JP2020031592A - Methods, devices and programs for identifying microorganisms - Google Patents

Abstract

To provide methods, devices and programs for quickly and simply identifying seven species of the genus Cronobacter.SOLUTION: The method for identifying microorganism of the invention comprises a step of extracting mass-to-charge ratios of peaks derived from biomarkers in a mass spectrum obtained by conducting mass spectrometry to a sample, and a step of identifying Cronobacter species contained in the sample on the basis of the mass-to-charge ratios, where ribosome-related proteins L32, L25, L24, RaiA and L20 are used as the biomarkers.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a microorganism identification method, a microorganism identification device, and a program.

  There are seven species of Chronobacter spp., And they are known as causative bacteria of infant Chronobacter infection. In some cases, epidemiological studies have reported that infant formula (milk powder) is the source of infection for Chronobacter. For this reason, codex standards for Chronobacter bacteria have been set for powdered milk.

  Chronobacter bacteria can cause severe symptoms, such as sepsis and meningitis, in infants when they are infected. Therefore, when Chronobacter is detected from powdered milk products and manufacturing processes, it detects bacterial species that exist in the external environment such as around products and manufacturing equipment, and the bacterial species detected from the external environment and the product It is necessary to investigate the source of contamination by comparing the bacterial species detected from the plant and the manufacturing process, and to take prompt measures.

  A protein analysis method using matrix-assisted laser desorption / ionization time-of-flight mass spectrometry (MALDI-TOF MS) is known as a simple identification method of microorganism species such as bacteria (Patent Document 1, Patent Document 1) 2). When MALDI-TOF MS is used, analysis results can be obtained in a short time using a very small amount of microorganism sample, and continuous analysis of multiple samples is easy, so that simple and rapid microorganism identification is possible. This method utilizes that about half of the peaks of the mass spectrum obtained by MALDI-TOF MS are derived from ribosome-related proteins. Using a given ribosome-related protein as a biomarker, compare the mass-to-charge ratio of the peak that appeared in the mass spectrum obtained from mass analysis of the microorganism with the calculated mass (theoretical value of mass) of the ribosome-related protein of a known microorganism, The biomarkers are assigned to the peaks that appear. Then, the microorganisms contained in the sample are identified using the biomarkers assigned to the peaks of the mass spectrum as indices.

  Patent Literature 1 discloses a mass spectrum obtained by MALDI-TOF MS of a ribosomal subunit protein leaked from the inside of a cell and a mass spectrum identified as the mass of the ribosomal subunit protein of a cell line to be compared It is disclosed that the cell type can be quickly identified by comparing the mass spectrum obtained by MALDI-TOF MS with the mass spectrum of the database as an index, as compared with a database of MALDI-TOF MS. In Patent Document 1, the species of Pseudomonas putida is identified and the strains are classified.

  Patent Document 2 discloses that a ribosomal protein is used as a biomarker, a mass spectrum peak obtained by MALDI-TOF MS is assigned to the biomarker, and the serotype of the coliform group is identified using the biomarker assigned to the mass spectrum peak as an index. Is disclosed.

Japanese Patent No. 4818981 Japanese Patent No. 6238069

  Since peaks (ribosome-related proteins) that differ in mass differ depending on the classification level of microorganisms, in order to identify Clonobacter bacteria using mass spectra obtained by MALDI-TOF MS, it is necessary to identify Cronobacter bacteria. It is necessary to select available biomarkers. However, it is generally difficult to select biomarkers that can identify microorganisms that are genetically closely related to each other with high reproducibility, such as some strains of the genus Chronobacter. At present, a biomarker that can be suitably used for identifying a bacterial species has not yet been established.

  Also, 16S rRNA gene analysis is widely used as a method for identifying the species of microorganisms. However, some species of the genus Chronobacter are genetically very closely related, so that all seven species cannot be identified. . Other known methods include the MLST (Multilocus Sequence Typing) method and the PCR (Polymerase Chain Reaction, PCR) method for identifying the species of Chronobacter bacteria. Takes time.

  Therefore, there is a need for a method for identifying microorganisms that can quickly and easily identify seven species of Chronobacter.

  The present invention has been made in view of the above-described problems, and provides a microorganism identification method, a microorganism identification device, and a program capable of quickly and easily identifying seven species of Chronobacter. With the goal.

  The method for identifying microorganisms according to the present invention comprises, in a mass spectrum obtained by mass spectrometry of a sample, a mass-to-charge ratio of a peak derived from a biomarker, an extraction step of extracting from the mass spectrum, and based on the mass-to-charge ratio. Identifying the species of the genus Chronobacter included in the sample, and using ribosome-related proteins L32, L25, L24, RaiA and L20 as the biomarkers.

  The apparatus for identifying microorganisms of the present invention is based on the mass-to-charge ratio of a peak derived from a biomarker in a mass spectrum obtained by mass analysis of a sample, and an extraction unit that extracts the mass-to-charge ratio from the mass spectrum. And an identification unit for identifying the species of the genus Clonobacter contained in the sample, and ribosome-related proteins L32, L25, L24, RaiA and L20 are used as the biomarkers.

  A program of the present invention causes a computer to execute the above-described method for identifying a microorganism.

  According to the present invention, the species of Chronobacter are identified from the mass spectrum obtained by MALDI-TOF MS using the ribosome-related proteins L32, L25, L24, RaiA and L20 as biomarkers. Bacterial species can be identified quickly and easily.

It is a schematic diagram showing the composition of the identification device of the microorganisms of the embodiment of the present invention.

  As a result of intensive studies, the present inventors have found that seven species of Cronobacter bacteria (C. sakazakii, C. malonaticus, C. dublinensis, C. turicensis, C. universalis, C. condimenti and C. muytjensii) The present inventors have found that ribosome-related proteins L32, L25, L24, RaiA and L20 can be suitably used as a biomarker for distinguishing (1) by mass spectrometry, leading to the present invention. The invention described below is based on this finding. It should be noted that the following embodiments are merely examples for explanation, and the present invention is not limited to the following embodiments. The present invention is included in the scope of the present invention as long as it has the features of

(1) Overall Configuration of Microorganism Identification Apparatus According to Embodiment of the Present Invention As shown in FIG. 1, a microorganism identification apparatus 1 according to this embodiment includes a mass analysis unit 2, an identification processing unit 3, and a display unit 4. Have. The mass spectrometry unit 2 is a mass spectrometer (hereinafter, referred to as a MALDI-TOF MS device) that performs mass spectrometry of a sample by matrix-assisted laser desorption / ionization time-of-flight mass spectrometry (MALDI-TOF MS). The mass spectrometry unit 2 obtains mass spectrum data of the sample by MALDI-TOF MS. As the mass spectrometer 2, a known MALDI-TOF MS device can be used. Note that the configuration of the mass spectrometer 2 is not limited as long as a mass spectrum of the ribosome-related protein contained in the sample, particularly the ribosome-related substance of the biomarker can be obtained. For example, another soft ionization method was used. A mass spectrometer or other mass spectrometry techniques can also be used. In the present embodiment, a sample prepared by the method described in “(3-2) Analysis by MALDI-TOF MS” is used. A sample prepared by a general method as a method for preparing a sample for mass spectrometry by MALDI-TOF MS can also be used for mass spectrometry of the present embodiment.

  The identification processing unit 3 analyzes the mass spectrum data acquired from the mass spectrometry unit 2 using the biomarkers, and identifies the bacterial species contained in the sample. The identification processing unit 3 includes an acquisition unit 5, a selection unit 6, an extraction unit 7, an identification unit 8, and a storage unit 9. The identification processing unit 3 may be realized as a set of hardware, with each unit being individual hardware, and the entity of the identification processing unit 3 may be a personal computer (PC) or a workstation, for example, in the storage unit 9 as a storage device of the PC. It may be realized by executing the function of each unit by the stored program. The acquisition unit 5 acquires mass spectrum data obtained by analyzing the sample by the mass analysis unit 2 from the mass analysis unit 2 and sends the data to the selection unit 6. Upon receiving the mass spectrum data from the acquisition unit 5, the selection unit 6 reads a biomarker mass database in which the theoretical value of the mass of each biomarker is described for each type of Clonobacter bacterium.

  The biomarker mass database is obtained by calculating the theoretical value of the mass of each biomarker for each species of Clonobacter genus, and is stored in a database, and is stored in the storage unit 9 in advance. As described above, the biomarkers are ribosome-related proteins L32, L25, L24, RaiA, and L20. In the present embodiment, five biomarkers are used. Note that the theoretical value of the mass of the biomarker may differ depending on the type of bacteria even for the same biomarker. Therefore, the theoretical value of the mass of the biomarker is registered in the biomarker mass database for each bacterial species.

  The selecting unit 6 compares the mass-to-charge ratio (m / z) of the peak appearing in the mass spectrum with the theoretical value of the mass of the biomarker, and selects a peak derived from the biomarker in the mass spectrum (selection step). . More specifically, the selection unit 6 reads the mass-to-charge ratio of the peak from the mass spectrum data, compares the mass-to-charge ratio of the read peak with the theoretical value of the mass of each biomarker, and determines the mass-to-charge ratio of the biomarker. It is assumed that a peak that coincides with the theoretical mass value with an error within 500 ppm can be assigned to the biomarker. The selecting unit 6 performs this operation for other biomarkers, and selects a peak that can be attributed to the biomarker as a peak derived from the biomarker. The selection unit 6 sends mass spectrum data in which a peak derived from a biomarker has been selected to the extraction unit 7.

