Sensors and Actuators B 221 (2015) 480–490
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Thermolysin entrapped in a gold nanoparticles/polymer composite for direct and sensitive conductometric biosensing of ochratoxin A in olive oil Fatma Dridi a,b , Mouna Marrakchi a,c , Mohamed Gargouri a , Alvaro Garcia-Cruz b , Sergei Dzyadevych d , Francis Vocanson e , Joelle Saulnier b , Nicole Jaffrezic-Renault b , Florence Lagarde b,∗ a
University of Carthage, Laboratory of Microbial Ecology and Technology, INSAT, BP 676, 1080 Tunis Cedex, Tunisia University of Lyon, Institute of Analytical Sciences, UMR CNRS-UCBL-ENS 5280, 5 Rue de la Doua, 69100 Villeurbanne, France c Tunis El Manar University, Higher Institute of Applied Biological Sciences (ISSBAT), 1006 Tunis, Tunisia d Laboratory of Biomolecular Electronics, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, 150 Zabolotnogo St., Kiev 03680, Ukraine e University of Lyon, University of Saint-Etienne, Laboratory Hubert Curien, UMR CNRS-UJM 5516, 42023 Saint-Etienne, France b
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Article history: Received 7 May 2015 Received in revised form 25 June 2015 Accepted 28 June 2015 Available online 2 July 2015 Keywords: Conductometric biosensor Thermolysin Ochratoxin A Polyvinyl alcohol Polyethylenimine Gold nanoparticles Olive oil
a b s t r a c t An original biosensor was developed for the direct conductometric detection of ochratoxin A (OTA) in olive oil samples. The biosensor is based on thermolysin (TLN) immobilization into a polyvinyl alcohol (PVA)/polyethylenimine (PEI) matrix containing gold nanoparticles (AuNPs) and cross-linked at the surface of gold interdigitated microelectrodes using glutaraldehyde. Under optimal conditions (35 min cross-linking time, working pH of 7 and temperature of 25 ◦ C), the biosensor response was linear up to 60 nM OTA, with a sensitivity of 597 S M−1 and a limit of detection of 1 nM. This value was 700 times lower than the detection limit obtained using the more classical method based on enzyme cross-linking in the presence of bovine serum albumin (BSA). PVA/PEI hydrogel creates a very favorable aqueous environment for the enzyme. In addition, interactions between protonated amino groups of PEI and negative charges of both citrated AuNPs and thermolysin improve their dispersion in the polymer blend, favoring enzyme stabilization and accessibility of the substrate. No conductometric signal was observed after OTA injection in the absence of AuNPs, in agreement with the insulating properties of the cross-linked PVA/PEI hydrogel film. Incorporation of AuNPs into the TLN/BSA biomembrane helped improving the sensitivity by 5.3 but this latter remained 140 times lower than the sensitivity of TLN/AuNPs/(PVA/PEI) biosensor. The study of enzyme kinetics showed that Vi vs [OTA] plot exhibited a non-hyperbolic trend, indicating that kinetics does not display a Michaelis–Menten behavior. Biosensor response times are longer (7–48 min) comparatively to TLN/BSA biosensor with a maximal value of 25 min. This difference is due to the diffusion phenomenon through the pores of the polymer membrane. The proposed OTA biosensor was very reproducible with a relative standard deviations (RSDs) in the 3–15% range and stable over a 30-days period when stored at 4 ◦ C in 20 mM phosphate buffer between two measurements. The method was further evaluated using commercial doped olive oil samples. No pretreatment of the sample was needed for testing and no matrix effect was observed. Recovery values were close to 100% demonstrating the suitability of the proposed method for OTA screening in olive oil. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Mycotoxins are natural contaminants of the human and animal food produced by toxinogenic molds of primarily Aspergillus,
∗ Corresponding author. E-mail address: fl
[email protected] (F. Lagarde). http://dx.doi.org/10.1016/j.snb.2015.06.120 0925-4005/© 2015 Elsevier B.V. All rights reserved.
Penicillium or Fusarium genus. They affect a broad range of agricultural products including cereals, cereal-based foods, fruits (including olives), milk and meat products with potential impact on human health and economy. More than 400 different mycotoxins have been currently identified with a large variety of chemical structures and therefore physicochemical and toxicological properties [1]. Among the various existing mycotoxins, ochratoxin A (OTA) has gained much attention during the last few years due to its toxic
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effects and its increasing frequency of detection in a large variety of commodities. OTA, a weak organic acid issue from the coupling between l-phenylalanine and a dihydrocoumarins family derivative (Eq. (1)), was firstly isolated in 1965 [2]. Although the genotoxic status of OTA is still controversial, many other adverse effects such as hepatotoxicity, teratogenicity, immunotoxicity, and neurotoxicity have been demonstrated on several species of animals [3]. OTA is also highly resistant to acidity and temperature and is therefore quite impossible to remove from contaminated foodstuffs [3], which constitutes a real threat for human health. Among the various methods proposed for the assessment of food contamination by OTA, immunological techniques such as EnzymeLinked ImmunoSorbent Assays (ELISAs) and radioimmunoassays (RIAs) [4] are relatively fast, simple and suitable for OTA screening. However, several steps of purification and concentration of the extract are required before quantification. Moreover, the accuracy of immunoassays can be strongly affected by cross-reactivity of antibodies with interfering substances [5]. Chromatographic techniques using molecular fluorescence or mass spectrometric detections are more powerful and selective [6,7]. Nevertheless, these methods are costful and require a highly trained staff. They generally include pre-concentration and cleanup procedures, and even sometimes additional derivatization steps. All of these conventional analytical methods have been extensively applied to the determination of OTA in a wide range of agricultural commodities [3]. Comparatively, there is little information about olive oil contamination by OTA although this is one of the most significant products of Mediterranean countries [8]. Moreover, olives are often stored for weeks in conditions that could promote mold growth before treatment [9] and it is well known that olive oil is practically the only vegetable oil that can be consumed directly in its raw state. Therefore, the development of analytical methods that enables fast, sensitive and easy determination of OTA in olive oil, is needed.
