CN111693597A - Identification method of ganglioside with high coverage and application thereof - Google Patents
Identification method of ganglioside with high coverage and application thereof Download PDFInfo
- Publication number
- CN111693597A CN111693597A CN202010538078.4A CN202010538078A CN111693597A CN 111693597 A CN111693597 A CN 111693597A CN 202010538078 A CN202010538078 A CN 202010538078A CN 111693597 A CN111693597 A CN 111693597A
- Authority
- CN
- China
- Prior art keywords
- ganglioside
- gangliosides
- candidate
- identifying
- acquisition
- 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.)
- Pending
Links
- 150000002270 gangliosides Chemical class 0.000 title claims abstract description 104
- 238000000034 method Methods 0.000 title claims abstract description 45
- 239000012634 fragment Substances 0.000 claims abstract description 28
- 238000006243 chemical reaction Methods 0.000 claims abstract description 19
- 238000012544 monitoring process Methods 0.000 claims abstract description 19
- 238000012216 screening Methods 0.000 claims abstract description 11
- 238000012795 verification Methods 0.000 claims abstract description 3
- 150000002500 ions Chemical class 0.000 claims description 62
- 238000001819 mass spectrum Methods 0.000 claims description 39
- 238000004458 analytical method Methods 0.000 claims description 10
- 238000004949 mass spectrometry Methods 0.000 claims description 9
- 150000001875 compounds Chemical class 0.000 claims description 7
- 238000000605 extraction Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 4
- 230000000155 isotopic effect Effects 0.000 claims description 2
- 239000000523 sample Substances 0.000 abstract description 8
- 239000012472 biological sample Substances 0.000 abstract description 4
- 230000035945 sensitivity Effects 0.000 abstract description 4
- 238000004885 tandem mass spectrometry Methods 0.000 description 18
- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 description 12
- 210000004556 brain Anatomy 0.000 description 7
- 239000000243 solution Substances 0.000 description 5
- 238000001228 spectrum Methods 0.000 description 5
- 230000004907 flux Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000002347 injection Methods 0.000 description 3
- 239000007924 injection Substances 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 150000002482 oligosaccharides Polymers 0.000 description 3
- YDNKGFDKKRUKPY-JHOUSYSJSA-N C16 ceramide Natural products CCCCCCCCCCCCCCCC(=O)N[C@@H](CO)[C@H](O)C=CCCCCCCCCCCCCC YDNKGFDKKRUKPY-JHOUSYSJSA-N 0.000 description 2
- 229940106189 ceramide Drugs 0.000 description 2
- ZVEQCJWYRWKARO-UHFFFAOYSA-N ceramide Natural products CCCCCCCCCCCCCCC(O)C(=O)NC(CO)C(O)C=CCCC=C(C)CCCCCCCCC ZVEQCJWYRWKARO-UHFFFAOYSA-N 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- CERZMXAJYMMUDR-UHFFFAOYSA-N neuraminic acid Natural products NC1C(O)CC(O)(C(O)=O)OC1C(O)C(O)CO CERZMXAJYMMUDR-UHFFFAOYSA-N 0.000 description 2
- VVGIYYKRAMHVLU-UHFFFAOYSA-N newbouldiamide Natural products CCCCCCCCCCCCCCCCCCCC(O)C(O)C(O)C(CO)NC(=O)CCCCCCCCCCCCCCCCC VVGIYYKRAMHVLU-UHFFFAOYSA-N 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 238000010175 APPswe/PSEN1dE9 Methods 0.000 description 1
- 102000003886 Glycoproteins Human genes 0.000 description 1
- 108090000288 Glycoproteins Proteins 0.000 description 1
- BZLVMXJERCGZMT-UHFFFAOYSA-N Methyl tert-butyl ether Chemical compound COC(C)(C)C BZLVMXJERCGZMT-UHFFFAOYSA-N 0.000 description 1
- CRJGESKKUOMBCT-VQTJNVASSA-N N-acetylsphinganine Chemical compound CCCCCCCCCCCCCCC[C@@H](O)[C@H](CO)NC(C)=O CRJGESKKUOMBCT-VQTJNVASSA-N 0.000 description 1
- 206010028980 Neoplasm Diseases 0.000 description 1
- 238000003556 assay Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- SQVRNKJHWKZAKO-UHFFFAOYSA-N beta-N-Acetyl-D-neuraminic acid Natural products CC(=O)NC1C(O)CC(O)(C(O)=O)OC1C(O)C(O)CO SQVRNKJHWKZAKO-UHFFFAOYSA-N 0.000 description 1
- 210000005013 brain tissue Anatomy 0.000 description 1
- 201000011510 cancer Diseases 0.000 description 1
- 238000000738 capillary electrophoresis-mass spectrometry Methods 0.000 description 1
- 210000004027 cell Anatomy 0.000 description 1
- 210000000170 cell membrane Anatomy 0.000 description 1
- 239000000287 crude extract Substances 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000003795 desorption Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000004108 freeze drying Methods 0.000 description 1
- 238000002290 gas chromatography-mass spectrometry Methods 0.000 description 1
- 150000002339 glycosphingolipids Chemical class 0.000 description 1
- 238000004896 high resolution mass spectrometry Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000000050 ionisation spectroscopy Methods 0.000 description 1