  The extraction unit 7 extracts the mass-to-charge ratio of the peak derived from the biomarker in the mass spectrum from the mass spectrum data (extraction step). More specifically, upon receiving the mass spectrum data from the selection unit 6, the extraction unit 7 extracts the mass-to-charge ratio of the peak derived from the biomarker selected by the selection unit 6 from the mass spectrum data in association with the biomarker. I do. For example, the extraction unit 7 associates the name of the ribosome-related protein of the biomarker with the mass-to-charge ratio of a peak derived from the biomarker. The extraction unit 7 sends the mass-to-charge ratio of the peak derived from the biomarker to the identification unit 8.

  The identification unit 8 identifies the species of Clonobacter genus contained in the sample based on the mass-to-charge ratio of the peak derived from the biomarker (identification step). Upon receiving the mass-to-charge ratio of the biomarker-derived peak, the identification unit 8 reads the biomarker mass database described above from the storage unit 9 and calculates the mass of the biomarker-derived peak obtained from the MALDI-TOF MS mass spectrum. The charge ratio (actual measured value of the mass of the biomarker) is compared with the theoretical value of the mass of the biomarker registered in the biomarker mass database. The identification unit 8 sequentially compares the biomarkers, and narrows down the bacterial species whose actual measured value of the mass matches the theoretical value of the mass with an error within 500 ppm. As a result of repeating the comparison operation, when the number of candidate bacterial species is reduced to one, the identifying unit 8 identifies the bacterial species as a bacterial species included in the sample. The identification unit 8 can display the identified bacterial species on the display unit 4 including, for example, a liquid crystal monitor, and allow the operator to confirm the identification result. The identification unit 8 can also store the identification result in the storage unit 9. At this time, the operator can input the name of the sample to the identification processing unit 3 using an input device (not shown), and the identification unit 8 can store the identification result together with the sample name in the storage unit 9.

  Depending on the prepared sample, some of the peaks derived from the biomarker ribosome-related protein may not be detected in the mass spectrum of the mass spectrometry by MALDI-TOF MS. However, in the present embodiment, since the ribosome-related proteins L32, L25, L24, RaiA and L20 are used as biomarkers, even in such a case, the species of Clonobacter genus contained in the sample is identified. it can. In addition, in the mass spectrum, some of the peaks derived from the biomarkers are not detected, and if it is difficult to identify the bacterial species, the same sample may be repeatedly subjected to mass spectrometry by MALDI-TOF MS, or described later. Mass spectrometry by MALDI-TOF MS using a sample that has been re-prepared back to the step of immobilizing the protein extract on the sample obtain. As a result, a peak derived from a biomarker that has not been detected in the previous mass spectrometry is detected, and it is possible to identify the bacterial species contained in the sample.

(2) Function and Effect In the above configuration, the microorganism identifying apparatus 1 extracts a mass-to-charge ratio of a biomarker-derived peak in a mass spectrum obtained by mass analysis of a sample from the mass spectrum (extraction step). ), Identifying the species of Clonobacter genus contained in the sample based on the mass-to-charge ratio (identification step), and using ribosome-related proteins L32, L25, L24, RaiA and L20 as biomarkers. did.

  Therefore, the microorganism identification device 1 identifies the species of the genus Clonobacter from the mass spectrum obtained by MALDI-TOF MS using the ribosome-related proteins L32, L25, L24, RaiA, and L20 as biomarkers. Seven species of genera can be identified quickly and easily.

(3) Selection of biomarkers In the present invention, the theoretical value of the mass of each ribosome-related protein and the MALDI-TOF MS of the reference strain of each of the seven Chronobacter bacteria are determined for each of the seven Chronobacter bacteria. By comparing the obtained ribosome-related proteins with the mass-to-charge ratios, ribosome-related proteins capable of distinguishing seven Chronobacter bacteria were selected, and the selected ribosome-related proteins were used as biomarkers. Hereinafter, selection of the biomarker will be described. Table 1 shows the reference strains of the seven species of Chronobacter genus used for the selection of biomarkers. JCM in Table 1 means that the source is the RIKEN BioResource Center, Microbial Material Development Department (Japan Collection of Microorganisms), and LMG means that the source is the Belgian Microorganisms Preservation Organization (Laboratorium voor Microbiologie). ATCC means that the source is the American Type Culture Collection.

(3-1) Calculation of theoretical value of mass of ribosome-related protein First, the theoretical value of mass of ribosome-related protein was calculated. First, the amino acid sequence information of the ribosome-related protein of each species of Chronobacter was obtained from the public database UniprotKB (Universal Protein Resource Knowledgebase) in which the amino acid sequence of the protein was published. Then, using the Compute pI / Mw tool (software that calculates the molecular weight from the amino acid sequence) of the Proteomics server ExPASy (Expert Protein Analysis System) provided by the Swiss Institute of Bioinformatics, the clonobacter spp. The theoretical value of the mass of the ribosome-related protein was calculated from the amino acid sequence of the ribosome-related protein of each bacterial species.

  In an expressed protein synthesized by ribosome translation, the starting terminal methionine residue is often cleaved by post-translational modification. The methionine residue is selected when the amino acid residue adjacent to the starting methionine residue (the second amino acid residue from the terminal) is any of glycine, alanine, serine, proline, valine, threonine, and cysteine. Is known to be easily cleaved (protein nucleic acid enzyme, Vol. 40, No. 4, p. 389-398 (1995)). Therefore, in the present invention, a ribosome-related protein in which the second amino acid residue from the terminal is glycine, alanine, serine, proline, valine, threonine, or cysteine is calculated in consideration of cleavage of methionine residues. The theoretical mass value was corrected by subtracting 131.19 Da from the calculated theoretical mass value. In addition, since the ions observed by MALDI-TOF MS are mainly protonated molecules [M + H] +, in the present invention, the mass 1.01 Da of the proton is added to the calculated theoretical value of the mass to obtain the theoretical value of the mass. Values were corrected.

(3-2) Analysis by MALDI-TOF MS Subsequently, mass analysis was performed by MALDI-TOF MS using a reference strain of the genus Clonobacter as a sample to obtain a mass spectrum. Here, a method of obtaining a mass spectrum by MALDI-TOF MS will be described by taking mass spectrometry of a reference strain of C. sakazakii as an example. The following methods are only typical examples, and the scope of the present invention is not limited thereto.

  First, a reference strain of C. sakazakii was spread on a trypticase soy agar medium (TSA: Trypticase Soy Agar, BD (BBL)) and cultured at 37 ° C. for 24 hours. Next, about half of the C. sakazakii colonies grown on the medium were collected and suspended in 300 μl of ultrapure water (Milli-Q water). To the suspension, 900 μl of ethanol for residual agricultural chemicals / PCB test (manufactured by Fujifilm Wako Pure Chemical Industries, Ltd.) was added, mixed, and centrifuged (centrifugation conditions: 21,500 × g, 2 min, 25 ° C.). The supernatant was removed and centrifuged again under the same conditions. The precipitate obtained by removing the supernatant was suspended in 70 μl of a 70% formic acid solution prepared using high-concentration formic acid (special grade, manufactured by Fujifilm Wako Pure Chemical Co., Ltd.), and tested for residual agricultural chemicals and PCB. After adding 70 μl of acetonitrile for use (manufactured by Fujifilm Wako Pure Chemical Industries, Ltd.), the suspension was mixed. The suspension was centrifuged (centrifugation conditions: 21,500 × g, 2 min, 25 ° C.), and the supernatant was used as a protein extract. The culture conditions of the reference strain and the method of extracting the ribosome-related protein are not limited to the above, and a sufficient amount of the ribosome-related protein to finally observe the molecular weight-related peak of the ribosome-related protein is taken out from the inside of the cell. And any conventionally known culture method or ribosome-related protein extraction / purification method may be used.

  Using a sinapinic acid as a matrix agent, a 50% acetonitrile solution containing 10 mg of sinapinic acid (manufactured by Fujifilm Wako Pure Chemical) and trifluoroacetic acid (special grade, manufactured by Fujifilm Wako Pure Chemical) at a concentration of 1%. To prepare a matrix agent solution. 1 μl of this matrix agent solution was dropped on a sample plate for MALDI-TOF measurement and air-dried. Thereafter, 1 μl of the protein extract was dropped on the region of the sample plate where the matrix agent solution was dropped, and dried. Thereafter, 1 μl of the matrix agent solution was again dropped into the region where the protein extract was dropped, and dried to obtain a sample of the C. sakazakii reference strain. The sample preparation method for MALDI-TOFMS measurement is not limited to the above, and may be performed according to a conventionally known sample preparation method used in MALDI-TOFMS measurement of proteins. In the above, sinapinic acid was used as the matrix agent, but CHCA (α-cyano-4-hydroxycinnamic acid) or the like can also be used.

