An exercise degree monitoring biosensor based on electrochemiluminescent detection of lactate in sweat

An exercise degree monitoring biosensor based on electrochemiluminescent detection of lactate in sweat

Sensors and Actuators B 143 (2010) 655–659 Contents lists available at ScienceDirect Sensors and Actuators B: Chemical journal homepage: www.elsevie...

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Sensors and Actuators B 143 (2010) 655–659

Contents lists available at ScienceDirect

Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb

An exercise degree monitoring biosensor based on electrochemiluminescent detection of lactate in sweat Xia Cai, Jilin Yan, Haihong Chu, Meisheng Wu, Yifeng Tu ∗ Institute of Analytical Chemistry, Department of Chemistry, Suzhou University, Dushu Lake Higher Education Town, China-Singapore Suzhou Industrial Park, Suzhou 215123, PR China

a r t i c l e

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Article history: Received 19 June 2009 Received in revised form 15 September 2009 Accepted 1 October 2009 Available online 12 October 2009 Keywords: Lactate Biosensor Electrochemiluminescence Monitoring of exercise degree Luminol

a b s t r a c t An electrochemiluminescent (ECL)-based lactate (LA) biosensor is developed with luminol as signaling species. LA was oxidized under the catalysis of immobilized lactic dehydrogenase (LDH) and pyruvate oxidase (PYOD) with nicotinamide adenine dinucleotide (NAD) as coenzyme. As a result, the reaction yielded the hydrogen peroxide, which enhanced the electrochemiluminescence of luminol, which was acceptable for sensing the LA concentration. The resulting biosensor showed excellent response for lactate. A detection limit of 8.9 × 10−12 mol/L was obtained with the relative standard deviation (RSD) of 4.13% (CLA 1.34 × 10−10 mol/L, n = 6) and an average recovery of 101.3% for real sweat sample. The research suggests that the ECL-based biosensor was practicable for detecting the LA in sweat samples of athletes during the exercitation for evaluation of exercise degree. © 2009 Elsevier B.V. All rights reserved.

1. Introduction Biosensor is a kind of artificial device that uses biological principium to detect the target matters [1,2]. It is generally constructed with a biological recognition element and a physical transducer. The transducer could be the electrode, photon detector, thermistor, quartz-crystal microbalance (QCM), surface plasmon resonance (SPR) device [3] and so on. The biological recognition elements are usually bioactive species such as enzymes, antibodies, DNA, receptors, tissues or microorganisms owing to their excellent selectivity for the target molecules [4]. Based on this design, those bioactive species react with or catalyze the reaction toward the target analyte to yield varied chemical or physical changes that would be finally signaled by a transducer. It realizes the transformation of chemical or biological information into recognizable and useful electronic signals, that provided rapid, accurate, and reliable information about the target analytes [5]. It is presently playing a significant role in application fields such as medicine, agriculture, food safety, homeland security, environmental as well as industrial monitoring. Among these devices, the chemical or biochemical luminescent sensors have also been reported [6]. Electrochemiluminescence (ECL) is a simple but sensitive method for analytical detections [7]. It provides a real-time

∗ Corresponding author. Tel.: +86 138 12768378; fax: +86 512 65101162. E-mail address: [email protected] (Y. Tu). 0925-4005/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.snb.2009.10.002

analytical approach with the feasibility of automation, low-cost instrumentation, while limited requirement of expensive reagents [8,9]. As a powerful technique, ECL has become an important analytical means in recent years [10,11]. Luminol is one of the most popular ECL species as it could give out strong emissions, especially with the presence of reactive oxygen species (ROSs) [12]. Luminol-based ECL detection has also been researched as a biosensing technique in optical sensors with oxidase as the catalyst [13]. It provides an opportunity to construct the enzymatic biosensors based on the ECL of luminol, which involves specific enzymatic reaction of substrate and the subsequent ECL reaction between luminol and hydrogen peroxide or related biological compounds which were produced in enzymatic reactions. It is well known that enzymes were among the most active and selective catalysts responsible for relevant chemical or biochemical reactions [14]. The strategy of enzyme immobilizing is the crucial process in biosensor creations [15]. The immobilized enzymes must be easily accessible and chemically inert towards the host matrix [16]. In recent years, there have been intensive reports on the adoption of carbon nanotubes (CNTs) for its significant advantages. It is practicable to improve the chemical or electrical properties of resulting devices due to its high surface activity, the meso-porous inner tubule and the well tunable structure. Enzymes, in particular oxidases, have been reported to be entrapped in CNTs matrices [17]. Lactate (LA) and its derivatives are widely subsistent chemicals. In human body, LA is one of the most important products of gly-

