CN117334257A - Lucid ganoderma multi-level screening mass spectrum database and establishment method and application thereof - Google Patents
Lucid ganoderma multi-level screening mass spectrum database and establishment method and application thereof Download PDFInfo
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Abstract
The invention belongs to the technical field of natural product detection, and particularly relates to a ganoderma lucidum multi-level screening mass spectrum database and an establishment method and application thereof. The establishment of the database comprises the following steps: (1) Constructing a primary mass spectrum database based on a ganoderma lucidum compound standard; (2) Based on the mass spectrum data of the ganoderma lucidum real-measurement sample and the published component information of the ganoderma lucidum, simulating fragment cracking by using an information processing platform, predicting a mobility value and carrying out data comparison to construct a secondary mass spectrum database; (3) Based on an open source type database, a three-level mass spectrum database is constructed by utilizing a mass spectrum data processing strategy of various traditional Chinese medicine complex components and phytochemistry taxonomies and combining an information processing platform to simulate fragment cracking and predict mobility values. The invention can realize qualitative screening of the ganoderma lucidum related samples without standard substances, and has the characteristics of high throughput, accuracy, simplicity, convenience, rapidness and the like.
Description
Technical Field
The invention belongs to the technical field of natural product detection, and particularly relates to a ganoderma lucidum multi-level screening mass spectrum database and an establishment method and application thereof.
Background
Ganoderma lucidum is a dry fruiting body of Polyporaceae fungus Ganoderma lucidum Ganoderma lucidum or Ganoderma sinense Ganoderma sinense, and is one of the well-known medicinal fungi in China. The efficacy and clinical application of ganoderma lucidum are recorded by ancient medical works such as Shennong's herbal channel, xin Xiu Ben Cao (new revised materia Medica), ben Cao gang mu (compendium of materia Medica) and the like, and the modern pharmacological clinical research also shows that ganoderma lucidum has the effects of resisting tumor, regulating immunity, protecting liver, resisting aging, preventing and treating cardiovascular diseases and the like.
The basic research shows that the ganoderma lucidum has complex chemical components and contains various active components such as ganoderan, triterpenes, proteins, amino acids, sterols, fatty acids and the like. In particular, the ganoderma triterpene component, which is one of the main active ingredients of ganoderma, has various activities such as anti-tumor, immunoregulation, antiviral, antiepileptic, anti-inflammatory, neuroprotection, etc. More than 320 ganoderma lucidum triterpene components are reported at present, more isomers exist, and the identification difficulty is high.
At present, a colorimetric method, a liquid chromatography and a liquid chromatography-mass spectrometry method are mostly adopted for analysis of ganoderma lucidum components. The methods have the advantages and disadvantages that the colorimetric method is low in detection cost, but can only be used for total content measurement and has larger interference; liquid chromatography is the most dominant detection technique, and component detection is usually performed in combination with an ultraviolet-visible light detector or the like, but is limited by the influence of standards, sensitivity, matrix interference, and the like, and it is difficult to identify each chromatographic peak during analysis.
The Chinese patent application CN201210222763.1 discloses a quality analysis method of medicines or health products, in particular to a quality control method of ganoderma lucidum water extract. In order to purposefully control the product quality, the sum of the content of crude polysaccharide and the content of ganoderic acid A, B, C2 is used as the quality control of the ganoderma lucidum water extract, which means that the ganoderma lucidum crude polysaccharide is extracted by a water extraction and alcohol precipitation method in sample research, the polysaccharide with a glucan structure in the polysaccharide is precipitated by a copper reagent, the content of the polysaccharide is measured by an ultraviolet spectrophotometry, the influence of auxiliary materials on measurement is eliminated, and the basis is provided for the quality control of the ganoderma lucidum water extract. But only the total content of the above components can be measured, and there is a large disturbance.
Chinese patent application CN201910560738 relates to characteristic spectrum and its construction method and application, especially HS-SPME/GC-MS characteristic spectrum of volatile components of Ganoderma lucidum and its construction method and application. The application discloses HS-SPME/GC-MS characteristic spectrum of volatile components of ganoderma lucidum, which is characterized in that qualitative analysis is carried out on a common peak by establishing the characteristic spectrum of ganoderma lucidum, and then distinguishing and identifying ganoderma lucidum to be detected or other edible fungi and related products thereof, and distinguishing different varieties of ganoderma lucidum by GC-MS characteristic spectrum analysis, but because ganoderma lucidum components are complex, more isomers exist, and detection is not accurate enough.
With the development of mass spectrometry technology, particularly high-resolution mass spectrometry technology, by virtue of the characteristics of high flux, high resolution, spectrum library search and the like, the method is widely applied in the analysis field, and natural products can be rapidly identified by matching with the functions of high flux, accurate molecular weight, spectrum library search and the like.
