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Sensors and Actuators B 160 (2011) 1098– 1105

Contents lists available at SciVerse ScienceDirect

Sensors and Actuators B: Chemical

j o ur nal homep a ge: www.elsev ier .com/ locate /snb

mperometric inhibition-based detection of organophosphorus pesticides innary and binary mixtures employing flow-injection analysis

vaylo Marinova, Yavor Ivanova, Nastya Vassilevab, Tzonka Godjevargovaa,∗

Department of Biotechnology, University, “Prof. Dr. Assen Zlatarov”, Prof. Yakimov Street 1, Bourgas 8010, BulgariaDepartment of Biotechnology and Food Products, University of Rousse “Angel Kanchev”–Technology College, Aprilsko vastanie Blvd. 3, Razgrad 7200, Bulgaria

r t i c l e i n f o

rticle history:eceived 27 July 2011eceived in revised form 9 September 2011ccepted 13 September 2011vailable online 17 September 2011

eywords:mperometric biosensor

mmobilized acetylcholinesteraseesticideslow-injection system

a b s t r a c t

The present work is focused on the application of an acetylthiocholine (ATCh) biosensor in a flow-injection system for the detection of organophosphorus pesticides. The optimal operating conditions ofthe flow-injection system were determined: flow-rate – 0.5 mL min−1, substrate concentration – 100 �M,incubation and reactivation time–10 min. A calibration plot was obtained for ATCh concentration rang-ing from 20 to 200 �M. A linear interval was detected along the calibration curve from 20 to 100 �Мwith a correlation coefficient R2 = 0.996. The sensitivity of the constructed biosensor was calculated to be0.083 �A �M−1 cm−2.

The application of the flow-injection system for detection and quantification of three organophos-phorus pesticides – paraoxon ethyl, monocrotophos and dichlorvos in unary solutions and in binarymixtures was investigated as well. The inhibition curves for each pesticide was plotted and the linearintervals were determined along with the corresponding equations and detection limits – 0.87 × 10−11 Mfor paraoxon, 1.08 × 10−11 M for monocrotophos and 1.22 × 10−10 M for dichlorvos. The bimolecular inhi-bition constants ki were calculated by performing amperometric measurements of the residual enzymeactivity after incubation for 10 min in a series of samples with varying pesticide concentrations (from2 to 100 �M). The highest inhibition potency was observed for paraoxon (2.3 × 105 M−1 min−1), and thelowest – for dichlorvos (3.5 × 104 M−1 min−1).

The flow-injection system was used in the detection of anti-cholinesterase activity of two binary mix-tures – paraoxon + monocrotophos and paraoxon + dichlorvos. It was interesting to observe that the total

anti-cholinesterase activity of the mixtures was lower than the anti-cholinesterase activity of paraoxonwith the same concentration in the sample.

The storage stability of the enzyme membrane was considerably improved with respect to our previouswork. After storage for 30 days, the enzyme membrane retained over 90% of its initial response. The half-life storage time of the enzyme membrane (50% residual activity) was almost tripled – from 25 to 75days.

. Introduction

Organophosphorus pesticides are widely employed in agri-ulture. Their principal action as pesticides is the inhibition ofcetylcholinesterase (AChE). AChE hydrolyses the neurotransmit-er acetylcholine in the synaptic membrane of nerve cells and plays

fundamental role in their function. A consequence of such hydrol-

sis reaction is the acetylation of the enzyme. However, this esterond is weak and is rapidly hydrolyzed during the recovery stage ofhe enzyme. Organophosphorus compounds inactivate the enzymey phosphorylation of the serine residue from the catalytic triad

∗ Corresponding author.E-mail address: godjevargova@yahoo.com (T. Godjevargova).

925-4005/$ – see front matter © 2011 Elsevier B.V. All rights reserved.oi:10.1016/j.snb.2011.09.033

© 2011 Elsevier B.V. All rights reserved.

in the enzyme active center. Because of the inherent toxicity ofthis type of pesticides, there is a considerable interest in the devel-opment of highly sensitive, selective, rapid and reliable analyticalmethods in their detection. On one hand, current analytical tech-niques, such as gas chromatography and liquid chromatographyare very sensitive and reliable. On the other hand, they are verytime-consuming and expensive, and they can be performed onlyby highly trained technicians.