  For the measurement, an autoflex speed (manufactured by Bruker) was used as a MALDI-TOF MS apparatus, and a flex control attached to the apparatus was used as measurement software. In the measurement software, the positive linear mode was selected, and the mass spectrum of the sample prepared by setting the spectrum range to m / z 3000 to 20000 was performed to obtain a mass spectrum of the C. sakazakii reference strain. For analysis of the mass spectrum, analysis software flex analysis attached to the apparatus was used. In the analysis, peaks having a signal-to-noise (S / N) ratio of 3 or more and a relative intensity threshold (Relative Intensity Threshold) of 1% or more were targeted. From the mass spectrum data of the C. sakazakii reference strain, the mass charge of the peak was determined. The ratio was read, and the mass-to-charge ratio of the read peak was compared with the theoretical value of the mass of the ribosome-related protein of the C. sakazakii reference strain. Then, it is assumed that the ribosome-related protein can be assigned to the peak whose mass-to-charge ratio matches the theoretical value of the mass of the ribosome-related protein of the C. sakazakii reference strain with an error within 500 ppm, and the ribosome-related protein is assigned to the peak of the mass spectrum. The protein was assigned. The results are shown in Table 2 together with theoretical values of the mass of the ribosome-related protein. Table 2 shows C. sakazakii and C. malonaticus. The gray spots in Table 2 indicate that no peak corresponding to the ribosome-related protein was observed. The unit is [Da]. This operation was performed on reference strains of all strains of the genus Clonobacter. Note that the method of acquiring and analyzing the mass spectrum is not limited to the above, and any conventionally known apparatus, measurement mode, spectrum range, analysis software, S / N ratio, relative intensity, and the like may be appropriately selected and combined.

(3-3) Selection of biomarker The theoretical value of the mass of each ribosome-related protein calculated for each species of Clonobacter genus, and each ribosome-related protein obtained from the mass spectrometry result of the reference strain of each strain Using the mass-to-charge ratio of the peak attributed to, a ribosome-related protein serving as a biomarker capable of identifying the species of Chronobacter was searched. As a result, it was found that seven reference strains of the genus Clonobacter can be distinguished from the mass patterns (patterns of theoretical mass values) of the five ribosome-related proteins (L32, L25, L24, RaiA, and L20). Proteins L32, L25, L24, RaiA and L20 were selected as biomarkers. Some ribosome-related proteins are hardly observed as peaks in mass spectrometry of mass spectrometry. Therefore, combining these five biomarkers made it possible to identify the species of the genus Clonobacter.

  Table 3 shows the theoretical value of the mass of the biomarker for each bacterial species and the mass-to-charge ratio of the biomarker obtained from the mass spectrometry results of each reference strain, that is, the measured value of the mass of the biomarker. In Table 3, for the same ribosome-related protein, there are bacterial strains in which Roman numerals and theoretical values of mass are described, and bacterial species in which only Roman numerals are described. In Table 3, in the same ribosome-related protein, the bacterial species with the same Roman numeral means that the theoretical mass value is the same. For example, the column L32 of C. malonaticus describes the Roman numeral I. This means that the theoretical value of the mass of L32 of C. malonaticus is the same as the theoretical value of the mass of L32 of C. sakazakii. If "No registration" is described, the amino acid sequence of the bacterial species and ribosome-related protein corresponding to the column of no registration is not registered in the amino acid sequence database (UniprotKB), and the theoretical mass Means that could not be calculated. A blank column means that there was no peak corresponding to the ribosome-related protein among the peaks appearing in the mass spectrum. The biomarker mass database used for the attribution of the biomarker to the peak of the mass spectrum and the identification of the bacterial species contained in the sample, as described in the above “(1) Overall configuration of the apparatus for identifying a microorganism according to the embodiment of the present invention” Is a table of Table 3 showing, for example, the theoretical value of the mass, and summarizes the theoretical value of the mass of each biomarker for each bacterial species.

(3-4) Verification of biomarker As verification of the biomarker, the ribosome-related proteins L32, L25, L24, RaiA, and the like were evaluated using the mass-to-charge ratio obtained from the mass spectrometry results of each reference strain shown in Table 3. It was verified whether L20 can be used as a biomarker to identify seven reference strains.

  First, using the data of C. sakazakii, it was verified whether the biomarker of the present invention could identify the bacterial species contained in the sample as C. sakazakii. When the theoretical value of the biomarker L20 was compared with the mass-to-charge ratio of L20 of C. sakazakii, it coincided with the theoretical mass of I, so that the bacterial species could be narrowed down to C. sakazakii and C. condimenti. Next, when the theoretical value of the biomarker L25 is compared with the mass-to-charge ratio of L.25 of C. sakazakii, it matches the theoretical mass of I. Therefore, it was possible to identify that the strain of the data of C. sakazakii was C. sakazakii. In this case, C. sakazakii was identified from the seven bacterial species using the biomarkers L20 and L25. For example, even when no peak corresponding to L25 was detected, a peak corresponding to L24 was detected. Then, since the theoretical value of L24 is different between C. sakazakii and C. condimenti, C. sakazakii could be identified using L20 and L24.

  Next, using the data of C. malonaticus, it was verified whether the biomarker of the present invention can identify that the bacterial species contained in the sample is C. malonaticus. When the theoretical value of the biomarker L20 is compared with the mass-to-charge ratio of L20 of C. malonaticus, it matches the theoretical value of II. Therefore, it was possible to identify that the species of the data of C. malonaticus was C. malonaticus. In this case, C. malonaticus was identified from the seven bacterial species using the biomarker L20. For example, even if no peak corresponding to L20 was detected, C. malonaticus showed that the theoretical value of RaiA was different from that of other species. Since it is different from the 6 bacterial species, C. malonaticus could be identified using RaiA.

  Next, using the data of C. dublinensis, it was verified whether the biomarker of the present invention could identify that the strain contained in the sample was C. dublinensis. When comparing the theoretical value of the biomarker L20 with the mass-to-charge ratio of L20 of C. dublinensis, it matches the theoretical value of III, so that it is possible to narrow down the bacterial species to C. dublinensis, C. universalis, and C. muytjensii. did it. Next, when the theoretical value of the biomarker L25 is compared with the mass-to-charge ratio of the C. dublinensis L25, it matches the theoretical value II. Therefore, it was possible to identify that the strain of the data of C. dublinensis was C. dublinensis. In this case, C. dublinensis was identified from the seven bacterial species using the biomarkers L20 and L25. For example, even when no peak corresponding to L20 was detected at all, the biomarkers RaiA and L25 were used. C. dublinensis could be identified. Specifically, by comparing the theoretical value of RaiA with the mass-to-charge ratio of RaiA of C. dublinensis, the bacterial species can be narrowed down to C. sakazakii, C. dublinensis, and C. muytjensii. C. dublinensis could be identified by comparing the theoretical value with the mass-to-charge ratio of L.25 of C. dublinensis.

  Subsequently, using the data of C. turicensis, it was verified whether the biomarker of the present invention could identify that the bacterial species contained in the sample was C. turicensis. When the theoretical value of the biomarker L24 was compared with the mass-to-charge ratio of L.24 of C. turicensis, it coincided with the theoretical value of mass II, so that the bacterial species could be narrowed down to C. turicensis and C. universalis. Next, when the theoretical value of the biomarker L25 and the mass-to-charge ratio of L25 of C. turicensis are compared, they agree with the theoretical value of II. Therefore, it was possible to identify that the strain of the data of C. turicensis was C. turicensis. In this case, C. turicensis was identified from the seven bacterial species using the biomarkers L24 and L25. For example, even when no peak corresponding to L24 was detected, the biomarkers L32 and L25 were used. C. turicensis could be identified. Specifically, by comparing the theoretical value of L32 with the mass-to-charge ratio of L.32 of C. turicensis, the bacterial species can be narrowed down to C. turicensis and C. universalis, and then the theoretical value of L25, By comparing the mass-to-charge ratio of C. turicensis L25, C. turicensis could be identified.

  Next, using the data of C. universalis, it was verified whether the biomarker of the present invention could identify that the bacterial species contained in the sample was C. universalis. When the theoretical value of the biomarker L24 was compared with the mass-to-charge ratio of L.24 of C. universalis, it coincided with the theoretical value of mass II, so that the bacterial species could be narrowed down to C. universalis and C. turicensis. Next, when the theoretical value of the biomarker L25 is compared with the mass-to-charge ratio of L.25 of C. universalis, it matches the theoretical value I. Therefore, it was possible to identify that the strain of the data of C. universalis was C. universalis. In this case, C. universalis was identified from the seven bacterial species using the biomarkers L24 and L25. For example, even when no peak corresponding to L24 was detected, the biomarkers L32 and L25 were used. C. universalis could be identified. Even when no peak corresponding to L25 was detected, C. universalis was able to identify C. universalis using RaiA because the theoretical value of RaiA was different from the other six strains. Furthermore, if a peak corresponding to L20 of C. universalis and C. turicensis was detected in this case, C. universalis could be identified using L32 and L20 or L24 and L20.

