Non-targeted cascade mass spectrum imaging method and device

Abstract

The invention relates to the technical field of mass spectrum imaging, in particular to a non-targeted cascade mass spectrum imaging method and device, and the method comprises the steps: obtaining a second-level mass spectrum of each pixel point, and carrying out the spectrum peak recognition and peak extraction, so as to obtain a first intensity matrix, and performing first-order deconvolution calculation to obtain a plurality of parent ion secondary mass spectrums and a corresponding relation between the parent ion secondary mass spectrums and fragment ions, generating a second intensity matrix in combination with adjacent pixel molecule composition information, performing second-order deconvolution calculation to obtain relative ion intensity of characteristic fragments generated by each parent ion in each pixel, and generating a multi-target mass spectrum imaging result. Therefore, the problems that in related technologies, mass spectrum imaging cannot be combined with a chromatographic separation technology generally, so that the analysis dimension is limited, and the data analysis difficulty is increased; the problems that the complexity and the cost of an instrument are increased, the application scene is limited and the stability and the usability are influenced due to the fact that data do not depend on acquisition and spectrum diagram deconvolution depends on a molecular composition modulation technology are solved.

Description

Technical Field

[0001] The present application relates to the technical field of mass spectrometry imaging, and in particular to a non-targeted tandem mass spectrometry imaging method and device. Background Art

[0002] Among related technologies, data-independent acquisition can improve ion utilization and data acquisition throughput. The key is to build a correspondence between parent ions and daughter ions to reconstruct a standard secondary spectrum for structural annotation. Deconvolution technology requires modulation of ion composition, such as ion migration technology, which realizes lipid structure annotation and in situ tissue imaging. In principle, this technology is also applicable to spatial imaging analysis of other metabolite ions.

[0003] However, among the related technologies, mass spectrometry imaging generally cannot be combined with chromatographic separation technology, which limits the analysis dimension and increases the difficulty of data analysis. Data-independent acquisition and spectrum deconvolution rely on molecular composition modulation technology, which increases the complexity and cost of the instrument, limits the application scenarios, and affects stability and ease of use, which urgently needs to be improved. Summary of the invention

[0004] The present application provides a non-targeted tandem mass spectrometry imaging method and device to solve the problems in the related art that mass spectrometry imaging cannot be combined with chromatographic separation technology as a whole, resulting in limited analysis dimensions and increased difficulty in data analysis; data-independent acquisition and spectrum deconvolution rely on molecular composition modulation technology, resulting in increased instrument complexity and cost, limited application scenarios, and affecting stability and ease of use.

[0005] The first aspect of the present application provides a non-targeted tandem mass spectrometry imaging method, comprising the following steps: obtaining a secondary mass spectrometer for each pixel; performing peak identification and peak extraction based on the secondary mass spectrometer to obtain a first intensity matrix of parent ions and fragment ions in the dimensions of mass-to-charge ratio and spatial position; performing a first-order deconvolution calculation on the first intensity matrix to obtain secondary mass spectra of multiple parent ions, and obtain the correspondence between parent ions and fragment ions; based on the obtained correspondence between parent ions and fragment ions, combined with the molecular composition information of adjacent pixels, assigning each tissue a fragment ion and a second intensity matrix of the corresponding parent ion in the dimensions of mass-to-charge ratio and spatial position; performing a second-order deconvolution calculation on the second intensity matrix to obtain the relative ion intensity of characteristic fragments generated by each parent ion in each pixel, and generate a multi-target mass spectrometry imaging result.

[0006] Through the above technical solution, the embodiment of the present application can fully mine the mass spectrometry data information by obtaining the secondary mass spectrogram of each pixel and a series of subsequent processing. The first intensity matrix obtained by peak recognition and peak extraction lays the foundation for subsequent analysis, and the parent ion secondary mass spectrogram and corresponding relationship obtained by the first-order deconvolution realize preliminary structural annotation. Combined with the adjacent pixel information to generate the second intensity matrix and the second-order deconvolution to calculate the relative ion intensity, accurately analyze the parent ion situation in each pixel, and finally generate multi-target mass spectrometry imaging results, including but not limited to large-scale lipid and metabolite structural annotation and spatial omics analysis, and no functional modules such as ion mobility separation are required, which reduces the hardware requirements for mass spectrometry instruments and improves sample ion utilization and imaging flux.

[0007] Optionally, in one embodiment of the present application, acquiring the secondary mass spectrum of each pixel point includes: acquiring the secondary mass spectrum of each pixel point in a data-independent mode of wide window full fragmentation, wherein different pixels are determined based on the target coverage of the molecular annotation to implement wide window fragmentation with different mass-to-charge ratio windows.

[0008] Through the above technical solution, the embodiment of the present application can obtain a secondary mass spectrum in a data-independent mode of wide window full fragmentation, while fragmenting a large number of parent ions, thereby improving ion utilization and data acquisition throughput. Based on the molecular annotation target coverage, different pixels are determined to use different mass-to-charge ratio windows for wide window fragmentation, which can obtain mass spectrum information more specifically, help improve the accuracy and comprehensiveness of molecular annotation, and better adapt to the analysis needs of different molecules in complex biological samples, thereby providing a better quality and richer data foundation for subsequent mass spectrometry imaging data processing, structural annotation, and multi-target imaging.

[0009] Optionally, in one embodiment of the present application, before obtaining the first intensity matrix of the parent ion and the fragment ions in the mass-to-charge ratio and spatial position dimensions, it also includes: dividing the parent ion and the fragment ions based on the mass-to-charge ratio of the parent ion being greater than the mass-to-charge ratio of the fragment ion, wherein the mass-to-charge ratio of the parent ion is limited to a preset wide window range.

[0010] Through the above technical solution, the embodiment of the present application can be based on the reasonable division of the mass-to-charge ratio of the parent ion and the fragment ion, that is, the mass-to-charge ratio of the parent ion is greater than that of the fragment ion and is limited to a preset wide window range, effectively distinguishing the two, providing a basis for subsequent accurate analysis, and helping to more accurately identify and track ion information during data processing, and improve the accuracy of mass spectrometry data analysis. Limiting the parent ion within a wide window range can ensure that enough parent ion information is obtained while avoiding interference from too many irrelevant ions, improving the pertinence and effectiveness of data acquisition, and thus optimizing the entire non-targeted tandem mass spectrometry imaging process.

