Antigen enrichment and cleaning method and system based on antigen capture magnetic bead technology

Abstract

The present invention provides an antigen enrichment and cleaning method and system based on antigen capture magnetic bead technology, which relates to the technical field of immunoassay. The method comprises: using the antigen capture magnetic bead technology to perform antibody coupling on a target antibody prepared according to an antigen to be detected, to obtain antibody-coupled magnetic beads, extracting magnetic bead characteristic parameter information based on antigen enrichment indexes and preparation parameters of the antibody-coupled magnetic beads to screen the antibody-coupled magnetic beads, and after obtaining the target antibody-coupled magnetic beads, specifically capturing a sample to be detected to obtain a labeled enriched antigen, and performing a targeted cleaning treatment on the labeled enriched antigen based on an antigen cleaning scheme. The present invention solves the technical problem that the control of antigen enrichment and cleaning in the prior art is insufficient, resulting in a low final qualified rate of antigen enrichment and cleaning, and realizes the rational and precise control of antigen enrichment and cleaning, thereby improving the qualified rate of antigen enrichment and cleaning as well as the quality and efficiency of immunoassay.

Description

Technical Field

[0001] The present invention relates to the technical field of immunoassay, and in particular to an antigen enrichment and cleaning method and system based on antigen capture magnetic bead technology. Background Art

[0002] With the development of science and technology, especially the development of antigen-antibody immunotechnology, there are many magnetic bead antibody coupling technologies in China, but the labeling effect is not ideal. Antigen-antibody immunoreaction is divided into two methods: competitive method and sandwich method. The sandwich method is a double antibody reaction with an antigen to form an antigen-antibody immune complex. Among them, the coated antibody is cross-linked with the magnetic beads to form a magnetic bead-coated antibody; the labeled antibody is cross-linked with the marker to form an antibody marker. The magnetic bead-coated antibody, antigen, that is, the detection object, and the antibody marker react together to form an antigen-antibody immune complex, and the unbound antibody marker is washed away through a magnetic separation process.

[0003] However, the existing technology lacks sufficient control over antigen enrichment and cleaning, which ultimately leads to a technical problem of low pass rate for antigen enrichment and cleaning. Summary of the invention

[0004] The present application provides an antigen enrichment and cleaning method and system based on antigen capture magnetic bead technology, which is used to solve the technical problem that the control of antigen enrichment and cleaning in the prior art is insufficient, resulting in a low pass rate of antigen enrichment and cleaning.

[0005] In view of the above problems, the present application provides an antigen enrichment and cleaning method and system based on antigen capture magnetic bead technology.

[0006] In the first aspect, the present application provides an antigen enrichment and cleaning method based on antigen capture magnetic bead technology, the method comprising: preparing a target antibody according to the antigen to be detected; using the antigen capture magnetic bead technology to couple the target antibody to obtain antibody-coupled magnetic beads; obtaining an antigen enrichment index, the antigen enrichment index including antigen yield, antigen purity, and antigen characteristics; extracting preparation parameters of the antibody-coupled magnetic beads to obtain magnetic bead characteristic parameter information; screening the antibody-coupled magnetic beads based on the antigen enrichment index and the magnetic bead characteristic parameter information to obtain target antibody-coupled magnetic beads; specifically capturing the sample to be detected based on the target antibody-coupled magnetic beads to obtain labeled enriched antigens; and performing a targeted cleaning treatment on the labeled enriched antigens based on the antigen cleaning scheme.

[0007] In the second aspect, the present application provides an antigen enrichment and cleaning system based on antigen capture magnetic bead technology, the system comprising: a preparation module, the preparation module is used to prepare a target antibody according to the antigen to be detected; an antibody coupling module, the antibody coupling module is used to couple the target antibody using antigen capture magnetic bead technology to obtain antibody-coupled magnetic beads; an index acquisition module, the index acquisition module is used to obtain an antigen enrichment index, the antigen enrichment index includes antigen yield, antigen purity, and antigen characteristics; a preparation parameter extraction module, the preparation parameter extraction module is used to extract preparation parameters of the antibody-coupled magnetic beads to obtain magnetic bead characteristic parameter information; a screening module, the screening module is used to screen the antibody-coupled magnetic beads based on the antigen enrichment index and the magnetic bead characteristic parameter information to obtain target antibody-coupled magnetic beads; a specific capture module, the specific capture module is used to specifically capture the sample to be detected based on the target antibody-coupled magnetic beads to obtain a labeled enriched antigen; a cleaning treatment module, the cleaning treatment module is used to perform a directional cleaning treatment on the labeled enriched antigen based on the antigen cleaning scheme.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] The present application provides an antigen enrichment and cleaning method based on antigen capture magnetic bead technology, which relates to the field of immunoassay technology. It solves the technical problem that the prior art lacks control over antigen enrichment and cleaning, resulting in a low qualified rate of antigen enrichment and cleaning, and realizes rational and precise control over antigen enrichment and cleaning, thereby improving the qualified rate of antigen enrichment and cleaning as well as the quality and efficiency of immunoassay. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A schematic diagram of the process of antigen enrichment and cleaning method based on antigen capture magnetic bead technology is provided for this application;