  Subsequently, using the data of C. condimenti, it was verified whether the biomarker of the present invention could identify that the strain contained in the sample was C. condimenti. When the theoretical value of the biomarker L20 and the mass-to-charge ratio of L20 of C. condimenti were compared with each other, they matched the theoretical value of I, so that the bacterial species could be narrowed down to C. condimenti and C. sakazakii. Next, when the theoretical value of the biomarker L25 and the mass-to-charge ratio of L.25 of C. condimenti are compared, they agree with the theoretical value II. Therefore, it was possible to identify that the strain of the data of C. condimenti was C. condimenti. In this case, since no peak corresponding to L.24 of C. condimenti was detected, C. condimenti was identified from seven bacterial species using biomarkers L20 and L25. For example, peaks corresponding to L20 and L25 were detected. Even if no was detected, if a peak corresponding to L24 was detected, the theoretical value of L.24 was different from the other six strains, so it was possible to identify C. condimenti using L24. did it.

  Finally, using the data of C. muytjensii, it was verified whether the strain contained in the biomarker of the present invention could be identified as C. muytjensii. Comparing the theoretical value of the biomarker L20 with the mass-to-charge ratio of L20 of C. muytjensii, which matches the theoretical mass of III, it is possible to narrow down the bacterial species to C. muytjensii, C. dublinensis, and C. universalis. did it. Next, comparing the theoretical value of the biomarker L25 with the mass-to-charge ratio of L25 of C. muytjensii, which matches the theoretical value I, the bacterial species could be narrowed down to C. muytjensii and C. universalis. A comparison of the theoretical value of the biomarker L24 with the mass-to-charge ratio of C. muytjensii L24 agrees with the theoretical value of I. Therefore, it was possible to identify that the strain of the data of C. muytjensii was C. muytjensii. In this case, C. muytjensii was identified from the seven strains using the biomarkers L20, L25 and L24. For example, even when no peak corresponding to L24 was detected, C. muytjensii and C. universalis Since the theoretical value of L32 was different, C. muytjensii could be identified using L32 instead of L24. Similarly, C. muytjensii could be identified by using RaiA instead of L24.

  From the above, it was confirmed that the use of the ribosome-related proteins L32, L25, L24, RaiA, and L20 as biomarkers allowed the identification of seven species of Chronobacter genus. In the present invention, since five ribosome-related proteins L32, L25, L24, RaiA and L20 are used as biomarkers, there are a plurality of combinations of biomarkers capable of identifying bacterial species. Therefore, in the present invention, even when, for example, one peak corresponding to a biomarker is not detected in the mass spectrum, the bacterial species can sometimes be identified by a combination of other biomarkers. Therefore, in the present invention, the number of cases where the mass spectrum is re-measured by MALDI-TOF MS can be reduced as much as the bacterial species can be identified by other combinations, and the bacterial species can be specified more easily.

(3-5) Verification of validity of bacterial species identification using biomarkers It was verified whether the results of bacterial species identification performed using ribosome-related proteins L32, L25, L24, RaiA, and L20 as biomarkers were valid. . The verification was carried out using the results of MALDI-TOF MS to identify the species using biomarkers according to the method of the present invention, and the gene analysis method Multilocus, which is said to be able to identify all seven species of Chronobacter. This was performed by comparing the results with the identification results obtained by the Sequence Typing (MLST) method. The MLST method is a molecular epidemiological analysis method for classifying fungal and bacterial strains. It is said that among the genes to be analyzed, seven species of Clonobacter genus can be identified by comparing the nucleotide sequence of fusA. (J. Clin. Microbiol., Vol. 50, No. 9, p. 3031-3039 (2012)). In the verification, the strains of 30 species of Clonobacter genus isolated from various environments and foods were identified by the method of the present invention and the MLST method.

  Since the identification of the bacterial species by the method of the present invention is the same as the method described above, the description will be omitted. Here, a method of analyzing the base sequence of the fusA gene of each strain by the MLST method will be described by taking as an example a case where one strain selected from 30 strains of Chronobacter is identified by the MLST method. First, the selected strain of Chronobacter was cultured. Then, DNA was extracted from the cultured Chronobacter bacterium. A small amount of a cultured colony of Chronobacter was suspended in 100 μl of a gene extraction reagent PrepMan Ultra (manufactured by Applied Biosystems) and heat-treated at 100 ° C. for 10 minutes. Thereafter, the mixture was centrifuged (centrifugation conditions: 21,500 × g, 3 minutes, 25 ° C.), and the supernatant was obtained as a DNA extract.

  Amplification reaction of the gene region fusA was carried out on the DNA of the genus Clonobacter extracted in the DNA extract using primers (Forward-GAAACCGTATGGCGTCAG, Reverse-AGAACCGAAGTGCAGACG). After the amplification product was purified using illustra GFX PCR DNA and Gel Band Purification Kit (GE Healthcare), a cycle sequence reaction was performed using primers (Forward-GCTGGATGCGGTAATTGA, Reverse-CCCATACCAGCGATGATG). Table 4 shows the conditions of the amplification reaction and the cycle sequence reaction (PCR conditions).

  After the amplification product obtained by the cycle sequence reaction was purified using DyeEx 2.0 Spin Kit (manufactured by QIAGEN), the nucleotide sequence of fusA was analyzed by a sequencer. The obtained nucleotide sequence was input to the MLST analysis database PubMLST, and the bacterial species was identified from the nucleotide sequence pattern of fusA. This operation was performed for other Chronobacter bacteria, and all 30 strains of Chronobacter were identified. Table 5 shows the analysis results by the method of the present invention and the analysis results by the MLST method.

  Table 5 also shows the mass-to-charge ratio of the peak observed by MALDI-TOF MS and to which the biomarker was assigned. The line “MALDI” in Table 5 shows the identification result by the method of the present invention, and the line “MLST” shows the identification result by the MLST method. As shown in Table 5, the identification results obtained by the method of the present invention all matched the identification results obtained by the MLST method. Thus, it was confirmed that the results of the identification of the seven species of Chronobacter by the method of the present invention were appropriate.

  In some strains, there were biomarkers for which no assigned peak was observed. However, by combining the mass patterns of the other biomarkers, it was possible to narrow down the species of the 30 strains of Clonobacter genus used for verification to one species. For example, in B-1391, the peaks of biomarkers L32, L25, and L24 were not observed, but the bacterial species could be identified as C. universalis by the peak of RaiA (m / z 12788.6). The 30 strains of Clonobacter bacteria used for the verification were identified as 23 strains of C. sakazakii, 3 strains of C. malonaticus, 2 strains of C. universalis, 1 strain of C. turicensis, and 1 strain of C. dublinensis.

(4) Comparative Example As a comparative example, an experiment was performed to identify seven reference strains of the genus Clonobacter by 16S rRNA gene analysis (500 bp) which is often used as a microorganism identification technique.

  First, reference strains of the genus Clonobacter were each cultured. Next, a small amount of a cultured colony of a standard strain of Clonobacter was suspended in 100 μl of a gene extraction reagent PrepMan Ultra (manufactured by Applied Biosystems), and heat-treated at 100 ° C. for 10 minutes. Thereafter, the mixture was centrifuged (centrifugation conditions: 21,500 × g, 3 minutes, 25 ° C.), and the supernatant was obtained as a DNA extract.

  Using the FAST MicroSeq 500 16S rDNA PCR Kit (Applied Biosystems), the obtained DNA extract was used to amplify the 16S rRNA gene region of the DNA extracted from the genus Clonobacter. After the amplification product was purified using GFX PCR DNA and Gel Band Purification Kit (GE Healthcare), a cycle sequence reaction was performed using MicroSeq 500 16S rDNA Bacterial Sequencing Kit (Applied Biosystems). Table 6 shows the conditions of the amplification reaction and the cycle sequence reaction (PCR conditions).

  After purifying the amplification product obtained by the cycle sequence reaction using the DyeEx 2.0 Spin Kit (manufactured by QIAGEN), the nucleotide sequence of DNA extracted from the genus Chronobacter by a sequencer (ABI PRISM Genetic Analyzer 3500xL, manufactured by Applied Biosystems) Was analyzed. The analyzed nucleotide sequence was input to the database EZ taxon, and strains having a homology of 99% or more were identified as strains of the reference strain. This was done for the other reference stocks. As a result, as shown in Table 7, in C. sakazakii and C. malonaticus, the homology of both reference strains was 99% or more, and C. sakazakii and C. malonaticus could not be distinguished from each other. Was. In addition, for C. turicensis and C. universalis, the homology of both reference strains was 99% or more, and C. turicensis and C. universalis could not be distinguished.

REFERENCE SIGNS LIST 1 identification device 2 mass analysis unit 3 identification processing unit 4 display unit 5 acquisition unit 6 selection unit 7 extraction unit 8 identification unit 9 storage unit

  The present invention relates to a microorganism identification method, a microorganism identification device, and a program.

  There are seven species of Chronobacter spp., And they are known as causative bacteria of infant Chronobacter infection. In some cases, epidemiological studies have reported that infant formula (milk powder) is the source of infection for Chronobacter. For this reason, codex standards for Chronobacter bacteria have been set for powdered milk.

  Chronobacter bacteria can cause severe symptoms, such as sepsis and meningitis, in infants when they are infected. Therefore, when Chronobacter is detected from powdered milk products and manufacturing processes, it detects bacterial species that exist in the external environment such as around products and manufacturing equipment, and the bacterial species detected from the external environment and the product It is necessary to investigate the source of contamination by comparing the bacterial species detected from the plant and the manufacturing process, and to take prompt measures.

