Multi-residue detection of pesticides using a sensitive immunochip assay based on nanogold enhancement

Analytica Chimica Acta xxx (2016) 1e10

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Multi-residue detection of pesticides using a sensitive immunochip assay based on nanogold enhancement Meijing Lan a, Yirong Guo a, *, Ying Zhao a, Yihua Liu a, b, Wenjun Gui a, Guonian Zhu a a b

Institute of Pesticide and Environmental Toxicology, Zhejiang University, 310058 Hangzhou, China Research Institute of Subtropical Forestry, Chinese Academy of Forestry, 311400 Fuyang, China

h i g h l i g h t s

g r a p h i c a l a b s t r a c t


A colorimetric immunochip assay for simultaneous detection of seven pesticides.
Nanogold was adopted for signal enhancement in the competitive immunoassay.
The sensitivity was comparable to that of enzyme-labeled monoplex immunoassay.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 14 June 2016 Received in revised form 28 July 2016 Accepted 30 July 2016 Available online xxx

This paper describes the development of a new multiplex immunoassay for simultaneous detection of seven pesticides (triazophos, methyl-parathion, fenpropathrin, carbofuran, thiacloprid, chlorothalonil, and carbendazim). Sixteen pairs of pesticide antibodies and antigens were screened for reactivity and cross-reaction. A microarray chip consisting of seven antigens immobilized on a nitrocellulose membrane was then constructed. Nanogold was employed for labeling and signal amplification to obtain a sensitive colorimetric immunoassay. The direct and indirect detection formats were further compared using primary antibody-gold and secondary antibody-gold conjugates as tracers. An integrated 7-plex immunochip assay based on the indirect model was established and optimized. The detection limits for the pesticides were 0.02e6.45 ng mL1, which meets detection requirements for pesticide residues. Naked-eye assessment showed the visual detection limits of the assay ranged from 1 to 100 ng mL1. Spiked recovery results demonstrated that the immunochip assay had potential for multi-analysis of pesticide residues in vegetables and fruits. The proposed microarray methodology is a flexible and versatile tool, which can be applied to other competitive multiplex immunoassays for small molecular compounds. © 2016 Elsevier B.V. All rights reserved.

Keywords: Pesticides Multi-residue Microarray Immunoassay Gold nanoparticles

1. Introduction During the growth period of agricultural plants, various

* Corresponding author. E-mail address: [email protected] (Y. Guo).

pesticides and mixtures thereof are widely used to prevent pest and disease damage. Accordingly, the effects of pesticide multi-residues in the environment and food products on public health become a global concern. Therefore, a simple and sensitive method or device for simultaneous detection of multiple pesticides is needed for practical surveillance. Immunoassays detect pesticides efficiently with high selectivity,

http://dx.doi.org/10.1016/j.aca.2016.07.044 0003-2670/© 2016 Elsevier B.V. All rights reserved.

Please cite this article in press as: M. Lan, et al., Multi-residue detection of pesticides using a sensitive immunochip assay based on nanogold enhancement, Analytica Chimica Acta (2016), http://dx.doi.org/10.1016/j.aca.2016.07.044

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M. Lan et al. / Analytica Chimica Acta xxx (2016) 1e10

sensitivity, and rapidity when used in parallel with classical chromatographic techniques. In addition, immunoassays are particularly fit for large-scale screening. Recent years have witnessed considerable progress among various types of immunoassays for pesticide detection, and the current trend is to develop a multianalyte immunoassay that can simultaneously identify and/or quantify more than two analytes in a single application. Two strategies are usually employed to prepare a multi-analyte immunoassay for pesticides: group-specific/broad-selective antibodies (Abs) or combinations of analyte-specific Abs (multi-Ab approach) [1]. The former is useful for determining the gross amount of several structurally similar pesticides, but cannot distinguish individual compounds [2]. The multi-Ab strategy is more flexible, and its assay platform is generally classified into suspension array (multi-marker mode) and planar array (spatial-resolved mode) [3]. The critical request for this strategy is to avoid shared-reactivity or cross-reaction, i.e., each Ab should only recognize its own antigen (Ag) and analyte, and there should be no interferences to other AgAb-analyte reactions within the same array. To date, however, there have been few reports on multi-analysis of pesticides by suspension array [4e7], probably because this technique depends on expensive instruments and fluorescent microspheres for signal measurement. By contrast, a planar array is much easier to obtain and use. Over the past decade, related studies have been increasingly reported, mainly using multi-line lateral flow immunostrips and multi-channel immunosensors [8]. For instance, a triplex immunoassay was developed for simultaneous detection of three pesticides, based on three competitive immunoreactions [9]. Nonetheless, limited multiplex capability is the main bottleneck of multi-analyte immunoassays. Planar microarray-based immunoassays with advantages of high-throughput and efficiency, have been increasingly developed as diagnostic tools, on the principle that immunoassay miniaturization offers high sensitivity and reduced reaction times because of shortened diffusion distances [10]. Such approach is considered as an immunochip technique, because diverse Abs or Ags are immobilized on planar supports. Microarray platforms have been explored mainly for medical applications, but have been applied in other fields, such as environmental monitoring and food control. To analyze small-molecular pollutants by competitive immunochip assays, Ags are commonly coated on the surface support such as modified glass slide [11,12], porous membrane [13,14], adhesive surface [15], and compact disk [16,17]. However, most previous reports on pesticide immunochips had limited targets, and the integration of more than five Ag/Ab pairs was rare for pesticidetargeted multi-analyte immunoassays. Recently, Dobosz et al. [18] developed a 10-plex immunochip assay to simultaneously determine 10 pesticide residues in water samples, by use of compact disks and a portable disk player detector. It is currently the most multiplexed immunoassay for pesticides from different chemical families. However, owing to the polycarbonate surface of the compact disks, the adsorption of protein is less efficient than with porous material, such as nitrocellulose (NC) membrane, which is a gold standard support for colorimetry-based methods. Immunoassays using porous membranes as solid phases are convenient and popular for field tests. These have 3D porous networks with large surface areas that enable to immobilize big amounts of accessible probes (large binding capacity), and can be used directly, without surface activation [19]. Among membranebased colorimetric immunoassays, colloidal gold is one of the most popular labels, though silver enhancement is usually performed to improve assay sensitivity. Nevertheless, a high background would likely appear because of the disadvantage of silver autonucleation. In addition, the time control of silver staining is crucial for detection sensitivity. By comparison, gold enhancement

