CN115290739A - Bacterial metabolite analysis method - Google Patents

Bacterial metabolite analysis method Download PDF

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CN115290739A
CN115290739A CN202210971858.7A CN202210971858A CN115290739A CN 115290739 A CN115290739 A CN 115290739A CN 202210971858 A CN202210971858 A CN 202210971858A CN 115290739 A CN115290739 A CN 115290739A
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CN115290739B (en
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黄光明
侯壮豪
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University of Science and Technology of China USTC
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Abstract

The disclosure provides a bacterial metabolite analysis method, which can be applied to 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 a target atom as a bacteria growth intake raw material and an experimental group culture medium which takes a compound replacing the target atom by an isotope as the bacteria growth intake raw material to obtain a control group bacteria and an experimental group bacteria; detecting mass spectra of the control group bacteria and the experimental group bacteria to obtain a control group mass spectrogram and an experimental group mass spectrogram; matching corresponding candidate metabolites aiming at each control mass spectrum peak in the control group mass spectrum to obtain an initial metabolite list; determining an isotope mass spectrum peak corresponding to the reference 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; and screening the initial metabolite list by using the number of atoms to obtain a final metabolite list so as to perform bacterial metabolite analysis according to the final metabolite list.

Description

Bacterial metabolite analysis method
Technical Field
The present disclosure relates to the field of biological mass spectrometry, and more particularly to a method for analyzing bacterial metabolites.
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 are developed at present for qualitative and quantitative analysis of cell metabolites, and a direct sample injection method based on induced electrospray mass spectrometry can realize detection of proteins and protein interactions of living cells and has great potential in the aspect of metabolite detection.
However, under limited mass spectrum resolution, mass spectrum peaks of metabolites with similar molecular weights overlap, so that a large number of false positives exist in the retrieval 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 problems, the present disclosure provides a bacterial metabolite analysis method including:
respectively culturing bacteria by using a control group culture medium and an experimental group culture medium to obtain a control group bacteria and an experimental group bacteria, wherein the control group culture medium takes a compound containing a target atom as an intake raw material for the growth of the bacteria; 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 uptake;
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;
aiming at each control mass spectrum peak in the control group mass spectrum, matching candidate metabolites corresponding to the control mass spectrum peak from a metabolite database to obtain an initial metabolite list;
determining an isotope mass spectrum peak corresponding to the reference mass spectrum peak from the experimental group mass spectrum;
determining the number of the target atoms contained in the actual metabolite corresponding to the reference mass spectrum peak according to the reference mass spectrum peak, the isotope mass spectrum peak and the target atoms to obtain 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 perform bacterial metabolite analysis according to the final metabolite list.
According to an embodiment of the present disclosure, the determining the isotope mass spectrum peak corresponding to the reference mass spectrum peak from the experimental group mass spectrum 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 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 reference mass spectrum peak.
According to an embodiment of the present disclosure, the preset condition includes determining 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 atom included in the actual metabolite corresponding to the reference mass spectrum peak from the reference mass spectrum peak, the isotopic mass spectrum peak, and the target atom, and obtaining the number of atoms includes:
determining a second mass shift corresponding to the target atom based on the reference mass spectrum peak and the isotopic mass spectrum peak;
and determining the number of the target atom contained 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, to obtain the atomic number.
According to an embodiment of the present disclosure, the screening the candidate metabolites in the initial metabolite list by using the number of atoms to obtain a final metabolite list includes:
determining, for each candidate metabolite in said initial metabolite list, a number of said target atoms comprised in said candidate metabolite;
determining the candidate metabolite as a target metabolite when the number of target atoms included in the candidate metabolite is equal to the number of atoms;
and obtaining the final metabolite list according to the target metabolites.
According to the embodiment of the present disclosure, the mass spectrometric detection of the bacteria in the control group and the bacteria in the experimental group to obtain a mass spectrogram of the control group and a mass spectrogram of the experimental group respectively comprises:
centrifuging the control group bacteria, removing supernatant, and then re-suspending to obtain re-suspended control group bacteria;
pouring the resuspended control group bacteria into a capillary spray needle, applying voltage to generate electrospray, and performing signal detection by using a mass spectrometer to obtain a mass spectrogram of the control group;
centrifuging the bacteria in the experimental group, removing supernatant, and then re-suspending to obtain re-suspended bacteria in the experimental group;
and (3) pouring the resuspended experimental group bacteria into a capillary spray needle, applying voltage to generate electrospray, and performing signal detection by using the mass spectrometer to obtain the experimental group mass spectrogram.
According to an embodiment of the present disclosure, the above bacterial metabolite analysis method further includes:
before the resuspended control group bacteria or the resuspended experimental group bacteria are poured into the capillary spray needle, the bacteria are lysed by using ultrasonic waves or methanol.
According to an embodiment of the present disclosure, the matching the candidate metabolites corresponding to the reference mass spectrum peak from the metabolite database includes:
determining for each metabolite in said metabolite database a difference between a peak value of said control mass spectrum peak and a molecular weight of said metabolite;
and determining the metabolite as the candidate metabolite corresponding to the reference mass spectrum peak when the absolute value of the difference is less than or equal to a preset precision value.
According to the embodiment of the disclosure, the preset precision value is determined according to the charge-to-mass ratio of the reference mass spectrum peak, and under the condition that the charge-to-mass ratio of the reference mass spectrum peak is less than or equal to 400, the preset precision value is 15ppm; when the charge-to-mass ratio of the reference mass spectrum peak is greater than 400, the preset precision value is 30ppm.
According to an embodiment of the present disclosure, the target atoms include one or more of carbon atoms, nitrogen atoms, oxygen atoms, hydrogen atoms, and chlorine atoms.