[0011] Figure 2 This application provides a schematic diagram of the process of obtaining target antibodies in an antigen enrichment and washing method based on antigen capture magnetic bead technology;

[0012] Figure 3 The present application provides a schematic diagram of the process of outputting target antibody-coupled magnetic beads in an antigen enrichment and cleaning method based on antigen capture magnetic bead technology;

[0013] Figure 4 The present application provides a schematic flow chart of an antigen cleaning scheme in an antigen enrichment and cleaning method based on antigen capture magnetic bead technology;

[0014] Figure 5A schematic diagram of the structure of an antigen enrichment and cleaning system based on antigen capture magnetic bead technology is provided for this application.

[0015] Explanation of the reference numerals: preparation module 1, antibody coupling module 2, index acquisition module 3, preparation parameter extraction module 4, screening module 5, specific capture module 6, cleaning treatment module 7. DETAILED DESCRIPTION

[0016] The present application provides an antigen enrichment and cleaning method and system based on antigen capture magnetic bead technology, which is used to solve the technical problem that the control of antigen enrichment and cleaning in the prior art is insufficient, resulting in a low pass rate of antigen enrichment and cleaning.

[0017] Embodiment 1

[0018] like Figure 1 As shown, the embodiment of the present application provides an antigen enrichment and cleaning method based on antigen capture magnetic bead technology, the method comprising:

[0019] Step S100: preparing a target antibody according to the antigen to be detected;

[0020] Specifically, an antigen enrichment and cleaning method based on antigen capture magnetic bead technology provided in an embodiment of the present application is applied to an antigen enrichment and cleaning system based on antigen capture magnetic bead technology. On the basis of the currently obtained antigen to be detected, an antigen epitope prediction model is constructed, and at the same time, the antigen to be detected is subjected to epitope analysis in the constructed antigen epitope prediction model to obtain the antigen epitope sequence. Furthermore, the antigen epitope sequence is used to prepare antibody synthesis by animal immunization, and the preliminary synthetic antibody is determined. The antibody evaluation index is set according to the antibody activity, antibody titer, antibody affinity, antibody linear range, antibody specificity, antibody purity, and antibody stability of the antibody, so that the determined preliminary synthetic antibody is evaluated and screened according to the antibody evaluation index, that is, the antibody that meets the antibody evaluation index is screened, and it is recorded as the target antibody, which serves as an important reference for the later realization of targeted cleaning of the antigen.

[0021] Step S200: using antigen capture magnetic bead technology to perform antibody coupling on the target antibody to obtain antibody-coupled magnetic beads;

[0022] Specifically, since the antigen and the antibody are in a corresponding relationship, the above-mentioned target antibody is anti-coupled using antigen capture magnetic bead technology, that is, the antigen on the cell surface can be combined with the specific monoclonal antibody connected to the magnetic beads. At the same time, in an external magnetic field, the cells connected to the magnetic beads through the antibody are adsorbed and retained in the magnetic field. For example, the size of the magnetic beads is basically the same as the size of the cells, and the surface is bound to a complex of CD3 and CD28 monoclonal antibodies. These monoclonal antibodies can activate human T cell surface molecules and are used for in vitro separation, activation and amplification of human T cells. By simultaneously coupling anti-CD3 and anti-CD28 antibodies to the magnetic beads, the corresponding antibody-coupled magnetic beads are obtained, thereby ensuring the directional cleaning of the antigen.

[0023] Step S300: obtaining antigen enrichment indexes, wherein the antigen enrichment indexes include antigen yield, antigen purity, and antigen characteristics;

[0024] Specifically, since the antigen needs to be enriched, it is necessary to set an index for antigen enrichment. The index needs to refer to the yield of the antigen, the purity of the antigen and the characteristics of the antigen, where the characteristics of the antigen may include antigen type, antigen density, antigen molecular weight, etc. The antigen enrichment index also depends on the specificity of the monoclonal antibody connected to the magnetic beads and the size of the magnetic beads, that is, the magnetism of the magnetic beads. If the magnetism of the magnetic beads is too small, the yield of the magnetic beads will not be high. If the magnetism of the magnetic beads is too large, it will affect the activity of the corresponding cells. The antigen enrichment index is set to lay a solid foundation for the subsequent directional cleaning of the antigen.

