further realizes the relative quantification of carbon-carbon double bond position isomers, and provides a new efficient and easy-to-use tool for the biological research of lipid isomers.
The application provides a lipid fine structure analysis process and control processing system, adopts the following technical scheme:
a lipid fine structure analysis flow and a control processing system have an instrument control function and have processing functions of data conversion, data analysis and report output.
The analysis process is executed by the control processing system and specifically comprises the following steps:
(1) detecting the sample by using liquid chromatography-primary mass spectrometry to obtain a primary mass spectrogram;
reading data of the primary mass spectrogram to obtain an accurate ion mass-to-charge ratio of the lipid primary mass spectrogram;
comparing the obtained accurate ion mass-to-charge ratio with a database A, determining lipid subclass information by combining the lipid retention time information, and determining a next liquid chromatography-mass spectrometry acquisition method according to the lipid subclass information;
(2) detecting a sample by using liquid chromatography-secondary mass spectrometry according to the liquid chromatography-mass spectrometry acquisition method determined in the step (1) to obtain a secondary mass spectrogram;
reading data of the secondary mass spectrogram to obtain an accurate ion mass-to-charge ratio of the lipid secondary mass spectrum;
comparing the obtained accurate ion mass-to-charge ratio with a database B to determine the composition of the fatty acid chains, and determining the next liquid chromatography-mass spectrometry acquisition method according to the composition of the fatty acid chains;
(3) according to the liquid chromatogram-mass spectrum collection method determined in the step (2), detecting a photochemical derivation product by utilizing liquid chromatogram separation-photochemical derivation-secondary mass spectrum to obtain a photochemical derivation-secondary mass spectrum;
reading data of the photochemical derivation-secondary mass spectrogram to obtain an accurate ion mass-to-charge ratio of the secondary mass spectrum of the photochemical derivation product;
comparing the obtained accurate ion mass-to-charge ratio with a database C to determine the position of the carbon-carbon double bond in the lipid;
and determining relative quantitative information of the isomers at the position of the carbon-carbon double bond of the lipid according to the mass spectrum fragment intensity ratio or the intensity sum ratio of unsaturated lipid photochemical derivative products.
By adopting the technical scheme, the application performs three-step analysis on the lipid: firstly, performing primary mass spectrometry on a sample, outputting a lipid subclass result, and completing the establishment of the method in the second step; triggering and operating the second-step method, carrying out secondary mass spectrometry on the sample, outputting a fatty acid chain composition result, and completing the establishment of the third-step method; and thirdly, triggering and operating the method in the third step, carrying out secondary mass spectrometry on the photochemical derivative products, analyzing characteristic fragment ions, and outputting a lipid fine structure. Photochemical derivatization (Patern oa-Buchi reaction, PB reaction) can derivatize the carbon-carbon double bond in lipids to chemically relatively stable oxetanes, and the structures can be selectively fragmented easily by low-energy CIDs, the relative abundance of the generated qualitative and quantitative ions is high, and quantitative and qualitative analyses of lipids are facilitated. By using the lipid fine structure analysis process provided by the application, all data of the lipid fine structure can be obtained. All data on lipid fine structure include, but are not limited to, lipid subclasses, fatty acid chain composition, carbon-carbon double bond positions, and relative quantitative information.
In the lipid fine structure analysis process provided by the present application, an automatic mode or an auxiliary manual mode can be selected. In the automatic mode, all operations in the technical scheme can be automatically realized, including sample detection (such as automatic creation and triggering operation of a full-flow method, instrument control and the like) and automatic analysis of data containing result comparison, analysis, determination and output. The auxiliary manual mode supports full-process guidance, parameter generation of a secondary mass spectrum acquisition method and automatic data analysis, and only manual operation is needed for process method creation and triggering operation. When the analysis process uses an assisted manual mode, the full process guidance process will provide the main parameters of the process method, including but not limited to precursor ion information of the secondary mass spectrum, to assist the staff in creating the process method.
In the lipid analysis process of the present application, the retention time of the lipid can be calibrated in advance, so that the retention time information can be used in the subsequent analysis process. The specific operation is as follows: detecting the appointed sample according to a liquid chromatogram-first-order mass spectrum method, obtaining the retention time of different types of lipids by extracting the chromatogram of the accurate ion mass-to-charge ratio of the known lipids in the appointed sample, and correcting the retention time. Wherein one or more analyses of the lipid fine structure may be performed after the retention time correction is completed.
In the lipid fine structure analysis process provided by the application, the automatic creation and triggering operation of a full-process method are supported, and meanwhile, the automatic analysis of data is also supported. By automatically analyzing the result and automatically generating an instrument flow method or assisting workers in setting an instrument analysis method, the lipid components in the complex sample can be quickly analyzed, and the working efficiency of the workers is greatly improved on the basis of realizing accurate automatic analysis and relative quantification of the carbon-carbon double bond position in the lipid.
Preferably, the sample is a sample comprising a lipid or lipid analogue.
Preferably, the sample is any one of traditional Chinese medicine, biological tissue, food, an isolated detection sample of a human body or an animal body and artificially synthesized biological tissue.
In the present application, the sample may be a traditional Chinese medicine. In particular, the sample may be cordyceps.
In the present application, the sample may be a biological tissue. In particular, the sample may be bovine liver.
In the present application, the sample may be an ex vivo test sample of a human or animal body. In particular, the sample may be serum.
In the present application, the sample may be a food product. In particular, the sample may be fish.
Preferably, the lipid retention time information in step (1) can be used to distinguish lipids having the same or similar accurate ion mass but belonging to different species.
Preferably, the lipid retention time information in step (1) may be calibrated in advance, so that the lipid retention time information can be used in the subsequent analysis process.
Preferably, the photochemical derivation reagent used in step (3) is a carbonyl-containing double bond reagent or its corresponding derivative.
Preferably, the photochemical derivation reagent used in the step (3) is mixed in the mobile phase, so that on-line derivation and detection can be realized.
Preferably, the photochemically derived wavelength in step (3) is 190-760 nm.
Preferably, the database a, the database B and the database C point to the same database or different databases containing the required corresponding information.
By adopting the technical scheme, when the databases A, B and C point to the same database, the database includes but is not limited to the retention time of lipid and analogues thereof, the retention time of photochemical derivative products of lipid and analogues thereof, the first-order mass spectrum accurate ion mass-to-charge ratio of lipid and analogues thereof, the second-order mass spectrum accurate ion mass-to-charge ratio of lipid and analogues thereof, the third-order mass spectrum accurate ion mass spectrum of lipid and analogues thereof, the third-order mass spectrum accurate ion mass charge ratio of lipid and analogues thereof, and other information. When the database a, the database B and the database C point to different databases, the three databases respectively include, but are not limited to, the corresponding information required by the databases.
Preferably, the mobile phase solvent is one or a mixture of water, methanol, ethanol, acetonitrile, acetone, isopropanol, buffer salt, organic acid, inorganic acid, organic base and inorganic base.