According to the embodiment of the present disclosure, since the bacteria are cultured using the control group culture medium and the experimental group culture medium, respectively, the control group bacteria and the experimental group bacteria are obtained, wherein the control group culture medium uses the compound containing the target atom as the raw material for the intake of the bacteria growth, and the experimental group culture medium uses the compound obtained by replacing the target atom with the isotope of the target atom as the raw material for the intake of the bacteria growth; then respectively carrying out mass spectrum detection on the bacteria in the control group and the bacteria in the experimental group, and matching corresponding candidate metabolites from a metabolite database aiming at each control mass spectrum peak in the mass spectrum of the control group to obtain an initial metabolite list; determining an isotope mass spectrum peak corresponding to the reference mass spectrum peak from the experimental group mass spectrum; determining the number of target atoms contained in the actual metabolite corresponding to the reference mass spectrum peak according to the reference mass spectrum peak, the isotope mass spectrum peak and the target atoms to obtain the number of atoms; and then screening candidate metabolites in the initial metabolite list by utilizing the atomic number to obtain a final metabolite list so as to carry out a bacterial metabolite analysis technical means according to the final metabolite list, so that the technical problems that in the related technology, due to limited mass spectrum resolution and overlapping mass spectrum peaks of metabolites with similar molecular weights, a large number of false positives exist in retrieval 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 are at least partially overcome, the number of false positive metabolites corresponding to the mass spectrum peaks is reduced, the identification confidence of metabolite distribution is improved, and the technical effect of obtaining more reliable metabolite identification information is facilitated.
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The foregoing and other objects, features and advantages of the disclosure will be apparent from the following description of embodiments of the disclosure, which proceeds with reference to the accompanying drawings, in which:
FIG. 1 shows a flow diagram of a bacterial metabolite analysis method according to an embodiment of the present disclosure;
FIG. 2 shows 12 C-glucose- 14 N-ammonium chloride was used as a control medium, 12 c-glucose- 15 Using N-ammonium chloride as the experimental group culture mediumA flow chart of a bacterial metabolite analysis method;
FIG. 3 shows 12 C-glucose- 14 N-ammonium chloride was used as a control medium, 13 c-glucose- 14 A flow chart of a bacterial metabolite analysis method using N-ammonium chloride as a culture medium of an experimental group;
FIG. 4 shows 12 C-glucose- 14 N-ammonium chloride was used as a control medium, 13 c-glucose- 15 A flow chart of a method for analyzing bacterial metabolites using N-ammonium chloride as a culture medium of an experimental group;
FIG. 5A shows a control mass spectrum of E.coli;
FIG. 5B shows a mass spectrometric peak profile of different endogenous compounds detected in E.coli;
FIG. 6 schematically shows [ glutathione + H ] in control group bacteria (d), experiment A group bacteria (B), experiment B group bacteria (C), and experiment C group bacteria (a)] + And based on 12 C-glucose- 14 Mass shift of N-ammonium chloride;
figure 7 shows an initial metabolite list corresponding to mass spectrum peaks for m/z = 308.0907;
FIG. 8 shows the use in culture media 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) obtained in viable cells ([ glutathione + Na)] + a-d; [ maltose + Na [ ]] + And isomers thereof, e-h; [ lysine + H ]] + And isomers thereof, i-1; [ glucose + Na ]] + And isomers thereof, m-p), in which the labeling is based on 12 C-glucose- 14 Mass shift of N-ammonium chloride;
FIG. 9 shows the use in culture media 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 Obtaining [ glutathione + K ] in viable cells by N-ammonium chloride (d)] + A representative mass spectrum of (1), in which the base is labeled 12 C-glucose- 14 Mass shift of N-ammonium chloride;
FIG. 10 shows three replicate mass spectra of E.coli cells measured by electrospray;
FIG. 11 shows the ion binding type of bacterial metabolites;
figure 12 shows an initial metabolite list corresponding to mass spectrum peaks for m/z = 1013.3094;
FIG. 13 shows a Venn diagram of the metabolites identified for the experimental group A bacteria (cell-C13N 14), the experimental group B bacteria (cell-C12N 15), the experimental group C bacteria (cell-C13N 15), and the control group bacteria (cell-C12N 14);
FIG. 14 shows confidence probability distribution plots for metabolites that have not been isotope filtered and isotope filtered; and
FIG. 15 shows a comparison of confidence probabilities for metabolites that were not isotope filtered versus those that were isotope filtered.
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 illustrative only 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 disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not 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 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 is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.
Where a convention analogous to "A, B and at least one of C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include, but not be limited to, systems that have 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 recognition and metabolic flux analysis of extracted samples and living cells, but their low sensitivity limits further applications. Raman spectroscopy enables relatively comprehensive metabolic detection, but spectral overlap of metabolites in organisms limits its further applications. Fluorescence spectroscopy has been used for metabolite dynamics monitoring in model cells, but is difficult to extend to the detection of non-targeted or unknown metabolites. Due to the high sensitivity and high throughput of biological samples and the absence of labeling requirements, mass spectrometry based on gas chromatography or high performance liquid chromatography combined with sampling pre-processing strategies such as liquid extraction and solid phase micro-extraction enrichment have become indispensable analytical tools in metabolite analysis. However, the requirements of sample preparation limit its application in the analysis of metabolites of living cells.
Direct sample introduction methods based on induced electrospray mass spectrometry have now enabled detection of proteins and protein interactions in living cells and have shown great potential in the detection of metabolites. However, under limited mass spectrum resolution, mass spectrum peaks of metabolites with similar molecular weights overlap, so that a large number of false positives exist in the retrieval 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 is directed to the above technical problems, and an isotope is used as a unique element source to label a metabolite, so that a mass spectrum peak of the metabolite generates a shift of a molecular weight, thereby calculating the number of isotope atoms included in the metabolite, and then the number of isotope atoms is used to screen the metabolite, so as to exclude false positive identification information identified by a bacterial metabolite, thereby helping to reduce the number of false positive metabolites corresponding to the mass spectrum peak, so that an identification confidence of metabolite allocation is significantly increased, and more reliable metabolic identification information is obtained. For example, by using 13 C and 15 n and other isotopes as the sole source of elements, using 13 C and 15 n and other isotopes mark the metabolites, so that the metabolites generate molecular weight deviation, the number of carbon atoms, nitrogen atoms and other atoms contained in the metabolites is calculated, the identification confidence of metabolite distribution is obviously increased, and the detection of non-target metabolites in living escherichia coli can be realized.
Specifically, embodiments of the present disclosure provide a bacterial metabolite analysis method, comprising: respectively culturing bacteria by using a control group culture medium and an experimental group culture medium to obtain a control group bacteria and an experimental group bacteria, wherein the control group culture medium takes a compound containing a target atom as an intake raw material for the growth of the bacteria; 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 uptake; 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 reference mass spectrum peaks from a metabolite database aiming at each reference mass spectrum peak in the reference group mass spectrum to obtain an initial metabolite list; determining an isotope mass spectrum peak corresponding to the reference mass spectrum peak from the experimental group mass spectrum; determining the number of the target atoms contained in the actual metabolite corresponding to the reference mass spectrum peak according to the reference 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 using the number of atoms to obtain a final metabolite list so as to perform bacterial metabolite analysis according to the final metabolite list.