[0025] Step S400: extracting preparation parameters of the antibody-coupled magnetic beads to obtain characteristic parameter information of the magnetic beads;

[0026] Specifically, in the process of using antigen capture magnetic bead technology, antibody-coupled magnetic beads need to be prepared, so the preparation parameters of antibody-coupled magnetic beads need to be extracted accordingly. The preparation parameters include the size of the magnetic beads and the properties of the magnetic beads. For example, the size of the antibody-coupled magnetic beads is 0.1-0.45 mm, and the high-quality monoclonal antibody magnetic beads produced by the antibody-coupled magnetic beads have been optimized for the sorting of leukocyte subpopulations. The antibody-coupled magnetic beads coated with specific monoclonal antibodies are added to the cell suspension, so that the antibody-coupled magnetic beads specifically bind to the cell subpopulation with the corresponding antigen. The cells connected with the antibody-coupled magnetic beads obtained by separation can be directly used for functional tests and detection by flow cytometry, and then the characteristic parameter information of the magnetic beads is obtained, so as to achieve a limited effect on the directional cleaning of the antigen.

[0027] Step S500: Screening the antibody-coupled magnetic beads based on the antigen enrichment index and the magnetic bead characteristic parameter information to obtain target antibody-coupled magnetic beads;

[0028] Specifically, the antibody-coupled magnetic beads are screened accordingly based on the magnetic bead characteristic parameter information obtained by extracting the preparation parameters of the antibody-coupled magnetic beads and the set antigen enrichment index. First, the magnetic bead characteristic parameter information is used as the magnetic bead sorting constraint condition, and the magnetic bead sorting space is determined. At the same time, the antigen enrichment index is used as the magnetic bead sorting index. Furthermore, based on the magnetic bead sorting index, the antibody-coupled magnetic beads are globally optimized in the magnetic bead sorting space, that is, antibody-coupled magnetic beads with small particle size, large surface area and good stability are screened, so that the optimal antibody-coupled magnetic beads are recorded as the target antibody-coupled magnetic beads for corresponding screening output, which has a far-reaching impact on the subsequent realization of directional cleaning of the antigen.

[0029] Step S600: specifically capturing the sample to be detected based on the target antibody coupled magnetic beads to obtain labeled enriched antigens;

[0030] Specifically, based on the one-to-one correspondence between antigens and antibodies, on the basis of the target antibody-coupled magnetic beads obtained by screening the antibody-coupled magnetic beads based on the antigen enrichment index and the magnetic bead characteristic parameter information, the antigen of the current sample to be tested is specifically captured, and the captured antigens corresponding to the antibodies in the current target antibody-coupled magnetic beads are enriched, and the enriched antigens are labeled at the same time, and then the corresponding labeled enriched antigens are obtained, which has a promoting effect on the directional cleaning of the antigen.

[0031] Step S700: Based on the antigen cleaning scheme, the labeled enriched antigens are subjected to a directional cleaning process.

[0032] Specifically, since the antigens have been enriched as mentioned above and the corresponding labeled enriched antigens have been obtained, and in the sample to be tested, the labeled antigens in the sample to be tested need to be cleared, so it is necessary to formulate a corresponding antigen cleaning scheme. First, the enrichment characteristic information of the labeled enriched antigens needs to be obtained, and then the enrichment characteristic information is divided into the degree of cleaning, and the corresponding antigen cleaning level is obtained. Furthermore, based on the enrichment characteristic information of the antigen, the antigen clearance in the sample to be tested is planned to obtain an antigen cleaning route, and then an antigen cleaning scheme is formulated according to the antigen cleaning level and the antigen cleaning route. Finally, based on the formulated antigen cleaning scheme, the above-mentioned labeled enriched antigens are cleaned in a determined direction, thereby realizing the rational and precise control of antigen enrichment and cleaning, thereby improving the qualified rate of antigen enrichment and cleaning as well as the quality and efficiency of immunoassay.

[0033] Furthermore, if Figure 2 As shown, step S100 of the present application also includes:

[0034] Step S110: constructing an antigen epitope prediction model;

[0035] Step S120: performing epitope analysis on the antigen to be detected based on the antigen epitope prediction model to obtain an antigen epitope sequence;

[0036] Step S130: preparing antibodies against the antigen epitope sequence by animal immunization to determine preliminary synthesized antibodies;

[0037] Step S140: Obtaining antibody evaluation indicators, wherein the antibody evaluation indicators include activity, potency, affinity, linear range, specificity, purity, and stability;

[0038] Step S150: evaluating and screening the preliminary synthesized antibodies according to the antibody evaluation index to obtain the target antibody.

