Real-time monitoring of fenitrothion in water samples using a silicon nanophotonic biosensor

Thisisthesubmittedversionofthefollowingarticle: Ramirez-PriegoP.,EstévezM.-C.,Díaz-LuisraveloH.J.,Manclús J.J.,MontoyaÁ.,LechugaL.M..Real-timemonitoringof fenitrothioninwatersamplesusingasiliconnanophotonic biosensor.AnalyticaChimicaActa,(2021).1152.338276:-. 10.1016/j.aca.2021.338276, whichhasbeenpublishedinfinalformat https://dx.doi.org/10.1016/j.aca.2021.338276© https://dx.doi.org/10.1016/j.aca.2021.338276.Thismanuscript versionismadeavailableundertheCC-BY-NC-ND4.0license http://creativecommons.org/licenses/by-nc-nd/4.0/ 1 Real-time monitoring of fenitrothion in water samples using a silicon nanophotonic biosensor Patricia Ramirez-Priego1, M.-Carmen Estévez1,*, Heriberto J. Díaz-Luisravelo1, Juan J. Manclús2, Ángel Montoya2 and Laura M. Lechuga1 1 Nanobiosensors and Bioanalytical Applications Group, Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC, BIST and CIBER-BBN, Campus UAB, Bellaterra, 08193 Barcelona, Spain 2 Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain * Corresponding author. E-mail address: mcarmen.estev[email protected] KEYWORDS: silicon photonics, optical sensor, environmental monitoring, pesticide, organophosphate, fenitrothion, label-free. ABSTRACT: Due to the large quantities of pesticides extensively used and their impact on the environment and human health, a prompt and reliable sensing technique could constitute an excellent tool for in-situ monitoring. With this aim, we have applied a highly sensitive photonic biosensor based on a bimodal waveguide interferometer (BiMW) for the rapid, label-free, and 2 specific quantification of fenitrothion (FN) directly in tap water samples. After an optimization protocol, the biosensor achieved a limit of detection (LOD) of 0.29 ng mL-1 (1.05 nM) and an IC50 of 1.71 ng mL-1 (6.09 nM) using a competitive immunoassay and employing diluted tap water. Moreover, the biosensor was successfully employed to determine FN concentration in blind tap water samples obtaining excellent recovery percentages with a time-to-result of only 20 minutes without any sample pre-treatment. The features of the biosensor suggest its potential application for real time, fast and sensitive screening of FN in water samples as an analytical tool for the monitoring of the water quality. 3 1. INTRODUCTION Fenitrothion [O,O-Dimethyl O-(3-methyl-4-nitrophenyl) phosphorothioate] (FN) (Figure 1), is a powerful organophosphate (OP) insecticide used in large quantities because of its efficacy, costeffectiveness, and availability [1]. This type of pesticide is extensively employed in agriculture and everyday household applications at worldwide level. Some of FN’s applications include the control of a wide range of insects in cereals, rice, fruits, vegetables, store grains, and other crops, as well as in public health programs to control flies, mosquitoes, and cockroaches [2,3]. The uncontrolled use of organophosphate insecticides represents a relevant risk to the environment as they are potentially toxic to non-target organisms, including humans. Their main mechanism of action is based on the inhibition of the enzyme acetylcholinesterase involved in nerve impulse transmission [1,4]. Additionally, several studies have demonstrated that they are also carcinogenic [5], cytotoxic [6], mutagenic, genotoxic[7,8], and immunotoxic [9]. Toxicity of FN has been tested in mice, rats, Guinea pigs, and rabbits showing an oral lethal dose (LD50) ranging between 250 and 870 mg Kg-1 [10,11]. In humans, the Food and Agriculture Organization of the United Nations (FAO), together with the World Health Organization (WHO) established an acceptable daily intake (ADI) of 0.005 mg Kg-1 [12]. Some of the chronic symptoms include general fatigue, headache, loss of memory, anorexia, nausea, and muscular weakness, among others [11]. For this reason, FN in particular, was recently banned in Europe and the United States; however, it is still used in Central and South America, Asia, and Africa [10,13,14]. Because of the toxicity of OP pesticides, including FN, the continuous monitoring in a wide range of samples such as