Fig. 1 shows a flow diagram of a method of bacterial metabolite analysis 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.
In operation S110, culturing bacteria using a control culture medium and an experimental culture medium, respectively, to obtain a control bacterium and an experimental bacterium, wherein the control culture medium uses a compound containing a target atom as an uptake 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 uptake.
According to an embodiment of the present disclosure, the target atoms include one or more of carbon atoms, nitrogen atoms, oxygen atoms, hydrogen atoms, and chlorine atoms.
According to an embodiment of the present disclosure, a target atom may be an atom. For example, the target atom is a carbon atom, and the control medium may comprise 12 C-glucose, the experimental group medium may include 13 C-glucose; if the target atom is a nitrogen atom, the control medium may include 14 N-ammonium chloride, the experimental group culture medium may include 15 N-ammonium chloride; if the target atom is oxygen, the control medium may include 16 O-H 2 O, the experimental group culture medium may include 17 O-H 2 O; if the target atom is hydrogen, the control medium may include 1 H-H 2 O, the experimental group culture medium may include 2 H-H 2 O。
According to embodiments of the present disclosure, the target atoms may also include two or more atoms. For example, the target atoms include carbon atoms and nitrogen atoms, will 12 C-glucose, 13 C-glucose, 14 N-ammonium chloride and 15 the N-ammonium chloride is arranged and combined to obtain a control group culture medium and an experimental group culture medium, wherein, 12 c-glucose- 14 N-ammonium chloride as 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 was used as the experimental group medium.
According to embodiments of the present disclosure, the control and experimental group media may further include inorganic salts, buffered salts, and water.
According to embodiments of the present disclosure, the inorganic salt may include sodium chloride, magnesium sulfate, and the like. The buffer salt may include disodium hydrogen phosphate, potassium dihydrogen phosphate, and the like.
In operation S120, mass spectrometry is performed on the control group of bacteria and the experimental group of bacteria, respectively, to obtain a control group mass spectrogram and an experimental group mass spectrogram.
According to the embodiment of the present disclosure, the mass spectrometric detection of the bacteria in the control group and the bacteria in the experimental group to obtain a mass spectrogram of the control group and a mass spectrogram of the experimental group respectively comprises: centrifuging the control group bacteria, removing supernatant, and then re-suspending to obtain re-suspended control group bacteria; pouring the resuspended control group bacteria into a capillary spray needle, applying voltage to generate electrospray, and performing signal detection by using a mass spectrometer to obtain a mass spectrogram of the control group; centrifuging the bacteria in the experimental group, removing supernatant, and then re-suspending to obtain re-suspended bacteria in the experimental group; and (3) pouring the resuspended experimental group bacteria into a capillary spray needle, applying voltage to generate electrospray, and performing signal detection by using the mass spectrometer to obtain the experimental group mass spectrogram.
According to the embodiment of the present disclosure, the control group bacteria or the experimental group bacteria are centrifuged, and after the supernatant is discarded, the control group bacteria or the experimental group bacteria can be resuspended by using deionized water.
According to this disclosed embodiment, through carrying out the centrifugation to control group bacterium or experimental group bacterium, abandon the supernatant fluid and use the deionized water heavy-suspension, help getting rid of the culture medium, avoid the metabolite in the culture medium to carry out the interference to follow-up detection.
According to an embodiment of the present disclosure, the above bacterial metabolite analysis method further includes: before the resuspended control group bacteria or resuspended experimental group bacteria are poured into the capillary spray needle, the bacteria are lysed by ultrasonic waves or methanol.
According to the embodiment of the disclosure, the bacteria are cracked, so that the release of metabolites in the bacteria is promoted, and the detection efficiency is improved.
According to an embodiment of the present disclosure, the applied voltage may be, for example, a direct current voltage or an induced voltage.
According to an embodiment of the present disclosure, the mass spectrometer may employ a high resolution mass spectrometer, for example, with a resolution greater than 60000.
In operation S130, for each control mass spectrum peak in the control group mass spectrum, a candidate metabolite corresponding to the control mass spectrum peak is matched from a metabolite database, so as to obtain an initial metabolite list.
According to an embodiment of the present disclosure, the matching of the candidate metabolites corresponding to the control mass spectrum peak from the metabolite database includes: determining for each metabolite in said metabolite database a difference between a peak value of said control mass spectrum peak and a molecular weight of said metabolite; and determining the metabolite as the candidate metabolite corresponding to the reference mass spectrum peak when the absolute value of the difference is less than or equal to a preset precision value.
According to the embodiment of the disclosure, the preset precision value is determined according to the charge-to-mass ratio of the reference mass spectrum peak, and the preset precision value is 15ppm when the charge-to-mass ratio of the reference mass spectrum peak is less than or equal to 400; when the charge-to-mass ratio of the reference mass spectrum peak is greater than 400, the preset precision value is 30ppm.
According to embodiments of the present disclosure, protonated ions [ M + H ] are utilized] + 、[M+Na] + 、[M+K] + 、[M-H 2 O+H] + And [ M + NH ] 4 ] + Peaks were used for peak assignment. That is, for each metabolite in the metabolite database, the molecular weight of the metabolite is compared with H, na, K, H 2 O+H、NH 4 The molecular weights of (a) and (b) are added to obtain the proton of the metaboliteIonizing the molecular weight of the ions; thereafter determining the difference between the peak value of the control mass spectral peak and the protonated ion molecular weight of the metabolite; and determining the metabolite as the candidate metabolite corresponding to the reference mass spectrum peak when the absolute value of the difference is less than or equal to a preset precision value.
According to an embodiment of the present disclosure, the initial metabolite list comprises the chemical composition of the candidate metabolites.
In operation S140, an isotopic mass spectrum peak corresponding to the reference mass spectrum peak is determined from the experimental group mass spectrum.
According to an embodiment of the present disclosure, the determining the isotope mass spectrum peak corresponding to the reference mass spectrum peak from the experimental group mass spectrum includes: determining a first mass shift between the experimental mass spectrum peak and the reference mass spectrum peak for each experimental mass spectrum peak in the experimental group mass spectrum; 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 reference mass spectrum peak.