[0039] Specifically, since it is necessary to prepare the target antibody corresponding to the antigen to be detected, the antigen epitope prediction model is first constructed. The construction process can be: to predict the antigen epitope, it is first necessary to extract the associated parameters, and the associated parameters may include the hydrophilicity of the antigen, the surface accessibility of the antigen, the plasticity of the antigen, the antigenicity of the antigen, the secondary structure of the antigen, etc., so as to obtain the epitope prediction parameters on the antigen. Furthermore, based on the epitope prediction parameters, data mining is performed and the mined data is summarized and integrated to complete the construction of the antigen epitope sequence database, and then the epitope prediction parameters and the antigen epitope sequence database are correspondingly identified as model sample information, and then the network model is supervised and trained based on the model sample information to obtain the corresponding antigen epitope prediction model.

[0040] Furthermore, in the obtained antigen epitope prediction model, the antigen epitopes in the antigen to be detected are analyzed accordingly, and the epitopes on the current antigen to be detected are sorted from large to small, and then the antigen epitope sequence of the current antigen to be detected is obtained, and the antibody synthesis of the antibody corresponding to the current antigen is prepared for the obtained antigen epitope sequence based on animal immunization, and the antibody that has been prepared and synthesized is recorded as a preliminary synthetic antibody, so that the evaluation index of the current antibody is determined based on antibody activity, antibody titer, antibody affinity, antibody linear range, antibody specificity, antibody purity, and antibody stability, and then the preliminary synthetic antibody is evaluated based on the antibody evaluation index, and then the weight analysis of each index in the obtained antibody evaluation index is performed, and the antibody performance evaluation information is correspondingly corrected based on the analyzed evaluation index weight distribution information, and finally the obtained antibody performance correction information is screened according to the antibody performance benchmark, and the screened antibody is recorded as a target antibody for output, so as to achieve the technical effect of providing an important basis for the later realization of directional cleaning of the antigen.

[0041] Furthermore, step S110 of the present application includes:

[0042] Step S111: extracting associated parameters for antigen epitope prediction to obtain epitope prediction parameters, wherein the epitope prediction parameters include hydrophilicity, surface accessibility, plasticity, antigenicity, and secondary structure;

[0043] Step S112: performing data mining based on the epitope prediction parameters to obtain an antigen epitope sequence database;

[0044] Step S113: marking the epitope prediction parameters and the antigen epitope sequence database as model sample information;

[0045] Step S114: Performing supervised training of a network model based on the model sample information to obtain the antigen epitope prediction model.

[0046] Specifically, based on the hydrophilicity of the antigen, the surface accessibility of the antigen, the plasticity of the antigen, the antigenicity of the antigen, and the secondary structure of the antigen, they are summarized and integrated and recorded as the epitope prediction parameters. The hydrophilicity of the antigen refers to the fact that the hydrophobic residues of the amino acids in the protein antigen are generally inside the protein, and the hydrophilic residues exist on the surface; the hydrophilic part of the protein is closely related to the protein antigen epitope, but the highly hydrophilic part is not necessarily the epitope, and the epitope is not necessarily the hydrophilic part. The surface accessibility of the antigen refers to the possibility that the amino acid residues in the protein antigen are contacted by solvent molecules. The plasticity of the antigen means that the conformation of the protein antigen is not constant, and its polypeptide chain skeleton has a certain degree of activity. The amino acid residues with strong activity are the sites with high plasticity and are easy to form antigen epitopes. The antigenicity of the antigen refers to the description of each amino acid by the frequency of its appearance in the antigenic region. This frequency is divided by the frequency of each amino acid in all proteins to deduce this scale value. The secondary structure of the antigen refers to the protein β-turn structure as a protruding structure, which often appears on the surface of the protein antigen, which is conducive to chimerism with antibodies and is more likely to become an antigen epitope.

[0047] Based on the obtained epitope prediction parameters, data mining is performed, that is, the existing antigen epitope data is mined through big data. The existing antigen epitope data refers to the total number of epitopes that bind to the antibody on the surface of the antigen, wherein the data mined from the existing antigen epitope data include but are not limited to conformational epitopes, sequential epitopes, T cell epitopes, functional epitopes, cryptic epitopes, hapten epitopes and carrier epitopes, etc. The antigen epitope sequence database is constructed from the data collected from the existing antigen epitope data mined as above, and the obtained epitope prediction parameters and the antigen epitope sequence database are recorded as model sample information together, and are labeled. Identification, and then based on the identified model sample information, supervised training is performed on the antigen epitope prediction model, that is, each group of training data in the current training data set includes model sample information; its supervised data set is supervised data that corresponds to the training data set one by one, and each group of training data in the training data set is input into the antigen epitope prediction model, and the output of the antigen epitope prediction model is supervised and adjusted through the supervised data corresponding to this group of training data. When the output result of the antigen epitope prediction model is consistent with the supervised data, the training of the current group is completed, and the training of all the training data in the training data set is completed, and the training of the antigen epitope prediction model is completed.

