CN111766383A - Method for detecting pathogenic virus and related protein thereof and predicting novel unknown virus - Google Patents
Method for detecting pathogenic virus and related protein thereof and predicting novel unknown virus Download PDFInfo
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Abstract
The invention provides a method for detecting pathogenic virus and related protein thereof and prejudging novel unknown virus, which comprises the steps of preparing a biochip containing a biomolecular layer in advance; injecting a sample to be detected into the flow cell, wherein the sample and different biomolecules modified at different positions on the biomolecule layer have different degrees of binding reaction; tracking different changes of reflected or transmitted light intensity at different sites caused by the occurrence of the binding reaction by using imaging equipment to form a signal set; and converting the signal set into a data set, performing pattern recognition on the data set by using an optimized algorithm model, analyzing whether the viruses contained in the sample belong to the discovered viruses, judging the types of the viruses if the viruses are the discovered viruses, and performing early warning if the viruses are unknown viruses. The invention can rapidly and timely identify the virus types, carry out early warning, arrange in advance, prevent and control the epidemic situation, and relieve the public health pressure at the initial stage of the epidemic situation, thereby reducing the casualties and the economic loss caused by the outbreak of the epidemic situation.
Description
Technical Field
The invention relates to the technical field of virus species identification, in particular to a method for detecting pathogenic viruses and related proteins thereof and prejudging novel unknown viruses.
Background
The virus is a microbe which is easy to mutate and switch hosts, and has great impact on the progress of human society. In the future, viruses will certainly attack human society repeatedly, causing huge casualties and economic losses.
The existing detection techniques for viruses, particularly SARS-CoV-2, can be broadly divided into methods such as isolation culture and identification of viruses, molecular diagnostic techniques, and immunoassay.
The virus isolation is always the gold standard for laboratory virus diagnosis in the virus isolation culture and identification method, the virus isolation is required to be carried out under the condition of virus culture, pathogenicity identification of the virus is carried out by using the classical Koch rule through collection of a series of samples (such as nasopharyngeal swab, tracheal suction, sputum or lung tissue, blood, excrement and the like) and virus which is successfully inoculated to human cells and cultured under the strict laboratory condition, morphological observation is carried out on virus particles by using an electron microscope, the whole gene of the virus is sequenced and detected by using a sequencing instrument, and finally the virus type is determined.
Molecular diagnostic techniques mainly include sequencing, amplification and nucleic acid detection techniques related to viral genes. The virus whole genome sequencing is the basis for developing other nucleic acid detection technologies, is usually applied to the identification and detection of unknown viruses, and provides reference information for the virus-caused diseases. Chinese scientists successfully isolate and culture SARS-CoV-2 from patients in a short time by using a second-generation sequencing technology and perform genome sequencing to determine that the virus belongs to the beta coronavirus genus and is the seventh coronavirus other than the six known human coronavirus, which provides great help for various scientists to develop a specific nucleic acid detection kit and a new technology aiming at the new coronavirus. The accuracy of genome sequencing for determining the diagnosis of a suspected patient is very high. However, virus isolation and culture need to be carried out by a special person in a biological laboratory with enough safety level, the time is long, the risk is high, and the method is not suitable for clinical rapid high-throughput screening and diagnosis. The nucleic acid detection technology based on Polymerase Chain Reaction (PCR) can be used for early diagnosis of suspected patients by collecting respiratory tract samples of the suspected patients and carrying out reverse transcription PCR (RT-PCR) on the premise of knowing the complete gene sequence of SARS-CoV-2. The method can be divided into traditional RT-PCR, real-time fluorescence quantitative RT-PCR and the like, and digital PCR which is combined with the microfluidic technology and can be absolutely quantitative. The series of technologies have been developed more mature and have high commercialization degree, and a plurality of companies produce kits and detection equipment matched with the technologies in the global range. Only in China, a plurality of enterprises have developed a nucleic acid detection kit for the new coronavirus and have provided a medical instrument registration certificate. Isothermal nucleic acid amplification techniques have also received increased attention in recent years. Among them, loop-mediated isothermal amplification (LAMP) is most widely used. The technology does not need strict temperature control conditions in the traditional PCR, can complete an amplification procedure in a constant temperature state, has detection sensitivity similar to that of real-time fluorescent quantitative RT-PCR, can complete amplification in about 1 hour, but has higher technical difficulty (mainly primer design