Rapid detection of nitrite and Listeria monocytogenes in food based on multiple simulated enzyme activities of Fe₃O₄-ZnO-MnO₂ nanocomposites

Abstract

Food safety has emerged as a paramount concern in global health, prompting innovative approaches to ensure the safety of people's sustenance. In this study, a novel strategy was devised to fabricate Fe₃O₄-ZnO-MnO₂ hybrid nanobiocatalysts, which exhibited remarkable enzymatic activity surpassing that of Horseradish peroxidase (HRP) catalysis. It demonstrated exceptional proficiency in decomposing 3,3′,5,5′-tetramethylbenzidine (TMB) without the need for harsh reaction conditions or the aid of H₂O₂. We established colorimetric detection systems based on Fe₃O₄-ZnO-MnO₂-TMB both for nitrite (NO₂⁻) and Listeria monocytogenes (LM) in food. Impressively, the detection limit of nitrite reached an astonishingly low level of 0.022 mg L⁻¹, and the detection limit for LM was determined to be 3.5 cfu mL⁻¹. These compelling results unequivocally validate the potential of these hybrid nanobiocatalysts to fortify food safety measures. Moreover, they serve as a valuable reference for the colorimetric detection of diverse analytes and the simultaneous detection of multiple targets.

Graphical abstract

Preparation procedure and enzymatic application of hybrid Fe₃O₄-ZnO-MnO₂ nanocatalysts.

Highlights

• •Fe₃O₄-ZnO-MnO₂ magnetic nanocomposites with various enzyme activities were successfully prepared.
• •Rapid and sensitive monitoring of nitrite and Listeria monocytogenes in food was realized based on TMB colorimetric system.
• •Nanomaterial-based solution for robust, rapid, and reliable food safety analysis.

1. Introduction

With the growing concern over food safety worldwide, it has become a major focus of global attention (Jiang et al., 2021). People are increasingly worried about the uncertainty surrounding food safety, leading to a sense of panic (He, Han, & Liu, 2019). Therefore, rapid identification of potential hazards in food is crucial to reassuring the public. As scientific advancements continue, food additives are not only used to enhance flavor but can also have adverse effects on consumers. Besides, research has shown that the contamination of food by pathogenic microorganisms can lead to foodborne illnesses, posing a serious threat to both physical and mental health (Kwon et al., 2021; Lefebvre et al., 2021; Y. Zhang et al., 2022). Therefore, accurately determining the presence of microorganisms and other additives in food is of utmost importance in ensuring dietary safety and reducing public anxiety.

To achieve rapid detection of food safety, two key factors must be considered: one is how to achieve signal amplification, and the other is how to quickly separate the target. In terms of realising signal amplification, natural enzymes, as a representative of fast catalysts, are widely used in various industrial and pharmaceutical fields (DiCosimo, McAuliffe, Poulose, & Bohlmann, 2013; Schmid et al., 2001). However, many factors, such as its high cost, cumbersome preparation procedure, harsh storage environment, and strict usage conditions, have limited its widespread application (Senko, Gladchenko, Maslova, & Efremenko, 2019; R. Zhang, Yan, & Fan, 2021). To address these issues, researchers explored functional nanocatalysts, which have been shown to have great potential to improve the catalytic function, efficiency, kinetic properties, and susceptibility to the diffusion of enzymes (Bilal et al., 2023; Kong et al., 2023; Liang, Fu, Yao, Li, & Li, 2022).

Currently, many research efforts have developed various nanobiocatalysts, including precious metals (Xu et al., 2019), metal oxides (Y. Li, Zhang, Qian, & Huang, 2022), metal sulphones (F. Li et al., 2023), carbon-based nanomaterials (Xia et al., 2022), metal-organic frameworks (MOFs) (Guo, Bao, Guo, Chen, & Wen, 2022), etc. Although the nanobiocatalysts disclosed above have been proven to have high catalytic efficiency and strong stability, most of the nanobiocatalysts are composed of expensive precious metals, which may make it difficult to control the cost of these nanobiocatalysts in applications. Therefore, further research on nanobiocatalysts with low prices and excellent performance is expected to achieve broad application prospects. Zinc‑manganese (ZnO-MnO₂) dioxide aqueous batteries have the advantages of low cost, abundant resources, low toxicity, and high working potential (Sambandam et al., 2022; N. Zhang et al., 2023). Inspired by zinc‑manganese batteries, we aim to develop nanobiocatellites with high catalytic efficiency, low cost, and strong stability using zinc‑manganese as a raw material.