[0048] In order to ensure the accuracy of the antigen epitope prediction model, the antigen epitope prediction model can be tested using a test data set. For example, the test accuracy can be set to 80%. When the test accuracy of the test data set meets 80%, the antigen epitope prediction model is constructed.

[0049] Furthermore, step S150 of the present application includes:

[0050] Step S151: evaluating the preliminary synthesized antibody based on the antibody evaluation index to obtain antibody performance evaluation information;

[0051] Step S152: performing a weight analysis on each indicator in the antibody evaluation index to obtain evaluation indicator weight distribution information;

[0052] Step S153: modifying the antibody performance evaluation information based on the evaluation index weight distribution information to obtain antibody performance modified evaluation information;

[0053] Step S154: screening the antibody performance correction evaluation information according to the antibody performance benchmark to obtain the target antibody.

[0054] Specifically, the current antibody evaluation indicators are determined based on antibody activity, antibody titer, antibody affinity, antibody linear range, antibody specificity, antibody purity, and antibody stability. Based on the antibody evaluation indicators, the preliminary synthetic antibodies determined by antibody synthesis preparation of antigen epitope sequences using animal immunization are evaluated accordingly, that is, the performance level of the current preliminary synthetic antibodies in each parameter in the antibody evaluation indicators is evaluated, and the evaluation results are recorded as antibody performance evaluation information. At the same time, a weight analysis is performed on each indicator in the obtained antibody evaluation indicators, that is, the weight distribution of each indicator parameter can be: the secondary structure weight accounts for 40%, the surface accessibility and flexibility are 15% each, and the hydrophilicity accounts for 30%. Therefore, when predicting antigen epitopes, a variety of different methods and software are referred to to make the prediction results more accurate, and the obtained antibody performance evaluation information is further corrected for deviations based on the set evaluation index weight distribution information, that is, the evaluation results in the antibody performance evaluation information corresponding to the current antibody are corrected accordingly based on the weight ratio of different parameters, and then the antibody performance corrected evaluation information is obtained, and finally the above-mentioned antibody performance corrected evaluation information is corrected and screened according to the antibody performance benchmark in the big data, and the corrected and screened results are used as the current target antibodies to ensure high efficiency in the targeted cleaning of antigens.

[0055] Furthermore, if Figure 3 As shown, step S500 of the present application also includes:

[0056] Step S510: using the magnetic bead characteristic parameter information as magnetic bead sorting constraint conditions, wherein the magnetic bead characteristic parameter information includes magnetic bead particle size, surface area, and stability;

[0057] Step S520: determining the magnetic bead sorting space according to the magnetic bead sorting constraint conditions;

[0058] Step S530: using the antigen enrichment index as a magnetic bead sorting index;

[0059] Step S540: performing global optimization in the magnetic bead sorting space based on the magnetic bead sorting index, and screening and outputting the target antibody-coupled magnetic beads.

[0060] Specifically, the magnetic bead characteristic parameter information obtained by extracting the preparation parameters of the antibody-coupled magnetic beads is used as the constraint conditions of the current magnetic bead sorting, and the magnetic bead characteristic parameter information includes the magnetic bead particle size, magnetic bead surface area, and magnetic bead stability. At the same time, the historical magnetic bead sorting records are collected, and the obtained magnetic bead sorting constraints are used as a set of magnetic bead sorting feature points, and the collected historical magnetic bead sorting optimization records are matched accordingly to obtain a set of historical magnetic bead characteristic sorting records, and the magnetic bead sorting space is set and determined, and the obtained antigen enrichment index is used as a magnetic bead sorting index, and the magnetic bead sorting index is used as a target, and a global optimization is performed in the determined magnetic bead sorting space. The global optimization can be based on the global optimization in the legacy algorithm to obtain the location of the global optimal solution of the expected target antibody-coupled magnetic beads.

[0061] The obtained target antibody-coupled magnetic beads are calculated according to the genetic algorithm to obtain the expected target antibody-coupled magnetic beads, the target antibody-coupled magnetic beads are obtained by optimal screening based on the magnetic bead sorting index in the set magnetic bead sorting space, and the obtained expected target antibody-coupled magnetic beads correspond to the obtained actual target antibody-coupled magnetic beads one by one, and the obtained actual target antibody-coupled magnetic beads are obtained based on the magnetic bead sorting index in the magnetic bead sorting space, and the expected target antibody-coupled magnetic beads are compared with the actual target antibody-coupled magnetic beads to obtain the antibody-coupled magnetic bead index comparison result of the two, and further generate index feedback data according to the obtained intelligence comparison result, wherein when the expected target antibody-coupled magnetic beads are corrected using the index feedback data, based on the comparison of the above-mentioned expected target antibody-coupled magnetic beads and the actual target antibody-coupled magnetic beads, the predicted value with the closest similarity is obtained, and the corresponding training data is the training data of the magnetic bead sorting index, and finally the expected target antibody-coupled magnetic beads selected by optimal screening are output as the current target antibody-coupled magnetic beads, so as to finally achieve the technical effect of providing a reference for the directional cleaning of the antigen.

