High-throughput fluorescence detection method, device and system and storage medium

Abstract

The embodiment of the invention discloses a high-throughput fluorescence detection method and system, relates to the field of molecular detection and artificial intelligence, and particularly relates to a high-throughput fluorescence detection method and system capable of simultaneously detecting and analyzing multiple target nucleic acids in a single reaction system. The multi-color code comprises a combination of different colors of the same molecular probe, and the multi-order code comprises a combination of fluorescence intensity of the same color; the coded molecular probes are distributed into at least two reaction units; in the transcoding link, carrying out super-multiple amplification on the molecular probe in each reaction unit, and carrying out multi-interval amplification on each reaction unit; in the decoding link, the reaction units passing through the transcoding link are used for decoding, the number of fluorescence coding positive reaction units corresponding to all the detection targets is obtained, and the actual content of the detection targets in the sample is obtained through calculation; according to the method, the detection efficiency is greatly improved, and the sample size required by detection is reduced.

Description

Technical Field

[0001] The present application relates to the field of molecular detection and artificial intelligence, and in particular to a high-throughput fluorescence detection technology and system that can be used for single-molecule quantitative detection of proteins, small molecules, and nucleic acid molecules. Background Art

[0002] With the development of biotechnology, more and more biological molecules (including proteins, small molecules and nucleic acid molecules, etc.) need to be analyzed simultaneously in applications. However, the current detection technology has a low throughput and cannot meet the existing needs. High-throughput detection technology has become an urgent need.

[0003] Existing nucleic acid molecule detection methods include qPCR, NGS, digital PCR and other methods: qPCR technology includes two main fluorescent detection methods: one is to use specific fluorescent probes (such as TaqMan probes), and the other is to use non-specific fluorescent dyes (such as SYBR Green I). qPCR detection is easy to operate, but there are disadvantages such as possible amplification bias, limitation of primers and probes, inability to determine the detection results of low-concentration templates, and large errors when using standard curves for quantitative detection. In particular, this method cannot be quantitative, and multiple reaction tubes need to be combined to detect multiple sites, and multiple sites cannot be detected at one time. The NGS method can obtain information on point mutations, small fragment insertions or deletions, copy number variations and structural variations, but this method has problems such as generally low read lengths and high error rates in the sequence splicing process. At the same time, this method is complex to operate, difficult to analyze data, and expensive, making it difficult to promote on a large scale in practical applications.

[0004] Digital PCR is a technology for absolute quantitative analysis of nucleic acid molecules. It distributes nucleic acid samples into a large number of independent, parallel micro-reaction units, so that each reaction unit contains as many template molecules as possible, and performs amplification, detection, and distribution statistics on this basis, thereby achieving absolute counting of target molecules. Digital PCR has higher sensitivity and accuracy, but is usually limited by primers and probes. Only single-digit fluorescence signals can be analyzed in one test, and the detection range is narrow.

[0005] Therefore, how to achieve high-throughput fluorescence detection and identification of multiple sites in a single reaction has become a technical problem that needs to be solved urgently in this field. Summary of the invention

[0006] In response to the above technical problems, the present application provides a high-throughput fluorescence detection method and system for simultaneously detecting and analyzing multiple target nucleic acids in a single reaction system. This method greatly improves the detection efficiency and reduces the sample amount required for detection.

[0007] In order to achieve the above object, the present invention adopts the following technical scheme:

[0008] In one aspect, a high-throughput fluorescence detection method is provided, wherein the process of performing high-throughput fluorescence detection comprises:

[0009] The fluorescence coding step includes: performing multi-color and multi-level coding on the same molecular probe to obtain the coded molecular probe, wherein the multi-color coding includes a combination of different colors of the same molecular probe, and the multi-level coding includes a combination of fluorescence intensities of the same color; one color corresponds to one wavelength of fluorescence; and the coded molecular probe is distributed to at least two reaction units;

[0010] The transcoding step includes: performing super-multiplex amplification on the molecular probes in each reaction unit and performing multi-interval amplification on each reaction unit;

[0011] The decoding step includes: using the reaction unit that has passed the transcoding step to perform decoding to obtain the content of the detection target corresponding to each fluorescent coding signal.

[0012] In another aspect, a high-throughput fluorescence detection system includes:

[0013] A coding module, used for performing multi-color and multi-level coding on the same molecular probe to obtain a coded molecular probe, wherein the multi-color coding includes a combination of different colors of the same molecular probe, and the multi-level coding includes a combination of fluorescence intensities of the same color; one color corresponds to one wavelength of fluorescence; the coded molecular probe is distributed to at least two reaction units;

[0014] A transcoding module, for performing super-multiplex amplification on the molecular probes in each reaction unit and performing multi-interval amplification on each reaction unit;

[0015] The decoding module is used to decode the reaction unit after the transcoding link to obtain the content of the detection target corresponding to each fluorescent coding signal.

[0016] Compared with the existing qPCR technology, the technical solution of the present application can simultaneously detect and analyze multiple target nucleic acids in a single reaction system. The analysis process is highly automated and does not require human intervention, which improves the detection efficiency and reduces the sample size required for detection. Compared with the dPCR technology, which is limited by primers and probes and has a narrow detection range, the method of the present application realizes the simultaneous detection and analysis of multiple target biomolecules in a single reaction system. In addition, compared with the xMAP technology based on poor signal amplification capability (currently only 1000 times at most), the detection method of the present application has a signal amplification factor much higher than this. It can improve the sensitivity and specificity of detection and reduce the risk of false positives and false negatives. At the same time, it can reduce the sample size and reaction time required for detection, and improve the efficiency and convenience of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a graph showing the high-throughput fluorescence coding detection results of the plasmid standard in Example 1 of the present invention.

