Riemerella anatipestifer bivalent inactivated vaccine strain screening and immunogenicity evaluation method and system

Abstract

The invention relates to the technical field of biological product cultivation, in particular to a riemerella anatipestifer bivalent inactivated vaccine strain screening and immunogenicity evaluation method which comprises the following steps: S1, vaccine strain screening; the method comprises the following steps: S1-1, separating and identifying pathogenic bacteria, namely collecting pathological tissue samples of liver and spleen of an affected duck, separating riemerella anatipestifer by virtue of a traditional culture method, analyzing and identifying the species of the strain by virtue of a PCR amplification technology and a 16S rRNA sequence, and further performing serotyping on the pathogenic bacteria. The screening and immunogenicity evaluation method of the riemerella anatipestifer bivalent inactivated vaccine is comprehensively optimized through a molecular biological technology, immunological evaluation and a data-driven evaluation system. Compared with the prior art, the scheme has remarkable advantages in the aspects of vaccine strain screening and evaluation efficiency and precision and data management and analysis, and provides solid technical support for development and application of vaccines.

Description

Technical Field

[0001] The invention relates to the technical field of veterinary biological product cultivation, and in particular to a method and system for screening Riemerella anatipestifer bivalent inactivated vaccine strains and evaluating immunogenicity. Background Art

[0002] Riemerella anatipestifer disease is commonly known as duck infectious serositis. Riemerella anatipestifer (RA) infection is a highly pathogenic, contact-contagious disease of many poultry species, including ducks, geese, and turkeys. It is a bacterial infectious disease that seriously harms ducklings and young ducks aged 2 to 7 weeks. The disease is more common in ducklings aged 10 to 35 days, with an incidence rate of up to 90% and a mortality rate of 5% to 75%. It is one of the major infectious diseases affecting the duck farming industry. The disease is widely present in duck farms around the world. Once the disease occurs in a duck farm, it is difficult to completely eliminate the infection. At present, the control of the disease mainly relies on antibiotic treatment, but with the increasing resistance of the bacteria to multiple antibiotics and the need for food safety, the need to develop a vaccine to prevent the disease in advance is becoming more and more urgent;

[0003] In the prior art, the screening of Riemerella anatipestifer vaccine strains usually relies on animal experiments and basic antibody detection. This traditional method has the following disadvantages:

[0004] Time-consuming and costly: The experimental cycle is long and requires a large amount of animal experiments and training resources.

[0005] Low screening efficiency: The lack of efficient molecular screening technology leads to low screening efficiency of excellent vaccine strains.

[0006] Single evaluation criteria: When evaluating immunogenicity, it mainly relies on antibody titer testing, ignoring the contribution of cellular immunity and lacking a comprehensive evaluation of the multi-dimensional immune response of the vaccine.

[0007] Therefore, a method and system for screening and immunogenicity evaluation of Riemerella anatipestifer bivalent inactivated vaccine strains was proposed. Summary of the invention

[0008] The purpose of the present invention is to provide a method and system for screening and immunogenicity evaluation of bivalent inactivated vaccine strains of Riemerella anatipestifer, which is optimized on the basis of the existing technology, combined with molecular biology technology, immunological analysis and big data modeling, for screening the optimal bivalent inactivated vaccine strain and systematically evaluating its immunogenicity. Compared with the existing technology, this method is more accurate and efficient, and reduces manual intervention and experimental costs to solve the problems raised in the above background technology.

[0009] To achieve the above object, the present invention provides the following technical solution: a method for screening a bivalent inactivated Riemerella anatipestifer vaccine strain and evaluating immunogenicity, comprising the following steps:

[0010] S1. Vaccine strain screening method;

[0011] S1-1. Isolation and identification of pathogens. Patients were collected from the liver and spleen of infected ducks. Riemerella anatipestifer was isolated by traditional culture. The strains were identified by PCR amplification and 16S rRNA sequence analysis. The pathogens were further serotyped.

