A quantitative detection method and kit for dabie bandavirus recombinant reassortment based on multiple digital PCR technology

Abstract

The application provides a quantitative detection method and kit for recombinant reassortment of dabie bunyavirus based on multiple digital PCR technology, and belongs to the field of infectious disease monitoring. The method comprises the following steps: providing a to-be-detected sample containing segmented viruses and viral nucleic acids; detecting the nucleic acids by using a multiple digital PCR reaction system containing multiple specific primer pairs and fluorescently labeled probes; amplifying and collecting and analyzing multi-channel fluorescence signals according to a fluorescence coding rule, and calculating absolute copy numbers of each genotype; and analyzing the distribution proportion within the genotype fragments and the combination mode between the fragments based on the copy numbers, and evaluating the characteristics and frequency of the viral recombinant reassortment event. The detection method and kit provided by the application can realize accurate quantification of all main genotypes of dabie bunyavirus.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of infectious disease monitoring, and particularly relates to a quantitative detection method and kit for recombinant reassortment of Dabie bunyavirus based on multiplex digital PCR technology. BACKGROUND

[0002] Dabie bunyavirus (DBV) is a segmented, single-stranded negative-strand RNA virus, and its genome is composed of large (L), medium (M), and small (S) segments. At least six major genotypes, A to F, have been found. The virus is the pathogen of fever with thrombocytopenia syndrome (SFTS) and poses a serious threat to human health. During the transmission of the virus in nature hosts (such as ticks and animals) and human populations, the segmented genome characteristics enable recombination and reassortment to become the key driving force for evolution. These events may lead to the virus acquiring new biological characteristics, such as enhanced transmission, pathogenicity, or immune escape ability, which brings great challenges to epidemic monitoring, risk assessment, and prevention and control.

[0003] At present, the identification and analysis of viral recombination and reassortment events mainly rely on sequencing-based genetic analysis methods, including whole genome sequencing, sequence alignment, and phylogenetic analysis. These methods belong to post hoc qualitative analysis and can reveal the evolutionary history of fixed, dominant recombination and reassortment strains in the transmission chain. However, it is difficult to perform real-time and accurate quantification of ongoing, low-frequency mixed infections and gene segment exchange events in samples; secondly, deep sequencing is costly and time-consuming, and requires higher concentration and quality of viral nucleic acid in samples, which is not suitable for large-scale screening or real-time monitoring.

[0004] In recent years, digital PCR (dPCR) technology has played an important role in trace pathogen detection and complex genetic variation analysis due to its advantage of absolute quantification of nucleic acid molecules without the need for a standard curve. Multiplex digital PCR (mdPCR) technology further integrates the high-throughput capability of multiplex PCR, and can theoretically simultaneously quantify multiple targets in a single reaction. However, there are still many challenges in applying mdPCR technology to DBV recombination and reassortment quantification. First, DBV contains three segments and six genotypes, and up to 18 typing targets need to be specifically detected in a limited number of fluorescence channels, making it difficult to balance high-throughput and high-specificity. Second, the complex multiplex reverse transcription reaction efficiency for RNA templates is uneven, which can seriously affect the quantitative accuracy of the initial template amount of each target, making the results of calculating the recombination frequency based on the copy number ratio unreliable. In addition, the sequences of different genotypes are highly similar, and traditional probes cannot effectively distinguish key SNP sites, which can easily lead to typing errors in mixed infection samples. Therefore, a new detection method is needed to solve the above problems to achieve accurate quantification of DBV recombination and reassortment events and promote related virology research and risk warning. SUMMARY

[0005] Therefore, the application provides a method and kit for quantitatively detecting DBV recombination and reassortment based on multiplex digital PCR technology, which can accurately quantify all major genotypes of DBV and directly and quantitatively monitor and evaluate the frequency of DBV recombination and reassortment events.

[0006] Specifically, the application is achieved by the following technical solutions:

[0007] The first aspect of the application provides a method for quantitatively detecting DBV recombination and reassortment based on multiplex digital PCR technology, which comprises:

[0008] providing a sample to be tested, wherein the sample contains a segmented virus, the genome of the segmented virus contains at least two segments, and the sample contains nucleic acid of the segmented virus; and the virus is DBV;

[0009] using three independent multiplex digital PCR reaction systems, i.e., system 1, system 2 and system 3, to perform parallel detection on the nucleic acid; wherein system 1 is used to detect A-F genotypes on the L segment of DBV, system 2 is used to detect A-E genotypes on the M segment and F genotype on the S segment of DBV, and system 3 is used to detect A-E genotypes on the S segment and F genotype on the M segment of DBV; each system contains specific primer pairs and probes for different genotypes on different genome segments of the virus, and the probes have distinguishable fluorescent reporter groups;

[0010] Based on the pre-established fluorescence coding rules that characterize the correspondence between each genotype and the fluorescent reporter group, digital PCR amplification and detection are performed on each reaction system, multi-channel fluorescence signals are collected, the fluorescence signals are analyzed based on the fluorescence coding rules, positive reaction units of each genotype are identified, and the absolute copy number of each genotype is calculated.

[0011] Based on the absolute copy number of each genotype, the distribution ratio of different genotypes within the same genomic segment and the genotype combination patterns between different genomic segments are analyzed to assess the characteristics and frequency of viral recombination or reassortment events.

[0012] A second aspect of this application provides a quantitative detection kit for Dabie Bandar virus recombinant reassortment based on multiplex digital PCR technology, the kit comprising:

[0013] The specific primer and probe premixes, packaged separately for systems 1, 2 and 3, have core components consisting of nucleotide sequences or their functionally equivalent variants shown in SEQ ID NO:1 to SEQ ID NO:24, SEQ ID NO:25 to SEQ ID NO:43 and SEQ ID NO:44 to SEQ ID NO:63;

[0014] PCR buffer, containing at least MgSO4 solution, dNTP mixture, reverse transcriptase and thermostable DNA polymerase;

[0015] And the instruction manual.

[0016] The method and kit for quantitative detection of Dabie Bandar virus recombinant reassortment based on multiplex digital PCR technology provided in this application have the following advantages:

[0017] 1. This method enables direct and quantitative assessment of viral recombination and reassortment events. Traditional methods typically only provide qualitative or semi-quantitative analysis of established recombination and reassortment events, making it difficult to perform real-time and accurate quantification of low-frequency mixed infections and gene fragment exchange events occurring in samples. This method uses multiplex digital PCR technology to obtain the absolute copy number of each viral genotype and calculates the distribution ratio and combination pattern based on this. This allows for direct and quantitative assessment of the frequency, type, and characteristics of recombination and reassortment events, making it particularly suitable for segmented viruses such as Dabie Bandar virus (DBV).

[0018] 2. A high-throughput, multi-target simultaneous detection and high-specificity analysis system was established. By designing multiple collaborative multiplex digital PCR reaction systems and using distinguishable fluorescent reporter groups to encode multiple targets, it is possible to simultaneously, specifically identify, and absolutely quantify multiple genotypes on multiple viral genome fragments in a single detection process. This method effectively overcomes the technical difficulties of low throughput and long time consumption in traditional methods, as well as the difficulty of achieving high-density target detection and ensuring specificity in a limited number of channels with conventional multiplex PCR.

