CN112611870B - Method for predicting titer of neutralizing antibody of novel coronavirus and kit thereof - Google Patents

Method for predicting titer of neutralizing antibody of novel coronavirus and kit thereof Download PDF

Info

Publication number
CN112611870B
CN112611870B CN202011523856.9A CN202011523856A CN112611870B CN 112611870 B CN112611870 B CN 112611870B CN 202011523856 A CN202011523856 A CN 202011523856A CN 112611870 B CN112611870 B CN 112611870B
Authority
CN
China
Prior art keywords
novel coronavirus
protein
quantum dot
pad
rbd
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202011523856.9A
Other languages
Chinese (zh)
Other versions
CN112611870A (en
Inventor
姚航平
陈喆
陈杭
曹少伟
陈秋强
沈明程
吴云
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hangzhou Kaiman Health Technology Co ltd
Original Assignee
Hangzhou Baolin Biotechnology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hangzhou Baolin Biotechnology Co ltd filed Critical Hangzhou Baolin Biotechnology Co ltd
Priority to CN202011523856.9A priority Critical patent/CN112611870B/en
Priority to PCT/CN2021/071877 priority patent/WO2022134241A1/en
Publication of CN112611870A publication Critical patent/CN112611870A/en
Application granted granted Critical
Publication of CN112611870B publication Critical patent/CN112611870B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
    • G01N33/56983—Viruses
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/543—Immunoassay; Biospecific binding assay; Materials therefor with an insoluble carrier for immobilising immunochemicals
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/558—Immunoassay; Biospecific binding assay; Materials therefor using diffusion or migration of antigen or antibody
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/58—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving labelled substances
    • G01N33/588—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving labelled substances with semiconductor nanocrystal label, e.g. quantum dots
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6854—Immunoglobulins
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/005—Assays involving biological materials from specific organisms or of a specific nature from viruses
    • G01N2333/08—RNA viruses
    • G01N2333/165—Coronaviridae, e.g. avian infectious bronchitis virus
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2469/00—Immunoassays for the detection of microorganisms
    • G01N2469/20—Detection of antibodies in sample from host which are directed against antigens from microorganisms

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Immunology (AREA)
  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Hematology (AREA)
  • Urology & Nephrology (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Cell Biology (AREA)
  • Food Science & Technology (AREA)
  • Medicinal Chemistry (AREA)
  • Biotechnology (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Microbiology (AREA)
  • Pathology (AREA)
  • Virology (AREA)
  • Crystallography & Structural Chemistry (AREA)
  • Materials Engineering (AREA)
  • Nanotechnology (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Tropical Medicine & Parasitology (AREA)
  • Peptides Or Proteins (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

The invention provides a method for predicting the titer of a neutralizing antibody of a novel coronavirus and a kit thereof, and relates to the technical field of the titer prediction of the neutralizing antibody, wherein the method for predicting the titer of the neutralizing antibody of the novel coronavirus comprises the following steps: firstly, providing a biological sample to be detected, and then detecting the expression level of the novel coronavirus specific protein in a serum sample after the novel coronavirus specific protein is combined with an affinity antibody; the detection result is then correlated with the neutralizing antibody titer to predict the neutralizing antibody titer of the novel coronavirus in the biological sample to be tested. The method can well predict the result of the neutralizing antibody of the novel coronavirus only through serum detection, has the advantages of simple operation, high detection speed, short detection period and safe detection environment compared with the existing plaque reduction neutralization test and pseudovirus neutralization titer detection, and can be used as an evaluation index of secondary relapse after novel coronavirus vaccination or infection.

