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Recent advances in immunoassays and biosensors for mycotoxins detection in feedstuffs and foods

Abstract

Mycotoxins are secondary metabolites produced by fungus. Many mycotoxin species are highly toxic and are frequently found in cereals and feedstuffs. So, powerful detection methods are vital and effective ways to prevent feed contamination. Traditional detection methods can no longer meet the needs of massive, real-time, simple, and fast mycotoxin monitoring. Rapid detection methods based on advanced material and sensor technology are the future trend. In this review, we highlight recent progress of mycotoxin rapid detection strategies in feedstuffs and foods, especially for simultaneous multiplex mycotoxin determination. Immunoassays, biosensors, and the prominent roles of nanomaterials are introduced. The principles of different types of recognition and signal transduction are explained, and the merits and pitfalls of these methods are compared. Furthermore, limitations and challenges of existing rapid sensing strategies and perspectives of future research are discussed.

Introduction

Topics related to food safety have been attracting significant attention all over the world. Contaminants in cereals and animal products are related closely to human health. Mycotoxins are secondary metabolites of fungus and may be produced during growth, production, processing, and storage of cereals, grains and feedstuffs [1]. There are over 300 mycotoxins identified, many of which are extremely toxic and difficult to degrade by cooking, baking or frying because of their high heat-stability [2]. The International Agency for Research on Cancer (IARC) has classified several mycotoxins into different categories based on their carcinogenic risk to human health. For example, aflatoxin B1 (AFB1) is the most carcinogenic mycotoxin and is classified as Group 1 while ochratoxin A (OTA) and fumonisin are classified into Group 2B as possibly carcinogenic in humans [3,4,5]. Many countries have developed standards to control mycotoxin contamination of food for safety reasons [6]. In China, maximum residue levels (MRLs) for mycotoxins in various foods have been strictly regulated in national food safety standard system. Consequently, a powerful detection method for mycotoxins is critical component in assuring food safety.

Traditional analytical methods such as enzyme-linked immunoassay (ELISA), thin layer chromatography, gas chromatography or high-performance liquid chromatography (HPLC) coupled with ultraviolet detection, fluorescence detector electron capture detectors, diode array detectors, and mass spectrometry (MS) detectors have been used to detect mycotoxins for decades [7,8,9,10]. Most of these traditional methods are accurate and sensitive but time-consuming, expensive, or require sophisticated instruments and professional technicians. They are not appropriate for a large number of samples and on-site screening. Because of demands from food industry professionals and government regulations, analytical methods that can detect multiple mycotoxins simultaneously and are fast, simple, sensitive, and low-cost with high-throughput have become the norm in the field of food safety and will continue into the future [11].

Rapid detection technology is a concept relative to traditional analysis methods and laboratory detection technology. It is often based on interdisciplinary subjects such as nanomaterials science, immunology, molecular biology, spectroscopy, and electrochemistry. Rapid detection is simple, cheap, easy to operate, and only requires portable instrument and a very short detection duration. It enables detection method to meet the need of the real-time on-site mycotoxins screening in the field of food safety. Herein, we review published research reports on rapid detection technology for mycotoxins from 2016 to 2021 including immunoassays and biosensors. Principles of recognition and signal transduction strategies are explained, and the pros and cons compared to existing method are discussed. Especially, we highlight studies on simultaneous detection of multiple mycotoxins. Limitations, challenges and perspectives of the future developments in this field are discussed.

Types of recognition strategies

Specific recognition of analytes is the primary step of rapid detection, which ensures the specificity and selectivity of the analytical method. In this section, different types of recognition elements for mycotoxin detection are introduced including antibodies, aptamers, and molecularly imprinted polymers (MIPs).

Antibodies

Antibodies are immunoglobulins produced by the immune system that specifically bind to the corresponding antigens. Based on the preparation processes used, antibodies are classified into polyclonal, monoclonal, or recombinant categories. Antibody-antigen recognition is regarded as a gold standard because of its properties of high specificity and affinity. Antibodies and antigens are the most widely commercialized recognition and capture agents applied in immunoassays and biosensors for clinical diagnosis, disease treatment, environment monitor, and food safety control [12,13,14,15]. However, there are obvious disadvantages of using antibodies. First, acquisition of high-quality antibodies requires immunization and purification which is a complex process that is time-consuming and costly. Second, antibodies are sensitive to pH and temperature conditions, which may narrow the practical application. Finally, only immunogenic and immunoreactive molecules can be identified by antibodies. Targets of small molecular weight need to conjugate with a carrier protein to enhance immunogenicity, but the chemical conjugation efficiency of mycotoxins to a protein carrier is low.

To overcome these limitations of antibodies, variable region of heavy chains antibody (nanobody) and phage-displayed mimotope peptides may be some utility in solving these antibody problems [16]. Nanobody as a naturally deficient light chain antibody is highly stable and small in size, which makes it easy to conserve and use. Phage displayed mimotope peptide can simulate the epitope of the target analytes so the hapten-carrier conjugate can be replaced by a mycotoxin-free mimic which also makes fabrication of green sensors possible [17,18,19,20,21].

Aptamers

Aptamers are small fragments of oligonucleotide sequences (single stranded DNA or RNA), which usually contain 10 to 100 bases. Aptamers bind to their targets by folding into specific three-dimensional structures. They are selected from a combinatorial DNA library by a technology named systematic evolution of ligands exponential enrichment (SELEX) and can bind to various targets ranging from ions to cells. Aptamers are usually considered to be ideal affinity reagents alternatives to antibodies. Compared to antibodies, aptamers are inexpensive, stable, reversible, not limited by immunogenicity of targets, and do not require immunization of animals during production. Aptamers have high bioavailability and are easy to modify. As an excellent alternative to antibodies, aptamers are being deployed in biosensor, disease diagnosis, and drug delivery [22,23,24]. However, acquiring aptamers with high affinity and sensitivity especially for small molecules is relatively inefficient. Over the past few years, selection techniques have been improved constantly. A series of novel SELEX-based techniques such as Cell-SELEX, Capillary electrophoresis-SELEX, Capture-SELEX, and Post-SELEX modifications have been developed. Compared with the original SELEX technique, aptamers developed with these new approaches display high affinity and specificity while selection processes are more efficient and cost-effective [25, 26]. Although aptamers are currently prevalent in scientific literatures, commercial aptamer-based mycotoxin detection kits are not yet available [27].

Molecularly imprinted polymers (MIPs)

Molecular imprinting is a technology developed based on bionic science and simulation of the interactions of enzymes with their target substrates and receptors with their antibodies in nature. Molecularly imprinted polymers (MIPs) are obtained by mixing imprinted molecules (template molecules) with appropriate functional monomers (usually small molecular compounds) and crosslinking agents. Then polymerize them and eluting the imprinted molecules by appropriate methods. Molecularly imprinted polymers have been called “artificial antibodies”. They are preserved easily, resistant to extreme conditions such as high temperature, high pressure, acid, and alkali, and difficult to destroy by biodegradation [28]. Consequently, MIPs are widely applied in optical sensors, electrochemical sensors, quartz crystal microbalances, simulated catalysis, membrane separations and solid phase extractions (SPE) [29,30,31,32,33]. In spite of these benefits, MIPs face several challenges in practical applications. A considerable drawback of MIPs is unspecific interactions, especially with small molecules, which requires non-imprinted polymers (NIPs) be employed to characterize nonspecific binding [34]. Selectivity and binding affinity of MIPs still require development to allow detection of target compounds in complex matrixes [33]. Commercialization of MIPs is in its infancy. Relatively few research studies focused on MIPs-based mycotoxin sensors are reported in the scientific literature.

Rapid detection strategies

Immunoassays

Immunoassays are based on immunological principles that use antibodies to recognize and capture target antigens or haptens. Enzyme-linked immunosorbent assays (ELISA) are early immunoassays that have been commercially applied in mycotoxin detection with good sensitivity and accuracy [35]. Enzyme-linked immunosorbent assays are simpler than instrumental methods such as HPLC and LC-MS/MS, but they still require complex operations and several hours of incubation and microplate washing procedures. Therefore, researchers have been working to develop various immunoassays for better analytical performance. New procedures such as fluorescent-linked immunosorbent assays (FLISA) and chemiluminescence enzyme immunoassays (CLEIA) can reduce detection duration and improves the sensitivity by relying on enhanced optical signals [36,37,38]. Lateral flow immunoassays (LFIA) and immunosensors have become popular analytical methods in recent years. In this part, LFIA is chiefly introduced and immunosensor is introduced in the following sensor section.

Lateral flow immunoassays

Lateral flow immunoassays (LFIA), also known as immunochromatographic assays (ICA), are the most frequently used and commercialized rapid sensing platform and widely applied in disease diagnosis, point-of-care testing (POCT) and food safety monitoring because of its low cost, rapidity and simplicity [39, 40]. The detection process is integrated on a small strip and the signal analysis requires portable instruments and very little time. Lateral flow immunoassays are highly convenient to achieve simultaneous detection of multiple mycotoxins by using multiple test lines and signal labels. There are two main detection principles used, sandwich assay (two types of antibodies are required) and competitive assay (one type of antibodies are required). Mycotoxin cannot acquire two types of recognition antibodies because it doesn’t own multiple epitopes, so the competitive LFIA is preferred.

High-quality antibodies and antigens are primary guarantees for the high sensitivity and specificity of LFIA. However, the recognition of limited immunogenic targets by antibodies has hindered development of LFIA in several fields of study. Secondly, there is a contradiction in the competitive detection mode itself. That is, within a certain range, the less quantity of antibodies makes the competition between free target analytes and the immobilized antigens more effective on the test zone. So, the lower the specific antibody concentration, the lower the detection limit. However, the amount of the label conjugated with antibody is reduced simultaneously with the low concentration of antibody, which decreases signal intensity of the test line and hinders successful detection of the targets.

To overcome these shortcomings above, researchers developed better-performed antibodies or signal labels with high luminescent intensity and stability [41]. Besides, the new detection principle based on fluorescence quenching that can directly response to changes of target analytes has been attempted [42].

Signal labels

Gold nanoparticles (AuNPs) are the most frequently used signal labels in LFIA because they are easy to synthesize, inexpensive, and emit visible red to purple light when they aggregate. However, an obvious drawback of AuNPs-based LFIA is the instability and weak optical intensity of AuNPs resulting in low sensitivity [41, 43]. Recently, non-spherical, multilayer AuNPs with varying colors such as flower-like AuNPs have been used in LFIA instead of traditional spherical AuNPs to improve the sensitivity [44,45,46]. Wu et al. [47] engineered gold nanoparticles to create multicolor labels such as red gold nanospheres, purple gold nanocacti, blue gold nanoflowers and black hyperbranched Au plasmonic blackbodies. Four mycotoxins (FB1, ZEN, OTA and AFB1) can be successfully detected in corn using this multicolor LFIA strip and limit of detection (LOD) for FB1, ZEN, OTA, and AFB1 were 3.27, 0.70, 0.10, and 0.06 ng/mL, respectively.

Use of various fluorescent labels with higher stability and signal intensity in LFIA to enhance the sensitivity has become commonplace. Quantum dots (QDs) are semiconductor nanoparticles that possess excellent optical properties including size-tunable emission, broad adsorption, narrow photoluminescence spectra, high photostability, large Stokes’s shift, and long fluorescence lifetime [48]. Fluorescent microspheres (FMs) are polymers that contain numerous fluorescent particles such as fluorescent dyes and quantum dots in the nanobeads. Fluorescent microspheres are more stable and have substantially higher fluorescent intensity than that of single fluorescent molecule [49]. Carbon-based nanoparticles (CNPs) such as carbon dots have desirable optical properties similar to quantum dots, and have low toxicity [50]. These materials are promising LFIA labels because they are water soluble and they are not easy to aggregate and precipitate. Functional groups like carboxyl can be easily modified on their surfaces, which helps them bind to antibodies with great stability due to covalent binding between hydroxyl and carboxyl groups.