Magnetic metal oxides have exceptional superparamagnetic properties, making them ideal for rapid separation and purification of target substances in detection systems (H. Liu et al., 2020; Manigandan et al., 2019; Wang et al., 2019). The hybridization of magnetic metal oxides (such as Fe₃O₄) and nanobiocatalysts (such as ZnO-MnO₂) will show strong advantages in analysis and detection through integrating separation and purification with signal amplification within the detection matrix. This innovative approach not only enhances the accuracy and sensitivity of food safety detection but also provides a reliable means to isolate and amplify signals, ensuring the reliable identification of hazardous substances, which holds immense potential for the rapid detection of food safety hazards.

Based on the activities of Fe₃O₄-ZnO-MnO₂ hybrid nanobiocatalysts against various substrates, this study proposed an all-around improvement plan for food safety using NO₂⁻ and LM as examples. By utilizing the Fe₃O₄-ZnO-MnO₂-TMB system, a rapid colorimetric detection system was developed. This research is of great significance for future studies on Fe₃O₄-ZnO-MnO₂ hybrid nanocomplexes in the fields of food safety and analytical chemistry, as it establishes a standard and provides guidance for future research endeavors. Furthermore, the establishment of a reliable detection system for NO₂⁻ and LM holds promising prospects for the detection of food additives and foodborne pathogens. This advancement addresses the urgent need for accurate and efficient detection methods in the food industry. By utilizing the unique properties of Fe₃O₄-ZnO-MnO₂ hybrid nano biocatalysts, this research opens up new avenues for enhancing food safety and ensuring the well-being of consumers. Continued research in this area will undoubtedly contribute to the development of innovative solutions for food safety monitoring and analysis.

2. Materials and methods

2.1. Reagents and apparatus

Ferric chloride hexahydrate (FeCl₃.6H₂O), trisodium citrate dihydrate (Na₃Cit.2H₂O), manganese chloride tetrahydrate (MnCl₂. 4H₂O), ethylene glycol (EG) was purchased from Aladdin reagents Co., Ltd. (Shanghai, China). Sodium hydroxide (NaOH), Zinc acetate (ZnAc) and sodium acetate (NaAc) were acquired from the National Pharmaceutical Group Chemical Reagents Co., Ltd. (Shanghai, China). Bovine serum albumin (BSA), TMB and HRP were received from Shanghai Macklin Biochemical Co., Ltd. (Shanghai, China). N-(3-(dimethylamino)-propyl)-N′-ethylcarbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS) were purchased from Sigma-Aldrich. (USA). As previously reported (L. Zhang et al., 2016), the 5′-amine-modified DNA aptamer (5’NH₂-TTT TTT TTT TAT CCATGG GGC GGA GAT GAG GGG GAG GAG GGC GGG TAC CCG GTT GAT-3′) was selected for recognition of LM, which was provided by Sangon Biotech Co., Ltd. (Shanghai, China). All other chemicals and reagents used were of analytical grade and were used without further purification.

All the UV–Vis absorption spectra were acquired using Agilent Cary 60 UV–Vis (Agilent, USA). All fluorescence spectra were obtained using the Edinburgh spectrofluorometer-FS5 (Edinburgh, UK). Transmission electron microscopy (TEM) of nanoparticles was measured on a JEOL JEM-2100 F transmission electron microscope at an accelerating voltage of 200 kV (JEOL, Japan). Fourier Transform Infrared spectra (FTIR) from 500 to 4000 cm⁻¹ were recorded using a Nicolet 6700 FTIR spectrometer (Thermo Inc., USA). Zetasizer Pro (Malvern Instruments, UK) performed the zeta potential measurements.

2.2. Synthesis of the Fe₃O₄-ZnO-MnO₂ hybrid nanocomposites

The core magnetic nanospheres (Fe₃O₄) were prepared by solvothermal method described in the literature (N. Zhang et al., 2022). Simply put, 4.0 g FeCl₃.6H₂O and 1.0 g Na₃Cit.2H₂O were dissolved in 100.0 mL EG and stirred vigorously with magnetic force to form a homogeneous yellow solution. Then added 6.0 g of NaAc and stirred at room temperature for another 0.5 h. The mixture was transferred to a 100.0 mL stainless steel autoclave lined with polytetrafluoroethylene and then heated to 200 °C for 10 h. After cooling to room temperature, the sediment was washed with deionized water and ethanol to clear and dried overnight in a vacuum oven at 60 °C.