difficulty) and is difficult to carry out high-flux detection. In addition, emerging gene editing techniques are also being applied recently to the detection of new coronavirus. The most notable is the SHERLLOCK technology combining CRISPR/Cas technology and recombinant polymerase amplification technology (RPA), which can amplify trace target RNA under isothermal conditions and perform visual detection within 1 hour. Has the characteristics of simple and convenient operation, rapidness, high sensitivity and the like. The nucleic acid mass spectrum technology also belongs to a novel technology, combines nucleic acid amplification and mass spectrum detection, and has the characteristics of high accuracy, high sensitivity, high flux and the like. Enterprises in China also develop nucleic acid mass spectrometry kits capable of detecting various pathogens simultaneously. However, this method requires a high-end mass spectrometer, has a very high instrument cost, and has a high qualification requirement for human operation. In a word, various nucleic acid detections taking a nucleic acid amplification technology as a core generally have higher sensitivity, but the detection result greatly depends on the quality of sample collection and storage (RNA is easy to degrade); the detection time is long and usually varies from several hours; the cost of the required reagent is high; the requirement on the operation of personnel is high, and the steps are complicated; the requirements for instrument equipment are high, wherein each type of nucleic acid amplification equipment and mass spectrometry equipment are very expensive.
The immune colloidal gold technology in the immune detection technology is one of the earliest researched and developed immune detection methods, and is widely applied to basic detection sites and field detection due to the inherent characteristics of convenient and quick operation, low cost and the like. In general, the technology can be used for directly detecting pathogen antigen protein, and can also be used for detecting specific IgM and IgG antibodies which are generated by human bodies through immune reaction. Several biological companies have been developed successfully in China to detect IgM and IgG antibodies in human blood that specifically react with SARS-CoV-2 protein. But it is unstable because sensitivity depends on the interaction between proteins. Signal amplification due to the absence of enzymatic reactions is generally lower than nucleic acid detection and is accompanied by higher false negative or false positive results. Therefore, the technology is only suitable for auxiliary diagnosis, rapid screening and epidemiological investigation. Moreover, because the production of human antibodies takes time, the immunoassay based on the detection of IgM and IgG has a certain window blank. The detection sensitivity can be improved to a great extent by marking fluorescent molecules and utilizing an enzyme-linked immunosorbent assay technology, but the detection cost and steps are increased, the advantage of time is sacrificed, and certain requirements are also made on a customized instrument.
In summary, the prior art is mostly a molecular diagnostic technique, and the core of the prior art is directed target nucleic acid amplification, so genome sequencing of pathogens such as viruses is a prerequisite. None of these techniques work effectively before gene sequence determination. However, the isolation culture, whole-gene sequencing and identification of viruses require a long time of work by a large number of professionals in high-safety-level laboratories. In addition, the detection technology based on nucleic acid amplification is indispensable and expensive for the requirements of instruments, and the required reagents are complex and complicated to operate. Due to the nucleic acid amplification reaction, the detection time is longer compared to the immunoassay.
Therefore, how to provide a method which has low cost and high accuracy, can rapidly detect viruses and has the capability of predicting unknown viruses is a technical problem to be solved urgently.
Disclosure of Invention
The invention aims to provide a method for detecting pathogenic viruses and related proteins thereof and predicting novel unknown viruses, so as to solve the problems in the prior art and quickly and accurately identify the viruses at low cost. In order to achieve the purpose, the invention provides the following scheme:
preparing a biochip comprising a biomolecule layer in advance; the biochip is formed by sequentially clinging a substrate material, a metal layer and a biological molecular layer from bottom to top; the biomolecule layer is modified to the metal layer by different biomolecules in an array form, and the biomolecule species comprise protein molecules, polypeptide molecules, oligonucleotide molecules, peptide nucleic acid molecules, oligosaccharide molecules and lipid molecules, or any combination of the above species;
injecting a sample to be detected into a flow cell, wherein the sample and different biomolecules modified at different positions on the biomolecule layer have different degrees of binding reaction;
tracking different changes of reflected or transmitted light intensity at different positions caused by the occurrence of the binding reaction by using imaging equipment to form a signal set;
and converting the signal set into a data set, performing pattern recognition on the data set by using an optimized algorithm model, analyzing whether the viruses contained in the sample belong to the discovered viruses, judging the types of the viruses if the viruses belong to the discovered viruses, and performing early warning if the viruses are unknown viruses.