[0011] Optionally, in one embodiment of the present application, the performing a first-order deconvolution calculation on the first intensity matrix includes: using the first intensity matrix to solve a first preset optimization problem to obtain the secondary mass spectrum.

[0012] Through the above-mentioned technical scheme, the embodiment of the present application can effectively integrate the rich information in the first intensity matrix, and convert the relationship between the parent ion and the fragment ion in terms of mass-to-charge ratio and spatial position into a clear secondary mass spectrum through optimization calculation, thereby improving the utilization and interpretability of the data. The process of solving the optimization problem can realize the intelligent processing of complex mass spectrometry data, avoid the subjectivity and limitations of manual analysis, and enhance the objectivity and accuracy of the results.

[0013] Optionally, in one embodiment of the present application, the performing a second-order deconvolution calculation on the second intensity matrix includes: using the second intensity matrix to solve a second preset optimization problem to obtain the relative ion intensity.

[0014] Through the above technical solution, the embodiment of the present application can accurately determine the relative ion intensity of characteristic fragments generated by each parent ion in each pixel, providing key quantitative data support for multi-target mass spectrometry imaging. At the same time, it helps to gain a deeper understanding of the distribution and metabolism of molecules in biological tissues, plays an important role in biomedical research, disease diagnosis and other fields, and improves the ability and level of non-targeted tandem mass spectrometry imaging technology to analyze complex biological samples.

[0015] The second aspect of the present application provides a non-targeted tandem mass spectrometry imaging device, including: an acquisition module, used to acquire a secondary mass spectrum of each pixel; a first data processing module, used to perform spectral peak identification and peak extraction based on the secondary mass spectrum to obtain a first intensity matrix of parent ions and fragment ions in the mass-to-charge ratio and spatial position dimensions; a first calculation module, used to perform a first-order deconvolution calculation on the first intensity matrix to acquire secondary mass spectra of multiple parent ions, and acquire the correspondence between parent ions and fragment ions; a second data processing module, used to assign each tissue a fragment ion and a second intensity matrix of the corresponding parent ion in the mass-to-charge ratio and spatial position dimensions based on the acquired correspondence between the parent ions and fragment ions and combined with the molecular composition information of adjacent pixels; a second calculation module, used to perform a second-order deconvolution calculation on the second intensity matrix to acquire the relative ion intensity of characteristic fragments generated by each parent ion in each pixel, and generate a multi-target mass spectrometry imaging result.

[0016] Through the above technical solution, the embodiment of the present application can fully mine the mass spectrometry data information by obtaining the secondary mass spectrogram of each pixel and a series of subsequent processing. The first intensity matrix obtained by peak recognition and peak extraction lays the foundation for subsequent analysis, and the parent ion secondary mass spectrogram and corresponding relationship obtained by the first-order deconvolution realize preliminary structural annotation. Combined with the adjacent pixel information to generate the second intensity matrix and the second-order deconvolution to calculate the relative ion intensity, accurately analyze the parent ion situation in each pixel, and finally generate multi-target mass spectrometry imaging results, including but not limited to large-scale lipid and metabolite structural annotation and spatial omics analysis, and no functional modules such as ion mobility separation are required, which reduces the hardware requirements for mass spectrometry instruments and improves sample ion utilization and imaging flux.

[0017] Optionally, in one embodiment of the present application, the acquisition module includes: acquiring the secondary mass spectrum of each pixel point in a data-independent mode of wide window full fragmentation, wherein different pixel points are determined based on the target coverage of molecular annotations to implement wide window fragmentation with different mass-to-charge ratio windows.

[0018] Through the above technical solution, the embodiment of the present application can obtain a secondary mass spectrum in a data-independent mode of wide window full fragmentation, while fragmenting a large number of parent ions, thereby improving ion utilization and data acquisition throughput. Based on the molecular annotation target coverage, different pixels are determined to use different mass-to-charge ratio windows for wide window fragmentation, which can obtain mass spectrum information more specifically, help improve the accuracy and comprehensiveness of molecular annotation, and better adapt to the analysis needs of different molecules in complex biological samples, thereby providing a better quality and richer data foundation for subsequent mass spectrometry imaging data processing, structural annotation, and multi-target imaging.

[0019] Optionally, in one embodiment of the present application, the first data processing module includes: a division unit, used to divide the parent ion and the fragment ion based on the mass-to-charge ratio of the parent ion being greater than the mass-to-charge ratio of the fragment ion, wherein the mass-to-charge ratio of the parent ion is limited to a preset wide window range.

[0020] Through the above technical solution, the embodiment of the present application can be based on the reasonable division of the mass-to-charge ratio of the parent ion and the fragment ion, that is, the mass-to-charge ratio of the parent ion is greater than that of the fragment ion and is limited to a preset wide window range, effectively distinguishing the two, providing a basis for subsequent accurate analysis, and helping to more accurately identify and track ion information during data processing, and improve the accuracy of mass spectrometry data analysis. Limiting the parent ion within a wide window range can ensure that enough parent ion information is obtained while avoiding interference from too many irrelevant ions, improving the pertinence and effectiveness of data acquisition, and thus optimizing the entire non-targeted tandem mass spectrometry imaging process.

[0021] Optionally, in one embodiment of the present application, the first calculation module includes: a first solving unit, used to solve a first preset optimization problem using the first intensity matrix to obtain the secondary mass spectrum.

[0022] Through the above-mentioned technical scheme, the embodiment of the present application can effectively integrate the rich information in the first intensity matrix, and convert the relationship between the parent ion and the fragment ion in terms of mass-to-charge ratio and spatial position into a clear secondary mass spectrum through optimization calculation, thereby improving the utilization and interpretability of the data. The process of solving the optimization problem can realize the intelligent processing of complex mass spectrometry data, avoid the subjectivity and limitations of manual analysis, and enhance the objectivity and accuracy of the results.

[0023] Optionally, in one embodiment of the present application, the second calculation unit includes: a second solving unit, used to solve a second preset optimization problem using the second intensity matrix to obtain the relative ion intensity.

