CN115290739B - Bacterial metabolite analysis method - Google Patents
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Abstract
The present disclosure provides a bacterial metabolite analysis method that may be applied in the field of biological mass spectrometry. The method comprises the following steps: culturing bacteria by using a control group culture medium which takes a compound containing target atoms as a bacterial growth intake raw material and an experimental group culture medium which takes a compound with isotopes replacing the target atoms as a bacterial growth intake raw material to obtain control group bacteria and experimental group bacteria; detecting mass spectra of bacteria in a control group and bacteria in an experimental group to obtain mass spectrograms of the control group and mass spectrograms of the experimental group; matching corresponding candidate metabolites aiming at each control mass spectrum peak in the mass spectrogram of the control group to obtain an initial metabolite list; determining an isotope mass spectrum peak corresponding to the control mass spectrum peak from the experimental group mass spectrum; determining the number of atoms according to the reference mass spectrum peak, the isotope mass spectrum peak and the target atoms; the initial metabolite list is screened using the number of atoms to obtain a final metabolite list, so that bacterial metabolite analysis is performed according to the final metabolite list.
Description
Technical Field
The present disclosure relates to the field of biological mass spectrometry, and more particularly to a bacterial metabolite analysis method.
Background
Metabolites play an important role in various biological processes of living cells, and direct detection of metabolites in living cells can provide a deeper understanding for life science research. Various analysis methods have been developed for qualitative and quantitative analysis of cell metabolites, direct injection methods based on electrospray mass spectrometry can realize detection of living cell proteins and protein interactions, and show great potential in metabolite detection.
However, under the condition of limited mass spectrum resolution, mass spectrum peaks of metabolites with similar molecular weights are overlapped, so that a large number of false positives exist in the search and identification of signal peaks in a metabolite database, the identification confidence of bacterial metabolites is low, and the accuracy of metabolite identification information is poor.
Disclosure of Invention
In view of the above, the present disclosure provides a bacterial metabolite analysis method comprising:
Culturing bacteria by using a control group culture medium and an experimental group culture medium respectively to obtain control group bacteria and experimental group bacteria, wherein the control group culture medium takes a compound containing target atoms as an intake raw material for bacterial growth; the experimental group culture medium uses a compound obtained by replacing the target atom with an isotope of the target atom as a raw material for bacterial growth and ingestion;
respectively carrying out mass spectrum detection on the bacteria in the control group and the bacteria in the experimental group to obtain a mass spectrum of the control group and a mass spectrum of the experimental group;
Matching candidate metabolites corresponding to the control mass spectrum peaks from a metabolite database aiming at each control mass spectrum peak in the control mass spectrum to obtain an initial metabolite list;
identifying isotope mass spectrometry peaks corresponding to the control mass spectrometry peaks from the experimental group mass spectrogram;
Determining the number of target atoms contained in the actual metabolite corresponding to the reference mass spectrum peak based on the reference mass spectrum peak, the isotope mass spectrum peak and the target atoms, thereby obtaining the number of atoms; and
And screening the candidate metabolites in the initial metabolite list by using the atomic number to obtain a final metabolite list, so as to facilitate bacterial metabolite analysis according to the final metabolite list.
According to an embodiment of the present disclosure, the determining an isotope mass spectrometry peak corresponding to the control mass spectrometry peak from the experimental group mass spectrogram includes:
Determining a first mass shift between the experimental mass spectrum peak and the control mass spectrum peak for each experimental mass spectrum peak in the experimental group mass spectrum;
And determining the experimental mass spectrum peak as the isotope mass spectrum peak corresponding to the control mass spectrum peak under the condition that the first mass shift meets the preset condition.
According to an embodiment of the present disclosure, the preset condition includes determination according to an atomic weight difference between an isotope of the target atom and the target atom.
According to an embodiment of the present disclosure, the determining the number of the target atoms included in the actual metabolite corresponding to the control mass spectrum peak based on the control mass spectrum peak, the isotope mass spectrum peak, and the target atoms, to obtain the number of atoms includes:
Determining a second mass shift corresponding to the target atom based on the reference mass spectrum peak and the isotope mass spectrum peak;
And determining the number of the target atoms included in the actual metabolite corresponding to the reference mass spectrum peak based on the difference between the isotope of the target atom and the atomic weight of the target atom and the second mass shift, thereby obtaining the number of atoms.
According to an embodiment of the present disclosure, the screening the candidate metabolites in the initial metabolite list using the atomic number to obtain a final metabolite list includes:
Determining the number of the target atoms contained in the candidate metabolites for each candidate metabolite in the initial metabolite list;
Determining the candidate metabolite as a target metabolite when the number of the target atoms contained in the candidate metabolite is the same as the number of the atoms;
the final metabolite list is obtained from the target metabolites.
According to an embodiment of the present disclosure, the performing mass spectrometry on the control group bacteria and the experimental group bacteria, respectively, to obtain a control group mass spectrum and an experimental group mass spectrum includes:
Centrifuging the bacteria of the control group, removing supernatant, and then re-suspending to obtain re-suspended bacteria of the control group;
pouring the resuspended bacteria of the control group into a capillary spray needle, applying voltage to generate electrospray, and detecting signals by using a mass spectrometer to obtain a mass spectrogram of the control group;
Centrifuging the experimental group bacteria, removing supernatant, and then re-suspending to obtain re-suspended experimental group bacteria;
And pouring the resuspended experimental group bacteria into a capillary needle, applying voltage to generate electrospray, and detecting signals by using the mass spectrometer to obtain the mass spectrogram of the experimental group.
According to an embodiment of the present disclosure, the above-described bacterial metabolite analysis method further includes:
Before the resuspended bacteria of the control group or the resuspended bacteria of the experimental group are poured into the capillary needle, the bacteria are lysed by ultrasonic waves or methanol.
According to an embodiment of the present disclosure, the matching of candidate metabolites corresponding to the control mass spectrum peak from the metabolite database comprises:
determining, for each metabolite in the metabolite database, a difference between a peak value of the control mass spectrum peak and a molecular weight of the metabolite;
and determining the metabolite as the candidate metabolite corresponding to the control mass spectrum peak when the absolute value of the difference is equal to or less than a preset precision value.
According to an embodiment of the present disclosure, the preset precision value is determined according to a charge-to-mass ratio of the compared mass spectrum peak, and is 15ppm when the charge-to-mass ratio of the compared mass spectrum peak is equal to or less than 400; in the case where the charge-to-mass ratio of the reference mass spectrum peak is more than 400, the preset precision value is 30ppm.
According to an embodiment of the present disclosure, the target atom includes one or more of a carbon atom, a nitrogen atom, an oxygen atom, a hydrogen atom, and a chlorine atom.
