Microorganism identification method and microorganism identification system

Abstract

To enable highly accurate microorganism identification using mass spectroscopy.SOLUTION: A mass spectrum of a microorganism to be tested is acquired (S101), for a plurality of kinds of known microorganisms, the classification groups of which are different, by searching a peak interval database that stores the classification groups to which the plurality of kinds of known microorganisms belong and particular peak intervals which is peak intervals specific to the classification groups among a plurality of peak intervals on the mass spectrum of the known microorganism associated with each other, a peak interval that matches anyone of intervals between peaks included in the mass spectrum of the microorganism to be tested from particular peak intervals registered in the peak interval database is selected (S102), then the classification group stored in the peak interval database associated with the selected particular peak interval is identified as a classification to which the microorganism to be tested belongs (S103).SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a method and system for identifying microorganisms using mass spectrometry. [Background technology]

[0002] There is a known method for identifying a microorganism based on a mass spectrum obtained by mass spectrometry of a test microorganism, that is, for identifying the taxonomic group (genus, species, subspecies, strain, or serotype, etc.) to which the microorganism belongs. Mass spectrometry allows analysis results to be obtained in a short time using a small amount of a microorganism sample, and also allows for easy continuous analysis of multiple samples, making it possible to easily and quickly identify microorganisms. In this method, first, a solution containing proteins extracted from the test microorganism or a suspension of the test microorganism is analyzed by matrix assisted laser desorption / ionization mass spectrometry (MALDI-MS) or the like. Then, the test microorganism is identified by comparing the m / z of each peak on the mass spectrum obtained by the above analysis with the m / z of a peak (marker peak) characteristic of each known microorganism previously recorded in a database (see, for example, Patent Document 1).

[0003] The m / z of ions measured by a mass spectrometer varies due to various factors such as changes in ambient temperature. The range of variation in this m / z is the mass accuracy of the instrument. To improve the mass accuracy, mass spectrometers calibrate the m / z axis (hereinafter sometimes referred to as "mass calibration") using measurement results for compounds whose theoretical m / z values ​​or extremely accurate measured values ​​(hereinafter referred to as "theoretical values, etc.") are known (see, for example, Patent Document 2).

[0004] Specifically, a standard sample containing a given compound whose theoretical m / z value is known is measured, and the actual m / z value is compared with the theoretical value to determine the mass deviation at that m / z (i.e., the difference between the actual m / z value and the theoretical value). A calibration curve showing the relationship between m / z and mass deviation is then created from the mass deviations obtained at different m / z values ​​for a plurality of compounds. The actual m / z value obtained by mass analysis of an unknown sample is calibrated based on the calibration curve created in this way. This allows the m / z of ions derived from the unknown sample to be determined with high accuracy.

[0005] Such mass calibration methods include the internal standard method, in which a standard sample and an unknown sample are mixed and measured simultaneously, and the external standard method, in which a standard sample and an unknown sample are measured separately. With the internal standard method, mass calibration is performed based on the results of measurements performed at the same time, so it is possible to perform mass calibration with higher accuracy than with the external standard method. However, with the internal standard method, ions from the standard sample may suppress the ionization of the unknown sample (ion suppression), and it may be difficult to distinguish peaks from the unknown sample and those from the standard sample. For these reasons, mass calibration is usually performed using the external standard method in microbial analysis using MALDI-MS. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2015-184020 A [Patent Document 2] JP 2005-292093 A Summary of the Invention [Problem to be solved by the invention]

[0007] In microbial analysis using MALDI-MS, E. coli is used as a standard sample for mass calibration using the external standard method as described above. In the MALDI mass spectrum of E. coli, peaks are observed over a wide range of m / z 4000-20000, making it possible to perform mass calibration over a wide range. However, as described above, mass calibration using the external standard method has a problem in that the calibration accuracy is lower than that of the internal standard method, and a relatively large error (for example, an error of about 500 to 1000 ppm) remains even after calibration. If such a relatively large error is allowed, it may not be possible to distinguish between closely related microorganisms or a peak may be erroneously determined, so that it has been difficult to perform highly accurate microbial identification in conventional microbial analysis using mass spectrometry.