Description

Method for predicting titer of neutralizing antibody of novel coronavirus and kit thereof
Technical Field
The invention relates to the technical field of neutralizing antibody titer prediction, in particular to a method for predicting the neutralizing antibody titer of a novel coronavirus and a kit thereof.
Background
After vaccination of humans, protective antibodies, i.e. neutralizing antibodies, can be produced by the immune response. The titer of the neutralizing antibody is measured, and the protective effect of the vaccine can be judged. And (4) detecting the titer of the neutralizing antibody of the new coronary patient after healing, and judging whether the risk of secondary infection exists.
Currently established methods for detecting the titer of neutralizing antibodies against coronavirus include a Plaque Reduction Neutralization Test (PRNT) and a Pseudovirus-Based Neutralization Assay (PBNA). PRNT detection uses live viruses, and is completed in a BSL-3 laboratory, and PRNT detection operation is complex, long in period and large in error. Although the pseudovirus with higher safety is used for neutralizing and detecting the pseudovirus, the process of infecting cells by live viruses cannot be simulated and replaced, and the pseudovirus also has the defects of complex operation, long period and large error, and cannot meet the requirements of quick, flux and accurate detection.
Therefore, it is important to research and develop a novel method and kit for predicting the titer of neutralizing antibodies against coronavirus, so as to rapidly evaluate the level of neutralizing titer in human body.
In view of the above, the present invention is particularly proposed.
Disclosure of Invention
The first purpose of the invention is to provide a method for predicting the titer of the neutralizing antibody of the novel coronavirus, the method can well predict the result of the neutralizing antibody of the novel coronavirus only by detecting serum, and compared with the existing plaque reduction neutralizing test and the detection of the titer of the neutralizing antibody of the pseudovirus, the method has the advantages of simple operation, high detection speed, short detection period and safe detection environment.
The second object of the present invention is to provide a novel coronavirus neutralizing antibody titer predicting kit used in the above-described predicting method.
In order to achieve the above purpose of the present invention, the following technical solutions are adopted:
the invention provides a method for predicting the titer of neutralizing antibodies of a novel coronavirus, which comprises the following steps:
(a) providing a biological sample to be detected, and detecting the expression level of the novel coronavirus specific protein in the serum sample after being combined with the affinity antibody;
(b) correlating the detection result of step (a) with the neutralizing antibody titer.
Further, the biological samples to be detected are serum and plasma of a new coronary patient after healing.
Further, the novel coronavirus specific protein comprises at least one of a novel coronavirus N protein, a novel coronavirus S2-ECD protein or a novel coronavirus S1-RBD protein;
preferably, the amino acid sequence of the novel coronavirus N protein is shown as Seq No. 01:
preferably, the amino acid sequence of the novel coronavirus S2-ECD protein is shown as Seq No. 02:
preferably, the amino acid sequence of the novel coronavirus S1-RBD protein is shown as Seq No. 03.
Further, the affinity antibody comprises at least one of anti-human IgA, anti-human IgG, and anti-human IgM;
preferably, the anti-human IgA comprises any one of a goat anti-human IgA polyclonal antibody, a mouse anti-human IgA monoclonal antibody, a rabbit anti-human IgA monoclonal antibody and a rabbit anti-human IgA polyclonal antibody;
preferably, the anti-human IgG comprises any one of a goat anti-human IgG polyclonal antibody, a mouse anti-human IgG monoclonal antibody, a rabbit anti-human IgG monoclonal antibody, and a rabbit anti-human IgG polyclonal antibody;
preferably, the anti-human IgM comprises any one of a goat anti-human IgM polyclonal antibody, a mouse anti-human IgM monoclonal antibody, a rabbit anti-human IgM monoclonal antibody, and a rabbit anti-human IgM polyclonal antibody.
Furthermore, the expression level of the novel coronavirus specific protein in the step (a) after being combined with the affinity antibody is detected by a quantum dot immunofluorescence method.
Further, the step (b) association is performed by using a software classification algorithm.
Further, the software classification algorithm includes at least one of logistic regression, support vector machine, and random forest.
The invention provides a novel coronavirus neutralizing antibody titer prediction kit, which comprises: a detection reagent strip containing a quantum dot specific protein complex;
the quantum dot specific protein compound is mainly obtained by coupling quantum dots with novel coronavirus specific proteins.
Further, the detection reagent strip comprises a bottom card, a sample pad, a quantum dot marker combining pad, a chromatography reaction membrane and absorbent paper;
wherein the quantum dot label binding pad adsorbs a quantum dot specific protein complex;
the chromatography reaction membrane is provided with a detection line, and the detection line comprises at least one of an IgA detection line, an IgG detection line and an IgM detection line.
Further, the kit also comprises an ultraviolet irradiation device.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a method for predicting the titer of neutralizing antibodies of a novel coronavirus, which comprises the following steps: firstly, providing a biological sample to be detected, and then detecting the expression level of the novel coronavirus specific protein in a serum sample after being combined with an affinity antibody; the detection result is then correlated with the neutralizing antibody titer to predict the neutralizing antibody titer of the novel coronavirus in the biological sample to be tested. The method can well predict the result of the neutralizing antibody of the novel coronavirus only through serum detection, has the advantages of simple operation, high detection speed, short detection period and safe detection environment compared with the existing plaque reduction neutralization test and pseudovirus neutralization titer detection, and can be used as an evaluation index of secondary relapse after novel coronavirus vaccination or infection.
The novel coronavirus neutralizing antibody titer prediction kit provided by the invention mainly comprises a detection reagent strip containing a quantum dot specific protein compound; the reagent strip adopts a quantum dot immunochromatography technology, takes a novel coronavirus N protein, a novel coronavirus S2-ECD protein and a novel coronavirus S1-RBD protein as detection antigens, uses quantum dot fluorescent microspheres to mark N, S1-RBD and S2-ECD antigen proteins to form a quantum dot specific protein complex, and then detects the plasma of the novel coronavirus. Meanwhile, the quantum dot immunochromatography used by the invention is rapid in detection, results are obtained within 10 minutes, the exposure risk of medical workers can be reduced by using serum to detect samples, the field operation can be realized by simple training, and hundreds of samples can be detected by each portable fluorescence detector within 1 hour.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
According to one aspect of the present invention, a method of predicting the titer of neutralizing antibodies against a novel coronavirus comprises the steps of:
(a) providing a biological sample to be detected, and detecting the expression level of the novel coronavirus specific protein in the serum sample after the novel coronavirus specific protein is combined with the affinity antibody;
(b) correlating the detection result of step (a) with the neutralizing antibody titer.
The invention provides a method for predicting the titer of neutralizing antibodies of a novel coronavirus, which comprises the following steps: firstly, providing a biological sample to be detected, and then detecting the expression level of the novel coronavirus specific protein in a serum sample after being combined with an affinity antibody; the detection result is then correlated with the neutralizing antibody titer to predict the neutralizing antibody titer of the novel coronavirus in the biological sample to be tested. The method can well predict the result of the neutralizing antibody of the novel coronavirus only through serum detection, has the advantages of simple operation, high detection speed, short detection period and safe detection environment compared with the existing plaque reduction neutralization test and pseudovirus neutralization titer detection, and can be used as an evaluation index of secondary relapse after novel coronavirus vaccination or infection.
In a preferred embodiment of the present invention, the biological sample to be tested is serum or plasma of a new coronary patient after healing.
In a preferred embodiment, the biological sample to be tested is serum or plasma of a new coronary patient after cure, and the probability of secondary recurrence of the patient after infection is predicted.
In a preferred embodiment of the present invention, the novel coronavirus specific protein comprises at least one of a novel coronavirus N protein, a novel coronavirus S2-ECD protein, or a novel coronavirus S1-RBD protein;
note: the novel coronavirus S2-ECD protein; is an extra-cellular domain (ECD) protein of a 2019-nCoVS2 subunit; the novel coronavirus S1-RBD protein is a 2019-nCoV surface spike protein S1 subunit Receptor Binding Domain (RBD) protein; the novel coronavirus N Protein is 2019-nCoV main Protein Nucleocapsid Protein (N Protein).
In the above preferred embodiment, the amino acid sequence of the N protein of the novel coronavirus is shown in Seq No. 01:
in the above preferred embodiment, the amino acid sequence of the novel coronavirus S2-ECD protein is represented by Seq No. 02:
in the above preferred embodiment, the amino acid sequence of the novel coronavirus S1-RBD protein is shown in Seq No. 03.
In a preferred embodiment of the present invention, the affinity antibody comprises at least one of anti-human IgA, anti-human IgG, and anti-human IgM;
in the above preferred embodiment, the anti-human IgA includes any one of a goat anti-human IgA polyclonal antibody, a mouse anti-human IgA monoclonal antibody, a rabbit anti-human IgA monoclonal antibody, and a rabbit anti-human IgA polyclonal antibody;
in the above preferred embodiment, the anti-human IgG includes any one of a goat anti-human IgG polyclonal antibody, a mouse anti-human IgG monoclonal antibody, a rabbit anti-human IgG monoclonal antibody, and a rabbit anti-human IgG polyclonal antibody;
in the above preferred embodiment, the anti-human IgM comprises any one of a goat anti-human IgM polyclonal antibody, a mouse anti-human IgM monoclonal antibody, a rabbit anti-human IgM monoclonal antibody, and a rabbit anti-human IgM polyclonal antibody.
In a preferred embodiment of the present invention, the expression level of the novel coronavirus specific protein of step (a) after binding to the affinity antibody is detected by quantum dot immunofluorescence.
As a preferred embodiment, the expression level of the novel coronavirus specific protein after being combined with the affinity antibody can be detected by a quantum dot immunofluorescence method, so that fluorescence data can be obtained more intuitively, and the later data analysis and calculation can be facilitated.
In a preferred embodiment of the present invention, the step (b) associating is performed by using a software classification algorithm.
In the above preferred embodiment, the software classification algorithm comprises at least one of logistic regression, support vector machine and random forest.
According to one aspect of the present invention, a novel coronavirus neutralizing antibody titer prediction kit comprises: a detection reagent strip containing a quantum dot specific protein complex;
the quantum dot specific protein compound is mainly obtained by coupling quantum dots with novel coronavirus specific proteins.
The novel coronavirus neutralizing antibody titer prediction kit provided by the invention mainly comprises a detection reagent strip containing a quantum dot specific protein complex; the reagent strip adopts a quantum dot immunochromatography technology, takes a novel coronavirus N protein, a novel coronavirus S2-ECD protein and a novel coronavirus S1-RBD protein as detection antigens, uses quantum dot fluorescent microspheres to mark N, S1-RBD and S2-ECD antigen proteins to form a quantum dot specific protein complex, and then detects plasma of the novel coronavirus. Meanwhile, the quantum dot immunochromatography used by the invention is rapid in detection, results are obtained within 10 minutes, the exposure risk of medical workers can be reduced by using serum to detect samples, the field operation can be realized by simple training, and hundreds of samples can be detected by each portable fluorescence detector within 1 hour.