According to the embodiment of the present disclosure, since the bacteria are respectively cultured using a control group medium and an experimental group medium, the control group medium takes a compound containing a target atom as an intake raw material for bacterial growth, and the experimental group medium takes a compound obtained by substituting an isotope of the target atom for the target atom as an intake raw material for bacterial growth; then mass spectrum detection is carried out on the bacteria in the control group and the bacteria in the experimental group respectively, and corresponding candidate metabolites are matched from a metabolite database aiming at each control mass spectrum peak in the mass spectrogram of the control group, so that an initial metabolite list is obtained; then determining isotope mass spectrum peaks corresponding to the control mass spectrum peaks from the mass spectrum of the experimental group; determining the number of target atoms contained in the actual metabolites corresponding to the control mass spectrum peaks according to the control mass spectrum peaks, the isotope mass spectrum peaks and the target atoms to obtain the number of atoms; and then screening candidate metabolites in the initial metabolite list by utilizing the number of atoms to obtain a final metabolite list so as to facilitate the technical means of analyzing the bacterial metabolites according to the final metabolite list, so that the technical effects that in the related technology, due to the fact that the mass spectrum resolution is limited and mass spectrum peaks of metabolites with similar molecular weights are overlapped, a large number of false positives exist in searching and identifying signal peaks in a metabolite database, the identification confidence of the bacterial metabolites is low, the accuracy of metabolite identification information is poor are achieved, the number of false positive metabolites corresponding to the mass spectrum peaks is reduced, the identification confidence of metabolite distribution is improved, and more reliable metabolic identification information is facilitated.
Drawings
The foregoing and other objects, features and advantages of the disclosure will be more apparent from the following description of embodiments of the disclosure with reference to the accompanying drawings, in which:
FIG. 1 shows a flow chart of a bacterial metabolite analysis method according to an embodiment of the present disclosure;
FIG. 2 shows a flow chart of a bacterial metabolite analysis method with 12 C-glucose/14 N-ammonium chloride as control medium and 12 C-glucose/15 N-ammonium chloride as experimental medium;
FIG. 3 shows a flow chart of a bacterial metabolite analysis method with 12 C-glucose/14 N-ammonium chloride as control medium and 13 C-glucose/14 N-ammonium chloride as experimental medium;
FIG. 4 shows a flow chart of a bacterial metabolite analysis method with 12 C-glucose/14 N-ammonium chloride as control medium and 13 C-glucose/15 N-ammonium chloride as experimental medium;
FIG. 5A shows a control mass spectrum of E.coli;
FIG. 5B shows mass spectra peak profiles of different endogenous compounds detected in E.coli;
FIG. 6 schematically shows representative mass spectral peaks of [ glutathione+H ] + in control group bacteria (d), experimental group A bacteria (B), experimental group B bacteria (C) and experimental group C bacteria (a), and mass shifts based on 12 C-glucose/14 N-ammonium chloride;
Fig. 7 shows a list of initial metabolites corresponding to mass spectral peaks for m/z= 308.0907;
FIG. 8 shows representative mass spectra of [ glutathione+Na ] + a-d; [ maltohexaose+Na ] + and its isomers, e-H; [ lysine+H ] + and its isomers, i-1; [ glucose+Na ] + and its isomers, m-p) obtained in living cells using 13 C-glucose/15 N-ammonium chloride (a, e, i, m), 13 C-glucose/14 N-ammonium chloride (b, f, j, N), 12 C-glucose/15 N-ammonium chloride (C, g, k, o) and 12 C-glucose/14 N-ammonium chloride (d, H, l, p) in a medium, the mass shift based on 12 C-glucose/14 N-ammonium chloride being marked;
FIG. 9 shows representative mass spectra obtained in a culture medium using 13 C-glucose/15 N-ammonium chloride (a), 13 C-glucose/14 N-ammonium chloride (b), 12 C-glucose/15 N-ammonium chloride (C) and 12 C-glucose/14 N-ammonium chloride (d) for [ glutathione+K ] + in living cells, mass shifts based on 12 C-glucose/14 N-ammonium chloride being marked in the mass spectra;
FIG. 10 shows three repeat mass spectra of E.coli cells measured by electrospray;
FIG. 11 shows the ionic binding type of bacterial metabolites;
Fig. 12 shows a list of initial metabolites corresponding to mass spectral peaks for m/z= 1013.3094;
FIG. 13 shows Venn diagrams of metabolites identified for group A bacteria (cell-C13N 14), group B bacteria (cell-C12N 15), group C bacteria (cell-C13N 15) and control group bacteria (cell-C12N 14);
FIG. 14 shows confidence probability distribution plots for metabolites that have not been isotopically filtered and isotopically filtered; and
Fig. 15 shows a graph comparing the confidence probability of an isotopically unfiltered metabolite to the confidence probability of an isotopically filtered metabolite.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is only exemplary and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and/or the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.
Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a convention should be interpreted in accordance with the meaning of one of skill in the art having generally understood the convention (e.g., "a system having at least one of A, B and C" would include, but not be limited to, systems having a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
Metabolites play an important role in various biological processes of living cells, and direct detection of metabolites in living cells can provide a deeper understanding for life science research.
Various analytical methods have been developed for qualitative and quantitative analysis of cellular metabolites. Nuclear magnetic resonance strategies have been used for metabolite identification and metabolic flux analysis of extracted samples and living cells, but their low sensitivity limits further applications. Raman spectroscopy enables a relatively comprehensive metabolic detection, but the spectral overlap of metabolites in organisms limits its further application. Fluorescence spectroscopy has been used for dynamic monitoring of metabolites in model cells, but is difficult to extend to detection of non-targeted or unknown metabolites. Mass spectrometry based on gas chromatography or on high performance liquid chromatography combined with sampling pretreatment strategies, such as liquid extraction and solid-phase microextraction enrichment, have become an essential analytical tool in metabolite analysis due to the high sensitivity and high throughput of biological samples and the need for labelling requirements. However, the requirements of sample preparation limit its use in the analysis of living cell metabolites.
Direct sampling methods based on electrospray mass spectrometry have now enabled detection of living cell proteins and protein interactions and show great potential in metabolite detection. However, under the condition of limited mass spectrum resolution, mass spectrum peaks of metabolites with similar molecular weights are overlapped, so that a large number of false positives exist in the search and identification of signal peaks in a metabolite database, the identification confidence of bacterial metabolites is low, and the accuracy of metabolite identification information is poor.