[0024] Through the above technical solution, the embodiment of the present application can accurately determine the relative ion intensity of characteristic fragments generated by each parent ion in each pixel, providing key quantitative data support for multi-target mass spectrometry imaging. At the same time, it helps to gain a deeper understanding of the distribution and metabolism of molecules in biological tissues, plays an important role in biomedical research, disease diagnosis and other fields, and improves the ability and level of non-targeted tandem mass spectrometry imaging technology to analyze complex biological samples.

[0025] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the non-targeted tandem mass spectrometry imaging method as described in the above embodiment.

[0026] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned non-targeted tandem mass spectrometry imaging method.

[0027] The fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, is used to implement the above non-targeted tandem mass spectrometry imaging method.

[0028] The present application embodiment can fully mine mass spectrometry data by obtaining the secondary mass spectrogram of each pixel and a series of processing, wherein the first intensity matrix obtained by spectral peak identification and peak extraction is the foundation for subsequent analysis, the first-order deconvolution realizes preliminary structural annotation, and the relative ion intensity calculated by the second-order deconvolution in combination with the adjacent pixel information can accurately analyze the parent ion in each pixel, and finally generate multi-target mass spectrometry imaging results, realizing including but not limited to large-scale lipid and metabolite structural annotation and spatial omics analysis, and without the need for specific functional modules, reducing the instrument hardware requirements and improving the sample ion utilization rate and imaging flux. At the same time, the secondary mass spectrogram is obtained in a specific data-independent mode, the ion utilization rate and data acquisition flux are improved, and the mass-to-charge ratio windows of different pixels are determined according to the molecular annotation target, so as to improve the accuracy and comprehensiveness of molecular annotation and adapt to the needs of complex sample analysis. In addition, based on the reasonable division of mass-to-charge ratio and the wide window limiting parent ion, the imaging process is optimized, and the optimization problem is solved by using the intensity matrix, which not only improves the data utilization rate and interpretability, but also enhances the objectivity and accuracy of the results, and can also provide quantitative support for multi-target imaging, help to deeply understand the molecular situation of biological tissues, and improve the analysis ability and level of technology for complex samples.

[0029] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0031] Figure 1 A flowchart of a non-targeted tandem mass spectrometry imaging method provided according to an embodiment of the present application;

[0032] Figure 2 A schematic diagram of the data collection principle according to an embodiment of the present application;

[0033] Figure 3 Schematic diagram of the principle of first-order deconvolution according to an embodiment of the present application;

[0034] Figure 4 It is a schematic diagram of the result of first-order deconvolution according to a specific embodiment of the present application;

[0035] Figure 5 A comparison diagram of the first-order deconvolution result and the in-situ targeted tandem mass spectrometry analysis result according to a specific embodiment of the present application;

[0036] Figure 6 It is a schematic diagram of the principle of second-order deconvolution according to a specific embodiment of the present application;

[0037] Figure 7This is a comparison result diagram of a second-order deconvolution mass spectrometry imaging diagram and an in-situ targeted tandem mass spectrometry diagram according to a specific embodiment of the present application;

[0038] Figure 8 A schematic diagram of second-order deconvolution mass spectrometry imaging of multiple groups of different lipid precursor ions according to a specific embodiment of the present application;

[0039] Fig. 9 A schematic diagram of the structure of a non-targeted tandem mass spectrometry imaging device provided according to an embodiment of the present application;

[0040] Fig.10 The figure is a structural example diagram of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0041] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0042] The following is a description of the non-targeted tandem mass spectrometry imaging method and device of the embodiment of the present application with reference to the accompanying drawings. In view of the related technologies mentioned in the above background technology, mass spectrometry imaging cannot be used in conjunction with chromatographic separation technology as a whole, resulting in limited analysis dimensions and increased difficulty in data analysis; data independent acquisition and spectrum deconvolution rely on molecular composition modulation technology, resulting in increased instrument complexity and cost, limited application scenarios, and problems affecting stability and ease of use. The present application provides a non-targeted tandem mass spectrometry imaging method, in which the mass spectrometry data information can be fully mined by obtaining the secondary mass spectrogram of each pixel and a series of subsequent processing. The first intensity matrix obtained by peak recognition and peak extraction lays the foundation for subsequent analysis, and the parent ion secondary mass spectrogram and corresponding relationship obtained by the first-order deconvolution realize preliminary structural annotation. The second intensity matrix and the second-order deconvolution are combined with the adjacent pixel information to calculate the relative ion intensity, accurately analyze the parent ion situation in each pixel, and finally generate multi-target mass spectrometry imaging results, including but not limited to large-scale lipid and metabolite structure annotation and spatial omics analysis, and no functional modules such as ion mobility separation are required, which reduces the hardware requirements for mass spectrometry instruments and improves sample ion utilization and imaging flux. This solves the problem in related technologies that mass spectrometry imaging cannot be combined with chromatographic separation technology in general, which limits the analysis dimension and increases the difficulty of data analysis; data-independent acquisition and spectrum deconvolution rely on molecular composition modulation technology, which increases instrument complexity and cost, limits application scenarios, and affects stability and ease of use.

[0043] Specifically, Figure 1A schematic diagram of a process of a non-targeted tandem mass spectrometry imaging method provided in an embodiment of the present application.

[0044] like Figure 1 As shown, the non-targeted tandem mass spectrometry imaging method comprises the following steps:

[0045] In step S101, a secondary mass spectrum of each pixel is obtained.

[0046] It is understandable that the sample ionization adopts a soft ionization source, which can be selected from a variety of soft ionization sources. For example, in the embodiment of the present application, collision induced dissociation technology can be used to excite ions using a fixed excitation energy. In actual operation, technicians can also select other ion fragmentation technologies including but not limited to ultraviolet dissociation, surface induced dissociation, electron capture induced dissociation, electron transfer induced dissociation, etc. according to specific needs to achieve ion excitation, and are not limited to these technologies, and can be flexibly selected according to actual conditions.

[0047] Optionally, in one embodiment of the present application, obtaining a secondary mass spectrum for each pixel point includes: obtaining a secondary mass spectrum for each pixel point in a data-independent mode of wide window full fragmentation, wherein different pixels are determined based on target coverage of molecular annotations to implement wide window fragmentation with different mass-to-charge ratio windows.