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colysis and hypoxia metabolism in myocytes and then be released into blood, and mass produced during physical actions [18]. The typical significance to monitor LA level in the blood is to evaluate the health status of kidney. High level of LA in blood will cause the LA poisoning, which induces some discomfort such as muscle ache or fatigue. Monitoring of blood LA is also suggested for scientifically programming the athletic training. But the unpleasant demerit of blood sampling from finger tip or vein makes it unpractical to be widely used. In this paper, a sensitive ECL-based biosensor will be reported for athletic application by detecting the LA in sweat. 2. Materials and methods 2.1. Instruments and reagents The ECL detection system used in this work was self-constructed as described in our previous paper [19]. A 5 mL tubular phial is used as an ECL cell. The phial was completely shielded with a silvermirror film, which has only a small window at the middle site of its bottom to allow the transmission of light. A discal platinum electrode is used as the basal working electrode. A platinum wire and an AgCl coated silver wire act as the auxiliary and reference electrodes, respectively. The ECL cell is mounted on the window of a photoelectric multiplier (PMT), meanwhile the cell and PMT are shielded in a black box. The PMT is powered by a negative high voltage (−1000 V DC) supplier and the photocurrents were recorded by a digital meter. A BAS-100A Electrochemical Analyzer (Bioanalysis System Inc., USA) is used as a potentiostat to exert the electrolytic potential with a digital pulse generator as the outer pulse source. Luminol was purchased from Fluka (USA) and lactate from Alfa Aesar (USA). Lactic dehydrogenase (LDH), nicotinamide adenine dinucleotide (NAD) and pyruvate oxidase (PYOD) were obtained from Sigma (USA). Carbon nanotubes (CNTs, less than 10 nm in diameter and 0.5–500 ␮m in length with least 95% of purity) were purchased from Shenzhen Nanotech Port (Shenzhen, China). The

CNTs were dispersed in dimethylformamide (DMF) ultrasonically as solid content of 0.33 g/mL. All other reagents were of analytical grade, double-distilled water was used throughout the experiment. 2.2. Fabrication of ECL-biosensor A discal platinum electrode was burnished with a sand paper, then polished with alumina slurry and washed with methanol and water under ultrasonic. Then, 6 ␮L of mixture of CNTs suspension and potassium ferrocyanide solution with 1:1 of volume was dripped onto its surface and waited for being air-dried. Finally, the sensor was constructed by loading the mixture of LDH, NAD and PYOD onto the electrode surface. The loading amounts of those species would be optimized for best sensing characters. After the water was evaporated, the enzymes were immobilized on CNTs due to adsorption [20]. 2.3. Optimization of experimental conditions The ECL of luminol is very sensitive and the intensity strongly susceptible to many environmental factors. In order to optimize the detection performance of biosensor, the pH, temperature and others were optimized, respectively. The experiments were carried out in the testing solution of phosphate buffer (pH 8.0) which contained 2 × 10−6 mol/L of luminol (testing solution A). For comparison, 6.68 × 10−5 g/mL of LDH, 6.67 × 10−5 g/mL of NAD and 4.2 × 10−6 g/mL of PYOD were contained in it to act as the referenced testing solution (testing solution B) for examining the ECL response of bare electrode. 2.4. The detection of sweat LA In an athletic training course, the sweat samples were collected with a micro-syringe when the sweat transuded from voluntary students. The volume of samples of every sampling is about 0.1 mL,

Fig. 1. The optimization of (A) buffer acidity, (B) temperature and (C) the loading amount of LDH, NAD and PYOD on ECL response of resulting biosensor.

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Table 1 The reproducibility of linear ECL response.