Preferably, the molar ratio of photochemically derivatizing agent to sample may be 1X 10 -9 ～1×10 9 。
Preferably, the instrument used in mass spectrometry is a time-of-flight mass spectrometer, an ion trap mass spectrometer or a triple quadrupole mass spectrometer.
Preferably, the fragmentation energy is 1-200 eV or similar energy corresponding to an instrument used in the mass spectrometry.
Preferably, the light reaction time in the step (3) is 0.1-1200 s.
Preferably, the analysis process uses either an automatic mode or an assisted manual mode.
Wherein, under the automatic mode, all operations in the technical scheme can be automatically realized. The auxiliary manual mode supports full-process guidance, parameter generation of a secondary mass spectrum acquisition method and automatic data analysis, and only manual operation is needed for process method creation and triggering operation.
When the analysis process uses an assisted manual mode, the full process guidance process will provide the main parameters of the process method, including but not limited to precursor ion information of the secondary mass spectrum, to assist the staff in creating the process method.
In summary, the present application has the following beneficial effects:
1. the method for automatically or manually analyzing the lipid fine structure by using the photochemical reaction and mass spectrometry combined technology is provided for the first time, and an analysis process for analyzing the lipid fine structure by using the photochemical reaction and mass spectrometry combined technology is established.
2. The analysis process provided by the application can be used for efficiently and quickly carrying out accurate analysis on different lipid components in a complex lipid system, comprises the positioning of carbon-carbon double bond positions and the relative quantification of carbon-carbon double bond position isomers, and provides a novel efficient and easy-to-use tool for the biological research of lipid isomers.
3. By using the lipid fine structure analysis process provided by the application, all data of the lipid fine structure can be obtained. All data on lipid fine structure include, but are not limited to, lipid subclasses, fatty acid chain composition, carbon-carbon double bond positions, and relative quantitative information.
4. In the lipid fine structure analysis process provided by the application, the automatic creation and triggering operation of a full-process method are supported, and meanwhile, the automatic analysis of data is also supported. By automatically analyzing the result and automatically generating an instrument flow method or assisting workers in setting an instrument analysis method, the lipid components in the complex sample can be quickly analyzed, and the working efficiency of the workers is greatly improved on the basis of realizing accurate automatic analysis and relative quantification of the carbon-carbon double bond position in the lipid.
Drawings
FIG. 1 is a primary mass spectrum of Phosphatidylethanolamine (PE) lipid.
FIG. 2 is a primary mass spectrum of Phosphatidylcholine (PC) lipid.
Figure 3 is a graphical presentation of a lipid subclass information results interface for the control treatment system.
Fig. 4 is an interface display diagram showing the results of controlling the fatty acid chain composition of lipids of the treatment system.
FIG. 5 shows the secondary mass spectrum of PE (16:0/18: 1).
Fig. 6 is a graphical presentation of the results of the carbon-carbon double bond position in the lipids controlling the treatment system.
FIG. 7 shows the secondary mass spectrum of the photo-derived reaction product of PE (16:0/18:1 (. DELTA.9)).
Detailed Description
The application provides a lipid fine structure analysis process and a control processing system, wherein the control processing system has an instrument control function and has processing functions of data conversion, data analysis and report output.
The analysis process is executed by the control processing system and specifically comprises the following steps:
(1) detecting the sample by using liquid chromatography-primary mass spectrometry to obtain a primary mass spectrogram;
reading data of the primary mass spectrogram to obtain an accurate ion mass-to-charge ratio of the lipid primary mass spectrogram;
and comparing the obtained accurate ion mass-to-charge ratio with a database A, determining lipid subclass information by combining the lipid retention time information, and determining a next liquid chromatography-mass spectrometry acquisition method according to the lipid subclass information.
The sample is a sample comprising a lipid or lipid analogue.
The sample is any one of traditional Chinese medicine, biological tissue, food, in-vitro detection sample of human body or animal body, and artificially synthesized biological tissue.
Wherein the lipid retention time information can be used to distinguish between lipids having the same or similar accurate ion mass but belonging to different species.
The lipid retention time information can be calibrated in advance, so that the lipid retention time information can be used in the subsequent analysis process.
(2) Detecting a sample by using liquid chromatography-secondary mass spectrometry according to the liquid chromatography-mass spectrometry acquisition method determined in the step (1) to obtain a secondary mass spectrogram;
reading data of the secondary mass spectrogram to obtain an accurate ion mass-to-charge ratio of the lipid secondary mass spectrum;
comparing the obtained accurate ion mass-to-charge ratio with a database B to determine the composition of the fatty acid chains, and determining the next liquid chromatography-mass spectrometry acquisition method according to the composition of the fatty acid chains;
(3) according to the liquid chromatogram-mass spectrum collection method determined in the step (2), detecting a photochemical derivation product by utilizing liquid chromatogram separation-photochemical derivation-secondary mass spectrum to obtain a photochemical derivation-secondary mass spectrum;
reading the data of the second-order mass spectrogram of the photochemical derivation to obtain the accurate ion mass-to-charge ratio of the second-order mass spectrogram of the photochemical derivation product;
comparing the obtained accurate ion mass-to-charge ratio with a database C to determine the position of the carbon-carbon double bond in the lipid;
and determining relative quantitative information of the isomers at the position of the carbon-carbon double bond of the lipid according to the mass spectrum fragment intensity ratio or the intensity sum ratio of unsaturated lipid photochemical derivative products.
The photochemical derivation reagent used in the step (3) is a double bond reaction reagent containing carbonyl or a corresponding derivative thereof.
In the present application, the photochemical derivatizing agent used is acetone.
In this application, the wavelength of the photochemical derivatization in step (3) is 190-760 nm.
Wherein the mobile phase solvent is one or more of water, methanol, ethanol, acetonitrile, acetone, isopropanol, buffer salt, organic acid, inorganic acid, organic base and inorganic base.
In the present application, the molar ratio of photochemically derivatizing agent to sample may be 1X 10 -9 ～1×10 9 。
The instrument used in mass spectrometry is a time-of-flight mass spectrometer, an ion trap mass spectrometer or a triple quadrupole mass spectrometer.
In the application, the fragmentation energy adopted in the mass spectrometry is 1-200 eV or similar energy corresponding to the instrument.
In the application, the illumination reaction time in the step (3) is 0.1-1200 s.
The database A, the database B and the database C point to the same database or different databases containing the required corresponding information.
The lipid fine structure analysis process provided by the present application may use an automatic mode or an auxiliary manual mode.
When the analysis process adopts an automatic mode, the step (1) is preceded by the following steps: automated correction of specified sample retention time. The method specifically comprises the following steps: collecting a specified sample according to a liquid chromatography-first-level mass spectrometry method; the retention time of the specified species of lipid is extracted and automatically corrected for the retention time.