[0048] Specifically, the secondary mass spectra of each pixel are obtained in a data-independent mode of wide window full fragmentation. According to the target coverage of molecular annotation, different pixels are selected to implement wide window fragmentation with different mass-to-charge ratio windows. The wide mass-to-charge ratio window range is adjustable. All ions in the wide mass-to-charge ratio window of each pixel are simultaneously fragmented and tandem mass spectrometry data is collected. When ionizing the compounds on the sample surface, there is no restriction on the spatial resolution, and it can be adapted to the spatial resolution range that can be achieved by the selected ionization method to ensure that data can be effectively acquired under different spatial resolution conditions to meet the needs of different application scenarios.

[0049] Further, after obtaining each pixel cascade mass spectrogram, the raw data file is converted into the data file of .mzML format by open source software MSConvert (Mass Spectrometry Convert, a tool in ProteoWizard software package, mainly used for format conversion of mass spectrum data file).It should be noted that, although the mass spectrum data formats collected by different manufacturers' instruments are different, the analysis method of the present application embodiment is not limited thereto.Then, the data file of .mzML format is processed using Python's open source library pymzml (Python mzML module, a Python library for processing .mzML format mass spectrum data file), which is converted into the data file of .npy format, the data file of the .npy format contains the cascade mass analysis data of the full fragmentation of each pixel wide window, so that further processing and analysis are performed subsequently.

[0050] In the actual execution process, pixels are clustered according to the initial data, and a variety of clustering algorithms can be used. For example, the embodiment of the present application adopts the KNN (K-Nearest Neighbors) algorithm. In specific operations, clustering algorithms including but not limited to K-means (K-means clustering algorithm), DBSCAN (Density-Based Spatial Clustering of Applications with Noise), GMM (Gaussian Mixture Model) and SOM (Self-Organizing Map) can also be selected to directly cluster pixels, or UMAP (Uniform Manifold Approximation and Projection), t-SNE (t-Distributed Stochastic Neighbor Embedding) and other dimensionality reduction algorithms can be used to indirectly cluster pixels. According to the clustering results, each category corresponds to an average mass spectrum.

[0051] The embodiment of the present application can use a soft ionization source for ionization with flexible technology selection. A variety of ion fragmentation technologies can be selected according to actual needs, without being limited to specific technologies, and can adapt to different experimental conditions and research needs, effectively exciting ions to obtain mass spectra; the mass spectrum is obtained in a data-independent mode of wide window full fragmentation, and different mass-to-charge ratio windows are selected based on the molecular annotation target coverage, which can improve the comprehensiveness of the molecular annotation. At the same time, the window range is adjustable, which increases the flexibility of the method; there are no strict restrictions on the spatial resolution, and it is adapted to the resolution range of different ionization methods. Effective data can be obtained under various spatial resolution conditions, broadening the application scenarios; during the data format conversion process, data in different manufacturers' formats can be processed and converted into a specific format through open source software, which is convenient for subsequent analysis, and the clustering algorithms are diverse. A variety of classic clustering algorithms can be used directly, and indirect clustering can be performed through a dimensionality reduction algorithm. The most appropriate method can be selected according to the actual situation, so that an average mass spectrum is obtained according to the clustering results, laying the foundation for subsequent precise analysis.

[0052] In step S102, peak identification and peak extraction are performed based on the secondary mass spectrum to obtain a first intensity matrix of parent ions and fragment ions in terms of mass-to-charge ratio and spatial position.

[0053] It is understandable that the intensity matrices of the parent ion and fragment ion in terms of mass-to-charge ratio and spatial position are obtained from the secondary mass spectrometry data, without the need for primary mass spectrometry acquisition. This data acquisition method is based on specific technical principles and can effectively utilize the information contained in the secondary mass spectrometry data, reduce unnecessary data acquisition processes, improve data acquisition efficiency, and also provide a data basis for subsequent analysis and processing.

[0054] Optionally, in one embodiment of the present application, before obtaining the first intensity matrix of the parent ion and the fragment ions in the mass-to-charge ratio and spatial position dimensions, it also includes: dividing the parent ion and the fragment ions based on the mass-to-charge ratio of the parent ion being greater than the mass-to-charge ratio of the fragment ions, wherein the mass-to-charge ratio of the parent ion is limited to a preset wide window range.

[0055] Specifically, the intensity matrix of the parent ion and fragment ion in the mass-to-charge ratio and spatial position dimensions is dynamically acquired, and its division is based on the fact that the mass-to-charge ratio of the parent ion is greater than the mass-to-charge ratio of the fragment ion, and the mass-to-charge ratio of the parent ion is limited to a set wide window range. For example, in actual operation, if the mass-to-charge ratio window is set to m / z750-m / z900 (only for example, can be adjusted according to specific needs), then in the data sorting process, the parent ion and fragment ion will be accurately distinguished based on this window range and the mass-to-charge ratio relationship, ensuring the accuracy and validity of the data in the intensity matrix, and providing a reasonable data classification basis for subsequent peak identification and peak extraction.

[0056] Further, according to the clustering result of step S101, the peak extraction operation is performed in each category, and a peak list is extracted from each category and summarized. Then, the raw data is binned according to the list and the maximum width of ±0.02 Dalton, and the data is reasonably divided to more accurately obtain the intensity information of the parent ion and fragment ion in the spatial position and mass-to-charge ratio dimensions, and finally the intensity matrix is ​​obtained, such as Figure 2 As shown in the figure, with a fixed isotope distribution ratio and a determination tolerance of ±0.005 Dalton, the direct subtraction method is used to preliminarily eliminate the influence of isotope distribution, which can reduce the interference of isotope distribution on the measurement of parent ion and fragment ion intensity, so that the obtained intensity matrix can more accurately reflect the actual ion situation.

