Development of a Nonenzymatic Colorimetric Sensor for the Detection of Uric Acid Based on Ionic Liquid-Mediated Nickel Nanostructures.

Uric acid (UA) is a metabolic byproduct of purine nucleotides and is excreted as a urine component. Abnormalities in UA metabolism cause localized inflammation due to crystal deposition and can lead to various diseases. In the current study, we successfully fabricated a biosensor based on 1-H-3-methylimidazolium acetate (ionic liquid, IL)-capped nickel nanoparticles (NiNPs) for the detection of uric acid in test samples. The structures of IL-capped NiNPs and their precursors were characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, and X-ray diffraction. The IL-capped NiNPs possessed intrinsic peroxidase-like properties and displayed selective UA quenching after interacting with 3,3',5,5'-tetramethylbenzidine (TMB) solution. Different parameters such as pH, time, IL, TMB, and UA concentration were optimized to obtain the best results for the proposed sensor. The UA biosensor shows good responses in the linear range from 1 × 10-8 to 2.40 × 10-6 M, with a lower limit of detection of 1.30 × 10-7 M, a limit of quantification of 4.3 × 10-7 M, and an R 2 value of 0.9994. For the colorimetric detection of UA, the proposed sensor gave a short time response of 4 min at room temperature and pH 7.5. The proposed sensing probe detects UA in real serum samples and could be used as a selective sensor for UA in the real sample detection.

Introduction

In humans, uric acid (UA), one of the most important metabolic byproducts of purine nucleotides, is excreted in the urine.[1] Overproduction of UA, generated from purine metabolism via xanthine oxidase, has been proven to play triggered roles in human disease onset. A precise increase in the serum UA level is directly associated with the disease severity and progression. At normal physiological pH, UA acts as a weak acid (pKα 5.8) and exists as urate salt, which upon excess deposition leads to UA crystal formation as monosodium urate (MSU). The normal UA reference level in human blood is 2.5 to 7 mg/dL in men and 1.5 to 6 mg/dL in women.[1,2] The normal physiological amount of UA in body fluids is balanced between excretion and generation.[3] However, in diseased conditions such as Lesch–Nyhan syndrome, hyperuricemia, gout, and renal failure, UA has been proposed as a key diagnostic marker.[4−6]

Normally, UA concentration is measured in urine, blood plasma, and exhaled breath condensate. Determination of UA concentration has been performed by uricase analysis,[7] chemiluminescence (CL),[8] capillary electrophoresis (CE)[9,10] high-performance liquid chromatography (HPLC),[11] electrochemistry, dry chemistry systems, biosensor methods, and so forth.[12] Generally, for the detection of UA, chromatographic techniques such as CE and HPLC make great contributions but require expensive instruments and complicated sample preparation procedures. However, for the detection of UA in real samples with a lower limit of detection and high accuracy, chemiluminescence and electrochemistry-based analytical methods are still preferred.[13] Nevertheless, for the accurate determination of UA, a simple, fast, and effective method is still required. As a prerequisite of low cost, feasibility, and simplicity of no need for sophisticated techniques, nonenzymatic chemosensor-based colorimetric biosensor development has gained great attention.[14] Colorimetric detection of UA reported by Zhao et al.[7] has shown the development of intrinsic peroxidase-like catalytic activity of BSA-stabilized Au nanoclusters. Although the sensor shows high sensitivity, it possesses less specificity due to its strong affinity toward Au and Ag nanoparticles.[15,16] Pal et al. reported a nonenzymatic platform for the colorimetric detection of UA based on Ni@MnO2.[17] The results presented are encouraging, but in their work, Ni nanostructures alone did not show any sensing activity. Tripathi et al. reported that using Ni thin films deposited by glancing angle deposition (GLAD) shows colorimetric sensing of UA in a nonenzymatic manner.[18] However, in their work, they showed that Ni alone does not show any considerable sensing response toward UA sensing.

Recently, our group has successfully shown the application of an ionic liquid (IL) in enhancing the sensing properties of nanomaterial-based sensing platforms for the detection of various analytes.[19,20] Owing to the emerging applications and versatile properties of ILs, we hypothesized the functionalization of NiNPs with 1-H-3-methylimidazolium acetate.

In sensing applications, metal–organic frameworks (MOFs) have gained great attention. Due to their huge surface areas, stability, variable architectures, exposed metal sites, and high and controllable pore size, they represent a novel class of porous organic–inorganic hybrid materials.[21] Although MOFs based on colorimetric sensors have achieved some success, the development of MOFs as enzyme mimics for bioanalysis applications is still required. Although these MOFs show excellent lattice stability, a small pore structure with a high density of active catalytic centers, and an easy synthesis process.[22] These characteristics of MOFs avoid the interference of other molecules in biological samples and become suitable for catalytic applications. However, their colorimetric detection application is still far from fully developed and is in its infancy stage.[23]

In this study, nickel nanoparticles (NiNPs) were prepared by using benzyl di-ethylene tri-amine as the stabilizing and reducing agent. Characterization of the prepared NiNPs was carried out with standard spectroscopic techniques, including X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and scanning electron microscopy (SEM). After the synthesis and characterization, these NiNPs were tuned with an IL as a colorimetric biosensor for UA detection. To achieve the optimum performance of these IL-capped NiNPs, different effecting parameters, such as pH, temperature, incubation period, amount of Ni/IL, TMB, and UA concentrations were optimized. Finally, for the qualitative and quantitative detection of UA, we developed a simple and cost-effective biosensor method that can be observed by naked eyes and UV–vis spectroscopy, respectively. Furthermore, the proposed sensor was practically applied for the determination of UA in real human serum samples.

Materials and Methods

Chemicals and Reagents

All the chemicals and reagents used in this study were of analytical grade and were acquired from Sigma Aldrich. These include nickel nitrate hexahydrate (NiNO3.6H2O, 97%), uric acid (C5H4N4O3, 98%), 1-methylimidazole (C4H6N2), 3,3′,5,5′-tetramethylbenzidine (TMB) sodium chloride (NaCl, 99%), acetic acid (CH3COOH, 97%), and sodium acetate (CH3COONa, 99%). Methanol and ethanol (Sigma Aldrich) were used as solvents for washing purposes. All the solutions were prepared in double-distilled water, and high-quality Pyrex glass was used throughout the experiment.

Instrumentation

The distinctive peaks of the prepared NiNPs were identified using an FTIR MX-300 system (Agilent Technologies, Danbury, Conn, USA), and the desired functional group spectrum within the range of 500–4000 cm–1 with 256 scans per sample at 4 cm–1 resolution was recorded. A scanning electron microscope (JSM-5910, Japan) equipped with an energy-dispersive X-ray (EDX) system was used for the size, morphology, and elemental analyses of the prepared nanoparticles. The crystal structure of the prepared nanoparticles was studied by using an XRD-6100 system (Bruker Smart Apex CCD) equipped with monochromatic Cu-Kα radiation (λ = 0.15418 nm). A quartz cuvette double beam UV–vis spectrophotometer (Shimadzu, UV-1800, Germany) was used for absorption spectra acquisition.

Preparation of Nickel Nanoparticles

To synthesize the desired NiNPs, a modified protocol was used as reported recently by our group.[24] Briefly, 0.02 and 0.004 M solutions of nickel nitrate hexahydrate (NiNO3·6H2O) and benzyl di-ethylene tri-amine were prepared in 50 mL double-distilled (dd) water, respectively. The 0.004 M solution of benzyl di-ethylene tri-amine was added dropwise to the nickel nitrate solution and thoroughly stirred for about 60 min at room temperature until the color of the mixture was changed from pale blue to black. The synthesized NiNPs were pelleted out by centrifugation at 4000 rpm for 10 min at 37 °C and oven-dried for 4 h at 50 °C after washing with ethanol twice. Finally, the synthesized NiNPs were stored in 2 mL Eppendorf tubes at room temperature for further use. The synthesis scheme of NiNPs is summarized in Figure A.

Figure 1

Schematic diagram for the synthesis of the desired uric acid biosensor. (A) Synthesis of NiNPs. (B) Synthesis of ILs. (C) Capping of NiNPs with the ionic liquid.

Synthesis of ILs

The synthesis of IL was carried out as per our published protocol.[25] Briefly, 0.01 M acetic acid and 0.01 M 1-methylimidazole were mixed with an equal ratio in two-neck flasks with constant stirring for 6 h under cooling. A concentrated yellow color solution of IL was obtained by a rotary evaporator and was stored at room temperature for further use (Figure B.

Capping of NiNPs with ILs

A china dish was used to soak roughly 6 mg of the produced NiNPs in 1 mL of IL (1-H-3-methylimidazolium acetate) for capping. Maceration of the IL-capped NiNPs was done for roughly 25 min with the use of a mortar and pestle to produce the desired dispersion, as shown in Figure C. Furthermore, the capping of the nanoparticles and IL was confirmed using FTIR analysis, as shown in Figure B , Section .

Figure 2

(A) FTIR spectrum of the prepared Ni nanoparticles. (B) Ionic liquid-capped Ni nanoparticles.

Colorimetric Nonenzymatic Detection of Uric Acid

Double-distilled water was used for the preparation of all solutions used. Briefly, 40 μL of capped NiNPs was mixed with TMB (0.08 M, 150 μL), H2O2 solution (0.04 M, 90 μL), PBS (0.06 M, 550 μL), and UA (2.4 × 10–6 M, 100 μL) and was incubated at ambient temperature for 4 min. A greenish color appeared before UA addition, which turned transparent after UA addition. The subsequent colorimetric change was observed by naked eyes, further confirmed by UV–vis spectrum (500–800 nm) analysis using a spectrophotometer.

Results and Discussion

FTIR Study of the Prepared Nickel Nanoparticles

The FTIR spectrum-based functional group analysis of the prepared NiNPs is shown in Figure A. The key participating molecules involved in the synthesis of NiNPs were investigated. The respective spectrum absorption bands are displayed at 3444, 1640, 1466, 1370, and 1048 cm–1, as shown in Figure A. The presence of the amine group is indicated by the N–H peaks at 3444 and 1640 cm–1, which were acquired from benzyl di-ethylene tri-amine used in the reduction of NiNPs. The 1466 cm–1 peak was assigned to the sp2 vibration of the C=H (alkene) bond. The existence of N–H peaks suggested that the amine group is bound to the surface of NiNPs. The C–H bending was observed at 1370 cm–1.[26] The IL-capped NiNP FTIR spectra have been shown in Figure B. Along with new peaks, peak shifting was observed at 1466 and 1370 to 1260 and 1230 cm–1 of amine-coated NiNPs, which confirms the capping of the ionic liquid 1-H-3-methylimidazolium acetate with the Ni nanoparticles.

XRD Profile of the Synthesized Ni Nanoparticles

The XRD spectrum profile of the prepared NiNPs shows sharp peaks at 20–80° that indicate its crystalline nature, as shown in Figure . No impurity peaks were found in the diffraction pattern, suggesting the ultrapure phase of their synthesis. The presence of five sharp and prominent diffraction peaks at 2θ values of 37.5°, 43.25°, 62.75°, 75.25°, and 80° corresponds to the crystal planes of (111), (200), (220), (222), and (311), respectively, corresponding to JCPDS Card No. 73-1523. The synthesized NiNP planes are face-centered cubic, with a lattice constant of 4.17 Å, agreeing well with the standard card data. Using the standard Debye-Scherrer equation, the average crystal size was calculated to be 35 nm, as determined from the corresponding X-ray spectral peak.[27,28]

Figure 3

XRD patterns of the synthesized NiNPs.

SEM Analysis of the Prepared Ni Nanoparticles

To investigate the size and structure morphology of the prepared NiNPs, SEM was used, as shown in Figure . The acquired SEM image shows irregular NiNP agglomerates with void spaces. The microstructures are not very clear, which have been confirmed by the Scherrer equation, as given in Section 3.2. This agglomeration of NiNPs is due to the increase in surface area-to-volume ratio that leads to an increase in attractive forces among the particles to form spherical shapes.[29]

Figure 4

SEM images of the prepared NiNPs.

IL-Capped NiNP-Based Colorimetric Detection of Uric Acid

The prepared NiNPs tuned with IL were used for the colorimetric detection of uric acid, as shown in Figure . The desired detection analysis was done by adding uric acid (2.4 μM,100 μL) after 4 min of incubation to the colorimetric mixture having NiNPs (40 μL), TMB (8 mM, 150 μL), H2O2 (4 mM,90 μL), and PBS (6 mM,550 μL) solutions. The colorimetric change (greenish to transparent) was observed by naked eyes, further confirmed by absorption spectrum analysis (Figure ). The same colorimetric mixture composition without UA was used as a normal control with a good absorption peak in the 550–700 nm range (Figure A). No absorption peak was seen in the test sample having UA (Figure B).

Figure 5

IL-capped NiNP-based colorimetric detection of uric acid. The absorption spectra were recorded for the colorimetric mixture having TMB (8 mM, 150 μL), H2O2 (4 mM, 90 μL), and PBS (6 mM, 550 μL) solutions with (2.4 μM, 100 μL) (B) or without UA. (A) control.

Proposed Mechanism for IL-Capped NiNP-Based Uric Acid Detection

The prepared IL-capped NiNPs act as a biocatalyst by producing hydroxide radicals from H2O2 reduction that oxidize the TMB solution. In the presence of uric acid, the oxidized TMB (blue-green) solution reverts to a colorless reduced TMB product. Meanwhile, UA is converted into intermediate Allontoin molecules that revert to UA in the presence of water molecules, as shown in Scheme .

Scheme 1

Proposed Reaction Mechanism for IL-Capped NiNP-Based Uric Acid Detection

Optimization of the Proposed Sensor

To investigate the potential biosensing role of the proposed IL-capped NiNPs, different key parameters were optimized before being tested in real blood samples. These are given below.

Optimization of IL-Capped NiNPs

As a key component of the proposed biosensor, different concentrations of the ionic liquid-tuned NiNPs (10–70 μL) were tested in a reaction mixture having the same composition as we mentioned in Section 3.2. Briefly, 40 μL of IL-capped NiNPs was enough to produce an optimum response. The reaction progress (blue-greenish to transparent) can be noticed easily via naked eyes. Further confirmations were done by absorption spectrum analysis by using a spectrophotometer, as shown in Figure A.

Figure 6

IL-capped NiNP biosensor optimization. The key effecting parameters were optimized to produce optimum results in the IL-capped NiNP biosensor reaction mixture for UA detection. (A) Concentration–response curves for IL-capped NiNP biosensor amounts (10–70 μL). (B) Effect of the TMB solution concentration–response curve (2–14 mM:150 μL) under optimized conditions. (C) Influence of H2O2 solution concentrations (1–7 mM) on IL-capped NiNP biosensor, under optimized conditions. (D) Effect of time variations (1–7 min) on IL-capped NiNP biosensor, under optimized reaction mixture conditions. (E) Impact of pH variations (1–13) on IL-capped NiNP biosensor, under optimized reaction mixture conditions.

Effect of TMB Concentration

As the main colorimetric reporter component of the proposed biosensor, different TMB concentrations (2–14 mM, 150 μL) were tested in a reaction mixture having the same composition as we mentioned in Section 3.2. Briefly, (8 mM, 150 μL) TMB solution was enough to produce an optimum color response in the absence of UA. In the presence of UA, the reaction progress (blue-greenish to transparent) can be noticed easily via naked eyes. Further confirmation was done by absorption spectrum analysis by using a spectrophotometer, as shown in Figure B. Irrespective of its previously reported 0.8 mM concentration,[30] in our current finding, the TMB solution shows the optimal result at 8 mM concentration only. The main possible reason for these 1000× detection limit differences may be the nature, composition, and oxidizing power of the different nanostructures.

Optimization of H2O2

H2O2 is the gold standard oxidizing reagent for the reporter TMB solution. Therefore, optimal H2O2 concentration (4 mM, 90 μL) was determined by using different H2O2 (1–7 mM) concentrations. The proposed biosensors (IL-capped NiNPs) showed a maximum response at this optimal (4 mM:90 μL) H2O2 concentration in the reaction mixture, as shown in Figure E. Meanwhile, the reported H2O2 concentration (8 mM:500 μL) was not suitable for our current (IL-capped NiNPs) biosensors.[31] The possible reasons may be its purity, sensitivity, reaction mixture composition, their peroxidase-like activities, and so forth.

pH Effect on the Proposed Biosensor

In the physiological system, pH is one of the most influential factors responsible for the onset of prohibition of a chemical reaction. The desired biosensor (IL-capped NiNPs) was calibrated at different pH modules (1–13) using hydrochloric acid (HCL) and sodium hydroxide (NaOH) solutions. The optimal result for the IL-capped NiNP biosensor was found at pH 7.5, as shown in Figure C. However, in a normal enzymatic scenario, the reaction occurs at pH 4.[3]

Effect of Time on the Proposed Biosensor

Time is one of the most influential factors in numerous biochemical reactions. Therefore, the desired biosensor (IL-capped NiNPs) was optimized at different time intervals (0–8 min). The optimal result was achieved after 4 min, irrespective of the previously reported 15 min intervals.[30] The desired time-based response (colorimetric change) was noticed by visual observation and confirmed by UV–vis spectrum analysis, as shown in Figure D.

Steady-State Kinetic Analysis

The Michaelis–Menten equation was used to calculate the Michaelis constant (Km) and maximum velocity (Vmax) for the proposed sensing platform (IL-capped NiNPs). As can be seen in Table the proposed platform demonstrates a very low Km value of 0.017 for TMB and 0.01 for H2O2. The lower value is desirable as it indicates that the IL-capped NiNPs have a greater affinity for the substrates. Moreover, when compared with the literature, the Vmax value of IL-capped NiNPs is higher, as can be seen in Table . In comparsion to the values obtained for other catalysts, it is clear that IL-capped NiNPs demonstrate good catalytic behavior for the oxidation of TMB in the presence of H2O2.

Table 1

Comparsion of Kinetic Parameters of IL-Capped NiNPs and HRP

catalysts	substrate	Vmax (10–8 M·s–1)	Km (mM)	ref
HRP	TMB	17.19	0.424	(32)
HRP	H2O2	10.55	3.240
IL-capped NiNPs	TMB	32	0.017	this work
IL-capped NiNPs	H2O2	45	0.01

Analytical Characteristics of the Proposed IL-Capped NiNP Biosensor

For the colorimetric detection of UA concentration, the key biosensing features of the proposed IL-capped NiNP biosensor were studied using standard calibration curves, as shown in Figure . Under optimized conditions, the proposed colorimetric sensing probe was tested in the uric acid concentration range of 1 × 10–8–2.4 × 10–6 M. It exhibited peroxidase-like activity in a wide linear range. The uric acid concentration in the reaction mixture was inversely proportional to the absorption peak that can be noticed from the reduction of the UV–vis spectral peak at 652, as shown in Figure . The proposed biosensor shows a good linear response in the range of 1 × 10–8–2.4 × 10–6 M, with an LOQ of 4.3 × 10–7 M, an LOD of 1.30 × 10–7 M, and an R2 value of 0.9994. These values were calculated by using the formulas (10σ/slope) for LOQ and (3σ/slope) for LOD. The slope value was derived from the linear curve, while σ shows the blank sample standard deviation. The proposed IL-capped NiNP biosensor shows a good limit of detection (LOD) of 1.3 μM and an R2 value of 0.995 compared to that of the literature-reported UA sensor.[3] Similarly, the analytical efficiency of the proposed IL-capped NiNP biosensor was good, as shown in Table compared with that of the already reported biosensors.[7,33−39]

Figure 7

IL-capped NiNP-based UA biosensing. Different UA concentrations (1 × 10–8–2.4 × 10–6 M) were mixed with an optimized reaction mixture. (A) Upper top right shows colorimetric change with respect to different concentrations of UA and the bottom graph represents the respective UV–vis spectra. (B) Calibration plot of UA concentration versus absorbance.

Table 2

Comparative Analysis of the Proposed IL-Capped NiNP Biosensor for Uric Acid Detection

s. no	materials used	linear range (μΜ)	limit of detection (μM)	ref
1	luminol–K3[Fe(CN)6]	4.8–179	3	(33)
2	uricase/AuNP/MWCNT Au electrode	10–800	10	(34)
3	TMB–Cu2+–uricase	1–100	640	(35)
4	CdTe nanoparticles	0.22–6	100	(36)
5	uricase/BSA-stabilized Au nanoclusters	2.0–200	0.36	(7)
6	uricase/HRP–CdS quantum dots	125–1000	125	(37)
7	nanocrystalline cobalt selenide TMB	2.0–40	500	(39)
8	Ni GLAD film	15–500	3.3	(18)
9	Ni@MnO2	1–40	0.24	(17)
8	IL-capped NiNPs	0.01–2.40	0.13	this work

IL-Capped NiNP Biosensor Interference Profile Studies

To investigate the potential UA detection selectivity with the peculiar sensitivity of IL-capped NiNP biosensor, interference profile studies were done. The absorbance response of the proposed biosensor was measured in the presence of other coexisting species, including ethanol, methanol, dopamine, urea, Ca+2, K+, ascorbic acid, glutathione, and UA, as shown in Figure . Except for UA, none of the coexisting species were found to reduce the oxidized TMB solution (greenish to transparent) in the presence of IL-capped NiNP biosensor. Thus, the obtained results demonstrate high selectivity and good sensitivity of IL-capped NiNP biosensors for UA detection. The results indicate that the coexistence of these interfering substances does not affect the detection of UA. Thus, the proposed biosensor shows great potential to be tested for UA detection in real serum samples.

Figure 8

IL-capped NiNP biosensor interference profiling. The interference to the IL-capped NiNP biosensor by the coexisting species at 2.40 × 10–6 M concentrations including (A) ethanol, (B) K+, (C) urea, (D) dopamine, (E) methanol, (F) Ca2+, (G) ascorbic acid, (H) glutathione, and(I) uric acid.

Clinical Applications of IL-Capped NiNP Biosensors

The proposed IL-capped NiNP biosensor was tested in real serum samples using the same experimental conditions, except for uric acid addition. Instead of direct UA addition, human serum samples (100 μL) were added to the reaction mixtures. Different UA concentrations of 0.295, 0.692, and 1.37 μM were spiked into the real serum samples by using the standard UA calibration method, as shown in Figure . Thus, by using different UA concentrations under the same optimized conditions, the unknown serum UA concentration was calculated based on a previously established calibration plot. The % recovery algorithm was used to calculate the findings, as displayed in Table . Finally, the proposed IL-capped NiNPs biosensor was tested for multiple serum samples’ UA detection. The proposed biosensor was able to detect UA in serum samples with the highest sensitivity and selectivity.

Figure 9

Real serum sample UA profile. IL-capped NiNP biosensor-based UV–vis spectra of the real blood serum samples at optimized reaction mixture conditions having different UA concentrations. However, the concentration of A is (3 × 10–7 M), B is (7 × 10–7 M), and C is (1.4 × 10–6 M).

Table 3

IL-Capped NiNP Biosensor-Based Detection of Uric Acid in Human Serum Samples

samples	detected (μM)	uric acid added (μM)	uric acid found (μM)	recovery (%)	RSD (%)
1	0.005	0.295	0.3	101.69	0.838
2	0.008	0.692	0.7	101.15	1.009
3	0.03	1.37	1.4	102.18	0.459

Conclusions

In the present study, we synthesized IL-capped NiNPs as efficient uric acid biosensors under normal physiological conditions. The proposed biosensor was confirmed by using standard spectroscopic techniques. Different parameters such as pH, time, TMB, and H2O2 solution were optimized. Under optimized conditions, the sensing probe for uric acid detection was tested successfully in a wide linear range, which gave a low limit of detection and low limit of quantification. This newly explored IL-tuned NiNP biosensor shows numerous advantages, including low cost, facile preparation, good stability, and high catalytic efficiency with peculiar selectivity in a minimal timeframe detection. The desired biosensor was able to detect UA with the highest sensitivity and selectivity, irrespective of the presence of coexisting molecules’ hindrances. Even more, with the same sensitivity and selectivity, UA was determined in real serum samples, suggesting their potential diagnostic role shortly. Therefore, we predict that soon the proposed IL-capped NiNP biosensor would be used for the selective detection of uric acid in multiple diverse sample analyses.