[0019] 3. It provides a stable and reliable basis for absolute quantitative analysis. Digital PCR technology can achieve absolute quantification of nucleic acid molecules without relying on a standard curve. This method utilizes this characteristic to provide a high-precision and highly reproducible data basis for subsequent quantitative analysis by accurately determining the absolute copy number of each genotype, ensuring the accuracy and reliability of the analytical results. Attached Figure Description

[0020] Figure 1 A flowchart of Example 1 of the Dabie Bandar virus recombination reassortment quantitative detection method based on multiplex digital PCR technology provided in this application;

[0021] Figure 2A This is a diagram showing the specificity test results of the L, M, and S systems in the FAM channel as illustrated in this application;

[0022] Figure 2B The diagram shows the Blank test results of the L, M and S systems in the FAM channel as presented in this application.

[0023] Figure 2C This is a graph showing the specificity test results of the L, M, and S systems on the HEX channel as illustrated in this application;

[0024] Figure 2D The diagram shows the Blank test results of the L, M and S systems in this application on the HEX channel.

[0025] Figure 2E This is a graph showing the specificity test results of the L, M, and S systems on the ROX channel as illustrated in this application;

[0026] Figure 2F The diagram shows the Blank test results of the L, M and S systems in the ROX channel as presented in this application.

[0027] Figure 2G This is a graph showing the specificity test results of the L, M, and S systems in the CY5 channel as illustrated in this application;

[0028] Figure 2H The diagram shows the Blank test results of the L, M and S systems shown in this application on the CY5 channel.

[0029] Figure 3A The optimization results diagram of the LA typing single system provided in this application;

[0030] Figure 3B The LC classification single-system optimization result diagram provided in this application;

[0031] Figure 3C The optimization results diagram of the LD classification single system provided in this application;

[0032] Figure 3D The LF classification single-system optimization result diagram provided in this application;

[0033] Figure 3E The image shows the optimization results of the MA classification single system provided in this application;

[0034] Figure 3F The MD classification single-system optimization result diagram provided in this application;

[0035] Figure 3G The ME typing single-system optimization result diagram provided in this application;

[0036] Figure 3H The SC classification single-system optimization result diagram provided in this application;

[0037] Figure 3I The optimization results diagram of the SF classification single system provided in this application;

[0038] Figure 4A The optimization results diagram of the L system provided for this application;

[0039] Figure 4B Another L-system optimization result diagram provided for this application;

[0040] Figure 5 The optimization results of the three systems on the RNA template provided for this application are shown in the figure;

[0041] Figure 6 The test results diagram of the multi-coded signal provided in this application;

[0042] Figure 7A The LA(FAM) test results provided in this application are shown in the figure.

[0043] Figure 7B The LB(HEX) test results provided in this application are shown in the figure.

[0044] Figure 7C The LC(ROX) test results provided in this application are shown in the figure.

[0045] Figure 7D The LD(CY5) test results diagram provided in this application;

[0046] Figure 7E The LE(FAM) test results diagram provided in this application;

[0047] Figure 7F The image shows the LE(HEX) test results provided in this application;

[0048] Figure 7G The LF(A425) test results diagram provided in this application;

[0049] Figure 7H The MA (FAM) test results diagram provided in this application;

[0050] Figure 7I The MB(HEX) test results provided in this application are shown in the figure.

[0051] Figure 7J The MC(ROX) test results provided in this application are shown in the figure.

[0052] Figure 7K The MD(CY5) test results provided in this application are shown in the figure.

[0053] Figure 7L The ME(A425) test results diagram provided in this application;

[0054] Figure 7M The SF(ROX) test results provided in this application are shown in the figure.

[0055] Figure 7N The SF(CY5) test results diagram provided in this application;

[0056] Figure 7O The SA (FAM) test results diagram provided in this application;

[0057] Figure 7P The SB(HEX) test results provided in this application are shown in the figure.

[0058] Figure 7Q The SC(ROX) test results provided in this application are shown in the figure.

[0059] Figure 7R The SD(CY5) test results provided in this application are shown in the figure.

[0060] Figure 7S The SE(A425) test result diagram provided for this application;

[0061] Figure 7T The MF(ROX) test results provided in this application are shown in the figure.

[0062] Figure 7UThe MF(CY5) test results provided for this application are shown in the figure. Detailed Implementation

[0063] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0064] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used herein are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0065] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0066] The following specific embodiments are given to illustrate the technical solution of this application in detail.

[0067] Example 1

[0068] Figure 1 This is a flowchart of Example 1 of the method for quantitative detection of Dabie Bandar virus recombination reassortment based on multiplex digital PCR technology provided in this application. Please refer to... Figure 1 The method provided in this embodiment may include:

[0069] S101. Provide a sample to be tested, wherein the sample contains a segmented virus, the genome of the segmented virus contains at least two segments, and the sample contains the nucleic acid of the segmented virus; the virus is Dabie Bandar virus.

[0070] It should be noted that this embodiment uses Dabie Bandar virus (DBV) as an example. DBV is a segmented, single-stranded, negative-sense RNA virus whose genome consists of three segments: large (L), medium (M), and small (S). The test sample refers to various biological specimens that may contain DBV. Based on the epidemiological characteristics of the virus, typical sources include, but are not limited to, clinical samples from patients exhibiting fever with thrombocytopenia syndrome (SFTS), such as acute-phase serum, plasma, or blood cell layers, as well as animal tissue samples that serve as potential reservoir hosts for the virus, such as spleen, lymphoid tissue homogenates, or tick specimens. The acquisition of these samples must comply with standard biosafety and ethical guidelines.

[0071] It should be noted that obtaining nucleic acid samples containing viral RNA from the test samples is specifically achieved by extracting total RNA. Total RNA refers to the sum of all ribonucleic acid molecules extracted from the test samples. It is a mixture containing multiple components, mainly including host messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA), etc., and also includes genomic RNA of pathogens (such as DBV) that may be present in the sample.

[0072] Obtaining nucleic acid samples containing viral RNA refers to the process of separating total RNA from the complex matrix of a sample, such as proteins, lipids, and cellular debris, using specific lysis and purification techniques. This operation is typically accomplished using commercially available column-based or magnetic bead-based RNA extraction kits. The principle involves using a lysis buffer to disrupt cells and the viral capsid, releasing nucleic acids, which are then specifically adsorbed onto a solid-phase carrier. After washing to remove impurities, a high-purity nucleic acid solution is finally obtained. Since DBV is an RNA virus, its genome replicates in the host cell cytoplasm; therefore, the total RNA successfully extracted from an infected sample contains viral genomic RNA. The concentration and purity of the nucleic acid sample obtained through this step can be measured to ensure quality. It serves as an unamplified initial template and is the material basis for subsequent reverse transcription, digital PCR amplification, and the final quantification of the absolute copy number of all genotypes.

[0073] S102. The nucleic acid is detected in parallel using three independent multiplex digital PCR reaction systems, namely System 1, System 2, and System 3. System 1 is used to detect the AF genotype on the L fragment of Dabie Banda virus, System 2 is used to detect the AE genotype on the M fragment and the F genotype on the S fragment of Dabie Banda virus, and System 3 is used to detect the AE genotype on the S fragment and the F genotype on the M fragment of Dabie Banda virus. Each system contains specific primer pairs and probes for different genotypes on different genomic fragments of the virus, and the probes have distinguishable fluorescent reporter groups.