presents lower backgrounds and better signal amplification owing to minimal autonucleation [20]. However, nanogold enhancers for signal amplification are scarcely applied in competitive immunoassays for sensitive detection of small chemicals. In the present work, we first report a NC membrane-based colorimetric immunochip assay for multi-residue pesticide detection, using secondary Ab-gold conjugate as a universal reporter and nanogold deposition for signal enhancement. The methodology was further verified by spiked recovery tests with vegetable and fruit samples, showing its potential for screening multiple pesticide residues in agricultural products. 2. Materials and methods 2.1. Reagents and materials Goat anti-mouse IgG and rabbit anti-goat IgG were obtained from Jiening Biological Technology (Shanghai, China). Pesticide standards were provided by Zhejiang Provincial Center for Disease Control and Prevention (Hangzhou, China). NH2OH$HCl, 2-(Nmorpholino) ethanesulfonic acid (MES), and bovine serum albumin (BSA) were supplied by Sangon (Shanghai, China). Chloroauric acid and a commercial silver enhancer kit (SE100) were purchased from Sigma-Aldrich (St. Louis, USA). Cleanert PSA (primary secondary amine) sorbent was obtained from Agela technologies (Tianjin, China). Methanol and acetonitrile of HPLC grade were obtained from Shanghai Zhenxing No.1 Chemical Plant (Shanghai, China). Buffer solutions were prepared with ultrapure water from a water purification system (Pall Corporation, USA). Other chemicals and solvents were of analytical grade or better. NH2OH$HCl gold enhancer solution was prepared with 1:1 (v:v) mixture of 40 mM NH2OH$HCl (pH 6.0) and 1% (w:v) HAuCl4. MESH2O2 gold enhancer solution was prepared with 2:3:5 (v:v:v) mixture of 4% (w:v) HAuCl4, 30% (w:w) H2O2, and 25 mM MES (pH 6.0). Phosphate buffered saline (PBS, 0.01 M, pH 7.4, comprising 7 mM Na2HPO4, 1.5 mM KH2PO4, 0.137 M NaCl, and 2.7 mM KCl) was self-prepared. Stock solution of each pesticide standard (1 mg/ mL) was prepared with pure methanol. Standard working solutions of various concentrations were diluted with 20% (v:v) methanolPBS when used in the immunochip analysis, concerning the solubility of all detected pesticides and the performance of multianalyte immunoassay. Most of the pesticide Ags and Abs were prepared in our laboratory [21,22]. Ags and Abs of imidaclothiz and thiacloprid were gifts from Nanjing Agricultural University (Nanjing, China), and those of chlorothalonil and carbendazim were supplied by Jiangnan University (Wuxi, China). All the Ags were conjugates of pesticide hapten-ovalbumin (OVA), for coating on the surface support. Nitrocellulose (NC) membrane (pore diameter 0.22 mm, high surface area) was purchased from Sartorius (Germany). Cucumber, Chinese cabbage, tomato, apple, and pear were collected from the local Walmart supermarket. 2.2. Screening of pesticide Ags and Abs Sensitivity and specificity of each Ab were first characterized by competitive indirect enzyme-linked immunosorbent assay (iELISA), based on the relevant coating Ag, using the target pesticide and its analogues as analytes. The procedures were described in detail in our previous work [22]. Each Ab should specifically recognize its own coating Ag, without significant cross-reaction with other coating Ags, to fulfill the purpose of multi-analyte immunoassay. The shared-reactivity among coating Ags and Abs was evaluated with non-competitive hybridization-based iELISA by measuring optical density (OD) at

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490 nm. Excluding the corresponding Ag/Ab pairs marked as 100%, all other shared-reactivity values were calculated using equation (1), i.e., ratio of OD between the two hybridization signals:

Shared  reactivityð%Þ ¼

ODantibodycorresponding antigen  100% ODantibodyuncorresponding antigen (1)

2.3. Preparation of colloidal gold-labeled antibodies The preparation of gold nanoparticles (AuNPs) of 20 nm average diameter and AuNP-antibody conjugates was accomplished according to the methods used in our previous works [23,24]. 2.4. Immunochip fabrication The NC membrane was first cut to an appropriate size. Then, the probes covering each Ag (capture probe), goat anti-mouse IgG (secondary Ab, positive control) and 0.01 M PBS buffer (blank, negative control), were spotted on the membrane carrier according to a particular array. The volume of each probe was 0.5 mL. After coating in an incubator (37  C) for 30 min, the immunochip was blocked with 10% (w:v) BSA in PBST (0.01 M PBS containing 0.05% (v:v) Tween 20, pH 7.4) at 37  C for another 30 min to minimize the nonspecific binding. Afterward, the chip was washed thoroughly with PBST, and it was dried for standby application. 2.5. Procedure of immunochip assay The immunochip test was based on the competitive inhibitory interaction. Pesticides in the samples and Ags coated on the membrane were individually recognized by their corresponding antibodies in the mixed reaction buffer. We compared two competitive models: direct model (primary Ab-AuNP conjugate) and indirect model (secondary Ab-AuNP conjugate). For the direct model (Fig. 1B), the sample solutions (prepared with 20% methanol-PBS) were directly mixed with primary AbAuNP conjugates. The pre-coated immunochip was then submerged in the mixture for 30 min under low-frequency oscillation. After thorough washing with PBST, the immunochip was treated with a gold enhancer solution at room temperature for 10 min, and it was then dipped into the ultrapure water to stop the reaction. Once dry, the immunochip was imaged in grayscale with ChemiDoc™ MP Imaging System (Bio-Rad Laboratories, California, USA). For the indirect model (Fig. 1A), immunochip construction was similar to that for the direct model, expect that rabbit anti-goat IgG was spotted as the positive control. For the test, the mixture of sample solutions with the primary Ab cocktails was added to the pre-coated immunochip for 30 min under low-frequency oscillation. After washing, the immunochip was immersed in the solution of secondary Ab-AuNP conjugate for another 30 min. The steps that followed were the same as described for the direct model. 2.6. Quantitative analysis Image analysis and signal quantification were performed with Image Lab 5.2 Software (Bio-Rad). The calibrated signal intensity of each Ag probe was defined as IA (absolute signal intensity of Ag microdot) minus IB (absolute signal intensity of background). All signal intensity results were obtained through the average values of two parallel microdots in the same array. The data of pesticide concentration and calibrated signal intensity were fitted into sigmoidal curves using the four-parameter logistic function of OriginPro 8.5.

