Non-enzymatic detection of uric acid in saliva samples using a laser-scribed graphene electrode modified with gold nanoparticles

Autores

Custodio, M.F. (UNICAMP) ; de Araujo, W.R. (UNICAMP)

Resumo

In this study, we developed an electroanalytical device using the laser-scribed graphene (LSG) method onto polyetherimide substrate for the detection of uric acid (UA) in saliva samples. The electrode underwent an anodic pretreatment (AT) and was later modified with gold nanoparticles (AuNPs). The AuNPs/AT/LSG sensor exhibited high sensitivity and selectivity performance for UA detection in phosphate buffer solution (pH = 7.0). The limit of detection was 1.34 μM. We demonstrate that UA can be detected without significant interference from some biomarkers that are normally present in saliva. The sensor was successfully applied in the analysis of UA in artificial saliva samples and the results indicated that the developed device is promising for the non-invasive monitoring of salivary UA.

Palavras chaves

Electrochemical sensor; Uric acid; Diagnostics

Introdução

Saliva is an excellent diagnostic fluid that provides an alternative to direct blood analysis through the permeation of blood constituents without any skin perforation for collection (KIM et al., 2015). The composition of saliva can reflect an individual's hormonal, emotional, metabolic, nutritional, and immunological status (GLEERUP et al., 2021). Saliva testing is currently used in the fields of toxicology, endocrinology, infectious diseases, and forensics. As saliva collection is non-invasive and relatively stress-free, saliva may serve as a potential alternative and universal diagnostic fluid (CARRO et al., 2017). Uric Acid (UA) is one of the main biomolecules present in physiological liquids and plays a crucial role in human metabolic processes (ELANGOVAN et al., 2020, SAMOSON et al., 2022). It is the final product of purine metabolism (GHOREISHI; BEHPOUR; SAEIDINEJAD, 2012). Monitoring the uric acid levels in the body fluids is of great importance, as abnormal levels of UA in human biofluids serve as an essential marker (XU et al., 2015, SAMOSON et al., 2022) of various diseases such as gout, hyperuricemia, kidney disease, Lesch-Nyhan syndrome, hypertension, and high cholesterol (GHOREISHI; BEHPOUR; SAEIDINEJAD, 2012, ELANGOVAN et al., 2020). The most used methods to determine UA include fluorescence spectroscopy, capillary electrophoresis, high-performance liquid chromatography, and bio- enzymatic colorimetry. While most of these methods are accurate and sensitive, operating costs can be high and the techniques used are unsuitable for analysis at the point of need (SAMOSON et al., 2022). Therefore, developing sensitive, simple, and fast analytical methods for detecting UA in routine analysis is essential (GHOREISHI; BEHPOUR; SAEIDINEJAD, 2012; GUAN et al., 2021). A promising alternative approach to UA detection is the use of electrochemical sensors, which is generally simple, inexpensive, fast, highly sensitive, and suitable for on-site monitoring. UA can be detected through non-enzymatic and enzymatic analyses (XU et al., 2015). Recently developed non-enzymatic UA sensors have employed various transition metal nanoparticles (MNPs) as catalytic materials, where UA can be detected through its oxidation at an electrode modified with a more stable catalytic material (SAMOSON et al., 2022). In the last decades, electrodes modified with carbonaceous material have been extensively researched in the field of electroanalytical chemistry. Among them, graphene (XU et al., 2018) has gained enormous attraction by the scientific community due to its unique properties such as rapid electronic mobility, self- assembly behavior, excellent conductivity, mechanical stability and flexibility (LAHCEN et al., 2020). In addition, graphene-based materials provide improved electrochemical performance in biochemical sensing (XU et al., 2018). Laser scribing of different substrates has emerged (RAUF et al., 2021) as a new method for 3D graphene production and has advantages over the chemical vapor deposition (CVD) process (LAHCEN et al., 2020). This new technique has only one step and its product is called laser scribed graphene (LSG). It is a method that allows the modification of a substrate into a porous 3D graphene structure, exhibiting high electrical conductivity (CARDOSO et al., 2019). The nature of chemical repeating units present in the substrate plays a key role in the fabrication of LSG electrodes (LAHCEN et al., 2020). For example, a brief literature review showed that polyimide (PI) and PEI substrates are successfully converted to graphene, while polymers with non-aromatic groups undergo almost complete degradation without any graphene formation (LAHCEN et al., 2020). Chemical modification of the electrode surface is a strategy to improve the performance of conventional electrodes for various applications, especially sensors (GHOREISHI; BEHPOUR; SAEIDINEJAD, 2012). Gold nanoparticles (AuNPs) have shown excellent performance in sensing, electronics, catalyst, and biomedical applications (ELANGOVAN et al., 2020) due to their special optical and electronic properties (GUAN et al., 2021). Due to their small dimensional size, good conductivity, and excellent catalytic activity, AuNPs have potential applications in the preparation of electrochemical sensors and biosensors where they work by efficiently channeling electrons between the electrode surface and the electrolyte (GHOREISHI; BEHPOUR; SAEIDINEJAD, 2012). In addition, AuNPs when integrated with carbon-based nanomaterials increase the electrocatalytic performance and sensitivity of the sensors (SAMOSON et al., 2022). In this work, we present the development of a portable electrochemical sensor using the LSG method on PEI polymer. The working electrode was modified with AuNPs by drop-casting technique for sensitive and non-enzymatic detection of uric acid present in saliva samples.