[0074] In this embodiment, the nucleic acid sample is detected using three independent, premixed multiplex digital PCR reaction systems, specifically including:

[0075] The nucleic acid sample was divided into three equal portions and mixed with systems 1, 2, and 3, respectively. System 1 was used to detect all AF genotypes on the L fragment of Dabie Bandar virus; system 2 was used to detect the AE genotype on the M fragment and the F genotype on the S fragment; system 3 was used to detect the AE genotype on the S fragment and the F genotype on the M fragment. Systems 1, 2, and 3 each contained the nucleotide sequences shown in SEQ ID NO:1 to SEQ ID NO:24, SEQ ID NO:25 to SEQ ID NO:43, and SEQ ID NO:44 to SEQ ID NO:63, or their functionally equivalent variants; the probes carried different fluorescent reporter groups. The reaction buffers of systems 1, 2, and 3 contained Mg... 2+ Unlike the final concentration of dNTPs, blocking probes were used for detection of at least one genotype.

[0076] It should be noted that the DBV genome consists of three independent RNA fragments: L, M, and S. Recombination and reassortment analysis requires knowledge of the genotypes on each of these three fragments. By dividing a sample into three equal parts and performing three independent parallel detection reactions, simultaneous and independent quantitative analysis of the three viral genome fragments in the same original sample can be ensured. Specifically, the limited number of fluorescence channels in a single system prevents the simultaneous assignment of unique fluorescence codes to all genotypes (3 fragments × 6 types = 18 targets). By splitting the detection targets into three systems, high-throughput and specific detection of all 18 targets can be achieved within a limited number of channels, allowing for accurate calculation of the combination relationships between different fragments. This trisection design eliminates potential errors from multiple sampling and ensures the consistency of data sources.

[0077] Multiplex digital PCR (dPCR) reaction systems are integrated reaction systems combining multiplex PCR technology with digital PCR (dPCR). The core of this system is that a single tube / system simultaneously contains specific primer pairs and fluorescently labeled probes targeting multiple targets, along with optimized reaction buffers, enzymes, nucleotides, and other components. This allows for simultaneous absolute quantification of multiple targets (such as different DBV fragments or genotypes) in a single reaction. The reaction buffer provides a stable pH environment, ionic strength, and necessary chemical components; enzymes include reverse transcriptase (used to convert RNA templates into cDNA) and thermostable DNA polymerases (such as Taq polymerase); nucleotides include deoxyribonucleoside triphosphates (dNTPs), which are the raw materials for synthesizing new DNA strands. Furthermore, the multiplex digital PCR reaction system also includes magnesium ions (Mg²⁺).2+ The study included specific primer pairs and probe combinations. Magnesium ions are a key cofactor for DNA polymerase, and their concentration directly affects enzyme activity and the specificity of primer annealing. Specific primer pairs and probe combinations are used to identify and amplify specific viral gene targets. The amount of reverse transcriptase used was 1.2 μL / 30 μL, and the amount of Taq polymerase used was 1 μL / 30 μL.

[0078] Specifically, the aliquoted nucleic acid samples (as templates) are added separately to the premixed multiplex digital PCR reaction system. After gentle mixing, these constitute complete systems 1, 2, and 3, ready for amplification. It should be noted that the premixed systems already contain all detection components for their respective target genotypes. That is, the premixed multiplex digital PCR reaction system refers to a semi-finished system without template (premixed primers / probes, reaction buffer, enzymes, Mg...). 2+ After being mixed with equal portions of nucleic acid samples (such as dNTPs), the final system consists of three parts: 1, 2, and 3 (including template).

[0079] Specifically, the detailed sequence configuration information for System 1, System 2, and System 3 is shown in Table 1:

[0080] Table 1. Detailed sequence configuration information for System 1, System 2, and System 3

[0081]

[0082] Please refer to Table 1. This cross-design effectively solves the problem of not being able to cover all 18 (3 fragments × 6 types) target points with a single tube in a limited reaction system. The detection of all targets is achieved through the reasonable division of labor among the three tubes.

[0083] Furthermore, it should be noted that for each target genotype (e.g., LA, MB), a pair of specific primers (upstream and downstream primers) was designed. Their function is to precisely locate and amplify the target gene sequence. Within the amplification region defined by each primer pair, a specific probe was designed. This probe has a fluorescent reporter group (e.g., FAM, HEX) covalently linked to its 5' end and a fluorescent quencher group linked to its 3' end. When the probe is intact, fluorescence is quenched; during PCR amplification, when the polymerase encounters the probe bound to the template, it hydrolyzes it, separating the reporter group from the quencher group, thus releasing a fluorescent signal. Each target probe carries a different color (type) of fluorescent reporter group, which serves as the fluorescent encoding. By detecting the combination of fluorescent colors emitted from each droplet after the reaction, it is possible to infer which specific viral genotype(s) was amplified in that droplet.

[0084] Furthermore, it should be noted that in this embodiment, 3×Maxuseful Buffer was used as the reaction buffer for systems 1, 2, and 3. This buffer is a digital PCR-specific buffer. Specifically, in the multiplex reverse transcription-digital PCR system constructed in this application, using this buffer provides a suitable environment for the reaction, supporting efficient and specific amplification of multiple targets, thereby obtaining fluorescence signals that can be accurately quantified. In practice, other digital PCR-specific buffers with similar functions may also be applicable to this embodiment, but this embodiment uses 3×Maxuseful Buffer as an example to demonstrate its feasibility.

[0085] Similarly, Mg in the premixed multiplex digital PCR reaction system 2+ The concentrations of Mg differ from those of dNTPs, therefore the concentrations of Mg in systems 1, 2, and 3 are different. 2+ The concentration of Mg also differs from that of dNTPs. 2+ The concentration of Mg and dNTPs is a key factor affecting the efficiency, specificity, and accuracy of PCR. Because the primer and probe sequences, quantities, and GC content differ in systems 1, 2, and 3, their optimal ion concentration requirements also differ. Specifically, in system 1, Mg... 2+ The final concentration was 2.0 mM, and the final concentration of dNTPs was 0.2 mM. These conditions were optimal for the balanced amplification of all genotype targets of the L fragment. In system 2, Mg... 2+ The final concentration was 2.5 mM, the final concentration of dNTPs was 0.2 mM, and the Mg concentration was slightly higher. 2+ Concentration may help stabilize the secondary structure or primer binding of the M fragment and SF target in multiple reactions; in system 3, Mg 2+ The final concentration was 2.0 mM, and the final concentration of dNTPs was 0.1 mM. The lower dNTP concentration helps to improve the rigor of amplification in this specific system and is beneficial for suppressing certain non-specific background signals.

[0086] It should be noted that blocking probes were used for the detection of at least one genotype. A blocking probe is a special oligonucleotide whose 3' end is chemically modified (e.g., phosphorylated) to prevent elongation by DNA polymerase. In this application, blocking probes were introduced for genotype pairs with highly similar sequences that are difficult to distinguish using ordinary probes alone (e.g., mutant and wild-type of a specific genotype). The principle is that the blocking probe perfectly matches one of the non-target sequences (e.g., wild-type) and binds preferentially. Because it cannot be elongated, the amplification of this non-target template is physically blocked. The target sequence (e.g., mutant), because it does not perfectly match the blocking probe, can still be bound and amplified by normal primers and fluorescent probes, thus generating a signal. This design greatly enhances the ability to distinguish closely related targets (genotyping resolution).

