LC-MSMS-based complex glycopeptide analysis method and application thereof

Abstract

The invention provides an LC-MSMS-based complex glycopeptide analysis method and application thereof, and provides a new analysis model for qualitative and relative quantitative analysis of complex glycoprotein by utilizing an LC-MSMS means. The model comprises a characteristic ion comparison module, an MS1 information acquisition module, a glycoform judgment module and a glycoform proportion calculation module. According to the method, sample pretreatment conditions are optimized, more suitable key mass spectrum parameters are adjusted, and an analysis model which is more credible compared with commercially available peptide map analysis software is established, so that analysis of complex glycoprotein, including multi-dimensional calculation of glycosylation sites, glycosylation proportions, qualitative analysis and relative quantitative analysis, is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of biological detection, and in particular relates to a complex glycopeptide analysis method based on LC-MSMS and an application thereof. Background Art

[0002] Glycoprotein is a protein containing oligosaccharide chains, which are connected by covalent bonds. The oligosaccharide chains are usually linked to the protein through glycosylation during co-translational modification or post-translational modification. When analyzing glycoproteins, conventional pre-treatment conditions, mass spectrometry parameter acquisition, and commercially available peptide map analysis databases have large differences in the sugar content ratio, glycoform type, and relative quantification of some glycosylation sites in some complex glycoproteins. Therefore, it is necessary to optimize a series of pre-treatments, source parameters, etc. for the above problems, and to propose a new glycopeptide analysis model.

[0003] Glycopeptide mass spectrometry detection and analysis is an important technology for studying the glycosylation modification of glycoproteins. Among them, mass spectrometry is highly efficient and sensitive, and is crucial in the analysis of glycopeptides.

[0004] Existing technologies and analytical strategies pose challenges to the analysis of complex glycoproteins. In the analysis of complex glycoproteins, the problem is that conventional pretreatment methods, equipment parameters provided by manufacturers, and commercially available analytical software cannot provide more reliable specific information on N-sugar modification sites, nor can they provide relatively quantitative and qualitative results.

[0005] Therefore, developing an analytical method or model that uses better sample pretreatment conditions, adjusts more suitable key mass spectrometry parameters, and is more credible than commercially available peptide mapping software (with sugar libraries) has important application prospects for the analysis of complex glycoproteins. Summary of the invention

[0006] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a complex glycopeptide analysis method based on LC-MSMS and its application. The present invention adopts more optimal sample pretreatment conditions, adjusts more suitable key mass spectrometry parameters, and has a more credible analysis model compared to commercially available peptide map analysis software (with sugar library), thereby achieving the analysis of complex glycoproteins, including multi-dimensional calculations of glycosylation sites, glycosylation ratios, qualitative analysis, and relative quantitative analysis.

[0007] In order to achieve the purpose of the invention, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a glycopeptide analysis method, the method comprising:

[0009] (1) Based on the fixed characteristic ion information and Y1 ion information of the glycopeptide, determine the cross-retention time (RT) that meets all search conditions, and lock the position of the sugar modification corresponding to the peptide to be identified in the extracted ion chromatogram (SIC spectrum);

[0010] (2) After determining that the fixed characteristic ions satisfy the screening conditions, select the spectral information with consistent retention time (RT), extract the corresponding MS2 information, determine that the information contained in MS2 meets the screening conditions, and search for the MS1 information corresponding to MS2;

[0011] (3) According to the MS1 information provided in MS2, the MS1 spectrum corresponding to MS2 is extracted, and the monoisotopic m / z value corresponding to MS1 is determined, which is used to calculate the monoisotopic peak molecular weight corresponding to the glycopeptide information. The calculated result is compared with the monoisotopic molecular weight of the peptide segment and the theoretical monoisotopic peak molecular weight result library in the sugar library to determine the corresponding glycoform;

[0012] (4) Count the glycoform information corresponding to the peptide segment, record the corresponding MS1 m / z intensity value (intensity), and calculate the glycoform ratio.

[0013] The present invention uses LC-MSMS means to propose a new analysis model for the qualitative and relative quantitative analysis of complex glycoproteins. Compared with the current analysis method, the conventional pre-treatment means, the equipment parameters provided by the manufacturer, the instrument method, and the supporting analysis software are used to analyze the sample, but in the current analysis method, for the glycosylation site and N-sugar modification type of complex glycoproteins, it is impossible to give more reliable N-sugar modification site specific information, and even the sugar type results given are inconsistent with the actual, on this basis, it is impossible to give the relative quantitative and qualitative results of the N-glycosylation modification of a certain site. The present invention achieves the analysis of complex glycoproteins by targeting sample pre-treatment conditions, adjusting more suitable key mass spectrometry parameters and new analysis models and processes, including multi-dimensional calculations of glycosylation sites, glycosylation ratios, qualitative analysis and relative quantitative analysis.