Inspired by previous research work, Zn-MnO₂ was synthesized in a similar way (Y. Liu et al., 2023). Specifically, 0.2 mM MnCl₂.4H₂O and 50.0 mg BSA were dissolved in 10.0 mL of pure water and reacted with intense stirring in a beaker for 30 min. Added 3.0 g NaOH, 5 min later, then dropped 0.2 mM ZnAc solution, reaction for 12 h. The precipitation was collected by centrifugation at 12000 rpm for 15 min. The resulting sediment was dried overnight at 50 °C.

The Fe₃O₄-ZnO-MnO₂ hybrid nanocomposites were prepared by electrostatic attraction reactions. 50.0 mg Fe₃O₄ nanoparticles and dissolved in 50.0 mL of ultrapure water, ultrasonic to a homogeneous state. Added 100.0 mg of ZnO-MnO₂ nanocomposite powder and stirred vigorously at 50 °C for 3 h. The final product was magnetically separated, and dried at 50 °C, and finally stored at 4 °C for future use.

2.3. Various catalytic activity tests of Fe₃O₄-ZnO-MnO₂ hybrid nanocomposites

Several enzyme reaction experiments were used to study the nano-simulated enzyme activity of Fe₃O₄-ZnO-MnO₂ hybrid nanocomposites. Firstly, the peroxidase activity was tested, and the catalytic activities of HRP, Fe₃O₄-Ag-MnO_2, and Fe₃O₄-ZnO-MnO₂ hybrid nanocomposites were compared in the presence of H₂O₂ with TMB as the chromogenic substrate. Secondly, in the absence of H₂O₂, the oxidase-like activities of HRP, Fe₃O₄-Ag-MnO₂, Zn-MnO₂ and Fe₃O₄-ZnO-MnO₂ hybrid nanocomposites were evaluated by TMB. Finally, the catalase-like activities of HRP, Fe₃O₄-Ag-MnO₂ and Fe₃O₄-ZnO-MnO₂ hybrid nanocomposites were studied for their ability to decompose oxygen generated by H₂O₂.

As a widely applicable commercial enzyme, HRP was used as a positive control in the enzyme activity assay below. The peroxidase activity was studied as below: 0.9 mL of Fe₃O₄-ZnO-MnO₂/Fe₃O₄-Ag-MnO₂ suspension (0.5 mg mL⁻¹), 0.1 mL of TMB solution (0.1 g mL⁻¹), and 1.0 μL of H₂O₂ (30 %) in sequence. The mixed liquor was incubated for 10 min at room temperature. The supernatant was sucked, and 0.1 mL of HCl (1.0 M) solution was added to terminate the reaction. The color and UV–Vis spectra ranging from 400 nm to 800 nm of the mixed solution were recorded.

The oxidase-like activity of various nanomaterials was evaluated by catalytic oxidation of TMB in the absence of H₂O₂. Simply put, 0.9 mL of nanomaterials water suspension (0.5 mg mL⁻¹) and 0.1 mL of TMB water solution (0.1 g mL⁻¹) were mixed well for 10 min at room temperature. The supernatant fluid was then measured by phone and UV–Vis's spectra.

The catalase-like activity of the nanocomplex was simply assessed by decomposing H₂O₂ to generate oxygen. In short, 1 mL Fe₃O₄-ZnO-MnO₂/Fe₃O₄-Ag-MnO₂ aqueous solution (0.5 mg mL⁻¹) was mixed with 10.0 μL H₂O₂ (30 %), respectively. The number of bubbles produced by each experimental tube was observed after 5.0 min.

2.4. Rapid detection of NO₂⁻ in food by visual quantitative method

Based on the oxidation effect of TMB⁺ on NO₂⁻, a rapid detection of NO₂⁻ in food was designed using the oxidase activity of Fe₃O₄-Ag-MnO₂ hybrid nanocomposites to catalyze the generation of TMB⁺ from TMB. Under suitable conditions, the oxidation product of 0.2 mL TMB was color-reacted with NO₂⁻ at different concentrations of 0.5 mL. After 20 min, the solution of each experimental tube was recorded by camera and UV–Vis spectra.

2.5. Rapid detection of LM in food by colorimetric fluorescence dual-mode

Before the establishment of the detection system, the various bacteria required for the experiment were first cultured. All strains listed in Supporting Information Table S1 were preserved in liquid nitrogen and 15.0 % glycerol and revived by streaking on Luria-Bertani (LB) agar plates. Only Vibrio parahaemolyticus was cultured in tryptone soybean broth supplemented with 3.0 % NaCl. Other strains were routinely cultured in the LB common medium. The bacterial concentration was determined by the conventional plate counting method.