[0087] Specifically, the primers, probes, and blocking probes used in System 1 contain the nucleotide sequences shown in SEQ ID NO:1 to SEQ ID NO:24, or their functionally equivalent variants. The primers and probes used in System 2 contain the nucleotide sequences shown in SEQ ID NO:25 to SEQ ID NO:43, or their functionally equivalent variants; and the primers and probes used in System 3 contain the nucleotide sequences shown in SEQ ID NO:44 to SEQ ID NO:63, or their functionally equivalent variants.

[0088] It should be noted that SEQ ID NO:1 to SEQ ID NO:24 sequences endow System 1 with the ability to detect the L fragment AF type, SEQ ID NO:25 to SEQ ID NO:43 sequences endow System 2 with the ability to detect the M fragment AE and SF types, and SEQ ID NO:44 to SEQ ID NO:63 sequences endow System 3 with the ability to detect the S fragment AE and MF types. Functionally equivalent variants refer to nucleotide sequences that have high homology to the listed SEQ ID NO sequences, can bind to the same target sequence under strict hybridization conditions, and ultimately achieve equivalent specificity, sensitivity, and quantitative function in the detection system.

[0089] S103. Based on the pre-established fluorescence coding rules that characterize the correspondence between each genotype and the fluorescent reporter group, digital PCR amplification and detection are performed on each reaction system, multi-channel fluorescence signals are collected, the fluorescence signals are analyzed based on the fluorescence coding rules, positive reaction units of each genotype are identified, and the absolute copy number of each genotype is calculated.

[0090] Specifically, the three mixed systems were subjected to droplet generation or chip partitioning, and a unified amplification program was run on the same digital PCR instrument. After amplification, multi-channel fluorescence signals of each partition were collected. Then, according to the pre-established fluorescence coding rules, the collected multi-channel fluorescence signals were analyzed to identify and count each positive partition. Based on the Poisson distribution principle, the absolute copy number concentration of each Dabie Bandar virus genotype target in the nucleic acid samples in systems 1, 2, and 3 was calculated.

[0091] It should be noted that the homogeneous reaction solution of each system is physically divided into tens of thousands to hundreds of thousands of independent reaction units (droplets or chip chambers) at the nanoliter level using a droplet generator or microfluidic chip technology. Ideally, each unit should contain no more than one target nucleic acid molecule (following a Poisson distribution). In this way, the subsequent amplification signal will directly reflect the presence or absence of the target molecule in each unit, thus achieving absolute counting without relying on a standard curve. Droplet generation and chip partitioning are two mainstream and mature technologies for achieving the above physical partitioning, and they are equivalent in principle. This application is compatible with both technologies, ensuring its implementation on platforms from different manufacturers.

[0092] After partitioning, the systems containing all independent reaction units were placed in the same digital PCR instrument and run a uniformly optimized thermal cycling program for all three systems. Specifically, the uniform amplification program included: reverse transcription at 50°C for 30 minutes; pre-denaturation at 95°C for 5 minutes; and 45 cycles, each cycle consisting of 10 seconds of denaturation at 95°C and 40 seconds of annealing extension at 58°C. Maintaining the temperature at 50°C for 30 minutes ensures that the viral genomic RNA template (and the RNA used as an internal control) is completely converted into more stable complementary DNA (cDNA) under the catalysis of reverse transcriptase within the system, providing a template for subsequent PCR amplification. Sufficient temperature and time ensure that various RNA templates can be reverse transcribed efficiently and thoroughly even in complex multiplex systems. The 5-minute pre-denaturation at 95°C is a secondary high-temperature step used to fully activate thermostable DNA polymerase and ensure that all double-stranded cDNA templates are completely unstranded into single strands, preparing for primer binding. In addition, denaturation at 95°C for 10 seconds uses a brief period of high temperature to unwind the newly amplified double-stranded DNA product, while annealing and extension at 58°C for 40 seconds is because at this temperature, each pair of specific primers can bind precisely and specifically to the target region of their cDNA template (annealing), and the DNA polymerase synthesizes a new DNA strand along the template starting from the primer (extension). When the polymerase encounters a fluorescent probe bound to the template, its 5'→3' exonuclease activity hydrolyzes the probe, separating the fluorescent reporter group from the quencher group and releasing the fluorescent signal specific to the target. After multiple cycles, the target sequence and the corresponding fluorescent signal in the positive reaction unit are amplified exponentially.

[0093] After the amplification process is complete, the digital PCR instrument automatically acquires fluorescence signals. The instrument uses a laser of a specific wavelength to excite each individual reaction unit and simultaneously acquires the emitted fluorescence intensity through multiple optical detection channels (such as FAM, HEX, ROX, CY5, Atto425, and Quasar705 channels). Ultimately, each reaction unit obtains a fluorescence intensity value on each fluorescence channel, thus forming a multidimensional fluorescence signal data point. The acquired signal is actually information on the presence / absence and color combinations of tens of thousands of independent reaction units across multiple fluorescence dimensions.

[0094] It should be noted that the pre-established fluorescence coding rules are the one-to-one or combined correspondences between each target genotype and the fluorescent reporter group (color) carried by its specific probe, which were determined during the design phase of step S102. Specifically, the pre-established fluorescence coding rules include: in system 1, LA corresponds to FAM, LB to HEX, LC to ROX, LD to CY5, LE to FAM+HEX, LF to Atto425, and the internal control DBV to Quasar705; in system 2, MA corresponds to FAM, MB to HEX, MC to ROX, MD to CY5, ME to Atto425, and SF to ROX+CY5; in system 3, SA corresponds to FAM, SB to HEX, SC to ROX, SD to CY5, SE to Atto425, and MF to ROX+CY5. See Table 1 for details.

[0095] In practice, the software of the digital PCR instrument automatically analyzes the multi-channel fluorescence intensity data collected by each independent reaction unit according to this rule. It determines whether the signal of the unit in each fluorescence channel exceeds the preset positive threshold. If a unit is positive in a single specific channel (such as the FAM channel) and negative in other related channels, it is determined that the unit contains the corresponding single genotype target (such as the LA type). If a unit is positive in two specific channels (such as the FAM and HEX channels) simultaneously, it is determined that the unit contains the corresponding genotype target using dual fluorescence encoding (such as the LE type). Dual fluorescence encoding enhances the reliability and specificity of signal interpretation in complex multiplex systems. Through this rule, the fluorescence color combination of each unit is translated back into the contained viral genotype information, thus completing the conversion from physical signal to biological meaning.

[0096] It should be noted that, based on the above analysis, the software will classify and count all valid reaction units. Positive regions refer to those with fluorescence signal intensity exceeding a set threshold and thus identified as containing a specific target genotype; negative regions refer to those where all target fluorescence channel signals are below the threshold. The software will count the number of positive regions corresponding to each genotype target (e.g., LA, LB, ... MF) in Systems 1, 2, and 3, and will also count the total number of negative regions in each system.

[0097] It should be noted that the core theory of absolute quantification in digital PCR is the Poisson distribution. Specifically, in a large number of independent partitions, nucleic acid molecules are randomly distributed among them. According to the Poisson distribution formula, the copy number concentration of the target molecule (expressed as copies per microliter, copies / μL) can be calculated using the following formula:

[0098] Concentration = -ln(1-p)*(N / V);

[0099] Where p = positive partition ratio (number of positive partitions / total number of effective partitions), N = total number of effective partitions, V = reaction liquid volume allocated to each partition (in microliters, determined by instrument parameters and total system volume), and ln is the natural logarithm.

