Nanobiosensor for Diclofop Detection Based on
Chemically Modified AFM P...
called functionalization. This technique is used to change
the chemica...
program [44]. All the undetermined force ...
cantilever surface. The next step in the treatment was the
Fig. 3. AFS force curves recorded in a PBS solution buffer at pH 7.0 f...
Fig. 5. Adhesion force histograms (n=19) for the occurrences (rela...
[16] S. Topuz, G. Ozhan, and B. Alpertunga, “Simultaneous determinatio...
[59] A. Noy, C. D. Frisbie, L. F. Rozsnyai, M. S. Wrighton, and C....
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Nanobiosensor for diclofop detection based on chemically modified afm probes (ieee sensors)

Published on: Mar 3, 2016

Transcripts - Nanobiosensor for diclofop detection based on chemically modified afm probes (ieee sensors)

  • 1. IEEE SENSORS JOURNAL, VOL. 14, NO. 5, MAY 2014 1467 Nanobiosensor for Diclofop Detection Based on Chemically Modified AFM Probes Carolina Castro Bueno, Adriano Moraes Amarante, Guedmiller S. Oliveira, Daiana Kotra Deda, Omar Teschke, Eduardo de Faria Franca, and Fábio L. Leite Abstract—Highly sensitive and selective functional nanobio- breaksensors are being developed because they have significant applications in the sustenance and conservation of natural resources and can be used in projects to identify degraded and contaminated areas (of both soil and water) and as environmental quality indicators. In the present study, a nanobiosensor was developed based on using theoretical models (molecular docking and molecular dynamics simulations) based on biomimicry of the action mechanism of herbicides in plants coupled with atomic force microscopy (AFM) tools. The herbicide molecules were detected at very low concentrations using a unique sensor construction: the AFM probes and the substrate were chemically functionalized to favor covalent bonding and promote molecular flexibility, as well as to achieve reproducible and accurate results. Computational methods were used to determine the binding energies associated with the enzyme-herbicide interactions, which were compared with experimental results for adhesion forces. The theoretical results showed that the diclofop herbicide could be assembled and attached onto the mica substrate surface and the ACCase enzyme on the AFM probe without damaging the diclofop molecule. The experimental results showed that using a specific agrochemical target molecule was more efficient than using other nonspecific agrochemicals. On average, there was a 90% difference between the values of specific recognition (diclo- fop) and nonspecific recognition (imazaquin, metsulfuron, and glyphosate). This result validated the selectivity and specificity of the nanobiosensor. The first evidence of diclofop detection by the AFM probe sensors has been presented in this paper. Index Terms—AFM, agrochemical detection, diclofop, enzyme- based nanobiosensor, molecular docking, molecular dynamics simulation. I. INTRODUCTION FOOD production was greatly increased in the nineteenth century by technological improvements in agricultural Manuscript received October 15, 2013; revised December 27, 2013; accepted January 8, 2014. Date of publication January 28, 2014; date of current version March 18, 2014. This work was supported in part by CAPES, in part by CNPq, in part by FAPESP under Grant 2007/05089-9, 2013/09746- 5, Proc. 2009/09120-3), CAPES, CNPq, nBioNet and in part by the Institute of Physics Gleb Wataghin. The associate editor coordinating the review of this paper and approving it for publication was Dr. Chang-Soo Kim. C. Castro Bueno, G. S. Oliveira, A. M. Amarante, D. K. Deda, and F. L. Leite are with the Nanoneurobiophysics Research Group, Department of Physics, Chemistry and Mathematics, Federal University of São Carlos, Sorocaba 18052-780, Brazil (e-mail:;;; daianakdn@; E. de Faria Franca is with the Chemistry Institute, Federal University of Uberlândia, Uberlândia 18052-780, Brazil (e-mail: O. Teschke is with the Institute of Physics Gleb Wataghin, Uni- versidade Estadual de Campinas, Campinas 13083-970, Brazil (e-mail: Color versions of one or more of the figures in this paper are available online at Digital Object Identifier 10.1109/JSEN.2014.2301997 techniques, such as the use of modern machinery, fertilisers, and agrochemical molecules [1], [2]. The indiscriminate use of agrochemicals on crops resulted in environmental con- tamination and toxic effects on human health [3], such as carcinogenic effects [4], [5] and in vivo and in vitro genotoxic effects on mammalian cells from chromosomal aberrations [6]. Current agrochemical detection methods rely almost entirely on mass spectroscopy (MS) [7], [8], magnetic solid phase extraction (MSPE) [9], gas chromatography-electron cap- ture (GC-ECD) [10], [11] via bacterial bioluminescent response [12], and high performance liquid chromatography (HPLC) [13], [14]. It is quite difficult to increase the detection limit (the sensitivity range) of these methods, and samples are frequently reported to thermally degrade before the detection procedure can be performed. In regard to its limits of detection for agrochemicals, it was reported 1µg/kg (HPLC) [15] and 0.1–4.6 µg/L (GC-MS) [16], for example. These values are not compensatory when confronted with the disadvantages of these techniques: costly apparatus, organic solvents, and purification of samples prior to assay, limiting the number of samples that can be examined. Recently, experimental studies and theoretical models have begun to address the challenge of establishing a causal link between subjective computational models and activity that can be measured in the laboratory in practice. Atomic force microscopy (AFM)-based sensors and biosensors (called nanobiosensors) have been fairly promising in exhibiting out- standing performance for detecting molecules with high speci- ficity and selectivity [17]–[19]. Understanding the theoretical and experimental physicochemical conditions and architec- tures of the molecules involved in nanosensor construction requires precise experimental management, such as to identify the ideal solution concentrations and pH of the medium, simulate the behavior of a smart surface, maintain system stability, and confirm that the sensory and target molecules retain their original characteristics, such as the ability to inhibit and to be inhibited. Thus, chemically modified AFM cantilever/probes can be matched with specific detection meth- ods and theoretical results for the entire process to create a sensor that can detect a wide variety of substances at very low concentrations. Atomic force spectroscopy (AFS) is generally used with AFM-based nanosensors [20], [21]. The AFS tool is centred using force-distance curves (force curves) that provide important data on the measurement of recognition events or either specific or nonspecific bonds, which are fundamental for creating and analyzing nanobiosensors [22]–[24]. Equally essential and useful in these biosensing systems is a tool 1530-437X © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See for more information.
