Sialic acid-containing sugar chain analysis method and sialic acid-containing sugar chain analysis device

Abstract

To improve the efficiency and increase the accuracy of analysis of a sialic acid-containing sugar chain.SOLUTION: Provided is a method for analyzing a sialic acid-containing sugar chain on the basis of the mass spectrum data of a sample that contains a sialic acid-containing sugar chain having been specifically modified to a sialic acid binding form, or a molecule having been modified by the sugar chain. This analysis method includes: a search condition setting step (S1); a peak detection step (S2); a composition estimation step (S3) for estimating a sugar chain composition and finding a sugar chain composition candidate with regard to each of the detected representative peaks; a peak cluster detection step (S4) including a plurality of peaks where the sialic acid counts and the sugar chain compositions other than sialic acid are estimated to be identical; a filtering step (S5) for included sialic acid counts, sialic acid binding form counts, sialic acid types, and super chain; and a display step (S6-S7) for creating and displaying a list of sugar chain composition candidates in such a manner that sugar chain composition candidates after selection can be visually discriminated.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a method and apparatus for analyzing glycans using mass spectrometry, and more specifically to an analytical method and apparatus that enable structural analysis of sialic acid-containing glycans, including the binding mode of sialic acid. Note that the term "glycan" as used herein includes not only glycans that exist independently, but also glycans that modify biomolecules such as proteins, peptides, lipids, and nucleic acids, i.e., modified glycans. [Background technology]

[0002] Glycan analysis is a major theme in fields such as life science, drug discovery, and medicine. In particular, understanding the linkage mode of sialic acid in sialic acid-containing glycans is an important task in glycan structural analysis. Against this background, methods for chemical modification specific to the linkage mode of sialic acid have been developed to efficiently perform structural analysis of sialic acid-containing glycans, including differences in linkage modes, using mass spectrometry. For example, Patent Document 1 and Non-Patent Document 1 disclose a sialic acid linkage-specific modification method known as the SALSA (Sialic Acid Linkage-Specific Alkylamidation) method.

[0003] The SALSA method utilizes the difference in the reactivity of the carboxylic acids that make up α2,3-sialic acid and α2,6-sialic acid when they react with amines to form amides. This derivatization results in a mass difference of 28 Da between α2,3-sialic acid and α2,6-sialic acid, allowing them to be distinguished from each other based on the results of mass spectrometry.

[0004] Patent Document 1 discloses a method for analyzing glycans based on mass spectral data obtained by mass spectrometry using the SALSA method as a pretreatment method. In this analytical method, glycan compositions are estimated by performing a brute force search for compositions using the type and number of monosaccharides as search conditions for the three sialic acid linkage isomer ion peaks derived from sialic acid-containing glycans detected at 28 Da intervals in the mass spectrum. From the glycan composition candidates obtained by this estimation, compositions containing two or more sialic acids and two or more α2,6-linkages for the peak showing the largest mass are extracted as highly plausible composition candidates, and these highly plausible composition candidates can be visually distinguished from other composition candidates whose plausibility as sialic acid-containing glycan isomers is questionable and displayed in a list format (see, for example, Figures 6 and 8 of Patent Document 1). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] International Publication No. 2017 / 145496 [Non-patent literature]

[0006] [Non-Patent Document 1] Takashi Nishikaze and five others, "Differentiation of Sialyl Linkage Isomers by One-Pot Sialic Acid Derivatization for Mass Spectrometry-Based Glycan Profiling," Analytical Chemistry, 2017, Vol. 89, pp. 2353-2360 Summary of the Invention [Problem to be solved by the invention]

[0007] The analytical method described in Patent Document 1 is a structural analysis technique for glycans containing a specific type of sialic acid, such as N-acetylneuraminic acid (Neu5Ac), but multiple molecular species of sialic acid are known. Besides N-acetylneuraminic acid, N-glycolylneuraminic acid (Neu5Gc) and deaminoneuraminic acid (Kdn) are well-known as major sialic acids, and the distribution of each molecular species is known to be specific to biological species and tissues. In principle, sialic acid-containing glycans containing sialic acid types other than Neu5Ac can also be analyzed in the same way as sialic acid-containing glycans containing Neu5Ac. However, the abundance of other molecular species is often significantly lower than that of the most abundant molecular species. Therefore, even when sialic acid linkage-specific modification is performed, some peaks corresponding to the expected combination of linkages are often not detected in the mass spectrum, making it difficult to narrow down the candidate compositions of such sialic acid-containing glycans.

