A rapid detection method for rice bacterial blight based on RPA-CRISPR / Cas12b technology

Abstract

The application discloses a rapid detection method for rice bacterial blight based on RPA-CRISPR / Cas12b. The reagent combination comprises a specific RPA primer pair and sgRNA, and the sequences are shown in SEQ ID NO. 1, SEQ ID NO. 2 and SEQ ID NO. 3. The detection method comprises: using the nucleic acid of a sample to be detected as a template, and performing RPA isothermal amplification by using the primer pair; incubating the amplification product with sgRNA, Cas12b protein and a fluorescent reporter molecule, activating the trans cleavage activity of Cas12b; and judging the result by detecting the fluorescence signal. The application integrates the optimized RPA and the CRISPR system in a centrifugal microfluidic chip, realizes the full-process closed tube and automatic detection, can be completed within 30 minutes, has a sensitivity of 0.156 pg / reaction, has no non-specific reaction to five kinds of close relatives such as Xa and Xap, has high sensitivity to XOO3 subtype, is not suitable for XOO2 subtype, has the advantages of rapidness, sensitivity, specificity and low equipment dependence, and is suitable for non-diagnostic detection in field, port and other field environments.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of nucleic acid detection, and particularly relates to a rapid detection method for Xanthomonas oryzae pv. oryzae based on RPA-CRISPR / Cas12b technology. BACKGROUND

[0002] Rice is a major food crop in the world, and its production safety is crucial. Rice bacterial leaf blight caused by Xanthomonas oryzae pv. oryzae (XOO) is a serious bacterial disease that can cause significant yield reduction or even total loss, so developing an efficient and accurate pathogen detection technology for early prevention and control of the disease is of great significance.

[0003] Currently, detection mainly relies on molecular detection techniques such as polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), and recombinase polymerase amplification (RPA). PCR technology has high sensitivity and specificity, but it is severely dependent on a thermal cycler, is complicated to operate, and takes a long time, making it difficult to apply to on-site rapid detection. Isothermal amplification technologies such as LAMP and RPA overcome the dependence on temperature cycling to some extent, significantly shorten the amplification time, and provide the possibility for the development of on-site detection.

[0004] However, these methods still have obvious limitations: first, most of them still need to be opened after detection for electrophoresis or test strip detection, which increases the risk of aerosol contamination and easily leads to false positive results; second, the entire process involves multiple steps of operation, which is difficult to integrate, limiting its application effectiveness in on-site environments such as ports and fields.

[0005] Therefore, there is an urgent need in the art for a new detection method that has high sensitivity and specificity, is easy to operate, is fast, and does not require complex instruments, in order to achieve on-site efficient detection of Xanthomonas oryzae pv. oryzae. SUMMARY

[0006] To achieve the above application purposes, the application adopts the following technical solutions:

[0007] The application provides a reagent combination for detecting Xanthomonas oryzae pv. oryzae (XOO), which comprises a specific RPA primer pair and an sgRNA.

[0008] The RPA primer pair consists of an upstream primer with a nucleotide sequence as shown in SEQ ID NO. 1 and a downstream primer with a nucleotide sequence as shown in SEQ ID NO. 2; and the sgRNA can target a specific sequence in the product amplified by the RPA primer pair.

[0009] Furthermore, the nucleotide sequence of the sgRNA is shown in SEQ ID NO.3.

[0010] This invention also provides a kit for detecting rice bacterial blight pathogen, comprising:

[0011] (1) The reagent combination;

[0012] (2) Cas12b protein;

[0013] (3) ssDNA reporter molecule, wherein one end of the reporter molecule is labeled with a fluorescent reporter group and the other end is labeled with a quencher group.

