Application of Fe-Cu bimetallic nano-enzyme in detection of beta-lactam antibiotics in food

Abstract

The invention discloses application of Fe-Cu bimetallic nano-enzyme to detection of beta-lactam antibiotics in food, and belongs to the technical field of nanotechnology and colorimetric sensing. The Fe-Cu bimetallic nano material prepared by the invention has three enzyme activities of peroxidase-like, laccase-like and oxidases-like, and a three-enzyme-activity channel colorimetric sensing array is constructed based on the inhibition effect of different beta-lactam antibiotics on the oxidation of a chromogenic substrate; the simple, convenient, rapid and reliable detection on the four beta-lactam antibiotics such as penicillin G, amoxicillin, oxacillin and carbenicillin is realized. The method specifically comprises the following steps: A, preparing Fe-Cu bimetallic nano-enzyme; b, optimizing reaction conditions of the sensing array; c, on the basis of the prepared Fe-Cu bimetallic nano-enzyme, constructing a beta-lactam antibiotic colorimetric sensing detection array; d, carrying out discriminant analysis on the colorimetric fingerprint spectrum obtained by detection by adopting a classical pattern recognition method; and E, detecting an actual sample.

Description

Technical Field

[0001] This invention belongs to the fields of nanotechnology and colorimetric sensing, specifically relating to a method for constructing a colorimetric sensing array using bimetallic nanozymes to detect β-lactams in food. Background Technology

[0002] β-lactam antibiotics, with their targeted antibacterial mechanism, are among the most widely used and valuable antibiotic classes in clinical practice. They work by binding the β-lactam ring to key enzymes synthesized in the bacterial cell wall, blocking cell wall synthesis and leading to bacterial lysis and death. Penicillin G, amoxicillin, carbenicillin, and oxacillin are typical representatives, each with its own advantages: penicillin G is effective against susceptible Gram-positive bacteria and is the cornerstone of infection treatment; amoxicillin has good gastric acid stability and is convenient to take orally, making it suitable for mild to moderate respiratory and urinary tract infections; carbenicillin can cover Pseudomonas aeruginosa and is used for severe cases such as burn infections and sepsis; oxacillin is resistant to β-lactamases and is a key drug for treating infections caused by enzyme-producing, drug-resistant Gram-positive bacteria.

[0003] With its widespread clinical application and industrialization, the abuse of these antibiotics has spread to livestock, aquaculture, and dairy processing, causing far-reaching harm. In animal husbandry, they are illegally used as growth promoters and used in excessive amounts or for extended periods. In dairy processing, they are used to mask excessive bacterial levels, and antibiotic-resistant treatments are used as routine preventative medications. This abuse not only leads to excessive drug residues in food, inducing allergies, intestinal flora imbalance, and affecting immune function in humans, but also accelerates the development and spread of antibiotic resistance. Resistant bacteria spread through the food chain and the environment, expanding the scope of harm. Therefore, there is an urgent need to develop methods for the immediate identification and quantitative detection of these antibiotics in food.

[0004] The performance of enzyme catalysis systems is the core of detection technology development. Natural enzymes, due to their high preparation cost, poor stability, and stringent storage and transportation conditions, are difficult to meet industrial needs. Nanozymes, as novel artificial enzymes, combine the physicochemical properties of nanomaterials with enzyme catalytic activity, providing a new direction for overcoming this bottleneck. To compensate for the performance shortcomings of single-metal nanozymes, bimetallic nanozymes have become a research hotspot and have been widely reported. By constructing bimetallic systems, they achieve performance leaps through intermetallic synergistic effects, demonstrating excellent application value in multiple fields. Reported systems such as iron-cobalt and iron-manganese have all shown advantages over single-metal nanozymes and natural enzymes.