In view of the above, the present disclosure aims at the above technical problems, and uses isotopes as a unique element source to mark metabolites, so that mass spectrum peaks of the metabolites generate a shift in molecular weight, thereby calculating the number of isotope atoms contained in the metabolites, and then uses the number of isotope atoms to screen the metabolites to exclude false positive identification information pointed by bacterial metabolites, thereby helping to reduce the number of false positive metabolites corresponding to mass spectrum peaks, so that the identification confidence of metabolite distribution is significantly increased, and more reliable metabolic identification information is obtained. For example, using 13 C and 15 N and other isotopes as the sole elemental sources, labeling metabolites with 13 C and 15 N and other isotopes causes a shift in molecular weight of the metabolites, thereby calculating the number of carbon and nitrogen atoms and other atoms contained in the metabolites, achieving a significant increase in the confidence of identification of metabolite assignments, and enabling detection of non-target metabolites in living escherichia coli.
Specifically, embodiments of the present disclosure provide a bacterial metabolite analysis method comprising: culturing bacteria by using a control group culture medium and an experimental group culture medium respectively to obtain control group bacteria and experimental group bacteria, wherein the control group culture medium takes a compound containing target atoms as an intake raw material for bacterial growth; the experimental group culture medium uses a compound obtained by replacing the target atom with an isotope of the target atom as a raw material for bacterial growth and ingestion; respectively carrying out mass spectrum detection on the bacteria in the control group and the bacteria in the experimental group to obtain a mass spectrum of the control group and a mass spectrum of the experimental group; matching candidate metabolites corresponding to the control mass spectrum peaks from a metabolite database aiming at each control mass spectrum peak in the control mass spectrum to obtain an initial metabolite list; identifying isotope mass spectrometry peaks corresponding to the control mass spectrometry peaks from the experimental group mass spectrogram; determining the number of target atoms contained in the actual metabolite corresponding to the reference mass spectrum peak based on the reference mass spectrum peak, the isotope mass spectrum peak and the target atoms, thereby obtaining the number of atoms; and screening the candidate metabolites in the initial metabolite list by using the atomic number to obtain a final metabolite list, so as to perform bacterial metabolite analysis according to the final metabolite list.
FIG. 1 shows a flow chart of a bacterial metabolite analysis method according to an embodiment of the present disclosure.
As shown in FIG. 1, the bacterial metabolite analysis method of this embodiment includes operations S110 to S160.
Culturing bacteria in a control group culture medium and an experimental group culture medium to obtain a control group bacteria and an experimental group bacteria, respectively, wherein the control group culture medium takes a compound containing target atoms as an intake raw material for bacterial growth; the experimental group medium uses a compound obtained by substituting the target atom with an isotope of the target atom as a raw material for bacterial growth and intake.
According to an embodiment of the present disclosure, the target atom includes one or more of a carbon atom, a nitrogen atom, an oxygen atom, a hydrogen atom, and a chlorine atom.
According to embodiments of the present disclosure, the target atom may be an atom. For example, the target atom is a carbon atom, the control group medium may include 12 C-glucose, and the experimental group medium may include 13 C-glucose; if the target atom is nitrogen atom, the control group culture medium can comprise 14 N-ammonium chloride, and the experimental group culture medium can comprise 15 N-ammonium chloride; if the target atom can also be an oxygen atom, the control group culture medium can comprise 16O-H2 O, and the experimental group culture medium can comprise 17O-H2 O; further, if the target atom is also a hydrogen atom, the control group medium may include 1H-H2 O and the experimental group medium may include 2H-H2 O.
According to embodiments of the present disclosure, the target atoms may also include two, i.e., more than two, atoms. For example, the target atoms comprise carbon atoms and nitrogen atoms, and 12 C-glucose, 13 C-glucose, 14 N-ammonium chloride and 15 N-ammonium chloride are arranged and combined to obtain a control group culture medium and an experimental group culture medium, wherein 12 C-glucose/14 N-ammonium chloride is used as the control group culture medium; 13 C-glucose/14 N-ammonium chloride, 12 C-glucose/15 N-ammonium chloride and 13 C-glucose/15 N-ammonium chloride were used as experimental group media.
According to embodiments of the present disclosure, the control group medium and the experimental group medium may further include inorganic salts, buffer salts, and water.
According to embodiments of the present disclosure, the inorganic salt may include sodium chloride, magnesium sulfate, and the like. The buffer salts may include disodium hydrogen phosphate, potassium dihydrogen phosphate, and the like.
In operation S120, mass spectrum detection is performed on the bacteria of the control group and the bacteria of the experimental group, respectively, to obtain a mass spectrum of the control group and a mass spectrum of the experimental group.
According to an embodiment of the present disclosure, the performing mass spectrometry on the control group bacteria and the experimental group bacteria, respectively, to obtain a control group mass spectrum and an experimental group mass spectrum includes: centrifuging the bacteria of the control group, removing supernatant, and then re-suspending to obtain re-suspended bacteria of the control group; pouring the resuspended bacteria of the control group into a capillary spray needle, applying voltage to generate electrospray, and detecting signals by using a mass spectrometer to obtain a mass spectrogram of the control group; centrifuging the experimental group bacteria, removing supernatant, and then re-suspending to obtain re-suspended experimental group bacteria; and pouring the resuspended experimental group bacteria into a capillary needle, applying voltage to generate electrospray, and detecting signals by using the mass spectrometer to obtain the mass spectrogram of the experimental group.
According to embodiments of the present disclosure, after centrifugation of the control or experimental group of bacteria, the supernatant is discarded, and then re-suspension with deionized water may be performed.
According to embodiments of the present disclosure, removal of the medium is facilitated by centrifugation of the control or experimental group of bacteria, discarding the supernatant, and then resuspension with deionized water, avoiding interference of subsequent detection by metabolites in the medium.
According to an embodiment of the present disclosure, the above-described bacterial metabolite analysis method further includes: before the resuspended control bacteria or the resuspended experimental bacteria are poured into the capillary needle, the bacteria are lysed by ultrasonic waves or methanol.
According to the embodiment of the disclosure, the lysis of bacteria helps to promote release of metabolites in bacteria and improve detection efficiency.
According to embodiments of the present disclosure, the applied voltage may employ, for example, a direct current voltage or an induced voltage.
According to embodiments of the present disclosure, a mass spectrometer may employ, for example, a high resolution mass spectrometer with a resolution greater than 60000.
In operation S130, for each of the control mass spectrum peaks in the control mass spectrum, candidate metabolites corresponding to the control mass spectrum peaks are matched from the metabolite database, and an initial metabolite list is obtained.
According to an embodiment of the present disclosure, the matching of candidate metabolites corresponding to the control mass spectrum peak from the metabolite database comprises: determining, for each metabolite in the metabolite database, a difference between a peak value of the control mass spectrum peak and a molecular weight of the metabolite; and determining the metabolite as the candidate metabolite corresponding to the control mass spectrum peak when the absolute value of the difference is equal to or less than a preset precision value.
