Metabolite profile library construction method, system, and database

Abstract

The application provides a metabolite spectrum library construction method and system and a database, relates to the field of metabolite spectrum library construction, and realizes extraction of standard substance spectrum and establishment of a spectrum library. The overall library construction logic is unified, the route is reliable, the spectrum quality is high, the spectrum can be traced and long-term optimized, and the accuracy of identification can be improved during sample identification.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of metabolite spectrum library construction, in particular to a metabolite spectrum library construction method, system and database. BACKGROUND

[0002] In the non-targeted identification of metabolites in samples, searching the library is the most critical link. Searching the library mainly includes two core parts: one is the technology and method used in searching the library, and the other is the metabolite spectrum library used as a reference. In the past, users generally selected commercial search library software provided by upstream instrument manufacturers, such as Compound Discovery, and matched related spectrum libraries, such as mzCloud, mzVault, ChemSpider, etc. However, such spectrum libraries have the problem of poor accuracy of data information, resulting in a low proportion of substances in the sample that can be accurately identified. In addition, due to differences in chromatographic conditions, the retention time and other parameters cannot be reused, which has an adverse effect on the identification results. In summary, the details of the information establishment of various existing public databases involved in the current metabolite spectrum library are not disclosed, and the data quality of the database information cannot meet the requirements. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a metabolite spectrum library construction method, system and database, which realizes the extraction of standard substance spectrum and the establishment of spectrum library, and has unified overall library construction logic, reliable route, high spectrum quality, traceability and long-term optimization, which can solve the above-mentioned problems existing in the prior art.

[0004] In a first aspect, the present application provides a metabolite spectrum library construction method, which comprises:

[0005] Obtaining a standard substance corresponding to a metabolite, determining substance information data and sum ion data of the standard substance;

[0006] Calculating spectrum matching information corresponding to the metabolite based on the substance information data and the sum ion data, and obtaining on-machine spectrum information of the substance corresponding to the standard substance by a mass spectrometer;

[0007] Obtaining sample spectrum information corresponding to the metabolite according to the spectrum matching information and the on-machine spectrum information, and obtaining characteristic ion information corresponding to the metabolite by using the sample spectrum information;

[0008] Determining a grouping strategy according to a type parameter of the standard substance, and obtaining spectrum integration information corresponding to the mixed sample grouping by a mass spectrometer after mixing and grouping the substances and the standard substance by using the grouping strategy;

[0009] Constructing a spectrum library corresponding to the metabolite by using the spectrum integration information.

[0010] Optionally, the step of obtaining the standard substance corresponding to the metabolite, determining the substance information data and the adduct ion data of the standard substance comprises:

[0011] Obtaining the standard substance corresponding to the plurality of metabolites contained in the spectrum library establishment process, and obtaining the molecular formula and the acquisition mode parameter corresponding to the standard substance;

[0012] Determining the substance information data of the standard substance according to the molecular formula and the acquisition mode parameter, and determining the adduct ion data corresponding to the standard substance based on the molecular formula.

[0013] Optionally, the spectrum matching information corresponding to the metabolite is calculated based on the substance information data and the adduct ion data, and the on-machine spectrum information of the substance corresponding to the standard substance is obtained by the mass spectrometer, comprising:

[0014] The molecular weight corresponding to the metabolite is calculated by using the molecular formula and the acquisition mode parameter corresponding to the substance information data;

[0015] The adduct molecular weight corresponding to the adduct ion data is determined according to the acquisition mode parameter, and the spectrum matching information corresponding to the metabolite is calculated based on the molecular weight and the adduct molecular weight;

[0016] An information table corresponding to the standard substance is obtained, the off-machine path corresponding to the mass spectrometer is obtained by using the row data in the information table, and the mass spectrum file contained in the off-machine path is obtained;

[0017] The on-machine spectrum information of the substance corresponding to the standard substance is obtained based on the mass spectrum file.

[0018] Optionally, the sample spectrum information corresponding to the metabolite is obtained according to the spectrum matching information and the on-machine spectrum information, comprising:

[0019] The mass spectrum file corresponding to the standard substance is determined by using the spectrum matching information and the on-machine spectrum information;

[0020] The storage unit contained in the mass spectrum file is obtained, and the numerical data and the array data contained in the storage unit are extracted;

[0021] The sample spectrum information corresponding to the metabolite is determined based on the numerical data and the array data.

[0022] Optionally, before the feature ion information corresponding to the metabolite is obtained by using the sample spectrum information, the method further comprises:

[0023] The effective secondary spectrum information corresponding to the numerical data and the array data in the storage unit is obtained based on the mass data and the charge data corresponding to the adduct ion data;

[0024] The sample spectrum information is updated by using the effective secondary spectrum information.

[0025] Optionally, the sample spectrum information is used to obtain the characteristic ion information corresponding to the metabolite, including:

[0026] Spectrum data corresponding to the sample spectrum information is obtained.

[0027] The spectrum ID corresponding to the spectrum data is determined according to the positive and negative mode parameters corresponding to the substance and the corresponding sum ion data, and the merging strategy corresponding to the spectrum is determined based on the spectrum ID.