[0008] The present invention has been made in view of the above-mentioned points, and an object of the present invention is to enable highly accurate identification of microorganisms by utilizing mass spectrometry. [Means for solving the problem]

[0009] The microorganism identification system according to the present invention, which has been developed to solve the above problems, a peak interval database that stores, for a plurality of types of known microorganisms having different taxonomic groups, a taxonomic group to which each of the plurality of types of known microorganisms belongs and a characteristic peak interval that is a peak interval characteristic of the taxonomic group among a plurality of peak intervals in a mass spectrum of the known microorganism, in association with each other; a mass spectrum acquisition unit for acquiring a mass spectrum of a test microorganism; a peak interval database search unit that selects, from the characteristic peak intervals registered in the peak interval database, a peak interval that matches any of a plurality of peak intervals included in the mass spectrum of the test microorganism within a predetermined error range; a taxonomic group identification unit that identifies a taxonomic group stored in the peak interval database in association with the characteristic peak interval selected by the peak interval database search unit as a taxonomic group to which the test microorganism belongs; The present invention is characterized in that it has the following features.

[0010] In addition, a method for identifying a microorganism according to the present invention, which has been made to solve the above problems, comprises: Obtaining a mass spectrum of the test microorganism; searching a peak interval database in which the taxonomic group to which each of the multiple known microorganisms belongs and the characteristic peak interval that is the peak interval characteristic of the taxonomic group among the intervals of the multiple peaks in the mass spectrum of the known microorganisms are stored in correspondence with each other, thereby selecting, from the characteristic peak intervals registered in the peak interval database, an interval that matches any of the intervals between the multiple peaks included in the mass spectrum of the test microorganism within a predetermined error range; Identifying a taxonomic group stored in the peak interval database in association with the selected characteristic peak interval as a taxonomic group to which the test microorganism belongs; It is characterized by the following. Effect of the Invention

[0011] According to the above-mentioned microbial identification system or microbial identification method of the present invention, the taxonomic group to which the test microorganism belongs can be identified based on the peak interval, which is less likely to deviate compared to the m / z values ​​of individual mass spectrum peaks, thereby enabling highly reliable microbial identification and enabling highly accurate microbial identification using mass spectrometry. [Brief description of the drawings]

[0012] [Figure 1] 1 is a block diagram showing a configuration of a main part of a mass spectrometry system according to an embodiment of the present invention. [Diagram 2] FIG. 1 is a schematic diagram conceptually showing characteristic peak intervals registered in a peak interval DB. [Diagram 3] 4 is a flowchart showing a procedure for executing microbial identification and mass calibration in the embodiment. [Figure 4] FIG. 1 is a schematic diagram conceptually showing the operation of comparing the mass spectrum of a test microorganism with a characteristic peak interval. [Diagram 5]MALDI mass spectrum of Staphylococcus bacteria. [Figure 6] MALDI mass spectrum of Staphylococcus cohnii subsp. urealyticus. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. Fig. 1 is a schematic diagram of a mass spectrometry system (corresponding to a microorganism identification system according to the present invention) according to one embodiment of the present invention. This mass spectrometry system has a mass spectrometer 10 and a control and processing unit 20.

[0014] The mass spectrometer 10 may have any configuration as long as it ionizes a sample by the Matrix Assisted Laser Desorption / Ionization (MALDI) method, but it is preferable to use a MALDI-TOFMS that combines a MALDI ion source with a Time-of-Flight Mass Spectrometer (TOFMS). Since the range of measurable mass-to-charge ratios in the MALDI-TOFMS is very wide, it can obtain mass spectra suitable for analyzing high-mass molecules such as proteins that are components of microorganisms.

[0015] The control / processing unit 20 is composed of a general-purpose computer such as a personal computer or dedicated hardware, or a combination of both, and includes an analysis control unit 21 for controlling the operation of the mass spectrometer 10, a data processing unit 30 for processing data obtained by measuring a sample using the mass spectrometer 10, a peak interval database (peak interval DB 23), a protein database (protein DB 24), and a data storage unit 22 for storing data generated by the data processing unit 30. In addition, a display monitor (display unit 41) composed of an LCD (Liquid Crystal Display) or the like is connected to the control / processing unit 20.