According to an embodiment of the present disclosure, the preset precision value is determined according to a charge-to-mass ratio of the compared mass spectrum peak, and is 15ppm when the charge-to-mass ratio of the compared mass spectrum peak is equal to or less than 400; in the case where the charge-to-mass ratio of the reference mass spectrum peak is more than 400, the preset precision value is 30ppm.
According to embodiments of the present disclosure, the protonated ions [ m+h ] +、[M+Na]+、[M+K]+、[M-H2O+H]+ and [ m+nh 4]+ peaks are utilized for peak partitioning. That is, for each metabolite in the metabolite database, the molecular weight of the metabolite is added to the molecular weight of H, na, K, H 2O+H、NH4 to obtain the protonated ion molecular weight of the metabolite; then determining the difference between the peak value of the control mass spectrum peak and the protonated ion molecular weight of the metabolite; and determining the metabolite as the candidate metabolite corresponding to the control mass spectrum peak when the absolute value of the difference is equal to or less than a preset precision value.
According to an embodiment of the present disclosure, the initial metabolite list includes chemical compositions of candidate metabolites.
In operation S140, an isotope mass spectrometry peak corresponding to the control mass spectrometry peak is determined from the experimental group mass spectrum.
According to an embodiment of the present disclosure, the determining an isotope mass spectrometry peak corresponding to the control mass spectrometry peak from the experimental group mass spectrogram includes: determining a first mass shift between the experimental mass spectrum peak and the control mass spectrum peak for each experimental mass spectrum peak in the experimental group mass spectrum; and determining the experimental mass spectrum peak as the isotope mass spectrum peak corresponding to the control mass spectrum peak under the condition that the first mass shift meets the preset condition.
According to an embodiment of the present disclosure, the preset condition includes determination according to an atomic weight difference between an isotope of the target atom and the target atom.
According to an embodiment of the present disclosure, the preset conditions may include, for example: the target atom is a carbon atom, and assuming that the metabolite has x carbon atoms, the preset condition may be the atomic weight difference of 13 C and 12 C multiplied by x. Since the atomic weight difference between 13 C and 12 C is 1.0034Da, when the first mass shift satisfies (1.0033 x), the experimental mass spectrum peak is determined to be the isotope mass spectrum peak corresponding to the control mass spectrum peak.
In one example, where the metabolite has x carbon atoms and y nitrogen atoms, the pre-set conditions are determined by the following formula for living cells cultured with 13 C-glucose/14 N-ammonium chloride as medium: Δm=1.0034·x (Da).
For living cells cultured with 12 C-glucose/15 N-ammonium chloride as medium, the pre-set conditions were determined by the following formula: Δm=0.9970·y (Da).
For living cells cultured with 13 C-glucose/15 N-ammonium chloride as medium, the pre-set conditions were determined by the following formula: Δm=1.0034·x+0.9970·y (Da).
According to embodiments of the present disclosure, other isotopes (e.g., hydrogen isotopes, chlorine isotopes, etc.) may perform mass shift calculations for the number of corresponding atoms according to the molecular weight of the added isotopes, obtaining corresponding preset conditions.
In operation S150, the number of target atoms included in the actual metabolite corresponding to the reference mass spectrum peak is determined based on the reference mass spectrum peak, the isotope mass spectrum peak, and the target atoms, to obtain the number of atoms.
According to an embodiment of the present disclosure, the determining the number of the target atoms included in the actual metabolite corresponding to the control mass spectrum peak based on the control mass spectrum peak, the isotope mass spectrum peak, and the target atoms, to obtain the number of atoms includes: determining a second mass shift corresponding to the target atom based on the reference mass spectrum peak and the isotope mass spectrum peak; and determining the number of the target atoms included in the actual metabolite corresponding to the reference mass spectrum peak based on the difference between the isotope of the target atom and the atomic weight of the target atom and the second mass shift, thereby obtaining the number of atoms.
According to an embodiment of the present disclosure, the second mass shift may include a peak difference between an isotope mass spectrum peak and a control mass spectrum peak, and the number of target atoms contained in the actual metabolite may be obtained by dividing the peak difference by a difference between the isotope of the target atom and the atomic weight of the target atom.
For example, in one embodiment, where the target atom is a carbon atom, the number of carbon atoms in the actual metabolite may be obtained by dividing the second mass displacement by the atomic weight difference of 13 C and 12 C.
According to an embodiment of the present disclosure, the screening the candidate metabolites in the initial metabolite list using the atomic number to obtain a final metabolite list includes: determining the number of the target atoms contained in the candidate metabolites for each candidate metabolite in the initial metabolite list; determining the candidate metabolite as a target metabolite when the number of the target atoms contained in the candidate metabolite is the same as the number of the atoms; the final metabolite list is obtained from the target metabolites.
In operation S160, the candidate metabolites in the initial metabolite list are screened using the atomic number to obtain a final metabolite list, so that bacterial metabolite analysis is performed according to the final metabolite list.
According to the embodiment of the present disclosure, since the bacteria are respectively cultured using a control group medium and an experimental group medium, the control group medium takes a compound containing a target atom as an intake raw material for bacterial growth, and the experimental group medium takes a compound obtained by substituting an isotope of the target atom for the target atom as an intake raw material for bacterial growth; then mass spectrum detection is carried out on the bacteria in the control group and the bacteria in the experimental group respectively, and corresponding candidate metabolites are matched from a metabolite database aiming at each control mass spectrum peak in the mass spectrogram of the control group, so that an initial metabolite list is obtained; then determining isotope mass spectrum peaks corresponding to the control mass spectrum peaks from the mass spectrum of the experimental group; determining the number of target atoms contained in the actual metabolites corresponding to the control mass spectrum peaks according to the control mass spectrum peaks, the isotope mass spectrum peaks and the target atoms to obtain the number of atoms; and then screening candidate metabolites in the initial metabolite list by utilizing the number of atoms to obtain a final metabolite list so as to facilitate the technical means of analyzing the bacterial metabolites according to the final metabolite list, so that the technical effects that in the related technology, due to the fact that the mass spectrum resolution is limited and mass spectrum peaks of metabolites with similar molecular weights are overlapped, a large number of false positives exist in searching and identifying signal peaks in a metabolite database, the identification confidence of the bacterial metabolites is low, the accuracy of metabolite identification information is poor are achieved, the number of false positive metabolites corresponding to the mass spectrum peaks is reduced, the identification confidence of metabolite distribution is improved, and more reliable metabolic identification information is facilitated.
FIG. 2 shows a flow chart of a bacterial metabolite analysis method with 12 C-glucose/14 N-ammonium chloride as control medium and 12 C-glucose/15 N-ammonium chloride as experimental medium.