[0028] The secondary spectrum corresponding to the sample spectrum information is obtained by using the merging strategy, and the characteristic ion information corresponding to the metabolite is determined based on the secondary spectrum.

[0029] Optionally, the grouping strategy is determined according to the type parameter of the standard sample, and after the substances and the standard samples are mixed and grouped by using the grouping strategy, the spectrum integration information corresponding to the mixed and grouped sample is obtained by using the mass spectrometer, including:

[0030] The type parameter corresponding to the standard sample is obtained, the nuclear mass ratio list corresponding to the standard sample is obtained according to the type parameter, and the grouping strategy is determined based on the nuclear mass ratio value in the nuclear mass ratio list.

[0031] After the substances are grouped by using the grouping strategy, the substances are mixed with the standard samples respectively to obtain the substance groups corresponding to the standard samples, and the on-machine spectrum data corresponding to the substance groups is obtained by using the mass spectrometer.

[0032] The actual on-machine retention time of the substance group in the mass spectrometer is obtained according to the on-machine spectrum data, and the first information and the second information of the substance group determined by using the actual on-machine retention time are used to generate the spectrum integration information.

[0033] Optionally, the spectrum integration information is used to construct the spectrum library corresponding to the metabolite, including:

[0034] The substance group corresponding to the mixed and grouped sample is obtained, and the first information and the second information corresponding to the substance group are determined.

[0035] The spectrum integration information is determined by using the retention time and the first information and the second information meeting the preset deviation range.

[0036] The spectrum library is constructed based on the spectrum integration information according to the standard sample.

[0037] In a second aspect, the present application provides a metabolite spectrum library construction system, which comprises:

[0038] A data acquisition module is used to obtain the standard sample corresponding to the metabolite, determine the substance information data and the sum ion data of the standard sample.

[0039] The data processing module is configured to calculate spectrum matching information corresponding to the metabolite based on the substance information data and the adduct ion data, and obtain spectrum information of a standard substance corresponding to the metabolite by using the mass spectrometer.

[0040] The characteristic ion information acquisition module is configured to acquire sample spectrum information corresponding to the metabolite according to the spectrum matching information and the spectrum information, and acquire characteristic ion information corresponding to the metabolite by using the sample spectrum information.

[0041] The retention time acquisition module is configured to determine a grouping strategy according to the type parameter of the standard substance, group the substance and the standard substance by mixing after using the grouping strategy, and acquire spectrum integration information corresponding to the mixed sample group by using the mass spectrometer.

[0042] The database generation module is configured to construct a spectrum library corresponding to the metabolite by using the spectrum integration information.

[0043] In a third aspect, the present application also provides a database comprising a processor and a memory, wherein the memory stores computer executable instructions capable of being executed by the processor, and the processor executes the computer executable instructions to implement the steps of the metabolite spectrum library construction method provided in the first aspect.

[0044] In a fourth aspect, the present application also provides a storage medium storing computer executable instructions, wherein the computer executable instructions, when called and executed by a processor, cause the processor to implement the steps of the metabolite spectrum library construction method provided in the first aspect.

[0045] The metabolite spectrum library construction method, system and database provided by the present application can realize extraction of standard substance spectrum and construction of a spectrum library, and have unified overall library construction logic, reliable route, high spectrum quality, traceability and long-term optimization, and can improve the accuracy of sample identification.

[0046] Other features and advantages of the present application will be set forth in the descriptions that follow, and in part will be apparent from the description or can be learned by practice of the application. The purposes and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

[0047] To make the above objectives, features and advantages of the present application more apparent, the following will describe a preferred embodiment in detail, and the accompanying drawings will be referred to, as follows. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings needed to be used in the specific embodiments or the prior art description. Obviously, the drawings described below are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0049] Figure 1 The flow chart of the metabolite spectrum library construction method provided by the embodiment of the present application;

[0050] Figure 2 The flow chart of step S101 in the metabolite spectrum library construction method provided by the embodiment of the present application;

[0051] Figure 3 The flow chart of step S102 in the metabolite spectrum library construction method provided by the embodiment of the present application;

[0052] Figure 4 The flow chart of step S103 in the metabolite spectrum library construction method provided by the embodiment of the present application, in which the sample spectrum information corresponding to the metabolite is obtained according to the spectrum matching information and the spectrum information obtained on the machine;

[0053] Figure 5 The flow chart before step S103 in the metabolite spectrum library construction method provided by the embodiment of the present application, in which the sample spectrum information is used to obtain the characteristic ion information corresponding to the metabolite;

[0054] Figure 6 The flow chart of step S103 in the metabolite spectrum library construction method provided by the embodiment of the present application, in which the sample spectrum information is used to obtain the characteristic ion information corresponding to the metabolite;

[0055] Figure 7 The flow chart of step S104 in the metabolite spectrum library construction method provided by the embodiment of the present application;

[0056] Figure 8A flow chart of step S105 in a metabolite spectrum library construction method provided by an embodiment of the present application;

[0057] Figure 9 A flow chart of another metabolite spectrum library construction method provided by an embodiment of the present application;

[0058] Figure 10 A structural schematic diagram of a metabolite spectrum library construction system provided by an embodiment of the present application;

[0059] Figure 11 A structural schematic diagram of a database provided by an embodiment of the present application.