[0014] This invention also provides a method for detecting rice bacterial blight pathogens for non-diagnostic purposes, comprising the following steps:

[0015] S1. Using the nucleic acid of the sample to be tested as a template, perform RPA reaction using specific primer pairs with nucleotide sequences as shown in SEQ ID NO.1 and SEQ ID NO.2;

[0016] S2, CRISPR detection reaction: The amplification product is mixed with sgRNA, Cas12b protein and single-stranded DNA fluorescent reporter molecule with the sequence shown in SEQ ID NO.3 and incubated at an incubator.

[0017] S3. Detect the fluorescence signal and determine whether the sample to be tested contains rice bacterial blight pathogen based on the fluorescence signal.

[0018] Furthermore, the RPA reaction is carried out at 43°C for 15 minutes; the isothermal incubation is carried out at 43°C for 10 minutes.

[0019] Furthermore, the RPA reaction, CRISPR detection reaction, and fluorescence signal detection are all automatically completed on the centrifugal microfluidic chip; the centrifugal microfluidic chip includes mutually isolated RPA reaction chambers and CRISPR detection chambers, wherein the RPA reaction chamber is pre-loaded with the RPA primer pair, and the CRISPR detection chamber is pre-loaded with the sgRNA. Beneficial effects

[0020] (1) The sgRNA and RPA primer pair designed in the application realizes ultra-high sensitivity detection of XOO pathogenic bacteria (minimum 0.156 pg / reaction, about 2.2 copies / reaction), and the sensitivity is equivalent to that of qPCR. Meanwhile, the system has no cross reaction with five common related pathogenic bacteria Xa, Xap, Xam, Xav and Xcm, has strong specificity, effectively avoids false positive results, and the detection result is accurate and reliable. In addition, the detection system has high sensitivity to XOO3 subtype, but is not suitable for XOO2 subtype, which also proves that the method has good subtype specificity.

[0021] (2) The entire detection process of the application, including RPA constant temperature amplification (43℃, 15min) and CRISPR detection reaction (43℃, 10min), can be completed within 30 minutes, greatly shortening the detection time and meeting the needs of on-site rapid detection (POCT).

[0022] (3) The application integrates RPA amplification and CRISPR detection into a closed centrifugal microfluidic chip, realizes the whole process closed tube operation of "sample in, result out", avoids the aerosol pollution risk caused by opening the cover to detect the product in the conventional method, and significantly improves the reliability and accuracy of the detection result.

[0023] (4) The application simplifies the complex multi-step operation into one-time sampling through reagent pre-freeze drying and chip design. The detection process is automatically completed by a portable device, without the need for complex thermal cycler and professional operators, greatly reducing the use threshold, and being suitable for limited resources such as grassroots units, ports and fields. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 It is the performance screening result graph of three candidate sgRNAs of XOO target in the embodiment of the application; (A) is a fluorescence curve; (B) is a fluorescence change rate.

[0025] Figure 2 It is the performance screening result graph of different RPA primer combinations of XOO target in the embodiment of the application; (A) is a fluorescence curve; (B) is a fluorescence change rate.

[0026] Figure 3 It is the sensitivity verification result graph of the detection method of the application for XOO target; (A) is a fluorescence curve; (B) is a fluorescence change rate.

[0027] Figure 4 It is the specificity verification confirmation result graph of the detection method of the application for XOO target; (A) is a fluorescence curve; (B) is a fluorescence change rate.

[0028] Figure 5Compatibility verification result map of the detection method XOO target described in the application; (A) is the fluorescence curve; (B) is the fluorescence change rate.

[0029] Figure 6 The interference verification result map of the detection method XOO target genome test rapid extraction process system described in the application; (A) is the fluorescence curve; (B) is the fluorescence change rate.

[0030] Figure 7 The detection effect map of the detection method XOO target bacteria liquid different concentration rapid extraction process described in the application; (A) is the fluorescence curve; (B) is the fluorescence change rate.

[0031] Figure 8 The XOO target bacteria liquid lysis test result map of the detection method described in the application is not a rapid extraction system; (A) is the fluorescence curve; (B) is the fluorescence change rate.