[0005] Accordingly, this study focuses on Fe-Cu bimetallic nanozymes, leveraging the differences in electronic structure and the complementarity of coordination environments between Fe³⁺ and Cu²⁺ to enhance electron transfer efficiency and synergistic catalytic effects between the two metals. Combined with a process design that uses dopamine hydrochloride complexation to regulate bimetallic dispersion and nitrogen atmosphere calcination in a tube furnace to regulate crystal structure, compared to previously reported bimetallic nanozyme systems, the Fe-Cu bimetallic nanozymes prepared in this study further optimize catalytic kinetics (improving the catalytic efficiency and substrate affinity of three enzymes: peroxidase-like, laccase-like, and oxidase-like) and environmental adaptability (enhancing stability in complex food matrices and significantly improving anti-interference capabilities). This effectively solves the problems of insufficient catalytic activity and poor detection reliability in complex scenarios associated with single-metal nanozymes, providing new technical support and practical pathways for the practical application of nanozymes in complex scenarios such as the detection of β-lactam antibiotics in food. Summary of the Invention

[0006] The purpose of this invention is to provide a method for detecting β-lactam antibiotics in food by constructing a colorimetric sensing array using bimetallic nanozymes, which achieves simple, convenient, and reliable visual detection of β-lactam antibiotics in food.

[0007] The objective of this invention is achieved through the following solution:

[0008] An application of a Fe-Cu bimetallic nanozyme for detecting β-lactam antibiotics in food, characterized by comprising the following steps:

[0009] A. Preparation of Fe-Cu bimetallic nanozymes;

[0010] B. Optimize the reaction conditions for peroxidase-like activity;

[0011] C. Optimize the reaction conditions for laccase-like activity;

[0012] D. Optimize the reaction conditions for oxidase-like activity;

[0013] E. Construct a specific colorimetric sensing array by utilizing three different enzyme activities;

[0014] F. Feature signal analysis and accurate discrimination;

[0015] G. Testing of actual samples.

[0016] In step A, the specific preparation process is as follows: Fe-Cu bimetallic nanozymes are prepared by sequentially adding 120 mL of ethanol, 10 mL of distilled water, and 3 mL of 28% ammonia solution to a clean conical flask, and stirring at a constant temperature of 60°C for 10 min. Then, 10 mL of a 50 mg / mL dopamine hydrochloride (DA) aqueous solution is added dropwise to the above system, followed by the injection of 3 mL of a mixed solution containing 27 mg FeCl3·6H2O and 51 mg CuCl2·2H2O, maintaining the reaction at 60°C for 12 h. After the reaction, the product is washed three times each with distilled water and ethanol, and dried in a forced-air drying oven until constant weight. The dried powder is transferred to a ceramic boat and placed in a tube furnace; the temperature is increased to 900°C at a heating rate of 5°C / min, and calcined at a constant temperature for 3 h under flowing nitrogen protection; after natural cooling to room temperature, the material is sealed and stored for later use.

[0017] In step B, the pH, reaction time, and substrate (TMB) concentration were optimized to determine the optimal conditions for peroxidase-like activity. The specific procedure was as follows: buffer solution, Fe-Cu bimetallic nanozyme dispersion, TMB solution, and H2O2 solution were added to the corresponding system. The mixture was incubated at 25°C, and the absorbance at 652 nm was measured using a UV-Vis spectrometer. Only one variable was changed for each test, with the following settings: pH range 3–5.5, reaction time range 1–7 min, and TMB concentration range 0.125–0.25 mM. The detection results were used to determine the optimal reaction conditions.

[0018] In step C, the pH and temperature for laccase activity were optimized to obtain the optimal conditions. The optimized conditions were: pH range 6–7, with intervals of 0.2; reaction temperature range 20–70℃. The absorbance value at 510 nm was recorded using a UV-Vis spectrometer.

[0019] In step D, the pH, material (Fe-Cu bimetallic nanozyme) concentration, and substrate (TMB) concentration were optimized to determine the optimal conditions for oxidase-like activity. The specific procedure was as follows: buffer solution, Fe-Cu bimetallic nanozyme dispersion, and TMB solution were added to the corresponding system. The mixture was incubated at 25°C, and then the absorbance at 652 nm was measured using a UV-Vis spectrometer. Only a single variable was changed for each test, with the following settings: pH range 3–5.5, material concentration range 5–25 μg / mL, and TMB concentration range 0.1–0.7 mM. The detection results were used to determine the optimal reaction conditions.

