Mass spectroscopy apparatus and method

Abstract

This invention provides a deisotope treatment applicable to a group of experimentally measured peaks (isotope peaks) that do not have monoisotopic peaks. [Solution] Based on the compositional formula 112 estimated from information within the low mass range and the mass 111 of the selected reference peak, the molecular formula is estimated. Based on the molecular formula, a theoretical peak group (isotope pattern) 116 is generated. By comparing the theoretical peak group 116 with the experimental peak group 98 including the reference peak, the monoisotopic mass is estimated. Then, the monoisotopic peak after deisotope processing is generated.

Description

[Technical Field]

[0001] The present invention relates to a mass spectral processing apparatus and method, and more particularly to deisotoping of mass spectra. [Background technology]

[0002] A mass spectrometry system consists of a mass spectrometer and an information processing unit. The mass spectrometer ionizes the sample, and mass spectrometry is performed on the resulting ions. The information processing unit corresponds to a mass spectrum processing unit. In the information processing unit, a mass spectrum is generated based on the detection signal from the mass spectrometer, and this mass spectrum is processed. Processing of the mass spectrum includes deisotope treatment as a pretreatment.

[0003] For example, a polymer is composed of multiple polymer molecules with different degrees of polymerization. The spectrum of a polymer contains multiple groups of peaks corresponding to multiple polymer molecules. Each group of peaks corresponds to an isotopic pattern and can be called an isotopic peak group.

[0004] Organic compounds are composed of elements such as C, H, O, and N. Each of these elements has multiple atoms with different mass numbers. Multiple atoms with such a relationship are called isotopes. In mass spectra, the isotopic peak group consists of multiple peaks originating from multiple isotopes. In nature, the abundance ratio of isotopes is fixed for each element. In the case of elements that make up organic compounds, the lightest isotope has the greatest abundance.

[0005] When a compound molecule is composed solely of the isotope with the highest abundance, the mass of that compound molecule is called the monoisotopic mass. In an isotopic peak group, the peak corresponding to the monoisotopic mass is called the monoisotopic peak. In isotopic peak groups arising from organic compounds such as polymers, lipids, and proteins, the peak located at the far left is the monoisotopic peak.

[0006] An isotopic peak group consists of a monoisotopic peak and one or more non-monoisotopic peaks (isotopic peaks in the narrow sense). Deisotope processing calculates the isotopic pattern and modifies the distribution of the isotopic peak group based on that pattern. Specifically, in deisotope processing, the intensities of individual non-monoisotopic peaks are added to the intensities of the monoisotopic peaks, and at the same time, the intensities of individual non-monoisotopic peaks are reduced.

[0007] Generally, deisotope is performed sequentially on the m / z axis, with multiple peaks being selected sequentially from the low-mass side to the high-mass side. Conventionally, the selected peaks are considered monoisotopic, and the group of peaks including the selected peaks is deisotope-treated. [Prior art documents] [Patent Documents]

[0008] [Patent Document 1] Japanese Patent Publication No. 2020-094892 [Patent Document 2] Japanese Patent Publication No. 2022-177442 [Patent Document 3] Japanese Patent Publication No. 2024-050094 [Overview of the project] [Problems that the invention aims to solve]

[0009] For example, the mass spectrum of a polymer contains multiple isotopic peak groups corresponding to multiple degrees of polymerization. Generally, the isotopic peak group in the low mass range on the m / z axis contains clearly visible monoisotopic peaks, but the isotopic peak group in the high mass range on the m / z axis does not contain clearly visible monoisotopic peaks. Even if a monoisotopic peak is present in the isotopic peak group, if it is small, the monoisotopic peak will be buried in noise.

[0010] If a group of isotopic peaks does not contain monoisotopic peaks, applying conventional deisotope processing to that group of isotopic peaks will result in incorrect deisotope processing results.

[0011] Patent documents 1 and 2 describe the processing or analysis of isotopic peak groups. However, neither patent documents 1 nor 2 describe deisotope processing in cases where monoisotopic peaks cannot be clearly identified. Patent document 3 describes KMD (Kendrick Mass Defect) analysis.

[0012] The object of the present invention is to provide a deisotope treatment that can be applied to a group of isotopic peaks (a group of experimentally measured peaks) that does not have a monoisotopic peak. [Means for solving the problem]

[0013] The mass spectrum processing apparatus according to the present invention includes a processor that processes a mass spectrum generated by mass spectrometry of a sample, wherein the processor generates a theoretical peak group as an isotopic pattern, estimates the monoisotopic mass corresponding to the measured peak group by comparing the theoretical peak group with the measured peak group in the mass spectrum, and generates a deisotopic peak as the peak corresponding to the monoisotopic mass based on the monoisotopic mass.