[0032] Figure 9 The XOO target bacteria liquid rapid extraction sensitivity verification result map of the detection method described in the application; (A) is the fluorescence curve; (B) is the fluorescence change rate.

[0033] Figure 10 The chip initial detection XOO target nucleic acid effect map of the detection method described in the application.

[0034] Figure 11 The detection effect map of the detection method chip confirming XOO target described in the application.

[0035] Figure 12 The XOO target genome chip sensitivity verification result map of the detection method described in the application. DETAILED DESCRIPTION

[0036] In order to make the person skilled in the art better understand the technical solutions in the application, the following will combine the embodiments to further explain the application.

[0037] The nucleotide sequence involved in the application is as follows:

[0038] SEQ ID NO. 1: The sequence shown is the nucleotide sequence of RPA primer XOO-RPA-F3.

[0039] SEQ ID NO. 2: The sequence shown is the nucleotide sequence of RPA primer XOO-RPA-R1.

[0040] SEQ ID NO. 3: The sequence shown is the nucleotide sequence of sgRNA target XOO-sgRNA.

[0041] SEQ ID NO. 4: The sequence shown is the nucleotide sequence of sgRNA target XOO-tale-2.

[0042] SEQ ID NO. 5: The sequence shown is the nucleotide sequence of sgRNA target XOO-rhs-1.

[0043] SEQ ID NO. 6: The sequence shown is the nucleotide sequence of PCR primer Xoo-F.

[0044] SEQ ID NO. 7: The sequence shown is the nucleotide sequence of PCR primer Xoo-R.

[0045] SEQ ID NO. 8: The sequence shown is the nucleotide sequence of PCR primer Xoo_rhsF1.

[0046] SEQ ID NO. 9: The sequence shown is the nucleotide sequence of PCR primer Xoo_rhsR1.

[0047] SEQ ID NO. 10: The sequence shown is the nucleotide sequence of PCR primer Xoo_avrF1.

[0048] SEQ ID NO. 11: The sequence shown is the nucleotide sequence of PCR primer Xoo_avrR1.

[0049] SEQ ID NO. 12: The sequence shown is the nucleotide sequence of RPA primer XOO-RPA-F1.

[0050] SEQ ID NO. 13: The sequence shown is the nucleotide sequence of RPA primer XOO-RPA-F2.

[0051] SEQ ID NO. 14: The sequence shown is the nucleotide sequence of RPA primer XOO-RPA-R2. Example

[0052] 1. Experimental materials

[0053] 1.1. Instruments and equipment

[0054] SynSor portable multi-target rapid detection equipment, XS-D-001 - Xunxi Biology; QPCR instrument - SLAN-96P - Shanghai Hongshi Medical Technology Co., Ltd.; PCR instrument (TC-S / 96 / G / H(b)BA) - Hangzhou Boyi Technology Co., Ltd.; Qubit 3.0 Fluorescence Meter - Thermo Fisher Scientific; Nanodrop 2000 ultramicro spectrophotometer - Thermo Fisher Scientific; Metal bath (DH100-2) - Hangzhou Ruicheng Instrument Co., Ltd.

[0055] 1.2、Reagents

[0056] SynSor AaCas 12b (C2c1) (XS-R-002) - Synthego; SynSor DNA / RNA Hot Start Master Mix (XS-R-101) - Synthego; SynSor CRISPR ssDNA Reporter (12b-FAM) (XS-R-201) - Synthego; SynSor sgRNA (XS-R-301) - Synthego; Gold MIX (Green) (TSE101) - Beijing Qikang Biotechnology Co., Ltd.; Water used is UltraPure™ Distilled water, Dnase, Rnase, Free (10977-015) - Yingwei Jieji (Shanghai) Trade Co., Ltd.

[0057] 2、Experimental Methods

[0058] 2.1、Detection Target

[0059] Target design and development were carried out for the target regions in Table 1.