[0060] Icon:

[0061] 1010 - data acquisition module; 1020 - data processing module; 1030 - characteristic ion information acquisition module; 1040 - retention time acquisition module; 1050 - database generation module;

[0062] 101 - processor; 102 - memory; 103 - bus; 104 - communication interface. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme of the present application will be described clearly and completely below in combination with embodiments. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0064] In the non-targeted identification of metabolites in samples, library searching is the most critical step. Library searching mainly includes two core parts: one is the technology and method used in library searching, and the other is the reference metabolite spectrum library. In the past, users generally chose commercial library searching software provided by upstream instrument manufacturers, such as Compound Discovery, and combined with related spectrum libraries, such as mzCloud, mzVault, ChemSpider, etc. However, such spectrum libraries have the problem of poor data information accuracy, resulting in a low proportion of substances in the sample that can be accurately identified. In addition, due to differences in chromatographic conditions, parameters such as retention time cannot be reused, and these factors have an adverse effect on the identification results. In summary, the details of the information of various public databases involved in the current metabolite spectrum library are not disclosed, and the data quality of the database information cannot meet the requirements. Based on this, the present application provides a metabolite spectrum library construction method, system and database, which realizes the extraction of standard substance spectrum and the establishment of spectrum library, the overall library construction logic is unified, the route is reliable, the spectrum quality is high, it can be traced and long-term optimized, and the accuracy of identification can be improved when identifying samples.

[0065] In order to facilitate the understanding of the present embodiment, first, a metabolite spectrum library construction method disclosed by the present embodiment is introduced in detail, as shown in the following formula (I), the method comprises: Figure 1

[0066] Step S101, obtaining a standard substance corresponding to a metabolite, determining substance information data and sum ion data of the standard substance.

[0067] The standard substance can be obtained by purchasing high-purity (≥98%) metabolite standard substances, or by synthesis, natural extraction. The batch stability, purity (such as confirmed by HPLC, NMR) and chemical structure correctness of the standard substance need to be verified. For isomers or structural analogs, additional stereochemical information (such as chiral configuration), isotopic labeling information (such as 13C, 2H markers) needs to be labeled to avoid confusion in subsequent identification. The substance information data acquisition process can be performed by recording the basic attributes of the standard substance: chemical name, CAS number, molecular formula, molecular weight, chemical classification (such as amino acids, fatty acids, nucleotides, etc.), physicochemical properties (such as water solubility, logP value).

[0068] ​Adduct ion data can predict possible adduct ion forms according to mass spectrometry ionization modes (such as ESI+, ESI-, APCI), for example: common adduct ions under ESI+ mode: [M+H]+, [M+Na]+, [M+NH4]+; common adduct ions under ESI- mode: [M-H]-, [M+HCOO]-. Through pre-experiment optimization of ionization conditions, the best adduct ion form of the target metabolite is determined (such as selecting the adduct ion with the highest response intensity).

[0069] Step S102, calculate the spectrum matching information corresponding to the metabolite based on the substance information data and the adduct ion data, and obtain the on-machine spectrum information of the standard substance corresponding to the substance through the mass spectrometer.

[0070] When calculating the theoretical spectrum matching information, the mass spectrometry fragment ions can be predicted based on the substance structure: using molecular simulation software (such as ChemSpider, MS / MS prediction tool under CE mode) to simulate the high-energy collision dissociation (HCD) or collision-induced dissociation (CID) process, to generate the mass-to-charge ratio (m / z), relative intensity and fragmentation path of the theoretical fragment ions.

[0071] Constructing the spectrum matching feature matrix can integrate the adduct ions, theoretical fragment ions and their predicted intensities to form a theoretical spectrum template for subsequent matching.

[0072] The on-machine spectrum information acquisition process involves chromatography-mass spectrometry combined condition optimization: the specific chromatography conditions use reversed phase (C18, C8) or hydrophilic interaction chromatography (HILIC) column, optimize the mobile phase composition (such as methanol-water system, acetonitrile-ammonium formate buffer), gradient elution program, column temperature (such as 40℃) and flow rate (0.3 mL / min) to realize efficient separation of metabolites.

[0073] The mass spectrometry parameters can use high-resolution mass spectrometers (such as Q-TOF, Orbitrap) to set the scan range (such as m / z 50-1500), resolution (such as 30,000 FWHM), collision energy (such as 10-40 eV gradient), and collect MS / MS data in data-dependent scanning (DDA) or data-independent scanning (DIA) mode. Each standard is injected separately (such as 10 μL, concentration 1-10 μM), repeated 3 times to ensure spectrum repeatability, and the original mass spectrometry data is recorded.

[0074] Step S103, obtain the sample spectrum information corresponding to the metabolite according to the spectrum matching information and the on-machine spectrum information, and obtain the characteristic ion information corresponding to the metabolite using the sample spectrum information.

[0075] Raw spectra preprocessing can use data processing software (such as XCMS, MZmine, Progenesis QI) to perform baseline correction, peak detection, peak alignment and denoising on raw mass spectrometry data, eliminating instrument noise and background interference. For MS / MS spectra, the m / z, intensity and corresponding retention time window (such as ±0.5 min) of the secondary fragment ions are extracted.