[0008] The present invention has been made to solve these problems, and its main object is to provide a method and apparatus for analyzing sialic acid-containing glycans that can improve the efficiency of the analysis of sialic acid-containing glycans containing various types of sialic acid and can improve the accuracy of the analysis. [Means for solving the problem]

[0009] One aspect of the method for analyzing sialic acid-containing sugar chains according to the present invention, which has been made to solve the above-mentioned problems, is a method for analyzing sialic acid-containing sugar chains based on mass spectrum data obtained by mass spectrometry of a sample containing sialic acid-containing sugar chains that have been modified specifically in a sialic acid binding mode or molecules modified with said sugar chains, comprising: a search condition setting step for setting glycan search conditions; a peak detection step of detecting a representative peak for each isotope peak cluster from the mass spectrum data; a composition estimation step of estimating the glycan composition of each representative peak detected in the peak detection step in accordance with the glycan search conditions to obtain glycan composition candidates; a peak cluster detection step of detecting isomeric peak clusters including a plurality of peaks that are presumed to have the same number of sialic acids and the same sugar chain composition other than sialic acid from the representative peaks detected in the peak detection step; a glycan composition filtering step of selecting the glycan composition candidates by applying predetermined constraints to each peak contained in the isomer peak cluster regarding the number of sialic acids contained, the number of bonding modes of sialic acids, the type of sialic acid, and the identity of glycan compositions other than sialic acid; a display step of creating and displaying a list of the glycan composition candidates in a manner that allows visual distinction between the glycan composition candidates selected by the glycan composition filtering step and other glycan composition candidates; It has.

[0010] One aspect of the sialic acid-containing sugar chain analyzing device according to the present invention, which has been made to solve the above-mentioned problems, is an analyzing device that analyzes the sialic acid-containing sugar chain based on mass spectrum data obtained by mass spectrometry of a sample containing a sialic acid-containing sugar chain that has been modified specifically in a sialic acid linkage mode or a molecule modified by the sugar chain, and a search condition setting unit that accepts the specification of glycan search conditions by a user and sets the glycan search conditions; a peak detection unit that detects a representative peak for each isotope peak cluster from the mass spectrum data; a composition estimation unit that estimates the glycan composition of each representative peak detected by the peak detection unit in accordance with the glycan search conditions to obtain glycan composition candidates; a peak cluster detection unit that detects isomeric peak clusters including a plurality of peaks that are presumed to have the same number of sialic acids and the same sugar chain composition other than sialic acid from the representative peaks detected by the peak detection unit; a glycan composition filtering unit that selects the glycan composition candidates by applying predetermined constraints regarding the number of sialic acids contained, the number of bonding modes of sialic acids, the type of sialic acid, and the identity of glycan compositions other than sialic acid to each peak contained in the isomer peak cluster; a display processing unit that creates and displays a list of the glycan composition candidates in a manner that allows visual distinction between the glycan composition candidates selected by the glycan composition filtering unit and other glycan composition candidates; Equipped with. [Effects of the Invention]

[0011] According to the above aspect of the present invention, even if ion peaks corresponding to some of the expected combinations of binding modes for some specific types of sialic acid are not detected among sialic acid-containing glycans in which the number of sialic acids contained is the same as that of the glycan composition other than sialic acid but the sialic acid binding mode and type are different, it is possible to accurately narrow down and present to the user the composition candidates of sialic acid-containing glycans containing the specific types of sialic acid. This improves the efficiency of actual measurement work such as MS / MS analysis for verifying whether the predicted composition candidates of sialic acid-containing glycans are valid, and the analysis work of the data collected thereby, allowing the structural analysis of sialic acid-containing glycans to be carried out more quickly and accurately. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a block diagram of one embodiment of a glycan analysis system including a sialic acid-containing glycan analysis device according to the present invention. [Figure 2] 1 is a flowchart showing the procedure of analysis processing in the sugar chain analysis system of this embodiment. [Figure 3] FIG. 1 shows an example of a mass spectrum and an explanatory diagram of an analysis of glycan composition based on peaks detected in the mass spectrum. [Figure 4] FIG. 4 shows peak clusters detected for the mass spectrum shown in FIG. 3 and the classification results of the peaks in each cluster. [Figure 5]FIG. 5 shows an example of a list of sugar chain composition candidates obtained for the six peaks shown in FIG. 4. [Figure 6] FIG. 5 shows an example of a list of sugar chain composition candidates obtained for the six peaks shown in FIG. 4. DETAILED DESCRIPTION OF THE INVENTION

[0013] In the above-mentioned aspect of the present invention, the molecule modified with a sialic acid-containing sugar chain is, for example, a biomolecule such as a protein, peptide, lipid, or nucleic acid modified with a sialic acid-containing sugar chain.