Capturing all the target bacteria as much as possible can effectively avoid false negative, so the capture efficiency of IMB nanoprobe was explored. Fe₃O₄-ZnO-MnO₂ suspension 5.0 mg mL⁻¹ was obtained, homogenized by ultrasonic dispersion, washed with PBS 3 times by magnetic adsorption, and then resuspended in 0.8 mL. 10 mg of EDC and NHS were added to activate surface carboxyl groups. 0.5 h later, washed with PBS by magnetic adsorption was performed again. The quantitative volume was 0.9 mL in PBS solution, and 0.1 mL of LM-specific aptamer (0.1 mM) was injected for an overnight reaction. Magnetic separation removes the unbound aptamers. The prepared Fe₃O₄-ZnO-MnO₂-Apt nanoprobes were stored at 4 °C for later use. Different amounts of Fe₃O₄-ZnO-MnO₂-Apt probes were co-incubated with 10⁶cfu mL⁻¹ concentrations of LM. The supernatant was taken after 0.5 h, diluted to a certain number, and coated for culture counting (Y. Liu et al., 2022).

In addition, a nanocomposite of Fe₃O₄-ZnO-MnO₂ was created to find LM in food based on its oxidase and occupying effects. Under optimized experimental conditions, 0.1 mL Apt-Fe₃O₄-ZnO-MnO₂ nanoprobe and 20.0 μL IgY-CV-CDs nanoprobe solutions were mixed with different concentrations of LM bacterial solution and incubated for 0.5 h. Magnetic separation was performed to remove the supernatant, and 1.0 mL of 80.0 μg mL⁻¹ TMB was added for color development for 5 min. Magnetic separation was used to record the color of the supernatant in the test tube under sunlight and ultraviolet light, respectively.

3. Results and discussion

3.1. Characteristics of Fe₃O₄-ZnO-MnO₂ hybrid nanocomposites

Graphic summary reveals the synthesis route of the Fe₃O₄-ZnO-MnO₂ hybrid nanocomplex. In order to the separation efficiency, superparamagnetic Fe₃O₄ nanospheres were used as the magnetic core. The surface was then coated with ZnO-MnO₂ nanocomposites to improve the catalytic efficiency. Through Zeta potential testing, the surface charge of Fe₃O₄ with a carboxyl group was −24.97 mV, and the surface charge of ZnO-MnO₂ nanocomplex was 28.23 mV. It can be combined by electrostatic adsorption.

The morphology and microstructure of the as-prepared materials were investigated by TEM. As displayed in Fig. 1a, the spherical Fe₃O₄ nanoparticles composed of many smaller magnetite nanospheres exhibit good monodisperses, with an average diameter of 123.54 nm. Based on the experience of successfully preparing hybrid nanocomposites in the past (Y. Liu et al., 2023), the performance of the prepared Fe₃O₄-ZnO-MnO₂ will be measured. The size of the hybrid composites increased by 164.41 nm due to the adhesion state of the Zn-MnO₂ composites (Fig. 1b). TEM characterization was also performed on ZnO-MnO₂ together, and the results showed a flaky morphology, which is due to the use of BSA as the template (Fig. S1a). The results of elemental analysis show that Zn and Mn elements exist in the ZnO-MnO₂ structure (Fig. S1b). TEM-energy dispersive X-ray spectroscopy (EDS) elemental mapping also shows strong elemental signals for Zn and Mn (Fig. S1c).

Fig. 1.

A series of characterization of Fe₃O₄-ZnO-MnO₂. a: TEM images of Fe₃O₄; b: TEM images of Fe₃O₄-ZnO-MnO₂; c: HRTEM image of Fe₃O₄-ZnO-MnO₂; d: TEM–EDS elemental mapping showing of Fe, Zn, Mn; e: Elemental analysis of Fe₃O₄-ZnO-MnO₂.

Next, HRTEM results showed that the lattice distance within the (301) plane of MnO₂ appearing on the surface of Fe₃O₄-ZnO-MnO₂ composites was 0.213 nm (X. Liu et al., 2012). At the same time, a lattice distance of 0.260 nm that matched the (002) plane of ZnO was found (Fig. 1c) (Prasad et al., 2020). It was easy to see in Fig. 1d that the Fe elements were mostly in the middle of the nanosphere and the Zn and Mn elements were mostly on the outside and top of the sphere. This shows that the ZnO-MnO₂ coating was successfully applied to the Fe₃O₄ nanosphere's surface. Moreover, the results of elemental analysis (Fig. 1d) showed that the peaks of elements Fe, Zn, and Mn were all present. The mass percentages of these elements were 92.18 % (Fe), 3.27 % (Zn), and 4.55 % (Mn), respectively.