At present, the analysis of the chemical components of ganoderma lucidum through a mass spectrometry or liquid chromatography-mass spectrometry technology is reported in the literature, but because ganoderma lucidum components are complex, more isomers exist, a systematic ganoderma lucidum chemical component mass spectrometry database is not formed yet, the number of directly identified chemical components is small, and the accuracy is not high. Based on this, provided herein are methods for identifying secondary metabolites in ganoderma lucidum by establishing a ganoderma lucidum multi-level high throughput screening mass spectrometry database that is a primary database (standard library), a secondary database (local library) and a tertiary database (online database) as the main components.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a ganoderma lucidum multi-level screening mass spectrum database and an establishment method and application thereof. The multi-level mass spectrum database capable of accurately identifying complex secondary metabolites in ganoderma lucidum is formed by taking the construction of a primary database (standard substance database), a secondary database (local database) and a tertiary database (online database) as main bodies, and the database is utilized to carry out high-throughput screening and identification on secondary metabolites in ganoderma lucidum.
In order to achieve the above purpose of the present invention, the present invention adopts the following specific technical scheme:
a method for establishing a ganoderma lucidum multi-level screening mass spectrum database comprises the following steps:
(1) Based on the ganoderma lucidum compound standard, carrying out data acquisition by using different acquisition modes of a high-resolution mass spectrometer, analyzing the data of the ganoderma lucidum compound standard and constructing a primary mass spectrum database;
(2) Based on the mass spectrum data of the ganoderma lucidum real-measurement sample and the published component information of the ganoderma lucidum, simulating fragment cracking by using an information processing platform, predicting a mobility value and carrying out data comparison to construct a secondary mass spectrum database;
(3) Based on an open source type database, a three-level mass spectrum database is constructed by utilizing a mass spectrum data processing strategy of various traditional Chinese medicine complex components and phytochemistry taxonomies and combining an information processing platform to simulate fragment cracking and predict mobility values.
Specifically, the method for establishing the primary mass spectrum database based on the standard substance comprises the following steps: and acquiring mass spectrum information of the standard substance by using different types of mass spectrometers under different acquisition modes and different mass spectrum parameter conditions, and establishing a primary mass spectrum database containing relevant information such as accurate molecular mass, structural formula, retention time, accurate molecular weight and ion intensity of primary fragments, accurate molecular weight and ion intensity of secondary fragments, ion mobility drift time, collision cross section and the like.
Preferably, the standard in the step (1) covers ganoderma lucidum triterpene representative components with different skeletons consisting of 24 carbons, 27 carbons and 30 carbons as parent nuclei; the different modes include MS E DDA, DIA, full Scan, MIM-EPI, SONAR, SWATH, and HDMS; the primary mass spectrum database comprises accurate molecular mass, structural formula, retention time, accurate molecular weight and ion intensity of primary fragments, accurate molecular weight and ion intensity of secondary fragments, ion mobility drift time and collision sectional area.
Preferably, in the step (1), the standard substance covers the ganoderma lucidum triterpene representative components with different frameworks formed by taking 24 carbons, 27 carbons and 30 carbons as parent nuclei, and the accurate retention time, the accurate molecular weight and ion intensity of the primary and secondary fragments, the ion mobility drift time, the collision cross section area and other mass spectrum information are collected, and meanwhile, the mass spectrum cracking rules of different parent nucleus frameworks are summarized; the different modes include MS E DDA, DIA, full Scan, MIM-EPI, SONAR, SWATH and HDMS.
Preferably, the primary database in step (1) includes information related to chemical formula, structural formula, retention time, precise molecular weight and ionic strength of the primary fragments, precise molecular weight and ionic strength of the secondary fragments, ion mobility drift time, collision cross-sectional area, and the like.
The primary database in the invention has the following characteristics: (1) Scanning modes are all inclusive, covering essentially all types of mass spectrometers and their scanning modes, including MS E DDA, DIA, full Scan, MIM-EPI, SONAR, SWATH, and HDMS; (2) The number and types of standard products are all, and the ganoderma lucidum triterpene representative components taking 24 carbons, 27 carbons and 30 carbons as parent nucleus frameworks are covered. The compounds of the same parent nucleus skeleton have similar cleavage rules, and the collection of the mass spectrum information of the representative compounds is helpful for summarizing the mass spectrum cleavage rules of different types of parent nucleus skeletons, which have important significance in identifying unknown compounds without standard substances, and can help identify the unknown compoundsA basic mother nucleus skeleton; (3) The compound information is accurate, such as accurate retention time, accurate molecular weight and ion strength of the primary and secondary fragments, ion mobility drift time, collision cross section area and the like. The ion mobility drift time and the collision cross section area are closely related to the mass-to-charge ratio of ions, the number of ion charges and the three-dimensional structure of the ions, so that the method has important significance for identifying the isomer and the similar structural compounds, and meanwhile, the separation of the other latitude on the basis of the retention time and the mass-to-charge ratio is realized, so that the identification result is more accurate.
Preferably, the information processing platform in the step (2) includes at least one of Peakview software, UNIFI software, masslynx software, progenesis QI software, massFrontier software, compound Discoverer software, tracefilter software, massHunter software, skyline software, MS-DIAL software and AllCCS platform; and the UNICFI software performs simulated fragment splitting matching, and the AllCCS platform performs mobility value prediction.
