Method for identifying sugar chain types of microorganisms

Abstract

To provide a microbial serotyping method capable of clarifying the repeated structure of sugar chains of microorganisms such as pathogenic bacteria by analysis of the analytical result obtained by mass spectrometry, directly identifying bacterial serotype regardless of antigen-antibody reaction, and displaying the result in an easy-to-understand manner.SOLUTION: The microbial serotyping method includes: (1)a step of mass spectrometry process in which the mass spectrum is acquired by performing the mass spectrometry using a mass spectrometer capable of acquiring accurate mass information of a test sample containing microorganisms to acquire mass information of each peak detected in the mass spectrum; (2) a discrimination step to discriminate the serotype of microorganisms based on the unit chemistry structure of the assumed microorganisms; and (3) a display step of displaying the result discriminated from the discriminating step in a display mode in which bands are displayed at different positions corresponding to the serotype.SELECTED DRAWING: Figure 8

Description

[Technical field]

[0001] The present invention relates to a method for distinguishing the sugar chain type of a microorganism. [Background technology]

[0002] Food poisoning can occur due to various reasons when food is ingested, and food poisoning caused by bacteria is called bacterial food poisoning. Bacterial food poisoning accounts for approximately 70-90% of all food poisoning cases, and many bacteria are known to cause bacterial food poisoning, such as Salmonella and enterohemorrhagic Escherichia coli.

[0003] For example, enterohemorrhagic E. coli infection is caused by infection with E. coli such as O157 that produces verotoxins, and its symptoms are primarily gastrointestinal symptoms. Typical symptoms include nausea and abdominal pain, often accompanied by diarrhea. Therefore, when such symptoms develop and there is a possibility of food poisoning, it is extremely important to identify the cause, and if it is caused by bacteria, to quickly and accurately identify the bacteria in order to cure the patient and prevent secondary infections.

[0004] There are two known methods for identifying pathogenic bacteria: immunological testing and genetic testing. When a person is infected with a microorganism such as a bacterium or a virus, the components of the microorganism, related toxins, metabolic substances, etc. act as antigenic stimuli in the body, and antibodies against the microorganism are produced. In other words, microorganism-related antigens and antibodies against them are present in the body of an infected person. Immunological testing is a method of directly or indirectly examining the presence of bacteria, etc. by detecting antigens and antibodies present in the body using an antigen-antibody reaction (for example, Patent Document 1).

[0005] On the other hand, known genetic tests include a PCR-based multiplex PCR method (E. coli O-genotyping PCR) and a BLAST search method (SerotypeFinder) using the wzx / wzy and wzm / wzt sequence sets (e.g., Non-Patent Document 1). [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2008-304275 A [Patent Document 2] JP 201790228 A [Non-patent literature]

[0007] [Non-Patent Document 1] Japanese Journal of Bacteriology 71(4):209-215,2016 [Non-Patent Document 2] J.Am.Soc.Mass Spectrom.25:1346-1355(2014) Summary of the Invention [Problem to be solved by the invention]

[0008] However, false negative and false positive results are inevitable in immunological tests, and especially in infectious disease tests, these false negative and false positive results can lead to serious consequences for patients. In addition, in genetic testing, genomic information may not yet be fully known.

[0009] Meanwhile, a method has been proposed in which a polymer having a unit chemical structure is measured by mass spectrometry, and the unit chemical structure and terminal structure are analyzed from the obtained mass spectrometry results (for example, Non-Patent Document 2 and Patent Document 2). Since bacteria have glycans having unit chemical structures, mass spectrometry of bacterial glycans makes it possible to eliminate false negative and false positive results that are unavoidable in conventional immunological tests.

[0010] However, unless the analyst is well versed in mass spectrometry, it is difficult to interpret the results of mass spectrometry, and a method for easily identifying the serotype of bacteria, etc. from the results has been demanded.

[0011] The present inventors have analyzed the results of analysis obtained by mass spectrometry to clarify the repeating structures of glycans in microorganisms such as pathogenic bacteria, and have discovered a method for directly identifying the serotype of bacteria without relying on antigen-antibody reactions and displaying the results in an easily understandable manner, thereby completing the present invention.