[0060]

[0061] Eight nucleic acid samples and one bacterial liquid sample were used for actual sample performance verification, and in addition, the bacterial liquid of each target was tested. The corresponding sample information is shown in Table 2 below.

[0062]

[0063] 2.2、sgRNA Design and Verification

[0064] 2.2.1、sgRNA Design

[0065] According to the selected regions or commonly used target regions in the literature, combined with the host background genome that needs to be avoided, we use bioinformatics algorithms to score sgRNA design according to PAM position, GC%, internal dimer structure, fragment structure openness, base position preference, specificity, etc. The score can be understood as the success probability. Generally, 3 candidate fragments with scores above 40 are retained. If the score is generally lower than 40, the number of candidate fragments needs to be increased to improve the success probability. If the sequence in the spacer has the risk of destroying the backbone secondary structure, it will be directly excluded from the candidate list to avoid the risk of specificity and sensitivity.

[0066] Based on the above design principles, sgRNAs were designed for each selected region for subsequent synthesis and verification. The spacer sequence of the designed sgRNA was analyzed for coverage and specificity using NCBI primer-BLAST. The alignment results showed that the designed sgRNA spacer sequence had 100% coverage within the detected species and good inclusivity; the number of bases matched across species was <15 nt, and the specificity was good. The sgRNAs used are shown in Table 3.

[0067]

[0068] 2.2.2, sgRNA performance verification

[0069] 2.2.2.1, PCR primer design

[0070] According to the position of the designed sgRNA, the region within 100 bp upstream and downstream of the sgRNA was selected to design PCR primers (see Table 4). The primers were designed using commonly used software for primer design, and the primer length was controlled at 20-35 bp. If there are multiple sgRNA design sites within the same target fragment, the PCR amplification product (fragment length controlled within 500 bp) will contain all the sgRNA binding sites, so that all sgRNAs can be verified under the same template.

[0071]

[0072] 2.2.2.2, template amplification verification

[0073] The plasmid / template DNA and the corresponding primers were used for PCR amplification to obtain high-concentration PCR products. The specific amplification system is shown in Table 5, and the corresponding PCR reaction program is shown in Table 6.

[0074]

[0075]

[0076] The amplification products of the target to be tested and the blank control were detected by Qubit double-stranded DNA nucleic acid fluorescent dye concentration. The concentration of the target to be tested should be higher than 2 ng / μL, and there should be a clear distinction from the concentration of the blank control.

[0077] 2.2.2.3, sgRNA verification

[0078] The CRISPR system was prepared according to the system in Table 7.

[0079]

[0080] Take 1 μL of about 10-100 ng of PCR amplification product and mix with the above CRISPR system, set 43℃ reaction for 15 min in qPCR instrument, collect FAM fluorescence signal every minute. According to the curve change of fluorescence signal, the performance or specificity of sgRNA is preliminarily verified. The endpoint of the fluorescence value curve of the target amplification product and the negative control should be significantly different.

[0081] The calculation formula of fluorescence intensity growth rate is as follows: .

[0082] Wherein, Fluorescence Slope represents the fluorescence growth rate, Rn represents the fluorescence signal of the nth minute, R1 represents the fluorescence signal of the first minute. Fluorescence Slope greater than 0.5 is positive, and Fluorescence Slope of negative group should not exceed 0.2.

[0083] 2.3, primer design and verification

[0084] 2.3.1, RPA primer design

[0085] In the detection range of target, select 30-35 base length fragments as RPA primer candidates; in order to ensure stability and specificity, the GC content of RPA primer should be between 40%-60%, and the RPA amplification fragment is usually 100-200 bp. In this project, the upstream and downstream primers are designed according to the primer design principle, and the NCBI primer-BLAST is used to verify the amplification coverage and specificity.

[0086] Based on the above design principles, the RPA primers shown in Table 8 are designed for each plasmid / template for subsequent synthesis and verification experiments.