Fig. 2. The ECL response of (a) bare platinum electrode and (b) resulting biosensor. The insert is the double-logarithmic chart of ECL intensity vs. concentration of LA over whole linear regression range on resulting biosensor.

they were deposited in centrifugal tubes and preserved in a refrigerator. For determination, 1 ␮L or 10 ␮L of the sample according to the exercise degree was sucked with micro-syringe to transfer into 1 mL of the testing solution A. Other conditions of determination were all the same as the standard LA sample. 3. Results and discussions 3.1. The optimization of important factors As general knowledge about ECL mechanism of luminol, high pH up to 12 is of benefit for higher yielding of luminol radicals [21] therefore the ECL intensity. But meanwhile, the enzymes might be deactivated under such high pH. Based on these considerations, the pH has to be optimized for the best ECL response. In the testing solution A, the experimental results showed that the maximal ECL signal was obtained at pH 8.0, as can be seen in Fig. 1A. It is also well known that the performance of enzyme is highly sensitive to the temperature. The ECL intensity of luminol without enzyme is strongest at about 21 ◦ C, while in presence of enzymes, the ECL signal reached its maximum under 30 ◦ C (see Fig. 1B). The joint action of LDH, NAD and PYOD can catalytically oxidize the LA to yield the H2 O2 , so their loading amounts greatly affect the ECL intensity. The ECL intensity reached the highest level while the optimal loading amounts of enzymes, it could be seen in Fig. 1C. Under these conditions, the ECL was highest responded to the concentration of LA. According to the experiments, it was found that the strongest ECL intensity was achieved when 17 ␮L of mixture was used that contained 6 ␮L of 16.7 mg/mL LDH, 5 ␮L of 20 mg/mL NAD and 6 ␮L of 0.8 mg/mL PYOD. 3.2. The characteristics of the ECL-biosensor As shown in Fig. 2, the ECL emission of resulting biosensor responded linearly upon the concentration of LA (line b). Compara-

Sequence

Slope

RSD (%)

Intercept

RSD (%)

1 2 3 4 5

0.6226 0.5919 0.6103 0.5961 0.6097

2.03

7.940 7.695 7.832 7.741 7.893

1.31

tively, smaller ECL signal was obtained on bare platinum electrode in testing solution B under the same conditions (line a) within same concentration range. There was approximate 10 multiples of analytical merit, it proves the higher sensitivity of ECL response obtained on biosensor than on bare electrode. The insert of Fig. 2 is a double-logarithmic illustration of ECL intensity vs. LA concentration within the range of 8.9 × 10−12 mol/L to 8.9 × 10−6 mol/L. It demonstrates a more sensitive and wider linear response range of resulting biosensor, the linear range could extended down to 8.9 × 10−12 mol/L. Comparatively, the linear response range on bare electrode is from 8.9 × 10−10 mol/L to 8.9 × 10−6 mol/L of LA concentration. It is clear that the resulting biosensor had a much lower detection limit for two magnitudes of orders. Also the stability of this biosensor was evaluated by the RSD of slope and intercept of the regression equations of logarithmic ECL intensity vs. log CLA that are included in Table 1. It suggests the quite good repeatability and stability of resulting biosensor. The relative standard deviation of the biosensor responded to 1.34 × 10−10 mol/L LA was 4.13% for six parallel measurements, which suggested a good reproducibility. Table 2 shows the results of determination of LA in sweat sample and the recovery. The 101.3% of average recovery and the 2.99% of RSD are quite satisfactory. If there were some activators or inhibitors within the sample, it might disturb the detection. Here some inorganic ions or organic substances were tested for their influence on the ECL measurement. The foreign species were considered not to be interferences if they merely caused a relative error of less than ±10% to the analytical signal of LA. The tolerance ratios were determined as 1000 folds for K+ , Na+ , Ca2+ and Cl− , 150 folds for uric acid and 100 folds for ascorbic acid. 3.3. Application of ECL-biosensor in monitoring of exercise degree The resulting biosensor could be applied for monitoring the exercise degree by detecting the LA in sweat. With the gradual increasing of exercise intensity, the amount of lactate in sweat was found as an orderly increase. From Fig. 3, the results of two voluntary students can be seen. Both the contents of lactate rose slowly at the beginning period of low intensity exercise, and then there appeared a sharp increase after sufficient exercise. 3.4. The detecting principle and kinetics The lactate could be catalytically dehydrogenated by LDH to yield the pyruvic acid with coenzyme NAD as receptor of hydrogen. The so-produced pyruvic acid could then be oxidized by oxygen under the catalysis of PYOD, and hydrogen peroxide was produced contemporary during this process as the reduction products of oxy-

Table 2 Determination results of the samples and recovery. Sample content (10−7 mol/L)

Added (10−7 mol/L)

Measured (10−7 mol/L)

Recovery (%)

Average bias (%)

RSD (%)

5.37

5.36

11.13 10.34 11.07 10.64

107.5 92.7 106.3 98.5

0.19

2.99

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Fig. 3. The LA level in sweat of (a) voluntary student A and (b) voluntary student B in athletic training course.

gen. The hydrogen peroxide could further be involved in the ECL reaction of luminol as an efficient intensifier. It could enhance the ECL intensity of luminol concurrent with the electron transfer assistance from potassium ferrocyanide. As the result, the ECL intensity of luminol on this biosensor was thereby controlled by the concentration of LA. The reaction process could be expressed as follows.