Time-resolved fluorescent microspheres (TRFMs) are recently employed as signal labels frequently. Lanthanides such as Eu (III), Tb (III) have much longer fluorescence lifetime than the previously mentioned fluorescent materials so that they can eliminate the background fluorescence interference from the matrix, thus improving the sensitivity of LFIA [51,52,53]. For example, Fig. 1A shows time-resolved fluorescent Eu/Tb (III) nanosphere and idiotypic nanobodies for multiplex detection of two mycotoxins simultaneously in maize [52]. Sensitivity of LFIA was improved by the enhanced fluorescence of Eu/Tb (III) nanosphere with the LOD of 0.05 and 0.07 ng/mL for AFB1 and ZEN, respectively. Another study reported novel α-Fe2O3 nanocubes used as LFIA label for simultaneously detecting two mycotoxins. These nanocubes have been employed to detect AFB1 and DON residues in mung bean, millet and corn, with the visual LOD for AFB1 and DON of 0.01 and 0.18 ng/mL, respectively [54].

Fig. 1
figure1

Structure and test procedure of LFIA. (A) Time-resolved fluorescent Eu/Tb (III) nanosphere for detecting AFB1 and ZEN; (B) multiplex SERS-based lateral flow immunosensor for the detection of six mycotoxins; (C) detection of OVA based on donor probe (CD-OVA) and accepter probe (AgNP-Ab). Diagrams A, B, and C are adapted from Ref. [52] Ref. [60] and Ref. [42], respectively

Researchers have compared various signal labels to provide a reference for selection of appropriate labels. For instance, colloidal gold (CG) and QDs as labels for multi-mycotoxin detection in cereal matrices have been compared. The QD-LFIA was more sensitive and economical than CG-LFIA [41]. In another study, CG and FMs were compared as the LFIA labels for T-2 toxin detection in rice, fresh milk, and chicken feed. The cut-off values of the CG-LFIA and the FMs-LFIA were 400 μg/kg and 100 μg/kg, respectively. And they found CG and FMs performed differently in different matrixes. Under the same experimental conditions, CG had better tolerance to milk while FMs had better tolerance to chicken feed [55]. A comparative study of LFIA of ZAE in cereals using CG, QDs and polystyrene microspheres (PMs) as signal label was conducted [56]. Researchers reported that QD-LFIA and PM-LFIA were ten times more sensitive than CG-LFIA. Besides, a smartphone-based dual mode LFIA device for multiplex mycotoxins in cereals was developed, which was integrated with AuNPs and TRFMs as labels. The result indicated that the LOD of TRFMs mode were lower than that of AuNPs mode [57].

Gold nanoparticles and sliver nanoparticles can provide another detectable signal termed Surface-Enhanced Raman Spectroscopy (SERS). Surface-Enhanced Raman Spectroscopy effect is the phenomenon that in the excitation region of some specially prepared metal good conductor surface or colloidal sol. The Raman scattering signal of adsorbed molecules is greatly enhanced compared with the ordinary Raman scattering signal because the enhanced electromagnetic field on the sample surface. When SERS nanotags (gold, silver or Au-Ag alloy nanoparticles labelled with Raman reporter molecules) are exposed to a laser light source, the incident field is obviously enhanced at active sites (electromagnetic “hot spots”) due to localized surface plasmon resonance effects [58, 59]. Combining SERS detection and lateral flow immunoassay is also regarded as a promising choice for highly sensitive and multiplex mycotoxin detection. Fig. 1B show a SERS-based LFIA combined dual-Raman label (DTNB and MBA) with triple-line LFIA and labelled-Au@Ag core-shell nanoparticles serving as SERS nanoprobes [60]. The SERS-based LFIA can be used for the detection of six common mycotoxins (AFB1, ZEN, FB1, DON, OTA and T-2) simultaneously in maize with high sensitivity and selectivity within 20 min. Signal acquisition requires only a portable Raman System.

Fluorescence quenching LFIA

In addition to competitive assays, researchers have explored LFIA based on fluorescence quenching principle to improve sensitivity. Competitive assays need many target analytes to compete with Immobilized antigen then make the signal of test lines “turn off”. The signal is an indirect signal, which leads to relative low sensitivity. While the fluorescence quenching LFIA can provide a “turn on” signal, which responses to the amount of target analytes directly [61, 62]. Inner-filter effect (IFE) and Förster resonance energy transfer (FRET) are widely used quenching mechanisms. Quenching agents usually are metal nanoparticles such as AuNPs or AgNPs. Inner-filter effect is a radiation energy transfer mechanism while Förster resonance energy transfer is a non-radiative process. Quenching effects occur when the absorption spectrum of the accepter (quencher) overlaps with the donor’s excitation or emission spectra. Antigens (analytes) are usually linked with fluorescence donors then immobilized on the test line. Antibodies are usually linked with fluorescence accepters (quenchers) which can bind to the analytes. If there is no analyte in the sample solution, antibodies-linked accepters will bind to antigens-linked donors resulting in fluorescence quenching of the donor. Conversely, if there are many analytes in the sample solution binding with antibodies-linked accepters, the donor’s fluorescence will be restored. Fig. 1C shows a fluorescence quenching LFIA based on the CdSe/ZnS quantum dots and gold/silver nanoparticles for straightforward detection of fumonisin in maize flour [42]. Silver nanoparticles overlapped excitation bands of the QDs, and AuNPs overlapped emission bands. The QD quenching was due to IFE. Silver nanoparticles were demonstrated to be more efficient in QDs quenching because absorbing the exciting light was more efficient in IFE. Compared to conventional AgNPs-based LFIAs, the visual detection limit was four times lower. Another attempt explored a quencher system based on FRET mechanism for fluorometric LFIA for zearalenone detection in cereal samples. Carbon dots were conjugated to ovalbumin as the donor signal probe and AgNPs-Antibody served as the acceptor signal probe. The LOD of the LFIA was 10 times better than the “turn-off” AgNPs-based LFIA [63].

Based on existing studies, fluorescence quenching LFIAs exhibited a better performance than traditional AgNPs-based LFIAs but there have been hardly any researches on multiple mycotoxin detection using fluorescence quenching LFIA. Most of traditional LFIAs and fluorescence quenching LFIA can only render qualitative or semi-quantitative results at present. False positive and false negative results are still a problem. Selected studies of LFIAs for mycotoxin detection published in recent years are listed and compared in Table 1.

Table 1 Summary of LFIA strips for detecting mycotoxins

Biosensors

Biosensors are detection devices that can convert the information measured into electrical signals or other information output of the required form. The biosensor system mainly consists of a biorecognition (biosensing) element and a transducer element. Biorecognition elements such as antibodies, antigens, nucleic acids, and enzymes are used to identify and sense target analytes. Transducer elements convert the physical quantity signal of generated by the recognition elements into detectable signals. According to the principle of the signal transduction, biosensors can be classified into electrochemical, optical, mass-sensitive, and thermal sensors. They have become vital and powerful analytical tools widely applied in various fields including medicine, food, agriculture, environment, and industry. Biosensor systems were introduced to enhance food safety in the 1980s and provide great commercial potential currently [16, 72,73,74]. In this section, electrochemical and optical biosensors for mycotoxin detection are mainly introduced.

Optical biosensors

Optical sensors rely on variation in optical signals generated by transducer from molecular recognition events on sensing element. This approach excels in superiorities of simplicity, speed of detection, sensitivity and visualization [75]. On the basis of optical signals, optical biosensors are divided into many subclasses including colorimetric, fluorescent, chemiluminescent and surface plasmon resonance. Optical biosensor systems also exhibit many possibilities for determination of multiple mycotoxins simultaneously.

Colorimetric biosensors

Colorimetric biosensors are based on color changes induced by target analytes that can be easily distinguished by the naked eye. Gold or silver nanoparticles are most frequently applied as indicators to utilize their surface plasmon resonance (SPR) properties. The general principle is that recognized targets induce aggregation of AuNPs or AgNPs from well-dispersed state resulting in color change from red to blue.

A colorimetric aptasensor for simultaneously detecting ochratoxin A and aflatoxin B1 in peanut was reported [76]. Researchers fabricated a Fe3O4/GO based platform and a Fe3O4@Au based platform for AFB1 and OTA sensing. Quantitative detection of OTA and AFB1 was respectively carried out by release of thymolphthalein and 3,3′,5,5′-tetramethylbenzidine catalyzed by gold nanoparticles, respectively. In this work, OTA and AFB1 were easily and visibly detected in one system with the linear ranges of 0.5–80 and 5–250 ng/mL and did not interfere with each other because of different color reaction conditions.

In another attempt, a colorimetric sensor based on array of gold and silver nanoparticles was fabricated for simultaneous detection of AFB1, AFG1, AFM1, OTA and ZEN [77]. Mycotoxin interactions with nanoparticles induced aggregation of gold or silver nanoparticles and the color changed. Every type of mycotoxin was recognized by its unique colorimetric signatures with the LOD of 2.7, 7.3, 2.1, 3.3 and 7.0 ng/mL for AFB1, AFG1, AFM1, OTA and ZEN, respectively. The developed colorimetric method had the advantages of high throughput, simplicity, rapidity and low cost. This system was tested in pistachio, wheat, coffee, and milk samples. Most of colorimetric sensors suffer the weakness of low sensitivity which suggests optical signal intensities still need further enhancement.

Fluorescent biosensors

At present, fluorescent biosensors are the most popular optical sensors because of their high sensitivity, stable signal, and fast response. Various nano-materials such as magnetic nanoparticles (MNPs), quantum dots (QDs), carbon nanoparticles (CNPs), gold nanoparticles (AuNPs), fluorescent nanobeads, and graphene oxide (GO) have been widely applied in construction of fluorescent sensors [78,79,80]. Lanthanide-based luminescent materials such as upconverting nanoparticles (UCNPs) and time-resolved fluorescence materials (TRFMs) have also become popular in recent years [81, 82]. After target analytes have been identified by recognition elements, quantitative sensing of one mycotoxin is achieved by the variation of fluorescent signals based on fluorescence quenching, fluorescence enhancement, or displacement of fluorescent labels.

Figure 2A shows dual DNA tweezers nanomachine has been utilized for simultaneous detection of AFB1 and OTA [83]. The fluorophores were quenched by the quencher when DNA tweezers were closed. In the presence of AFB1 and OTA, DNA tweezers opened after the aptamer strands bind with their corresponding targets resulting in the activated fluorescent signals. The aptasensor exhibited satisfactory applicability in food samples including corn, peanut, olive oil, peanut oil, and coffee.

Fig. 2
figure2

Schematic illustration of the optical sensing platforms. (A) Dual DNA tweezers nanomachine for simultaneous detection of AFB1 and OTA; (B) a FRET-based platform using WS2 nanosheet and dual-color gold nanoclusters (AuNCs) for simultaneous detection of AFB1 and ZEN; (C) a fluorescence aptasensor for FB1 and OTA detection by using TRF-NPs and MNPs; Diagrams A, B, and C are adapted from Ref. [83], Ref. [84], and Ref. [81], respectively

A FRET-based platform was developed by WS2 nanosheet and dual-color gold nanoclusters (AuNCs) for simultaneous detection of AFB1 and ZEN in maize [84]. Gold nanoclusters and WS2 were connected by AFB1/ZEN-aptamer-BSA resulting in fluorescent quenching of AuNCs. Fluorescence turned on when target analytes were present (Fig. 2B). The sensor achieved multiplex target determinations in a homogeneous system with excellent simplicity, sensitivity, and selectivity. However, this system can only provide semiquantitative detection. Another FRET-based platform was proposed using GO/Fe3O4 as a single energy acceptor, which can quench the dual aptamer-modified QDs simultaneously and eliminate background interference effectively by magnetic separation [85]. This system successfully detected AFB1 and FB1 in peanut with the LOD of 6.7 and 16.2 pg/mL, respectively.