[0087]

[0088] 2.4, chip verification

[0089] 2.4.1, chip detection process

[0090] Nucleic acids and bacterial liquid are used for verification in this part.

[0091] Using the system determined in 3.2, the target nucleic acid sample is verified. First, the sample is quickly extracted, and then the sample lysate is diluted 8 times to prepare the RPA system. After mixing evenly, the chip is detected, and the fluorescence signal is judged according to the shooting.

[0092] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of the chip is shown in Table 9, and the total detection time is about 28 min.

[0093] The test process of

[0094] 3. Experimental results

[0095] 3.1. Screening results of sgRNA

[0096] The fluorescence intensity of the amplification product of each sgRNA and the corresponding template was determined by CRISPR reaction. The amplification curve and the fluorescence growth rate analysis results are shown in Figure 1 , and the results of the fluorescence value change are shown in Table 10. The analysis results show that the XOO target XOO-sgRNA has good effect.

[0097]

[0098] 3.2. Screening results of RPA primers

[0099] The nucleic acid sample was diluted to 10 ng / μL to screen different combinations of RPA primers, and a two-step CRISPR reverse reaction was performed. The first step was RPA amplification reaction, and then the RPA amplification product was mixed with the CRISPR reaction solution for CRISPR reaction.

[0100] The change of the fluorescence slope of the target amplification product within 15 min should be more than 0.5 to be determined as effective detection; the change of the original fluorescence value of the negative control and the blank control within 15 min should be less than 0.2.

[0101] The effective amplification rate of each primer at each dilution gradient is shown in Table 11.

[0102]

[0103] The analysis results show that:

[0104] Most of the designed primers targeting the XOO target can achieve amplification of the sample. After comparing the performance, the RPA-XOO-F3R1 primer pair with better amplification performance Figure 2 was selected for the next sensitivity verification.

[0105] 3.3. Construction and verification of detection system

[0106] 3.3.1. Sensitivity verification of detection system

[0107] The genomic template is diluted down to gradient dilution, and the genomic addition amount in unit reaction is set to contain 156 pg, 15.6 pg, 7.8 pg, 1.56 pg, 0.78 pg, 0.156 pg, and 0.078 pg, which is appropriately adjusted according to the effect of different targets. The primers and sgRNA combinations determined in 3.2, and the same CRISPR system are used to verify the sensitivity of the target. Each gradient is verified by 3 experimental repeats.

[0108] The amplification curves and fluorescence signal growth rates of the sensitivity verification of each target are shown as follows, XOO Figure 3 ) can detect 0.156 pg of nucleic acid sample at the lowest.

[0109] According to the significance analysis of the sensitivity verification experiment results, it can be preliminarily judged that the detection limit of the primer and the corresponding target is shown in Table 12.

[0110]

[0111] According to the relationship between the genomic copy number and the genomic quality in the previous study, the sensitivity of XOO is about 2.2 copies / T.

[0112] 3.3.2, detection system specificity verification

[0113] 5 cross-species are used for target specificity test, with the target species as the positive control, the cross-species as the specificity verification test group, and water as the negative control template. The primers and sgRNA combinations determined in 3.2, and the same CRISPR system are used to verify the specificity of the target. Each cross-reaction is verified by 2 experimental repeats.

[0114] The results of the specificity verification of XOO target are shown in Figure 4 The verification results show that the XOO target detects XOO sample as positive, and the detection results are negative in Xa, Xap, Xam, Xav, and Xcm, which are 5 cross-species, indicating that the XOO target has good specificity in cross-species.

[0115] 3.3.3, detection system sample compatibility test

[0116] The nucleic acid is diluted to 10 ng / μL for this part of verification.

[0117] The existing detection system is used to verify the actual sample of the target nucleic acid. Each actual sample is verified by 2 experimental repeats.

[0118] The amplification curves and fluorescence signal growth rates of different subtypes of genomic samples are shown as follows: XOO target can be compatible with XOO3, and cannot be compatible with XOO2, as shown in Figure 5 .

