An accurate quantitative structural analog immunodetection method and application thereof

Abstract

The application discloses an immune detection method for accurately quantifying structural analogues and application thereof. The immune detection method can realize accurate, intuitive and rapid identification and quantification of target analytes by combining wide-spectrum antibodies and specific antibodies to recognize structural analogues and by establishing a three-dimensional curved surface model through a multilayer perception machine model, and can solve the problem of false positive results in the detection process due to the high structural similarity between a certain target analyte and another substance in the immune analysis method, especially for analytes with indistinctive characteristic structures and cross substances, which are often difficult to prepare high-specificity antibodies. The immune detection method is simple to operate, does not require experimental personnel to take multiple verification measures, and greatly reduces the cost burden of detection. The application has great significance and broad application prospect for improving the accuracy of rapid detection of residual substances in food.

Description

Technical Field

[0001] This invention belongs to the field of food safety immunoassay technology, and more specifically, relates to an immunoassay method for accurately quantifying structural analogs and its application. Background Technology

[0002] Immunoassay, a bioanalytical method based on the principle of specific binding between antigens and antibodies, plays a crucial role in the screening and quantitative assessment of harmful substances in food due to its high specificity, sensitivity, ease of operation, and high analytical efficiency. However, this technology also faces the problem of antibody cross-reactivity, which weakens its specificity advantage to some extent. Taking pesticide residue detection as an example, many pesticide molecules, such as organophosphates like methamidophos and dimethoate, and pyrethroids like cypermethrin and deltamethrin, often have overlapping antigenic epitopes due to their similar structures, easily leading to cross-reactivity between antibodies against the same type of pesticide, thus producing false positive results. Furthermore, food matrices contain many complex components, some of which have structures similar to the target analyte. These components may also bind non-specifically to antibodies. For example, florfenicol in meat and eggs interferes with the detection of thiamphenicol, amines in serum interfere with the detection of histamine, and polyphenolic compounds such as tea polyphenols and anthocyanins confuse the detection results of mycotoxins. Given the existence of cross-reactivity, the specificity of immunoassay cannot be absolutely guaranteed. To ensure the accuracy of test results and avoid missed detections or misjudgments, laboratory personnel need to adopt multiple verification methods, which undoubtedly increases the cost of testing.

[0003] However, current solutions to antibody cross-reactivity issues primarily rely on hapten design. This "starting from scratch" approach is time-consuming, labor-intensive, and increases experimental costs. For structurally highly similar target analytes, certain risks remain. For example, in preparing thiamphenicol monoclonal antibodies, due to their high structural similarity to florfenicol and the high steric flexibility of their hydroxyl group (the only difference being florfenicol), they are less likely to be recognized as a characteristic group by the antibody. Therefore, the resulting antibody is highly likely to cross-recognize florfenicol, leading to inaccurate or false positive results. To address this challenge, developing a method that innovates upon existing mature immunoassay techniques, eliminates the need for multiple validation measures, and minimizes testing costs, is crucial for accurately identifying and quantifying homologous structural analogs. Summary of the Invention

[0004] The purpose of this invention is to overcome the above-mentioned defects and deficiencies in the prior art and to provide an accurate quantitative immunoassay method for structural analogs.

[0005] A second objective of this invention is to provide an application of the aforementioned immune detection method.

[0006] The above-mentioned objective of this invention is achieved through the following technical solution:

[0007] This invention first provides an immunoassay method for quantitatively detecting structural analogs in a sample, wherein the sample contains a first substance and a second substance, the first substance and the second substance being structural analogs, and the immunoassay method includes the following steps:

[0008] S1. Use broad-spectrum antibodies to detect standard solutions of the first and second substances at known concentrations, with the measured signal value as the ordinate and the concentration as the abscissa, and establish the first and second standard curves respectively.

[0009] S2. Using a broad-spectrum antibody, different concentrations of a mixture of the first and second substances were detected, and a three-dimensional concentration curve surface model was established using a multilayer perceptron regression model; the three-dimensional concentration curve surface was constructed with the signal value obtained from the detection of the mixture by the broad-spectrum antibody as the Z-axis, and the concentrations of the first and second substances as the X and Y axes, respectively.