[0057] The embodiments of the present application can obtain an intensity matrix from secondary mass spectrometry data, avoid primary mass spectrometry acquisition, simplify the process, improve efficiency and lay a data foundation for subsequent analysis; divide the parent ion and fragment ion mass-to-charge ratio relationship and the preset wide window range to ensure the accuracy and effectiveness of the intensity matrix data, and provide a reasonable classification basis for spectral peak identification, etc.; perform peak extraction and binning operations based on the clustering results, and by aggregating the peak list and binning according to a specific width, the intensity information of the ions in the spatial and mass-to-charge ratio dimensions can be accurately obtained, which is helpful to construct a high-quality intensity matrix; use a fixed isotope distribution ratio and determination tolerance to directly subtract to eliminate isotope effects, reduce interference, make the intensity matrix more accurately reflect the actual ion situation, and improve the overall data quality and analysis reliability.

[0058] In step S103, a first-order deconvolution calculation is performed on the first intensity matrix to obtain secondary mass spectra of multiple parent ions and obtain the corresponding relationship between the parent ions and the fragment ions.

[0059] It is important for those skilled in the art to understand that in the first-order deconvolution, it is assumed that in the same tandem mass spectrometry analysis, the quantitative relationship between the parent ion and the corresponding fragment ion remains unchanged, and this quantitative relationship is independent of the parent ion intensity. This assumption provides a theoretical basis for subsequent calculations based on mathematical models, which simplifies the complex ion interaction relationship when processing data and focuses on solving the relationship between the parent ion and the fragment ion using the intensity matrix.

[0060] Optionally, in one embodiment of the present application, a first-order deconvolution calculation is performed on the first intensity matrix, including: using the first intensity matrix to solve a first preset optimization problem to obtain a secondary mass spectrum.

[0061] In the actual implementation process, the first-order deconvolution calculation of the parent ion and fragment ion intensity matrix corresponding to the selected pixel point data is performed based on the elastic regression network algorithm, such as Figure 3As shown. This algorithm has unique advantages in processing such data and can effectively assign fragment ions to the cascade spectra of the parent ions to which they belong. In the specific calculation process, the data in the intensity matrix is ​​input into the elastic regression network algorithm model, and the accurate assignment of fragment ions is gradually achieved through the calculation and iteration of the model. The secondary mass spectra of each parent ion are obtained through first-order deconvolution calculation. These secondary mass spectra are the key basis for further analysis of the structure of the parent ions. Then, according to the pre-set annotation rules, the obtained secondary mass spectra are used to realize the structural annotation of the parent ions. The annotation rules may include but are not limited to determining the structural characteristics of the parent ions through comparison and analysis based on known mass spectral characteristics, ion fragmentation patterns and other information.

[0062] Furthermore, according to the annotation results, the correspondence between the parent ion and the fragment ion is obtained. It should be noted that this correspondence mainly covers the qualitative information of the molecular structure, but does not include quantitative information. It provides basic data at the structural level for subsequent quantitative analysis and helps to understand the relationship between the parent ion and the fragment ion at the molecular structure level.

[0063] The following describes step S103 in detail with reference to a specific embodiment.

[0064] In some embodiments, assuming that under consistent tandem mass spectrometry conditions, the theoretical tandem mass spectrometer generated by the parent ion with a signal intensity of 1 unit remains unchanged, the portion of the tandem mass spectrometry data containing only fragment ions is recorded as a vector When the precursor ion signal p i When the intensity is p, there is a corresponding phase There is the following equation:

[0065]

[0066] in, It is the fragment ion part of the tandem mass spectrum collected in the actual experimental process, and L is the channel number of the fragment ion.

[0067] In particular, since the embodiment of the present application adopts a data-independent mode of wide window full fragmentation, several different parent ions in the window will be fragmented simultaneously, and the collected tandem mass spectrometry data is a tandem mass spectrogram of multiple parent ions. The weighted sum of (M is the number of parent ion channels) has the following equation:

[0068]

[0069] Among them, the matrix Denoted as a matrix In this embodiment, the matrix C is the variable to be solved. After solving, the parent ions can be annotated. In view of the distribution of certain parent ions in specific areas, the pixel selection strategy of this embodiment is intended to ensure the representativeness of each area. Specifically, an equal number of pixels are randomly selected from each category of pixels. The solvability depends on whether the rank of the matrix P is greater than M. Therefore, at least M pixels of data are required to determine the matrix C. In view of the fact that there may be some randomly selected pixels that show low heterogeneity in lipid composition, this embodiment selects N pixels (where N>M) to maintain basic solvability conditions, in Represented as a matrix Therefore, the following relationship holds:

[0070] P×C=F,

[0071] Among them, the matrix Represents the intensity information of the fragment ions in the spatial position (N pixels) and mass-to-charge ratio dimensions.

[0072] It should be noted that in this embodiment, only the tandem mass spectrometry data after ion excitation is collected, and the primary mass spectrometry data is not collected, so the parent ion intensity before fragmentation cannot be directly obtained. In this example, the parent ion intensity after fragmentation is used to replace the parent ion intensity before fragmentation, which does not affect the final solution. The first-order deconvolution is ultimately transformed into a solution to this problem:

[0073]

[0074] After obtaining the approximate solution of matrix C, the coefficient matrix of fragment ions generated by parent ions can be obtained: It should be noted that, during the specific implementation process, those skilled in the art may also solve the optimization problem by methods including but not limited to non-negative least squares method, Lasso regression, etc., without specific limitation.

[0075] In this embodiment, the matrix C is solved column by column, and the matrix P changes dynamically accordingly. When solving the Kth column of the matrix C, the corresponding mass-to-charge ratio is m / z k fragment ions. The mass-to-charge ratio of the parent ion must be greater than the mass-to-charge ratio of the fragment ion, and the mass-to-charge ratio of the parent ion must fall within the set wide mass-to-charge ratio window. For example, the mass-to-charge ratio window adopted in this embodiment is m / z750-m / z900, and the data that does not meet the conditions in the mass-to-charge ratio dimension is temporarily set to zero. It should be noted that this embodiment does not limit the range of the mass-to-charge ratio window. The data deconvolution method in this embodiment does not need to rely on a database, and has the characteristics of being fast, simple, automated and accurate.