[0016] The data processing unit 30 includes, as functional blocks, a spectrum generating unit 31 that generates a mass spectrum based on data obtained by measuring a sample using the mass spectrometer 10, a peak interval DB searching unit 32 that searches the peak interval DB 23, a taxonomic group identifying unit 33 that identifies microorganisms based on the search results, a first calibration unit 34 that calibrates the mass spectrum based on the contents registered in the peak interval DB, a protein DB searching unit 35 that searches the protein DB 24, a peak assignment unit 36 ​​that assigns peaks on the mass spectrum based on the search results, and a second calibration unit 37 that recalibrates the mass spectrum based on the contents recorded in the protein DB 24. Note that all of these functional blocks are basically functional means that are realized in the form of software by a CPU provided in a computer constituting the control and processing unit 20 reading out a dedicated program installed in a storage unit consisting of a large-capacity storage device such as a HDD (Hard Disk Drive) or SSD (Solid State Drive) into the memory of the computer and executing it. The dedicated program does not necessarily have to be a stand-alone program, but may be, for example, a function incorporated into a part of a program for controlling mass spectrometer 10, and the form thereof is not particularly limited.

[0017] Protein DB24 contains information on the classification of known microorganisms (genus, species, subspecies, strains, serotypes, etc.), the names of proteins contained in the microorganisms, and the theoretical m / z values ​​or Actual measurement The values ​​and are stored in correspondence with each other.

[0018] Information on the base sequences of genes encoding proteins derived from various microorganisms or the amino acid sequences of the proteins are stored in public databases (hereinafter, public DBs) such as the GenBank database in the United States, the EMBL database in Europe, and the DDBJ database in Japan. Therefore, the protein DB 24 can be constructed, for example, based on information registered in the public DBs as described above. Specifically, first, the DNA base sequences of genes (e.g., genes of ribosomal proteins) of various proteins contained in a given known microorganism (e.g., multiple types of known microorganisms belonging to the taxonomic group to be analyzed) are obtained from a public DB, and the calculated molecular weights of various proteins contained in the known microorganisms are derived by translating them into amino acid sequences. Note that, if the amino acid sequence of the protein is registered in the public DB, the calculated molecular weight may be obtained directly from the amino acid sequence. In addition, the calculated molecular weight may be corrected by adding cleavage of the N-terminal initiation methionine residue or post-translational modification. Next, the calculated molecular weights of various proteins are converted into theoretical values ​​of m / z of ions derived from the proteins (theoretical m / z). In this conversion, it is desirable to convert the calculated molecular weight of various proteins into the theoretical m / z of the ions obtained when the proteins are mass-analyzed by the same ionization method and mass separation method as those used by the mass spectrometer 10 in this embodiment. When a biological sample is analyzed by MALDI-TOFMS, the theoretical m / z of the ions obtained by the mass spectrometer 10 in this embodiment is mainly [M+H] + (M is a molecule, H is a hydrogen atom), [MH] - , or [M+Na] + It is known that molecular weight-related ions such as m / z (Na is a sodium atom) are detected. Therefore, it is relatively easy to convert the calculated molecular weight as described above into the theoretical m / z of the ion. The theoretical m / z of the ions of various proteins calculated as described above is associated with the protein name and the name of the microorganism, and stored in a large-capacity storage device or the like provided in the computer constituting the control / processing unit 20, thereby constructing the protein DB 24.

[0019] In addition, in the protein DB24, for some or all of the various proteins for the multiple types of known microorganisms, instead of the theoretical m / z of ions as described above, actual measured values ​​of ions (actual m / z) obtained by actually performing mass analysis of the known microorganisms using an ionization method and mass separation method similar to those of the mass spectrometer 10 in this embodiment may be registered.

[0020] In the peak interval DB23, for each of a plurality of different types of known microorganisms, information on the species to which the known microorganism belongs, information on the mass spectrum peak interval (hereinafter referred to as the "specific peak interval") specific to the known microorganism belonging to the species, and information on the m / z of the plurality of peaks forming the specific peak interval are stored in a corresponding manner. Note that these values ​​(i.e., the value of the specific peak interval and the value of the m / z of each peak) may be theoretical values ​​or actual measured values. Note that the theoretical values ​​are preferably calculated molecular weights of various proteins contained in the plurality of types of known microorganisms, converted into theoretical m / z of ions obtained when the proteins are mass-analyzed by the same ionization method and mass separation method as those used by the mass spectrometer 10 in this embodiment. Also, the actual measured values ​​are preferably values ​​obtained by actually mass-analyzing each of the plurality of types of known microorganisms by the same ionization method and mass separation method as those used by the mass spectrometer 10 in this embodiment.

