Microbial Sensor for Determination of Tannic Acid

MICROCHEMICAL JOURNAL ARTICLE NO.

60, 201–209 (1998)

MJ981667

Microbial Sensor for Determination of Tannic Acid Yi Bin Zhao,* Meng Liang Wen,* Shi Qing Liu,† Zhi Hua Liu,* Wu Di Zhang,‡ Yun Yao,* and Chang Yi Wang*,1 *Department of Chemistry, Yunnan University, Kunming, Yunnan 650091, People’s Republic of China; †Laboratory of Industrial Microbial Fermentation Engineering, Yunnan University, Kunming, Yunnan 650091, People’s Republic of China; and ‡Laboratory of Rural Energy, Yunnan Normal University, Kunming, Yunnan 650092, People’s Republic of China Received March 2, 1998; accepted September 9, 1998 A fungus biosensor based on an oxygen electrode and Aspergillus ustus immobilized in poly(vinyl alcohol) was developed to determine tannic acid in a batch system. The optimum temperature was 30.0°C and the optimum pH was 7.0 in 0.10 M phosphate buffer. The regression equation of the 0.53 0.08 calibration curve between 0.0250 and 1.025 mM was ~x ln y!~20.727242x /54! 1 C~x ln y!~20.218912x / 2! 5 A 1 B/x (r $ 0.99985). The sensor had a life of at least 2 weeks; it yielded a negligible response to the compounds commonly coexisting with vegetable tannins. © 1998 Academic Press

INTRODUCTION The quantitation of vegetable tannins goes back to the early part of the 19th century (1). It is why, in 1897, the first leather chemists’ society was formed (2). Although large quantities of vegetable tanning materials are still being used, and recently tannins have been found to have antitumor, antiperoxidation, antivirus, and other physiological activities, no single, universally acceptable, standard official method of tannin quantitation exists (3). To make an effort toward resolving the problem, the present authors developed a microbial sensor to determine tannic acid, the most commonly used standard for tannin quantitation. Degradation of tannins by bacteria and fungi had been studied and reviewed extensively (4, 5). This study was the application of such degradation to tannin quantitation. The current quantitative methods are based on the principles of redox, metal complexing, anthocyanidin formation by acid catalysis in butanol without or with Fe31, condensation of vanillin with the phloroglucinol ring catalyzed by hydrochloric acid, and protein or alkaloid binding (6, 7). Compared with these methods, the proposed tannic acid sensor, in common with other biosensors (8, 9), has a high selectivity in complex biological sample solutions. Since it measures directly without any troublesome operations, the sensor is easily automated as well as more suitable for monitoring and process control. MATERIALS AND METHODS Reagents and Apparatus Tannic acid (Zunyi No. 2 Chemical Works, Guizhou, China) was a mixture of polygalloyl– glucose esters from gallnuts of Rhus chinensis. All chemicals were of reagent 1

To whom all correspondence should be addressed. Fax: 186 871 515 3832. E-mail: [email protected]. 201 0026-265X/98 $25.00 Copyright © 1998 by Academic Press All rights of reproduction in any form reserved.

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FIG. 1. Schematic diagram of microbial electrode.