  • 2. 1468 IEEE SENSORS JOURNAL, VOL. 14, NO. 5, MAY 2014 called functionalization. This technique is used to change the chemical properties at the surface, such that a standard molecular design can be used to immobilize target analytes and sensory molecules [25]–[27]. In this respect, the aim of this work was to develop an AFM-enzyme-based nanosensor to detect agrochemical molecules, in particular, the diclofop molecule. Diclofop [(R,S)-2-[4-(2,4-dichlorophenoxy)-phenoxy]propanoate acid methyl ester (DM)] is a post emergence herbicide used to control wild oats and annual grasses in wheat and barley [28] and belongs to the aryloxyphenoxypropionates (APPs) class of herbicides. Diclofop related studies are important due to the large volume used in agriculture worldwide. As an example, it was published that the total annual usage of diclofop methyl in China in 2006 was one to five million kilograms [29]. In addition, it has been informed that almost 75% of the active ingredient on diclofop molecule may fall onto soil surfaces upon application [30], and because of that, this compound may become common in the environment [28]. Regarding the relevance of diclofop detection on environment, our research group has been reported two important published papers that addressed theoretically and experimentally data over the relevance of this kind of analysis. Franca et al. (2011) [31] reported through a combination of molecular docking, molecular dynamics and quantum chemical calculations that it is possible to establish a bridge between the experimental calculated adhesion force and the theoretical simulated results. Oliveira et al. (2013) [32] reported the modeling of the proper enzyme orientation on an functionalized AFM tip. It was showed that after 50 ns of MD simulations the orientation assumed by the enzyme has influence on the exposition of the enzyme binding sites. Also, in another study from our research group, has been investigating the number of enzymes that cover the AFM tip by using statistical calculations of the enzyme dimensions and AFM tip area (results not reported yet). For sensor’s purposes, the mode of action of diclofop chemical group is important: they inhibit the homomeric plastidic ACCase (acetyl-CoA carboxylase) enzyme [33], [34]. This enzyme is present in almost all weed species, and therefore, the diclofop herbicide is applied to crops in post- emergency operations. Inhibiting the action of the ACCase enzyme interrupts the biosynthesis of fatty acids, resulting in plant death of grass species [35], [36]. The design and construction of the nanobiosensor are based on the biomimicry of the natural process of host-guest interac- tions, i.e., the nanobiosensor design is based on the diclofop action mechanism, which consists on the specific binding of the herbicide to the enzyme ACCase to inhibit the action of the enzyme inside a plant cell. Thus, the assembly of the molecules in the functionalization process is the key to achieving selectivity and specificity. The correct arrangement of molecules results in a unique architecture of the target and sensory molecules, in such way that their active sites remain available for reaction and the formation of the specific complex. The ACCase enzyme belongs to a multigene family and is regulated by a complex network of developmental and environmental signals in response to both internal and external stimuli [37]. This enzyme is a biotin-dependent molecule that catalyses the irreversible carboxylation of acetyl-CoA to malonyl-CoA through the two catalytic activities of biotin carboxylase and carboxyl transferase. The most important purpose of ACCase is to enable the malonyl-CoA substrate to control lipid biosynthesis in the chloroplasts and plas- tids of non-green tissues [38], [39]. The diclofop inhibits ACCase in several stages. First, the herbicide reduces the electrochemical potentials across the plant cell membranes and disrupts the transmembrane proton gradient (via electrolyte leakage), resulting in membrane peroxidation and the subse- quent uncontrolled release of the cell’s electrolytes inside the plasma membrane. The plasma membrane and the subcellular membranes are essential for grouping and supporting cellular physiological processes; thus, damaging the plasma membrane negatively affects the biochemical functions and the viability of the cell [39]. Once inside the plasma, the diclofop molecules promote ACCase inhibition by causing plant disease symp- toms, such as a decline in chlorophyll and carbohydrate pro- duction, ending in chlorosis and subsequent plant death [40]. This action mechanism was used to design the nanobiosensor by incorporating the architecture of biomaterials that mimic complex biological structures. Biomimicry incorporates con- cepts and strategies from nature into sustainable, useful, and efficient materials engineering of nanosensing applications by using AFM and natural binding pathways. In this context, through the use of force curves, the adhe- sion force between two surfaces or molecules, or the force required to break the interaction between them, can be mea- sured [41], [42]. Studies have been and are being advanced by our research group using AFS to succeed the detection of agrochemical through recognitions events of biomolecules, such as enzymes and antibodies. In this study, we first present a brief