[0014] Furthermore, the sialic acid linkage-specific modification, which is the premise of the above-mentioned embodiment of the present invention, is typically the SALSA method disclosed in the above-mentioned Patent Document 1 and Non-Patent Document 1, but is not limited thereto. For example, any sialic acid linkage-specific chemical modification (derivatization) may be used to distinguish at least two or more different sialic acid linkages, such as α2,3-linked, α2,6-linked, and α2,8-linked, based on mass differences.

[0015] Furthermore, in the above-mentioned aspect of the present invention, the type of mass spectrometer used to perform mass analysis on a sample containing sialic acid-containing glycans, etc. is not particularly limited, and examples that can be used include ion trap mass spectrometers, linear ion trap mass spectrometers, TOF / TOF mass spectrometers, quadrupole time-of-flight (Q-TOF) mass spectrometers, quadrupole ion trap mass spectrometers, Fourier transform ion cyclotron resonance mass spectrometers, etc. High mass accuracy is desirable for estimating glycan composition based on mass values.

[0016] Hereinafter, one embodiment of a glycan analysis system including an analysis device for carrying out the sialic acid-containing glycan analysis method according to the present invention will be described with reference to the accompanying drawings. FIG. 1 is a schematic block diagram of this glycan analysis system.

[0017] As shown in Figure 1, this system includes a mass analysis unit 1 that performs mass analysis on a sample, an analysis control unit 2 that controls the mass analysis unit 1, a data analysis unit 3 that performs analysis processing on data obtained by mass analysis, and an input unit 4 and a display unit 5 that serve as user interfaces.

[0018] The data analysis unit 3 includes, as functional blocks, a data storage unit 30, a peak detection unit 31, a glycan search condition setting unit 32, an isomer peak cluster detection unit 33, a glycan composition estimation unit 34, a glycan composition filtering unit 35, a glycan composition candidate list creation unit 36, a display processing unit 37, and a precursor ion selection reception unit 38. The glycan search condition setting unit 32 includes, as a subordinate functional block, a glycan search condition storage unit 320.

[0019] The mass analyzer 1 can be of any type, but when performing MS / MS analysis as described below, a mass analyzer having a function of dissociating ions by collision-induced dissociation (CID) or the like, such as an ion trap or collision cell, is used. Furthermore, to estimate the composition from the mass-to-charge ratio value as described below, it is preferable that the accuracy and resolution of the m / z value are high. Therefore, a time-of-flight mass separator, a Fourier transform ion cyclotron resonance mass separator, or the like is suitable as the mass separator.

[0020] Furthermore, the mass analysis unit 1 may be a liquid chromatograph mass analyzer (LC-MS) instead of a mass analyzer alone, or may be configured to prepare multiple samples by separating and fractionating the eluate whose components have been separated by liquid chromatography, and then subjecting each of the multiple samples to mass analysis using a mass analyzer.

[0021] In this system, the data analysis unit 3 is actually a personal computer or a more powerful workstation, and a dedicated data processing program installed on such a computer is run on the computer to realize the functions of each functional block shown in Figure 1. In this case, the input unit 4 is a keyboard and pointing device (such as a mouse) attached to the computer, and the display unit 5 is a monitor also attached to the computer.

[0022] The procedure for analyzing sialic acid-containing sugar chains in this sugar chain analysis system will be explained below with reference to experimental examples and Figures 2 to 6. Figure 2 is a flowchart showing the procedure for sugar chain analysis processing carried out mainly by the data analysis unit 3.

[0023] When analyzing sialic acid-containing glycans using this glycan analysis system, a sample containing sialic acid-containing glycans or molecules modified with sialic acid-containing glycans (glycopeptides, glycolipids, etc.) is first pretreated with sialic acid linkage-specific chemical modification. Examples of sialic acid linkage-specific modification methods that can be used include, but are not limited to, the SALSA method described in Non-Patent Document 1. As described above, in the SALSA method, the masses of the modified products differ by 28 Da between cases where the sialic acid contained in the glycan is α2,3-linked and cases where the sialic acid is α2,6-linked, even if the other glycan compositions are identical.

[0024] Next, the sample pretreated by sialic acid bond-specific chemical modification is subjected to mass spectrometry by the mass spectrometry unit 1. Mass spectrum data over a predetermined m / z range obtained by mass spectrometry is sent from the mass spectrometry unit 1 to the data analysis unit 3 and stored in the data storage unit 30.