According to an embodiment of the present disclosure, the preset condition includes determining according to an atomic weight difference between the 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 predetermined condition may be 13 C and 12 the atomic weight difference of C is multiplied by x. Due to the fact that 13 C and 12 and when the atomic weight difference of C is 1.0034Da and the first mass shift meets (1.0033 x), determining that the experimental mass spectrum peak is the isotope mass spectrum peak corresponding to the reference mass spectrum peak.
In one embodiment, the metabolite has x carbon atoms and y nitrogen atoms, for use 13 C-glucose- 14 The preset conditions of living cells cultured in the medium of N-ammonium chloride are determined by the following formula: Δ m =1.0034 · x (Da).
For use of 12 C-glucose- 15 N-ammonium chloride as a culture medium, and the preset conditions are determined by the following formula: Δ m =0.9970·y(Da)。
For use of 13 C-glucose- 15 The preset conditions of living cells cultured in the medium of N-ammonium chloride are determined by the following formula: Δ m =1.0034 · x +0.9970 · y (Da).
According to the embodiment of the present disclosure, other isotopes (e.g., hydrogen isotope, chlorine isotope, etc.) may perform mass shift calculation of the corresponding number of atoms according to the molecular weight of the added isotope, so as to obtain the 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 isotopic mass spectrum peak, and the target atoms, and the number of atoms is obtained.
According to an embodiment of the present disclosure, the determining the number of the target atom included in the actual metabolite corresponding to the reference mass spectrum peak from the reference mass spectrum peak, the isotopic mass spectrum peak, and the target atom, and obtaining the number of atoms includes: determining a second mass shift corresponding to the target atom based on the reference mass spectrum peak and the isotopic mass spectrum peak; and determining the number of the target atom contained 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, to obtain the atomic number.
According to an embodiment of the present disclosure, the second mass shift may include a peak difference of the isotope mass spectrum peak and the reference mass spectrum peak, and the number of the target atoms included 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, then the number of carbon atoms in the actual metabolite can be removed from the second mass position to 13 C and 12 the atomic weight difference of C.
According to an embodiment of the present disclosure, the screening the candidate metabolites in the initial metabolite list by using the number of atoms to obtain a final metabolite list includes: determining, for each candidate metabolite in said initial metabolite list, a number of said target atoms comprised in said candidate metabolite; determining the candidate metabolite as a target metabolite when the number of target atoms included in the candidate metabolite is equal to the number of atoms; and obtaining the final metabolite list according to the target metabolites.
In operation S160, the candidate metabolites in the initial metabolite list are screened by using the number of atoms to obtain a final metabolite list, so as to perform bacterial metabolite analysis according to the final metabolite list.
According to the embodiment of the present disclosure, since the bacteria are cultured using the control group culture medium and the experimental group culture medium, respectively, the control group bacteria and the experimental group bacteria are obtained, wherein the control group culture medium uses the compound containing the target atom as the raw material for the intake of the bacteria growth, and the experimental group culture medium uses the compound obtained by replacing the target atom with the isotope of the target atom as the raw material for the intake of the bacteria growth; then respectively carrying out mass spectrum detection on the bacteria in the control group and the bacteria in the experimental group, and matching corresponding candidate metabolites from a metabolite database aiming at each control mass spectrum peak in the mass spectrum of the control group to obtain an initial metabolite list; determining an isotope mass spectrum peak corresponding to the reference mass spectrum peak from the experimental group mass spectrum; determining the number of target atoms contained in the actual metabolite corresponding to the reference mass spectrum peak according to the reference mass spectrum peak, the isotope mass spectrum peak and the target atoms to obtain the number of atoms; and then screening candidate metabolites in the initial metabolite list by utilizing the atomic number to obtain a final metabolite list so as to carry out a bacterial metabolite analysis technical means according to the final metabolite list, so that the technical problems that in the related technology, mass spectrum resolution is limited, mass spectrum peaks of metabolites with similar molecular weights are overlapped, so that a large number of false positives exist in retrieval 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 are at least partially overcome, the number of false positive metabolites corresponding to the mass spectrum peaks is reduced, the identification confidence of metabolite distribution is improved, and the technical effect of obtaining more reliable metabolic identification information is facilitated.
FIG. 2 shows in order 12 C-glucose- 14 N-ammonium chloride was used as a control medium, 12 c-glucose- 15 Flow chart of a method for analyzing bacterial metabolites using N-ammonium chloride as a culture medium of the experimental group.
As shown in fig. 2, the method of this embodiment includes operations S201 to S209.
In operation S201, utilizing an include 12 C-glucose- 14 And (5) culturing the bacteria in a culture medium of N-ammonium chloride to obtain a control group of bacteria.
In operation S202, mass spectrometry is performed after the control group of bacteria is ionized, so as to obtain a control group mass spectrogram.
In operation S203, a reference mass spectrum peak in the reference mass spectrum is extracted, and candidate metabolites corresponding to the reference mass spectrum peak are matched from the metabolite database, so as to obtain an initial metabolite list.
In operation S204, utilizing an include 12 C-glucose- 15 The bacteria were cultured in N-ammonium chloride medium to obtain the first experimental group of bacteria.
In operation S205, the first experimental group of bacteria is ionized and then subjected to mass spectrometry, so as to obtain a first experimental group mass spectrogram.
In operation S206, a first experimental mass spectrum peak in the first experimental group mass spectrum is extracted to obtain an isotopic mass spectrum peak corresponding to the reference mass spectrum peak.
In operation S207, a mass number shift is determined from the isotopic mass spectrum peak and the reference mass spectrum peak.
In operation S208, according to 15 N and 14 atomic weight difference and mass number shift determination for N 15 The number of N.
In operation S209, utilize 15 N quantity screening of the initial metabolite list obtained 15 N refers to the metabolite list after assignment.
FIG. 3 shows 12 C-glucose- 14 N-ammonium chloride was used as a control medium, 13 c-glucose- 14 N-ammonium chloride asFlow chart of a method for bacterial metabolite analysis of experimental group media.
As shown in fig. 3, the method of this embodiment includes operations S301 to S309.
In operation S301, utilizing an include 12 C-glucose- 14 And (5) culturing the bacteria in a culture medium of N-ammonium chloride to obtain a control group of bacteria.
In operation S302, mass spectrometry is performed after the control group of bacteria is ionized, so as to obtain a control group mass spectrogram.
In operation S303, a control mass spectrum peak in the control mass spectrum is extracted, and candidate metabolites corresponding to the control mass spectrum peak are matched from the metabolite database, resulting in an initial metabolite list.