Preferably, the substrate material is selected from transparent materials with a refractive index between 1.0 and 3.0, including but not limited to glass, quartz, and plexiglass.
Preferably, the metal layer is distributed on the substrate material in a form of a continuous, an array, a radiation arrangement or a combination of the patterns, so that different biomolecules can be modified at different sites on the metal layer;
the metal layer material includes but is not limited to a metal film, a metal film with periodic nanostructure holes, and metal particles with periodic nanostructures; the metal species include, but are not limited to, gold, silver, platinum, copper, aluminum.
Preferably, the modification method comprises chemical covalent bond completion through metal-sulfhydryl, chemical covalent bond completion on a layer of self-assembly molecules, coordination bond completion and other physical adsorption completion.
Preferably, the imaging device comprises a surface plasmon resonance, SPR, spectroscopic imaging device, raman imaging device, fluorescence and other optical means imaging device or any combination of the above imaging techniques.
Preferably, the biochip is used with the imaging device, and is adapted to be used in a whole according to different imaging technologies, and the modified parts include the composition of biochip material and the form of imaging detection.
Preferably, when the algorithm model is optimized, a plurality of virus samples with known classes and protein samples thereof are prepared in advance and numbered; and with the aid of the imaging equipment, sequentially acquiring signal characteristics of the viruses with known types and proteins thereof when the viruses and the proteins thereof are combined with a bio-molecular layer of the biochip, and labeling the signal characteristics according to the types of the viruses to obtain the corresponding relation between the viruses of the specific types and the signal characteristics.
Preferably, the set of signals generated by the binding reaction is converted into a data set, namely:
{ΔI(x,y)},x＝1,2,...,N,y＝1,2,...,M
wherein, Delta I (x, y) represents the light signal change value before and after each site reaction, and (x, y) represents the position information of the site;
there are K classes of pathogens P1,P2,...,PKGiven a set of probe data
D＝{(ΔI1(x,y),P1),(ΔI2(x,y),P2),...,(ΔIK(x,y),PK)}，
Pairing the K classes one by using a classification recognition algorithm so as to realize the detection of pathogen species, namely:
PK＝f(ΔIk(x,y)),k＝1,2,...,K
wherein f (-) represents a classification recognition model, namely the optimized algorithm model, and the classification recognition algorithm comprises but is not limited to a partial least square method, a support vector machine and an artificial neural network method;
after obtaining the classification model f (-) with a given detection dataset D, for the unknown optical variation signal Δ I (x, y), the corresponding pathogen class is obtained: pkF (Δ I (x, y)), K ∈ {1, 2.., K }, thereby identifying whether the virus in the sample to be tested is a known virus and its category;
the data set processing mode can also utilize a feature extraction method to preprocess the original optical signal delta I (x, y) and establish an identification model between pathogen information and features, namely:
Pk＝f(hk),k＝1,2,...,K
wherein h isk＝f'(ΔIk(x, y)) is the optical signal Δ I for the kth pathogenk(x, y) a characteristic value, f' () representing a functional transformation relationship between the original optical signal and the characteristic value; corresponding feature extraction methods include, but are not limited to, Principal Component Analysis (PCA) methods.