[0020] In step E, the peroxidase-like activity, laccase-like activity, and oxidase-like activity of the nanozyme material are selected to construct a colorimetric sensing array. The specifications of the colorimetric sensing array are three types of enzyme activity * four analytes * five parallel sets. For each enzyme activity reaction system, the nanozyme, quantitative analytes, and corresponding buffer solutions are first added to centrifuge tubes and incubated for 20 min, and then the corresponding reagents are added for reaction. Specifically: for the peroxidase-like activity system, H2O2 and the chromogenic substrate 3'3'5'5'-tetramethylbenzidine (TMB) are added, and the reaction is carried out for 5 min; for the laccase-like activity system, 4-aminoantipyrine (4-AP) and 2,4-dichlorophenol (2,4-DP) are added, and the reaction is carried out for 15 min; for the oxidase-like activity system, the chromogenic substrate 3'3'5'5'-tetramethylbenzidine (TMB) is added, and the reaction is carried out for 5 min, thus obtaining the colorimetric sensing array of the antibiotic to be tested.

[0021] In step F, the classical linear discriminant analysis (LDA) pattern recognition method is used to identify and analyze the feature signal spectrum obtained in step E, and the accurate identification of different types of β-lactam antibiotics is achieved through data clustering.

[0022] In step G, pure milk and poultry farm wastewater were selected as typical actual samples. Pretreatment steps including homogenization, extraction, centrifugation, filtration, and concentration purification were performed to eliminate matrix interference, obtaining the supernatant of the sample to be tested. The supernatant was then spiked to prepare spiked actual samples containing different types of β-lactam antibiotics. These samples were then substituted into the colorimetric sensor array constructed in step E, and incubated under the optimal reaction conditions optimized in steps B, C, and D. The absorbance changes of each system were recorded, and characteristic signal spectra were generated. High-performance liquid chromatography (HPLC) was used as a control method to verify the accuracy of this detection method, ensuring that it can meet the needs of rapid screening and qualitative analysis of β-lactam antibiotics in actual samples. Attached Figure Description

[0023] Figure 1 TEM image of the Fe-Cu bimetallic nanozyme proposed in Example 2.

[0024] Figure 2 The high-resolution XPS spectrum of the Fe-Cu bimetallic nanozyme proposed in Example 2.

[0025] Figure 3 The X-ray diffraction (XRD) pattern and Raman spectrum of the Fe-Cu bimetallic nanozyme proposed in Example 2 are shown below.

[0026] Figure 4 The peroxidase activity conditions for the Fe-Cu bimetallic nanozyme in Example 3 were optimized.

[0027] Figure 5The laccase activity conditions for Fe-Cu bimetallic nanozymes in Example 4 were optimized.

[0028] Figure 6 The oxidase activity conditions for the Fe-Cu bimetallic nanozyme in Example 5 were optimized.

[0029] Figure 7 This is a linear discriminant analysis diagram of different types of antibiotics based on a colorimetric sensor array, as shown in Example 6.

[0030] Figure 8 This is a linear discriminant analysis diagram of antibiotics of different concentrations based on a colorimetric sensor array, as shown in Example 6.

[0031] Figure 9 This is a linear discriminant analysis diagram of a binary and ternary antibiotic mixture system based on a colorimetric sensor array, as shown in Example 6. Detailed Implementation

[0032] Example 1:

[0033] The preparation of Fe-Cu bimetallic nanozymes specifically includes: adding quantitative amounts of ethanol, deionized water, and 28% (w / w) NH3·H2O sequentially to a clean conical flask, and stirring in a constant temperature environment at a specific temperature. A certain concentration of dopamine hydrochloride aqueous solution is then added dropwise to the above system, followed by the injection of 3 mL of a mixed solution of FeCl3·6H2O and CuCl2·2H2O in a predetermined mass ratio, and the reaction is carried out at a constant temperature. After the reaction is complete, the product is washed several times with deionized water and ethanol, respectively, and dried to constant weight in a forced-air drying oven. The dried powder is transferred to a ceramic boat and placed in a tube furnace; the temperature is raised to 900℃ at a certain heating rate, and calcined at a constant temperature under flowing nitrogen protection. After naturally cooling to room temperature, the material is sealed and stored for later use.