[0014] In the present invention, in step (1), the fixed characteristic ion information of the glycopeptide includes that shown in Table 1.

[0015] Table 1

[0016]

[0017] Preferably, in step (1), the Y1 ion information refers to the m / z value of the peptide to be identified and HexNAc (203.079).

[0018] Preferably, in step (1), the Y1 ion information includes the sum m of the monoisotopic molecular weights of the peptide to be identified and HexNAc and the possible charge number z.

[0019] In the present invention, the Y1 ion information comes from the automatic calculation of the software based on the amino acid sequence of the peptide to be identified.

[0020] Preferably, in step (2), the MS2 information includes: fixed characteristic ions of glycopeptides, Y1 ions and series Y / B ion information.

[0021] Preferably, in step (2), the MS1 information includes: the specific value of m / z and the specific value of z of the glycopeptide.

[0022] Preferably, in step (3), the formula for calculating the monoisotopic peak molecular weight corresponding to the glycopeptide information includes:

[0023] m / z×zz×1.00783=glycopeptide monoisotopic peak molecular weight

[0024] Wherein, m / z represents the mass-to-charge ratio, the specific value of the first cluster of monoisotopic peaks in the MS1 spectrum; m represents the molecular weight; z represents the charge number, which is an integer; and 1.00783 represents the monoisotopic molecular weight of hydrogen (H).

[0025] Preferably, the molecular weight of the glycoform is calculated by deducting the monoisotopic molecular weight of the corresponding peptide segment from the monoisotopic peak molecular weight of the glycopeptide.

[0026] Preferably, in step (3), the standard for determining the corresponding glycoform is: if the deviation range between the inferred calculated glycoform molecular weight and the theoretical molecular weight of a glycoform in the glycogen library is within ±20 ppm, it is determined to be the glycoform.

[0027] Preferably, in step (4), the formula for calculating the glycoform ratio is:

[0028] Strength 1 / ∑strength*100%;

[0029] Among them, intensity 1 represents the m / z intensity of a certain glycoform of the glycopeptide, and ∑ intensity represents the sum of the m / z intensities of all glycoforms of the glycopeptide corresponding to the glycopeptide.

[0030] In a second aspect, the present invention provides a glycopeptide analysis model, the model comprising:

[0031] The characteristic ion comparison module determines the cross-retention time (RT) that meets all search conditions based on the fixed characteristic ion information and Y1 ion information of the glycopeptide, and locks the position of the sugar modification corresponding to the peptide to be tested in the extracted ion chromatogram (SIC spectrum);

[0032] The MS1 information acquisition module selects the spectral information with the same retention time under the conditions of the fixed characteristic ions that meet the screening, extracts the corresponding MS2 information, determines that the information contained in the MS2 meets the screening conditions, and searches for the MS1 information corresponding to the MS2;

[0033] The glycoform determination module extracts the MS1 spectrum corresponding to MS2 according to the MS1 information provided in MS2, determines the monoisotopic m / z value corresponding to MS1, and uses it to calculate the monoisotopic peak molecular weight corresponding to the glycopeptide information. The corresponding glycoform is determined by comparing the calculated result with the monoisotopic molecular weight of the peptide segment and the theoretical monoisotopic peak molecular weight result library in the sugar library;

[0034] The glycoform ratio calculation module counts the glycoform information corresponding to the peptide segment, records the intensity of the corresponding MS1 m / z, and calculates the glycoform ratio.

[0035] Preferably, in the characteristic ion comparison module, the Y1 ion refers to the m / z value of the peptide to be identified and HexNAc (203.079).

[0036] Preferably, in the characteristic ion comparison module, the Y1 ion information is automatically calculated by the software based on the amino acid sequence of the peptide to be identified, and the Y1 ion information includes the sum m of the monoisotopic molecular weights of the peptide to be identified and HexNAc and the possible charge number z.

[0037] Preferably, in the MS1 information acquisition module, the MS2 information includes: fixed characteristic ions of glycopeptides, Y1 ions and series Y / B ion information.

[0038] Preferably, in the MS1 information acquisition module, the MS1 information includes: a specific value of m / z and a specific value of z of the glycopeptide.

