Beta-mno2-ssdna bridging array and method for detecting organophosphorus pesticides by using the same

Abstract

The application discloses a kind of β-MnO2-ssDNA bridging array, it includes β-MnO2-ssDNA composite material and the detection channel formed by 9 groups of hydrolase and nuclease bridged using it, wherein, ssDNA is selected according to nuclease type;Nuclease is selected from LbCas12a, TtAgo, DNase I;Hydrolase is selected from AChE, BChE, ALP.The β-MnO2-ssDNA bridging array is applied to organic pesticide detection, and the protein competition effect of organic phosphorus pesticide and hydrolase, nuclease in detection channel can effectively amplify the subtle differences between structure similar organic phosphorus pesticides, significantly improve the qualitative classification accuracy of structure similar organic phosphorus pesticides (up to 100%), realize the rapid qualitative identification of organic phosphorus pesticide, and the limit of quantification involved is low, linear range is wide, meet the trace organic phosphorus pesticide residue detection demand in food matrix.

Description

Technical Field

[0001] This invention belongs to the field of chemical analysis and detection technology, specifically relating to a β-MnO2-ssDNA composite material bridging hydrolase / nuclease array and its high-resolution detection method for organophosphorus pesticides. Background Technology

[0002] Organophosphorus pesticides (OPs) are a class of insecticides widely used in agricultural production. They are characterized by high insecticidal efficiency and low cost. However, most OOPs are highly toxic, and even structurally similar OOPs (such as chlorpyrifos and methyl parathion, malathion and dimethoate) can exhibit significant differences in toxicity, environmental stability, and residue risks, even with only minor structural differences. Excessive residues of OOPs in food can lead to varying degrees of harm. Therefore, accurate differentiation and quantitative detection of multiple OOPs in food are of great significance.

[0003] Currently, common methods for detecting organophosphorus pesticides include high-performance liquid chromatography (HPLC), gas chromatography-mass spectrometry (GC-MS), enzyme inhibition assays, and immunoassays. However, these methods have significant limitations: large-scale instrumental analysis methods rely on expensive equipment and specialized operators, involve complex sample pretreatment, and are time-consuming, making rapid on-site detection difficult; traditional enzyme inhibition and immunoassay methods, while simple to operate, lack specificity and cannot effectively distinguish structurally similar organophosphorus pesticides, easily leading to cross-reactions and misdiagnosis; existing array sensing technologies are mostly based on single enzyme-catalyzed reaction mechanisms, resulting in low resolution and failing to meet the need for accurate differentiation of multiple components (especially for similar organophosphorus pesticides).

[0004] Xue et al. (Machine-Learning-Assisted CRISPR / Cas12a Biosensors for Monitoring Organophosphorus Pesticide Degradation) provided a CRISPR / Cas12a dual-enzyme cascade detection scheme mediated by MnO2 nanosheets. Using sheet-like MnO2 as a carrier, and AChE and CRISPR / Cas12a as the detection system, the MnO2 is reduced by TCh catalyzed by AChE to release ssDNA and activate the fluorescence signal. This is combined with a smartphone and SEL model to achieve OPs detection. However, this scheme cannot effectively distinguish structurally similar homologues, has a detection limit of 4.62 pg / mL (approximately 15.4 nM), and a narrow linear range (0.01–10 ng / mL), making it difficult to meet the needs of trace residue detection.

[0005] The development of methods that are easy to operate, highly sensitive, and have strong resolution, enabling rapid differentiation and detection of multiple structurally similar organophosphorus pesticides in complex matrices, has become an urgent need in the field of safety testing. Summary of the Invention

[0006] The main objective of this invention is to address the problems and shortcomings of existing organophosphorus pesticide detection technologies by providing a β-MnO2-ssDNA-bridged hydrolase / nuclease array and a method for high-resolution detection of organophosphorus pesticides using it. The method is simple to operate, highly sensitive, and has strong resolution, enabling rapid differentiation and detection of multiple structurally similar organophosphorus pesticides in complex matrices, and has wide applicability.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A β-MnO2-ssDNA bridging array comprises a β-MnO2-ssDNA composite material and detection channels formed by nine groups of hydrolases and nucleases connected by the composite material. The ssDNA is selected according to the nuclease type, and the β-MnO2-ssDNA composite materials for different detection channels are constructed according to the nuclease type. The nuclease in each detection channel is one of LbCas12a, TtAgo, or DNase I; the hydrolases in each detection channel are one of AChE, BChE, or ALP.

[0008] In the above scheme, the selection requirements for ssDNA based on the nuclease type are as follows: for LbCas12a, select 5-10nt FQ-DNA; for TtAgo, the required FQ-DNA should be complementary to the gDNA in the TtAgo system, and the optimal length is 12-15nt; for DNase I, select 15-25nt FQ-DNA.