[0076] The embodiments of the present application can simplify complex ion interaction relationships based on reasonable assumptions, focus on using the intensity matrix to solve the relationship between the parent ion and the fragment ion, provide a solid theoretical basis for the calculation, and make the calculation process more targeted and feasible; by using the first intensity matrix to solve the preset optimization problem, the secondary mass spectra of multiple parent ions can be effectively obtained, providing a key basis for in-depth analysis of the parent ion structure; the elastic regression network algorithm is used for calculation to ensure that the fragment ions are accurately assigned to the cascade spectrum of the parent ion to which they belong, and accurate assignment is achieved through calculation and iteration of the model during specific calculations; according to annotation rules such as known mass spectral characteristics and ion fragment patterns, the parent ion can be structurally annotated to determine its structural characteristics. The corresponding relationship between the parent ion and the fragment ion finally obtained does not involve quantitative information, but provides important basic data at the structural level for subsequent quantitative analysis, which helps to fully understand the relationship between the two in molecular structure.

[0077] In step S104, based on the acquired correspondence between the parent ions and the fragment ions and combined with the molecular composition information of the adjacent pixels, a second intensity matrix of the fragment ions and the corresponding parent ions in the dimensions of mass-to-charge ratio and spatial position is assigned to each tissue.

[0078] It is understandable that the introduction of molecular composition information of adjacent pixels is crucial. Since tissues have certain continuity and correlation in space, the molecular composition of adjacent pixels can provide supplement and reference for the analysis of target tissues. By collecting and integrating the molecular composition information of adjacent pixels, a more comprehensive molecular distribution can be obtained, thereby better understanding the position and characteristics of the target tissue in the overall environment.

[0079] In the actual implementation process, the corresponding relationship between the parent ion and the fragment ion and the adjacent pixel molecules are combined to give each tissue a second intensity matrix of the fragment ion and the corresponding parent ion in the mass-to-charge ratio and spatial position dimensions. For each tissue, the intensity information of its fragment ions and corresponding parent ions will be reorganized and reconstructed in the two important dimensions of mass-to-charge ratio and spatial position. In the mass-to-charge ratio dimension, it can accurately reflect the intensity distribution of ions with different mass-to-charge ratios, thereby providing a basis for identifying and distinguishing different types of ions; in the spatial position dimension, it can clearly show the distribution position and distribution pattern of ions in the tissue, which helps to reveal the spatial heterogeneity of molecules in the tissue, and provides a solid data foundation for further analysis such as subsequent second-order deconvolution calculations and multi-target mass spectrometry imaging.

[0080] In step S105, a second-order deconvolution calculation is performed on the second intensity matrix to obtain the relative ion intensity of the characteristic fragments generated by each parent ion in each pixel, and generate a multi-target mass spectrometry imaging result.

[0081] It is important for those skilled in the art to understand that the second-order deconvolution is based on two important assumptions. First, in the same tandem mass spectrometry analysis, the quantitative relationship between the parent ion and the corresponding fragment ion remains constant, which provides the basic premise for the subsequent calculation of the quantitative relationship based on the mathematical model; second, it is assumed that the ratio of isomers / isobars of adjacent pixels is consistent in space. This assumption makes it possible to use the information of adjacent pixels to infer the situation of the target pixel, thereby providing the possibility of obtaining a more accurate quantitative relationship.

[0082] In the actual implementation process, based on the correspondence between the parent ion and the fragment ion obtained by the first-order deconvolution in step S104, and based on the intensity information of the fragment ions and the corresponding parent ions at the target pixel points and nearby pixel points (such as using a 2x2 pixel grid to cover the target pixel, and the grid size can be adjusted according to the number of parent ions corresponding to the fragment ions), these intensity information comes from the second intensity matrix constructed previously. The combination of these data provides a sufficient data basis for the second-order deconvolution calculation.

[0083] Optionally, in one embodiment of the present application, a second-order deconvolution calculation is performed on the second intensity matrix, including: using the second intensity matrix to solve a second preset optimization problem to obtain relative ion intensity.

[0084] Specifically, according to the above data, it is substituted into the preset optimization problem for second-order deconvolution calculation. Specifically, through a specific mathematical model and algorithm (such as including but not limited to optimization methods based on minimizing specific functions, the specific optimization method is not limited), the quantitative relationship between the target pixel parent ion and the fragment ion is solved, so as to obtain the relative ion intensity of the characteristic fragments generated by each parent ion in each pixel.

[0085] Furthermore, based on the second-order deconvolution results, the proportional relationship between isomers / isobars is obtained, and these results are used to reconstruct the spatial distribution of isomers / isobars. By spatially integrating and visualizing the quantitative information and isomer / isobar ratio information within each pixel, multi-target mass spectrometry imaging is ultimately achieved, generating multi-target mass spectrometry imaging results with rich information, which can clearly display information such as the spatial distribution and relative content of different parent ions and their characteristic fragments in biological tissues.

[0086] The following is a specific example to illustrate step S105 in detail.

[0087] Specifically, this example obtained a tandem mass spectrum of 175 parent ions on a single frozen section of mouse cerebellum by first-order deconvolution. Figure 4As shown in Figure 2, the secondary mass spectra obtained by deconvolution of non-targeted tandem mass spectrometry are highly similar to those obtained by targeted tandem mass spectrometry. It should be noted that the isolation window of targeted tandem mass spectrometry is often set to ±0.5 Daltons, such as Figure 5 As shown, the interfering parent ion and the target parent ion are fragmented simultaneously, and the embodiments of the present application can avoid such interference.

[0088] In this embodiment, there is no additional analysis method, which helps to reduce the loss of ions. The data-independent acquisition mode is relatively friendly to low-abundance ions, such as Figure 5 As shown, the relative signal intensity is as low as 0.12%, and the corresponding cascade spectrum can also be solved in this embodiment.