[0014] The mass spectrometry processing method according to the present invention is a method for processing a mass spectrum generated by mass spectrometry of a sample in an information processing apparatus, the method including: generating a theoretical peak group as an isotope pattern; estimating a monoisotopic mass corresponding to the measured peak group by comparing the theoretical peak group with the measured peak group in the mass spectrum; and generating a deisotoped monoisotopic peak as a peak corresponding to the monoisotopic mass based on the monoisotopic mass.

Advantages of the Invention

[0015] According to the present invention, it becomes possible to apply appropriate deisotoping processing to an isotope peak group (measured peak group) that does not have a monoisotopic peak.

Brief Description of the Drawings

[0016] [Figure 1] It is a diagram showing a configuration example of a mass spectrometry system according to an embodiment. [Figure 2] It is a diagram showing a configuration example of a high mass range deisotoping processor according to an embodiment. [Figure 3] It is an example of a mass spectrum of a polymer. [Figure 4] It is a diagram showing an example of a peak group included in the first low mass range. [Figure 5] It is a diagram showing an example of a peak group included in the second low mass range. [Figure 6] It is a diagram showing an example of a peak group included in the high mass range. [Figure 7] It is a diagram showing conventional deisotoping processing. [[ID=--34]] [Figure 8] It is a diagram showing deisotoping processing according to an embodiment. <- [Figure 9] It is a diagram showing a first example of deisotoping processing according to an embodiment. [Figure 10] It is an explanatory diagram showing a pattern matching method. [Figure 11]This is a flowchart showing the first embodiment. [Figure 12] This is an explanatory diagram showing the first embodiment. [Figure 13] This figure shows a second embodiment of the deisotope treatment according to the embodiment. [Figure 14] This figure shows the KMD plot before and after deisotope treatment. [Modes for carrying out the invention]

[0017] The embodiments will be described below with reference to the drawings.

[0018] (1) Outline of the Embodiment The mass spectrum processing apparatus according to this embodiment includes a processor that processes the mass spectrum generated by mass spectrometry of a sample. The processor generates a theoretical peak group as an isotopic pattern, estimates the monoisotopic mass corresponding to the experimental peak group by comparing the theoretical peak group with the experimental peak group in the mass spectrum, and generates a deisotope-treated monoisotopic peak as the peak corresponding to the monoisotopic mass based on the monoisotopic mass.

[0019] With the above configuration, even if the measured peak group does not contain monoisotopic peaks (or if the monoisotopic peaks are buried in noise), it is possible to identify the monoisotopic mass and associate the deisotope-processed monoisotopic peak with the monoisotopic mass. Therefore, it is possible to avoid performing incorrect deisotope processing.

[0020] The experimentally measured peak group corresponds to the isotopic pattern, or to a group of peaks that include the isotopic pattern. When comparing the theoretical peak group with the experimentally measured peak group, the entire theoretical peak group may be compared with the entire experimental peak group, or a part of the theoretical peak group (e.g., a specific peak) may be compared with a part of the experimental peak group (e.g., a specific peak). The same deisotope treatment may be applied to both the low-mass range and the high-mass range, or different deisotope treatments may be applied to each mass range.

[0021] In the embodiment, the processor identifies a reference mass based on a reference peak in the mass spectrum and generates a theoretical peak group based on the estimated or specified compositional formula and the reference mass. In the embodiment, the reference peak corresponds to the lightest peak in the experimental peak group. If the experimental peak group does not contain a monoisotopic peak, the lightest peak that is a non-monoisotopic peak becomes the reference peak. The reference mass is the mass corresponding to the reference peak. Here, the mass is precisely in m / z. However, if the charge number is 1, m / z can be considered as the mass. Wherever it is possible to generate a theoretical peak group, a peak other than the lightest peak in the experimental peak group may be used as the reference peak.

[0022] In embodiments, the processor identifies the constituent elemental information of the ion or the major part of the ion corresponding to the reference peak based on the estimated or specified empirical formula and the reference mass, and generates a group of theoretical peaks based on the constituent elemental information. The constituent elemental information includes information identifying multiple elements contained in the ion or its major part, and information identifying the number of atoms for each element. The major part is typically the main chain in a molecule (the part corresponding to repeating units × degree of polymerization). If the mass of the major part is very large, the change in the isotopic pattern due to non-major parts can be ignored. Even if there are some errors in the constituent elemental information, the effect of these errors in the deisotope processing is small. From such a viewpoint, a standard empirical formula may be used instead of the estimated empirical formula.

[0023] In this embodiment, the mass spectrum includes a low-mass range and a higher-mass range. The high-mass range includes the measured peak group. The processor estimates the empirical formula based on the information in the low-mass range. This configuration improves the accuracy of the empirical formula estimation, thereby increasing the accuracy or reliability of the deisotope processing results.

[0024] In this embodiment, the information within the low-mass range includes the measured monoisotopic mass corresponding to the measured monoisotopic peak within the low-mass range. Generally, monoisotopic peaks are easily observed in the low-mass range, while they are difficult to observe in the high-mass range. From this perspective, information within the low-mass range is utilized when performing deisotope processing on the high-mass range.