The invention discloses the following technical effects: the invention provides a method for detecting pathogenic viruses and related proteins thereof and predicting novel unknown viruses by utilizing a combination principle similar to immunoassay and based on an optical cross-sensing technology. According to the technical scheme, different biomolecules are placed at different positions of a biochip, imaging equipment is utilized to track different changes of reflected or transmitted light intensity at different positions caused by binding reaction to form a signal set, the signal set is converted into a data set, an optimized algorithm model is utilized to perform pattern recognition on the data set, whether viruses contained in a sample belong to found viruses or not is analyzed, the types of the viruses are judged if the viruses are found, and early warning is performed if the viruses are unknown, so that the aims of detecting pathogenic viruses and related proteins thereof and prejudging novel unknown viruses are fulfilled. The biochip has the advantages of high speed, sensitivity, high specificity, low cost, high throughput and the like, and can play roles in infection screening, suspected case diagnosis, epidemiological investigation and the like at ordinary times and in epidemic outbreak periods. More importantly, the chip has the capability of predicting pathogens such as novel unknown viruses, and the like, so that when a new epidemic situation appears in the future, early warning can be rapidly and timely carried out, advanced layout and epidemic prevention and control of relevant departments are assisted, public health pressure at the initial stage of the epidemic situation can be greatly relieved, and casualties and economic losses caused by epidemic situation outbreaks are reduced. The biochip of the invention can integrate specific biochips aiming at different types of pathogens on the same biochip through super-array modification and micro-fluidic design, thereby further improving the detection efficiency and simultaneously enlarging the application range of the biochip.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic diagram of the design and cross-sensing of a biochip of the present invention;
FIG. 2 is a schematic diagram of the transmission and reflection modes of the detection method of the present invention;
FIG. 3 is a flowchart of a method for determining virus type according to the present invention;
FIG. 4 is the schematic diagram of the biochip structure and response for detecting coronavirus by SPR imaging.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Referring to fig. 1-4, the present invention provides a method for detecting pathogenic viruses and their associated proteins and predicting new unknown viruses.
This example prepares a biochip in advance, which is formed by sequentially attaching a substrate material, a metal layer and a bio-molecular layer. Usually, the substrate material is a material that has little influence on light or meets certain optical requirements, such as glass, quartz, and organic glass. The metal layer is a metal film, a metal film with periodic nanostructure holes or metal particles with periodic nanostructures. The thickness of the metal film or particle is in the nanometer scale range, and the metal is selected from gold, silver, platinum, copper and aluminum. The metal layer can be continuous or distributed on the substrate material in an array form, the array form is not limited to regular quadrangle as periodic unit arrangement, but also regular hexagon, circle, diamond as periodic unit arrangement, radiation arrangement, linear arrangement and any other arrangement form which can provide a plurality of corresponding biomolecule modifications at different sites. The biomolecule layer can be modified to a continuous metal layer by different biomolecules in an array form, and can also be modified to a metal layer already having an array form by different biomolecules in a mutually corresponding manner, as shown in fig. 1. The biomolecules used for modification in this embodiment include proteins such as antibodies, cell receptor proteins, polypeptides such as peptide chain molecules or cyclic peptide molecules designed according to the amino acid sequence of the specific binding domain of the receptor protein, peptide molecules selected from a library of polypeptides, peptide molecules modified by other small molecules with auxiliary binding, oligonucleotides such as aptamers, nucleic acid molecules with specific sequences, oligosaccharides such as chitosan, lipid molecules, and complex molecules such as glycoproteins and peptide nucleic acids PNA with certain recognition and binding ability combined from the above-mentioned classes of molecules. The composition and combination of biomolecules can be adjusted depending on the particular pathogen being detected, and the modification can be accomplished by chemical covalent, coordination, or physical adsorption.
The biochip of the present embodiment can be specifically designed to target a series of different viruses of the same species or other pathogens, such as coronavirus, influenza virus, HIV virus, by the composition and arrangement of the modified biomolecules, and the same designed biochip can be used for the pathogens of the same species.
The biochip of the present invention can be applied to an optical cross-sensing detection apparatus. The optical cross-sensing techniques employed may be SPR imaging, spectroscopic imaging, Raman imaging, fluorescence and other optical means imaging techniques. The detection mode may be a reflective type (light does not penetrate the biochip) or a transmissive type (light penetrates the biochip) as shown in FIG. 2, depending on the optical technique used and the configuration of the biochip. Generally, the detection device includes a light source, an optical element, a flow cell associated with a biochip, and a detector.