[0009] Furthermore, for the TtAgo system, a base complementary pairing design is performed on the 3' end of the gDNA (different from the traditional 5' end design), which has higher fluorescence response intensity and improves the signal-to-noise ratio.

[0010] In the above scheme, the β-MnO2-ssDNA composite material has a nanorod structure with abundant oxygen vacancies and special positive charge, and its length is 800-1500nm and its diameter is 2-5nm.

[0011] In the above scheme, the β-MnO2-ssDNA composite material is obtained by mixing β-MnO2 with ssDNA determined according to the nuclease type in water and then biologically incubating it.

[0012] In the above scheme, the molar ratio of β-MnO2 to ssDNA is 10~12:1. In the above schemes, biological incubation is carried out using the CRISPR / Cas12a system, the Argonaute system, or the DNase system.

[0013] Furthermore, in the CRISPR / Cas12a system, the β-MnO2 concentration is 0.2-0.5 mg / mL, the activator concentration is 10-20 nM, and 5-10 nt FQ-ssDNA is selected with a concentration of 0.1-0.2 μM; in the Argonaute system, the β-MnO2 concentration is 0.2-0.5 mg / mL, and 12-15 nt FQ-ssDNA is selected with a concentration of 0.04-0.06 μM; in the DNase system, the β-MnO2 concentration is 0.2-0.5 mg / mL, and 15-25 nt FQ-ssDNA is selected with a concentration of 0.025-0.04 μM.

[0014] Furthermore, the activator introduced into the CRISPR / Cas12a system is a 22nt ssDNA, which must match the crRNA sequence.

[0015] In the above method, β-MnO2 is obtained by dissolving MnSO4 and (NH4)2S2O8 in water, stirring until homogeneous, and then carrying out a hydrothermal reaction (140~160℃, 12~16h). This invention employs a completely inorganic reaction system to synthesize ligand-free manganese dioxide, which can effectively promote convenient and efficient centrifugal separation of nucleic acids.

[0016] Furthermore, the molar ratio of MnSO4 to (NH4)2S2O8 is 1:1-1.5.

[0017] Preferably, during the preparation of β-MnO2, the concentration of MnSO4 is 0.2-0.25 mol / L.

[0018] The β-MnO2 obtained in this invention exhibits excellent adsorption capacity for ssDNA, and when ascorbic acid (AA) is used as an etchant to trigger a self-sacrificial reaction, it can efficiently release the adsorbed ssDNA, with a desorption efficiency significantly better than other crystal phases (α-MnO2, β-MnO2, γ-MnO2, δ-MnO2, ε-MnO2, λ-MnO2). In addition, the β-MnO2 crystal surface has the most abundant oxygen vacancies, which promotes the formation of a stable β-MnO2-ssDNA composite material.

[0019] This invention also provides a method for detecting multiple organophosphorus pesticides in food based on the above-mentioned β-MnO2-ssDNA bridging array. Using a β-MnO2-ssDNA composite material as a self-sacrificing bridging agent, a multi-channel (9-channel) array of hydrolases / nucleases is constructed. Through the cumulative differentiation effect induced by protein competition within the channels, combined with digital coding or machine learning algorithms, the method achieves the distinguishable detection of multiple organophosphorus pesticides. The specific steps include: 1) Preparation of DNA-Ag NPs: Dissolve hairpin DNA in nuclease-free water to prepare hairpin DNA solution (concentration 500-800 μM), heat (80-95℃, 5-8 min), and then cool to room temperature; mix the hairpin DNA solution with buffer (concentration 0.2-0.25 M, pH 7.0-8.0), add silver salt solution (AgNO3, etc.; concentration 10-12 mM), vortex to mix, centrifuge, and equilibrate (18-22 min to promote complete reaction). Add reducing agent solution (NaBH4, etc.) for reduction, vortex and centrifuge again to obtain DNA-Ag NPs solution. Store at 4℃ for more than 3 days before use. The preparation process does not require complicated equipment. 2) Construction of hydrolase / nuclease array Three hydrolases were selected: AChE, BChE, and ALP; three nucleases were selected: LbCas12a, TtAgo, and DNase I; the hydrolases and nucleases were bridged by the β-MnO2-ssDNA complex to construct a 3×3 multichannel array, including nine different combinations of detection channels: AChE / LbCas12a, AChE / TtAgo, AChE / DNase I, BChE / LbCas12a, BChE / TtAgo, BChE / DNase I, ALP / LbCas12a, ALP / TtAgo, and ALP / DNase I.