Specifically, the method for establishing the secondary database based on the reported component information of ganoderma lucidum is as follows: collecting mass spectrum data of a ganoderma lucidum sample, selecting ganoderma lucidum related components to construct an initial data set, and carrying out double accurate simulation by utilizing information processing platforms such as UNIFI, GNPS and SIRIUS 4 and the like through simulated fragment cracking and mobility value prediction based on the initial data set to construct a secondary mass spectrum database capable of accurately identifying a compound structure.
Preferably, the source of the information of the reported components of the ganoderma genus in the step (2) includes public literature information, large chemical databases (Reaxys, pubchem, scibinder, TCM, etc.).
Preferably, the information processing platform in the step (2) includes Peakview software, UNIFI software, masslynx software, progenesis QI software, massFrontier software, compound Discoverer software, tracefilter software, massHunter software, skyline software, MS-DIAL software, allCCS platform.
Further preferably, UNIFI software is selected for simulated patch-splitting matching and an AllCCS platform is selected for mobility value prediction.
The secondary mass spectrum database in the invention has the following characteristics: (1) The coverage range is wide, and all reported component information of ganoderma lucidum is covered, including literature data, large chemical databases such as reaxys, scifinder, pubchem and other information about ganoderma lucidum chemical components; (2) The accuracy is high, and accurate fragment simulation and mobility value prediction are carried out on the compound by utilizing a plurality of information platforms such as UNIFI, GNPS, SIRIUS, allCCS and the like to obtain accurate compound identification information.
Specifically, the method for establishing the three-level database based on the open source database updated in real time comprises the following steps: the three-level mass spectrum database capable of accurately identifying the structure of the compound is constructed by utilizing a mass spectrum data processing strategy of various traditional Chinese medicine complex components and phytochemical taxonomies and combining information platforms such as UNIFI, GNPS, SIRIUS 4 and the like to simulate fragment cracking and accurately confirm mobility value prediction.
Preferably, the open source database in step (3) includes an open source database of ChemSpider, COCONUT, super Natural II, NPASS, massbank, KEGG, fooDB, etc. in an amount exceeding 350, and the open source database has the following characteristics: (1) The coating is wide in coverage and covers all chemical components known at present, including artificial synthetic products and natural products. (2) Real-time performance, the information in the library is updated regularly, so that the accuracy and instantaneity of the information in the library are guaranteed.
Preferably, the traditional Chinese medicine complex composition mass spectrum data processing strategy in the step (3) comprises: at least one of a template compound-based mass spectrum dendrogram similarity filtering technique, a "patch tree" strategy for de novo identification of unknown compounds based on patch fingerprint features, a molecular network based on secondary patch similarity scores, and a molecular descriptor-based compound prediction strategy; the phytochemical taxonomies include ganoderma chemical taxonomies based on formation of ganoderma related biosynthetic pathways and/or parent nuclei of known chemical structures based on studies of ganoderma chemical composition.
The three-stage mass spectrum database in the invention has the following characteristics: (1) Real-time property, related compound information in the database can be updated and expanded in real time; (2) The accuracy is based on a traditional Chinese medicine complex component mass spectrum data processing strategy and phytochemistry taxonomies, and the simulation of fragment cracking and mobility value prediction are carried out by combining a scientific information system, so that accurate compound identification information can be obtained.
The invention also relates to a database established by the establishment method, and the database is updated periodically or in real time.
The invention also relates to application of the database established by the establishment method in identifying secondary metabolites in ganoderma lucidum.
Preferably, the step of identifying secondary metabolites in ganoderma lucidum comprises the following steps:
(1) Preparing a sample solution and collecting data;
(2) And comparing and identifying the mass spectrum data of the sample to be identified with a primary mass spectrum database, a secondary mass spectrum database and a tertiary mass spectrum database respectively by utilizing an information processing platform.
Preferably, the preparation method of the sample solution in the step (1) includes: extracting Ganoderma sample with solvent under ultrasonic wave, and filtering to obtain the final product; the solvent is selected from water or 70-100% methanol, preferably 100% methanol; the ultrasonic extraction time is 20-60min, and the filtration is 0.22-0.5 μm microporous membrane filtration.
Specifically, the data acquisition method of the sample solution provided by the invention comprises the following steps: direct injection mass spectrometer, liquid chromatography-mass spectrometer, desorption electrospray ionization mass spectrometer (DESI-MS), real-time direct analysis mass spectrometry (DART-MS), matrix assisted laser desorption ionization mass spectrometry (MALDI-MS).
Preferably, the device for data collection in step (1) is selected from one or more of mass spectrometer, liquid chromatograph, desorption electrospray ionization mass spectrometer (DESI-MS), real-time direct analysis mass spectrometry (DART-MS) and matrix assisted laser desorption ionization mass spectrometry (MALDI-MS), preferably liquid chromatograph; the ion source used by the liquid chromatography-mass spectrometer is selected from one of ESI, ESCI, APCI, EI and CI, and ESI is preferred.
Further preferably, the data acquisition is performed by a liquid chromatography-mass spectrometer and a direct injection mass spectrometer; preferably, a liquid chromatography-mass spectrometer.
In the invention, the influence of different methods of directly injecting mass spectrographs, liquid chromatography-mass spectrometry, DESI-MS and the like for acquiring mass spectrum data on the identification result is considered in consideration of that most secondary metabolites in ganoderma are the same type of compounds and have more isomers. The results show that the liquid chromatography-mass spectrometry can obtain better peak capacity and has better separation degree for isomers of the same type of compounds in the ganoderma.