The detection mechanism of the biochip mainly utilizes different binding reactions of viruses and proteins thereof at different sites of the biochip to generate 'fingerprint' information for effectively identifying the pathogen viruses, and then converts the 'fingerprint' information into an intuitive detection result by utilizing a certain data processing algorithm, as shown in fig. 3.
Specifically, the binding reaction of the virus and its proteins to the chip is followed by the optical detection device used, resulting in a varying set of optical signals, namely:
{ΔI(x,y)},x＝1,2,...,N,y＝1,2,...,M
wherein, the delta I (x, y) represents the change value of the optical signal before and after the reaction of each site, and the (x, y) represents the position information of the site. There are K classes of pathogenic viruses P1,P2,...,PKGiven a set of probe data
D＝{(ΔI1(x,y),P1),(ΔI2(x,y),P2),...,(ΔIK(x,y),PK)}，
Pairing the K classes one by using a classification recognition algorithm so as to realize the detection of pathogen virus species, namely:
PK＝f(ΔIk(x,y)),k＝1,2,...,K
wherein f (-) represents a classification recognition model, and the classification recognition algorithm comprises but not only Partial Least Squares (PLS), a Support Vector Machine (SVM), an Artificial Neural Network (ANN) and other algorithms.
After obtaining the classification model f (-) with a given detection dataset D, for the unknown optical change signal Δ I (x, y), the corresponding pathogen virus class can be obtained: pk＝f(ΔI(x,y)),k∈{1,2,...,K}。
Further, aiming at specific types of pathogens, collecting corresponding light change signal sets under concentration change, and establishing a recognition model of concentration information, thereby realizing detection of pathogen viruses and protein concentration information thereof. In this embodiment, a discrimination confidence interval is set, and if the confidence of the result obtained by the unknown sample is very low, the unknown sample is considered not to belong to the pathogen virus species corresponding to the specific biochip; if the confidence of the result obtained by the unknown sample is higher but can not be clearly identified, the unknown sample is considered to be possibly a completely new variant homogeneous pathogenic virus, and an early warning is provided.
In order to directly establish an identification model between pathogen virus information and optical signals, in particular, to further improve the stability and accuracy of chip detection, an original optical signal Δ I (x, y) can be preprocessed by using a feature extraction method to establish an identification model between pathogen information and features, that is:
Pk＝f(hk),k＝1,2,...,K
wherein h isk＝f'(ΔIk(x, y)) is the optical signal Δ I for the kth pathogenkThe characteristic value of (x, y), f' (. cndot.) represents the functional transfer relationship between the original optical signal and the characteristic value. Corresponding feature extraction methods include, but are not limited to, Principal Component Analysis (PCA) methods.
Meanwhile, the biochip can integrate the design of specific biochips for different types of pathogens into the same biochip through super-array modification and microfluidic design, so that the detection efficiency is further improved.
Example 1: SPR imaging detection of new coronavirus and other coronaviruses
This example includes a biochip composed of a base material, a metal layer, and a bio-molecular layer. The substrate material is glass. The metal layer is a metal film. The thickness of the metal film is between 5 nanometers and 500 nanometers, and the metal is selected to be gold. The metal layers are distributed in an array over the base material (fig. 4). The biomolecular layer is modified by different monoclonal or polyclonal antibodies corresponding to different antigens of coronavirus (such as spike S protein, nucleocapsid N protein, membrane M protein, envelope E protein and the like), receptor protein or auxiliary protein corresponding to coronavirus S protein such as human ACE2, CD26, CD147, TMPRSS2 and the like, and a plurality of related polypeptide molecules designed by key sequences of binding sites of the receptor proteins are modified on a metal film distributed in the form of an array. The modification is mainly accomplished by gold-sulfhydryl chemical covalent bond, or by chemical covalent bond or physical adsorption on a layer of self-assembled Polyoxyethylene (PEG) molecules.
The biochip is applied to SPR imaging detection equipment, and the detection mode adopts a reflection mode (light does not penetrate through the biochip) due to the requirements of an SPR technology and the characteristics of the biochip, and a light source and a flow cell are arranged on the opposite sides of the biochip.
