CN114544981A - Marker for determining PFOS (Perfluorooctane sulfonate) exposure obtained based on lipidomics technology and application thereof - Google Patents
Marker for determining PFOS (Perfluorooctane sulfonate) exposure obtained based on lipidomics technology and application thereof Download PDFInfo
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Abstract
The invention discloses a method for obtaining a marker for judging PFOS exposure based on lipidomics technology. The invention analyzes the fingerprint of lipidomics of serum of experimental animals under the conditions of PFOS exposure and normal control based on UPLC-HRMS lipidomics technology to obtain 26 differential lipid compounds which can be used as a biomarker for judging whether an organism has PFOS exposure. The 26 lipid compounds include 11 LPC classes, 3 LPE classes, 2 NAE classes, 9 PC classes and 1 PE class lipid compounds. By detecting the 26 different lipid compounds in the serum, whether the organism has PFOS exposure or not can be judged by utilizing the lipidomics technology under the condition of not utilizing PFOS standards, the PFOS exposure can be conveniently and quickly judged, and further harm to the environment caused by the use of the PFOS standards is prevented.
Description
Technical Field
The invention belongs to the technical field of analysis, and particularly relates to a marker for determining PFOS (Perfluorooctane sulfonate) exposure obtained based on lipidomics technology and application thereof.
Background
The molecular formula of the perfluorooctane sulfonate (PFOS) is C8F17SO3It is a perfluoro compound of octanesulfonic acid, and perfluorooctanesulfonic acid is one of the most widely used compounds among perfluoro compounds. Since PFOS has a low molecular polarizability and C-F bonds have a short bond length and a high bond energy, PFOS has excellent thermal stability, chemical stability and surfaceActive, and widely used in various industrial products such as cosmetics, carpets, leather, metal plating, wax, semiconductors, pesticides, paper, textile and fire fighting foams, etc. PFOS was produced by 3M company since the 40 th 19 th century, and with the progress of synthesis processes and technologies, the production amount of PFOS in the world has increased greatly, and in 1970 to 2002, the historical total production amount of PFOS in the world has reached 9.6 ten thousand tons, and the discharge amount into wastewater has been about 2700 tons. But PFOS is difficult to degrade under natural conditions due to its stability, has bio-enrichment and long-distance migration properties, and is found even in antarctic penguins and seals. Thus in 2009 PFOS and its salts were classified as novel persistent organic pollutants in the "stockholm convention".
It has been shown that PFOS may cause toxicity to human body and organ damage, including various toxicities such as hepatotoxicity, nephrotoxicity, neurotoxicity and cardiovascular toxicity, and its toxic effects are aggravated with the age of human body due to the continuous accumulation of PFOS in the body. Therefore, the PFOS exposure is discovered in time, and the toxicity caused by PFOS accumulation can be reduced to the maximum extent.
Lipidomics is a discipline for the overall analysis of lipid pathways and networks in biological systems, lipidomics is all lipids in a cell, tissue or organism, is a branch of the metabolome, and is more focused on the analysis of lipid compounds than metabolomics.
Disclosure of Invention
The technical problem to be solved by the invention is how to obtain a marker for PFOS exposure in an organism and/or how to detect PFOS exposure in an organism and/or how to predict the toxicity mechanism of PFOS to an organism.
In order to solve the technical problems, the invention firstly provides application of 26 lipid compounds as biomarkers in preparing products for predicting whether organisms are in a perfluorooctane sulfonate toxic environment.
The 26 lipid compounds may include 11 Lysophosphatidylcholine (LPC) lipid compounds, 3 Lysophosphatidylethanolamine (LPE) lipid compounds, 2N-acylethanolamine (NAE) lipid compounds, 9 Phosphatidylcholine (PC) lipid compounds, 1 Phosphatidylethanolamine (PE) lipid compound.
The 11 lysophosphatidylcholine lipid compounds can be LPC 15:0, LPC 16:1, LPC 17:0, LPC 18:1, LPC 18:2, LPC 20:1, LPC 20:2, LPC 20:3, and LPC 20: 4.
The 3 lysophosphatidylethanolamine lipid compounds may be LPE 16:0, LPE 18:0 and LPE 18: 2.