[0018] Figure 2-1 , 2-2 2-3 are the fluorescence coding detection result diagrams of three copy number loading amounts in Example 1 of the present invention; wherein, Figure 2-1 , 2-2 , 2-3 are the detection results of 500 copies, 50 copies, and 5 copies respectively.

[0019] Figure 3 This is a graph showing the high-throughput fluorescence coding detection results of the plasmid standard in Example 2 of the present invention.

[0020] Figure 4 This is a graph showing the high-throughput fluorescence coding detection results of the plasmid standard in Example 3 of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention will be described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention. It can be understood by those skilled in the art that, unless specifically stated, the singular forms "one", "one", "said" and "the" used herein may also include plural forms. It should be further understood that the term "including" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or their groups. It should be understood that when we say that an element is "connected" or "coupled" to another element, it can be directly connected or coupled to other elements, or there may also be intermediate elements. In addition, the "connection" or "coupling" used here may include wireless connection or coupling. The term "and / or" used herein includes any unit and all combinations of one or more associated listed items. It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as generally understood by those of ordinary skill in the art to which the present invention belongs. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless defined as herein.

[0022] The high-throughput fluorescence detection method provided in the embodiment of the present invention specifically includes the following steps:

[0023] The fluorescence coding link includes: performing multi-color and multi-level coding on the same molecular probe to obtain the coded molecular probe, wherein the multi-color coding includes a combination of different colors of the same molecular probe, and the multi-level coding includes a combination of fluorescence intensities of the same color; one color corresponds to fluorescence of one wavelength. The coded molecular probe is distributed to at least two reaction units. Specifically, fluorescence coding is a technology that uses the emission spectrum characteristics of fluorescent molecules to mark and detect target substances. Fluorescence coding can be divided into two methods: multi-color and multi-level. Multi-color means: multi-color fluorescence coding refers to fluorescence coding on the same molecular probe, which is encoded as a combination of fluorescence of several different wavelengths. This method can increase the amount of information and sensitivity of the coding, while reducing the number and cost of probes. Multi-color fluorescence coding can be used for simultaneous observation and analysis of multiple targets or processes of target biological molecules. Multi-level means: multi-level fluorescence coding means that each fluorescence wavelength can select multiple fluorescence intensities. This method can further improve the capacity and complexity of the coding, while avoiding crosstalk or overlap between different colors. Multi-level fluorescence coding can be used for high-throughput, high-precision, and high-specificity biomolecule detection. For example: combinations of fluorescence of different wavelengths can be established to obtain the 1st to Nth combinations, and the correspondence between the established combinations and the molecular probes can be recorded, wherein each combination includes at least fluorescence wavelengths, and N is a positive integer greater than or equal to 2; in the nth combination, a fluorescence intensity combination M of wavelength fluorescence ni is established, M = {m1…mj}, wherein i represents the number of the fluorescence wavelength in the combination, and j represents the number of the fluorescence intensity.

[0024] The transcoding step includes: performing super-multiplex amplification on the molecular probes in each reaction unit, and performing multi-interval amplification on each reaction unit.

[0025] Among them, super-multiplex amplification refers to the simultaneous presence of multiple pairs of primers and multiple probes in the smallest reaction unit, which can simultaneously amplify and identify the template under specific temperature changes. Multi-interval amplification refers to the simultaneous uniform amplification of multiple reaction units. Using the principle of Poisson distribution, the template biomolecules are diluted to the extent that each reaction unit contains only one or zero target molecules, and then PCR reactions are performed in each reaction unit, and the fluorescence signal is used to determine whether each reaction unit has undergone effective amplification.

[0026] In the following embodiment, the preferred super-multiplex amplification method includes: referring to the applicant's previous patent "Digital amplification detection method, detection product and detection kit for simultaneously identifying multiple gene types" (publication number: CN114196740A), when synthesizing primers, first only three bases are selected to significantly reduce non-specific binding during amplification; and a nucleotide sequence that can form a three-dimensional structure and a small molecule compound are added to the 5' end of the primer, which can significantly reduce the generation of dimers between primers, reduce non-specific amplification, and improve the binding specificity and binding strength of the primer to the template, and the binding stability, and can achieve multiple amplification of a single reaction system. When designing probes, based on the double probe shedding technology, at least two probes are set for each target gene, and the set probe does not contain a reference probe; multiple different probes are combined with the target gene, and cover different regions of the target gene to achieve comprehensive detection of the target gene mutation site, so that the simultaneous detection of multiple gene types or gene mutations of the target gene can be achieved through one detection, and the detection process is more efficient.

[0027] In the following embodiment, the preferred multi-interval amplification method includes: the reaction system can be divided into multiple intervals through the instability of one fluid (dispersed phase fluid) entering another (continuous phase fluid). The method of generating droplets can be passive or active. The generation of droplets does not require external drive, and the stable occurrence of droplets uses additional energy input to maintain and promote the interface instability of droplet generation. In principle, in active control, the balance of interfacial forces can be adjusted through two basic strategies: by changing inherent parameters such as flow rate and material properties to change viscosity, inertia and capillary forces; or by using external power equipment, such as syringe pumps, peristaltic pumps and other pump equipment to introduce additional forces: such as electricity, magnetism, centrifugal force, sound waves, dielectric effects of electrodes, photothermal effects, etc., can all be used as the power for droplet generation. At this stage, the equipment that maintains the continuous and stable generation of droplets mainly includes syringe pumps, peristaltic pumps, electromagnetic, pneumatic pumps, syringes, centrifuge equipment, etc. It is also possible to use a specially designed microfluidic chip with pre-fabricated microwells of corresponding volume and number on the chip, use driving force to evenly disperse the reaction system into different microwells, and use capillary action or physical sealing to block the liquid system between different microwells to achieve multi-zone division of the reaction system.