[0010] S3. Use specific antibodies to detect standard solutions of the first substance at known concentrations, and establish the fourth standard curve with the measured signal value as the ordinate and the concentration as the abscissa.

[0011] S4. Use a broad-spectrum antibody to detect the sample to be tested, and substitute the detection results into the three-dimensional concentration curve surface model obtained in S2 to obtain a series of concentration combination subsets of the two structural analogs;

[0012] S5. Use a specific antibody to detect the sample to be tested, obtain the concentration of the first substance according to the fourth standard curve, and locate the combination subset of the concentration and the concentration obtained in S4 on the three-dimensional concentration curve surface model obtained in S2 to obtain the concentration value of the second substance.

[0013] The structural analogues are compounds that exhibit cross-reactivity in immunoassays;

[0014] The specific antibody can only recognize the first substance;

[0015] The broad-spectrum antibody can simultaneously recognize the first substance and the second substance.

[0016] This invention establishes an immunoassay method using a broad-spectrum antibody capable of recognizing two structural analogs and a specific antibody that can only specifically recognize one of the structural analogs. Specifically, a standard curve is established by detecting standard solutions of two structural analogs using a broad-spectrum antibody. Based on this standard curve, mixed solutions of the two structural analogs at known concentrations are detected using the broad-spectrum antibody. The obtained data are then used to establish a three-dimensional concentration surface model using a multilayer perceptron regression model. When detecting samples containing two structural analogs, the broad-spectrum antibody is first used to obtain the corresponding signal value. This signal value corresponds to a subset of the two drug concentrations in the mixture, so this subset has multiple possibilities. The specific antibody is then used to detect the sample to obtain the concentration of the structural analog. Finally, based on the constructed surface model, the signal value detected by the broad-spectrum antibody and the concentration of one structural analog are substituted into the model to accurately determine the concentration of the other drug in the mixed system.

[0017] This invention compares the performance of Origin, Matlab, and Multilayer Perceptron (MLP) in constructing three-dimensional curve-surface models, focusing on accuracy, ease of operation, and visual intuitiveness. The three-dimensional curve-surface models obtained by fitting Origin's Gaussian 2D function and Matlab's programming language yielded less than ideal predictions for thiamphenicol in actual testing. Therefore, MLP was ultimately selected for modeling and application. Using this method, false positives can be eliminated due to the presence of a structural analogue when a highly specific monoclonal antibody for a particular drug is unavailable, thus improving detection accuracy. Furthermore, this method can quantify the concentrations of two structurally similar drugs in the system.

[0018] Further, step S2 involves preparing standard solutions of different concentrations for the first and second substances based on the linear range of the standard curves obtained from the first and second standard curves in S1, and mixing them to obtain a mixed solution. The fluorescence signal value obtained by detecting the mixed solution with a broad-spectrum antibody is used as the Z-axis of the three-dimensional coordinate system. The different concentrations of the two structural analogs correspond to the X and Y axes respectively to form the base, thus establishing a three-dimensional concentration dataset. The data points corresponding to different concentration combinations in the three-dimensional concentration dataset are modeled using a multilayer perceptron regression model to obtain a three-dimensional concentration curve surface model.

[0019] Furthermore, the structural analogues are small molecule compounds.

[0020] Furthermore, the first substance is florfenicol, and the second substance is thiamphenicol.

[0021] Furthermore, the effective detection range of the immunoassay method for the first substance is the intersection of the concentration range of the specific antibody for the first substance, obtained by locating it in the three-dimensional curve surface model, and the detection range of the broad-spectrum antibody for the first substance; the effective detection range of the second substance is the detection range of the broad-spectrum antibody for the second substance.

[0022] Preferably, the effective detection range of the immunoassay method for florfenicol is 0.14–0.55 ng / mL, and the effective detection range for thiamphenicol is 0.04–1.69 ng / mL.

