Quantitative method and system for polyunsaturated lipid carbon-carbon double bond isomer

Abstract

The invention discloses a polyunsaturated lipid carbon-carbon double bond isomer quantification method and system, and relates to the technical field of quantitative analysis, and the method comprises the following steps: collecting a lipid sample, and identifying the diagnosis ion strength of C = C in polyunsaturated lipid; according to a dynamic association algorithm, establishing a relationship between the C = C isomer of the polyunsaturated lipid and the diagnostic ion strength; using a polyunsaturated lipid standard substance to obtain a diagnostic ion strength deviation coefficient caused by a liquid chromatography-mass spectrometry method at different positions C = C; and based on the deviation coefficient and a dynamic association algorithm result, carrying out deconvolution on the diagnosis ion strength to obtain the C = C isomer strength of the polyunsaturated lipid. According to the method, a C = C isomer quantification method based on C = C diagnosis ions is optimized, the strength deviation caused by a derivation method or secondary mass spectrometry fragmentation efficiency is calibrated by associating the strength of a plurality of C = C diagnosis ions and performing deconvolution calculation, and accurate quantification of the polyunsaturated lipid C = C isomer is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of quantitative analysis, and more particularly to a quantitative method and system for polyunsaturated lipid carbon-carbon double bond isomers. Background Art

[0002] Unsaturated lipids are an important class of biomolecules containing carbon-carbon double bonds (C=C). C=C can occur at different positions in the fatty acid chain, resulting in lipids with the same total carbon number and degree of unsaturation having C=C isomers. The position of the double bond directly affects the bioactivity of lipids and is associated with important metabolic functions such as regulating cell membrane fluidity and inflammatory responses. Polyunsaturated lipids are lipids containing two or more C=Cs. Because each double bond has multiple possible positional distributions, polyunsaturated lipids produce complex C=C isomers. The content of each isomer is closely related to pathological mechanisms such as cancer metastasis, cerebral ischemia, and metabolic diseases. Therefore, accurately quantifying lipid C=C isomers has important biological significance.

[0003] Currently, strategies for quantifying only monounsaturated lipid C=C isomers using liquid chromatography-mass spectrometry (LC-MS) methods based on chemical derivatization and dissociation techniques have matured, such as aziridine derivatization, photocatalytic cycloaddition Paternò-Bǜchi reaction, and free radical-induced cleavage. These techniques can produce position-specific diagnostic ions during secondary mass spectrometry fragmentation of C=C, and quantitative analysis of C=C isomers can be performed by analyzing the diagnostic ion intensities.

[0004] However, when using the same strategy to quantify polyunsaturated lipid C=C isomers, some C=C residues on different fatty acid chains in lipids containing multiple fatty acid chains (such as phospholipids and glycerides) produce identical diagnostic ions, which significantly interferes with the quantification of polyunsaturated lipid C=C isomers and prevents accurate quantitative results. Furthermore, different double bonds in polyunsaturated lipids may have different derivatization or fragmentation efficiencies, further complicating quantitative analysis. Consequently, an effective quantification strategy for polyunsaturated lipid C=C isomers is currently lacking.

[0005] Therefore, how to propose a quantitative method and system for carbon-carbon double bond isomers of polyunsaturated lipids and effectively perform accurate quantitative analysis of polyunsaturated lipid C=C isomers is an urgent problem that needs to be solved by those skilled in the art. Summary of the Invention

[0006] In light of this, the present invention provides a method and system for quantifying carbon-carbon double bond isomers of polyunsaturated lipids. By leveraging data processing algorithms, this method accurately quantifies C=C isomers of polyunsaturated lipids, providing a reliable approach for lipidomics research. To achieve this objective, the present invention employs the following technical solutions:

[0007] A method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids, comprising:

[0008] Collect lipid samples and identify the diagnostic ion intensity of C=C in polyunsaturated lipids;

[0009] The relationship between the C=C isomers of polyunsaturated lipids and the diagnostic ion intensities was established based on the dynamic correlation algorithm;

[0010] Using polyunsaturated lipid standards, the diagnostic ion intensity deviation coefficients caused by LC-MS were obtained for C=C at different positions;

[0011] The diagnostic ion intensities were deconvoluted based on the deviation coefficient and the results of the dynamic correlation algorithm to obtain the C=C isomer intensities of polyunsaturated lipids.

[0012] Optionally, the identifying the diagnostic ion intensity of C=C in the polyunsaturated lipids includes: obtaining diagnostic ion intensity data of C=C in the lipid sample by liquid chromatography-mass spectrometry based on chemical derivatization or dissociation technology, and identifying the diagnostic ion intensity of each C=C of the polyunsaturated lipids.