[0021] The contents of the peak interval DB23 can be created by extracting a part of the contents of the protein DB24. For example, the m / z of ions derived from various proteins recorded in the protein DB24 is compared between multiple types of known microorganisms, multiple m / z values ​​that are commonly included in known microorganisms belonging to a specific species and not included in microorganisms belonging to other species are identified, and the peak interval DB23 can be created by obtaining each m / z value (corresponding to the m / z of the peak) and the difference between the m / z values ​​(corresponding to the peak interval) between the multiple types of known microorganisms. Alternatively, the peak interval DB23 may be created by comparing the intervals between the m / z values ​​of ions of various proteins registered in the protein DB for multiple types of known microorganisms, identifying m / z intervals that are commonly included in known microorganisms belonging to a specific species and not included in microorganisms belonging to other species, and obtaining each m / z value (corresponding to the m / z of the peak) that forms the m / z interval (corresponding to the unique peak interval).

[0022] FIG. 2 conceptually illustrates characteristic peak intervals registered in the peak interval DB 23. The distance between black bands in the figure represents the characteristic peak interval for each known microorganism. The width of the black band indicates the allowable error of the characteristic peak interval, and the magnitude of this allowable error varies depending on the mass accuracy, but it is preferable to set it within approximately ±200 ppm. Also, while FIG. 2 illustrates a characteristic peak interval formed by two or three peaks for each known microorganism, the characteristic peak interval may be formed by four or more peaks (preferably 10 or less).

[0023] In this embodiment, the protein DB 24 or the peak interval DB 23 is stored in the control / processing unit 20, but this is not limiting, and either or both of these DBs may be stored in an external device connected via an interface (not shown) provided in the control / processing unit 20. Also, either or both of these DBs may be stored in a server on the Internet, and the control / processing unit 20 may be connected to the Internet via the interface, thereby making it possible to use the database. As such protein DB 24 or peak interval DB 23, a database prepared in advance by a public institution or a manufacturer of the mass spectrometer 10, or, for example, a database independently constructed by a user may be used.

[0024] Hereinafter, the procedure for performing microbial identification and mass calibration using the mass spectrometry system according to this embodiment will be described with reference to the flowchart of FIG.

[0025] First, the user prepares a sample containing components of a test microorganism (a microorganism whose genus is identified but whose species is not), sets the sample in the mass spectrometer 10, and executes mass analysis. In this case, the sample may be a cell extract, or a cell extract from which cellular components such as ribosomal proteins have been purified, or intact microbial cells or a suspension of the microbial cells may be used as is.

[0026] The spectrum generating unit 31 acquires a detection signal obtained from the mass spectrometer 10, and creates a mass spectrum of the test microorganism based on the detection signal (step S101).

[0027] Next, the peak interval DB search unit 32 compares the mass spectrum of the test microorganism with the characteristic peak intervals of the known microorganisms stored in the peak interval DB 23, and selects a characteristic peak interval that matches any of the intervals between multiple peaks included in the mass spectrum of the test microorganism within a predetermined error range (step S102). FIG. 4 is a schematic diagram conceptually illustrating the operation of comparing the mass spectrum of the test microorganism with the characteristic peak interval by the peak interval DB search unit 32. The figure shows a state in which the characteristic peak intervals of each known microorganism are slid in the m / z axis direction on the mass spectrum of the test microorganism, while searching for a point that matches any of the characteristic peak intervals within a predetermined error range. The figure also shows an example in which a point that matches the characteristic peak interval of the known microorganism A is not found on the mass spectrum of the test microorganism, but a point that matches the characteristic peak interval of the known microorganism B is found.

[0028] Next, the taxonomic group identification unit 33 identifies the "species" of known microorganisms stored in the peak interval DB 23 in association with the characteristic peak interval selected in step S102 as the species to which the test microorganism belongs (step S103). In mass spectrometry, deviations in m / z values ​​are likely to occur, but deviations in peak intervals are relatively unlikely to occur. Therefore, as described above, highly reliable microorganism identification can be performed by identifying the taxonomic group to which the test microorganism belongs based on the magnitude of the peak interval, regardless of the m / z values ​​of individual peaks. Information on the species of the test microorganism identified in step S103 is displayed on the display unit 41 and stored in the data storage unit 22.