[0028] The decoding step includes: using the reaction unit that has passed the transcoding step to perform decoding to obtain the content of the detection target corresponding to each fluorescent coding signal.

[0029] Specifically, in the multi-color coding of the fluorescence coding link, it includes: selecting n colors from m colors to form a multi-color fluorescence coding, and the number of combinations obtained is n and m are both positive integers, and when n=m / 2, the number of combinations is the largest. For example, the preferred multi-color coding method includes: when n colors are selected from m colors to form a multi-color coding, when n=m / 2, the number of combinations is the largest, and if m is an odd number, n can be (m±1) / 2. At this time, the specific combination types can be shown in the following Table 1:

[0030] Table 1 Fluorescence coding combinations

[0031] ABC ABD ABE ABF ACD ACE ACF ADE ADF AEF BCD BCE BCF BDE BDF BEF CDE CDF CEF DEF

[0032] The formula is: For example, in a 6-color system, 3 colors are selected from the 6 colors (AF channels) to form a probe. There are a total of C(6,3)=20 combinations:

[0033] In the multi-level coding of the fluorescence coding link, it includes: in the process of selecting multi-level coding for a single color, a multi-level combination number is obtained, wherein, if the weakest fluorescence intensity that can be effectively resolved by the single color channel is o, and the strongest fluorescence intensity is p, then o*2 q <p<o*2 q+1 , q is the number of orders supported by the monochrome channel. For example, the maximum number of multi-order combinations is: q A *q B *q C *......*q n , where q A ,q B ...is the order number of the fluorescence channel corresponding to the selected code. According to the code number n, the number of order combinations is the product of the order numbers of n channels. For example: in a 6-color system, 3 colors are selected from 6 colors (AF channels) to form a probe, and there are C(6,3)=20 combinations. If each channel can support at least 2 orders of signal differentiation, 20*2*2*2=160 signal combinations can be achieved.

[0034] Furthermore, in the decoding link, it includes: collecting the fluorescence intensity data of each reaction unit in different fluorescence channels and establishing a data matrix; performing high-dimensional clustering on the data matrix and sorting after clustering; performing MASK processing on the sorted high-dimensional data matrix, and then performing dimensionality reduction processing to obtain the content of the detection target corresponding to each fluorescent coding signal.

[0035] Specifically, the method of collecting the fluorescence intensity data of each reaction unit in different fluorescence channels and establishing a data matrix includes: collecting the fluorescence intensity of each reaction unit in different fluorescence channels, obtaining an array (i1, i2, i3...i m ), where m corresponds to the number of fluorescence channels, i m Then is the fluorescence intensity of the reaction unit in the fluorescence channel m;

[0036] The fluorescence intensity data of all reaction units are combined to form the first high-dimensional matrix corresponding to sample a, where there are k reaction units corresponding to sample a: The fluorescence intensity data of the l reaction units of the positive reference b are merged to obtain the second high-dimensional matrix:

[0037] The performing high-dimensional clustering on the data matrix comprises: for each row of data in the second high-dimensional matrix, i , if its ∈-neighborhood contains at least MinPts elements, then x i Determine as a core object, ∈ represents the radius of the data point, MinPts represents the minimum number of data points in the neighborhood with a radius of ∈; all density-reachable core objects x i Together with all elements in the corresponding ∈-neighborhood, it forms a density cluster y i ; The unclustered elements x in the second high-dimensional matrix k Assign the same label label1, and the rest of the density clusters y i The elements in the label are given label i , get the high-dimensional matrix after clustering. For example: using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, the input parameters (∈, MinPts) are used to describe the density of sample distribution in the neighborhood. Among them, ∈ describes the neighborhood distance threshold (radius) of a data point, and MinPts describes the minimum number of data points in the neighborhood with a radius of ∈. Calculate the first high-dimensional matrix:

[0038] a) Calculate the core object: For any element x in each row of data in the second high-dimensional matrix i , if its ∈-neighborhood contains at least MinPts elements, then x i It is a core object. Traverse and calculate to get all core objects.

[0039] b) Determine whether the density is reachable: Determine whether a core object x i Are there other core objects x in the ∈-neighborhood? j , if it exists, then we can determine x i With x j Density can reach.

[0040] c) Divide density clustering: All core objects x that can be reached by density are divided into i Together with all elements in the corresponding ∈-neighborhood, it forms a density cluster y i

[0041] All the unclustered elements x in the second highest dimensional matrix k Assign the same label label1, and the rest of the clusters y i All elements in the same i , and get a new high-dimensional matrix:

[0042]

[0043] The sorting after clustering includes: obtaining the average value of the elements in each cluster in m fluorescence channels; comparing the average values ​​of the elements in each cluster and sorting them to obtain the sorting of the average values ​​of each element in different clusters, and then obtaining the total score of each cluster according to the sorting of the average values ​​of the elements in different clusters; sorting using the total score of each cluster. For example: for all clustered elements, for a certain cluster y i , the average value of all elements in m fluorescence channels can be obtained (i 1-average ,i 2-average ,i 3-average ...i m-average ).