- 150000002632 lipids Chemical class 0.000 description 1
- 238000004811 liquid chromatography Methods 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 230000004879 molecular function Effects 0.000 description 1
- 238000010172 mouse model Methods 0.000 description 1
- 210000000653 nervous system Anatomy 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
- 238000000746 purification Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- SQVRNKJHWKZAKO-OQPLDHBCSA-N sialic acid Chemical compound CC(=O)N[C@@H]1[C@@H](O)C[C@@](O)(C(O)=O)OC1[C@H](O)[C@H](O)CO SQVRNKJHWKZAKO-OQPLDHBCSA-N 0.000 description 1
- 230000019491 signal transduction Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 210000000225 synapse Anatomy 0.000 description 1
- 238000010257 thawing Methods 0.000 description 1
- 238000011830 transgenic mouse model Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/62—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating the ionisation of gases, e.g. aerosols; by investigating electric discharges, e.g. emission of cathode
Landscapes
- Chemical & Material Sciences (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Electrochemistry (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth 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 invention relates to a method for identifying ganglioside with high coverage and application thereof, comprising the following steps: (1) acquiring data of a sample by using a data independent acquisition method in a negative ion mode to obtain original data; (2) deconvoluting the original data to obtain parent ion and fragment ion information; (3) screening the ion to obtain candidate ganglioside; (4) removing non-rational candidate gangliosides; (5) and (4) carrying out negative ion parallel reaction monitoring verification on the obtained result, and analyzing the result to obtain a ganglioside identification result. The method is used for identifying the ganglioside, has high sensitivity and wide coverage, can detect trace ganglioside in a small amount of biological samples, and has good application prospect in the field of metabonomics.
Description
Technical Field
The invention belongs to the technical field of mass spectrometry, and particularly relates to a ganglioside identification method and application thereof, in particular to a ganglioside identification method with high coverage and application thereof.
Background
Gangliosides are a class of glycosphingolipids consisting of a ceramide molecule and an oligosaccharide core containing sialic acid. They are present on the surface of cell membranes in the form of lipid rafts, vesicles, domains and synapses, with oligosaccharide chains protruding extracellularly, interacting with other gangliosides or glycoproteins from neighboring cells to perform various molecular functions, such as adhesion and signal transduction. Gangliosides are particularly abundant in the nervous system, and furthermore, precise analysis of gangliosides is becoming increasingly important in functional studies associated with cancer. Therefore, it is very important to develop a high coverage assay for ganglioside identification.
The mass spectrometric identification of different gangliosides is a challenging problem due to similar physicochemical properties, variable oligosaccharide chain structures and ceramide fatty acid chain lengths. The high-resolution mass spectrometry technology is the mainstream of the technology due to the excellent multi-stage mass spectrometry capability and high resolution. At present, mass spectrometry technologies such as gas chromatography/mass spectrometry, matrix-assisted laser desorption/ionization/mass spectrometry imaging, ion mobility mass spectrometry, capillary electrophoresis/mass spectrometry, liquid chromatography/mass spectrometry and the like are well applied to ganglioside analysis, but the existing methods have advantages and disadvantages.
Because of the inherent limitations of the prior art and the low natural abundance of gangliosides, it is often necessary to extract gangliosides from large amounts of biological samples, such as by the most classical "Folch" method followed by C18 purification, to greatly increase the analytical coverage, which is too complicated to perform, and it would therefore be of great interest to develop a high coverage method for identifying gangliosides.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a ganglioside identification method and application thereof, in particular to a ganglioside identification method with high coverage and application thereof.