The 2N-acylethanolamine lipid compounds can be NAE 20:0 and NAE 26: 5.
The 9 phosphatidylcholine lipid compounds may be PC 34:1, PC 34:2, PC 36:4, PC 38:5, PC 38:6, PC 40:6 and PC 40: 7.
The 1 phosphatidylethanolamine lipid compound may be PE 38: 4.
In order to solve the technical problems, the invention also provides application of the substance for detecting the content of 26 lipid compounds in preparing a product for predicting whether an organism is in a perfluorooctane sulfonate toxic environment.
The 26 lipid compounds may include 11 Lysophosphatidylcholine (LPC) lipid compounds, 3 Lysophosphatidylethanolamine (LPE) lipid compounds, 2N-acylethanolamine (NAE) lipid compounds, 9 Phosphatidylcholine (PC) lipid compounds, 1 Phosphatidylethanolamine (PE) lipid compound.
The 11 lysophosphatidylcholine lipid compounds can be LPC 15:0, LPC 16:1, LPC 17:0, LPC 18:1, LPC 18:2, LPC 20:1, LPC 20:2, LPC 20:3, and LPC 20: 4.
The 3 lysophosphatidylethanolamine lipid compounds may be LPE 16:0, LPE 18:0 and LPE 18: 2.
The 2N-acylethanolamine lipid compounds can be NAE 20:0 and NAE 26: 5.
The 9 phosphatidylcholine lipid compounds may be PC 34:1, PC 34:2, PC 36:4, PC 38:5, PC 38:6, PC 40:6 and PC 40: 7.
The 1 phosphatidylethanolamine lipid compound may be PE 38: 4.
In the above application, the molecular formula of the LPC 15:0 is C23H48NO7P, the molecular formula of the LPC 16:0 is C24H50NO7P, the molecular formula of the LPC 16:1 is C24H48NO7P, the molecular formula of the LPC 17:0 is C25H52NO7P, the molecular formula of the LPC 18:0 is C26H54NO7P, the molecular formula of the LPC 18:1 is C26H52NO7P, the molecular formula of the LPC 18:2 is C26H50NO7P, the molecular formula of the LPC 20:1 is C28H56NO7P, the molecular formula of the LPC 20:2 is C28H54NO7P, and the molecular formula of the LPC 20:3 is C28H52NO 7P; the molecular formula of LPC 20:4 is C28H50NO 7P.
The molecular formula of LPE 16:0 is C21H44NO7P, the molecular formula of LPE 18:0 is C23H48NO7P, and the molecular formula of LPE 18:2 is C23H44NO 7P.
The molecular formula of the NAE 20:0 is C22H45NO2, the molecular formula of the NAE 26:5 is C28H47NO2,
the molecular formula of the PC 34:1 is C42H82NO8P, the molecular formula of the PC 34:2 is C42H80NO8P, the molecular formula of the PC 36:2 is C44H84NO8P, the molecular formula of the PC 36:4 is C44H80NO8P, the molecular formula of the PC 38:4 is C46H84NO8P, the molecular formula of the PC 38:5 is C46H82NO8P, the molecular formula of the PC 38:6 is C46H80NO8P, the molecular formula of the PC 40:6 is C48H84NO8P, and the molecular formula of the PC 40:7 is C48H82NO 8P.
The molecular formula of the PE 38:4 is C43H78NO 8P.
In the above-described applications, the substance may be a reagent, a kit and/or a system.
In the above application, the system may be a system for obtaining a lipid metabolism fingerprint of a serum sample of the organism.
In the above applications, the system may be a hplc-quadrupole orbitrap mass spectrometer and reagents related thereto. The system can also be a high performance liquid chromatography-triple quadrupole mass spectrometer or a high performance liquid chromatography-quadrupole linear ion trap mass spectrometer and related reagents thereof.
In order to solve the technical problems, the invention also provides a method for predicting the toxicity mechanism of the perfluorooctane sulfonate. The method comprises the following steps:
a1, obtaining a serum sample; dividing an experimental animal into a control group and a PFOS (Perfluorooctane-phosphate) exposed group, and carrying out blank solvent administration treatment on the control group, carrying out PFOS solution administration treatment on the PFOS exposed group, wherein the solute of the PFOS solution is PFOS, and the solvent of the PFOS solution is the blank solvent; serum samples of the control group and the PFOS-exposed group were obtained by obtaining serum from whole blood of the control group and the PFOS-exposed group, respectively.