3

Assay sensitivity and limit of detection (LOD) were respectively based on IC50 (50% inhibitory concentration) and IC10 (10% inhibitory concentration) values, which were calculated according to standard calibration curves. The visual limit of detection (vLOD) or semi-quantitative value using the naked eyes was defined as the minimum pesticide concentration that obviously weakened the Ag probe color compared with that of the positive control. Assay selectivity was assessed by cross-reactivities between analytes and other analogues, based on the following formula: cross-reactivity ¼ [(IC50 of target analyte)/(IC50 of other analogues)]  100%. 2.7. Recovery test of spiked samples Spiked recovery tests of cucumber, Chinese cabbage, tomato, apple, and pear samples were used to evaluate the applicability of the novel immunochip assay. Pesticide-free blank samples were confirmed by mass spectrometer. Following homogenization, each sample (10.0 g) was fortified with different levels of mixed pesticide standards in methanol and allowed to stand at room temperature overnight. Vegetable and fruit samples were treated with QuEChERS (Quick, Easy, Cheap, Rugged, Effective, and Safe) extraction method, which is widely used for preparing samples for analysis of multiclass pesticide residues [25]. Acetonitrile (10.0 mL) was added to each sample, and the mixture was vigorously shaken for 2 min using a vortex mixer. Next, 4.0 g anhydrous MgSO4 and 1.0 g NaCl were added, followed by shaking for another 1 min. Following centrifugation at 4000 rpm for 5 min, 1.0 mL of the upper layer was transferred to a micro-tube containing 25 mg PSA and 0.15 g anhydrous MgSO4. After 30 s shaking and 1 min centrifugation, 0.5 mL of the supernatant was transferred to a glass tube and evaporated under a nitrogen stream at 40  C. The dried residue was redissolved with a certain volume of 20% methanol-PBS and the diluted sample liquid was tested with the immunochip assay. 3. Results and discussion 3.1. Specific Ag-Ab pairs for the multiplex immunochip In the current study, the multi-target analytes were various types of insecticides or fungicides commonly used in agricultural fields. Developing a competitive multi-analyte immunoassay involves the integration of multiple combinations of Ag-Ab-analyte, with each combination having its own optimal working conditions [15]. Therefore, the first priority was to select the proper immunoreagents from a pool of anti-pesticide Abs and their related Ags. Table S1 lists characteristics of the collected 16 pairs of Ag-Ab, including the Ab type (monoclonal/mAb or poloclonal/pAb), hapten structure, assay sensitivity (evaluated by competitive iELISA) and selectivity (less than 10% cross-reactivity with related analogs was not shown). Most of the tested Abs were highly sensitive and specific to the corresponding pesticides, although some Abs displayed broad-specificity to 2e3 pesticides that had structural similarities. In a multiplexed immunoassay, as the number of target analytes increases, the chance to accomplish a highly selective multi-analyte assay decreases, as non-specific binding signals tend to appear. Since mixed Abs can contact all Ags coated on the membrane carrier, highly specific Abs, without any shared reaction to the unrelated Ags, are required to attain simultaneous detection of multiple analytes. Fig. 2A shows possible phenomena during the multiplexed non-competitive immunoassay, including ideal and undesirable situations. Hence, we carried out a screening test of the AgAb cross-reaction by non-competitive hybridization-based iELISA

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Fig. 1. Schematic illustration of two models for simultaneous detection of seven pesticides by the competitive immunochip assay. Seven kinds of coating Ags, primary Abs, and target analytes are respectively present in seven different colors.

to choose suitable Ag-Ab pairs for immunochip integration. The tested shared-reactivity should be similarly applicable, considering that membrane-based immunoassays are similar to iELISAs in principle. Fig. 2B shows the various levels of cross-reactions among the collected Ag-Ab pairs. Compared with mAbs, pAbs were likely to have stronger shared-reactivity to uncorresponding Ags, which agreed with the findings of a recent multi-residue immunoassay report [18]. Concretely, the pAbs of CHBu, imidacloprid, and thiacloprid could nearly recognize other pesticide hapten-OVA conjugates to different extents, excluding chlorothalonil and carbendazim. This phenomenon may be ascribed to the common moiety of the spacer arm e(CH2)nCOOH in these various pesticide haptens (see Table S1), which may cause cross-reactions because of the nature of pAbs. However, anti-chlorpyrifos mAbs 13H11 and 13C7 also brought certain degrees of shared-reactivity to the other organophosphorus hapten-OVA conjugates, and CHBu-13H11 mAb even recognized BFNB-OVA very well. The unexpected results could be attributed to the same spacer arm involved with the Ag conjugates, which also contributed to the Ag-Ab binding. Note that specific mAbs should be selected carefully, based on different heterologous coating Ags, particularly for developing multiplexed immunoassays. Additionally, greater similarity of chemical structures between the target and non-target haptens led to higher probability of

shared reactions among Ags and Abs. This is easily predicted according to the features of Ags and Abs. For instance, anti-parathion mAbs PA-7C2, PA-2G6, and PA-7B2 had very high shared-reactivity to M1605-OVA (Ag of methyl-parathion). As the spacer arm position in PA0314-OVA was different from those of haptens PA0304OVA and M1605-OVA, mAb M1605 only displayed obvious shared-reactivity to PA0304-OVA. Therefore, either mAb M1605 or mAb PA could be used in the multiplex immunochip. As for the sensitivity to methyl-parathion, mAb PA-7B2 offered the lowest IC50 value. Considering both sensitivity and recognition spectrum, the broad-specific mAb PA-7B2 was selected for detecting methylparathion, parathion, and fenitrothion. A previous study indicated that <10% shared-reactivity could be ignored in multiplexed immunoassays [26]. Thus, after a series of comparisons, the mAb/Ag pairs THHE-8C10/THBU-OVA (abbreviated as “T”), PA-7B2/PA0304-OVA (MP), NC-S-2-1C3/NC-S-2-OVA (N), BFNB-C8/BFNB-OVA (BN), thiacloprid mAb/thiacloprid-OVA (S), chlorothalonil mAb/chlorothalonil-OVA (BJ), and carbendazim mAb/carbendazim-OVA (D), were selected as immunoreagent candidates for fabricating the immunochip. 3.2. Signal enhancement for the colorimetric immunoassay Gold nano-materials have been extensively investigated and play a major role in analytical applications. Signal enhancement is a