Biosensors represent an alternative method to quickly detectneurotoxins and have been an active research area for the pasttwenty years. A variety of biosensors have been constructedbased on the utilization of different enzymes [1,2], nanomaterials

[3], as well as on the approach of pesticide detection – directmeasurement [4] or inhibition-based one [5]. The operation of abiosensor could be greatly facilitated and even automated withits integration in a flow-injection system. Various constructions

I. Marinov et al. / Sensors and Actuators B 160 (2011) 1098– 1105 1099

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oe

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aiTimfloa

2

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f continuous flow systems were reported [6–9], all providing anvidence for the greater efficiency of the flow-injection system.

The irreversible inhibition of enzyme was explained withhe formation of covalently phosphorylaled enzyme complexnd represented by the biomolecular inhibition rate constant ki.he following kinetic model, proposed by Main [10], was uti-ized for the calculation of the bimolecular inhibition constant kiScheme 1):where EH – enzyme; AB – organophosphorus pesticide;B-EH – unstable enzyme-inhibitor complex; BH – leaving acidicroup; EA – stable enzyme inhibitor complex. Assuming that thegeing of EA and the spontaneous reactivation of the enzyme occurt very low rates (k3 and k4 are very small) the kinetic model coulde simplified to (Scheme 2):where Kd = k−1/k1. The potency of an

nhibitor is much determined by how stable the enzyme-inhibitoromplex is (as expressed by the size of Kd) and how fast the acylatednzyme is formed (expressed as the size of k2). The bimolecu-ar inhibition constant comprising Kd and k2, used to describe thetrength of an inhibitor, is expressed as [11]:

i = k2

Kd(1)

The continuous use of the pesticide biosensor, however, requireshe reactivation of inhibited enzyme, which has been demonstratedy using oximes such as pyridine-2-aldoxime methiodide (2-PAM

odide) [12], 1,1′-trimethylene bis 4-formyl-pyridinium bromideioxime [13], monoquaternary pyridinium oximes [14], etc.

Here we describe a flow-injection system with integratedmperometric biosensor featuring an replaceable AChE-mmobilzed membrane with incorporated gold nanoparticles.his is very important for the detection of irreversible enzymenhibitors, because of the easier replacement of the enzyme

embrane and utilization of a single working electrode. Theow-injection system was employed in the detection of threerganophosphorus pesticides – paraoxon ethyl, monocrotophosnd dichlorvos in model pesticide solutions and binary mixtures.

. Materials and methods

.1. Materials and reagents

Acrylonitrile–methylmethacrylate–sodium vinylsulfonateembranes (PAN) were prepared without support according to

methodology described in our previous work [15]. The ternaryopolymer (acrylonitrile – 91.3%; methylmethacrylate – 7.3%,

odium vinylsulfonate – 1.4%) was a product of Lukoil Neftochim,ourgas. Ultrafiltration membranes of acrylonitrile copolymerere measured to be 4 �m thick and could retain substances witholecular weight higher than 60,000 Da.

Scheme 2.

1.

Acetylthiocholine chloride (ATCh) and AChE (Type C3389,500 U mg−1 from electric eel) and pyridine-2-aldoxime methochlo-ride (2-PAM) were purchased from Sigma–Aldrich (St. Louis, USA)and used as received. Bovine serum albumin (BSA), glutaraldehyde(GA), paraoxon, dichlorvos, monocrotophos and a colloid solutionof gold nanoparticles (GNPs) (concentration of 5.74 × 1012 particlesper milliliter and average size of 9.7 nm) were also purchased fromSigma–Aldrich. Phosphate buffer solution (0.1 M PBS, pH 7.6, con-taining 0.9% NaCl) and other reagents were of analytical reagentgrade. All solutions were prepared in double-distilled water.