A2, extracting the lipid compounds of the serum sample.
A3, detecting the fingerprint of lipid metabolism of the lipid compound, and preprocessing the fingerprint to obtain the peak area matrix of the control group and the PFOS exposure group.
A4, analyzing the peak area matrix to obtain the differential lipid compounds of the control group and the PFOS exposure group, and analyzing the differential lipid compounds to obtain the toxicity mechanism of the PFOS.
The differential lipid compounds may be lipid compounds that differ in the amount of serum sample in the control group and PFOS-exposed group.
Among the above methods, the method for analyzing the peak area matrix by a4 may include the following steps: establishing an orthogonal partial least square discriminant analysis model by using the peak area matrix; and calculating the coefficient value of the variation weight of the orthogonal partial least squares discriminant analysis model and t test to obtain the differential lipid compounds of the control group and the PFOS exposure group.
The screening conditions for the differential lipid compounds of the control group and the PFOS-exposed group may specifically be such that the coefficient of variation weight (VIP) value is greater than 1 and the p-value of the t-test is less than 0.05 as the screening criteria.
Among the above methods, the method for preprocessing the fingerprint map in a3 may be preprocessing using msodial software.
The pre-treatment using msdail software may specifically include steps of peak identification, peak alignment, peak matching, noise filtering, compound identification, and peak area normalization, and the specific pre-treatment parameters are MS1 tolerance 0.01Da, MS2 tolerance 0.025Da, Minimum peak height 10000, Mass slice width 0.1Da, Sigma window value 0.5, Accurate Mass tolerance (MS1) 0.01Da, and Accurate Mass tolerance (MS2) 0.05 Da.
In the method described above, the blank solvent described in a1 may be a 2% aqueous solution of tween 20. The concentration of the PFOS solution can be 1-10 mg/mL. The concentration of the PFOS solution can be 1 mg/mL.
The experimental animal may be a rat or a mouse. The dose of PFOS administered is 1-20mg PFOS/kg rat/mouse body weight. The dose of the PFOS to be administered may be specifically 5mg PFOS/kg rat/mouse body weight.
In the method, the step of analyzing and screening the peak area matrix by A3 may further comprise a principal component analysis step. The principal component analysis may be used to normalize the matrix of peak areas to detect the overall difference in samples between the control and PFOS exposed groups.
The principal component analysis may comprise the steps of: the peak area matrix is introduced into SIMCA-P software, the one-dimensional principal component analysis is carried out on the peak area matrix of the fingerprint of the quality control sample (the serum of each sample of the control group and the PFOS exposure group with the same volume is mixed to be used as the quality control sample), and the two-dimensional principal component analysis is carried out on the peak area matrix of all samples (the serum sample of the control group and the PFOS exposure group and the quality control sample).
In order to solve the technical problem, the invention also provides a device for predicting the toxicity mechanism of the perfluorooctane sulfonate. The apparatus may include the following modules:
b1, a serum sample acquisition module: obtaining serum samples of a control group of experimental animals and a PFOS exposure group of experimental animals; and carrying out blank solvent administration treatment on the experimental animal control group, and carrying out PFOS solution administration treatment on the experimental animal PFOS exposure group.
B2, sample pretreatment and lipid compound extraction module: for obtaining lipid compounds in a serum sample.
B3, omics detection and pretreatment module for lipid compounds: and the fingerprint is used for obtaining the fingerprint of the lipid metabolism of the serum sample, and identifying and obtaining the lipid compound and the peak area matrix of the lipid compound from the fingerprint.
B4, a multivariate statistical analysis module: and analyzing the differential lipid compounds to obtain the toxicity mechanism of the PFOS.