overview of relevant theoretical studies, such as docking calculations for different regions of the sensing element to show cluster formation, and the use of molecular dynamics to measure the interaction energies in a system to guarantee that the original characteristics of molecules are retained following their insertion into the system. These theoretical results were used to adjust and optimize the experimental parameters in this study to delineate a recognition mecha- nism based on AFS principles. Finally, this work is the first report of the development of an enzyme-based nanobiosen- sor and its application to diclofop detection using AFM probe sensors in conjunction with theoretical and experimental studies. II. MATERIALS AND METHODS A. Computational Procedure - Molecular System The enzymatic model of the ACCase enzyme was taken from the Protein Data Bank online repository, PDB ID: 1UYR and all missed residues were rebuilt according to the Franca et al. (2011) considerations [31]. In addition, the APTES and diclofop molecular structures were built using Jmol program [43] and the optimized geometry of both mole- cules were scanned quantum mechanically using ORCA 2.8.0
  • 3. BUENO et al.: NANOBIOSENSOR FOR DICLOFOP DETECTION 1469 TABLE I SIMULATED SYSTEM program [44]. All the undetermined force field parameters to run molecular dynamics (MD) simulations were extracted from the harmonic fitting curves through quantum mechanical calculations. B. Computational Procedure - Molecular Docking To carry out docking calculations, the enzyme and herbicide molecules were used in the AutoDock 4.0 program [45]. The herbicide (diclofop) was restrained within a tridimensional grid and was docked on a rigid ACCase enzyme using Gasteiger-Huckel method [46] for partial charges considera- tion. A pre-defined 3D grid was created in several regions along the enzyme to evaluate the clustered configurations with favorable binding energies. Lamarckian genetic algorithm (LGA) was applied to survey the conformational space of the unit system to obtain a set containing a 10 LGA docked structure. C. Computational Procedure - Molecular Dynamics Simulation The clustered docked positions of the diclofop and the linker-diclofop set were used to perform MD simula- tions in order to quantify the interaction energies resulting from van der Waals and electrostatic considerations. These MD calculations were performed using NAMD 2.7 soft- ware [47], and the results were analyzed using Tool Command Language (TCL) scripts implanted in the VMD program [48]. Langevin thermostat and piston [49] were applied to the system to minimize, calibrate and equilibrate the energy at 310K, and 1 atm. The NVT ensemble was used, and a cut off of 1.4 nm was employed for the short-range electrostatic and van der Waals interactions. The long-range contribu- tions were modeled using the Particle Mesh Ewald (PME) method [50]. All force field parameters were implemented on the CHARMM Force Field [51] protocol. The simulated systems can be observed on Table I, where the system ACCase+diclofop, was defined by E-I (enzyme-inhibitor), and the system ACCase+APTES+diclofop was defined by E-F-I (enzyme-functionalized-inhibitor). D. Experimental Procedure - Materials The acetyl-CoA carboxylase enzyme was purchased from CUSABIO (Hubei Province, P. R. China) as a part of the bovine acetyl-CoA carboxylase Synthetase ELISA Kit (which is used to perform the standard method for a specific molecular ligand-receptor). An animal ACCase enzyme was commer- cially available and was therefore used instead of a vegetal Fig. 1. Schematic representation of showing the nanosensor design: (A) cantilever; (B) AFM tip; and (C) structure of APTES-glutaraldehyde system bound to the Si3N4+acetyl-CoA carboxylase (molecular formula: C23H38N7O17P3S) substrate (drawing is not to scale and all bonds are not shown). ACCase enzyme and because of crystallographic evidence for the similarity and mechanism of action between animals and plants. It is also known that some aryloxyphenoxypropionate herbicides and their analogues interfere with the maintenance of transmembrane electrochemical gradients in animal sys- tems; similar observations have been reported for plants [52]. The ACCase enzyme from the kit used in this work was in its purified form and it was brought to room temperature 30 min before usage. The process of enzyme reconstitution is very quick and, at first, consists on the centrifugation of the standard vial at 8,000 rpm for 30s. After this process, the standard is reconstituted with 1.0 mL of sample diluent provided by the manufacturer. Finally, it is allowed to the standard to sit for a minimum of 15 minutes with a gentle and uniform agitation (to avoid foaming). All the ACCase standards were prepared fresh for each assay and used in a four-hour period (lifetime of the enzyme). This reconstitution solution of the ACCase enzyme from now on will be referred as ACCase standard. Super pure-grade materials were used in the functionalization procedure: 3-aminopropyltriethoxysilane (APTES), triethylamine (TEA) and glutaraldehyde (as a 25% aqueous solution), which were all purchased from Sigma-Aldrich (St. Louis, MO). The herbicides diclofop, imazaquin, glyphosate, and metsulfuron were also purchased from Sigma-Aldrich (St. Louis, MO). AFM cantilevers with sharpened pyramidal tips (Si3N4 tips) were purchased from ThermoMicroscopes Microlevers (Sunnyvale, CA). E. Experimental Procedure - Nanobiosensor Assembly The fabrication of the nanobiosensors was based on the work of Etchegaray et al. [17] and da Silva et al. [22]. The AFM cantilevers were first placed in a sterile Petri dish and sterilised under UV light for 30 minutes. The first step in the functionalization of the AFM cantilevers and probes was the silanisation of the surface with APTES [Fig. 1(a)]. This reaction produced molecular arrays on the AFM cantilever surface via interactions between the silicon oxide groups on the cantilever surface and the silanol group in the silane. The AFM tips were exposed to APTES and triethylamine vapours for over 30 minutes to bind the APTES to the