[0025] In this embodiment, the processor identifies the relative position of the theoretical monoisotopic peak with respect to the theoretical peak group and estimates the monoisotopic mass by applying the relative position to the experimental peak group. This configuration allows for the appropriate estimation of monoisotopic masses that are difficult to observe.

[0026] In this embodiment, the processor calculates the mass difference between the theoretical maximum peak and the theoretical monoisotopic peak in the theoretical peak group as the relative position, and estimates the monoisotopic mass by subtracting the mass difference from the mass corresponding to the measured maximum peak in the measured peak group. This configuration makes it possible to estimate the monoisotopic mass in a simple manner.

[0027] In this embodiment, the mass spectrum includes multiple measured peaks arranged from low-mass to high-mass on the mass axis. The processor sequentially performs deisotope processing while sequentially selecting the multiple measured peaks in the order from low-mass to high-mass.

[0028] In this embodiment, the mass spectrum includes a low-mass range and a high-mass range that is higher than the low-mass range. The processor sequentially performs a first deisotope treatment while sequentially selecting a plurality of measured peaks included in the low-mass range, and then sequentially performs a second deisotope treatment, which is different from the first deisotope treatment, while sequentially selecting a plurality of measured peaks included in the high-mass range.

[0029] The second deisotope processing includes generating a theoretical peak group, estimating the monoisotopic mass, and generating the monoisotopic peak after deisotope processing. This configuration switches the deisotope algorithm depending on the mass. For example, the deisotope algorithm may be switched depending on the intensity of the monoisotopic peak in the calculated isotopic peak.

[0030] The mass spectrum processing method according to this embodiment is a method for processing a mass spectrum generated by mass spectrometry of a sample in an information processing device. Specifically, the mass spectrum processing method includes a first step, a second step, and a third step. In the first step, a theoretical peak group as an isotopic pattern is generated. In the second step, the monoisotopic mass corresponding to the measured peak group is estimated by comparing the theoretical peak group with the measured peak group in the mass spectrum. In the third step, a deisotope-treated monoisotopic peak is generated as the peak corresponding to the monoisotopic mass based on the monoisotopic mass.

[0031] The mass spectrum processing method described above can be implemented by software functionality. A program for executing the mass spectrum processing method may be installed on an information processing device via a network or a portable storage medium. The information processing device has a non-temporary storage medium for storing the program.

[0032] (2) Details of the embodiment Figure 1 discloses a mass spectrometry system according to an embodiment. The mass spectrometry system acquires a mass spectrum by mass spectrometry of a polymer sample and analyzes one or more polymers contained in the polymer sample based on that mass spectrum.

[0033] The mass spectrum processing system consists of a measuring device 10 and an information processing device 12. The measuring device 10 is a mass spectrometer, and the information processing device 12 is a computer. The information processing device 12 corresponds to a mass spectrum processing device.

[0034] In the illustrated configuration example, the measuring device 10 performs mass spectrometry on a polymer sample S. The measuring device 10 consists of an ion source 16, a mass spectrometer 18, and a detector 20. The ion source 16 is, for example, an ion source that follows the MALDI (Matrix Assisted Laser Desorption / Ionization) method or the ESI (Electrospray Ionization) method. The polymer sample S is ionized in the ion source 16. The mass spectrometer 18 is, for example, a time-of-flight mass spectrometer. Other types of mass spectrometers may be used as the mass spectrometer 18. The detector 20 detects individual ions that have passed through the mass spectrometer 18. The detection signal output from the detector 20 is converted into detection data by a signal processing circuit (not shown), and this detection data is sent to the information processing device 12. Instead of the polymer sample S, lipid samples, bio-derived substances, etc., may be measured.

[0035] The information processing device 12 includes a processor 22, memory (not shown), an input device (not shown), and a display device 26. The processor 22 performs multiple functions. In Figure 1, these multiple functions are represented by multiple blocks. The processor 22 is composed of, for example, a CPU that executes programs.

[0036] The spectrum generator 28 generates a mass spectrum based on the input detection data. The horizontal axis of the mass spectrum is the m / z axis (mass axis), and its vertical axis is the intensity axis (ionic intensity axis). The spectrum generator 28 has a peak list generator (not shown). The peak list consists of multiple peak information corresponding to multiple peaks included in the mass spectrum. Each peak information is a list element, and each peak information consists of a combination of m / z and intensity. When generating the peak list, for example, for each peak, the m / z corresponding to the centroid point of that peak is identified, and the area of ​​that peak is identified as the ionic intensity.

[0037] The deisotope processor 30 applies deisotope processing to the mass spectrum (specifically, the peak list). Specifically, the deisotope processor 30 sequentially selects peaks from the low-mass side to the high-mass side, and applies deisotope processing based on the isotope pattern to the group of peaks that include the selected peaks.