[0020] For different hydrolases, the organophosphorus pesticide solution (50-100 U / mL), hydrolase (50-100 U / mL), and buffer solution (concentration 1-10 mM) were mixed and incubated (35-40°C, 400-600 rpm, 10-30 min), followed by the addition of substrates (1-5 mM for all; where AChE corresponds to substrate ATCh, BChE corresponds to substrate BTCh, and ALP corresponds to substrate AAP) and incubation continued (10-20 min). Incubate β-MnO2-ssDNA with the above solution (5-10 min; room temperature), and collect the supernatant by centrifugation (5000-8000 rpm, 2-5 min). Then, add the obtained supernatant to different nuclease systems. The specific processing steps are as follows: For the LbCas12a system (three groups), the supernatant was incubated with LbCas12a, crRNA, reaction buffer I (NEBuffer 2.1, NEBuffer 4, etc. can be used; pH value is 6.5-8.0), RNase inhibitor and water at 35-40°C for 30-45 minutes. For the TtAgo system (three groups), the supernatant was incubated with TtAgo, gDNA, reaction buffer II (ThermoPol Reaction Buffer, etc.; pH 8-9) and water at 75-85°C for 30-45 minutes. For the DNase I system (three groups): Add DNA-Ag NPs solution, reaction buffer III (DNase I Reaction Buffer, etc. can be used; pH value is 7-8), DNase I and water (DEPC) to the supernatant, and incubate at 35-40℃ for 10-15 minutes; After the reaction, the fluorescence intensity of the solution was recorded using an automated microplate reader; the fluorescence signal of each channel was detected. Specifically, the LbCas12a system and TtAgo system recorded the fluorescence spectrum and fluorescence peak intensity (at 525 nm) in the wavelength range of 500-600 nm under 460 nm excitation light; the DNase system recorded the fluorescence spectrum and fluorescence peak intensity (at 535 nm and 630 nm, respectively) in the wavelength range of 500-600 nm under 460 nm excitation light and 600-700 nm under 565 nm excitation light.

[0021] 3) Qualitative and quantitative analysis of various organophosphorus pesticides Based on the fluorescence response efficiency of each channel, a characteristic fingerprint spectrum is constructed, and a digital coding method is used to distinguish different organophosphorus pesticides: using the same nuclease as a fixed unit, the channels corresponding to the three hydrolases are assigned codes (such as "1", "2", "3", etc.) in descending order of fluorescence response efficiency, forming a unique digital code for each organophosphorus pesticide, thereby realizing the detection of organophosphorus pesticide types; And / or, a classification model is established using the Random Forest (RF) machine learning algorithm, with fluorescence characteristic parameters (500-600 nm fluorescence spectral data for LbCas and TtAgo systems, and 500-600 and 600-700 nm fluorescence spectral data for Dnase I system) as input variables and organophosphorus pesticide types as output variables, to achieve accurate classification of 19 structurally similar organophosphorus pesticides.

[0022] Furthermore, based on the fluorescence signal changes of the target organophosphorus pesticide in the optimal channel, a linear regression equation was established between the fluorescence intensity difference (the difference before and after the addition of organophosphorus pesticide) and the pesticide concentration. Then, the pesticide residue was quantitatively detected based on the measured sample fluorescence signal values.

[0023] Furthermore, the optimal channel is the one with the largest difference in fluorescence intensity before and after the addition of organophosphorus pesticides, and the highest detection signal-to-noise ratio of the system.

[0024] Preferably, the concentrations of OPs, hydrolase, substrate, and β-MnO2-ssDNA introduced in step 2) are 285 nM, 50 U / mL, 1 mM, and 0.5 mg / mL, respectively.

[0025] Preferably, for the LbCas12a system, the concentrations of each component are LbCas12a (1 µM) and crRNA (2 µM); for the Argonaute system, the concentrations of each component are TtAgo (10 nM) and gDNA (100 nM); and for the DNase system, the concentrations of each component are DNA-Ag NPs (0.5 µM) and DNase I (100 U / mL).

[0026] In the above scheme, the organophosphorus pesticides include 19 structurally similar organophosphorus compounds such as chlorpyrifos, malathion, dimethoate, fenitrothion, profenofos, dichlorvos, triazophos, trichlorfon, dithion, methyl parathion, fenthion, methamidophos, methyl pyrimidine, isopropylthion, imidacloprid, ethyl glutathione, quinalphos, acephate, and phorate. The test samples cover environmental water samples such as river water, tomatoes, and artemisia, as well as food and traditional Chinese medicine samples, without the need for complicated pretreatment.

[0027] In the above scheme, chlorpyrifos is used as a typical target for quantitative detection, with a linear range of 285 fM to 285 nM and a detection limit (LOD) as low as 31 fM (3σ / k), which meets the requirements for trace residue detection.

[0028] In the above scheme, the competitive reaction between the nuclease and the hydrolase can achieve a cascaded regulation that kills two birds with one stone, without the need to add additional regulatory reagents, thus simplifying the detection process.

[0029] In the above scheme, signal reading adopts fluorescence detection mode, including fluorescence intensity changes of fluorescence resonance energy transfer probe (FQ-ssDNA) and ratio fluorescence (F535 / F630) changes of quantum size effect probe (DNA-Ag NPs), etc., and the detection instruments are conventional and readily available.