[0062] Furthermore, step S520 of the present application includes:

[0063] Step S521: collecting and obtaining historical magnetic bead sorting records;

[0064] Step S522: using the magnetic bead sorting constraint conditions as a magnetic bead sorting feature point set;

[0065] Step S523: matching the historical magnetic bead sorting optimization records based on the magnetic bead sorting feature point set to obtain a historical magnetic bead feature sorting record set;

[0066] Step S524: Based on the historical magnetic bead feature sorting record set, the magnetic bead sorting space is set.

[0067] Specifically, the records of magnetic bead sorting before the current moment are extracted, and then the obtained magnetic bead sorting constraints are used as a set of magnetic bead sorting feature points, that is, the characteristics of magnetic bead sorting are summarized in the process of magnetic bead sorting. Furthermore, the historical magnetic bead sorting records are first matched and integrated through the magnetic bead sorting feature points. The historical magnetic bead sorting records include magnetic bead sorting characteristics and their antigen enrichment information, that is, a sorting model is constructed based on the data of the historical magnetic bead sorting records, and then the magnetic bead parameters are optimized, so as to obtain the corresponding historical magnetic bead sorting optimization records, and then the obtained historical magnetic bead sorting optimization records are matched based on the set of magnetic bead sorting feature points, and the historical magnetic bead feature sorting records that match the historical magnetic bead sorting optimization records in the magnetic bead sorting feature point set are extracted and summarized, and finally, on the basis of the summarized set of historical magnetic bead feature sorting records, the current magnetic bead sorting space is determined and set to achieve the technical effect of directional cleaning of antigens.

[0068] Furthermore, if Figure 4 As shown, step S700 of the present application also includes:

[0069] Step S710: obtaining enrichment characteristic information of the labeled enriched antigen;

[0070] Step S720: classifying the enrichment characteristic information according to the degree of cleaning to obtain the antigen cleaning level;

[0071] Step S730: planning an antigen cleaning route based on the enrichment characteristic information;

[0072] Step S740: generating the antigen cleaning scheme according to the antigen cleaning level and the antigen cleaning route.

[0073] Specifically, based on the range of antigen enrichment, the distribution of antigens, and the number of antigens, the enrichment characteristics of the marked enriched antigens are screened accordingly, and the screened enrichment characteristic information is divided into the degree of cleaning. For example, if the cleaning degree of the antigen is 80% or above, it is regarded as primary cleaning, if the clarity of the antigen is 60%-80%, it is regarded as secondary cleaning, and if the cleaning degree of the antigen is 60% or below, it is regarded as tertiary cleaning, thereby obtaining the corresponding antigen cleaning level. Furthermore, based on the enrichment characteristic information of the antigen, the antigen clearance in the sample to be tested is planned. For example, according to the number of antigens, the difficulty of antigen cleaning, the number of antigen cleaning times, and the distance between antigens, the antigen cleaning route is formulated, and then the antigen cleaning level and the antigen cleaning route are integrated to generate the corresponding antigen cleaning plan, thereby realizing the rational and precise control of antigen enrichment and cleaning, thereby improving the qualified rate of antigen enrichment and cleaning as well as the quality and efficiency of immunoassay.

[0074] Embodiment 2

[0075] Based on the same inventive concept as the antigen enrichment and cleaning method based on antigen capture magnetic bead technology in the aforementioned embodiment, Figure 5 As shown, the present application provides an antigen enrichment and cleaning system based on antigen capture magnetic bead technology, the system comprising:

[0076] Preparation module 1, the preparation module 1 is used to prepare the target antibody according to the antigen to be detected;

[0077] Antibody coupling module 2, the antibody coupling module 2 is used to perform antibody coupling on the target antibody using antigen capture magnetic bead technology to obtain antibody-coupled magnetic beads;

[0078] An index obtaining module 3, wherein the index obtaining module 3 is used to obtain an antigen enrichment index, wherein the antigen enrichment index includes an antigen yield, an antigen purity, and an antigen characteristic;

[0079] A preparation parameter extraction module 4, wherein the preparation parameter extraction module 4 is used to extract preparation parameters of the antibody-coupled magnetic beads to obtain characteristic parameter information of the magnetic beads;

[0080] A screening module 5, wherein the screening module 5 is used to screen the antibody-coupled magnetic beads based on the antigen enrichment index and the magnetic bead characteristic parameter information to obtain target antibody-coupled magnetic beads;

[0081] A specific capture module 6, which is used to specifically capture the sample to be detected based on the target antibody coupled magnetic beads to obtain labeled enriched antigens;

[0082] The cleaning module 7 is used to perform a directional cleaning process on the labeled enriched antigen based on an antigen cleaning scheme.