[0023] Furthermore, the broad-spectrum antibody mentioned in step S1 and the specific antibody mentioned in step S3 are monoclonal antibodies.

[0024] Furthermore, the broad-spectrum antibody is a monoclonal antibody that simultaneously recognizes thiamphenicol and florfenicol.

[0025] Furthermore, the specific antibody mentioned in step S3 is a monoclonal antibody that specifically recognizes florfenicol.

[0026] Preferably, the immunoassay is performed using a time-resolved fluorescent microsphere immunochromatography method.

[0027] Preferably, the immunoassay is performed using a time-resolved fluorescent microsphere immunoassay strip.

[0028] Preferably, the immunoassay is a time-resolved fluorescent microsphere immunochromatography method established using the disappearance method.

[0029] More preferably, the detection using the time-resolved fluorescent microsphere immunoassay strip includes the following steps:

[0030] S1. Preparation of time-resolved fluorescent microsphere probes (TRFMs probes): Time-resolved fluorescent microspheres are activated and then covalently coupled with broad-spectrum antibodies or specific antibodies to prepare the probes.

[0031] S2. Assembly of the test strip: The test strip consists of four components: absorbent filter paper, nitrocellulose membrane (NC membrane), sample pad, and PVC base plate. In the pre-preparation, two fixed test lines are set on the NC membrane. The line closer to the absorbent filter paper is the control line (C line), drawn with diluted goat anti-mouse secondary antibody IgG. The line closer to the sample pad is the detection line (T line), drawn with diluted coating antigen. A 2mm overlap between the absorbent filter paper and the sample pad must be ensured to contact the NC membrane. The width of the cut test strip is 3.5mm. Time-resolved fluorescent microsphere immunochromatographic test strips based on broad-spectrum antibodies and specific antibodies are prepared respectively.

[0032] S3. Test strip detection: Mix the TRFMs probe with the sample solution to be tested, let it stand to react, and then insert it vertically into the pre-packaged test strip to react. After the timer expires, remove the test strip and place it in a special test strip holder. Under ultraviolet light, observe the color intensity of negative and positive results with the naked eye, and use an immunochromatographic reader to measure the values ​​of the T line and C line.

[0033] As a preferred embodiment, the immune detection method includes the following steps:

[0034] S1. Using TRFMs probes loaded with broad-spectrum antibodies, two known structural analogs at different concentrations were detected. Detection was performed using time-resolved fluorescent microsphere immunochromatographic strips based on broad-spectrum antibodies. The values ​​of the T and C lines were read. Standard curves were plotted with the analyte concentration as the x-axis and B / B0 as the y-axis (B0 being the T / C value at zero drug concentration, and B being the T / C value at a drug concentration of x). Then, using a specific antibody that can only specifically recognize one of the structural analogs, a standard curve was plotted using the same method for the specific antibody against one of the structural analogs.

[0035] S2. Construction of a three-dimensional curve surface model: Based on the standard IC50 curves of the broad-spectrum antibody against two structural analogs... 20 ~IC 80 Based on this, two structural analogs diluted according to concentration gradients were mixed in equal volumes, and then detected using a broad-spectrum antibody time-resolved fluorescent microsphere test strip. The test strip signal was read, and the read signal value (B / B0) was mapped to the Z-axis of the three-dimensional coordinate system. The different concentration mixtures of the two structural analogs were mapped to the base formed by the X and Y axes. Finally, the signal value points corresponding to different concentration combinations in the three-dimensional coordinate system were instantiated using the Multilayer Perceptron (MLP) regression model class provided in the Scikit-learn library to construct the MLP regression model and build a three-dimensional concentration curve surface.

[0036] S3. Detection using a two-well method: After detecting the sample with a broad-spectrum antibody, substitute the read fluorescence signal value into the coordinate axis curve to obtain a series of concentration combinations of the two structural analogs; then detect the same sample with a specific antibody to obtain the concentration of one of the structural analogs, and locate the concentration of the structural analog on the concentration combination obtained by the broad-spectrum antibody detection to obtain the concentration value of the other structural analog.