[0030] In the above scheme, the fluorescence response efficiency is: the change in fluorescence intensity (the difference in fluorescence intensity relative to the control group without organophosphorus compounds ΔF) or the change in ratio fluorescence intensity (the difference in ratio fluorescence intensity relative to the control group without organophosphorus compounds ΔF) in the presence of organophosphorus compounds (OPs). 535 / F 630 The ratio of fluorescence signal to that of the control group (without OPs).

[0031] The present invention also provides a dynamic degradation monitoring method for organophosphorus pesticides, which can be achieved through three convenient methods: ultraviolet irradiation (such as 254 nm or 365 nm), heating (60-70℃), or ultrasound (1200-1500 W), to reflect the pesticide degradation efficiency in real time.

[0032] In the above scheme, the machine learning algorithm is the Random Forest (RF) algorithm, which has a classification accuracy of 100%; the digital encoding strategy generates unique identifiers by assigning values ​​based on fluorescence response efficiency, which can quickly identify individuals without the need for professional data analysis skills.

[0033] Compared with the prior art, the beneficial effects of the present invention include: 1. This invention prepares nanorod-shaped β-MnO2 with excellent binding and response mechanisms through crystal phase regulation. For different nuclease systems, corresponding β-MnO2-ssDNA composite materials are constructed, which have efficient ssDNA adsorption-desorption properties. As a self-sacrificing bridging agent, it can realize the efficient cascade reaction of hydrolases and nucleases, effectively solving the technical bottleneck of no direct substrate-product association in the enzyme-catalyzed reaction in traditional enzyme arrays.

[0034] 2. The constructed 3×3 hydrolase / nuclease array utilizes the protein competition effect between organophosphorus pesticides and hydrolases / nucleases within the channels to effectively amplify subtle differences between structurally similar organophosphorus pesticides. Through the cumulative differentiation effect, high-resolution differentiation is achieved, and the qualitative classification accuracy of 19 structurally similar organophosphorus pesticides reaches 100%.

[0035] 3. Combining digital coding and random forest algorithms, this method achieves rapid qualitative identification of organophosphorus pesticides while ensuring the accuracy of classification results. It is easy to operate without complex data analysis, and has a low quantitative detection limit and a wide linear range, meeting the needs for detecting trace organophosphorus pesticide residues in food.

[0036] 4. The detection process does not require large instruments and is suitable for rapid on-site detection and batch sample screening, enabling the degradation monitoring of organophosphorus pesticide residues in real samples, and has broad application prospects. Attached Figure Description

[0037] Figure 1 These are transmission electron microscope (TEM) images and selected area electron diffraction (SAED) images of β-MnO2 used in this invention.

[0038] Figure 2 The chemical structures of the 19 organophosphorus pesticides detected in this invention are shown.

[0039] Figure 3 This is a schematic diagram illustrating the construction and detection principle of the 3×3 array as described in Embodiment 1 of the present invention.

[0040] Figure 4 These are simplified numerical codes corresponding to the 19 pesticides involved in this invention.

[0041] Figure 5 This is a schematic diagram of the high-resolution biosensor scheme for detecting organophosphorus pesticides in samples according to the present invention.

[0042] Figure 6 This is a linear range graph of gradient concentrations of chlorpyrifos in the sample described in Example 2 of the present invention, where a is the fluorescence spectrum used for the detection of chlorpyrifos in the sample; b is a partial calibration curve of the difference between the concentration of chlorpyrifos spiked in the sample (285fM to 285nM) and the fluorescence intensity.

[0043] Figure 7 This is the result of dynamic degradation monitoring of chlorpyrifos in Example 3.

[0044] Figure 8 The confusion matrix is ​​for the training set (blue) and prediction set (red) using the 1×3 array described in Comparative Example 2.

[0045] Figure 9 The confusion matrix is ​​for the training set (blue) and prediction set (red) using the 3×1 array described in Comparative Example 2.

[0046] Figure 10 The confusion matrix is ​​for the training set (blue) and prediction set (red) using the 3×3 array described in Example 1. Detailed Implementation

[0047] The applicant will now provide a more detailed description of the present invention with reference to specific embodiments, so that those skilled in the art can more clearly understand the present invention. However, the following content should not be construed as limiting the scope of protection claimed in the claims of the present invention.

[0048] The fluorescence spectroscopy measurement conditions are as follows: emission wavelength 500-600 nm and excitation wavelength 460 nm in LbCas12a and TtAgo systems, and emission wavelength 500-600 nm and excitation wavelength 460 nm and emission wavelength 600-700 nm and excitation wavelength 565 nm in DNase system.