The application firstly provides a method for automatically analyzing or assisting manual lipid fine structure by using a photochemical reaction and mass spectrometry combined technology, and establishes an analysis process for analyzing the lipid fine structure by using the photochemical reaction and mass spectrometry combined technology. The analysis process provided by the application can be used for efficiently, quickly, systematically and simply carrying out accurate analysis on different lipid components in a complex lipid system, comprises the positioning of carbon-carbon double bond positions and the relative quantification of carbon-carbon double bond position isomers, and provides a new efficient and easy-to-use tool for lipid-biology research. By using the lipid fine structure analysis flow and the control processing system provided by the application, all data of the lipid fine structure can be obtained. All data on lipid fine structure include, but are not limited to, lipid subclasses, fatty acid chain composition, carbon-carbon double bond position, and isomer relative quantitative information.
The present application will be described in further detail below with reference to FIGS. 1 to 7, examples 1 to 4, and comparative example 1.
Examples
Example 1
This example provides a lipid fine structure analysis protocol.
Specifically, in this embodiment, an automatic mode is adopted, and the system is operated by an experimenter, and the lipid fine structure of the commercially available cordyceps sinensis is identified by using the liquid chromatography separation of the HILIC and the time-of-flight mass spectrometry detection and taking the commercially available cordyceps sinensis as a detection object.
Wherein the mass spectrum platform is Waters UPLC-QTOF.
A chromatographic system: ACQUITY UPLC I-Class (ultra high liquid chromatography); a chromatographic column: ACQUITY UPLC HILIC (100X 2.1mM, 1.7 μm), mobile phase acetone/acetonitrile (5/3, v/v) (A) -ammonium acetate in water (10mM) (B), flow rate: 0.4mL/min, gradient elution: 0min 88% A, 0.5min 85% A, 2.5min 85% A, 4.5min 88% A, 6min 88% A; injection volume 1 μ L, column temperature: at 30 ℃.
Mass spectrometry system: waters Xevo G2-XS QTOF (high resolution Mass Spectrometry); an acquisition mode: sensitivity mode ESI +, MSE, capillary voltage: 2.5 kV; taper hole voltage: 40V; source temperature: 120 ℃; temperature of atomized gas: 500 ℃; flow rate of atomizing gas: 800L/h; taper hole air flow rate: 50L/h; collection quality range: 50-1200; lock mass: leucine Enkephalin (LE)400 ng/mL; scanning time: 0.2 s; collision energy: low CE 6eV, High CE 10-45 eV.
The analysis process specifically comprises the following steps:
first, automatic correction of specified sample retention time
Collecting lipid such as PC (phosphatidylcholine), PE (phosphatidylethanolamine), PG (phosphatidylglycerol), PI (phosphatidylinositol), PS (phosphatidylserine) and SM (sphingomyelin) by liquid chromatography-primary mass spectrometry; the retention times of the above-mentioned various lipids were extracted and the retention times were automatically corrected.
Retention times for different lipids were obtained as shown in table 1.
TABLE 1 retention time of different lipids
| Lipid type | Retention time (min) | Lipid type | Retention time (min) |
| PC | 3.8-4.2 | PI | 1-1.5 |
| PE | 2.3-2.7 | PS | 4.5-6.0 |
| PG | 1-1.5 | SM | 4.1-4.6 |
Second, analysis of lipid component
Sample pre-treatment is required before lipid analysis.
Sample pretreatment: pulverizing commercially available Cordyceps 5g, sieving with 200 mesh sieve, collecting powder 50mg, adding CH 2 Cl 2 -CH 3 OH (2:1, V/V) (0 ℃) mixed solvent 1mL, vortexed and stood, added with water 1mL, centrifuged, removed organic phase nitrogen for drying, added with acetonitrile-isopropanol (CH) 3 CN-IPA, 1:1, V/V) mixed solvent of 500 mu L is redissolved, and after centrifugation of 10000r/min for 10min, the supernatant is taken to obtain sample treatment liquid;
(1) detecting the sample treatment solution by using liquid chromatography-primary mass spectrometry, automatically feeding a sample, and scanning the primary mass spectrometry to obtain a primary mass spectrogram;
interpreting the data of the primary mass spectrogram: the accurate ion mass-to-charge ratios of the primary mass spectra of the different lipids were obtained from table 1 and fig. 1 (primary mass spectrum of PE lipids) and fig. 2 (primary mass spectrum of PC lipids).
Comparing the obtained accurate ion mass-to-charge ratio with a database A, determining lipid subclasses by combining lipid retention time information, outputting lipid subclass results, and controlling a treatment system, wherein the result interface is shown in FIG. 3 and all the results are shown in Table 2.
Table 2 example 1-results of lipid subclass detection in cordyceps sinensis
As shown in table 2, the sample contained lipid subclass information of 30 PCs, 33 PEs, 41 PGs, 17 PIs, 13 PSs, 8 SMs. And automatically obtaining main parameters required by the second-step liquid chromatography-mass spectrometry instrument according to the obtained lipid subclass information, and generating a second-step liquid chromatography-mass spectrometry acquisition method.
(2) According to the liquid chromatogram-mass spectrum collection method determined in the step (1), detecting a sample by using a liquid chromatogram separation-secondary mass spectrum, automatically feeding a sample, and scanning the secondary mass spectrum to obtain a secondary mass spectrum.
And reading the data of the secondary mass spectrogram to obtain the accurate ion mass-to-charge ratio of the lipid secondary mass spectrum.
According to the obtained accurate ion mass-to-charge ratio, the fatty acid chain composition information is automatically obtained from the secondary mass spectrogram by comparing with the database B, the result interface of the control processing system is shown in figure 4, and all the results are shown in table 3.
Table 3 example 1-information on fatty acid chain composition in cordyceps sinensis
Taking PE (34:1) with serial number 41 as an example, with reference to the secondary mass spectrum of PE (16: 0-18: 1) in FIG. 5, the two fatty acid chains of 2 PE chains are 16:0 and 18:1, respectively, obtained by automatic software analysis.
As shown in Table 3, the fatty acid chain composition information of 28 PCs, 35 PEs, 18 PGs, 17 PIs, and 8 PSs was obtained by the software automatic analysis. And automatically obtaining main parameters required by the liquid chromatography-mass spectrometry instrument in the third step according to the obtained fatty acid chain composition information, and generating a liquid chromatography-mass spectrometry acquisition method in the third step.
(3) Enabling the light derivatization equipment to enter a PB reaction mode automatically by software, and scanning a photochemical derivatization product of the lipid product after the light derivatization reaction by utilizing a liquid chromatography separation-photochemical derivatization-secondary mass spectrum according to the liquid chromatography-mass spectrum acquisition method determined in the step (2) to obtain a photochemical derivatization-secondary mass spectrum;
interpretation of data from photochemical derivatization-secondary mass spectra: automatically obtaining the accurate ion mass-to-charge ratio of the secondary mass spectrum of the photochemical derivation product from the photochemical derivation-secondary mass spectrum;
the position of the carbon-carbon double bond in the lipid was determined from the exact ion mass-to-charge ratio obtained, compared to database C, and the resulting interface for control of the treatment system is shown in fig. 6, with all results in table 4.