[0037] This invention also provides applications of any of the above-described immunoassay methods in immunoassays to reduce interference or minimize false positive results. Specifically, the application is to avoid false positives due to antibody cross-reaction when a target analyte in the sample is structurally highly similar to another substance, thereby improving the accuracy of the detection.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] This invention provides an immunoassay method for accurately identifying and quantifying structural analogs in samples. This method combines broad-spectrum antibodies and specific antibodies to identify structural analogs, and utilizes a multilayer perceptron model to establish a three-dimensional surface model, enabling precise, intuitive, and rapid identification and quantification of target analytes. This solves the problem of false positives in immunoassays caused by structural similarity between a target analyte and another substance. Particularly for analytes with indistinguishable characteristic structures from cross-referenced substances, it is often difficult to prepare highly specific antibodies. Therefore, this invention eliminates the possibility of false positives due to the presence of another structural analog in the absence of highly specific antibodies for a particular drug, thus improving detection accuracy. Furthermore, this method can quantify the concentrations of two structurally similar drugs in the system. Moreover, the immunoassay method is simple to operate, requiring no multiple verification measures by laboratory personnel, significantly reducing the cost burden of detection. This invention has significant implications and broad application prospects for improving the accuracy of rapid detection of residues in food. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the test strip obtained in Example 1.

[0041] Figure 2 This is a standard curve of thiamphenicol and florfenicol obtained by time-resolved fluorescent microsphere immunochromatography with 2-9g broad-spectrum antibody in Example 2.

[0042] Figure 3 This is a standard curve of florfenicol obtained by the time-resolved fluorescent microsphere immunochromatography method using florfenicol FF15 specific antibody in Example 2.

[0043] Figure 4 This is a dataset of three-dimensional concentrations of the 2-9g broad-spectrum antibody against the mixed sample of thiamphenicol and florfenicol in Example 3.

[0044] Figure 5 The surface diagram of the three-dimensional model constructed for Example 3. Detailed Implementation

[0045] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but the embodiments do not limit the present invention in any way. Unless otherwise specified, the reagents, methods and equipment used in the present invention are conventional reagents, methods and equipment in this technical field.

[0046] Unless otherwise specified, all reagents and materials used in the following examples are commercially available.

[0047] Example 1: Preparation of time-resolved fluorescent microsphere immunochromatographic test strips containing 2-9g broad-spectrum thiamphenicol antibody and FF15 florfenicol specific antibody.

[0048] The amino acid sequence of the 2-9g broad-spectrum antibody for thiamphenicol is shown below: DIVLTQSPASLAVSLGQRATISYRASKSVNTSGYSYMHWNQQKPGQQPRLLTYLVSNLESGVPARFSGSGSGTDFTLNIHPVEEEDAATNYCQHIREPTRSEGGPRWKSNVGGGGSGGGGSGGGSASMKISCKASGFSFNGYYMNWVSQSHGNNLDWIGLIAPYSVYTAYNQKFKGKATLTADKSSGTAFMELLSLTSEDSAVYYCARPYYAGNSYVHMDYWGQGTSVTVSS.

[0049] The structure of the coating antigen TAP-H1-OVA corresponding to the 2-9g broad-spectrum antibody of thiamphenicol is shown in Formula I:

[0050]

[0051] The FF15 florfenicol specific antibody and the corresponding coating antigen FFD-OVA were prepared according to patents CN201711484698.9 and CN201711484702.1.