[0025] When the user specifies the data to be analyzed using the input unit 4 and issues an instruction to execute the analysis, the data analysis unit 3 starts the analysis process according to the procedure shown in FIG. The glycan search condition setting unit 32 displays a predetermined glycan search condition setting screen on the screen of the display unit 5 and accepts input of glycan search conditions by the user (step S1). However, glycan search conditions set by default may also be set automatically, regardless of user input. Furthermore, in addition to glycan search conditions, it is also possible to accept user input of peak detection conditions for detecting peaks from mass spectrum data. The glycan search conditions and peak detection conditions that have been input or set by default are saved in the glycan search condition saving unit 320.

[0026] Specifically, the glycan search conditions can include, for example, the sialic acid linkage-specific modification method to be used, the mass tolerance for estimating the glycan composition, the expected ion species, and the type and number of sugar residues (including sialic acid) to be searched for. On the other hand, the peak detection conditions may include, for example, the signal intensity or SN ratio that is a threshold for recognizing a peak.

[0027] When the actual analysis begins, the peak detection unit 31 reads out the mass spectrum data to be analyzed, stored in the data storage unit 30, and detects monoisotopic ion peaks as representative peaks for each isotope peak cluster according to the peak detection conditions. Generally, for biological molecules such as glycans, the peak with the smallest m / z value among multiple isotope ion peaks that appear at intervals of 1 Da can be detected as the monoisotopic ion peak. The peak detection unit 31 then calculates the m / z value of each detected ion peak to create a peak list (step S2). Note that instead of the m / z value of the monoisotopic ion peak, the average (center of gravity) m / z value of multiple isotope ion peaks may be calculated. That is, for each group of isotope ion peaks derived from the same glycan, a representative m / z value for that group may be calculated.

[0028] Next, the glycan composition estimation unit 34 estimates the glycan composition for each peak listed in the peak list created in step S2 according to the glycan search conditions stored in the glycan search condition storage unit 320, and obtains glycan composition candidates (step S3). Specifically, under the constraints of the type and number of sugar residues specified as the glycan search conditions, an exhaustive search is performed for glycan compositions that match the m / z value of the ion peak within a specified mass accuracy range. The glycan composition that is found is then designated as the glycan composition candidate corresponding to that ion peak. When glycan composition candidates are obtained, the candidates are not necessarily narrowed down to one for one ion peak, and multiple candidates may be obtained.

[0029] Next, the isomer peak cluster detection unit 33 detects isomer peak clusters including multiple peaks that are presumed to have the same number of sialic acids and the same sugar chain composition other than sialic acid from the peaks in the peak list created in step S2 (step S4).

[0030] Here, the SALSA method is used for sialic acid linkage-specific modification. In accordance with the SALSA method, adjacent ion peaks between α2,6-sialic acid and α2,3-sialic acid, spaced 28 Da apart by an m / z difference, are detected from the peak list. These peaks are determined to be identical sialic acid linkage isomer peak clusters, which are composed of linkage isomers of sialic acid-containing glycans with the same number of sialic acids, type of sialic acid, and glycan composition other than sialic acid. The allowable error for the peak spacing used for this detection can be, for example, m / z 0.1. The adjacent peak spacing required to determine a single isomer peak cluster varies depending on the sialic acid linkage-specific modification method used. Naturally, the number of ion peaks contained in a single isomer peak cluster varies depending on the number of sialic acids contained in the sialic acid-containing glycan, the linkage mode of the sialic acid, and other factors.

[0031] Furthermore, the isomer peak cluster detection unit 33 determines whether the ion peaks contained in the detected multiple different same-type sialic acid binding isomer peak clusters are arranged at m / z value intervals corresponding to the sugar residue mass difference between different types of sialic acids specified as the glycan search conditions. The isomer peak clusters each containing ion peaks that fall within that m / z value interval are recognized as different-type sialic acid binding isomer peak clusters, which have the same number of sialic acids and sugar chain composition other than sialic acids, but differ only in the type of sialic acid. Then, all different-type sialic acid binding isomer peak clusters that have the same number of sialic acids and sugar chain composition other than sialic acids are recognized as different-type sialic acid binding isomer peak clusters. - The ion peaks contained in the above are identified as isomer peak clusters.

[0032] Here, a specific example based on an experiment will be shown. In an experiment conducted by the present inventors, N-glycans that modify fetuin, a glycoprotein in the blood of fetal bovine, were Deglycosylation The glycan mixture was cleaved using PNGase, an enzyme, and then concentrated to prepare a sample. The sialic acids contained in this sample were specifically modified with the SALSA method, and then further modified with the sialic acid bond type. To, The samples to be analyzed were prepared by labeling the reducing ends of the glycans with anthranilic acid (AA labeling). This labeling was a pretreatment to promote ionization in negative ion mode. The samples obtained in this manner were subjected to mass analysis in negative ion mode using a matrix-assisted laser desorption / ionization ion trap time-of-flight mass spectrometer (MALDI-IT-TOFMS), and mass spectral data were obtained.