Time-resolved fluorescence materials are also excellent materials for fluorescent probes design because of its long fluorescence lifetime, which provides anti-interference capability. For example, Fig. 2C shows a fluorescence aptasensor for FB1 and OTA detection in maize samples by using time-resolved fluorescence nanoparticles (TRF-NPs) and MNPs [81]. The aptamer-MNPs and cDNA-TRF-NPs formed the duplex structure. With the addition of FB1 and OTA, the aptamer-MNPs bound to FB1 and OTA then dissociated from its cDNA, leading to a decrease in fluorescent intensity when magnetic separation. The sensor was user-friendly with LOD for FB1 and OTA were 0.019 and 0.015 pg/mL, respectively. The aptasensor exhibited better practicability than common fluorescent system in complex metrics because of the unique merits of TRFM-NPs.

Chemiluminescence and electrochemiluminescence biosensors

Chemiluminescence is a light radiation phenomenon resulting from a chemical reaction, which is also an important tool for molecular sensing. But, low luminescence intensity of chemiluminescence needs to be enhanced by enzymes or metal nanoparticles in practical applications [86]. For instance, a AgNPs modified surface-plasmon-coupled chemiluminescence immunosensor was developed for aflatoxin B1 and ochratoxins A detection in red yeast rice [87]. The generated chemiluminescence signal on the chip was amplified by AgNPs through the SPR phenomenon, which greatly enhanced sensitivity of the biosensor. The chip array offered a high-throughput detection mode for multiple targets. But several incubations and washing operations were needed, which complicated the assay. The problem of uneven brightness made advanced instruments and equipment necessary to achieve acceptable readings.

Electrochemiluminescence (ECL), as a subclass of chemiluminescence or electrochemistry, is regarded as the reverse of photoelectron chemistry. Voltage or current serves as the excitation source and the generated chemiluminescence is used as the detectable signal. With ECL, the electro-active species generated in the vicinity of the electrode surface are in excited states emitting light that arises from the high-energy electron-transfer reactions of these species. Luminol and Ru (bpy)32+ are classic ECL luminophores while QDs are beginning to be applied to ECL sensors to achieve higher efficiency and stability of ECL [88, 89]. Electrochemiluminescence-based sensors have fast response, high sensitivity and low background interference, which is a promising strategy for applying in rapid detection [90]. However, ECL biosensors have similar drawbacks observed with electrochemical biosensors, such as instability of electrode including the degradation biosensing reagents and the instable optical signal of ECL luminophores. And few ECL instruments have been reported. Advanced and portable equipment is urgently needed.

A nicking endonuclease-powered DNA walking machine was proposed to fabricate an ECL aptasensor for OTA detection [91]. Quantum dots produced ECL signal and was greatly amplified by DNA walking machine, which increased the sensitivity of this ECL sensor. This ECL aptasensor showed satisfactory recoveries of OTA in beer and wine with the LOD of 12 pmol/L. Other researchers developed a label-free ZnCdS@ZnS QDs-based ECL immunosensor for AFB1 detection in lotus seed [92]. Quantum dots and Nafion were assembled on Au electrode surface as ECL signal probes and anti-AFB1 antibodies were coupled as the capturing element. Using of Nafion and core-shell QDs greatly enhanced the ECL signal thus improved the sensitivity. The label-free design simplified the synthesis steps and reduced detection time.

Surface plasmon resonance biosensors

Surface plasmon resonance (SPR) sensors are optical sensors based on changes in the refractive index due to the mass changes that occur when molecules bind to the sensor surface. These changes in refractive index can provide direct recognition information between a target and a probe on the sensor surface. Therefore, SPR sensor enables monitoring the real-time interaction among molecules on a tiny chip which can be a powerful analytical tool for purpose of medical diagnostics, food safety analysis and environmental monitoring [19, 93].

A competitive-type SPR sensor for DON and OTA detection by imaging nanoplasmonics was developed [94]. A portable nanostructured imaging surface plasmon resonance (iSPR) chip was immobilized with 3-dimensional carboxymethylated dextran. Afterwards, target mycotoxins and immobilized mycotoxins competitively bound to the corresponding antibodies producing SPR signals. The SPR-based sensor achieved portable detection for DON and OTA in beer with the LOD of 17 and 7 ng/mL, respectively.

Another study described a SPR-based aptasensor in a direct assay format for AFB1 detection. The aptamers were modified on the commercial sensor chip surface, and the SPR signals increased when AFB1 bound to aptamers to achieve quantification with the LOD of 0.4 nmol/L (124.8 pg/mL) [95]. A label-free microfluidic SPR biosensor based on nanoparticles integrated gold chip for Aflatoxin B1 detection was developed. A self-assembled monolayer (SAM) Au chip was modified with AFB1 antibodies and functionalized lipoic acid AuNPs were deposited on it. This multilayer functionalized AuNPs modified Au chip exhibited better sensing performance than bare self-assembled Au chip with the LOD of 0.003 nmol/L (0.93 pg/mL) [96].

By comparing these studies, we can infer that direct SPR-sensors are simpler and more sensitive than indirect SPR-sensors. However, because the small molecule analytes (such as mycotoxins) cannot cause obvious mass concentration changes at the sensor surface, the direct SPR-sensor’s chip surface must be modified with noble metal NPs for signal amplification. More advanced portable SPR instruments are required for practical application.

Optical biosensor platforms that recently reported for mycotoxin determinations are listed in Table 2.

Table 2 Summary of optical biosensor platforms for detecting mycotoxins

Electrochemical biosensors

Electrochemical biosensors are based on changes in outputted electrical signals that produced by the chemical reactions between electrode-immobilized recognition elements and target analytes. According to the types of detectable electrical signals, electrochemical sensors can be categorized into amperometric, potentiometric, conductometric, impedimetric and voltammetric methods. Besides, the electrode system (working electrode, reference electrode and counter electrode) is vital to the sensors because identification of target analytes needs to be finished on the electrode. The electrode is also used to conduct electrical signals [12, 109].

Traditional electrochemical immunosensors using general electrodes have some defects of low sensitivity, low stability, and inability to detect multiple targets simultaneously. To address these issues, improving performance of working electrodes and achieving signal amplification have become necessary. Commonly used working electrodes such as glass carbon, gold, and silver electrodes have recently been modified with various nanomaterials (carbon nanotubes, graphene oxide, metal nanoparticles, thin-layer MoS2, and porous metal organic framework) to increase their surface area [110,111,112,113]. As a result, the nanostructured rough electrode surface can be immobilized with more recognition reagents and more sufficient contact with the analytes so that sensitivity and conductivity are greatly improved [114]. For example, a facile electrochemical immunosensor was constructed for rapid detection of ZEN using thin-layer molybdenum disulfide and thionin composites (MoS2-Thi). Thin-layer MoS2 is an important graphene analog that is used frequently as a supporting substrate for stabilizing nanoparticles [112]. In this research, ZEN monoclonal antibodies were modified with platinum (Pt) nanoparticles then immobilized on MoS2-Thi composites to obtain synergistic signal amplification. Therefore, this immunosensor was easy to operate as well as offered a higher sensitivity compared with the original ZEN monoclonal antibodies.

Screen-printed electrodes have become popular for their advantages of reliability, reproducibility, ductility, ease of mass production, and low costs. They are variable in shape and small enough to be combined with miniaturized devices. Similarly, screen-printed electrodes are also modified with various nanomaterials to enhance sensitivity of electrochemical sensors [115,116,117].

Microfluidic systems employed in electrochemical immunosensor is an ideal choice to reduce detection time, improve stability and detect multiple targets simultaneously [118]. For example, Lu et al. [119] reported a dual-channel microfluidic electrochemical immunosensor for FB1 and DON detection in corn. Three-electrodes were etched on transparent indium tinoxide (ITO)-coated glass. A sample solution was introduced in the capillary-driven polydimethylsiloxane (PDMS) microfluidic channel. This microfluidic electrochemical immunosensor exhibited high potential for practical application with the LOD of 97 and 35 pg/mL for FB1 and DON, respectively. However, there are few reports on electrochemical immunosensors for detection of multiple mycotoxins.

Since antibody’s degradation is still a hinder for regeneration of electrochemical immunosensor sensing elements, aptamer-based sensors (aptasenor) have attracted more and more attention recently. Aptasensors exhibit greater diversity and universality than immunosensors. They are easier to construct for multiple analytes detection systems and sensitivity of aptasensor can be greatly improved by a ratiometric mode. Fig. 3A shows a hairpin DNA-based ratiometric electrochemical aptasensor for simultaneous detection of AFB1 and OTA [120]. Ferrocene-labelled AFB1 aptamer (Fc-Apt1) and methylene blue-labelled OTA aptamer (MB-Apt2) served as binding probes and current signal indicators. Both aptamers were complementary to the carboxylic acid (AQ)-labelled hairpin DNA that served as reference signal. It was applied to analyze AFB1 and OTA in corn and wheat samples with high sensitivity and reliability. Similarly, Wei et al. [121] designed a unique Y-shaped complementary DNA structure for simultaneously hybridizing with OTA and FB1 aptamer. OTA and FB1 aptamers were immobilized with thionine and thiolated ferrocene as signal indicators. It was applied to detect OTA and FB1 in beer with the LOD of 0.47 and 0.26 pg/mL, respectively.

Fig. 3
figure3

Schematic illustration of the electrochemical sensing platforms. (A) Hairpin DNA-based ratiometric electrochemical aptasensor for simultaneous detection of AFB1 and OTA; (B) dual-target electrochemical aptasensor was developed based on co-reduced molybdenum disulfide and gold nanoparticles (rMoS2-Au) modified electrodes. Diagrams A and B are adapted from Ref. [120] and Ref. [122], respectively

Another dual-target electrochemical aptasensor was developed based on co-reduced molybdenum disulfide and gold nanoparticles (rMoS2-Au) modified electrodes [122]. Aptamers of AFB1 and ZEN were binding with thionine and 6-(Ferrocenyl) hexanethiol modified complementary strands, respectively (Fig. 3B). This platform obtained satisfactory recoveries of AFB1 and ZEN in maize with the LOD as low as 0.4 pg/mL. Li et al. reported a ratiometric electrochemical aptasensor for AFB1 detection in peanut. Ferrocene-labelled aptamer (Fc-apt) served as the response signal and reduced graphene oxide (THI-rGO) functionalized with thionine was used as the reference signal. In this study, ratiometric detection was achieved by formation of Fc-apt-AFB1 complex which resulted in decreased current intensity of Fc (IFc), and increased current intensity of THI (ITHI) [123]. It is worth mentioning that sensitivity of this sensor can be adjusted by changing the assembly of Fc-apt, which exhibited high sensitivity and selectivity.

Molecularly imprinted polymers (MIPs) can serve as the recognition elements in electrochemical sensors which are favorable alternatives to antibodies. MIPs are mechanical and chemical stable and provide thickness-controlled MIP films on electrode surfaces, which permit direct communication between the films and the transducer. A novel MIP-sensor with two functionalization methods for AFB2 detection in milk was developed. Researches compared ZnO-NPs/chitosan (CS)/AFB2 and ZnO-NPs/Cs/polypyrrole (PPy)/AFB2 composite that electrodeposited on the screen-printed electrode [124]. They showed that ZnO-NPs/CS/PPy/AFB2 functionalized composite had greater sensitivity than ZnO-NPs/CS/AFB2. This MIP-sensor exhibited good specificity, reproducibility and stability as well as extremely low LOD (0.2 fg/mL). Differential pulse voltammetry (DPV) techniques used in this study had a faster and more sensitive response compared to the electrochemical impedance spectroscopy.

In general, electrochemical biosensors show reliable sensitivity and selectivity as well as great potential for miniaturization and portability. But the modification steps involved in the electrochemical biosensors’ preparation are complicated. Reproducibility and interference resistance of traditional electrodes in complex matrices still is problematic. Compared with optical detection methods, there are no huge advantages for development of multiple target detection systems. Table 3 summarizes the important parameters of electrochemical biosensor platforms that have been published in recent years for mycotoxin determinations.