[0052] The specific preparation method of the time-resolved fluorescent microsphere immunochromatographic test strip is as follows:

[0053] 1) Preparation of TRFMs probes

[0054] (1) Microsphere washing: Add 500 μL of 0.05 mol / L MES buffer solution (pH = 6.5) to the centrifuge tube, then add 50 μL of 200 nm TRFMs, mix well and sonicate for 1 min; centrifuge at 15000 r / min at 4℃ for 10 min, discard the supernatant, add 500 μL of 0.05 mol / L MES again, sonicate for 1 min, and resuspend the microspheres;

[0055] (2) Microsphere activation: Add 5 μL of 10 mg / mL NHS to the solution obtained in step (1), mix quickly for 10 s, and immediately add 5 μL of 10 mg / mL EDC, vortex to mix. Place in a constant temperature shaker and activate at 37℃ and 250 r / min for 30 min. After activation, centrifuge at 25℃ and 15000 r / min for 15 min, and discard the supernatant. Add 500 μL of 0.05 mol / L BB buffer solution (pH = 8.0), sonicate for 1 min to resuspend the microspheres;

[0056] (3) Antibody conjugation: Add 3 μL of 2-9 g broad-spectrum antibody diluted to 1 mg / mL by 0.01 mol / L PB or 2 μL of FF15 florfenicol specific antibody diluted to 5 mg / mL by 0.01 mol / L PB to the solution obtained in step (2), and place it in a constant temperature incubator with shaking (230 r / min, 25℃) for 60 min for conjugation reaction;

[0057] (4) Blocking: After coupling, add 1 mL of 10% BSA blocking solution to the tube in step (3), vortex to mix, and place it in a constant temperature incubator shaker (230 r / min, 25℃) for 30 min of blocking reaction.

[0058] (5) Centrifugation: After step (4) is completed, centrifuge at 15000 r / min, 25℃ for 15 min. The coupled product will precipitate at the bottom of the centrifuge tube and the supernatant will be discarded.

[0059] (6) Resuspension: Add 200 μL of gold-labeled reconstitution solution to the centrifuge tube in step (5), vortex and sonicate repeatedly 2-3 times to fully disperse the microspheres, and then place at 4℃ for later use.

[0060] 2) Assembly, principle, and testing steps of the test strip

[0061] (1) Assembly of the test strip: The lateral flow immunochromatographic test strip consists of four components: absorbent filter paper, nitrocellulose membrane (NC membrane), sample pad, and PVC base plate. In the pre-preparation, two fixed test lines are set on the NC membrane. The line closer to the absorbent filter paper is the control line (C line), drawn with diluted goat anti-mouse antibody. The line closer to the sample pad is the detection line (T line), drawn with diluted coating agent. The coating agent for the 2-9g broad-spectrum thiamphenicol antibody test strip is TAP-H1-OVA, and the coating agent for the florfenicol FF15 specific antibody test strip is FFD-OVA. A 2mm overlap between the absorbent filter paper and the sample pad must be maintained in contact with the NC membrane. The width of the cut test strip is 3.5mm. A schematic diagram of the assembled test strip is shown below. Figure 1 As shown.

[0062] (2) Detection principle: In the microwell, after the analyte reacts with the TRFMs probes, the test strip is inserted and, under capillary action, the solution is chromatographically deposited along the test strip towards the absorbent filter paper. The TRFMs probes that do not bind to the analyte will move to the area where the coating is fixed, causing the T line to appear; the remaining TRFMs probes will bind specifically to the goat anti-mouse membrane on the NC membrane, causing the C line to appear. Under ultraviolet light, the colorimetric results can be observed with the naked eye for qualitative analysis, while a detector can be used for qualitative and quantitative detection.

[0063] (3) Detection procedure: Place an appropriate amount of TRFMs probe into the microwell, then add 100 μL of thiamphenicol or florfenicol solution diluted with standard diluent. Mix the TRFMs probe by repeatedly pipetting and blowing. After the microwell is allowed to stand for 3 minutes, insert the probe vertically into the pre-loaded test strip and react for 5 minutes. After the time is up, remove the probe and place it into the dedicated test strip cartridge. Under ultraviolet light, observe the color intensity of negative and positive results with the naked eye, and use an immunochromatographic reader to determine the values ​​of the T line and C line.

[0064] Example 2: Establishment of standard curves for time-resolved fluorescent microsphere immunochromatographic test strips containing 2-9g broad-spectrum thiamphenicol antibody and FF15 florfenicol specific antibody.

[0065] 1) Establishment of standard curves for florfenicol and thiamphenicol using a broad-spectrum antibody time-resolved fluorescent microsphere immunochromatography method with 2-9g thiamphenicol.