In the above-described device, the sample pretreatment and lipid compound extraction module described in B2 can be specifically established by a method comprising the steps of: pipetting 200. mu.L of the serum sample into an EP tube, adding 400. mu.L of MTBE and 80. mu.L of methanol, vortexing for 30s and mixing, then placing the sample in a centrifuge, centrifuging for 15min at 3000rpm, pipetting 200. mu.L of the supernatant into a new EP tube after the centrifugation is finished, then adding 200. mu.L of MTBE into the centrifuged EP tube, repeating the above steps, and combining the supernatants. The supernatant was centrifuged at 15000rpm for 10min and transferred to a new EP tube, nitrogen was blown to dryness, 200. mu.L of a mixed solution of dichloromethane: methanol (1:1, v/v) was added to dissolve, and the dissolved solution was transferred to a sample bottle to obtain the lipid compounds in the serum sample.
The omics detection and pretreatment module for lipid compounds described in B3 may comprise the following modules:
b3-1 fingerprint obtaining module: for obtaining a fingerprint of the lipid metabolism of said serum sample.
The B3-1 fingerprint acquisition module can be specifically established by a method comprising the following steps:
the UPLC-Q-Orbitrap serum assay was used to obtain fingerprints of the original lipid metabolism of control and PFOS exposed group serum samples.
B3-2 fingerprint preprocessing module: the method is used for preprocessing the fingerprint of the original lipid metabolism to obtain peak area matrixes of the fingerprints of the serum samples of a control group and a PFOS exposure group.
The B3-2 fingerprint preprocessing module can be specifically established by a method comprising the following steps:
preprocessing the fingerprint by MSDIAL software, including the steps of peak identification, peak alignment, peak matching, noise filtering, compound identification, peak area normalization and the like, wherein specific preprocessing parameters are MS1 tolerence 0.01Da, MS2 tolerence 0.025Da, Minimum peak height 10000, Mass slice width 0.1Da, Sigma window value 0.5, Accurate Mass tolerence (MS1) 0.01Da, and Accurate Mass tolerence (MS2) 0.05 Da. And obtaining the peak area matrixes of the fingerprints of the serum samples of the control group and the PFOS exposure group.
The multivariate statistical analysis module of B4 can comprise the following modules:
b4-1 principal component analysis module: for normalization of the matrix of peak areas obtained, the overall difference of the samples between the control and PFOS-exposed groups was examined.
B4-2 orthogonal partial least squares analysis module: the variable weight coefficient values and t-test used to determine the differential lipid compounds by orthogonal partial least squares discriminant analysis.
In order to solve the above technical problem, the present invention also provides a computer-readable storage medium storing a computer program. The computer program may cause a computer to perform the steps of the method as described above. The computer program causes the computer to also run the modules of the apparatus as described above.
The invention analyzes the fingerprint of lipidomics of serum of experimental animals under the conditions of PFOS exposure and normal control based on UPLC-HRMS lipidomics technology, and obtains 26 differential lipid compounds which can be used as a biomarker for judging whether an organism has PFOS exposure. The 26 lipid compounds comprise 11 LPC lipid compounds, 3 LPE lipid compounds, 2 NAE lipid compounds, 9 PC lipid compounds and 1 PE lipid compounds. By detecting the 26 different lipid compounds in the serum, the condition that whether an organism has PFOS exposure or not can be judged by using a lipidomics technology under the condition that PFOS standards are not used, and the PFOS exposure can be conveniently and quickly judged.
Drawings
FIG. 1 is a score plot of one-dimensional principal component analysis of a quality control sample according to an embodiment of the present invention. The abscissa is the sample number and the ordinate is the one-dimensional principal component score.
FIG. 2 is a two-dimensional principal component analysis plot of all samples in an embodiment of the present invention. The abscissa is the first-dimension principal component score and the ordinate is the second-dimension principal component score.
FIG. 3 is a graph of the OPLS-DA score in an embodiment of the present invention. The abscissa represents the principal component score and the ordinate represents the orthogonal component score.
Detailed Description
The present invention is described in further detail below with reference to specific embodiments, which are given for the purpose of illustration only and are not intended to limit the scope of the invention. The examples provided below serve as a guide for further modifications by a person skilled in the art and do not constitute a limitation of the invention in any way.
The experimental procedures in the following examples, unless otherwise specified, were carried out in a conventional manner according to the techniques or conditions described in the literature in this field or according to the product instructions. Materials, reagents and the like used in the following examples are commercially available unless otherwise specified.