TABLE 4 example 1-carbon double bond position and ion Strength information in Cordyceps sinensis
Taking PE (34:1) with the serial number of 10 as an example, the lipid fine structure can be obtained by automatic analysis through software and combining with the secondary mass spectrum of the light-derived reaction product of FIG. 7(PE (16:0/18:1 (. DELTA.9))) to obtain PE (16:0/18:1 (. DELTA.9)).
As shown in Table 4, 8 PC, 10 PE, 4 PG, 7 PI and 3 PS in the cordyceps lipid extract are finally obtained through the analysis process, and the structural information can be accurate to the carbon-carbon double bond position information.
Example 2
This example provides a lipid fine structure analysis protocol.
Specifically, in this embodiment, an auxiliary manual mode is adopted, the system is operated by an experimenter, and the lipid fine structure of the commercially available bovine liver polar lipid extract is identified by using HILIC liquid chromatography separation and time-of-flight mass spectrometry detection and taking the commercially available bovine liver polar lipid extract as a detection object.
Wherein the mass spectrum platform is AB-4500QTRAP liquid chromatography-mass spectrum tandem mass spectrometer (AB Sciex, USA).
A chromatographic system: a chromatographic column: HILIC column (150 mm. times.2.1 mm, silica spheres, 2.7 μm) (Sigma-Aldrich); the mobile phase was acetone/acetonitrile (50/50, v/v) (a) -ammonium acetate in water (10mM) (B) with flow rates: 0.2mL/min, gradient elution: 0min 90% A, 5min 85% A, 8min 80% A, 8-15 min 80% A, 16min 70% A, 20min 70% A; injection volume 2 μ L, column temperature: at 30 ℃.
Mass spectrometry system: NLS and PIS: electrospray ion source (ESI) positive ion mode; gas1, gas2 at 30psi, air curtain at 40psi, collision air: high, the electrospray voltage is 4500V, the gasification temperature is 400 ℃, the injection voltage is 10V, the cluster removing voltage is 150V, and the collision energy is 40 eV; LC-MSMS: electrospray ion source (ESI) negative ion mode; gas1, gas2 at 30psi, air curtain at 40psi, collision air: high, the electric spray voltage is 4500V, the gasification temperature is 400 ℃, and the collision energy is 40 eV; LC-PB-MSMS: electrospray ion source (ESI) positive ion mode; electrospray ion source (ESI) positive ion mode; gas1, gas2 at 30psi, air curtain at 40psi, collision air: high, the electrospray voltage is 4500V, the vaporization temperature is 400 ℃, the injection voltage is 10V, the cluster removing voltage is 150V, and the collision energy is 42 eV.
The analysis process specifically comprises the following steps:
first, automatic correction of specified sample retention time
The retention times for the different lipids were obtained as in "one, auto-calibration of specified sample retention times" in example 1.
Second, analysis of lipid component
Sample pre-treatment is required before lipid analysis.
Sample pretreatment: dissolving 100mg of a commercially available bovine liver polar lipid extract in 1mL of methanol to prepare a solution to be detected; when in use, the solution to be detected is diluted to obtain 100mg/L sample treatment solution;
(1) detecting the sample treatment solution by using liquid chromatography-primary mass spectrometry, setting a liquid phase sample injection and primary mass spectrometry scanning method on a liquid chromatography-mass spectrometry instrument by researchers, and triggering detection to obtain a primary mass spectrogram;
when the data acquisition is finished, a researcher leads result data of the primary mass spectrum into software for assisting manual analysis, and the software is operated to compare retention time of different lipids and the result of the primary mass spectrum, so that accurate ion mass-to-charge ratio of the lipid primary mass spectrum is obtained.
And comparing the obtained accurate ion mass-to-charge ratio with the database A, determining the lipid subclass by combining the lipid retention time information, and outputting the lipid subclass result as shown in table 5.
TABLE 5 example 2 detection of lipid subclasses in bovine liver polar lipid extract
As shown in table 5, this sample contained lipid subclass information for 34 PCs, 28 PEs, 22 PGs, 25 PIs, 7 PSs, 19 SMs. And automatically obtaining main parameters required by the second-step liquid chromatography-mass spectrometry instrument according to the obtained lipid subclass information.
(2) And (2) setting a liquid chromatography-mass spectrometry method according to the liquid chromatography-mass spectrometry acquisition method determined in the step (1), then controlling liquid phase sampling and secondary scanning of the mass spectrometry, triggering detection, and obtaining a secondary mass spectrogram.
When the data acquisition is finished, a researcher imports the data into software for assisting manual analysis, and the software automatically reads the data of the secondary mass spectrum to obtain the accurate ion mass-to-charge ratio of the lipid secondary mass spectrum.
And comparing the obtained accurate ion mass-to-charge ratio with the database B, and automatically obtaining the fatty acid chain composition information from the secondary mass spectrogram. As shown in table 6.
Table 6 example 2-fatty acid chain composition information in bovine liver polar lipid extract
As shown in table 6, the software automatically analyzed the fatty acid chain information of 43 kinds of PCs, 47 kinds of PE, 28 kinds of PG, 34 kinds of PI, 7 kinds of PS, and 1 kind of SM in total. And automatically generating main parameters required by the liquid chromatography-mass spectrometer in the third step according to the obtained fatty acid chain composition information.
(3) A researcher manually enables the light derivatization equipment to enter a PB reaction mode, sets a liquid chromatography-mass spectrometry method according to the liquid chromatography-mass spectrometry acquisition method determined in the step (2), controls liquid phase sample injection and mass spectrometry to scan the photochemical derivatization sample, triggers detection, and obtains a photochemical derivatization-secondary mass spectrogram;
when the data acquisition is finished, a researcher introduces the result data of the secondary mass spectrum into software for assisting manual analysis, and the software automatically obtains the accurate ion mass-to-charge ratio of the secondary mass spectrum of the photochemical derivative product from the photochemical derivative-secondary mass spectrogram;
from the exact ion mass to charge ratio obtained, the position of the carbon-carbon double bond in the lipid was determined by comparison with database C, as shown in table 7.
Table 7 example 2-carbon double bond position and ion intensity information in polar lipid extract of bovine liver
As shown in Table 7, through the above analysis process, 17 PCs, 11 PEs, 1 PI and 1 SM in the polar lipid extract of bovine liver can be finally obtained, and the structural information can be accurate to the position information of carbon-carbon double bonds.
Example 3
This example provides a lipid fine structure analysis protocol.
Specifically, the embodiment adopts an automatic mode, the system is operated by experimenters, HILIC liquid chromatography separation and quadrupole time-of-flight mass spectrometry are used, and the serum of the diabetes patient is taken as a detection object to identify the lipid fine structure of the serum of the diabetes patient.
Wherein the mass spectrum platform is Waters UPLC-QTOF.
A chromatographic system: ACQUITY UPLC I-Class; a chromatographic column: ACQUITY UPLC HILIC (100X 2.1mM, 1.7 μm), mobile phase acetone/acetonitrile (5/3, v/v) (A) -ammonium acetate in water (10mM) (B), flow rate: 0.4mL/min, gradient elution: 0min 88% A, 0.5min 85% A, 2.5min 85% A, 4.5min 88% A, 6min 88% A; injection volume 1 μ L, column temperature: at 30 ℃.