[0013] Optionally, the dynamic association algorithm includes:

[0014] (nx)>>(n-1, n-2,..., n-(x-1), nx);

[0015] (n-(x-1))>>(n-1,...,n-(x-1))+(n-1,...,nx);

[0016] (n-(x-2))>>(n-1,…,n-(x-2))+…+(n-1,…,nx);

[0017] …

[0018] (n-3)>>(n-1, n-2, n-3)+……+(n-1,……,nx);

[0019] (n-2)>>(n-1, n-2)+……+(n-1,……,nx);

[0020] (n-1)>>(n-1)+……+(n-1,……,nx);

[0021] Among them, (n-1), (n-2), ..., (nx) represent the C=C diagnostic ions at the specified positions; (n-1), (n-1, n-2), ..., (n-1, n-2, ..., n-(x-1), nx) represent the double bond isomers at the specified positions.

[0022] Optionally, the dynamic association algorithm further includes:

[0023] If the lipid double bond position combination is determined to be (n-1, n-(x-2), n-(x-1), nx) in the analysis results, the presence of C=C isomers (n-(x-2), n-(x-1), nx), (n-(x-1), nx), and (nx) will be dynamically identified;

[0024] Through the association algorithm, multiple C=C isomers are associated with each double bond intensity actually measured. The diagnostic ion intensity of (nx) comes only from (n-1, n-(x-2), n-(x-1), nx) and is only associated with it; (n-(x-1)) is simultaneously associated with (n-1, n-(x-2), n-(x-1)) and (n-1, n-(x-2), n-(x-1), nx), and so on. (n-(x-2)) is associated with three C=C isomers, and (n-1) is associated with all four C=C isomers.

[0025] Optionally, the use of polyunsaturated lipid standards to obtain diagnostic ion intensity deviation coefficients of C=C at different positions caused by liquid chromatography-mass spectrometry includes: using multiple polyunsaturated lipid standards to obtain diagnostic ion intensity deviation coefficients of double bonds at different positions caused by chemical derivatization or dissociation technology through mass spectrometry analysis.

[0026] Optionally, the deconvolution of the diagnostic ion intensity based on the deviation coefficient and the dynamic correlation algorithm result to obtain the C=C isomer intensity of the polyunsaturated lipid includes:

[0027] (n-1, n-2,..., n-(x-1), nx)=(nx);

[0028] (n-1,...,n-(x-1))=(n-(x-1))-(k2 / k1)×(nx);

[0029] (n-1,...,n-(x-2))=(n-(x-2))-(k3 / k2)×(n-(x-1));

[0030] …

[0031] (n-1, n-2, n-3)=(n-3)-(k(x-2) / k(x-3))×(n-4);

[0032] (n-1, n-2)=(n-2)-(k(x-1) / k(x-2))×(n-3);

[0033] (n-1)=(n-1)-(kx / k(x-1))×(n-2);

[0034] Among them, (n-1), (n-2), ..., (nx) represent the C=C diagnostic ions at the specified positions; (n-1), (n-1, n-2), ..., (n-1, n-2, ..., n-(x-1), nx) represent the double bond isomers at the specified positions, and k1, k2, ..., k(x-2), k(x-1), kx represent the deviation coefficients of C=C.

[0035] Optionally, deconvolution of the diagnostic ion intensity based on the deviation coefficient and the dynamic correlation algorithm result further includes:

[0036] S1: (nx) is only associated with (n-1, n-(x-2), n-(x-1), nx), so the intensity of (n-1, n-(x-2), n-(x-1), nx) is referred to by the intensity of (nx), and the intensity of (n-1, n-(x-2), n-(x-1), nx) is calculated, that is, (n-1, n-(x-2), n-(x-1), nx) = (nx);

[0037] S2: (n-(x-1)) is associated with (n-1, n-(x-2), n-(x-1), nx) and (n-1, n-(x-2), n-(x-1)), so use (n-(x-1)) minus the intensity represented by (n-1, n-(x-2), n-(x-1), nx) in (n-(x-1)) to calculate the intensity of (n-1, n-(x-2), n-(x-1));

[0038] A deviation coefficient is introduced to represent the deviation of C=C at different positions due to the analysis method, and k1, ..., kx are used to represent the deviation coefficients of C=C respectively. The intensity represented by (n-1, n-(x-2), n-(x-1), nx) in (n-(x-1)) is converted from (nx) to: (k(x-2) / k1)×(nx), thereby calculating the intensity of (n-1, n-(x-2), n-(x-1)), that is, (n-1, n-(x-2), n-(x-1))=(n-(x-1))-(k(x-2) / k1)×(nx);