  • 4. 1470 IEEE SENSORS JOURNAL, VOL. 14, NO. 5, MAY 2014 cantilever surface. The next step in the treatment was the introduction of the bifunctional reagent glutaraldehyde [see Fig. 1(b)], which provided a reactive termination (aldehyde group) that could react with the amine (−NH2) groups of the APTES [see Fig. 1(c)] on the AFM tip surface. At this stage, the glutaraldehyde acted as a spacer to provide flexibility between the enzyme and the herbicide, thereby enhancing the sensitivity of the sensor. The AFM cantilevers were immersed in a 1 × 10−3 molL−1 glutaraldehyde aqueous solution and allowed to react for 40 minutes. MilliQ water was then used to wash off any substances that were not covalently attached to the AFM cantilever surfaces. After the washing process, the sensing element (i.e., the ACCase enzyme) was induced to covalently bind to the terminal fragment of the aforementioned glutaraldehyde molecule by immersing the AFM cantilevers in a 4 µgL−1 ACCase enzyme solution. The rapid washing process ensured that the MilliQ water did not modify the enzyme structure and thereby affect the force measurements. These samples were incubated for 35 minutes at room temperature. At the end of the entire procedure, the cantilevers were used for AFM/AFS measurements. F. Experimental Procedure - Immobilization of Target Molecules A similar procedure to that described in Section II.E was used to assemble and covalently immobilize the target molecules (the herbicides) on the substrate system (i.e., a fresh muscovite mica layer). The first step in the functionalization procedure was the formation of a covalent bond between the hydroxyl groups present on the surface of the mica muscovite and the silanol group of the APTES molecules. Next, the amino group of the APTES molecule was chemically reacted with the carboxyl groups (-COOH) of the diclofop herbicide molecule. This reaction formed a peptide bond between the groups; the geometry of the herbicide molecules was such that they could inhibit the enzyme, thereby removing the need to introduce a glutaraldehyde spacer into the target substrate system. After exposure to APTES and TEA vapours, the substrates were immediately immersed into the 1 mM agrochemical solutions. The target molecules were immobilized on the surface and covered the entire area. G. Experimental Procedure - AFM and AFS The Atomic Force Microscope ThermoMicroscope Auto- Probe CP was used in the AFS experiments. In addition, according to the manufacturer, the curvature radius of the sharpened pyramidal tip used is <20 nm. The cantilevers were calibrated using the method described by Sader et al. [53], i.e., the system was subjected to a vibration and the resonant frequency in air was measured. The force measures were obtained by approximating the tip retraction rate as 10 µms−1. The contact mode was used to measure all the force curves; these analyses were performed in a 20 × 10−3 molL−1 sodium phosphate buffer at pH 7.0. Twenty measurements were made for each probe, corresponding to approximately 19 statistically valid measurements. All the measurements were obtained using two cycles at a scan rate of 0.043 nm/s Fig. 2. Representation of the diclofop molecule and the E-I system in binding site mode for the ACCase enzyme: (A and B) schematic and crystallographic representation of the interactions between the diclofop and the ACCase binding site, showing diclofop (in green) and binding mode (in magenta); (C) diclofop docked at a binding site mode; and (D) E-I system docked at a ACCase binding site mode. and Si3N4 tips suitable for the contact mode with a spring constant (k) of 0.038± 0.003 N/m (which was calculated by averaging the values for 10 tips). The TopoMetrix SPMLab 4.0 and OriginPro 8 programs were used to perform the statistical analysis. H. Experimental Procedure - Raman Spectroscopy For the RAMAN spectroscopy, one drop of the ACCase standard solution was dispensed on a silicon nitride surface (tip material), in order to verify the mechanism of absorption and its film assembly on Si3N4. All the functionalization steps were also carried out on a silicon nitride surface with the same purpose. RAMAN spectra were obtained using a hand-held spectrometer (FirstGuardTM/Raman Analyser V2.2.0), with a 1064 nm laser as the excitation source. The output of the laser power was set at 300 mW, and the integration time was set at 5000 ms. The program OriginPro 8 was used for the statistical analysis. III. RESULTS AND DISCUSSION A. Molecular Docking and Molecular Dynamics The herbicide diclofop inhibits ACCase enzyme by blocking one of the