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Based on the direct coupling between specific biological recognition elements and physical transducers, biosensors are promising alternatives to conventional analytic methods. They have been proposed for a wide range of applications including medical [10] and environmental applications [11] as well as food quality control [12]. Biosensors developed for mycotoxins detection rely on mechanical [13], optical [14] or electrochemical transduction mode [15]. Owing to their sensitivity, simplicity, low cost, and possible miniaturization and integration in automated devices, electrochemical biosensors are very promising and are currently the object of intense research. Antibodies [16], specific ligands as aptamers [17–19] and artificial receptors as molecularly imprinted polymers [20] have been extensively used for the development of selective electrochemical biosensors for mycotoxins detection. Comparatively, enzymes have been more rarely exploited, although they are cheaper to produce and easier to manipulate than antibodies or aptamers. Enzyme biosensors based on activation or inhibition processes have been reported for Altenaria mycotoxins [21] or aflatoxin B1 detection [22,23]. To the best of our knowledge, only one enzyme-based electrochemical biosensor has been proposed for OTA detection [24,25] and relies on toxin oxidation by H2 O2 using horseradish peroxidase as catalyzer. Whatever the mechanism involved, immobilization of the enzymes onto the transducer surface is a necessary and critical step in the biosensor design. This step affects the sensitivity, selectivity and robustness of biosensors by influencing enzyme orientation, stability and activity. Various immobilization strategies have been reported including adsorption, covalent binding, entrapment or cross-linking [26]. Cross-linking the enzymes with glutaraldehyde (GA) in the presence of a functionally inert protein such as bovine serum albumin (BSA) is a widespread method [27]. Using this technique, several conductometric biosensors have been developed in our group [28–30]. Enzyme entrapment in polymeric matrices has also attracted much attention in recent years. Most of the studies
Fig. 1. Interdigitated electrodes and protocols used for their modification by TLN/AuNPs/(PVA/PEI) (a), TLN/(PVA/PEI) (b), TLN/AuNPs/BSA (c) and TLN/BSA (d) biomembranes.
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carried out in view of the elaboration of electrochemical biosensors use conducting polymers such as polyaniline or polypyrrole [31] but composites based on polymer hydrogels incorporating conductive nanoparticles or nanostructures are of high interest for electrochemical biosensing applications [32]. Poly(vinyl alcohol) (PVA) is a nontoxic, hydrophilic and highly biocompatible synthetic polymer [33], with a high water content and minimal diffusion restrictions that provide the immobilized enzyme with a microenvironment close to that of the soluble one [34]. In the same way, polyethyleneimine (PEI) is a polycationic water soluble polymer bearing ionized amino groups able to interact with anionic groups located at proteins surface and constitutes a good matrix for enzyme stabilization [35]. Blending PEI and PVA produces flexible networks of high porosity with enhanced mechanical strength and thermal stability due to the formation of strong hydrogen bondings between amino groups of the PEI chain and hydroxyl groups of the PVA chain [36]. Higher water stability can be achieved by further cross-linking with glutaraldehyde (GA). In spite of these numerous advantages and their abundant use for the production of functional membranes, (PVA/PEI) blends have been very rarely used for the elaboration of biosensors [37]. In this work, an original biosensor is designed for the direct and rapid conductometric detection of OTA in olive oil. The biosensor is based on the entrapment of thermolysin enzyme (TLN) into a PVA/PEI matrix containing gold nanoparticles and cross-linked using GA vapors. The proposed method is very simple, does not require the use of additional chemicals or sample pre-treatment before analysis. This is also the first time that a biosensor is developed for OTA detection in olive oil samples. TLN is a thermostable and low cost commercial proteolytic enzyme produced by the Gram-positive bacteria Bacillus thermoproteolyticus which catalyzes the cleavage of amide bonds with a specific activity for amino acids such as phenylalanine [38]. TLN is expected to cleave the amide bond connecting l--phenylalanine to the OT␣ moiety into the OTA molecule according to Eq. (1), generating charged products, as it has been demonstrated for other proteolytic enzymes such as carboxypeptidase A and Y [39–41], Protease A or Pancreatin [42]. This capacity to degrade OTA into less toxic compounds using whole fungi or bacteria, cell extracts or isolated enzymes has been extensively evaluated in view of food detoxification [40], but this is the first time that it is used for analytical purpose. Bearing a globally negative charge at neutral pH (pI = 5.4), TLN is well-suited for incorporation into PEI based polymer matrices. A differential mode of measurement was used to minimize unspecific signal variations due to changes in medium composition or temperature. The influence of different parameters, i.e. pH, temperature and crosslinking time, on the biosensor performances was investigated and the proposed TLN immobilization method was compared to the more classical one consisting in enzyme cross-linking by GA in presence of BSA.