[0076] The core feature construction of the feature ion information extraction process can include: parent ion features: accurate mass number (error ≤5 ppm) and charge number of the sum ion; fragment ion features: m / z and relative intensity ratio (such as the top 3 characteristic fragments) of high-intensity fragments; retention time features: retention time (RT) obtained by single needle injection, used for subsequent mixed sample grouping verification.

[0077] Abnormal spectrum data is removed through isotope peak verification (such as [M+1] peak intensity consistent with theoretical isotope abundance) and fragment ion rationality check (such as excluding non-characteristic sum ion fragments).

[0078] In step S104, the grouping strategy is determined according to the type parameter of the standard substance, and after the mixed sample grouping of the substance and the standard substance is performed using the grouping strategy, the spectrum integration information corresponding to the mixed sample grouping is obtained by the mass spectrometer.

[0079] The grouping strategy is based on the grouping of the physicochemical properties and chromatographic behavior of the standard substance, and can include polarity grouping, molecular weight grouping and chemical stability grouping. Specifically, polar substances (such as amino acids, nucleotides) in the polarity grouping are separated by HILIC column, and non-polar substances (such as fatty acids, steroids) are separated by reversed-phase column. Small molecules (<500 Da) and large molecules (such as polypeptides) in the molecular weight grouping are separated by injection. Acid / base sensitive and easily oxidized metabolites (such as aldehydes, polyphenols) are separately grouped in the chemical stability grouping, and the pretreatment conditions (such as the addition of antioxidants) are optimized.

[0080] The mixed sample strategy can set each group to contain 10-20 standard substances, prepare a mixed standard solution by equal concentration mixing, reduce the number of injections and improve the efficiency of chromatographic separation.

[0081] Batch injection (such as 3 times) is performed on the mixed standard grouping, the same chromatographic conditions (consistent with single needle injection) are used, and the mean value and standard deviation (RSD ≤2%) of the retention time of each metabolite are recorded.

[0082] A retention time correction factor (such as using a known retention time internal standard, such as caffeine, toluenesulfonic acid) is introduced to correct the retention time drift between different batches by software (such as RT-aligner), and the cross-sample comparability is improved.

[0083] Step S105, construct a spectrum library corresponding to the metabolite by using the spectrum integration information.

[0084] This step realizes multi-dimensional spectrum information integration. In the data alignment and fusion process, the MS / MS spectrum of single needle injection can be associated with the retention time of mixed sample grouping. The accurate mass number (parent ion and fragment ion), secondary spectrum fragment network (such as the fragmentation relationship between fragment ions), retention time and chromatographic peak shape parameters (such as peak width, symmetry), sum ion type and optimized mass spectrum parameters (such as collision energy) of each metabolite can be integrated through the retention time-mass to charge ratio (RT-m / z) matrix.

[0085] The structured construction of the spectrum library needs to establish a database field system, including basic information, mass spectrum characteristics, chromatographic characteristics and metadata. Specifically, the basic information can involve chemical name, CAS number, molecular formula, molecular weight; the mass spectrum characteristics can involve parent ion m / z, fragment ion list (m / z + intensity), MS / MS spectrum file (mzXML or mgf format); the chromatographic characteristics can involve retention time, chromatographic column type, mobile phase conditions; the metadata can involve standard purity, mass spectrometer model, data acquisition date.

[0086] In actual scenarios, open source or other related database formats (such as mzCloud, HMDB compatible format) can be used for storage, which is convenient for subsequent library search software to call. In general terms, the quality of the test spectrum library is mainly in the form of direct library search using mixed standard samples. That is, it is known which substances are in the sample, and the library search is performed to see how many can be identified and how many are incorrectly identified. Generally, the main indicators for identification standards include parent ion mass deviation (<=10ppm, which depends on the resolution of the mass spectrometer, 10-25), fragment ion matching degree (which has some recognized scoring methods, dot product or spectral entropy, we use the spectral entropy method to score 0.5 or more), and retention time deviation, which is generally measured in seconds, and a deviation of 10s is considered to be a relatively strict requirement in actual scenarios.

[0087] Optionally, the step S101 of acquiring the standard substance corresponding to the metabolite, determining the substance information data of the standard substance, and acquiring the sum ion data of the standard substance is as shown in Figure 2 , which includes:

[0088] Step S201, acquiring the standard substance corresponding to the plurality of metabolites contained in the spectrum library establishment process, and acquiring the molecular formula and acquisition mode parameters corresponding to the standard substance;

[0089] Step S202, determining the substance information data of the standard substance according to the molecular formula and acquisition mode parameters, and determining the sum ion data corresponding to the standard substance based on the molecular formula.

[0090] For each standard sample participating in the library construction, there is a molecular formula and a positive and negative acquisition mode, which is used to calculate the primary molecular weight and the possible mass-to-charge ratio. Each standard sample is obtained from a mass spectrometer, and the purchased standard sample is dissolved and diluted before being loaded onto the instrument. The signal collected by the mass spectrometer is saved in a file.raw. The file is first converted to an mgf file using open source software msconvert, and then can be used for library construction. The adduct ion data is calculated according to the molecular information of the substance, and then the mass-to-charge ratio of the parent ion of the substance is calculated for spectrum extraction.