Mass spectrometry system: waters Xevo G2-XS QTOF; an acquisition mode: sensitivity mode ESI +, MSE, capillary voltage: 2.5 kV; taper hole voltage: 40V; source temperature: 120 ℃; temperature of atomized gas: 500 ℃; flow rate of atomizing gas: 800L/h; taper hole air flow rate: 50L/h; collection quality range: 50-1200; lock mass: leucine Enkephalin (LE)400 ng/mL; scanning time: 0.2 s; collision energy: low CE 6eV, High CE 10-45 eV.
The analysis process specifically comprises the following steps:
first, automatic correction of specified sample retention time
The retention times for the different lipids were obtained as in "one, auto-calibration of specified sample retention times" in example 1.
Second, analysis of lipid component
Sample pre-treatment is required before lipid analysis.
Sample pretreatment: adding CH into 30 μ L of blood serum of diabetes patient thawed at 4 deg.C 2 Cl 2 -CH 3 OH (2:1, V/V) (containing 0.1 g/L2, 6-di-tert-butyl-4-methylphenol, 0 ℃) mixed solvent 600 mu L, whirling and standing, adding water 200 mu L, centrifuging, removing organic phase nitrogen for drying, adding acetonitrile-isopropanol (CH) 3 CN-IPA, 1:1, V/V) mixed solvent of 500 mu L is redissolved, and the supernatant is taken after centrifugation of 10000r/min for 10min, thus obtaining sample treatment solution;
(1) detecting the sample treatment solution by using liquid chromatography-primary mass spectrometry, automatically feeding a sample, and scanning the primary mass spectrometry to obtain a primary mass spectrogram;
interpreting the data of the primary mass spectrogram: and comparing the retention time of different lipids and the result of the primary mass spectrum by software to obtain the accurate ion mass-to-charge ratio of the primary mass spectrum of different lipids.
And comparing the obtained accurate ion mass-to-charge ratio with the database A, determining lipid subclass information by combining the lipid retention time information, and outputting a lipid subclass result, wherein the results are shown in a table 8.
TABLE 8 example 3 results of lipid subclass assay in serum
As shown in table 8, this sample contained lipid subclass information for 37 PCs, 13 PEs, 27 PGs, 20 PIs, 16 PSs, 31 SMs. And automatically obtaining main parameters required by the second-step liquid chromatography-mass spectrometry instrument according to the obtained lipid subclass information, and generating a second-step liquid chromatography-mass spectrometry acquisition method.
(2) According to the liquid chromatogram-mass spectrum collection method determined in the step (1), detecting a sample by using a liquid chromatogram separation-secondary mass spectrum, automatically feeding a sample, and scanning the secondary mass spectrum to obtain a secondary mass spectrum.
And (3) reading data of the secondary mass spectrogram: obtaining the accurate ion mass-to-charge ratio of the lipid secondary mass spectrum.
According to the obtained accurate ion mass-to-charge ratio, the fatty acid chain composition information is obtained by comparing with the database B, as shown in Table 9.
Table 9 example 3 fatty acid chain composition information in serum
As shown in table 9, the fatty acid chain composition information of 71 PCs, 15 PEs, 6 PGs, 14 PIs, 1 PS and 11 SMs was automatically analyzed by the software. And automatically obtaining main parameters required by the liquid chromatography-mass spectrometry instrument in the third step according to the obtained fatty acid chain composition information, and generating a liquid chromatography-mass spectrometry acquisition method in the third step.
(3) Enabling the light derivatization equipment to enter a PB reaction mode automatically by software, and scanning a photochemical derivatization product of the lipid product after the light derivatization reaction by utilizing a liquid chromatography separation-photochemical derivatization-secondary mass spectrum according to the liquid chromatography-mass spectrum acquisition method determined in the step (2) to obtain a photochemical derivatization-secondary mass spectrum;
interpretation of data from photochemical derivatization-secondary mass spectra: automatically obtaining the accurate ion mass-to-charge ratio of the secondary mass spectrum of the photochemical derivation product from the photochemical derivation-secondary mass spectrum;
and comparing the obtained accurate ion mass-to-charge ratio with a database C to determine the position of the carbon-carbon double bond in the lipid. And determining the relative quantitative information of the lipid carbon-carbon double bond position isomers according to the mass spectrum fragment intensity ratio or the intensity sum ratio of the photochemical derivative products of the lipid carbon-carbon double bond position isomers, as shown in Table 10.
TABLE 10 EXAMPLE 3 carbon-carbon double bond position in serum and Ionic Strength information
As shown in Table 10, 32 PCs, 6 PEs, 1 PG, 1 PI, 1 PS and 10 SM in the serum lipid extract of the diabetic patients were finally obtained through the above analysis process, and the structural information could be accurate to the carbon-carbon double bond position. As shown in Table 10, 3 sets of two-bond positional isomers were detected in the serum samples, and the ratio of the sum of the qualitative ionic strengths of PC (16: 0-18: 1 (. DELTA.9)) and PC (16: 0-18: 1 (. DELTA.11)) was 2.40 in the case of PC (16: 0-18: 1).
Example 4
The embodiment provides a lipid fine structure analysis flow and a control processing system.
Specifically, in the embodiment, an auxiliary manual mode is adopted, the system is operated by experimenters, HILIC liquid chromatography separation and time-of-flight mass spectrometry are used, and the lipid fine structure of the fish lipid extract is identified by taking the fish lipid extract as a detection object.
Wherein the mass spectrum platform is AB-4500QTRAP liquid chromatogram-mass spectrum tandem mass spectrometer (AB Sciex company in USA).
A chromatographic system: a chromatographic column: HILIC column (150 mm. times.2.1 mm, silica spheres, 2.7 μm) (Sigma-Aldrich); the mobile phase was acetone/acetonitrile (50/50, v/v) (a) -ammonium acetate in water (10mM) (B) with flow rates: 0.2mL/min, gradient elution: 0min 90% A, 5min 85% A, 8min 80% A, 8-15 min 80% A, 16min 70% A, 20min 70% A; injection volume 2 μ L, column temperature: at 30 ℃.
Mass spectrometry system: NLS and PIS: electrospray ion source (ESI) positive ion mode; gas1, gas2 at 30psi, air curtain at 40psi, collision air: high, the electrospray voltage is 4500V, the gasification temperature is 400 ℃, the injection voltage is 10V, the cluster removing voltage is 150V, and the collision energy is 40 eV; LC-MSMS: electrospray ion source (ESI) negative ion mode; gas1, gas2 at 30psi, air curtain at 40psi, collision air: high, the electric spray voltage is 4500V, the gasification temperature is 400 ℃, and the collision energy is 40 eV; LC-PB-MSMS: electrospray ion source (ESI) positive ion mode; electrospray ion source (ESI) positive ion mode; gas1, gas2 at 30psi, air curtain at 40psi, collision air: high, the electrospray voltage is 4500V, the vaporization temperature is 400 ℃, the injection voltage is 10V, the cluster removing voltage is 150V, and the collision energy is 42 eV.