The reagents used in the following examples were formulated as follows:
aqueous solution containing 2% Tween 20: tween 20 (purchased from Sigma-Aldrich) was dissolved in sterile water to give a 2% by volume aqueous solution of Tween 20.
Preparing a PFOS solution with the mass concentration of 1 mg/mL: PFOS (purchased from Sigma-Aldrich) was dissolved in an aqueous solution containing 2% Tween 20 to give a PFOS solution at a mass concentration of 1 mg/mL. The experimental samples in the examples of the present invention each contained 4 replicates.
Example 1 detection of markers for PFOS Exposure based on Lipomics technology
Construction of PFOS-exposed rat model
(1) Sprague-Dawley rats (from the laboratory animal technology Co., Ltd., Wei Tony, Beijing) 6-8 weeks old were selected, and a total of 8 rats were selected, 4 rats were selected for male and female. The 8 rats with the same or similar birth date and the same sex weights were recorded with age (6 weeks in male rats and 6 weeks in female rats) and weight (281 + -13 g in male rats and 190 + -6 g in female rats). 8 rats were randomized into 2 groups, one control and one PFOS-exposed group, each group having 2 males and females. Rats in the control and PFOS-exposed groups were not housed in one cage.
(2) The experiment was performed 1 week after the rats were housed. Each rat in the control group is dosed with an aqueous solution containing 2% Tween 20 once a day, and the dosing volume is the average value of the dosing volumes of the rats in the exposure group on the day; PFOS exposure group PFOS solution with mass concentration of 1mg/mL was administered once a day to each rat (fresh daily configuration), and PFOS exposure group was administered at a dose of 5mg PFOS/kg rat body weight. Each group was administered by gavage at the same time every morning for 28 consecutive days.
2. Collection of serum samples
On day 29, 8 rats of the control group and the PFOS-exposed group were sacrificed using carbon dioxide at the same time, and then serum samples were collected from each rat of the control group and the PFOS-exposed group, respectively, and the same volume of serum was taken from each sample serum of the control group and the PFOS-exposed group and mixed as a quality control sample (QC sample). After pretreatment, the control group, the PFOS exposure group and the quality control serum sample are subjected to lipidomics detection by using an ultra-high performance liquid chromatography-quadrupole rod Orbitrap mass spectrometer (UPLC-Q-Orbitrap) to obtain the original lipid fingerprint of chromatographic and mass spectrometric information.
The specific operation is as follows:
2.1 Experimental materials
The reagents used included: methanol (Merck, germany), methyl tert-butyl ether (MTBE, Honeywell, usa), dichloromethane (Merck, germany), formic acid (Honeywell, usa), acetonitrile (Avantor, usa).
The apparatus used comprises: centrifuge (Beijing Ding Hao Yuan science and technology Co., Ltd.), KAMS3 vortex oscillator (IKA, Germany), C18 chromatographic column (Waters, USA), Q-Excative ultra high performance liquid chromatography-quadrupole rod orbitrap mass spectrometry (Thermo Fisher, USA).
2.2 sample pretreatment and lipid Compound extraction
A. Thawing a serum sample at 4 ℃, sucking 200 mu L of the serum sample into a 1.5mL EP tube, adding 400 mu L of MTBE and 80 mu L of methanol, swirling for 30s, and uniformly mixing to obtain a mixed solution;
B. placing the mixed solution in a centrifuge, centrifuging at 3000rpm for 15min, sucking 200 μ L of the supernatant into a new EP tube after the centrifugation is finished, adding 200 μ L of MTBE into the centrifuged EP tube, repeating the above steps, and combining the supernatants.
C. The supernatant was centrifuged at 15000rpm for 10min and transferred to a new EP tube, nitrogen was blown to dryness, 200. mu.L of a mixed solution of dichloromethane: methanol (1:1, v/v) was added to dissolve the supernatant, and the dissolved solution was transferred to a sample bottle to obtain a serum sample pretreatment solution to be tested. The same pretreatment method was used to obtain a pretreatment solution for the quality-controlled sample.
Detection, map preprocessing and lipid identification of LC-MS lipidomics
The UPLC-Q-Orbitrap serum assay was used to obtain fingerprints of the original lipid metabolism of control and PFOS-exposed serum samples and QC samples.