Preferably, the mode of data acquisition in step (1) is selected from DDA, DIA, full Scan, MS E One or more of MIM-EPI, SONAR, SWATH and HDMS; preferably, SONAR and HDMS.
In the present invention, the method comprises the steps of performing a method of measuring DDA, DIA, full Scan, MS E Mass spectrum acquisition modes such as MIM-EPI, SONAR, SWATH, HDMS and the like are compared. The result shows that the SONAR+HDMS mode can greatly reduce the complexity of a spectrogram and improve the signal to noise ratio while belonging to high-energy fragments, and increases the separation of one dimension (mobility value) in the traditional acquisition means, so that the identification accuracy is further improved by confirming one more latitude compound.
Specifically, the comparison and identification method with the primary mass spectrum database in the step (2) is as follows: and importing the acquired information into an information processing platform, and matching with a primary mass spectrum database. Qualitative analysis validation criteria: the retention time deviation is +/-0.15 min; the mass error of the parent ion monoisotope is less than 3.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 3.5ppm and the number of the matched fragments is at least 6; the deviation of the mobility value is less than 5%. The comparison result of the screened component and a component in the primary database meets all qualitative analysis confirmation standards at the same time, and the screened component can be regarded as the component.
Specifically, the comparison and identification method with the secondary mass spectrum database in the step (2) is as follows: and (3) importing the acquired information into an information processing platform, and obtaining corresponding matching degree (0-50, and the higher the matching degree is, the higher the prediction accuracy is) through double accurate simulation matching of simulated fragment splitting and mobility value prediction with a secondary mass spectrum database. Qualitative analysis validation criteria: the retention time deviation is +/-0.15 min; the mass error of the parent ion monoisotope is less than 3.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 3.5ppm and the number of the matched fragments is at least 4; the deviation of the mobility value is less than 5%; the matching degree is more than or equal to 30. The comparison result of the screened component and a component in the primary database meets all qualitative analysis confirmation standards at the same time, and the screened component can be regarded as the component.
Specifically, the comparison and identification method with the tertiary mass spectrum database in the step (2) is as follows: and importing the acquired information into an information processing platform, and obtaining corresponding matching degree through double accurate simulation matching of simulated fragment cracking and mobility value prediction with a three-stage mass spectrum database. Simultaneous qualitative analysis validation criteria: the compound is present in Ganoderma genus; the mass error of the parent ion monoisotope is less than 4.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 4.5ppm and the number of the matched fragments is at least 3; the deviation of the mobility value is less than 8%; the oil-water distribution coefficient is close to the peak time of the component chromatograph; the matching degree is more than or equal to 20. The matching result of the screened component and a component in the three-level database meets all qualitative analysis confirmation standards, and can be regarded as the component.
Preferably, the information processing platform in the step (2) is selected from one or more of Peakview software, UNIFI software, masslynx software, progenesis QI software, massFrontier software, compound Discoverer software, tracefilter software, massHunter software, skyline software, MS-DIAL software and AllCCS platform. Preferably, UNIFI software is selected for simulated patch-off matching and an AllCCS platform is selected for mobility value prediction.
Compared with the prior art, the invention has the following beneficial effects:
(1) The ganoderma lucidum database constructed in a multi-level mode can realize qualitative screening of ganoderma lucidum related samples under the condition of no standard substance, has the characteristics of high flux, accuracy, simplicity, rapidness and the like, solves the problems of limited standard substances, large workload, untimely database updating and the like in the traditional identification process, and provides technical support for ganoderma lucidum substance basic research and drug effect substance identification;
(2) The multi-layer data base constructed by the invention increases one-dimensional (ion mobility) separation in the traditional method, thereby confirming the compound with one more latitude (mobility value) and further improving the identification accuracy. In addition, a plurality of information processing platforms such as a UNIFI scientific information system and a molecular network platform are combined to carry out simulation matching on fragments and mobility values, so that the accuracy and reliability of compound identification are greatly improved;
(3) The three-level database constructed by the invention combines a plurality of traditional Chinese medicine complex component mass spectrum data processing strategies such as a Molecular Network (MN) based on a secondary fragment similarity score and a compound prediction strategy based on a molecular descriptor while using an open source database updated in real time, and combines phytochemical taxonomies with information processing platforms such as UNIFI, GNPS, SIRIUS 4 and the like, thereby avoiding errors caused by the fact that the isomerides and the open source database contain too many compounds, and further improving the accuracy and reliability of compound identification.
Drawings
FIG. 1 is a flowchart of the establishment and application of a ganoderma lucidum multi-layer high throughput screening mass spectrometry database;
FIG. 2 is a schematic diagram of a primary database creation and comparison process;
FIGS. 3 and 4 are schematic diagrams of a secondary database creation and comparison process;
FIG. 5 is a schematic diagram of a three-level database creation and comparison process;
FIGS. 6 and 7 are visual views of the authentication results of the GNPS information processing platform;
FIG. 8 is a Principal Component Analysis (PCA) plot of different Ganoderma samples based on the identification of a multi-level screening database, wherein BR is white ganoderma lucidum; CC-Ganoderma lucidum; CZ-ganoderma lucidum; GT-Ganoderma tsugae; GW-Wei-Ganoderma lucidum; NF-south ganoderma; SS-Ganoderma Applanatum; WB-ganoderma lucidum without stem.