In a preferred embodiment of the present invention, the detection reagent strip comprises a bottom card, a sample pad, a quantum dot label binding pad, a chromatography reaction membrane and absorbent paper;
wherein the quantum dot label binding pad adsorbs a quantum dot specific protein complex;
the chromatography reaction membrane is provided with a detection line, and the detection line comprises at least one of an IgA detection line, an IgG detection line and an IgM detection line.
In the above preferred embodiment, the chromatography reaction membrane comprises one of NC membrane, PVDF membrane or nylon membrane, preferably nitrocellulose membrane;
in the above preferred embodiment, the bottom card comprises one of a PVC bottom card or a PC bottom card, preferably a PC bottom card;
in the above preferred embodiment, the release liner comprises one of a glass fiber membrane, a polyester membrane, a blood filtration membrane, preferably a glass fiber membrane;
in the above preferred embodiment, the sample pad comprises one of a glass fiber membrane, a polyester membrane, and a blood filtration membrane, preferably a glass fiber membrane;
in the above preferred embodiment, the absorbent paper comprises one of thick filter paper, glass fiber, or blood filter membrane, preferably thick filter paper.
In the above preferred embodiment, the chromatography reaction membrane is provided with a detection line and a quality control line;
the detection line comprises at least one of an IgA detection line, an IgG detection line and an IgM detection line, wherein the IgA detection line contains anti-human IgA; the IgG detection line contains anti-human IgG; the IgM detection line contains anti-human IgM;
the quality control line contains goat anti-rabbit IgG antibody;
in a preferred embodiment of the present invention, the kit further comprises an ultraviolet irradiation device.
The technical solution of the present invention will be further described with reference to the following examples.
Example 1
Preparing novel coronavirus recombinant antigen N protein, S1-RBD protein and S2-ECD protein:
(1) PCR amplifying N gene, S2-ECD gene and S1-RBD protein of the coded novel coronavirus antigen by adopting a gene cloning technology;
(2) and transferring the N gene into escherichia coli for expression, transferring the S2-ECD gene into 293 cells for expression, and transferring the S1-RBD protein into 293 cells for expression to obtain the novel coronavirus recombinant antigen N protein, the S2-ECD protein and the S1-RBD protein.
Example 2
Preparing a chromatographic reaction membrane (two detection lines of IgA and IgG):
and (3) sticking an NC membrane with the width of 25cm to the middle area of the PC bottom card, then respectively diluting the anti-human IgA, anti-human IgG and goat anti-rabbit IgG antibodies to 0.2-1 mg/ml in PBS diluent, and scratching the detection line area and the quality control line area corresponding to the NC membrane by using a gold spraying film scratching instrument. Drying in an oven at 37 ℃ for 12-24h, and sealing for later use.
Example 3
Preparing a chromatography reaction membrane (IgM and IgG detection lines):
attaching an NC membrane with the width of 25cm to the middle area of a PC bottom card, then respectively diluting anti-human IgM, anti-human IgG and goat anti-rabbit IgG antibodies to 0.2-1 mg/ml in PBS diluent, and scratching a detection line area and a quality control line area corresponding to the NC membrane by using a gold spraying film scratching instrument. Drying in an oven at 37 ℃ for 12-24h, and sealing for later use.
Example 4
Preparing a chromatographic reaction membrane (three detection lines of IgA, IgM and IgG):
attaching an NC membrane with the width of 25cm to the middle area of a PC bottom card, then respectively diluting anti-human IgA, anti-human IgM, anti-human IgG and goat anti-rabbit IgG antibodies to 0.2-1 mg/ml in PBS diluent, and scribing on a detection line area and a quality control line area corresponding to the NC membrane by using a gold spraying film scribing instrument. Drying in an oven at 37 ℃ for 12-24h, and sealing for later use.
Example 5
Preparing a sample pad:
uniformly coating 20-100 mM Tris-HCl diluent (pH 8.0, containing 0.5% BSA, 0.5% PVP and 0.5% TWEEN-20) on an untreated release pad by using a liquid transfer gun and a coating rod, drying at 37 ℃ for 12-24h, and sealing for later use.
Example 6
Preparing quantum dot-marker protein complex (specific protein is novel coronavirus N protein):
(1) and adding 200 mul of qds into 800 mul of MES (pH 6) buffer solution, adding 40-160 mul of EDC and 10-40 mul of NHS for activation, and activating for 15-60 min at 37 ℃. The activated solution was centrifuged under certain conditions and the supernatant removed with a pipette.
(2) And (3) re-dissolving the precipitate obtained after the centrifugation in the step (1) by using 1000 mul of 10-50 mM MES (pH 6) buffer solution, and if the re-dissolving is not complete, using ultrasonic to assist the re-dissolving. And centrifuging the re-dissolved solution under a certain condition, removing a supernatant by using a liquid transfer gun, re-dissolving the precipitate by using 1000 mu l of 10-50 mM MES (pH 6) buffer solution, and if the re-dissolving is not complete, carrying out ultrasonic-assisted re-dissolving (the step can be omitted).
(3) And adding 20-100 mul of the novel coronavirus N protein diluted to 1mg/ml by 10-50 mM MES (pH 6) buffer solution into the redissolved solution, and coupling at 37 ℃ for 60-300 min.
(4) And adding 100 mul of 20-100 mM Tris-HCl diluent (pH8.0, containing 100-500 mM glycine +10% BSA) for sealing after the coupling is finished, and sealing for 30-120 min at 37 ℃.
(5) Centrifuging the sealed solution under certain conditions, and removing the supernatant by using a pipette. And (3) redissolving the sediment by using 1000 mul of Tris-HCl diluent, continuing centrifuging under certain conditions if redissolution is not complete and can be assisted by ultrasonic, and removing the supernatant by using a liquid transfer gun (the step can be omitted). And (3) carrying out redissolution precipitation on 1000 mul of 20-100 mM Tris-HCl diluent (pH8.0), and if the redissolution is not complete, carrying out ultrasonic-assisted redissolution, and storing at 4 ℃ to obtain the quantum dot-labeled protein complex.
Example 7
Preparing a quantum dot-marker protein complex (the specific protein is a novel coronavirus S2-ECD protein):
in this embodiment, except for step (3), the following steps are performed: adding 20-100 mul of novel coronavirus S2-ECD protein diluted to 1mg/ml by 10-50 mM MES (pH 6) buffer solution into the redissolved solution, and coupling at 37 ℃ for 60-300 min. "otherwise, the same procedure as in example 6 was repeated.
Example 8
Preparing a quantum dot-marker protein complex (the specific protein is a novel coronavirus S1-RBD protein):
in this embodiment, except for the step (3): and adding 20-100 ul of the novel coronavirus S1-RBD protein diluted to 1mg/ml by 10-50 mM MES (pH 6) buffer solution into the redissolved solution, and coupling at 37 ℃ for 60-300 min. "otherwise, the same procedure as in example 6 was repeated.
Example 9
Preparing a quantum dot label binding pad (the specific protein is a novel coronavirus N protein):
diluting the quantum dot-labeled protein complex prepared in the example 6 by 20-100 mM Tris-HCl diluent (pH 8.0, containing 0.5% BSA and 2% trehalose) according to requirements, spraying the diluted solution on a treated release pad by using a film-scribing gold spraying instrument, and drying at 37 ℃ for 12-24h to obtain the quantum dot label binding pad. Or diluting the quantum dot-labeled protein complex prepared in the embodiment 7 by 20-100 mM Tris-HCl diluent (pH 8.0, containing 0.5% BSA and 2% trehalose) according to requirements, spraying the diluted quantum dot-labeled protein complex on an untreated release pad by using a liquid transfer gun, uniformly coating the release pad by using a coating rod, finally putting the release pad into a freeze dryer for freeze drying, and sealing the bag for later use after the program is run.
Example 10
Preparing a quantum dot marker binding pad (the specific protein is a novel coronavirus S2-ECD protein):
diluting the quantum dot-labeled protein complex prepared in example 7 by 20-100 mM Tris-HCl diluent (pH 8.0, containing 0.5% BSA and 2% trehalose) according to requirements, spraying the diluted solution on a treated release pad by using a film-scribing gold spraying instrument, and drying at 37 ℃ for 12-24h to obtain the quantum dot label binding pad. Or diluting the quantum dot-labeled protein complex prepared in the embodiment 7 by 20-100 mM Tris-HCl diluent (pH 8.0, containing 0.5% BSA and 2% trehalose) according to requirements, spraying the diluted quantum dot-labeled protein complex on an untreated release pad by using a liquid transfer gun, uniformly coating the release pad by using a coating rod, finally putting the release pad into a freeze dryer for freeze drying, and sealing the bag for later use after the program is run.
Example 11
Preparing a quantum dot label binding pad (the specific protein is a novel coronavirus S1-RBD protein):
diluting the quantum dot-labeled protein complex prepared in the example 8 by 20-100 mM Tris-HCl diluent (pH 8.0, containing 0.5% BSA and 2% trehalose) according to requirements, spraying the diluted solution on a treated release pad by using a film-scribing gold spraying instrument, and drying at 37 ℃ for 12-24h to obtain the quantum dot label binding pad. Or diluting the quantum dot-labeled protein complex prepared in the embodiment 7 by 20-100 mM Tris-HCl diluent (pH 8.0, containing 0.5% BSA and 2% trehalose) according to requirements, spraying the diluted quantum dot-labeled protein complex on an untreated release pad by using a liquid transfer gun, uniformly coating the release pad by using a coating rod, finally putting the release pad into a freeze dryer for freeze drying, and sealing the bag for later use after the program is run.
Example 12
A novel reagent strip for detecting coronavirus is prepared by the following steps:
the chromatographic reaction membrane prepared in the example 4, the quantum dot marker combination pad prepared in the example 9, the sample pad prepared in the example 5 and the absorbent paper are overlapped and adhered on the PVC backboard;
the sample pad and the quantum dot marker combination pad are sequentially lapped at one end of the chromatographic reaction membrane, the absorbent paper is lapped at the other end of the chromatographic reaction membrane, and then the parameters of the slitter are adjusted to slit the test paper strips into test paper strips with the width of 3-4 mm.
Example 13
This example is the same as example 12 except that the quantum dot label bonding pad prepared in example 9 was replaced with the quantum dot label bonding pad prepared in example 10.
Example 14
This example is the same as example 12 except that the quantum dot label bonding pad prepared in example 9 was replaced with the quantum dot label bonding pad prepared in example 11.
Example 15
This example is the same as example 12 except that the chromatography reaction membrane of example 4 was replaced with the chromatography reaction membrane of example 3.
Example 16
This example is the same as example 13 except that the chromatography reaction membrane of example 4 was replaced with the chromatography reaction membrane of example 3.
Example 17
This example is the same as example 14 except that the chromatography reaction membrane of example 4 was replaced with the chromatography reaction membrane of example 3.
Example 18
This example is the same as example 12 except that the chromatography reaction membrane of example 4 was replaced with the chromatography reaction membrane of example 2.
Example 19
This example is the same as example 13 except that the chromatographic reaction membrane in example 4 was replaced with the chromatographic reaction membrane in example 2.
Example 20
This example is the same as example 14 except that the chromatography reaction membrane of example 4 was replaced with the chromatography reaction membrane of example 2.
The arrangement of the specific protein and detection line of the reagent strip in the above examples 12-19 is as follows:
group of Specific proteins Detection line
Example 12 N protein IgA 、 IgM 、 IgG
Example 13 S2-ECD protein IgA 、 IgM 、 IgG