[0012] That is, the present invention (1) a mass spectrometry step of obtaining a mass spectrum by mass spectrometry of a test sample containing a microorganism using a mass spectrometer capable of obtaining accurate mass information, and obtaining mass information of each peak detected in the mass spectrum; (2) a discrimination step of discriminating the serotype of the microorganism based on the assumed unit chemical structure of the microorganism; (3) a display step of displaying the results of the discrimination step in a display format in which bands are displayed at different positions corresponding to serotypes; and a method for determining the serotype of a microorganism, comprising: Effect of the Invention

[0013] According to the present invention, by analyzing the analytical results obtained by mass spectrometry, it is possible to clarify the repeating structures of the glycans of microorganisms such as pathogenic bacteria, directly identify the serotype of the bacteria without relying on antigen-antibody reactions, and display the results in an easily understandable manner. [Brief description of the drawings]

[0014] [Figure 1] FIG. 1 is a schematic diagram showing the steps of the serotyping method of the present invention. [Diagram 2] FIG. 2 is a schematic diagram showing a preferred embodiment of the selection step in the present invention. [Diagram 3] 1 shows a MALDI mass spectrum of the microorganisms contained in the test sample. [Figure 4] In the examples, this is a diagram in which KMD values ​​are plotted against RKM values ​​using a unit chemical structure obtained by assuming that the serotype of the microorganism contained in the test sample is O26. [Diagram 5]In the examples, this is a diagram in which KMD values ​​are plotted against RKM values ​​using unit chemical structures obtained by assuming that the serotype of the microorganism contained in the test sample is O103. [Figure 6] In the Examples, this is a diagram in which KMD values ​​are plotted against RKM values ​​using a unit chemical structure obtained by assuming that the serotype of the microorganism contained in the test sample is O111. [Figure 7] This is a plot of KMD values ​​against RKM values ​​using unit chemical structures obtained by assuming that the serotype of the microorganism contained in the test sample obtained in the example is O157. Kendrick mass information KM is distributed only for a specific RKM. [Figure 8] FIG. 2 is a schematic diagram showing one of the display formats in the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] A microorganism generally refers to an organism whose presence cannot be detected by the naked eye and whose size is small enough to be observed under a microscope, etc., and the serotyping method of the present invention can be suitably applied to such microorganisms, including eubacteria, archaea, and eukaryotes. In particular, applying the serotyping method of the present invention to eubacteria such as Escherichia coli can be effectively used in the diagnosis of food poisoning, etc.

[0016] Most E. coli are harmless, but those that are particularly pathogenic are called pathogenic E. coli. Pathogenic E. coli include enteropathogenic E. coli, enteroinvasive E. coli, enterotoxigenic E. coli, enterohemorrhagic E. coli, enterodiffuse-adherent E. coli, and enteroaggregative E. coli, which cause diseases within the intestinal tract (diarrheagenic E. coli), and extraintestinal pathogenic E. coli, such as uropathogenic E. coli and meningitis / septicemia-causing E. coli, which cause diseases outside the intestinal tract.

[0017] The serotyping method of the present invention can be suitably applied to enterohemorrhagic E. coli among the pathogenic E. coli. Enterohemorrhagic E. coli is an E. coli that produces verotoxins, and examples of O antigens include O1, O2, O5, O18, O25, O26, O55, O74, O91, O103, O104, O105, O111, O113, O114, O115, O117, O118, O119, O121, O128, O143, O145, O153, O157, O161, O165, and O172. The serotyping method of the present invention can be suitably applied to O26, O103, O111, and O157.

[0018] As shown diagrammatically in FIG. 1, the serotyping method of the present invention includes a mass spectrometry step of obtaining a mass spectrum by mass spectrometry of a test sample containing the microorganism using a mass spectrometer capable of obtaining accurate mass information, and obtaining mass information of each peak detected in the mass spectrum.