  A protein analysis method using matrix-assisted laser desorption / ionization time-of-flight mass spectrometry (MALDI-TOF MS) is known as a simple identification method of microorganism species such as bacteria (Patent Document 1, Patent Document 1) 2). When MALDI-TOF MS is used, analysis results can be obtained in a short time using a very small amount of microorganism sample, and continuous analysis of multiple samples is easy, so that simple and rapid microorganism identification is possible. This method utilizes that about half of the peaks of the mass spectrum obtained by MALDI-TOF MS are derived from ribosome-related proteins. Using a given ribosome-related protein as a biomarker, compare the mass-to-charge ratio of the peak that appeared in the mass spectrum obtained from mass analysis of the microorganism with the calculated mass (theoretical value of mass) of the ribosome-related protein of a known microorganism, The biomarkers are assigned to the peaks that appear. Then, the microorganisms contained in the sample are identified using the biomarkers assigned to the peaks of the mass spectrum as indices.

  Patent Literature 1 discloses a mass spectrum obtained by MALDI-TOF MS of a ribosomal subunit protein leaked from the inside of a cell and a mass spectrum identified as the mass of the ribosomal subunit protein of a cell line to be compared It is disclosed that the cell type can be quickly identified by comparing the mass spectrum obtained by MALDI-TOF MS with the mass spectrum of the database as an index, as compared with a database of MALDI-TOF MS. In Patent Document 1, the species of Pseudomonas putida is identified and the strains are classified.

  Patent Document 2 discloses that a ribosomal protein is used as a biomarker, a mass spectrum peak obtained by MALDI-TOF MS is assigned to the biomarker, and the serotype of the coliform group is identified using the biomarker assigned to the mass spectrum peak as an index. Is disclosed.

Japanese Patent No. 4818981 Japanese Patent No. 6238069

  Since peaks (ribosome-related proteins) that differ in mass differ depending on the classification level of microorganisms, in order to identify Clonobacter bacteria using mass spectra obtained by MALDI-TOF MS, it is necessary to identify Cronobacter bacteria. It is necessary to select available biomarkers. However, it is generally difficult to select biomarkers that can identify microorganisms that are genetically closely related to each other with high reproducibility, such as some strains of the genus Chronobacter. At present, a biomarker that can be suitably used for identifying a bacterial species has not yet been established.

  Also, 16S rRNA gene analysis is widely used as a method for identifying the species of microorganisms. However, some species of the genus Chronobacter are genetically very closely related, so that all seven species cannot be identified. . Other known methods include the MLST (Multilocus Sequence Typing) method and the PCR (Polymerase Chain Reaction, PCR) method for identifying the species of Chronobacter bacteria. Takes time.

  Therefore, there is a need for a method for identifying microorganisms that can quickly and easily identify seven species of Chronobacter.

  The present invention has been made in view of the above-described problems, and provides a microorganism identification method, a microorganism identification device, and a program capable of quickly and easily identifying seven species of Chronobacter. With the goal.

  The method for identifying microorganisms according to the present invention comprises, in a mass spectrum obtained by mass spectrometry of a sample, a mass-to-charge ratio of a peak derived from a biomarker, an extraction step of extracting from the mass spectrum, and based on the mass-to-charge ratio. Identifying the species of the genus Chronobacter included in the sample, and using ribosome-related proteins L32, L25, L24, RaiA and L20 as the biomarkers.

  The apparatus for identifying microorganisms of the present invention is based on the mass-to-charge ratio of a peak derived from a biomarker in a mass spectrum obtained by mass analysis of a sample, and an extraction unit that extracts the mass-to-charge ratio from the mass spectrum. And an identification unit for identifying the species of the genus Clonobacter contained in the sample, and ribosome-related proteins L32, L25, L24, RaiA and L20 are used as the biomarkers.

  A program of the present invention causes a computer to execute the above-described method for identifying a microorganism.

  According to the present invention, the species of Chronobacter are identified from the mass spectrum obtained by MALDI-TOF MS using the ribosome-related proteins L32, L25, L24, RaiA and L20 as biomarkers. Bacterial species can be identified quickly and easily.

It is a schematic diagram showing the composition of the identification device of the microorganisms of the embodiment of the present invention.

  As a result of intensive studies, the present inventors have found that seven species of Cronobacter bacteria (C. sakazakii, C. malonaticus, C. dublinensis, C. turicensis, C. universalis, C. condimenti and C. muytjensii) The present inventors have found that ribosome-related proteins L32, L25, L24, RaiA and L20 can be suitably used as a biomarker for distinguishing (1) by mass spectrometry, leading to the present invention. The invention described below is based on this finding. It should be noted that the following embodiments are merely examples for explanation, and the present invention is not limited to the following embodiments. The present invention is included in the scope of the present invention as long as it has the features of

(1) Overall Configuration of Microorganism Identification Apparatus According to Embodiment of the Present Invention As shown in FIG. 1, a microorganism identification apparatus 1 according to this embodiment includes a mass analysis unit 2, an identification processing unit 3, and a display unit 4. Have. The mass spectrometer 2 is a mass spectrometer (hereinafter, referred to as a MALDI-TOF MS device) that performs mass spectrometry of a sample by matrix-assisted laser desorption / ionization time-of-flight mass spectrometry (MALDI-TOF MS). The mass spectrometry unit 2 obtains mass spectrum data of the sample by MALDI-TOF MS. As the mass spectrometer 2, a known MALDI-TOF MS device can be used. Note that the configuration of the mass spectrometer 2 is not limited as long as a mass spectrum of the ribosome-related protein contained in the sample, particularly the ribosome-related substance of the biomarker can be obtained. For example, another soft ionization method was used. A mass spectrometer or other mass spectrometry techniques can also be used. In the present embodiment, a sample prepared by the method described in “(3-2) Analysis by MALDI-TOF MS” is used. A sample prepared by a general method as a method for preparing a sample for mass spectrometry by MALDI-TOF MS can also be used for mass spectrometry of the present embodiment.

  The identification processing unit 3 analyzes the mass spectrum data acquired from the mass spectrometry unit 2 using the biomarkers, and identifies the bacterial species contained in the sample. The identification processing unit 3 includes an acquisition unit 5, a selection unit 6, an extraction unit 7, an identification unit 8, and a storage unit 9. The identification processing unit 3 may be realized as a set of hardware, with each unit being individual hardware, and the entity of the identification processing unit 3 may be a personal computer (PC) or a workstation, for example, in the storage unit 9 as a storage device of the PC. It may be realized by executing the function of each unit by the stored program. The acquisition unit 5 acquires mass spectrum data obtained by analyzing the sample by the mass analysis unit 2 from the mass analysis unit 2 and sends the data to the selection unit 6. Upon receiving the mass spectrum data from the acquisition unit 5, the selection unit 6 reads a biomarker mass database in which the theoretical value of the mass of each biomarker is described for each type of Clonobacter bacterium.

  The biomarker mass database is obtained by calculating the theoretical value of the mass of each biomarker for each species of Clonobacter genus, and is stored in a database, and is stored in the storage unit 9 in advance. As described above, the biomarkers are ribosome-related proteins L32, L25, L24, RaiA, and L20. In the present embodiment, five biomarkers are used. Note that the theoretical value of the mass of the biomarker may differ depending on the type of bacteria even for the same biomarker. Therefore, the theoretical value of the mass of the biomarker is registered in the biomarker mass database for each bacterial species.

  The selecting unit 6 compares the mass-to-charge ratio (m / z) of the peak appearing in the mass spectrum with the theoretical value of the mass of the biomarker, and selects a peak derived from the biomarker in the mass spectrum (selection step). . More specifically, the selection unit 6 reads the mass-to-charge ratio of the peak from the mass spectrum data, compares the mass-to-charge ratio of the read peak with the theoretical value of the mass of each biomarker, and determines the mass-to-charge ratio of the biomarker. It is assumed that a peak that coincides with the theoretical mass value with an error within 500 ppm can be assigned to the biomarker. The selecting unit 6 performs this operation for other biomarkers, and selects a peak that can be attributed to the biomarker as a peak derived from the biomarker. The selection unit 6 sends mass spectrum data in which a peak derived from a biomarker has been selected to the extraction unit 7.

  The extraction unit 7 extracts the mass-to-charge ratio of the peak derived from the biomarker in the mass spectrum from the mass spectrum data (extraction step). More specifically, upon receiving the mass spectrum data from the selection unit 6, the extraction unit 7 extracts the mass-to-charge ratio of the peak derived from the biomarker selected by the selection unit 6 from the mass spectrum data in association with the biomarker. I do. For example, the extraction unit 7 associates the name of the ribosome-related protein of the biomarker with the mass-to-charge ratio of a peak derived from the biomarker. The extraction unit 7 sends the mass-to-charge ratio of the peak derived from the biomarker to the identification unit 8.