Material e métodos

All reagents used were of analytical grade. AuNPs suspension was synthesized by the hydrothermal method according to Melo Jr. and collaborators (MELO JR. et al., 2012). Synthetic saliva was prepared from a mixture of 13.2 mg of NaCl, 96.4 mg of KCl, 17.2 mg of CaCl2, 65.0 mg of KH2PO4, 20.4 mg of urea, and 17.4 mg of lactic acid in 100 ml of deionized water. The LSG electrochemical sensors were fabricated onto PEI substrate using a CO2 laser printer equipped with a 50W laser tube (Multivisi – Visutec Router VS4040C, Brazil). For the fabrication of the electrode design, the Corel Draw® was used, the laser power was optimized as 11%, and the scan rate was 40 mm s-1. Then, Ag/AgCl conductive ink from Creative Materials® was painted to create the pseudoreference electrode. The ink was cured at 100 ºC for 30 min in a drying oven FANEM® SP-Brasil model 315 SE. Finally, Norbond® Saint Gobain insulating tape was applied to delimit the electrode area and the electrochemical cell. Electrochemical measurements were performed using a PalmSens3 potentiostat/galvanostat (Randhoeve, Houten, Netherlands) with a laptop running the PSTrace 5.9 software. First, to evaluate the sensor response, measurements were performed with and without electrochemical pretreatments. The anodic treatment (AT) consists of applying the potential of +1.8 V for 200 s in 0.1 mol L-1 NaOH, and the cathodic treatment (CT) consisted in applying the potential of -1.5 V for 200 s in 0.1 mol L-1 H2SO4. The voltammetric characterization of the electrodes and UA was performed by cyclic voltammetry (CV) technique using 100 µL of 0.1 mol L-1 phosphate buffer solution (PBS), pH 7.4, in the potential range of -0.2 to 1.0 V at 50 mV s-1. For the mass transport study, CV measurements were performed in the scan rate values ranging from 10 to 200 mV s- 1 using 0.1 mol L-1 PBS pH 7.4 as supporting electrolyte and 0.5 mmol L-1 UA solution. To study the effect of pH on the voltammetric response of UA, analyses were performed with pH values in the range of 5 to 9. The analytical curve was built using differential pulse voltammetry (DPV) in the potential range of -0.4 to +0.5 V at a scan rate of 0.03 V s-1, with the step of 5 mV and amplitude of 50 mV. Measurements were performed in triplicate using different sensors. To evaluate the accuracy of the proposed method, an addition and recovery study was carried out in which concentrations of 200 and 400 µmol L-1 were spiked into prepared saliva samples to mimic the usual levels for healthy and hyperuricemic individuals, respectively. For analysis of spiked samples, a 20-fold dilution of synthetic saliva in PBS pH=7.0 was performed. Solutions of lactic acid, glucose, creatinine, and ascorbic acid were prepared and analyzed to evaluate the selectivity of the method. These tests were carried out under optimized conditions using a 1:1 proportion between uric acid:interfering species at 100 μmol L-1.