[0049] In the following examples, the preparation method of β-MnO2 includes the following steps: 1.352 g of MnSO4·H2O and 1.826 g of (NH4)2S2O8 were weighed and dissolved together in 40 mL of deionized water, and the mixture was magnetically stirred for 30 min until the solution was homogeneous; the resulting mixture was transferred to a 50 mL polytetrafluoroethylene-lined stainless steel autoclave and reacted at 140 °C for 12 h; after the reaction, the product was centrifuged at 5000 rpm for 2 min, washed three times alternately with deionized water and ethanol until the pH of the supernatant was consistent with that of deionized water, vacuum dried overnight, and the β-MnO2 powder was collected for later use. This powder can be stored in a dry environment for more than 6 months without special storage conditions; the TEM and SAED images of the obtained β-MnO2 powder are shown in [reference needed]. Figure 1 As can be seen from the figure, β-MnO2 has a rod-like structure and is well-crystallized. Further tests show that the obtained β-MnO2 has an oxygen vacancy rate as high as 32.8%, is positively charged, and has a potential of 8.8 mV.

[0050] In the following embodiments, the preparation method of the β-MnO2-ssDNA composite material includes the following steps: Select the corresponding ssDNA based on the nuclease type: For the LbCas12a system, 8 μL of 0.1 mg / mL β-MnO2 dispersion was mixed with 3 μL of 10 nM activator solution and 5 μL of 0.1 μM 5 nt FQ-ssDNA solution, incubated at 37 °C for 60 min, centrifuged at 5000 rpm for 2 min, and the precipitate was collected to obtain the MnO2-ssDNA composite material for LbCas12a. For the TtAgo system, 8 μL of 0.1 mg / mL β-MnO2 and 4 μL of 0.04 μM 14nt FQ-ssDNA were mixed and incubated. After centrifugation, the precipitate was collected to obtain the MnO2-ssDNA composite material for the TtAgo system. For the DNase I system, 8 μL of 0.1 mg / mL β-MnO2 and 4 μL of 0.025 μM 20nt FQ-ssDNA were mixed and incubated. After centrifugation, the precipitate was collected to obtain the MnO2-ssDNA composite material for the TtAgo system. The resulting composite materials were stored in a refrigerator at 4°C.

[0051] In the following examples, the preparation method of DNA-Ag NPs includes the following steps: hairpin DNA is dissolved in nuclease-free water to prepare a 500 μM solution, heated at 95°C for 5 min and then cooled to 25°C. 40 μL of the hairpin DNA solution is mixed with 50 μL of 200 mM PBS buffer (pH 7.4), and the volume is brought up to 374 μL with nuclease-free water. 24 μL of 10 mM AgNO3 solution is added, the mixture is vortexed and centrifuged at 14000 rpm for 1 min, equilibrated for 20 min, and then 12 μL of freshly prepared 10 mM NaBH4 solution is added for reduction. After vortexing and centrifugation again, the solution is stored at 4°C for more than 3 days before use.

[0052] The nucleic acid sequences used in the following examples are shown in Table 1.

[0053] Table 1. Oligonucleotide sequences used in this invention

[0054] Example 1 A β-MnO2-ssDNA bridging array and its high-resolution detection method for organophosphorus pesticides are disclosed. A 3×3 array is constructed and applied for the qualitative detection of organophosphorus pesticides. The specific steps include: During array construction, three hydrolases—AChE, BChE, and ALP—were bridged with three nucleases—LbCas12a, TtAgo, and DNase I—using corresponding MnO2-ssDNA composite materials to form nine detection channels. Specifically, these were nine detection channels with combinations of AChE / LbCas12a, AChE / TtAgo, AChE / DNase I, BChE / LbCas12a, BChE / TtAgo, BChE / DNase I, ALP / LbCas12a, ALP / TtAgo, and ALP / DNase I. Each channel contained 5 U / mL of hydrolases and 33.3 nM (LbCas12a), 0.67 nM (TtAgo), and 10 U / mL (DNase I), respectively. The specific procedures are as follows: 1) Preparation of β-MnO2-ssDNA for different nuclease systems: For the LbCas12 system, 8 μL of β-MnO2 dispersion (0.5 mg / mL), 3 μL of activator (see Table 1) solution (10 nM), and 5 μL of FQ-ssDNA (5 nt; see Table 1) solution (0.1 μM) were co-incubated for 60 min (CRISPR / Cas12a system). For the TtAgo system, 8 μL of β-MnO2 dispersion (0.5 mg / mL) and 4 μL of FQ-ssDNA (14 nt; see Table 1) solution (0.5 μM) were co-incubated (Argonaute system) at 37 °C for 60 min. For the DNase I system, 8 μL of βMnO2 dispersion (0.5 mg / mL) and 4 μL of FQ-ssDNA (20 nt; see Table 1) solution (0.1 μM) were co-incubated at 37 °C for 60 min (DNase system).