In order to achieve the purpose, the invention adopts the following technical scheme:
in one aspect, the present invention provides a high coverage ganglioside identification method, comprising the steps of:
(1) acquiring data of a sample containing ganglioside by a mass spectrometer in a negative ion mode by using a data-independent acquisition method to obtain original data;
(2) deconvoluting the original data to obtain parent ion and fragment ion information;
(3) screening the ion to obtain candidate ganglioside;
(4) carrying out parent ion peak extraction on the candidate ganglioside, and removing unreasonable candidate ganglioside;
(5) and (4) carrying out negative ion parallel reaction monitoring verification on the result obtained in the step (4) by adopting a mass spectrometer, and analyzing the result to obtain a ganglioside identification result.
The high coverage degree refers to that in a sample with a certain content of ganglioside, the identified ganglioside types are more abundant, and 137 ganglioside types are identified in the invention when the ganglioside in the brain tissue of a mouse is identified.
The identification method is an identification method based on data-independent and parallel reaction monitoring mass spectrum acquisition, the data-independent mass spectrum acquisition is combined with fragment ion screening for the first time, all potential ganglioside is are analyzed, the ganglioside comprises ganglioside containing N-glycosyl neuraminic acid and modified ganglioside, and then targeted parallel reaction monitoring analysis is obtained by utilizing gradient collision energy, and high-sensitivity identification and structure analysis are carried out on low-abundance ganglioside. The method is used for identifying the ganglioside, has high sensitivity and wide coverage, can detect trace ganglioside in a small amount of biological samples, and has good application prospect in the field of metabonomics.
Preferably, the mass spectrometer of step (1) is a Q-active mass spectrometer.
Preferably, the data collection in step (1) is performed in the negative ion mode by using 20-28 continuous mass windows in the range of 600-1800m/z, and the window width is 50-65 m/z.
The number of mass windows may be 20, 21, 22, 23, 24, 25, 26, 27 or 28.
The window width of the mass window can be 50m/z, 52m/z, 55m/z, 58m/z, 60m/z, 62m/z, 63m/z or 65m/z, and any other point value in the above range can be selected, and is not repeated herein.
Preferably, the primary mass spectrum acquisition resolution in the data acquisition process in the step (1) is 70000-140000, such as 70000 or 140000; the secondary mass spectrum acquisition resolution is 17500-70000, such as 17500, 35000 or 70000, and any other point value in the above range can be selected, which is not described herein again.
Preferably, the automatic gain control of the primary mass spectrum acquisition in the data acquisition process of the step (1) is 1 × 106-3×106E.g. 1 × 106Or 3 × 106And any other point value in the range can be selected, which is not described in detail herein, and the automatic gain control of the secondary mass spectrum acquisition is 1 × 105-5×105E.g. 1 × 105、2×105Or 5 × 105And the other arbitrary point values in the above range can be selected, and are not described in detail herein.
Preferably, the step (1) is performed by using a step energy for the secondary mass spectrometric acquisition collision energy during the data acquisition, wherein the energy is set to 5-10eV (such as 5eV, 6eV, 7eV, 8eV, 9eV, or 10 eV), 25-30eV (such as 25eV, 26eV, 27eV, 28eV, 29eV, or 30 eV), and 32-40eV (such as 32eV, 34eV, 35eV, 37eV, 38eV, or 40 eV).
Specifically, the specific operation of the step (1) is to adopt a data-independent acquisition method in a negative ion mode to acquire the ganglioside sample, wherein the acquisition parameters comprise that 20-28 continuous mass windows are used in the range of 600-1800m/z and the negative ion mode is adopted to acquire the ganglioside sample, the window width is 50-65m/z, the primary mass spectrum acquisition resolution is 70000-140000, the secondary mass spectrum acquisition resolution is 17500-70000, and the primary mass spectrum acquisition AGC target (automatic gain control) is set to be 1 × 106-3×106The second-order mass spectrum acquisition AGC target (automatic gain control) is set at 1 × 105-5×105(ii) a Setting maximum injection time (maximum injection time) of primary and secondary mass spectrum acquisition at 50-200 ms; the secondary mass spectrum acquisition collision energy adopts stepping energy, and the energy value is set to be 5-10, 25-30 and 32-40 eV.
Preferably, the operation of deconvolving the raw data in the step (2) to obtain the information of the parent ions and the fragment ions specifically includes: the obtained raw data is deconvoluted using the open source software MS-DIAL to achieve the grouping of parent and fragment ions.