In operation S304, utilizing includes 13 C-glucose- 14 And (4) culturing the bacteria in a culture medium of N-ammonium chloride to obtain a second experimental group of bacteria.
In operation S305, the second experimental group of bacteria is ionized and then subjected to mass spectrometry, so as to obtain a second experimental group mass spectrogram.
In operation S306, a second experimental mass spectrum peak in the second experimental group mass spectrum is extracted to obtain an isotopic mass spectrum peak corresponding to the reference mass spectrum peak.
In operation S307, a mass number shift is determined from the isotopic mass spectrum peak and the reference mass spectrum peak.
In operation S308, according to 13 C and 12 atomic weight difference and mass number offset determination for C 13 The number of C.
In operation S309, utilize 13 Quantity of C screening of the initial metabolite list obtained 13 List of metabolites after C assignment.
FIG. 4 shows 12 C-glucose- 14 N-ammonium chloride was used as a control medium, 13 c-glucose- 15 Flow chart of a method for analyzing bacterial metabolites using N-ammonium chloride as a culture medium of the experimental group.
As shown in fig. 4, the method of this embodiment includes operations S401 to S409.
In operation S401, utilizing an include 12 C-glucose- 14 N-chloroAnd (4) culturing the bacteria in an ammonium culture medium to obtain the control group bacteria.
In operation S402, mass spectrometry is performed after the control group bacteria are ionized, so as to obtain a control group mass spectrogram.
In operation S403, a reference mass spectrum peak in the reference mass spectrum is extracted, and candidate metabolites corresponding to the reference mass spectrum peak are matched from the metabolite database, so as to obtain an initial metabolite list.
In operation S404, utilizing an include 13 C-glucose- 15 And (5) culturing the bacteria in a culture medium of N-ammonium chloride to obtain a third experimental group of bacteria.
In operation S405, the third experimental group of bacteria is ionized and then subjected to mass spectrometry, so as to obtain a third experimental group mass spectrogram.
In operation S406, a third experimental mass spectrum peak in the third experimental group mass spectrum is extracted to obtain an isotopic mass spectrum peak corresponding to the reference mass spectrum peak.
In operation S407, a mass number shift is determined from the isotopic mass spectrum peak and the reference mass spectrum peak.
In operation S408, according to 13 C and 12 the difference in atomic weight of C, 15 N and 14 atomic weight difference and mass number shift determination for N 13 Number of C and 15 the number of N.
In operation S409, utilize 13 Number of C and 15 n quantity screening of the initial metabolite list obtained 13 C and 15 n refers to the metabolite list after assignment.
According to an embodiment of the present disclosure, utilize 13 C and 15 n and other isotopes as the sole source of elements 13 C and 15 n and other isotopes mark the metabolites, so that the metabolites generate molecular weight deviation, the number of carbon atoms, nitrogen atoms and other atoms contained in the metabolites is calculated, the identification confidence of metabolite distribution is obviously increased, and a large number of false positive identification results are eliminated.
It should be noted that, unless explicitly stated that there is an execution sequence between different operations or there is an execution sequence between different operations in technical implementation, the execution sequence between multiple operations may not be sequential, or multiple operations may be executed simultaneously in the flowchart in this disclosure.
In order that the objects, aspects and advantages of the present disclosure will become more apparent, the present invention is further described in detail below with reference to specific embodiments thereof and the accompanying drawings.
Example 1 identification of glutathione in bacteria
(1) Bacterial culture
Coli cells were cultured using M9 medium as a carbon and nitrogen modified medium. Wherein to comprise 12 C glucose- 14 The culture medium of N-ammonium chloride was used as a control medium to contain 13 C glucose- 14 The culture medium of N-ammonium chloride was used as the group A culture medium for experiments to contain 12 C glucose- 15 Culture medium of N-ammonium chloride was used as the group B culture medium of experiment to contain 13 C glucose- 15 N-ammonium chloride medium was used as the experimental group C medium.
Wherein, 12 c glucose- 14 Coli ER2566 cells derived from N-ammonium chloride were prepared as follows: colonies of freshly transformed cells grown on LB agar with the appropriate antibiotic were inoculated into 2mL of M9 medium (containing 6.8g L) -1 Na 2 HPO 4 ，3g L -1 KH 2 PO 4 ，0.5g L -1 NaCl，2mM L -1 MgSO 4 ，0.5g L -1 14 N-ammonium chloride, 4g L -1 12 C-glucose) as a control bacterial sample.
13 C glucose- 14 Coli ER2566 cells derived from N-ammonium chloride were prepared as follows: colonies of freshly transformed cells grown on LB agar with the appropriate antibiotic were inoculated into 2mL of M9 medium (containing 6.8g L) -1 Na 2 HPO 4 ，3g L -1 KH 2 PO 4 ，0.5g L -1 NaCl，2mM L -1 MgSO 4 ，0.5g L -1 14 N-ammonium chloride, 4g L -1 13 C-glucose) as a bacterial sample for experiment group a.
12 C glucose- 15 Coli ER2566 cells derived from N-ammonium chloride were prepared as follows: colonies of freshly transformed cells grown on LB agar with the appropriate antibiotic were inoculated into 2mL of M9 medium (containing 6.8g L) -1 Na 2 HPO 4 ，3g L -1 KH 2 PO 4 ，0.5g L -1 NaCl，2mM L -1 MgSO 4 ，0.5g L -1 15 N-ammonium chloride, 4g L -1 12 C-glucose) as a bacterial sample for experiment group B.
13 C glucose- 15 Coli ER2566 cells derived from N-ammonium chloride were prepared as follows: colonies of freshly transformed cells grown on LB agar with the appropriate antibiotic were inoculated into 2mL of M9 medium (containing 6.8g L) -1 Na 2 HPO 4 ，3g L -1 KH 2 PO 4 ，0.5g L -1 NaCl，2mM L -1 MgSO 4 ，0.5g L -1 15 N-ammonium chloride, 4g L -1 13 C-glucose) as a bacterial sample for experiment group C.
And (3) culturing the bacterial samples of the control group, the bacterial samples of the experiment group A, the bacterial samples of the experiment group B and the bacterial samples of the experiment group C at 37 ℃, and obtaining the bacteria (cell-C12N 14) of the control group, the bacteria (cell-C13N 14) of the experiment group A, the bacteria (cell-C12N 15) of the experiment group B and the bacteria (cell-C13N 15) of the experiment group C after the OD600 reaches 0.8.