[0100] It should be noted that the highly optimized reaction system (buffer, ion concentration, probe design) in S102 ensures that the fluorescence signal in each droplet / partition is clear, specific, and has low background, thereby making the interpretation of positive partitions and the calculation of absolute quantification based on Poisson distribution highly accurate and reliable.

[0101] In practice, the analysis software of the digital PCR instrument automatically applies this formula, using the number of positive partitions and the total number of partitions corresponding to each genotype obtained in the previous step, to calculate the absolute copy number concentration of each detected Dabie Bandar virus genotype target in the original nucleic acid sample in Systems 1, 2, and 3. The absoluteness of this calculation result lies in the fact that it does not depend on any standard curve or reference sample, but is based solely on physical partitioning and statistical principles, thus possessing extremely high accuracy and reproducibility, and can directly reflect the true molecular quantity of each viral genotype in the original sample.

[0102] S104. Based on the absolute copy number of each genotype, analyze the distribution ratio of different genotypes within the same genomic fragment and the genotype combination pattern between different genomic fragments, and evaluate the characteristics and frequency of viral recombination or reassortment events.

[0103] Based on the absolute copy number of different genotypes on each obtained fragment, the distribution ratio of different genotypes within the same viral fragment is calculated, and the combination pattern of genotypes between different fragments is analyzed to assess the frequency and characteristics of potential recombination or reassortment events of Dabie Bandar virus in the sample.

[0104] It's important to note that calculating the distribution ratio of different genotypes within the same viral fragment aims to determine whether co-infection exists at the level of a single viral genome fragment (L, M, or S), i.e., whether different genotypes of the same fragment are present simultaneously in the same sample (e.g., genotypes A and C are present on fragment L). Specifically, for each of the three fragments L, M, and S, the absolute copy numbers of all detected different genotypes on that fragment are summed to obtain the total viral copy number of that fragment. Then, the absolute copy number of each specific genotype is divided by the total copy number of that fragment to obtain the percentage composition or distribution ratio of that genotype within that fragment. If two or more genotypes appear within a single fragment and each accounts for a certain proportion (e.g., each > 1%), it indicates co-infection with different viral strains in the sample. Co-infection is a necessary prerequisite for fragment exchange (reassortment) or gene recombination events in the viral genome.

[0105] The purpose of analyzing genotype combination patterns among different fragments is to further determine whether fragment rearrangement has occurred in the viral particle genome, i.e., whether fragments from different parental strains have combined into the same progeny viral particle, based on the confirmed possibility of co-infection. Specifically, based on independently quantitatively obtained, one-to-one corresponding data from three systems, all theoretically possible LMS genotype combinations of viral genomes in the sample can be reconstructed. This is then compared with known, common viral strain genotype profiles (e.g., a typical combination for a prevalent strain is LA / MB / SC). If a large number of genomes exhibit atypical, mixed combination patterns (e.g., a large number of viral particles show the LA / MD / SC combination, while parental strain A usually pairs with MB, and parental strain D usually pairs with SF), this indicates gene reassortment. By analyzing the proportion of various combination patterns in the total viral population, the frequency of occurrence of different reassorted progeny viruses can be quantified.

[0106] By integrating the above analyses, the incidence of recombination / reassortment events can be modeled and estimated. For example, reassortment frequency can be quantified as the percentage of progeny virus particles producing non-parental LMS combinations in the context of co-infection. This provides a quantitative indicator for viral evolutionary dynamics research. Furthermore, analysis can further reveal the preferences and directions of reassortment events. For instance, whether certain fragments (such as the M fragment) are more prone to exchange, or whether certain genotype combinations (such as the combination of L fragment type A and M fragment type D) occur particularly frequently, these characteristics help to understand the driving forces and constraints of viral evolution. Finally, by assessing the frequency and characteristics of recombination / reassortment events, the genetic diversity level and evolutionary activity of the viral population in the current sample can be scientifically determined, and warnings can be issued regarding the potential emergence of risky strains with new characteristics (such as enhanced transmissibility, altered pathogenicity, or immune evasion).

[0107] The method provided in this embodiment achieves simultaneous absolute quantification of all six major genotypes of the three fragments of Dabie Banda virus within a limited fluorescence channel through a three-system cross-design and fluorescence coding strategy. Relying on deeply optimized dedicated reaction buffers, differentiated ion concentrations, and blocking probes, it ensures the specificity, sensitivity, and quantitative accuracy of complex multiplex reverse transcription-PCR reactions. Finally, based on the absolute copy number of each genotype target, this method can directly calculate the co-infection ratio within viral fragments and the reassortment frequency between fragments, thus advancing the assessment of recombination and reassortment events from traditional qualitative tracing to a new stage of quantifiable and dynamic monitoring. This method is not only applicable to Dabie Banda virus but also provides a general technical framework for the quantitative analysis of recombination and reassortment of other segmented viruses, offering a powerful quantitative tool for virus evolution research, early warning of novel strains, and precise prevention and control.

[0108] Example 1: Design and preparation of detection primers, probes and templates

[0109] Objective: To provide highly specific molecular tools and standard templates of known concentrations required to validate the methods of this application.

[0110] Analysis was performed on the sequence files of Dabie Bandar (L.fasta, M.fasta, and M.fasta). The A, B, C, D, E, and F genotypes in the L, M, and S fragments were individually aligned. A conservatism threshold of 95% was set to obtain individual conserved sequences for each of A, B, C, D, E, and F. Alignment between these conserved sequences was then performed to identify SNP sites that distinguish a specific genotype from the other five genotypes. Appropriate sites were selected for system design for each genotype. The plasmid template was truncated to a length of approximately 500 bp to the left and right of the SNP site. If the genotype SNP sites were adjacent, the genotype system was included in the template of the same sequence during template truncation. The templates were used to synthesize the corresponding mutant (MT) and wild-type (WT) genotypes. Tables 2, 3, and 4 show the system coding information, primer / probe sequences, and template sequences, respectively.

[0111] Table 2 System Coding Information

[0112]

[0113] Table 3 Primer and probe sequences

[0114]

[0115] Table 4 Template sequence list

[0116]

[0117] Specifically, the template is prepared as follows:

[0118] 1. Plasmid template preparation

[0119] We commissioned Sangon Biotech to construct the pUC57 plasmid containing the target amplification fragment. The plasmid template preparation process is as follows:

[0120] Plasmid dilution: Add the synthesized plasmid to Low TE buffer, mix well, and the concentration should be approximately 80 ng / μL; centrifuge gently and incubate at 4°C for 30 minutes to ensure complete precipitation of the plasmid template;

[0121] Plasmid digestion: The circular plasmid was converted into a linear molecule using BspQI restriction endonuclease. The digestion system is shown in Table 5. The reaction conditions were 50℃ for 60 minutes and 80℃ for 20 minutes.

[0122] The enzyme digestion system is prepared as shown in Table 5 (20 μL system):

[0123] Table 5. Preparation of Enzyme Digestion System

[0124]

[0125] Serial dilution: The concentration of plasmid after enzyme digestion is approximately 2 × 10⁻⁶. 9copies / μL, serially diluted 10-fold to approximately 2×10⁻⁶ copies / μL, 3 Copies / μL were then frozen at -20°C. Simultaneously, a pair of primers and probes were designed on the plasmid backbone for subsequent evaluation of the accuracy of pathogen quantification.