[0019] An example of a mass spectrometer capable of acquiring mass information is a MALDI-TOFMS mass spectrometer that combines Matrix Assisted Laser Desorption / Ionization and Time of Flight Mass Spectrometry. An example of a MALDI-TOFMS mass spectrometer is the AXIMA (registered trademark) series manufactured by Shimadzu Corporation.

[0020] Using a mass spectrometer capable of obtaining the above-mentioned accurate mass information, mass analysis of a test sample containing microorganisms is performed to obtain mass spectrum data, and accurate mass information of each peak appearing in the mass spectrum data is obtained.

[0021] The serotype discrimination method of the present invention includes, following the mass analysis step, a discrimination step of discriminating the serotype of a microorganism based on an assumed unit chemical structure of the microorganism, and a display step of displaying the results of the discrimination step in a display format in which bands are displayed at different positions corresponding to the serotype.

[0022] The discrimination step preferably discriminates the serotype of a microorganism in a specimen sample through the following steps (i) to (vi): (i) a repeated mass information assignment step of repeatedly assigning mass information to each assumed microorganism based on the unit chemical structure of the assumed microorganism; (ii) a KM value acquisition step of performing a Kendrick mass conversion calculation process for multiplying the mass information of each peak obtained in the mass analysis step by an integer conversion coefficient of a repeat unit mass based on each of the specified repeat mass information, thereby acquiring a KM value of each peak; (iii) an NKM value acquisition step of determining an NKM value from the KM value; (iv) a KMD value acquisition step of acquiring a KMD value from the NKM value and the KM value; an RKM value acquisition step of acquiring information on the remainder RKM value obtained by dividing the integer NKM value by the integer value of the repeating unit; (v) an analysis step of plotting, on a two-dimensional plane, the RKM value and the KMD value obtained by each combination of the NKM value and the integer mass of the repeating unit for each peak obtained in the mass analysis step; and (vi) a selection step of selecting an integer conversion coefficient of a repeating unit mass such that the KMD value is distributed only for a specific RKM value in the analysis step; Through the steps (1) to (6) above, the serotype of the microorganism is identified based on the unit chemical structure of the glycan structure from the integer conversion coefficient of the repeating unit mass selected in the selection step.

[0023] In the repeating mass information assignment step, a repeating mass information assignment step is performed in which repeating mass information is assigned to each assumed microorganism based on the unit chemical structure of the assumed microorganism. The sugar chains of microorganisms have repeating structures made of different types of constituent sugars depending on the serotype. Therefore, repeating mass information determined in advance from the sugar chains of the assumed microorganism is assigned to each assumed microorganism.

[0024] For example, for representative serotypes of enterohemorrhagic Escherichia coli, repeat mass information such as that shown in Table 1 below can be obtained.

[0025] [Table 1]

[0026] In the repeat mass information assignment step, the obtained repeat mass information is assigned to each serotype and sugar type.

[0027] In the KM value acquisition step, a Kendrick mass conversion calculation process is performed on the accurate mass information of each peak obtained in the mass analysis step based on the specified repeated mass information, and a KM value of each peak is acquired.

[0028] Kendrick mass conversion calculation processing was proposed by Kendrick et al. to perform elemental composition analysis of saturated hydrocarbons with a repeating structure of methylene group (CH2) units. When the repeating unit is CH2, the exact mass of CH2 on the IUPAC mass scale (theoretical value: 14.01565) is defined as Kendrick mass (KM) = 14, and the observed exact mass (observed (IUPAC) mass) of each peak that appears in the mass spectrum is converted to Kendrick mass (KM value) according to the following formula. KM value = observed (IUPAC) mass x 14.00000 / 14.01565

[0029] The repeating unit structure is not limited to CH2. For example, if the sample is a polymer, the repeating unit structure may be a monomer. Thus, the above formula is generally: KM = observed (IUPAC) mass of each peak × integer mass of unit structure / IUPAC mass of unit structure (1) Hereinafter, "integer mass of unit structure / IUPAC mass of unit structure" may be referred to as "integer conversion coefficient of repeating unit mass."