[0089] Furthermore, the second-order spectrum deconvolution is performed. The principle of the second-order deconvolution is as follows Figure 6 As shown. After the first stage of deconvolution, the annotation column labels are obtained, and the relationship between the parent ion and its corresponding fragment ion is established. It should be noted that in order to achieve the quantitative relationship between the parent ion and the fragment ion of the target pixel, it is necessary to use the molecular composition and intensity information of the pixel points adjacent to the target pixel point. In this embodiment, since most of the fragment ions come from at most 4 different parent ions, a 2x2 pixel grid (covering the target pixel) is used in this embodiment, and the intensity information of the fragment ion of a single pixel point in the grid and its corresponding parent ion can be expressed as:

[0090]

[0091] in, is the total ion intensity of the i-th parent ion of the j-th fragment ion and all isomers / isobars of the parent ion, which can be directly obtained in the embodiment; α i is the ionic strength p of the i-th parent ion i and The ratio of the i-th parent ion to the j-th fragment ion it produces is c i The product of:

[0092]

[0093] Among them, c i is the intensity ratio of the parent ion and the fragment ion generated by it. In this embodiment, it is assumed that the pixel grid is 2x2. The ratio remains unchanged, that is, the ratio between isomers / isomers of the same weight remains unchanged, so α i Can replace c i Reflects quantitative relationships.

[0094] Furthermore, in this embodiment, a 2x2 pixel grid (covering the target pixel) is used. The intensity information of the fragment ions and their corresponding parent ions at all pixel points in the grid can be expressed as (where k is the number of parent ions that can produce the fragment), the second-order deconvolution solves the following equation:

[0095]

[0096] So we get the vector It should be noted that this embodiment does not limit the optimization method for solving this problem.

[0097] In this embodiment, the pixel grid is slid with a step size of 1 to gradually solve the vector of each target pixel point. like Figure 6 shown.

[0098] It should be noted that the size of the pixel grid in this embodiment is determined by the number of parent ions corresponding to the fragment ions. If the number of parent ions is greater than 4, a 3x3 pixel grid is used, and so on.

[0099] Furthermore, the spatial distribution of each parent ion is reconstructed, and this embodiment can realize the spatial visualization of isobars and isomers. Figure 7 As shown in FIG. 1 , this example visualizes the spatial distribution of a pair of isobars / isomers and finds that they are quite different and highly consistent with the results obtained by in situ targeted tandem mass spectrometry imaging. Figure 8 As shown, this example visualizes the spatial distribution of six pairs of isobars / isomers.

[0100] The embodiment of the present application can be based on two reasonable assumptions to lay the foundation for calculating the quantitative relationship, effectively use the information of adjacent pixels to infer the target pixel situation, and improve the accuracy of the quantitative relationship. During the execution process, the corresponding relationship obtained by the first-order deconvolution and the intensity information of the target and nearby pixels are fully integrated to provide solid data support for the second-order deconvolution. By solving the second preset optimization problem, the relative ion intensity of the characteristic fragments generated by the parent ion in each pixel can be accurately obtained, and then the proportional relationship between isomers / isoheavy objects can be obtained.

[0101] According to the non-targeted tandem mass spectrometry imaging method proposed in the embodiment of the present application, tandem mass spectrometry data in a non-data-dependent mode can be obtained, and the intensity matrix of the parent ion and fragment ion in the mass-to-charge ratio and spatial position dimensions can be obtained; the intensity information of the parent ion and fragment ion of multiple pixels is first-order deconvolved to obtain the corresponding relationship between the parent ion and the fragment ion, and the automatic annotation of the molecular structure in the mass spectrometry imaging data is realized; the intensity information of the fragment ion and the corresponding parent ion of the target pixel and its neighboring pixels is second-order deconvolved to obtain the quantitative relationship between the parent ion and the fragment ion, and the non-targeted tandem mass spectrometry imaging is realized, which simplifies the process of mass spectrometry imaging, does not require the assistance of other gas phase separation technologies, can automatically annotate mass spectrometry imaging data, and reduces the hardware requirements for mass spectrometry imaging instruments. At the same time, mass spectrometry imaging of multiple target ions is realized, which improves the utilization rate of analysis samples and mass spectrometry imaging flux.

[0102] Next, the non-targeted tandem mass spectrometry imaging device proposed according to the embodiment of the present application is described with reference to the accompanying drawings.

[0103] Fig. 9 It is a block diagram of a non-targeted tandem mass spectrometry imaging device according to an embodiment of the present application.

[0104] like Fig. 9 As shown, the non-targeted tandem mass spectrometry imaging device 10 includes: an acquisition module 100 , a first data processing module 200 , a first calculation module 300 , a second data processing module 400 and a second calculation module 500 .

[0105] The acquisition module 100 is used to acquire the secondary mass spectrum of each pixel point.

[0106] The first data processing module 200 is used to perform peak recognition and peak extraction according to the secondary mass spectrum to obtain a first intensity matrix of parent ions and fragment ions in terms of mass-to-charge ratio and spatial position.

[0107] The first calculation module 300 is used to perform a first-order deconvolution calculation on the first intensity matrix to obtain secondary mass spectra of multiple parent ions and obtain the corresponding relationship between the parent ions and the fragment ions.

[0108] The second data processing module 400 is used to assign a second intensity matrix of fragment ions and corresponding parent ions in the dimensions of mass-to-charge ratio and spatial position to each tissue based on the acquired correspondence between parent ions and fragment ions and combined with the molecular composition information of adjacent pixels.

[0109] The second calculation module 500 is used to perform a second-order deconvolution calculation on the second intensity matrix to obtain the relative ion intensity of the characteristic fragments generated by each parent ion in each pixel, and generate a multi-target mass spectrometry imaging result.

[0110] Optionally, in one embodiment of the present application, the acquisition module 100 includes: acquiring a secondary mass spectrum of each pixel point in a data-independent mode of wide window full fragmentation, wherein different pixel points are determined based on the target coverage of the molecular annotation to implement wide window fragmentation with different mass-to-charge ratio windows.

[0111] Optionally, in one embodiment of the present application, the first data processing module 200 includes: a division unit for dividing parent ions and fragment ions based on the mass-to-charge ratio of the parent ions being greater than the mass-to-charge ratio of the fragment ions, wherein the mass-to-charge ratio of the parent ions is limited to a preset wide window range.

[0112] Optionally, in one embodiment of the present application, the first calculation module 300 includes: a first solving unit, used to solve a first preset optimization problem using a first intensity matrix to obtain a secondary mass spectrum.

[0113] Optionally, in one embodiment of the present application, the second calculation unit 500 includes: a second solving unit, used to solve a second preset optimization problem using a second intensity matrix to obtain a relative ion intensity.