Resultado e discussão

Cyclic voltammograms were recorded in the potential range of -0.2 to 1.0 V at 50 mV s-1 in PBS medium to evaluate the response of UA in our LSG sensor with and without electrochemical treatments, Figure 1A. It is possible to verify that the LSG electrode presented a low and stable background signal (blank solution), which is very attractive for use as an electrochemical sensor. When UA was added, it showed a poorly defined irreversible oxidation process under the conditions used. Subsequently, some electrochemical treatments were evaluated, aiming to introduce functional groups on the LSG surface that can act as catalytic centers for electronic transfer. Figure 1A exhibited the comparison of the electrochemical performance of the LSG sensor before and after AT and CT treatments. It is noteworthy that both surface treatments of the electrode caused a significant increase in current signals with superior kinetics and a catalytic effect. Given the best analytical response was obtained for the AT condition in NaOH 0.1 mol L-1, this condition was chosen to further studies. After choosing the treatment, the drop-casting modification of the sensor with AuNPs was studied by varying the volume applied to the electrode surface from 1 to 5 µL, Figure 1B. The AuNPs were used aiming to improve the analytical performance of electrodes, both by increasing surface area and the possibility of associating catalytic effects with its use. After adding the AuNPs, it was allowed to dry for 30 min. The blank and analyte were measured by CV for each modified electrode in the potential range of -0.4 to 0.5 V. It was observed that with the increase in the amount of AuNPs used in the surface modification of the working electrode, there was an increase in the peak current of the UA. The best analytical condition was the use of 5 µL of AuNPs since it provided the highest and a well-defined peak current, Figure 1B. Subsequently, a pH study was carried out in the pH range of 5 to 9, Figure 1C. The resulting plot of the peak potential of UA oxidation versus pH is shown in Figure 1D. The highest oxidation current intensity was obtained in a more acidic medium and there is a tendency to decrease with increasing pH. The peak potential values decreased linearly with increasing pH at a rate of 83 mV/pH, suggesting that the oxidation process occurs with the same proportion of electrons and protons. Considering that the objective is to work in conditions closest to the reality of the salivary environment, we can define pH = 7.0 as the best way to proceed since it is the pH corresponding to the most common salivary pH range (6.8 - 7.2), according to the existing consensus in the literature on oral pH (TOLENTINO, 2009). In addition, pH = 7.0 provided anticipation in the detection potential compared to acidic medium (close to 0V), which minimize selectivity issues. To investigate the mass transport phenomena involved in the redox processes of uric acid, the scan rate study was performed, Figure 1E. In this study, the uric acid anodic process has a slope of 0.824, Figure 1F, indicating an adsorptive characteristic of the electrochemical process. Figure 1: (A) CVs obtained for 0.5 mmol L-1 UA without treatment (black line), with anodic treatment (red line), and with cathodic treatment (blue line) of the LSG sensor at 50 mV s-1. Inserted in A is the expanded CV recorded for PBS pH 7.4 (dashed line) and 0.5 mmol L-1 UA (black line) using LSG without any previous treatment. (B) CVs recorded for the optimization study of AuNPs used to modify the treated sensor. 0.5 mmol L-1 UA was used without AuNPs (black line), with 1 µL of AuNPs (green line), 3 µL of AuNPs (blue line), and 5 µL of AuNPs (red line). (C) Study of the effect of pH on the 0.5 mmol L-1 UA response in the sensor with optimized conditions in the pH range of 5.0 (black line) to 9.0 (magenta line). (D) Graph of peak potential versus pH for UA response. (E) CVs were recorded using the LSG sensor with optimized conditions containing 0.5 mmol L−1 UA in PBS medium, pH = 7.0, at different scan rates (10, 20, 30, 40, 100, and 200 mV s-1). (F) The plot of the logarithm of peak current versus the logarithm of scan rate (v). After the optimization of the AuNPs/AT/LSG sensor (laser-scribed graphene/anodically treated/modified with gold nanoparticles), a DPV technique was used and the main instrumental parameters were optimized to improve the sensitivity of the method. A 0.1 mmol L-1 UA response was evaluated by changing the step and amplitude potential from 3 to 12 mV and from 