[0066] Thiamphenicol and florfenicol standards were prepared into 1000 ng / mL solutions using 0.2 mol / L PB. Thiamphenicol and florfenicol were then diluted with 0.2 mol / L PB at 5-fold concentration gradients. 100 μL of each concentration gradient of thiamphenicol and florfenicol was added to each well. Subsequently, 8 μL of 2-9 g of broad-spectrum antibody probe was added to each well. After standing for 3 minutes, 2-9 g of time-resolved fluorescent microsphere test strips were inserted into each well. Chromatography was performed for 5 minutes. After chromatography, the strips were removed and placed into a dedicated test strip holder. The color intensity of negative and positive results was observed visually under UV light, and the T and C lines were measured using an immunochromatographic reader. The analyte concentration was plotted as the x-axis, and B / B0 as the y-axis (B0 being the T / C value at zero drug concentration, and B being the T / C value at a drug concentration of x). Each drug gradient experiment was repeated three times using Origin. In 2022, a standard curve for the drug to be tested was established using graphing software. The standard curves for 2-9g antibodies against thiamphenicol and florfenicol are shown below. Figure 2 As shown, the IC50 of 2-9g antibody against thiamphenicol and florfenicol is... 50 The concentrations were 0.26 ng / mL and 0.15 ng / mL, respectively, with linear ranges IC50 and IC50 values. 20 ~IC 80The concentrations were 0.04 ng / mL to 1.69 ng / mL and 0.04 ng / mL to 0.55 ng / mL, respectively.

[0067] 2) Establishment of a standard curve for florfenicol using FF15 florfenicol-specific antibody.

[0068] Florfenicol standard was prepared into a 1000 ng / mL solution using 0.1 mol / L PB. Then, florfenicol standard was diluted with 0.1 mol / L PB at 5-fold concentration gradients. 100 μL of each concentration gradient of florfenicol was added to the microwells. Subsequently, 6 μL of FF15 florfenicol-specific antibody probe was added to each well. After standing for 3 minutes, FF15 time-resolved fluorescent microsphere test strips were inserted into each well. The chromatography time was 5 minutes. After chromatography, the strips were removed and placed into a dedicated test strip holder. Under UV light, the color intensity of negative and positive results was observed visually, and the T and C lines were measured using an immunochromatographic reader. The analyte concentration was plotted as the x-axis, and B / B0 as the y-axis (B0 is the T / C value at zero drug concentration, and B is the T / C value at a drug concentration of x). Each drug gradient experiment was repeated three times. A standard curve for the analyte was constructed using Origin 2022 plotting software. The standard curve of florfenicol FF15 specific antibody against florfenicol is shown below. Figure 3 As shown, the IC50 of FF15 florfenicol-specific antibody against florfenicol is... 50 The concentration was 0.40 ng / mL, and the IC50 concentration was 0.40 ng / mL. 20 ~IC 80 The concentration ranges from 0.07 ng / mL to 2.30 ng / mL.