Specifically, step (2)The specific operation is as follows: deconvoluting the obtained data independent of the original data by using open source software MS-DIAL to realize the grouping of the parent ions and the fragment ions; the matching parameters are as follows: MS1 tolerance (first mass spectrum tolerance mass deviation) is set to be 0.005-0.01 Da, MS2 tolerance (second mass spectrum tolerance mass deviation) is set to be 0.005-0.025 Da; minimum peak height was set to 3000 + 10000; molecular species are set to [ M-H ]]-And [ M-2H]2-(ii) a The retention time tolerance is set to 0.02-0.1 min; the sigma window value (sigma window width) is set to be 0.2-0.5, and other parameters are default parameters; and deriving a parent ion and fragment ion grouping list in the MS/MS.
Preferably, the step (3) of screening the ion to obtain the candidate ganglioside specifically comprises: screening the compound obtained in step (2) by using 290.0880 +/-10 ppm characteristic fragments, and regarding the compound containing the fragments as candidate ganglioside.
Preferably, the non-rational candidate gangliosides of step (4) include poor peaked candidate gangliosides, candidate gangliosides derived from blank background, candidate gangliosides derived from isotopic peaks, and candidate gangliosides with more than 3 charges.
The "poorly peaked candidate gangliosides" referred to above means that the peaks are asymmetrically shaped.
Preferably, the mass spectrometer of step (5) is a Q-active mass spectrometer.
Preferably, the secondary mass spectrum acquisition resolution in the negative ion parallel reaction monitoring process in step (5) is 17500-70000, such as 17500, 35000 or 70000, and any other point value within the above range can be selected, which is not described herein again.
Preferably, the automatic gain control of secondary mass spectrum acquisition in the negative ion parallel reaction monitoring process in the step (5) is 1 × 105-5×105E.g. 1 × 105、2×105Or 5 × 105And the other arbitrary point values in the above range can be selected, and are not described in detail herein.
Preferably, the secondary mass spectrum collection collision energy in the negative ion parallel reaction monitoring process in step (5) adopts a single energy, and the energy values are sequentially set to 5-10eV (such as 5eV, 6eV, 7eV, 8eV, 9eV, 10eV, etc.), 15-25eV (such as 15eV, 18eV, 20eV, 22eV, 24eV, 25eV, etc.), and 28-35eV (such as 28eV, 29eV, 30eV, 32eV, 34eV, 35eV, etc.).
Preferably, the parsing the result in step (5) includes: and analyzing by using LipidSearch software and/or a LipidMaps database, and outputting a ganglioside identification list.
Specifically, the specific operation of step (5) is: carrying out negative ion parallel reaction monitoring mass spectrum acquisition on the result obtained in the step (4); the acquisition parameters are as follows: the secondary mass spectrum acquisition resolution is set to 17500-70000, the AGC target (automatic gain control) is set to 1E5-5E5, and the maximum IT (maximum injection time) is set to 50-200 ms; the collision energy is respectively collected by adopting three separate energies which are respectively set at 5-10, 15-25 and 28-35 eV; and automatically analyzing the obtained result by LipidSearch software and combining manual checking, manually deducing unknown components by referring to a LipidMaps database and combining fragment ions, and outputting a ganglioside identification list.
In another aspect, the present invention provides the use of a high coverage ganglioside identification method as described above for identifying gangliosides.
Compared with the prior art, the invention has the following beneficial effects:
the identification method is an identification method based on data-independent and parallel reaction monitoring mass spectrum acquisition, the data-independent mass spectrum acquisition is combined with fragment ion screening for the first time, all potential ganglioside is are analyzed, the ganglioside comprises ganglioside containing N-glycosyl neuraminic acid and modified ganglioside, and then targeted parallel reaction monitoring analysis is obtained by utilizing gradient collision energy, and high-sensitivity identification and structure analysis are carried out on low-abundance ganglioside. The method is used for identifying the ganglioside, has high sensitivity and wide coverage, can detect trace ganglioside in a small amount of biological samples, and has good application prospect in the field of metabonomics.
Drawings
FIG. 1 is a schematic flow diagram of a method for identifying gangliosides in accordance with the present invention;
FIG. 2 is the MS/MS spectrum of the mixed ganglioside standard of example 1;
FIG. 3 is a spectrum of the deconvolution MS/MS of the mixed ganglioside standard of example 1;
FIG. 4 is a parallel reaction monitoring MS/MS spectrum of GT1b (38:1) in the mixed ganglioside standard of example 1;
FIG. 5 is a total ion flux chromatogram (marked as a solid line) and a ganglioside extraction ion flux chromatogram (marked as a dashed line) of a mouse brain extract in example 2.