[0044] After that, the average values ​​of fluorescence channels of different clusters were compared, and the average center-based sequencing (ACBS) algorithm was used to compare all clusters from i to 1-average to m-average The order is as follows:

[0045] Sequence 1: label i1 <label i2 <...<label n

[0046] Sequence 2: label j1 <label j2 <...<label n

[0047] …

[0048] For each sorting sequence, the first cluster is assigned a score of 0, the second cluster is assigned a score of 1, and so on until the last cluster is assigned a score of n. Each cluster can then get a total score of N. sum . Compare the N of each cluster sum , we can get the clustering sequence Sequence cluster For N sumIf the clusters are equal, compare the results of Sequence 1 and sort the cluster with a higher ranking in Sequence 1 at the top of Sequence 2. cluster In the front.

[0049] Furthermore, it is necessary to perform MASK processing on the sorted high-dimensional data matrix, and then perform dimensionality reduction processing to obtain the content of the detection target corresponding to each fluorescent coding signal, wherein the MASK processing includes:

[0050] For Sequence cluster For each cluster in , use the convex hull algorithm (convex hu II). According to each point in the cluster, take the minimum point a1 as the starting point, then take the nearest point a2 to get a vector u, and then extend to the next nearest point a3 to get a vector v, and calculate u*v, that is, its vector cross product:

[0051]

[0052] It can also be expressed as:

[0053] u×v=(u2V3i+u3v1j+u1v2k)-(u3v2i+u1v3j+u2v1k)

[0054] =(u2v3-u3v2)i+(u3v1-u1v3)j+(u1v2-u2v1)k

[0055] According to the sign of the vector cross product, if the cross product is negative, it means that the adjacent point a3 is on the clockwise side of the vector u, then the vector from a1 to a3 is used as the edge vector, and then the next adjacent point is found to repeat the above process. Finally, the edge range A of each cluster of the second high-dimensional matrix is ​​obtained. i Use A i As a condition, each element of the second high-dimensional matrix is ​​differentiated to obtain i A collection of elements in a range, and assigns the same label to each element in the collection i , get a new first high-dimensional matrix:

[0056] In this embodiment, multiple dimensionality reduction processes are used, including: using the PCA (Principal components analysis) algorithm to reduce the dimensionality of the new first high-dimensional matrix:

[0057] a) Organize the original data into a matrix X with n rows and m columns;

[0058] b) Zero-mean each row of X, that is, subtract the mean of this row;

[0059] c) Find the covariance matrix

[0060] d) Find the eigenvalues ​​and corresponding eigenvectors of the covariance matrix C;

[0061] e) Arrange the eigenvectors into a matrix row by row from top to bottom according to the corresponding eigenvalues, and take the first k rows to form the matrix P;

[0062] f) Y = PX is the data after dimension reduction to k dimension.

[0063] Then, combined with the sorting and labeling results, each element in the matrix P corresponding to the first high-dimensional matrix is ​​assigned the same label, thereby obtaining the number of elements of each fluorescent coding probe. Based on the number of elements, combined with Poisson distribution, the copy number of the amplification site corresponding to the fluorescent coding marker can be calculated:

[0064]

[0065] To meet the display requirements, the first high-dimensional matrix will be reduced in dimension using the tSNE dimensionality reduction algorithm:

[0066]

[0067] g) Calculate the parameters of the cost function: Perp

[0068] h) Optimization parameters: set the number of iterations T, learning rate n, momentum a(t)

[0069] i) The target result is a low-dimensional data representation Y t =y1...,y n

[0070] j) Start optimization

[0071] Calculate the conditional probability P under a given Perp, where Initialize Y randomly with N(0, 10-4I); then iterate from t=1 to T and do the following:

[0072] Calculate q in low dimensions ij ;

[0073] Calculate the gradient;

[0074] renew

[0075] Finally, combined with the sorting and labeling results, each element of the corresponding first high-dimensional matrix in the final matrix Y is assigned the same label to obtain the number of elements of each fluorescent coding probe. With the help of the same label, the association between the elements of the original first high-dimensional matrix, the PCA reduced dimension matrix P, and the tSNE reduced dimension matrix Y is established.

[0076] This embodiment also provides a high-throughput fluorescence detection device. Each virtual module in the device can be written based on the existing computer programming method to form a corresponding program module. Each program module is used to run the algorithm model of the above encoding link, transcoding link and decoding link. The system includes:

[0077] A coding module, used for performing multi-color and multi-level coding on the same molecular probe to obtain a coded molecular probe, wherein the multi-color coding includes a combination of different colors of the same molecular probe, and the multi-level coding includes a combination of fluorescence intensities of the same color; one color corresponds to one wavelength of fluorescence; the coded molecular probe is distributed to at least two reaction units;

[0078] A transcoding module, for performing super-multiplex amplification on the molecular probes in each reaction unit and performing multi-interval amplification on each reaction unit;

[0079] The decoding module uses the reaction units that have passed the transcoding link to perform decoding, obtains the number of fluorescence-encoded positive reaction units corresponding to each detection target, and calculates the actual content of the detection target in the sample.

[0080] The embodiment of the present invention further provides a storage medium storing a computer program or instruction, such as the above-mentioned computer program written based on the currently available computer programming method, and forming a corresponding program module. When the computer program or instruction is executed, the method in the embodiment is implemented.