Table 3 Summary of electrochemical sensor platforms for detecting mycotoxins

Others

Photoelectrochemical sensors

Photoelectrochemical (PEC) sensors are emerging as an analytical technology that combines features of both optics and electrochemistry. In PEC sensors, light source, electrochemical workstation, and signal acquisition system are main components. Light is used as the excitation source and the generated photocurrent is used as the detection signal, which significantly reduces background interference [136]. Photoactive material, as a transducer for the conversion from biological recognition events to observable PEC signals, plays a crucial role in the PEC biosensing platform. Semiconductors (such as QDs) and semiconductor-based heterojunctions (such as graphene and reduced graphene oxide) are commonly used [137,138,139]. However, PEC biosensors have no obvious advantages over common electrochemical biosensors in sensitivity, simplicity, and practicability at present. Multiple mycotoxins detected by PEC sensors have not been found yet. The detection instruments used for PEC sensor still need a simplification [140].

Metal−organic frameworks (MOFs)

In recent years, a novel material has been be applied in fluorescent and electrochemical sensing, termed metal−organic frameworks (MOFs). Metal−organic frameworks are porous coordination polymers with huge surface area, that exhibit excellent optical, electrochemical and catalytic properties [111, 141]. Luminescent metal−organic frameworks (LMOFs), a subclass of MOFs, display outstanding optical properties such as large stokes shifts, high quantum yield, characteristically narrow emission spectra, and long fluorescence lifetime. They also function in recognition and enrichment of targets due to the porous and easily modified structure, which are considered as promising chemical sensor materials [142, 143]. Hu et al. [144] firstly reported a highly luminescent Zn-based metal−organic framework for AFB1 sensing in 2015. The blue luminescence of MOFs can be quenched by AFB1 efficiently and specifically with the LOD of 46 ppb. Another water-stable LMOFs was developed for sensitive and rapid detection of AFB1 in walnut and almond beverages [145]. The LMOF was synthesized by 1,2,4,5-tetrakis (4-carboxyphenyl) benzene (H4TCPB) and highly water-stable Zr, which exhibited raging fluorescence quenching when AFB1 existed with the LOD of 19.97 ppb. These proposed MOFs provide a sensor platform that is very easy to synthesize and operate, but the sensitivity of MOF sensors was not as good as that of other electrochemical and optical biosensors. Anti-interference capability and specific selectivity in complex matrix related to MOFs still requires investigation.

Conclusion and perspectives

Various mycotoxin contamination occurs frequently and unavoidably in feedstuffs and cereals, which poses enormous risks to public health and leads to economic losses. This paper introduces advanced analytical methods and nanomaterials for mycotoxin detection in recent years including immunoassays and biosensors, especially for multiple mycotoxin detections. Target recognition, signal transduction, and nanoparticles are keys to rapid detection techniques. Analytical methods introduced in this paper are divided into many categories based on these three aspects.

Colorimetric immunoassays are simple, visible, and low-cost methods without the requirement of expensive instruments but the instability, background interference, and poor sensitivity are considerable drawbacks. Therefore, many fluorescent nanoparticles have been introduced to rapid detection and greatly enhance sensitivity and stability. However, some fluorescent signal labels are susceptible to fluorescent bleaching, autofluorescence or environmental interference and require complex labeling steps. Electrochemical biosensors are classic and powerful sensing strategy because of their high sensitivity and ability to be miniaturized, but they are hard to resist interferences, complex electrode modifications are required and electrode fouling and degradation still need to be solved. Photoelectrochemical and electrochemiluminescence sensors are regarded as combining the merits of optical and electrochemical strategies, which show low background, fast response, and high sensitivity. However, the absence of advanced PEC and ECL instrumentation limits practical application. And signal stability and ability to analyze multiple targets of PEC and ECL sensors is not sufficient. Label-free SPR biosensors simplify preparation and detection procedures. They have excellent analytical performance and offers direct and real-time detection platforms by using tiny chips, which make them have great potential for commercial detection of mycotoxins. But SPR sensors are not sensitive to binding events of low molecular weight molecules so that some modifications on chips and sophisticated instruments are still required. Both advantages and disadvantages exist in each kind of detection strategy. We need to choose the appropriate approach according to the conditions and requirements.

In spite of numerous successes with laboratory-based mycotoxin detection, there are still many limitations and challenges to conquer in achieving practical applications.

Firstly, nanomaterials are widely applied almost in all sensing strategies but the function of nanomaterials currently available are not perfect. There are many studies improving material properties and biosensor performances by using hybrid nanostructured materials, but they are not convenient for practical application and mass manufacturing. Developing promising nanomaterials that have excellent optical or electrochemical properties, but also are inexpensive, easy to prepare and environmentally friendly is still a focus of future research. This is also one of the core driving forces behind development of biosensor and immunoassay-based analytical methods.

Secondly, most of the existing sensing strategies are based on single signal output, which are susceptible to instrument conditions and environmental interferences resulting in poor reproducibility and stability. To overcome this drawback, ratiometric sensor with dual signals is an ideal solution. Detection results are based on the ratio of two signals enable self-built-in corrections thus greatly improving sensitivity and accuracy of sensing method. Two different luminescent particles connected together to form a FRET system in optical sensors or two signal labels served as response/reference system in electrochemical sensors are mainstream of ratiometric sensor design. But there are few reports on the detection of mycotoxins by ratiometric biosensors at present.

Lastly, simplicity, sensitivity, and high throughput have not really been implemented simultaneously in a rapid detection method. High-sensitive methods such as electrochemical biosensors often require complex modification operations, while simple and portable LFIA tend to produce qualitative or semi-quantitative detection results. Nowadays, with the development of micro-electro-mechanical systems (MEMS), sensor devices can be miniaturized at a tiny size. There are more and more reports on smartphone-based microfluidic biosensor systems which provide the portable, rapid, and sensitive sensing platforms. This is also a future trend that makes biosensors to better serve humans. Moreover, faced with a wide variety of mycotoxins, there have been many reports on the LFIA strip with multiplex test lines, multiplex SPR biochips, biosensors with multiple labels and integrating biosensors with microarrays and microfluidic systems. Most examples discussed in this paper are appropriate for up to three to six mycotoxins and involved complex designs. But achieving high-throughput quantitative detection of a dozen to dozens of analytes under the premise of guaranteed sensitivity still needs hard work.

Despite many challenges, rapid detection methods based on cross-discipline play an increasingly important role in food safety, industrial manufacture, environmental monitoring, and clinical diagnoses. Traditional determination technology has not been adapted to the demands of rapid, on-site, and large-scale screening. Fast, simple, sensitive, low-cost, and high-throughput analytical methods with portable instrument are growing need. With development of nanomaterials and biosensor technology, rapid detection will receive much more attention in the future.

Availability of data and materials

Not applicable.

Abbreviations

AFB1:

Aflatoxin B1

OTA:

Ochratoxin A

MRLs:

Maximum residue levels

ELISA:

Enzyme-linked immunoassay

HPLC:

High-performance liquid chromatography

LC-MS/MS:

Liquid chromatography-tandem mass spectrometry

MS:

Mass spectrometry

MIPs:

Molecularly imprinted polymers

SELEX:

Systematic evolution of ligands exponential enrichment

SPE:

Solid phase extractions

NIPs:

Non-imprinted polymers

FLISA:

Fluorescent-linked immunosorbent assays

CLEIA:

Chemiluminescence enzyme immunoassays

LFIA:

Lateral-flow immunoassays

POCT:

Point-of-care testing

AuNPs:

Gold nanoparticles

FB1:

Fumonisin B1

ZEN:

Zearalenone

FMs:

Fluorescent microspheres

CNPs:

Carbon-based nanoparticles

TRFMs:

Time-resolved fluorescent microspheres

CG:

Colloidal gold

PMs:

Polystyrene microspheres

SERS:

Surface-enhanced raman spectroscopy

IFE:

Inner-filter effect

FRET:

Förster resonance energy transfer

DON:

Deoxynivalenol

T−2:

T-2 toxin

SPR:

Surface plasmon resonance

MNPs:

Magnetic nanoparticles

GO:

Graphene oxide

QDs:

Quantum dots

UCNPs:

Upconverting nanoparticles

AuNCs:

Gold nanoclusters

LOD:

Limit of detection

PEC:

Photoelectrochemical

MOFs:

Metal−organic frameworks

References

  1. 1.

    Yang Y, Li G, Wu D, Liu J, Li X, Luo P, et al. Recent advances on toxicity and determination methods of mycotoxins in foodstuffs. Trends Food Sci Technol. 2020;96:233–52. https://doi.org/10.1016/j.tifs.2019.12.021.

    CAS  Article  Google Scholar 

  2. 2.

    Zhou SY, Xu LG, Kuang H, Xiao J, Xu CL. Immunoassays for rapid mycotoxin detection: state of the art. Analyst. 2020;145(22):7088–102. https://doi.org/10.1039/D0AN01408G.

    CAS  Article  PubMed  Google Scholar 

  3. 3.

    Xue Z, Zhang Y, Yu W, Zhang J, Wang J, Wan F, et al. Recent advances in aflatoxin B1 detection based on nanotechnology and nanomaterials-a review. Anal Chim Acta. 2019;1069:1–27. https://doi.org/10.1016/j.aca.2019.04.032.

    CAS  Article  PubMed  Google Scholar 

  4. 4.

    Xu L, Zhang Z, Zhang Q, Li P. Mycotoxin determination in foods using advanced sensors based on antibodies or aptamers. Toxins. 2016;8:239. https://doi.org/10.3390/toxins8080239.

  5. 5.

    Gallo A, Giuberti G, Frisvad JC, Bertuzzi T, Nielsen KF. Review on mycotoxin issues in ruminants: occurrence in forages, effects of mycotoxin ingestion on health status and animal performance and practical strategies to counteract their negative effects. Toxins. 2015;7(8):3057–111. https://doi.org/10.3390/toxins7083057.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Van Egmond HP, Schothorst RC, Jonker MA. Regulations relating to mycotoxins in food. Anal Bioanal Chem. 2007;389(1):147–57. https://doi.org/10.1007/s00216-007-1317-9.

    CAS  Article  PubMed  Google Scholar 

  7. 7.

    Njumbe Ediage E, Van Poucke C, De Saeger S. A multi-analyte LC-MS/MS method for the analysis of 23 mycotoxins in different sorghum varieties: the forgotten sample matrix. Food Chem. 2015;177:397–404. https://doi.org/10.1016/j.foodchem.2015.01.060.

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Pei SC, Lee WJ, Zhang GP, Hu XF, Eremin SA, Zhang LJ. Development of anti-zearalenone monoclonal antibody and detection of zearalenone in corn products from China by ELISA. Food Control. 2013;31(1):65–70. https://doi.org/10.1016/j.foodcont.2012.09.006.

    CAS  Article  Google Scholar 

  9. 9.

    Tkaczyk A, Jedziniak P. Dilute-and-shoot HPLC-UV method for determination of urinary creatinine as a normalization tool in mycotoxin biomonitoring in pigs. Molecules. 2020;25:13.

    Article  Google Scholar 

  10. 10.

    Grippi F, Crosta L, Aiello G, Tolomeo M, Oliveri F, Gebbia N, et al. Determination of stilbenes in Sicilian pistachio by high-performance liquid chromatographic diode array (HPLC-DAD/FLD) and evaluation of eventually mycotoxin contamination. Food Chem. 2008;107(1):483–8. https://doi.org/10.1016/j.foodchem.2007.07.079.

    CAS  Article  Google Scholar 

  11. 11.

    Chauhan R, Singh J, Sachdev T, Basu T, Malhotra BD. Recent advances in mycotoxins detection. Biosens Bioelectron. 2016;81:532–45. https://doi.org/10.1016/j.bios.2016.03.004.

    CAS  Article  PubMed  Google Scholar 

  12. 12.