Example 14 S1-RBD protein IgA 、 IgM 、 IgG
Example 15 N protein IgM 、 IgG
Example 16 S2-ECD protein IgM 、 IgG
Example 17 S1-RBD protein IgM 、 IgG
Example 18 N protein IgA 、 IgG
Example 19 S2-ECD protein IgA 、 IgG
Example 20 S1-RBD protein IgA 、 IgG
Example 21
A novel coronavirus neutralizing antibody titer prediction kit comprising the detection reagent strips of example 12 and example 14.
Example 22
A novel coronavirus neutralizing antibody titer prediction kit comprising the detection reagent strips of example 15, example 16 and example 17.
Example 23
A novel coronavirus neutralizing antibody titer prediction kit comprising the detection reagent strips of example 18 and example 20.
Example 24
A novel coronavirus neutralizing antibody titer prediction kit comprising the detection reagent strips of example 15 and example 17.
Example 25
A novel coronavirus neutralizing antibody titer prediction kit comprising the test strip of example 14.
Experimental example 1 true titer detection
To better verify the accuracy of the method for predicting the titer of neutralizing antibodies against the novel coronavirus, the applicant carried out the detection of the true neutralizing titer of the serum samples of 580 cured patients with the new corona patients by using the gold standard for neutralizing titer (plaque reduction neutralization test), and the specific method was as follows:
1. and taking a new 96-well plate, adding 50 mul of to-be-detected serum stock solution into each 1-10 rows of holes, adding 50 mul of 100TCID50/50 mul of virus solution into each hole by using an 8-channel hole arranging gun, and slightly blowing to uniformly mix the serum and the virus solution. Adding 50 mu l of maintenance liquid into each hole in 11 rows, adding 50 mu l of standard positive serum into the first hole in 11 rows, and diluting the standard positive serum by 1:2, 1:22 to 1:28 times. And adding 50 mul of standard negative serum stock solution into the 1 st hole in the 12 columns, and then adding 50 mul of 100TCID50/50 mul of virus solution. Carrying out 4 times of continuous 10-time dilution on 100TCID50/50 ul of virus solution by using a maintenance solution, diluting into 10TCID50/50 ul, 1TCID50/50 ul and 0.1TCID50/50 ul, sequentially adding the diluted solution to 3-6 holes in the 12 th row, adding 50 ul to each hole, and adding 50 ul of maintenance solution to each hole. The plates were placed in CO at 37 deg.C 2 And neutralizing for 1h in an incubator.
2. The maintenance solution in the culture plate with cells growing to a monolayer is poured off, and then the serum virus solution which is neutralized for 1h in the previous step is transferred to the culture plate with cells growing to a monolayer, and care is taken when transferring so that the added solution blows off the cells.
3. And adding 150 mul of maintenance liquid into each hole, oscillating on a micro oscillator for 30s, and uniformly mixing. The plates were placed in CO at 37 deg.C 2 In the incubator, the results are recorded after 96 h.
The judgment result is to meet the following requirements: the antibody has no obvious cytotoxicity; normal cell control is established; virus control CPE reached +++. The lowest concentration of antibody or the highest dilution of antibody that inhibits the cytopathic effect of cells infected with the novel coronavirus of 100TCID50 (protecting 50% of the cells from disease) is the anti-virally effective concentration or titer of the antibody.
Wherein, when the neutralizing titer is lower than 40 corresponding antibody level samples, no protection effect is generated; when the neutralizing titer is higher than 40 corresponding antibody level samples, a protective effect is indicated.
Example 26
The novel coronavirus neutralizing antibody titer prediction kit of examples 21 to 25 was used to detect serum samples of 580 cured patients in experiment example 1, and to measure fluorescence values of IgA detection line, IgG detection line, and IgM detection line after detection of each sample, wherein the specific detection results were as follows:
sample numbering S1-IgM S1-IgG S1-IgA S2-IgA S2-IgG S2-IgM
1 0.006 0 0 0.002 0.003 0.011
2 0.007 0 0 0.001 0.003 0.012
3 0.007 0 0 0.002 0.003 0.01
4 0.005 0 0.001 0.002 0.005 0.013
5 0.005 0.001 0 0.004 0.001 0.006
6 0.007 0 0 0.04 0.002 0.012
7 0.019 0 0 0.284 0.006 0.021
8 0.258 0.083 0.005 0.823 0.15 0.041
9 0.349 0.139 0.004 0.263 0.414 0.053
10 0.326 0.228 0.005 0.167 0.506 0.098
11 0.225 0.195 0.002 0.093 0.492 0.024
12 0.09 0.122 0.001 0.033 0.295 0.018
13 0.037 0.021 0.001 0.015 0.142 0.012
14 0 0 0 0.001 0.004 0.009
15 0.003 0 0.001 0.014 0.01 0.011
16 0.06 0.013 0.009 0.278 0.445 0.021
17 0.054 0.003 0.002 0.11 0.572 0.005
18 0.01 0 0.001 0.052 0.396 0.004
19 0.002 0 0 0.001 0.002 0.005
20 0.002 0 0 0.003 0.002 0.004
21 0.012 0.002 0.001 0.002 0.003 0.004
22 0.037 0 0 0.008 0.03 0.009
23 0.484 0.009 0.001 0.005 0.334 0.037
24 0.777 0.076 0.005 0.002 0.502 0.031
25 0.719 0.044 0.001 0.003 0.56 0.015
26 0.753 0.057 0.001 0 0.56 0.016
27 0.416 0.092 0.002 0.005 0.527 0.022
28 0.001 0 0 0.003 0.001 0.004
29 0.001 0 0 0.007 0.001 0.004
30 0.002 0.001 0.001 0.007 0.003 0.005
31 0.103 0.148 0.001 0.018 0.302 0.023
32 0.051 0.247 0.002 0.009 0.247 0.018
33 0.024 0.265 0.001 0.003 0.305 0.032
34 0.04 0.186 0.001 0.009 0.372 0.02
35 0.023 0.215 0.001 0.003 0.28 0.009
36 0.006 0.083 0.001 0.003 0.166 0.006
37 0.001 0 0.001 0.002 0.001 0.004
38 0.002 0 0 0.008 0.003 0.006
39 0.006 0 0 0.002 0.003 0.015
40 0.288 0.227 0.003 0.048 0.27 0.107
41 0.197 0.225 0.001 0.025 0.305 0.089
42 0.129 0.227 0.001 0.011 0.326 0.065
43 0.043 0.124 0.002 0.011 0.141 0.015
44 0.024 0.032 0.001 0.008 0.107 0.015
45 0.004 0 0 0.002 0.003 0.008
46 0.331 0.022 0.015 0.081 0.138 0.199
47 0.152 0.045 0.009 0.021 0.164 0.195
48 0.138 0.092 0.005 0.026 0.167 0.174
49 0.177 0.694 0.009 0.011 0.441 0.113
50 0.121 0.895 0.002 0.006 0.486 0.103
51 0.025 0.996 0 0.002 0.369 0.022
52 0.002 0 0.001 0.002 0.001 0.004
53 0.007 0.001 0.002 0.006 0.022 0.008
54 0.267 0.179 0.233 0.044 0.677 0.022
55 0.251 0.184 0.21 0.02 0.703 0.038
56 0.213 0.167 0.121 0.017 0.659 0.028
57 0.029 0.078 0.066 0.006 0.626 0.004
58 0.013 0.023 0.033 0.004 0.461 0.006
59 0.014 0 0 0.003 0.003 0.02
60 0.01 0 0 0 0.002 0.017
61 0.058 0.008 0.001 0.021 0.523 0.045
62 0.052 0.036 0.006 0.008 0.64 0.021
63 0.049 0.066 0.007 0.004 0.492 0.089
64 0.055 0.049 0.001 0.004 0.371 0.028
65 0.012 0.034 0.001 0.01 0.233 0.017
66 0.011 0.027 0.001 0.007 0.243 0.014
67 0.001 0 0 0.001 0.002 0.005
68 0.018 0 0.005 0.013 0.007 0.224
69 0.018 0.001 0.009 0.014 0.017 0.301
70 0.033 0.006 0.012 0.008 0.013 0.198
71 0.012 0.007 0.006 0.004 0.012 0.038
72 0.017 0.005 0.004 0.005 0.013 0.055
73 0.003 0 0.001 0.005 0.005 0.008
74 0.001 0 0 0.003 0.002 0.006
75 0.118 0.726 0.029 0.012 0.56 0.074
76 0.122 0.947 0.03 0.006 0.556 0.102
77 0.083 0.58 0.003 0.001 0.504 0.037
78 0.006 0.01 0.001 0.006 0.106 0.011
79 0.08 0.029 0.053 0.307 0.284 0.277
80 0.099 0.011 0.021 0.247 0.234 0.291
81 0.135 0.02 0.009 0.073 0.294 0.355
82 0.148 0.017 0.007 0.051 0.328 0.251
83 0.125 0.023 0.005 0.024 0.421 0.105
84 0.107 0.017 0.003 0.013 0.505 0.131
85 0.057 0.022 0.003 0.02 0.545 0.069
86 0.067 0.004 0.002 0.014 0.511 0.029
87 0.021 0.001 0.002 0.013 0.477 0.047
88 0.076 0.002 0.003 0.041 0.071 0.044
89 0.195 0.31 0.007 0.068 0.448 0.031
90 0.174 0.214 0.006 0.012 0.508 0.023
91 0.139 0.139 0.003 0.002 0.391 0.017
92 0.002 0.002 0.001 0.03 0.003 0.009
93 0.088 0.233 0.075 0.438 0.12 0.042
94 0.105 0.257 0.053 0.299 0.167 0.113
95 0.063 0.258 0.004 0.045 0.209 0.057
96 0.037 0.215 0.002 0.013 0.245 0.044
97 0.003 0 0 0.2 0.041 0.035
98 0.004 0.003 0 0.002 0.002 0.008
99 0.016 0.055 0.001 0.074 0.415 0.014
100 0.002 0 0 0.015 0.119 0.011
101 0.002 0 0 0.008 0.013 0.005
102 0.07 0.086 0.06 0.272 0.647 0.051
103 0.089 0.184 0.035 0.158 0.717 0.052
104 0.006 0.001 0 0.001 0.002 0.006
105 0.033 0.219 0.032 0.015 0.315 0.298
106 0.037 0.357 0.006 0.004 0.271 0.288
107 0.038 0.753 0.008 0.003 0.285 0.143
108 0.006 0.002 0 0.008 0.003 0.008
109 0.012 0.001 0 0.006 0.004 0.035
110 0.251 0.222 0.033 0.104 0.207 0.275
111 0.258 0.236 0.021 0.02 0.358 0.09
112 0.189 0.183 0.004 0.006 0.324 0.03
113 0.014 0.112 0.001 0.005 0.121 0.009
114 0.01 0.024 0.001 0.004 0.033 0.011
115 0.017 0.002 0.002 0.015 0.596 0.01
116 0.074 0.097 0.002 0.002 0.616 0.009
117 0.101 0.098 0.001 0.001 0.633 0.011
118 0.026 0.046 0.001 0.002 0.577 0.007
119 0.017 0.01 0.001 0.002 0.474 0.008
120 0.001 0.001 0 0.003 0.006 0.013
121 0.002 0.002 0 0.003 0.01 0.015
122 0.028 0.089 0.002 0.027 0.319 0.241
123 0.001 0 0 0.005 0.002 0.005
124 0.003 0.309 0.061 0.028 0.294 0.021
125 0.005 0.267 0.023 0.016 0.334 0.024
126 0.005 0.236 0.012 0.008 0.256 0.012
127 0.016 0.001 0.001 0.003 0.207 0.017
128 0.001 0 0 0.01 0.002 0.014
129 0.002 0 0.002 0.012 0.054 0.094
130 0.005 0.007 0.003 0.004 0.152 0.058
131 0.005 0.016 0.004 0.003 0.199 0.036
132 0.009 0.015 0.006 0.001 0.239 0.059
133 0.001 0.001 0.003 0.005 0.048 0.015
134 0.004 0 0 0.004 0.003 0.01
135 0.015 0.003 0 0.008 0.017 0.015
136 0.006 0.01 0.004 0.005 0.025 0.009
137 0.013 0.062 0.011 0.003 0.069 0.021
138 0.001 0 0 0.001 0.003 0.011
139 0.018 0.017 0.338 0.013 0.09 0.072
140 0.031 0.043 0.15 0.012 0.197 0.061
141 0.046 0.067 0.075 0.002 0.274 0.031
142 0.024 0.036 0.038 0.001 0.175 0.02
143 0.014 0.035 0.059 0.002 0.174 0.05
144 0.008 0 0 0.01 0.016 0.018
145 0.038 0.233 0.01 0.318 0.293 0.115
146 0.071 0.237 0.007 0.349 0.396 0.099
147 0.105 0.367 0.008 0.2 0.444 0.06
148 0.098 0.293 0.003 0.092 0.591 0.048
149 0.213 0.259 0.005 0.042 0.692 0.027
150 0.024 0.015 0.034 0.082 0.42 0.044
151 0.044 0.084 0.188 0.188 0.459 0.044
152 0.068 0.115 0.15 0.106 0.403 0.101
153 0.085 0.167 0.028 0.036 0.467 0.083
154 0.09 0.135 0.008 0.018 0.474 0.099
155 0.07 0.15 0.005 0.012 0.503 0.05
156 0.004 0 0 0.023 0.024 0.044
157 0.003 0 0 0.017 0.016 0.029
158 0.011 0.002 0.005 0.365 0.463 0.24
159 0.014 0.005 0.007 0.353 0.473 0.254
160 0.056 0.049 0.045 0.105 0.298 0.132
161 0.067 0.063 0.037 0.062 0.347 0.145
162 0.011 0.002 0.006 0.006 0.328 0.012
163 0.014 0.005 0.01 0.005 0.459 0.018
164 0.009 0.242 0.012 0.005 0.283 0.009
165 0.002 0.016 0.002 0.006 0.501 0.018
166 0.001 0 0 0.002 0.004 0.013
167 0.001 0.001 0 0.008 0.002 0.024
168 0.019 0 0.001 0.047 0.012 0.227
169 0.031 0.003 0.001 0.059 0.031 0.399
170 0.037 0.003 0.001 0.041 0.036 0.45
171 0.061 0.035 0 0.015 0.108 0.404
172 0.036 0.044 0.001 0.015 0.129 0.362
173 0.027 0.045 0 0.01 0.154 0.308
174 0.028 0.129 0.001 0.01 0.367 0.344
175 0.042 0.133 0.001 0.004 0.382 0.398
176 0.078 0.193 0.002 0.01 0.422 0.217
177 0.006 0.075 0.001 0.004 0.313 0.083
178 0.003 0.016 0.001 0.005 0.194 0.036
179 0.002 0.001 0 0.006 0.003 0.064
180 0.004 0.001 0 0.009 0.002 0.104
181 0.19 0.557 0.035 0.019 0.127 1
182 0.097 0.666 0.008 0.01 0.167 0.961
183 0.05 0.671 0.003 0.012 0.227 0.785
184 0.003 0.02 0.004 0.046 0.229 0.752
185 0.004 0.089 0.009 0.045 0.492 0.022
186 0.008 0.067 0.007 0.02 0.333 0.046
187 0.007 0.063 0.003 0.011 0.344 0.065
188 0.006 0.109 0.001 0.006 0.564 0.014
189 0.003 0.074 0.001 0.005 0.403 0.016
190 0.001 0.012 0.001 0.002 0.251 0.014
191 0.002 0.001 0 0.005 0.151 0.015
192 0.008 0 0 0.004 0.001 0.005
193 0.931 0.295 0.007 0.021 0.747 0.062
194 1 0.526 0.008 0.018 0.777 0.102
195 0.769 0.311 0.005 0.013 0.829 0.026
196 0.007 0.082 0.014 0.021 0.458 0.006
197 0.007 0.162 0.006 0.016 0.385 0.006
198 0.014 0.127 0.004 0.098 0.381 0.01
199 0.022 0.143 0.005 0.004 0.517 0.007
200 0.011 0.116 0.002 0 0.528 0.011
201 0.011 0.082 0.001 0.001 0.561 0.004
202 0.001 0.005 0 0.002 0.2 0.011
203 0.001 0.001 0 0.003 0.122 0.008
204 0.027 0.012 0.002 0.115 0.268 0.105
205 0.026 0.015 0.004 0.048 0.153 0.152
206 0.032 0.012 0.005 0.032 0.11 0.096
207 0.033 0.009 0.003 0.023 0.123 0.078
208 0.077 0.012 0.005 0.015 0.131 0.069
209 0.074 0.029 0.004 0.005 0.599 0.046
210 0.099 0.012 0.001 0.004 0.563 0.025
211 0.052 0.005 0.001 0.002 0.578 0.024
212 0.029 0.002 0.001 0.005 0.405 0.018
213 0.004 0.004 0.009 0.005 0.044 0.009
214 0.032 0.032 0.004 0.005 0.15 0.006
215 0.037 0.025 0.002 0.002 0.119 0.006
216 0.04 0.015 0.002 0.003 0.087 0.008
217 0.011 0.001 0.001 0.003 0.01 0.011
218 0.009 0.001 0 0.002 0.006 0.007
219 0.141 0.275 0.101 0.19 0.239 0.242
220 0.079 0.113 0.065 0.113 0.142 0.158
221 0.189 0.186 0.049 0.09 0.223 0.365
222 0.105 0.101 0.016 0.009 0.236 0.417
223 0.02 0.086 0.026 0.024 0.186 0.093
224 0.019 0.112 0.013 0.052 0.41 0.05
225 0.01 0.07 0.017 0.017 0.22 0.081
226 0.009 0.056 0.01 0.014 0.172 0.038
227 0.008 0.034 0.003 0.005 0.237 0.157
228 0.003 0.021 0.009 0.01 0.19 0.026
229 0.002 0.002 0.003 0.004 0.079 0.016
230 0.046 0.028 0.003 0.017 0.11 0.01
231 0.057 0.067 0.004 0.023 0.152 0.01
232 0.092 0.166 0.006 0.034 0.198 0.009
233 0.094 0.185 0.005 0.016 0.254 0.01
234 0.076 0.192 0.003 0.013 0.359 0.017
235 0.1 0.176 0.001 0.013 0.396 0.015
236 0.004 0.001 0.001 0.011 0.074 0.022