[0081] The high-throughput fluorescence detection device in this embodiment can be specifically operated on a computer device in a high-throughput fluorescence detection system, and the system includes:

[0082] Experimental equipment, used to install the reaction unit and provide experimental conditions for super-multiplex amplification of the molecular probes in the reaction unit;

[0083] an image acquisition device for capturing images of the reaction unit;

[0084] Computer equipment, used for fluorescence encoding, transcoding and decoding.

[0085] This embodiment realizes the simultaneous detection and analysis of multiple target nucleic acids in a single reaction system. The analysis process is highly automated and does not require human intervention, which improves the detection efficiency and reduces the sample volume required for detection. Compared with existing detection methods, the method of this application has the following advantages:

[0086] 1) Compared with the existing qPCR technology, the high-throughput molecular detection technology of the present application can achieve more target molecules and accurate quantification in a single reaction system.

[0087] 2) Compared with the longer NGS detection cycle (about 10 days), the method of this application can generally complete the entire detection process and provide the test results within 1 day, and the data analysis process is highly automated and does not require human intervention.

[0088] 3) Compared with the dPCR technology which has a narrow detection range due to the limitation of primers and probes, the method of the present application realizes the simultaneous detection and analysis of multiple target biomolecules in a single reaction system.

[0089] 4) Compared with the xMAP technology based on poor signal amplification capability (currently only up to 1000 times), the detection method of the present application has a much higher signal amplification factor than this. It can improve the sensitivity and specificity of the detection and reduce the risk of false positives and false negatives. At the same time, it can reduce the sample volume and reaction time required for the detection, and improve the efficiency and convenience of the detection.

[0090] 5) This technology is characterized by high efficiency, simplicity, and high throughput, and has broad application prospects in the biomedical field.

[0091] In combination with the above embodiments, possible applications and test examples in practical applications are provided for illustration.

[0092] Example 121 High-throughput fluorescence detection of chromosome

[0093] In this example, 42 sets of primer probes were designed for 42 fragments evenly distributed on human chromosome 21, and copy number quantitative detection was performed separately. A total of 42 sets of primer probes were designed using the Primer3 primer probe online design tool (http: / / primer3.wi.mit.edu / ), and then the primer probes were ordered using the fluorescent coding method, and the digital PCR universal kit was used to perform detection separately to verify the implementation of automatic clustering analysis.

[0094] Experimental steps:

[0095] Mix 42 sets of primers and probes according to the coding principle, add 2x reaction premix, add water to 50uL, vortex to mix, and centrifuge briefly.

[0096] The formula of the premix is ​​as shown in the following table (the premix in the following embodiments is the same; in specific implementations, other conventional premixes in the art may also be used).

[0097] Components concentration KCl 50mM NH4Cl 30mM β-Lactoglobulin 80ng / ul glycerin 3％ BSA 80ng / ul dNTPs 0.3mM Taq polymerase 2.5U Tris-HCl buffer 20mM MgCl2 2.5mM 008-FluoroSurfactant 2％

[0098] The reaction system formula is as follows:

[0099] Component name Addition amount (ul) 2X reaction master mix 25 VIC Dye 2.5 F / P / R_1-14 4.5 F / P / R_15-28 4.5 F / P / R_29-42 4.5 Sample / NC 2.5 water 6.5 Total 50

[0100] Transfer the reaction system and droplet generation oil to the corresponding holes of the chip. Load the chip onto the chip holder, load the PCR plate onto the PCR plate holder, and use the droplet generator to select the corresponding program to generate droplets. After the droplet generation is completed, place the PCR plate into the film sealing instrument for film sealing.

[0101] Place the PCR plate into the PCR amplification instrument for amplification. The amplification procedure is as follows:

[0102]

[0103] After PCR amplification, the PCR plate was transferred to the biochip analyzer for droplet detection to obtain the pre-decoding fluorescence signal.

[0104] As mentioned above, it can be written based on the existing computer programming method and form corresponding program modules, each of which is used to run the algorithm models of the above encoding link, transcoding link and decoding link, and these program modules are used to design and encapsulate the final analysis software. The analysis software is used to automatically decode and analyze the data, complete the above decoding link, and obtain the final result.

[0105] The primer-probe combinations are shown in Table 2 below:

[0106] Table 2 42 sets of primers and probes

[0107]

[0108]

[0109]

[0110] The results of high-throughput fluorescence coding detection of plasmid standards in Example 1 are as follows Figure 1 As shown. After reading, the fluorescence results of the droplets are decoded to obtain multiple clusters. Figure 1 In the figure, Negative represents negative droplets, the numbers represent the group numbers of the primer probes in the above table, the ordinate Dimension A is the new dimension A obtained after dimensionality reduction, and the abscissa Dimension B is the new dimension B obtained after dimensionality reduction (the coordinates in the following figures have the same meaning).

[0111] 1. Sensitivity test

[0112] The sensitivity was verified by normal human gDNA containing 42 fragments evenly distributed on chromosome 21. Three batches were tested using a universal digital PCR kit adapted for a high-throughput fluorescent encoding system at three copy number loadings (500 copies, 50 copies, and 5 copies), with 20 replicates per group in each batch. When the positive result was greater than 95%, it was considered qualified.