[0091] Optionally, the step S102 of calculating the spectrum matching information corresponding to the metabolite based on the substance information data and the adduct ion data and obtaining the on-machine spectrum information of the substance corresponding to the standard sample by the mass spectrometer is as shown in Figure 3

[0092] Step S301, calculating the molecular weight corresponding to the metabolite by using the molecular formula corresponding to the substance information data and the acquisition mode parameter;

[0093] Step S302, determining the adduct molecular weight corresponding to the adduct ion data according to the acquisition mode parameter, and calculating the spectrum matching information corresponding to the metabolite based on the molecular weight and the adduct molecular weight;

[0094] Step S303, obtaining the information table corresponding to the standard sample, obtaining the off-machine path corresponding to the mass spectrometer by using the row data in the information table, and obtaining the mass spectrum file contained in the off-machine path;

[0095] Step S304, obtaining the on-machine spectrum information of the substance corresponding to the standard sample based on the mass spectrum file.

[0096] In actual scenarios, the information such as the molecular weight of the substance is already available, and the corresponding substance name or cas number can be directly obtained. The molecular formula can be obtained by querying through an interface such as pubchem.

[0097] All the following processes use the example substance information NC3H5O6P Phosphoenolpyruvic acid 0.1HFX10 CN N285.mgf.

[0098] ​The accurate molecular weight is calculated as 167.98238, and 5 significant digits are retained. The main logic is to calculate the accurate molecular weight by adding the accurate element mass and the molecular formula of the substance. According to the experience of mass spectrometry, the substance may have 8 main forms of additive ions (two positive and two negative) generated in the ion source. The mass of the additive form of the substance is obtained according to the list of additive ions and stored as a dictionary {'[M-H]-': 166.97508, '[M-H-H2O]-': 148.96458, '[M+HCOOH-H]-': 212.98058, '[M+CH3COOH-H]-': 226.99628}. The positive or negative additive ion is used, depending on the ion source mode when the standard actually machine. In the case of no prior substance characteristics, the substance needs to be separately put on the positive mode / negative mode, and then according to the positive and negative ion information, the corresponding secondary spectrum is collected.

[0099] All the standard information is traversed according to the row of the standard information table, the filename information is HFX10 CN N285.mgf, the mass spectrum file of the standard off-line path is found according to the information, and the file information is parsed. According to the standard file searching, the spectrum in the deviation range is extracted, the matching instrument platform first mass deviation parameter deltaMs1 is set, and it is judged whether the first information in the corresponding storage unit of the substance is in the mass deviation range. The deviation range is set as the size deviation deltaMs1 of the additive ion mass of the substance.

[0100] Optionally, the sample spectrum information corresponding to the metabolite is obtained according to the spectrum matching information and the on-machine spectrum information, as shown in the following formula: Figure 4 As shown in the following formula:

[0101] Step S401, determining the mass spectrum file corresponding to the standard by using the spectrum matching information and the on-machine spectrum information;

[0102] Step S402, obtaining the storage unit contained in the mass spectrum file, and extracting the numerical data and array data contained in the storage unit;

[0103] Step S403, determining the sample spectrum information corresponding to the metabolite based on the numerical data and the array data.

[0104] The file is an mgf format file, each storage unit is a secondary mass spectrum information of the sample, and the information contained therein is: numerical first-level mz and intensity, array type secondary mz and intensity. By obtaining the storage unit contained in the mass spectrum file, the numerical data and array data contained in the storage unit are extracted, and then the sample spectrum information corresponding to the metabolite is determined based on the numerical data and the array data.

[0105] Optionally, before acquiring the characteristic ion information corresponding to the metabolite by using the sample spectrum information, the method further includes: Figure 5 as shown in the formula (1), the method further includes:

[0106] In step S501, the effective MS / MS spectrum information corresponding to the numerical data and the array data in the storage unit is acquired based on the mass data and the charge data corresponding to the sum ion data.

[0107] In step S502, the sample spectrum information is updated by using the effective MS / MS spectrum information.

[0108] In actual scenarios, it is necessary to determine whether the MS / MS information is effective and to save the effective MS / MS spectrum. To determine whether the MS / MS spectrum is effective, the MS / MS array information in the storage unit needs to be referred to. It is necessary to cyclically determine whether the mass-to-charge ratio of each sub-ion is within the set relative mass deviation range of the parent ion. The relative mass deviation range of the parent ion is calculated according to the mass and the charge number of the sum ion, and the calculation formula is: high = round(ppm / 1000000 * v + v, 5); low = round(-ppm / 1000000 * v + v, 5). Wherein, v is the accurate molecular weight of the sum ion. The effective MS / MS spectrum units that meet the conditions are extracted, and the format is processed and arranged into library information. For example, the substance Phosphoenolpyruvic acid can collect 3 pieces of MS / MS information that meet the conditions in HFX10 CN N285.mgf, and the format of the MS / MS information is the paired mz and intensity information.

[0109] Optionally, the characteristic ion information corresponding to the metabolite is acquired by using the sample spectrum information, as shown in the formula (1), the method includes: Figure 6

[0110] In step S601, the spectrum data corresponding to the sample spectrum information is acquired.