237 0.068 0.671 0.039 0.191 0.691 0.061
238 0.043 0.677 0.03 0.112 0.712 0.064
239 0.058 0.77 0.031 0.097 0.673 0.08
240 0.004 0.001 0.001 0.015 0.005 0.007
241 0.071 0.086 0.003 0.016 0.333 0.012
242 0.081 0.079 0.002 0.005 0.31 0.02
243 0.054 0.051 0.001 0.002 0.242 0.018
244 0.073 0.078 0.001 0.004 0.346 0.028
245 0.017 0.024 0.001 0.005 0.104 0.007
246 0.01 0.006 0 0.003 0.062 0.008
247 0.048 0.008 0.008 0.055 0.196 0.064
248 0.099 0.045 0.015 0.221 0.356 0.048
249 0.192 0.065 0.016 0.128 0.526 0.103
250 0.093 0.106 0.021 0.237 0.36 0.041
251 0.095 0.074 0.022 0.108 0.313 0.033
252 0.02 0.1 0.03 0.021 0.218 0.086
253 0.092 0.05 0.016 0.111 0.308 0.029
254 0.008 0.007 0.002 0.014 0.288 0.009
255 0.001 0 0 0.002 0.006 0.006
256 0 0.002 0 0.008 0.105 0.006
257 0 0.002 0 0.004 0.132 0.004
258 0.002 0 0.002 0.012 0.005 0.01
259 0.007 0.057 0 0.032 0.432 0.011
260 0.02 0.413 0 0.008 0.389 0.009
261 0.039 0.058 0.031 0.038 0.325 0.024
262 0.04 0.34 0.195 0.129 0.721 0.079
263 0.148 0.282 0.159 0.053 0.5 0.058
264 0.093 0.307 0.175 0.082 0.653 0.218
265 0.064 0.277 0.106 0.021 0.697 0.132
266 0.009 0.088 0.003 0.006 0.327 0.026
267 0.305 0.404 0.144 0.65 0.748 0.049
268 0.017 0.013 0.002 0.003 0.214 0.015
269 0.011 0.005 0 0.001 0.061 0.005
270 0.003 0.004 0.001 0.003 0.034 0.009
271 0.001 0.001 0.115 0.007 0.002 0.005
272 0.006 0.004 0.777 0.014 0.022 0.022
273 0.028 0.025 1 0.024 0.52 0.05
274 0.035 0.042 0.94 0.02 0.579 0.044
275 0.083 0.117 0.179 0.006 0.64 0.131
276 0.067 0.214 0.067 0.001 0.7 0.197
277 0.016 0.089 0.001 0.004 0.544 0.049
278 0.003 0.013 0.001 0.004 0.325 0.01
279 0.02 0.143 0.006 0.066 0.503 0.035
280 0.079 0.538 0.04 0.039 0.554 0.036
281 0.099 0.508 0.022 0.018 0.624 0.056
282 0.042 0.201 0.004 0.024 0.53 0.013
283 0.008 0.064 0.001 0.014 0.435 0.005
284 0.013 0.006 0 0.007 0.245 0.004
285 0.017 0.091 0.004 0.074 0.548 0.047
286 0.057 0.135 0.004 0.048 0.55 0.151
287 0.18 0.626 0.006 0.024 0.784 0.044
288 0.193 0.306 0.001 0.008 0.652 0.064
289 0.001 0 0 0.004 0.003 0.006
290 0.002 0.005 0.001 0.002 0.009 0.007
291 0.006 0 0 0.001 0.003 0.006
292 0.004 0.001 0 0 0.002 0.005
293 0.002 0 0 0.008 0.001 0.003
294 0.001 0.001 0 0.001 0.004 0.008
295 0.008 0.065 0.017 0.125 0.126 0.01
296 0.011 0.081 0.021 0.12 0.161 0.016
297 0.016 0 0.001 0.008 0.064 0.03
298 0.017 0.003 0.001 0.004 0.592 0.036
299 0.052 0.021 0.004 0.008 0.837 0.079
300 0.068 0.012 0.002 0.004 0.734 0.169
301 0.045 0.008 0.001 0.001 0.727 0.125
302 0.023 0.001 0.002 0.004 0.634 0.017
303 0.018 0 0.001 0.005 0.497 0.014
304 0.002 0 0.007 0.022 0.113 0.016
305 0.057 0.035 0.011 0.195 0.435 0.029
306 0.006 0.002 0.012 0.056 0.184 0.015
307 0.011 0.024 0.028 0.081 0.242 0.047
308 0.019 0.182 0.027 0.06 0.317 0.043
309 0.104 0.075 0.023 0.068 0.332 0.045
310 0.003 0.041 0.004 0.013 0.539 0.023
311 0.007 0 0.002 0.021 0.093 0.022
312 0.049 0.16 0.132 0.308 0.624 0.064
313 0.01 0.001 0.001 0.021 0.017 0.01
314 0 0.018 0 0 0.01 0.003
315 0.064 0.271 0.003 0.079 0.695 0.011
316 0.072 0.328 0.003 0.064 0.574 0.014
317 0.092 0.496 0.002 0.037 0.734 0.014
318 0.142 0.799 0.002 0.014 0.816 0.046
319 0.159 0.732 0.002 0.013 0.831 0.027
320 0.117 0.777 0.002 0.01 0.831 0.015
321 0.002 0 0 0.004 0.005 0.01
322 0.033 0.283 0.03 0.044 0.654 0.052
323 0.031 0.4 0.056 0.028 0.781 0.032
324 0.018 0.384 0.019 0.009 1 0.019
325 0.025 0.245 0.017 0.004 0.733 0.058
326 0.017 0.226 0.021 0.013 0.721 0.037
327 0.009 0.169 0.015 0.002 0.697 0.01
328 0.007 0.002 0.003 0.23 0.27 0.031
329 0.033 0.15 0.015 0.509 0.717 0.066
330 0.058 0.509 0.024 0.207 0.716 0.054
331 0.011 0.083 0.004 0.017 0.458 0.013
332 0.006 0.014 0.001 0.011 0.339 0.01
333 0.05 0 0 0.008 0.05 0.017
334 0.17 0.011 0.003 0.034 0.414 0.055
335 0.153 0.036 0.002 0.008 0.364 0.027
336 0.086 0.108 0.001 0.003 0.39 0.034
337 0.002 0.004 0 0.002 0.064 0.006
338 0.004 0 0 0.009 0.004 0.013
339 0.021 0 0.004 0.004 0.006 0.018
340 0.465 0.023 0.157 0.35 0.442 0.202
341 0.31 0.027 0.244 0.1 0.393 0.044
342 0.302 0.019 0.15 0.053 0.38 0.034
343 0.463 0.029 0.041 0.014 0.246 0.055
344 0.208 0.042 0.015 0.006 0.173 0.045
345 0.002 0.006 0.001 0.008 0.389 0.013
346 0.002 0.045 0.002 0.004 0.414 0.011
347 0.006 0.08 0 0.006 0.657 0.022
348 0.005 0.039 0 0 0.588 0.018
349 0.006 0.062 0.003 0.089 0.188 0.015
350 0.039 0.238 0.008 0.05 0.454 0.014
351 0.026 0.304 0.009 0.024 0.489 0.013
352 0.066 0.221 0.004 0.014 0.479 0.019
353 0.038 0.256 0.028 0.162 0.639 0.055
354 0.053 0.092 0.011 0.025 0.345 0.047
355 0.009 0.412 0.028 0.099 0.557 0.047
356 0.029 0.11 0.017 0.021 0.413 0.097
357 0.009 0.505 0.01 0.027 0.493 0.033
358 0.007 0.491 0.007 0.015 0.605 0.038
359 0.011 0.624 0.008 0.004 0.569 0.112
360 0.007 0.267 0.001 0.006 0.321 0.02
361 0.105 0.048 0.003 0.007 0.26 0.172
362 0.066 0.158 0.015 0.027 0.472 0.068
363 0.09 0.32 0.055 0.047 0.627 0.103
364 0.307 0.288 0.068 0.049 0.556 0.189
365 0.022 0.069 0.006 0.007 0.394 0.02
366 0.005 0.002 0.006 0.281 0.119 0.021
367 0.075 0.175 0.002 0.044 0.56 0.061
368 0.022 0.103 0.001 0.008 0.463 0.061
369 0.005 0.024 0 0.021 0.391 0.014
370 0.003 0.009 0.001 0.01 0.262 0.016
371 0.001 0 0 0.01 0.047 0.006
372 0.038 0.315 0.002 0.077 0.756 0.022
373 0.026 0.387 0.002 0.03 0.771 0.029
374 0.033 0.628 0.007 0.027 0.661 0.015
375 0.074 0.757 0.006 0.008 0.66 0.022
376 0.039 0.796 0.004 0.002 0.686 0.019
377 0.028 0.833 0.001 0.002 0.639 0.009
378 0.009 0.756 0.003 0.003 0.622 0.004
379 0.004 0.542 0.001 0.002 0.38 0.012
380 0.001 0.001 0 0.002 0.004 0.008
381 0.001 0.001 0 0.002 0.003 0.005
382 0.003 0.003 0.004 0.009 0.122 0.019
383 0.012 0.162 0.027 0.013 0.48 0.022
384 0.021 0.16 0.018 0.012 0.503 0.039
385 0.006 0.11 0.01 0.006 0.336 0.012
386 0.007 0.023 0.002 0.005 0.182 0.014
387 0.031 0.033 0 0.009 0.157 0.045
388 0.035 0.06 0.001 0.009 0.16 0.038
389 0.022 0.046 0 0.004 0.207 0.036
390 0.019 0.043 0 0.007 0.216 0.03
391 0.006 0.004 0 0.003 0.2 0.014
392 0.004 0.001 0 0.003 0.129 0.012
393 0.016 0.019 0.604 0.008 0.184 0.045
394 0.014 0.017 0.686 0.011 0.098 0.056
395 0.01 0.014 0.646 0.011 0.118 0.056
396 0.006 0.365 0.005 0.422 0.597 0.01
397 0.008 0.534 0.015 0.394 0.732 0.017
398 0.006 0.512 0.011 0.358 0.692 0.016
399 0.004 0.562 0.027 0.337 0.808 0.013
400 0.015 0.313 0.003 0.044 0.68 0.016
401 0.012 0.293 0.004 0.035 0.684 0.014
402 0.006 0.104 0.001 0.034 0.431 0.006
403 0.008 0.022 0.001 0.023 0.23 0.012
404 0.03 0.051 0.021 0.152 0.159 0.017
405 0.09 0.28 0.023 0.079 0.285 0.026
406 0.152 0.517 0.031 0.089 0.325 0.018
407 0.101 0.718 0.025 0.092 0.417 0.019
408 0.127 0.731 0.024 0.075 0.413 0.017
409 0.011 0.199 0.002 0.012 0.162 0.009
410 0.024 0.074 0.04 0.302 0.052 0.033
411 0.032 0.227 0.102 0.222 0.167 0.049
412 0.036 0.304 0.045 0.153 0.43 0.078
413 0.064 0.278 0.013 0.025 0.638 0.066
414 0.065 0.195 0.005 0.018 0.617 0.047
415 0 0 0 0.008 0.218 0.086
416 0.001 0.001 0.001 0.008 0.002 0.004
417 0.003 0.003 0 0.005 0.216 0.002
418 0.02 0.009 0.013 0.043 0.424 0.097
419 0.009 0.014 0.002 0.003 0.121 0.015
420 0.01 0.012 0.001 0.004 0.16 0.018
421 0.004 0.024 0.001 0.003 0.451 0.007
422 0.002 0 0.001 0.001 0.045 0.004
423 0.001 0 0 0.006 0.003 0.009
424 0.024 0.045 0.009 0.034 0.169 0.052
425 0.01 0.12 0.003 0.007 0.373 0.022
426 0.003 0 0 0.015 0.015 0.023
427 0.057 0.035 0.006 0.252 0.745 0.127
428 0.05 0.061 0.005 0.321 0.881 0.087
429 0.181 0.818 0.031 0.041 0.788 0.137
430 0.115 0.918 0.048 0.024 0.783 0.043
431 0.025 0.972 0.009 0.02 0.901 0.013
432 0.006 1 0.001 0.022 0.698 0.02
433 0.002 0.701 0.001 0.012 0.669 0
434 0.003 0 0.001 0.575 0.421 0.033
435 0.005 0.001 0.003 1 0.593 0.024
436 0.01 0.025 0.003 0.484 0.76 0.036
437 0.003 0.007 0.02 0.011 0.347 0.007
438 0.018 0.178 0.107 0.013 0.421 0.029
439 0.001 0.153 0.065 0.008 0.004 0.01
440 0.007 0.022 0.001 0.09 0.268 0.022
441 0.011 0.026 0.001 0.069 0.418 0.035
442 0.02 0.085 0 0.02 0.493 0.039
443 0.02 0.039 0 0.01 0.394 0.039
444 0.045 0.549 0.056 0.175 0.581 0.021
445 0.002 0.001 0.001 0.009 0.008 0.012
446 0.003 0.002 0.001 0.01 0.02 0.018
447 0.007 0.009 0.001 0.012 0.057 0.033
448 0.014 0.094 0 0.005 0.222 0.015
449 0.015 0.083 0 0.002 0.118 0.012
450 0.015 0.04 0.001 0.001 0.145 0.015
451 0.004 0.004 0.001 0.005 0.083 0.015
452 0.023 0.01 0.009 0.118 0.367 0.041
453 0.032 0.037 0.01 0.136 0.435 0.048
454 0.049 0.085 0.008 0.055 0.452 0.047
455 0.106 0.143 0.017 0.037 0.643 0.052
456 0.171 0.084 0.007 0.01 0.66 0.017
457 0.084 0.042 0.005 0.003 0.554 0.014
458 0.025 0.003 0.001 0.037 0.101 0.054
459 0.075 0.042 0.005 0.084 0.252 0.057
460 0.16 0.162 0.004 0.022 0.538 0.188
461 0.154 0.113 0.005 0.036 0.543 0.126
462 0.025 0.071 0.004 0.008 0.572 0.051
463 0.014 0.025 0.002 0.007 0.408 0.039
464 0.001 0 0 0.002 0.006 0.012
465 0.002 0.003 0.001 0.001 0.001 0.003
466 0.178 0.065 0.013 0.176 0.226 0.096
467 0.265 0.118 0.011 0.061 0.239 0.129
468 0.14 0.089 0.003 0.026 0.288 0.08
469 0.18 0.234 0.005 0.011 0.441 0.078
470 0.02 0.064 0.002 0.01 0.387 0.021
471 0.004 0.003 0.001 0.005 0.193 0.015
472 0.119 0.215 0.213 0.205 0.3 0.041
473 0.081 0.241 0.367 0.027 0.255 0.036
474 0.055 0.245 0.186 0.013 0.335 0.027
475 0.138 0.234 0.157 0.008 0.463 0.022
476 0.072 0.229 0.113 0.004 0.379 0.017
477 0.048 0.182 0.065 0.001 0.272 0.007
478 0.011 0.164 0.079 0.006 0.121 0.007
479 0.004 0.054 0.013 0.002 0.034 0.006
480 0.273 0.007 0.003 0.015 0.179 0.124
481 0.206 0.01 0.002 0.016 0.188 0.041
482 0.172 0.019 0.001 0.016 0.257 0.052
483 0.198 0.017 0.002 0.009 0.149 0.022
484 0.156 0.002 0.001 0.003 0.07 0.029
485 0.126 0.002 0.002 0.009 0.035 0.019
486 0.322 0.011 0.001 0.001 0.152 0.041
487 0.336 0.015 0 0.002 0.206 0.024
488 0.149 0.052 0 0.002 0.297 0.01
489 0.014 0.026 0 0.002 0.424 0.005
490 0.015 0.551 0.003 0.206 0.481 0.045
491 0.008 0.445 0.002 0.02 0.543 0.044
492 0.003 0.537 0.002 0.019 0.614 0.073
493 0.003 0.553 0.002 0.009 0.661 0.041
494 0.004 0.853 0 0.004 0.685 0.142
495 0.001 0.628 0 0.01 0.626 0.086
496 0 0.216 0.001 0.01 0.718 0.032
497 0 0.057 0 0.004 0.496 0.019
498 0.028 0.102 0.011 0.093 0.199 0.063
499 0.004 0.293 0 0.053 0.191 0.012
500 0.139 0.317 0.001 0.011 0.317 0.024
501 0.581 0.212 0 0.003 0.464 0.079
502 0.291 0.189 0.001 0.009 0.438 0.03
503 0.204 0.16 0 0.005 0.462 0.028
504 0.004 0.001 0.001 0.001 0.344 0.01
505 0.069 0.037 0.02 0.035 0.274 0.031
506 0.069 0.039 0.017 0.025 0.369 0.059
507 0.089 0.066 0.011 0.013 0.247 0.035
508 0.001 0.022 0.001 0.004 0.128 0.022
509 0.006 0.005 0.001 0.018 0.006 0.014
510 0.036 0.051 0.013 0.117 0.419 0.09
511 0.04 0.135 0.039 0.055 0.496 0.11
512 0.009 0.001 0.002 0.003 0.298 0.022
513 0.014 0.003 0.005 0.003 0.256 0.013
514 0.021 0.764 0.044 0.098 0.701 0.059
515 0.009 0.033 0.002 0.002 0.448 0.016
516 0.004 0.026 0.001 0.001 0.439 0.011
517 0.008 0.013 0.003 0.004 0.187 0.017
518 0.012 0.043 0.038 0.253 0.214 0.017
519 0.02 0.178 0.05 0.276 0.221 0.018
520 0.021 0.109 0.006 0.008 0.427 0.025
521 0.012 0.083 0.003 0.006 0.408 0.009
522 0.001 0.038 0.001 0.003 0.215 0.006
523 0 0.632 0.001 0.012 0.115 0.018
524 0.004 0.007 0.001 0.003 0.003 0.008
525 0 0.016 0.002 0.006 0.005 0.009
526 0 0.018 0.001 0.002 0.007 0.012
527 0.048 0.508 0.011 0.094 0.644 0.138
528 0.018 0.639 0.014 0.089 0.714 0.068
529 0.03 0.82 0.023 0.08 0.746 0.046
530 0.002 0.079 0.001 0.004 0.164 0.005
531 0.001 0.108 0 0.005 0.247 0.01
532 0.001 0.009 0 0.001 0.012 0.006
533 0.038 0.002 0 0.005 0.004 0.004
534 0 0 0 0.005 0 0.003
535 0.029 0.284 0.009 0.293 0.766 0.031
536 0.008 0.011 0.002 0.031 0.601 0.011
537 0.006 0.012 0.002 0.022 0.541 0.013
538 0.001 0.003 0.002 0.003 0.383 0.004
539 0 0.002 0.002 0.006 0.133 0.004
540 0.01 0.001 0.121 0.009 0.061 0.03
541 0.012 0.002 0.017 0.007 0.165 0.017
542 0.007 0.174 0.017 0.353 0.23 0.032
543 0.006 0.245 0.022 0.303 0.338 0.041
544 0.005 0.227 0.014 0.233 0.362 0.028
545 0.003 0.177 0.008 0.102 0.321 0.026
546 0.002 0.236 0.003 0.017 0.289 0.01
547 0.002 0.062 0.001 0.004 0.07 0.011
548 0.016 0.155 0.539 0.024 0.562 0.012
549 0.013 0.017 0.037 0.093 0.266 0.056
550 0.012 0.052 0.114 0.165 0.247 0.032
551 0.216 0.191 0.043 0.1 0.564 0.058
552 0.048 0.156 0.024 0.081 0.542 0.081
553 0.007 0.005 0.003 0.02 0.105 0.015
554 0.166 0.676 0.001 0.101 0.681 0.035
555 0.069 0.302 0.001 0.147 0.654 0.009
556 0.139 0.249 0 0.059 0.601 0.023
557 0.147 0.18 0 0.044 0.54 0.039
558 0.047 0.208 0 0.021 0.554 0.029
559 0.035 0.002 0 0.006 0.116 0.028
560 0.025 0.715 0.001 0.001 0.777 0.024
561 0.006 0.548 0.001 0.001 0.654 0.017
562 0.002 0.007 0 0.004 0.122 0.008
563 0.125 0.112 0.001 0.003 0.363 0.051
564 0.105 0.135 0.002 0.006 0.343 0.071
565 0.164 0.189 0.002 0.003 0.402 0.046
566 0.179 0.179 0.003 0.004 0.421 0.05
567 0.08 0.21 0 0 0.53 0.019
568 0.032 0.091 0 0.002 0.528 0.006
569 0.025 0.005 0.094 0.008 0.012 0.022
570 0.043 0.015 0.67 0.005 0.025 0.021
571 0.071 0.017 0.639 0.01 0.061 0.023
572 0.001 0 0.001 0.002 0.005 0.01
573 0.056 0.071 0.011 0.007 0.344 0.031
574 0.017 0.019 0.005 0.005 0.104 0.007
575 0.013 0.001 0.001 0.007 0.005 0.016