(GA, grade II, 25% aqueous solution), KH2 PO4 (>99%), K2 HPO4 (98%), ethanol (>99.8%), poly(ethyleneimine) (PEI branched, Mw = 750 000, 50% in water) and poly(vinyl alcohol) (PVA 88% hydrolyzed, Mw = 88 000) were purchased from Sigma. Glycerol (>99%) was from Acros Organics. All aqueous solutions were prepared using ultrapure water (resistivity >18 M cm) obtained from a MilliQ purification system. 2.2. Transducer design The transducer used consists in two pairs of gold interdigitated electrodes on a single chip (Fig. 1). It was manufactured in the Lashkaryov Institute of Semiconductor Physics (Kiev, Ukraine) by deposition on a ceramic substrate (5 mm × 30 mm). A chromium layer (50 nm thickness) was used to improve gold adherence onto the substrate (150 nm thickness). Both the digit width and interdigital distance were 20 m, and their length was about 1.0 mm, resulting in a sensitive area of about 1 mm2 for each electrode [43]. Before use, electrodes were cleaned with ultrapure water and ethanol and the pads were covered manually with BlocJelt acrylic varnish (ITW Spraytec, Asnieres sur Seine, France) for insulation. 2.3. Synthesis of gold nanoparticles Citrate-stabilized gold nanoparticles (Au NPs) were synthesized according to Turkevich and Frens method [44]. In brief, 42 mL of a solution containing 6 × 10−5 mol of gold (III) chloride trihydrate in bidistilled water was stirred and heated to reflux in a 0.1 L flask equipped with a condenser. Glassware and stirrer were cleaned before use with aqua regia, acetone and bidistilled water. Then, 14 mL of an aqueous solution containing 1.8 × 10−4 mol of sodium citrate dihydrate was added under heating. During the addition, the yellow gold chloride solution turned to brown and to ruby-red, indicating the formation of gold clusters. The mixture was allowed to react for 30 min under reflux and gentle agitation and was cooled down to room temperature under continuous stirring to yield the final NPs suspension. Gold nanoparticles were characterized by transmission electron microscopy (TEM) (Fig. S1 in Supporting information). Mean nanoparticles diameter, as calculated from TEM images using ImageJ software was 23 ± 5 nm. NPs concentration, calculated assuming that gold is arranged in a centered-face cubic lattice with a compacity factor of 0.74, and taking a value of 0.146 nm for Au radius, was 1.7 × 1012 nanoparticles/mL. 2.4. Enzyme immobilization 2.4.1. (PVA/PEI)/TLN modified electrodes Preparation of (PVA/PEI) blend: Two concentrated PVA and PEI solutions (12 wt%) were first prepared. The first one was obtained
(1) 80 ◦ C
2. Experimental 2.1. Chemicals Ochratoxin A from Petromyces albertensis (OTA, ≥98%), thermolysin (TLN) from B. thermoproteolyticus rokko (50–100 units/mg protein), bovine serum albumin (BSA, ≥96%), glutaraldehyde
by dissolving PVA powder into water at for 3 h under magnetic stirring, and then cooling it down to room temperature. PEI solution was obtained by simple dilution of the commercial 50 wt% solution in water. Adequate volumes of both solutions were further mixed under magnetic stirring overnight to achieve a homogeneous solution with a PVA/PEI mass ratio of 3 [45]. The solution was finally diluted by a factor of 100 to reduce the viscosity and facilitate further manipulations.
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Preparation of electrode membranes: Four mixtures were prepared separately. The first one contained 5 mg of TLN, 20 L of the Au NPs solution, 50 L of the diluted (PVA/PEI) solution and 30 L of 20 mM phosphate buffer pH 7. In the second one, TLN was replaced by BSA. In the third one, AuNPs solution was replaced by 20 mM phosphate buffer pH 7. In the last one, TLN and AuNPs solution were replaced by BSA and 20 mM phosphate buffer pH 7, respectively. Preparation of TLN/(PVA/PEI) modified sensors: The TLN/AuNPs/(PVA/PEI) sensors were produced by casting 0.4 L of the first mixture on the working pair of electrodes (Fig. 1a) while 0.4 L of the second mixture was deposited on the reference pair. Controls without AuNPs, called “TLN/(PVA/PEI) sensors”, were prepared the same way except that the first mixture was replaced by the third (Fig. 1b) and the second was replaced by the fourth. 2.4.2. BSA/TLN modified electrodes The TLN/BSA modified electrodes, containing or not AuNPs (“TLN/BSA sensors” and “TLN/AuNPs/BSA sensors”, respectively) were prepared using the same methodology as for PVA/PEI modified electrodes, except that (PVA/PEI) solution was replaced by 5 mg of BSA and then 10% (m/v) glycerol was added (Fig. 1c and d). All the TLN/(PVA/PEI) and TLN/BSA based solutions were prepared just before the first utilization and stored at −20 ◦ C until further use. Glycerol or (PVA/PEI) matrix helps protecting the enzyme upon low temperature degradation when stored in solution at −20 ◦ C. All sensor chips were subsequently placed in a saturated GA vapor atmosphere for cross-linking. Then, membranes were dried at room temperature for 1 h and biosensors were kept dry overnight at 4 ◦ C. Biosensors were used immediately after their preparation or stored in a 20 mM phosphate buffer at 4 ◦ C until measurements.
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polarization concentration on the microelectrode surface. After stabilization of the differential output signal, small aliquots (5–75 L) of concentrated solutions of OTA prepared in 5 mM phosphate buffer and ethanol 1:1 (v:v) were added to achieve final concentrations in the 0.5–150 M range for the TLN/BSA modified sensors and 2–200 nM range for the TLN/AuNPs/(PVA/PEI) modified sensors. OTA concentrated solutions were stored in the dark and used within two weeks. Three replicate measurements were performed for each OTA concentration. The biosensor response, corresponding to the evolution of the differential conductance after OTA addition, was recorded. The observed steady-state response Gss (Fig. 2) results from the equilibrium between the production of ions inside the membrane through the enzymatic reaction and the diffusive flux of enzymatic reaction products away from the transducer surface, in the boundary layer. Initial rates of reaction were calculated from the first linear portion of the conductometric response (Vi ). The background noise (N) was measured in the stable part of the response just before injection. The detection limit was calculated as OTA concentration generating a Gss /N of 3. 2.7. Olive oil samples preparation Virgin olive oil sample was bought in a French supermarket and used as purchased or spiked with different OTA concentrations. For that, a 15 M OTA solution was prepared in ethanol and different volumes were added to 100 mL olive oil to achieve concentrations of 1.25, 5 and 10 M OTA. Then, 20 L of each solution was injected in the measurement cell to get final concentrations of 5, 20 and 40 nM OTA. 3. Results and discussion