[0033] In the above experimental example, the sugar chain search conditions were determined as follows: Sialic acid linkage specific modification method: SALSA method Labeling method: AA labeling Mass tolerance for estimating glycan composition: m / z 0.2 Mass interval tolerance for isomeric peak cluster detection: m / z 0.1 Ion species: Deprotonated ions The types and numbers of sugar residues to be searched for: 3-15 hexose, 2-14 HexNAc, 0-2 fucose (dHex), 0-5 Neu5Ac (sialic acid), 0-5 Neu5Gc (sialic acid)

[0034] A portion of the mass spectrum obtained by the above experimental example is shown in Figure 3. In the m / z range shown in Figure 3, the following monoisotopic ion peaks were detected by processing the mass spectrum in step S2: m / z 3038.1, m / z 3066.2, m / z 3082.2, m / z 3094.2, m / z 3110.2, and m / z 3122.2. Furthermore, based on the peak list containing these peaks, the processing in step S4, i.e., detecting a group of peaks spaced 28 Da apart by the m / z difference between α2,6-sialic acid and α2,3-sialic acid, resulted in the detection of m / z 3038.1, m / z 3066.2, m / z 3122.2. 3 Two sets of peak clusters of the same sialic acid linkage isomer were detected, each containing four singly charged ion peaks at m / z 3094.2 and m / z 3122.2, and two singly charged ion peaks at m / z 3082.2 and m / z 3110.2, respectively.

[0035] It was confirmed that some of the peaks contained in each of the two pairs of peak clusters of the same type of sialic acid linkage isomer were arranged at intervals of m / z 16, which corresponds to the difference in sugar residue mass between N-acetylneuraminic acid (Neu5Ac) and N-glycolylneuraminic acid (Neu5Gc), two types of sialic acids specified as glycan search conditions. Therefore, the two pairs of peak clusters of the same type of sialic acid linkage isomer were detected as peak clusters of different types of sialic acid linkage isomers, and these peak clusters of different types of sialic acid linkage isomers were detected as peak clusters of different types of sialic acid linkage isomers. - All peaks contained in the above were detected as isomeric peak clusters with the same number of sialic acids and the same sugar chain composition other than sialic acids.

[0036] Furthermore, as described above, the isomer peak cluster detection unit 33 classifies multiple peaks that are aligned based on the mass difference between sugar residues of different sialic acids as peaks with the same peak index #n. In the above experimental example, as shown in FIG. 4 , the peak with the smallest mass value, m / z 3038.1, among all the peaks contained in the two pairs of different sialic acid linkage isomer peak clusters (cluster 1, cluster 2), was classified as the peak with peak index #1 and in same-type sialic acid linkage isomer peak cluster 1 (cluster 1). The peak with m / z 3066.2, which has a mass value 28 Da larger than this peak and the second smallest mass value in the peak cluster, was classified as peak index #2. The peak with m / z 3082.18, detected with a mass difference of 16 Da from the m / z 3066.2 peak, had the same peak index #2 and was classified as same-type sialic acid linkage isomer peak cluster 2 (cluster 2). Similarly, the peaks at m / z 3094.2 and m / z 3110.2 were classified as peak index #3, and the peak at m / z 3122.2 was classified as peak index #4.

[0037] In this example, a heterogeneous sialic acid binding isomer peak cluster was found from multiple peaks contained in two pairs of same-type sialic acid binding isomer peak clusters, but a heterogeneous sialic acid binding isomer peak cluster may also be formed by detecting one heterogeneous sialic acid-containing sugar chain peak having a different heterogeneous sialic acid residue mass from a portion of the peaks contained in one pair of same-type sialic acid binding isomer peak clusters.

[0038] Returning to the flowchart of FIG. 2, the explanation will be continued. Next, the glycan composition filtering unit 35 selects each of the glycan composition candidates obtained in step S3 for each peak included in the isomer peak cluster by imposing constraints on the number of sialic acids, the number of sialic acid bonding modes, the type of sialic acid, and the identity of the glycan composition other than sialic acid, as exemplified below (step S5).