grade without further purification. Solutions were prepared using distilled, deionized water. The serially diluted standard tannic acid solutions in phosphate-buffered saline (PBS) at pH 7.0 were freshly prepared with 0.10 M PBS (pH 7.0) and sodium hydroxide (NaOH) solution. Oxygen-consuming rate measurements and pH measurements were performed on two Model LM-1 digital oxygen analyzers combined with oxygen electrodes (Institute of Metallurgy, Chinese Academy of Sciences, Shanghai, People’s Republic of China) and a Model-901 microprocessor ionalyzer (Orion Research Inc., Cambridge, MA), respectively. The oxygen-based sensor system has been described previously (10, 11). Culture and Immobilization of Microorganisms Aspergillus ustus screened through 20% Eupatorium adenophorum extract agar had shown high activity for the degradation of toxic tannins in E. adenophorum (12). Cultures of Aspergillus ustus maintained on wheat bran with tannic acid at 4°C were transferred to sterile 250-ml Erlenmeyer flasks containing 125 ml of potato dextrose medium composed of 20% potato extract and 2% glucose. The flasks were kept on a rotary shaker at 180 rpm for 7 to 10 days at 28°C. The sclerotia harvested were spherical, yellow green, 3 to 4 mm in diameter, with a few rhizomorphs on every surface, and filling clear solutions in the flasks. Cultures were puddled in a food chopper; 10 ml of the resulting suspension containing about 0.6 g of wet chip sclerotia was mixed with 9 ml of 10% poly(vinyl alcohol) (PVA) solution in 9-cm Petri dishes; the air-dried PVA membranes were elastic, about 300 mm thick, and stored in 2% glucose solution at 4°C. Preparation of Tannic Acid Sensors As shown in Fig. 1, the sensor–transducer was a polarographic oxygen electrode covered with a Teflon membrane 15 mm thick. A nylon screen (200 mesh) and a PVA membrane cut into circles were outside it. All three membranes were compacted to the

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electrode core with an electrode gland nut. The sensing head was immersed in 0.500 mM tannic acid solution in PBS at pH 7.0 (Solution A) at room temperature for 1 to 2 days, and there was a thin, uniform, greenish-black subiculum with a high respiratory activity between the PVA membrane and the nylon screen. The prepared sensors were stored in 2% glucose solution at 4°C. Procedure for Batch Measurements The sensing head was immersed in Solution A at room temperature overnight or at 30°C for 3 h for the induction of the substrate-specific enzyme system. The fresh mycelium outside the nylon screen was shaved off with a razor blade; the sensor was inserted in a thermostated 15-ml circulating-water jacket containing 10.0 ml of 0.10 M PBS (pH 7.0, 30.0°C). Owing to ample magnetic stirring and oxygen exchange between the solution and the surrounding air, the oxygen concentration was constant around the outer sensingmembrane surface. Thus, the relative oxygen concentration detected inside depended directly on the oxygen consumption rate in the sensing membrane, and was different from the concentration that had relied indirectly on the anoxybiotic degree around the outer surface in a previous experiment (10). After the transformation from the concentration into current in the sensor, the oxygen analyzer connected to the sensor amplified the signal of the concentration by transferring the current to voltage. The resulting millivolt value displayed by the analyzer became stable after 5 to 6 h. The stable value was taken as a blank value. Several microliters of 50.0 mM tannic acid solution in PBS (pH 7.0) was injected into 0.10 M PBS, an analyzer reading was recorded every 30 s, and the lowest millivolt value was in 30 to 120 min. The difference, DE (mV), between the blank value and the lowest value was used as the relative scale for the microbial respiration increase to represent the concentration of respirable substrate; that is, the relation of DE to concentration was on a quantitative basis. The lowest millivolt value of the next sample was obtained after a sample solution was injected again with/without changing the solution in the jacket before the injection. The average measurement time per sample was generally less than that in the three basic methods (3) and some other methods (7). The batch system, not a flow injection analysis (FIA) system, was chosen because the compound of high molecular mass required a long residence time of the sample at the sensor for exoenzymatic predigestion (13). RESULTS PVA Membrane Composition and Fresh Subiculum Before the mixing, phenazine methosulfate (0.20 g), 4,49-dipyridyl (0.10, 0.20, and 0.40 g) and ferrocene (0.10, 0.20, 0.30, 0.60, and 1.00 g) were added to the Petri dishes respectively. Phenazine methosulfate and 4,49-dipyridyl killed or inhibited the microorganisms; the sediment of ferrocene retarded mass transfers as well as thickened the membrane, and the response was laggard, with millivolt-value fluctuation in a great range. Therefore, it was inadvisable to add other electronic mediators on condition that oxygen was the electronic mediator. The sensibility of the tannic acid sensor was due to fresh subiculum between the PVA membrane and the nylon screen, rather than chip sclerotia in the PVA membrane. As the sensing head of the sensor was immersed in Solution A, the oxygen consumption rate increased (the blank value decreasing), as did the response (DE)

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FIG. 2. Calibration curves of tannic acid sensors in 0.10 M PBS (pH 7.0, 30.0°C) either immersed in Solution A at room temperature overnight after sensor assembly (a) or in useful sensor life (b, c) or immersed in Solution A at room temperature for 20 days after sensor assembly (d).