The FTIR spectra of Fe₃O₄, Zn-MnO₂, and Fe₃O₄-ZnO-MnO₂ were demonstrated in Fig.S2a. Comparing the spectra results of Fe₃O₄ and Fe₃O₄-ZnO-MnO₂, both showed a wide absorption band near 580 cm⁻¹, which was caused by the vibration of the Fe − O bond, and a C O stretching vibration peak appeared at 1726 cm⁻¹ (Y. Liu et al., 2019). Combined with the spectra curves of Zn-MnO₂ and Fe₃O₄-ZnO-MnO₂, the peaks observed in the region 475 cm⁻¹ were a result of the Zn—O vibrations (Munir et al., 2023). The peaks at 1078 cm⁻¹ and 638 cm⁻¹ were related to the stretching of O–Mn–O vibrations (Hoseinpour & Ghaemi, 2018). This confirmed the presence of ZnO-MnO₂ in the Fe₃O₄-ZnO-MnO₂ again.

We further studied the magnetic properties of VSM. As shown in Fig.S2b, the magnetization curves of Fe₃O₄ and Fe₃O₄-ZnO-MnO₂ hybrid composites show no remanence or coercivity at room temperature, indicating their superparamagnetic character. The saturation magnetization values of Fe₃O₄ and Fe₃O₄-ZnO-MnO₂ were 56.50 emu g⁻¹ and 50.03 emu g⁻¹, respectively. Fe₃O₄-ZnO-MnO₂, dispersed in a turbidized and uniform aqueous solution, can be separated within 1 min under the action of an external magnetic field to form a clear and transparent solution. This feature lays the foundation for subsequent rapid separation applications.

3.2. Catalytic performance test of Fe₃O₄-ZnO-MnO₂

HRP was used as a positive control for enzyme activity. We performed color reaction with TMB and tested UV–Vis's spectra to verify the peroxidase and oxidase properties of Fe₃O₄-ZnO-MnO₂. Meanwhile, the enzyme activity was compared with that of previously synthesized Fe₃O₄-Ag-MnO₂ nanocomposites. From Fig. 2a, we can see that the two nanocomplexes have equal catalytic capacity. Even if HRP has the best catalytic effect, the absorbance value was not very different from that of the two nanocomposites. The color of the inserted test tubes was almost the same. These results indicate that the two nanocomplexes have the potential to replace HRP in peroxidase applications. Fig. 2b shows the results of TMB color development catalyzed by HRP and a variety of nanoparticles. Our previous experiments demonstrated that Fe₃O₄ cannot catalyze the oxidation of TMB in the absence of H₂O₂. Here, we further performed the experiment of HRP catalyzing TMB without the help of H₂O₂, and the results displayed that TMB could not be oxidized to appear blue. The other three nanomaterials can oxidize TMB from colorless to blue. The UV–vis spectra data showed almost no absorption at 652 nm (A652_nm) in the HRP group, which was consistent with the colorlessness shown in the insert images. The other three nanomaterials have maximum absorption peaks at 652 nm. Both Fe₃O₄-Ag-MnO₂ and ZnO-MnO₂ had pretty much the same catalytic effects. This suggests that ZnO-MnO₂ helped Fe₃O₄-Ag-MnO₂'s high oxidation effect. The absorbance values of the two nanomaterials were both higher than Fe₃O₄-Ag-MnO₂, indicating that the catalytic effect of Fe₃O₄-ZnO-MnO₂ on oxide TMB was stronger than that of Fe₃O₄-Ag-MnO₂ in the absence of H₂O₂, prompting that the Fe₃O₄-ZnO-MnO₂-TMB system has a good application prospect in colorimetric detection. Catalase test results show that H₂O₂ alone at room temperature produces no bubbles. HRP and two nanocomplexes could produce O₂ from H₂O₂. The bubbles of Fe₃O₄-Ag-MnO₂ were slightly lower than those of HRP and Fe₃O₄-ZnO-MnO₂, suggesting that the catalase activity of Fe₃O₄-ZnO-MnO₂ was not different from that of HRP and was higher than that of Fe₃O₄-Ag-MnO₂(Fig. 2c).

Fig. 2.

a Visual and UV–Vis spectra of HRP(1), Fe₃O₄–Ag–MnO₂ (2) and Fe₃O₄-ZnO-MnO₂ (3) catalyzed the oxidation of chromogenic substrates in the presence of H₂O₂ to produce different color reactions; b Visual and UV–Vis spectra of HRP (1), Fe₃O₄–Ag–MnO₂ (2), ZnO-MnO₂ (3) and Fe₃O₄-ZnO-MnO₂ (4) catalyzed the oxidation of chromogenic substrates in the absence of H₂O₂ to produce different color reactions; c Pictures of different substances catalyzing the decomposition of H₂O₂ to generate O₂ (1: H₂O₂ alone, 2: HRP 3: Fe₃O₄–Ag–MnO₂, 4: Fe₃O₄-ZnO-MnO₂).