    Alhamoud Y, Yang D, Fiati Kenston SS, Liu G, Liu L, Zhou H, et al. Advances in biosensors for the detection of ochratoxin a: bio-receptors, nanomaterials, and their applications. Biosens Bioelectron. 2019;141:111418. https://doi.org/10.1016/j.bios.2019.111418.

    CAS  Article  PubMed  Google Scholar 

  13. 13.

    Ding L, Chen X, He L, Yu F, Yu S, Wang J, et al. Fluorometric immunoassay for the simultaneous determination of the tumor markers carcinoembryonic antigen and cytokeratin 19 fragment using two kinds of CdSe/ZnS quantum dot nanobeads and magnetic beads. Mikrochim Acta. 2020;187(3):171. https://doi.org/10.1007/s00604-019-3914-7.

    CAS  Article  PubMed  Google Scholar 

  14. 14.

    Lv Y, Wang F, Li N, Wu R, Li J, Shen H, et al. Development of dual quantum dots-based fluorescence-linked immunosorbent assay for simultaneous detection on inflammation biomarkers. Sensor Actuat B Chem. 2019;301:127118. https://doi.org/10.1016/j.snb.2019.127118.

    CAS  Article  Google Scholar 

  15. 15.

    Li M, Ma M, Hua X, Shi H, Wang Q, Wang M. Quantum dots-based fluoroimmunoassay for the simultaneous detection of clothianidin and thiacloprid in environmental and agricultural samples. RSC Adv. 2015;5(4):3039–44. https://doi.org/10.1039/C4RA13305F.

    CAS  Article  Google Scholar 

  16. 16.

    Bueno D, Istamboulie G, Munoz R, Marty JL. Determination of mycotoxins in food: a review of bioanalytical to analytical methods. Appl Spectrosc Rev. 2015;50(9):728–74. https://doi.org/10.1080/05704928.2015.1072092.

    CAS  Article  Google Scholar 

  17. 17.

    Ren W, Xu Y, Huang Z, Li Y, Tu Z, Zou L, et al. Single-chain variable fragment antibody-based immunochromatographic strip for rapid detection of fumonisin B1 in maize samples. Food Chem. 2020;319:126546. https://doi.org/10.1016/j.foodchem.2020.126546.

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Hou SL, Ma ZE, Meng H, Xu Y, He QH. Ultrasensitive and green electrochemical immunosensor for mycotoxin ochratoxin a based on phage displayed mimotope peptide. Talanta. 2019;194:919–24. https://doi.org/10.1016/j.talanta.2018.10.081.

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Mahmoudpour M, Ezzati Nazhad Dolatabadi J, Torbati M, Pirpour Tazehkand A, Homayouni-Rad A, de la Guardia M. Nanomaterials and new biorecognition molecules based surface plasmon resonance biosensors for mycotoxin detection. Biosens Bioelectron. 2019;143:111603.

    CAS  Article  Google Scholar 

  20. 20.

    Tang Z, Liu X, Wang Y, Chen Q, Hammock BD, Xu Y. Nanobody-based fluorescence resonance energy transfer immunoassay for noncompetitive and simultaneous detection of ochratoxin a and ochratoxin B. Environ Pollut. 2019;251:238–45. https://doi.org/10.1016/j.envpol.2019.04.135.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Peltomaa R, Farka Z, Mickert MJ, Brandmeier JC, Pastucha M, Hlavacek A, et al. Competitive upconversion-linked immunoassay using peptide mimetics for the detection of the mycotoxin zearalenone. Biosens Bioelectron. 2020;170:112683. https://doi.org/10.1016/j.bios.2020.112683.

    CAS  Article  PubMed  Google Scholar 

  22. 22.

    Xiang WW, Lv QX, Shi HX, Xie B, Gao L. Aptamer-based biosensor for detecting carcinoembryonic antigen. Talanta. 2020;214:17.

    Article  Google Scholar 

  23. 23.

    Sinha K, Das MC. Quantitative detection of neurotransmitter using aptamer: from diagnosis to therapeutics. J Biosci. 2020;45:12.

    Article  Google Scholar 

  24. 24.

    He F, Wen NC, Xiao DP, Yan JH, Xiong HJ, Cai SD, et al. Aptamer-based targeted drug delivery systems: current potential and challenges. Curr Med Chem. 2020;27(13):2189–219. https://doi.org/10.2174/0929867325666181008142831.

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Darmostuk M, Rimpelova S, Gbelcova H, Ruml T. Current approaches in SELEX: An update to aptamer selection technology. Biotechnol Adv. 2015;33(6):1141–61. https://doi.org/10.1016/j.biotechadv.2015.02.008.

    CAS  Article  PubMed  Google Scholar 

  26. 26.

    Guo X, Wen F, Zheng N, Saive M, Fauconnier ML, Wang J. Aptamer-based biosensor for detection of mycotoxins. Front Chem. 2020;8:195. https://doi.org/10.3389/fchem.2020.00195.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Chen A, Yang S. Replacing antibodies with aptamers in lateral flow immunoassay. Biosens Bioelectron. 2015;71:230–42. https://doi.org/10.1016/j.bios.2015.04.041.

    CAS  Article  PubMed  Google Scholar 

  28. 28.

    Gaudin V. Advances in biosensor development for the screening of antibiotic residues in food products of animal origin - a comprehensive review. Biosens Bioelectron. 2017;90:363–77. https://doi.org/10.1016/j.bios.2016.12.005.

    CAS  Article  PubMed  Google Scholar 

  29. 29.

    Bezdekova J, Zemankova K, Hutarova J, Kociova S, Smerkova K, Adam V, et al. Magnetic molecularly imprinted polymers used for selective isolation and detection of Staphylococcus aureus. Food Chem. 2020;321:8.

    Article  Google Scholar 

  30. 30.

    Cao YR, Feng TY, Xu J, Xue CH. Recent advances of molecularly imprinted polymer-based sensors in the detection of food safety hazard factors. Biosens Bioelectron. 2019;141:18.

    Google Scholar 

  31. 31.

    Ahmadi R, Noroozian E, Jassbi AR. Molecularly imprinted polymer solid-phase extraction for the analysis of 1,8-cineole in thyme and sagebrush distillates. J Iran Chem Soc. 2020;17(5):1153–61. https://doi.org/10.1007/s13738-019-01840-x.

    Article  Google Scholar 

  32. 32.

    Choi SW, Chang HJ, Lee N, Chun HS. A surface plasmon resonance sensor for the detection of deoxynivalenol using a molecularly imprinted polymer. Sensors. 2011;11:8654–64.

    CAS  Article  Google Scholar 

  33. 33.

    Fu H, Xu W, Wang H, Liao S, Chen G. Preparation of magnetic molecularly imprinted polymers for the identification of zearalenone in grains. Anal Bioanal Chem. 2020;412(19):4725–37. https://doi.org/10.1007/s00216-020-02729-y.

    CAS  Article  PubMed  Google Scholar 

  34. 34.

    Ahmad OS, Bedwell TS, Esen C, Garcia-Cruz A, Piletsky SA. Molecularly imprinted polymers in electrochemical and optical sensors. Trends Biotechnol. 2019;37(3):294–309. https://doi.org/10.1016/j.tibtech.2018.08.009.

    CAS  Article  PubMed  Google Scholar 

  35. 35.

    Kolosova AY, Shim WB, Yang ZY, Eremin SA, Chung DH. Direct competitive ELISA based on a monoclonal antibody for detection of aflatoxin B1. Stabilization of ELISA kit components and application to grain samples. Anal Bioanal Chem. 2006;384(1):286–94. https://doi.org/10.1007/s00216-005-0103-9.

    CAS  Article  PubMed  Google Scholar 

  36. 36.

    Zhang F, Liu B, Sheng W, Zhang Y, Liu Q, Li S, et al. Fluoroimmunoassays for the detection of zearalenone in maize using CdTe/CdS/ZnS quantum dots. Food Chem. 2018;255:421–8. https://doi.org/10.1016/j.foodchem.2018.02.060.

    CAS  Article  PubMed  Google Scholar 

  37. 37.

    Li Y, Liu G, Fu X, He J, Wang Z, Hou J, et al. High-sensitive chemiluminescent elisa method investigation for the determination of deoxynivalenol in rice. Food Anal Methods. 2014;8:656–60.

    Article  Google Scholar 

  38. 38.

    Lu T, Zhan S, Zhou Y, Chen X, Huang X, Leng Y, et al. Fluorescence ELISA based on CAT-regulated fluorescence quenching of CdTe QDs for sensitive detection of FB1. Anal Methods. 2018;10(48):5797–802. https://doi.org/10.1039/C8AY02065E.

    CAS  Article  Google Scholar 

  39. 39.

    Gowri A, Ashwin Kumar N, Suresh Anand BS. Recent advances in nanomaterials based biosensors for point of care (PoC) diagnosis of Covid-19 - a minireview. TrAC Trend Anal Chem. 2021;137:116205. https://doi.org/10.1016/j.trac.2021.116205.

    CAS  Article  Google Scholar 

  40. 40.

    Qian JQ, He QQ, Liu LL, Wang M, Wang BM, Cui LW. Rapid quantification of artemisinin derivatives in antimalarial drugs with dipstick immunoassays. J Pharm Biomed Anal. 2020;191:8.

    Article  Google Scholar 

  41. 41.

    Foubert A, Beloglazova NV, De Saeger S. Comparative study of colloidal gold and quantum dots as labels for multiplex screening tests for multi-mycotoxin detection. Anal Chim Acta. 2017;955:48–57. https://doi.org/10.1016/j.aca.2016.11.042.

    CAS  Article  PubMed  Google Scholar 

  42. 42.

    Anfossi L, Di Nardo F, Cavalera S, Giovannoli C, Spano G, Speranskaya ES, et al. A lateral flow immunoassay for straightforward determination of fumonisin mycotoxins based on the quenching of the fluorescence of CdSe/ZnS quantum dots by gold and silver nanoparticles. Mikrochim Acta. 2018;185(2):94. https://doi.org/10.1007/s00604-017-2642-0.

    CAS  Article  PubMed  Google Scholar 

  43. 43.

    Yao J, Sun Y, Li Q, Wang F, Teng M, Yang Y, et al. Colloidal gold-McAb probe-based rapid immunoassay strip for simultaneous detection of fumonisins in maize. J Sci Food Agric. 2017;97(7):2223–9. https://doi.org/10.1002/jsfa.8032.

    CAS  Article  PubMed  Google Scholar 

  44. 44.

    Huang X, Huang X, Xie J, Li X, Huang Z. Rapid simultaneous detection of fumonisin B1 and deoxynivalenol in grain by immunochromatographic test strip. Anal Biochem. 2020;606:113878. https://doi.org/10.1016/j.ab.2020.113878.

    CAS  Article  PubMed  Google Scholar 

  45. 45.

    Huang X, Huang T, Li X, Huang Z. Flower-like gold nanoparticles-based immunochromatographic test strip for rapid simultaneous detection of fumonisin B1 and deoxynivalenol in Chinese traditional medicine. J Pharm Biomed Anal. 2020;177:112895. https://doi.org/10.1016/j.jpba.2019.112895.

    CAS  Article  PubMed  Google Scholar 

  46. 46.

    Di Nardo F, Baggiani C, Giovannoli C, Spano G, Anfossi L. Multicolor immunochromatographic strip test based on gold nanoparticles for the determination of aflatoxin B1 and fumonisins. Microchim Acta. 2017;184(5):1295–304. https://doi.org/10.1007/s00604-017-2121-7.

    CAS  Article  Google Scholar 

  47. 47.

    Wu Y, Zhou Y, Huang H, Chen X, Leng Y, Lai W, et al. Engineered gold nanoparticles as multicolor labels for simultaneous multi-mycotoxin detection on the immunochromatographic test strip nanosensor. Sensor Actuat B Chem. 2020;316:128107. https://doi.org/10.1016/j.snb.2020.128107.