2.5. Atomic force microscopy analysis (AFM) AFM characterizations were performed using square gold substrates, fabricated by the Laboratoire d’Analyse et d’Architecture des Systèmes (LAAS, CNRS Toulouse), and covered by TLN/AuNPs/(PVA/PEI) or TLN/BSA biomembranes prepared as described in the previous section. (1 0 0)-Oriented, P-type (3–5 cm) silicon wafers were thermally oxidized to grow a 800 nm-thick field oxide. Then, a 30 nm-thick titanium layer followed by a 300 nm-thick gold top layer were deposited by evaporation under vacuum. AFM measurements were performed in air under ambient conditions (minimum resolution: 5 m2 ) using a Nano observer instrument (CSI Company, France) and a BIO 77 silicon nitride Si3 N4 tip (LOT Oriel group Europa, Germany) for contact mode. The cantilever contained a “V” shaped sharp silicon tip bearing an integrated standard profile tip (nominal spring constant: 1.3 N/m, frequency: 95.87 kHz, 100 m length, 18 m width and 0.60 m thickness). Images were recorded at 893 mV amplitude, −519 mV set point, tip DC at 596 nV and a tip Bias DC of 5.96 × 10−7 . Measurements were performed in contact mode with a speed of 1.25 lines per second and 1024 resolution (5 m × 5 m) spots were analyzed. 2.6. Conductometric measurements Measurements were carried out in 5 mL of a 5 mM phosphate buffer solution pH 7 under magnetic stirring using a double wall glass electrochemical cell thermostated with a Minichiller circulating thermal regulator from Huber (Germany). The biosensor was immersed in the solution and an alternating voltage (10 mV amplitude, 100 kHz frequency) generated by a low-frequency wave-form generator (SR830 Lock-in amplifier from Stanford Research Systems) was applied. These conditions were used to reduce faradaic processes, double-layer charging and
3.1. AFM characterization of TLN/BSA and TLN/AuNPs/(PVA/PEI) biomembranes The influence of TLN mode of immobilization on the topography of TLN/AuNPs/(PVA/PEI) and TLN/BSA sensors surface was investigated by AFM. For that, TLN/AuNPs/(PVA/PEI) and TLN/BSA biomembrane solutions, prepared as described in Section 2.3, were casted on 1 cm2 square gold electrodes and a central zone of 0.5 cm2 was explored by analyzing 200 spots of 25 m2 each. No significant difference was obtained from one spot to another. The same procedure was used to characterize the gold substrate before biomembrane casting. A homogenous granular surface with globular particles of about 50 nm diameter was observed for the bare gold electrode (Fig. 3a), while the gold surface covered with TLN/AuNPs/(PVA/PEI) biomembrane displayed an organized and homogeneous surface with tubular structures of 1250 ± 120 nm length, 397 ± 11 nm width and 309 ± 50 nm height (Fig. 3b). About 120 structures of this type were found per 25 m2 . These objects may correspond to cross-linked polymeric structures encapsulating gold nanoparticles and TLN, the tubular arrangement adopted resulting from the interactions between protonated amino groups of highly branched PEI [46] and negative charges of both citrated AuNPs and TLN (pI = 5.1). Replacement of the polymer blend by BSA and glycerol resulted in a completely different but still homogeneous organization and assembling of the surface (Fig. 3c). In this case, globular type structures with an average height of 269 ± 22 nm and an average diameter of 397 ± 24 nm were observed. BSA is a globular protein with approximate dimensions of 4 nm × 4 nm × 14 nm. Sequential adsorption of BSA onto various substrates, e.g. gold [47], mica [48,49] or polymers [50,51] have been investigated and characterized by AFM. The observed morphology of protein patterns depends on the substrate and on BSA concentration of the solution in contact with the solid
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Fig. 2. Evolution of the trends of a typical biosensor response and main parameters deduced with OTA concentration. Concentration 1 < Concentration 2 < Concentration 3.
support but topography is generally different form the one we observed. Recently, Jasti et al. reported the formation of crosslinked trypsin aggregates on BSA-coated polymer support. BSA deposits of average 180–230 nm diameter and 55 nm height were observed by AFM, while further binding of trypsin produced objects of 700–900 nm breadth and 90 nm height [51]. In our work, BSA and TLN are not adsorbed sequentially but casted simultaneously onto the electrode. However, we may reasonably hypothesize that the protuberant structures observed in Fig. 3c also correspond to TLN/BSA cross-linked aggregates owing to the highly concentrated protein solutions prepared for the elaboration of BSA sensors (5 wt% of each protein in 20 mM phosphate buffer). 3.2. Optimization of AuNPs/PVA/PEI biosensor 3.2.1. Cross-linking time Cross-linking time is an important parameter that affects the stability and permeability of sensor membranes. In order to define
optimal cross-linking conditions, three TLN/AuNPs/(PVA/PEI) biosensors were prepared, setting the exposure times to saturated GA vapors at 15 min, 25 min, 35 min, 45 min and 60 min, respectively. As shown in Fig. 4 (full symbols), the steady-state biosensor response recorded after injection of 8 nM OTA increased with crosslinking time until 35 min and decreased beyond this value. The same trend was observed for TLN/BSA biosensor, but variations were more pronounced in this case (Fig. 4, open symbols). For example, 60% of the BSA sensor signal was lost by decreasing the cross-linking time from 35 to 25 min, while the signal decreased only by 15% for the AuNPs/PVA/PEI modified electrode. The lowest values observed at the shortest exposure time (15 min) may be attributed to (i) enzyme leakage due to insufficient cross-linking and/or (ii) TLN inactivation due to the relative high conformational freedom of the enzyme within the cross-linked network. Increasing the exposure time to 25 min resulted in the formation of a tighter polymer network, limiting release and flexibility of the enzyme and generating enhanced responses. However, a lack of linearity
Fig. 3. AFM images of 5 m × 5 m the bare gold electrode (a), the TLN/AuNPs/(PVA/PEI) (b) and the TLN/BSA (c) biomembranes.
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values ranging from 5 to 9 for a 4 nM OTA concentration (Fig. 5a). The response increased up to pH 6, remained stable in the 6–7 range and sharply declined afterwards, in good agreement with results reported for free TLN catalyzing the hydrolysis of either N-furylacryloylglycyl-l-leucinamide [52] or Z-Gly-Leu-Ala peptide [38]. Comparatively, the range of optimal working pH was slightly wider (6–8) for the TLN/BSA modified electrode. pH 7 was therefore retained for further measurements.