3.3. Feasibility test of visual detection of Fe₃O₄-ZnO-MnO₂ hybrid nanocomposites

In order to explore the application of Fe₃O₄-ZnO-MnO₂ in analytical detection, we utilized its efficient catalytic activity towards TMB and designed a colorimetric determination for nitrite in food. As shown in the illustrations in Fig. 3a, Fe₃O₄-ZnO-MnO₂ oxidized colorless TMB to blue, and the color became green after mixing with a small amount of nitrite, and the color became brown-yellow after adding more amount. The UV–Vis spectra data shown that the A652_nm decreases with an increase in the concentration of nitrite in the system. The results confirmed that the Fe₃O₄-ZnO-MnO₂-TMB system could be used to measure the content of nitrite at different concentrations in food.

Fig. 3.

a: Feasibility verification of nitrite detection using UV–vis absorption spectra and photographs (Inset) (1: Oxidized TMB, 2: Oxidized TMB+ 10 mg L⁻¹ NO₂⁻, 3: Oxidized TMB+ 40 mg L⁻¹ NO₂⁻); b: Feasibility verification of LM detection using UV–vis absorption spectra and Photographs (Inset) (1: Blank, 2: with 10³ cfu mL⁻¹ LM).

In addition to the determination of small molecules, further exploration of the Fe₃O₄-ZnO-MnO₂-TMB system is needed for the analysis of large-molecule substances. Taking the common foodborne pathogen LM as an example, the target bacteria were attached to the surface of the Fe₃O₄-ZnO-MnO₂ nanoprobe through an immunological specific reaction, which covered the active site of catalytic oxidation of TMB, thus causing the catalytic ability of the target substance to be weakened. Fig. 3b confirms the feasibility of this application. When the target bacteria are present, the experimental color decreases, and the A652_nm value is also lower than that of the blank control group. These results indicated that the inorganic small molecule nitrite and biological foodborne pathogens could be determined based on the Fe₃O₄-ZnO-MnO₂-TMB system.

3.4. Optimizing the detection of NO₂⁻

In the determination program of nitrite, several key factors must be considered, including TMB concentration, pH value of the detection system, temperature, TMB oxidation time, color development time, etc. The absorption at 652 nm was used as the basis for data processing here. The results in Fig. S3a show that with a catalyst content of 0.5 mg mL⁻¹, the absorption at 652 nm increased with the increase in TMB concentration, and the increase rate decreased when the content was 0.4. Therefore, the influence of the TMB dosage of 0.4 mg mL⁻¹. The influence of pH on catalysts cannot be ignored. Fig. S3b represents that with the increase in pH, the absorption at 652 nm increased successively and then gradually decreased. The catalytic effect was best when pH was 4, and the pH of the subsequent detection system was set to 4. The optimization of temperature was exhibited in Fig. S3c. It can be seen that both low and high temperatures have adverse effects on the catalytic effect, while the reaction was optimal at room temperature. Therefore, subsequent experiments were conducted at room temperature. The oxidation time of Fe₃O₄-ZnO-MnO₂ on TMB showed that the A652_nm rose slowly after 5 min. In order to save time, the subsequent oxidation time was set at 5 min. The oxidized blue TMB product was used for color reaction on 60 mg L⁻¹ nitrite, and the A652_nm did not increase significantly after 20 min, and the reaction was terminated after 20 min in the follow-up experiment.

3.5. Key applications of NO₂⁻ detection methods in food

Under optimized experimental conditions, colorimetric determination was performed on NO₂⁻ at a concentration of 0–60 mg L⁻¹. The result is shown in Fig. 4. As can be seen from the inset, when the target substance was not present in the system, the color was blue. As the concentration of nitrite increased, the blue gradually deepened. When the concentration was 5 mg L⁻¹, there was a significant color difference between the deepening of the blue degree of the experimental tube and the blank control. Therefore, the naked eye detection limit was determined to be 5 mg L⁻¹. Established a linear regression curve with the absorbance at 652 nm as the vertical axis and the nitrite concentration as the horizontal axis. Within 0–15 mg L⁻¹, Y = 0.0245× + 0.3012, R² = 0.9569; Within 15–60 mg L⁻¹, Y = -0.0113× + 0.7895, R² = 0.9949. The detection limit for NO₂⁻ was calculated to be 0.022 mg L⁻¹ according to the rule of 3δ/S (δ represents blank standard deviation, S stands for slope). The above results indicate that the Fe₃O₄-ZnO-MnO₂-TMB system was suitable for rapid colorimetric detection of nitrite. The correlation comparison between the proposed detection system and other analytical methods for detecting NO₂⁻ was shown in Table S2. It can be seen that the detection system established by this research institute has unique advantages in many aspects such as detection range, operation process and detection time, and the detection limit was far lower than the China's national food safety standard and the World Health Organization (WHO) and the European Scientific Committee for Food (SCF) (Alsaiari et al., 2022). Therefore, it was reasonable to think that this system has the potential to be applied in the field of food safety rapid detection and screening.