The analysis process specifically comprises the following steps:
first, automatic correction of specified sample retention time
The retention times for the different lipids were obtained as in "one, auto-calibration of specified sample retention times" in example 1.
Second, analysis of lipid component
Sample pre-treatment is required before lipid analysis.
The sample processing method comprises the following steps: chopping grass carp fish to obtain a fish sample, adding 1g of the fish sample into 10mL of ethanol, crushing in a homogenizer to obtain fish slurry, centrifuging, transferring 1mL of organic phase nitrogen for drying, adding 500 mu L of acetone for redissolving, centrifuging, transferring the organic phase nitrogen for drying, and obtaining a fish extract sample; dissolving 100mg of a fish extract sample in 1mL of methanol to obtain a sample treatment solution; when in use, the sample treatment solution is diluted to obtain 100mg/L solution for detection;
(1) detecting the sample treatment solution by using liquid chromatography-primary mass spectrometry, setting a liquid phase sample injection and primary mass spectrometry scanning method on a liquid chromatography-mass spectrometry instrument by researchers, and triggering detection to obtain a primary mass spectrogram;
when the data acquisition is finished, a researcher introduces the result data of the primary mass spectrum into software for assisting manual analysis, and the software is operated to compare the retention time of different lipids and the result of the primary mass spectrum, so as to obtain the accurate ion mass-to-charge ratio of the lipid primary mass spectrum.
And comparing the obtained accurate ion mass-to-charge ratio with the database A, determining the lipid subclass by combining the lipid retention time information, and outputting the lipid subclass result as shown in table 11.
TABLE 11 example 4 detection of lipid subclasses in Fish lipid extract
As shown in table 11, the sample contained lipid subclass information of 13 PCs, 7 PEs, 13 PGs, 12 PIs, 3 PSs, and 11 SMs. And automatically generating main parameters required by the second-step liquid chromatography-mass spectrometry instrument according to the obtained lipid subclass information.
(2) And (2) setting a liquid chromatography-mass spectrometry method according to the liquid chromatography-mass spectrometry acquisition method determined in the step (1), then controlling liquid phase sample injection and mass spectrometry secondary scanning, triggering detection, and obtaining a secondary mass spectrogram.
When the data acquisition is finished, a researcher imports the data into software for assisting manual analysis, and the software automatically reads the data of the secondary mass spectrum to obtain the accurate ion mass-to-charge ratio of the lipid secondary mass spectrum.
And comparing the obtained accurate ion mass-to-charge ratio with the database B, and automatically obtaining the fatty acid chain composition information from the secondary mass spectrogram. As shown in table 12.
Table 12 example 4-fatty acid chain composition information in fish lipid extract
As shown in table 12, the software analyzed the fatty acid chain information of 21 PC, 16 PE, 19 PG, 14 PI, and 4 PS lipids in total. And automatically generating main parameters required by the liquid chromatography-mass spectrometer in the third step according to the obtained fatty acid chain composition information.
(3) A researcher manually enables the light derivatization equipment to enter a PB reaction mode, sets a liquid chromatography-mass spectrometry method according to the liquid chromatography-mass spectrometry acquisition method determined in the step (2), controls liquid phase sampling and mass spectrometry to scan photochemical derivatization products, triggers detection, and obtains a photochemical derivatization-secondary mass spectrogram;
when the data acquisition is finished, a researcher introduces the result data of the secondary mass spectrum into software for assisting manual analysis, and the software automatically obtains the accurate ion mass-to-charge ratio of the secondary mass spectrum of the photochemical derivative product from the photochemical derivative-secondary mass spectrogram;
from the exact ion mass to charge ratio obtained, the position of the carbon-carbon double bond in the lipid was determined by comparison with database C, as shown in table 13.
Table 13 example 4-carbon double bond position and ionic strength information in fish lipid extract
As shown in table 13, 10 PCs, 8 PEs and 1 PI of the fish polar lipid extract were finally obtained through the above analysis procedure, and the structural information could be accurate to the carbon-carbon double bond position information.
Comparative example 1
This comparative example provides a procedure for lipid fine structure analysis.
The present comparative example differs from example 1 in that "step (3) is not present in the" second, lipid component analysis "step: and (3) detecting the photochemical derivative products by utilizing liquid chromatography separation-photochemical derivative-secondary mass spectrometry. The method comprises the following specific steps:
(1) and detecting the sample treatment solution by using liquid chromatography-primary mass spectrometry to obtain lipid subclass information of the sample containing 30 kinds of PC, 33 kinds of PE, 41 kinds of PG, 17 kinds of PI, 13 kinds of PS and 8 kinds of SM.
(2) And detecting the sample by using liquid chromatography-secondary mass spectrometry, and automatically analyzing by software to obtain the fatty acid chain structure information of 28 types of PC, 35 types of PE, 18 types of PG, 17 types of PI and 8 types of PS.
By comparing the detection results of example 1 and comparative example 1, it can be seen that the analysis procedure provided in comparative example 1 can only obtain lipid subclass information and fatty acid chain information of the sample, but cannot accurately obtain information on the position of the carbon-carbon double bond. The lipid fine structure analysis process provided by the application can obtain all data of the lipid fine structure. All data on lipid fine structure include, but are not limited to, lipid subclasses, fatty acid chain composition, carbon-carbon double bond position and relative quantitative information, especially positional information that can be accurate to carbon-carbon double bonds. The analysis process provided by the application can be used for efficiently and quickly carrying out accurate analysis on different lipid components in a complex lipid system, including the positioning of carbon-carbon double bond positions, so that the relative quantification of carbon-carbon double bond position isomers is realized, and a novel efficient and easy-to-use tool is provided for the biological research of lipid isomers.
In addition, in the lipid fine structure analysis process provided by the application, automatic creation and triggering operation of a full-process method are supported, and automatic analysis of data is also supported. By means of an automatic analysis result and an automatic generation instrument flow method or an analysis method set by auxiliary workers, lipid components in complex samples can be analyzed rapidly, and on the basis of realizing accurate automatic analysis and relative quantification of carbon-carbon double bond positions in lipid, the working efficiency of the workers is greatly improved. In the related art, all spectra need to be resolved manually in a method capable of being accurate to carbon-carbon double bonds, it takes 3-5min for a person skilled in resolving the spectra to resolve one mass spectrum, while in a large number of lipid analyses many mass spectra need to be analyzed, and generally, each sample analysis requires at least 1-2 days. Considering that the establishment of each step of the experimental method needs to be carried out after data is manually analyzed, the analysis speed of the sample is further reduced. Therefore, by utilizing the lipid fine structure analysis process provided by the application, the analysis time can be shortened to several seconds to several minutes, and if the process is in an automatic mode, the complexity of manual analysis and method establishment is saved, and the time spent on analyzing the lipid fine structure is greatly shortened.