[0119] 3.4, Development of rapid extraction process for bacterial liquid sample

[0120] 3.4.1, Evaluation of the interference of rapid extraction process on the system

[0121] The interference of the rapid extraction process of the target genome test on the detection system was evaluated, and the mixed solution obtained from the original sample (hereinafter referred to as the original solution) was used as the positive control. The rapid extraction process was used to prepare the sample as the test group. The primers and sgRNA combination determined in 3.2, as well as the same CRISPR system, were used for verification (). Figure 6 Each cross-reaction was verified twice.

[0122] 3.4.2, Feasibility verification of bacterial liquid rapid extraction system

[0123] The bacterial liquid was diluted 10 times and 100 times, respectively, for this part of the verification.

[0124] The existing detection system was used to verify the target bacterial liquid sample. Each actual sample was verified twice.

[0125] The amplification curves and fluorescence signal growth rates of bacterial liquid samples of different concentrations are shown below. The two concentrations of XOO bacterial liquid could not be detected Figure 7 Overall, the rapid extraction process can be used to lyse the bacterial liquid for detection.

[0126] 3.4.3, Performance verification of non-rapid extraction system bacterial liquid

[0127] The bacterial liquid sample 1E6 CFU / mL was tested. The primers, templates and sgRNA combination determined in 3.2, as well as the same CRISPR system, were used. The rapid extraction system was used as the positive control to test the bacterial lysis effect of the non-rapid extraction process system (normal saline), and each test was verified twice.

[0128] The detection effect of normal saline lysis bacterial liquid is shown below, and the XOO target bacterial liquid rapid extraction and normal saline lysis both did not appear positive signal, which is the same as 3.4.2, and is the embodiment of not containing subtypes, see Figure 8 .

[0129] 3.4.4, Sensitivity verification of bacterial liquid rapid extraction process

[0130] Gradient dilution was performed with the bacterial liquid sample, and the gradient settings included 1E6 CFU / mL, 1E5 CFU / mL, 1E4 CFU / mL, 1E3 CFU / mL, 1E2 CFU / mL, 1E1 CFU / mL, 1 CFU / mL, and the corresponding single reaction bacterial colony numbers were 156 CFU, 15.6 CFU, 1.56 CFU, 0.156 CFU, 0.0156 CFU, 0.00156 CFU, and 0.000156 CFU, respectively. The primers, templates, and sgRNA combinations determined in 3.2, as well as the same CRISPR system, were used to verify the sensitivity of the target bacterial liquid. Each gradient was repeated twice for verification.

[0131] The amplification curve and fluorescence signal growth rate of the sensitivity verification of the bacterial liquid are shown as follows: the XOO target bacterial liquid sample was not detected ( Figure 9 ).

[0132] 3.5, Chip detection results

[0133] 3.5.1, Chip initial detection results

[0134] The nucleic acid sample was diluted to a concentration of 10 ng / μL. First, the rapid extraction process was performed on the chip for preliminary testing, and the verification results of the target are as follows: Figure 10 XOO2 target XOO was not detected, and XOO3 could be detected.

[0135] 3.5.2, Chip confirmation of detection effect of XOO target

[0136] The XOO target nucleic acid sample was diluted to 10 ng / μL, and the target primers and sgRNA screened in 3.2 were used for verification. Two-step CRISPR transreaction was adopted, and the first step was RPA amplification reaction. Then the RPA amplification product was mixed with the CRISPR reaction solution for CRISPR reaction. After completing the chip process, the results were interpreted according to the brightness change of the detection hole. In the chip setting, hole 3 corresponds to the XOO target.

[0137] The target verification results are as follows: Figure 11 The XOO target detection system corresponds to chip hole 3, which is positive when the sample is XOO genome.