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Fig. 2. Shared-reactivity of Ag-Ab pairs evaluated by non-competitive iELISAs. (A) Schematic of possible Ag-Ab reactions; (B) results of mutual hybridizations among 16 Abs and 12 Ags.

helpful procedure for improving the sensitivity of gold-based assays. Previous reports concluded that gold deposition enhanced detection sensitivity more than the typical silver deposition [27,28]. This study employed the conventional method of silver staining for signal amplification, as well as gold reduction and deposition [29,30], to enlarge immunogold particles. We first used the pair T for comparison testing. After the direct reaction between Ag (THBU-OVA, different amounts) coated on the NC membrane and gold-labeled THHE-8C10 mAb (50 times dilution), the fresh prepared NH2OH$HCl and MES-H2O2 gold enhancer solutions were respectively added for 10 min. The silver enhancer solution was used for 15 min, according to the commercial kit's instructions. Fig. 3 shows signal intensity enhancement was practically the same among silver staining for 15 min, NH2OH$HCl gold enhancing for 10 min, and MES-H2O2 gold enhancing for 10 min. In other words, gold enhancement proved more efficient than silver enhancement, and it helped to shorten the total time of the assay. This was attributable to gold-enhanced particles being much larger than those enhanced by silver, owing to the unique growth mechanism of gold deposition, that is, the continuous clustering of new AuNPs on the immunogold surface and little autonucleation in solution [28,31]. The NH2OH$HCl gold enhancer solution was chosen as it offered

the most advantages with regard to reagent cost, time consumption, and complexity of preparation. Considering that HAuCl4 is the source of Au3þ ions and is reduced to the bulk metal (new AuNPs), its content should be further optimized. Table S2 shows that, when coated with higher concentrations of THBU-OVA (312.5e10,000 mg/ L), 0.031%e0.25% of HAuCl4 played an important role in the signal enhancement (P < 0.05). However, there was no significant difference in signal intensity as HAuCl4 content increased from 0.25% to 1%. Therefore, a mixture of 0.25% HAuCl4 and 40 mM NH2OH$HCl was adopted as the enhancer solution in the following experiments. 3.3. Immunochip assay development and optimization To establish the immunochip assay, two types of detection model (direct and indirect competitive immunoassays, Fig. 1) were investigated and compared. We first tried the direct model by using cocktails of gold-labeled primary Abs. However, it was difficult to optimize the working concentration of each mAb-AuNP conjugate and coating Ag, since color intensity of the positive control (goat anti-mouse IgG at 80 mg/L) was always much stronger than those of the Ag spots (even using a high amount of Ag). This phenomenon may be attributable to the higher affinity of goat anti-mouse IgG with primary mouse mAbs, compared to coating Ags. Moreover,

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Silver enhancer 15 min NH2OH·HCl gold enhancer 10 min MES-H2O2 gold enhancer 10 min

30000

25000

Intensity

20000

15000

10000

5000

0 10000

5000

2500

1250

625

312

156

78

39

-1

THBU-OVA concentration (mg L ) Fig. 3. Comparison of three enhancer solutions for signal amplification (n ¼ 3). Taken the pair T for the model, different amounts of THBU-OVA were coated on the NC membrane and 50 times dilution of gold-labeled THHE-8C10 mAb was added for the direct non-competitive immunoreactions. After washing, three kinds of enhancer solutions were individually used. The color development was respectively stopped after silver staining for 15 min, NH2OH$HCl or MES-H2O2 gold enhancing for 10 min.

using primary Ab-AuNP conjugates may introduce conflicts in competitive immunoassays, because fewer primary Abs (high dilution of the conjugates) is preferred for improving the inhibition from the free analyte, which in turn will lead to reduced signals from labels and affect the method performance [32]. Therefore, we ceased further attempts on the direct model, despite its timesaving advantage in principle. In contrast, despite needing an additional step for secondary Ab reaction, the indirect model possessed many remarkable advantages. As listed in Table S3, it reduced consumption of Ag and Ab, and the assay sensitivity increased substantially (IC50 increased from 6.6 ng mL1 to 1.6 ng mL1 for triazophos; from undetectable (46.5% inhibition at 1 mg L1) to 2.5 ng mL1 for fenpropathrin). This phenomenon may be due to the amplification role of the secondary Ab-AuNP conjugate. Furthermore, separating the labeling and interaction stages in competitive immunoassays allows primary Abs to be decreased, as the detection limit is no longer constrained by the need to maintain sufficient gold labels [32]. Additionally, the indirect model avoids individualized preparations for each primary Ab-AuNP conjugate, as different Abs may vary slightly in features, such as isotype. Thus, the indirect model is easier to use than the direct model for multiplexed assay development and optimization, and it was employed as the detection model for the immunochip assay. Determining the optimal concentration for each Ag or Ab was based on principles described by Wang et al. [11]: (1) the hybridization signal under the optimal Ag or Ab concentration should be of sufficient strength (taking the hybridization signal of the rabbit anti-goat IgG as the control intensity in the same array); (2) ensure the optimum concentration selected was under the plateau phase. Clearly, lower Ag concentration coincided with a weaker the hybridization signal between Ag and Ab that could be generated under the same conditions, and vice versa. The corresponding dose-response curves are shown in Fig. S1. According to the defined principle, a four-parameter logistic function was used to determine the 80% effective concentration (EC80) as the working concentration. Hence, the optimal Ag concentrations were 15.5, 19.8, 43.4, 38.9, 662.6, 193.3, and 286.2 mg L1 for THBU-OVA, PA0304-OVA,