[0039] <Restrictions> (1) In this example, four peak indices are obtained by the isomer peak cluster detection unit 33. Therefore, all peaks contain the same number of sialic acids (three or more), and the candidate glycan compositions that are identical in composition other than sialic acid are valid as sialic acid-containing glycans. Generally, when N peak indices are obtained, the glycan corresponding to the original peak contains N-1 or more sialic acids. (2) Furthermore, based on the mass relationship of each peak, peaks classified as peak index #1 should contain three or more α2,3-linked sialic acids, peaks classified as peak index #2 should contain two or more α2,3-linked sialic acids and one or more α2,6-linked sialic acids, peaks classified as peak index #3 should contain one or more α2,3-linked sialic acids and two or more α2,6-linked sialic acids, and peaks classified as peak index #4 should contain three or more α2,6-linked sialic acids. Furthermore, peaks classified as same-type sialic acid linkage isomer peak cluster 2 should have a glycan composition in which one type of sialic acid is substituted from Neu5Ac to Neu5Gc among the glycan compositions of the same peak index in same-type sialic acid linkage isomer peak cluster 1. In addition, the above-mentioned constraints are also written for each peak in FIG.

[0040] The number of glycan composition candidates is usually significantly reduced by the selection by the glycan composition filtering unit 35. The glycan composition candidate list creation unit 36 ​​collects the glycan composition candidates estimated in step S3 corresponding to each peak contained in the isomer peak cluster detected in step S4, and creates a glycan composition candidate list associated with each peak in the isomer peak cluster. In addition, the glycan composition candidate list creation unit 36 ​​uses the glycan composition candidates selected (remaining in the filtering) in step S5 in the glycan composition candidate list. and Unselected glycan composition candidates and of The information is displayed in a visually identifiable manner (step S6). Then, the display processing unit 37 displays the created list of sugar chain composition candidates on the screen of the display unit 5 (step S7).

[0041] 5 and 6 are examples of lists of glycan composition candidates obtained for the six peaks in the above experimental example. In this example, the glycan composition candidates (Composition) selected as valid by the glycan composition filtering unit 35 are shown in bold, while the other glycan composition candidates are shown in thin type and in a lighter color. The manner of identification is not limited to this, and it is sufficient to display them in a manner that makes it visually difficult to confuse, such as by showing both glycan composition candidates in different colored characters or by changing the background color. Furthermore, it is also possible to selectively display only valid glycan composition candidates or only invalid glycan composition candidates according to user specifications.

[0042] 5 and 6, the "Conventional Method" column on the right side lists the glycan composition candidates that are deemed plausible by the method described in Patent Document 1 and those that are deemed implausible by the method described in Patent Document 1. However, this conventional method column is provided solely for the purpose of comparing the method according to this embodiment with the method according to the prior art, and is not included in the list of glycan composition candidates displayed by the device of this embodiment.

[0043] In Figures 5 and 6, by comparing the bold / thin type distinction in the Composition column with the plausible / implausible distinction in the conventional method column, it can be seen that some of the glycan composition candidates that were selected as valid by the conventional method are deemed invalid by the method of this embodiment. Specifically, there are differences between the results of estimating the validity of the glycan composition candidates for peaks m / z 3082.18 and m / z 3110.21 belonging to cluster 2 between the conventional technology and the method of this embodiment. It can be confirmed that the glycan composition candidates that were deemed valid by the conventional technology, shown in the dotted line box in the conventional method column in Figures 5 and 6, were not selected as invalid by the method of this embodiment.

[0044] Even with conventional methods, the predicted glycan composition candidates are appropriately narrowed down for glycans belonging to cluster 1, and in that respect, the method is highly useful. On the other hand, the method of this embodiment uses uniform constraints across sialic acid-containing glycan clusters containing different types of sialic acid, so it is possible to narrow down the appropriate glycan composition even when only a portion of the linkage isomer peaks of glycans containing any type of sialic acid are detected. Therefore, compared to conventional methods, this method has the advantage of being able to appropriately narrow down candidates for a wider range of glycans.

[0045] When it is desired to experimentally determine the glycan composition or glycan structure of a peak for which multiple glycan composition candidates have been listed, it is necessary to perform MS / MS analysis targeting the ions corresponding to that peak. In this case, the user performs an operation to specify an arbitrary peak as a precursor ion in, for example, the displayed mass spectrum or glycan composition candidate list. In response to this operation, the precursor ion selection receiving unit 38 selects the specified ion peak as the precursor ion for the MS / MS analysis.

[0046] This selection information is sent to the analysis controller 2, which controls the mass spectrometer 1 to perform MS / MS analysis targeting the selected precursor ion, specifically, product ion scan measurement using an ion dissociation technique such as CID. This allows the mass spectrometer 1 to perform MS / MS analysis of a sample containing glycans that have been specifically modified with sialic acid linkages, and acquire MS / MS spectral data. Since multiple product ion peaks derived from the target sialic acid-containing glycans are observed in the MS / MS spectrum, the user can verify which of multiple glycan composition candidates is appropriate, or whether one glycan composition candidate is appropriate, based on the m / z values ​​of those peaks.