[0039] S3: (n-(x-2)) is associated with (n-1, n-(x-2), n-(x-1), nx), (n-1, n-(x-2), n-(x-1)) and (n-1, n-(x-2)), so the intensity of (n-1, n-(x-2)) is calculated by subtracting the intensities represented by (n-1, n-(x-2), n-(x-1), nx) and (n-1, n-(x-2), n-(x-1)) in (n-(x-2)) from (n-(x-2));

[0040] Since (n-1, n-(x-2), n-(x-1), nx) and (n-1, n-(x-2), n-(x-1)) together constitute the intensity of (n-(x-1)), we convert them into the intensity of (n-(x-2)) represented by the two, that is, (k(x-1) / k(x-2))×(n-(x-1)), and thus calculate (n-1, n-(x-2))=(n-(x-2))–(k(x-1) / k(x-2))×(n-(x-1));

[0041] S4: The steps are the same as S2 and S3. The intensity formula of (n-1) is calculated as (n-1) = (n-1) – (kx / k(x-1)) × (n-(x-2)).

[0042] Optionally, a polyunsaturated lipid carbon-carbon double bond isomer quantification system comprising:

[0043] Acquisition module: used to collect lipid samples and identify the diagnostic ion intensity of C=C in polyunsaturated lipids;

[0044] Dynamic correlation module: used to establish the relationship between the C=C isomers of polyunsaturated lipids and the diagnostic ion intensity based on the dynamic correlation algorithm;

[0045] Deviation coefficient acquisition module: used to obtain the diagnostic ion intensity deviation coefficient of C=C at different positions caused by liquid chromatography-mass spectrometry using polyunsaturated lipid standards;

[0046] Deconvolution module: used to deconvolve the diagnostic ion intensity based on the deviation coefficient and the results of the dynamic correlation algorithm to obtain the C=C isomer intensity of polyunsaturated lipids.

[0047] It can be seen from the above technical solution that, compared with the prior art, the present invention discloses a method and system for quantifying carbon-carbon double bond isomers of polyunsaturated lipids, which has the following beneficial effects:

[0048] The present invention proposes a method for quantifying carbon-carbon double bond isomers in polyunsaturated lipids, comprising: collecting a lipid sample and identifying the diagnostic ion intensity of C=C in the polyunsaturated lipid; establishing a relationship between the C=C isomers of the polyunsaturated lipid and the diagnostic ion intensity based on a dynamic correlation algorithm; using a polyunsaturated lipid standard to obtain the diagnostic ion intensity deviation coefficient caused by liquid chromatography-mass spectrometry for C=C at different positions; and deconvolving the diagnostic ion intensity based on the deviation coefficient and the results of the dynamic correlation algorithm to obtain the C=C isomer intensity of the polyunsaturated lipid. The present invention optimizes the current C=C isomer quantification method based on the C=C diagnostic ion at the algorithm level. By dynamically correlating the intensities of multiple C=C diagnostic ions, the actual intensities of different C=C isomers are deconvoluted and calculated. The deviation of the C=C diagnostic ion intensity at different positions caused by the derivatization method or secondary mass spectrometry fragmentation efficiency is then calibrated based on the deviation coefficient, thereby accurately quantifying the C=C isomers of the polyunsaturated lipids. From the perspective of data processing algorithms, the present invention proposes a method for the precise quantification of polyunsaturated lipid C=C isomers based on diagnostic ion association and deconvolution algorithms. This method is compatible with current technologies for the quantification of C=C isomers based on C=C diagnostic ions, enabling accurate quantification of polyunsaturated lipid C=C isomers and providing reliable technical support for lipidomics research. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0050] Figure 1 This is a schematic flow chart of a method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids provided by the present invention.

[0051] Figure 2 This is a schematic diagram of the principle of a method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids provided by the present invention.

[0052] Figure 3 This is a flow chart of the deconvolution algorithm provided by the present invention. DETAILED DESCRIPTION

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0054] The present invention discloses a method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids. Figure 1 Shown, including:

[0055] Collect lipid samples and identify the diagnostic ion intensity of C=C in polyunsaturated lipids;

[0056] The relationship between the C=C isomers of polyunsaturated lipids and the diagnostic ion intensities was established based on the dynamic correlation algorithm;

[0057] Using polyunsaturated lipid standards, the diagnostic ion intensity deviation coefficients caused by LC-MS were obtained for C=C at different positions;

[0058] The diagnostic ion intensities were deconvoluted based on the deviation coefficient and the results of the dynamic correlation algorithm to obtain the C=C isomer intensities of polyunsaturated lipids.