As shown in fig. 2, the method of this embodiment includes operations S201 to S209.
In operation S201, bacteria are cultured using a medium containing 12 C-glucose/14 N-ammonium chloride, to obtain bacteria of a control group.
In operation S202, mass spectrometry is performed after ionization of bacteria in the control group, so as to obtain a mass spectrum of the control group.
In operation S203, a control mass spectrum peak in the mass spectrum of the control group is extracted, and candidate metabolites corresponding to the control mass spectrum peak are matched from the metabolite database, thereby obtaining an initial metabolite list.
In operation S204, bacteria are cultured using a medium comprising 12 C-glucose/15 N-ammonium chloride, resulting in bacteria of a first experimental group.
In operation S205, mass spectrometry is performed after ionization of the bacteria of the first experimental group, so as to obtain a mass spectrum of the first experimental group.
In operation S206, a first experimental mass spectrum peak in the mass spectrum of the first experimental group is extracted, and an isotope mass spectrum peak corresponding to the control mass spectrum peak is obtained.
In operation S207, a mass number shift is determined from the isotope mass spectrometry peak and the control mass spectrometry peak.
In operation S208, the number of 15 N is determined according to the atomic weight difference of 15 N and 14 N and the mass number offset.
In operation S209, the initial metabolite list is screened with the number 15 N, resulting in a metabolite list identified by 15 N.
FIG. 3 shows a flow chart of a bacterial metabolite analysis method with 12 C-glucose/14 N-ammonium chloride as control medium and 13 C-glucose/14 N-ammonium chloride as experimental medium.
As shown in fig. 3, the method of this embodiment includes operations S301 to S309.
In operation S301, bacteria are cultured using a medium containing 12 C-glucose/14 N-ammonium chloride, to obtain bacteria of a control group.
In operation S302, mass spectrometry is performed after ionization of bacteria in the control group, so as to obtain a mass spectrum of the control group.
In operation S303, a control mass spectrum peak in the mass spectrum of the control group is extracted, and candidate metabolites corresponding to the control mass spectrum peak are matched from the metabolite database, thereby obtaining an initial metabolite list.
In operation S304, bacteria are cultured using a medium comprising 13 C-glucose/14 N-ammonium chloride, resulting in bacteria of a second experimental group.
In operation S305, mass spectrometry is performed after ionization of the bacteria of the second experimental group, and a mass spectrum of the second experimental group is obtained.
In operation S306, a second experimental mass spectrum peak in the second experimental group mass spectrum is extracted, and an isotope mass spectrum peak corresponding to the control mass spectrum peak is obtained.
In operation S307, a mass number offset is determined from the isotope mass spectrometry peak and the control mass spectrometry peak.
In operation S308, the number of 13 C is determined according to the atomic weight difference of 13 C and 12 C and the mass number offset.
In operation S309, the initial metabolite list is screened using the number of 13 C, resulting in a metabolite list after being identified by 13 C.
FIG. 4 shows a flow chart of a bacterial metabolite analysis method with 12 C-glucose/14 N-ammonium chloride as control medium and 13 C-glucose/15 N-ammonium chloride as experimental medium.
As shown in fig. 4, the method of this embodiment includes operations S401 to S409.
In operation S401, bacteria are cultured using a medium containing 12 C-glucose/14 N-ammonium chloride, to obtain bacteria of a control group.
In operation S402, mass spectrometry is performed after ionization of bacteria in the control group, and a mass spectrum of the control group is obtained.
In operation S403, a control mass spectrum peak in the mass spectrum of the control group is extracted, and candidate metabolites corresponding to the control mass spectrum peak are matched from the metabolite database, thereby obtaining an initial metabolite list.
In operation S404, bacteria are cultured using a medium comprising 13 C-glucose/15 N-ammonium chloride, resulting in bacteria of a third experimental group.
In operation S405, mass spectrometry is performed after ionization of the bacteria of the third experimental group, so as to obtain a mass spectrum of the third experimental group.
In operation S406, a third experimental mass spectrum peak in the third experimental group mass spectrum is extracted to obtain an isotope mass spectrum peak corresponding to the control mass spectrum peak.
In operation S407, a mass number offset is determined from the isotope mass spectrometry peak and the control mass spectrometry peak.
In operation S408, the number of 13 C and the number of 15 N are determined from the atomic weight difference of 13 C and 12 C, the atomic weight difference of 15 N and 14 N, and the mass number offset.
In operation S409, the initial metabolite list is screened using the number of 13 C and the number of 15 N, resulting in a metabolite list identified by 13 C and 15 N.
According to embodiments of the present disclosure, 13 C and 15 N and other isotopes are used as the sole elemental sources, and 13 C and 15 N and other isotopes are used to label the metabolites to create a shift in molecular weight, thereby calculating the number of carbon and nitrogen atoms and other atoms contained in the metabolites, achieving a significant increase in the confidence of identification of the metabolite assignments, eliminating a large number of false positive identification results.
It should be noted that, unless there is an execution sequence between different operations or an execution sequence between different operations in technical implementation, the execution sequence between multiple operations may be different, and multiple operations may also be executed simultaneously in the embodiment of the disclosure.
In order to make the objects, technical solutions and advantages of the present disclosure more apparent, the present invention will be further described in detail below with reference to specific embodiments thereof with reference to the accompanying drawings.
Example 1 identification of glutathione in bacteria
(1) Bacterial culture
Coli cells were cultured using M9 medium as a modified medium for carbon nitrogen. Wherein, the culture medium containing 12 C glucose/14 N-ammonium chloride is used as a control group culture medium, the culture medium containing 13 C glucose/14 N-ammonium chloride is used as an experiment A group culture medium, the culture medium containing 12 C glucose/15 N-ammonium chloride is used as an experiment B group culture medium, and the culture medium containing 13 C glucose/15 N-ammonium chloride is used as an experiment C group culture medium.
Wherein 12 C glucose/14 N-ammonium chloride derived E.coli ER2566 cells were prepared as follows: the newly transformed cell colonies grown on LB agar containing the appropriate antibiotics were inoculated into 2mL of M9 medium (containing 6.8g L-1 Na2HPO4,3g L-1 KH2PO4,0.5g L-1 NaCl,2mM L-1 MgSO4,0.5g L-1 14N- ammonium chloride, 4g L -1 12 C-glucose) as bacterial samples of the control group.
13 E.coli ER2566 cells from C glucose/14 N-ammonium chloride were prepared as follows: the newly transformed cell colonies grown on LB agar containing the appropriate antibiotics were inoculated into 2mL of M9 medium (containing 6.8g L-1 Na2HPO4,3g L-1KH2PO4,0.5g L-1 NaCl,2mM L-1 MgSO4,0.5g L-1 14N- ammonium chloride, 4g L -1 13 C-glucose) as bacterial samples for experiment A.