The kinetic study is useful for supporting the above-mentioned discussion. As can be seen in Fig. 4, at ambient temperature, the initial reaction rate that was conversed from the instantaneous ECL intensity was calculated and illustrated along with the successively added amount of LA in testing solution. Clearly, it matched very well with the Michaelis–Menten equation [22]. It demonstrates that the ECL response on this biosensor could be attributed to a typical enzyme catalytic reaction. According to Lineweaver–Burk method [23], the values of Vmax and KM were calculated to be 2.60 × 10−8 mol/L/s and 2.09 × 10−9 mol/L, respectively. The KM here is much smaller than the reported data obtained in free solution [24]. It indicates that the activity of enzyme was obviously promoted after immobilized by CNTs. 3.5. The meanings of exercise degree monitoring by assay of sweat If there was a lower intensity in the training course, the limited amount of lactate could be metabolized in liver [25]. The balance between the generation and the elimination did not cause the severe increase of LA amount in sweat, it could be seen during the period of 25 min for voluntary student A and 35 min for

Fig. 4. The Michaelis–Menten curve of resulting biosensor.

voluntary student B in Fig. 3. However, when it reached a certain intensity of exercise, the production of lactate was faster, so that the concentration of LA in sweat began to sharply rise. This point of time can be regarded as a critical point of mutation of metabolism from aerobic to anaerobic [26]. It means that with the increasing exercise intensity, the ratio of energy from anaerobic

metabolism will gradually increase. When anaerobic metabolism predominated, the production of LA is much faster than the clearance rate by the liver, so the accumulative amount of LA rose sharply and caused the symptoms of fatigue such as ache and clonus. Each person has a different “critical point”, and its value can reflect the exercise capacity. The difference between voluntary students A and B in Fig. 3 revealed it clearly. It means that the training could delay the appearance of “critical point” for trained athlete than an amateurish one. 4. Conclusion This paper shows that the enzyme recognition and catalysis were powerful functions for successfully coupled with an optical detection based on ECL of luminol to develop the ECL-based biosensor. The designed LA sensor for exercise degree monitoring is a model of excellent achievement. It shows very sensitive response to LA with good stability and reproducibility, even to be applied in detection of real human sweat samples. The wide linear range and low detection limit for LA declares its great potential of applications. Blood samplings are needed no longer during monitoring

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exercise degree instead by sweat in future, which decreases the infection of pathogen. We believe it might be a very useful tool for researches of LA for sport medicine and so on.

[19] [20] [21] [22]

Acknowledgement

[23]

This work was supported by the National Natural Science Foundation of China (20275025 and 20675055).

[24] [25] [26]

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Biographies Xia Cai received her B.S. degree in 2007 in Nanjing Xiaozhuang University. She is currently pursuing her M.S. degree in Suzhou University under the supervision of Professor Yifeng Tu. Her research focuses on the ECL biosensors. Jilin Yan received his PhD degree from Changchun Institute of Applied Chemistry, the Chinese Academy of Sciences in 2006. Then he worked as a postdoctoral research associated in the Chemistry Department in University of Florida. Currently he is an associate professor at the Chemistry Department in Suzhou University, China. His research interests include ECL sensing and molecular recognition. Haihong Chu received her B.S. and M.S. degree in Suzhou University. She is currently pursuing her PhD degree in Suzhou University under the supervision of Professor Yifeng Tu. Her research focuses on the ECL sensors. Meisheng Wu received her B.S. degree in 2006 in Suzhou University. She is currently pursuing her M.S. degree in Suzhou University under the supervision of Professor Yifeng Tu. Her research focuses on the ECL biosensors. Yifeng Tu received his PhD degree in Department of Chemistry, Nanjing University, P.R. China in 2001. Presently, he is a professor in the Department of Chemistry, Suzhou University, P.R. China. His current interests are to develop electrochemical biosensors and electrochemiluminescent detectors for biomedical applications.