two available active sites [54]. The blockage occurs via electrostatic and van der Waals interactions of the diclofop to the following residues: Tyr1738A, Gly1998B, Val2002B, Gly1734A, and Phe1956B Ala1627A (see Fig. 2). The Phe1956B residue was removed from Fig. 2(b)–(d) in order to make the binding site easy to view. The process of the ACCase inhibition was reproduced according to the docking methodology [Fig. 2(a)] and the residues were purple coloured as can be seen in Fig. 2(b)–(d). Fig. 2(b) shows the best conformation and position of the diclofop (in green), it was obtained from crystallographic data, and Fig. 2(c) and (d) show the best positions and conformations obtained from the molecular docking calculations to the diclofop and E-I system set. The final docked position is almost the same from the crystallography achievements. Molecular Dynamics simulations were carried out to deter- mine the binding energies of the clustered docking posi- tions. These calculations were performed considering the fluctuations and mobility of the set in aqueous solution.
  • 5. BUENO et al.: NANOBIOSENSOR FOR DICLOFOP DETECTION 1471 TABLE II CALCULATED INTERACTION ENERGIES OF THE REPRESENTED SYSTEM. THE ENERGIES WERE SCORED IN kcal/mol Each system was initially energy-minimised and energy- equilibrated during 1 ns. Table II shows the electrostatic and van der Waals (vdW) contributions to the interaction forces that kept the ligands attached to the ACCase enzyme. When the inhibitor diclofop occupied the binding site of the ACCase enzyme, the electro- static interactions were the primary contribution to the total energy. In contrast, when this inhibitor bonded to the cross- linker, the vdW interactions were the primary contribution for the total energy. At the end of the inhibition process, one of the oxygen of the carboxyl group from the diclofop was available in solution, whereas the remaining oxygen was incorporated into a hydrophobic pocket formed by the residues in the reaction. Comparing the binding energies of the E-I system and the diclofop inhibitor in Table II, it shows that the oxygen interaction has facilitated the inhibition process in the E-I system. This result corroborated the experimental results. Theoretically, the diclofop herbicide could be assembled and attached to the mica substrate surface and the ACCase enzyme on the AFM probe without damaging the molecule’s abilities to inhibit and be inhibited. Therefore, the binding energy results from the simulations showed that the diclofop retained its features of being a specific inhibitor of the ACCase enzyme even after immobi- lization on mica substrate. In the following section, we present experimentally how the functionalization method works and the results from experimental analysis, where the signal of the AFM force curves comes from the herbicide-binding site interaction. In this context, we have determined the proper orientation of the enzyme on a functionalized AFM tip through MD simulations [32]. Also, enzyme-enzyme interaction has been simulated at the presence of the functionalized surface (results not reported) and we have estimated the number of active interactions by assuming an energetically favorable orientation of the enzymes on a surface. Therefore, it is possible to infer that the number of enzyme binding sites available by calculating the unbinding energy of one diclofop molecule through steered molecular dynamics. Depending on the number of binding sites available, it is possible to integrate the simulated force curve in order to infer a theoretical value to a specific substrate interacting with a target enzyme. B. Using Raman Spectroscopy for the Analysis and Monitoring of the Nanobiosensor Assembly The probe functionalization process was characterized using Raman Spectroscopy. The Raman spectrum for the ACCase TABLE III COMPARISON OF BAND ASSIGNMENTS FOR THE RAMAN SPECTRA OF THE ACCASE AND AFTER THE FINAL FUNCTIONALIZATION STEP was characterized by five peaks, which could be associated with the final Raman spectrum of the nanobiosensor (which is labelled in light grey in Table III). Table III shows that functionalization with the ACCase enzyme produced similar peaks in the 450-460 cm−1 region in the Raman spectra. These peaks could be assigned to carbon out-of-plane bending vibrations [55]; in the 990-1050 cm−1 region, the peaks corresponded to the C-N vibration / NH2 vibration [56]: the signal increased in this region in the nanobiosensor spectrum because of the large number of C-N bonds in the enzyme structure. The signals in the final regions of the spectrum (1367 and 1462 cm−1) could be attributed to COO− stretching vibrations / CH deformation / C-NH2 stretching and CH3 and / or CH2 deformations [56], [57]. These similar values (nanobiosensor and standard) show that the enzyme was covalently attached to the silicon nitride surface. C. Agrochemical Detection by Nanobiosensor Topographical images were used to verify the absorption of the molecules on mica. The profile studies (data not shown) provide the dimensions for the surrounding area of the film assembled on mica, from where can be deduce that the height of this films corresponds to 2.4 nm and 2.93 nm. Based on the number of carbon-carbon bonds and considering the average distance from 0.1 to 0.15 nm for each connection at the molecule, it is suggested that