[0039] Preferably, in the glycoform determination module, the formula for calculating the monoisotopic peak molecular weight corresponding to the glycopeptide information includes:

[0040] m / z×zz×1.00783=glycopeptide monoisotopic peak molecular weight

[0041] Wherein, m / z represents the mass-to-charge ratio, the specific value of the first cluster of monoisotopic peaks in the MS1 spectrum; m represents the molecular weight; z represents the charge number, which is an integer; and 1.00783 represents the monoisotopic molecular weight of H.

[0042] Preferably, the molecular weight of the glycoform is calculated by deducting the monoisotopic molecular weight of the corresponding peptide segment from the monoisotopic peak molecular weight of the glycopeptide.

[0043] Preferably, in the glycoform judgment module, the standard for judging the corresponding glycoform is: if the deviation range between the inferred and calculated glycoform molecular weight and the theoretical molecular weight of a glycoform in the glycogen library is within ±20ppm, it is judged to be the glycoform.

[0044] Preferably, in the glycoform ratio calculation module, the formula for calculating the glycoform ratio is:

[0045] Strength 1 / ∑strength*100%;

[0046] Among them, intensity 1 represents the m / z intensity of a certain glycoform of the glycopeptide, and ∑ intensity represents the sum of the m / z intensities of all glycoforms of the glycopeptide corresponding to the glycopeptide.

[0047] In a third aspect, the present invention provides a complex glycopeptide analysis method based on LC-MSMS, the method comprising:

[0048] (S1) denaturing, alkylating and enzymatically digesting the glycopeptide sample to be tested;

[0049] (S2) performing LC-MSMS analysis on the digested samples;

[0050] (S3) Based on the glycopeptide analysis method described in the first aspect, the detection results are analyzed and the glycoform ratio is calculated.

[0051] Preferably, in step (S1), the enzymatic digestion is carried out in a solution.

[0052] Preferably, the enzyme digestion system of the solution digestion is 20-50 mM Tris-HCl, with a pH of 7.5-8.0.

[0053] Among them, 20-50mM Tris-HCl can be, for example, 20mM, 25mM, 30mM, 35mM, 40mM, 45mM or 50mM, etc. The pH of 7.5-8.0 can be, for example, 7.5, 7.6, 7.7, 7.8, 7.9 or 8.0, etc.

[0054] Preferably, the initial addition amount of the enzyme during the solution enzymatic digestion process is protein: enzyme = (20-25): 1, W / W; for example, it can be 20:1, 21:1, 22:1, 23:1, 24:1 or 25:1, etc.

[0055] Preferably, in step (S2), the liquid chromatography conditions in the LC-MSMS analysis include:

[0056] The elution was performed by gradient elution; mobile phase A was 0.1-0.2% formic acid aqueous solution, mobile phase B was 0.1-0.2% formic acid acetonitrile solution; column temperature was 58-62°C, detection wavelength was 214±5nm, injection volume was 2-20μL, flow rate was 0.2-0.3mL / min, and elution conditions included:

[0057] In the first 0-3 minutes, the volume fraction of mobile phase B was 3-4%, and the rest was mobile phase A;

[0058] From 3 to 85 minutes, the volume fraction of mobile phase B changed from 3-4% to 32-33% at a constant rate, and the rest was mobile phase A;

[0059] At 85-90 minutes, the volume fraction of mobile phase B changed from 32-33% to 90-91% at a constant rate, and the rest was mobile phase A;

[0060] At 90-95 min, the volume fraction of mobile phase B was 90-91%, and the rest was mobile phase A;

[0061] At 95-95.1 min, the volume fraction of mobile phase B changed from 90-91% to 3-4% at a constant rate, and the rest was mobile phase A;

[0062] From 95.1 to 105 min, the volume fraction of mobile phase B was 3-4%, and the rest was mobile phase A.

[0063] Preferably, in step (S2), the source parameter conditions in the LC-MSMS analysis are: auxiliary gas temperature AT = 350°C, ion transfer tube temperature CT = 250°C.

[0064] In a preferred embodiment of the present invention, in step (S2), the liquid chromatography conditions in the LC-MSMS analysis are shown in Table 2.

[0065] Table 2

[0066]

[0067] In a preferred embodiment of the present invention, in step (S2), the mass spectrometry conditions in the LC-MSMS analysis are shown in Table 3.