[0012] S1-2, Molecular screening of bivalent vaccine strains, genetic diversity analysis of isolated Riemerella anatipestifer strains was performed through multi-locus sequence typing and whole genome sequencing molecular marker technology, and two representative strains of different serotypes, serotype 1 and serotype 2, were screened out;

[0013] S1-3, in vitro antigen expression detection, using immunoblotting and enzyme-linked immunosorbent assay methods to detect the expression of the main antigenic proteins of the strains, and screen out high-expression strains expressing the main protective antigens, such as OMP protein and LPS, for vaccine development;

[0014] S2. Immunogenicity assessment methods;

[0015] S2-1. Establishment of animal model: Select healthy ducklings, such as 1-day-old or 3-week-old ducklings, for immunization experiments. Use different selected bivalent inactivated vaccine strains for immunization, and set up high-dose, medium-dose, low-dose groups and a blank control group;

[0016] S2-2, Antibody titer evaluation, regularly test the antibody titer in the serum of each group of ducklings after immunization by indirect ELISA, test the IgG and IgM levels respectively, and draw the antibody generation curve;

[0017] S2-3, Cellular immune analysis, flow cytometry was used to analyze the ratio of CD4+T cells and CD8+T cells in the peripheral blood of ducklings after immunization to evaluate the cellular immune response;

[0018] S2-4, protection experiment, at an appropriate time after vaccination, such as 14 days, 28 days, conduct a challenge experiment, record the morbidity and mortality of ducklings in different dose groups, and evaluate the protective efficacy of the vaccine strain;

[0019] S2-5. Evaluation of the persistence of immune memory. Follow-up tests are conducted on each group of ducklings at different times after immunization, such as 30 days, 60 days, and 90 days, to evaluate the persistence of immune memory.

[0020] Preferably, the S1 vaccine strain screening method adopts high-throughput screening technology, which integrates gene editing screening tools, CRISPR-Cas9 and transcriptome analysis technology on the basis of the original screening method based on multi-locus sequence typing and whole genome sequencing to achieve high-precision screening of vaccine strain genes and expression levels.

[0021] Preferably, the CRISPR screening: by using gene editing technology, specific genes of different vaccine strains are knocked out or overexpressed, the effects on immunogenicity and antigen expression are observed, and genotype strains that can induce high levels of immune responses are screened out.

[0022] Preferably, the transcriptome analysis: uses RNA-seq technology to detect the gene expression profiles of different strains, and screens strains that can highly express major protective antigens, OMP, and LPS during the infection process to ensure that the vaccine strain has strong antigenicity.

[0023] Preferably, in the S2-2, antibody titer evaluation step, cytokine detection and memory cell evaluation are further introduced on the basis of the original antibody titer and T cell immune detection to more comprehensively evaluate the immunogenicity of the vaccine.

[0024] Preferably, the cytokine detection: multiple ELISA or flow cytometry is used to detect the secretion levels of IL-2, IFN-γ, and TNF-α cytokines after immunization to evaluate the immune strength stimulated by the vaccine.

[0025] Preferably, the memory cell analysis: uses flow cytometry to detect central memory T cells and effector memory T cells formed after immunization to predict the long-term protective efficacy of the vaccine.

[0026] Preferably, the antigen-specific immune analysis: combining the molecular screening results, targeting the antigen specificity of different vaccine strains, using an antigen peptide library to design an immune response analysis tool to simulate the immune effect of the vaccine strain in actual infection;

[0027] Antigen-specific T cell analysis:

[0028] Aiming at the screened dominant antigen, OMP protein, a peptide library was designed and used to stimulate T cells of immunized ducks to analyze the intensity of their immune response and help evaluate the antigenic efficacy of the vaccine.