[0083] Furthermore, the system also includes:

[0084] A model building module, wherein the model building module is used to build an antigen epitope prediction model;

[0085] An epitope analysis module, which is used to perform epitope analysis on the antigen to be detected based on the antigen epitope prediction model to obtain an antigen epitope sequence;

[0086] An antibody synthesis preparation module, which is used to synthesize and prepare antibodies against the antigen epitope sequence by animal immunization to determine preliminary synthesized antibodies;

[0087] An antibody evaluation index module, which is used to obtain antibody evaluation indicators, including activity, potency, affinity, linear range, specificity, purity, and stability;

[0088] An evaluation and screening module is used to evaluate and screen the preliminary synthesized antibodies according to the antibody evaluation index to obtain the target antibody.

[0089] Furthermore, the system also includes:

[0090] An associated parameter extraction module, which is used to extract associated parameters for antigen epitope prediction to obtain epitope prediction parameters, wherein the epitope prediction parameters include hydrophilicity, surface accessibility, plasticity, antigenicity, and secondary structure;

[0091] A data mining module, the data mining module is used to perform data mining based on the epitope prediction parameters to obtain an antigen epitope sequence database;

[0092] An information identification module, the information identification module is used to identify the epitope prediction parameters and the antigen epitope sequence database as model sample information;

[0093] A training module is used to perform supervised training of a network model based on the model sample information to obtain the antigen epitope prediction model.

[0094] Furthermore, the system also includes:

[0095] An evaluation module, wherein the evaluation module is used to evaluate the preliminary synthesized antibody based on the antibody evaluation index to obtain antibody performance evaluation information;

[0096] A weight analysis module, which is used to perform a weight analysis on each indicator in the antibody evaluation index to obtain evaluation index weight distribution information;

[0097] A correction module, the correction module is used to correct the antibody performance evaluation information based on the evaluation index weight distribution information to obtain antibody performance correction evaluation information;

[0098] An information screening module is used to screen the antibody performance correction evaluation information according to the antibody performance benchmark to obtain the target antibody.

[0099] Furthermore, the system also includes:

[0100] A constraint condition module, wherein the constraint condition module is used to use the magnetic bead characteristic parameter information as a magnetic bead sorting constraint condition, wherein the magnetic bead characteristic parameter information includes magnetic bead particle size, surface area, and stability;

[0101] A space determination module, the space determination module is used to determine the magnetic bead sorting space according to the magnetic bead sorting constraint conditions;

[0102] A sorting index module, wherein the sorting index module is used to use the antigen enrichment index as a magnetic bead sorting index;

[0103] A global optimization module is used to perform global optimization in the magnetic bead sorting space based on the magnetic bead sorting index, and screen and output the target antibody-coupled magnetic beads.

[0104] Furthermore, the system also includes:

[0105] A sorting record collection module, which is used to collect and obtain historical magnetic bead sorting records;

[0106] A sorting constraint condition module, wherein the sorting constraint condition module is used to use the magnetic bead sorting constraint condition as a magnetic bead sorting feature point set;

[0107] A record matching module, the record matching module is used to match the historical magnetic bead sorting optimization record based on the magnetic bead sorting feature point set to obtain a historical magnetic bead feature sorting record set;

[0108] A sorting record set module, wherein the sorting record set module is used to set the magnetic bead sorting space based on the historical magnetic bead feature sorting record set.

[0109] Furthermore, the system also includes:

[0110] A feature acquisition module, the feature acquisition module is used to obtain enrichment feature information of the marker enriched antigen;

[0111] A cleaning degree classification module, wherein the cleaning degree classification module is used to classify the enrichment characteristic information into cleaning degrees to obtain an antigen cleaning grade;

[0112] A route module, the route module is used to plan an antigen cleaning route based on the enrichment feature information;

[0113] A scheme module is used to generate the antigen cleaning scheme according to the antigen cleaning level and the antigen cleaning route.