[0068] Table 3

[0069]

[0070] In a fourth aspect, the present invention provides the application of the glycopeptide analysis method described in the first aspect, the glycopeptide analysis model described in the second aspect, or the complex glycopeptide analysis method based on LC-MSMS described in the third aspect in glycopeptide analysis.

[0071] The numerical range described in the present invention not only includes the point values ​​listed above, but also includes any point values ​​between the above numerical ranges that are not listed. Due to space limitations and for the sake of simplicity, the present invention no longer exhaustively lists the specific point values ​​included in the range.

[0072] Compared with the prior art, the present invention has the following beneficial effects:

[0073] (1) Provide new analytical strategies and models for complex glycoproteins and conduct multi-dimensional verification.

[0074] (2) Provide more accurate N-glycosylation site information, glycopeptide qualitative analysis, and N-sugar relative ratio analysis for complex glycoproteins.

[0075] (3) Avoid erroneous glycoform information and missed glycoform information generated by the analysis process of commercially available software. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 It is the software that provides glycopeptide MS2 information.

[0077] Figure 2 is the characteristic ion extraction chromatogram.

[0078] Figure 3 It is the MS2 spectrum information of glycopeptide.

[0079] Figure 4 It is the MS1 spectrum information corresponding to MS2.

[0080] Figure 5 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0081] The technical solution of the present invention is further described below by specific implementation methods. It should be understood by those skilled in the art that the embodiments are only to help understand the present invention and should not be regarded as specific limitations of the present invention.

[0082] If no specific techniques or conditions are specified in the examples, the techniques or conditions described in the literature in the field or the product instructions are used. If no manufacturer is specified for the reagents or instruments used, they are all conventional products that can be purchased through regular channels.

[0083] Comparative Example 1

[0084] This comparative example provides a glycopeptide analysis method, comprising the following steps:

[0085] (1) Denaturation reduction: Take an appropriate amount of sample and add it to 6 M guanidine hydrochloride, 20 mM Tris-HCl (pH 7.8), then add 1 M DTT to a final concentration of 20 mM, react at 56 °C for 30 min, and cool to room temperature.

[0086] (2) Alkylation: Add 1 M IAM to a final concentration of 50 mM and react at room temperature in the dark for 45 min.

[0087] (3) Liquid replacement: The sample was replaced into Tris-HCl (pH 7.8) using a 10KD flat membrane.

[0088] (4) The sample was directly processed on the flat membrane, and the enzyme digestion ratio was 25:1 (w / w) at 37°C for 2-6 h.

[0089] (5) After the digestion, the sample is acidified and loaded onto the machine for data acquisition using LC-MSMS and data analysis using the supporting analysis software.

[0090] (6) Among the ion source parameters, the auxiliary gas temperature (AT) is 280°C and the ion transfer tube temperature (CT) is 270°C.

[0091] The liquid chromatography conditions in the LC-MSMS analysis are shown in Table 2 (the same as the aforementioned Table 2).

[0092] Table 2

[0093]

[0094] The mass spectrometry conditions in the LC-MSMS analysis are shown in Table 3 (same as the aforementioned Table 3).

[0095] Table 3

[0096]

[0097]

[0098] Experimental results: After the sample was collected, no reliable result information for the peptide was found in the database search.

[0099] From the results of Comparative Example 1, it can be seen that (see Figure 1, providing glycosylation modification results for the peptide segment), the sugar type of the glycopeptide is A4Sg1G2, but the N-sugar modification produced by this cell line cannot contain Sg (Neu5Gc) type sialic acid sugars, and the corresponding Neu5Gc characteristic ions are not found in the MS2 information, and there is no Y1 ion information. Therefore, this information can only prove that the data is glycopeptide information, but it is impossible to determine whether it is the N-sugar modification of the target peptide segment, nor can it obtain what type of glycoform modification it is, that is, the software results have a large deviation. Conventional pre-treatment conditions, mass spectrometry parameter acquisition, and commercially available peptide map analysis databases have large errors in the sugar content ratio, glycoform type, and relative quantification of some glycosylation sites in some complex glycoproteins, and even cannot be identified. Therefore, it is necessary to optimize a series of pre-treatments, source parameters, etc. for the above problems, and to propose a new glycopeptide analysis model.

[0100] Example 1

[0101] This embodiment provides a glycopeptide analysis method, which comprises the following steps:

[0102] (1) Denaturation reduction: Take an appropriate amount of sample and add it to 6 M guanidine hydrochloride, 20 mM Tris-HCl (pH 7.8), then add 1 M DTT to a final concentration of 20 mM, react at 56 °C for 30 min, and cool to room temperature.