[0126] lacZ-F (upstream primer): 5'-gtgtgaaattgttatccgctca-3';

[0127] lacZ-R (downstream primer): 5'- caccccaggctttacacttta-3';

[0128] lacZ-P (probe): 5'FAM-tccacacaacatacgagccgg-BHQ1-3'.

[0129] 2. Preparation of RNA template

[0130] RNA templates were used to simulate the reverse transcription process of RNA viruses and to evaluate the reverse transcription efficiency of the system. The RNA template was prepared as follows:

[0131] Preparation of PCR products containing the T7 recognition region

[0132] All synthesized target fragments were inserted at the same location on the pUC57 plasmid. However, pUC57 lacks a T7 promoter recognition region. Therefore, a pair of shared primers containing the T7 promoter recognition region were first used to amplify the target fragments (upstream: CGATGCATCTAGATATCGGATC; downstream: TAATACGACTCACTATAGGGAATGTGAGTTAGCTC, where TAATACGACTCACTATAGGG is the T7 promoter recognition region). The amplification product was 706 bp. Amplification was performed using the high-fidelity enzyme KOD DNA polymerase. The amplification system was prepared as shown in Table 6.

[0133] Table 6 Preparation of amplification system

[0134]

[0135] The amplification procedure is shown in Table 7:

[0136] Table 7 Amplification Procedure

[0137]

[0138] Briefly centrifuge the T7 RNA Polymerase Mix and place it on ice. Thaw 10× Transcription Buffer and ribonucleotides (ATP, CTP, GTP, UTP), centrifuge, place 10× Transcription Buffer at room temperature, and place the four ribonucleotides on ice. Prepare the transcription reaction at room temperature as shown in Table 8:

[0139] Table 8. Preparation of transcription reactions at room temperature

[0140]

[0141] Mix the above reaction solution, briefly centrifuge to the bottom of the test tube, and incubate at 37°C for 2 hours.

[0142] DNA digestion

[0143] After the reaction was complete, 2 μL of DNase I (RNase-free) was added to each PCR tube and incubated at 37°C for 30 min; then inactivated at 65°C for 10 min to remove DNA.

[0144] RNA template dilution and aliquoting

[0145] Based on previous experimental results, when the amount of plasmid added is 80 ng / μL (≈10¹⁰ copies / μL), the concentration of RNA template after transcription is approximately 10. 11 The RNA yield is on the order of copies / μL. Theoretically, RNA yield is directly proportional to the amount of plasmid used. If the plasmid powder concentration is low, adjust the dilution gradient according to the actual concentration.

[0146] Take 5 μL of the above plasmid template and add it to 495 μL of water. Mix thoroughly to achieve a concentration of approximately 10. 9 copies / μL (gradient 2);

[0147] Take 5 μL of the above plasmid template and add it to 495 μL of water. Mix thoroughly to achieve a concentration of approximately 10. 7 copies / μL (gradient 4);

[0148] Take 5 μL of the above plasmid template and add it to 495 μL of RNA dilution buffer. Mix thoroughly to achieve a concentration of approximately 10. 5 copies / μL (gradient 6);

[0149] Take 5 μL of the above plasmid template and add it to 495 μL of RNA dilution buffer. Mix thoroughly to achieve a concentration of approximately 10. 3 copies / μL (gradient 8);

[0150] The dilution gradients are shown in Table 9:

[0151] Table 9 Dilution gradient

[0152]

[0153] Quantification of RNA in vitro transcription template

[0154] Quantification of gradient 8 (or higher) was performed using the Lacz system. Two microarrays were used for quantification of each template. RNA in vitro transcription template quantification is shown in Table 10.

[0155] Table 10 Quantification of RNA in vitro transcription template 1

[0156]

[0157] Based on the actual quantitative results of the first round, if the quantitative result exceeds the detection limit or the copy number is too low (<100 copies / uL), a template with an appropriate gradient is selected for further quantitative analysis, as shown in Table 11:

[0158] Table 11 Quantification of RNA in vitro transcription template 2

[0159]

[0160] DNA digestion efficiency test

[0161] Select a suitable gradient template (>10) 4 DNA residue was quantified using the Lacz system (copies / μL). One microarray was used to quantify each in vitro transcribed RNA template. DNA digestion efficiency is shown in Tables 12 and 13.

[0162] Table 12 DNA Digestion Efficiency Test 1

[0163]

[0164] Table 13 DNA Digestion Efficiency Test 2

[0165]

[0166] RNA in vitro transcription template dilution and aliquoting

[0167] Based on the quantitative results, select an appropriate gradient to dilute the RNA template to a concentration of approximately 5 × 10⁻⁶. 3 Aliquots / μL (1mL) were dispensed into 50μL PCR tubes and stored at -70℃. The remaining RNA template was labeled and stored in sample tubes at -70℃.

[0168] Example 2: Performance Verification of the Detection Method

[0169] Objective: To comprehensively verify the specificity, sensitivity, accuracy, and application potential of the method described in this application in recombinant reassortment analysis using the standard prepared in Example 1.

[0170] Specificity verification

[0171] Figure 2A This is a graph showing the specificity test results of the L, M, and S systems in the FAM channel as illustrated in this application. Figure 2B The graph shows the Blank test results of the L, M, and S systems in the FAM channel as illustrated in this application. Figure 2C This is a graph showing the specificity test results of the L, M, and S systems on the HEX channel as illustrated in this application. Figure 2D The graph shows the Blank test results of the L, M, and S systems on the HEX channel as illustrated in this application. Figure 2E This is a graph showing the specificity test results of the L, M, and S systems on the ROX channel as illustrated in this application. Figure 2F The graph shows the Blank test results of the L, M, and S systems shown in this application on the ROX channel. Figure 2G This is a graph showing the specificity test results of the L, M, and S systems in the CY5 channel as illustrated in this application. Figure 2H For the Blank test results of the L, M, and S systems shown in this application on the CY5 channel, please refer to... Figures 2A-2H After optimization, the system showed high specificity against a human genome background. Replacing the buffer with 3×Maxuseful and increasing the annealing temperature to 58℃ significantly reduced the background in some channels. The Blank control showed no abnormal specks. Figures 3A-3H This demonstrates that the system has good specificity and no obvious non-specific amplification.

[0172] Quantitative accuracy verification

[0173] The quantitative results of the L, M, S systems and the LacZ system designed on the plasmid backbone were compared, and the test results are shown in Table 14 below:

[0174] Table 14 Quantitative results of single-system, L, M, S, and LacZ systems on the same plasmid.

[0175]

[0176] Please refer to Table 14. There is no significant difference in the quantitative results of the single system, L, M, S system and LacZ system on the same plasmid, indicating that the quantitative accuracy of the complex multiplex system meets the requirements and can provide reliable absolute copy number data for recombination and reassortment analysis.