[0113] Table 3 Human gDNA sensitivity test results

[0114]

[0115]

[0116]

[0117]

[0118] The fluorescence coding detection results of three copy number loading amounts (500 copies, 50 copies, and 5 copies) are as follows Figure 2-1 , 2-2 The results of the sensitivity test of human gDNA are shown in Table 3. Figure 2-1 , 2-2 , 2-3 are the detection results of 500 copies, 50 copies, and 5 copies respectively.

[0119] 2. Specificity test

[0120] The specific test was verified by four randomly selected primer probes on the autosomes. In normal human gDNA samples, the copy number of each test site on the autosomes was consistent with the copy number of each test site on chromosome 21. The results of human gDNA specificity test are shown in Table 4.

[0121] Table 4 Human gDNA specific detection results

[0122]

[0123] 3. Precision test

[0124] The precision was verified by 50 copies of normal human gDNA. Three tests were performed on each site in the same batch, and a single test of three batches of each site was analyzed and calculated. The results of the human gDNA precision test are shown in Table 5.

[0125] Table 5 Human gDNA precision test results

[0126]

[0127]

[0128] Example 2 High-throughput fluorescence detection of rice genome

[0129] In this example, reference was made to "Rice functional genomics research: past decade and future." (Li, Yan, et al. Molecular plant 11.3 (2018): 359-380.). For the seven genes related to rice grain quality on the rice genome, three fragments were selected for each gene, and a total of 21 sets of primer probes were designed using the Primer3 primer probe online design tool (http: / / primer3.wi.mit.edu / ). Subsequently, the primer probes were ordered using the fluorescence encoding method, and the digital PCR universal kit was used to perform copy number quantitative detection, thereby obtaining the copy number variation of the relevant genes and evaluating the association between rice grain quality and gene expression.

[0130] Experimental steps:

[0131] Mix 21 sets of primers and probes according to the coding principle, add 2x reaction premix, add water to 50uL, vortex to mix, and centrifuge briefly. The premix formula is as follows:

[0132] Components concentration KCl 50mM NH4Cl 30mM β-Lactoglobulin 80ng / ul glycerin 3％ BSA 80ng / ul dNTPs 0.3mM Taq polymerase 2.5U Tris-HCl buffer 20mM MgCl2 2.5mM 008-FluoroSurfactant 2％

[0133] The reaction system formula is as follows:

[0134] Component name Addition amount (ul) 2X reaction master mix 25 VIC Dye 2.5 F / P / R_1-7 2 F / P / R_8-14 2 F / P / R_15-21 2 Sample / NC 2.5 water 14 Total 50

[0135] ·Add the reaction system to the corresponding wells of the pre-loaded oil chip. Load the chip onto the chip holder and use the droplet generator to select the corresponding program to generate droplets.

[0136] Place the chip into a PCR amplification instrument for amplification. The amplification procedure is as follows:

[0137]

[0138]

[0139] After PCR amplification, transfer the chip to a biochip reader for scanning and photographing to obtain the fluorescence signal before decoding.

[0140] Use analysis software to automatically decode and analyze the data and obtain the final results.

[0141] Table 6 Rice genome primer probe combinations

[0142]

[0143]

[0144] The results of high-throughput fluorescence coding detection of plasmid standards in Example 2 are as follows: Figure 3 As shown: After reading, the fluorescence results of the droplets are decoded to obtain multiple clusters. In the figure, Negative represents negative droplets, and the gene-number represents the group number of each group of primers and probes in the above table. The combination of primers and probes for the rice genome is shown in Table 6.

[0145] 1. Sensitivity test

[0146] The sensitivity was verified by rice genome gDNA standard. Three batches were tested with three copy number loadings (500 copies, 50 copies, and 5 copies), and 20 replicates were performed in each batch and group. When the positive result was greater than 95%, it was judged to be qualified. The results of the rice genome sensitivity test are shown in Table 7.

[0147] Table 7 Rice genome sensitivity test results

[0148]

[0149]

[0150] 2. Specificity test

[0151] The specific test was verified by four primer probes randomly selected on other chromosomes. In the rice genome gDNA standard, the copy number of each test site of rice grain quality-related genes was consistent with the copy number of four test sites randomly selected on other chromosomes. The results of the rice genome specific test are shown in Table 8.

[0152] Table 8 Rice genome specific test results

[0153]

[0154] 3. Precision test

[0155] The precision was verified by 50 copies of rice genome gDNA standard. Three tests were performed on each site in the same batch, and a single test of three batches of each site was analyzed and calculated. The rice genome specific test results are shown in Table 9.

[0156] Table 9 Rice genome specific test results

[0157]

[0158]

[0159] Example 3 High-throughput fluorescence detection of Saccharomyces cerevisiae

[0160] This example refers to the literature "Research Trends in Genetic Improvement of Brewer's Yeast" (Zhang Liuying, Food and Fermentation Industries 26.6 (2000): 47). For the 13 genes that may be involved in conventional genetic engineering on the genome of brewer's yeast (Saccharomyces cerevisiae), one fragment was selected for each gene, and two fragments were selected for the brewer's yeast housekeeping gene. A total of 15 sets of primer probes were designed using the Primer3 primer probe online design tool (http: / / primer3.wi.mit.edu / ). Subsequently, the primer probes were ordered using the fluorescent encoding method, and the digital PCR universal kit was used to perform copy number quantitative detection, thereby obtaining the copy number of the relevant genes and evaluating the changes in the carrying levels of the relevant genes in brewer's yeast after genetic engineering.

[0161] Experimental steps:

[0162] Mix the 13 sets of primers and probes according to the coding principle, add 2x reaction premix, and add water.