[0038] The mass spectrum has a low-mass range and a high-mass range. Monoisotopic peaks are easily observed in the low-mass range, and less easily observed in the high-mass range. The same deisotope treatment may be applied across the entire mass range, or different deisotope treatments may be applied to each mass range. In this embodiment, a first deisotope treatment is applied to the low-mass range, and a second deisotope treatment is applied to the high-mass range. Here, the first deisotope treatment is a conventional deisotope treatment, and the second deisotope treatment is a deisotope treatment according to this embodiment. The module that performs the deisotope treatment according to this embodiment is the high-mass range deisotope processor 32.

[0039] The KMD analyzer 34 performs KMD analysis on the mass spectrum after deisotope treatment. A KMD plot is generated as a result of the KMD analysis. An RKM (Remainder of Kendrick Mass) plot may be generated along with, or instead of, the KMD plot. KMD analysis is well-known. The spectral analyzer 36 applies analyses other than KMD analysis to the mass spectrum after deisotope treatment.

[0040] The mass spectrum before deisotope processing or the mass spectrum after the first deisotope processing may be input to the KMD analyzer 34 (see reference numeral 40A). The processing result may be used in the second deisotope processing performed in the high-mass-range deisotope processor 32 (see reference numeral 42A). Similarly, the mass spectrum before deisotope processing or the mass spectrum after the first deisotope processing may be input to the spectrum analyzer 36 (see reference numeral 40B). The processing result may be used in the second deisotope processing performed in the high-mass-range deisotope processor 32 (see reference numeral 42B).

[0041] The display processor 38 receives input such as the mass spectrum before deisotope processing, the mass spectrum after deisotope processing, KMD analysis results, spectral analysis results, etc. The display processor 38 generates an image to be displayed on the display 26. This image includes the mass spectrum before deisotope processing, the mass spectrum after deisotope processing, KMD analysis results, spectral analysis results, etc.

[0042] Figure 2 shows an example configuration of the high-mass-range deisotope processor 32. The high-mass-range deisotope processor 32 includes a composition formula estimator 40, a molecular formula estimator 42, an isotope pattern generator 44, a monoisotopic mass estimator 46, and a peak processor 48.

[0043] The composition formula estimator 40 estimates the composition formula based on information contained in the low-mass range of the mass spectrum. For example, if a polymer sample contains multiple polymers, multiple composition formulas will be estimated.

[0044] The information included in the low-mass range is, for example, the monoisotopic mass belonging to the low-mass range. Compositional estimation based on the monoisotopic mass may determine the empirical formula corresponding to the ion as a whole. Alternatively, the mass of monomer units (repeating units) may be determined from the peak spacing in the mass spectrum, and the empirical formula of the monomer unit may be estimated based on that mass. When estimating the empirical formula, estimation conditions are given in advance. These estimation conditions include, for example, lower and upper limits on the number of atoms for each element.

[0045] Based on the KMD plot obtained from the KMD analysis, the compositional formula of the entire ion or its main chain may be estimated. Based on the results of the mass spectral analysis, the compositional formula of the entire ion or its main chain may be estimated. Preferably, the compositional formula of the entire ion is estimated, but assuming a high degree of polymerization, the mass of the non-main chain portion becomes relatively small, so the compositional formula of the main chain portion may be estimated.

[0046] The molecular formula estimator 42 generates a molecular formula based on the estimated empirical formula and the reference mass described later. A molecular formula is a type of constituent element information. Constituent element information includes information that identifies multiple elements constituting an ion or its main chain, and information that identifies the number of atoms for each element. When the estimated empirical formula is the empirical formula of the ion or the entire ion, the constituent element information corresponds to the molecular formula.

[0047] The isotope pattern generator 44 generates isotope patterns based on estimated constituent element information (e.g., molecular formula). Information such as isotope lists for each element and the abundance ratios for each isotope is pre-registered. The generated isotope patterns are theoretical peak groups obtained by calculation or simulation. Generally, after generating the theoretical peak group, the experimental peak group corresponding to the theoretical peak group is identified from the mass spectrum. Alternatively, after generating the theoretical peak group, the theoretical peak group is applied to the mass spectrum, and as a result, the experimental peak group is identified.

[0048] The monoisotopic mass estimator 46 estimates the monoisotopic mass belonging to the experimental peak group based on the theoretical peak group and the experimental peak group. Specifically, the monoisotopic mass estimator 46 performs pattern matching between the theoretical peak group and the experimental peak group to estimate the monoisotopic mass. This will be described in detail later.

[0049] The peak processor 48 processes or modifies the mass spectrum. Specifically, the peak processor 48 adds monoisotopic peaks to the measured peak group and subtracts the theoretical peak group (isotope pattern) from the measured peak group. According to this embodiment, even in the high-mass range where monoisotopic peaks are difficult to observe, it is possible to correctly estimate the monoisotopic mass and associate the monoisotopic peak with that monoisotopic mass.