(2) Mass spectrometric detection
The control group bacteria, the experiment A group bacteria (cell-C13N 14), the experiment B group bacteria (cell-C12N 15) and the experiment C group bacteria (cell-C13N 15) are collected by centrifugation, resuspended in 1mL of deionized water, and recovered at 4 ℃ to obtain the resuspended control group bacteria, resuspended experiment A group bacteria, resuspended experiment B group bacteria and resuspended experiment C group bacteria respectively.
The supernatants of resuspending control group bacteria, resuspending experiment group a bacteria, resuspending experiment group B bacteria, and resuspending experiment group C bacteria were diluted 10-fold with 10mM ammonium acetate for the experiments.
Injecting the diluted bacteria of the heavy suspension control group, the bacteria of the heavy suspension experiment group A, the bacteria of the heavy suspension experiment group B and the bacteria cells of the heavy suspension experiment group C into a capillary tube respectively, applying alternating voltage by using induction electrospray, 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 AC voltage is set at 200Hz, 10kVp-p and the frequency of the sine wave. The basic parameters of the mass spectrometer were set as: the orbitrap mass spectrometer was an exact Plus mass spectrometer (ThermoFisher Scientific, CA, USA) with acquisition parameters: the radio frequency level of S-Lens is 50%, the capillary transmission temperature is 275 ℃, the average spectrum frame number is 1 frame, the mass resolution is 140000, the mass scanning range is 100-1500, and the AGC threshold value is 1e6.
(3) And reading the mass spectrum of the control group to obtain a control mass spectrum peak. For the detected control mass spectrum peaks, a metabolite dataset of a Human Metabolome Database (HMDB) was used for a search with a search accuracy quality of 10ppm, obtaining an initial metabolite list and constituent atomic information.
FIG. 5A shows a control mass spectrum of E.coli.
FIG. 5B shows the mass spectral peaks of different endogenous compounds detected in E.coli.
As shown in fig. 5A to 5B, the mass spectrum peaks in the mass spectrum of the control group of the escherichia coli metabolites include, for example: 104.0709 (assigned as [ C ] 1 H 9 NO 2 +H] + ) 134.0446 (designated as [ C ] 4 H 7 NO 4 +H] + ) 147.1125 (designated as [ C ] 6 H 14 N2O 2 +H] + ) 188.1756 (designated as [ C ] 9 H 21 N 3 O+H] + ) 203.0522 (designated as [ C ] 6 H 12 O 6 +Na] + ) 308.0908 (designated as [ C ] 10 H 17 N 3 O 6 S+H] + )。
(4) Respectively reading an experiment A group mass spectrogram, an experiment B group mass spectrogram and an experiment C group mass spectrogram according to carbon atom (C) ((C)) 12 C/ 13 C) And nitrogen atom(s) < 14 N/ 15 N) mass displacement of isotopes further assigning mass spectral peaks and calculating 13 C number and 15 n number of using 13 C number and 15 and N screening the initial metabolite list to obtain a final metabolite list.
FIG. 6 shows [ glutathione + H ] in control group bacteria (d), experiment A group bacteria (B), experiment B group bacteria (C), and experiment C group bacteria (a)]+ and based on 12 C-glucose- 14 Mass shift of N-ammonium chloride.
Fig. 7 shows the initial metabolite list corresponding to mass spectrum peaks for m/z = 308.0907.
As shown in fig. 6 and 7, in the absence of a carbon/nitrogen marker (control group bacteria, cell-C12N 14), mass spectrum peak m/z =308.0908 was detected and 6 candidate metabolites were assigned within a mass error of 5ppm, so the probability of placement was 1/6.
By nitrogen atom labeling (experiment B group bacteria, cell-C12N 15), detected m/z =311.0816 mass spectrum peak (as in figure 6C diagram), relative to 308.0908, mass shift 2.9908, can pass 3 × (5363 ×) (cell-C12N 15) 15 N- 14 N) the number of tentative N atoms is 3.
By carbon atom labeling (experiment A group bacteria, cell-C13N 14), detected m/z =318.1240 mass spectrum peak (as in figure 6 b), relative to 308.0908, mass shift 10.0332, can pass 10 × (b) in 308.0908 13 C- 12 C) The number of tentative C atoms is 10.
In the case of labeling by carbon and nitrogen atoms (experimental group C bacteria, cell-C13N 15), a mass spectrum peak at m/z =321.1153 was detected (as in panel a in fig. 6), with a mass shift of 13.0622 relative to 308.0907, which can be according to 10 × (cell-C13N 15) 13 C- 12 C)+3×( 15 N- 14 N) the number of C atoms tentatively was 10, the number of N atoms was 3.
Referring to fig. 7, of the 6 candidate metabolites, only glutathione contained 3 nitrogen atoms and 10 carbon atoms, and therefore the use of isotopic labeling allowed m/z =308.0908 to be the only identification of glutathione. I.e., the final metabolite list corresponding to mass spectral peak 308.0908 comprises glutathione, a metabolite. Thus, the use of isotopic labeling in live cell metabolite mass spectrometry improves the recognition confidence of m/z assignments.
FIG. 8 shows the use in culture media 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) obtained in viable cells ([ glutathione + Na)] + a-d; [ maltose + Na [ ]] + And isomers thereof, e-h; [ lysine + H ]] + And isomers thereof, i-l; [ glucose + Na ]] + And isomers thereof, m-p), in which the labeling is based on 12 C-glucose- 14 Mass shift of N-ammonium chloride.
FIG. 9 shows the use in culture media 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 Obtaining [ glutathione + K ] in viable cells by N-ammonium chloride (d)] + A representative mass spectrum of (1), in which the base is labeled 12 C-glucose- 14 Mass shift of N-ammonium chloride.
As shown in FIGS. 8 and 9, since 2.9908 mass shift peak found in experimental group B bacteria (cell-C12N 15), 10.0332 mass shift peak found in experimental group A bacteria (cell-C13N 14), and 13.0622 mass shift peak found in experimental group C bacteria (cell-C13N 15), mass spectrum peaks m/z =330.0727 (FIGS. 8 a-d) and 340.0468 (FIG. 9) can be assigned to [ glutathione + Na ] respectively] + And [ glutathione + K ]] + 。
FIG. 10 shows three replicate mass spectra of E.coli cells measured by electrospray.