[0029] Next, the first calibration unit 34 performs mass calibration of the mass spectrum of the test microorganism based on the search result in step S102 (step S104). Specifically, the m / z (value registered in the peak interval DB 23; hereinafter referred to as "registered m / z") of a plurality of peaks forming the characteristic peak interval selected in step S102 is compared with the m / z (hereinafter referred to as "measured m / z") of a plurality of peaks forming a peak interval that matches the characteristic peak interval within a predetermined error range on the mass spectrum of the test microorganism, and calculates first calibration information for calibrating the m / z axis of the mass spectrum of the test microorganism based on the difference between the registered m / z and the measured m / z of corresponding peaks. The first calibration information can be derived as, for example, a calculation formula. The first calibration unit 34 uses this first calibration information to mass calibrate the mass spectrum of the test microorganism, thereby generating a mass spectrum with high mass accuracy (hereinafter referred to as "calibrated mass spectrum"). For example, in the example shown in Figure 4 above, mass calibration is performed so that the measured m / z of three peaks (peaks indicated by upward arrows in the figure) in the mass spectrum of the test microorganism that have intervals that match the characteristic peak interval of known microorganism B matches each of the three registered m / z values ​​stored in peak interval DB23 in correspondence with the characteristic peak interval of known microorganism B.

[0030] Next, the protein DB search unit 35 searches the protein DB 24 to assign each peak present on the calibrated mass spectrum. That is, the m / z value of each peak present on the calibrated mass spectrum (hereinafter referred to as "calibrated peak") is read, and the value is compared with the m / z value of an ion derived from various proteins (those included in the microbial species identified in step S103) registered in the protein DB 24 (step S105). Then, the calibrated peak for which a protein with a matching m / z value within a predetermined error range is identified is determined to be a peak derived from the protein (step S106). The assignment results of each peak in step S106 are displayed on the display unit 41 and stored in the data storage unit 22.

[0031] Next, the second calibration unit 37 compares the m / z of the calibrated peak whose corresponding protein was identified in step S106 with the m / z value of the protein registered in the protein DB 24, and calculates second calibration information (e.g., a calculation formula) for converting the former to the latter. Then, the calibrated mass spectrum is recalibrated based on the second calibration information to generate a mass spectrum with even higher mass accuracy (step S107). The mass spectrum generated as described above (mass spectrum after the second calibration process) is displayed on the display unit 41 and stored in the data storage unit 22.

[0032] As a result of the above, the mass spectrum after the second calibration stored in the data storage unit 22 is registered, for example, in a new or existing mass spectral library in which mass spectra of various microorganisms are registered, and used for comparison with mass spectra of other unknown microorganisms.

[0033] Although specific examples of the form for carrying out the present invention have been described above, the present invention is not limited to the above-described embodiments, and appropriate modifications are permitted within the scope of the spirit of the present invention.

[0034] For example, the microorganism identification system, the microorganism identification method, or the program according to the present invention does not necessarily have to execute all steps from step S101 to step S107, and may, for example, execute only the steps (steps S101 to S103) from acquiring the mass spectrum to identifying the test microorganism. Alternatively, it may execute only the steps (steps S101 to S104) from acquiring the mass spectrum to the first calibration process, or it may execute only the steps (steps S101 to S106) from acquiring the mass spectrum to attributing the peaks.

[0035] In the above embodiment, the taxonomic group identification unit 33 identifies the "species" to which the test microorganism belongs, but it is not limited thereto and may identify other taxonomic groups to which the test microorganism belongs, such as "genus," "subspecies," "strain," or "serotype." In this case, the peak interval DB 23 is registered with the intervals of mass spectral peaks (characteristic peak intervals) characteristic of the taxonomic group to be identified, and the m / z of multiple mass spectral peaks that form the characteristic peak intervals. EXAMPLES

[0036] Staphylococcus bacteria were used as test microorganisms and were measured by MALDI-MS (linear mode). In the measurement, the test microorganisms were applied to a MALDI sample plate, and a matrix agent (sinapic acid) was dropped on the plate and dried to prepare a sample / matrix mixed crystal.

[0037] The mass spectrum obtained by the above measurement is shown in Figure 5. Using the interval between peaks a and c in the figure, which is m / z 1656.3, as a clue, a peak interval DB (registering theoretical values ​​of peak intervals characteristic of the species to which each microorganism belongs, for multiple known types of microorganisms belonging to the genus Staphylococcus) was searched, and the result suggested that the test microorganism was Staphylococcus cohnii subsp. cohnii.