[0059] Furthermore, the identification of diagnostic ion intensities of C=C in polyunsaturated lipids includes: obtaining diagnostic ion intensity data of C=C in lipid samples using a liquid chromatography-mass spectrometry method based on chemical derivatization or dissociation technology, and identifying the diagnostic ion intensity of each C=C of the polyunsaturated lipids.

[0060] Furthermore, the dynamic association algorithm includes:

[0061] (nx)>>(n-1, n-2,..., n-(x-1), nx);

[0062] (n-(x-1))>>(n-1,...,n-(x-1))+(n-1,...,nx);

[0063] (n-(x-2))>>(n-1,…,n-(x-2))+…+(n-1,…,nx);

[0064] …

[0065] (n-3)>>(n-1, n-2, n-3)+……+(n-1,……,nx);

[0066] (n-2)>>(n-1, n-2)+……+(n-1,……,nx);

[0067] (n-1)>>(n-1)+……+(n-1,……,nx);

[0068] Among them, (n-1), (n-2), ..., (nx) represent the C=C diagnostic ions at the specified positions; (n-1), (n-1, n-2), ..., (n-1, n-2, ..., n-(x-1), nx) represent the double bond isomers at the specified positions.

[0069] Furthermore, the dynamic association algorithm also includes:

[0070] If the lipid double bond position combination is determined to be (n-1, n-(x-2), n-(x-1), nx) in the analysis results, the presence of C=C isomers (n-(x-2), n-(x-1), nx), (n-(x-1), nx), and (nx) will be dynamically identified;

[0071] Through the association algorithm, multiple C=C isomers are associated with each double bond intensity actually measured. The diagnostic ion intensity of (nx) comes only from (n-1, n-(x-2), n-(x-1), nx) and is only associated with it; (n-(x-1)) is simultaneously associated with (n-1, n-(x-2), n-(x-1)) and (n-1, n-(x-2), n-(x-1), nx), and so on. (n-(x-2)) is associated with three C=C isomers, and (n-1) is associated with all four C=C isomers.

[0072] Furthermore, the use of polyunsaturated lipid standards to obtain diagnostic ion intensity deviation coefficients caused by liquid chromatography-mass spectrometry for C=C at different positions includes: using multiple polyunsaturated lipid standards to obtain diagnostic ion intensity deviation coefficients caused by chemical derivatization or dissociation technology for double bonds at different positions through mass spectrometry analysis.

[0073] Furthermore, the diagnostic ion intensity is deconvoluted based on the deviation coefficient and the dynamic correlation algorithm result to obtain the C=C isomer intensity of the polyunsaturated lipid, including:

[0074] (n-1, n-2,..., n-(x-1), nx)=(nx);

[0075] (n-1,...,n-(x-1))=(n-(x-1))-(k2 / k1)×(nx);

[0076] (n-1,...,n-(x-2))=(n-(x-2))-(k3 / k2)×(n-(x-1));

[0077] …

[0078] (n-1, n-2, n-3)=(n-3)-(k(x-2) / k(x-3))×(n-4);

[0079] (n-1, n-2)=(n-2)-(k(x-1) / k(x-2))×(n-3);

[0080] (n-1)=(n-1)-(kx / k(x-1))×(n-2);

[0081] Among them, (n-1), (n-2), ..., (nx) represent the C=C diagnostic ions at the specified positions; (n-1), (n-1, n-2), ..., (n-1, n-2, ..., n-(x-1), nx) represent the double bond isomers at the specified positions, and k1, k2, ..., k(x-2), k(x-1), kx represent the deviation coefficients of C=C.

[0082] Furthermore, the deconvolution of the diagnostic ion intensity based on the deviation coefficient and the dynamic correlation algorithm result further includes:

[0083] S1: (nx) is only associated with (n-1, n-(x-2), n-(x-1), nx), so the intensity of (n-1, n-(x-2), n-(x-1), nx) is referred to by the intensity of (nx), and the intensity of (n-1, n-(x-2), n-(x-1), nx) is calculated, that is, (n-1, n-(x-2), n-(x-1), nx) = (nx);

[0084] S2: (n-(x-1)) is associated with (n-1, n-(x-2), n-(x-1), nx) and (n-1, n-(x-2), n-(x-1)), so use (n-(x-1)) minus the intensity represented by (n-1, n-(x-2), n-(x-1), nx) in (n-(x-1)) to calculate the intensity of (n-1, n-(x-2), n-(x-1));