[0050] Figure 3 shows an example of a mass spectrum before deisotope treatment. In the mass spectrum 50, the horizontal axis is the m / z axis and the vertical axis is the intensity axis. The mass spectrum 50 has a first low-mass range 52A, a second low-mass range 52B, and a high-mass range 52C. The second low-mass range 52B can also be called the intermediate-mass range. The first low-mass range 52A contains multiple experimentally measured peak groups 54. The second low-mass range 52B contains multiple experimentally measured peak groups 56. The high-mass range 52C contains multiple experimentally measured peak groups 58. Each of the experimentally measured peak groups 54, 56, and 58 corresponds to an isotopic pattern.

[0051] Figure 4 shows the measured peak group 54 shown in Figure 3. The measured peak group 54 is the ion H(CH2) n OH + This corresponds to the isotopic pattern derived from [the original material], and the degree of polymerization (or number of repetitions) n is 10. The experimentally measured peak group 54 consists of a relatively small number of peaks. Among them, peak 54A is a monoisotopic peak.

[0052] Figure 5 shows the measured peak group 56 shown in Figure 4. The measured peak group 56 is the ion H(CH2) n OH + This corresponds to the isotopic pattern derived from [the substance]. The degree of polymerization n is 200. The experimental peak group 56 consists of multiple peaks, which have a bell-shaped distribution. Among the experimental peak group 56, peak 56A is a monoisotopic peak.

[0053] Figure 6 shows the measured peak group 58 shown in Figure 3. The measured peak group 58 is the ion H(CH2) n OH + This corresponds to the isotopic pattern derived from , with a polymerization degree n of 500. The measured peak group 58 consists of numerous peaks, which have a bell-shaped distribution. Among the measured peak group 58, peak 58A is a monoisotopic peak. In the illustrated example, peak 58A is very small. Specifically, peak 58A is buried in noise, it is smaller than the threshold Th, and is not actually observed.

[0054] Figure 7 shows the first deisotope treatment. (A) shows the measured peak group before deisotope treatment. The symbol 60 indicates the monoisotopic mass. The measured peak group (A) includes the monoisotopic peak 62.

[0055] (B) shows the measured peak group after deisotope treatment. In the measured peak group (B), the intensities of multiple non-monoisotopic peaks (isotope peaks) are added to the intensity of the monoisotopic peak (see reference numeral 66). Reference numeral 64 shows the large monoisotopic peak after the addition.

[0056] The first deisotope treatment is applicable only when the monoisotopic peak can be clearly identified. In contrast, the deisotope treatment (second deisotope treatment) according to the embodiment described below can be applied even when the monoisotopic peak cannot be clearly identified.

[0057] Figure 8 schematically shows the second deisotope treatment. (A) shows the measured peak group before deisotope treatment. Reference numeral 70 indicates the monoisotopic mass. The measured peak group (A) does not contain any monoisotopic peaks. The lightest peak 72 in the measured peak group (A) is a non-monoisotopic peak. If the first deisotope treatment were applied to the measured peak group (A) (see reference numeral 74), the lightest peak 72 would increase (see reference numeral 76).

[0058] (B) shows the experimentally measured peak group after the second deisotope treatment. In the experimentally measured peak group (B), the intensities of multiple non-monoisotopic peaks (isotope peaks) are aggregated at the position corresponding to the monoisotopic mass (see reference numeral 78), resulting in a large aggregated peak 80. Peak 80 corresponds to the monoisotopic peak.

[0059] A first example of the second deisotope treatment will be described using Figures 9 to 12.

[0060] In Figure 9, reference numeral 100 indicates multiple processes performed by the processor. The mass spectrum 84 has a low-mass range 86A and a high-mass range 86B. As indicated by reference numeral 88, multiple peaks are sequentially selected in mass order from the low-mass side to the high-mass side. For each selected peak, a deisotope treatment is applied to the group of peaks containing that peak.

[0061] Deisotope treatment (specifically, the first deisotope treatment) has already been completed for the low-mass range 86A. The low-mass range 86A includes peak 92 after deisotope treatment. Deisotope treatment (specifically, the second deisotope treatment) has also already been completed for the leading group of measured peaks 94 within the high-mass range 86B. The high-mass range 86B includes peak 96 after deisotope treatment.

[0062] Prior to the second deisotope treatment, the empirical formula is estimated based on the information contained in the low mass range, as indicated by reference numeral 102. In the illustrated example, the empirical formula is estimated based on the mass corresponding to the monoisotopic peak 92 (monoisotopic mass) (see reference numeral 106). Typically, the empirical formula is estimated for each peak contained in the low mass range. For example, if a polymer sample contains multiple polymers, multiple empirical formulas 104 will be estimated. Multiple empirical formulas 104 may be estimated based on a pre-generated KMD plot 108. Peak spacing analysis may be applied to the mass spectrum, and one or more empirical formulas may be estimated from the results.