[0163] To 50uL, vortex to mix, and centrifuge briefly. The formula of the premix is ​​as follows:

[0164] Components concentration KCl 50mM NH4Cl 30mM β-Lactoglobulin 80ng / ul glycerin 3％ BSA 80ng / ul dNTPs 0.3mM Taq polymerase 2.5U Tris-HCl buffer 20mM MgCl2 2.5mM 008-FluoroSurfactant 2％

[0165] The reaction system formula is as follows:

[0166] Component name Addition amount (ul) 2X reaction master mix 25 VIC Dye 2.5 F / P / R_1-13 4 Sample / NC 2.5 water 16 Total 50

[0167] Transfer the reaction system and droplet generation oil to the corresponding holes of the chip. Load the chip onto the chip holder, load the PCR plate onto the PCR plate holder, and use the droplet generator to select the corresponding program to generate droplets. After the droplet generation is completed, place the PCR plate into the film sealing instrument for film sealing.

[0168] Place the PCR plate into the PCR amplification instrument for amplification. The amplification procedure is as follows:

[0169]

[0170]

[0171] After PCR amplification, the PCR plate was transferred to the biochip analyzer for droplet detection to obtain the pre-decoding fluorescence signal.

[0172] Use analysis software to automatically decode and analyze the data and obtain the final results.

[0173] Table 10 Saccharomyces cerevisiae primer probe combination

[0174]

[0175]

[0176] The results of high-throughput fluorescence coding detection of plasmid standards in Example 3 are as follows Figure 4 As shown. After reading, the fluorescence results of the droplets are decoded to obtain multiple clusters. In the figure, Negative represents negative droplets, and genes represent the group numbers of the primer probes in the above table. The combination of primers and probes for Saccharomyces cerevisiae is shown in Table 10.

[0177] 1. Sensitivity test

[0178] The sensitivity was verified by plasmid standards. Three batches were tested with three copy number loadings (500 copies, 50 copies, and 5 copies), and 20 replicates were performed in each batch and group. When the positive result was greater than 95%, it was judged to be qualified. The results of the sensitivity test of Saccharomyces cerevisiae are shown in Table 11.

[0179] Table 11 Saccharomyces cerevisiae sensitivity test results

[0180]

[0181]

[0182] 2. Specificity test

[0183] For the specificity test, Escherichia coli gDNA standard and tropical Candida DNA standard (both purchased from Beina Chuanglian Biotechnology Co., Ltd.) were used to verify the binding effect of 15 sets of primer probes. If there is no non-specific signal, the specificity is qualified. The results of the Saccharomyces cerevisiae specificity test are shown in Table 12.

[0184] Table 12 Saccharomyces cerevisiae specificity test results

[0185]

[0186]

[0187] 2. Precision test

[0188] The precision was verified by using 50 copies of plasmid standard. Three tests were performed on each site in the same batch, and a single test of three batches of each site was analyzed and calculated. The results of the precision test of Saccharomyces cerevisiae are shown in Table 13.

[0189] Table 13 Saccharomyces cerevisiae precision test results

[0190]

[0191]

[0192] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The above is only a specific implementation method of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or replacements that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A high-throughput fluorescence detection method, characterized in that: The process of performing high-throughput fluorescence detection includes: Step 1: Fluorescence coding, including: performing multi-color and multi-level coding on the same molecular probe to obtain a coded molecular probe, wherein the multi-color coding includes a combination of different colors of the same molecular probe, and the multi-level coding includes a combination of fluorescence intensities of the same color; one color corresponds to one wavelength of fluorescence; the coded molecular probe is distributed to at least two reaction units; Step 2: transcoding, including: performing super-multiplex amplification on the molecular probes in each reaction unit, and performing multi-interval amplification on each reaction unit; Step 3: decoding step, including: decoding using the reaction unit that has passed the transcoding step to obtain the content of the detection target corresponding to each fluorescent coding signal.

2. The method according to claim 1, characterized in that In the multi-color coding of the fluorescent coding link of step 1, it includes: Select n colors from m colors to form multi-color fluorescence coding, and the number of combinations obtained is Both n and m are positive integers, and when n=m / 2, the number of combinations is the largest.

3. The method according to claim 1, characterized in that: In the multi-stage encoding of the fluorescence encoding link of step 1, it includes: In the process of selecting multi-order encoding for a single color, the number of multi-order combinations is obtained. If the weakest fluorescence intensity that can be effectively resolved by the single color channel is o and the strongest fluorescence intensity is p, then o*2 q <p<o*2 q+1 , q is the number of divisions supported by the monochrome channel.

4. The method according to claim 1, characterized in that: The decoding process of step 3 includes: Collect the fluorescence intensity data of each reaction unit in different fluorescence channels and establish a data matrix; The sorted high-dimensional data matrix is ​​subjected to MASK processing, and then dimensionality reduction processing is performed to obtain the content of the detection target corresponding to each fluorescent coding signal.