Detailed Description
In order to make the person skilled in the art better understand the present invention, the technical solution of the present invention will be further explained with reference to the drawings and the examples, but the scope of the present invention is not limited in any way by the examples.
Example 1 establishment of a database of ganoderma lucidum multilayer high throughput screening Mass spectra
As shown in fig. 1, the establishment flow of the ganoderma lucidum multilayer high-throughput screening mass spectrum database of the invention is specifically as follows:
(1) First-level database creation
Standards of the compounds contained in ganoderma lucidum (containing purity and NMR identification certificates) were collected, and the names and CAS numbers of the obtained compounds are shown in table 1 in detail.
Weighing 5mg of each ganoderma lucidum compound standard substance respectively, adding methanol to dilute to 50mL, and uniformly mixing to prepare a single standard solution with the content of 0.1 mg/mL. Injecting a Synta XS high-resolution liquid chromatography mass spectrometer, wherein the instrument parameters are as follows:
the column was a C18 UPLC column (2.1 mm. Times.100 mm,1.8 μm); the mobile phase was 0.1% (v/v) formic acid water (A) -acetonitrile (B). 0-9min,20-28% B;9-28min,28-60% B; gradient eluting with 60-100% B for 28-45min at a flow rate of 0.3mL min -1 The column temperature is 30 ℃ and the sample injection amount is 1 mu L. Adopting electrospray ion source to analyze in negative ion mode, wherein the mass scanning range is 100-1500Da, the ion source temperature is 150 ℃, the capillary voltage is 3kV, the taper hole voltage is 40V, the collision energy is 20-50eV, the atomization gas pressure is 6.0bar, the atomization gas temperature is 500 ℃, and the atomization gas flow is 1000 L.h -1 . Leucine-enkephalin (ESI-554.2615 Da) solution as correction fluid with concentration of 200pg.mL -1 。
And recording the information of retention time, accurate molecular weight and ionic strength of the primary and secondary fragments, mobility drift time, collision sectional area and the like of the compound, and simultaneously summarizing mass spectrum cracking rules of different mother nucleus frameworks. Based on this, a primary database based on the information of the ganoderma lucidum compound standard substance is formed, as shown in fig. 2.
TABLE 1 ganoderma lucidum compounds covered by the current primary database
(2) Establishment of secondary database
Collecting Ganoderma samples of different Ganoderma genus (Ganoderma Applanatum Ganodermo applanatum, ganoderma south Ganodermo australe, ganoderma long and narrow spore Ganodermo boninense, ganoderma with handle Ganodermo gibbosum, ganoderma lucidum Ganodermo leucocontextum, ganoderma lucidum Ganodermo multipileum, ganoderma lucidum Ganodermo resinaceum, ganoderma lucidum Ganodermo lucidum, ganoderma sinense Ganodermo sinense, ganoderma sinensis Ganoderm tsugqe, and Ganoderma weber Ganodermo weberianum), weighing 0.1g each time, placing into 50mL centrifuge tube, accurately adding 40mL methanol, extracting with ultrasound for 30min, collecting supernatant 1mL in 1.5mL centrifuge tube, centrifuging for 10min at 13000r/min, and collecting supernatant, and injecting into Synapt XS high resolution liquid chromatography-mass spectrometer with the following instrument parameters:
the column was a C18 UPLC column (2.1 mm. Times.100 mm,1.8 μm); the mobile phase was 0.1% (v/v) formic acid water (A) -acetonitrile (B). 0-9min,20-28% B;9-28min,28-60% B; gradient eluting with 60-100% B for 28-45min at a flow rate of 0.3mL min -1 The column temperature is 30 ℃ and the sample injection amount is 1 mu L. Adopting electrospray ion source to analyze in negative ion mode, wherein the mass scanning range is 100-1500Da, the ion source temperature is 150 ℃, the capillary voltage is 3kV, the taper hole voltage is 40V, the collision energy is 20-50eV, the atomization gas pressure is 6.0bar, the atomization gas temperature is 500 ℃, and the atomization gas flow is 1000 L.h -1 . Leucine-enkephalin (ESI-554.2615 Da) solution as correction fluid with concentration of 200pg.mL -1 。
Sample data are collected, and information such as retention time, accurate molecular weight, ion strength, mobility drift time, collision sectional area and the like of all primary and secondary ions are recorded.
Collecting data information of all the reported compounds of all the ganoderma genus contained in all the related documents and large chemical databases to form an initial data set, wherein the data set contains information such as ganoderma lucidum basal source attribution, name, molecular formula, structural formula, secondary fragments, oil-water distribution coefficient and the like of the compounds. And by using information processing platforms such as UNIFI, GNPS and SIRIUS 4, the method performs double accurate simulation comparison between the simulated fragment cracking and the mobility value prediction and all components in the acquired ganoderma lucidum sample. The mass number error of the monoisotopic element satisfying the parent ion is less than 3.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 3.5ppm and the number of the matched fragments is at least 4; the deviation of the mobility value is less than 5%; the oil-water distribution coefficient is close to the peak time of the component chromatograph; the matching degree is more than or equal to 30, and the qualitative determination of the component can be completed. Based on this, a qualitative component is formed into a secondary mass spectrum database capable of achieving accurate identification of the structure and retention time of the compound, as shown in fig. 3 and 4.