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0 10
15
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25
30
35
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Cross-linking time, min Fig. 4. Effect of cross-linking time on the steady-state response of TLN/AuNPs/(PVA/PEI) modified electrode after injection of 8 nM OTA (䊏), and BSA/TLN modified electrode after injection of 10 M OTA (䊐). The conductance variations were calculated by comparison to the maximum which was set at 100% (n = 3).
of TLN/AuNPs/(PVA/PEI) biosensor response was observed at this exposure time value (Fig. S2, full triangles, in Supporting information). Improvement of signal intensity and linearity by increasing exposure time to 35 min (Fig. S2, full circles) was consistent with the rigidification of TLN structure and network tightening induced by higher cross-linking degree. Higher reaction times resulted in increased conformational constraints and led to enzyme inactivation. Release and denaturation processes are likely to be attenuated in presence of (PVA/PEI) matrix, the latter being able to create a more favorable environment around the enzyme and to prevent its release by forming hydrogen and ionic bindings. Considering these results, a 35-min exposure time was chosen for further experiments. 3.2.2. pH of electrolyte solution It is well known that enzyme activity depends on pH and that optimal working range may be different depending on whether the enzyme is immobilized or free in solution. To determine the optimal working pH, TLN/AuNPs/(PVA/PEI) biosensor was prepared in quadruplicate and measurements were performed at different pH
3.2.3. Working temperature In a further set of experiments, we investigated the influence of temperature on TLN/AuNPs/(PVA/PEI) biosensor response in the 10–50 ◦ C range. (PVA/PEI) blends are known to be highly stable and are not expected to degrade in this domain of temperature [36]. As seen in Fig. 5b, the signal was maximal in the 20–40 ◦ C domain and was similar to that obtained for TLN/BSA sensor. The steadystate response of both biosensors was divided by 2 by increasing the temperature from 40 to 50 ◦ C. This result is not likely to be due to thermal inactivation of the enzyme. Indeed, free TLN has been reported as one of the most thermostable metalloproteases able to keep 50% activity even after 30 min incubation at 87 ◦ C [53]. Moreover, immobilization process is expected to rigidify the protein structure, resulting in enhanced thermal stability. The significant fall in biosensor signals may be ascribed to OTA degradation or binding to the biomembrane [54]. Taking into account results from the pH and temperature optimization experiments, biosensors were further operated at 25 ◦ C and pH 7. 3.3. Analytical characteristics of the biosensors 3.3.1. Biosensors linearity and sensitivity The linearity and sensitivity of TLN/AuNPs/(PVA/PEI) biosensors were assessed and compared to the performances of TLN/BSA biosensors. For that, 10 standard solutions were used and three measurements were performed at each concentration level. As expected, an increase in conductance was observed upon addition of increasing amounts of OTA in both cases (Fig. 6). However, the sensitivity was considerably improved by replacing BSA by AuNPs/(PVA/PEI) composite in the biosensor fabrication. The best limit of detection (LOD), obtained for AuNPs/PVA/PEI biosensor, was 1 nM, 700 times better than for BSA biosensor (0.7 M). The conductometric response was linear up to 60 nM for the AuNPs/PVA/PEI biosensor and up to 75 M for the TLN/BSA biosensor. A large number of electrochemical biosensors have been
Fig. 5. Effect of pH (a) and temperature (b) on the biosensors response. 䊏: TLN/AuNPs/(PVA/PEI) modified electrode; [OTA] = 4 nM; 䊐: BSA/TLN modified electrode; [OTA] = 5 M.
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Table 1 Comparison of analytical performances of the proposed TLN conductometric biosensor with other electrochemical biosensors recently reported in the literature. CA: chronoamperometry; EIS: electrochemical impedance spectroscopy; DPV: differential pulse voltammetry; SWV: square wave voltammetry; CV: cyclic voltammetry; GO: graphene oxide. Bioreceptor
Detection
Linear range (nM)
Limit of detection (nM)
Nanomaterials
Real samples analysis
Reference
Enzymes
CA CA Conductometry
24–203 0.25–2 2–100
27 0.25 1
No No Au NPs
Spiked beer Spiked beer and roasted coffee Spiked olive oil
[24] [25] This work
Antibodies
EIS
Up to 24 2.47–50 0.024–12 Up to 148 2.5–2500 0.024–50
2.4 1.2 0.024 30 0.5 0.020
No No Magnetic NPs No Au NPs Magnetic NPs
No No Spiked white wine No Spiked corn Spiked red wine
[56] [57] [58] [59] [60] [61]
No Au NPs Au NPs No Au NPs Au NPs Au NPs/GO
Spiked wheat Spiked red wine Spiked red wine Spiked red wine Spiked red wine Spiked beer Spiked red wine
[62] [63] [19] [64] [65] [66] [18]
CA DPV SWV Aptamers
CA DPV SWV CV EIS EIS
0.024–0.050 0.001–50 0.0025–2.5 0.00024–2.4 0.24–50 0.1–100 0.001–123
0.001 0.0003 0.00075 0.0002 0.07 0.02 0.00074
already reported for OTA detection, most of them relying on the affinity of the molecule for specific antibodies or aptamers [18–19,55–66]. As seen in Table 1, aptasensors recently proposed in the literature are far more sensitive than any other type of biosensor ever proposed. However, their elaboration is generally based on sophisticated architectures that require the use of multiple and/or additional costful components and their operation is
Fig. 6. Evolution of biosensors response with OTA concentration TLN/AuNPs/(PVA/PEI) (a) and BSA/TLN (b) modified electrodes (n = 3).