Before detection, known different types of coronaviruses or representative antigen molecules thereof (e.g., spike S protein, nucleocapsid N protein, membrane M protein, envelope E protein, etc.) are injected into the flow cell separately to undergo different binding reactions with different biomolecules modified at different sites on a specific biochip. This different binding reaction will be tracked by the SPR imaging device, causing different changes in reflected light intensity at different sites (FIG. 4. DELTA.R), constituting a signal set. The signal set includes signal strength information and location information of the site. The signal set is converted into a data set after being recorded. Aiming at different coronaviruses or antigen molecules thereof, the steps before detection are repeated and sufficient data sets are obtained, all the obtained data sets are preprocessed and then subjected to feature extraction, feature values of the feature extraction and the corresponding different coronaviruses or the antigen molecules thereof form a training set, training and optimization of an intelligent algorithm are carried out, and sufficient accuracy is achieved. The intelligent algorithm includes but is not limited to neural network algorithms, machine learning, and other related algorithms that can meet the demand. The intelligent algorithm is specific to a biochip that can detect coronaviruses.
In the detection, a sample containing unknown coronavirus or its antigen molecule is injected into the flow cell to perform different binding reactions with different biomolecules modified at different sites on the biochip. The different binding reactions are tracked by the SPR imaging device, causing different changes in reflected light intensity at different sites, which constitute a signal set. The signal set includes signal strength information and location information of the site. The signal set is converted into a data set after being recorded. The data set is used as an input value to obtain a classification result through the above intelligent algorithm for the coronavirus, and the specific category, concentration and classification confidence coefficient of the unknown coronavirus are given. If the confidence of the result obtained by the unknown sample is very low, considering that the unknown sample may not belong to the coronavirus category; if the confidence of the result obtained by the unknown sample is higher but can not be clearly identified, the unknown sample is considered to be a novel coronavirus with brand new variation, and an early warning is provided. The biochip can integrate the design of specific biochips for different types of viruses into the same biochip through the design of super-array modification and micro-fluidic, further improves the detection efficiency, and utilizes one sample to judge the types of the viruses.
The invention provides a biochip for detecting and identifying pathogens such as viruses and the like and a using method thereof by utilizing a combination principle similar to immunoassay and based on a cross-sensing technology of SPR imaging. The chip technology has the advantages of high speed, sensitivity, high specificity, low cost, high throughput and the like, and can play roles in infection screening, suspected case diagnosis, epidemiological investigation and the like at ordinary times and in epidemic outbreak periods.
More specifically, the technical scheme of the invention includes that different biomolecules are placed at different positions of a biochip, different changes of reflected or transmitted light intensity at different positions caused by binding reaction are tracked by an imaging device to form a signal set, the signal set is converted into a data set, the data set is subjected to pattern recognition by an optimized algorithm model, whether viruses contained in a sample belong to discovered viruses or not is analyzed, the types of the viruses are judged if the viruses belong to the discovered viruses, and early warning is performed if the viruses belong to unknown viruses, so that the aims of detecting pathogenic viruses and related proteins thereof and prejudging novel unknown viruses are fulfilled. The technology of the invention has the capability of predicting pathogens such as novel unknown viruses, and the like, so that when new epidemic situation appears in the future, early warning can be rapidly and timely carried out, advanced layout and epidemic situation prevention and control of relevant departments can be assisted, the public health pressure at the initial stage of the epidemic situation can be greatly relieved, and casualties and economic loss caused by epidemic situation outbreak can be reduced.