[0069] Example 3: Construction of a 3D Curved Surface Model

[0070] IC50 of 2-9g broad-spectrum antibody against thiamphenicol and florfenicol standard curves 20 ~IC 80 Based on this, the initial concentrations of thiamphenicol and florfenicol were prepared as 24 ng / mL and 14 ng / mL, respectively. Then, they were diluted according to a two-fold concentration gradient, with thiamphenicol diluted to 10 concentration gradients and florfenicol diluted to 11 concentration gradients. The concentration solutions of each gradient of thiamphenicol and each gradient of florfenicol were mixed in equal volumes, resulting in a total of 110 concentration combinations, which were added to the microwells (50 μL each, 100 μL in total). Then, 8 μL of 2-9 g of thiamphenicol broad-spectrum antibody probe was added to each well. After standing for 3 minutes, the broad-spectrum antibody time-resolved fluorescent microsphere test strip was inserted for chromatography for 5 minutes. After chromatography, the test strip signal was read, and the read signal value (B / B0) was mapped to the Z-axis in three-dimensional space. The different concentration mixtures of the two drugs were mapped to the bottom surface formed by the X and Y axes, forming a three-dimensional spatial concentration combination signal value point consisting of 110 points. Each point was tested in triplicate. Figure 4 A three-dimensional concentration dataset of 2-9g broad-spectrum antibody against a mixed sample of thiamphenicol and florfenicol was generated. This dataset was then used to construct and apply a three-dimensional surface model. Three methods were employed in this embodiment: Origin, Matlab, and Multilayer Perceptron (MLP). The accuracy, ease of operation, and visual intuitiveness were compared. The three-dimensional surface model obtained by fitting the Gaussian 2D function from Origin and the Matlab software program did not yield ideal predictions for thiamphenicol in actual testing. Therefore, MLP was ultimately selected for modeling and application. The signal value points corresponding to different concentration combinations in three-dimensional space were modeled using the MLP regression model class provided in the Scikit-learn library. The resulting model is the concentration surface model of thiamphenicol and florfenicol. The created MLP regression model was also evaluated. The three-dimensional surface model is shown below. Figure 5 The model evaluation values ​​were MSE = 2.07, RMSE = 1.44, MAE = 0.90, and R0.05. 2 =0.94, indicating that the constructed three-dimensional concentration curve model is good, with little difference from the real perfect model and a high degree of similarity.

[0071] The detection range of the specific antibody against florfenicol, converted and located on a three-dimensional curve model, is the concentration range obtained. The intersection of this concentration range with the detection range of the broad-spectrum antibody against florfenicol is the detection range of the immunoassay method for florfenicol of this invention. That is, the effective detection range of the immunoassay method constructed in this invention for florfenicol is 0.14-0.55 ng / mL, and the effective detection range for thiamphenicol is 0.04-1.69 ng / mL.

[0072] Example 4: Application and Accuracy of the Precise Identification Method for Structural Analogs

[0073] A two-well method was used. First, thiamphenicol and florfenicol standards were diluted to three concentrations within the linear range of the standard curve using 0.2 mol / L PB. Then, 50 μL of each concentration was combined and added to the microwells in equal volumes (total 100 μL). These concentration combinations were: ① 0.1 ng / mL thiamphenicol + 0.14 ng / mL florfenicol, ② 0.30 ng / mL thiamphenicol + 0.20 ng / mL florfenicol, and ③ 1.6 ng / mL thiamphenicol + 0.55 ng / mL florfenicol. These combinations were used for broad-spectrum antibody test strip detection. Then, 0.1 mol / L PB was used to prepare the same drug concentration combination in the same manner and added to the other microwell for florfenicol-specific antibody test strip detection. Add 8 μL of 2-9 g of thiamphenicol broad-spectrum antibody probe to each well of the sample in 0.2 mol / L PB diluent, and add 6 μL of FF15 florfenicol specific antibody probe to each well of the sample in 0.1 mol / L PB diluent. After standing for 3 minutes to mix thoroughly, insert the corresponding time-resolved fluorescent microsphere test strips for chromatography for 5 minutes. After chromatography, read the signal values ​​of both test strips, and perform the detection process in triplicate. Substitute the signal values ​​read from the 2-9 g broad-spectrum antibody test strip and the florfenicol concentration values ​​obtained from the FF15 florfenicol specific antibody test strip into the model for localization. This allows the concentration of thiamphenicol in the mixed drug sample to be located on the three-dimensional curve.

[0074] The final results of the mixed drug samples obtained in this embodiment are shown in Table 1. ① Thiamphenicol: 0.12±0.01 ng / mL, recovery rate 120.00%, coefficient of variation 8.33%; Florfenicol: 0.15±0.01 ng / mL, recovery rate 107.14%, coefficient of variation 6.67%; ② Thiamphenicol: 0.29±0.01 ng / mL, recovery rate 97.67%, coefficient of variation 3.45%; Florfenicol: 0.21±0.02 ng / mL, recovery rate 105.00%, coefficient of variation 9.52%; ③ Thiamphenicol: 1.63±0.11 ng / mL, recovery rate 101.88%, coefficient of variation 6.75%; Florfenicol: 0.60±0.03 ng / mL, recovery rate 109.10%, coefficient of variation 5.00%. This invention demonstrates that the method can accurately distinguish and quantify samples containing both thiamphenicol and florfenicol within a certain concentration range.