(3) Three-level database creation
The simulation fragment cracking and mobility value prediction are carried out by utilizing a plurality of open source databases updated in real time, such as chemspider, massBank, KEGG and the like, and combining platforms of UNIFI scientific information system, GNPS, SIRIUS 4 and the like, and double accurate simulation comparison is carried out on unidentified components of the primary and secondary databases in the ganoderma lucidum samples, so that the corresponding matching degree is obtained. For compounds meeting the requirement that the compound exists in ganoderma, the mass number error of parent ion monoisotopic element is less than 3.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 3.5ppm and the number of the matched fragments is at least 3; the deviation of the mobility value is less than 8%; the oil-water distribution coefficient is close to the peak time of the component chromatograph; the matching degree is more than or equal to 20; the component can be characterized by the compound type of Ganoderma. Based on this, a qualitative component was formed into a three-stage mass spectrum database capable of achieving accurate identification of the structure of the compound, as shown in fig. 5.
Example 2 identification of Ganoderma lucidum Secondary metabolite based on Multi-level Mass Spectrometry database
(1) Sample preparation to be tested
Accurately weighing 0.1g of ganoderma lucidum sample (ganoderma lucidum ) sample powder, placing the powder into a 50mL centrifuge tube, accurately adding 40mL of methanol, performing ultrasonic extraction for 30min, taking 1mL of supernatant into a 1.5mL centrifuge tube, centrifuging for 10min at 13000r/min, and taking the supernatant as a sample to be detected for later use.
(2) Primary and secondary mass spectrogram acquisition of sample to be detected
And detecting a sample to be detected by a Synapt XS high-resolution liquid chromatography-mass spectrometer, wherein the acquisition parameters of the instrument are as follows:
chromatographic conditions: the column was a C18 UPLC column (2.1 mm. Times.100 mm,1.8 μm); the mobile phase was 0.1% (v/v) formic acid water (A) -acetonitrile (B). 0-9min,20-28% B;9-28min,28-60% B; gradient eluting with 60-100% B for 28-45min at a flow rate of 0.3mL min -1 The column temperature is 30 ℃ and the sample injection amount is 1 mu L.
Mass spectrometry conditions: adopting electrospray ion source to analyze in negative ion mode, wherein the mass scanning range is 100-1500Da, the ion source temperature is 150 ℃, the capillary voltage is 3kV, the taper hole voltage is 40V, the collision energy is 20-50eV, the atomization gas pressure is 6.0bar, the atomization gas temperature is 500 ℃, and the atomization gas flow is 1000 L.h -1 . leucine-Enkephalin (ESI) - :554.2615 Da) solution is used as correction fluid, and the concentration is 200 pg.mL -1 。
(3) Qualitative analysis of the composition
The collected information is imported into scientific information systems such as UNIFI, and the like, matching is carried out through a primary database, and qualitative analysis is carried out to confirm the standard: the retention time deviation is +/-0.15 min; the mass error of the parent ion monoisotope is less than 3.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 3.5ppm and the number of the matched fragments is at least 6; the deviation of the mobility value is less than 5%. From which 29 components are determined in total based on the primary database.
And secondly, carrying out simulated fragment cracking and mobility value prediction dual accurate simulation comparison through a secondary database to obtain corresponding matching degree. Qualitative analysis validation criteria: the retention time deviation is +/-0.15 min; the mass error of the parent ion monoisotope is less than 3.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 3.5ppm and the number of the matched fragments is at least 4; the deviation of the mobility value is less than 5%; the matching degree is more than or equal to 30. From which 142 components were determined in total based on the secondary database.
And finally, further comparing through a three-level database to obtain the corresponding matching degree. Qualitative analysis validation criteria: the compound exists in ganoderma genus, and the mass number error of parent ion monoisotope is less than 4.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 4.5ppm and the number of the matched fragments is at least 4; the deviation of the mobility value is less than 8%; the oil-water distribution coefficient is close to the peak time of the component; the matching degree is more than or equal to 20. From which 33 components are determined in total based on a three-level database.
Finally, searching through a ganoderma lucidum database constructed in a multi-level mode, and identifying 204 components from ganoderma lucidum samples, wherein specific identification information is shown in the following table 2. This embodiment has the following advantages over the currently existing methods: (1) Compared with the two-dimensional separation and identification method of retention time and primary and secondary fragment information in the traditional identification, the identification result is accurate, and the one-dimensional separation of mobility value is increased, so that the identification result is more accurate. (2) The identification efficiency is high, the traditional method is based on manual calibration, the whole identification period is long, more than two months are needed for identifying 100 compounds, but according to the embodiment, the database is automatically searched and identified by software, more than 200 components (within 30 minutes) can be identified from the ganoderma lucidum sample at one time, and the analysis efficiency is remarkably improved. (3) The technical threshold for identifying the compound is low, and the traditional method needs personnel to have strong knowledge of analytical chemistry, phytochemistry and mass spectrum to accurately judge the identification result, but by the embodiment, the software is used for automatically searching and judging the data, so that the technical capability requirement on operators is low.