    CAS  Article  Google Scholar 

  48. 48.

    Guo L, Shao Y, Duan H, Ma W, Leng Y, Huang X, et al. Magnetic quantum dot nanobead-based fluorescent immunochromatographic assay for the highly sensitive detection of aflatoxin b1 in dark soy sauce. Anal Chem. 2019;91(7):4727–34. https://doi.org/10.1021/acs.analchem.9b00223.

    CAS  Article  PubMed  Google Scholar 

  49. 49.

    Liu M, Zeng L-F, Yang Y-J, Hu L-M, Lai W-H. Fluorescent microsphere immunochromatographic assays for detecting bone alkaline phosphatase based on biolayer interferometry-selected antibody. RSC Adv. 2017;7(52):32952–9. https://doi.org/10.1039/C7RA03756B.

    CAS  Article  Google Scholar 

  50. 50.

    Tang DP, Lin YX, Zhou Q. Carbon dots prepared from Litchi chinensis and modified with manganese dioxide nanosheets for use in a competitive fluorometric immunoassay for aflatoxin B-1. Microchim Acta. 2018;185:9.

    Article  Google Scholar 

  51. 51.

    Altunbas O, Ozdas A, Yilmaz MD. Luminescent detection of Ochratoxin a using terbium chelated mesoporous silica nanoparticles. J Hazard Mater. 2020;382:121049. https://doi.org/10.1016/j.jhazmat.2019.121049.

    CAS  Article  PubMed  Google Scholar 

  52. 52.

    Tang X, Li P, Zhang Q, Zhang Z, Zhang W, Jiang J. Time-resolved fluorescence immunochromatographic assay developed using two idiotypic nanobodies for rapid, quantitative, and simultaneous detection of aflatoxin and zearalenone in maize and its products. Anal Chem. 2017;89(21):11520–8. https://doi.org/10.1021/acs.analchem.7b02794.

    CAS  Article  PubMed  Google Scholar 

  53. 53.

    Wang D, Zhang Z, Li P, Zhang Q, Zhang W. Time-resolved fluorescent immunochromatography of aflatoxin b1 in soybean sauce: a rapid and sensitive quantitative analysis. Sensors. 2016;16:1094. https://doi.org/10.3390/s16071094.

  54. 54.

    Zhao S, Bu T, He K, Bai F, Zhang M, Tian Y, et al. A novel α-Fe2O3 nanocubes-based multiplex immunochromatographic assay for simultaneous detection of deoxynivalenol and aflatoxin B1 in food samples. Food Control. 2021;123:107811. https://doi.org/10.1016/j.foodcont.2020.107811.

    CAS  Article  Google Scholar 

  55. 55.

    Zhang X, Wu C, Wen K, Jiang H, Shen J, Zhang S, et al. Comparison of fluorescent microspheres and colloidal gold as labels in lateral flow immunochromatographic assays for the detection of T-2 toxin. Molecules. 2015;21:E27.

    Article  Google Scholar 

  56. 56.

    Li SJ, Sheng W, Wen W, Gu Y, Wang JP, Wang S. Three kinds of lateral flow immunochromatographic assays based on the use of nanoparticle labels for fluorometric determination of zearalenone. Mikrochim Acta. 2018;185(4):238. https://doi.org/10.1007/s00604-018-2778-6.

    CAS  Article  PubMed  Google Scholar 

  57. 57.

    Liu Z, Hua Q, Wang J, Liang Z, Li J, Wu J, et al. A smartphone-based dual detection mode device integrated with two lateral flow immunoassays for multiplex mycotoxins in cereals. Biosens Bioelectron. 2020;158:112178. https://doi.org/10.1016/j.bios.2020.112178.

    CAS  Article  PubMed  Google Scholar 

  58. 58.

    Wang X, Park SG, Ko J, Xiao X, Giannini V, Maier SA, et al. Sensitive and reproducible immunoassay of multiple mycotoxins using surface-enhanced raman scattering mapping on 3d plasmonic nanopillar arrays. Small. 2018;14:e1801623.

    Article  Google Scholar 

  59. 59.

    Ko J, Lee C, Choo J. Highly sensitive SERS-based immunoassay of aflatoxin B1 using silica-encapsulated hollow gold nanoparticles. J Hazard Mater. 2015;285:11–7. https://doi.org/10.1016/j.jhazmat.2014.11.018.

    CAS  Article  PubMed  Google Scholar 

  60. 60.

    Zhang W, Tang S, Jin Y, Yang C, He L, Wang J, et al. Multiplex SERS-based lateral flow immunosensor for the detection of major mycotoxins in maize utilizing dual Raman labels and triple test lines. J Hazard Mater. 2020;393:122348. https://doi.org/10.1016/j.jhazmat.2020.122348.

    CAS  Article  PubMed  Google Scholar 

  61. 61.

    Jiang H, Zhang W, Li J, Nie L, Wu K, Duan H, et al. Inner-filter effect based fluorescence-quenching immunochromotographic assay for sensitive detection of aflatoxin B1 in soybean sauce. Food Control. 2018;94:71–6. https://doi.org/10.1016/j.foodcont.2018.06.030.

    CAS  Article  Google Scholar 

  62. 62.

    Oh HK, Joung HA, Jung M, Lee H, Kim MG. Rapid and simple detection of ochratoxin a using fluorescence resonance energy transfer on lateral flow immunoassay (FRET-LFI). Toxins. 2019;11.

  63. 63.

    Li S, Wang J, Sheng W, Wen W, Gu Y, Wang S. Fluorometric lateral flow immunochromatographic zearalenone assay by exploiting a quencher system composed of carbon dots and silver nanoparticles. Mikrochim Acta. 2018;185(8):388. https://doi.org/10.1007/s00604-018-2916-1.

    CAS  Article  PubMed  Google Scholar 

  64. 64.

    Xu Y, Ma B, Chen E, Yu X, Ye Z, Sun C, et al. Dual fluorescent immunochromatographic assay for simultaneous quantitative detection of citrinin and zearalenone in corn samples. Food Chem. 2021;336:127713. https://doi.org/10.1016/j.foodchem.2020.127713.

    CAS  Article  PubMed  Google Scholar 

  65. 65.

    Jin Y, Chen Q, Luo S, He L, Fan R, Zhang S, et al. Dual near-infrared fluorescence-based lateral flow immunosensor for the detection of zearalenone and deoxynivalenol in maize. Food Chem. 2021;336:127718. https://doi.org/10.1016/j.foodchem.2020.127718.

    CAS  Article  PubMed  Google Scholar 

  66. 66.

    Duan H, Li Y, Shao Y, Huang X, Xiong Y. Multicolor quantum dot nanobeads for simultaneous multiplex immunochromatographic detection of mycotoxins in maize. Sensors Actuators B Chem. 2019;291:411–7. https://doi.org/10.1016/j.snb.2019.04.101.

    CAS  Article  Google Scholar 

  67. 67.

    Goryacheva OA, Guhrenz C, Schneider K, Beloglazova NV, Goryacheva IY, De Saeger S, et al. Silanized luminescent quantum dots for the simultaneous multicolor lateral flow immunoassay of two mycotoxins. ACS Appl Mater Interfaces. 2020;12(22):24575–84. https://doi.org/10.1021/acsami.0c05099.

    CAS  Article  PubMed  Google Scholar 

  68. 68.

    Li R, Meng C, Wen Y, Fu W, He P. Fluorometric lateral flow immunoassay for simultaneous determination of three mycotoxins (aflatoxin B1, zearalenone and deoxynivalenol) using quantum dot microbeads. Mikrochim Acta. 2019;186(12):748. https://doi.org/10.1007/s00604-019-3879-6.

    CAS  Article  PubMed  Google Scholar 

  69. 69.

    Zhang X, Yu X, Wen K, Li C, Mujtaba Mari G, Jiang H, et al. Multiplex lateral flow immunoassays based on amorphous carbon nanoparticles for detecting three fusarium mycotoxins in maize. J Agric Food Chem. 2017;65(36):8063–71. https://doi.org/10.1021/acs.jafc.7b02827.

    CAS  Article  PubMed  Google Scholar 

  70. 70.

    Shao Y, Duan H, Zhou S, Ma T, Guo L, Huang X, et al. Biotin-streptavidin system-mediated ratiometric multiplex immunochromatographic assay for simultaneous and accurate quantification of three mycotoxins. J Agric Food Chem. 2019;67(32):9022–31. https://doi.org/10.1021/acs.jafc.9b03222.

    CAS  Article  PubMed  Google Scholar 

  71. 71.

    Li R, Bu T, Zhao Y, Sun X, Wang Q, Tian Y, et al. Polydopamine coated zirconium metal-organic frameworks-based immunochromatographic assay for highly sensitive detection of deoxynivalenol. Anal Chim Acta. 2020;1131:109–17. https://doi.org/10.1016/j.aca.2020.07.052.

    CAS  Article  PubMed  Google Scholar 

  72. 72.

    Evans GP, Briers MG, Rawson DM. Can biosensors help to protect drinking-water. Biosensors. 1986;2(5):287–300. https://doi.org/10.1016/0265-928X(86)80008-6.

    CAS  Article  PubMed  Google Scholar 

  73. 73.

    Guilbault GG, Schmid RD. Biosensors for the determination of drug substances. Biotechnol Appl Biochem. 1991;14(2):133–45.

    CAS  PubMed  Google Scholar 

  74. 74.

    Evtugyn G, Hianik T. Electrochemical immuno- and aptasensors for mycotoxin determination. Chemosensors. 2019;7:29.

    Article  Google Scholar 

  75. 75.

    Chen H, Zhang L, Hu Y, Zhou C, Lan W, Fu H, et al. Nanomaterials as optical sensors for application in rapid detection of food contaminants, quality and authenticity. Sensors Actuators B Chem. 2021;329:129135. https://doi.org/10.1016/j.snb.2020.129135.

    CAS  Article  Google Scholar 

  76. 76.

    Zhu W, Li L, Zhou Z, Yang X, Hao N, Guo Y, et al. A colorimetric biosensor for simultaneous ochratoxin a and aflatoxins B1 detection in agricultural products. Food Chem. 2020;319:126544. https://doi.org/10.1016/j.foodchem.2020.126544.

    CAS  Article  PubMed  Google Scholar 

  77. 77.

    Sheini A. Colorimetric aggregation assay based on array of gold and silver nanoparticles for simultaneous analysis of aflatoxins, ochratoxin and zearalenone by using chemometric analysis and paper based analytical devices. Mikrochim Acta. 2020;187:167.

    CAS  Article  Google Scholar 

  78. 78.

    Wang X, Gao X, He J, Hu X, Li Y, Li X, et al. Systematic truncating of aptamers to create high-performance graphene oxide (GO)-based aptasensors for the multiplex detection of mycotoxins. Analyst. 2019;144(12):3826–35. https://doi.org/10.1039/C9AN00624A.

    CAS  Article  PubMed  Google Scholar 

  79. 79.

    Lu X, Wang C, Qian J, Ren C, An K, Wang K. Target-driven switch-on fluorescence aptasensor for trace aflatoxin B1 determination based on highly fluorescent ternary CdZnTe quantum dots. Anal Chim Acta. 2019;1047:163–71. https://doi.org/10.1016/j.aca.2018.10.002.

    CAS  Article  PubMed  Google Scholar 

  80. 80.

    Wang C, Tan R, Chen D. Fluorescence method for quickly detecting ochratoxin a in flour and beer using nitrogen doped carbon dots and silver nanoparticles. Talanta. 2018;182:363–70. https://doi.org/10.1016/j.talanta.2018.02.007.

    CAS  Article  PubMed  Google Scholar 

  81. 81.

    Niazi S, Khan IM, Yan L, Khan MI, Mohsin A, Duan N, et al. Simultaneous detection of fumonisin B1 and ochratoxin a using dual-color, time-resolved luminescent nanoparticles (NaYF4: Ce, Tb and NH2-Eu/DPA@SiO2) as labels. Anal Bioanal Chem. 2019;411(7):1453–65. https://doi.org/10.1007/s00216-019-01580-0.