Detailed Description
The technical solution of the present invention is further explained by the following embodiments. It should be understood by those skilled in the art that the examples are only for the understanding of the present invention and should not be construed as the specific limitations of the present invention.
Example 1
In this example, GT1b (38:1) was identified in the mixed ganglioside standard by the following procedure:
(1) sample pretreatment: the mixed ganglioside standard was dissolved in 10% methanol solution at a concentration of 30. mu.g/mL.
(2) The method comprises the steps of adopting a data independent acquisition method in a negative ion mode to acquire samples, wherein acquisition parameters comprise that 22 continuous mass windows are used for acquisition in the range of 600-1800m/z, the window width is 60 m/z., the acquisition resolution of primary and secondary mass spectra is 70000 and 17500 respectively, and AGC targets (automatic gain control) for acquisition of the primary and secondary mass spectra are set to be 3 × 106And 1 × 105. The primary and secondary mass spectrometric acquisitions maximum IT are set at 200ms and 50ms, respectively. The secondary mass spectrum acquires collision energy by adopting stepping energy, the energy values are set to be 10, 28 and 35eV, and an original MS/MS spectrogram is finally obtained, as shown in FIG. 2.
(3) Using software MS-DIAL to make the data obtained in step (2) independent of the original dataAnd performing deconvolution to realize the grouping of the parent ions and the fragment ions. The matching parameters are as follows: MS1 tolerance is set to 0.01Da, MS2 tolerance is set to 0.025Da, minimum peak light is set to 5000, molecular species is set to [ M-H [ ]]-And [ M-2H]2-The retentition time tolerance is set to 0.05min, the sigma window value is set to 0.3, and other parameters are default parameters. And obtaining a deconvolution MS/MS spectrogram, and deriving a parent ion and fragment ion grouping list in the MS/MS. The deconvolved MS/MS spectrum is shown in FIG. 3.
(4) Characteristic fragment ion screening was performed using 290.0880 + -10 ppm and compounds containing the fragment were defined as candidate gangliosides.
(5) Unreasonable candidate ganglioside with peak shape difference, blank background, isotope peak and charge more than 3 is removed by primary mass spectrum peak extraction.
(6) And (4) carrying out negative ion parallel reaction monitoring mass spectrum acquisition on the result obtained in the step (5), wherein the acquisition parameters comprise that the secondary mass spectrum acquisition resolution is set at 17500, and the AGC target is set at 1 × 105Maximum IT is set at 50 ms. The collision energy was collected using three separate energy sources, set at 10, 20, and 30eV, respectively. A parallel reaction monitoring MS/MS spectrum was obtained as shown in FIG. 4.
(7) Automatically analyzing the result obtained in the step (6) by LipidSearch software and combining manual checking; and (3) manually deducing the MS/MS spectrogram by referring to a LipidMaps database and combining fragment ion analysis on the unknown components. The parent ion mass deviation is set to less than 5ppm and the fragment ion is set to less than 20 ppm. The ganglioside identification list is exported.
Example 2
This example identifies gangliosides in mouse brain by the following procedure:
(1) mouse brain pretreatment: after thawing, 10mg of rat brain (mouse model APP/PS1 transgenic mouse, rat brain from Jiangsu Elaeagni Biotech, Inc.) was sampled, and 100. mu.L water and 300. mu.L methanol were added. Grind with a ball mill set at 25Hz for 2min and repeat 2 times. The resulting homogenate was extracted with 200. mu.L of water and 1000. mu.L of MTBE with shaking for 1 hour, followed by standing for separation, taking 400. mu.L of the aqueous layer, freeze-drying, and redissolving in 40. mu.L of a 10% methanol solution.
(2) Taking the ganglioside crude extract obtained in the step (1) and a blank control (10% methanol solution) as an analysis sample to carry out mass spectrum detection, adopting a data-independent acquisition method in a negative ion mode to carry out data acquisition on the sample, wherein the acquisition parameters comprise that 22 continuous mass windows are used for acquisition in the range of 600-1800m/z, the window width is 60 m/z., the acquisition resolution of primary and secondary mass spectra is 70000 and 17500 respectively, and the AGC target (automatic gain control) for the primary and secondary mass spectra acquisition is respectively set at 3 × 106And 1 × 105. The primary and secondary mass spectrometric acquisitions maximum IT are set at 200ms and 50ms, respectively. The secondary mass spectrum acquires collision energy by adopting stepping energy, the energy values are set to be 10, 28 and 35eV, and an original MS/MS spectrogram is finally obtained.