[0063] Next, based on the reference mass 111 corresponding to the selected reference peak, a specific compositional formula 112 that satisfies the approximation conditions is selected from among several compositional formulas. In this process, the degree of polymerization is determined. As a result, the molecular formula is estimated, as indicated by the symbol 110. Instead of the molecular formula, elemental composition information of the main chain portion may be estimated. In the illustrated example, the experimental peak group 98 does not contain any monoisotopic peaks. The experimental peak group 98 consists only of multiple non-monoisotopic peaks. The lightest peak among them is the reference peak, and the mass corresponding to the lightest peak is the reference mass. The reference mass is close to the monoisotopic mass.

[0064] Next, as indicated by symbol 114, an isotope pattern, or theoretical peak group 116, is generated based on the molecular formula. In practice, after the generation of the theoretical peak group 116, the corresponding experimental peak group 98 is identified based on the theoretical peak group 116. As indicated by symbol 118, the monoisotopic mass corresponding to the experimental peak group 98 is estimated by comparing the theoretical peak group 116 with the experimental peak group 98. This will be described in detail later. Prior to comparing the theoretical peak group 116 with the experimental peak group 98, the necessary gain adjustments are usually performed on the theoretical peak group 116.

[0065] In peak processing 120, the sum of peak intensities is calculated based on the theoretical peak group (see reference numeral 122), and the peak corresponding to the sum of peak intensities (total intensity) is assigned to the monoisotopic mass. In other words, a new peak (monoisotopic peak) is added to the mass spectrum 84. Also, in peak processing 120, the theoretical peak group 116 is subtracted from the experimental peak group 98. If the experimental peak group 98 consists of a pure isotopic pattern, the experimental peak group 98 is replaced by the newly generated monoisotopic peak.

[0066] The above second deisotope treatment is performed for each selected peak. Finally, the deisotope treatment of the entire mass spectrum 84 is completed.

[0067] Figure 10 shows a pattern matching method for estimating monoisotopic masses. The experimental peak group 124 does not contain a monoisotopic peak. The theoretical peak group 126, represented by a dashed line, corresponds to the isotope pattern generated based on the estimated molecular formula. The theoretical peak group 126 is shifted along the m / z axis to achieve the best matching result between theoretical peak group 126 and experimental peak group 124 (see reference numeral 128). The theoretical peak group 130, represented by a solid line, is the result after matching. Reference numeral 132 indicates the theoretical monoisotopic peak. Based on the position of the shifted theoretical monoisotopic peak 132, i.e., the shifted theoretical monoisotopic mass, the monoisotopic mass corresponding to experimental peak group 124 is estimated (see reference numeral 134).

[0068] Based on the total intensity of the non-monoisotopic peak group 136 in the theoretical peak group 130, a monoisotopic peak corresponding to the estimated monoisotopic mass is generated and added to the mass spectrum. In addition, the non-monoisotopic peak group 136 in the theoretical peak group 130 is subtracted from the non-monoisotopic peak group 134 in the experimental peak group 124. As described above, the scale of the theoretical peak group 126 is adjusted as necessary prior to or during the comparison of the theoretical peak group 126 and the experimental peak group 124.

[0069] Next, with reference to Figure 12, the deisotope processing algorithm according to the first embodiment will be specifically described based on Figure 11.

[0070] In Figure 11, at S10, a reference peak is selected from the mass spectrum. As already explained, multiple peaks are sequentially selected as reference peaks in order of mass, from the low-mass side to the high-mass side. In Figure 12, the upper panel shows the experimental peak group 140. The experimental peak group 140 does not include monoisotopic peaks. In the illustrated example, the lightest peak 144 in the experimental peak group 140 is the reference peak.

[0071] In FIG. 11, in S12, a molecular formula is estimated based on the previously estimated compositional formula and the mass (reference mass) corresponding to the reference peak. At that time, the degree of polymerization in the molecular formula is specified. For example, the compositional formula list is H-(CH2CH2O) n -OH and H-(SiCH3CH3O) n -OH, and when the reference mass (exactly m / z) is 46244.53, the molecular formula H-(CH2CH2O) 1050 -OH is specified. The m / z corresponding to H-(CH2CH2O) 1050 -OH is 46245.53, and this value is closest to the above-mentioned 46244.53.

[0072] In FIG. 11, in S14, an isotope pattern, that is, a theoretical peak group, is generated based on the molecular formula. In FIG. 12, the theoretical peak group is shifted along the m / z axis (see reference numeral 148) so that the theoretical monoisotopic peak 146 in the generated theoretical peak group coincides with the lightest peak 144 in the measured peak group 140. That is, an offset is added to the entire theoretical peak group. In FIG. 12, reference numeral 142 indicates the theoretical peak group after the shift.