[0038] Next, the same measurement was performed five times on another strain of Staphylococcus subsp. cohnii. The actual m / z values ​​(before mass calibration) of the mass spectrum peaks corresponding to the above peaks a and c and the intervals between those peaks are shown in Table 1.

[0039] [Table 1]

[0040] As shown in Table 1, the peak interval corresponding to peak a and peak c in the above-mentioned different strain of Staphylococcus subsp. cohnii was m / z 1655.8 to 1656.4, which was almost identical to the interval between peak a and peak c in the mass spectrum shown in Figure 5. Furthermore, these values ​​were in agreement with the theoretical value (m / z 1655.9) of the peak interval registered in the peak interval DB within ±0.5 Da.

[0041] Peak a is the peak of a hypothetical protein (function unknown: theoretical m / z 4909.36), and peak c is the peak of a UPF0337 protein (theoretical m / z 6565.24). Based on the theoretical m / z (above) of these two peaks, the m / z axis of the mass spectrum in FIG. 5 was calibrated (self-calibration). As a result, the m / z of peak a and the m / z of peak c on the spectrum both matched the theoretical values. From the above results, it was speculated that the Staphylococcus bacteria shown in FIG. 5 were Staphylococcus cohnii subsp. cohnii.

[0042] In addition, a previously created protein DB was searched for proteins having theoretical m / z values ​​matching the m / z values ​​of each peak on the mass spectrum after the above-mentioned self-calibration, and it was confirmed that the mass spectrum contained peaks matching the theoretical m / z values ​​of ribosomal proteins L30, L32, S20, and S21. EXAMPLES

[0043] The mass spectrum obtained by performing MALDI-MS measurement (linear mode) in the same manner as in Example 1 using Staphylococcus cohnii subsp. urealyticus, which is highly related to the above-mentioned Staphylococcus cohnii subsp. cohnii, as the test microorganism is shown in FIG. 6. The interval between peaks a and b on the mass spectrum is m / z 1182.2. When this peak interval was compared with the above-mentioned peak interval DB, it was confirmed that it matched the peak interval registered as being specific to Staphylococcus cohnii subsp. urealyticus, but did not match the peak interval registered as being specific to the related Staphylococcus cohnii subsp. cohnii. From this, it is clear that the present invention Akira It was suggested that this method could also be used to identify microorganisms at the subspecies level.

[0044] Furthermore, the mass spectrum of Fig. 6 was mass calibrated (self-calibration) using the theoretical m / z values ​​of peaks a and b of Staphylococcus cohnii subsp. urealyticus registered in the peak interval DB, and the protein DB was searched for proteins having theoretical m / z values ​​that match the m / z values ​​of each peak on the calibrated mass spectrum. As a result, it was confirmed that peaks matching the theoretical m / z values ​​of ribosomal proteins S20, L24, L28, L29, L30, L33, L34, L35, and L36 were present on the calibrated mass spectrum.

[0045] [Various aspects] It will be appreciated by those skilled in the art that the exemplary embodiments described above are examples of the following aspects.

[0046] (Item 1) A microorganism identification system according to one aspect of the present invention comprises: a peak interval database that stores, for a plurality of types of known microorganisms having different taxonomic groups, a taxonomic group to which each of the plurality of types of known microorganisms belongs and a characteristic peak interval that is a peak interval characteristic of the taxonomic group among a plurality of peak intervals in a mass spectrum of the known microorganism, in association with each other; a mass spectrum acquisition unit for acquiring a mass spectrum of a test microorganism; a peak interval database search unit that selects, from the characteristic peak intervals registered in the peak interval database, a peak interval that matches any of a plurality of peak intervals included in the mass spectrum of the test microorganism within a predetermined error range; a taxonomic group identification unit that identifies a taxonomic group stored in the peak interval database in association with the characteristic peak interval selected by the peak interval database search unit as a taxonomic group to which the test microorganism belongs; It has the following.