12 E.coli ER2566 cells from C glucose/15 N-ammonium chloride were prepared as follows: the newly transformed cell colonies grown on LB agar containing the appropriate antibiotics were inoculated into 2mL of M9 medium (containing 6.8g L-1 Na2HPO4,3g L-1KH2PO4,0.5g L-1 NaCl,2mM L-1 MgSO4,0.5g L-1 15N- ammonium chloride, 4g L -1 12 C-glucose) as bacterial samples for experiment B.
13 E.coli ER2566 cells from C glucose/15 N-ammonium chloride were prepared as follows: the newly transformed cell colonies grown on LB agar containing the appropriate antibiotics were inoculated into 2mL of M9 medium (containing 6.8g L-1 Na2HPO4,3g L-1KH2PO4,0.5g L-1 NaCl,2mM L-1 MgSO4,0.5g L-1 15N- ammonium chloride, 4g L -1 13 C-glucose) as bacterial samples for experiment group C.
After the above-mentioned bacterial samples of the control group, the bacterial sample of the experiment A group, the bacterial sample of the experiment B group and the bacterial sample of the experiment C group were cultured at 37℃and the OD600 reached 0.8, the bacteria of the control group (cell-C12N 14), the bacteria of the experiment A group (cell-C13N 14), the bacteria of the experiment B group (cell-C12N 15) and the bacteria of the experiment C group (cell-C13N 15) were obtained.
(2) Mass spectrometry detection
The control bacteria, the test group A bacteria (cell-C13N 14), the test group B bacteria (cell-C12N 15) and the test group C bacteria (cell-C13N 15) were collected by centrifugation, resuspended in 1mL of deionized water, and recovered at 4℃to obtain the resuspended control bacteria, the resuspended test group A bacteria, the resuspended test group B bacteria and the resuspended test group C bacteria, respectively.
Supernatants from the control, the A, B and C bacteria were diluted 10-fold with 10mM ammonium acetate for the experiments.
And respectively injecting the diluted bacteria of the re-suspension control group, the re-suspension experiment group A, the re-suspension experiment group B and the re-suspension experiment group C into a capillary, applying alternating voltage by using induction electric spray, and collecting mass spectrograms to obtain a mass spectrogram of the control group, a mass spectrogram of the experiment group A, a mass spectrogram of the experiment group B and a mass spectrogram of the experiment group C. Wherein the alternating voltage is set to 200Hz, 10kVp-p and the frequency of the sine wave. The basic parameters of the mass spectrometer are set as follows: orbitrap mass spectrum is Exactive Plus mass spectrometer (ThermoFisher Scientific, CA, USA) with acquisition parameters: S-Lens radio frequency level 50%, capillary transmission temperature 275 ℃, average spectrum frame number 1 frame, mass resolution 140000, mass scanning range 100-1500, AGC threshold 1e6.
(3) And reading a mass spectrum of the control group to obtain a control mass spectrum peak. For the detected control mass spectrum peak, the metabolite dataset of the Human Metabolome Database (HMDB) was used to retrieve with a retrieval accuracy mass of 10ppm, obtaining an initial metabolite list and constituent atomic information.
Fig. 5A shows a mass spectrum of a control group of e.
FIG. 5B shows a mass spectrum peak profile of different endogenous compounds detected in E.coli.
As shown in fig. 5A to 5B, mass spectrum peaks in the mass spectrum of the control group of e.coli metabolites include, for example: 104.0709 (designated as [ C 1H9NO2+H]+ ], 134.0446 (designated as [ C 4H7NO4+H]+ ]), 147.1125 (designated as [ C 6H14N2O2+H]+ ]), 188.1756 (designated as [ C 9H21N3O+H]+ ]), 203.0522 (designated as [ C 6H12O6+Na]+ ]), 308.0908 (designated as [ C 10H17N3O6S+H]+ ]).
(4) And respectively reading an experiment A group mass spectrogram, an experiment B group mass spectrogram and an experiment C group mass spectrogram, further distributing mass spectrum peaks according to mass displacement of isotopes of carbon atoms (12C/13 C) and nitrogen atoms (14N/15 N), calculating 13 C numbers and 15 N numbers, and screening an initial metabolite list by using 13 C numbers and 15 N numbers to obtain a final metabolite list.
FIG. 6 shows representative mass spectral peaks of [ glutathione+H ] + in control group bacteria (d), experimental group A bacteria (B), experimental group B bacteria (C) and experimental group C bacteria (a), and mass shifts based on 12 C-glucose/14 N-ammonium chloride.
Fig. 7 shows a list of initial metabolites corresponding to mass spectral peaks for m/z= 308.0907.
As shown in fig. 6 and 7, in the absence of carbon/nitrogen labeling (control bacteria, cell-C12N 14), mass spectrum peak m/z= 308.0908 was detected and 6 candidate metabolites were allocated within a mass error of 5ppm, thus giving a probability of 1/6.
In the case of labeling with nitrogen atoms (group B bacteria, cell-C12N 15), a mass spectrum peak at m/z= 311.0816 (as in graph C in fig. 6) was detected, which was shifted by 2.9908 with respect to 308.0908, the number of N atoms that could be tentatively set to 3 by 3× (15N-14 N).
In the case of labeling with carbon atoms (group a bacteria, cell-C13N 14), a mass spectrum peak at m/z= 318.1240 (as in b plot in fig. 6) was detected, which was shifted by 10.0332 with respect to 308.0908, the number of C atoms that could be tentatively set to 10 by 10× (13C-12 C).
In the case of labeling with carbon and nitrogen atoms (experimental group C bacteria, cell-C13N 15), a mass spectrum peak at m/z= 321.1153 (as in a graph of fig. 6) was detected, which was shifted by 13.0622 with respect to 308.0907, the number of C atoms could be 10 according to 10× (13C-12C)+3×(15N-14 N) tentative, and the number of N atoms was 3.
Referring to fig. 7, of the 6 candidate metabolites, only glutathione contains 3 nitrogen atoms and 10 carbon atoms, so that the use of isotopic labeling can make m/z= 308.0908 the unique identification of glutathione. I.e. the final metabolite list corresponding to mass spectrum peak 308.0908 contains the metabolite glutathione. Thus, the use of isotopic labeling in live cell metabolite mass spectrometry improves the recognition confidence of m/z assignments.