[0034] Example 2:

[0035] To clarify the morphology, size, and chemical composition of bimetallic nanozymes, a variety of characterization methods were used for systematic analysis. The results are as follows: (1) Microscopic morphology characterization: The morphological characteristics of the material were observed by transmission electron microscopy (TEM) and high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM). Figure 1 The results showed that the synthesized bimetallic nanozymes exhibited a particle structure, and their morphology and size could be clearly observed. (2) Chemical composition and valence state analysis: X-ray electron spectroscopy (XPS) was used to record XPS spectra with Al Kα as the excitation source to analyze the chemical composition, elemental valence state and chemical bond state of the material. The results are as follows: Figure 2As shown. XPS full-spectrum results indicate that the bimetallic nanozyme contains five elements: C, N, O, Fe, and Cu; high-resolution Fe 2p spectra show that Fe 2p... 1 / 2 With Fe 2p 3 / 2 The binding energies are concentrated at 724.0 eV and 711.0 eV respectively, confirming that Fe is the element with the highest binding energy. 2+ Valence states exist; the high-resolution N 1s spectrum can be decomposed into three characteristic peaks: pyridine N, graphitic N, and N oxide, indicating that N has been successfully doped into graphene and participates in the structural construction of bimetallic nanozymes. (3) Phase and defect analysis: The results are as follows Figure 3 As shown, the phase composition of the material was characterized by X-ray electron diffraction (XRD). The intensity ratio (ID to GG) of the bimetallic nanozyme is shown. D / I G The value of 1.99 indicates that N atoms introduce a large number of defect sites, providing abundant active centers for catalytic reactions.

[0036] Example 3:

[0037] To obtain the optimal peroxidase-like catalytic activity of Fe-Cu bimetallic nanozymes, the pH, substrate concentration, and reaction time of the reaction system were optimized. The basic experimental system consisted of 850 μL HAc-NaAc buffer to which 50 μL H₂O₂, 50 μL TMB, and 50 μL of a 2.5 μg / mL bimetallic nanozyme were added sequentially. The absorption spectra of the system were measured using a UV spectrophotometer to screen for the optimal levels of each factor. The results are as follows: Figure 4 As shown: (1) pH optimization: The pH gradient of the HAc-NaAc buffer solution was set to 3.0 ~ 5.5. The catalytic activity of the system first increased and then decreased with pH, ​​and reached its peak at pH = 3.5, which was determined to be the optimal pH value. This condition was used in subsequent experiments. (2) TMB concentration optimization: The TMB concentration range was selected as 0.125 - 0.25 mM, and the absorbance at 652 nm was monitored. It increased with increasing TMB concentration, and the absorbance was the highest when the concentration reached 0.25 mM. Considering both substrate amount and reaction rate, 0.25 mM was determined to be the optimal concentration. (3) Reaction time optimization: A time gradient of 1-7 min was set, and the absorbance was measured once every minute. The absorbance increased rapidly in the first 5 min, and the increase slowed down in the 5-7 min. Considering both efficiency and reaction sufficiency, 5 min was selected as the optimal reaction time.

[0038] Example 4:

[0039] To obtain the optimal laccase-like catalytic activity of the bimetallic nanozyme, the pH and reaction temperature of the reaction system were optimized, and the results are as follows: Figure 5As shown. Experimental basic system: 100 μL of 2,4-dichlorophenol (2,4-DP), 100 μL of 4-aminophenol (4-AP) and 50 μL of 10 μg / mL bimetallic nanozyme were added to 850 μL MES buffer in sequence. The absorption spectrum of the system was measured by UV spectrophotometer to screen the optimal level of each factor: (1) pH value optimization: The pH gradient of MES buffer was set to 6.0 ~ 7.0. The catalytic activity of the system reached its peak at pH=6.8, which was determined to be the optimal pH. The buffer was prepared under this condition in subsequent experiments; (2) Reaction temperature optimization: The temperature range of 20 ~ 70℃ was selected, and the absorbance at 510 nm was monitored. It increased rapidly with the increase of temperature and reached the maximum value at 70℃. Considering the convenience of detection operation and the activity stability of nanomaterials, 25℃ (room temperature) was selected as the reaction temperature for subsequent detection.