NC-S-2-OVA, BFNB-OVA, thiacloprid-OVA, chlorothalonil-OVA, and carbendazim-OVA, respectively (Fig. S1A). Likewise, the optimal Ab concentrations were 0.37, 0.19, 2.9, 0.78, 1.95, 3.32 and 3.7 mg L1 for THHE-8C10, PA-7B2, NC-S-2-1C3, BFNB-C8, thiacloprid mAb, chlorothalonil mAb, and carbendazim mAb, respectively (Fig. S1B). Finally, the optimal concentration for the positive control spot (rabbit anti-goat IgG) was 15.5 mg L1. The working concentration of the gold-labeled goat anti-mouse IgG (secondary Ab-AuNP conjugate) was also optimized. Various dilution times (1:20e1:1600) of the second Ab-AuNP conjugate were applied for the chromogenic immunoreaction. As seen from Fig. S2, the signal intensity of all pairs remained stable between 1:20 and 1:50 dilution time, while that of some pairs decreased as the dilution time changed from 1:50 to 1:1600. Thus, 1:50 was defined as the optimal titer of the prepared secondary Ab-AuNP conjugate. 3.4. Characterization of the 7-plex immunochip assay Based on the extensive pretest of cross-reactivity by iELISAs, the 7 selected Ag-Ab pairs must confer high specificity in the multiplex immunochip. Fig. 4 presents the individual chromogenic reactions caused by adding a single Ab on the integrated immunochip, indicating scarce cross-reaction among these Ags and Abs. It also suggested that the seven pesticides could be detected simultaneously and distinguishably by the integrated 7-plex immunochip. Moreover, secondary Ab-AuNP conjugate was directly added on the Ag-coated chip without the first step of primary mAbs. After signal enhancement, there was still negative on the area of all Ag spots, except the positive control with high signal. This indicated no cross-reaction between the secondary Ab-AuNP conjugate and different Ags. In addition, the negative control spots also proved that the assay system had no significant nonspecific binding after the chip was well blocked with BSA. Fig. 5 shows the standard calibration curves for the detection of triazophos, methyl-parathion, carbofuran, fenpropathrin, thiacloprid, chlorothalonil, and carbendazim, respectively. They were based on the mean values of six replicates performed on different

Please cite this article in press as: M. Lan, et al., Multi-residue detection of pesticides using a sensitive immunochip assay based on nanogold enhancement, Analytica Chimica Acta (2016), http://dx.doi.org/10.1016/j.aca.2016.07.044

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Fig. 4. Specificity among the involved Ags and Abs in the 7-plex immunochip. Single Ab of THHE-8C10 (T), PA-7B2 (MP), NC-S-2-1C3 (N), BFNB-C8 (BN), thiacloprid mAb (S), chlorothalonil mAb (BJ), and carbendazim mAb (D) was respectively used for the chip assay in the indirect detection model (images 1e7).

chips and different days. Clearly, the signal intensity from each microdot decreased as the relevant pesticide increased, as expected in a competitive immunoassay. The parameters of calibration curves, including the logistic function, calculated IC10 and IC50 values, and linear working range (IC20-IC80) are all listed in Table 1. The logistic correlation coefficients (R2) were all over 0.96, suggesting a good correlation between signal intensity and related pesticide concentration. The LOD (equal to IC10) of the seven pesticides were 0.02 ng mL1 (triazophos), 0.82 ng mL1 (methylparathion), 0.13 ng mL1 (fenpropathrin), 4.44 ng mL1 (carbofuran), 6.45 ng mL1 (thiacloprid), 0.41 ng mL1 (chlorothalonil), and 0.04 ng mL1 (carbendazim), respectively, which demonstrated the immunochip test could meet detection requirements of these pesticide residues. Generally, the linear working ranges covered

2e3 orders of magnitude, and the sensitivities (IC50) of the 7-plex immunochip were comparable to those of monoplex iELISAs using the same immunoreagents. Furthermore, the sensitivity for fenpropathrin was nearly 10-fold greater than that from iELISA. These results are attributable to the high efficiency of the nanogold enhancer for signal amplification in the final step. The assay's vLOD, which caused notably weakened color of microdot (color changed from dark to gray ), was in the range of 1e100 ng/mL for all seven pesticides. Therefore, the assay would be suitable for on-site rapid screening of samples to determine the degree of pesticide contamination. Cross-reactivities between target pesticides and their analogs from the same chemical families should be rechecked to characterize the selectivity of the immunochip system. No remarkable

Fig. 5. Images and standard curves of the immunochip assay for the 7 pesticides. The array layout is the same as in Fig. 4. The concentrations of each pesticide in images from left to right are 0.01, 0.05, 0.1, 0.5, 1.0, 5.0, 10, and 50 ng mL1 for triazophos and fenpropathrin; 0.1, 0.5, 1.0, 5.0, 10, 50, 100, and 500 ng mL1 for methyl-parathion; 0.5, 1.0, 5.0, 10, 25, 50, 100, and 500 ng mL1 for carbofuran; 0.5, 1.0, 5.0, 10, 50, 100, 500, and 1000 ng mL1 for thiacloprid; 0.05, 0.1, 0.5, 1.0, 2.0, 5.0, 10, and 50 ng mL1 for chlorothalonil; 0.005, 0.01, 0.05, 0.1, 0.5, 1.0, 5.0, and 10 ng mL1 for carbendazim. The error bars in curves correspond to the standard deviations of the data points (n ¼ 6).

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Table 1 Analytical parameters of the 7-plex immunochip assay. Pesticide

Standard curve

Triazophos Methyl-parathion Fenpropathrin Carbofuran Thiacloprid Chlorothalonil Carbendazim

y y y y y y y

a

¼ ¼ ¼ ¼ ¼ ¼ ¼

23326/(1þ(x/0.4168)^0.8182)e352.7 26683/(1þ(x/16.90)^0.7448)þ599.7 27934/(1þ(x/1.761)^0.6955)þ1799 27460/(1þ(x/22.62)^1.3028)þ4500 25868/(1þ(x/46.87)^0.9523)þ694.6 26597/(1þ(x/2.238)^1.2512)þ1259 22433/(1þ(x/1.1698)^1.6353)e770

R2

Linear range (ng mL1)

LOD (ng mL1)

IC50 (ng mL1)

vLOD (ng mL1)

iELISA IC50 (ng mL1)

MRLa (ng g1)

0.9962 0.9889 0.9838 0.9951 0.9865 0.9697 0.9900

0.038e4.57 2.63e108.68 0.24e12.92 7.80e65.55 10.93e200.95 0.74e6.78 0.078e2.82

0.02 0.82 0.13 4.44 6.45 0.41 0.04

0.42 ± 0.03 16.90 ± 1.94 1.76 ± 0.27 22.62 ± 3.52 46.87 ± 5.43 2.24 ± 0.48 0.47 ± 0.06