for
so complex that a low-cost mass production of these devices as well as their repeated use for real samples analysis can not be reasonably envisaged. Compared to them, our biosensor offers the advantages to be more simple and robust, to rely on the direct detection of OTA and to be easily regenerable using phosphate buffer. Its LOD is close or lower than most of the recently developed immunosensors and than the only two existing enzyme-based biosensors (Table 1). In order to evaluate the contribution of AuNPs and (PVA/PEI) polymer matrix to the differences observed between TLN/AuNPs/(PVA/PEI) and TLN/BSA biosensors response, two sets of controls (AuNPs/BSA/TLN and (PVA/PEI)/TLN biosensors) were prepared as described in Section 2.3 and measured for OTA concentrations of 0.5, 1 and 2 M. No significant response was observed for the TLN/(PVA/PEI) sensor, which is consistent with insulating properties of the cross-linked (PVA/PEI) hydrogel film at the surface of the flat interdigitated electrode (Fig. S3, full triangles, in Supporting information). The film of micrometric thickness contains TLN but only a very small amount of enzymes located in some tenths or hundred nanometers at the gel-electrode interface can produce a signal, which is hardly detectable. AuNPs offer high conductivity and large surface area due to their small diameter. The conductive nano-objects, when incorporated into the hydrogel, can act as implanted nanoelectrodes that shorten charge transfer distances and electrical wire between the active sites of the enzyme and the electrode [67]. The formation of composites with hydrogels ensures a better dispersion of the NPs, favoring enzyme stabilization and accessibility of the substrate, and producing films with enhanced mass transport and electron transfer properties [68]. For these different reasons, NPs/hydrogels nanocomposites are particularly attractive for the elaboration of electrochemical biosensors [32]. A significant enhancement of BSA sensor sensitivity was also observed following the incorporation of AuNPs (4.286 S/M instead of 0.8059 S/M, as seen in Fig. S3, full squares), confirming the positive effect of the conductive nano-objects on the conductometric signal, in agreement with previous results obtained in our group [69]. However, the substitution of (PVA/PEI) blend by BSA induced a significant loss of sensitivity (4.286 S/M instead of 597 S/M). It may be hypothesized that OTA diffusion through the TLN/AuNPs/BSA or TLN/BSA network is hindered due to the formation of cross-linked aggregates, while OTA access to the enzyme is facilitated when high water content and porous TLN/AuNPs/(PVA/PEI) hydrogel is used as immobilization matrix.
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Fig. 7. Initial velocity Vi as a function of OTA concentration for TLN/BSA modified electrode (a) and TLN/AuNPs/(PVA/PEI) modified electrode (b). Full circles: experimental data, dashed line: recalculated curve after fitting. Fig. 8. Evolution of TLN/AuNPs/(PVA/PEI) (a) and TLN/BSA (b) biosensors response time with OTA concentration (n = 3).
3.3.2. Biosensor response time The influence of TLN mode of immobilization on the kinetics of OTA degradation was further investigated. This process is governed by both enzymatic reaction and substrate/products diffusion through the biomembrane. The initial rate of degradation was assumed to be proportional to Vi = d(G)/dt at t = 0 and was deduced from the first linear portion of the biosensors response. As shown in Fig. 7a, Vi vs [OTA] plot exhibits an hyperbolic form in the 0–150 M range when TLN is immobilized by cross-linking in the presence of BSA. The Michaelis–Menten behavior of TLN was confirmed by fitting experimental data to the linearized form of Michaelis–Menten equation (Eq. (2)): app
K 1 1 1 = app + M app × [OTA] Vi Vmax Vmax app
app
(2)
are the theoretical apparent where Vmax and KM Michaelis–Menten maximal reaction velocity and constant. The 1/Vi vs 1/[OTA] curve fitted well with a linear model app app (r2 = 0.993) and KM and Vmax , deduced from the slope and intercept of the regression line, were respectively 26 M and 3.3 S min−1 (Fig. S4 in Supporting information). Comparatively, an ordinary Michaelis–Menten mechanism was observed for the TLN reaction [70] and Morihara and Tsuzuki reported KM values in the mM range for model tripeptides containing phenylalanine (e.g. Z-Phe-Gly-Ala, Z-Phe-Leu-Ala, Z-Phe-Gly-Ala) [38]. However, in this case hydrolysis was catalyzed by free and not immobilized thermolysin and substrates were different from OTA. It is known
that thermolysin immobilization can result either in a decrease or in an increase of KM value [71]. Fig. 7b represents Vi vs [OTA] plot obtained for TLN/AuNPs/(PVA/PEI) biosensor. The trend of the curve is obviously nonhyperbolic, indicating that kinetics does not display a Michaelis–Menten behavior. A low regression coefficient (r2 = 0.9574) was obtained by trying to fit the data of 1/Vi vs 1/[OTA] curve with a linear regression model. The observed cooperativity phenomenon could be explained by OTA transfer constraint from macroenvironment to the electrode microenvironment coupled to TLN-catalyzed hydrolysis. It is likely that a more complex model including not only Michaelis–Menten but also diffusion terms should be used to fit data in this case [72]. In addition to the initial velocity, one important information extractable from the biosensor response is the time needed to achieve steady-state response. As seen in Fig. 8a, biosensor response time increased from 7 to 48 min for OTA concentrations varying in the 4–200 nM range for the TLN/AuNPs/(PVA/PEI) sensor. Comparatively, TLN/BSA modified electrodes exhibited shorter response times, with a maximal value of only 25 min achieved for about 150 M OTA (Fig. 8b). This difference is consistent with a lower rate of diffusion through the pores of the polymer membrane. 3.3.3. Inter-sensor and intra-sensor short-term reproducibility Reproducibility is one of the most essential factors for biosensors practical application.