TABLE 2 identification of Ganoderma lucidum (Ganoderma lucidum) secondary metabolite based on Multi-level Mass Spectrometry database
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Example 3 identification of secondary metabolites of different varieties of Ganoderma lucidum based on Multi-level Mass Spectrometry database
(1) Material preparation
0.1g of powder of different types of ganoderma lucidum samples (ganoderma lucidum Ganodermo applanatum, ganoderma lucidum Ganodermo australe, ganoderma lucidum Ganodermo leucocontextum, ganoderma lucidum Ganodermo multipileum, ganoderma lucidum Ganodermo resinaceum, ganoderma lucidum Ganodermo lucidum, ganoderma lucidum Ganodermo sinense, ganoderma lucidum Ganoderm tsugqe and ganoderma weber Ganodermo weberianum) is accurately weighed, the powder is respectively placed in 50mL centrifuge tubes, 40mL of methanol is accurately added, ultrasonic extraction is carried out for 30min, 1mL of supernatant is taken in a 1.5mL centrifuge tube, and 13000r/min is centrifuged for 10min, and the supernatant is taken as a sample to be measured for standby.
(2) Primary and secondary mass spectrogram acquisition of sample to be detected
And detecting a sample to be detected by a Synta XS liquid chromatography-mass spectrometer, wherein the parameters of the instrument are as follows:
chromatographic conditions: the column was a C18 UPLC column (2.1 mm. Times.100 mm,1.8 μm); the mobile phase was 0.1% (v/v) formic acid water (A) -acetonitrile (B). 0-9min,20-28% B;9-28min,28-60% B; gradient eluting with 60-100% B for 28-45min at a flow rate of 0.3mL min -1 The column temperature is 30 ℃ and the sample injection amount is 1 mu L.
Mass spectrometry conditions: adopting electrospray ion source to analyze in negative ion mode, wherein the mass scanning range is 100-1500Da, the ion source temperature is 150 ℃, the capillary voltage is 3kV, the taper hole voltage is 40V, the collision energy is 20-50eV, the atomization gas pressure is 6.0bar, the atomization gas temperature is 500 ℃, and the atomization gas flow is 1000 L.h -1 . leucine-Enkephalin (ESI) - :554.2615 Da) solution is used as correction fluid, and the concentration is 200 pg.mL -1 。
(3) Qualitative analysis of the composition
The collected information is imported into scientific information systems such as UNIFI, and the like, matching is carried out through a primary database, and qualitative analysis is carried out to confirm the standard: the retention time deviation is +/-0.15 min; the mass error of the parent ion monoisotope is less than 3.5ppm; the mass number error of the fragment ions is less than 3.5ppm; the relative abundance deviation of isotopes is less than 5%; the deviation of the mobility value is less than 5%; the number of matching chips is at least 6.
And secondly, carrying out simulated fragment cracking and mobility value prediction dual accurate simulation comparison through a secondary database to obtain corresponding matching degree. Meanwhile, the GNPS information processing platform is adopted to further simulate fragment cracking of unidentified components, the unidentified components are compared with an initial data set of a secondary database, the visual results are shown in fig. 6 and 7, and the unidentified components are input into the secondary database. Qualitative analysis validation criteria: the retention time deviation is +/-0.15 min; the mass error of the parent ion monoisotope is less than 3.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 3.5ppm and the number of the matched fragments is at least 4; the deviation of the mobility value is less than 5%; the matching degree is more than or equal to 30.
And finally, further comparing through a three-level database. Qualitative analysis validation criteria: the compound belongs to the genus ganoderma, and the mass number error of parent ion monoisotope is less than 4.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 4.5ppm; the number of matching fragments is at least 3; the deviation of the mobility value is less than 8%; the matching degree is more than or equal to 20; the oil-water partition coefficient is close to the peak time of the component and the compound type exists in ganoderma.
By searching the ganoderma lucidum database constructed in a multi-level manner, 408 secondary metabolites were identified in total from different ganoderma lucidum samples (table 3) and were subjected to multivariate statistical analysis based on the identified components (fig. 8), it was found that the different ganoderma lucidum samples could be distinguished based on the identified compounds. This example shows that this method has the following advantages over the conventional method: (1) The identification efficiency is high, multiple groups of data can be automatically identified in a short time, and more components can be identified; (2) The application range is wide, and besides the component identification of the basal sources (ganoderma lucidum and ganoderma sinensis) specified under ganoderma lucidum item in Chinese pharmacopoeia, other ganoderma samples can be identified.
TABLE 3 identification results and intensity values of different varieties of Ganoderma lucidum secondary metabolites based on a multi-level mass spectrum database
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The foregoing detailed description is directed to one of the possible embodiments of the present invention, which is not intended to limit the scope of the invention, but is to be accorded the full scope of all such equivalents and modifications so as not to depart from the scope of the invention.