1 50 5 50 100 5 1

1.9 6.4 16.2 62.5 29.3 0.5 0.5

50 10 100 20 20 50 20

The lowest value of the maximum residue limit (MRL) defined for a certain pesticide according to China National food safety standards GB2763-2014.

signal intensity of each test spot from the non-competitive immunochip assay. Clearly, the matrix extract without dilution continued to affect signal development. Taken into account all the spots, 5-fold dilution was adopted to eliminate matrix interference, which required notably less dilution time than one-step extraction by methanol without further purification. Although the QuEChERS approach required more steps, the assay sensitivities for multiresidue pesticides in real samples were not highly compromised by the dilution factor. Recovery tests of spiked samples were performed with two fortified levels of each pesticide. Table 2 shows the mean recoveries ranged from 73.9% to 115.9%, with coefficient of variation (CV) between 6.3% and 14.1%, which generally conformed to the requirements of multi-residue pesticide detection. Hence, the proposed immunochip test showed promise for the simultaneous monitoring of these pesticide residues in real samples.

cross-reactivity (<5%) towards the analogs of triazophos, carbofuran, fenpropathrin, thiacloprid, and chlorothalonil was observed. As expected, the immunochip could also detect benomyl (IC50 ¼ 6.3 ng mL1), fenitrothion (IC50 ¼ 77.9 ng mL1), and parathion (IC50 ¼ 279.5 ng mL1), which was attributed to the broad specificity of carbendazim mAb and PA-7B2. Nevertheless, the sensitivities to parathion and fenitrothion were almost 10 times less than those from iELISAs (Table S1). It must be related to a major bottleneck that integrating more than five pairs of Ag/Ab reactions together gave interferences on the assay performances to some analytes, which was also previously reported [6]. 3.5. Analysis of spiked food samples Multi-residue analysis of seven pesticides was carried out for spiked vegetables and fruits to assess the practicality of the immunochip assay. However, matrix effect is a common challenge encountered in application of an immunoassay to food samples. The chemical components (sugar, organic acid, pigment, and so on) from sample matrices may affect immunoreactions or signal development, decreasing the assay's reliability. When tested by iELISAs, samples are often rapidly extracted via methanol, followed by simple dilution with suitable working buffers to eliminate matrix interference, but this dilution (usually 20e100 times) significantly reduces the assay's detectability for real samples [33e35]. In the current study, the QuEChERS method was employed for sample extraction and purification, using cucumber, Chinese cabbage, tomato, apple, and pear as samples. Sample cleanup, using dispersive solid-phase extraction with PSA and anhydrous MgSO4 to reduce the matrix effect from vegetable and fruit samples, is very efficient, so the dilution factors can be scaled back prior to immunoassays [36]. Fig. S3 shows the matrix influence on the maximum

3.6. Advantages and limitations of this work The proposed approach exhibits some advantages over other analytical methods for multiple pesticides. First, the target analytes can be from diverse chemical groups, unlike only the two classes of pesticides (organophosphates and carbamates) to which the acetylcholinesterase-based rapid test is limited [37]. Second, compared with standard chromatographic techniques for multiresidue detection of pesticides, no expensive instruments or materials were used for the immunoassay in this study. Qualitative results can be determined visually, while semi-quantification of target analytes can be easily achieved by grayscale image acquisition using a desktop scanner, rather than the sophisticated devices needed for the suspension array system, such as a fluorescent reader coupled with a flow cytometer. Therefore, the membrane-

Table 2 Recoveries of spiked samples tested by the developed immunochip assay (n ¼ 3)a. Sample

Cucumber

Chinese cabbage

Tomato

Apple

Pear

a

Pesticide spiked (ng g1)

Detected (ng Recovery (%) CV (%) Detected (ng Recovery (%) CV (%) Detected (ng Recovery (%) CV (%) Detected (ng Recovery (%) CV (%) Detected (ng Recovery (%) CV (%)

g

1

)

g1)

g1)

g1)

g1)

Triazophos

Methyl-Parathion

Fenpropathrin

Carbofuran

Thiacloprid

Chlorothalonil

Carbendazim

2

10

50

250

5

25

50

250

100

500

5

25

2

10

2.32 115.9 10.3 2.19 109.5 13.6 2.28 114.0 14.1 2.23 111.5 13.4 2.17 108.5 12.8

10.77 107.7 9.1 9.27 92.7 9.2 8.3 83.0 11.5 9.41 94.1 10.2 10.51 105.1 8.7

38.05 76.1 11.1 42.82 85.6 6.9 45.9 91.8 9.4 43.75 87.5 11.0 44.82 89.6 10.7

262.25 104.9 6.8 207.83 83.1 8.6 235.5 94.2 7.9 210.18 84.1 8.8 197.53 79.0 8.3

4.59 91.9 13.9 4.71 94.2 11.9 5.47 109.4 11.2 5.27 105.4 12.5 5.04 100.8 11.5

20.10 80.4 8.5 23.61 94.4 11.1 20.8 83.2 12.4 25.64 102.6 9.6 23.76 95.0 9.4

36.95 73.9 7.1 44.47 88.9 7.7 45.86 91.7 9.2 42.78 85.6 9.8 45.14 90.3 8.7

244.75 97.9 13.4 216.36 86.5 5.9 211.5 84.6 10.3 209.53 83.8 6.3 201.97 80.8 8.4

79.31 79.3 10.2 74.61 74.6 9.8 87.45 87.5 8.6 76.84 76.8 7.6 80.37 80.4 9.3

429.11 85.8 9.0 403.54 80.7 8.7 388.4 77.7 9.2 410.67 82.1 7.2 386.29 77.3 6.9

5.19 103.7 6.6 4.79 95.8 12.3 5.42 108.4 12.8 4.82 96.4 10.8 5.22 104.4 11.8

24.03 96.1 11.9 22.08 88.3 10.8 23.4 93.6 10.5 20.96 83.8 10.4 24.27 97.1 9.8

1.79 89.5 9.7 2.12 106.0 14.8 2.31 115.5 13.7 2.16 108.0 14.1 2.25 112.5 13.1

10.49 104.9 8.9 9.39 93.9 13.0 9.16 91.6 12.1 11.34 113.4 12.7 9.62 96.2 10.7

Detected concentration or recovery is the average of 3 replicates.