[0111] In step S602, the spectrum ID corresponding to the spectrum data is determined according to the positive and negative mode parameters corresponding to the substance and the sum ion data corresponding to the substance, and the merging strategy corresponding to the spectrum is determined based on the spectrum ID.

[0112] In step S603, the MS / MS spectrum corresponding to the sample spectrum information is acquired by using the merging strategy, and the characteristic ion information corresponding to the metabolite is determined based on the MS / MS spectrum.

[0113] ​The process of obtaining characteristic ions involves a spectrum merging and compression process. After obtaining all spectrum data of the current batch library, the spectrum is merged according to the positive and negative modes and the adduct ions. First, the spectrum data format is processed, and the substance, mode and adduct ion are connected with '--' as the spectrum ID, which is used to determine which spectra need to be merged. The sub-ion information is arranged into a one-dimensional array of mz and intensity, and connected into a row. The spectrum merging is mainly based on the relative mass tolerance of the sub-ion and the proportion of the signal intensity. The sub-ions within the acceptable deviation range are merged to form characteristic sub-ions, and new spectra are formed which can represent all the secondary spectra collected under the same mode and with the same adduct ion of the substance.

[0114] Optionally, the grouping strategy is determined according to the type parameter of the standard sample, and the substance and the standard sample are mixed and grouped using the grouping strategy. Then, the spectrum integration information corresponding to the mixed sample group is obtained by the mass spectrometer in step S104, as shown in Figure 7 .

[0115] In step S701, the type parameter corresponding to the standard sample is obtained, the nuclear mass ratio list corresponding to the standard sample is obtained according to the type parameter, and the grouping strategy is determined based on the nuclear mass ratio value in the nuclear mass ratio list.

[0116] In step S702, the substance is grouped using the grouping strategy, and then mixed with the standard sample to obtain the substance group corresponding to the standard sample. The spectrum data of the substance group is obtained by the mass spectrometer.

[0117] In step S703, the actual retention time of the substance group in the mass spectrometer is obtained according to the spectrum data, and the first-level information and the second-level information of the substance group determined by the actual retention time are used to generate the spectrum integration information.

[0118] After the above spectrum is collected, the successfully built library of substances generates ion pairs. That is, for each substance, positive and negative modes, and adduct forms, the signal intensity of the sub-ion is sorted, and the mass-to-charge ratio of the top 3 ions with the strongest signal is taken as the characteristic ion under the condition.

[0119] In order to efficiently extract the retention time (RT) of all substances in the actual production environment, the sorting classification algorithm is used to classify the batch of standard samples first. The basic logic of the algorithm is as follows: first, calculate the list of accurate molecular weights MZ corresponding to all possible adduct forms of all substances; then sort the list by MZ; traverse from the beginning, take out the substances with MZ deviation within 0.5 Da, and take out all the corresponding adduct form MZ of the substance; after one traversal, the remaining substances form a group; the extracted substances are recycled for the above process.

[0120] Optionally, the spectrum integration information is used to construct the spectrum library corresponding to the metabolites in step S105, as shown inFigure 8 As shown in the figure, comprising:

[0121] Step S801, obtaining the substance group corresponding to the mixed sample group, and determining the first-level information and the second-level information corresponding to the substance group;

[0122] Step S802, determining the spectrum integration information by using the retention time and the first-level information and the second-level information meeting the preset deviation range;

[0123] Step S803, constructing the spectrum library according to the standard sample based on the spectrum integration information.

[0124] The generated substance group is taken out to the standard LC-MS / MS machine for machine operation, that is, through standard chromatography and mass spectrometry. After the machine operation, the data is extracted by using the Python script to extract all the first-level and second-level information, and then it is judged whether the first-level and second-level information is in the deviation range according to the similar spectrum extraction logic. The difference is that only the existence of the characteristic ion needs to be judged. In the case of successful matching, the actual machine retention time of the substance in this machine operation is obtained and stored in the database.

[0125] Specifically, the overall process in the above embodiment can refer to the flowchart of another metabolite spectrum library construction method shown in Figure 9 The flowchart of another metabolite spectrum library construction method is not repeated.

[0126] From the metabolite spectrum library construction method mentioned in the above embodiment, it can be known that the method realizes the extraction of the standard sample spectrum and the establishment of the spectrum library, the overall library construction logic is unified, the route is reliable, the spectrum quality is high, it can be traced and long-term optimized, and the accuracy of identification can be improved when the sample is identified.

[0127] Corresponding to the metabolite spectrum library construction method provided in the foregoing embodiment, the embodiment of the present application provides a metabolite spectrum library construction system, as shown in Figure 10 The system comprises:

[0128] The data acquisition module 1010 is configured to acquire the standard sample corresponding to the metabolite, determine the substance information data and the sum ion data of the standard sample;

[0129] The data processing module 1020 is configured to calculate the spectrum matching information corresponding to the metabolite based on the substance information data and the sum ion data, and acquire the machine spectrum information of the substance corresponding to the standard sample by using the mass spectrometer;

[0130] The characteristic ion information acquisition module 1030 is configured to acquire the sample spectrum information corresponding to the metabolite according to the spectrum matching information and the machine spectrum information, and acquire the characteristic ion information corresponding to the metabolite by using the sample spectrum information;

[0131] The retention time acquisition module 1040 is configured to determine a grouping strategy according to the type parameter of the standard sample, and after the sample and the standard sample are mixed and grouped by using the grouping strategy, acquire spectrum integration information corresponding to the mixed and grouped sample by using the mass spectrometer.