[0055] 2) For different hydrolases, a mixture of 4 µL OPs (285 nM), 4 µL hydrolases (all 50 U / mL), and 4 µL Tris-HCl (pH 7.5 for AChE and BChE, pH 8.5 for ALP) was incubated at 37°C and 500 rpm for 45 minutes. Then, 4 µL of substrate (ATCh for AChE, BTCh for BChE, and AAP for ALP; all at 1 mM) was added and incubated for another 10 minutes to obtain dispersions of different hydrolases. 3) Incubate 8 µL of the β-MnO2-ssDNA dispersion (0.5 mg / mL) for different nucleases obtained in step 1) with the hydrolytic enzyme dispersion obtained in step 2) for 10 minutes (37℃), and collect the supernatant by centrifugation (5000 rpm, 2 minutes); then, add the obtained supernatant to different nuclease systems, as follows: For the LbCas12a system, the supernatant was incubated with 1 µL LbCas12a (1 µM), 1 µL crRNA (2.5 µM), 0.5 µL 10×NEBuffer 2.1 buffer, 0.2 µL RNase inhibitor (2000 U / mL) and 13.3 µL DEPC water at 37°C for 45 minutes. For the TtAgo system, the supernatant was incubated with 2 µL TtAgo (10 nM), 4 µL gDNA (100 nM), 3 µL 10×ThermoPol reaction buffer and 7 µL DEPC at 80°C for 30 minutes. For the DNase system, the supernatant was incubated with 4 µL DNA-Ag NPs (0.5 µM), 4 µL 1×DNase I reaction buffer, 4 µL DNase I (100 U / mL) and 4 µL DEPC water at 37°C for 10 minutes. 4) After the reaction is completed, the fluorescence intensity of the solution is recorded using an ELISA reader. The fluorescence response efficiency (defined as the ratio of the change in fluorescence intensity (ΔF) or ratio fluorescence (ΔF535 / F630) in the presence of OPs to the fluorescence signal of the control group (OPs)) is assigned three levels, "1", "2" and "3", in descending order of value, thus forming a unique digital coding system for identifying organophosphorus compounds with similar structures.

[0056] In addition, machine learning can be used for qualitative analysis of organophosphorus pesticides. A fully automated ELISA reader can be used to collect the fluorescence spectra of solutions in each channel. Each sample is tested 20 times to obtain batch spectral data. The obtained fluorescence signals are then input into a random forest algorithm model, which can identify 19 types (e.g., ...). Figure 2 Qualitative identification of organophosphorus pesticides (named OP-1 to OP-19 in sequence).

[0057] The classification accuracy using the above method of the present invention reaches 100%; alternatively, unique numerical codes can be generated by assigning values ​​of 1, 2, and 3 in descending order of fluorescence response efficiency (e.g., chlorpyrifos is coded as 312), which can quickly distinguish them without the need for professional software.

[0058] Figure 3 The diagram shows the construction and detection principle of the 3×3 array. Due to the inherent differences in the binding affinity and competition priority between organophosphorus compounds with different structures and the nine enzyme combinations, a unique fluorescent response fingerprint will be formed in the nine channels of the array. By collecting the fingerprint signal and classifying it using a random forest machine learning algorithm or parsing it with digital encoding, the accurate qualitative differentiation of 19 structurally similar organophosphorus compounds can be achieved.

[0059] Figure 4 The numerical codes corresponding to 19 organophosphorus pesticides are displayed.

[0060] Example 2 A quantitative detection method for chlorpyrifos in actual samples, using the AChE / LbCas12a detection pathway as described in Example 1 and chlorpyrifos as the detection target, specifically includes the following steps: 1) Artemisia argyi samples were extracted using the QuEChERS kit and then diluted 20 times (to be tested), without the need for additional purification steps; Mix 0.1 mg / mL β-MnO2 solution with 0.1 μM 5nt ssDNA (compatible with LbCas12a), incubate at 37℃ for 60 min, centrifuge at 5000 rpm for 2 min, and collect the precipitate to obtain the β-MnO2-ssDNA composite material, and store at 4℃ for later use.

[0061] 2) First, mix 4µL of the test solution with 4µL of hydrolase (50U / mL) and 4µL of Tris-HCl (pH 7.5) and incubate for 30 minutes (37°C, 500rpm). Then add 4µL of the corresponding substrate of the hydrolase (1mM) and continue incubation for 10 minutes.

[0062] Take 8 µL of β-MnO2-ssDNA (0.5 mg / mL) dispersion and incubate with the above solution for 10 minutes. Centrifuge to collect the supernatant (5000 rpm, 2 minutes). Then, incubate the obtained supernatant with 1 µL LbCas12a, 1 µL crRNA, 0.5 µL 10×NEBuffer 2.1, 0.2 µL RNase inhibitor and 13.3 µL DEPC water at 37°C for 45 minutes. Subsequently, under 460 nm excitation light, the fluorescence spectrum in the 500-600 nm range was used for quantitative detection. The results showed that the quantitative detection of chlorpyrifos in the sample was achieved by the linear change of fluorescence intensity of the AChE channel (AChE / LbCas12a).