a monolayer of APTES form a self-assembled monolayers [42] of 0.5 nm of height. Likewise, one glutaraldehyde molecule might have a height of approximately 1 nm. The data from the three-dimensional structure of molecules of diclofop and imazaquin, for example, is estimated to have a height of ∼1.5 nm and 1.4 nm, respec- tively. Added to an arrangement with APTES-glutaraldehyde polymerization of 1.5 nm formed in the functionalization process, corresponding to the total height of the film. The AFM force curves were used to quantify the inter- actions between the AFM tip and the sample. The curves corresponded to two force components: a curve approximation (not shown) representing a repulsion event and a withdrawal curve, which could have negative components when there was a chemical interaction between the AFM tip and the substrate. In this paper, the contact mode, which produces
  • 6. 1472 IEEE SENSORS JOURNAL, VOL. 14, NO. 5, MAY 2014 Fig. 3. AFS force curves recorded in a PBS solution buffer at pH 7.0 for the developed agrochemical nanobiosensor: the blue curve represents a specific recognition event for a single biomolecular complex formed by the interaction between ACCase and diclofop (the specific chemical that inhibits the enzyme action); in contrast, the other curves represent nonspecific recognition events with low, almost null adhesion forces. force curves as a function of distance, was used to confirm the system architecture and the specific recognition between the enzyme and the herbicide. The force curves were performed in an aqueous medium, in which the interactions were weak and were thus in agreement with the results of [58] and Noy et al. [59]. Fig. 3 presents the force curves obtained for the functionalized AFM tip and substrates modified with four different herbicides (i.e., 3 nonspecific herbicides, imazaquin, metsulfuron, and glyphosate, and 1 specific herbicide, diclo- fop). A simple interpretation of the force curves shown in Fig. 3 from the aforementioned data is that the shape of the adhesion curve (i.e., the withdrawal curve) can be attributed to the selectivity and specificity of the nanobiosensor for the herbicide under consideration (diclofop). More than one set of molecules may have participated in the recognition process. Fig. 3 shows that the magnitude of the diclofop adhesion forces was 85% higher (6.0±1.0nN) than those of the her- bicide imazaquin (0.8±0.1nN) and 93% higher than those of the herbicide metsulfuron (0.3±0.1nN). These differences in the adhesion forces were expected because these herbi- cides (imazaquin and metsulfuron) inhibit the action of the enzyme acetolactate synthase (ALS) [60]–[62] and conse- quently are non-specific ligands of (i.e., do not inhibit) the enzyme ACCase. Likewise, the magnitude of the diclofop adhesion forces was 90% higher than the herbicide glyphosate (0.6±0.1 nN). This difference in the adhesion forces was also expected because the herbicide glyphosate inhibits the enzyme EPSP (5-enolpyruvyl shikimate-3-phosphate synthase) [63]–[65] and consequently, is also a non-specific ligand of (i.e., does not inhibit) the enzyme ACCase. The total difference between the values for specific recognition (for the diclofop inhibitor) and nonspecific recognition (for the Fig. 4. AFS force curves recorded in a PBS solution buffer at pH 7.0 for the control experiment for substrates without any agrochemical coating and by saturating the tip with the complementary blocking agent (inset). non-inhibitors imazaquin, metsulfuron and glyphosate) was approximately 90%. This result validated the selectivity and specificity of the nanobiosensor. Control experiments, in which the biorecognition process was inhibited or invalidated, were used to confirm the speci- ficity of the detected specific recognition events on statistical grounds, besides to verify and calibrate the influence of coatings by functionalization process. The control experiments were performed on substrates without any agrochemical coat- ing (Fig. 4) and by saturating the tip with the complementary blocking agent (i.e., the anti-ACCase antibody) (Fig. 4 inset). On average, a significant decrease of 98% of the probability of adhesion in the force curves was observed for these control experiments. The modulation in the vertical lines showed in the force curves of the control experiments occurred due the probe–sample interactions. Interactions of this nature generally alter the overall spring constant of the system. Since the ACCase enzyme is inhibited by diclofop in vivo, and this inhibition depends on a specific recognition process, the control experiments showed lower values of adhesion force compared to the results previous discussed and occurs essentially by van der Waals interactions or by electrostatic, hydrophilic, and hydrophobic interactions, among others [42]. As a final point, the histograms in Fig. 5 were used to determine several specific adhesion force values. The most important results were as follows: at a given loading rate, the most probable adhesion force (which can be used to standardise sensor operation on a large scale); the difference between the adhesion forces for each group of herbicides (specific and nonspecific); and the statistical probability of the adhesion values that appear in the experimental measurements. All the peaks for the different statistical distributions of the herbicides, such as the adhesion force of the recognition event, could be fit with a Gaussian function. Comparing this system with other biosensors defined in the literature is challenging because of the many differences between our system and the systems in other studies, such as the physical and chemical nature of the molecules, the surface topography and characteristics, the charges involved in the recognition event, the different transduction modes,