The present embodiment is only for explaining the present application, and it is not limited to the present application, and those skilled in the art can make modifications of the present embodiment without inventive contribution as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present application.
Claims (10)
1. A lipid fine structure analysis process is characterized by comprising the following steps:
(1) detecting the sample by using liquid chromatography-primary mass spectrometry to obtain a primary mass spectrogram;
reading data of the primary mass spectrum to obtain an accurate ion mass-to-charge ratio of the lipid primary mass spectrum;
comparing the obtained accurate ion mass-to-charge ratio with a database A, determining lipid subclass information by combining the lipid retention time information, and determining a next liquid chromatography-mass spectrometry acquisition method according to the lipid subclass information;
(2) detecting a sample by using liquid chromatography-secondary mass spectrometry according to the liquid chromatography-mass spectrometry acquisition method determined in the step (1) to obtain a secondary mass spectrogram;
reading data of the secondary mass spectrogram to obtain an accurate ion mass-to-charge ratio of the lipid secondary mass spectrum;
comparing the obtained accurate ion mass-to-charge ratio with a database B to determine the composition of the fatty acid chains, and determining the next liquid chromatography-mass spectrometry acquisition method according to the composition of the fatty acid chains;
(3) according to the liquid chromatogram-mass spectrum collection method determined in the step (2), detecting a photochemical derivation product by utilizing liquid chromatogram separation-photochemical derivation-secondary mass spectrum to obtain a photochemical derivation-secondary mass spectrum;
reading data of the photochemical derivation-secondary mass spectrogram to obtain an accurate ion mass-to-charge ratio of the secondary mass spectrum of the photochemical derivation product;
comparing the obtained accurate ion mass-to-charge ratio with a database C to determine the position of the carbon-carbon double bond in the lipid;
and determining relative quantitative information of the isomers at the position of the carbon-carbon double bond of the lipid according to the mass spectrum fragment intensity ratio or the intensity sum ratio of unsaturated lipid photochemical derivative products.
2. The process of claim 1, wherein the lipid fine structure analysis comprises: the sample is a sample comprising a lipid or lipid analogue.
3. The process of claim 2, wherein the lipid fine structure analysis comprises: the sample is any one of traditional Chinese medicine, biological tissue, food, in-vitro detection sample of human body or animal body, and artificially synthesized biological tissue.
4. The process of claim 1, wherein the lipid fine structure analysis comprises: the lipid retention time information in step (1) can be used to distinguish lipids having the same or similar accurate ion mass but belonging to different species.
5. The process of claim 4, wherein the lipid fine structure analysis step comprises: the lipid retention time information in step (1) can be calibrated in advance, so that the lipid retention time information can be used in the subsequent analysis process.
6. The process of claim 1, wherein the lipid fine structure analysis comprises: the photochemical derivation reagent used in the step (3) is a double bond reaction reagent containing carbonyl or a corresponding derivative thereof.
7. The process of claim 1, wherein the lipid fine structure analysis comprises: and (3) mixing the photochemical derivation reagent used in the step (3) into a mobile phase to realize online derivation and detection.
8. The process of claim 1, wherein the lipid fine structure analysis comprises: the database A, the database B and the database C point to the same database or different databases containing the required corresponding information.
9. The process of claim 1, wherein the lipid fine structure analysis comprises: the analysis process uses either an automatic mode or an assisted manual mode.
10. A control processing system for performing the lipid fine structure analysis procedure of any one of claims 1 to 9, characterized by: the control processing system has an instrument control function and has processing functions of data conversion, data analysis and report output.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210380764.2A CN114894949B (en) | 2022-04-12 | 2022-04-12 | Lipid fine structure analysis flow and control processing system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210380764.2A CN114894949B (en) | 2022-04-12 | 2022-04-12 | Lipid fine structure analysis flow and control processing system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114894949A true CN114894949A (en) | 2022-08-12 |
| CN114894949B CN114894949B (en) | 2024-08-30 |
Family
ID=82717051
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210380764.2A Active CN114894949B (en) | 2022-04-12 | 2022-04-12 | Lipid fine structure analysis flow and control processing system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114894949B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118425382A (en) * | 2024-05-07 | 2024-08-02 | 中国农业科学院北京畜牧兽医研究所 | Method for identifying double bond position in linear unsaturated fatty acid in livestock and poultry meat based on photochemical reaction principle |
Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003028849A (en) * | 2001-07-10 | 2003-01-29 | Hiromasa Tojo | Simultaneous autoanalyzer for lipid compound |
| CN102565222A (en) * | 2011-12-26 | 2012-07-11 | 浙江大学 | Ion chromatography-online photochemical derivatization-fluorescence analysis system for measuring carbamazepine content in tablets |
| CN102565223A (en) * | 2011-12-26 | 2012-07-11 | 浙江大学 | System for detecting riboflavin in health care product through ion chromatography, on-line photochemical derivation and fluorescence analysis |
| CN105259277A (en) * | 2015-07-23 | 2016-01-20 | 中国科学院西北高原生物研究所 | Method for detecting residual quantity of 18 sulfanilamide drugs in beef and mutton |
| CN105911157A (en) * | 2016-04-08 | 2016-08-31 | 云南健牛生物科技有限公司 | Novel method for rapid detection of aflatoxin in food |
| CN107389779A (en) * | 2016-11-01 | 2017-11-24 | 苏州芷宁信息科技有限公司 | A kind of rapid analysis method of chemical constitution |
| EP3422005A1 (en) * | 2017-06-27 | 2019-01-02 | Medizinische Universität Graz | Determining enrichments of tracers of glucose by mass spectrometry |
| CN109148257A (en) * | 2017-06-28 | 2019-01-04 | 株式会社岛津制作所 | The lipid analytic method and mass spectrometer of mass spectral analysis are used |
| WO2019032049A1 (en) * | 2017-08-07 | 2019-02-14 | Agency For Science, Technology And Research | Rapid analysis and identification of lipids from liquid chromatography-mass spectrometry (lc-ms) data |