The chromatographic column parameters in the liquid chromatographic method of the chromatography-mass spectrometry combined method are a Waters Xbridge C18 chromatographic column (specification is 2.1mm multiplied by 100mm, particle size is 3.5 μm), the sample injection volume is 10 μ L, the temperature of a sample tray is 4 ℃, the flow rate is 0.2mL/min, the mobile phase is divided into a mobile phase A and a mobile phase B, wherein the mobile phase A is 0.1% formic acid aqueous solution, the mobile phase B is 0.1% formic acid acetonitrile solution, and the gradient elution program is as follows: keeping the phase B at 40% during 0-5 min, increasing the phase B from 40% to 97% during 5-14 min, keeping the phase B at 97% during 14-16 min, decreasing the phase B at 40% during 16-16.5 min, and keeping the phase B at 40% during 16.5-21 min.
The mass spectrum conditions are as follows: the electrostatic orbit trap high-resolution mass spectrum adopts an electrospray ion source positive mode, the capillary voltage is 4kV, the capillary temperature is 320 ℃, the sheath gas is 40Arb, the auxiliary gas is 10Arb, and the mass spectrum scanning mode adopts Full-MS/dd-MS2The scanning range is 200-2000m/z, MSX count is 1, and TopN is 5.
Preprocessing the fingerprint by MSDIAL software (http:// prime. psc. key. jp/complexes/MSDIAL/main. html), including the steps of peak identification, peak alignment, peak matching, noise filtering, compound identification, peak area normalization, etc., wherein the specific preprocessing parameters are MS1 tolerance 0.01Da, MS2 tolerance 0.025Da, Minimum peak height 10000, Mass slot width 0.1Da, Sigma window 0.5, Accurate Mass tolerance (MS1) 0.01Da, and Accurate Mass tolerance (MS2) 0.05 Da.
After pretreatment of the serum sample and the quality control sample, the lipid compounds were identified by msodial's local lipid database. 226 lipid compounds were identified from the fingerprints of the original lipid metabolism of the serum samples and the QC samples, and a peak area matrix of the lipid compounds was obtained.
4. Multivariate statistical analysis
And (3) analyzing the peak area matrixes of the serum samples and the QC samples of the control group and the PFOS exposed group obtained in the step (3) by adopting multivariate statistical analysis, and verifying and evaluating the quality control of the data.
4.1 principal Components analysis
The obtained matrix of peak areas was normalized, and the overall profile of lipid metabolism fingerprint was analyzed by Principal Component Analysis (PCA), and the overall difference of the samples between the control group and the PFOS-exposed group was observed.
Specifically, the obtained peak area matrix is introduced into SIMCA-P software (version 14.1), and one-dimensional principal component analysis is performed on a quality control sample (QC sample), the result is shown in FIG. 1, and the principal component scores of the QC sample (QC 1-QC4 in FIG. 1) are all within 2 times of standard deviation (shown in 2std.dev. and-2 std.dev. in FIG. 1), which indicates that the instrument has good stability. On the basis, two-dimensional principal component analysis is carried out on all serum samples of a Control group and a PFOS exposure group, the result is shown in figure 3, QC samples are relatively gathered together (QC 1-QC4 in figure 2), the quality Control of the experiment is reliable, meanwhile, the difference exists between the Control group (Control, C _1-C _4 in figure 2) and the PFOS exposure group (5 mg/kg in figure 2, S2_1-S2_4), the samples of the same group have classification trend, the exposure of the PFOS changes the lipid metabolism of rats, and the success of constructing a PFOS exposure rat model is also shown.
4.2 orthogonal partial least squares analysis
In order to further analyze the influence of PFOS exposure on the lipid metabolism of rats and obtain more obvious classification trend, the supervised learning method can obtain better effect, so that an OPLS-DA model is established to analyze the influence of the lipid metabolism after PFOS exposure.
As shown in FIG. 3, the Control group (Control, C _1-C _4 in FIG. 3) and the PFOS-exposed group (5 mg/kg, S2_1-S2_4 in FIG. 3) showed significant differences in lipid metabolism profiles, and there was a classification trend between the samples in the same group. Wherein the model parameter R2X＝0.726、R2Y ═ 0.997 and Q20.997 indicates that the model has higher interpretation capability and prediction capability, and the established model has higher credibility.