2.2. Apparatus

The flow-injection system comprised the following elements:three electrodes – a platinum working electrode, a standardcalomel electrode (SCE) and an auxiliary platinum wire elec-trode; a flow-cell with a working volume of 0.275 mL; a peristalticpump and an amperometric detector (Palm Instruments BV, TheNetherlands). The flow-injection system configuration is presentedin Fig. 1:

2.3. Chemical modification of PAN membranes

A piece of PAN membrane was immersed in 10% NaOH for 20 minat 40 ◦C. The membrane unit was then washed with distilled waterand placed in 1 M HCl at room temperature for 120 min. The colorof the hydrolyzed yellowish PAN membrane turned into white. Themodified PAN membranes were immersed in a 10% solution of ethy-lene diamine for 1 h at room temperature in order to react with thesuperficial carboxyl groups via one of the terminal NH2 groups,leaving the other NH2 group free. Those membranes were used ascarriers for the enzyme immobilization, described in Section 2.4.

2.4. AChE immobilization onto chemically modified PANmembranes

An immobilization mixture was prepared containing AChE, BSA,and GA. 0.50 mL GNPs and 0.1 M PBS (pH 7.6) were added so thatthe mixture volume was rounded to 1 mL. The concentration of thecomponents in the mixture was as follows: 0.1 U/mL AChE, 0.5%BSA, 0.7% GA. The modified membrane was immersed in the mix-ture for 24 h at 4 ◦C in order to let the components diffuse intothe pores of the membrane. The prepared enzyme membrane waswashed with bi-distilled water and 0.1 M PBS, pH 7.6.

2.5. Flow injection measurements with AChE-immobilizedmembranes

The amperometric detection of AChE hydrolysis of ATCh chlo-ride is based on monitoring the oxidation current of thiocholine

formed in the enzymatic reaction. The prepared enzyme membraneand the working electrode (with a platinum disk 1 cm in diameterand surface of 0.785 cm2) were assembled as depicted in Fig. 1B. Thephosphate-buffer flow-rate was varied from 0.1 to 1.7 mL min−1

1100 I. Marinov et al. / Sensors and Actuators B 160 (2011) 1098– 1105

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tered current went through a peak value (at 0.5 mL min ) with theincrease of the flow-rate, after which the current slightly decreasedand was insignificantly influenced by the flow-rate increment. Thestronger the current, the better the signal-to-noise ratio, that is why

Fig. 1. (A) Flow-injection system; (B) Enzyme me

nd the working potential was set to 630 mV vs. SCE. The substrateolution was fed to the flow-cell in two ways: by spiking a 100 �l of00 �M ATCh solution into the carrier stream and by a continuousow of 100 �M ATCh solution.

.6. Inhibition measurements and determination of theimolecular inhibition constant ki

The degree of inhibition (I%) exerted by each organophospho-us pesticide on the enzymatic activity was calculated as a relativeecrease of the amperometric response after a contact of thenzyme carrier with a pesticide solution. The initial amperomet-ic response R0 of the biosensor to a continuous flow of 100 �Molution of ATCh was first measured. After washing the membraneith 0.1 M PBS (pH 7.6), a pesticide solution (concentrations rang-

ng from 10−11 to 10−3 M) was flowed through the cell for 10 min.his was again followed by washing the membrane with 0.1 MBS (pH 7.6) and the biosensor response Rt to a continuous flowf 100 �M ATCh solution was measured. The inhibition I% was cal-ulated according to the following equation:

% = (R0 − Rt)R0

× 100 (2)

The bimolecular inhibition constants of each pesticide, ki, werealculated by performing amperometric measurements of theesidual enzyme activity after incubation for a certain period ofime in a series of samples with varying pesticide concentrationsfrom 2 to 100 �M). Taking into consideration Scheme 2 the ratef inhibition could be described by a time-dependent simple irre-ersible inhibition equation [16]:

EI∗] = [ET ](1 − e−k′t) (3)

here [EI*] is the concentration of the generated stablenzyme–inhibitor complex, [ET] is the total amount of active immo-ilized enzyme, and k’ is described by the equation below:

′ = k2[I0]Kd + [I0]

(4)

here [I0] is the corresponding pesticide molar concentration andI0] � [ET]. The linearization and rearrangement of Eq. (3) yields the

ollowing equation [13]:

1I0

= k2

Kd

t

ln(ET /E)− 1

Kd(5)

e – working electrode assembly in the flow-cell.

where ET/E is the ratio between initial and residual enzyme activityafter incubation in a pesticide solution for a certain period of time“t”.