  The identification unit 8 identifies the species of Clonobacter genus contained in the sample based on the mass-to-charge ratio of the peak derived from the biomarker (identification step). Upon receiving the mass-to-charge ratio of the biomarker-derived peak, the identification unit 8 reads the biomarker mass database described above from the storage unit 9 and calculates the mass of the biomarker-derived peak obtained from the MALDI-TOF MS mass spectrum. The charge ratio (actual measured value of the mass of the biomarker) is compared with the theoretical value of the mass of the biomarker registered in the biomarker mass database. The identification unit 8 sequentially compares the biomarkers, and narrows down the bacterial species whose actual measured value of the mass matches the theoretical value of the mass with an error within 500 ppm. As a result of repeating the comparison operation, when the number of candidate bacterial species is reduced to one, the identifying unit 8 identifies the bacterial species as a bacterial species included in the sample. The identification unit 8 can display the identified bacterial species on the display unit 4 including, for example, a liquid crystal monitor, and allow the operator to confirm the identification result. The identification unit 8 can also store the identification result in the storage unit 9. At this time, the operator can input the name of the sample to the identification processing unit 3 using an input device (not shown), and the identification unit 8 can store the identification result together with the sample name in the storage unit 9.

  Depending on the prepared sample, some of the peaks derived from the biomarker ribosome-related protein may not be detected in the mass spectrum of the mass spectrometry by MALDI-TOF MS. However, in the present embodiment, since the ribosome-related proteins L32, L25, L24, RaiA and L20 are used as biomarkers, even in such a case, the species of Clonobacter genus contained in the sample is identified. it can. In addition, in the mass spectrum, some of the peaks derived from the biomarkers are not detected, and if it is difficult to identify the bacterial species, the same sample may be repeatedly subjected to mass spectrometry by MALDI-TOF MS, or described later. Mass spectrometry by MALDI-TOF MS using a sample that has been re-prepared back to the step of immobilizing the protein extract on the sample obtain. As a result, a peak derived from a biomarker that has not been detected in the previous mass spectrometry is detected, and it is possible to identify the bacterial species contained in the sample.

(2) Function and Effect In the above configuration, the microorganism identifying apparatus 1 extracts a mass-to-charge ratio of a biomarker-derived peak in a mass spectrum obtained by mass analysis of a sample from the mass spectrum (extraction step). ), Identifying the species of Clonobacter genus contained in the sample based on the mass-to-charge ratio (identification step), and using ribosome-related proteins L32, L25, L24, RaiA and L20 as biomarkers. did.

  Therefore, the microorganism identification device 1 identifies the species of the genus Clonobacter from the mass spectrum obtained by MALDI-TOF MS using the ribosome-related proteins L32, L25, L24, RaiA, and L20 as biomarkers. Seven species of genera can be identified quickly and easily.

(3) Selection of biomarkers In the present invention, the theoretical value of the mass of each ribosome-related protein and the MALDI-TOF MS of the reference strain of each of the seven Chronobacter bacteria are determined for each of the seven Chronobacter bacteria. By comparing the obtained ribosome-related proteins with the mass-to-charge ratios, ribosome-related proteins capable of distinguishing seven Chronobacter bacteria were selected, and the selected ribosome-related proteins were used as biomarkers. Hereinafter, selection of the biomarker will be described. Table 1 shows the reference strains of the seven species of Chronobacter genus used for the selection of biomarkers. JCM in Table 1 means that the source is the RIKEN BioResource Center, Microbial Material Development Department (Japan Collection of Microorganisms), and LMG means that the source is the Belgian Microorganisms Preservation Organization (Laboratorium voor Microbiologie). ATCC means that the source is the American Type Culture Collection.

(3-1) Calculation of theoretical value of mass of ribosome-related protein First, the theoretical value of mass of ribosome-related protein was calculated. First, the amino acid sequence information of the ribosome-related protein of each species of Chronobacter was obtained from the public database UniprotKB (Universal Protein Resource Knowledgebase) in which the amino acid sequence of the protein was published. Then, using the Compute pI / Mw tool (software that calculates the molecular weight from the amino acid sequence) of the Proteomics server ExPASy (Expert Protein Analysis System) provided by the Swiss Institute of Bioinformatics, the clonobacter spp. The theoretical value of the mass of the ribosome-related protein was calculated from the amino acid sequence of the ribosome-related protein of each bacterial species.

  In an expressed protein synthesized by ribosome translation, the starting terminal methionine residue is often cleaved by post-translational modification. The methionine residue is selected when the amino acid residue adjacent to the starting methionine residue (the second amino acid residue from the terminal) is any of glycine, alanine, serine, proline, valine, threonine, and cysteine. Is known to be easily cleaved (protein nucleic acid enzyme, Vol. 40, No. 4, p. 389-398 (1995)). Therefore, in the present invention, a ribosome-related protein in which the second amino acid residue from the terminal is glycine, alanine, serine, proline, valine, threonine, or cysteine is calculated in consideration of cleavage of methionine residues. The theoretical mass value was corrected by subtracting 131.19 Da from the calculated theoretical mass value. In addition, since the ions observed by MALDI-TOF MS are mainly protonated molecules [M + H] +, in the present invention, the mass 1.01 Da of the proton is added to the calculated theoretical value of the mass to obtain the theoretical value of the mass. Values were corrected.

(3-2) Analysis by MALDI-TOF MS Subsequently, mass analysis was performed by MALDI-TOF MS using a reference strain of the genus Clonobacter as a sample to obtain a mass spectrum. Here, a method of obtaining a mass spectrum by MALDI-TOF MS will be described by taking mass spectrometry of a reference strain of C. sakazakii as an example. The following methods are only typical examples, and the scope of the present invention is not limited thereto.

  First, a reference strain of C. sakazakii was spread on a trypticase soy agar medium (TSA: Trypticase Soy Agar, BD (BBL)) and cultured at 37 ° C. for 24 hours. Next, about half of the C. sakazakii colonies grown on the medium were collected and suspended in 300 μl of ultrapure water (Milli-Q water). To the suspension, 900 μl of ethanol for residual agricultural chemicals / PCB test (manufactured by Fujifilm Wako Pure Chemical Industries, Ltd.) was added, mixed, and centrifuged (centrifugation conditions: 21,500 × g, 2 min, 25 ° C.). The supernatant was removed and centrifuged again under the same conditions. The precipitate obtained by removing the supernatant was suspended in 70 μl of a 70% formic acid solution prepared using high-concentration formic acid (special grade, manufactured by Fujifilm Wako Pure Chemical Co., Ltd.), and tested for residual agricultural chemicals and PCB. After adding 70 μl of acetonitrile for use (manufactured by Fujifilm Wako Pure Chemical Industries, Ltd.), the suspension was mixed. The suspension was centrifuged (centrifugation conditions: 21,500 × g, 2 min, 25 ° C.), and the supernatant was used as a protein extract. The culture conditions of the reference strain and the method of extracting the ribosome-related protein are not limited to the above, and a sufficient amount of the ribosome-related protein to finally observe the molecular weight-related peak of the ribosome-related protein is taken out from the inside of the cell. And any conventionally known culture method or ribosome-related protein extraction / purification method may be used.

  Using a sinapinic acid as a matrix agent, a 50% acetonitrile solution containing 10 mg of sinapinic acid (manufactured by Fujifilm Wako Pure Chemical) and trifluoroacetic acid (special grade, manufactured by Fujifilm Wako Pure Chemical) at a concentration of 1%. To prepare a matrix agent solution. 1 μl of this matrix agent solution was dropped on a sample plate for MALDI-TOF measurement and air-dried. Thereafter, 1 μl of the protein extract was dropped on the region of the sample plate where the matrix agent solution was dropped, and dried. Thereafter, 1 μl of the matrix agent solution was again dropped into the region where the protein extract was dropped, and dried to obtain a sample of the C. sakazakii reference strain. The sample preparation method for MALDI-TOFMS measurement is not limited to the above, and may be performed according to a conventionally known sample preparation method used in MALDI-TOFMS measurement of proteins. In the above, sinapinic acid was used as the matrix agent, but CHCA (α-cyano-4-hydroxycinnamic acid) or the like can also be used.

  For the measurement, an autoflex speed (manufactured by Bruker) was used as a MALDI-TOF MS apparatus, and a flex control attached to the apparatus was used as measurement software. In the measurement software, the positive linear mode was selected, and the mass spectrum of the sample prepared by setting the spectrum range to m / z 3000 to 20000 was performed to obtain a mass spectrum of the C. sakazakii reference strain. For analysis of the mass spectrum, analysis software flex analysis attached to the apparatus was used. In the analysis, peaks having a signal-to-noise (S / N) ratio of 3 or more and a relative intensity threshold (Relative Intensity Threshold) of 1% or more were targeted. From the mass spectrum data of the C. sakazakii reference strain, the mass charge of the peak was determined. The ratio was read, and the mass-to-charge ratio of the read peak was compared with the theoretical value of the mass of the ribosome-related protein of the C. sakazakii reference strain. Then, it is assumed that the ribosome-related protein can be assigned to the peak whose mass-to-charge ratio matches the theoretical value of the mass of the ribosome-related protein of the C. sakazakii reference strain with an error within 500 ppm, and the ribosome-related protein is assigned to the peak of the mass spectrum. The protein was assigned. The results are shown in Table 2 together with theoretical values of the mass of the ribosome-related protein. Table 2 shows C. sakazakii and C. malonaticus. The gray spots in Table 2 indicate that no peak corresponding to the ribosome-related protein was observed. The unit is [Da]. This operation was performed on reference strains of all strains of the genus Clonobacter. Note that the method of acquiring and analyzing the mass spectrum is not limited to the above, and any conventionally known apparatus, measurement mode, spectrum range, analysis software, S / N ratio, relative intensity, and the like may be appropriately selected and combined.