576 0.016 0.112 0 0.013 0.374 0.021
577 0.07 0.148 0.047 0.036 0.428 0.028
578 0.089 0.106 0.021 0.029 0.491 0.017
579 0.087 0.039 0.002 0.011 0.447 0.015
580 0.018 0 0.001 0.038 0.005 0.012
Experimental example 2
The fluorescence data obtained by the kit prepared in example 21 was used to perform an algorithmic analysis of the neutralizing titer (whether the sample has a protective effect) of the serum samples of 580 cured patients with new corona patients, as follows:
(1) LR-based neutralization titer level prediction method:
the feature vector of the fluorescence data obtained from the kit prepared in example 21 was input into a LR model trained in advance and calculated to obtain a probability value of the classification of the target serum. The model is obtained by training feature vectors corresponding to the antibody level indexes in a plurality of unprotected sera and the antibody level indexes in a plurality of protected sera.
The preferred function values are: the specific detection result of y =2.09686313 (S1-IgM) + 3.05375507 (S1-IgG) + 0.91398949 (S1-IgA) + 0.2027609 (S2-IgA) + 4.79033777 (S2-IgG) + 1.13682287 (S2-IgM) -0.382805366 is as follows:
Figure T_220818140924632_632660003
and calculating the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate of the model:
true positive 97.07 % True negative 67.65 %
False positive 32.35 % False negative 2.93 %
Rate of accuracy 90 . 17%
(2) The method for predicting the neutralization titer level based on the support SVM comprises the following steps:
normalizing the fluorescence data obtained by the kit prepared in the embodiment 21 to obtain a feature vector of the fluorescence data, randomly selecting 80% of data sets as a training set, using the rest 20% of data sets as a test set, and using the training set for training an SVM (support vector machine) model to obtain an optimal classification hyperplane;
training the SVM model by using a training set to obtain an optimal combination of wavelet basis function parameters corresponding to the characteristic signal group and a corresponding optimal support vector machine classification model; in the process, the parameter combination of the wavelet basis functions is optimized by adopting a self-adaptive genetic algorithm, and the optimized optimal parameter combination is utilized to ensure that the classification coincidence rate of the support vector machine is highest.
The specific detection result is as follows:
Figure T_220818140924710_710789005
and the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate of the model are calculated, and the classifier based on the feature set obtains 89.66% of comprehensive success rate.
True positive 92.79% True negative 79.41%
False positive 20.59% False negative 7.21%
Rate of accuracy 89.66%
(3) RF-based neutralization titer level prediction method:
after pretreatment, 80% of data sets are randomly selected as training sets, the rest 20% of data sets are used as test sets, the training sets are used for training the RF model, and the specific detection result is as follows:
Figure T_220818140924776_776255007
and the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate of the model are calculated, and the classifier based on the feature set obtains 98.10% of comprehensive success rate.
True positive 98.65% True negative 96.32%
False positive 3.68% False negative 1.35%
Rate of accuracy 98.10%
Experimental example 3
The fluorescence data obtained by the kit prepared in example 22 was used to perform an algorithmic analysis of the neutralizing titer (whether the sample has a protective effect) of the serum samples of 580 cured patients with new corona patients, as follows:
(1) LR-based neutralization titer level prediction method:
the feature vector of the fluorescence data obtained from the kit prepared in example 22 is input into a pre-trained LR model for calculation, and the probability value of the classification of the target serum is obtained. The model is obtained by training feature vectors corresponding to the antibody level indexes in a plurality of unprotected sera and the antibody level indexes in a plurality of protected sera.
The preferred function values are: the specific detection result of y =3.18895222 (S1-IgG) + 0.94068715 (S1-IgA) +0.34774695 (S2-IgA) +4.96019302 (S2-IgG) -0.297491254 is as follows:
Figure T_220818140924823_823082009
and calculating the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate of the model:
true positive 97.07% True negative 66.18%
False positive 33.82% False negative 2.93%
Rate of accuracy 89.83%
(2) The method for predicting the neutralization titer level based on the support SVM comprises the following steps:
normalizing the fluorescence data obtained by the kit prepared in the embodiment 21 to obtain a feature vector of the fluorescence data, randomly selecting 80% of data sets as a training set, using the rest 20% of data sets as a test set, and using the training set for training an SVM (support vector machine) model to obtain an optimal classification hyperplane;
training the SVM model by using a training set to obtain an optimal combination of wavelet basis function parameters corresponding to the characteristic signal group and a corresponding optimal support vector machine classification model; in the process, the parameter combination of the wavelet basis functions is optimized by adopting a self-adaptive genetic algorithm, and the optimized optimal parameter combination is utilized to ensure that the classification coincidence rate of the support vector machine is highest.
The specific detection result is as follows:
Figure T_220818140924885_885590011
and the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate of the model are calculated, and the classifier based on the feature set obtains 89.48% of comprehensive success rate.
True positive 92.79% True negative 78.68%
False positive 21.32% False negative 7.21%
Rate of accuracy 89.48%
(3) RF-based neutralization titer level prediction method:
after pretreatment, 80% of data sets are randomly selected as training sets, the rest 20% of data sets are used as test sets, the training sets are used for training the RF model, and the specific detection result is as follows:
Figure T_220818140924936_936341013
and the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate of the model are calculated, and the classifier based on the feature set achieves the comprehensive success rate of 98.62 percent.
True positive 99.32% True negative 96.32%
False positive 3.68% False negative 0.68%
Rate of accuracy 98.62%
Experimental example 4
The fluorescence data obtained by the kit prepared in example 23 was used to perform an algorithmic analysis of the neutralizing titer (whether the sample has a protective effect) of the serum samples of 580 cured patients with new corona patients, as follows:
(1) LR-based neutralization titer level prediction method:
the feature vector of the fluorescence data obtained from the kit prepared in example 22 is input into a pre-trained LR model for calculation, and the probability value of the classification of the target serum is obtained. The model is obtained by training a plurality of unprotected serum antibody level indexes and a plurality of protective serum antibody level indexes corresponding to feature vectors.
The preferred function values are: y =2.12011703 (S1-IgM) + 3.06835539 (S1-IgG) +4.78491836 (S2-IgG) + 1.14629294 (S2-IgM) -0.354555657
The specific detection result is as follows:
Figure T_220818140925014_014991015
and calculating the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate of the model:
true positive 97.30% True negative 67.65%
False positive 32.35% False negative 2.70%
Rate of accuracy 90.34%
(2) The method for predicting the neutralization titer level based on the support SVM comprises the following steps:
normalizing the fluorescence data obtained by the kit prepared in the embodiment 21 to obtain a feature vector of the fluorescence data, randomly selecting 80% of data sets as a training set, using the rest 20% of data sets as a test set, and using the training set for training an SVM (support vector machine) model to obtain an optimal classification hyperplane;
training the SVM model by using a training set to obtain an optimal combination of wavelet basis function parameters corresponding to the characteristic signal group and a corresponding optimal support vector machine classification model; in the process, a self-adaptive genetic algorithm is adopted to optimize the parameter combination of the wavelet basis functions, and the optimized optimal parameter combination is utilized to enable the classification coincidence rate of the support vector machine to be highest.
The specific detection result is as follows:
Figure T_220818140925258_258628017
and the true positive rate, false positive rate, true negative rate, false negative rate and prediction accuracy under the model are calculated, and the classifier based on the feature set obtains 89.83% of comprehensive success rate.
True positive 92.34% True negative 81.62%
False positive 18.38% False negative 7.66%
Rate of accuracy 89.83%
(3) RF-based neutralization titer level prediction method:
after pretreatment, 80% of data sets are randomly selected as training sets, the rest 20% of data sets are used as test sets, the training sets are used for training the RF model, and the specific detection result is as follows:
Figure T_220818140925305_305516019
and the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate of the model are calculated, and the classifier based on the feature set obtains 97.93% of comprehensive success rate.
True positive 9 8.65 % True negative 9 5.59 %
False positive 4.41 % False negative 1.35 %
Rate of accuracy 9 7.93 %
Experimental example 5
The fluorescence data obtained by the kit prepared in example 24 was used to perform an algorithmic analysis of the neutralizing titer (whether the sample has a protective effect) of the serum samples of 580 cured patients with new corona patients, as follows:
(1) LR-based neutralization titer level prediction method:
the feature vector of the fluorescence data obtained from the kit prepared in example 22 is input into a pre-trained LR model for calculation, and the probability value of the classification of the target serum is obtained. The model is obtained by training feature vectors corresponding to the antibody level indexes in a plurality of unprotected sera and the antibody level indexes in a plurality of protected sera.
The preferred function values are: y =5.63203179 (S2-IgG) -0.183104242
The specific detection result is as follows:
Figure T_220818140925354_354336021
and calculating the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate of the model:
true positive 96.85% True negative 68.38%
False positive 31.62% False negative 3.15%
Rate of accuracy 90.17%
(2) The method for predicting the neutralization titer level based on the support SVM comprises the following steps:
normalizing the fluorescence data obtained by the kit prepared in the embodiment 21 to obtain a feature vector of the fluorescence data, randomly selecting 80% of data sets as a training set, using the rest 20% of data sets as a test set, and using the training set for training an SVM (support vector machine) model to obtain an optimal classification hyperplane;
training the SVM model by using a training set to obtain an optimal combination of wavelet basis function parameters corresponding to the characteristic signal group and a corresponding optimal support vector machine classification model; in the process, the parameter combination of the wavelet basis functions is optimized by adopting a self-adaptive genetic algorithm, and the optimized optimal parameter combination is utilized to ensure that the classification coincidence rate of the support vector machine is highest.
The specific detection result is as follows:
Figure T_220818140925401_401209023
and the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate of the model are calculated, and the classifier based on the feature set obtains 88.62% of comprehensive success rate.
True positive 93.47 % True negative 72.79 %
False positive 27.21 % False negative 6.53 %
Rate of accuracy 88.62 %
(3) RF-based neutralization titer level prediction method:
after pretreatment, 80% of data sets are randomly selected as training sets, the rest 20% of data sets are used as test sets, the training sets are used for training the RF model, and the specific detection result is as follows:
Figure T_220818140925448_448099025
and the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate of the model are calculated, and the classifier based on the feature set achieves the comprehensive success rate of 92.93 percent.
True positive 94.37% True negative 88.24%
False positive 11.76% False negative 5.63%
Rate of accuracy 92.93%
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.