FIG. 8 shows representative mass spectra of [ glutathione+Na ] + a-d; [ maltohexaose+Na ] + and its isomers, e-H; [ lysine+H ] + and its isomers, i-l; [ glucose+Na ] + and its isomers, m-p) in mass spectra based on 12 C-glucose/14 N-ammonium chloride obtained in living cells using 13 C-glucose/15 N-ammonium chloride (a, e, i, m), 13 C-glucose/14 N-ammonium chloride (b, f, j, N), 12 C-glucose/15 N-ammonium chloride (C, g, k, o) and 12 C-glucose/14 N-ammonium chloride (d, H, l, p) in a medium.
FIG. 9 shows representative mass spectra of [ glutathione+K ] + obtained in living cells using 13 C-glucose/15 N-ammonium chloride (a), 13 C-glucose/14 N-ammonium chloride (b), 12 C-glucose/15 N-ammonium chloride (C) and 12 C-glucose/14 N-ammonium chloride (d) in a medium, the mass shift based on 12 C-glucose/14 N-ammonium chloride being marked in the mass spectra.
As shown in fig. 8 and 9, since the 2.9908 mass shift peak found in the experimental group B bacteria (cell-C12N 15), the 10.0332 mass shift peak found in the experimental group a bacteria (cell-C13N 14), and the 13.0622 mass shift peak found in the experimental group C bacteria (cell-C13N 15), mass spectrum peaks m/z= 330.0727 (fig. 8 a-d) and 340.0468 (fig. 9) can be assigned to [ glutathione+na ] + and [ glutathione+k ] +, respectively.
Figure 10 shows three repeat mass spectra of e.coli cells measured by electrospray.
FIG. 11 shows the ionic binding type of bacterial metabolites.
As shown in fig. 10 and 11, the mass spectrogram of the control group of this example detected more than 3000M/z features, and 223 features were finally confirmed by the following isotope labeling experiments (fig. 10), which contained 30% [ m+h ] +、22%[M+H-H2O]+、19%[M+Na]+、18%[M+NH4]+ and 12% [ m+k ] + (fig. 11).
To evaluate the reproducibility and robustness of the methods provided by the present disclosure, three batches of E.coli cell suspensions were tested, with mass spectra and metabolites showing strong correlations between batches. As shown in fig. 10, the correlation coefficient in the mass spectrum is greater than 0.92, and the correlation coefficient in the metabolite is greater than 0.98. The method shows high reproducibility and robustness in the direct analysis of metabolites of living E.coli cells.
Example 2 identification of oligosaccharides in bacteria
The method for identifying oligosaccharides in bacteria was the same as in example 1. The following example of [ C 36H62O31+Na]+ ] further illustrates that the confidence probability can be increased using the methods provided by the present disclosure.
Fig. 12 shows a list of initial metabolites corresponding to mass spectral peaks for m/z= 1013.3094.
As shown in the mass spectrum h in fig. 8 and fig. 12, in the absence of the carbon/nitrogen label (control bacteria, cell-C12N 14), a mass spectrum peak at m/z= 1013.3094 was detected, and 6 candidate metabolites were allocated within a mass error of 15ppm, thus giving a probability of 1/6.
As in the mass spectrum g in fig. 8, in the case of labeling by nitrogen atom (experimental group B bacteria, cell-C12N 15), a mass spectrum peak at m/z= 1013.3094 was detected, indicating that the candidate was free of nitrogen atom.
In the case of labeling with carbon atoms (experimental group a bacteria, cell-C13N 14) as in the mass spectrum f in fig. 8, a mass spectrum peak at m/z= 1049.4298 was detected, and the mass shift was 36.1204 with respect to 1013.3094, and the number of C atoms was tentatively 36 by 36× (13C-12 C).
In the case of labeling with carbon and nitrogen atoms (experimental group C bacteria, cell-C13N 15) as in the mass spectrum e of fig. 8, a mass spectrum peak at m/z= 1049.4298 was detected, which was mass shifted by 36.1204 with respect to 1013.3094, and the number of C atoms was tentatively 36 by 36× (13C-12C)+0×(15N-14 N), without N atoms.
Referring to fig. 12, among the 6 candidate metabolites, 3 compounds (pgg-dextran/a Zhu Tang/maltohexaose) contained 0 nitrogen atom and 36 carbon atoms, and thus, the candidate metabolites corresponding to m/z= 1013.3094 contained 3, with a confidence increased to 1/3.
Example 3 search of metabolite batches in bacteria
Following steps (1) to (3) in example 1, determining the number of carbon atoms by using a mass spectrum of the experimental group A bacteria (cell-C13N 14), and screening an initial metabolite list by using the number of carbon atoms to obtain an experimental group A metabolite list; determining the number of nitrogen atoms by utilizing a mass spectrogram of the bacteria (cell-C12N 15) in the experiment B group, and screening an initial metabolite list by utilizing the number of the nitrogen atoms to obtain the metabolite list in the experiment B group; and determining the number of carbon atoms and the number of nitrogen atoms by utilizing a mass spectrogram of the experimental group C bacteria (cell-C13N 15), and screening an initial metabolite list by utilizing the combination of the number of carbon atoms and the number of nitrogen atoms to obtain an experimental group C metabolite list.
FIG. 13 shows Venn diagrams of metabolites identified for group A bacteria (cell, C13N 14), group B bacteria (cell-C12N 15), group C bacteria (cell-C13N 15), and control group bacteria (cell-C12N 14).
Fig. 14 shows confidence probability distribution plots for metabolites that have not been isotopically filtered and isotopically filtered.
Fig. 15 shows a graph comparing the confidence probability of an isotopically unfiltered metabolite to the confidence probability of an isotopically filtered metabolite.
This example compares the initial metabolite list, the experimental group a metabolite list, the experimental group B metabolite list, the experimental group C metabolite list to evaluate the global improvement in allocation confidence.
As shown in fig. 13, 992 features were assigned to candidate features without a carbon/nitrogen label (cell-C12N 14), containing 78% (769/992) false positive identification. 350 features were assigned to candidate features by carbon atom labeling (cell-C13N 14), and these features were confirmed by carbon number, including 37% (132/350) false positive identification. Candidate features were assigned to 340 features by nitrogen atom labeling (cell-C12N 15) and these features were confirmed by nitrogen atom number, including 50% (172/340) false positives and about 29% (99/340) false negative identifications. 223 features were assigned to candidate features by carbon and nitrogen labeling (cell-C13N 15) and confirmed with nitrogen or carbon atoms. By this strategy, 78% of false positive features are identified and rejected, thereby increasing the confidence of identification of metabolite assignments.
As shown in fig. 14, the identification results of the non-isotopically filtered and isotopically filtered metabolites were compared, and the metabolites were ranked in order of higher confidence, wherein the rounded points represent the confidence probability distribution of the non-isotopically filtered metabolites and the rectangles represent the confidence probability distribution of the isotopically filtered metabolites. Under the condition that the carbon and nitrogen atom labeling and filtering are used, the overall identification confidence of the metabolites is higher than that of the identification result without using the isotope tracking labeling, so that the identification confidence of the metabolites in bacteria can be remarkably improved by the bacterial metabolite analysis method provided by the disclosure.