[0063] Based on the linear relationship between fluorescence intensity change and chlorpyrifos concentration ( Figure 6 The content of chlorpyrifos in the sample was calculated. The detection limit of chlorpyrifos in Artemisia argyi was 51 fM, and the recovery rate was 88.9%~112.0%. The detection results were consistent with those of the HPLC method and met the accuracy requirements of actual detection (Table 2). Figure 5 A schematic diagram of quantitative detection of organophosphorus pesticides is shown.

[0064] Table 2. Determination of spiked recovery rate of chlorpyrifos in Artemisia argyi poisoning.

[0065] In the table, "NF" indicates not detected.

[0066] The results showed that the recovery rates of chlorpyrifos at three different concentrations in Artemisia argyi matrix remained between 88.9% and 112%, enabling the quantification of chlorpyrifos in Artemisia argyi matrix.

[0067] Example 3 A method for monitoring the dynamic degradation of chlorpyrifos includes the following steps: Samples of river water, tomatoes, and mugwort containing 285 nM chlorpyrifos were treated with ultraviolet irradiation (254 nm / 365 nm), heating (60 °C), or ultrasound (1500 W) for 0–120 min, respectively. Samples were taken at different time points, and fluorescence intensity was detected according to the method described in Example 2. The degradation efficiency was evaluated by the degree of fluorescence recovery.

[0068] The results showed that ultrasonic treatment had the highest degradation efficiency, achieving efficient degradation of chlorpyrifos within 120 minutes. This monitoring process requires no complex instruments and can provide real-time feedback on the degradation effect, providing technical support for pesticide residue control. Figure 7 ).

[0069] Comparative Example 1 A β-MnO2-ssDNA bridging array is prepared in a manner largely similar to that of Example 1, except that conventional ligand-modified (tetramethylammonium hydroxide) manganese dioxide is used instead of the β-MnO2 described in this invention. The preparation method of the ligand-modified manganese dioxide includes the following steps: In a conical flask equipped with a magnetic stirrer, 20 mL of a mixed solution containing 3 wt% hydrogen peroxide and 0.6 mol / L tetramethylammonium hydroxide is rapidly added to 10 mL of a 0.3 mol / L manganese chloride solution. After reacting overnight, the solution is centrifuged and washed three times with water and methanol, respectively. The resulting solid is dried in a vacuum oven at 60°C for 6 hours and ground into powder. The powder is then dispersed in an ultrasonic cleaner for 10 hours, and the supernatant is collected by centrifugation to obtain the desired MnO2 nanosheet solution, which is stored at 4°C for later use.

[0070] The test results showed that the enhanced water dispersibility introduced by the modified ligands hindered the centrifugation and extraction of ssDNA. Simultaneously, the adsorbed ssDNA retained its ability to perform base pairing, resulting in high background fluorescence. Furthermore, the adsorption of ssDNA on manganese dioxide was affected by steric hindrance, electrostatic interactions, and other factors caused by the surface-modified ligands, leading to a decrease in nucleic acid adsorption rate and a reduction in the fluorescence efficiency of DNA digestion by nucleases, thus preventing the accurate identification of organophosphorus pesticides.

[0071] The ligand-free β-MnO2 used in this invention enables convenient centrifugation separation of nucleic acids (5000 rpm, 2 min), which can promote the efficient detection of organophosphorus pesticides.

[0072] Comparative Example 2 A β-MnO2-ssDNA bridging array and its detection method for organophosphorus pesticides are largely the same as the preparation and detection methods in Example 1, with the only difference being: 1) Use a "1×3" array (select only one type of hydrolytic enzyme array); 2) Use a “3×1” array (select only one type of endonuclease array).

[0073] The results show that for the "1×3" array system, although the accuracy of all training sets (blue, n=14) can reach 100%, the accuracy of the 1400 prediction sets (red, n=6) is 79.8%, 74.6%, and 91.2%, respectively. For the “3×1” array system, although the accuracy of all training sets can reach 100%, the accuracy of the prediction set (red, n=6) is 88.6%, 75.6% and 83.3% respectively.

[0074] Both of the above detection systems fall far short of the 100% prediction accuracy of the "3×3" array described in this invention (see details). Figure 8-10 ).

[0075] The above embodiments are merely illustrative examples and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations; therefore, any obvious variations or modifications derived therefrom remain within the scope of protection of this invention.

Claims

1. A β-MnO2-ssDNA bridging array, characterized in that, It includes a β-MnO2-ssDNA composite material and detection channels formed by nine groups of hydrolases and nucleases connected by it. The ssDNA is selected according to the nuclease type, and β-MnO2-ssDNA composite materials are constructed for different detection channels. The nucleases are one of LbCas12a, TtAgo, and DNase I. The hydrolases are one of AChE, BChE, and ALP.

