In Vivo Detection of Glutamate in Tomatoes by an Enzyme-Based Electrochemical Biosensor.

The in vivo and on-site detection of key physiology parameters in plants will be of great relevance for precision agriculture and food technology. In this work, a sensitive enzymatic glutamate sensor was successfully developed. To enhance the conductivity and catalytic ability and to fix the glutamate oxidase, Au-Pt nanoparticles were first deposited on screen-printed electrodes, and then carboxylated graphene oxide and carboxylated multiwalled carbon nanotubes were fabricated for the synthesis of the electrode. The detection range of the glutamate sensor is widest (2 μM to 16 mM) up to date, and its detection limit is relatively low (0.14 μM). A number of standard curves were built in the pH range of 3.5-7.5, which can be applied in various plants and fruits. Using this sensor, the glutamate level in tomatoes was determined in vivo. This glutamate sensor has important practical value in precision agriculture. Our strategy also provides a way to establish the detection modes for other biomolecules in plants.

Introduction

l-Glutamate is an amino acid which occurs naturally in plants. It plays an important role in protein metabolism, provides energy and materials for plant growth, and promotes the development of plant organs. Glutamate also links nitrogen metabolism[1,2] with carbon metabolism to produce aminobutyric acid,[3,4] arginine,[5] serine, cysteine, and other substances required for plant metabolism, which provides conditions for plant environmental adaptability. In addition, glutamate is an important nutrient in fruits; it is an important indicator for fruit yield and quality. With the development of precision agriculture, researchers hope to monitor the changes of glutamate content in plants in vivo and on site and timely evaluate the growth status of plants and the nutritional level of fruits, so as to realize the precise regulation of agriculture and serve food technology.

Different techniques have been used for detecting glutamate, for example, chromatography,[6,7] spectrophotometry,[8,9] fluorimetry,[10,11] and so on. However, these methods are all used in vitro. The plant samples need to be pretreated. This process is complex and time-consuming, and some important biological information will always be lost during this process. In vivo techniques for detecting glutamate have also been developed, such as nuclear magnetic resonance spectroscopy,[12] positron emission tomography, and so on. However, these apparatuses are expensive and not portable. They are not adaptable for on-site application in precision agriculture.

Electrochemical sensors are one of the most potential approaches for in vivo and on-site monitoring of biomolecules, because of their simplicity, sensitivity, portability, and easy-to-miniaturize and -integrate nature.[13−18] Several in vivo electrochemical sensors for glutamate have been developed. For example, for in vivo glutamate monitoring in spinal cord, Nguyen et al. have fabricated a flexible glutamate biosensor using a simple direct ink writing technique.[19] Ganesana et al. developed a microbiosensor for in vivo monitoring of glutamate release in the brain.[20] However, these glutamate sensors were developed based on the application in humans or animals. The content of glutamate in plants is much higher than that in animals and humans. For example, the glutamate in watermelon is about 12 mM,[21] while the glutamate in the extracellular space of the human brain is in the range of 4–350 μM.[22] Moreover, the pH of plant juice is quite different from that of blood of animals and humans. Most fruits are acidic. The pH value of plant juice varies greatly according to different species, different growth stages, and different tissue types. Therefore, the developed glutamate sensors are not suitable for plants, and there is an urgent need for developing in vivo and on-site sensors for glutamate in plants.

To develop a practical sensor which can be widely used in agriculture, screen-printed electrodes (SPEs) were applied because of their low cost and mature manufacturing technology. For enzymatic biosensors, the enzyme plays a crucial role in oxidizing and detecting the target molecules. In our work, l-glutamate oxidase (GlutaOx) was used as it does not need the help of coenzymes.[23] Nanomaterials have been widely used in electrochemical biosensors to improve their performance. Carboxylated graphene oxide (GO–COOH) and carboxylated multiwalled carbon nanotubes (MWNT–COOH) are introduced into this sensor, because they not only have the advantages of excellent catalytic ability and a large surface area,[24−29] but also the −COOH groups in them can be used to fix the enzyme by EDC/NHS coupling. To further enhance the electrochemical catalytic ability of the electrode, Au–Pt nanoparticles (NPs) were also deposited on the electrode, as metal NPs have a high surface/volume ratio and unusual electronic properties.[30,31] The developed glutamate sensor is simple and practical, with the widest detection range and a lower detection limit. In addition, as the pH value of plant juice varies greatly according to different species, different growth stages, and different tissue types, a number of working curves for the glutamate sensor were built under different pH values. Our strategy supplies a way for monitoring glutamate in vivo in a larger variety of plants and fruits.