[0177] Signal specificity and optimization verification

[0178] For genotypes with highly similar sequences, precise differentiation was achieved through probe adjustment and the introduction of blocking probes:

[0179] Figure 3A Please refer to the optimization results diagram of the LA typing single system provided in this application. Figure 3A For the LA typing single system (LA-P1 mutant signal & wild signal vs LA-P2 mutant signal & wild signal), we tried to adjust the probe to enhance its positive signal intensity or signal clustering. It was found that the new probe had no expected effect, so we retained LA-P1. Figure 3B Please refer to the optimization results diagram of the LC classification single system provided in this application. Figure 3B For the LC typing single system (LC-P1 mutant signal & wild signal vs LC-P2 mutant signal & wild signal), we tried to adjust the probe to enhance its positive signal intensity or signal clustering. The results showed that the adjustment was in line with expectations. The new probe LC-P2 was then used for subsequent testing. Figure 3C Please refer to the optimization results diagram of the LD classification single system provided in this application. Figure 3C For the LD typing single system (LD-P1 mutant signal & wild signal vs LD-P2 mutant signal & wild signal), we tried to adjust the probe to enhance its positive signal intensity or signal clustering. The adjustment results met expectations. The new probe LD-P2 was then used for subsequent testing. Figure 3D Please refer to the optimization results diagram of the LF classification single system provided in this application. Figure 3D For the LF typing single system (LF-P1 mutant signal & wild signal vs LF-P2R mutant signal & wild signal), we tried to adjust the probe to enhance its positive signal intensity or signal clustering. The adjustment results met expectations. The new probe LF-P2R was then used for subsequent testing. Figure 3E Please refer to the MA typing single-system optimization result diagram provided in this application. Figure 3E For the MA typing single system (MA-P1 mutant signal & wild signal vs MA-P2F mutant signal & wild signal), we tried to adjust the probe to enhance its positive signal intensity or signal clustering. The adjustment results met expectations. The new probe MA-P2F was then used for subsequent testing. Figure 3F Please refer to the MD classification single-system optimization result diagram provided in this application. Figure 3F For the MD typing single system (MD-P1 mutant signal & wild signal vs MD-P2C mutant signal & wild signal), we tried to adjust the probe to enhance its positive signal intensity or signal clustering. The adjustment results met expectations. The new probe MD-P2C was then used for testing. Figure 3G Please refer to the ME typing single-system optimization result diagram provided for this application. Figure 3GFigures A and B in the diagram show that the fluorescence channel of the probe was changed while the sequence was optimized. For the ME typing single system (ME-P1 mutant signal & wild signal vs ME-P2H mutant signal & wild signal), we tried to adjust the probe to enhance its positive signal intensity or signal clustering. The adjustment results met expectations. The new probe ME-P2H was then used for subsequent testing. Figure 3H Please refer to the optimization results diagram of the SC classification single system provided in this application. Figure 3H For the SC typing single system (SC-P1 mutant signal & wild signal with or without quenching probe test), we tried to adjust the probe to enhance its positive signal intensity or signal clustering. The adjustment results met expectations. In the future, the SC-P1B quenching probe will be added to the SC system. Figure 3I Please refer to the optimization results diagram of the SF subtyping single system provided in this application. Figure 3I For the SF typing single system (SF-P1 mutant signal & wild signal vs SF-P2 mutant signal & wild signal), we tried to adjust the probe to enhance its positive signal intensity or signal clustering. The adjustment results met expectations, and the new probe SF-P2 was used for subsequent testing.

[0180] The adjusted sequences are shown in Table 15:

[0181] Table 15 Adjusted Sequence

[0182]

[0183] Please refer to Table 15. Figures 3B-3G 3I, by adjusting the probe sequences of LC, LD, LF, MA, MD, ME, and SF, signal clustering and positive signal intensity were significantly improved. Please refer to... Figure 3H It can be seen that the addition of the quenching probe SC-P1B to the SC classification system further reduces background noise and improves signal specificity.

[0184] To increase the signal differentiation between LA mutant and wild-type LA in the L system, a blocking probe for LA was designed. The LA blocking probe is relatively long and overlaps with LA-F1. Therefore, LA-F2 was designed to replace LA-F1. The experimental results showed that LA-F2 has a cleavage effect on LE-P1-1. Therefore, LA-F2 was abandoned and LA-F3 was redesigned. Figure 4A Please refer to the optimization result diagram of the L system provided in this application. Figure 4A ( Figure 4ASpecifically, in the L system, the LA target signal was tested with and without the blocking probe (LA-P1PO4-2) for both mutant and wild-type templates. For the L system (L-A1 vs L-A1-WT test with the blocking probe LA-P1PO4-2 added), the system's ability to distinguish between mutant and wild-type templates was adjusted. It was found that the blocking probe suppressed the wild-type template signal, thus enhancing the system's signal differentiation between mutant and wild-type templates. Subsequent tests added the blocking probe LA-P1PO4-2, while using LA-F3 as the upstream primer. Figure 4B For another L-system optimization result diagram provided in this application, please refer to... Figure 4B ( Figure 4B Specifically, in the L system, the test results of the mutant template signal and wild template signal of the LD target were tested with and without the blocking probe (LD-P2PO4). For the L system (L-D1 vs L-D1-WT test with the blocking probe LD-P2PO4 added), we tried to adjust the system's ability to distinguish between mutant and wild types. It can be seen that the blocking probe can enhance the system's ability to distinguish between mutant and wild signals. The blocking probe LD-P2PO4 was added in subsequent tests.

[0185] Applicability verification for RNA samples

[0186] Based on the univariate tests, the optimal conditions were combined for testing, while further fine-tuning of some variables was carried out. In the variable combination tests, the reverse transcription efficiency and the one-dimensional scatter plot were used for comprehensive judgment. Comparisons between the reverse transcription efficiency of the optimal combination and the test results of the Dabie Banda system on RNA templates are shown in Tables 16, 17, and 18.

[0187] Table 16 Variable Combination Test Results 1

[0188]

[0189] Table 17 Variable Combination Test Results 2

[0190]

[0191] Table 18 Variable Combination Test Results 3

[0192]

[0193] Please refer to Tables 16-18. The results of the optimization of reverse transcription efficiency for RNA templates show that by adjusting the dNTP concentration and the amount of Taq enzyme, the reverse transcription efficiency of each system was significantly improved. Specifically, the reverse transcription efficiency of the LB system increased from 16.77% to 170.40%, and that of the SF system increased from 9.81% to 14.11%.

[0194] Figure 5 Please refer to the optimized results of the three systems on the RNA template provided for this application. Figure 5 By swapping the SF in the S system with the MF in the M system, upstream and downstream interference between target sites on the RNA template is eliminated, ensuring the system's accuracy in detecting real RNA samples.

[0195] Integrated system performance verification

[0196] Figure 6 Please refer to the test result diagram of the multi-coded signal provided in this application. Figure 6 Figure A in the middle is good and Figure 6 Figure B shows that after optimizing reverse transcription efficiency, multiple coding signals were tested. The ME (FAM+HEX) encoded signal was significantly suppressed in the system. The primers for ME were readjusted to ME-F2+ME-R2. After testing, the adjusted ME signal returned to normal. That is, after optimizing the primer combination, the signal intensity of the ME mutant template increased, and the signal clustering was significantly improved.

[0197] In multiple encoding, considering the possibility of multiple genotypes entering the same chamber simultaneously during genotyping detection, especially when multiple genotyping systems are designed close together, there is a small probability of interpretation errors. Therefore, genotyping systems are encoded individually as much as possible to reduce interference. Since most probes in the system have MGB-modified 3' ends, the probes themselves are relatively short, and the steric hindrance of MGB modification is large. The binding efficiency of different fluorescent labels varies greatly. Generally, the longer the emission wavelength, the more complex the molecular structure, and the larger the volume, the more steric repulsion occurs with the MGB group, affecting the binding efficiency of the probe to the target sequence and thus reducing the fluorescence signal output. Based on the test results, it was found that when the SB, SE, and SF systems are on the same template, primer pairing errors between the three systems are likely to occur. Therefore, the SF in the S system and the MF in the M system were swapped. After the swap, the probe concentration in the ROX channel was readjusted. Taking into account the above principles, the system was re-encoded, and the encoding tables are shown in Tables 19, 20, and 21.