[0085] A deviation coefficient is introduced to represent the deviation of C=C at different positions due to the analysis method, and k1, ..., kx are used to represent the deviation coefficients of C=C respectively. The intensity represented by (n-1, n-(x-2), n-(x-1), nx) in (n-(x-1)) is converted from (nx) to: (k(x-2) / k1)×(nx), thereby calculating the intensity of (n-1, n-(x-2), n-(x-1)), that is, (n-1, n-(x-2), n-(x-1))=(n-(x-1))-(k(x-2) / k1)×(nx);

[0086] S3: (n-(x-2)) is associated with (n-1, n-(x-2), n-(x-1), nx), (n-1, n-(x-2), n-(x-1)) and (n-1, n-(x-2)), so the intensity of (n-1, n-(x-2)) is calculated by subtracting the intensities represented by (n-1, n-(x-2), n-(x-1), nx) and (n-1, n-(x-2), n-(x-1)) in (n-(x-2)) from (n-(x-2));

[0087] Since (n-1, n-(x-2), n-(x-1), nx) and (n-1, n-(x-2), n-(x-1)) together constitute the intensity of (n-(x-1)), we convert them into the intensity of (n-(x-2)) represented by the two, that is, (k(x-1) / k(x-2))×(n-(x-1)), and thus calculate (n-1, n-(x-2))=(n-(x-2))–(k(x-1) / k(x-2))×(n-(x-1));

[0088] S4: The steps are the same as S2 and S3. The intensity formula of (n-1) is calculated as (n-1) = (n-1) – (kx / k(x-1)) × (n-(x-2)).

[0089] In a specific embodiment, a polyunsaturated lipid carbon-carbon double bond isomer quantification system comprises:

[0090] Acquisition module: used to collect lipid samples and identify the diagnostic ion intensity of C=C in polyunsaturated lipids;

[0091] Dynamic correlation module: used to establish the relationship between the C=C isomers of polyunsaturated lipids and the diagnostic ion intensity based on the dynamic correlation algorithm;

[0092] Deviation coefficient acquisition module: used to obtain the diagnostic ion intensity deviation coefficient of C=C at different positions caused by liquid chromatography-mass spectrometry using polyunsaturated lipid standards;

[0093] Deconvolution module: used to deconvolve the diagnostic ion intensity based on the deviation coefficient and the results of the dynamic correlation algorithm to obtain the C=C isomer intensity of polyunsaturated lipids.

[0094] In a specific embodiment, a method for quantifying carbon-carbon double bond isomers in polyunsaturated lipids comprises the following steps: first, using a liquid chromatography-mass spectrometry method based on chemical derivatization or dissociation technology to obtain C=C diagnostic ion intensity data in a lipid sample, identifying the diagnostic ion intensity of each C=C of the polyunsaturated lipid, then establishing a relationship between the C=C isomer and the double bond diagnostic ion intensity using a dynamic correlation algorithm, and deconvoluting the diagnostic ion intensity to calculate the C=C isomer intensity. To increase the quantitative accuracy of the algorithm, multiple polyunsaturated lipid standards are used before analysis, and mass spectrometry analysis is performed to obtain the diagnostic ion intensity deviation coefficient caused by the chemical derivatization or dissociation technology at different double bond positions, which is used to assist in the deconvolution calculation of the C=C isomer.

[0095] In a specific embodiment, the dynamic association algorithm includes:

[0096] (n-15)>>(n-6, n-9, n-12, n-15);

[0097] (n-12)>>(n-6, n-9, n-12)+(n-6, n-9, n-12, n-15);

[0098] (n-9)>>(n-6, n-9)+(n-6, n-9, n-12)+(n-6, n-9, n-12, n-15);

[0099] (n-6)>>(n-6)+(n-6,n-9)+(n-6,n-9,n-12)+(n-6,n-9,n-12,n-15).

[0100] Among them, based on the C=C position information and the unsaturation distribution in the fatty acid chain determined by mass spectrometry analysis, the C=C isomer information and its correlation with the intensity of each C=C diagnostic ion are dynamically identified.

[0101] Specifically, when analyzing lipids with multiple fatty acid chains, current double bond position identification technology identifies four consecutive double bonds (n-6, n-9, n-12, n-15). Since some of the double bond diagnostic ions of the two fatty acid chains are the same, it is assumed that three double bonds (n-6, n-9, n-12), two double bonds (n-6, n-9), and a single double bond (n-6) are all present. These four double bond forms will combine to form different C=C isomers. In current research and applications, the content of these four double bond forms is used as the final C=C isomer quantification target. Therefore, the C=C isomer quantification referred to in the embodiments of the present invention also refers to the quantification of the relative content of different double bond forms.