5. Screening of lipid biomarkers:
on the basis of establishing an OPLS-DA model, VIP values and t tests of orthogonal partial least squares discriminant analysis (OPLS-DA) are used for screening lipid biomarkers of PFOS exposure.
Lipid biomarkers of PFOS exposure were obtained by calculating the coefficient of variation weight (VIP) value for the OPLS-DA model and screening differential lipid compounds by t-test.
VIP >1 and p <0.05 are selected as screening standards, lipid biomarkers of 26 control groups and PFOS exposure groups are screened out, the screening results of the lipid biomarkers and the variation trend of the lipid biomarkers are shown in Table 1, 11 of the 26 differential lipid compounds serving as the lipid biomarkers are LPC (lysophosphatidylcholine), 3 of the lipid biomarkers are LPE (lysophosphatidylethanolamine), 2 of the lipid biomarkers are NAE (N-acylethanolamine), 9 of the lipid biomarkers are PC (phosphatidylcholine), and 1 of the lipid biomarkers is PE (phosphatidylethanolamine), and the expression trends of the lipid biomarkers are all down-regulated.
TABLE 1 Table of information on differences between PFOS-exposed biomarker groups
26 different lipid compounds are closely linked to the healthy homeostasis of an organism: the down-regulation of LPC lipids results in a decrease in the permeability of the endothelial cells of the coronary arteries, which increases the risk of cardiovascular diseases in the organism; the LPE lipid plays an important role in maintaining normal liver function of organisms, and the reduction of the content of the LPE lipid can increase the incidence of fatty liver disease of the organisms; the down-regulation of the lipid content of NAE can affect the progress of obesity and metabolic diseases of organisms, and the reduction of NAE can cause disorder on reproductive function; the PC lipid has the functions of regulating fat absorption of organisms and protecting heart, and the reduction of the content thereof can cause the metabolic disorder of lipid substances in the organisms, increase the morbidity of hyperlipidemia and coronary heart disease and influence the healthy steady state of the organisms; the PE lipid has the effect of preventing organism liver cirrhosis and atherosclerosis, and the reduction of the content of the PE lipid can induce the occurrence of organism liver cirrhosis and atherosclerosis diseases. Thus, 26 differential lipid compounds can be used to predict the toxic mechanism of action of PFOS on organisms; meanwhile, the 26 differential lipid compounds can also be used as the biomarkers of PFOS exposure, and can be used for judging and predicting the PFOS exposure condition of organisms, so that whether the organisms have PFOS exposure or not can be conveniently and quickly judged and predicted.
The present invention has been described in detail above. It will be apparent to those skilled in the art that the invention can be practiced in a wide range of equivalent parameters, concentrations, and conditions without departing from the spirit and scope of the invention and without undue experimentation. While the invention has been described with reference to specific embodiments, it will be appreciated that the invention can be further modified. In general, this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. The use of some of the essential features is possible within the scope of the claims attached below.
Claims (10)
- The application of 1.26 lipid compounds as biomarkers in the preparation of products for predicting whether organisms are in a perfluorooctane sulfonate toxic environment;the 26 lipid compounds comprise 11 lysophosphatidylcholine lipid compounds, 3 lysophosphatidylethanolamine lipid compounds, 2N-acylethanolamine lipid compounds, 9 phosphatidylcholine lipid compounds and 1 phosphatidylethanolamine lipid compound;the 11 lysophosphatidylcholine lipid compounds are LPC 15:0, LPC 16:1, LPC 17:0, LPC 18:1, LPC 18:2, LPC 20:1, LPC 20:2, LPC 20:3 and LPC 20: 4; the 3 lysophosphatidylethanolamine lipid compounds are LPE 16:0, LPE 18:0 and LPE 18: 2; the 2N-acylethanolamine lipid compounds are NAE 20:0 and NAE 26: 5; the 9 phosphatidylcholine lipid compounds are PC 34:1, PC 34:2, PC 36:4, PC 38:5, PC 38:6, PC 40:6 and PC 40: 7; the 1 phosphatidylethanolamine lipid compound is PE 38: 4.
- 2. The application of the substance for detecting the content of 26 lipid compounds in preparing a product for predicting whether an organism is in a perfluorooctane sulfonate toxic environment;the 26 lipid compounds comprise 11 lysophosphatidylcholine lipid compounds, 3 lysophosphatidylethanolamine lipid compounds, 2N-acylethanolamine lipid compounds, 9 phosphatidylcholine lipid compounds and 1 phosphatidylethanolamine lipid compound;the 11 lysophosphatidylcholine lipid compounds are LPC 15:0, LPC 16:1, LPC 17:0, LPC 18:1, LPC 18:2, LPC 20:1, LPC 20:2, LPC 20:3 and LPC 20: 4; the 3 lysophosphatidylethanolamine lipid compounds are LPE 16:0, LPE 18:0 and LPE 18: 2; the 2N-acylethanolamine lipid compounds are NAE 20:0 and NAE 26: 5; the 9 phosphatidylcholine lipid compounds are PC 34:1, PC 34:2, PC 36:4, PC 38:5, PC 38:6, PC 40:6 and PC 40: 7; the 1 phosphatidylethanolamine lipid compound is PE 38: 4.
- 3. Use according to claim 2, characterized in that: the substance is a reagent, a kit and/or a system.
- 4. Use according to claim 3, characterized in that: the system is used for obtaining the lipid metabolism fingerprint of the organism serum sample.
- 5. Use according to claim 4, characterized in that: the system is a high performance liquid chromatography-quadrupole rod orbit trap mass spectrometer.
- 6. A method of predicting the toxicity mechanism of perfluorooctanesulfonic acid, the method comprising the steps of:a1, obtaining a serum sample; dividing an experimental animal into a control group and a PFOS (Perfluorooctane-phosphate) exposed group, and carrying out blank solvent administration treatment on the control group, carrying out PFOS solution administration treatment on the PFOS exposed group, wherein the solute of the PFOS solution is PFOS, and the solvent of the PFOS solution is the blank solvent; obtaining serum from whole blood of experimental animals of the control group and the PFOS exposure group respectively to obtain a serum sample of the control group and a serum sample of the PFOS exposure group;a2, extracting lipid compounds of the serum sample;a3, detecting a fingerprint of lipid metabolism of the lipid compound, and preprocessing the fingerprint to obtain peak area matrixes of the control group and the PFOS exposure group;a4, analyzing the peak area matrix to obtain the differential lipid compounds of the control group and the PFOS exposure group, and analyzing the differential lipid compounds to obtain the toxicity mechanism of the PFOS.
- 7. The method of claim 6, wherein: the method for analyzing the peak area matrix by A4 comprises the following steps: establishing an orthogonal partial least square discriminant analysis model by using the peak area matrix; and calculating the coefficient value of the variation weight of the orthogonal partial least squares discriminant analysis model and t test to obtain the differential lipid compounds of the control group and the PFOS exposure group.
- 8. The method according to claim 6 or 7, characterized in that: the preprocessing method for the fingerprint in a3 is to use msodial software for preprocessing.
- 9. An apparatus for predicting perfluorooctane sulfonate toxicity mechanism, the apparatus comprising the following modules:b1, a serum sample acquisition module: obtaining serum samples of a control group of experimental animals and a PFOS exposure group of experimental animals; carrying out blank solvent administration treatment on the experimental animal control group, and carrying out PFOS solution administration treatment on the experimental animal PFOS exposure group;b2, sample pretreatment and lipid compound extraction module: for obtaining lipid compounds in a serum sample;b3, omics detection and pretreatment module of lipid compounds: the fingerprint is used for obtaining the lipid metabolism of the serum sample and identifying a lipid compound and a peak area matrix of the lipid compound from the fingerprint;b4, a multivariate statistical analysis module: and analyzing the differential lipid compounds to obtain the toxicity mechanism of the PFOS.
- 10. A computer-readable storage medium having stored thereon a computer program for causing a computer to execute the steps of the method according to any of claims 1-6 or causing a computer to execute the modules of the apparatus according to any of claims 7-8.
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