[0073] Based on the plurality of theoretical peaks constituting the theoretical peak group 142 after the shift, a plurality of integration intervals 150 are set. Each integration interval 152 has a size of -0.1 u to +0.1 u centered on each theoretical peak. In the measured peak group 140, the peaks belonging to each integration interval 152 are added. By performing such filtering, even if a plurality of measured peak groups corresponding to a plurality of polymers are mixed, it is possible to correctly extract the target peak group. Therefore, such filtering is executed as necessary.

[0074] In Figure 11, in S16, the maximum peak is identified in the filtered measured peak group. In Figure 12, the symbol 156 indicates the maximum peak in the measured peak group 140. The range 154 between the maximum peak 147 in the theoretical peak group 142 and the theoretical monoisotopic peak 146 may be used as the search range for the maximum peak 156.

[0075] In Figure 11, the monoisotopic mass is estimated in S18 based on the maximum peak. Specifically, in Figure 12, the monoisotopic mass 161 is estimated by subtracting the mass difference 158 between the maximum peak 147 and the theoretical monoisotopic peak 146 in the theoretical peak group 142 from the mass corresponding to the maximum peak 156 (see reference numeral 160).

[0076] In Figure 11, in S20, the molecular formula is re-determined based on the estimated monoisotopic mass. In S22, the molecular formula estimated in S12 is compared with the molecular formula estimated in S20. If the two molecular formulas match, the estimated monoisotopic mass is determined to be correct. If the two molecular formulas do not match, another empirical formula is selected in S12, and the molecular formula is estimated based on it. Subsequently, each step from S14 onward is repeated.

[0077] In S24, peak processing is performed. Specifically, in Figure 12, the total intensity value is calculated based on the theoretical peak group 142, and a monoisotopic peak 162 corresponding to the monoisotopic mass 161 is generated based on this total intensity value. In addition, the theoretical peak group 142 is subtracted from the measured peak group 140. If a negative value occurs after the subtraction, the negative value is replaced with 0. During the subtraction, the heaviest peak (rightmost peak) in the theoretical peak group 142 may be ignored.

[0078] In S26, it is determined whether or not there are any unselected peaks. If there are, each process from S10 onward is executed again.

[0079] Figure 13 shows a second embodiment. In Figure 13, elements similar to those shown in Figure 12 are denoted by the same reference numerals, and their descriptions are omitted.

[0080] In the second embodiment, the composition formula 200 is specified in advance. For example, the composition formula 200 is Averagen(C), which is the average composition of amino acids. 4.9384 H 7.7583 N 1.3577 O 1.4773 S 0.0417 ) is specified. As indicated by symbol 110A, the degree of polymerization n is determined based on the reference mass 111 corresponding to the selected reference peak, thereby determining the molecular formula or elemental composition information (C 4.9384 H 7.7583 N 1.3577 O 1.4773 S 0.0417 ) n It is estimated that...

[0081] Next, as indicated by symbol 114A, an isotopic pattern, or theoretical peak group 116A, is generated based on the estimated molecular formula. Subsequently, as indicated by symbol 118A, the theoretical peak group 116A is compared with the corresponding experimental peak group 98, and the monoisotopic mass is estimated from the comparison result.

[0082] According to this second embodiment, although the deisotope accuracy is reduced, the compositional formula estimation is unnecessary, so rapid deisotope processing can be expected.

[0083] The deisotope algorithms shown in Figures 11 and 12 can be applied to the entire mass spectrum. That is, if the measured peak group includes monoisotopic peaks, the result is the same as conventional deisotope processing.

[0084] As already explained, the deisotope treatment may be switched depending on the mass range. For example, the deisotope algorithm may be switched depending on the level of monoisotopic peaks in the theoretical peak group. For example, if the monoisotopic peak level is 40% or more of the maximum peak level, the first deisotope treatment may be applied, and if the monoisotopic peak level is less than 40% of the maximum peak level, the second deisotope treatment may be applied.

[0085] Figure 14 shows the NMD plot generated based on the mass spectrum after deisotope treatment. This KMD plot is exaggerated to illustrate the effects according to the embodiment and does not necessarily correspond to the actual values. The horizontal axis represents NKM (Nominal Kendrick Mass), and the vertical axis represents KMD.

[0086] In the illustrated example, two polymers with different terminal groups are represented by two display element sequences 202 and 204. Each display element sequence 202 and 204 consists of multiple display elements 202a and 204a arranged parallel to the horizontal axis. When conventional deisotope treatment is applied to the high-mass range of the mass spectrum, an incorrect deisotope treatment result is obtained. That is, in each display element sequence 202 and 204, multiple display elements 202A and 204A are generated that are shifted in the vertical axis direction. In contrast, when the deisotope treatment according to this embodiment is applied, multiple display elements 202B and 204B are generated that are displayed in the correct positions. Similar advantages can be obtained even when applying analyses other than KMD analysis to the mass spectrum.