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Table 2 OTA recoveries in fortified olive oil samples. SDs were calculated from three replicate measurements. Added concentration (M)
Detected concentration (M)
Recovery ± SD (%)
1.25 5 10
1.20 4.9 10.1
96 ± 3 98 ± 4 101 ± 3
Intra-sensor short-term reproducibility was first calculated from the three measurements of OTA performed at each concentration level of the calibration curves presented in Fig. 6. Relative standard deviations (RSDs) were between 2% and 6% in the concentration range studied. Inter-sensor reproducibility was also determined at different OTA concentrations in the linear part of the calibration curves using four different electrodes. RSDs were in the 3–15% range for the TLN/AuNPs/(PVA/PEI) modified electrode and in the 4–20% range for the TLN/BSA modified electrode, indicating a relatively good inter-sensor reproducibility of both types of modified electrode. 3.3.4. Storage stability Long-term storage stability was also studied. For that, four modified electrodes of each type were fabricated and their responses were measured at irregular intervals over 30 days. In the meantime, electrodes were rinsed with doubly distilled water and stored at +4 ◦ C in 20 mM phosphate buffer (pH 7). As shown in Fig. S5 (Supporting information), biosensors were stable over a long period. Only 5% of the initial value was lost after 15 days and more than 90% remained after 30 days, independently of the enzyme immobilization method. The slight decrease of biosensors response observed after 15 days may be attributed to the progressive decrease of TLN activity. From these results, it can be concluded that (PVA/PEI) polymers and BSA have a similar protecting and stabilizing effect on TLN. 3.3.5. OTA determination in olive oil samples TLN/AuNPs/(PVA/PEI) biosensor was further used to evaluate its ability to quantify OTA in olive oil samples. A commercial olive oil sample, was spiked at three concentration levels (1.25, 5 and 10 M OTA) and 20 L of each of the raw and fortified samples was injected in the 5 mL electrochemical cell. No response could be recorded in the raw sample, showing that OTA concentration was below 0.25 M. OTA quantification in fortified samples was performed using the calibration curve presented in Fig. 6a. As shown in Table 2, recovery values were close to 100%, demonstrating the applicability of the biosensor to the analysis of olive oil real samples. Tests were carried out without any pretreatment of the sample, OTA being released directly into the buffer from the drop of immiscible oil. 4. Conclusion A novel method for TLN immobilization into a (PVA/PEI) polymer matrix including AuNPs was proposed for the elaboration of an enzyme biosensor for OTA determination. The TLN/AuNPs/(PVA/PEI) based method enabled improving the limit of detection by a factor of 700. A linear response was achieved up to 60 nM OTA. The biosensor exhibited shorter response times, with a maximal value of 48 min achieved for about 200 nM OTA. Longterm stability over 30 days and good reproducibility inter and intra sensors were also observed. The newly designed biosensor was successfully applied to the quantification of OTA in olive oil samples demonstrating the suitability of the proposed method for practical application to olive oil analysis without any pretreatment of the
sample and with a recovery values close to 100%. No matrix effect was recorded. The proposed method is far simpler and faster than HPLC. It does not require the use of expensive reagents as ELISA and it does not depend on the optical properties of the sample as it is the case of spectrophotometric methods. Owing to the small size of the electrodes and the availability of portable instrumentation, this method may be also easily adaptable for on-site analysis. The ease of performance and cost effectiveness of the proposed system for OTA detection and the good results obtained in terms of recovery in real samples demonstrate the high potential of this method as a screening procedure for OTA in olive oil samples. Acknowledgments This work was supported through PHC Utique programme (project n◦ 12G0911), by NATO’s Public Diplomacy Division in the framework of “Science for Peace” (project CBP. NUKR SFP 984173) and EU through IRSES Marie Curie NANODEV project n◦ 318524. F. Dridi thanks the Ministry of Higher Education of Tunisia and French Institute of Tunis for her mobility grants. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.snb.2015.06.120 References [1] S. Marin, A.J. Ramos, G. Cano-Sancho, V. Sanchis, Mycotoxins: occurrence, toxicology, and exposure assessment, Food Chem. Toxicol. Int. J. Publ. Br. Ind. Biol. Res. Assoc. 60 (2013) 218–237. [2] K.J. van der Merwe, P.S. Steyn, L. Fourie, D.B. Scott, J.J. Theron, Ochratoxin A, a toxic metabolite produced by Aspergillus ochraceus, Nature 205 (1965) 1112–1113. [3] A. el Khoury, A. Atoui, Ochratoxin a: general overview and actual molecular status, Toxins 2 (2010) 461–493. [4] E.P. Meulenberg, Immunochemical methods for ochratoxin A detection: a review, Toxins 4 (2012) 244–266. [5] H.J. Lee, A.D. Meldrum, N. Rivera, D. Ryu, Cross-reactivity of antibodies with phenolic compounds in pistachios during quantification of ochratoxin A by commercial enzyme-linked immunosorbent assay kits, J. Food Prot. 77 (2014) 1754–1759. [6] K.T.N. Nguyen, D. Ryu, Development of a stir bar sorptive extraction method for analysis of ochratoxin A in beer, J. AOAC Int. 97 (2014) 1092–1096. [7] I.R. Pizzutti, A. de Kok, J. Scholten, L.W. Righi, C.D. Cardoso, G.N. Rohers, R.C. da Silva, Development, optimization and validation of a multimethod for the determination of 36 mycotoxins in wines by liquid chromatography–tandem mass spectrometry, Talanta 129 (2014) 352–363. [8] R. Ferracane, A. Tafuri, A. Logieco, F. Galvano, D. Balzano, A. Ritieni, Simultaneous determination of aflatoxin B1 and ochratoxin A and their natural occurrence in Mediterranean virgin olive oil, Food Addit. Contam. 24 (2007) 173–180. [9] A. Papachristou, P. Markaki, Determination of ochratoxin A in virgin olive oils of Greek origin by immunoaffinity column clean-up and high-performance liquid chromatography, Food Addit. Contam. 21 (2004) 85–92. [10] J. Kirsch, C. Siltanen, Q. Zhou, A. Revzin, A. Simonian, Biosensor technology: recent advances in threat agent detection and medicine, Chem. Soc. Rev. 42 (2013) 8733–8768. [11] F. Lagarde, N. Jaffrezic-Renault, Cell-based electrochemical biosensors for water quality assessment, Anal. Bioanal. Chem. 400 (2011) 947–964. ´ ´ [12] M. Sliwi nska, P. Wi´sniewska, T. Dymerski, J. Namie´snik, W. Wardencki, Food analysis using artificial senses, J. Agric. Food Chem. 62 (2014) 1423–1448. [13] X. Jin, X. Jin, X. Liu, L. Chen, J. Jiang, G. Shen, R. Yu, Biocatalyzed deposition amplification for detection of aflatoxin B1 based on quartz crystal microbalance, Anal. Chim. Acta 645 (2009) 92–97. [14] J.-H. Park, J.-Y. Byun, H. Mun, W.-B. Shim, Y.-B. Shin, T. Li, M.-G. Kim, A regeneratable, label-free, localized surface plasmon resonance (LSPR) aptasensor for the detection of ochratoxin A, Biosens. Bioelectron. 59 (2014) 321–327. [15] J.C. Vidal, L. Bonel, A. Ezquerra, S. Hernández, J.R. Bertolín, C. Cubel, J.R. Castillo, Electrochemical affinity biosensors for detection of mycotoxins: a review, Biosens. Bioelectron. 49 (2013) 146–158. [16] J.C. Vidal, L. Bonel, A. Ezquerra, P. Duato, J.R. Castillo, An electrochemical immunosensor for ochratoxin A determination in wines based on a monoclonal antibody and paramagnetic microbeads, Anal. Bioanal. Chem. 403 (2012) 1585–1593.