2.7. Reactivation of the immobilized AChE

After each inhibition measurement the immobilized enzymewas reactivated by feeding a 5 mM solution of 2-PAM to the cellfor 10 minutes. This was followed by a thorough washing of themembranes with 0.1 M PBS (pH 7.6).

3. Results and discussion

3.1. Flow-rate optimization

Since the biosensor measurements were performed in dynamicconditions, there should be an optimum flow rate of feeding thesubstrate to the electrochemical cell, at which the resulting currentwould reach a maximum. As can be seen from Fig. 2 the regis-

−1

Fig. 2. Dependence of the biosensor response to 100 �l of 100 �M ATCh solution onthe carrier flow-rate.

I. Marinov et al. / Sensors and Actuators B 160 (2011) 1098– 1105 1101

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dtoooflrtwstfloralacaedAsaa

The experimental results revealed that monocrotophos featuredtwo linear intervals, unlike the other two pesticides. The first linearinterval was characterized by a slope quite similar to the slope char-acteristic for dichlorvos, which would suggest similar sensitivity of

ig. 3. Dependence of the biosensor response 100 �l of 100 �M ATCh solution onhe substrate concentration at 0.5 mL min−1 carrier flow-rate.

.5 mL min−1 was selected as the optimum flow-rate to carry outurther experiments.

.2. Optimization of the substrate concentration

Fig. 3 displays the relation between ATCh concentration andhe generated current at each addition of substrate at the opti-

um flow-rate of 0.5 mL min−1. As can be seen from the plothe linearity of the relation extended to 100 �M substrate con-entration with a good correlation (R2 = 0.997) and sensitivity –.083 �A �M−1 cm−2, which is a quotient of the values of thelope (0.065 �A �M−1) and the surface of the enzyme membrane0.785 cm2). After that point of 100 �M, the generated currentended to increase less with the increment of ATCh concentra-ion. The substrate concentration of 100 �M was chosen for furtherxperiments.

.3. Optimization of the incubation and reactivation times

Each measurement cycle consists of calibration (in order toetermine the initial enzyme membrane activity), incubation ofhe enzyme membrane in the investigated sample, measurementf the residual activity of the immobilized enzyme, reactivationf the inhibited sensor and calibration again. The duration ofne measurement cycle could be greatly reduced when using aow-injection system mainly by reducing the incubation and theeactivation time. In our previous work [15] the reported dura-ion of the incubation and reactivation steps was 50 min whichas mainly due to the fact that the latter were performed under

tatic conditions (the enzyme membrane was immersed in the pes-icide sample as well as in the solution of 2-PAM). The employedow-injection system was expected to intensify the mass transferf inhibitor/reactivator molecules to the immobilized enzyme thuseducing the time for each step of the analytical cycle. A series ofmperometric measurements were carried out in order to estab-ish the time for achieving a steady-state current as a response to

continuous flow of substrate (0.5 mL min−1) with varying con-entrations. A constant current would be generated as a result of

constant diffusion flux of ATCh molecules to the immobilizednzyme and the time to saturate all exposed active sites wouldepend mainly on analyte diffusivity under equal other conditions.

s can be seen from Fig. 4, at higher substrate concentrations ateady-state current was achieved for approximately 5 min, whilet lower substrate concentrations the time interval for reaching

steady-state response was approximately 9–10 min. A 10-min

Fig. 4. Time and concentration gradient dependence of the formation of a steady-state biosensor response.

interval was chosen for the incubation and reactivation step underthe assumption that the mass-transfer of the pesticide moleculesand 2-PAM molecules would be similar under equal other condi-tions.

3.4. Inhibition detection in model pesticide solutions

A series of experiments were carried out, involving measure-ments of the biosensor signal before and after the incubation ofthe carrier in a pesticide solution with a definite concentration.The relations between the degree of inhibition (I%) and the corre-sponding pesticide concentration (ranging from 10−11 to 10−3 M)are presented in Fig. 5.