[0047] (2) The microorganism identification system according to claim 1, wherein the peak interval database further stores m / z of a plurality of peaks forming the characteristic peak interval for each of the plurality of types of known microorganisms, a first calibration unit that calibrates the m / z axis of the mass spectrum of the test microorganism based on the difference between the m / z of a plurality of peaks forming the characteristic peak interval, which is stored in the peak interval database in association with the characteristic peak interval selected by the peak interval database search unit, and the m / z of a plurality of mass spectrum peaks forming a peak interval that matches the characteristic peak interval within a predetermined error range on the mass spectrum of the test microorganism; It may further comprise:

[0048] (3) The microorganism identification system according to the second aspect of the present invention comprises: a protein database storing, for each of the plurality of types of known microorganisms, m / z values ​​of ions derived from each of the plurality of types of proteins contained in the known microorganisms; a protein database search unit that compares the mass spectrum of the test microorganism after the calibration by the first calibration unit with the m / z of ions derived from each of the multiple types of proteins registered in the protein database; a peak attribution section for attributing a peak on the mass spectrum of the calibrated test microorganism to a protein from which the peak originates, based on a comparison result by the protein database search section; It may further comprise:

[0049] (4) The microorganism identification system according to (3), recalibrating the m / z axis of the mass spectrum of the test microorganism after the calibration based on the difference between the m / z of a peak assigned to any one of the plurality of types of proteins on the mass spectrum of the test microorganism after the calibration and the m / z of the protein stored in the protein database; 2nd calibration section , It may further comprise:

[0050] (Item 5) A method for identifying a microorganism according to one aspect of the present invention comprises: Obtaining a mass spectrum of the test microorganism; searching a peak interval database in which the taxonomic group to which each of the multiple known microorganisms belongs and the characteristic peak interval that is the peak interval characteristic of the taxonomic group among the intervals of the multiple peaks in the mass spectrum of the known microorganisms are stored in correspondence with each other, thereby selecting, from the characteristic peak intervals registered in the peak interval database, an interval that matches any of the intervals between the multiple peaks included in the mass spectrum of the test microorganism within a predetermined error range; Identifying a taxonomic group stored in the peak interval database in association with the selected characteristic peak interval as a taxonomic group to which the test microorganism belongs; It is something.

[0051] (Item 6) The method for identifying a microorganism according to item 5 further comprises: The m / z axis of the mass spectrum of the test microorganism may be calibrated based on the difference between the m / z of multiple peaks forming the selected characteristic peak interval, which is stored in the peak interval database in correspondence with the selected characteristic peak interval, and the m / z of multiple mass spectral peaks forming a peak interval that matches the characteristic peak interval within a predetermined error range on the mass spectrum of the test microorganism.

[0052] (Item 7) The method for identifying a microorganism according to item 6 further comprises: After the calibration The method may assign peaks in the mass spectrum of the test microorganism after calibration to the proteins from which the peaks originate, based on the results of comparing the mass spectrum of the test microorganism with the m / z of ions derived from each of the multiple types of proteins registered in a protein database that stores, for each of the multiple types of known microorganisms, the m / z of ions derived from each of the multiple types of proteins contained in the known microorganisms.

[0053] (Item 8) The method for identifying a microorganism according to item 7 further comprises: The m / z axis of the mass spectrum of the test microorganism after the calibration may be recalibrated based on the difference between the m / z of a peak assigned to any one of the multiple types of proteins on the mass spectrum of the test microorganism after the calibration and the m / z of the protein stored in the protein database.

[0054] (Item 9) A program according to one aspect of the present invention causes a computer to execute the method for identifying a microorganism according to any one of items 5 to 8.

[0055] According to the microbial identification system described in paragraph 1 or the microbial identification method described in paragraph 5, highly reliable microbial identification can be performed by identifying the taxonomic group to which the test microorganism belongs based on the interval between mass spectrum peaks, which is less likely to shift compared to the m / z value of the mass spectrum peak.

[0056] According to the microbial identification system described in paragraph 2 or the microbial identification method described in paragraph 6, mass calibration (self-calibration) is performed using a peak originally contained in the mass spectrum of the test microorganism as a reference, thereby making it possible to obtain a mass spectrum with higher mass accuracy than mass calibration by conventional external calibration methods.

[0057] According to the microbial identification system described in paragraph 3 or the microbial identification method described in paragraph 7, accurate peak assignment can be performed by searching a protein DB using the mass spectrum with high mass accuracy obtained by the self-calibration.