[0102] For example, for a glyceride containing four double bonds, if the analysis results show the corresponding positions of the four double bonds of the lipid as (n-6, n-9, n-12, n-15), the system will dynamically identify the presence of four C=C isomers: (n-6, n-9, n-12), (n-6, n-9), and (n-6). These four C=C isomers are then associated with each of the actual double bond intensities measured using an association algorithm. For example, the diagnostic ion intensity for (n-15) is derived solely from (n-6, n-9, n-12, n-15) and is therefore associated only with it. (n-12) is associated with both (n-6, n-9, n-12) and (n-6, n-9, n-12, n-15), (n-9) is associated with all three C=C isomers, and (n-6) is associated with all four C=C isomers. Therefore, a dynamic correlation algorithm was used to establish a relationship between the C=C diagnostic ion intensity and the C=C isomers. For ease of distinction, in the examples of the present invention, italics represent C=C diagnostic ions at designated positions, such as (n-6), while non-italics represent double bond isomers at designated positions, such as (n-6).

[0103] In a specific embodiment, the deconvolution algorithm specifically includes:

[0104] The dynamic correlation algorithm has identified the correlation between the C=C diagnostic ion intensity and the C=C isomer. Therefore, by deconvolving the C=C diagnostic ion intensity, the accurate C=C isomer intensity can be calculated, such as Figure 3 As shown, the specific steps of the deconvolution method designed in this embodiment are as follows:

[0105] S1: Since (n-15) is only associated with (n-6, n-9, n-12, n-15), the intensity of (n-6, n-9, n-12, n-15) can be referred to by the intensity of (n-15), thus calculating the intensity of (n-6, n-9, n-12, n-15), that is, (n-6, n-9, n-12, n-15) = (n-15);

[0106] S2: (n-12) is associated with (n-6, n-9, n-12, n-15) and (n-6, n-9, n-12). Therefore, the intensity of (n-6, n-9, n-12) can be calculated by subtracting the intensity represented by (n-6, n-9, n-12, n-15) in (n-12) from (n-12). In 1., (n-15) has been used to refer to the intensity of (n-6, n-9, n-12, n-15). Therefore, the intensity of (n-6, n-9, n-12, n-15) can be calculated by converting (n-15) to the intensity represented by (n-12) to calculate the intensity of (n-6, n-9, n-12, n-15). Since the diagnostic ion intensities of C=C at different positions may vary due to the efficiency of the derivatization reaction or fragmentation, a coefficient of variation is introduced here to represent the deviation of C=C at different positions due to the analytical method. k1-k4 represent the coefficients of variation of the four C=Cs, respectively. The intensities represented by (n-6, n-9, n-12, n-15) in (n-12) can be calculated by converting (n-15) to (k2 / k1)×(n-15). Thus, the intensities of (n-6, n-9, n-12) can be calculated, i.e., (n-6, n-9, n-12)=(n-12)-(k2 / k1)×(n-15);

[0107] S3: (n-9) is associated with (n-6, n-9, n-12, n-15), (n-6, n-9, n-12), and (n-6, n-9). Therefore, the intensity of (n-6, n-9) can be calculated by subtracting the intensities represented by (n-6, n-9, n-12, n-15) and (n-6, n-9, n-12) in (n-9) from (n-9). Since (n-6, n-9, n-12, n-15) and (n-6, n-9, n-12) together make up the intensity of (n-12), we convert it to the intensity of (n-9) represented by the two, that is, (k3 / k2) × (n-12). Thus, (n-6, n-9) can be directly calculated, that is, (n-6, n-9) = (n-9) – (k3 / k2) × (n-12);

[0108] The same steps as S2 and S3 can be used to directly calculate the strength of (n-6): (n-6) = (n-6) – (k4 / k3) × (n-9).

[0109] In a specific embodiment, a schematic diagram of the principle of a method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids is shown as follows: Figure 2 As shown, for any polyunsaturated lipid, the C=C isomer intensity can be calculated by the method of the present invention. The detailed calculation process and formula are shown in the figure.