soil, sediments, air, water, and food is crucial [15,16]. Indeed, one of the most common causes of human exposure is through drinking-water supplies due to pesticide leaching from contaminated soils to the groundwater [17]. WHO has published international standards for drinking water by publishing 4 Guideline Values (GV) for different pesticides. Although a GV for FN has not been given (judging by the occurrence of the pesticide at concentration well below those of health concern), a healthbased value (HBV) of 8 g L-1 [18,19]. can be calculated based on toxicity studies. Conventional methods for the detection of FN and other OP pesticides include liquid and gas chromatography [20–22], mass spectroscopy [23,24], capillary electrophoresis [25], and EnzymeLinked ImmunoSorbent Assay (ELISA) [26,27]. These methods are highly sensitive for the determination of OP pesticides. However, these techniques require laborious and time-consuming sample preparation and the use of bulky laboratory equipment and trained staff, making them unsuitable for in-field testing. To facilitate continuous routine analysis in real-time scenarios, the implementation of analytical tools that overcome these limitations and provide equal or even better levels of sensitivity are still in demand. Biosensors are one of the preferred options, as these devices can offer straightforward, rapid, portable, and low-sample and reagents consumption designs. Several electrochemical biosensors have been described for the detection of different OPs, including, chlorpyrifos, dichlorvos, parathion, and parathion-methyl , achieving a limit of detection (LOD) between 0.004 and 10 ng mL-1 [28–30]. Several examples have also been reported for the specific detection of FN. For instance, Ensafi et al. and Qi et al. employed an electrochemical sensor functionalized with graphene and metal oxide nanostructured material, achieving a LOD of 0.45 and 2.20 ng mL-1, respectively, for FN in water samples [31,32]. Moreover, Kant also functionalized a Surface Plasmon Resonance (SPR) biosensor with similar nanostructures, reaching a LOD of 11.40 ng mL-1 in the case of FN in environmental samples [33]. We here propose the use of a highly sensitive photonic biosensor based on bimodal waveguide interferometers (BiMW) [34]. This design has already demonstrated numerous advantages over conventional methods, such as unprecedented sensitivity, rapid, label-free, and real-time 5 monitoring. Moreover, BiMW sensor chips are fabricated with standard microelectronics technology, enabling a reduction in fabrication costs and, therefore, in the final analysis cost. All the above advantages of the BiMW biosensor make this device an ideal candidate for on-site monitoring of OP pesticides. This BiMW device has already been employed for several clinical [35–38] and environmental [39,40] applications with real samples, for example for the specific detection of the biocide Irgarol 1051 in seawater, combining high specific custom-designed antibodies against the selected contaminant and the extreme sensitivity of the BiMW sensor [39]. The working principle of a BiMW biosensor relies on the interaction within the evanescent wave, an electromagnetic field associated to a monochromatic light propagating through the waveguide, which allows the excitation of two light modes [34]. These modes produce an interference pattern that is dependent on the local refractive index at the surface of the waveguide. Any event at the sensor surface, such as the binding of an analyte to its specific receptor, results in a change in the effective refractive index, which produces a phase shift between the two modes, and hence, an interference pattern that can be monitored in real-time. In this work, we have optimized and validated the BiMW biosensor device to identify and quantify FN in tap water samples. The detection strategy consists of a competitive immunoassay by employing a highly specific monoclonal antibody produced against FN. The optimization of the immunosensor has been focused on two aspects: firstly, on improving the analytical parameters compared with routine detection methods and state-of-the-art biosensors, and secondly, on avoiding any previous sample pre-treatment or extraction for directly analyzing real water samples. 