(3) And (3) deconvoluting the independent original data of the data obtained in the step (2) by using software MS-DIAL to realize the grouping of the parent ions and the fragment ions. The matching parameters are as follows: MS1 tolerance is set to 0.01Da, MS2 tolerance is set to 0.025Da, minimum peak light is set to 5000, molecular species is set to [ M-H [ ]]-And [ M-2H]2-The retentition time tolerance is set to 0.05min, the sigma window value is set to 0.3, and other parameters are default parameters. And obtaining a deconvolution MS/MS spectrogram, and deriving a parent ion and fragment ion grouping list in the MS/MS.
(4) And (4) screening characteristic fragment ions by using 290.0880 +/-10 ppm of the compound obtained in the step (3), and defining the compound containing the fragment as candidate ganglioside.
(5) Unreasonable candidate ganglioside with peak shape difference, blank background, isotope peak and charge more than 2 is removed by primary mass spectrum peak extraction.
(6) And (4) carrying out negative ion parallel reaction monitoring mass spectrum acquisition on the result obtained in the step (5), wherein the acquisition parameters comprise that the secondary mass spectrum acquisition resolution is set at 17500, and the AGC target is set at 1 × 105Maximum IT is set at 50 ms. The collision energy was collected using three separate energy sources, set at 10, 20, and 30eV, respectively. Obtaining a parallel reaction monitoring MS/MS spectrogram.
(7) Automatically analyzing the result obtained in the step (6) by LipidSearch software and combining manual checking; and (3) manually deducing the MS/MS spectrogram by referring to a LipidMaps database and combining fragment ion analysis on the unknown components. The parent ion mass deviation is set to less than 5ppm and the fragment ion is set to less than 20 ppm. The ganglioside identification list is exported as shown in table 1. The total ion flux chromatogram of the mouse brain extract (marked as a solid line) and the ganglioside extract ion flux chromatogram (marked as a dashed line) are shown in fig. 5.
TABLE 1
From the data results of example 1, it can be seen that: the method for identifying ganglioside has high sensitivity and wide coverage, and can detect trace ganglioside in a small amount of rat brain to identify 137 ganglioside.
The applicant states that the present invention is illustrated by the above examples to describe a high coverage ganglioside identification method and its application, but the present invention is not limited to the above examples, i.e. it does not mean that the present invention must rely on the above examples to be implemented. It should be understood by those skilled in the art that any modification of the present invention, equivalent substitutions of the raw materials of the product of the present invention, addition of auxiliary components, selection of specific modes, etc., are within the scope and disclosure of the present invention.
The preferred embodiments of the present invention have been described in detail, however, the present invention is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present invention within the technical idea of the present invention, and these simple modifications are within the protective scope of the present invention.
It should be noted that the various technical features described in the above embodiments can be combined in any suitable manner without contradiction, and the invention is not described in any way for the possible combinations in order to avoid unnecessary repetition.
Claims (10)
1. A method for identifying gangliosides with high coverage, which comprises the following steps:
(1) acquiring data of a sample containing ganglioside by a mass spectrometer in a negative ion mode by using a data-independent acquisition method to obtain original data;
(2) deconvoluting the original data to obtain parent ion and fragment ion information;
(3) screening the ion to obtain candidate ganglioside;
(4) carrying out parent ion peak extraction on the candidate ganglioside, and removing unreasonable candidate ganglioside;
(5) and (4) carrying out negative ion parallel reaction monitoring verification on the result obtained in the step (4) by adopting a mass spectrometer, and analyzing the result to obtain a ganglioside identification result.
2. The method for identifying gangliosides with high coverage as defined in claim 1, wherein the mass spectrometer of step (1) is a Q-active mass spectrometer;
preferably, the data acquisition in the step (1) is performed in a negative ion mode by using 20-28 continuous mass windows within the range of 600-1800m/z, wherein the window width is 50-65 m/z;
preferably, the primary mass spectrum acquisition resolution in the data acquisition process in the step (1) is 70000-140000, and the secondary mass spectrum acquisition resolution is 17500-70000.