5. The method according to claim 4, characterized in that The step of collecting the fluorescence intensity data of each reaction unit in different fluorescence channels and establishing a data matrix includes: Collect the fluorescence intensity of each reaction unit in different fluorescence channels to obtain the array corresponding to each reaction unit (i1, i2, i3...i m ), where m corresponds to the number of fluorescence channels, i m Then is the fluorescence intensity of the reaction unit in the fluorescence channel m; The fluorescence intensity data of all reaction units are combined to form the first high-dimensional matrix corresponding to sample a, where there are k reaction units corresponding to sample a: The fluorescence intensity data of the l reaction units of the positive reference b are merged to obtain the second high-dimensional matrix:

6. The method according to claim 4, characterized in that The MASK processing comprises: For Sequence cluster For each cluster in , according to each point in the cluster, in each calculation cycle, take the minimum point a1 as the starting point, then take the point a2 closest to the starting point to get a vector u, and then extend to the next adjacent point a3 to get another vector v, and then calculate the value of the vector cross product u*v; If the value of u*v is negative, the vector from a1 to a3 is used as the edge vector, and the next adjacent point is found and the calculation cycle is repeated until the edge range A of each cluster of the second high-dimensional matrix is ​​obtained. i ; Afterwards, A i Differentiate each element of the second high-dimensional matrix under the condition and get i A collection of elements in a range, and assigns the same label to each element in the collection i , and get a new first high-dimensional matrix.

7. The method according to claim 4, characterized in that Also includes: Before establishing the data matrix, high-dimensional clustering is performed on the data matrix.

8. The method according to claim 7, characterized in that Also includes: Sorting is performed after high-dimensional clustering is performed on the data matrix.

9. The method according to claim 8, characterized in that The performing high-dimensional clustering on the data matrix comprises: For the element x composed of each row of data in the second high-dimensional matrix i , if its ∈-neighborhood contains at least MinPts elements, then x i Determined as a core object, ∈ represents the radius of the data point, and MinPts represents the minimum number of data points in the neighborhood with a radius of ∈; All density-reachable core objects x i Together with all elements in the corresponding ∈-neighborhood, it forms a density cluster y i ; The unclustered elements x in the second high-dimensional matrix k Assign the same label label1, and the rest of the density clusters y i The elements in the label are given label i , and obtain the high-dimensional matrix after clustering.

10. The method according to claim 9, characterized in that The sorting after clustering includes: Get the average value of the elements in each cluster in m fluorescence channels; Compare the average values ​​of the elements in each cluster and sort them to get the sorting of the average values ​​of each element in different clusters, and then get the total score of each cluster according to the sorting of the average values ​​of the elements in different clusters; The ranking is done using the total score of each cluster.

11. The method according to claim 10, characterized in that The dimensionality reduction process comprises: Through multiple dimensionality reduction processing, the new first high-dimensional matrix is ​​reduced in dimensionality; The number of elements of the fluorescent coding probe is obtained from the first high-dimensional matrix after dimension reduction.

12. The method according to claim 11, characterized in that In the process of multiple dimensionality reduction processing, the PCA algorithm is used to reduce the dimension of the new first high-dimensional matrix, including: a) taking the first high-dimensional matrix as the original data and forming a matrix X with n rows and m columns by columns; b) Zero-mean each row of X; c) Get the covariance matrix d) Obtain the eigenvalues ​​and corresponding eigenvectors of the covariance matrix C; e) Arrange the eigenvectors into a matrix by row from top to bottom according to the corresponding eigenvalues, and take the first k rows to form the matrix P; f) The data after dimension reduction to k dimension is Y, where Y=PX.

13. The method according to claim 12, characterized in that The step of obtaining the number of elements of the fluorescent coding probe from the first high-dimensional matrix after dimensionality reduction includes: Combined with the sorting and labeling results, each element of the corresponding first high-dimensional matrix in the matrix P is assigned the same label, thereby obtaining the number of elements of each fluorescent coding probe.

14. A high-throughput fluorescence detection device, characterized in that: include: A coding module, used for performing multi-color and multi-level coding on the same molecular probe to obtain a coded molecular probe, wherein the multi-color coding includes a combination of different colors of the same molecular probe, and the multi-level coding includes a combination of fluorescence intensities of the same color; one color corresponds to one wavelength of fluorescence; the coded molecular probe is distributed to at least two reaction units; A transcoding module, for performing super-multiplex amplification on the molecular probes in each reaction unit and performing multi-interval amplification on each reaction unit; The decoding module is used to decode the reaction unit after the transcoding link to obtain the content of the detection target corresponding to each fluorescent coding signal.

15. A high-throughput fluorescence detection system, characterized in that: include: Experimental equipment, used to install the reaction unit and provide experimental conditions for super-multiplex amplification of the molecular probes in the reaction unit; A fluorescence acquisition device, used to acquire image data of the reaction unit; Computer equipment, used in the fluorescence encoding, transcoding and decoding stages; The fluorescence coding step includes: performing multi-color and multi-level coding on the same molecular probe to obtain the coded molecular probe, wherein the multi-color coding includes a combination of different colors of the same molecular probe, and the multi-level coding includes a combination of fluorescence intensities of the same color; one color corresponds to one wavelength of fluorescence; the coded molecular probe is distributed to at least two reaction units; The transcoding step includes: performing super-multiplex amplification on the molecular probes in each reaction unit, and performing multi-interval amplification on each reaction unit; The decoding link includes: decoding using the reaction unit that has passed the transcoding link to obtain the content of the detection target corresponding to each fluorescent coding signal.

16. The system according to claim 15, characterized in that The fluorescence collection device includes: an imaging device for photographing the reaction unit and collecting the images as optical signals.

17. The system according to claim 16, characterized in that The fluorescence collection device also includes: a photoelectric conversion device, which is used to convert the captured optical signal into image data.

18. A storage medium, characterized in that: A computer program or instruction is stored, and when the computer program or instruction is executed, the method according to any one of claims 1 to 13 is implemented.

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