[0030] Based on the repeating mass information of the glycan of the assumed microorganism specified in the repeating mass information specification process, the KM value of each peak is obtained in the KM value acquisition process by performing Kendrick mass conversion calculation processing using the formula (1) for each peak appearing in the mass spectrum data obtained in the mass analysis process.

[0031] Furthermore, the NKM value is obtained by using the integer closest to the KM value obtained in the KM value obtaining process as the NKM value, and the NKM value is obtained from the difference between the obtained NKM value and the KM value in the KMD value obtaining process, thereby obtaining the NKM value and the KMD value. The KMD value is defined by the following formula (2). KMD value = KM value - NKM value (2)

[0032] In the RKM value acquisition step, the NKM value is divided by the integer mass of the unit structure, and the RKM value, which is the remainder, is acquired. The integer masses of the unit structures of the representative serotypes of, for example, the above-mentioned enterohemorrhagic E. coli are shown in Table 1.

[0033] The KM value acquisition step, NKM value acquisition step, KMD value acquisition step, and RKM value information acquisition step are performed for all mass information of the assumed microorganisms designated in the mass information designation step of the repeat unit for the mass information of each peak obtained in the mass analysis step. Therefore, for each peak obtained in the mass analysis step, the KM value, NKM value, KMD value, and RKM value are obtained for each mass information of the assumed microorganisms, respectively.

[0034] In the analysis step, the RKM value of each peak obtained in the mass analysis step and the corresponding KMD value are plotted on a two-dimensional plane based on the mass information of each assumed microorganism. When plotting on a two-dimensional plane, for example, it is preferable to plot the RKM on the x-axis and the KMD value on the y-axis, since this makes it easy to understand the tendency of each point.

[0035] When the analysis step is performed based on the mass information of microorganisms not present in the specimen, the RKM value and the KMD value have no correlation and are randomly distributed on a two-dimensional plane. However, when the analysis step is performed based on the mass information of microorganisms present in the specimen, a plot is obtained in which the KMD value is distributed only for a specific RKM value.

[0036] In addition, "KMD values ​​are distributed only for specific RKM values" means that there are multiple groups of KMD values ​​with the same RKM value, and the different KMD values ​​that form the groups range from -1 to 1. In addition, the number of groups of KMD values ​​with the same RKM value, i.e., the number of different RKMs, depends on the number of monosaccharides that compose the glycan of each microorganism, but since hydrogen and salts may be added or removed, the number is often about twice the number of constituent monosaccharides.

[0037] In the selection step, if a plot in which KMD is distributed only for a specific RKM is obtained from the plots obtained in the analysis step, an integer conversion coefficient of the repeating unit mass that gives such a plot is selected.

[0038] The serotype of the microorganism contained in the test sample can be identified by identifying the chemical structure of the glycan of the microorganism to be analyzed from the integer conversion coefficient of the repeating unit mass selected in the selection step.

[0039] In the selection step, for example, a plot in which KMD is distributed only for a specific RKM may be visually selected. As shown in FIG. 2, a learning model may be acquired based on a plot distribution pattern to learn whether the conversion coefficient of the repeating unit mass of various expected glycans is suitable for the glycan structure analysis of a sample, and a two-dimensional plot consisting of RKM values ​​and KMD values ​​obtained using the learning model may be discriminated to discriminate a serotype in which KMD values ​​are distributed only for a specific RKM value. A learning model may be acquired by machine learning using past data, or a threshold value or the like may be set in advance for a two-dimensional plot in which KMD values ​​are distributed only for a specific RKM value, and a two-dimensional plot that satisfies the threshold value may be selected to discriminate a serotype.

[0040] The serotype determined in the determination step is then displayed in a predetermined format through a display step, thereby enabling even an operator who is not familiar with mass spectrometry to easily determine the serotype.