[0198] Table 19 Multiple Coding Table 1

[0199]

[0200] Table 20 Multiple Coding Table 2

[0201]

[0202] Table 21 Multiple Coding Table 3

[0203]

[0204] The system configuration is shown in Table 22:

[0205] Table 22 Configuration of Multiple Coding Systems

[0206]

[0207] Figure 7A The image shows the LA (FAM) test results provided in this application. Figure 7B The graph shows the LB(HEX) test results provided in this application. Figure 7C The image shows the LC(ROX) test results provided in this application. Figure 7D The image shows the LD(CY5) test results provided in this application. Figure 7E The image shows the LE(FAM) test results provided in this application. Figure 7F The image shows the LE(HEX) test results provided in this application. Figure 7G The image shows the test results for LF(A425) provided in this application. Figure 7H The image shows the MA (FAM) test results provided in this application. Figure 7I The image shows the MB(HEX) test results provided in this application. Figure 7J The image shows the MC(ROX) test results provided in this application. Figure 7K The image shows the MD(CY5) test results provided in this application. Figure 7L The image shows the ME(A425) test results provided in this application. Figure 7M The image shows the SF(ROX) test results provided in this application. Figure 7N The image shows the SF(CY5) test results provided in this application. Figure 7O The image shows the SA (FAM) test results provided in this application. Figure 7P The image shows the SB(HEX) test results provided in this application. Figure 7Q The image shows the SC(ROX) test results provided in this application. Figure 7R The image shows the SD(CY5) test results provided in this application. Figure 7S The image shows the SE(A425) test results provided in this application. Figure 7T The image shows the MF(ROX) test results provided in this application. Figure 7U The MF(CY5) test results provided for this application are shown in the figure.

[0208] Please refer to Figure 6 , Figures 7A-7U The results of the multiple coding signal test showed that the optimized three-system had clear signals in each fluorescence channel and no obvious mutual interference. Please refer to Tables 19-22. The final determined fluorescence coding rules (Tables 19-21) and system preparation (Table 22) enabled high-throughput simultaneous detection of 18 genotype targets, proving that the integrated system is stable and reliable.

[0209] Example 2

[0210] Corresponding to the aforementioned embodiment of the Dabie Bandar virus recombinant reassortment quantitative detection method based on multiplex digital PCR technology, this application also provides an embodiment of a Dabie Bandar virus recombinant reassortment quantitative detection kit based on multiplex digital PCR technology. The kit includes:

[0211] The specific primer and probe premixes, packaged separately for systems 1, 2 and 3, have core components consisting of nucleotide sequences or their functionally equivalent variants shown in SEQ ID NO:1 to SEQ ID NO:24, SEQ ID NO:25 to SEQ ID NO:43 and SEQ ID NO:44 to SEQ ID NO:63;

[0212] PCR buffer, containing at least MgSO4 solution, dNTP mixture, reverse transcriptase and thermostable DNA polymerase;

[0213] And the instruction manual.

[0214] For details, please refer to the previous introduction; they will not be repeated here.

[0215] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A quantitative detection method for Dabie Bandar virus recombinant reassortment based on multiplex digital PCR technology, characterized in that, The method is for non-diagnostic purposes, and the method includes: A sample to be tested is provided, the sample containing a segmented virus, the genome of the segmented virus comprising at least two segments, and the sample containing the nucleic acid of the segmented virus; the virus is Dabie Bandar virus; The nucleic acid was detected in parallel using three independent multiplex digital PCR reaction systems, namely System 1, System 2, and System 3. System 1 was used to detect the AF genotype on the L fragment of Dabie Banda virus, System 2 was used to detect the AE genotype on the M fragment and the F genotype on the S fragment of Dabie Banda virus, and System 3 was used to detect the AE genotype on the S fragment and the F genotype on the M fragment of Dabie Banda virus. Systems 1, 2, and 3 contained specific primer pairs and probes with nucleotide sequences as shown in SEQ ID NO:1 to SEQ ID NO:24, SEQ ID NO:25 to SEQ ID NO:43, and SEQ ID NO:44 to SEQ ID NO:63, and the probes carried distinguishable fluorescent reporter groups. Based on the pre-established fluorescence coding rules that characterize the correspondence between each genotype and the fluorescent reporter group, digital PCR amplification and detection are performed on each reaction system, multi-channel fluorescence signals are collected, the fluorescence signals are analyzed based on the fluorescence coding rules, positive reaction units of each genotype are identified, and the absolute copy number of each genotype is calculated. Based on the absolute copy number of each genotype, the distribution ratio of different genotypes within the same genomic segment and the genotype combination patterns between different genomic segments are analyzed to assess the characteristics and frequency of viral recombination or reassortment events.

2. The method according to claim 1, characterized in that, Systems 1, 2, and 3 use a uniform amplification procedure, which includes: a reverse transcription reaction at 50°C for 30 minutes; pre-denaturation at 95°C for 5 minutes; and 45 cycles, each cycle including denaturation at 95°C for 10 seconds and annealing extension at 58°C for 40 seconds.

3. The method according to claim 1, characterized in that, The reaction buffer solutions of systems 1, 2, and 3 contain Mg 2+ Unlike the final concentration of dNTPs, in system 1, Mg 2+ The final concentration was 2.0 mM, and the final concentration of dNTPs was 0.2 mM; in system 2, Mg 2+ The final concentration was 2.5 mM, and the final concentration of dNTPs was 0.2 mM; in system 3, Mg 2+ The final concentration was 2.0 mM, and the final concentration of dNTPs was 0.1 mM.

4. The method according to claim 1, characterized in that, For the detection of at least one genotype, blocking probes were used.

5. The method according to claim 1, characterized in that, The fluorescence coding rules include: In system 1, LA corresponds to FAM, LB corresponds to HEX, LC corresponds to ROX, LD corresponds to CY5, LE corresponds to FAM+HEX, LF corresponds to Atto425, and the internal parameter DBV corresponds to Quasar705. In system 2, MA corresponds to FAM, MB corresponds to HEX, MC corresponds to ROX, MD corresponds to CY5, ME corresponds to Atto425, and SF corresponds to ROX+CY5. In system 3, SA corresponds to FAM, SB corresponds to HEX, SC corresponds to ROX, SD corresponds to CY5, SE corresponds to Atto425, and MF corresponds to ROX+CY5.

6. A quantitative detection kit for Dabie Bandar virus recombinant reassortment based on multiplex digital PCR technology, characterized in that, The kit includes: The specific primer and probe premixes are packaged and correspond to systems 1, 2 and 3 respectively, wherein the nucleotide sequences of the specific primer and probe premixes are shown as SEQ ID NO:1 to SEQ ID NO:24, SEQ ID NO:25 to SEQ ID NO:43 and SEQ ID NO:44 to SEQ ID NO:63; PCR buffer, containing at least MgSO4 solution, dNTP mixture, reverse transcriptase and thermostable DNA polymerase; And the instruction manual.

Images