[0058] According to the microbial identification system described in item 4 or the microbial identification method described in item 8, a mass spectrum with higher mass accuracy can be obtained by recalibrating the mass spectrum after the self-calibration based on the peak assignment results. [Explanation of symbols]

[0059] 10...Mass spectrometer 20...Control and processing section 21...Analysis control section 22...Data storage unit 23…Peak interval DB 24...Protein Database 30...Data processing unit 31...Spectrum generation unit 32…Peak interval DB search section 33...Taxon identification part 34…1st calibration section 35…Protein DB Search Section 36…Peak assignment section 37…Second calibration section 41...Display section

Claims

1. a peak interval database that stores, for a plurality of types of known microorganisms having different taxonomic groups, a taxonomic group to which each of the plurality of types of known microorganisms belongs and a characteristic peak interval that is a peak interval characteristic of the taxonomic group among a plurality of peak intervals on a mass spectrum of the known microorganism, in association with each other; a mass spectrum acquisition unit for acquiring a mass spectrum of a test microorganism; a peak interval database search unit that selects, from the characteristic peak intervals registered in the peak interval database, a peak interval that matches any of a plurality of peak intervals included in the mass spectrum of the test microorganism within a predetermined error range; a taxonomic group identification unit that identifies a taxonomic group stored in the peak interval database in association with the characteristic peak interval selected by the peak interval database search unit as a taxonomic group to which the test microorganism belongs; A microorganism identification system having

2. the peak interval database further stores m / z of a plurality of peaks forming the characteristic peak interval for each of the plurality of types of known microorganisms, Furthermore, a first calibration unit that calibrates the m / z axis of the mass spectrum of the test microorganism based on the difference between the m / z of a plurality of peaks forming the characteristic peak interval, which is stored in the peak interval database in association with the characteristic peak interval selected by the peak interval database search unit, and the m / z of a plurality of mass spectrum peaks forming a peak interval that coincides with the characteristic peak interval within a predetermined error range on the mass spectrum of the test microorganism; The microorganism identification system according to claim 1 , comprising:

3. Furthermore, a protein database storing, for each of the plurality of types of known microorganisms, m / z values ​​of ions derived from each of the plurality of types of proteins contained in the known microorganisms; a protein database search unit that compares the mass spectrum of the test microorganism after the calibration by the first calibration unit with the m / z of ions derived from each of the multiple types of proteins registered in the protein database; a peak attribution section for attributing a peak on the mass spectrum of the calibrated test microorganism to a protein from which the peak originates, based on a comparison result by the protein database search section; The microorganism identification system according to claim 2 , comprising:

4. Furthermore, a second calibration unit that recalibrates the m / z axis of the mass spectrum of the test microorganism after the calibration based on the difference between the m / z of a peak assigned to any one of the plurality of types of proteins on the mass spectrum of the test microorganism after the calibration and the m / z of the protein stored in the protein database; The microorganism identification system according to claim 3 , comprising:

5. Obtaining a mass spectrum of the test microorganism; searching a peak interval database in which the taxonomic group to which each of the multiple known microorganisms belongs and the characteristic peak interval that is the peak interval characteristic of the taxonomic group among the intervals of the multiple peaks in the mass spectrum of the known microorganisms are stored in correspondence with each other, thereby selecting, from the characteristic peak intervals registered in the peak interval database, an interval that matches any of the intervals between the multiple peaks included in the mass spectrum of the test microorganism within a predetermined error range; Identifying a taxonomic group stored in the peak interval database in association with the selected characteristic peak interval as a taxonomic group to which the test microorganism belongs; Methods for identifying microorganisms.

6. Furthermore, calibrating the m / z axis of the mass spectrum of the test microorganism based on the difference between the m / z of a plurality of peaks forming the selected characteristic peak interval, which is stored in the peak interval database in association with the characteristic peak interval, and the m / z of a plurality of mass spectrum peaks forming a peak interval that matches the characteristic peak interval within a predetermined error range on the mass spectrum of the test microorganism; The method for identifying a microorganism according to claim 5.

7. Furthermore, Attributing a peak on the mass spectrum of the test microorganism after calibration to a protein from which the peak originates, based on a result of comparing the mass spectrum of the test microorganism after calibration with at least the m / z of an ion derived from each of the multiple proteins registered in a protein database storing, for each of the multiple types of known microorganisms, the m / z of an ion derived from each of the multiple proteins contained in the known microorganism. The method for identifying a microorganism according to claim 6.

8. Furthermore, recalibrating the m / z axis of the mass spectrum of the test microorganism after the calibration based on the difference between the m / z of a peak assigned to any one of the plurality of types of proteins on the mass spectrum of the test microorganism after the calibration and the m / z of the protein stored in the protein database; The method for identifying a microorganism according to claim 7.

9. A program for causing a computer to execute the method for identifying a microorganism according to any one of claims 5 to 8.

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