30 to 120 mV, respectively. The best conditions were obtained when using a step of 5 mV and an amplitude of 50 mV. The analytical curve was obtained in the concentration ranging from 2 to 200 μmol L−1 UA using optimized parameters. Figures 2A and 2B show the DPV plots and respective analytical curve using the peak current from the DPV data. We identified two linear regions, the first from 2 to 60 μmol L−1 UA and the second from 60 to 200 μmol L−1 UA. For the first linear region, we have a sensitivity of 0.094 μA/μmol L−1 and an R2 of 0.998. For the second linear region, the sensitivity is 0.046 μA/μmol L−1, and the R2 of 0.971. The limit of detection (LOD) and the limit of quantification (LOQ) were calculated as 1.34 μmol L−1 and 4.46 μmol L−1, respectively. Figure 2: (A) DPV recorded with AuNPs/AT/LSG electrode in PBS medium, pH 7.0, in the concentration ranging from 2 to 200 μmol L−1 UA. (B) Analytical curve constructed using the average of the peak currents including the error bars (n = 3). Parameters: potential from -0.4 to +0.5 V; scan rate of 0.03 V s-1; step of 5 mV and amplitude of 50 mV. Considering that the salivary environment is composed of a multitude of biomarkers, the potential interference of the major compounds found in biofluids were evaluated, i.e., ascorbic acid (AA), lactic acid (Lac), glucose (Glu), and creatinine (Cre). When evaluating the UA response in the presence of these interfering species, it was found that Glu caused a 9.3% peak current variation, and all other species provided relative current variations lower than 3.7%, highlighting the adequate selectivity of the non-enzymatic LSG sensor. To assess the applicability of the proposed sensor (AuNPs/AT/LSG) in practical analysis, the electrochemical response was studied in artificial saliva that has an electrolyte concentration similar to human saliva. Saliva was prepared according to the method used by Bao et al. (BAO; KAUR; KIM, 2019) and its pH was adjusted to 6.9. Before electrochemical detection of UA, saliva samples containing 200 and 400 µmol L-1 UA were prepared and then diluted 20x in PBS solution, pH 7.0. The dilution process was necessary to work within the linear range of our method, considering that healthy patients have UA concentrations around 200 µmol L-1 and clinical patients who suffer from gout, for example, have much higher levels of UA concentrations (~400 µmol L-1). In this way, a standard addition method was performed for salivary UA quantification in these samples, simulating the application of the proposed sensor for real cases. Table 1 shows the results obtained, with recoveries ranging from 94 to 120%, which confirms the accuracy of the AuNPs/AT/LSG sensor for the determination of salivary UA. Table 1: Detection of uric acid in artificial saliva samples using the AuNPs/AT/LSG sensor. The concentration of added uric acid (μmol L-1) Uric acid detected (μmol L-1) Recovery (%) 200.0 240.0 120.0% 200.0 188.2 94.1% 400.0 436.0 109.0% 400.0 390.0 97.5% This work presented a non-enzymatic sensor for salivary uric acid detection with a low LOD and wide working concentration range. The proposed LSG/AT/AuNPs electrode presents analytical performance comparable or superior to those obtained with several other sensors, including enzymatic ones.

Conclusões

This work described a portable, accessible, and non-enzymatic electrochemical sensor for UA detection using a CO2 laser-scribing procedure on PEI substrate. The LSG electrodes were anodically treated in 0.1 mol L-1 NaOH and modified with AuNP suspension to improve the analytical and catalytical performance of the electrodes. The AuNPs/AT/LSG electrode features high sensitivity of 0.094 μA/μmol L−1, a working concentration range of 2 μM – 200 μM, and a low LOD of 1.34 μM. The selectivity of the method was studied by evaluating the major salivary biomarkers such as glucose, lactate, creatinine, and ascorbic acid. They did not show significant changes (< 9.3%) in the UA response, confirming adequate selectivity of our method. The recovery studies performed in artificial saliva samples spiked with UA similar to healthy and hyperuricemic conditions resulted in recoveries in the range of 94 to 120%, demonstrating the accuracy and robustness of the AuNPs/AT/LSG sensor toward noninvasive monitoring of UA in saliva samples.

Agradecimentos

The authors acknowledge the IQ-UNICAMP and the Brazilian agencies CAPES, CNPq, and FAPESP. A special thanks to FAEPEX/PRP/UNICAMP for the master's scholarship (Process: 2387/21).

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