[0029] The Riemerella anatipestifer bivalent inactivated vaccine strain screening and immunogenicity assessment system includes data input and management: the multi-dimensional data of strain screening, antigen expression, antibody titer, cellular immunity, and challenge experiment are entered into the system for unified management and analysis;

[0030] Data model construction: Use machine learning models to train the vaccine strain screening results and immunogenicity assessment data, predict the immune protection efficacy of the vaccine strain, simulate the time dynamics of different immune responses after vaccination, and evaluate the vaccine protection period through mathematical modeling;

[0031] Result output and optimization: The system automatically generates immunogenicity analysis reports for each vaccine strain based on input data, recommends the best vaccine strain combination, and outputs the protective efficacy prediction data of the bivalent vaccine;

[0032] Real-time data monitoring and feedback: Build a real-time data monitoring and feedback system to automatically record and analyze vaccine strain screening, antibody production, cellular immunity and virus protection experiment data. The system automatically generates optimization suggestions.

[0033] Preferably, the real-time data monitoring and feedback includes a real-time feedback optimization model:

[0034] The system automatically adjusts the experimental process and evaluation criteria based on the real-time collected data. For example, it automatically recommends adjustments to the vaccination dose based on changes in antibody titers.

[0035] Dynamic evaluation and optimization of vaccine protection effect: Dynamic modeling of long-term protection effect:

[0036] Immune memory and protection persistence assessment: In the immunogenicity assessment system, the dynamic model of immune memory is introduced to dynamically simulate the length of the protection period by tracking the changes in long-term immune memory cells after vaccination;

[0037] Formula description:

[0038] M(t)=M0·e -λt

[0039] Where: M(t) is the number of memory T cells at time t, M0 is the initial number of memory T cells, and λ is the memory cell decay rate;

[0040] Modeling formula for long-term protection effect:

[0041] Predict the protective effect of vaccines at different time points through comprehensive simulation of cellular immunity and antibody production:

[0042]

[0043] Where: A(t) is the antibody titer, M(t) is the number of memory T cells, A threshold and M threshold are the protection thresholds for antibodies and memory T cells, respectively;

[0044] Multi-factor dynamic simulation of virus challenge experiment: infection exposure and pathogen load modeling:

[0045] A multi-factor dynamic model was established for different challenge intensities and pathogen loads to simulate the protective effect of vaccinated ducks under different pathogen exposure levels. By simulating the effects of different environments and pathogen loads, the actual protective ability of the vaccine in a complex environment was predicted.

[0046] Infection Exposure Model:

[0047] I(t)=P exposure ·(1-e -γA(t) )·B(t)

[0048] Where: I(t) is the infection probability at time t, P exposure is the probability of pathogen exposure, γ is the neutralization effect constant of antibodies on pathogens, and B(t) is the change of pathogen load over time;

[0049] Automated analysis and optimization of challenge experiment data: Use automated data analysis tools to conduct statistical analysis on the morbidity and mortality rates of different doses and exposure times in the challenge experiment, optimize the challenge experiment process based on vaccine dose and immunization time, generate experimental reports in real time, and provide optimization suggestions.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] 1. Through molecular biology technology, immunological evaluation and data-driven evaluation system, the screening and immunogenicity evaluation methods of Riemerella anatipestifer bivalent inactivated vaccine have been fully optimized. Compared with existing technologies, this solution has significant advantages in vaccine strain screening and evaluation efficiency, accuracy, and data management and analysis, providing solid technical support for vaccine development and application;

[0052] 2. Through high-throughput screening tools (such as CRISPR and RNA-seq) and automated screening platforms, vaccine strains with high immunogenicity can be screened quickly and accurately, reducing experimental time and labor costs.