[0040] Example 5:

[0041] To obtain the optimal oxidase-like catalytic activity of bimetallic nanozymes, the pH value, material concentration, and TMB substrate concentration of the reaction system were optimized. The results are as follows: Figure 6 As shown. Experimental basic system: 100 μL TMB and 50 μL bimetallic nanozyme were added sequentially to 850 μL HAc-NaAc buffer. The absorption spectrum of the system was measured by UV spectrophotometer to screen the optimal level of each factor: (1) pH value optimization: The pH gradient of HAc-NaAc buffer was set to 3.0 ~ 5.5. The catalytic activity of the system reached its peak when pH = 3.5. After pH > 3.5, the activity decreased with increasing pH. This pH was determined to be the optimal condition and was used in subsequent tests; (2) Material concentration optimization: The concentration of bimetallic nanozyme was selected to be 5~25 μg / mL. The absorbance at 625 nm was monitored. It increased with increasing concentration and reached its maximum value at 25 μg / mL. This was determined to be the optimal material concentration; (3) TMB concentration optimization: The concentration gradient was set to 0.1~0.7 mM. The change in absorbance at 625 nm was analyzed. It first increased with increasing concentration and then tended to level off at 0.5 ~ 0.7 mM. Considering both economy and reaction sufficiency, 0.5 was determined to be optimal. mM is the optimal TMB concentration.

[0042] Example 6:

[0043] This paper constructs a three-channel colorimetric sensing array based on the combined peroxidase, laccase, and oxidase-like activities of Fe-Cu bimetallic nanozymes. By utilizing the specific colorimetric response signals generated by different enzyme activity systems after the addition of a target β-lactam antibiotic, efficient differentiation and accurate detection of this antibiotic in food are achieved. The specific steps are as follows:

[0044] (1) Determination of standard curves for four β-lactam antibiotics

[0045] Four standard solutions of β-lactam antibiotics were prepared and reacted in three enzyme activity systems, as follows:

[0046] a. Peroxidase-like activity system: Add 50 μL of 12.5 μg / mL nanozyme solution and 50 μL of antibiotic standard solution to 800 μL HAc-NaAc buffer and incubate for 20 min; then add 50 μL of 5 mM H2O2 and 50 μL of 0.25 mMTMB and react at room temperature for 5 min.

[0047] b. Laccase-like activity system: Add 50 μL of 12.5 μg / mL nanozyme solution and 50 μL of antibiotic standard solution to 700 μL MES buffer and incubate for 20 min; then add 100 μL of 1 mM 2,4-DP and 100 μL of 1 mM 4-AP and react at room temperature for 15 min.

[0048] c. Oxidase-like activity system: Add 50 μL of 25 μg / mL bimetallic nanozyme and 50 μL of antibiotic standard solution to 800 μL HAc-NaAc buffer and incubate for 20 min; then add 100 μL of 0.5 mM TMB and react at room temperature for 5 min.

[0049] The absorbance values ​​at 652 nm for each system were recorded using a UV spectrophotometer. ΔA = A0 - A (where A0 is the initial absorbance and A is the absorbance after the addition of the analyte) was defined. A standard curve was plotted using Origin software with ΔA as the ordinate and the concentration of the analyte as the abscissa.

[0050] (2) Differentiation and detection of four β-lactam antibiotics

[0051] Leveraging the sensitivity and simplicity of a three-channel colorimetric sensor array, this study differentiated and detected four β-lactam antibiotics: penicillin G (PE), amoxicillin (AM), carbenicillin (CA), and oxacillin (OX). Standard solutions for the four antibiotics were prepared, and reactions were performed under the conditions described above for the three enzyme activity systems. The absorbance changes at 652 nm were recorded using a multi-functional microplate reader. Five parallel determinations were performed for each antibiotic in each system, resulting in a 3*4*5 array data matrix. Linear discriminant analysis (LDA) was performed using SPSS software, and a scoring plot was generated. The results showed (…). Figure 7 This visualization detection method can successfully distinguish four β-lactam antibiotics at a concentration of 40 μM; and this sensor array can effectively distinguish four antibiotics at different concentrations. Figure 8 From top to bottom, they are PE, AM, OX, and CA.