[0132] The database generation module 1050 is configured to construct a spectrum library corresponding to the metabolite by using the spectrum integration information.

[0133] It can be known from the metabolite spectrum library construction system mentioned in the above embodiment that the system realizes extraction of standard sample spectrum and establishment of a spectrum library, the overall library construction logic is unified, the route is reliable, the spectrum quality is high, the spectrum can be traced and long-term optimized, and the accuracy of identification can be improved when the sample is identified.

[0134] The metabolite spectrum library construction system provided in the embodiment has the same implementation principle and technical effects as the metabolite spectrum library construction method, and for brevity of description, the part of the system embodiment not mentioned can be referred to the corresponding content in the metabolite spectrum library construction method.

[0135] The embodiment also provides a database, and a structure diagram of the database is shown in Figure 11 The device includes a processor 101 and a memory 102; the memory 102 is configured to store one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the steps of the metabolite spectrum library construction method.

[0136] Figure 11 The database shown in the figure also includes a bus 103 and a communication interface 104, and the processor 101, the communication interface 104 and the memory 102 are connected through the bus 103.

[0137] The memory 102 can include a high-speed random access memory (RAM) and can also include a non-volatile memory, for example, at least one disk memory. The bus 103 can be an ISA bus, a PCI bus or an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 11 Only one bidirectional arrow is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0138] The communication interface 104 is configured to be connected with at least one user terminal and other network units through a network interface, and send the encapsulated IPv4 packet or IPv4 packet to the user terminal through the network interface.

[0139] The processor 101 can be an integrated circuit chip having a processing capability of signals. In the implementation process, each step of the above method can be completed by the integrated logic circuit of hardware in the processor 101 or the instruction in the form of software. The processor 101 described above can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. Each method, step and logic block diagram disclosed in the embodiment of the present disclosure can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the embodiment of the present disclosure can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor for execution. The software module can be located in a random access memory, a flash memory, a read only memory, a programmable read only memory or an electrically erasable programmable memory, a register or other mature storage medium in the art. The storage medium is located in the memory 102, and the processor 101 reads the information in the memory 102 and combines the hardware to complete the steps of the method of the above embodiment.

[0140] The embodiment of the present application further provides a storage medium, and the storage medium stores a computer program. When the computer program is run by a processor, the steps of the metabolite spectrum library construction method in the above embodiment are executed.

[0141] In several embodiments provided in the present application, it should be understood that the disclosed system, device, equipment and method can be implemented by other ways. The system embodiment described above is only schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or components shown or discussed can be indirect coupling or communication connection through some communication interface, equipment or unit, and can be electrical, mechanical or other forms.

[0142] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, i.e. may be located in one place, or may be distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0143] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0144] If the functions are realized in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solutions of the present application or the part of the present application that essentially contributes to the prior art or the part of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for making a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk, and various program code storage media.

[0145] Finally, it should be noted that: the above-described embodiments are only specific embodiments of the present application, used to illustrate the technical solutions of the present application, and not to limit them, the protection scope of the present application is not limited thereto, although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand: any skilled person in the art within the technical range disclosed by the present application, they can still modify or easily think of changes to the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part of the technical features; and these modifications, changes or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and all should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for constructing a metabolite spectral library, characterized in that, The method includes: Obtain the corresponding standards for the metabolites, and determine the material information data and ion addition data of the standards; Based on the substance information data and the added ion data, the spectral matching information corresponding to the metabolite is calculated, and the on-machine spectral information of the substance corresponding to the standard is obtained by mass spectrometry. Based on the spectral matching information and the on-machine spectral information, obtain the sample spectral information corresponding to the metabolite, and use the sample spectral information to obtain the characteristic ion information corresponding to the metabolite; A grouping strategy is determined based on the type parameters of the standard, and the substance and the standard are mixed and grouped using the grouping strategy. Then, the integrated spectral information corresponding to the mixed group is obtained by the mass spectrometer. The spectral integration information is used to construct a spectral library corresponding to the metabolite; Based on the spectral matching information and the on-machine spectral information, the sample spectral information corresponding to the metabolite is obtained, including: The mass spectrometry file corresponding to the standard is determined using the spectral matching information and the on-machine spectral information. Obtain the storage units contained in the mass spectrometry file, and extract the numerical data and array data contained in the storage units; The sample spectral information corresponding to the metabolite is determined based on the numerical data and the array data; Obtaining the characteristic ion information corresponding to the metabolite using the sample spectral information includes: Obtain the spectral data corresponding to the sample spectral information; The spectrum ID corresponding to the spectrum data is determined based on the positive and negative mode parameters corresponding to the substance and the corresponding summed ion data, and the merging strategy corresponding to the spectrum is determined based on the spectrum ID; The merging strategy is used to obtain the secondary spectrum corresponding to the sample spectrum information, and the characteristic ion information corresponding to the metabolite is determined based on the secondary spectrum.