[0114] It should be noted that the aforementioned explanation of the embodiment of the non-targeted tandem mass spectrometry imaging method is also applicable to the non-targeted tandem mass spectrometry imaging device of this embodiment, and will not be repeated here.

[0115] According to the non-targeted tandem mass spectrometry imaging device proposed in the embodiment of the present application, tandem mass spectrometry data in a non-data-dependent mode can be obtained, and the intensity matrix of the parent ion and the fragment ion in the mass-to-charge ratio and spatial position dimensions can be obtained; the intensity information of the parent ion and the fragment ion of multiple pixels is first-order deconvolved to obtain the corresponding relationship between the parent ion and the fragment ion, and the automatic annotation of the molecular structure in the mass spectrometry imaging data is realized; the intensity information of the fragment ion and the corresponding parent ion of the target pixel and its neighboring pixels is second-order deconvolved to obtain the quantitative relationship between the parent ion and the fragment ion, and the non-targeted tandem mass spectrometry imaging is realized, which simplifies the process of mass spectrometry imaging, does not require the assistance of other gas phase separation technologies, can automatically annotate the mass spectrometry imaging data, and reduces the hardware requirements for the mass spectrometry imaging instrument. At the same time, the mass spectrometry imaging of multiple target ions is realized, and the utilization rate of the analysis samples and the mass spectrometry imaging flux are improved.

[0116] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0117] A memory 1001 , a processor 1002 , and a computer program stored in the memory 1001 and executable on the processor 1002 .

[0118] When the processor 1002 executes the program, the non-targeted tandem mass spectrometry imaging method provided in the above embodiment is implemented.

[0119] Furthermore, the electronic device further comprises:

[0120] The communication interface 1003 is used for communication between the memory 1001 and the processor 1002 .

[0121] The memory 1001 is used to store computer programs that can be executed on the processor 1002 .

[0122] The memory 1001 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0123] If the memory 1001, the processor 1002 and the communication interface 1003 are implemented independently, the communication interface 1003, the memory 1001 and the processor 1002 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.10 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0124] Optionally, in a specific implementation, if the memory 1001, the processor 1002 and the communication interface 1003 are integrated on a chip, the memory 1001, the processor 1002 and the communication interface 1003 can communicate with each other through an internal interface.

[0125] The processor 1002 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0126] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned non-targeted tandem mass spectrometry imaging method.

[0127] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed, is used to implement the above non-targeted tandem mass spectrometry imaging method.

[0128] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0129] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0130] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0131] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0132] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of multiple of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0133] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0134] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0135] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A non-targeted tandem mass spectrometry imaging method, characterized in that: The following steps are involved: Obtain the secondary mass spectrum of each pixel; Performing peak identification and peak extraction according to the secondary mass spectrum to obtain a first intensity matrix of parent ions and fragment ions in terms of mass-to-charge ratio and spatial position; Performing a first-order deconvolution calculation on the first intensity matrix to obtain secondary mass spectra of multiple parent ions and obtain a corresponding relationship between parent ions and fragment ions; Based on the obtained correspondence between the parent ions and the fragment ions, combined with the molecular composition information of adjacent pixels, each tissue is given a second intensity matrix of the fragment ions and the corresponding parent ions in the dimensions of mass-to-charge ratio and spatial position; A second-order deconvolution calculation is performed on the second intensity matrix to obtain the relative ion intensity of characteristic fragments generated by each parent ion in each pixel, thereby generating a multi-target mass spectrometry imaging result.

2. The method according to claim 1, characterized in that The step of obtaining a secondary mass spectrum of each pixel point includes: The secondary mass spectrum of each pixel point is obtained in a data-independent mode of wide window full fragmentation, wherein different pixel points are determined to be subjected to wide window fragmentation with different mass-to-charge ratio windows based on the target coverage of the molecular annotation.

3. The method according to claim 1, characterized in that Before obtaining the first intensity matrix of the parent ion and the fragment ion in terms of mass-to-charge ratio and spatial position, the method further comprises: The parent ions and the fragment ions are divided based on the fact that the mass-to-charge ratio of the parent ions is greater than the mass-to-charge ratio of the fragment ions, wherein the mass-to-charge ratio of the parent ions is limited within a preset wide window range.

4. The method according to claim 1, characterized in that: The performing a first-order deconvolution calculation on the first intensity matrix includes: The first intensity matrix is ​​used to solve a first preset optimization problem to obtain the secondary mass spectrum.

5. The method according to claim 1, characterized in that The performing a second-order deconvolution calculation on the second intensity matrix comprises: The second intensity matrix is ​​used to solve a second preset optimization problem to obtain the relative ion intensity.

6. A non-targeted tandem mass spectrometry imaging device, characterized in that: include: An acquisition module, used to obtain a secondary mass spectrum of each pixel; A first data processing module is used to perform peak identification and peak extraction according to the secondary mass spectrum to obtain a first intensity matrix of parent ions and fragment ions in terms of mass-to-charge ratio and spatial position; A first calculation module, used for performing a first-order deconvolution calculation on the first intensity matrix to obtain secondary mass spectra of multiple parent ions and obtain a corresponding relationship between parent ions and fragment ions; A second data processing module is used to assign a second intensity matrix of fragment ions and corresponding parent ions in the dimensions of mass-to-charge ratio and spatial position to each tissue based on the correspondence between the acquired parent ions and fragment ions and in combination with the molecular composition information of adjacent pixels; The second calculation module is used to perform a second-order deconvolution calculation on the second intensity matrix to obtain the relative ion intensity of the characteristic fragments generated by each parent ion in each pixel and generate a multi-target mass spectrometry imaging result.

7. The device according to claim 6, characterized in that The acquisition module comprises: The secondary mass spectrum of each pixel point is obtained in a data-independent mode of wide window full fragmentation, wherein different pixel points are determined to be subjected to wide window fragmentation with different mass-to-charge ratio windows based on the target coverage of the molecular annotation.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the non-targeted tandem mass spectrometry imaging method according to any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the non-targeted tandem mass spectrometry imaging method as described in any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that The computer program is executed to implement the non-targeted tandem mass spectrometry imaging method according to any one of claims 1 to 5.

Images