[0138] 3.5.3, Sensitivity of three target bacterial liquid rapid extraction under chip process

[0139] Gradient dilution was performed with bacterial liquid or genomic sample, and the target primers screened in 3.2 were verified by sgRNA, and a two-step CRISPR transreaction was adopted, RPA amplification reaction was performed in the first step, and then the RPA amplification product was mixed with the CRISPR reaction solution for CRISPR reaction, and the algorithm program of the instrument was used to distinguish the positive and negative (the holes with boxes outside are positive holes).

[0140] The XOO target genome chip detection result is as shown in the following table: Figure 12 The XOO target chip can be detected, and under the chip process, the minimum genome sample of 1 pg / T can be detected per hole, which is equivalent to about 22 copies per reaction.

[0141] In summary, the present application develops an isothermal amplification detection method based on RPA and CRISPR for XOO targets, which breaks away from the dependence on complex instrument equipment platform of traditional molecular biology methods, greatly simplifies the detection platform; through system establishment and verification, the overall detection time of the target is shortened to within half an hour, and there is still room for further reduction in the future; at the same time, the sensitivity, specificity and POCT platform of the target detection technology are verified, and the results show that the developed detection method has good sensitivity and specificity, and the actual sample verification results are consistent with the results of the gold standard detection method. The target detection limit and verification data are as follows:

[0142] XOO target sgRNA is determined by XOO-sgRNA, and RPA-XOO-F3 / R1 is used for detection effect, the minimum is 0.156 pg per reaction, which is equivalent to about 2.2 copies per reaction, which is specific in Xa, Xap, Xam, Xav and Xcm, cannot contain XOO2 subtype, and can contain XOO3 subtype. The minimum genomic sample of 1 pg / T can be detected on the chip with the rapid extraction process, which is equivalent to about 14.1 copies per reaction.

Claims

1. A reagent combination for detecting Xanthomonas oryzae pv. oryzae (XOO), the pathogen of rice bacterial blight, characterized in that, Including specific RPA primer pairs and sgRNA; The RPA primer pair consists of an upstream primer with a nucleotide sequence as shown in SEQ ID NO.1 and a downstream primer with a nucleotide sequence as shown in SEQ ID NO.2; the sgRNA is capable of targeting a specific sequence in the product amplified by the RPA primer pair; the nucleotide sequence of the sgRNA is shown in SEQ ID NO.

3.

2. A kit for detecting rice bacterial blight pathogen, characterized in that, Include: (1) The reagent combination according to claim 1; (2) Cas12b protein; (3) ssDNA reporter molecule, wherein one end of the reporter molecule is labeled with a fluorescent reporter group and the other end is labeled with a quencher group.

3. A method for detecting rice bacterial blight pathogens (not for diagnostic purposes), characterized in that, Includes the following steps: S1. Using the nucleic acid of the sample to be tested as a template, perform RPA reaction using specific primer pairs with nucleotide sequences as shown in SEQ ID NO.1 and SEQ ID NO.2; S2, CRISPR detection reaction: The amplification product is mixed with sgRNA, Cas12b protein and single-stranded DNA fluorescent reporter molecule with the sequence shown in SEQ ID NO.3 and incubated at an incubator. S3. Detect the fluorescence signal and determine whether the sample to be tested contains rice bacterial blight pathogen based on the fluorescence signal.

4. The detection method according to claim 3, characterized in that, The RPA reaction was carried out at 43°C for 15 minutes; the isothermal incubation was carried out at 43°C for 10 minutes.

5. The detection method according to claim 3, characterized in that, The RPA reaction, CRISPR detection reaction, and fluorescence signal detection are all automatically completed on a centrifugal microfluidic chip; the centrifugal microfluidic chip includes an RPA reaction chamber and a CRISPR detection chamber that are isolated from each other, wherein the RPA reaction chamber is pre-loaded with the RPA primer pair of claim 1, and the CRISPR detection chamber is pre-loaded with the sgRNA of claim 1.

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