[0103] (2) Alkylation: Add 1 M IAM to a final concentration of 50 mM and react at room temperature in the dark for 45 min.

[0104] (3) Liquid exchange: Replace the sample into the corresponding enzyme digestion buffer for enzyme digestion of the sample.

[0105] (4) The enzyme digestion ratio was 25:1 (w / w) and the digestion was carried out at 37°C for 2-6 h.

[0106] (5) After the digestion, the sample was acidified and loaded onto the machine for data acquisition using LC-MSMS, and data analysis was performed using the supporting analysis software. The parameters of LC-MSMS are shown in Tables 2 and 3.

[0107] (6) Among the ion source parameters, the auxiliary gas temperature (AT) is 350°C and the ion transfer tube temperature (CT) is 250°C.

[0108] The data were analyzed using the analysis software provided by the instrument. The experimental results are shown in Table 4 below:

[0109] Table 4

[0110] Modification Modification ratio% A1G0F 0.00 A2G0F 29.89 A2G1F 0.00 A2G2F 11.27 M5 19.95 A2S1G1F 13.33 A2S1G0F 7.32 A2S2F 3.64 Unglycosylated 14.60 Sialyl sugar content 24.29

[0111] The results show that: compared with the results in Comparative Example 1 (no N-sugar modification was found in this peptide), the optimized pre-treatment method and source parameter method can identify the presence of abundant N-sugar modifications on this peptide, and the identified glycopeptide results almost all have MS2 information, providing data support and judgment basis for the reliability and authenticity of the results.

[0112] Example 2

[0113] This example investigates the pretreatment conditions in the analysis method in Example 1. This example adopts the on-membrane enzyme cleavage method. The experimental steps are as follows:

[0114] (1) Denaturation reduction: Take an appropriate amount of sample and add it to 6 M guanidine hydrochloride, 20 mM Tris-HCl (pH 7.8), then add 1 M DTT to a final concentration of 20 mM, react at 56 °C for 30 min, and cool to room temperature.

[0115] (2) Alkylation: Add 1 M IAM to a final concentration of 50 mM and react at room temperature in the dark for 45 min.

[0116] (3) Replacement of solution: Replace the sample with the corresponding enzyme digestion buffer (see Table 5) for sample digestion. Solution digestion uses 10KD vertical membrane replacement, and on-membrane digestion uses 10KD flat membrane replacement.

[0117] (4) Enzyme digestion was performed at a ratio of protein:enzyme = 25:1 (w / w) at 37°C for 4 h. The enzyme digestion scheme is shown in Table 6.

[0118] (5) After the digestion, the sample was acidified and loaded onto the machine, and data was collected by LC-MSMS, and data was analyzed by the supporting analysis software. The parameters of LC-MSMS are shown in Tables 2 and 3.

[0119] (6) Among the ion source parameters, the auxiliary gas temperature (AT) is 280°C and the ion transfer tube temperature (CT) is 270°C.

[0120] The data was analyzed using the analysis software provided by the instrument. The experimental results are shown in Table 5 below:

[0121] Table 5

[0122]

[0123] The experimental conditions corresponding to the experimental condition numbers are shown in Table 6.

[0124] Table 6

[0125]

[0126] According to the results, no reliable glycopeptide results of the target peptide were detected in the A0 experimental group and the A4 experimental group; the data of A1, A2 and A3 proved that the same enzyme cleavage method but different enzyme cleavage solutions had a huge impact on the richness of detectable glycopeptides; in summary, it was proved that the enzyme cleavage method (solution enzyme cleavage and membrane enzyme cleavage) and the type of enzyme cleavage solution were important parameters for the identification of glycopeptides, and the results of this round of optimization showed that the A1 enzyme cleavage condition was the best.

[0127] Example 3

[0128] This example optimizes and investigates the mass spectrometry detection conditions in the analysis method in Example 1, aiming to find universal mass spectrometry parameter information for the analysis of complex glycopeptides. The auxiliary gas temperature (AT) and ion transfer tube temperature (CT) of glycopeptides were investigated, and the investigation contents are shown in Table 7.

[0129] Table 7

[0130] Experiment number Ion transfer tube temperature CT / ℃ Auxiliary gas temperature AT / ℃ B1 250 250 B2 350 350 B3 250 350 B4 350 250

[0131] (1) Denaturation reduction: Take an appropriate amount of sample and add it to 6 M guanidine hydrochloride, 20 mM Tris-HCl (pH 7.8), then add 1 M DTT to a final concentration of 20 mM, react at 56 °C for 30 min, and cool to room temperature.