[0041] The display format may be, for example, a format in which a color, figure, or letter is determined in advance for each serotype, and the serotype determined in the determination step is displayed as a color, figure, or letter, or a display format similar to that of an existing test method. An example of a display format similar to that of an existing test method is a display format by immunochromatography performed in a test based on an antibody-antigen reaction. For example, when determining the serotype of enterohemorrhagic Escherichia coli, as shown in FIG. 1, a display format in which lines are displayed in different positions corresponding to the serotypes O26, O103, O111, and O157 allows even analysts familiar with tests based on antibody-antigen reactions to easily determine the serotype.

[0042] The serotype discrimination method of the present invention includes the above-mentioned mass analysis step, integer conversion coefficient designation step for repeating unit mass, KM acquisition step, NKM acquisition step, KMD acquisition step, RKM acquisition step, RKM information acquisition step, analysis step, selection step, discrimination step and display step. EXAMPLES

[0043] The present invention will now be described in detail with reference to examples, but the scope of the present invention is not limited to these examples.

[0044] Escherichia coli of serotype O157 was used as the microorganism contained in the test sample, and mass spectrometry of the test sample was performed.

[0045] As a result of mass spectrometry of the test sample, the MALDI mass spectrum shown in FIG. 3 was obtained.

[0046] The assumed serotypes of the microorganisms are O26, O103, O111, and O157, and the integer conversion coefficients of the repeating unit mass of the glycan corresponding to each serotype are shown in Table 2.

[0047] [Table 2]

[0048] The RKM value and KMD value obtained for each peak of the MALDI mass spectrum shown in FIG. 3 were plotted on a two-dimensional plane with the RKM value on the x-axis and the KMD value on the y-axis, using the KM value calculated by multiplying the observed mass by the integer conversion coefficient of the repeating unit mass in Table 2, and the NKM value calculated by rounding off the KM value. When the microbial serotype was O26 and the two-dimensional surface was plotted, the points were randomly distributed on the two-dimensional surface, and there was no correlation between the RKM and KMD values, as shown in Figure 4. Similarly, when the microbial serotype was O103 (Figure 5) or O111 (Figure 6), the points were randomly distributed on the two-dimensional surface.

[0049] On the other hand, when the RKM and KMD values ​​were similarly plotted on a two-dimensional plane with the microbial serotype set to O157, several KMD values ​​for a particular RKM generated groups, with all the points aligned on several lines parallel to the y-axis (Figure 7).

[0050] From the above results, it was found that the microorganism contained in the test sample was Escherichia coli of serotype O157. Based on the above results, the rightmost line, which is the display format of O157 shown in Figure 8, was displayed.

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

[0052] [1] (1) a mass spectrometry step of obtaining a mass spectrum by mass spectrometry of a test sample containing a microorganism using a mass spectrometer capable of obtaining accurate mass information, and obtaining mass information of each peak detected in the mass spectrum; (2) a discrimination step of discriminating the serotype of the microorganism by analyzing the analytical results obtained by mass spectrometry based on the repeating unit chemical structure of the assumed glycan structure of the microorganism; (3) a display step of displaying the results of the discrimination step in a display format in which bands are displayed at different positions corresponding to serotypes; A method for identifying a serotype of a microorganism, comprising: The determining step includes: (i) The assumed microorganism Repeating glycan structures a repeating mass information assignment step of repeatedly assigning mass information to each assumed microorganism based on the unit chemical structure; (ii) a KM value acquisition step of performing a Kendrick mass conversion calculation process for multiplying the mass information of each peak obtained in the mass analysis step by an integer conversion coefficient of a repeat unit mass based on each of the specified repeat mass information, thereby acquiring a KM value of each peak; (iii) an NKM value acquisition step of determining an NKM value from the KM value; (iv) a KMD value acquisition step of acquiring a KMD value from the NKM value and the KM value, and a remainder of the value obtained by dividing the NKM value by an integer value of the repeating unit. is An RKM value acquisition step for acquiring information on the RKM value; (v) an analysis step of plotting, on a two-dimensional plane, the RKM value and the KMD value obtained by each combination of the NKM value and the integer mass of the repeating unit for each peak obtained in the mass analysis step; and (vi) a selection step of selecting an integer conversion coefficient of a repeating unit mass such that the KMD value is distributed only for a specific RKM value in the analysis step; Including, determining the serotype of the microorganism based on the unit chemical structure of the glycan structure from the integer conversion coefficient of the repeating unit mass selected in the selection step; In the selection process, a learning model is obtained that is trained based on a plot distribution pattern to determine whether the conversion coefficients of the repeating unit masses of various anticipated glycans are suitable for glycan structural analysis of a sample, a two-dimensional plot consisting of RKM values ​​and KMD values ​​obtained using the learning model is discriminated, and serotypes in which KMD values ​​are distributed only for specific RKM values ​​are discriminated, which is a method for discriminating serotypes of microorganisms.