2. MATERIALS AND METHODS 2.1. Chemical and biological reagents 6 Organic solvents (acetone, ethanol, methanol, and ethanol absolute), hydrochloric acid (HCl, 37%), and nitric acid (HNO3, 65%) were purchased from Panreac (Barcelona, Spain). Triethoxysilane polyethylene glycol carboxylic acid (silane-PEG-COOH, 600 Da) was supplied by Nanocs (New York, US). Reagents for carboxylic acid activation (N-(3-dimethylaminopropyl)- N’-ethylcarbodiimide hydrochloride (EDC) and N-hydroxysulfosuccinimide (sulfo-NHS)), 1,4dioxane, fenitrothion (FN) analytical standard, bovine serum albumin (BSA), ovalbumin (OVA), and all reagents used for buffer preparation, hapten synthesis, and conjugation were provided by Sigma-Aldrich (Steinheim, Germany). The buffers employed were the following: phosphate buffer saline (PBS; 10 mM Na2HPO4, 1.8 mM KH2PO4, 2.7 mM KCl and 137 mM NaCl, pH 7.4), PBST (PBS with different concentrations of Tween 20, pH 7.4), MES buffer (0.1 M 2-(Nmorpholino)ethanesulfonic acid (MES), pH 5.5), acetate buffer (10 mM pH 5.0), ethanolamine hydrochloride (1 M, pH 8.5). Milli-Q water was employed for all the buffers preparation. 2.2. Immunoreagents preparation. Hapten FN4C (Figure 1) was prepared by the introduction of a ω-amino acid as an amide linkage of a suitable thiophosphate reagent, as previously described [41]. Briefly, ethyl dichlorothiophosphate was reacted with sodium 3-methyl-4-nitrophenolate followed by sodium 4aminobutyrate. Finally, the thiophosphoramide hapten was purified by column chromatography and its structure confirmed by nuclear magnetic resonance spectroscopy: 1H NMR (CDCl3) δ 8.03 (d, 1H, ArH5), 7.22 (m, 2H, ArH2,6), 4.19 (q+q, 2H, CH2O), 3.39 (m, 1H, NH), 3.17 (m, 2H, CH2N), 2.61 (s, 3H, ArCH3), 2.46 (t, 2H, OOCCH2), 1.88 (m, 2H, CH2), 1.37 (t, 3H, CH3). Hapten-protein conjugation (to BSA and OVA) was carried out by the N-hydroxysuccinimideactive ester method as described [41], and the conjugation was characterized by UV spectroscopy. 7 The hapten to protein molar ratio was estimated from hapten and protein spectral data. Apparent molar ratios of BSAand OVA-FN4C conjugates were 18 and 4, respectively. Monoclonal antibody (mAb) LIB-FN4C22 was obtained from mice immunized with the BSAFN4C conjugate and applying the monoclonal antibody technology, essentially as described [41]. 2.3. Bimodal waveguide sensor The BiMW sensor chip (3 cm x 1 cm; Figure 2A) was fabricated in silicon nitride (Si3N4) at waferscale in a cleanroom facility, as previously described [34]. Each chip integrates an array of 20 independent bimodal waveguides. The working principle of the BiMW sensor relies on the behavior of light propagating through a waveguide, which allows only the propagation of the fundamental and first propagating modes of transverse electric polarized light (Figure 2A). In brief, light from a polarized diode laser ( = 660 nm; Hitachi; Tokyo, Japan) is first confined through the waveguide core in a single (fundamental) mode. After a certain distance, this fundamental mode is coupled into a bimodal section through a step junction that allows the appearance of the first propagating mode. These two modes travel across the sensing area and exit the waveguide. The evanescent field of the waveguide decays within the external medium and is altered by any change occurring on the close surface. This principle is exploited for sensing purposes. A sensing window is opened along the bimodal section of the waveguide, where the bioreceptors can be immobilized, and the detection occurs. Therefore, any refractive index change in this area, such as the one induced by the binding (or detachment) of any molecule, affects the propagating modes and results in an interferometric phase shift (Δφ) between the two modes, modifying the intensity distribution at the sensor chip output. The intensity is recorded by a two-sectional photodetector (Hamamatsu Photonics, Hamamatsu, Japan) and processed through an acquisition card. An alloptical phase modulation method previously developed based on Fourier Series deconvolution is 8 applied [42], transforming the interference signal into a linear one able to continuously quantify the phase shifts between both modes. A fluidic system to ensure the liquid circulation to the sensing area is incorporated. It includes: a five-channel polydimethylsiloxane (PDMS) microfluidic cell (channel dimensions = 1.25 mm wide x 500 m height) which is sealing the sensor chip, a syringe pump (New Era; New York, US) to guarantee a continuous flow rate of a running buffer, and a 6port injection valve (VICI; Texas, US), that allows the sequential loading of the sample loop (100 L) and injection of the different solutions. 