Claims (10)
1. The method for establishing the ganoderma lucidum multi-level screening mass spectrum database is characterized by comprising the following steps of:
(1) Based on the ganoderma lucidum compound standard, carrying out data acquisition by using different acquisition modes of a high-resolution mass spectrometer, analyzing the data of the ganoderma lucidum compound standard and constructing a primary mass spectrum database;
(2) Based on the mass spectrum data of the ganoderma lucidum real-measurement sample and the published component information of the ganoderma lucidum, simulating fragment cracking by using an information processing platform, predicting a mobility value and carrying out data comparison to construct a secondary mass spectrum database;
(3) Based on an open source type database, a three-level mass spectrum database is constructed by utilizing a mass spectrum data processing strategy of various traditional Chinese medicine complex components and phytochemistry taxonomies and combining an information processing platform to simulate fragment cracking and predict mobility values.
2. The method according to claim 1, wherein the standard in the step (1) comprises ganoderma lucidum triterpene representative components with different skeletons consisting of 24 carbons, 27 carbons and 30 carbons as parent nuclei; the different acquisition modes include MS E DDA, DIA, full Scan, MIM-EPI, SONAR, SWATH, and HDMS; the primary mass spectrum database comprises accurate molecular mass, structural formula, retention time, accurate molecular weight and ion intensity of primary fragments, accurate molecular weight and ion intensity of secondary fragments, ion mobility drift time and collision sectional area.
3. The method according to claim 1, wherein the information processing platform in step (2) includes at least one of Peakview software, UNIFI software, masslynx software, progenesis QI software, massfront software, compound Discoverer software, tracefilter software, massHunter software, skyline software, MS-DIAL software, and AllCCS platform; and the UNICFI software performs simulated fragment splitting matching, and the AllCCS platform performs mobility value prediction.
4. The method according to claim 1, wherein the traditional Chinese medicine complex composition mass spectrum data processing strategy in step (3) comprises: at least one of a template compound-based mass spectrum dendrogram similarity filtering technique, a "patch tree" strategy for de novo identification of unknown compounds based on patch fingerprint features, a molecular network based on secondary patch similarity scores, and a molecular descriptor-based compound prediction strategy; the phytochemical taxonomies include ganoderma chemical taxonomies based on formation of ganoderma related biosynthetic pathways and/or parent nuclei of known chemical structures based on studies of ganoderma chemical composition.
5. A database built by the building method according to any one of claims 1-4, characterized in that the database is updated periodically or in real time.
6. Use of a database created by the method of any one of claims 1-4 for identifying secondary metabolites in ganoderma lucidum.
7. The use according to claim 6, wherein the step of identifying secondary metabolites in ganoderma lucidum comprises:
(1) Preparing a sample solution and collecting data;
(2) And comparing and identifying the mass spectrum data of the sample to be identified with a primary mass spectrum database, a secondary mass spectrum database and a tertiary mass spectrum database respectively by utilizing an information processing platform.
8. The use according to claim 7, wherein the method for preparing the test solution in step (1) comprises: extracting Ganoderma sample with solvent under ultrasonic wave, and filtering to obtain the final product; the solvent is selected from water or 70-100% methanol; the ultrasonic extraction time is 20-60min.
9. The use of claim 7, wherein the data acquisition device in step (1) is selected from one or more of mass spectrometer, liquid chromatography, DESI-MS, DART-MS, and MALDI-MS; the ion source used by the liquid chromatography-mass spectrometer is selected from one of ESI, ESCI, APCI, EI and CI; the mode of data acquisition is selected from DDA, DIA, full Scan, MS E One or more of MIM-EPI, SONAR, SWATH and HDMS.
10. The use of claim 7, wherein the validation criteria for the comparative authentication in step (2) comprises:
s1: qualitative analysis of the primary mass spectrometry database confirms the standard: the retention time deviation is +/-0.15 min; the mass error of the parent ion monoisotope is less than 3.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 3.5ppm and the number of the matched fragments is at least 6; the deviation of the mobility value is less than 5%; the comparison result of the screened component and a certain component in the primary database meets all qualitative analysis confirmation standards at the same time, namely the component is considered;
s2: qualitative analysis of the secondary mass spectrometry database confirms the standard: the retention time deviation is +/-0.15 min; the mass error of the parent ion monoisotope is less than 3.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 3.5ppm and the number of the matched fragments is at least 4; the deviation of the mobility value is less than 5%; the matching degree is more than or equal to 30; the matching degree is obtained by performing double accurate simulation matching of simulated fragment splitting and mobility value prediction with a secondary mass spectrum database; the comparison result of the screened component and a certain component in the secondary database meets all qualitative analysis confirmation standards at the same time, namely the component is considered;
s3: qualitative analysis of the tertiary mass spectrometry database confirms the standard: the mass error of the parent ion monoisotope is less than 4.5ppm; the relative abundance deviation of isotopes is less than 5%; the mass number error of the fragment ions is less than 4.5ppm and the number of the matched fragments is at least 3; the deviation of the mobility value is less than 8%; the matching degree is more than or equal to 20; the comparison result of the screened component and a component in the three-level database meets all qualitative analysis confirmation standards at the same time, namely the component is considered.
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