(3-3) Selection of biomarker The theoretical value of the mass of each ribosome-related protein calculated for each species of Clonobacter genus, and each ribosome-related protein obtained from the mass spectrometry result of the reference strain of each strain Using the mass-to-charge ratio of the peak attributed to, a ribosome-related protein serving as a biomarker capable of identifying the species of Chronobacter was searched. As a result, it was found that seven reference strains of the genus Clonobacter can be distinguished from the mass patterns (patterns of theoretical mass values) of the five ribosome-related proteins (L32, L25, L24, RaiA, and L20). Proteins L32, L25, L24, RaiA and L20 were selected as biomarkers. Some ribosome-related proteins are hardly observed as peaks in mass spectrometry of mass spectrometry. Therefore, combining these five biomarkers made it possible to identify the species of the genus Clonobacter.

  Table 3 shows the theoretical value of the mass of the biomarker for each bacterial species and the mass-to-charge ratio of the biomarker obtained from the mass spectrometry results of each reference strain, that is, the measured value of the mass of the biomarker. In Table 3, for the same ribosome-related protein, there are bacterial strains in which Roman numerals and theoretical values of mass are described, and bacterial species in which only Roman numerals are described. In Table 3, in the same ribosome-related protein, the bacterial species with the same Roman numeral means that the theoretical mass value is the same. For example, the column L32 of C. malonaticus describes the Roman numeral I. This means that the theoretical value of the mass of L32 of C. malonaticus is the same as the theoretical value of the mass of L32 of C. sakazakii. If "No registration" is described, the amino acid sequence of the bacterial species and ribosome-related protein corresponding to the column of no registration is not registered in the amino acid sequence database (UniprotKB), and the theoretical mass Means that could not be calculated. A blank column means that there was no peak corresponding to the ribosome-related protein among the peaks appearing in the mass spectrum. The biomarker mass database used for the attribution of the biomarker to the peak of the mass spectrum and the identification of the bacterial species contained in the sample, as described in the above “(1) Overall configuration of the apparatus for identifying a microorganism according to the embodiment of the present invention” Is a table of Table 3 showing, for example, the theoretical value of the mass, and summarizes the theoretical value of the mass of each biomarker for each bacterial species.

(3-4) Verification of biomarker As verification of the biomarker, the ribosome-related proteins L32, L25, L24, RaiA, and the like were evaluated using the mass-to-charge ratio obtained from the mass spectrometry results of each reference strain shown in Table 3. It was verified whether L20 can be used as a biomarker to identify seven reference strains.

  First, using the data of C. sakazakii, it was verified whether the biomarker of the present invention could identify the bacterial species contained in the sample as C. sakazakii. When the theoretical value of the biomarker L20 was compared with the mass-to-charge ratio of L20 of C. sakazakii, it coincided with the theoretical mass of I, so that the bacterial species could be narrowed down to C. sakazakii and C. condimenti. Next, when the theoretical value of the biomarker L25 is compared with the mass-to-charge ratio of L.25 of C. sakazakii, it matches the theoretical mass of I. Therefore, it was possible to identify that the strain of the data of C. sakazakii was C. sakazakii. In this case, C. sakazakii was identified from the seven bacterial species using the biomarkers L20 and L25. For example, even when no peak corresponding to L25 was detected, a peak corresponding to L24 was detected. Then, since the theoretical value of L24 is different between C. sakazakii and C. condimenti, C. sakazakii could be identified using L20 and L24.

  Next, using the data of C. malonaticus, it was verified whether the biomarker of the present invention can identify that the bacterial species contained in the sample is C. malonaticus. When the theoretical value of the biomarker L20 is compared with the mass-to-charge ratio of L20 of C. malonaticus, it matches the theoretical value of II. Therefore, it was possible to identify that the species of the data of C. malonaticus was C. malonaticus. In this case, C. malonaticus was identified from the seven bacterial species using the biomarker L20. For example, even if no peak corresponding to L20 was detected, C. malonaticus showed that the theoretical value of RaiA was different from that of other species. Since it is different from the 6 bacterial species, C. malonaticus could be identified using RaiA.

  Next, using the data of C. dublinensis, it was verified whether the biomarker of the present invention could identify that the strain contained in the sample was C. dublinensis. When comparing the theoretical value of the biomarker L20 with the mass-to-charge ratio of L20 of C. dublinensis, it matches the theoretical value of III, so that it is possible to narrow down the bacterial species to C. dublinensis, C. universalis, and C. muytjensii. did it. Next, when the theoretical value of the biomarker L25 is compared with the mass-to-charge ratio of the C. dublinensis L25, it matches the theoretical value II. Therefore, it was possible to identify that the strain of the data of C. dublinensis was C. dublinensis. In this case, C. dublinensis was identified from the seven bacterial species using the biomarkers L20 and L25. For example, even when no peak corresponding to L20 was detected at all, the biomarkers RaiA and L25 were used. C. dublinensis could be identified. Specifically, by comparing the theoretical value of RaiA with the mass-to-charge ratio of RaiA of C. dublinensis, the bacterial species can be narrowed down to C. sakazakii, C. dublinensis, and C. muytjensii. C. dublinensis could be identified by comparing the theoretical value with the mass-to-charge ratio of L.25 of C. dublinensis.

  Subsequently, using the data of C. turicensis, it was verified whether the biomarker of the present invention could identify that the bacterial species contained in the sample was C. turicensis. When the theoretical value of the biomarker L24 was compared with the mass-to-charge ratio of L.24 of C. turicensis, it coincided with the theoretical value of mass II, so that the bacterial species could be narrowed down to C. turicensis and C. universalis. Next, when the theoretical value of the biomarker L25 and the mass-to-charge ratio of L25 of C. turicensis are compared, they agree with the theoretical value of II. Therefore, it was possible to identify that the strain of the data of C. turicensis was C. turicensis. In this case, C. turicensis was identified from the seven bacterial species using the biomarkers L24 and L25. For example, even when no peak corresponding to L24 was detected, the biomarkers L32 and L25 were used. C. turicensis could be identified. Specifically, by comparing the theoretical value of L32 with the mass-to-charge ratio of L.32 of C. turicensis, the bacterial species can be narrowed down to C. turicensis and C. universalis, and then the theoretical value of L25, By comparing the mass-to-charge ratio of C. turicensis L25, C. turicensis could be identified.

  Next, using the data of C. universalis, it was verified whether the biomarker of the present invention could identify that the bacterial species contained in the sample was C. universalis. When the theoretical value of the biomarker L24 was compared with the mass-to-charge ratio of L.24 of C. universalis, it coincided with the theoretical value of mass II, so that the bacterial species could be narrowed down to C. universalis and C. turicensis. Next, when the theoretical value of the biomarker L25 is compared with the mass-to-charge ratio of L.25 of C. universalis, it matches the theoretical value I. Therefore, it was possible to identify that the strain of the data of C. universalis was C. universalis. In this case, C. universalis was identified from the seven bacterial species using the biomarkers L24 and L25. For example, even when no peak corresponding to L24 was detected, the biomarkers L32 and L25 were used. C. universalis could be identified. Even when no peak corresponding to L25 was detected, C. universalis was able to identify C. universalis using RaiA because the theoretical value of RaiA was different from the other six strains. Furthermore, if a peak corresponding to L20 of C. universalis and C. turicensis was detected in this case, C. universalis could be identified using L32 and L20 or L24 and L20.

  Subsequently, using the data of C. condimenti, it was verified whether the biomarker of the present invention could identify that the strain contained in the sample was C. condimenti. When the theoretical value of the biomarker L20 and the mass-to-charge ratio of L20 of C. condimenti were compared with each other, they matched the theoretical value of I, so that the bacterial species could be narrowed down to C. condimenti and C. sakazakii. Next, when the theoretical value of the biomarker L25 and the mass-to-charge ratio of L.25 of C. condimenti are compared, they agree with the theoretical value II. Therefore, it was possible to identify that the strain of the data of C. condimenti was C. condimenti. In this case, since no peak corresponding to L.24 of C. condimenti was detected, C. condimenti was identified from seven bacterial species using biomarkers L20 and L25. For example, peaks corresponding to L20 and L25 were detected. Even if no was detected, if a peak corresponding to L24 was detected, the theoretical value of L.24 was different from the other six strains, so it was possible to identify C. condimenti using L24. did it.

  Finally, using the data of C. muytjensii, it was verified whether the strain contained in the biomarker of the present invention could be identified as C. muytjensii. Comparing the theoretical value of the biomarker L20 with the mass-to-charge ratio of L20 of C. muytjensii, which matches the theoretical mass of III, it is possible to narrow down the bacterial species to C. muytjensii, C. dublinensis, and C. universalis. did it. Next, comparing the theoretical value of the biomarker L25 with the mass-to-charge ratio of L25 of C. muytjensii, which matches the theoretical value I, the bacterial species could be narrowed down to C. muytjensii and C. universalis. A comparison of the theoretical value of the biomarker L24 with the mass-to-charge ratio of C. muytjensii L24 agrees with the theoretical value of I. Therefore, it was possible to identify that the strain of the data of C. muytjensii was C. muytjensii. In this case, C. muytjensii was identified from the seven strains using the biomarkers L20, L25 and L24. For example, even when no peak corresponding to L24 was detected, C. muytjensii and C. universalis Since the theoretical value of L32 was different, C. muytjensii could be identified using L32 instead of L24. Similarly, C. muytjensii could be identified by using RaiA instead of L24.