Please cite this article in press as: M. Lan, et al., Multi-residue detection of pesticides using a sensitive immunochip assay based on nanogold enhancement, Analytica Chimica Acta (2016), http://dx.doi.org/10.1016/j.aca.2016.07.044

M. Lan et al. / Analytica Chimica Acta xxx (2016) 1e10

based colorimetric immunochip assay is a flexible, simple, and costeffective method for multi-analyte determination. As expected for developing multiplex immunoassays, the shared-reactivity of the assay components was a key limitation to high multi-analyte capacity. Our results showed that hybridizationbased iELISA is an effective and fast method for evaluating the shared-reactivity among multiple Ags and Abs. Using mAbs specific to their own analytes is preferable for eliminating the crossreactions in multiplex immunochip assays. Moreover, conditions for the multiplex assay should be moderated to be universal for all the target analytes, though the sensitivity for some analytes will be lower than that in monoplex assays. In this proof-of-concept study, nanogold enhancement in competitive immunoassays proved effective for signal enlargement, via the clustering of new AuNPs around the immunogold particles immobilized on the membrane support. However, only one size of AuNPs (20 nm) was used for making immunogold conjugates. In future studies, we will attempt to improve assay performances by labeling with smaller AuNPs (e.g., 10 nm), which may provide better signal amplification [17]. 4. Conclusions We explored an integrated, rapid, sensitive, and colorimetric immunochip assay for multi-residue analysis of seven pesticides from six different chemical groups. The microarray chip consisted of seven Ags as capture probes coated on the NC membrane, as well as rabbit anti-goat IgG served as positive control. The indirect competitive immunoreaction was performed by mixing primary specific Abs and samples, followed by adding the nanogold-labeled secondary Ab as the uniform tracer. Finally, visual signal amplification was achieved by an optimized nanogold enhancer solution. The gold-based 7-plex immunoassay exhibited sensitivity generally comparable to those of enzyme-labeled monoplex immunoassays, and the detection could be accomplished within 1.5 h. Regarding food sample tests, the QuEChERS method coupled with several dilution times was suggested for sample preparation, so as to guarantee the sensitivity for each pesticide in multi-residue detection by the immunochip assay. Furthermore, the proposed colorimetric membrane-based immunochip can be miniaturized and integrated into a microfluidic system for a portable or automatic immunosensor. The chip can also be integrated into a 96- or 48-well format (one microarray per well) to improve sample throughput and reduce the total detection time for large-scale samples. Additionally, the assay model can be applied to different multi-analyte tests for other small molecular compounds. Overall, the current work laid a basis for development of high-throughput, sensitive, and rapid analytical technologies for environmental monitoring and food quality control. Acknowledgements This work was financially supported by the Special Fund for Agro-scientific Research in the Public Interest (No. 201203094-3), National Natural Science Foundation of China (No. 31401768), Fundamental Research Fund for the Central Universities (2014QNA6022), and Science-Technology Project Fund in Zhejiang Province of China (2016C32004). Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.aca.2016.07.044.