2. The method for constructing a metabolite spectrum library according to claim 1, characterized in that, The steps of obtaining standards corresponding to metabolites and determining the material information data and added ion data of the standards include: Obtain the standards corresponding to the multiple metabolites included in the process of establishing the spectral library, and obtain the molecular formula and acquisition mode parameters corresponding to the standards; The material information data of the standard is determined based on the molecular formula and the acquisition mode parameters, and the addition ion data corresponding to the standard is determined based on the molecular formula.

3. The method for constructing a metabolite spectrum library according to claim 2, characterized in that, Based on the substance information data and the summed ion data, the spectral matching information corresponding to the metabolite is calculated, and the on-disc spectral information of the substance corresponding to the standard is obtained by mass spectrometry, including: The molecular weight of the metabolite is calculated using the molecular formula corresponding to the substance information data and the acquisition mode parameters. The summed molecular weight corresponding to the summed ion data is determined according to the acquisition mode parameters, and the spectral matching information corresponding to the metabolite is calculated based on the molecular weight and the summed molecular weight. Obtain the information table corresponding to the standard, use the row data in the information table to obtain the discharging path of the mass spectrometer, and obtain the mass spectrometry file contained in the discharging path; Based on the mass spectrometry file, obtain the spectroscopic spectral information of the substance corresponding to the standard.

4. The method for constructing a metabolite spectrum library according to claim 1, characterized in that, Before obtaining the characteristic ion information corresponding to the metabolite using the sample spectral information, the method further includes: Based on the mass and charge data corresponding to the summed ion data, obtain the valid secondary spectrum information corresponding to the numerical data and the array data in the storage unit; The sample spectrum information is updated using the effective secondary spectrum information.

5. The method for constructing a metabolite spectrum library according to claim 1, characterized in that, The steps include determining a grouping strategy based on the type parameters of the standard, mixing and grouping the substance and the standard using the grouping strategy, and then obtaining the integrated spectral information corresponding to the mixed grouping using the mass spectrometer. Obtain the type parameter corresponding to the standard product, obtain the nucleus-mass ratio list corresponding to the standard product according to the type parameter, and determine the grouping strategy based on the nucleus-mass ratio values ​​in the nucleus-mass ratio list; After the substances are grouped using the grouping strategy, they are mixed with the standards to obtain the substance groups corresponding to the standards, and the mass spectrometer is used to obtain the on-machine spectrum data of the substance groups. The actual retention time of the substance group in the mass spectrometer is obtained based on the on-machine spectral data, and the primary and secondary information of the substance group determined by the actual retention time are used to generate the spectral integration information.

6. The method for constructing a metabolite spectrum library according to claim 5, characterized in that, Constructing a spectral library corresponding to the metabolite using the spectral integration information includes: Obtain the substance group corresponding to the mixed sample group, and determine the primary information and the secondary information corresponding to the substance group; The spectral integration information is determined using the retention time and the primary and secondary information that satisfy a preset deviation range. The spectral library is constructed based on the integrated spectral information and the standard samples.

7. A system for constructing a metabolite spectral library, characterized in that, The system includes: The data acquisition module is used to acquire the standard corresponding to the metabolite and determine the material information data and the summed ion data of the standard. The data processing module is used to calculate the spectral matching information corresponding to the metabolite based on the substance information data and the added ion data, and to obtain the on-machine spectral information of the substance corresponding to the standard through a mass spectrometer; The feature ion information acquisition module is used to acquire the sample spectrum information corresponding to the metabolite based on the spectrum matching information and the on-machine spectrum information, and to acquire the feature ion information corresponding to the metabolite using the sample spectrum information; The retention time acquisition module is used to determine a grouping strategy based on the type parameters of the standard, and after mixing and grouping the substance and the standard using the grouping strategy, acquire the integrated spectral information corresponding to the mixed group through the mass spectrometer. A database generation module is used to construct a spectral library corresponding to the metabolite using the spectral integration information. In the process of acquiring the sample spectrum information corresponding to the metabolite based on the spectrum matching information and the on-machine spectrum information, the feature ion information acquisition module is further configured to: determine the mass spectrometry file corresponding to the standard using the spectrum matching information and the on-machine spectrum information; acquire the storage units contained in the mass spectrometry file, and extract the numerical data and array data contained in the storage units; and determine the sample spectrum information corresponding to the metabolite based on the numerical data and the array data. In the process of acquiring the characteristic ion information of the metabolite using the sample spectrum information, the characteristic ion information acquisition module is also used to: acquire the spectral data corresponding to the sample spectrum information; determine the spectral ID corresponding to the spectral data based on the positive and negative mode parameters corresponding to the substance and the corresponding summed ion data, and determine the merging strategy corresponding to the spectrum based on the spectral ID; acquire the secondary spectrum corresponding to the sample spectrum information using the merging strategy, and determine the characteristic ion information corresponding to the metabolite based on the secondary spectrum.

8. A database system, characterized in that, The method includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, the processor executing the computer-executable instructions to implement the steps of the method for constructing a metabolite spectrum library according to any one of claims 1 to 6.

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