[0087] Various known methods can be used to compare theoretical peak sets with experimental peak sets. For example, dynamic programming may be used. The degree of matching may be evaluated using cosine similarity or the like. When matching, information such as peak width and peak area may be considered in addition to peak level. [Explanation of symbols]

[0088] 10 Measuring devices, 12 Information processing devices, 28 Spectrum generators, 30 Deisotope processors, 32 High-mass range deisotope processors, 38 Display processors, 40 Composition formula estimators, 42 Molecular formula estimators, 44 Isotope pattern generators, 46 Monoisotopic mass estimators, 48 ​​Peak processors.

Claims

1. It includes a processor that processes the mass spectrum generated by mass spectrometry of a sample, The aforementioned processor, We generate a theoretical peak group as an isotopic pattern, By comparing the theoretical peak group with the experimentally measured peak group in the mass spectrum, the monoisotopic mass corresponding to the experimentally measured peak group is estimated. Based on the aforementioned monoisotopic mass, a monoisotopic peak after deisotope treatment is generated as the peak corresponding to the aforementioned monoisotopic mass. A mass spectral processing apparatus characterized by the following:

2. In the mass spectral processing apparatus according to claim 1, The aforementioned processor, Based on the reference peak in the mass spectrum, the reference mass is identified. Based on the estimated or specified compositional formula and the reference mass, the theoretical peak group is generated. A mass spectral processing apparatus characterized by the following:

3. In the mass spectral processing apparatus according to claim 2, The aforementioned reference peak corresponds to the lightest peak among the measured peak group. A mass spectral processing apparatus characterized by the following:

4. In the mass spectral processing apparatus according to claim 2, The aforementioned processor, Based on the estimated or specified compositional formula and the reference mass, information on the constituent elements of the ion corresponding to the reference peak or the main part of the ion is identified. Based on the constituent element information, the theoretical peak group is generated. A mass spectral processing apparatus characterized by the following:

5. In the mass spectral processing apparatus according to claim 2, The aforementioned mass spectrum includes a low-mass range and a higher-mass range, The aforementioned high-mass range includes the measured peak group, The processor estimates the composition formula based on the information within the low mass range. A mass spectral processing apparatus characterized by the following:

6. In the mass spectral processing apparatus according to claim 5, The information within the low mass range includes the measured monoisotopic mass corresponding to the measured monoisotopic peak within the low mass range. A mass spectral processing apparatus characterized by the following:

7. In the mass spectral processing apparatus according to claim 1, The aforementioned processor, The relative positions of the theoretical monoisotopic peaks with respect to the aforementioned theoretical peak group are identified. The monoisotopic mass is estimated by applying the relative position to the measured peak group. A mass spectral processing apparatus characterized by the following:

8. In the mass spectral processing apparatus according to claim 7, The aforementioned processor, In the aforementioned theoretical peak group, the mass difference between the theoretical maximum peak and the theoretical monoisotopic peak is calculated as the relative position. The monoisotopic mass is estimated by subtracting the mass difference from the mass corresponding to the maximum peak measured in the measured peak group. A mass spectral processing apparatus characterized by the following:

9. In the mass spectral processing apparatus according to claim 1, The mass spectrum includes multiple measured peaks aligned from the low-mass side to the high-mass side along the mass axis. Deisotope processing is performed sequentially while sequentially selecting the multiple measured peaks in the order from the low-mass side to the high-mass side. A mass spectral processing apparatus characterized by the following:

10. In the mass spectral processing apparatus according to claim 9, The aforementioned mass spectrum includes a low-mass range and a higher-mass range, The aforementioned processor, The first deisotope treatment is performed sequentially while sequentially selecting multiple measured peaks included in the low mass range. A second deisotope treatment, different from the first deisotope treatment, is sequentially performed while sequentially selecting multiple measured peaks included in the high-mass range. The second deisotope treatment includes generating the theoretical peak group, estimating the monoisotopic mass, and generating the monoisotopic peak after the deisotope treatment. A mass spectral processing apparatus characterized by the following:

11. A mass spectrum processing method for processing a mass spectrum generated by mass spectrometry of a sample in an information processing device, The process of generating a theoretical peak group as an isotopic pattern, A step of estimating the monoisotopic mass corresponding to the measured peak group by comparing the theoretical peak group with the measured peak group in the mass spectrum, A step of generating a monoisotopic peak after deisotope treatment as a peak corresponding to the monoisotopic mass, based on the aforementioned monoisotopic mass, A mass spectral processing method characterized by including the following.

12. A program for processing the mass spectrum generated by mass spectrometry of a sample in an information processing device, The function of generating theoretical peak groups as isotopic patterns, The function includes estimating the monoisotopic mass corresponding to the measured peak group by comparing the theoretical peak group with the measured peak group in the mass spectrum, Based on the aforementioned monoisotopic mass, a function is provided to generate a monoisotopic peak after deisotope treatment as a peak corresponding to the aforementioned monoisotopic mass. A program characterized by including the following.

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