2.4. Surface functionalization. Before surface functionalization, the sensor chips were consecutively sonicated for 5 min in acetone, ethanol, milli-Q water, and 10 min in methanol/HCl 1:1 (v/v), to remove organic contamination. The sensor chips were then rinsed with water and dried with a stream of nitrogen. A layer of active hydroxyl groups was generated onto the sensor surface using oxygen plasma (Electronic Diener; Ebhausen, Germany) for 5 min at 45 sccm gas flow, followed by immersion in a 15% HNO3 solution at 75 C for 25 min. After rinsing generously with water and drying under N2 flow, the sensor chip was immediately functionalized with silane-PEG-COOH, following the protocol previously detailed [35]. Briefly, the sensor chip was incubated with a solution of the silane (25 mg mL-1 in ethanol absolute/water 95:5 (v/v)) for 2 h at 4 C. After the incubation, the sensor chip was sequentially rinsed with ethanol and water and dried with a nitrogen stream. Finally, the sensor chip was subject to a curing process at high temperature, by placing it within a glass recipient and in a conventional autoclave for 90 min at 121 C and a pressure of 1.5 bars. 2.5. BSA-FN4C covalent immobilization The silanized sensor chip was placed on the experimental setup for the in-situ immobilization of the BSA-FN4C conjugate through covalent binding of the carboxylic groups introduced on the 15 With all the above-selected immunoassay parameters, complete calibration curves were carried out with FN concentrations ranging from 1.95 nM to 5 M diluted in the two selected buffers (PBST 0.05% and 0.5%). Samples were flowed over the BSA-FN4C coated surface after a preincubation of 10 minutes with a fixed concentration of LIB-FN4C22 antibody (1 g mL-1). As shown in Figure 4 and Table 1, a clear influence of the Tween percentage in the immunoassay was observed. The PBST with ten times more concentrated Tween 20 (PBST 0.5% Tween) resulted in a significant worsening of the sensitivity of around one order of magnitude (both in the LOD and the IC50). The main analytical parameters for each of the assays are summarized in Table 1. According to these results, PBST 0.05% was finally selected for the evaluation in tap water samples. Under these conditions, a LOD and IC50 of 0.93 nM (0.26 ng mL-1) and 5.88 nM (1.65 ng mL-1) were reached, respectively, and the linear working range was found between 1.84 and 18.74 nM (0.52 and 5.25 ng mL-1). The coefficient of variation (CV) for both intra-assays and inter-assays for the main analytical parameters were well-below 10 and 15%, respectively (see Table 2), which are values commonly acceptable for bioanalytical methods [43]. These results corroborate the excellent reproducibility and low variability of the competitive immunoassay for the detection of FN. The specificity of the antibody, previously evaluated by ELISA measuring the cross-reactivity (CR) with other pesticides having a molecular structure closely related to FN, showed excellent performance as summarized in Table S1. All the compounds exhibited a value lower than 0.1%, except parathion-ethyl that was slightly recognized by the antibody (CR = 2.5%), probably related to its high structural similarity to FN. Nevertheless this cross-reactivity is low and overall the results indicate that LIB-FN4C22 is highly specific against FN. Table 1. Analytical parameters for the competitive immunoassay for FN in buffer and tap water (1:1). LOD (IC90) (ng mL-1) IC50 (ng mL-1) Working Range (IC80 – IC20) HillSlope 16 (ng mL-1) PBST 0.05% 0.26 1.65 0.52 – 5.25 -1.195 PBST 0.5% 1.91 24.4 4.89 – 122.3 -0.875 Tap water:PBST 2x (1:1) 0.29 1.71 0.56 – 5.17 -1.251 Table 2. Intra-assay and inter-assay variability of the main analytical parameters for the competitive immunoassay in PBST 0.05%. Intra-assaya Inter-assayb Average  SD %CV Average  SD %CV IC50 (ng mL-1) 1.59  0.11 6.82 1.65  0.06 3.74 LOD (ng mL-1) 0.25  0.01 5.84 0.26  0.008 3.26 Δφmax (rad) 1.80  0.02 1.11 1.81  0.03 1.66 HillSlope -1.15  0.03 2.61 -1.20  0.03 4.17 a Triplicates within the same biofunctionalized BiMW sensor chip. b Triplicates with three different biofunctionalized BiMW sensor chips. 