    CAS  Article  PubMed  Google Scholar 

  82. 82.

    Yang M, Cui M, Wang W, Yang Y, Chang J, Hao J, et al. Background-free upconversion-encoded microspheres for mycotoxin detection based on a rapid visualization method. Anal Bioanal Chem. 2020;412(1):81–91. https://doi.org/10.1007/s00216-019-02206-1.

    CAS  Article  PubMed  Google Scholar 

  83. 83.

    Xiong Z, Wang Q, Xie Y, Li N, Yun W, Yang L. Simultaneous detection of aflatoxin B1 and ochratoxin a in food samples by dual DNA tweezers nanomachine. Food Chem. 2021;338:128122. https://doi.org/10.1016/j.foodchem.2020.128122.

    CAS  Article  PubMed  Google Scholar 

  84. 84.

    Khan IM, Niazi S, Yu Y, Mohsin A, Mushtaq BS, Iqbal MW, et al. Aptamer induced multicolored auncs-WS2 “turn on” FRET nano platform for dual-color simultaneous detection of aflatoxinb (1) and zearalenone. Anal Chem. 2019;91(21):14085–92. https://doi.org/10.1021/acs.analchem.9b03880.

    CAS  Article  PubMed  Google Scholar 

  85. 85.

    Wang C, Huang X, Tian X, Zhang X, Yu S, Chang X, et al. A multiplexed FRET aptasensor for the simultaneous detection of mycotoxins with magnetically controlled graphene oxide/Fe3O4 as a single energy acceptor. Analyst. 2019;144(20):6004–10. https://doi.org/10.1039/C9AN01593K.

    CAS  Article  PubMed  Google Scholar 

  86. 86.

    Sharma R, Ragavan KV, Abhijith KS, Akanksha, Thakur MS. Synergistic catalysis by gold nanoparticles and metal ions for enhanced chemiluminescence. RSC Adv. 2015;5:31434–8.

    CAS  Article  Google Scholar 

  87. 87.

    Jiang F, Li P, Zong C, Yang H. Surface-plasmon-coupled chemiluminescence amplification of silver nanoparticles modified immunosensor for high-throughput ultrasensitive detection of multiple mycotoxins. Anal Chim Acta. 2020;1114:58–65. https://doi.org/10.1016/j.aca.2020.03.052.

    CAS  Article  PubMed  Google Scholar 

  88. 88.

    Ma C, Cao Y, Gou X, Zhu JJ. Recent progress in electrochemiluminescence sensing and imaging. Anal Chem. 2020;92(1):431–54. https://doi.org/10.1021/acs.analchem.9b04947.

    CAS  Article  PubMed  Google Scholar 

  89. 89.

    Chen X, Liu Y, Ma Q. Recent advances in quantum dot-based electrochemiluminescence sensors. J Mater Chem C. 2018;6(5):942–59. https://doi.org/10.1039/C7TC05474B.

    CAS  Article  Google Scholar 

  90. 90.

    Chen MM, Wang Y, Cheng SB, Wen W, Zhang X, Wang S, et al. Construction of highly efficient resonance energy transfer platform inside a nanosphere for ultrasensitive electrochemiluminescence detection. Anal Chem. 2018;90(8):5075–81. https://doi.org/10.1021/acs.analchem.7b05074.

    CAS  Article  PubMed  Google Scholar 

  91. 91.

    Wei M, Wang C, Xu E, Chen J, Xu X, Wei W, et al. A simple and sensitive electrochemiluminescence aptasensor for determination of ochratoxin a based on a nicking endonuclease-powered DNA walking machine. Food Chem. 2019;282:141–6. https://doi.org/10.1016/j.foodchem.2019.01.011.

    CAS  Article  PubMed  Google Scholar 

  92. 92.

    Sun C, Liao X, Jia B, Shi L, Zhang D, Wang R, et al. Development of a ZnCdS@ZnS quantum dots-based label-free electrochemiluminescence immunosensor for sensitive determination of aflatoxin B1 in lotus seed. Mikrochim Acta. 2020;187(4):236. https://doi.org/10.1007/s00604-020-4179-x.

    CAS  Article  PubMed  Google Scholar 

  93. 93.

    Homola J. Surface plasmon resonance sensors for detection of chemical and biological species. Chem Rev. 2008;108(2):462–93. https://doi.org/10.1021/cr068107d.

    CAS  Article  PubMed  Google Scholar 

  94. 94.

    Joshi S, Annida RM, Zuilhof H, van Beek TA, Nielen MW. Analysis of mycotoxins in beer using a portable nanostructured imaging surface plasmon resonance biosensor. J Agric Food Chem. 2016;64(43):8263–71. https://doi.org/10.1021/acs.jafc.6b04106.

    CAS  Article  PubMed  Google Scholar 

  95. 95.

    Sun L, Wu L, Zhao Q. Aptamer based surface plasmon resonance sensor for aflatoxin B1. Microchim Acta. 2017;184(8):2605–10. https://doi.org/10.1007/s00604-017-2265-5.

    CAS  Article  Google Scholar 

  96. 96.

    Bhardwaj H, Sumana G, Marquette CA. A label-free ultrasensitive microfluidic surface Plasmon resonance biosensor for aflatoxin B1 detection using nanoparticles integrated gold chip. Food Chem. 2020;307:125530. https://doi.org/10.1016/j.foodchem.2019.125530.

    CAS  Article  PubMed  Google Scholar 

  97. 97.

    Kasoju A, Shrikrishna NS, Shahdeo D, Khan AA, Alanazi AM, Gandhi S. Microfluidic paper device for rapid detection of aflatoxin B1 using an aptamer based colorimetric assay. RSC Adv. 2020;10(20):11843–50. https://doi.org/10.1039/D0RA00062K.

    CAS  Article  Google Scholar 

  98. 98.

    Sun S, Zhao R, Feng S, Xie Y. Colorimetric zearalenone assay based on the use of an aptamer and of gold nanoparticles with peroxidase-like activity. Mikrochim Acta. 2018;185(12):535. https://doi.org/10.1007/s00604-018-3078-x.

    CAS  Article  PubMed  Google Scholar 

  99. 99.

    Li J, Cai T, Li W, Li W, Song L, Li Q, et al. Highly sensitive simultaneous detection of multiple mycotoxins using a protein microarray on a tio2-modified porous silicon surface. J Agric Food Chem. 2021;69(1):528–36. https://doi.org/10.1021/acs.jafc.0c06859.

    CAS  Article  PubMed  Google Scholar 

  100. 100.

    Wu Z, He D, Cui B, Jin Z, Xu E, Yuan C, et al. Trimer-based aptasensor for simultaneous determination of multiple mycotoxins using SERS and fluorimetry. Mikrochim Acta. 2020;187(9):495. https://doi.org/10.1007/s00604-020-04487-1.

    CAS  Article  PubMed  Google Scholar 

  101. 101.

    He D, Wu Z, Cui B, Jin Z, Xu E. A fluorometric method for aptamer-based simultaneous determination of two kinds of the fusarium mycotoxins zearalenone and fumonisin B1 making use of gold nanorods and upconversion nanoparticles. Mikrochim Acta. 2020;187(4):254. https://doi.org/10.1007/s00604-020-04236-4.

    CAS  Article  PubMed  Google Scholar 

  102. 102.

    Qian J, Ren C, Wang C, Chen W, Lu X, Li H, et al. Magnetically controlled fluorescence aptasensor for simultaneous determination of ochratoxin a and aflatoxin B1. Anal Chim Acta. 2018;1019:119–27. https://doi.org/10.1016/j.aca.2018.02.063.

    CAS  Article  PubMed  Google Scholar 

  103. 103.

    Niazi S, Khan IM, Yu Y, Pasha I, Shoaib M, Mohsin A, et al. A “turnon” aptasensor for simultaneous and time-resolved fluorometric determination of zearalenone, trichothecenes a and aflatoxin B1 using WS2 as a quencher. Mikrochim Acta. 2019;186(8):575. https://doi.org/10.1007/s00604-019-3570-y.

    CAS  Article  PubMed  Google Scholar 

  104. 104.

    Lv X, Li Y, Yan T, Pang X, Cao W, Du B, et al. Electrochemiluminescence modified electrodes based on RuSi@Ru (bpy)3(2+) loaded with gold functioned nanoporous CO/Co3O4 for detection of mycotoxin deoxynivalenol. Biosens Bioelectron. 2015;70:28–33. https://doi.org/10.1016/j.bios.2015.03.020.

    CAS  Article  PubMed  Google Scholar 

  105. 105.

    Khoshfetrat SM, Bagheri H, Mehrgardi MA. Visual electrochemiluminescence biosensing of aflatoxin M1 based on luminol-functionalized, silver nanoparticle-decorated graphene oxide. Biosens Bioelectron. 2018;100:382–8. https://doi.org/10.1016/j.bios.2017.09.035.

    CAS  Article  PubMed  Google Scholar 

  106. 106.

    Wei T, Ren P, Huang L, Ouyang Z, Wang Z, Kong X, et al. Simultaneous detection of aflatoxin B1, ochratoxin a, zearalenone and deoxynivalenol in corn and wheat using surface plasmon resonance. Food Chem. 2019;300:125176. https://doi.org/10.1016/j.foodchem.2019.125176.

    CAS  Article  PubMed  Google Scholar 

  107. 107.

    Moon J, Byun J, Kim H, Lim EK, Jeong J, Jung J, et al. On-site detection of aflatoxin b1 in grains by a palm-sized surface plasmon resonance sensor. Sensors. 2018;18:598. https://doi.org/10.3390/s18020598.

  108. 108.

    Zhu Z, Feng M, Zuo L, Zhu Z, Wang F, Chen L, et al. An aptamer based surface plasmon resonance biosensor for the detection of ochratoxin a in wine and peanut oil. Biosens Bioelectron. 2015;65:320–6. https://doi.org/10.1016/j.bios.2014.10.059.

    CAS  Article  PubMed  Google Scholar 

  109. 109.

    Li Y, Wang Z, Sun L, Liu L, Xu C, Kuang H. Nanoparticle-based sensors for food contaminants. TrAC Trend Anal Chem. 2019;113:74–83. https://doi.org/10.1016/j.trac.2019.01.012.

    CAS  Article  Google Scholar 

  110. 110.

    Yang X, Zhou X, Zhang X, Qing Y, Luo M, Liu X, et al. A highly sensitive electrochemical immunosensor for fumonisin b1detection in corn using single-walled carbon nanotubes/chitosan. Electroanalysis. 2015;27(11):2679–87. https://doi.org/10.1002/elan.201500169.

    CAS  Article  Google Scholar 

  111. 111.

    Jiang M, Braiek M, Florea A, Chrouda A, Farre C, Bonhomme A, et al. Aflatoxin B1 detection using a highly-sensitive molecularly-imprinted electrochemical sensor based on an electropolymerized metal organic framework. Toxins. 2015;7:3540–53.

    CAS  Article  Google Scholar 

  112. 112.

    Jiang K, Nie D, Huang Q, Fan K, Tang Z, Wu Y, et al. Thin-layer MoS2 and thionin composite-based electrochemical sensing platform for rapid and sensitive detection of zearalenone in human biofluids. Biosens Bioelectron. 2019;130:322–9. https://doi.org/10.1016/j.bios.2019.02.003.

    CAS  Article  PubMed  Google Scholar 

  113. 113.

    Zhong H, Yu C, Gao R, Chen J, Yu Y, Geng Y, et al. A novel sandwich aptasensor for detecting T-2 toxin based on rGO-TEPA-au@Pt nanorods with a dual signal amplification strategy. Biosens Bioelectron. 2019;144:111635. https://doi.org/10.1016/j.bios.2019.111635.

    CAS  Article  PubMed  Google Scholar 

  114. 114.