[0110] In a specific embodiment, the actual effect of the lipid C=C isomer intensity calculated using this embodiment was compared with the direct use of the sum of all double bond diagnostic ion intensities as the quantitative value. The results are shown in Table 1. Directly using the sum of the diagnostic ion intensities as the quantitative value will result in the C=C isomer of the same lipid, such as the four C=C isomers of TG (54:5), always having the highest intensity value for the isomer with the largest number of double bonds. The intensity values ​​of each C=C isomer decrease as the number of double bonds decreases. This is because different C=C isomers in current C=C position detection technologies have the same diagnostic ion. Therefore, directly counting the diagnostic ion intensity as the C=C isomer will produce significant errors. After calculation using the method in this embodiment, the intensity value of each isomer is no longer related to the number of double bonds, but more accurately reflects the true C=C isomer intensity. In addition, the calculated intensity value is lower than 100 or even less than 0 in the data. This is due to the fluctuation of the mass spectrometry acquisition signal. The C=C isomer with an intensity below the mass spectrometry effective signal threshold is not actually present in the sample, but is a false positive result caused by the same diagnostic ion. Therefore, the polyunsaturated lipid quantification method proposed in this example can accurately quantify the lipid C=C isomer intensity and can assist in eliminating false positive results caused by current technologies for detecting C=C positions.

[0111] Table 1 Comparison of the calculated intensity and the sum of the diagnostic ion intensities of the method under different lipid C=C isomers

[0112] Lipid name C=C isomer Diagnostic ion intensity summation This method calculates the intensity TG (54:5) (n-6) 6066 137 TG (54:5) (n-6, n-9) 11995 3872 TG (54:5) (n-6, n-9, n-12) 14052 1775 TG (54:5) (n-6, n-9, n-12, n-15) 14334 282 TG (56:4) (n-6) 4651 59 TG (56:4) (n-6, n-9) 9243 -345 TG (56:4) (n-6, n-9, n-12) 14180 4196 TG (56:4) (n-6, n-9, n-12, n-15) 14921 741 TG (56:5) (n-6) 6270 1105 TG (56:5) (n-6, n-9) 11435 1191 TG (56:5) (n-6, n-9, n-12) 15409 2934 TG (56:5) (n-6, n-9, n-12, n-15) 16449 1040

[0113] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0114] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids, characterized in that: include: Collect lipid samples and identify the diagnostic ion intensity of C=C in polyunsaturated lipids; The relationship between the C=C isomers of polyunsaturated lipids and the diagnostic ion intensities was established based on the dynamic correlation algorithm. Using polyunsaturated lipid standards, the diagnostic ion intensity deviation coefficients caused by LC-MS were obtained for C=C at different positions; The diagnostic ion intensities were deconvoluted based on the deviation coefficient and the results of the dynamic correlation algorithm to obtain the C=C isomer intensities of polyunsaturated lipids.

2. A method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids according to claim 1, characterized in that: The method of identifying the diagnostic ion intensity of C=C in polyunsaturated lipids includes obtaining diagnostic ion intensity data of C=C in lipid samples by liquid chromatography-mass spectrometry based on chemical derivatization or dissociation technology, and identifying the diagnostic ion intensity of each C=C in polyunsaturated lipids.

3. A method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids according to claim 1, characterized in that: The dynamic association algorithm includes: (nx)>>(n-1, n-2,..., n-(x-1), nx); (n-(x-1))>>(n-1,...,n-(x-1))+(n-1,...,nx); (n-(x-2))>>(n-1,…,n-(x-2))+…+(n-1,…,nx); …… (n-3)>>(n-1, n-2, n-3)+……+(n-1,……,nx); (n-2)>>(n-1, n-2)+……+(n-1,……,nx); (n-1)>>(n-1)+……+(n-1,……,nx); Among them, (n-1), (n-2), ..., (nx) represent the C=C diagnostic ions at the specified positions; (n-1), (n-1, n-2), ..., (n-1, n-2, ..., n-(x-1), nx) represent the double bond isomers at the specified positions.

4. A method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids according to claim 3, characterized in that: The dynamic association algorithm also includes: If the lipid double bond position combination is determined to be (n-1, n-(x-2), n-(x-1), nx) in the analysis results, the presence of C=C isomers (n-(x-2), n-(x-1), nx), (n-(x-1), nx), and (nx) will be dynamically identified; Through the association algorithm, multiple C=C isomers are associated with each double bond intensity actually measured. The diagnostic ion intensity of (nx) comes only from (n-1, n-(x-2), n-(x-1), nx) and is only associated with it; (n-(x-1)) is simultaneously associated with (n-1, n-(x-2), n-(x-1)) and (n-1, n-(x-2), n-(x-1), nx), and so on. (n-(x-2)) is associated with three C=C isomers, and (n-1) is associated with all four C=C isomers.