FIG. 11 shows the ion binding type of bacterial metabolites.
As shown in FIGS. 10 and 11, the mass spectrum of the control group of this example detected 3000M/z features, and 223 features were finally confirmed by the subsequent isotope labeling experiment (see FIG. 10), which contained 30% [ M + H ]] + 、22％[M+H-H 2 O] + 、19％[M+Na] + 、18％[M+NH 4 ] + And 12% [ M + K ]] + (as shown in 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, both mass spectra and metabolites showed strong correlation between batches. As shown in fig. 10, the correlation coefficient in the mass spectrum was greater than 0.92, and the correlation coefficient in the metabolite was greater than 0.98. The method shows high reproducibility and robustness in the direct analysis of metabolites of live E.coli cells.
Example 2 identification of oligosaccharides in bacteria
The identification of oligosaccharides in bacteria was performed in the same manner as in example 1. Below is represented by [ C 36 H 62 O 31 +Na] + The confidence probability can be improved using the methods provided by the present disclosure is further illustrated for example purposes.
Fig. 12 shows the initial metabolite list corresponding to mass spectrum peaks for m/z = 1013.3094.
As shown in the mass spectrum h in fig. 8 and fig. 12, in the absence of a carbon/nitrogen marker (control group bacteria, cell-C12N 14), a mass spectrum peak at m/z =1013.3094 was detected, allocating 6 candidate metabolites within a 15ppm mass error, thus the placement probability was 1/6.
As mass spectrum g in fig. 8, mass spectrum peak at m/z =1013.3094 was detected by nitrogen atom labeling (experiment group B bacteria, cell-C12N 15), indicating that the candidate does not contain nitrogen atoms.
As mass spectrum f in FIG. 8, in the case of labeling by carbon atom (experiment group A bacteria, cell-C13N 14), a mass spectrum peak at m/z =1049.4298 was detected, the mass was shifted 36.1204 relative to 1013.3094, and the mass was determined by 36 × (cell-C13N 14) 13 C- 12 C) The number of tentative C atoms is 36.
As mass spectrum e in FIG. 8, in the case of labeling by carbon and nitrogen atoms (experimental group C bacteria, cell-C13N 15), a mass spectrum peak at m/z =1049.4298 was detected, mass shifted 36.1204 relative to 1013.3094, and the peak could be identified by 36 × (C) (cell-C13N 15) 13 C- 12 C)+0×( 15 N- 14 N) the number of C atoms tentatively was 36, no N atoms.
Referring to fig. 12, of the 6 candidate metabolites, 3 compounds (pgg-glucan/a Zhu Tang/maltohexaose) contained 0 nitrogen atoms and 36 carbon atoms, and thus, m/z =1013.3094 corresponding to the candidate metabolite contained 3, increasing the confidence probability to 1/3.
Example 3 search for metabolite batching in bacteria
Following the steps (1) to (3) in the example 1, determining the number of carbon atoms by using a mass spectrogram of the experiment A group bacteria (cell-C13N 14), and screening an initial metabolite list by using the number of the carbon atoms to obtain an experiment A group metabolite list; determining the number of nitrogen atoms by using a mass spectrogram of an experiment group B bacterium (cell-C12N 15), and screening an initial metabolite list by using the number of the nitrogen atoms to obtain an experiment group B metabolite list; determining the number of carbon atoms and the number of nitrogen atoms by using a mass spectrogram of the experimental group C bacteria (cell-C13N 15), and screening an initial metabolite list by combining the number of the carbon atoms and the number of the nitrogen atoms to obtain an experimental group C metabolite list.
FIG. 13 shows a Venn diagram of metabolites identified for experimental group A bacteria (cell, C13N 14), experimental group B bacteria (cell-C12N 15), experimental group C bacteria (cell-C13N 15), and control group bacteria (cell-C12N 14).
FIG. 14 shows confidence probability distribution plots for metabolites that were not isotope filtered and isotope filtered.
FIG. 15 shows a graph comparing the confidence probability of an isotope unfiltered metabolite and the confidence probability of an isotope filtered metabolite.
This example compares the initial metabolite list, the experiment group a metabolite list, the experiment group B metabolite list, and the experiment group C metabolite list to evaluate the global improvement in assignment confidence.
As shown in FIG. 13, in the absence of the carbon/nitrogen marker (cell-C12N 14), 992 features were assigned to candidate features, containing 78% (769/992) of false positive identifications. 350 features were assigned to candidate features by carbon atom labeling (cell-C13N 14), which were confirmed by carbon atom number, and contained 37% (132/350) of false positive identifications. 340 features were assigned candidate features by nitrogen atom labeling (cell-C12N 15), which were confirmed by the number of nitrogen atoms, and contained 50% (172/340) false positives and 29% (99/340) false negative identifications. 223 features were assigned to candidate features by carbon and nitrogen atom labeling (cell-C13N 15) and confirmed with either nitrogen or carbon atoms. With this strategy, 78% of false positive features were identified and rejected, thereby increasing the identification confidence of metabolite assignment.
As shown in fig. 14, the identification results without isotope filtering and with isotope filtering were compared and the metabolites were ranked from high to low in the confidence of the assignments, wherein the round dots represent the confidence probability distribution of the metabolites without isotope filtering and the rectangles represent the confidence probability distribution of the metabolites with isotope filtering. In the case of using carbon and nitrogen atom labeling and filtering, the overall confidence of identification of metabolites is higher than that of identification without using isotope tracking labeling, thereby indicating that the bacterial metabolite analysis method provided by the present disclosure can significantly improve the confidence of identification of metabolites in bacteria.
As shown in fig. 15, histogram statistics were performed on the confidence probabilities of the isotope-unfiltered metabolites and the confidence probabilities of the isotope-filtered metabolites, and in the case of labeling and filtering with carbon and nitrogen atoms, about 60 features were identified as unique candidate features, and 35 features were assigned to 2 candidate features. Mass spectral peaks based on carbon and nitrogen atom labeling and filtering (isotope filtering) with a confidence probability below 0.05 are significantly reduced compared to mass spectral peaks that are not carbon/nitrogen labeled (not isotope filtering). Thus, confidence in metabolite identification based on carbon/nitrogen labeling is generally improved.
According to the embodiment of the disclosure, an analysis method for improving the confidence of identification of a metabolite in a direct injection mass spectrometry bacterium is provided, in which an isotope compound is used as an isotope source for bacterium culture, the mass number offset of the metabolite after the bacterium culture is calculated, and a chemical composition included in the bacterium metabolite is obtained, so as to eliminate false positive identification information for identification of the bacterium metabolite in the direct injection method.
Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.
The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.

Claims (10)

1. A bacterial metabolite analysis method, comprising:
respectively culturing bacteria by using a control group culture medium and an experimental group culture medium to obtain a control group bacteria and an experimental group bacteria, wherein the control group culture medium takes a compound containing a target atom as an intake raw material for the growth of the bacteria; 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 uptake;
respectively carrying out mass spectrum detection on the control group bacteria and the experimental group bacteria to obtain a control group mass spectrogram and an experimental group mass spectrogram;
for each control mass spectral peak in the control group mass spectrogram, matching candidate metabolites corresponding to the control mass spectral peak from a metabolite database to obtain an initial metabolite list;
determining isotopic mass spectrum peaks corresponding to the control mass spectrum peaks from the experimental group mass spectrum;
determining the number of the target atoms contained in the actual metabolite corresponding to the reference mass spectrum peak according to the reference mass spectrum peak, the isotope mass spectrum peak and the target atoms to obtain 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 perform bacterial metabolite analysis according to the final metabolite list.
2. The method of claim 1, wherein said determining from said experimental group mass spectrum a isotopic mass peak corresponding to said control mass spectrum peak comprises:
determining, for each experimental mass spectral peak in the experimental group mass spectral spectrum, a first mass shift between the experimental mass spectral peak and the control mass spectral 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 reference mass spectrum peak.
3. The method of claim 2, wherein the preset condition comprises determining from an atomic weight difference between an isotope of the target atom and the target atom.
4. The method of claim 1, wherein the determining, from the control mass spectral peak, the isotopic mass spectral peak, and the target atom, the number of target atoms contained in the actual metabolite corresponding to the control mass spectral peak comprises:
determining a second mass shift corresponding to the target atom from the reference mass spectral peak and the isotopic mass spectral peak;
and determining the number of the target atoms contained in the actual metabolite corresponding to the reference mass spectrum peak according to the difference between the isotopes 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 using said atomic number to obtain a final metabolite list comprises:
determining, for each candidate metabolite in the initial metabolite list, a number of the 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 included in the candidate metabolite is determined to be the same as the number of atoms;
and obtaining the final metabolite list according to the target metabolites.
6. The method of claim 1, wherein the performing mass spectrometric detection on the control group of bacteria and the experimental group of bacteria respectively to obtain a control group mass spectrogram and an experimental group mass spectrogram comprises:
centrifuging the control group bacteria, removing supernatant, and then re-suspending to obtain re-suspended control group bacteria;
pouring the resuspended control group bacteria into a capillary spray needle, applying voltage to generate electrospray, and performing signal detection by using a mass spectrometer to obtain a control group mass spectrogram;
centrifuging the experimental group bacteria, removing supernatant, and then re-suspending to obtain re-suspended experimental group bacteria;
and (3) pouring the resuspended experimental group bacteria into a capillary spray needle, applying voltage to generate electrospray, and performing signal detection by using the mass spectrometer to obtain the experimental group mass spectrogram.
7. The method of claim 6, further comprising:
before the resuspended control group bacteria or the resuspended experimental group bacteria are poured into a capillary needle, bacterial lysis is performed by using ultrasonic waves or methanol.
8. The method of claim 1, wherein said matching candidate metabolites from a metabolite database corresponding to said control mass spectral peaks comprises:
determining, for each metabolite in the metabolite database, a difference between a peak value of the control mass spectral peak and a molecular weight of the metabolite;
and determining the metabolite as the candidate metabolite corresponding to the reference mass spectrum peak when the absolute value of the difference is less than or equal to a preset precision value.
9. The method of claim 8, wherein the preset precision value is determined from the charge-to-mass ratio of the reference mass peak, the preset precision value being 15ppm in the case that the charge-to-mass ratio of the reference mass peak is equal to or less than 400; and in the case that the charge-to-mass ratio of the reference mass spectrum peak is greater than 400, the preset precision value is 30ppm.
10. The method of claim 1, wherein the target atoms include one or more of carbon atoms, nitrogen atoms, oxygen atoms, hydrogen atoms, chlorine atoms.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006337176A (en) * 2005-06-02 2006-12-14 Eisai R & D Management Co Ltd Determination method of metabolite
CN101155924A (en) * 2005-04-05 2008-04-02 爱尔伯股份公司 Production of highly isotopically labelled, secondary, microbial metabolic products, and corresponding metabolic products
WO2018157067A1 (en) * 2017-02-24 2018-08-30 Iroa Technologies, Llc Iroa metabolomics workflow for improved accuracy, identification and quantitation
CN114577916A (en) * 2020-12-01 2022-06-03 中国科学院大连化学物理研究所 Analysis method of stable isotope labeling metabolic flow based on chip nanoliter electrospray mass spectrum

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101155924A (en) * 2005-04-05 2008-04-02 爱尔伯股份公司 Production of highly isotopically labelled, secondary, microbial metabolic products, and corresponding metabolic products
JP2006337176A (en) * 2005-06-02 2006-12-14 Eisai R & D Management Co Ltd Determination method of metabolite
WO2018157067A1 (en) * 2017-02-24 2018-08-30 Iroa Technologies, Llc Iroa metabolomics workflow for improved accuracy, identification and quantitation
CN110392830A (en) * 2017-02-24 2019-10-29 伊罗亚科技有限公司 For improved precision, the IROA metabolism group workflow of identification and quantification
CN114577916A (en) * 2020-12-01 2022-06-03 中国科学院大连化学物理研究所 Analysis method of stable isotope labeling metabolic flow based on chip nanoliter electrospray mass spectrum

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
刘彦伯;梅占龙;郭珍玉;曾春薇;栾合密;闻博;刘斯奇;: "基于质谱信号的代谢物鉴定:生物信息学的机遇与挑战", 生命的化学, no. 01, 15 February 2017 (2017-02-15) *
欧阳;孙晓红;闫静;褚金芳;闫存玉;: "稳定同位素标记技术在生物分子相对定量分析研究中的应用与进展", 科学通报, no. 27, 30 September 2013 (2013-09-30) *
王庆昭;杨育谛;陈洵;赵学明;: "大肠杆菌代谢物组测定中抽提方法的比较分析", 分析化学, no. 09, 25 September 2006 (2006-09-25) *

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