[0053] By combining cytokine and memory cell assessments, a more comprehensive immunogenicity assessment system was constructed, which can accurately predict the long-term protective ability of the vaccine. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1It is a flow chart of the method for screening Riemerella anatipestifer bivalent inactivated vaccine strains and evaluating immunogenicity of the present invention;

[0056] Figure 2 It is a block diagram of the Riemerella anatipestifer bivalent inactivated vaccine strain screening and immunogenicity evaluation system of the present invention;

[0057] Figure 3 This is a data table of antibody titers after vaccination with different strain vaccines of the present invention;

[0058] Figure 4 This is a data table showing the effects of different doses of the vaccine of the present invention on cellular immunity;

[0059] Figure 5 This is a data table showing the effects of different doses of the vaccine of the present invention on the protection rate against virus infection;

[0060] Figure 6 This is a parameter table of vaccine protection effects under different virus attack intensities of the present invention;

[0061] Figure 7 This is a parameter table of the number of memory T cells at different time points after vaccination with the vaccine of the present invention. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] See also Figures 1 to 7 , the present invention provides a technical solution:

[0064] The method for screening and immunogenicity evaluation of Riemerella anatipestifer bivalent inactivated vaccine strains comprises the following steps:

[0065] S1. Vaccine strain screening method;

[0066] S1-1. Isolation and identification of pathogens. Patients were collected from the liver and spleen of infected ducks. Riemerella anatipestifer was isolated by traditional culture. The strains were identified by PCR amplification and 16S rRNA sequence analysis. The pathogens were further serotyped.

[0067] S1-2, Molecular screening of bivalent vaccine strains, genetic diversity analysis of isolated Riemerella anatipestifer strains was performed through multi-locus sequence typing and whole genome sequencing molecular marker technology, and two representative strains of different serotypes, serotype 1 and serotype 2, were screened out;

[0068] S1-3, in vitro antigen expression detection, using immunoblotting and enzyme-linked immunosorbent assay methods to detect the expression of the main antigenic proteins of the strains, and screen out high-expression strains expressing the main protective antigens, such as OMP protein and LPS, for vaccine development;

[0069] S2. Immunogenicity assessment methods;

[0070] S2-1. Establishment of animal model: Select healthy ducklings, such as 1-day-old or 3-week-old ducklings, for immunization experiments. Use different selected bivalent inactivated vaccine strains for immunization, and set up high-dose, medium-dose, low-dose groups and a blank control group;

[0071] S2-2, Antibody titer evaluation, regularly test the antibody titer in the serum of each group of ducklings after immunization by indirect ELISA, test the IgG and IgM levels respectively, and draw the antibody generation curve;

[0072] S2-3, Cellular immune analysis, flow cytometry was used to analyze the ratio of CD4+T cells and CD8+T cells in the peripheral blood of ducklings after immunization to evaluate the cellular immune response;

[0073] S2-4, protection experiment, at an appropriate time after vaccination, such as 14 days, 28 days, conduct a challenge experiment, record the morbidity and mortality of ducklings in different dose groups, and evaluate the protective efficacy of the vaccine strain;

[0074] S2-5. Evaluation of the persistence of immune memory. Follow-up tests are conducted on each group of ducklings at different times after immunization, such as 30 days, 60 days, and 90 days, to evaluate the persistence of immune memory.

[0075] Specifically, the S1 vaccine strain screening method adopts high-throughput screening technology, which integrates gene editing screening tools, CRISPR-Cas9 and transcriptome analysis technology on the basis of the original screening method based on multi-site sequence typing and whole genome sequencing to achieve high-precision screening of vaccine strain genes and expression levels.

[0076] Specifically, the CRISPR screening: through gene editing technology, specific genes of different vaccine strains are knocked out or overexpressed, the effects on immunogenicity and antigen expression are observed, and the genotype strains that can induce high levels of immune responses are screened out.

[0077] Specifically, the transcriptome analysis: uses RNA-seq technology to detect the gene expression profiles of different strains, and screens strains that can highly express major protective antigens, OMP, and LPS during the infection process to ensure that the vaccine strain has strong antigenicity.

[0078] Specifically, in the S2-2, antibody titer evaluation step, cytokine detection and memory cell evaluation are further introduced on the basis of the original antibody titer and T cell immune detection to more comprehensively evaluate the immunogenicity of the vaccine.