[0132] (2) Alkylation: Add 1 M IAM to a final concentration of 50 mM and react at room temperature in the dark for 45 min.

[0133] (3) Liquid exchange: The sample was replaced with 20 mM Tris-HCl pH 7.8 using a 10KD vertical membrane for enzyme digestion of the sample.

[0134] (4) Enzymatic digestion was performed in 20 mM Tris-HCl pH 7.8 at a ratio of protein: enzyme = 25:1 (w / w) at 37°C for 4 h.

[0135] (5) After the digestion, the sample was acidified and loaded onto the machine for data acquisition using LC-MSMS, and data analysis was performed using the supporting analysis software. The parameters of LC-MSMS are shown in Tables 2 and 3.

[0136] The data were analyzed using the analysis software provided by the instrument. The experimental results are shown in Table 8.

[0137] Table 8

[0138]

[0139] Compared with non-sialylated N-sugars, sialic acid sugars are negatively charged. For glycopeptides with sialic acid sugars, they have the characteristic of lower ionization efficiency, so this type of glycoform analysis is used as a representative, and the main glycoform results are examined at the same time, and the results are compared and analyzed. Specific results are shown in Table 8. According to the results shown in Table 8, the number of glycoforms under the B1 condition is obviously small, and the A2S2F in the B2 and B4 results is 0.00%, so the subsequent data analysis model mainly relies on the data generated by the B3 source parameter conditions (i.e., ion transfer tube temperature = 250°C, auxiliary gas temperature = 350°C) for analysis. The optimized glycopeptide results of B3 almost all have MS2 information, so the optimized source parameter conditions can better reflect the complex glycoform results and lay the foundation for further analysis of glycoforms.

[0140] The new model designed in the present invention is used to analyze the data collected by B3 in this embodiment. The analysis steps are as follows:

[0141] (1) Based on the partial ion information and Y1 ion in the glycopeptide characteristic ions (Table 1, the same as Table 1 above), determine the crossover RT (min) that meets all search conditions and lock the position of the sugar modification corresponding to the peptide in the SIC spectrum. Example Figure 2 , the cross RT corresponds to the graph information marked as ① in the figure.

[0142] (2) After determining that the characteristic ion conditions that meet the screening are met, select the spectrum information with consistent RT, extract its corresponding MS2 information, determine the accuracy of the screening conditions, and search for the MS1 information corresponding to MS2. See the example for an example. Figure 3 (corresponding Figure 2 The MS2 information marked as ① is extracted in the figure. The spectrum results show that the figure is an MS2 spectrum that meets all the screening conditions, and according to the spectrum information, the corresponding MS1 information is determined ( Figure 3 marked in ).

[0143] (3) According to the MS1 information provided in MS2, the MS1 spectrum corresponding to MS2 is extracted to determine the specific m / z value and the z value of the monoisotopic peak corresponding to MS1, which are used to calculate the molecular weight of the monoisotopic peak corresponding to the glycopeptide information.

[0144] (4) For example, see Figure 4According to the value of the monoisotopic peak position marked in the figure, m / z=1245.01, z=4, the corresponding glycopeptide monoisotopic peak molecular weight is calculated as: 1245.01*4-4*1.00783=4976.0087, and the known peptide monoisotopic molecular weight is 2916.2753, then the monoisotopic molecular weight of the sugar modification corresponding to the peptide is 4976.0087-2916.2753=2059.7334, which is close to the theoretical monoisotopic peak molecular weight of A2S1G1F glycoform (2059.7349). The deviation calculated based on this is -0.31ppm, and it is judged that this information is a known peptide with A2S1G1F glycoform.

[0145] Table 1

[0146]

[0147] Experimental results: The analysis results using the analysis model of the present invention are shown in Table 9

[0148] Table 9

[0149]

[0150] According to the data analysis of Table 9 and B3 of Table 8, the result information of A2G1F-a and A2G1F-b analyzed in Table 9, the MS1 and MS2 information of this glycoform is good, but the commercially available analysis software does not give the result. At the same time, since the analysis model is based on the results of the joint extraction of MS1 and MS2 information of glycopeptides, the result information provided by the analysis model is relatively more comprehensive, and the authenticity and reliability of the data are more convincing.