The detection limit was calculated on the basis of 10 ampero-metric measurements of the biosensor response to a blank sample(without pesticide) and can be regarded as the inhibitor con-centration that reduces the mean biosensor response with thetripled value of the standard deviation of the measured biosensorresponses. Table 1 contains summarized data comprising the linearintervals with the corresponding equations, correlation coefficients(R2) and the respective detection limits for each pesticide.

Fig. 5. Inhibition curves of paraoxon (�), monocrotophos (�), dichlorvos (�).

1102 I. Marinov et al. / Sensors and Actuators B 160 (2011) 1098– 1105

Table 1Characteristics of the flow-injection biosensor system for inhibition-based detection of pesticides.

Pesticide Interval of linearity (M) R2 Equation Detection limit (M)

Paraoxon 1.0 × 10−7–2.5 × 10−6 0.996 Y = 23.34 ln X + 395.3 0.87 × 10−11

Dichlorvos 1.0 × 10−8–1.0 × 10−5 0.995 Y = 3.450 ln X + 69.60 1.22 × 10−10

Monocrotophos 1.0 × 10−9–3.0 × 10−6 0.994 Y = 3.980 ln X + 90.80 1.08 × 10−11

1.0 × 10−5–1.0 × 10−4 0.993 Y = 15.65 ln X + 229.5

F(

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3

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sb

Table 2Bimolecular inhibition constants ki of the three pesticides.

Pesticide ki (M−1 min−1)a References

Paraoxon ethyl 2.3 × 105 Present work2.2 × 105 [17]1.7 × 105 [18]1.2 × 105 [19]3.0 × 105 [20]2.9 × 105 [21]

Monocrotophos 5.1 × 104 Present workDichlorvos 3.5 × 104 Present work

4.3 × 104 [17]4.2 × 104 [22]1.7 × 104 [23]2.6 × 104 [24]

paraoxon – dichlorvos. This result is easily explainable consider-ing the speculations so far, namely, monocrotophos being more

Table 3Binary mixtures of paraoxon, monocrotophos and dichlorvos.

Mixtures Pesticide concentration (�M)

Paraoxon 1 3 5 7 9

ig. 6. Inhibition kinetics plots for paraoxon (�), monocrotophos (�) and dichlorvos�).

he biosensor towards the two pesticides. However the detectionimits and the intervals of linearity for both pesticides clearly evi-enced for the greater inhibition potency of monocrotophos withespect to dichlorvos. Paraoxon featured the steepest slope, hencehe greatest sensitivity within the linearity interval, as well as theowest detection limit, proving that paraoxon was the most potentnhibitor amongst the three. However at low concentrations ofhe pesticides (from 10−10 to 10−7 M) monocrotophos exhibitedigher inhibition activity than paraoxon as can be seen from Fig. 5.his observation could be explained with a plausible assumptionor the existence of a diffusion barrier near the biosensor sur-ace, generated by the hydrodynamic conditions in the flow-cell.his means that at low pesticide concentrations monocrotophosolecules were mass-transferred more easily to the immobilizedChE than paraoxon molecules thus ostensibly enhancing the inhi-ition potency of monocrotophos with respect to paraoxon. Withoncentrations greater than 10−7 M the role of this diffusion bar-ier appears to diminish and the exhibited inhibition activities ofhe pesticides were as anticipated.

.5. Inhibition kinetics and calculation of ki

The procedure of calculating the bimolecular inhibition con-tants ki for each pesticide included the measurement of the initialnd residual enzyme activity (the ratio of which is expressed asT/E) after incubation in a pesticide solution for a period of 10 mins selected in Section 3.3. Employing Eq. (5) the ratio t/[ln(ET/E)]as plotted against the corresponding reciprocal pesticide concen-

ration 1/I0, which yielded a line, the slope of which gives ki andhe intercept – the reciprocal of Kd for the corresponding pesticideFig. 6):

The values of the bimolecular constant of inhibition ki are pre-ented in Table 2. They are in coherence with the results reportedy other authors.

a All values of ki are inherent for electric eel AChE.