3.2. Analysis in tap water. Accuracy study Widely used pesticides, including fenitrothion, have the potential to eventually contaminate natural waters and also reach water systems, becoming harmful for humans and other organisms by ingestion or direct contact with them. Then, the feasibility of using the developed immunosensor to analyze water samples was assessed using tap water. To evaluate matrix effects, 1 g mL-1 of the mAb LIB-FN4C22 was prepared in tap water and injected over the sensor surface. Lower detection signals were observed in comparison with the ones obtained previously in buffer conditions (Figure S2). This result reveals that some water parameters like pH, ionic strength, or the concentration of certain compounds interfere in the assay performance. To correct this effect, samples were diluted 1:1 in PBST 2x (i.e., PBS 20 mM with 0.1% Tween 20). When monitoring the sensor response to the flow of tap water (1:1) in the absence of the antibody, a negligible signal was observed (Figure S2) confirming the lack of any nonspecific adsorption. The same phase variation as in buffer conditions was obtained when the antibody in tap water was diluted 1:1 in 17 PBST 2x (Figure S2), indicating that buffered tap water does not affect the interaction of the antibody with the hapten immobilized on the sensor surface. Tap water was spiked with different FN concentrations in the range from 1.95 nM to 5 M. The samples were then incubated for 10 minutes with a fixed concentration of the LIB-FN4C22 antibody (1 g mL-1), diluted in PBST 2x, before injection onto the BSA-FN4C coated sensor surface. As shown and compared in Figure 5 and Table 1, calibration curves obtained in PBST 0.05% and in tap water samples (1:1) exhibited non-significant differences concerning assay sensitivity. In particular, a LOD of 1.05 nM (0.29 ng mL-1), an IC50 of 6.09 nM (1.71 ng mL-1), and a working range from 2.01 and 18.45 nM (0.56 to 5.17 ng mL-1) were reached for FN detection in tap water samples. The accuracy of our biosensor for the determination of the FN concentration was then evaluated with tap water samples fortified with FN within and far above the working range of the immunoassay. Seven blind samples (concentration unknown for the researcher performing the analysis) were prepared (S1 – S7). Before the injection over the sensor surface, all samples were diluted 1:1 in PBST 2x (or more if necessary, to fall within the dynamic range, as in the case of samples S1 and S2). The sensor response was monitored in real-time for each analyzed sample (see Figure S3), and the signal was interpolated in the calibration curve obtained for FN (Figure 5). FN concentrations obtained by duplicate with the biosensor were calculated and listed in Table 3. A good correlation was observed between FN concentrations obtained with the biosensor and the real concentration. Accuracy values indicate a slight overestimation (i.e., above 100%) except for the lowest concentration, which is around 80%. Overall, these values are within the accepted accuracy range between 80 – 120%. These results confirm the high accuracy and feasibility of the 18 developed label-free biosensor to analyze FN in water in less than 20 minutes without the need for any sample pre-treatment. Overall, we have established a biosensor-based immunoassay for the detection of FN in water with an analytical performance slightly better than some examples reported in the literature using a conventional ELISA (LOD of 0.30 or 0.90 ng mL-1) and electrochemical sensors (LOD of 0.45 and 2.20 ng mL-1), employing different immunoreagents [26,27,31,32]. Furthermore, the