    Rusling JF, Bishop GW, Doan NM, Papadimitrakopoulos F. Nanomaterials and biomaterials in electrochemical arrays for protein detection. J Mater Chem B. 2014;2(1):12–30. https://doi.org/10.1039/C3TB21323D.

    CAS  Article  Google Scholar 

  115. 115.

    Beitollahi H, Mohammadi SZ, Safaei M, Tajik S. Applications of electrochemical sensors and biosensors based on modified screen-printed electrodes: a review. Anal Methods. 2020;12(12):1547–60. https://doi.org/10.1039/C9AY02598G.

    Article  Google Scholar 

  116. 116.

    Ben Abdallah Z, Grauby-Heywang C, Beven L, Cassagnere S, Moroté F, Maillard E, et al. Development of an ultrasensitive label-free immunosensor for fungal aflatoxin B1 detection. Biochem Eng J. 2019;150:107262. https://doi.org/10.1016/j.bej.2019.107262.

    CAS  Article  Google Scholar 

  117. 117.

    Yugender Goud K, Sunil Kumar V, Hayat A, Vengatajalabathy Gobi K, Song H, Kim KH, et al. A highly sensitive electrochemical immunosensor for zearalenone using screen-printed disposable electrodes. J Electroanal Chem. 2019;832:336–42. https://doi.org/10.1016/j.jelechem.2018.10.058.

    CAS  Article  Google Scholar 

  118. 118.

    Reverte L, Prieto SB, Campas M. New advances in electrochemical biosensors for the detection of toxins: nanomaterials, magnetic beads and microfluidics systems. A review. Anal Chim Acta. 2016;908:8–21. https://doi.org/10.1016/j.aca.2015.11.050.

    CAS  Article  PubMed  Google Scholar 

  119. 119.

    Lu L, Gunasekaran S. Dual-channel ITO-microfluidic electrochemical immunosensor for simultaneous detection of two mycotoxins. Talanta. 2019;194:709–16. https://doi.org/10.1016/j.talanta.2018.10.091.

    CAS  Article  PubMed  Google Scholar 

  120. 120.

    Zhu C, Liu D, Li Y, Ma S, Wang M, You T. Hairpin DNA assisted dual-ratiometric electrochemical aptasensor with high reliability and anti-interference ability for simultaneous detection of aflatoxin B1 and ochratoxin a. Biosens Bioelectron. 2021;174:112654. https://doi.org/10.1016/j.bios.2020.112654.

    CAS  Article  PubMed  Google Scholar 

  121. 121.

    Wei M, Xin L, Feng S, Liu Y. Simultaneous electrochemical determination of ochratoxin a and fumonisin B1 with an aptasensor based on the use of a Y-shaped DNA structure on gold nanorods. Mikrochim Acta. 2020;187(2):102. https://doi.org/10.1007/s00604-019-4089-y.

    CAS  Article  PubMed  Google Scholar 

  122. 122.

    Han Z, Tang Z, Jiang K, Huang Q, Meng J, Nie D, et al. Dual-target electrochemical aptasensor based on co-reduced molybdenum disulfide and au NPs (rMoS2-au) for multiplex detection of mycotoxins. Biosens Bioelectron. 2020;150:111894. https://doi.org/10.1016/j.bios.2019.111894.

    CAS  Article  PubMed  Google Scholar 

  123. 123.

    Li Y, Liu D, Zhu C, Shen X, Liu Y, You T. Sensitivity programmable ratiometric electrochemical aptasensor based on signal engineering for the detection of aflatoxin B1 in peanut. J Hazard Mater. 2020;387:122001. https://doi.org/10.1016/j.jhazmat.2019.122001.

    CAS  Article  PubMed  Google Scholar 

  124. 124.

    El Alami El Hassani N, Bouchikhi B, El Bari N. Recent development of an electrochemical imprinted sensor for the detection of trace-level of unmetabolized aflatoxin B2 in dairy milk. J Electroanal Chem. 2020;865:114123. https://doi.org/10.1016/j.jelechem.2020.114123.

  125. 125.

    Sun C, Liao X, Huang P, Shan G, Ma X, Fu L, et al. A self-assembled electrochemical immunosensor for ultra-sensitive detection of ochratoxin a in medicinal and edible malt. Food Chem. 2020;315:126289. https://doi.org/10.1016/j.foodchem.2020.126289.

    CAS  Article  PubMed  Google Scholar 

  126. 126.

    Costa MP, Frías IAM, Andrade CAS, Oliveira MDL. Impedimetric immunoassay for aflatoxin B1 using a cysteine modified gold electrode with covalently immobilized carbon nanotubes. Microchim Acta. 2017;184(9):3205–13. https://doi.org/10.1007/s00604-017-2308-y.

    CAS  Article  Google Scholar 

  127. 127.

    Xu W, Qing Y, Chen S, Chen J, Qin Z, Qiu J, et al. Electrochemical indirect competitive immunoassay for ultrasensitive detection of zearalenone based on a glassy carbon electrode modified with carboxylated multi-walled carbon nanotubes and chitosan. Microchim Acta. 2017;184(9):3339–47. https://doi.org/10.1007/s00604-017-2342-9.

    CAS  Article  Google Scholar 

  128. 128.

    Kunene K, Weber M, Sabela M, Voiry D, Kanchi S, Bisetty K, et al. Highly-efficient electrochemical label-free immunosensor for the detection of ochratoxin a in coffee samples. Sensors Actuators B Chem. 2020;305:127438. https://doi.org/10.1016/j.snb.2019.127438.

    CAS  Article  Google Scholar 

  129. 129.

    Bhardwaj H, Pandey MK, Rajesh, Sumana G. Electrochemical aflatoxin B1 immunosensor based on the use of graphene quantum dots and gold nanoparticles. Mikrochim Acta. 2019;186:592.

    Article  Google Scholar 

  130. 130.

    Wang C, Qian J, An K, Huang X, Zhao L, Liu Q, et al. Magneto-controlled aptasensor for simultaneous electrochemical detection of dual mycotoxins in maize using metal sulfide quantum dots coated silica as labels. Biosens Bioelectron. 2017;89:802–9. https://doi.org/10.1016/j.bios.2016.10.010.

    CAS  Article  PubMed  Google Scholar 

  131. 131.

    Wang C, Li Y, Zhao Q. A signal-on electrochemical aptasensor for rapid detection of aflatoxin B1 based on competition with complementary DNA. Biosens Bioelectron. 2019;144:111641. https://doi.org/10.1016/j.bios.2019.111641.

    CAS  Article  PubMed  Google Scholar 

  132. 132.

    Azri FA, Eissa S, Zourob M, Chinnappan R, Sukor R, Yusof NA, et al. Electrochemical determination of zearalenone using a label-free competitive aptasensor. Mikrochim Acta. 2020;187(5):266. https://doi.org/10.1007/s00604-020-4218-7.

    CAS  Article  PubMed  Google Scholar 

  133. 133.

    Jahangiri-Dehaghani F, Zare HR, Shekari Z. Measurement of aflatoxin M1 in powder and pasteurized milk samples by using a label-free electrochemical aptasensor based on platinum nanoparticles loaded on Fe-based metal-organic frameworks. Food Chem. 2020;310:125820. https://doi.org/10.1016/j.foodchem.2019.125820.

    CAS  Article  PubMed  Google Scholar 

  134. 134.

    Radi AE, Eissa A, Wahdan T. Molecularly imprinted impedimetric sensor for determination of mycotoxin zearalenone. Electroanalysis. 2020;32(8):1788–94. https://doi.org/10.1002/elan.201900528.

    CAS  Article  Google Scholar 

  135. 135.

    Radi AE, Eissa A, Wahdan T. Impedimetric sensor for deoxynivalenol based on electropolymerised molecularly imprinted polymer on the surface of screen-printed gold electrode. Int J Environ Anal Chem. 2019:1–12. https://doi.org/10.1080/03067319.2019.1699548.

  136. 136.

    Zhou Q, Tang D. Recent advances in photoelectrochemical biosensors for analysis of mycotoxins in food. TrAC Trend Anal Chem. 2020;124:115814. https://doi.org/10.1016/j.trac.2020.115814.

    CAS  Article  Google Scholar 

  137. 137.

    Zhang B, Lu Y, Yang C, Guo Q, Nie G. Simple “signal-on” photoelectrochemical aptasensor for ultrasensitive detecting AFB1 based on electrochemically reduced graphene oxide/poly (5-formylindole)/au nanocomposites. Biosens Bioelectron. 2019;134:42–8. https://doi.org/10.1016/j.bios.2019.03.048.

    CAS  Article  PubMed  Google Scholar 

  138. 138.

    Mao L, Wang X, Guo Y, Yao L, Xue X, Wang HX, et al. A synergistic approach to enhance the photoelectrochemical performance of carbon dots for molecular imprinting sensors. Nanoscale. 2019;11(16):7885–92. https://doi.org/10.1039/C9NR01675A.

    CAS  Article  PubMed  Google Scholar 

  139. 139.

    Mao L, Ji K, Yao L, Xue X, Wen W, Zhang X, et al. Molecularly imprinted photoelectrochemical sensor for fumonisin B1 based on GO-CdS heterojunction. Biosens Bioelectron. 2019;127:57–63. https://doi.org/10.1016/j.bios.2018.11.040.

    CAS  Article  PubMed  Google Scholar 

  140. 140.

    Ge L, Liu Q, Hao N, Kun W. Recent developments of photoelectrochemical biosensors for food analysis. J Mater Chem B. 2019;7(46):7283–300. https://doi.org/10.1039/C9TB01644A.

    CAS  Article  PubMed  Google Scholar 

  141. 141.

    Xu Z, Long LL, Chen YQ, Chen ML, Cheng YH. A nanozyme-linked immunosorbent assay based on metal-organic frameworks (MOFs) for sensitive detection of aflatoxin B1. Food Chem. 2021;338:128039. https://doi.org/10.1016/j.foodchem.2020.128039.

    CAS  Article  PubMed  Google Scholar 

  142. 142.

    Dong J, Zhao D, Lu Y, Sun W-Y. Photoluminescent metal–organic frameworks and their application for sensing biomolecules. J Mater Chem A. 2019;7(40):22744–67. https://doi.org/10.1039/C9TA07022B.

    CAS  Article  Google Scholar 

  143. 143.

    Safaei M, Foroughi MM, Ebrahimpoor N, Jahani S, Omidi A, Khatami M. A review on metal-organic frameworks: synthesis and applications. TrAC Trend Anal Chem. 2019;118:401–25. https://doi.org/10.1016/j.trac.2019.06.007.

    CAS  Article  Google Scholar 

  144. 144.

    Hu Z, Lustig WP, Zhang J, Zheng C, Wang H, Teat SJ, et al. Effective detection of mycotoxins by a highly luminescent metal-organic framework. J Am Chem Soc. 2015;137(51):16209–15. https://doi.org/10.1021/jacs.5b10308.

    CAS  Article  PubMed  Google Scholar 

  145. 145.

    Li Z, Xu X, Fu Y, Guo Y, Zhang Q, Zhang Q, et al. A water-stable luminescent metal–organic framework for effective detection of aflatoxin B1 in walnut and almond beverages. RSC Adv. 2019;9(2):620–5. https://doi.org/10.1039/C8RA07804A.

    CAS  Article  Google Scholar 

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Funding

The financial support from the National Key Research and Development Program of China (2017YFC1600300).

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RL wrote the manuscript. YW and FW revised the manuscript. PL revised and finalized the manuscript. All authors read and approved the final manuscript.

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Correspondence to Pingli He.

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Li, R., Wen, Y., Wang, F. et al. Recent advances in immunoassays and biosensors for mycotoxins detection in feedstuffs and foods. J Animal Sci Biotechnol 12, 108 (2021). https://doi.org/10.1186/s40104-021-00629-4

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Keywords

  • Biosensors
  • Immunoassays
  • Multiple detection
  • Mycotoxins
  • Nanomaterials
  • Rapid detection