[0053] [2] A method for distinguishing a serotype as described in [1] above, in which in the analysis step, the RKM value is plotted on the x-axis and the KMD value is plotted on the y-axis.

[0054] [3] The serotype discrimination method described in [2] above, characterized in that in the analysis step, a group of multiple KMD values ​​is generated for a specific RKM value, and it is determined whether all points are aligned on multiple straight lines parallel to the y-axis, and the results are output.

[0056] The above-mentioned inventions [1] to [ 3 According to the paper, by analyzing the results obtained by mass spectrometry, it is possible to clarify the repeating structure of the glycans of microorganisms such as pathogenic bacteria, directly identify the serotype of the bacteria without relying on antigen-antibody reactions, and display the results in an easy-to-understand manner.

Claims

1. (1) a mass spectrometry step of obtaining a mass spectrum by mass spectrometry of a test sample containing a microorganism using a mass spectrometer capable of obtaining accurate mass information, and obtaining mass information of each peak detected in the mass spectrum; (2) a step of identifying the serotype of a microorganism by analyzing the analytical results obtained by mass spectrometry based on the repeating unit chemical structure of the assumed glycan structure of the microorganism; (3) a display step of displaying the results of the discrimination step in a display format in which bands are displayed at different positions corresponding to serotypes; A method for identifying a serotype of a microorganism, comprising: The determining step includes: (i) a repeating mass information assignment step of assigning repeating mass information to each assumed microorganism based on the repeating unit chemical structure of the sugar chain structure of the assumed microorganism; (ii) a KM value acquisition step of performing a Kendrick mass conversion calculation process for multiplying the mass information of each peak obtained in the mass analysis step by an integer conversion coefficient of a repeat unit mass based on the specified repeat mass information, thereby acquiring a KM value of each peak; (iii) an NKM value acquisition step of determining an NKM value from the KM value; (iv) a KMD value acquisition step of acquiring a KMD value from the NKM value and the KM value, and an RKM value acquisition step of acquiring information on an RKM value, which is the remainder of the value obtained by dividing the NKM value by the integer value of the repeating unit; (v) an analysis step of plotting the RKM value and KMD value obtained by each combination of the NKM value and the integer mass of the repeating unit for each peak obtained in the mass analysis step on a two-dimensional plane; and (vi) a selection step of selecting an integer conversion coefficient of a repeating unit mass such that the KMD value is distributed only for a specific RKM value in the analysis step; Including, determining the serotype of the microorganism based on the unit chemical structure of the glycan structure from the integer conversion coefficient of the repeating unit mass selected in the selection step; In the selection process, a learning model is obtained that is trained based on a plot distribution pattern to determine whether the conversion coefficients of the repeating unit masses of various types of anticipated glycans are suitable for analyzing the glycan structure of a sample, a two-dimensional plot consisting of RKM values ​​and KMD values ​​obtained using the learning model is discriminated, and a serotype in which KMD values ​​are distributed only for a specific RKM value is discriminated, which is a method for discriminating the serotype of a microorganism.

2. The method for distinguishing a serotype according to claim 1, wherein in the analyzing step, the RKM value is plotted on the x-axis and the KMD value is plotted on the y-axis.

3. The serotype discrimination method described in claim 2, characterized in that in the analysis step, a group of multiple KMD values ​​is generated for a specific RKM value, and it is determined whether all points are aligned on multiple straight lines parallel to the y-axis, and the results are output.

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