[0151] In summary, for complex glycoproteins, at the peptide level, the present invention optimizes the pretreatment method, source parameter conditions, MS2 parameter information and constructs a new calculation model (such as Figure 5 Compared with the common calculation process, it can provide more accurate, comprehensive and reliable glycopeptide data results, and provide a new analysis model for the later complex glycopeptide data analysis.

[0152] The applicant declares that the above is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention shall fall within the protection scope and disclosure scope of the present invention.

Claims

1. A glycopeptide analysis method, characterized in that: The method comprises: (1) Based on the fixed characteristic ion information and Y1 ion information of the glycopeptide, determine the cross-retention time that meets all search conditions and lock the position of the sugar modification corresponding to the peptide to be identified in the extracted ion chromatogram; (2) After determining that the fixed characteristic ions satisfy the screening conditions, select the spectral information with the same retention time, extract the corresponding MS2 information, determine that the information contained in MS2 meets the screening conditions, and search for the MS1 information corresponding to MS2; (3) According to the MS1 information provided in MS2, the MS1 spectrum corresponding to MS2 is extracted to determine the monoisotopic m / z value corresponding to MS1, which is used to calculate the monoisotopic peak molecular weight corresponding to the glycopeptide information. The calculated result is compared with the monoisotopic molecular weight of the peptide segment and the theoretical monoisotopic peak molecular weight result library in the sugar library to determine the corresponding glycoform; (4) Count the glycoform information corresponding to the peptide segment, record the corresponding MS1 m / z intensity value, and calculate the glycoform ratio.

2. The glycopeptide analysis method according to claim 1, characterized in that In step (1), the Y1 ion information refers to the m / z value of the peptide to be identified and HexNAc (203.079); Preferably, in step (1), the Y1 ion information includes the sum m of the monoisotopic molecular weights of the peptide to be identified and HexNAc and the possible charge number z.

3. The glycopeptide analysis method according to claim 1 or 2, characterized in that: In step (2), the MS2 information includes: fixed characteristic ions, Y1 ions and series Y / B ion information of glycopeptides; Preferably, in step (2), the MS1 information includes: the specific value of m / z and the specific value of z of the glycopeptide.

4. The glycopeptide analysis method according to any one of claims 1 to 3, characterized in that: In step (3), the formula for calculating the monoisotopic peak molecular weight corresponding to the glycopeptide information includes: m / z×zz×1.00783=glycopeptide monoisotopic peak molecular weight Wherein, m / z represents the mass-to-charge ratio, the specific value of the first cluster of monoisotopic peaks in the MS1 spectrum; m represents the molecular weight; z represents the charge number, which is an integer; 1.00783 represents the monoisotopic molecular weight of hydrogen; Preferably, the molecular weight of the glycoform calculated by inference is the molecular weight of the monoisotopic peak of the glycopeptide minus the monoisotopic molecular weight of the corresponding peptide segment; Preferably, in step (3), the standard for determining the corresponding glycoform is: if the deviation range between the inferred calculated glycoform molecular weight and the theoretical molecular weight of a glycoform in the glycogen library is within ±20 ppm, it is determined to be the glycoform.

5. The glycopeptide analysis method according to any one of claims 1 to 4, characterized in that: In step (4), the formula for calculating the glycoform ratio is: Strength 1 / ∑strength*100%; Among them, intensity 1 represents the m / z intensity of a certain glycoform of the glycopeptide, and ∑ intensity represents the sum of the m / z intensities of all glycoforms of the glycopeptide corresponding to the glycopeptide.

6. A glycopeptide analysis model, characterized in that: The model includes: The characteristic ion comparison module determines the cross-retention time that meets all search conditions based on the fixed characteristic ion information and Y1 ion information of the glycopeptide, and locks the position of the sugar modification corresponding to the peptide to be tested in the extracted ion chromatogram; The MS1 information acquisition module selects the spectral information with the same retention time under the conditions of the fixed characteristic ions that meet the screening, extracts the corresponding MS2 information, determines that the information contained in the MS2 meets the screening conditions, and searches for the MS1 information corresponding to the MS2; The glycoform determination module extracts the MS1 spectrum corresponding to MS2 according to the MS1 information provided in MS2, determines the monoisotopic m / z value corresponding to MS1, and uses it to calculate the monoisotopic peak molecular weight corresponding to the glycopeptide information. The corresponding glycoform is determined by comparing the calculated result with the monoisotopic molecular weight of the peptide segment and the theoretical monoisotopic peak molecular weight result library in the sugar library; The glycoform ratio calculation module counts the glycoform information corresponding to the peptide segment, records the corresponding MS1 m / z intensity, and calculates the glycoform ratio.