Claims (8)
1. A method for detecting pathogenic viruses and related proteins thereof and predicting novel unknown viruses, comprising the following steps:
preparing a biochip comprising a biomolecule layer in advance; the biochip is formed by sequentially clinging a substrate material, a metal layer and a biological molecular layer from bottom to top; the biomolecule layer is modified to the metal layer by different biomolecules in an array form, and the biomolecule species comprise protein molecules, polypeptide molecules, oligonucleotide molecules, peptide nucleic acid molecules, oligosaccharide molecules and lipid molecules, or any combination of the above species;
injecting a sample to be detected into a flow cell, wherein the sample and different biomolecules modified at different positions on the biomolecule layer have different degrees of binding reaction;
tracking different changes of reflected or transmitted light intensity at different positions caused by the occurrence of the binding reaction by using imaging equipment to form a signal set;
and converting the signal set into a data set, performing pattern recognition on the data set by using an optimized algorithm model, analyzing whether the viruses contained in the sample belong to the discovered viruses, judging the types of the viruses if the viruses belong to the discovered viruses, and performing early warning if the viruses are unknown viruses.
2. The method for detecting pathogenic viruses and their related proteins and prognosing new unknown viruses according to claim 1, wherein the substrate material is selected from transparent materials with refractive index between 1.0-3.0, including but not limited to glass, quartz, plexiglass.
3. The method according to claim 1 for detecting pathogenic viruses and their related proteins and prognosing new unknown viruses, wherein the metal layer is distributed on the substrate material in a continuous, array, radial arrangement or a combination of said patterns, such that different biomolecules can be modified at different sites on the metal layer;
the metal layer material includes but is not limited to a metal film, a metal film with periodic nanostructure holes, and metal particles with periodic nanostructures; the metal species include, but are not limited to, gold, silver, platinum, copper, aluminum.
4. The method of claim 1, wherein the modification comprises chemical covalent bonding of metal-thiol groups, chemical covalent bonding of a layer of self-assembled molecules, coordination bonding, and other physical adsorption.
5. The method of claim 1, wherein the imaging device comprises Surface Plasmon Resonance (SPR) imaging, spectroscopic imaging, Raman imaging, fluorescence and other optical imaging, or any combination thereof.
6. The method of claim 5, wherein the biochip is used with the imaging device and adapted to perform overall modification according to different imaging techniques, the modification including the composition of biochip material and the imaging detection format.
7. The method for detecting pathogenic viruses and related proteins thereof and predicting new unknown viruses according to claim 1, wherein, in optimizing the algorithm model, several samples of known viruses of the same category and proteins thereof are prepared in advance and numbered; and with the aid of the imaging equipment, sequentially acquiring signal characteristics of the viruses with known types and proteins thereof when the viruses and the proteins thereof are combined with a bio-molecular layer of the biochip, and labeling the signal characteristics according to the types of the viruses to obtain the corresponding relation between the viruses of the specific types and the signal characteristics.
8. The method of claim 7, wherein the signal set generated by the binding reaction is converted into a data set comprising:
{ΔI(x,y)},x＝1,2,...,N,y＝1,2,...,M
wherein, Delta I (x, y) represents the light signal change value before and after each site reaction, and (x, y) represents the position information of the site;
there are K classes of pathogens P1,P2,...,PKGiven a set of probe data
D＝{(ΔI1(x,y),P1),(ΔI2(x,y),P2),...,(ΔIK(x,y),PK)}，
Pairing the K classes one by using a classification recognition algorithm so as to realize the detection of pathogen species, namely:
PK＝f(ΔIk(x,y)),k＝1,2,...,K
wherein f (-) represents a classification recognition model, namely the optimized algorithm model, and the classification recognition algorithm comprises but is not limited to a partial least square method, a support vector machine and an artificial neural network method;
after obtaining the classification model f (-) with a given detection dataset D, for the unknown optical variation signal Δ I (x, y), the corresponding pathogen class is obtained: pkF (Δ I (x, y)), K ∈ {1, 2.., K }, thereby identifying whether the virus in the sample to be tested is a known virus and its category;
the data set processing mode can also utilize a feature extraction method to preprocess the original optical signal delta I (x, y) and establish an identification model between pathogen information and features, namely:
Pk＝f(hk),k＝1,2,...,K
wherein h isk＝f'(ΔIk(x, y)) is the optical signal Δ I for the kth pathogenk(x, y) a characteristic value, f' () representing a functional transformation relationship between the original optical signal and the characteristic value; corresponding feature extraction methods include, but are not limited to, Principal Component Analysis (PCA) methods.
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