3. The method for identifying gangliosides with high coverage as claimed in claim 1 or 2, wherein the automatic gain control of the primary mass spectrometry acquisition during the data acquisition of step (1) is 1 × 106-3×106The automatic gain control for the secondary mass spectrometry acquisition was 1 × 105-5×105；
Preferably, the collision energy of secondary mass spectrum acquisition in the data acquisition process of the step (1) adopts stepping energy, and the energy values are set to be 5-10eV, 25-30eV and 32-40eV in sequence.
4. The method for identifying gangliosides with high coverage as claimed in any one of claims 1-3, wherein the operation of deconvoluting the raw data in step (2) to obtain information of parent ions and fragment ions specifically comprises: the obtained raw data is deconvoluted using the open source software MS-DIAL to achieve the grouping of parent and fragment ions.
5. The method for identifying gangliosides with high coverage as claimed in any one of claims 1-4, wherein the step (3) of performing the daughter ion screening to obtain candidate gangliosides specifically comprises: screening the compound obtained in step (2) by using 290.0880 +/-10 ppm characteristic fragments, and regarding the compound containing the fragments as candidate ganglioside.
6. The method for identifying gangliosides with high coverage as in any one of claims 1-5, wherein the non-rational candidate gangliosides of step (4) comprise candidate gangliosides with poor peak shape, candidate gangliosides derived from blank background, candidate gangliosides derived from isotopic peaks, and candidate gangliosides with more than 3 charges.
7. The method for identifying gangliosides with high coverage as claimed in any one of claims 1-6, wherein the mass spectrometer of step (5) is a Q-exact mass spectrometer;
preferably, the secondary mass spectrum acquisition resolution in the negative ion parallel reaction monitoring process in the step (5) is 17500-70000.
8. The method for identifying gangliosides with high coverage as in any one of claims 1-7, wherein the automatic gain control of secondary mass spectrometry acquisition during the monitoring of the negative ion parallel reaction of step (5) is 1 × 105-5×105；
Preferably, the secondary mass spectrum acquisition collision energy in the negative ion parallel reaction monitoring process in the step (5) adopts single energy, and the energy values are set to be 5-10eV, 15-25eV and 28-35eV in sequence.
9. The method for identifying gangliosides with high coverage as defined in any of claims 1-8, wherein the analysis of the results in step (5) comprises: and analyzing by using LipidSearch software and/or a LipidMaps database, and outputting a ganglioside identification list.
10. Use of the high coverage ganglioside identification method of any one of claims 1-9 for identifying gangliosides.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010538078.4A CN111693597A (en) | 2020-06-12 | 2020-06-12 | Identification method of ganglioside with high coverage and application thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010538078.4A CN111693597A (en) | 2020-06-12 | 2020-06-12 | Identification method of ganglioside with high coverage and application thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111693597A true CN111693597A (en) | 2020-09-22 |
Family
ID=72480690
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010538078.4A Pending CN111693597A (en) | 2020-06-12 | 2020-06-12 | Identification method of ganglioside with high coverage and application thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111693597A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113284563A (en) * | 2021-04-20 | 2021-08-20 | 厦门大学 | Screening method and system for protein mass spectrum quantitative analysis result |
| CN114235979A (en) * | 2021-11-15 | 2022-03-25 | 南方科技大学 | Marine microorganism lipid ion mobility mass spectrometry method and application |
| CN114965835A (en) * | 2022-05-26 | 2022-08-30 | 南方科技大学 | Identification method of ganglioside and application thereof |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170168068A1 (en) * | 2015-12-11 | 2017-06-15 | Council Of Scientific & Industrial Research | In vitro process for the quantification of carboxymethyl and carboxyethyl level of albumin in a sample |
| US20170292960A1 (en) * | 2014-10-01 | 2017-10-12 | Micromass Uk Limited | Mass Spectrometry for Determining if a Mutated Variant of a Target Protein is Present in a Sample |
| CN110243985A (en) * | 2019-06-26 | 2019-09-17 | 南方科技大学 | A kind of Mass Spectrometry detection method of biomolecule |
-
2020