(Figs. 2a, 2d), while the subiculum grew (thickened) without chip sclerotia growth in the PVA membrane. Considering the mechanical strength and the oxygen diffusion rate, PVA membrane thickness, which depended on the amount of PVA, was between 50 and 400 mm. Temperature Selection Conventionally, the stable millivolt value at 20.0°C involving microbial respiration in PBS (pH 7.0) acted as a blank value at every constant temperature, which resulted in an apparent temperature curve (Fig. 3a). The stable millivolt value [the sensor in PBS (pH

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FIG. 3. Effect of temperature on respiratory activity of microorganisms in tannic acid sensor. The sensor was immersed in 50.0 mM tannic acid solution in 0.10 M PBS (pH 7.0). Each of the lowest millivolt values was obtained at a constant temperature during the rise from 20.0°C. (a) Apparent temperature curve. (b) True temperature curve.

7.0)] at 20.0°C not involving respiration (the microorganisms killed) acted as blank value at 20.0°C. The effect of temperature on the dissolved oxygen concentration was deducted (14) from the blank value, and the results acted as blank values at the other temperatures not involving respiration. All these absolute blank values resulted in a true temperature curve (Fig. 3b). The highest respiratory activity was between 35.0 and 40.0°C (Fig. 3b), and the shortest equilibrium time was at 40.0°C. Nevertheless, millivolt values were unstable from 35.0°C up; at 40.0°C, the respiratory enzymes were gradually inactivated and respiratory activity decreased after a time. Consequently, 30.0°C was selected as the measurement temperature for value stability, measurement length, and high respiratory activity. pH Selection The effect of pH on the dissolved oxygen concentration was negligible, and the stable millivolt value [the sensor in PBS (30.0°C)] at pH 7.00 not involving respiration acted as a blank value at every constant pH, which resulted in a true pH curve (Fig. 4). At pH 6.36

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FIG. 4. Effect of pH on respiratory activity of microorganisms in tannic acid sensor. The sensor was immersed in 50.0 mM tannic acid solution in 0.10 M PBS (30.0°C). Each of the lowest millivolt values was obtained at a constant pH during the addition of NaOH solution from pH 4.48.

and below, respiratory activity was high, but the millivolt value was unstable and the equilibrium time long. Above pH 6.74, the millivolt value was stable and the pH high; respiratory activity was high and the equilibrium time short. Nevertheless, tannase (tannin acyl hydrolase, EC 3.1.1.20) had low activity (15) and tannic acid was easily oxygenated at high pH (e.g., pH 7.66). Consequently, for value stability, determinand stabilization, and tannase adaptation pH 7.0 was selected as the measurement pH. Calibration Curve and Recovery The calibration curves of oxygen-based microbiosensors have generally been represented by linear equations (e.g., Y 5 A 1 BX) or enzymatic kinetic equations (e.g., 1/Y 5 A 1 B/X). However, the curves of these equations are quite different from actual

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MICROBIAL SENSOR FOR TANNIC ACID TABLE 1 Recovery of Tannic Acid Concentrationsa Recovery (%) Concentration (mM)

1b

2b

3b

4b

5b

Average recovery (%)

RSD (%)

0.0750 0.150 0.275 0.525

100.3 98.2 101.4 101.9

95.7 97.3 100.4 104.5

100.0 98.0 99.8 102.6

95.7 99.7 102.7 104.8

96.9 101.7 102.0 103.6

97.7 99.0 101.3 103.5

2.3 1.8 1.2 1.2

a The standards (0.0250 and 1.025 mM) were measured once each time (number). The procedure was that described in the text. b Number.

calibration curves. With monovariant nonlinear regression analysis (16), a calibration curve equation for the tannic acid sensor was deduced in this study. The equation is ~ x ln y! ~20.727242x

0.53/54!

1 C~ x ln y! ~20.218912x

0.08/ 2!