3.6. Inhibition detection in binary pesticide mixtures

The ostensibly enhanced anticholinesterase activity ofmonocrotophos over paraoxon, which was observed at lowpesticide concentrations, was taken into account during the inves-tigation of the inhibition exerted by mixtures of the pesticides, sothat the pesticide concentrations were selected to be at least 10times greater than 10−7 M. Two sets of samples were prepared asdescribed in Table 3:

The resulting inhibition curves are shown in Fig. 7:As can be seen from Fig. 7, the inhibition curves of the mix-

tures paraoxon – dichlorvos and paraoxon – monocrotophos differfrom the inhibition curve of pure paraoxon. It was interesting toobserve that a binary mixture containing paraoxon with a givenconcentration inhibited the immobilized enzyme to a lesser degreethan the paraoxon sample with the same concentration of thepesticide. Similar observations were reported by other authorsas well [25] for binary mixtures of carbamates: aldicarb – car-bofuran and aldicarb – carbaryl. Taking into consideration thestructural differences between organophosphorous and carbamatepesticides, such phenomenon could be explained with a possiblecompetition of the two pesticides in each mixture for the enzymeactive centers, rather than with some form of allosteric modula-tion of the enzyme–inhibitor interaction. As it was in our case,the mass transfer was diffusion-limited and the first to reach theactive centers were the molecules of the pesticide with the higherdiffusion coefficient under equal other conditions (see Table 4).Furthermore, the samples containing paraoxon – monocrotophosexhibited higher inhibition potency than the binary mixtures of

Dichlorvos 5 5 5 5 5

Paraoxon 1 3 5 7 9Monocrotophos 5 5 5 5 5

I. Marinov et al. / Sensors and Actuators B 160 (2011) 1098– 1105 1103

Table 4Structural dependence of the diffusivity (expressed as diffusion coefficient D) and inhibition potency (expressed as bimolecular inhibition constant ki) of the three pesticides.

Structural formula of the pesticide molecule Partially positivecharge at P atom (e)

ki × 105

(M−1 min−1)Van der Waalsradius (A)

D × 10−6

(cm2 s−1)

0.118 2.30 5.04 4.67

0.085 0.51 4.26 5.52

0.074 0.35 4.25 5.54

pc

ti[maTtip

culated according to the equation:

TC

otent inhibitor than dichlorvos and featuring a similar diffusionoefficient, would reduce the enzyme activity to a greater extent.

That the degree of inhibition depends on pesticide concentra-ion and diffusion coefficient, when enzyme-inhibitor interactions controlled by diffusion, was theoretically justified by Zhang et al.26]. Furthermore the inhibition potency of a pesticide is also deter-

ined by the electronegativity of the leaving group BH (Scheme 1)fter the formation of the stable enzyme–inhibitor complex [11].he more electronegative this group, the greater is the partial posi-

ive charge at the phosphorus atom in the phosphate group, whichn turn makes it more electrophylic and more capable of cou-ling with the serine residue from the enzyme active center. The

able 5omparison of the biosensor operational and storage characteristics with such reported b

Pesticide Detection limit (M) Incubation time (min)

Paraoxon ethyl 1.0 × 10−7 5

Paraoxon ethyl 1.1 × 10−7 8

Paraoxon ethyl 4.0 × 10−13 6

Paraoxon ethyl 1.0 × 10−9 10

Paraoxon methyl 1.0 × 10−9

15Dichlorvos 1.0 × 10−10

Dichlorvos 1.0 × 10−17 20

Dichlorvos 1.0 × 10−8 15

Paraoxon ethyl 0.87 × 10−11

10Dichlorvos 1.22 × 10−10

Monocrotophos 1.08 × 10−11

data in Table 4 confirms the dependence of the inhibition potency(expressed as ki) on the partially positive charge at P atom (thegreater the charge, the greater the bimolecular inhibition constant).

The calculation of the partially positive charges (expressed inelementary charge units “e”; 1e = 1.602 × 10−19 coulombs) at thephosphorus atoms and Van der Waals molecular radii was per-formed by “MarvinSketch version 5.5.1.0”. For more details referto http://www.chemaxon.com. The diffusion coefficients were cal-

D ≈ kBT

6��r(6)

y other authors.