  From the above, it was confirmed that the use of the ribosome-related proteins L32, L25, L24, RaiA, and L20 as biomarkers allowed the identification of seven species of Chronobacter genus. In the present invention, since five ribosome-related proteins L32, L25, L24, RaiA and L20 are used as biomarkers, there are a plurality of combinations of biomarkers capable of identifying bacterial species. Therefore, in the present invention, even when, for example, one peak corresponding to a biomarker is not detected in the mass spectrum, the bacterial species can sometimes be identified by a combination of other biomarkers. Therefore, in the present invention, the number of cases where the mass spectrum is re-measured by MALDI-TOF MS can be reduced as much as the bacterial species can be identified by other combinations, and the bacterial species can be specified more easily.

(3-5) Verification of validity of bacterial species identification using biomarkers It was verified whether the results of bacterial species identification performed using ribosome-related proteins L32, L25, L24, RaiA, and L20 as biomarkers were valid. . The verification was carried out using the results of MALDI-TOF MS to identify the species using biomarkers according to the method of the present invention, and the gene analysis method Multilocus, which is said to be able to identify all seven species of Chronobacter. This was performed by comparing the results with the identification results obtained by the Sequence Typing (MLST) method. The MLST method is a molecular epidemiological analysis method for classifying fungal and bacterial strains. It is said that among the genes to be analyzed, seven species of Clonobacter genus can be identified by comparing the nucleotide sequence of fusA. (J. Clin. Microbiol., Vol. 50, No. 9, p. 3031-3039 (2012)). In the verification, the strains of 30 species of Clonobacter genus isolated from various environments and foods were identified by the method of the present invention and the MLST method.

  Since the identification of the bacterial species by the method of the present invention is the same as the method described above, the description will be omitted. Here, a method of analyzing the base sequence of the fusA gene of each strain by the MLST method will be described by taking as an example a case where one strain selected from 30 strains of Chronobacter is identified by the MLST method. First, the selected strain of Chronobacter was cultured. Then, DNA was extracted from the cultured Chronobacter bacterium. A small amount of a cultured colony of Chronobacter was suspended in 100 μl of a gene extraction reagent PrepMan Ultra (manufactured by Applied Biosystems) and heat-treated at 100 ° C. for 10 minutes. Thereafter, the mixture was centrifuged (centrifugation conditions: 21,500 × g, 3 minutes, 25 ° C.), and the supernatant was obtained as a DNA extract.

  Amplification reaction of the gene region fusA was carried out on the DNA of the genus Clonobacter extracted in the DNA extract using primers (Forward-GAAACCGTATGGCGTCAG, Reverse-AGAACCGAAGTGCAGACG). After the amplification product was purified using illustra GFX PCR DNA and Gel Band Purification Kit (GE Healthcare), a cycle sequence reaction was performed using primers (Forward-GCTGGATGCGGTAATTGA, Reverse-CCCATACCAGCGATGATG). Table 4 shows the conditions of the amplification reaction and the cycle sequence reaction (PCR conditions).

  After the amplification product obtained by the cycle sequence reaction was purified using DyeEx 2.0 Spin Kit (manufactured by QIAGEN), the nucleotide sequence of fusA was analyzed by a sequencer. The obtained nucleotide sequence was input to the MLST analysis database PubMLST, and the bacterial species was identified from the nucleotide sequence pattern of fusA. This operation was performed for other Chronobacter bacteria, and all 30 strains of Chronobacter were identified. Table 5 shows the analysis results by the method of the present invention and the analysis results by the MLST method.

  Table 5 also shows the mass-to-charge ratio of the peak observed by MALDI-TOF MS and to which the biomarker was assigned. The line “MALDI” in Table 5 shows the identification result by the method of the present invention, and the line “MLST” shows the identification result by the MLST method. As shown in Table 5, the identification results obtained by the method of the present invention all matched the identification results obtained by the MLST method. Thus, it was confirmed that the results of the identification of the seven species of Chronobacter by the method of the present invention were appropriate.

  In some strains, there were biomarkers for which no assigned peak was observed. However, by combining the mass patterns of other biomarkers, it was possible to narrow down the strains of the 30 strains of Clonobacter genus used for verification to one strain. For example, in B-1391, the peaks of biomarkers L32, L25, and L24 were not observed, but the bacterial species could be identified as C. universalis by the peak of RaiA (m / z 122788.6). The 30 Cronobacter bacteria used for the verification were identified as 23 strains of C. sakazakii, 3 strains of C. malonaticus, 2 strains of C. universalis, 1 strain of C. turicensis, and 1 strain of C. dublinensis.

(4) Comparative Example As a comparative example, an experiment was performed to identify seven reference strains of the genus Clonobacter by 16S rRNA gene analysis (500 bp) which is often used as a microorganism identification technique.

  First, reference strains of the genus Clonobacter were each cultured. Next, a small amount of a cultured colony of a standard strain of Clonobacter was suspended in 100 μl of a gene extraction reagent PrepMan Ultra (manufactured by Applied Biosystems), and heat-treated at 100 ° C. for 10 minutes. Thereafter, the mixture was centrifuged (centrifugation conditions: 21,500 × g, 3 minutes, 25 ° C.), and the supernatant was obtained as a DNA extract.

  Using the FAST MicroSeq 500 16S rDNA PCR Kit (Applied Biosystems), the obtained DNA extract was used to amplify the 16S rRNA gene region of the DNA extracted from the genus Clonobacter. After the amplification product was purified using GFX PCR DNA and Gel Band Purification Kit (GE Healthcare), a cycle sequence reaction was performed using MicroSeq 500 16S rDNA Bacterial Sequencing Kit (Applied Biosystems). Table 6 shows the conditions of the amplification reaction and the cycle sequence reaction (PCR conditions).

  After purifying the amplification product obtained by the cycle sequence reaction using the DyeEx 2.0 Spin Kit (manufactured by QIAGEN), the nucleotide sequence of the DNA extracted from the genus Chronobacter by a sequencer (ABI PRISM Genetic Analyzer 3500xL, manufactured by Applied Biosystems) Was analyzed. The analyzed nucleotide sequence was input to the database EZ taxon, and strains having a homology of 99% or more were identified as strains of the reference strain. This was done for the other reference stocks. As a result, as shown in Table 7, in C. sakazakii and C. malonaticus, the homology of both reference strains was 99% or more, and C. sakazakii and C. malonaticus could not be distinguished from each other. Was. In addition, for C. turicensis and C. universalis, the homology of both reference strains was 99% or more, and C. turicensis and C. universalis could not be distinguished.

REFERENCE SIGNS LIST 1 identification device 2 mass analysis unit 3 identification processing unit 4 display unit 5 acquisition unit 6 selection unit 7 extraction unit 8 identification unit 9 storage unit

SEQ ID NO: 1: forward primer
SEQ ID NO: 2: Reverse primer
SEQ ID NO: 3: forward primer
SEQ ID NO: 4: Reverse primer

Claims (9)

An extraction step of extracting a mass-to-charge ratio of a biomarker-derived peak in a mass spectrum obtained by mass analysis of a sample, from the mass spectrum,
Based on the mass-to-charge ratio, an identification step of identifying the species of Clonobacter genus contained in the sample,
A method for identifying a microorganism, wherein ribosome-related proteins L32, L25, L24, RaiA, and L20 are used as the biomarkers. The method according to claim 1, further comprising: comparing a mass-to-charge ratio of a peak appearing in the mass spectrum with a theoretical value of the mass of the biomarker to select a peak derived from the biomarker in the mass spectrum. A method for identifying microorganisms. The microorganism according to claim 1, wherein the identification step identifies the bacterial species by comparing the mass-to-charge ratio with a theoretical value of the mass of the biomarker calculated for each bacterial species of the genus Clonobacter. Identification method. The microorganism according to any one of claims 1 to 3, wherein the Clonobacter bacterium is C. sakazakii, C. malonaticus, C. dublinensis, C. turicensis, C. universalis, C. condimenti, and C. muytjensii. Identification method. In the mass spectrum obtained by mass analysis of the sample, the mass-to-charge ratio of the peak derived from the biomarker, an extraction unit that extracts from the mass spectrum,
Based on the mass-to-charge ratio, having an identification unit for identifying the species of Clonobacter genus contained in the sample,
A microorganism identification device using ribosome-related proteins L32, L25, L24, RaiA and L20 as the biomarkers. The mass-to-charge ratio of the peak appearing in the mass spectrum, and a theoretical value of the mass of the biomarker are compared, and a selection unit that selects the peak derived from the biomarker in the mass spectrum is further provided. Microorganism identification device. The microorganism according to claim 5, wherein the identification unit identifies the bacterial species by comparing the mass-to-charge ratio with a theoretical value of the mass of the biomarker calculated for each bacterial species of the genus Clonobacter. Identification device. The microorganism according to any one of claims 5 to 7, wherein the Clonobacter bacterium is C. sakazakii, C. malonaticus, C. dublinensis, C. turicensis, C. universalis, C. condimenti, and C. muytjensii. Identification device. A program for causing a computer to execute the microorganism identification method according to claim 1.