2. The β-MnO2-ssDNA bridging array according to claim 1, characterized in that, The selection requirements for ssDNA based on the nuclease type are as follows: for LbCas12a, select 5-10nt FQ-DNA; for TtAgo, use FQ-DNA with a length of 12-15nt that is complementary to the gDNA in the TtAgo system; for DNase I, select 15-25nt FQ-DNA.

3. The β-MnO2-ssDNA bridging array according to claim 1, characterized in that, In the β-MnO2-ssDNA composite material, β-MnO2 has a nanorod structure with a length of 800-1500 nm and a diameter of 2-5 nm.

4. The β-MnO2-ssDNA bridging array according to claim 1, characterized in that, The β-MnO2-ssDNA composite material was obtained by mixing β-MnO2 with ssDNA determined according to the nuclease type in water and then incubating them biologically.

5. The β-MnO2-ssDNA bridging array according to claim 1, characterized in that, The β-MnO2 is obtained by dissolving MnSO4 and (NH4)2S2O8 in water, stirring until homogeneous, and then carrying out a hydrothermal reaction.

6. The β-MnO2-ssDNA bridging array according to claim 1, characterized in that, It includes detection channels formed by nine combinations of AChE and LbCas12a, AChE and TtAgo, AChE and DNase I, BChE and LbCas12a, BChE and TtAgo, BChE and DNase I, ALP and LbCas12a, ALP and TtAgo, and ALP and DNase I.

7. A method for detecting organophosphorus pesticides using the β-MnO2-ssDNA bridging array according to any one of claims 1 to 6, characterized in that, Specifically, the following steps are included: 1) Preparation of DNA-Ag NPs: Mix hairpin DNA solution with buffer, add silver salt solution, mix well and centrifuge, equilibrate, add reducing agent for reduction, centrifuge to obtain DNA-Ag NPs dispersion; 2) Construction of hydrolase / nuclease array Three hydrolases were selected: AChE, BChE, and ALP; three nucleases were selected: LbCas12a, TtAgo, and DNase I; different combinations of hydrolases and nucleases were bridged with β-MnO2-ssDNA composite material to construct a 3×3 multichannel array. The specific steps are as follows: 2-1) For different hydrolases, the organophosphorus pesticide solution, hydrolase and buffer solution were mixed and incubated, and then the corresponding substrate was added and incubated for a longer period of time. 2-2) Incubate the β-MnO2-ssDNA composite material with the solution obtained in 2-1), and collect the supernatant by centrifugation; then add the obtained supernatant to different nuclease systems for incubation treatment, and the specific treatment steps are as follows: For the LbCas12a system, the supernatant was mixed with LbCas12a, crRNA, reaction buffer I, RNase inhibitor and water, and incubated at room temperature. For the TtAgo system, the supernatant was mixed with TtAgo, gDNA, reaction buffer II and water, and then heated and incubated. For the DNase I system, the supernatant was added to DNA-Ag NPs solution, reaction buffer III, DNase I and water and mixed, and then incubated at room temperature. After the reaction is complete, the fluorescence signal of each detection channel is detected; 3) Qualitative and quantitative analysis of various organophosphorus pesticides Based on the fluorescence response efficiency of each detection channel, a characteristic fingerprint spectrum is constructed, and a digital coding method is used to distinguish different organophosphorus pesticides, thereby achieving qualitative detection of organophosphorus pesticide types. And / or, a classification model is established using the random forest machine learning algorithm, with fluorescence feature parameters as input variables and organophosphorus pesticide types as output variables, to achieve accurate classification of organophosphorus pesticides with similar structures.

8. The method according to claim 7, characterized in that, The fluorescence signals include: for the LbCas12a and TtAgo systems, the fluorescence spectra and peak fluorescence intensities in the 500-600 nm wavelength range under 460 nm excitation light were recorded; for the DNase system, the fluorescence spectra and corresponding peak fluorescence intensities in the 500-600 nm range under 460 nm excitation light and the 600-700 nm range under 565 nm excitation light were recorded.

9. The method according to claim 7, characterized in that, The specific steps of the digital coding method include: using the same nuclease as a fixed unit, assigning values ​​to the detection channels corresponding to the three hydrolases according to the descending order of fluorescence response efficiency, thus forming a digital code corresponding to each organophosphorus pesticide.

10. The method according to claim 7, characterized in that, By utilizing the fluorescence signal changes of the target organophosphorus pesticide in the optimal channel, a linear regression equation was established between the fluorescence intensity difference before and after the addition of the organophosphorus pesticide and the pesticide concentration. Then, the pesticide residue was quantitatively detected based on the measured sample fluorescence signal values. The optimal channel is the one that exhibits the greatest difference in fluorescence intensity before and after the addition of organophosphorus pesticides.

Images