Claims (1)

1. The construction method of the neutralizing antibody titer prediction model based on random forests and used for novel coronavirus vaccination or secondary recurrence evaluation after infection is characterized in that a kit used by the construction method comprises the following steps: a detection reagent strip containing a quantum dot specific protein complex;
the detection reagent strip comprises a bottom card, a sample pad, a quantum dot marker combination pad, a chromatography reaction membrane and absorbent paper;
wherein the quantum dot label binding pad adsorbs a quantum dot specific protein complex; the quantum dot specific protein compound is mainly obtained by coupling quantum dots with novel coronavirus specific proteins;
the novel coronavirus specific protein is novel coronavirus S2-ECD protein and novel coronavirus S1-RBD protein;
the novel coronavirus S2-ECD protein is an extra-cellular domain (ECD) protein of 2019-nCoVS2 subunit; the novel coronavirus S1-RBD protein is a 2019-nCoV surface spike protein S1 subunit Receptor Binding Domain (RBD) protein;
the chromatography reaction membrane is provided with detection lines which are an IgA detection line and an IgG detection line;
the preparation method of the kit comprises the following steps:
(a) preparing novel coronavirus recombinant antigens S1-RBD protein and S2-ECD protein:
(1) PCR amplifying S2-ECD gene and S1-RBD gene encoding the novel coronavirus antigen by adopting a gene cloning technology;
(2) transferring the S2-ECD gene into 293 cells to express the gene, transferring the S1-RBD gene into 293 cells to express the gene, and obtaining novel coronavirus recombinant antigens S2-ECD protein and S1-RBD protein;
(b) and preparing a chromatographic reaction membrane:
attaching an NC film with the width of 25cm to the middle area of a PC bottom card, then respectively diluting anti-human IgA, anti-human IgG and goat anti-rabbit IgG antibodies to 0.2-1 mg/ml by using PBS diluent, and scribing on a detection line area and a quality control line area corresponding to the NC film by using a gold spraying film scribing instrument; drying in a 37 ℃ oven for 12-24h, and sealing the bag for later use;
(c) preparing a sample pad:
uniformly coating 20-100 mM Tris-HCl diluent with pH of 8.0, containing 0.5% BSA, 0.5% PVP and 0.5% TWEEN-20 on an untreated sample pad by using a liquid transfer gun and a coating rod, drying at 37 ℃ for 12-24h, and sealing for later use;
(d) preparing a quantum dot-labeled protein complex:
(1) adding 200 mul of qds into 800 mul of MES buffer solution with pH of 6, adding 40-160 mul of EDC and 10-40 mul of NHS for activation, and activating for 15-60 min at 37 ℃; centrifuging the activated solution, and removing the supernatant by using a pipette;
(2) re-dissolving the precipitate obtained in the step (1) after centrifugation by using 1000 mul of 10-50 mM MES buffer solution with pH value of 6, and if re-dissolving is not thorough, re-dissolving by using ultrasonic assistance; centrifuging the redissolved solution, removing supernatant by using a pipette gun, redissolving and precipitating by using 1000 microliter 10-50 mM MES buffer solution with pH of 6, and if the redissolution is not complete, using ultrasonic to assist the redissolution;
(3) adding 20-100 mul of novel coronavirus S1-RBD protein or S2-ECD protein diluted to 1mg/ml by 10-50 mM MES buffer solution with pH of 6 into the re-solution, and coupling at 37 ℃ for 60-300 min;
(4) after the coupling is finished, adding 100 mul of Tris-HCl diluent with pH8.0 and 20-100 mM containing 100-500 mM glycine and 10% BSA for sealing, and sealing for 30-120 min at 37 ℃;
(5) centrifuging the sealed solution, and removing the supernatant by using a pipette; carrying out redissolution precipitation on 500-1000 mu l Tris-HCl diluent, if the redissolution is not thorough, using ultrasonic to assist the redissolution, continuing centrifugation, and using a liquid transfer gun to remove supernatant; carrying out redissolution precipitation on 500-1000 mul of 20-100 mM Tris-HCl diluent with pH of 8.0, if redissolution is not thorough, using ultrasonic to assist redissolution, and storing at 4 ℃, so as to respectively obtain a quantum dot marker of which the specific protein is novel coronavirus S2-ECD protein and a quantum dot marker of which the specific protein is novel coronavirus S1-RBD protein;
(e) preparing a quantum dot marker binding pad:
diluting the prepared quantum dot marker with the specific protein of the novel coronavirus S2-ECD protein or the quantum dot marker with the specific protein of the novel coronavirus S1-RBD protein by a Tris-HCl diluent with the concentration of 20-100 mM, the pH value of the Tris-HCl diluent is 8.0, the Tris-HCl diluent contains 0.5% BSA and 2% trehalose for 20-100 times, spraying the diluted solution on a treated release pad by a film-drawing gold spraying instrument, and drying the treated release pad at 37 ℃ for 12-24 hours to respectively obtain a quantum dot marker binding pad with the specific protein of the novel coronavirus S2-ECD protein and a quantum dot marker binding pad with the specific protein of the novel coronavirus S1-RBD protein;
or diluting the prepared quantum dot marker with the specific protein of the novel coronavirus S2-ECD protein or the quantum dot marker with the specific protein of the novel coronavirus S1-RBD protein by 20-100 times with Tris-HCl diluent of which the pH is 8.0 and which contains 0.5% BSA and 2% trehalose, spraying the diluted solution onto an untreated release pad by using a liquid transfer gun, uniformly coating the release pad by using a coating rod, finally putting the release pad into a freeze dryer for freeze drying, and sealing the bag for later use after the program is run to respectively obtain a quantum dot marker combination pad with the specific protein of the novel coronavirus S2-ECD protein and a quantum dot marker combination pad with the specific protein of the novel coronavirus S1-RBD protein;
(f) the preparation method of the reagent strip comprises the following steps:
overlapping and adhering the prepared chromatographic reaction membrane, the prepared quantum dot marker binding pad with specific protein being novel coronavirus S2-ECD protein or the prepared quantum dot marker binding pad with specific protein being novel coronavirus S1-RBD protein, the prepared sample pad and absorbent paper on a PVC (polyvinyl chloride) back plate;
wherein, the sample pad and the quantum dot marker combination pad are sequentially lapped at one end of the chromatography reaction membrane, the absorbent paper is lapped at the other end of the chromatography reaction membrane, and then the parameters of the slitter are adjusted to slit the sample pad and the quantum dot marker combination pad into test strips with the width of 3-4 mm;
respectively obtaining a novel coronavirus detection reagent strip of which the specific protein on the binding pad is a quantum dot marker of the novel coronavirus S2-ECD protein and a novel coronavirus detection reagent strip of which the specific protein on the binding pad is a quantum dot marker of the novel coronavirus S1-RBD protein;
the construction method of the prediction model comprises the following steps:
the prepared kit is used for detecting serum samples of 580 cured new crown patients to obtain fluorescence data;
the obtained fluorescence data were used to perform an algorithmic analysis of the neutralization titers of the serum samples of 580 cured patients with new corona, as follows:
after pretreatment, 80% of data sets are randomly selected as training sets, the rest 20% of data sets are used as test sets, the training sets are used for training the RF model, and the specific detection result is as follows:
Figure T_220817152311028_028187001
the true positive rate, the false positive rate, the true negative rate, the false negative rate and the prediction accuracy rate under the model are calculated, and a classifier based on the feature set obtains a comprehensive success rate of 98.62 percent;
true positive 99.32% True negative 96.32% False positive 3.68% False negative 0.68% Rate of accuracy 98.62%
The construction method of the random forest based neutralizing antibody titer prediction model for novel coronavirus vaccination or secondary relapse assessment after infection is used for non-diagnostic and/or therapeutic purposes.
CN202011523856.9A 2020-12-21 2020-12-21 Method for predicting titer of neutralizing antibody of novel coronavirus and kit thereof Active CN112611870B (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN202011523856.9A CN112611870B (en) 2020-12-21 2020-12-21 Method for predicting titer of neutralizing antibody of novel coronavirus and kit thereof
PCT/CN2021/071877 WO2022134241A1 (en) 2020-12-21 2021-01-14 Method for predicting novel coronavirus neutralizing antibody titers and kit therefor