Materials and Methods

Reagents

GlutaOx, glutamate monosodium salt monohydrate, 1-(3-dimethylaminopropyl)-3-ethylcarbodiimide hydrochloride (EDC), N-hydroxysuccinimide (NHS), Nafion solution (5 wt%), bovine serum albumin (BSA), and gold(III) chloride trihydrate (HAuCl4·3H2O) were purchased from Sigma. GO–COOH and MWNT–COOH were purchased from Xianfeng Nanomaterials Technology Co., Ltd. Chloroplatinic acid hexahydrate (H2PtCl6) was purchased from Macleans Biochemical Technology Co., Ltd. (Shanghai, China). Ascorbic acid, lysine, valine, aspartic acid, alanine, isoleucine, phenylalanine, leucine, glycine, and proline were purchased from Sinopharm Chemical Reagent Co., Ltd. Company (Shanghai China). The rest of the reagents are of analytical grade.

Apparatus

For studying the morphology of the modified electrode, a SEM 500 field emission scanning electron microscope system (ZEISS, Germany) was used to study the morphology of the different modified electrode, and energy-dispersive X-ray spectroscopy (EDS) which was equipped on the SEM was used to study the composition and distribution of elements of the Nafion/GlutaOx/GO–COOH–MWNT–COOH/Au–Pt/SPE sensor. All electrochemical tests are performed on an Autolab electrochemical workstation (Metrohm, Switzerland). The SPE was bought from Ningbo Mxense Biotechnology Co., Ltd. The working electrode and counter electrode are both made of carbon-based materials. The reference electrode is made of silver/silver chloride. All electrochemical measurements are performed at room temperature.

Nanomaterial Preparation and Electrode Fabrication

The HAuCl4/H2PtCl6 solution was prepared by dissolving 0.081 mM HAuCl4 and 0.160 mM H2PtCl6 in 0.5 mol/L H2SO4. The nanocomposite of GO–COOH/MWNT–COOH was obtained by dissolving GO–COOH/MWNT–COOH (15 mg/5 mg) and EDC/NHS (10 mM/20 mM) in 10 mL DDW and subjecting it to ultrasound for 2 h. In the presence of EDC and NHS, the −COOH group in GO–COOH and MWNT–COOH can easily react with the −NH2 group in GlutaOx to form amide bonds, so as to fix the enzyme. The modification process of the SPE and illustration of in vivo detection of glutamate in tomatoes are shown in Figure . After cleaning, the SPE was put into 5 mL of HAuCI4/H2PtCl6 solution for electrodeposition. The I–T method was used to deposit Au/Pt NPs on the SPE. The deposition voltage, time, and concentration of the HAuCI4/H2PtCl6 solution were optimized. After washing, GO–COOH/MWNT–COOH solution of 3 μL was modified on the SPE. After dropping GO–COOH/MWNT–COOH solution three times, the electrode was dried at room temperature. Then 4 μL of BSA/GlutaOx was modified on the SPE. Finally, 2 μL of 0.5 wt% Nafion solution was added to the SPE.

Figure 1

Schematic diagram of the preparation process of the glutamate sensor (A), and schematic illustration of in vivo detection of glutamate in tomato fruits (B).

Results and Discussion

Morphology and Structure Study of the Nafion/GlutaOx/GO–COOH–MWNT–COOH/Au–Pt/SPE

Figure shows the SEM characterization of electrodes. The bare SPE is shown in Figure a; no impurity was found on the surface of the SPE. After electrodeposition, the deposited Au/Pt NPs are densely arranged on the surface of the SPE in a regular spherical nanostructure (Figure b). The diameter of Au/Pt NPs is about 50–100 nm. The deposition of Au/Pt NPs will significantly increase the effective surface area and electrocatalytic performance of the SPE. When GO–COOH/MWNT–COOH was modified on the surface of the SPE (Figure c), tubular MWNT–COOH can be observed interspersing between layered GO–COOH. When GlutaOx was modified on the SPE surface (Figure d), the SPE surface became more compact and rougher. Finally, Nafion was dropped onto the SPE surface (Figure e), and membrane-like structures can be clearly seen. Figure f–k show the EDS mapping analysis results of Nafion/GlutaOx/GO–COOH–MWNT–COOH/Au–Pt/SPE, and the signals of C, Au, F, Pt, O, and N elements are obtained. The existence of the C element is attributed to the C element in GO–COOH, MWNT–COOH, and carbon materials of the working electrode of SPE. The deposition of Au–Pt NPs accounts for the appearance of Au and Pt elements. The existence of O elements is attributed to the GlutaOx, GO–COOH, and MWNT–COOH. The existence of N elements is mainly attributed to the GlutaOx. Nafion contains F elements, which leads to the appearance of F in the EDS results. Combined with the results of SEM and EDS mapping, various materials have been confirmed to be modified successfully on the electrode surface.

Figure 2

SEM images of bare SPE (a), Au–Pt/SPE (b), GO–COOH–MWNT–COOH/Au–Pt/SPE (c), GlutaOx/GO–COOH–MWNT–COOH/Au–Pt/SPE (d), and Nafion/GlutaOx/GO–COOH–MWNT–COOH/Au–Pt/SPE (e). (f)–(k) are the EDS mapping results for the Nafion/GlutaOx/GO–COOH–MWNT–COOH/Au–Pt/SPE.

Electrochemical Characterization of the Sensor Preparation Process

The modification process of the electrode was studied by cyclic voltammetry (CV) (Figure S1A). The CV test is carried out in a 5 mM [Fe(CN)6]3–/4–solution (containing 0.1 M KCL). Compared with the bare SPE (curve a), when Au/Pt NPs were deposited on the SPE (curve b), peak current increased significantly, indicating that the Au–Pt nanoparticles increased the conductivity of electrode. When the GO–COOH–MWNT–COOH solution (curve c) was dropped on the SPE, as the conductivity of GO–COOH–MWNT–COOH is weaker compared with that of Au/Pt NPs, peak current decreased. After the modification of GlutaOx (curve d), the redox current decreased further because GlutaOx is not conductive. After the modification of Nafion (curve e), the redox peak is almost invisible. AC impedance was measured in the 0.01 Hz–100.0 kHz range (Figure S1B) and was fitted by a simple circuit. Compared to the bare SPE (curve a, Rct = 1.11 kΩ), Rct decreased when the electrode was modified with Au/Pt NPs (curve b, Rct = 506 Ω), because of the good conductivity of Au/Pt NPs. Rct increased after the modification of GO–COOH–MWNT–COOH, because the conductivity of GO–COOH–MWNT–COOH was weaker compared with that of Au/Pt NPs (curve c, Rct = 733 Ω). After the modification of GlutaOx (curve d, Rct = 800 Ω) and Nafion (curve e, Rct = 10.5 KΩ), Rct increased further because of the insulated properties of these molecules. The CV and electrochemical impedance spectroscopy (EIS) results both confirmed the successful modification of the electrode.

Optimization of Sensor Preparation Conditions

Glutamate is nonelectroactive. The theoretical basis for development of the enzyme-based glutamate sensor is that the enzyme can oxidize glutamate, which produces a secondary electroactive product. In particular, the GlutaOx can catalyze glutamate into α-ketoglutarate, ammonia, and H2O2. H2O2 is then oxidized at the electrode surface. The equations of reactions are as follows:[32]

Considering the great influence of potential on the sensitivity, the influence of potential on the electrochemical sensor was estimated by the I–T method. As shown in Figure S2A, by continuously adding 200 μM glutamate to 0.01 M PBS solution (pH 4.5), the effects of different applied potentials (0.5–0.9 V) on the sensor were studied. The signal-to-noise ratio (S/N) is defined as the ratio of current response signal to background noise, which can reflect the sensitivity of the detection system. It can be seen that the signal-to-noise ratio initially increases, reaches the maximum at 0.8 V, and then decreases gradually (Figure S2B). Therefore, an applied potential of 0.8 V was selected in the following experiments.

The preparation conditions of the sensor were also optimized. The optimization effects were judged according to the response current of 0.5 mM glutamate. The deposition effect of Au/Pt NPs is affected by the deposition time, so the deposition time of Au/Pt NPs was optimized. The result is shown in Figure S2C. The response current increases as the deposition time increases from 400 to 1000 s. As the deposition time continues to increase, the response current will gradually decrease. Therefore, the deposition time of 1000 s was selected as the electrodeposition time of Au/Pt NPs for the sensor.

The concentration of HAuCl4/H2PtCl6 was optimized. The HAuCl4/H2PtCl6 concentration of 0.016 mM/0.032 mM was used for initial electrodeposition, and then their concentrations were expanded by 5, 10, 15, and 20 times for optimization. The results are shown in Figure S2D. When the expanded time was 5, that is, the concentration ratio of HAuCl4/H2PtCl6 is 0.081 mM/0.160 mM, the response current of glutamate is the largest, and the response current decreases with the further increase of the expanded times. Therefore, in this study, the HAuCl4/H2PtCl6 concentration of 0.081 mM/0.160 mM was used to deposit Au/Pt NPs on the electrode.

The ratio of GO–COOH/MWNT–COOH has an important effect on the catalysis of GlutaOx. In the experiment, different ratios (4:0, 3:1, 2:2, 1:3, 0:4) of GO–COOH/MWNT–COOH on the effect of response current were investigated. From Figure S2E, when GO–COOH: MWNT–COOH is 3:1, the response current is the largest, indicating that the GO–COOH/MWNT–COOH composite material has the best synergistic effect when 3:1 is used as the ratio of GO–COOH/MWNT–COOH.

The dropping volume of GO–COOH/MWNT–COOH was also optimized. The result is shown in Figure S2F. The response current increases with the increase of volume from 3 to 9 μL, and the response current reaches the maximum at 9 μL. Therefore, 9 μL of GO–COOH/MWNT–COOH was used for the experiment.

Analytical Performance of the Glutamate Sensor

As the pH of plant samples varies significantly, sensor performance toward glutamate may change according to different plant samples. Thus, the quantitative analysis of glutamate under different pH conditions was investigated. As shown in Figure , for pH 3.5, the sensor performance is the worst. The linear range of the sensor in this pH can be divided into two sections, that is, 400 μM–2 mM and 2–10 mM. The detection limit for pH 3.5 (LOD; S/N = 3) is 272.2 μM. For pH 4.5–7.5, the linear range of the sensor can be divided into four sections, including 2–20 μM, 20–200 μM, 200 μM–2 mM, and 2–14 mM (or 16 mM for pH 5.5). The LOD for pH 4.5, 5.5, 6.5, and 7.5 is 0.35, 0.18, 0.69, and 0.14 μM, respectively. These results indicate that the pH value of the electrolyte has a great influence on the response capacity of the sensor to glutamate, which may be caused by the deprotonation of the amide functional groups in glutamate.[33] Therefore, sensor sensitivity toward glutamate may differ as plant pH varies significantly. The detection capacity of the sensor to glutamate under pH 5.5 is the best in this range. The detailed information for the linearity and detection equations of the sensor under different pH conditions is shown in Figures S3–S7.

Figure 3

Representative amperometric curves of the Nafion/GlutaOx/GO–COOH–MWNT–COOH/Au–Pt/SPE sensor for detection of different concentrations of glutamate under different pH at an applied potential of 0.8 V. (a) pH = 3.5, (b) pH = 4.5, (c) pH = 5.5, (d) pH = 6.5, and (e) pH = 7.5.

Figure shows the current response of the sensor to glutamate at different pH values in the form of “contour”. The whole linear range is divided into four segments:2–20 μM (Figure A); 20–200 μM (Figure B); 200 μM–2 mM (Figure C); 2–16 mM (Figure D). The corresponding glutamate concentration can be obtained intuitively through the pH value and response current. Compared to other enzymatic glutamate sensors reported previously[22,34−41] (Table ), the detection range of the developed glutamate sensor is widest (2 μM to 16 mM) and its detection limit is relatively low (0.14 μM). The linear range of the sensor contains the whole range of glutamate in most plants and fruits. In addition, the upper detection limit of this sensor can reach 16 mM; therefore, this sensor is suited to quantitatively detect glutamate in vivo in various fruits and plants.

Figure 4

Step current of the Nafion/GlutaOx/GO–COOH–MWNT–COOH/Au–Pt/SPE sensor as functions of pH and glutamate concentration. (A) 2–20 μM, (B) 20–200 μM, (C) 200 μM–2 mM, and (D) 2–16 mM.

Table 1

Comparison of This Work with Various Glutamate Sensors

electrode matrix	linear range (mM)	LOD (μM)	enzyme	technique	references
[C3(OH)2mim][BF4]–Au/Pt	0.0005–0.02	0.17	GlutaOx	DPV	(22)
graphene/GCE	0.0001–1	0.03		DPV	(34)
Au/Crbxl-RGO/PtNPs	0.004–0.9	0.1	GLDH	DPV	(35)
Ni/Pb–core–shell	0.0001–0.5	0.052	GLDH	DPV	(36)
MB-SPCE	0.0125–0.15	1.5	GLDH	DPV	(37)
GlOx/DNA-Cu(II)/PAA/GC	0.001–0.1	1	GlutaOx	It	(38)
PtNPs/AuNAE	0.1–1.4	14	GlutaOx	DPV	(39)
Pt/ta-C/APTES/GlOx	0.01–0.5	10	GlutaOx	It	(40)
GlOx/silicalite/Pt	0.0025–0.45	1	GlutaOx	It	(41)
Nafion/GlutaOx/GO–COOH–MWNT–COOH/Au–Pt	0.002–16	0.14	GlutaOx	It	this work

To test the selectivity of the sensor, a variety of interferents were tested according to the approximate actual content of each amino acid in fruits (tomato was used as the model).[21,42] The results are shown in Figure . The current response of interfering substances is significantly lower than that of glutamate, indicating that the developed sensor has excellent selectivity to glutamate. One fabricated glutamate sensor was tested 10 times using the same glutamate concentration (Figure S8A), the RSD was 4.35%. Ten glutamate sensors were also applied to test glutamate solutions of the same concentration (Figure S8B), and the RSD was 2.1%. These results indicated that the sensor has good reproducibility. After the modified electrodes were stored at 4 °C for 2 weeks, there was about 88% sensing ability remained for glutamate, indicating that the modified electrodes were highly stable.

Figure 5

Selection performance test of the Nafion/GlutaOx/GO–COOH–MWNT–COOH/Au–Pt/SPE sensor.

Practical Detection of Glutamate in Tomatoes

To test the prospect of the sensor in detecting practical samples, a standard addition method was used. As shown in Table S1, the recovery of glutamate in the tomato samples was in the range of 99.4–108.7% (n = 5), which suggested that the sensor is accurate and reliable.

Considering the impedance difference of glutamate standard solution, tomato juice, and tomato fruit, EIS and the impedance time technique were used to test the impedance of glutamate standard solution, 100% tomato juice, and tomato fruit (Figure A/B). The results showed that the Rct of tomato juice (1207 Ω) was close to that of glutamate standard solution (1242 Ω), but the Rct value of tomato fruits reached 2550 Ω, which was about twice that of tomato juice. Using the heterogeneous charge-transfer resistance as a correction index, a similar current response of glutamate can be obtained in tomatoes (0.75 μA) and tomato juice (0.77 μA). Thus, the following equation is proposed to calibrate the glutamate in tomatoes

Figure 6

EIS diagram (A) and impedance time diagram (B) of the tomato fruit, tomato juice, and glutamate solution. (C) I–T curve of glutamate in red and green tomatoes in tomato plants.

In this equation, I and Ifruit are the response current for glutamate in glutamate solution and tomato fruit, and ZGlu solution and Zfruit are the Rct values of glutamate solution and tomato fruit. Then the real glutamate content in tomato fruits can be obtained after substituting the corrected I into the linear regression equation.

The constructed glutamate sensor was used to detect glutamate in different growth stages of tomatoes. The glutamate level was monitored in situ by inserting the sensor directly into the tomato. After inserting, the I–T current response quickly reaches a steady state (about 500 s). The I–T curves of glutamate in green and red fruits are shown in Figure C. The corresponding impedance results of red tomato and green tomato were shown in Figure S9. Using the equation mentioned above, the current responses of the green (pH = 4.0) and red tomato fruits (pH = 4.5) are 0.51 and 0.96 μA, which correspond to the glutamate concentration of 1298 and 1375 μM according to the step current model. This result is roughly the same as the glutamate content in tomatoes reported in previous research,[43] indicating that the glutamate content in tomato fruits increases significantly during tomato fruit ripening. These results may be related to the high protein turnover rate of the ripening stage. These results also indicated that the sensor can be used to in situ monitor the glutamate level in fruits.

Conclusions

In this work, a new amperometric glutamate sensor based on the Nafion/GlutaOx/GO–COOH–MWNT–COOH/Au–Pt/SPE was developed. Compared with the glutamate sensors reported previously, the detection range of our fabricated glutamate sensor is widest, which contains the whole concentration range of glutamate in varieties of fruits and plants. Its application for in vivo monitoring of glutamate content in tomatoes was also demonstrated. In addition, as the pH value of plant juice varies greatly, a number of working curves for the glutamate sensor were built at different pH values, which can be applied for determining glutamate in vivo in varieties of fruits and plants. The glutamate sensor has important applied value in precision agriculture. Our strategy also provides a way to establish the detection modes for other biomolecules.