7. The glycopeptide analysis model according to claim 6, characterized in that In the characteristic ion comparison module, the Y1 ion information refers to the m / z value of the peptide to be identified and HexNAc (203.079); Preferably, in the characteristic ion comparison module, the Y1 ion information is automatically calculated by the software based on the amino acid sequence of the peptide to be identified, and the Y1 ion information includes the sum m of the monoisotopic molecular weights of the peptide to be identified and HexNAc and the possible charge number z; Preferably, in the MS1 information acquisition module, the MS2 information includes: fixed characteristic ions, Y1 ions and series Y / B ion information of glycopeptides; Preferably, in the MS1 information acquisition module, the MS1 information includes: a specific value of m / z and a specific value of z of the glycopeptide; Preferably, in the glycoform determination module, the formula for calculating the monoisotopic peak molecular weight corresponding to the glycopeptide information includes: m / z×zz×1.00783=glycopeptide monoisotopic peak molecular weight Wherein, m / z represents the mass-to-charge ratio, the specific value of the first cluster of monoisotopic peaks in the MS1 spectrum; m represents the molecular weight; z represents the charge number, which is an integer; 1.00783 represents the monoisotopic molecular weight of hydrogen; Preferably, the molecular weight of the glycoform calculated by inference is the molecular weight of the monoisotopic peak of the glycopeptide minus the monoisotopic molecular weight of the corresponding peptide segment; Preferably, in the sugar form judgment module, the standard for judging the corresponding sugar form is: if the deviation range between the inferred and calculated sugar form molecular weight and the theoretical molecular weight of a sugar form in the sugar library is within ±20ppm, it is judged to be the sugar form; Preferably, in the glycoform ratio calculation module, the formula for calculating the glycoform ratio is: Strength 1 / ∑strength*100%; Among them, intensity 1 represents the m / z intensity of a certain glycoform of the glycopeptide, and ∑ intensity represents the sum of the m / z intensities of all glycoforms of the glycopeptide corresponding to the glycopeptide.

8. A complex glycopeptide analysis method based on LC-MSMS, characterized in that: The method comprises: (S1) denaturing, alkylating and enzymatically digesting the glycopeptide sample to be tested; (S2) performing LC-MSMS analysis on the digested samples; (S3) Analyzing the detection results based on the glycopeptide analysis method according to any one of claims 1 to 5, and calculating the glycoform ratio.

9. The complex glycopeptide analysis method based on LC-MSMS according to claim 8, characterized in that: Step (S1), the enzymatic digestion is carried out by solution digestion; Preferably, the enzyme digestion system of the solution digestion is 20-50 mM Tris-HCl, pH 7.5-8.0; Preferably, the initial amount of enzyme added during the solution digestion process is protein: enzyme = (20-25): 1, W / W; Preferably, in step (S2), the liquid chromatography conditions in the LC-MSMS analysis include: The elution was performed by gradient elution; mobile phase A was 0.1-0.2% formic acid aqueous solution, mobile phase B was 0.1-0.2% formic acid acetonitrile solution; column temperature was 58-62°C, detection wavelength was 214±5nm, injection volume was 2-20μL, flow rate was 0.2-0.3mL / min, and elution conditions included: In the first 0-3 minutes, the volume fraction of mobile phase B was 3-4%, and the rest was mobile phase A; From 3 to 85 minutes, the volume fraction of mobile phase B changed from 3-4% to 32-33% at a constant rate, and the rest was mobile phase A; At 85-90 minutes, the volume fraction of mobile phase B changed from 32-33% to 90-91% at a constant rate, and the rest was mobile phase A; At 90-95 min, the volume fraction of mobile phase B was 90-91%, and the rest was mobile phase A; At 95-95.1 min, the volume fraction of mobile phase B changed from 90-91% to 3-4% at a constant rate, and the rest was mobile phase A; From 95.1 to 105 min, the volume fraction of mobile phase B was 3-4%, and the rest was mobile phase A; Preferably, in step (S2), the source parameter conditions in the LC-MSMS analysis are: auxiliary gas temperature AT = 350°C, ion transfer tube temperature CT = 250°C.

10. Use of the glycopeptide analysis method according to any one of claims 1 to 5, the glycopeptide analysis model according to claim 6 or 7, or the complex glycopeptide analysis method based on LC-MSMS according to claim 8 or 9 in glycopeptide analysis.

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