[0047] As described above, the sugar chain analysis system of this embodiment can efficiently perform structural analysis of sialic acid-containing sugar chains, including the sialic acid binding mode.

[0048] The order of the steps in the flowchart shown in Figure 2 can be changed as appropriate as long as it does not affect the actual processing content of each step. For example, the order of the processing of steps S3 and S4 can be changed, and the setting of glycan search conditions in step S1 can be performed at any time before the estimation of glycan composition in step S3.

[0049] Furthermore, the isomer peak cluster detection unit 33 may detect different sialic acid binding mode isomer peak clusters for all combinations of selectable types of sialic acids, regardless of whether multiple types of sialic acids are specified as the sugar residues to be searched in the glycan search condition setting unit 32, and may add the combination of sialic acid types corresponding to the mass difference of the peaks contained in the detected clusters to the sugar residues to be searched in the glycan search condition setting unit 32, and then perform glycan composition estimation.

[0050] Furthermore, the above embodiment is merely an example of the present invention, and it goes without saying that any appropriate modifications, alterations, additions, etc. made within the spirit of the present invention will also fall within the scope of the claims of the present application.

[0051] [Various aspects] It will be appreciated by those skilled in the art that the exemplary embodiments described above are examples of the following aspects.

[0052] (Item 1) One aspect of the method for analyzing sialic acid-containing sugar chains according to the present invention is a method for analyzing sialic acid-containing sugar chains based on mass spectrum data obtained by mass spectrometry of a sample containing sialic acid-containing sugar chains that have been modified specifically in a sialic acid linkage mode or molecules modified with said sugar chains, comprising: a search condition setting step for setting glycan search conditions; a peak detection step of detecting a representative peak for each isotope peak cluster from the mass spectrum data; a composition estimation step of estimating the glycan composition of each representative peak detected in the peak detection step in accordance with the glycan search conditions to obtain glycan composition candidates; a peak cluster detection step of detecting isomeric peak clusters including a plurality of peaks that are presumed to have the same number of sialic acids and the same sugar chain composition other than sialic acid from the representative peaks detected in the peak detection step; a glycan composition filtering step of selecting the glycan composition candidates by applying predetermined constraints to each peak contained in the isomer peak cluster regarding the number of sialic acids contained, the number of bonding modes of sialic acids, the type of sialic acid, and the identity of glycan compositions other than sialic acid; a display step of creating and displaying a list of the glycan composition candidates in a manner that allows visual distinction between the glycan composition candidates selected by the glycan composition filtering step and other glycan composition candidates; It has.

[0053] (Item 3) Furthermore, one aspect of the sialic acid-containing sugar chain analyzing device according to the present invention is an analyzing device that analyzes the sialic acid-containing sugar chain based on mass spectrum data obtained by mass spectrometry of a sample containing a sialic acid-containing sugar chain that has been modified specifically to a sialic acid linkage or a molecule modified by the sugar chain, comprising: a search condition setting unit that accepts the specification of glycan search conditions by a user and sets the glycan search conditions; a peak detection unit that detects a representative peak for each isotope peak cluster from the mass spectrum data; a composition estimation unit that estimates the glycan composition of each representative peak detected by the peak detection unit in accordance with the glycan search conditions to obtain glycan composition candidates; a peak cluster detection unit that detects isomeric peak clusters including a plurality of peaks that are presumed to have the same number of sialic acids and the same sugar chain composition other than sialic acid from the representative peaks detected by the peak detection unit; a glycan composition filtering unit that selects the glycan composition candidates by applying predetermined constraints regarding the number of sialic acids contained, the number of bonding modes of sialic acids, the type of sialic acid, and the identity of glycan compositions other than sialic acid to each peak contained in the isomer peak cluster; a display processing unit that creates and displays a list of the glycan composition candidates in a manner that allows visual distinction between the glycan composition candidates selected by the glycan composition filtering unit and other glycan composition candidates; Equipped with.

[0054] In the method for analyzing sialic acid-containing sugar chains described in paragraph 1, the steps are not necessarily performed in the order described above, and the order of execution can be changed as appropriate. For example, the isomer peak cluster detection step can be performed before the composition estimation step. In that case, the peak detection Process It is only necessary to estimate the composition of only the peaks included in the peak cluster among the peaks detected in step 1, and this does not impede the subsequent processing.