5. A method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids according to claim 1, characterized in that: The method of using polyunsaturated lipid standards to obtain diagnostic ion intensity deviation coefficients caused by liquid chromatography-mass spectrometry for C=C at different positions includes: using multiple polyunsaturated lipid standards to obtain diagnostic ion intensity deviation coefficients caused by chemical derivatization or dissociation technology for double bonds at different positions through mass spectrometry analysis.

6. A method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids according to claim 1, characterized in that: Deconvolution of the diagnostic ion intensity based on the deviation coefficient and the dynamic correlation algorithm result to obtain the C=C isomer intensity of the polyunsaturated lipid includes: (n-1, n-2,..., n-(x-1), nx)=(nx); (n-1,...,n-(x-1))=(n-(x-1))-(k2 / k1)×(nx); (n-1,...,n-(x-2))=(n-(x-2))-(k3 / k2)×(n-(x-1)); …… (n-1, n-2, n-3)=(n-3)-(k(x-2) / k(x-3))×(n-4); (n-1, n-2)=(n-2)-(k(x-1) / k(x-2))×(n-3); (n-1)=(n-1)-(kx / k(x-1))×(n-2); Among them, (n-1), (n-2), ..., (nx) represent the C=C diagnostic ions at the specified positions; (n-1), (n-1, n-2), ..., (n-1, n-2, ..., n-(x-1), nx) represent the double bond isomers at the specified positions, and k1, k2, ..., k(x-2), k(x-1), kx represent the deviation coefficients of C=C.

7. A method for quantifying carbon-carbon double bond isomers of polyunsaturated lipids according to claim 6, characterized in that: Deconvolution of the diagnostic ion intensity based on the deviation coefficient and the dynamic correlation algorithm result further includes: S1: (nx) is only associated with (n-1, n-(x-2), n-(x-1), nx), so the intensity of (n-1, n-(x-2), n-(x-1), nx) is referred to by the intensity of (nx), and the intensity of (n-1, n-(x-2), n-(x-1), nx) is calculated, that is, (n-1, n-(x-2), n-(x-1), nx) = (nx); S2: (n-(x-1)) is associated with (n-1, n-(x-2), n-(x-1), nx) and (n-1, n-(x-2), n-(x-1)), so use (n-(x-1)) minus the intensity represented by (n-1, n-(x-2), n-(x-1), nx) in (n-(x-1)) to calculate the intensity of (n-1, n-(x-2), n-(x-1)); A deviation coefficient is introduced to represent the deviation of C=C at different positions due to the analysis method, and k1, ..., kx are used to represent the deviation coefficients of C=C respectively. The intensity represented by (n-1, n-(x-2), n-(x-1), nx) in (n-(x-1)) is converted from (nx) to: (k(x-2) / k1)×(nx), thereby calculating the intensity of (n-1, n-(x-2), n-(x-1)), that is, (n-1, n-(x-2), n-(x-1))=(n-(x-1))-(k(x-2) / k1)×(nx); S3: (n-(x-2)) is associated with (n-1, n-(x-2), n-(x-1), nx), (n-1, n-(x-2), n-(x-1)) and (n-1, n-(x-2)), so the intensity of (n-1, n-(x-2)) is calculated by subtracting the intensities represented by (n-1, n-(x-2), n-(x-1), nx) and (n-1, n-(x-2), n-(x-1)) in (n-(x-2)) from (n-(x-2)); Since (n-1, n-(x-2), n-(x-1), nx) and (n-1, n-(x-2), n-(x-1)) together constitute the intensity of (n-(x-1)), we convert them into the intensity of (n-(x-2)) represented by the two, that is, (k(x-1) / k(x-2))×(n-(x-1)), and thus calculate (n-1, n-(x-2))=(n-(x-2))–(k(x-1) / k(x-2))×(n-(x-1)); S4: The steps are the same as S2 and S3. The intensity formula of (n-1) is calculated as (n-1) = (n-1) – (kx / k(x-1)) × (n-(x-2)).

8. A polyunsaturated lipid carbon-carbon double bond isomer quantification system, characterized in that: include: Acquisition module: used to collect lipid samples and identify the diagnostic ion intensity of C=C in polyunsaturated lipids; Dynamic correlation module: used to establish the relationship between the C=C isomers of polyunsaturated lipids and the diagnostic ion intensity based on the dynamic correlation algorithm; Deviation coefficient acquisition module: used to obtain the diagnostic ion intensity deviation coefficient of C=C at different positions caused by liquid chromatography-mass spectrometry using polyunsaturated lipid standards; Deconvolution module: used to deconvolve the diagnostic ion intensity based on the deviation coefficient and the results of the dynamic correlation algorithm to obtain the C=C isomer intensity of polyunsaturated lipids.

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