5 A 1 B/x ,

where x is the tannic acid concentration (1025 M), y is DE (mV), and A, B, and C are three undetermined coefficients. The application range is between 0.0250 and 1.025 mM tannic acid; the correlation coefficient, r (n 5 6), is 0.99985 or above in useful sensor life. The left of the equation was Y in Y 5 A 1 BX, while 1/x was X. The functional relationships between x, y and X, Y were obtained after various functional relations had been tried for a maximum fit between the curves of a resulting equation and the actual curves of the sensor. In the range between (x ln y)∧(20.727242x∧0.53/54) and (x ln y)∧(20.218912x∧0.08/2), each tannic acid sensor had a point represented by a value of C. Two standards were measured once a day for the values of A and B of each sensor, and three standards were measured after the sensor preparation for the value of C of each sensor. The recoveries of tannic acid concentrations (Table 1) were obtained by this quantitative method. As substantiated, the measurement results were reliable and consistent. Consequently, this method was practicable. Reproducibility and Lifetime As described otherwhere (17), the calibration curve changed little every day, but this was due to the growth of the subiculum in tannic acid solution in PBS. With discontinuous employment of the sensor, the 2% glucose solution survived the subiculum and inhibited its growth, so the lifetime of the sensor was more than 1 month. With continuous employment, the subiculum was continuously immersed in tannic acid solution in PBS and continuously grew, so the lifetime was only 2 weeks. As shown in Fig. 2d, the increase in respiratory activity of the subiculum, which is thick, was large and liable to saturation in the high concentration region. In the low concentration region (the linear range of the sensor), the equilibrium time of the sensor was long and the sensor was unpractical. Thus, it was necessary to replace the PVA membrane with the thick subic-

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ZHAO ET AL. TABLE 2 Relative Response of Tannic Acid Sensor to Compoundsa Compounds

Relative response (%)

Compound

Relative response (%)

Tannic acid Succinic acidb,e, f c,d, f L-Tyrosine Salicylic acidc,e trans-Cinnamic acidc,e, f Ethanold, f Citric acide, f Theophyllinee Theobrominee Oxalic acide, f

100.0 9.9 34.2 27.5 100.8 116.3 14.2 0.4 22.1 23.4

Catecholb b,d–f D-Glucose c,d, f L-Tryptophan c Benzoic acid Mandelic acidc,e Acetic acidd, f Formic acide Caffeinee e D,L-Malic acid

31.7 50.2 25.8 88.3 14.2 53.5 14.8 22.6 4.7

a Each compound was a 0.15 mM solution in 0.10 M PBS (pH 7.0, 30.0°C). Each time, several compounds were individually measured after measurement on tannic acid. b Metabolic intermediate of tannic acid. c Analogue of tannic acid. d Common interferent of microbiosensors. e Commonly coexisting compound of vegetable tannins. f The millivolt value at 120 min was taken as the lowest millivolt value.

ulum. However, the storage life of the air-dried PVA membranes was longer than half a year. Selectivity The relative responses to the first three kinds (Table 2) resembled those presented otherwhere (18). The commonly coexisting compounds of notable interference were trans-cinnamic acid and D-glucose. Therefore, the tannic acid sensor had sufficient selectivity to quantitate vegetable tannins. DISCUSSION The tannic acid sensor based on microbial respiration represents a new approach to the convenient and low-cost quantitation of vegetable tannins. The sensor has given valuable selectivity and recovery, thus providing a useful reference method. Additionally, the following improvements are required before the sensor becomes widely accepted in leather, food and other industries: ● addition of an appropriate growth inhibitor for the lifetime and reproducibility of the sensor; ● predigestion of tannins with tannase before the sensory measurement to shorten the equilibrium time, application of the FIA system (for measurement automaticity, continuity, and rapidity), and enhancement of the sensory selectivity (on account of the shortened residence time and constancy of enzyme induction time).

ACKNOWLEDGMENTS The authors gratefully acknowledge work support from the Science Fund of Application and Foundation of Yunnan (Grant 96B008M) and the Scientific Research Fund of the Yunnan Education Commission (Grant 9512062).

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