  • 7. BUENO et al.: NANOBIOSENSOR FOR DICLOFOP DETECTION 1473 Fig. 5. Adhesion force histograms (n=19) for the occurrences (relative frequency) of adhesion force values for the sensing systems at the nanoscale: (A) ACCase/imazaquin; (B) ACCase/metsulfuron; (C) ACCase/glyphosate; and (D) ACCase/diclofop; the histograms were fitted to Gaussian functions to identify the most probable adhesion force value to determine a standard value for specific and nonspecific recognition events and signals. and the functionalization method used for the nanobiosensor active area. This is the first report of the detection of an APP herbicide by an AFM-tip-based nanobiosensor. IV. CONCLUSION The results from this study provide important guidance on designing highly sensitive and selective AFM-tip-based nanosensors using biomimicry of the action mechanism of herbicides on plants. Surface functionalization was success- fully used to attach sensory and target molecules to the AFM tip, which enabled the detection of small concentrations in real time under near-physiological conditions and without labelling. In this context, the novelty and advantage of AFM sensors are, among other facts, the detection limits (as AFM resolution limits) that this system can reach: the range of pictogram and, in the best scenario, the detection of a single molecule with a very narrow and sharpened tip, such as a carbon nanotube tip and a controlled and standardized functionalization process. The experimental results showed that the specific inter- action was the primary contribution to the greater adhesion force, especially for the ACCase-diclofop interaction, because diclofop is a specific inhibitor for ACCase. The difference between the specific and nonspecific recognition values was 90% on average. The theoretical results also provided a direct interface with the experimental research, showing that nanosensor molecules could be assembled and attached to the mica substrate surface and the AFM probe without damaging the molecules’ mode of action. Studies are currently being carried out to determine the theoretical and experimental force of the interactions between the herbicides and their inhibitors and we have already begun investigating the response behavior of the sensor for samples in which several agrochemical groups interact in a solution. More work is needed to improve the AFS signals, and because of that, our research group is concentrating efforts to figure how the immobilization process works, in order to estimate, as accurate as possible, the forces involved on herbicide-enzyme interactions as well as the improvements to the nanoscale detection device to monitor residues in the environment. ACKNOWLEDGMENT The authors would like to thank Mr. L. Bonugli for his significant contributions to the AFM measurements, Mr. J. R. Castro for technical assistance and the Institute of Physics Gleb Wataghin for the experimental assays support. Also, the authors acknowledge FAPESP (Proc. 2007/05089- 9; Proc. 2013/09746-5; Proc. 2009/09120-3), CAPES, CNPq, FAPEMIG (CEX - APQ-02176-11) and nBioNet for their financial support. REFERENCES [1] S. R. Mousavi, and M. Rezaei, “Nanotechnology in agriculture and food production,” J. Appl. Environ. Biol. Sci., vol. 1, no. 10, pp. 414–419, 2011. [2] Z. Jha, N. Behar, S. N. Sharma, G. Chandel, D. K. Sharma, and M. P. Pandey, “Nanotechnology: Prospects of agricultural Advance- ment,” Nano Vis., vol. 1, no. 2, pp. 88–100, 2011. [3] W. C. Chien, C. H. Chung, J. J. K. Jaakkola, C.-M. Chu, S. Kao, S. L. 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Carolina Castro Bueno received the Degree in environmental engineering from Pontificia Univer- sidade Catolica de Campinas in 2009, and the M.S. degree in materials science - nanotechnol- ogy and nanoscience in the area of microscopy and atomic force spectroscopy with emphasis on nanoscopy/nanobiosensors for monitoring environ- mental quality in agriculture in 2013. She has worked in the areas of nanotechnology, nanoscience and atomic force microscopy, with emphasis on stud- ies that involve the construction of smart surfaces for creating nanobiosensors. Currently, she is pursuing the Doctoral degree in environmental sciences working with Biochar development and engineering at Universidade Estadual Paulista. Adriano Moraes Amarante was born in Soro- caba, Brazil. He received the Degree in bio- physics technology from the College of Technology São Paulo, FATEC, Sorocaba, in 2006, the B.Sc. degree in physics from the University of São Carlos in 2013, and the M.Sc. degree in materials science and engineering from the University of São Carlos in 2013. Since 2007, he has been developing several different types of computational simulation to inter- pret biological sensors-based to be used as probes for agriculture and diseases detection. His research activity includes molecular dynamics simulation