- 2020-06-12 CN CN202010538078.4A patent/CN111693597A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170292960A1 (en) * | 2014-10-01 | 2017-10-12 | Micromass Uk Limited | Mass Spectrometry for Determining if a Mutated Variant of a Target Protein is Present in a Sample |
| US20170168068A1 (en) * | 2015-12-11 | 2017-06-15 | Council Of Scientific & Industrial Research | In vitro process for the quantification of carboxymethyl and carboxyethyl level of albumin in a sample |
| CN110243985A (en) * | 2019-06-26 | 2019-09-17 | 南方科技大学 | A kind of Mass Spectrometry detection method of biomolecule |
Non-Patent Citations (2)
| Title |
|---|
| PENG H 等: ""Untargeted identification of organo-bromine compounds in lake sediments by ultrahigh-resolution mass spectrometry with the data-independent precursor isolation and characteristic fragment method"", 《ANALYTICAL CHEMISTRY》 * |
| 张美娟等: "高分辨质谱-非信息依赖数据采集-后靶向筛查策略在不明原因食物中毒鉴定中的应用", 《分析化学》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113284563A (en) * | 2021-04-20 | 2021-08-20 | 厦门大学 | Screening method and system for protein mass spectrum quantitative analysis result |
| CN113284563B (en) * | 2021-04-20 | 2024-04-09 | 厦门大学 | Screening method and system for protein mass spectrum quantitative analysis result |
| CN114235979A (en) * | 2021-11-15 | 2022-03-25 | 南方科技大学 | Marine microorganism lipid ion mobility mass spectrometry method and application |
| CN114235979B (en) * | 2021-11-15 | 2024-05-10 | 南方科技大学 | Mass spectrometry analysis method and application of lipid ion mobility of marine microorganisms |
| CN114965835A (en) * | 2022-05-26 | 2022-08-30 | 南方科技大学 | Identification method of ganglioside and application thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111693597A (en) | Identification method of ganglioside with high coverage and application thereof | |
| CA2476597C (en) | Mass spectrometry method for analysing mixtures of substances | |
| US9213033B2 (en) | Method for highly multiplexed quantitation of peptides by mass spectrometry and labeling reagent sets therefor | |
| US8426155B2 (en) | Proteome analysis in mass spectrometers containing RF ion traps | |
| US10197576B2 (en) | Mass spectrometry imaging with substance identification | |
| Nischwitz et al. | Mass spectrometric identification of novel arsinothioyl-sugars in marine bivalves and algae | |
| DE102005041655A1 (en) | Generation of multiply charged ions for tandem mass spectrometry | |
| CN110579555B (en) | Ion pair selection method for pseudo-targeted metabonomics analysis | |
| Li et al. | Fast screening of flavonoids from switchgrass and Mikania micrantha by liquid chromatography hybrid-ion trap time-of-flight mass spectrometry | |
| CN111936851A (en) | Methods and systems for detecting vitamin D metabolites | |
| JP2022534369A (en) | Mass Spectrometry Assays for Detecting Metabolites | |
| DE102014002079B4 (en) | ion fragmentation | |
| Caniato et al. | Capillary gas chromatography/positive and negative ion chemical ionization mass spectrometry on pyrrolizidine alkaloids of Senecio inaequidens using ammonia and hydroxyl ions as the reagent species | |
| US20190195887A1 (en) | Method and device for analyzing protein or peptide | |
| CN115684428B (en) | Method for non-targeted qualitative detection of bisphenol substances based on dansyl chloride derivative combined with in-mass spectrum source cleavage | |
| CN110879259A (en) | Establishment method for high-throughput identification of carotenoid and carotenoid database by utilizing LC-MS/MS | |
| CN111337600A (en) | Method for pre-treating soil and detecting various bisphenol compounds in soil | |
| CN110794075B (en) | Analysis method of oil-tea camellia seed oil saponin compounds | |
| CN113219101A (en) | Detection and screening method for exogenous risk substances in wine and application of detection and screening method in detection | |
| CN111896669A (en) | Method for identifying amino-containing metabolite isomer by direct mass spectrometry and application thereof | |
| CN110609097A (en) | Method for screening phosphatidylserine compounds | |
| CN113092627B (en) | Method for detecting cannabinoid component in cosmetics | |
| CN112285240B (en) | Detection method for three active ingredients of thunberg fritillary bulb in biological sample based on solid phase extraction-liquid chromatography-mass spectrometry | |
| CN115047110B (en) | Method for rapidly detecting selenium polysaccharide in selenium-enriched beans | |
| CN112881577B (en) | Liquid chromatography-mass spectrometry-based molecular characterization method for nitrogen-containing compounds in petroleum fractions |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200922 |
|
| RJ01 | Rejection of invention patent application after publication |