[0079] Specifically, the cytokine detection: multiple ELISA or flow cytometry is used to detect the secretion levels of IL-2, IFN-γ, and TNF-α cytokines after immunization to evaluate the immune strength stimulated by the vaccine.

[0080] Specifically, the memory cell analysis: flow cytometry is used to detect central memory T cells and effector memory T cells formed after immunization to predict the long-term protective efficacy of the vaccine.

[0081] Specifically, the antigen-specific immune analysis: combining the molecular screening results, targeting the antigen specificity of different vaccine strains, using antigen peptide libraries to design immune response analysis tools to simulate the immune effects of vaccine strains in actual infection;

[0082] Antigen-specific T cell analysis:

[0083] Aiming at the screened dominant antigen, OMP protein, a peptide library was designed and used to stimulate T cells of immunized ducks to analyze the intensity of their immune response and help evaluate the antigenic efficacy of the vaccine.

[0084] The Riemerella anatipestifer bivalent inactivated vaccine strain screening and immunogenicity assessment system includes data input and management: the multi-dimensional data of strain screening, antigen expression, antibody titer, cellular immunity, and challenge experiment are entered into the system for unified management and analysis;

[0085] Data model construction: Use machine learning models to train the vaccine strain screening results and immunogenicity assessment data, predict the immune protection efficacy of the vaccine strain, simulate the time dynamics of different immune responses after vaccination, and evaluate the vaccine protection period through mathematical modeling;

[0086] Result output and optimization: The system automatically generates immunogenicity analysis reports for each vaccine strain based on input data, recommends the best vaccine strain combination, and outputs the protective efficacy prediction data of the bivalent vaccine;

[0087] Real-time data monitoring and feedback: Build a real-time data monitoring and feedback system to automatically record and analyze vaccine strain screening, antibody production, cellular immunity and virus protection experiment data. The system automatically generates optimization suggestions.

[0088] Specifically, the real-time data monitoring and feedback includes a real-time feedback optimization model:

[0089] The system automatically adjusts the experimental process and evaluation criteria based on the real-time collected data. For example, it automatically recommends adjustments to the vaccination dose based on changes in antibody titers.

[0090] Dynamic evaluation and optimization of vaccine protection effect: Dynamic modeling of long-term protection effect:

[0091] Immune memory and protection persistence assessment: In the immunogenicity assessment system, the dynamic model of immune memory is introduced to dynamically simulate the length of the protection period by tracking the changes in long-term immune memory cells after vaccination;

[0092] Formula description:

[0093] M(t)=M0·e -λt

[0094] Where: M(t) is the number of memory T cells at time t, M0 is the initial number of memory T cells, and λ is the memory cell decay rate;

[0095] Modeling formula for long-term protection effect:

[0096] Predict the protective effect of vaccines at different time points through comprehensive simulation of cellular immunity and antibody production:

[0097]

[0098] Where: A(t) is the antibody titer, M(t) is the number of memory T cells, A threshold and M threshold are the protection thresholds for antibodies and memory T cells, respectively;

[0099] Multi-factor dynamic simulation of virus challenge experiment: infection exposure and pathogen load modeling:

[0100] A multi-factor dynamic model was established for different challenge intensities and pathogen loads to simulate the protective effect of vaccinated ducks under different pathogen exposure levels. By simulating the effects of different environments and pathogen loads, the actual protective ability of the vaccine in a complex environment was predicted.

[0101] Infection Exposure Model:

[0102] I(t)=P exposure ·(1-e -γA(t) )·B(t)

[0103] Where: I(t) is the infection probability at time t, P exposure is the probability of pathogen exposure, γ is the neutralization effect constant of antibodies on pathogens, and B(t) is the change of pathogen load over time;