[0114] Through the above-mentioned detailed description of an antigen enrichment and cleaning method based on antigen capture magnetic bead technology, a person skilled in the art can clearly know that an antigen enrichment and cleaning system based on antigen capture magnetic bead technology in this embodiment is described. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0115] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An antigen enrichment and cleaning method based on antigen capture magnetic bead technology, characterized in that: The method comprises: According to the antigen to be detected, prepare and obtain the target antibody; Using antigen capture magnetic bead technology to perform antibody coupling on the target antibody to obtain antibody-coupled magnetic beads; Obtaining antigen enrichment indicators, wherein the antigen enrichment indicators include antigen yield, antigen purity, and antigen characteristics; Extracting preparation parameters of the antibody-coupled magnetic beads to obtain characteristic parameter information of the magnetic beads; Screening the antibody-coupled magnetic beads based on the antigen enrichment index and the magnetic bead characteristic parameter information to obtain target antibody-coupled magnetic beads; Based on the target antibody coupled magnetic beads, the sample to be detected is specifically captured to obtain a labeled enriched antigen; Based on the antigen cleaning scheme, the labeled enriched antigen is subjected to a directional cleaning treatment; Wherein, the antibody-coupled magnetic beads are screened based on the antigen enrichment index and the magnetic bead characteristic parameter information to obtain the target antibody-coupled magnetic beads, including: Using the magnetic bead characteristic parameter information as magnetic bead sorting constraint conditions, wherein the magnetic bead characteristic parameter information includes magnetic bead particle size, surface area, and stability; Determining the magnetic bead sorting space according to the magnetic bead sorting constraint conditions; Using the antigen enrichment index as a magnetic bead sorting index; Performing global optimization in the magnetic bead sorting space based on the magnetic bead sorting index, screening and outputting the target antibody-coupled magnetic beads; Wherein, determining the magnetic bead sorting space according to the magnetic bead sorting constraint condition comprises: Collect and obtain historical magnetic bead sorting records; The magnetic bead sorting constraint condition is used as a magnetic bead sorting feature point set; Matching the historical magnetic bead sorting optimization records based on the magnetic bead sorting feature point set to obtain a historical magnetic bead feature sorting record set; Based on the historical magnetic bead feature sorting record set, setting the magnetic bead sorting space; Wherein, obtaining the antigen cleaning scheme comprises: Obtaining enrichment characteristic information of the labeled enriched antigen; Classifying the degree of cleaning of the enriched characteristic information to obtain an antigen cleaning grade; Based on the enrichment characteristic information, planning an antigen cleaning route; The antigen cleaning scheme is generated according to the antigen cleaning level and the antigen cleaning route.

2. The method according to claim 1, characterized in that The method of preparing the target antibody according to the antigen to be detected comprises: Construct an antigen epitope prediction model; Performing epitope analysis on the antigen to be detected based on the antigen epitope prediction model to obtain an antigen epitope sequence; Using animal immunization to prepare antibodies against the antigen epitope sequence, and determining preliminary synthetic antibodies; Obtaining antibody evaluation indicators, wherein the antibody evaluation indicators include activity, potency, affinity, linear range, specificity, purity, and stability; The preliminary synthesized antibodies are evaluated and screened according to the antibody evaluation index to obtain the target antibody.

3. The method according to claim 2, characterized in that The constructing of the antigen epitope prediction model comprises: Extracting associated parameters for antigen epitope prediction to obtain epitope prediction parameters, wherein the epitope prediction parameters include hydrophilicity, surface accessibility, plasticity, antigenicity, and secondary structure; Perform data mining based on the epitope prediction parameters to obtain an antigen epitope sequence database; Identify the epitope prediction parameters and the antigen epitope sequence database as model sample information; Based on the model sample information, network model supervision training is performed to obtain the antigen epitope prediction model.

4. The method according to claim 2, characterized in that The step of evaluating and screening the preliminary synthesized antibodies according to the antibody evaluation index to obtain the target antibody comprises: Evaluating the preliminary synthesized antibody based on the antibody evaluation index to obtain antibody performance evaluation information; Performing a weight analysis on each indicator in the antibody evaluation index to obtain evaluation indicator weight distribution information; Modifying the antibody performance evaluation information based on the evaluation index weight distribution information to obtain antibody performance modified evaluation information; The antibody performance correction evaluation information is screened according to the antibody performance benchmark to obtain the target antibody.

5. An antigen enrichment and cleaning system based on antigen capture magnetic bead technology, characterized in that: For executing the method according to any one of claims 1 to 4, the system comprises: A preparation module, which is used to prepare a target antibody according to the antigen to be detected; An antibody coupling module, which is used to perform antibody coupling on the target antibody using antigen capture magnetic bead technology to obtain antibody-coupled magnetic beads; An index acquisition module, which is used to obtain antigen enrichment indicators, including antigen yield, antigen purity, and antigen characteristics; A preparation parameter extraction module, which is used to extract preparation parameters of the antibody-coupled magnetic beads to obtain characteristic parameter information of the magnetic beads; A screening module, wherein the screening module is used to screen the antibody-coupled magnetic beads based on the antigen enrichment index and the magnetic bead characteristic parameter information to obtain target antibody-coupled magnetic beads; A specific capture module, which is used to specifically capture the sample to be detected based on the target antibody coupled magnetic beads to obtain labeled enriched antigens; A cleaning processing module is used to perform a directional cleaning process on the labeled enriched antigen based on an antigen cleaning scheme.

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