As shown in fig. 15, histogram statistics were performed on the confidence probabilities of the non-isotopically filtered metabolites and the confidence probabilities of the isotopically filtered metabolites, and in the case of labeling and filtering by carbon and nitrogen atoms, about 60 features were assigned as unique candidate features, and 35 features were assigned to 2 candidate features. Mass spectral peaks with confidence probabilities below 0.05 based on carbon and nitrogen atom labeling and filtering (isotopically filtered) are significantly reduced compared to mass spectral peaks without carbon/nitrogen labeling (isotopically filtered). Thus, metabolite identification confidence based on carbon/nitrogen labeling is generally increased.
According to the embodiment of the disclosure, an analysis method for improving the confidence of identifying a metabolite in a direct sample injection mass spectrometry bacterium is provided, an isotope compound is used as an isotope source for bacterial culture, the mass number offset of the metabolite after bacterial culture is calculated, the chemical composition contained in the bacterial metabolite is obtained, false positive identification information of identifying the bacterial metabolite in the direct sample injection method is eliminated, and the analysis method is different from the prior art in that the isotope labeling mode is used for improving the confidence of identifying the bacterial metabolite in the direct sample injection method, and more reliable metabolite identification information is obtained.
Those skilled in the art will appreciate that the features recited in the various embodiments of the disclosure and/or in the claims may be provided in a variety of combinations and/or combinations, even if such combinations or combinations are not explicitly recited in the disclosure. In particular, the features recited in the various embodiments of the present disclosure and/or the claims may be variously combined and/or combined without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of the present disclosure.
The embodiments of the present disclosure are described above. These examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the disclosure, and such alternatives and modifications are intended to fall within the scope of the disclosure.
Claims (10)
1. A method of bacterial metabolite analysis comprising:
Culturing bacteria by using a control group culture medium and an experimental group culture medium respectively to obtain control group bacteria and experimental group bacteria, wherein the control group culture medium takes a compound containing target atoms as an intake raw material for bacterial growth; the experimental group culture medium uses a compound obtained by replacing the target atom with the isotope of the target atom as a raw material for bacterial growth and ingestion;
Respectively carrying out mass spectrum detection on the bacteria in the control group and the bacteria in the experimental group to obtain a mass spectrum of the control group and a mass spectrum of the experimental group;
Matching candidate metabolites corresponding to the control mass spectrum peaks from a metabolite database aiming at each control mass spectrum peak in the control mass spectrum to obtain an initial metabolite list;
determining an isotope mass spectrometry peak corresponding to the control mass spectrometry peak from the experimental group mass spectrogram;
Determining the number of target atoms contained in an actual metabolite corresponding to the control mass spectrum peak according to the control mass spectrum peak, the isotope mass spectrum peak and the target atoms to obtain the number of atoms; and
Screening the candidate metabolites in the initial metabolite list by utilizing the atomic number to obtain a final metabolite list so as to facilitate bacterial metabolite analysis according to the final metabolite list.
2. The method of claim 1, wherein the determining from the experimental group mass spectrum an isotope mass spectrum peak corresponding to the control mass spectrum peak comprises:
determining, for each experimental mass spectrum peak in the experimental group mass spectrum, a first mass shift between the experimental mass spectrum peak and the control mass spectrum peak;
And under the condition that the first mass displacement meets a preset condition, determining the experimental mass spectrum peak as the isotope mass spectrum peak corresponding to the control mass spectrum peak.
3. The method of claim 2, wherein the preset condition comprises a determination based on an atomic weight difference between an isotope of the target atom and the target atom.
4. The method of claim 1, wherein the determining the number of target atoms contained in the actual metabolite corresponding to the control mass spectrum peak from the control mass spectrum peak, the isotope mass spectrum peak, and the target atoms, the resulting number of atoms comprises:
determining a second mass shift corresponding to the target atom from the control mass spectrum peak and the isotope mass spectrum peak;
and determining the number of the target atoms contained in the actual metabolites corresponding to the control mass spectrum peak according to the difference value between the isotope of the target atoms and the atomic weight of the target atoms and the second mass shift, so as to obtain the atomic number.
5. The method of claim 1, wherein said screening said candidate metabolites in said initial metabolite list with said atomic number to obtain a final metabolite list comprises:
Determining, for each candidate metabolite in the initial metabolite list, the number of target atoms contained in the candidate metabolite;
Determining the candidate metabolite as a target metabolite in the case where the number of the target atoms contained in the candidate metabolite is determined to be the same as the number of atoms;
The final metabolite list is obtained from the target metabolites.
6. The method of claim 1, wherein the mass spectrometric detection of the control group of bacteria and the experimental group of bacteria, respectively, to obtain a control group mass spectrum and an experimental group mass spectrum comprises:
Centrifuging the bacteria of the control group, discarding the supernatant, and then re-suspending to obtain the bacteria of the control group after re-suspending;
Filling the resuspended bacteria of the control group into a capillary spray needle, applying voltage to generate electrospray, and detecting signals by using a mass spectrometer to obtain a mass spectrogram of the control group;
centrifuging the experimental group bacteria, removing supernatant, and then re-suspending to obtain re-suspended experimental group bacteria;
and pouring the resuspended experimental group bacteria into a capillary spray needle, applying voltage to generate electrospray, and detecting signals by using the mass spectrometer to obtain the mass spectrogram of the experimental group.
7. The method of claim 6, further comprising:
Before the resuspended control group bacteria or the resuspended experimental group bacteria are poured into the capillary needle, the bacteria are lysed by ultrasonic waves or methanol.
8. The method of claim 1, wherein said matching candidate metabolites corresponding to the control mass spectral peak from a metabolite database comprises:
Determining, for each metabolite in the metabolite database, a difference between a peak value of the control mass spectrum peak and a molecular weight of the metabolite;
And under the condition that the absolute value of the difference value is smaller than or equal to a preset precision value, determining the metabolite as the candidate metabolite corresponding to the contrast mass spectrum peak.
9. The method of claim 8, wherein the preset precision value is determined according to a charge-to-mass ratio of a reference mass spectrum peak, and is 15ppm in the case that the charge-to-mass ratio of the reference mass spectrum peak is 400 or less; in the case that the charge-to-mass ratio of the control mass spectrum peak is greater than 400, the preset precision value is 30ppm.
10. The method of claim 1, wherein the target atom comprises one or more of a carbon atom, a nitrogen atom, an oxygen atom, a hydrogen atom, a chlorine atom.
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