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011523856.9A CN112611870B (en) 2020-12-21 2020-12-21 Method for predicting titer of neutralizing antibody of novel coronavirus and kit thereof

Publications (2)

Publication Number Publication Date
CN112611870A CN112611870A (en) 2021-04-06
CN112611870B true CN112611870B (en) 2022-09-16

Family

ID=75243974

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011523856.9A Active CN112611870B (en) 2020-12-21 2020-12-21 Method for predicting titer of neutralizing antibody of novel coronavirus and kit thereof

Country Status (2)

Country Link
CN (1) CN112611870B (en)
WO (1) WO2022134241A1 (en)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113252908B (en) * 2021-06-09 2021-09-28 泛肽生物科技(浙江)有限公司 Flow type kit for detecting novel coronavirus neutralizing antibody and detection method
CN113834930A (en) * 2021-07-18 2021-12-24 杭州迈尔德生物科技有限公司 Novel coronavirus neutralizing antibody rapid detection kit based on quantum dot fluorescence and application thereof
CN113267634B (en) * 2021-07-20 2021-10-08 南京申基医药科技有限公司 Test strip for combined detection of IgG, IgM and neutralizing antibody, preparation method thereof and kit

Family Cites Families (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016139659A1 (en) * 2015-03-01 2016-09-09 Immunarray Ltd. Diagnosis of systemic lupus erythematosus using protein, peptide and oligonucleotide antigens
CN110658343B (en) * 2019-10-12 2023-02-14 中山大学附属第六医院 Application of immunoglobulin detection reagent in preparation of colorectal cancer diagnostic agent
LT3869199T (en) * 2020-02-20 2022-07-11 Euroimmun Medizinische Labordiagnostika Ag A method and reagents for the diagnosis of sars-cov-2
CN111239392B (en) * 2020-02-26 2023-04-21 浙江诺迦生物科技有限公司 Novel serological diagnosis kit for coronavirus pneumonia (COVID-19)
CN111007139B (en) * 2020-03-09 2020-06-23 中国疾病预防控制中心传染病预防控制所 Rapid brucella infection detection method based on serum
CN111426844A (en) * 2020-03-13 2020-07-17 南京农业大学 Novel fluorescence immunochromatographic test strip for combined detection of coronavirus SARS-CoV-2 IgG-IgM antibody
CN111351927A (en) * 2020-03-17 2020-06-30 陈韬 Antibody matrix detection method (MEGA method) aiming at pathogen antigen and multi-connected detection card
CN111413498B (en) * 2020-04-08 2023-08-04 复旦大学附属中山医院 Autoantibody 7-AAb detection panel for liver cell liver cancer and application thereof
CN111856027B (en) * 2020-04-16 2022-05-10 中国科学院苏州纳米技术与纳米仿生研究所 New coronavirus antibody detection kit suitable for examination of patients without obvious symptoms
CN111521818B (en) * 2020-04-27 2021-11-02 深圳海博生物技术有限公司 Application of specific IgA in preparation of kit for evaluating COVID-19 disease risk, disease severity and prognosis evaluation
DE20175031T1 (en) * 2020-05-15 2021-09-09 Euroimmun Medizinische Labordiagnostika Ag Method for determining the effectiveness of a SARS-CoV-2 vaccine
CN111579782B (en) * 2020-05-25 2023-10-10 山西瑞豪生物科技有限公司 Biomedical detection method for intelligent fluorescent multi-marker
CN111562368A (en) * 2020-06-18 2020-08-21 威海威高生物科技有限公司 SARS-CoV-2 neutralizing antibody detection kit
CN112051400A (en) * 2020-09-03 2020-12-08 江苏美克医学技术有限公司 Immunochromatography kit for detecting novel coronavirus neutralizing antibody and detection method
CN112098644B (en) * 2020-09-11 2022-03-08 江苏美克医学技术有限公司 Kit for detecting novel coronavirus neutralizing antibody by enzyme-linked immunosorbent assay and detection method thereof

Also Published As

Publication number Publication date
WO2022134241A1 (en) 2022-06-30
CN112611870A (en) 2021-04-06

Similar Documents

Publication Publication Date Title
CN112611870B (en) Method for predicting titer of neutralizing antibody of novel coronavirus and kit thereof
Bauer The potential significance of high avidity immunoglobulin G (IgG) for protective immunity towards SARS-CoV-2
Kennedy et al. Varicella-zoster virus gene expression in latently infected and explanted human ganglia
Bossart et al. Neutralization assays for differential henipavirus serology using Bio-Plex protein array systems
Tewari et al. Characterization of immune responses to baculovirus-expressed equine herpesvirus type 1 glycoproteins D and H in a murine model
CN112375768A (en) Pseudo-virus of COVID-19 coronavirus, preparation method and application thereof
CN106442981B (en) A kind of 1 type antibody indirect ELISA diagnostic kit of human bocavirus
CN112592390A (en) Novel coronavirus specific antigen peptide and use thereof
Dieterle et al. Genetic depletion studies inform receptor usage by virulent hantaviruses in human endothelial cells
WO2023066396A1 (en) Core amino acid sequence group for targeted recognition of anti-sars-cov-2 neutralizing antibodies n-igy-pabs, and use thereof
CN116041489A (en) Monkey pox virus binding protein and application thereof, and monkey pox virus detection kit
Lowry et al. Immunity in strain 2 guinea-pigs inoculated with vaccinia virus recombinants expressing varicella-zoster virus glycoproteins I, IV, V or the protein product of the immediate early gene 62
CN113189333A (en) Kit containing quantum dot immunofluorescence detection reagent strip and application of kit
Gowrishankar et al. Productive varicella-zoster virus infection of cultured intact human ganglia
Randall et al. Glycoproteins with type common and type specific antigenic sites excreted from cells infected with herpes simplex virus types 1 and 2
CN113791212B (en) Novel coronavirus neutralizing antibody magnetic bead fluorescence detection kit and detection method thereof
US20050106563A1 (en) Epitope profiles of SARS coronavirus
US20230168247A1 (en) Specificity enhancing reagents for covid-19 antibody testing
Foà-Tomasi et al. Identification of an 85 kDa phosphoprotein as an immunodominant protein specific for human herpesvirus 7-infected cells
Hackney et al. In vitro and in ovo expression of chicken gamma interferon by a defective RNA of avian coronavirus infectious bronchitis virus
US20210403529A1 (en) Tcr-enriched clonotype, acquisition method and use thereof
Lin et al. Antibody responses of cattle with respiratory coronavirus infections during pathogenesis of shipping fever pneumonia are lower with antigens of enteric strains than with those of a respiratory strain
Fujima et al. Discrimination of antibody to herpes B virus from antibody to herpes simplex virus types 1 and 2 in human and macaque sera
Kydd et al. A molecular approach to the identification of cytotoxic T-lymphocyte epitopes within equine herpesvirus 1
SUGIURA et al. Evaluation of enzyme-linked immunosorbent assay for titration of antibody to equine herpesvirus type 1

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right

Effective date of registration: 20230909

Address after: Room 303, block a, 3 / F, building 1, 351 Changhe Road, Changhe street, Binjiang District, Hangzhou City, Zhejiang Province 310000

Patentee after: Hangzhou Kaiman Health Technology Co.,Ltd.

Address before: Room 403-5, building 1, Zhongbo building, Xianlin street, Yuhang District, Hangzhou, Zhejiang 311100

Patentee before: Hangzhou Baolin Biotechnology Co.,Ltd.

TR01 Transfer of patent right