and experimental-theoretical interpretation. Since 2009, he has been a Researcher with the Federal University of São Carlos, Brazil, and a member of the Nanoneurobiophysics Research Group. Guedmiller S. Oliveira received the B.S. and M.S. degrees in physical chemistry from the Federal University of Uberlândia and the Ph.D. degree in physical chemistry from the Federal University of São Carlos, Brazil, in 2006, 2009, and 2013, respec- tively. Since 2007, he has been working with com- puter simulation of the matter, providing an atomistic point of view of the experimental procedures. In 2012, he was visiting the University of Houston, Biology and Biochemistry Laboratory, supervised by Prof. J. M. Briggs, where he developed a theoretical model to interpret the immobilization of biological systems on functionalized surfaces for nanosensors applications. His knowledge base incorporates quan- tum mechanics theory, molecular dynamics simulation, and it combines results from experimental and theoretical analysis through statistical thermodynamics to better understand macromolecular phenomena. Currently, he is a Post- Doctoral Researcher at the Federal University of São Carlos, Sorocaba. Daiana Kotra Deda received the B.Sc. degree in chemistry from the State University of Midwestern, Brazil, in 2006, and the Ph.D. degree in inorganic chemistry from the University of São Paulo, Brazil, in 2011, for research on the development of nanoen- capsulated photosensitizers for cancer treatment by photodynamic therapy. Currently, she is a post- doctoral with the Chemistry Institute, University of São Paulo. Her main research interest is the development and characterization of nanomaterials and the study of their interaction with biological systems, in vitro and in vivo toxic effects and their application as alternative methods for treatment and diagnosis of diseases. Omar Teschke was born in Santo Angelo, Brazil, in 1944. He received the B.S. degree in electri- cal engineering from Universidade Federal do Rio Grande Sul, Porto Alegre, in 1967, the M.S. degree in electrical engineering from Universidade Catolica do Rio de Janeiro in 1969, under the supervision of Prof. S. M. Rezende, and the Ph.D. degree in electrical engineering from the University of Cali- fornia Berkeley in 1975, under the supervision of J. R. Whinnery. After teaching at the Universidade Catolica do Rio de Janeiro from 1969 to 1971, he was a Visiting Staff Member with Bell Laboratories Holmdel, NJ, USA, from 1975 to 1977. He joined the Departamento de Fisica Aplicada, Instituto de Fisica, UNICAMP, in 1977. Currently, he is a Professor and his research interest are interfacial processes including self-organization and self-assembly and experimental techniques for probing the liquid state, specially interfacial process in living species. Eduardo de Faria Franca is a Professor of the- oretical chemistry with the Federal University of Uberlândia. He received the Degree from the Federal University of Uberlândia in 2003, and the Ph.D. degree in chemical physics from the Federal Uni- versity of São Carlos in 2009, where he worked with Prof. L. C. G. Freitas. As a trainee in the Pacific Northwest National Laboratory, he was with Prof. R. D. Lins and developed a new force-field for the chitin and chitosan biopolymers and elucidated new insights about these natural polymers using molecular dynamics simulation. In 2009, he was a post-doctoral with the polymer group: Prof. Bernhard Gross, University of São Paulo, to help on the development of a new nanobiossensor using an AFM microscope. His theoretical work assisted the construction of a sensible and selective biosensor capable to detect herbicides in nanomolar concentration. He joined the Federal University of Uberlândia as a Professor of chemistry in 2010. He has been the author or co-author of many publications in theoretical chemistry and crystallography since 2002. His actual projects include the development biosensors, antitumor drugs, biofuels, and the use of biopolymer chitosan for waste water treatment and production of artificial tissues. Fábio L. Leite was born in Itanhaem, Brazil. He received the B.Sc. degree in physics from São Paulo State University, UNESP, Rio Claro, in 2000, and the M.Sc. and Ph.D. degrees in mate- rials science and engineering from the University of São Paulo, São Carlos, in 2002 and 2006, respectively. Between 2007 and 2008, he was a Post-Doctoral Researcher with the Alan Graham MacDiarmid Institute of Innovation and Business, Embrapa Agricultural Instrumentation (Embrapa) with Dr. O. N. de Oliveira Jr., Dr. L. H. C. Mattoso (Embrapa) and Alan Graham MacDiarmid, University of Pennsylvania Nobel Prize in chemistry in 2000. His efforts in the MacDiarmid Institute focused on conducting polymers, nanosensors and atomic force microscopy with environmental applications. Since 2009, he has been an Assistant Prof. and Researcher with the Federal University of São Carlos, Sorocaba, and the Head of the Nanoneurobiophysics Research Group. He is the author of over 40 published papers, two books, ten book chapters, and two patents. His research interests are related to the development of nanobiosensors using AFM and computational nanotechnological for application in studies of a variety neurodegenerative and autoimmune diseases.

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