[0104] Automated analysis and optimization of challenge experiment data: Use automated data analysis tools to conduct statistical analysis on the morbidity and mortality rates of different doses and exposure times in the challenge experiment, optimize the challenge experiment process based on vaccine dose and immunization time, generate experimental reports in real time, and provide optimization suggestions.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for screening and evaluating the immunogenicity of a Riemerella anatipestifer bivalent inactivated vaccine strain, characterized in that: The steps include: S1. Vaccine strain screening method; S1-1. Isolation and identification of pathogens. Patients were collected from the liver and spleen of infected ducks. Riemerella anatipestifer was isolated by traditional culture. The strains were identified by PCR amplification and 16S rRNA sequence analysis. The pathogens were further serotyped. S1-2, Molecular screening of bivalent vaccine strains, genetic diversity analysis of isolated Riemerella anatipestifer strains was performed through multi-locus sequence typing and whole genome sequencing molecular marker technology, and two representative strains of different serotypes, serotype 1 and serotype 2, were screened out; S1-3, in vitro antigen expression detection, using immunoblotting and enzyme-linked immunosorbent assay methods to detect the expression of the main antigenic proteins of the strains, and screen out high-expression strains expressing the main protective antigens, such as OMP protein and LPS, for vaccine development; S2. Immunogenicity assessment methods; S2-1. Establishment of animal model. Select healthy ducklings, such as 1-day-old and 3-week-old ducklings, for immunization experiments. Use different selected bivalent inactivated vaccine strains for immunization, and set up high-dose, medium-dose, low-dose groups and blank control groups. S2-2, Antibody titer evaluation, regularly test the antibody titer in the serum of each group of ducklings after immunization by indirect ELISA, test the IgG and IgM levels respectively, and draw the antibody generation curve; S2-3, Cellular immune analysis, flow cytometry was used to analyze the ratio of CD4+T cells and CD8+T cells in the peripheral blood of ducklings after immunization to evaluate the cellular immune response; S2-4, protection experiment, at an appropriate time after vaccination, such as 14 days, 28 days, conduct a challenge experiment, record the morbidity and mortality of ducklings in different dose groups, and evaluate the protective efficacy of the vaccine strain; S2-5. Evaluation of the persistence of immune memory. Follow-up tests are conducted on each group of ducklings at different times after immunization, such as 30 days, 60 days, and 90 days, to evaluate the persistence of immune memory.

2. The method for screening and immunogenicity assessment of Riemerella anatipestifer bivalent inactivated vaccine strains according to claim 1, characterized in that: The S1 vaccine strain screening method adopts high-throughput screening technology. On the basis of the original screening method based on multi-site sequence typing and whole genome sequencing, it integrates gene editing screening tools, CRISPR-Cas9 and transcriptome analysis technology to achieve high-precision screening of vaccine strain genes and expression levels.

3. The method and system for screening and immunogenicity assessment of Riemerella anatipestifer bivalent inactivated vaccine strains according to claim 2, characterized in that: The CRISPR screening: through gene editing technology, specific genes of different vaccine strains are knocked out or overexpressed, the effects on immunogenicity and antigen expression are observed, and the genotype strains that can induce high levels of immune responses are screened out.

4. The method for screening and immunogenicity assessment of Riemerella anatipestifer bivalent inactivated vaccine strains according to claim 3, characterized in that: The transcriptome analysis: RNA-seq technology is used to detect the gene expression profiles of different strains, and strains that can highly express major protective antigens, OMP, and LPS during the infection process are screened to ensure that the vaccine strain has strong antigenicity.

5. The method for screening and immunogenicity assessment of Riemerella anatipestifer bivalent inactivated vaccine strains according to claim 4, characterized in that: In the S2-2, antibody titer evaluation step, cytokine detection and memory cell evaluation are further introduced on the basis of the original antibody titer and T cell immune detection to more comprehensively evaluate the immunogenicity of the vaccine.

6. The method for screening and immunogenicity assessment of Riemerella anatipestifer bivalent inactivated vaccine strains according to claim 5, characterized in that: The cytokine detection: multiple ELISA and flow cytometry are used to detect the secretion levels of IL-2, IFN-γ, and TNF-α cytokines after immunization to evaluate the immune strength stimulated by the vaccine.