Storage time (days) Residual activity (%) Reference

30 90 [27]180 50 [28]21 85 [29]21 ∼70 [30]Single use screen-printed electrodes [24]

92 65 [31]150 ∼90 [32]

75 50Presentwork

1104 I. Marinov et al. / Sensors and Actua

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3

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ig. 7. Inhibition curves of paraoxon samples (�) and mixtures of paraoxon –onocrotophos (�) and paraoxon – dichlorvos (�).

here kB – Boltzmann constant JK−1; T – room temperature (25 ◦C),; � – dynamic viscosity of the 0.9% saline solution, mPa.s; r – Vaner Waals molecular radius, m.

.7. Operational and storage stability

The intra-assay precision of the sensor was evaluated by assay-ng one enzyme electrode for ten replicate determinations and theelative standard deviation was calculated to be 2.02% for 100 �l.1 mM solution of ATCh. These results were indicative of a goodeproducibility regarding ATCh determination.

When the flow-injection system was not in use, the enzymeembrane was stored at 4 ◦C in 0.1 M PBS, pH 7.6, containing 0.9%aCl. The storage conditions considerably reduced the enzymeembrane deactivation in comparison with our previous work

15]. The half-life storage time of the enzyme membrane (50% resid-al activity) was almost tripled – from 25 to 75 days. After storageor 30 days the enzyme membrane retained over 90% of its initialesponse, which is in coherence with other authors’ reports (seeable 5 below).

. Conclusions

The present work was focused on the employment of a single-nzyme biosensor for detection of organophosphorus pesticides in

flow-injection system. The working conditions were optimizedo that the throughput of the analytical system was improved andhe incubation, measurement and reactivation time of one analyti-al cycle was reduced twice in comparison with our previous work15], where analytical measurements were conducted under staticonditions. Anti-cholinesterase activities (expressed by the detec-ion limits and the bimolecular inhibition constants) of three pes-icides – paraoxon ethyl, monocrotophos and dichlorvos as well asheir mixtures were assessed by the use of a flow-injection system.he total inhibition effect exerted by the binary pesticide mixturesas found to be lower than the anti-cholinesterase activity of theost potent inhibitor amongst the three – paraoxon. This com-

etitive behavior is worth being investigated in detail since it mayresent an opportunity for the discrimination between two or moreesticides present in an analyzed sample by employing chemomet-ics and only one type of acetylcholinesterase. The differentiation

[

tors B 160 (2011) 1098– 1105

could be based on the reduction of the anti-cholinesterase activ-ity of a supplementary inhibitor (pesticide) with known and highinhibition potency. The degree of reduction would depend on thediffusivity (expressed by the diffusion coefficients D), the inhibitionpotency (expressed by the bimolecular inhibition constants ki) andthe concentration of the pesticides, present in the sample.

Acknowledgments

The authors gratefully acknowledge to the Bulgarian Ministryof Education and to the National Science Fund for their financialsupport and encouragement of the scientific research work in stateuniversities.

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detection enzyme methods for determination of different contaminants in the food.Immobilized enzymes on membranes have been applied to the construction of flowinjection systems and biosensors for determination of low concentrations of glu-cose (immobilized glucose oxidase), heavy metal (immobilized urease), pesticides

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Biographies

Ivaylo Marinov is a PhD student in the Department of Biotechnology, “Prof. Dr.Assen Zlatarov” University, Bourgas. The field of his work encompasses immobilizedenzyme systems and amperometric biosensors for the detection of organophospho-rus pesticides.

Yavor Ivanov is a scientific researcher in the Department of Biotechnology, “Prof.Dr. Assen Zlatarov” University, Bourgas. His present research interests comprise thestudy of immobilized enzymes, new nano materials and amperometric biosensors.

Nastya Vassileva is an associate professor in the Department of Biotechnology andFood Products, University of Rousse “Angel Kanchev” – Technology College, Aprilskovastanie Blvd. 3, Razgrad. Her current interests are immobilization of microbial cellsand enzymes on polymer membranes.

Tzonka Godjevargova is a professor of Enzymology and Head of the Department ofBiotechnology in “Prof. Dr. Assen Zlatarov” University. She is also Head of Labora-tory “Buluritest” for production of diagnostic test-strips. Her research interest hasbeen focused on the field of the development of simplified, inexpensive control and

(immobilized acetyl cholinesterase) and phenols (immobilized laccase).