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Biographies Fatma Dridi received her M.Sc. degree in Microbiology from the Tunis El Manar University in 2010. She is currently a Ph.D. student at the National Institute of Applied Science and Technology (INSAT) from Carthage University and the Institute of Analytical Sciences (ISA) from the University of Lyon. Her research work is focused on the design and development of new enzymatic electrochemical biosensors for ochratoxin A detection. Mouna Marrackchi is Assistant Professor in the Higher Institute of Applied Biological Sciences of Tunis (ISSBAT) at Tunis El Manar University and researcher in the Laboratory of Microbial Ecology and Technology at INSAT. She received her engineering degree in Industrial Biology from INSAT in 2002 and her M.Sc. degree in Medical and Biological Engineering from the University of Lyon in 2003. In December 2006, she obtained her Ph.D. in Bioengineering from the Ecole Centrale of Lyon. Her research activities deal with the immobilization of bioreceptors such as enzymes, aptamers, microorganisms and antibodies for biosensors development and their application in various fields. Mohamed Gargouri is Professor in Bioengineering at INSAT. He received his M.Sc. degree in Enzymatic Engineering, Bioconversion and Microbiology from the Technological University of Compiègne in 1994 and a Ph.D. in Biochemistry-Biotechnology at La Rochelle University in 1997. His research activities deal with enzyme engineering in non-conventional media applied in bioenergy, biomolecule production, in food or analytical purposes; as biorefinery of extremophile plants, aroma biosynthesis coupled to extraction, enzyme process modelization, and involvement of oxidative or hydrolytic enzymes in the improvement of food quality as well as biosensors for toxin analysis. Alvaro Garcia-Cruz received his Chemical Engineer degree at the University of Guanajuato, Mexico, in 2008, and a M.Sc. degree in Catalysis and Physical Chemistry from the Claude Bernard University Lyon 1 in 2010. He is currently a Ph.D. student at ISA, working in the design, fabrication and characterization of chemical sensors and biosensors for various applications in the frame of NATO and European projects (SensorART, SEA-on-CHIP, HEARTEN). He had an excellence scholarship from CONACYT from 2012 until 2015. Sergei Dzyadevych is Full Professor at the Institute of High Technologies of Taras Shevchenko Kiev National University (TSKNU) and Chief researcher of the Laboratory of Biomolecular Electronics at the Institute of Molecular Biology and Genetics (National Academy of Sciences of Ukraine). He received his M.Sc. degree in
Radiophysics and Electronics from TSKNU in 1992, a Ph.D. degree in Biotechnology from Palladin Institute of Biochemistry (Kiev) in 1995 and a Doctor Science degree in Biotechnology in 2005. His fields of interest are conductometric, ENFETs and amperometric biosensors, mainly applied to biomedical, food and environmental monitoring. He published more than 110 papers. Francis Vocanson is Full Professor in Chemistry at the Jean Monnet University. He received his M.Sc. degree in Industrial Chemistry in 1990 and a Ph.D. degree in Chemistry in 1994 from the University Lyon 1. His main current research activities deal with the synthesis and characterization of micro and nanostructured materials based on inorganic materials prepared by sol–gel methods (SiO2 , TiO2 ) and on metallic nanoparticles (Au, Ag) for optics and sensors applications. Joelle Saulnier is Associate Professor at the University of Lyon. She received her M.Sc. degree in biochemistry in 1985 and her Ph.D. degree in biochemistry at the University of Lyon in 1989. She began her career at the University of Lyon in the laboratory of Analytical Biochemistry in 1991 and joined the Institute of Analytical Sciences in 2008. Her research interests include the development of specific and selective enzymatic assays and biosensors for enzyme and metabolite detection in various samples, with a particular focus on the optimization of enzyme behavior in solution and at liquid–solid interfaces. Nicole Jaffrezic-Renault is Director of Research Emeritus at the National Center for Scientific Research (CNRS). She received her engineering degree from the Ecole Nationale Supérieure de Chimie, Paris, in 1971 and a Ph.D. in Physical Sciences from the University of Paris in 1976. She joined Claude Bernard University Lyon 1 in 2007. Past president of the Chemical Micro Sensor Club (CMC2), president of the Analytical Division of the French Chemical Society, she has coordinated several European and national projects and published more than 500 papers with more than 7900 citations. Her research activities at ISA include the conception and design of (bio)chemical sensors and their integration in microsystems. Florence Lagarde is full-time researcher at CNRS since 1991. She graduated from the ENSIC engineer school, Nancy, and obtained a M.Sc. in chemical engineering in 1987. She received her Ph.D. degree in Polymer Physical Chemistry from the University of Strasbourg in 1991. She started her career at the Laboratory of Inorganic and Analytical Chemistry of Strasbourg and joined the Institute of Analytical Sciences, Lyon University, in 2004. She currently develops innovative strategies for the robust and efficient immobilization of biomolecules or biomimics onto electroactive surfaces in view of the development of electrochemical biosensors for environmental, food and health applications.