7. The method for screening and immunogenicity assessment of a bivalent inactivated Riemerella anatipestifer vaccine strain according to claim 6, characterized in that: The memory cell analysis: flow cytometry is used to detect central memory T cells and effector memory T cells formed after immunization to predict the long-term protective efficacy of the vaccine.

8. The method for screening and immunogenicity assessment of Riemerella anatipestifer bivalent inactivated vaccine strains according to claim 7, characterized in that: The antigen-specific immune analysis: combining the molecular screening results, targeting the antigen specificity of different vaccine strains, using the antigen peptide library to design an immune response analysis tool to simulate the immune effect of the vaccine strain in actual infection; Antigen-specific T cell analysis: Aiming at the screened dominant antigen, OMP protein, a peptide library was designed and used to stimulate T cells of immunized ducks to analyze the intensity of their immune response and help evaluate the antigenic efficacy of the vaccine.

9. The system for screening and immunogenicity evaluation of Riemerella anatipestifer bivalent inactivated vaccine strains according to any one of claims 1 to 8, characterized in that: Including data input and management: entering multi-dimensional data of strain screening, antigen expression, antibody titer, cellular immunity, and virus attack experiments into the system for unified management and analysis; Data model construction: Use machine learning models to train the vaccine strain screening results and immunogenicity assessment data, predict the immune protection efficacy of the vaccine strain, simulate the time dynamics of different immune responses after vaccination, and evaluate the vaccine protection period through mathematical modeling; Result output and optimization: The system automatically generates immunogenicity analysis reports for each vaccine strain based on input data, recommends the best vaccine strain combination, and outputs the protective efficacy prediction data of the bivalent vaccine; Real-time data monitoring and feedback: Build a real-time data monitoring and feedback system to automatically record and analyze vaccine strain screening, antibody production, cellular immunity and virus protection experiment data. The system automatically generates optimization suggestions.

10. The Riemerella anatipestifer bivalent inactivated vaccine strain screening and immunogenicity evaluation system according to claim 9, characterized in that: The real-time data monitoring and feedback includes a real-time feedback optimization model: The system automatically adjusts the experimental process and evaluation criteria based on the real-time collected data. For example, it automatically recommends adjustments to the vaccination dose based on changes in antibody titers. Dynamic evaluation and optimization of vaccine protection effect: Dynamic modeling of long-term protection effect: Immune memory and protection persistence assessment: In the immunogenicity assessment system, the dynamic model of immune memory is introduced to dynamically simulate the length of the protection period by tracking the changes in long-term immune memory cells after vaccination; Formula description: M(t)=M0·e -λt Where: M(t) is the number of memory T cells at time t, M0 is the initial number of memory T cells, and λ is the memory cell decay rate; Modeling formula for long-term protection effect: Predict the protective effect of vaccines at different time points through comprehensive simulation of cellular immunity and antibody production: Where: A(t) is the antibody titer, M(t) is the number of memory T cells, A threshold and M threshold are the protection thresholds for antibodies and memory T cells, respectively; Multi-factor dynamic simulation of virus challenge experiment: infection exposure and pathogen load modeling: A multi-factor dynamic model was established for different challenge intensities and pathogen loads to simulate the protective effect of vaccinated ducks under different pathogen exposure levels. By simulating the effects of different environments and pathogen loads, the actual protective ability of the vaccine in a complex environment was predicted. Infection Exposure Model: I(t)=P exposure ·(1-e -γA(t) )·B(t) Where: I(t) is the infection probability at time t, P exposure is the probability of pathogen exposure, γ is the neutralization effect constant of antibodies on pathogens, and B(t) is the change of pathogen load over time; Automated analysis and optimization of challenge experiment data: Use automated data analysis tools to conduct statistical analysis on the morbidity and mortality rates of different doses and exposure times in the challenge experiment, optimize the challenge experiment process based on vaccine dose and immunization time, generate experimental reports in real time, and provide optimization suggestions.

Images