Fig. 4.

a: The linear relationship between A652_nm and NO₂⁻ concentrations from 0 to 60 mg L⁻¹(Inset: photographs of the system with different concentrations of NO₂⁻); b: Selectivity and interference studies (Inset: photographs, 110: blank, Cl⁻, P₂O₄⁴⁻, Ca²⁺, Mg²⁺, K⁺, citric acid, glucose, alcohol, NO₂⁻).

Precision and accuracy are two very important performance indexes in the analysis method. The precision and accuracy of the proposed method were measured by the standard recovery and Relative standard deviation (RSD). Several common interfering substances were selected to evaluate the anti-interference performance of the detection system, in which the concentration of NO₂⁻ was 10 mg L⁻¹ and the concentration of interfering substances was 100 mg L⁻¹. The results displayed that even if it was 10 times higher, it still did not affect the recognition of nitrite, hinting that the detection system can react specifically to nitrite. Taking fired mustard and sausage as examples, the application potential of detection systems in food was studied. The results exhibited that the spiked recovery rate was 83.71–102.95 % and the RSD was less than 16 %, which proved that the detection system could be used for the determination of nitrite content in food (Table 1).

Table 1.

The recoveries and RSD values of detection system in spiked food samples ($\overline{x}\pm s$, n = 3).

Sample	Finded (mg L−1)	Added(mg L−1)	Calculated(mg L−1)	Recovery rate (%)	RSD (%)
Fuling mustard (mg L−1)		5.00	5.72 ± 0.56	93.77	9.75
	1.10	10.00	10.59 ± 0.60	95.40	5.69
		5.00	6.28 ± 0.97	102.95	15.48
		10.00	10.21 ± 0.88	91.98	8.65
Sausage (mg L−1)		5.00	6.7 ± 0.69	90.44	10.22
	2.43	10.00	11.58 ± 0.88	93.16	7.65
		5.00	6.22 ± 0.80	83.71	12.83
		10.00	11.56 ± 0.96	93.00	8.35
Milk (cfu mL−1)		5 × 10	(5.10 ± 0.62) × 10	102.02	12.16
	0	5 × 102	(4.75 ± 0.56) × 102	95.01	11.79
		5 × 10	(5.41 ± 0.49) × 10	108.25	9.06
		5 × 102	(4.98 ± 1.02) × 102	99.67	20.48
Pork (cfu mL−1)		5 × 10	(5.23 ± 0.81) × 10	104.62	15.49
	0	5 × 102	(4.67 ± 0.62) × 102	93.49	13.28
		5 × 10	(5.05 ± 0.99) × 10	101.09	19.60
		5 × 102	(4.88 ± 0.91) × 102	97.68	18.65

3.6. Optimizing the detection of LM

In the determination procedure of LM, the content of the immunomagnetic nanoprobes in the detection process of LM was first optimized. Fig. S4a and S4b showed the number of bacteria in the positive control group and the number of bacteria in the supernatant when the immunomagnetic nanoprobe was 0.5 mg mL⁻¹, respectively. It was calculated that the capture rate was 95.67 % at this time, suggesting that almost majority of the target bacteria could be captured. Fig. S4c showed that the target bacteria were attached to the surface by the Fe₃O₄-ZnO-MnO₂-Apt nanoprobe. It was proved that the magnetic nanoprobe could have immune recognition reaction with the target bacteria, so the dosage of the immunomagnetic nanoprobe in the subsequent experiment was 0.5 mg mL⁻¹. Besides, in order to better visualize the measurement, the TMB dosage was optimized. As shown in Fig. S5a, when the concentration of TMB was 0.08 mg mL⁻¹, the increase rate slowed down, and the amount of TMB used in subsequent experiments was 0.08 mg mL⁻¹. Similarly, the different color development time of TMB was measured, and the result was also stable after 5 min (Fig. S5b).