[0052] (3) Validation of the detection performance of the sensor array on the mixed system of β-lactam antibiotics

[0053] To verify the performance of the sensor array, binary and ternary mixtures of β-lactam antibiotics were tested: OX-CA binary mixtures with a total concentration of 50 μM and molar ratios of 10:0, 1:9, 2:8, 3:7, 4:6, 5:5, 6:4, 8:2, 9:1, and 0:10, and PE-AM-CA ternary mixtures with a total concentration of 50 μM and molar ratios of 1:2:7, 2:2:6, 3:4:3, 4:5:1, and 5:3:2 were prepared; the reactions were carried out as described above, and the absorbance was measured. The results were obtained by LDA analysis. Figure 9 As shown, the results indicate that the colorimetric sensor array can successfully identify the aforementioned binary and ternary mixed systems.

[0054] Example 7:

[0055] Pure milk and wastewater from poultry farms were selected as actual samples to analyze and verify the performance of the colorimetric sensor in actual application environments. As shown in Table 1, the recovery rate was between 90% and 110%, proving that the method has good accuracy and reliability in the determination of β-lactam antibiotics in actual samples.

[0056] Table 1. Actual sample test results

[0057]

Claims

1. The application of Fe-Cu bimetallic nanozyme in the detection of β-lactam antibiotics in food, characterized by: The prepared Fe-Cu bimetallic nanozyme has three types of enzyme activities: peroxide-like nanozyme, laccase-like nanozyme, and oxide-like nanozyme. Based on these three types of enzyme activities, a three-channel colorimetric sensor array was constructed to realize the detection and differentiation of four β-lactam antibiotics.

2. The application of the Fe-Cu bimetallic nanozyme according to claim 1 in the detection of β-lactam antibiotics in food, characterized in that: Under optimal conditions for the activities of the three enzymes, a colorimetric sensing array with the specifications of "three enzyme activities × four analytes × five sets of parallel experiments" was constructed.

3. The application of the Fe-Cu bimetallic nanozyme according to claim 1 in the detection of β-lactam antibiotics in food, characterized in that: The three-channel reaction systems are: (1) Peroxidase-like activity system: sodium acetate buffer + nanozyme solution + antibiotic standard solution + 3,3',5,5'-tetramethylbenzidine solution + hydrogen peroxide solution; (2) Laccase-like activity system: 2-morpholinoethanesulfonic acid buffer + nanozyme solution + antibiotic standard solution + 2,4-dichlorophenol + 4-aminobitiline; (3) Peroxidase-like activity system: sodium acetate buffer + nanozyme solution + antibiotic standard solution + 3,3',5,5'-tetramethylbenzidine solution.

4. The application of the Fe-Cu bimetallic nanozyme according to claim 1 in the detection of β-lactam antibiotics in food, characterized in that: The system achieves triple precision in differentiating four types of β-lactam antibiotics: gradient differentiation of different concentrations of the same antibiotic, specific differentiation of different types of antibiotics at the same concentration, and differentiation of binary and ternary mixed antibiotic systems.

5. The application of the Fe-Cu bimetallic nanozyme according to claim 1 in the detection of β-lactam antibiotics in food, characterized in that: Pure milk and wastewater from poultry farms were selected as actual test samples for pretreatment. A spiked test method was used, in which a preset concentration of β-lactam antibiotic standard was added to the pretreated actual sample, mixed, and allowed to stand for 5 minutes. The β-lactam antibiotics in the pretreated sample were detected by the three-channel colorimetric sensor array constructed above. At the same time, high performance liquid chromatography was used to verify the detection results to ensure the accuracy and reliability of the detection method.

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