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References [1] H. Jiang, M. Fan, Multi-Analyte immunoassay for pesticides: a review, Anal. Lett. 45 (2012) 1347e1364. [2] H. Zhang, S. Wang, G. Fang, Applications and recent developments of multianalyte simultaneous analysis by enzyme-linked immunosorbent assays, J. Immunol. Methods 368 (2011) 1e23. [3] A.A. Ellington, I.J. Kullo, K.R. Bailey, G.G. Klee, Antibody-based protein multiplex platforms: technical and operational challenges, Clin. Chem. 56 (2010) 186e193. [4] R.E. Biagini, J.P. Smith, D.L. Sammons, B.A. MacKenzie, C.A.F. Striley, S.K. Robertson, J.E. Snawder, Development of a sensitivity enhanced multiplexed fluorescence covalent microbead immunosorbent assay (FCMIA) for the measurement of glyphosate, atrazine and metolachlor mercapturate in water and urine, Anal. Bioanal. Chem. 379 (2004) 368e374. [5] X. Wang, Z. Mu, F. Shangguan, R. Liu, Y. Pu, L. Yin, Rapid and sensitive suspension array for multiplex detection of organophosphorus pesticides and carbamate pesticides based on silicaehydrogel hybrid microbeads, J. Hazard. Mater 273 (2014) 287e292. [6] N. Liu, Z. Gao, H. Ma, P. Su, X. Ma, X. Li, G. Ou, Simultaneous and rapid detection of multiple pesticide and veterinary drug residues by suspension array technology, Biosens. Bioelectron. 41 (2013) 710e716. [7] Y. Guo, J. Tian, C. Liang, G. Zhu, W. Gui, Multiplex bead-array competitive immunoassay for simultaneous detection of three pesticides in vegetables, Microchim. Acta 180 (2013) 387e395. [8] X. Yan, H. Li, Y. Yan, X. Su, Developments in pesticide analysis by multi-analyte immunoassays: a review, Anal. Methods 6 (2014) 3543e3554. [9] L. Wang, J. Cai, Y. Wang, Q. Fang, S. Wang, Q. Cheng, D. Du, Y. Lin, F. Liu, A bareeye-based lateral flow immunoassay based on the use of gold nanoparticles for simultaneous detection of three pesticides, Microchim. Acta 181 (2014) 1565e1572. [10] R.P. Ekins, Invited papers from the 25th international symposium organized by the swedish academy of pharmaceutical Sciences multi-analyte immunoassay, J. Pharm. Biomed. Anal. 7 (1989) 155e168. [11] Y. Wang, N. Liu, B. Ning, M. Liu, Z. Lv, Z. Sun, Y. Peng, C. Chen, J. Li, Z. Gao, Simultaneous and rapid detection of six different mycotoxins using an immunochip, Biosens. Bioelectron. 34 (2012) 44e50. [12] W. Hu, X. Li, G. He, Z. Zhang, X. Zheng, P. Li, C.M. Li, Sensitive competitive immunoassay of multiple mycotoxins with non-fouling antigen microarray, Biosens. Bioelectron. 50 (2013) 338e344. [13] M.Y. Rubtsova, J.V. Samsonova, A.M. Egorov, R.D. Schmid, Simultaneous determination of several pesticides with chemiluminescent immunoassay on a multi-spot membrane strip, Food Agric. Immunol. 10 (1998) 223e235. [14] N. Taranova, N. Byzova, V. Zaiko, T. Starovoitova, Y. Vengerov, A. Zherdev, B. Dzantiev, Integration of lateral flow and microarray technologies for multiplex immunoassay: application to the determination of drugs of abuse, Microchim. Acta 180 (2013) 1165e1172. [15] C. Desmet, L.J. Blum, C.A. Marquette, High-Throughput multiplexed competitive immunoassay for pollutants sensing in water, Anal. Chem. 84 (2012) 10267e10276. [16] S. Morais, L.A. Tortajada-Genaro, T. Arnandis-Chover, R. Puchades, A. Maquieira, Multiplexed microimmunoassays on a digital versatile disk, Anal. Chem. 81 (2009) 5646e5654. [17] P. Dobosz, S. Morais, R. Puchades, A. Maquieira, Nanogold bioconjugates for direct and sensitive multiplexed immunosensing, Biosens. Bioelectron. 69 (2015) 294e300.  Maquieira, Massive immuno [18] P. Dobosz, S. Morais, E. Bonet, R. Puchades, A. multiresidue screening of water pollutants, Anal. Chem. 87 (2015) 9817e9824. [19] G.C. Le Goff, B.P. Corgier, C.A. Mandon, G. De Crozals, C. Chaix, L.J. Blum, C.A. Marquette, Impact of immobilization support on colorimetric microarrays performances, Biosens. Bioelectron. 35 (2012) 94e100. [20] K.F. Lei, Y.K.C. Butt, Colorimetric immunoassay chip based on gold nanoparticles and gold enhancement, Microfluid. Nanofluid 8 (2010) 131e137. [21] G. Zhu, M. Jin, W. Gui, Y. Guo, R. Jin, C. Wang, C. Liang, Y. Liu, S. Wang, Development of a direct competitive enzyme-linked immunoassay for carbofuran in vegetables, Food Chem. 107 (2008) 1737e1742. [22] R. Liu, Y. Liu, M. Lan, N. Taheri, J. Cheng, Y. Guo, G. Zhu, Evaluation of a watersoluble adjuvant for the development of monoclonal antibodies against smallmolecule compounds, J. Zhejiang Univ. Sci. B 17 (2016) 282e293. [23] Y.R. Guo, S.Y. Liu, W.J. Gui, G.N. Zhu, Gold immunochromatographic assay for simultaneous detection of carbofuran and triazophos in water samples, Anal. Biochem. 389 (2009) 32e39. [24] W.J. Gui, S.T. Wang, Y.R. Guo, G.N. Zhu, Development of a one-step strip for the detection of triazophos residues in environmental samples, Anal. Biochem. 377 (2008) 202e208. [25] A. Wilkowska, M. Biziuk, Determination of pesticide residues in food matrices using the QuEChERS methodology, Food Chem. 125 (2011) 803e812. [26] V.V. Krishhan, I.H. Khan, P.A. Luciw, Multiplexed microbead immunoassays by flow cytometry for molecular profiling: basic concepts and proteomics applications, Crit. Rev. Biotechnol. 29 (2009) 29e43. [27] Z. Ma, S.F. Sui, Naked-Eye sensitive detection of immunoglubulin G by enlargement of Au nanoparticles in vitro, Angew. Chem. Int. Ed. 41 (2002) 2176e2179.

Please cite this article in press as: M. Lan, et al., Multi-residue detection of pesticides using a sensitive immunochip assay based on nanogold enhancement, Analytica Chimica Acta (2016), http://dx.doi.org/10.1016/j.aca.2016.07.044

10

M. Lan et al. / Analytica Chimica Acta xxx (2016) 1e10

[28] D. Kim, W.L. Daniel, C.A. Mirkin, Microarray-Based multiplexed scanometric immunoassay for protein cancer markers using gold nanoparticle probes, Anal. Chem. 81 (2009) 9183e9187. [29] K.R. Brown, M.J. Natan, Hydroxylamine seeding of colloidal Au nanoparticles in solution and on surfaces, Langmuir 14 (1998) 726e728. Sarma, Synthesis of Au nanoparticleeconductive polyaniline com[30] T. Kumara posite using H 2 O 2 as oxidising as well as reducing agent, Chem. Commun. (2002) 1048e1049. [31] J. Li, M. Zou, Y. Chen, Q. Xue, F. Zhang, B. Li, Y. Wang, X. Qi, Y. Yang, Gold immunochromatographic strips for enhanced detection of Avian influenza and Newcastle disease viruses, Anal. Chim. Acta 782 (2013) 54e58. [32] A. Urusov, A. Zherdev, B. Dzantiev, Use of gold nanoparticle-labeled secondary antibodies to improve the sensitivity of an immunochromatographic assay for aflatoxin B1, Microchim. Acta 181 (2014) 1939e1946. [33] Y.Z. Piao, Y.J. Kim, Y.A. Kim, H. Lee, B.D. Hammock, Y.T. Lee, Development of ELISAs for the class-specific determination of organophosphorus pesticides,

J. Agric. Food. Chem. 57 (2009) 10004e10013. [34] F.A. Esteve-Turrillas, A. Abad-Fuentes, J.V. Mercader, Determination of fenhexamid residues in grape must, kiwifruit, and strawberry samples by enzyme-linked immunosorbent assay, Food Chem. 124 (2011) 1727e1733. [35] Z. Xu, H. Deng, X. Deng, J. Yang, Y. Jiang, D. Zeng, F. Huang, Y. Shen, H. Lei, H. Wang, Y. Sun, Monitoring of organophosphorus pesticides in vegetables using monoclonal antibody-based direct competitive ELISA followed by HPLCeMS/MS, Food Chem. 131 (2012) 1569e1576. [36] F. Zhao, C. Hu, H. Wang, L. Zhao, Z. Yang, Development of a MAb-based immunoassay for the simultaneous determination of O,O-diethyl and O,Odimethyl organophosphorus pesticides in vegetable and fruit samples pretreated with QuEChERS, Anal. Bioanal. Chem. 407 (2015) 8959e8970. [37] S. Qian, H. Lin, Colorimetric sensor array for detection and identification of organophosphorus and carbamate pesticides, Anal. Chem. 87 (2015) 5395e5400.

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