[0075] Table 1. Results of the accuracy test for adding recovery method.

[0076]

[0077]

[0078] The above embodiments are one preferred implementation of the present invention, but the implementation of the present invention is not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. An immunoassay method for quantitatively detecting structural analogs in a sample, characterized in that, The sample to be tested contains a first substance and a second substance, which are structural analogs. The immunoassay method includes the following steps: S1. Use broad-spectrum antibodies to detect standard solutions of the first and second substances at known concentrations, with the measured signal value as the ordinate and the concentration as the abscissa, and establish the first and second standard curves respectively. S2. Using a broad-spectrum antibody, different concentrations of a mixture of the first and second substances were detected, and a three-dimensional concentration curve surface model was established using a multilayer perceptron regression model; the three-dimensional concentration curve surface was constructed with the signal value obtained from the detection of the mixture by the broad-spectrum antibody as the Z-axis, and the concentrations of the first and second substances as the X and Y axes, respectively. S3. Use specific antibodies to detect standard solutions of the first substance at known concentrations, and establish a fourth standard curve with the measured signal value as the ordinate and the concentration as the abscissa. S4. Use a broad-spectrum antibody to detect the sample to be tested, and substitute the detection results into the three-dimensional concentration curve surface model obtained in S2 to obtain a series of concentration combination subsets of the two structural analogs; S5. Use a specific antibody to detect the sample to be tested, obtain the concentration of the first substance according to the fourth standard curve, and locate the combination subset of the concentration and the concentration obtained in S4 on the three-dimensional concentration curve surface model obtained in S2 to obtain the concentration value of the second substance. The structural analogues are compounds that exhibit cross-reactivity in immunoassays; The specific antibody can only recognize the first substance; The broad-spectrum antibody can simultaneously recognize the first substance and the second substance; Step S2 involves preparing standard solutions of different concentrations for the first and second substances based on the linear range of the standard curves obtained from the first and second standard curves in S1, and mixing them to obtain a mixed solution. The fluorescence signal value obtained by detecting the mixed solution with a broad-spectrum antibody is used as the Z-axis of the three-dimensional coordinate system. The different concentrations of the two structural analogs are used to form the X and Y axes to form the base, respectively, to establish a three-dimensional concentration dataset. The data points corresponding to different concentration combinations in the three-dimensional concentration dataset are modeled using a multilayer perceptron regression model to obtain a three-dimensional concentration curve surface model.

2. The immunoassay method according to claim 1, characterized in that, The structural analogues are small molecule compounds.

3. The immunoassay method according to claim 1, characterized in that, The first substance is florfenicol, and the second substance is thiamphenicol.

4. The immunoassay method according to claim 1, characterized in that, The broad-spectrum antibody mentioned in step S1 and the specific antibody mentioned in step S3 are monoclonal antibodies.

5. The immunoassay method according to claim 1, characterized in that, The broad-spectrum antibody is a monoclonal antibody that simultaneously recognizes thiamphenicol and florfenicol.

6. The immunoassay method according to claim 1, characterized in that, The specific antibody mentioned in step S3 is a monoclonal antibody that specifically recognizes florfenicol.

7. The immunoassay method according to claim 1, characterized in that, The immunoassay was performed using time-resolved fluorescent microsphere immunochromatography.

8. The immunoassay method according to claim 7, characterized in that, The immunoassay was performed using time-resolved fluorescent microsphere immunoassay strips.

9. The immunoassay method according to claim 3, characterized in that, The effective detection range of the immunoassay method for florfenicol is 0.14–0.55 ng / mL, and the effective detection range for thiamphenicol is 0.04–1.69 ng / mL.

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