| CN109374723A (en) * | 2018-09-30 | 2019-02-22 | 中国农业科学院油料作物研究所 | A kind of free fatty acid mass spectrometry quantitative analysis method based on double Derivatives |
| CN109406687A (en) * | 2018-12-29 | 2019-03-01 | 清华大学 | A kind of high-throughput method for detecting double phosphatide |
| CN109507315A (en) * | 2018-11-15 | 2019-03-22 | 宁夏医科大学 | Complex samples GC-MS, which is automatically parsed, realizes that compound accurately identifies and the method for otherness component screening |
| CN109738532A (en) * | 2018-12-31 | 2019-05-10 | 复旦大学 | A method of automatically parsing stable isotope labeling sugar chain quantitative mass spectral data |
| CN110441383A (en) * | 2019-07-05 | 2019-11-12 | 清华大学 | Method based on epoxidation and Mass Spectrometric Identification unsaturated lipids carbon-carbon double bond position |
| CN110806456A (en) * | 2019-11-12 | 2020-02-18 | 浙江工业大学 | Method for automatically analyzing non-targeted metabolic Profile data in UPLC-HRMS Profile mode |
| CN111505135A (en) * | 2020-04-01 | 2020-08-07 | 清华大学 | Method for applying acetophenone derivatives to unsaturated lipid analysis |
| CN111902719A (en) * | 2018-02-19 | 2020-11-06 | 塞尔诺生物科学有限责任公司 | Reliable automated mass spectrometry |
| CN118150722A (en) * | 2024-01-08 | 2024-06-07 | 武汉大学中南医院 | Method for determining efficacy of cordyceps sinensis based on systemic biological response |
-
2022
- 2022-04-12 CN CN202210380764.2A patent/CN114894949B/en active Active
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003028849A (en) * | 2001-07-10 | 2003-01-29 | Hiromasa Tojo | Simultaneous autoanalyzer for lipid compound |
| CN102565222A (en) * | 2011-12-26 | 2012-07-11 | 浙江大学 | Ion chromatography-online photochemical derivatization-fluorescence analysis system for measuring carbamazepine content in tablets |
| CN102565223A (en) * | 2011-12-26 | 2012-07-11 | 浙江大学 | System for detecting riboflavin in health care product through ion chromatography, on-line photochemical derivation and fluorescence analysis |
| CN105259277A (en) * | 2015-07-23 | 2016-01-20 | 中国科学院西北高原生物研究所 | Method for detecting residual quantity of 18 sulfanilamide drugs in beef and mutton |
| CN105911157A (en) * | 2016-04-08 | 2016-08-31 | 云南健牛生物科技有限公司 | Novel method for rapid detection of aflatoxin in food |
| CN107389779A (en) * | 2016-11-01 | 2017-11-24 | 苏州芷宁信息科技有限公司 | A kind of rapid analysis method of chemical constitution |
| EP3422005A1 (en) * | 2017-06-27 | 2019-01-02 | Medizinische Universität Graz | Determining enrichments of tracers of glucose by mass spectrometry |
| CN109148257A (en) * | 2017-06-28 | 2019-01-04 | 株式会社岛津制作所 | The lipid analytic method and mass spectrometer of mass spectral analysis are used |
| WO2019032049A1 (en) * | 2017-08-07 | 2019-02-14 | Agency For Science, Technology And Research | Rapid analysis and identification of lipids from liquid chromatography-mass spectrometry (lc-ms) data |
| CN111902719A (en) * | 2018-02-19 | 2020-11-06 | 塞尔诺生物科学有限责任公司 | Reliable automated mass spectrometry |
| CN109374723A (en) * | 2018-09-30 | 2019-02-22 | 中国农业科学院油料作物研究所 | A kind of free fatty acid mass spectrometry quantitative analysis method based on double Derivatives |
| CN109507315A (en) * | 2018-11-15 | 2019-03-22 | 宁夏医科大学 | Complex samples GC-MS, which is automatically parsed, realizes that compound accurately identifies and the method for otherness component screening |
| CN109406687A (en) * | 2018-12-29 | 2019-03-01 | 清华大学 | A kind of high-throughput method for detecting double phosphatide |
| CN109738532A (en) * | 2018-12-31 | 2019-05-10 | 复旦大学 | A method of automatically parsing stable isotope labeling sugar chain quantitative mass spectral data |
| CN110441383A (en) * | 2019-07-05 | 2019-11-12 | 清华大学 | Method based on epoxidation and Mass Spectrometric Identification unsaturated lipids carbon-carbon double bond position |
| CN110806456A (en) * | 2019-11-12 | 2020-02-18 | 浙江工业大学 | Method for automatically analyzing non-targeted metabolic Profile data in UPLC-HRMS Profile mode |
| CN111505135A (en) * | 2020-04-01 | 2020-08-07 | 清华大学 | Method for applying acetophenone derivatives to unsaturated lipid analysis |
| CN118150722A (en) * | 2024-01-08 | 2024-06-07 | 武汉大学中南医院 | Method for determining efficacy of cordyceps sinensis based on systemic biological response |
Non-Patent Citations (2)
| Title |
|---|
| 蒋潇潇 等: "光化学反应-串联质谱法鉴定细胞中不饱和卵磷脂双键的位置", 分析化学, vol. 45, no. 12, pages 1988 - 1995 * |
| 马潇潇 等: "Paternò-Büchi(PB)反应与串联质谱结合实现不饱和脂质精确结构解析", 分析测试学报, vol. 39, no. 01, pages 19 - 27 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118425382A (en) * | 2024-05-07 | 2024-08-02 | 中国农业科学院北京畜牧兽医研究所 | Method for identifying double bond position in linear unsaturated fatty acid in livestock and poultry meat based on photochemical reaction principle |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114894949B (en) | 2024-08-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11921122B2 (en) | Methods for detecting vitamin D metabolites by mass spectrometry | |
| US12066446B2 (en) | Methods for detecting dihydroxyvitamin D metabolites by mass spectrometry | |
| US11061005B2 (en) | Mass spectrometry assay method for detection and quantitation of organic acid metabolites | |
| US8617898B2 (en) | Quantitative analysis of vitamin D3, vitamin D2, and metabolites thereof | |
| EP2633325B1 (en) | Lc-ms separation and detection of vitamin d metabolites | |
| CA2779688C (en) | Quantitation of insulin-like growth factor-i and insulin-like growth factor-ii with high-resolution mass spectrometry | |
| JP6462020B2 (en) | Detection method of reverse triiodothyronine by mass spectrometry | |
| WO2006107992A2 (en) | Methods for detecting vitamin d metabolites by mass spectrometry | |
| CN107064330A (en) | Pass through mass spectrography quantitative insulin | |
| CN111936851A (en) | Methods and systems for detecting vitamin D metabolites | |
| CN109781909A (en) | A kind of detection method and kit of human serum 25-hydroxy-vitamin D | |
| CN114894949A (en) | Lipid fine structure analysis process and control processing system | |
| CN108593790B (en) | Method for simultaneously detecting 24,25(OH)2D and 25OHD of serum | |
| CN116183801A (en) | Liquid chromatography-mass spectrometry method, kit and system for detecting insulin and C peptide | |
| CN114280192B (en) | Method for detecting vitamin D and metabolite thereof | |
| Luo et al. | Comparison of liquid chromatography-high-resolution tandem mass spectrometry (MS2) and multi-stage mass spectrometry (MS3) for screening toxic natural products | |
| KR20060123270A (en) | Method for the determination of 25-hydroxycholecalciferol in feed | |
| EP3654032B1 (en) | Disease detection method | |
| CN117334257A (en) | Lucid ganoderma multi-level screening mass spectrum database and establishment method and application thereof | |
| AU2023248408A1 (en) | Detection of insulin-like growth factor-2 variants by mass spectrometry | |
| CN116046929A (en) | Qualitative and quantitative analysis method for unsaturated lipid isomer based on microwave-assisted MMPP epoxidation technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |