Non-invasive selenium level prediction method based on saliva selenoprotein p detection and application

Abstract

The present application belongs to the technical field of biological detection, and particularly relates to a non-invasive selenium level prediction method based on saliva selenoprotein P detection and application. The present application immunizes mice with heterologously expressed antigen SELENOP (40-194 aa) to generate antibodies, and monoclonal antibodies capable of efficiently recognizing SELENOP are screened and obtained; an ELISA detection method is established using the obtained monoclonal antibodies. The selenium content in human plasma and saliva is detected and analyzed using the detection method and an ICP-MS selenium content detection method, and it is found that there is a significant positive correlation between the three, and a correlation curve between saliva selenoprotein P and human plasma selenium content is established, thereby achieving the purpose of evaluating human selenium level through non-invasive saliva selenoprotein P detection. The technical scheme provided by the present application can be used for large-scale screening and routine health monitoring.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of biological detection, and particularly relates to a non-invasive selenium level prediction method based on saliva selenoprotein P detection and application. BACKGROUND

[0002] Selenium, as an essential trace element for human body, plays an irreplaceable role in key physiological processes such as antioxidant defense, immune regulation and thyroid hormone metabolism. Studies have shown that selenium deficiency is closely related to various chronic diseases such as cardiovascular disease, cancer and thyroid dysfunction, while excessive intake may also cause toxicity. Therefore, accurate assessment of human selenium levels and development of personalized selenium supplementation strategies have become an important issue in the fields of public health and clinical nutrition. However, there is a widespread problem of blindness in current selenium supplementation practices, and it is urgent to establish a scientific and convenient detection method and guidance standard to balance the selenium nutritional needs and safety of different populations.

[0003] Currently, the detection of human selenium levels mainly relies on blood, urine or hair samples, and uses techniques such as hydride atomic fluorescence spectrometry (AFS), fluorescence spectrophotometry and inductively coupled plasma mass spectrometry (ICP-MS) to determine total selenium content. Patent CN113030373A proposes a chemiluminescence detection method based on blood selenium, but it still relies on the invasive blood sampling process. In recent years, selenoprotein P has attracted much attention due to its high correlation with selenium metabolism, and research has confirmed that its serum concentration can more directly reflect the bioavailability of selenium. However, existing detection methods mostly focus on total selenium content, and sample collection is complex, for example, urine selenium needs to be collected for 24 hours, and hair selenium is easily disturbed by detergents and growth cycles, making it difficult to meet the needs of convenience and precision in clinical practice.

[0004] The existing selenium detection technology has the following significant defects: (1) invasiveness and sampling limitations: blood selenium detection requires intravenous puncture, and the compliance of children, pregnant women and frequent monitoring groups is poor; urine selenium detection is limited by the sampling time (24 hours) and individual differences (such as kidney function and dietary fluctuations), and the error rate is as high as 30%; (2) single biomarker selection: total selenium content cannot distinguish between inorganic selenium and bioactive selenium forms (such as selenocysteine), leading to a disconnection between the evaluation results and physiological functions. For example, cancer patients may exhibit a paradoxical state of "normal total selenium but functional selenium deficiency" due to selenium protein synthesis disorders; (3) lack of personalized guidance: existing methods do not integrate selenium protein kinetic parameters (such as SEPP1 half-life), genetic polymorphisms (such as GPx1 genotype) and pathological factors (such as increased selenium requirements for diabetic patients), making it difficult to develop dynamic selenium supplementation programs. Studies have shown that traditional blood selenium detection can have a prediction error of up to 40% for elderly populations, as it ignores the age-related decline in selenium absorption rate; (4) insufficient technical cost and popularity: ICP-MS equipment is expensive (more than 2 million yuan per unit), fluorescence methods have low sensitivity (detection limit > 1 μg / L), and there is a lack of standardized detection systems for non-invasive samples such as saliva, which restricts the application of basic medical treatment.

[0005] In summary, the existing technology has not solved the core bottlenecks in the "accurate detection - function evaluation - personalized intervention" chain, and a new method needs to be developed to predict human selenium levels. SUMMARY

[0006] In view of the problems existing in the prior art, the technical problems to be solved by the present application include:

[0007] 1) To provide a simple, low-cost and non-invasive selenium level detection method: detecting selenium protein P through saliva samples solves the problems of complex blood sampling, high cost and strong invasiveness in traditional methods, making the detection process more convenient and fast, and suitable for large-scale population health monitoring.

[0008] 2) To realize accurate prediction of selenium level: by establishing the correlation curve between saliva selenium protein P and total selenium content, the present application can accurately predict the selenium status of the human body by measuring the level of saliva selenium protein P, thereby providing data support for personalized selenium supplementation programs, and avoiding the inaccurate prediction problem caused by only measuring total selenium content in the prior art.

[0009] 3) To promote the widespread application of saliva selenium protein P as a biomarker: the present application develops an ELISA rapid detection method based on selenium protein P detection, thereby promoting the standardized application of saliva selenium protein P as a selenium level evaluation and selenium supplementation guide.

[0010] By solving the above technical problems, the selenium level evaluation precision and efficiency can be significantly improved, personalized management of selenium supplementation is promoted, and health needs of different populations are met.

[0011] The application provides a selenium protein P antigen truncated body, and the amino acid sequence of the truncated body is 40-194 aa of the sequence shown in SEQ ID NO. 2.

[0012] The application also provides a gene for coding the selenium protein P antigen truncated body as defined in claim 1, and the nucleotide sequence is 118-582 nt of the sequence shown in SEQ ID NO. 1.

[0013] The application also provides an expression vector comprising the coding gene.

[0014] The application also provides application of the selenium protein P antigen truncated body in preparation of a selenium protein P antibody detection reagent.

[0015] The application also provides a selenium protein P antibody, and the monoclonal antibody is obtained by immunizing mice with the selenium protein P antigen truncated body.

[0016] The application also provides an ELISA kit for detecting the selenium protein P, wherein the kit comprises the selenium protein P antibody obtained by using the selenium protein P antigen truncated body.

[0017] The application also provides a non-invasive selenium level prediction method based on saliva selenium protein P detection, wherein the content of the selenium protein P in saliva is detected by using the ELISA kit, and the selenium level is predicted by referring to the correlation curve between the saliva selenium protein P and the content of the total selenium in plasma.

[0018] Further, the correlation curve between the saliva selenium protein P and the content of the total selenium in plasma is constructed by sequentially establishing the correlation curve between the content of the saliva selenium protein P and the content of the plasma selenium protein P and the correlation curve between the content of the plasma selenium protein P and the content of the total selenium in plasma.

[0019] The application also provides application of the non-invasive selenium level prediction method based on saliva selenium protein P detection in evaluation of the selenium level of a living body for non-diagnostic and therapeutic purposes, in particular in evaluation of the selenium level of a human body.

[0020] In conclusion, the application has the following advantages and positive effects:

[0021] The detection method provided by the present application can quickly and accurately determine the content of selenoprotein P through non-invasive saliva samples or conventional blood samples, thereby predicting the selenium level of the human body. Compared with traditional selenium detection methods, the present application has the following advantages:

[0022] Simple, fast and low cost: ELISA detection method is simple to operate and low in cost, suitable for large-scale screening and routine health monitoring.

[0023] High precision: Selenoprotein P as a biological active marker of selenium can more accurately reflect the selenium level of the human body.

[0024] Non-invasive: saliva sample collection is convenient and suitable for wide application in health management and development of individualized selenium supplementation plan.

[0025] Through the present application, accurate evaluation of selenium level can be realized, and individualized selenium supplementation guidance can be provided for different populations (such as pregnant women, the elderly, children, etc.).

[0026] The present application solves a series of problems in the prior art by proposing a method for predicting the selenium level of the human body based on detecting the content of selenoprotein P in saliva. Compared with the prior art, the present application has the following significant advantages:

[0027] 1) Non-invasive and convenient sample collection method: Traditional selenium level detection methods mainly rely on blood or urine sample collection. These methods are usually invasive and may cause discomfort to patients, especially when large-scale health screening is required. In addition, blood sample collection requires professional personnel and special equipment, increasing the operation difficulty and time cost. In contrast, the present application uses saliva samples as a substitute. Saliva sample collection is simple, non-invasive and comfortable, which not only reduces the burden of patients, but also improves the efficiency of sample collection, suitable for large-scale health screening of the population, especially for children, pregnant women, the elderly and other special groups. This improvement significantly improves the universality and convenience of detection.

[0028] 2) Customized selenoprotein P monoclonal antibody to improve detection accuracy and specificity: The present application uses a customized human selenoprotein P monoclonal antibody, which makes the detection of selenoprotein P have higher specificity and sensitivity. Compared with the non-specific antibodies or cross-reactive antibodies widely used in the prior art, the present application can effectively avoid the interference of other proteins through the precise design of the antibody, thereby improving the accuracy of the selenoprotein P detection result. This improvement provides a more reliable biomarker for accurate evaluation of selenium level.

[0029] 3) Rapid and efficient indirect ELISA detection method: The present application uses indirect ELISA (enzyme-linked immunosorbent assay) technology for quantitative detection of selenoprotein P, which only needs one capture antibody and one enzyme-labeled antibody, and has the advantages of simple operation, short detection period and low cost. Compared with high-end technologies such as ICP-MS, ELISA method not only requires less equipment, but also can be efficiently carried out in a conventional laboratory environment, and can quickly screen a large number of samples. In practical application, ELISA method provides an economical and efficient detection means for public health agencies, hospitals, clinical laboratories, etc.

[0030] 4) Predict selenium level by selenoprotein P to avoid the limitation of relying only on total selenium content: Traditional selenium level detection usually relies on the determination of total selenium content in blood or urine, however, total selenium content cannot fully reflect the biological activity and metabolic state of selenium in the body, and requires high-end instruments such as ICP-MS, and the operation process is complicated. The present application can more accurately evaluate the selenium level of the human body by determining the content of selenoprotein P, because selenoprotein P is the main carrier protein of selenium, and is closely related to the absorption, transport and utilization of selenium. Therefore, the present application can avoid the problem that the existing method cannot accurately reflect the biological function of selenium, and provide more scientific evaluation results of selenium level.

[0031] 5) Establish the correlation curve between selenoprotein P and total selenium content to provide personalized selenium supplementation guidance: The present application can realize accurate prediction of selenium level by establishing the correlation curve between selenoprotein P content and total selenium content. The advantage of this technical scheme is that it can scientifically predict the selenium status in the body according to the selenoprotein P level of the individual, thereby providing data support for the development of personalized selenium supplementation scheme. Through this method, the problems of excessive or insufficient selenium supplementation caused by blind supplementation can be avoided, ensuring the safety and effectiveness of selenium supplementation. This improvement provides personalized nutrition guidance for different populations (such as pregnant women, the elderly, children, etc.), which has important public health significance.

[0032] Strong adaptability and wide application prospect: The technology of the present application can not only be used for the evaluation of selenium level in clinic, but also can be widely applied in various health management, disease prevention, health monitoring of the elderly, etc. The selenium level prediction method based on selenoprotein P detection can play an important role in public health projects, individual nutrition management, disease prevention, etc. In addition, the technology is also suitable for the nutrition management of special groups such as athletes, the elderly, children, etc., and provides new technical support for personalized health management BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 is the result of amino acid sequence specificity and conservation analysis;

[0034] Figure 2 is the result of antigen epitope prediction;

[0035] Figure 3 PCR verification results of expression vector construction

[0036] Figure 4 Western blot verification results of antigen purification

[0037] Figure 5 ELISA sensitivity verification results of mouse monoclonal antibody

[0038] Figure 6 Plasma selenium protein P-plasma total selenium content correlation analysis

[0039] Figure 7 Saliva selenium protein P-plasma selenium protein P content correlation analysis

[0040] Figure 8 Saliva selenium protein P-plasma total selenium content correlation analysis

[0041] Figure 9 Saliva selenium protein P-plasma total selenium content correlation curve

[0042] Figure 10 Principle diagram of the present application. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application is further described in detail below in combination with examples. The equipment and reagents used in each example and test example can be obtained from commercial channels if not specifically stated. The specific examples described herein are only used to explain the present application and do not limit the present application.

[0044] According to the information contained in the present application, various changes to the precise description of the present application can be easily made by those skilled in the art without departing from the spirit and scope of the appended claims. It should be understood that the scope of the present application is not limited to the defined processes, properties or components, as these embodiments and other descriptions are only illustrative of specific aspects of the present application. In fact, various changes to the embodiments of the present application that are obvious to those skilled in the art or related fields are encompassed within the scope of the appended claims.

[0045] For a better understanding of the present application without restricting the scope thereof, all numbers expressing quantities of components, percentages, and other numerical values used in this application are to be understood as modified in all instances by the term "about". Thus, unless otherwise indicated, the numerical parameters set forth in the specification and attached claims are approximations that can vary depending upon the desired properties sought to be obtained by the present application. At the very least, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. In the present application, "about" means within 10% and preferably within 5% of a given value or range.

[0046] When the temperature is not specifically limited in the following embodiments of the present application, it is under normal temperature conditions. Normal temperature refers to the natural room temperature conditions in all seasons, without additional cooling or heating treatment, and the general normal temperature is controlled at 10-30°C, preferably 15-25°C.

[0047] In the examples, the experimental methods not specified in the specific conditions are generally carried out according to the conventional conditions, such as the methods required by the "Molecular Cloning Experiment Guide" (Chinese Edition) (J. Sambrook, M.R. Green, ed., He Fuji translation. Fourth Edition, Beijing: Science Press, 2017) and the purchased reagent kits, etc.

[0048] There are 25 kinds of selenium proteins in humans, among which selenium protein P (SELENOP) is a main protein for storing and transporting selenium in mammals. It is mainly synthesized in the liver and transports selenium elements through blood circulation, and is widely distributed in the liver, brain and kidney, blood, saliva and other organs and body fluids. One of the remarkable features of selenium protein P is that it contains a large number of selenocysteine (Sec) residues, usually with 10 or more Sec residues, which makes it the main storage and transport protein of selenium in the body. Selenocysteine is the key to the effective execution of the biological function of selenium protein P, which endows it with strong antioxidant capacity and selenium transport capacity. Therefore, the determination of the content of SELENOP can be used as an effective indicator to evaluate the selenium nutritional status of the human body. Considering the invasiveness and tediousness of blood collection, we innovatively used saliva samples to detect the content of selenium protein P in the human body to characterize the selenium content level in the human body, and found that there is a significant positive correlation between the content of saliva selenium protein, plasma selenium protein and total plasma selenium.

[0049] The application obtains the screening antigen SELENOP (40-194aa) by heterologous expression of the antigen SELENOP (40-194aa) in the strain E. coli Rosetta and protein purification, and then the recombinant SELENOP protein is introduced into the mouse by immunization to stimulate the immune system of the mouse to produce antibodies. Then, the spleen cells of the mouse are collected and fused with myeloma cells to form hybridoma cells. Subsequently, the monoclonal antibody capable of efficiently recognizing SELENOP is obtained through screening and cloning. After obtaining the monoclonal antibody, an indirect ELISA detection method of selenoprotein P is optimized and improved, the method uses the mouse monoclonal antibody of SELENOP as a capture antibody and goat anti-mouse F(ab')2 as an enzyme-labeled antibody, and can rapidly and sensitively detect the content of selenoprotein P in blood and saliva.

[0050] Subsequently, by using the ELISA detection method and the selenium content detection method of ICP-MS, the content of selenoprotein P in the plasma and saliva of more than ten human samples and the total selenium content in the plasma are detected simultaneously, and the correlation analysis is performed on the three groups of data. It is found that there is a significant positive correlation between the content of selenoprotein P in saliva and the content of selenoprotein P in plasma and the total selenium content, and the correlation curve between the content of selenoprotein P in saliva and the content of selenium in human plasma is established. Through the above work, the content of selenium in human blood can be rapidly and non-invasively judged by the ELISA detection of selenoprotein P in saliva, which is used for large-scale screening and routine health monitoring. In addition, according to the level of selenoprotein P in saliva, the selenium intake required by different groups of people is determined, and scientific selenium supplementation strategies for different groups of people are formulated to achieve accurate and scientific selenium supplementation. At the same time, the relationship between selenium content and various chronic diseases is studied, which lays a foundation for guiding the application of organic selenium in disease treatment.

[0051] The technical solutions of the application will be described in detail below in combination with specific embodiments.

[0052] Example 1 Heterologous expression of antigen selenoprotein P

[0053] 1. Selection of antigen region

[0054] The application performs specific and antigen epitope prediction on different antigen regions (such as Table 1, expression route: 40-194aa, 260-381aa; polypeptide route: 331-343aa, 28-40aa. The nucleotide sequence of SELENOP antigen is SEQ ID NO. 1, and the amino acid sequence is SEQ ID NO. 2) of selenoprotein P. It is found through analysis that the performance of different antigen regions is quite different, and the truncated SELENOP antigen (40-194aa) is superior in all aspects, so this region is selected for heterologous expression and purification, and mouse monoclonal antibody is produced by mouse immunization injection.

[0055] Table 1 Selection of antigen regions

[0056]

[0057]

[0058] Amino acid sequence specificity and conservation analysis: such as Figure 1 As shown, in Homo sapiens, gene specificity analysis revealed that this gene exhibited good specificity. This was further demonstrated through antigenic epitope analysis (…). Figure 2 This also indicates that this protein segment can serve as a suitable antigenic epitope.

[0059] 2. Construction of expression vector and preparation of antigen

[0060] After synthesizing the full SELENOP (40-194aa) gene, the pET-28a-SUMO vector was double-digested with BamHI and XhoI, and the SELENOP gene PCR product was also digested with the same restriction enzymes. Subsequently, the digested SELENOP gene fragment was ligated to the linearized pET-28a-SUMO vector using T4 DNA ligase to construct a recombinant plasmid. The ligation product was transformed into *E. coli* (e.g., DH5α), plated on an antibiotic selection plate, and positive clones were selected. The successful construction of the pET-28a-SUMO recombinant vector containing the SELENOP gene was verified by restriction enzyme digestion and sequencing. The vector was transformed into the expression strain *E. coli* Rosetta, cultured until the OD reached 600 nm to 0.5-0.6, induced with 0.8 mM IPTG at 37°C for 4 hours, and after lysis and purification, the protein was identified. Results are as follows: Figure 4 The purified protein is the correct size and can be used for subsequent mouse immunization to produce selenoprotein P monoclonal antibody.

[0061] Example 2: Expression of human selenoprotein P monoclonal mouse antibody

[0062] First, the recombinant SELENOP protein prepared in Example 1 was introduced into mice by immunization to stimulate their immune system to produce antibodies (Table 2). Next, referring to the method of Ma Jingchang et al. (Ma Jingchang, Wu Shuwen, Wang Yuling, et al. Preparation and application of mouse anti-human tumor suppressor 2 (ST2) monoclonal antibody [J]. Journal of Cell and Molecular Immunology, 2021, 37(11): 1026-1031. DOI: 10.13423 / j.cnki.cjcmi.009298.), the mouse spleen cells were collected and fused with antibody-producing cell line myeloma cells SP2 / 0 to form hybridoma cells. Subsequently, through screening and cloning, monoclonal antibodies capable of efficiently recognizing SELENOP were obtained. Finally, antibodies with high specificity and high affinity were selected for large-scale culture and purification to obtain selenium protein P mouse monoclonal antibody CMC0619-01-A for various ELISA detection, with an antibody concentration of 1.32 mg / mL. Then, through the following ELISA experiment, it was proved that the antibody had good titer and could meet the experimental needs of ELISA detection, etc. Figure 5

[0063] Experimental scheme:

[0064] Coating: SELENOP (40-194 aa)-HIS-SUMO, 1 μg / mL, 25 μl / well, coating (384-well plate) at 4°C overnight

[0065] Blocking: ELISA blocking solution 50 μl / well, room temperature incubation for 1 h.

[0066] Primary antibody: antibody 1 μg / ml as the starting concentration, 3-fold gradient dilution, 8 gradients, 25 μl / well, room temperature incubation for 1 h.

[0067] Secondary antibody: Peroxidase-conjugated AffiniPure Goat Anti-Mouse IgG (H+L) [Jackson ImmunoResearch, 115-035-003], 1:10000, 25 μl / well, room temperature incubation for 1 h.

[0068] Color development: TMB [Thermo Fisher, 34029] (1:5), 25 μl / well, room temperature color development for 3 min.

[0069] Note: NC is diluent Buffer

[0070] Table 2: Mouse antigen injection immunization record

[0071] Number of immunizations Immunization cycle Time of immunization Immunization dose (ug) Immunization adjuvant State of immunized animals First immunization 0 days 2022 / 9 / 20 100 ug / animal Complete Freund's adjuvant Good Second immunization 14 days 2022 / 10 / 4 100 ug / animal Incomplete Freund's adjuvant Good Third immunization 28 days 2022 / 10 / 18 100 ug / animal Incomplete Freund's adjuvant Good Fourth immunization 42 days 2022 / 11 / 1 100 ug / animal Incomplete Freund's adjuvant Good Fifth immunization 56 days 2022 / 11 / 15 100 ug / animal Incomplete Freund's adjuvant Good Sixth immunization 70 days 2022 / 11 / 29 100 ug / animal Incomplete Freund's adjuvant Good Seventh immunization 388 days 2023 / 10 / 13 100 ug / animal Incomplete Freund's adjuvant Good Booster immunization 402 days 2023 / 10 / 27 100 ug / animal / Good Blood collection from immunized animals 407 days 2023 / 11 / 01 / / / ​

[0072] Establishment of ELISA rapid detection method

[0073] 1. Detection principle and steps

[0074] First, the mouse monoclonal capture antibody is immobilized on the surface of the ELISA plate, and the F(ab')2 region of the capture antibody can specifically bind to the target antigen-selenoprotein P. Then, the saliva sample to be tested (containing selenoprotein P in the sample) and the standard are added to the plate, and after incubation, the selenoprotein P antigen in the sample binds to the F(ab')2 region of the capture antibody. At the same time, the selenoprotein P concentration in the standard is also fixed through a similar binding reaction. Next, HRP-labeled anti-mouse F(ab')2 secondary antibody is added. This labeled secondary antibody can bind to the remaining F(ab')2 region of the capture antibody. The labeled secondary antibody binds to the capture antibody, bringing in horseradish peroxidase (HRP), thereby providing signal amplification in the subsequent reaction. In the reaction system, HRP catalyzes the substrate reaction of TMB substrate developing solution. TMB substrate produces blue soluble material under the catalysis of HRP, and the color depth is proportional to the amount of HRP in the reaction system, while the amount of HRP is inversely proportional to the concentration of selenoprotein P in the sample. Finally, sulfuric acid is added to stop the reaction, and the developing solution changes from blue to yellow. By detecting the absorbance value of the reaction system at 450 nm, the content of selenoprotein P in the sample can be quantitatively determined. The absorbance value is inversely proportional to the concentration of selenoprotein P in the sample, and a higher absorbance value represents a lower antigen concentration, and a lower absorbance value represents a higher antigen concentration. This process can achieve accurate quantitative detection of selenoprotein P.

[0075] Using the above ELISA technique, a standard curve is established according to the absorbance value of the selenoprotein P standard, and then the selenoprotein P concentration in the saliva sample is calculated according to the absorbance value generated after incubation of the saliva sample, to obtain the actual content of selenoprotein P in the saliva sample. Through this process, we can accurately calculate the concentration of the target antigen (selenoprotein P) in the sample, ensuring the reliability and accuracy of the detection results.

[0076] The specific steps are as follows:

[0077] Capture antibody coating: The selenoprotein P monoclonal antibody prepared in Example 2 is immobilized on the surface of the ELISA plate.

[0078] Blocking the plate: Add 5% BSA for 2 hours.

[0079] Sample processing: Add the saliva or blood sample dilution sample to the plate, and incubate to allow selenoprotein P to bind to the capture antibody.

[0080] Washing and detection: binding was performed using HRP-labeled goat anti-mouse F(ab')2 antibody, followed by an enzymatic reaction after adding substrate, and finally the concentration of selenoprotein P was quantitatively detected by measuring color change or optical density (OD value).

[0081] The content of selenoprotein P in the sample was calculated by a standard curve, and then the selenium level in vivo was predicted.

[0082] 2. Establishment of ELISA detection method for selenoprotein P content in saliva

[0083] 1) Collection of saliva samples: The saliva collection time was 9 o'clock in the morning. The subjects avoided drinking and eating oily, spicy and other foods that could change the pH value of saliva within 12 hours before collection. Carefully brushed teeth and rinsed mouth before collection, thoroughly cleaned the oral cavity, and waited at least 10 min before saliva collection. Under any stimulation, the tip of the tongue was pressed against the palate to let the saliva flow naturally into the saliva collector. During the collection process, licking the tongue and other behaviors that stimulate saliva secretion were prohibited. The collection should be completed within 5 min. After the saliva was collected, the whole saliva was centrifuged (4℃, 2000g, 30min). The supernatant saliva was taken, the corresponding volume of protease inhibitor was added, and the protein was quantified by BCA method, and stored at -20°.

[0084] 2) Capture antibody coating: dilute the primary antibody to 0.6 μg / ml concentration with ELISA coating buffer (50 mM sodium bicarbonate, pH 9.6), add 100 μL volume per well to the enzyme-labeled hole, and incubate at 4℃ overnight;

[0085] 3) Washing: discard the liquid in the hole, add 350 μL of washing liquid PBST (PBS with 1% Tween) per hole, stand for 30 s, wash 3 times, and pat dry;

[0086] 4) Blocking the hole plate: add 200 μL of 5% BSA blocking solution (dissolved in PBST) per hole, block at 37℃ for 2 h; repeat step 3);

[0087] 5) Incubation of saliva samples and standard protein: dilute the standard with PBS (pH 7.2) to 0, 1, 5, 10, 20, 40, 60, 80, 100 ng / μL, respectively, add 100 μL per well, add 100 μL of saliva diluent to the blank hole, and incubate at 37℃ for 1.5 hours; repeat step 3);

[0088] 6) Enzyme-labeled antibody incubation: dilute HRP-enzyme-labeled antibody with antibody diluent at a ratio of 1:20000, add 100 μL of diluted enzyme-labeled antibody to each well, incubate at 37℃ for 1 hour, and preheat TMB at 37℃; repeat step 3);

[0089] 7) Color development: Add 90 μL TMB solution to each well, incubate at 37°C for 15 minutes in the dark;

[0090] 8) Reaction termination: Immediately add 50 μL stop solution (2 mol / L sulfuric acid) to each well to terminate the reaction;

[0091] 9) Absorbance measurement: Measure the absorbance of each well at 450 nm wavelength within 5 minutes using an enzyme label meter;

[0092] Calculation result: Make a standard curve and calculate the selenium protein P concentration of the sample.

[0093] Example 4 Correlation analysis of saliva selenium protein P and total selenium content

[0094] 1. Quantitative detection of total selenium content in blood

[0095] In order to establish the correlation between saliva selenium protein P and total selenium content, the present application also uses ICP-MS (inductively coupled plasma mass spectrometry) to quantitatively detect the total selenium content in blood. The specific steps include:

[0096] Pretreat the blood sample to remove cell precipitate and obtain plasma, and ionize the sample by microwave digestion instrument.

[0097] High-precision determination of total selenium content in plasma sample by ICP-MS.

[0098] 2. Correlation analysis of saliva selenium protein P and total selenium content and establishment of prediction model

[0099] After obtaining the detection results of selenium protein P content and total selenium content in multiple groups of samples, the present application establishes the correlation curve between selenium protein P content and total selenium level by statistical method (regression analysis). This curve can be used to predict the total selenium level in blood through the content of saliva selenium protein P. This correlation curve provides a scientific basis for selenium supplementation, which can predict the selenium level of individuals according to the detected selenium protein P content and provide support for personalized selenium supplementation plan. This technology is suitable for health screening, nutrition assessment and clinical intervention fields.

[0100] Advantages: Customized human selenium protein P monoclonal antibody: The use of customized human monoclonal antibody ensures high specificity detection of selenium protein P and avoids interference of other proteins.

[0101] Dual detection of saliva and blood samples: Through the combination of saliva and blood samples, a more diversified and flexible selenium level evaluation method is provided.

[0102] ELISA and ICP-MS double detection combination: ELISA detects selenoprotein P in saliva, and ICP-MS detects total selenium content. Through the correlation analysis of the two, accurate data support is provided for selenium level prediction.

[0103] Standard curve and personalized selenium supplement scheme: by establishing the correlation curve between selenoprotein P and total selenium content, the personalized prediction of selenium level is realized, and the scientific basis for the personalized management of selenium supplementation is provided.

[0104] 3. Establishment of saliva selenoprotein P and human plasma selenium content correlation curve

[0105] The ELISA detection method of saliva selenoprotein P has been established in Example 3. At the same time, the saliva samples and plasma samples of the same subject were collected in this application. The detection of selenoprotein P in saliva samples is shown in Example 3.

[0106] The detection of total selenium content in plasma samples uses a microwave digestion system for high temperature and high pressure digestion of samples to decompose organic components in the tissue and convert selenium into a soluble form. After digestion, the sample solution is cooled and diluted with 2% dilute nitric acid to the appropriate volume, and then the selenium content is quantitatively analyzed by inductively coupled plasma mass spectrometry (ICP-MS). The basic steps are as follows:

[0107] 1) Microwave digestion reaction tank, cover, and pellet are placed in 10-20% nitric acid overnight, washed, dried, and ready for use;

[0108] 2) Sample pre-acid removal: add 200 μL of saliva sample to each tube, add 8 mL of concentrated nitric acid, and pre-acid removal at 120 degrees for 20 min;

[0109] 3) Microwave digestion: tighten the tube cap, load the turntable, and open the acid removal program: 140 degrees for 5 min, 180 degrees for 25 min microwave digestion;

[0110] 4) Sample acid removal: slowly open the lid in the fume hood, and remove the acid at 160 degrees to 0.5-1 ml;

[0111] 5) Volume setting and sample analysis: after step 4) acid removal, set the volume to 10 mL, and quantitatively analyze the selenium content in the sample by inductively coupled plasma mass spectrometry (ICP-MS).

[0112] Through the above method, the content of saliva selenoprotein P and the total selenium content in plasma are determined, and then the linear relationship between the content of saliva selenoprotein P and the total selenium content in plasma is established according to these experimental data. The specific steps are as follows:

[0113] Data collection: Through the detection of saliva samples and plasma samples of different subjects in the experiment, the concentration of selenoprotein P in saliva samples and the concentration of total selenium in plasma of 10 subjects were collected and determined.

[0114] Data processing: The ELISA detection results of selenoprotein P in saliva of each subject (unit: ng / mL) were paired with the ICP-MS detection results of total selenium in plasma of each subject (unit: μg / L), and a set of comparative data was arranged to form a corresponding table of saliva selenoprotein P content and plasma total selenium content.

[0115] Table 3: Detection statistics of plasma total selenium content, plasma selenoprotein P content and saliva selenoprotein P content of subjects

[0116]

[0117] Statistical analysis: Regression analysis was performed using statistical software, and a suitable regression model (such as linear regression model) was selected to fit the relationship between saliva selenoprotein P content and plasma total selenium content. The specific steps are as follows:

[0118] The concentration of selenoprotein P in plasma was taken as the independent variable (X axis), and the total selenium content in plasma was taken as the dependent variable (Y axis). Analysis showed that there was a positive correlation between the two ( Figure 6 ), a best regression line was fitted by least squares method, the regression equation was calculated, and the linear regression formula was obtained: y = 0.0596x - 30.647 (R 2 = 0.9795).

[0119] The concentration of selenoprotein P in saliva was taken as the independent variable (X axis), and the selenoprotein P content in plasma was taken as the dependent variable (Y axis). Analysis showed that there was a positive correlation between the two ( Figure 7 ), a best regression line was fitted by least squares method, the regression equation was calculated, and the linear regression formula was obtained: y = 0.6631x - 142.91 (R 2 = 0.9809)

[0120] The concentration of selenoprotein P in saliva was taken as the independent variable (X axis), and the total selenium content in plasma was taken as the dependent variable (Y axis). Analysis showed that there was a positive correlation between the two ( Figure 8 ), a best regression line was fitted by least squares method, the regression equation was calculated, and the linear regression formula was obtained: y = 0.0876x - 14.722 (R 2 = 0.9506)

[0121] Linear relationship verification: After establishing the linear regression model, a verification step was performed: by randomly sampling a subject XXX's saliva and plasma samples, the samples were diluted by gradient, and the selenium protein P content in saliva was detected by ELISA, and the total selenium content in plasma was detected by ICP-MS, and the regression standard curve of the two was established (y = 0.086x - 3.2795 R 2 = 0.9909). And take this as the standard curve, predict the plasma total selenium content of samples 1 to 12. Compare the predicted data with the actual detection data, and analyze the reliability of the predicted data.

[0122] Establish a selenium level prediction model:

[0123] The regression model established by the above steps ( Figure 9 ) can be used to predict the selenium level in human plasma. By determining the selenium protein P content (selenium protein P) in the saliva sample, combined with the regression equation, the plasma selenium level of the subject can be accurately predicted (Table 4). The model can provide a basis for selenium health management, supplement demand assessment and personalized nutrition plan development.

[0124] Table 4: Saliva selenium protein P content, plasma total selenium content and predicted plasma selenium content according to the correlation curve of the two

[0125]

[0126] The prediction result, through the detection of saliva selenium protein P, can significantly reflect the human blood selenium content level, with an error rate of 3%-15%, and an average error rate of about 8%. The results show that by determining the selenium protein P content (selenium protein P) in the saliva sample, combined with the regression equation, the plasma selenium level of the subject can be basically predicted. The model can provide a basis for selenium health management, supplement demand assessment and personalized nutrition plan development.

[0127] Experimental data verification and model optimization:

[0128] In order to further verify the applicability and accuracy of the established linear relationship, different batches of samples can be used for cross-validation to verify the prediction accuracy of the model. If there is a large deviation or error, the prediction ability of the model can be further improved by optimizing the regression model (such as using nonlinear regression, weighted regression, etc.).

[0129] The present application provides a method for detecting selenium protein P based on saliva samples, and by establishing a correlation model between saliva selenium protein P and human blood selenium content, the principle schematic diagram is as follows Figure 10The method can accurately detect the content of selenoprotein P in saliva by a simple and convenient saliva collection process and a high-sensitivity ELISA technology, and can effectively predict the selenium content in blood based on the established blood selenium prediction model between the content of selenoprotein P in saliva and the blood selenium level, thereby providing a scientific basis for selenium supplementation and health management, and being widely applicable to personal nutrition and health management, public health monitoring, and the development of individualized selenium nutrition intervention programs. Meanwhile, the technology has the advantages of simple operation, low cost and large-scale application, and has great market potential and application prospect.

[0130] The above merely describes preferred embodiments of the present application and is not intended to limit the present application, and any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A selenoprotein P antigen truncation, characterized in that: The amino acid sequence of the said truncation is from aa 40 to aa 194 of the sequence of SEQ ID NO.

2.

2. A gene encoding the selenoprotein P antigen truncation as claimed in claim 1, the nucleotide sequence of which is from nt 118 to nt 582 of the sequence of SEQ ID NO. 1.

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