high sensitivity and specificity of our methodology for the determination of FN in water samples meet the health-based value imposed for drinking water by WHO (8 g mL-1) and also the minimum amount set by Australia, as the most restrictive value currently established (7 g mL-1) [19,44]. Table 3. Accuracy study performed with blind samples with the immunosensor. Samples Concentration Accuracy (%) Spiked Measureda nM ng mL-1 ng mL-1 S1 200 55.91 58.32  3.89 104.3 S2 75 20.97 20.48  5.23 97.7 S3 20 5.59 5.67  0.41 101.4 S4 15 4.19 4.80  0.46 114.5 S5 10 2.80 3.09  0.22 110.7 S6 5 1.40 1.10  0.01 78.8 S7 1 0.28 < LOD - a mean ±SD of two measurements 4. CONCLUSIONS We have developed a biosensor for the straightforward, label-free, and real-time fenitrothion detection in tap water based on a highly sensitive interferometric detection. The strategy consists of a competitive immunoassay format that combines the covalent immobilization of a BSA conjugate carrying FN hapten molecules with specific monoclonal antibodies against the insecticide. The binding of the antibody to the coated sensor surface is inversely proportional to FN concentration in the sample. Several parameters affecting the immunoassay sensitivity have 19 been optimized, achieving a LOD of 1.05 nM (0.29 ng mL-1) and IC50 of 6.09 nM (1.71 ng mL-1) in tap water with short time-to-result (20 min), which are sufficient for the health-based value calculated for drinking water by WHO (8 µg mL-1). Furthermore, the biosensor accuracy has been evaluated with blind tap water samples showing an excellent correlation with spiked fenitrothion concentrations. Given these promising results, further steps will include the integration of the biosensor in a portable platform, which will promote pushing the technology from laboratory prototypes to compact devices able to perform continuous in-field monitoring of water quality without sample pre-treatment. ASSOCIATED CONTENT Supporting Information. Additional figures and tables showing the optimization of several parameters directly affecting the surface biofunctionalization process and the performance of the immunoassay (i.e. immobilization buffer, conjugate and antibody concentrations, and regeneration cycles), analytical parameters for the indirect competitive immunoassay in buffer and tap water, cross-reactivity of the antibody to a set of different pesticides, and finally, sensorgrams showing the detection of FN in tap water blind samples. AUTHOR INFORMATION Corresponding Author * M.- Carmen Estévez – Nanobiosensors and Bioanalytical Applications Group (NanoB2A), Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC, CIBER-BBN and BIST, 08193 Barcelona, Spain; e-mail: [email protected] Author Contributions 20 The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Notes The authors declare no competing financial interest. ACKNOWLEDGMENTS This work received financial support from DIONISOS Project (Retos Colaboración RTC-20176222-5). The ICN2 is funded by the CERCA programme / Generalitat de Catalunya. The ICN2 is supported by the Severo Ochoa Centres of Excellence programme, funded by the Spanish Research Agency (AEI, grant no. SEV-2017-0706). ABBREVIATIONS ADI, acceptable daily intake; BiMW, bimodal waveguide Interferometer; BSA, bovine serum albumin; CR, cross-reactivity; CV, coefficient of variation; EDC, N-(3-dimethylaminopropyl)-N’- ethylcarbodiimide hydrochloride; ELISA, Enzyme-Linked ImmunoSorbent Assay; FAO, Food and Agriculture Organization; FN, Fenitrothion; IC50, half-maximal inhibitory concentration; LD50, lethal dose; LOD, limit of detection; mAb, monoclonal antibody; OP, Organophosphate; OVA, ovalbumin; PBS, phosphate buffer saline; PBST, PBS with different concentrations of Tween 20; PDMS, polydimethylsiloxane; SD, standard deviation; Si3N4, silicon nitride; SilanePEG-COOH, Triethoxysilane polyethylene glycol carboxylic acid; SPR, Surface Plasmon Resonance; sulfo-NHS, N-hydroxysulfosuccinimide; Δφ, phase variation. REFERENCES [1] F. Sánchez-Santed, M.T. Colomina, E. Herrero Hernández, Organophosphate pesticide 21 exposure and neurodegeneration, Cortex. 74 (2016) 417–426. 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