[0055] According to the sialic acid-containing glycan analysis method described in Item 1 and the sialic acid-containing glycan analysis apparatus described in Item 3, even if ion peaks corresponding to some of the expected combinations of binding modes for some specific types of sialic acids are not detected among sialic acid-containing glycans in which the glycan composition other than sialic acid and the number of sialic acids contained are the same but the sialic acid binding mode and type are different, it is possible to accurately narrow down and present to the user candidate compositions of sialic acid-containing glycans containing those specific types of sialic acids. This improves the efficiency of actual measurement work such as MS / MS analysis for verifying whether the predicted candidate compositions of sialic acid-containing glycans are valid, and the analysis of the data collected thereby, allowing for faster and more accurate structural analysis of sialic acid-containing glycans.

[0056] (Item 2) In the method for analyzing sialic acid-containing sugar chains according to item 1, the peak cluster detection step In Attempt to detect isomer peak clusters and obtain isomer peak cluster information It can be found from Sialic acid The type of information set in the search condition setting step Glycan search conditions Regarding In addition The sugar chain composition is estimated in the composition estimation step. execution do It can be said that

[0057] According to the sialic acid-containing glycan analysis method described in item 2, even if a sample contains a sialic acid-containing glycan containing a type of sialic acid that the user has not anticipated in advance, the structure of the sialic acid-containing glycan can be analyzed. [Explanation of symbols]

[0058] 1...Mass spectrometry section 2...Analysis control unit 3...Data analysis section 30...Data storage section 31...Peak detector 32...Glycan search condition setting section 320...Glycan search condition storage section 33...Isomeric peak cluster detection section 34...Glycan composition estimation section 35...Glycan composition filtering section 36...Glycan composition candidate list creation section 37...Display processing unit 38...Precursor ion selection acceptance unit 4...Input section 5...Display section

Claims

1. An analytical method for analyzing a sialic acid-containing sugar chain based on mass spectrum data obtained by mass spectrometry of a sample containing a sialic acid-containing sugar chain that has been modified specifically to a sialic acid binding mode or a molecule modified by said sugar chain, comprising: a search condition setting step for setting glycan search conditions; a peak detection step of detecting a representative peak for each isotope peak cluster from the mass spectrum data; a composition estimation step of estimating the glycan composition of each representative peak detected in the peak detection step in accordance with the glycan search conditions to obtain glycan composition candidates; a peak cluster detection step of detecting isomeric peak clusters including a plurality of peaks that are presumed to have the same number of sialic acids and the same sugar chain composition other than sialic acid from the representative peaks detected in the peak detection step; a glycan composition filtering step of selecting the glycan composition candidates by applying predetermined constraints to each peak contained in the isomer peak cluster, which are set based on the mass-to-charge ratio of each peak contained in the isomer peak cluster, regarding the number of sialic acids contained, the number of bonding modes of sialic acids, and the type of sialic acid, and the identity of the glycan composition other than sialic acid; a display step of creating and displaying a list of the glycan composition candidates in a manner that allows visual distinction between the glycan composition candidates selected by the glycan composition filtering step and other glycan composition candidates; A method for analyzing sialic acid-containing sugar chains comprising:

2. 2. The method for analyzing sialic acid-containing glycans according to claim 1, wherein detection of an isomer peak cluster is attempted in the peak cluster detection step, and information on the type of sialic acid obtained from the isomer peak cluster information obtained as a result thereof is added to the glycan search conditions set in the search condition setting step, and then estimation of the glycan composition in the composition estimation step is performed.

3. An analytical device for analyzing a sialic acid-containing sugar chain based on mass spectrum data obtained by mass spectrometry of a sample containing a sialic acid-containing sugar chain that has been modified specifically to a sialic acid binding mode or a molecule modified by said sugar chain, comprising: a search condition setting unit that accepts the specification of glycan search conditions by a user and sets the glycan search conditions; a peak detection unit that detects a representative peak for each isotope peak cluster from the mass spectrum data; a composition estimation unit that estimates the glycan composition of each representative peak detected by the peak detection unit in accordance with the glycan search conditions to obtain glycan composition candidates; a peak cluster detection unit that detects isomeric peak clusters including a plurality of peaks that are presumed to have the same number of sialic acids and the same sugar chain composition other than sialic acid from the representative peaks detected by the peak detection unit; a glycan composition filtering unit that selects the glycan composition candidates by applying, to each peak included in the isomer peak cluster, predetermined constraints regarding the number of sialic acids contained, the number of bonding modes of sialic acids, and the type of sialic acid, and the identity of the glycan composition other than sialic acid, which are set based on the mass-to-charge ratio of each peak included in the isomer peak cluster; a display processing unit that creates and displays a list of the glycan composition candidates in a manner that allows visual distinction between the glycan composition candidates selected by the glycan composition filtering unit and other glycan composition candidates; A sialic acid-containing sugar chain analysis device comprising:

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