3.7. Applications of LM detection methods in food

Quantitative determination of 0–10⁶ cfu mL⁻¹ LM under optimal experimental conditions. The illustrations in Fig. 5a show that there was a color difference between the detection tube and the PBS blank tube when the target bacteria concentration was 10³ cfu mL⁻¹, and the naked-eye detection limit of the detection system was defined as 10³ cfu mL⁻¹. A linear regression curve was established with the A652_nm for TMB oxidation products as the vertical axis and the log value for target bacterial concentration as the horizontal axis: Y = -0.0215lgC + 0.2057, R² = 0.9825. The detection limit for LM was calculated to be 3.5 cfu mL⁻¹ according to the rule of 3δ/S (δ represents the blank standard deviation and S represents the slope). Table S3 summarized the colorimetric detection methods of LM published in recent years. It can be seen that compared with other methods, the proposed method has the advantages of simple operation, sensitivity, and strong specificity. The superior performance of our colorimetric method was mainly attributed to the effective capture and separation effects of Fe₃O₄-ZnO-MnO₂ hybrid magnetic nanoparticles and the TMB-mediated signal amplification system. Another huge advantage of our proposed approach is time savings, which is crucial for quickly controlling food safety and reducing economic losses.

Fig. 5.

a: The linear relationship between A652_nm and logarithm of LM concentration from 0 to 10⁶ cfu mL⁻¹(Inset: photographs of the system with different concentrations of LM); b: Selectivity and interference studies of A652_nm (Inset: photographs, 19: Blank, SA, O157:H7, Shigella, VP, S. typhimurium, mixture, mixture + LM, LM).

According to the similarity analysis of the bacterial survival matrix, 5 common foodborne pathogens were selected for anti-interference analysis. The illustration in Fig. 5c shows that the blue of the blank was similar to that of other interfering bacteria, while the blue of the test tube containing the target bacteria was obviously lighter. The A652_nm corresponds to the color. It was proven that the detection system has an excellent ability to identify target bacteria. Meat and milk were selected as samples for the food simulation experiments. The results showed that the spiked recovery rate was 93.49–108.25 %, and the RSD was below 21 %, as illustrated in Table 1. This indicates that the detection system can be applied to the determination of LM content in food.

4. Conclusion

In conclusion, this study successfully synthesized the Fe₃O₄-ZnO-MnO₂ hybrid nanocomplex with diverse enzyme activities. The peroxidase, catalase, and oxidase activities of the nanocomplex were comparable to those of HRP, demonstrating its excellent enzymatic properties. Specifically, using the Fe₃O₄-ZnO-MnO₂-TMB system as a model, the nanoscale enzyme exhibited remarkable performance in detecting both small molecules like nitrite and large molecules like LM. This highlights the significant potential of the hybrid nanocomplex for applications in food detection. The advantages of the Fe₃O₄-ZnO-MnO₂ hybrid nanocomplex over HRP lie in its unique properties, such as enhanced catalytic activity, stability, and potential for large-scale production. These features make it a promising alternative for various analytical applications, including food safety. The successful development of this nanocomposite paves the way for future research on its application in detecting other target substances. However, this study only discussed the detection of one target object, which could not meet the needs of the coexistence of multiple contaminants in food matrices, and did not fully apply the diverse enzyme activities of nanoenzymes. These deficiencies will prompt us to continue our in-depth study. In short, this study contributes to the advancement of nanobiocatalysts in the field of food safety and analytical chemistry, providing a solid foundation for further research and practical applications.

Funding

This study was supported by the Chinese National Natural Science Foundation (Grant No. 82003502 and 21904053), the Science and Technology Plan Project of Yantai (Grant No. 2022XDRH004), the Natural Science Foundation of Shandong Province (Grant No. ZR2023MB107), Shandong Key Laboratory of Biochemical Analysis (SKLBA2307) and the Youth Innovation Technology Project of Higher School in Shandong Province (Food Nanotechnology innovation team).

CRediT authorship contribution statement

Shuyang Sun: Conceptualization. Wenteng Qiao: Formal analysis. Feng Yin: Methodology. Wei Mi: Formal analysis. LuliangWang: Funding acquisition. Yuhan Jia: Formal analysis. Mengjiao Wang: Software. Xinhui Liu: Software. Dacheng Wang: Conceptualization. Daotan Liu: Software. Chao Zhao: Conceptualization. Xiuling Song: Formal analysis. Yushen Liu: Writing – original draft, Funding acquisition. Yue Zhai: Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

Supplementary material

Data availability

Data will be made available on request.