Gold-binding peptide as a selective layer for electrochemical detection of SARS-CoV-2 antibodies

Abstract

Electrochemical immunosensors are excellent alternatives to prepare portable platforms used for rapid and inexpensive diagnostic of infectious diseases such as the recently emerged COVID-19. Incorporating synthetic peptides as selective recognition layers combined with nanomaterials such as gold nanoparticles (AuNPs) can significantly enhance the analytical performance of immunosensors. In the present study, an electrochemical immunosensor based on solid-binding peptide was built and evaluated towards SARS-CoV-2 Anti-S antibodies detection. The peptide used as recognition site has two important portions: one based on the viral receptor binding domain (RBD), capable of recognizing antibodies of the spike protein (Anti-S), and another suitable for interacting with gold nanoparticles. Gold-binding peptide (Pept/AuNP) dispersion was used directly to modify a screen-printed carbon electrode (SPE). The voltammetric behavior of the [Fe(CN)₆]^3-/4- probe after every construction and detection step was recorded using cyclic voltammetry by assessing the stability of the Pept/AuNP as a recognition layer onto the electrode surface. Differential pulse voltammetry was used as a detection technique, and a linear working range from 75 ng mL⁻¹ to 15 μg mL⁻¹ was established, with 1.059 μA dec⁻¹ of sensitivity and R² = 0.984. The response selectivity against SARS-CoV-2 Anti-S antibodies was investigated in presence of concomitant species. The immunosensor was used to detect SARS-CoV-2 Anti-spike protein (Anti-S) antibodies in human serum samples, successfully differentiating between negative and positive responses of samples at a 95% confidence level. Therefore, the gold-binding peptide is a promising tool to be applied as a selective layer for antibody detection.

Graphical abstract

1. Introduction

Rapid and inexpensive immunodiagnostic assays have become essential for profiling responses against infections and conducting epidemiological surveillance, especially after the emergence of the SARS-CoV-2 disease in late 2019. Even though traditional techniques such as ELISA (enzyme-linked immunosorbent assay) have great detection performance, they also have some drawbacks by requiring non-portable instrumentation, labor-intensive procedures, and highly skilled personnel. In this scenario, using electrochemical immunosensors as a diagnostic platform could be an advantageous alternative in terms of portability, low-cost, ease of operation, and point-of-care applicability [1,2].

However, there are still some limitations associated with electrochemical immunosensors regarding their sensitivity and selectivity. In order to overcome these drawbacks, new recognition sites, e.g., peptides designed to specifically bind to different types of viruses and some carbon and metal nanomaterials, have been integrated into immunosensor devices [[3], [4], [5]]. Designed peptides have stood out in the development of diagnostic platforms due to their specificity, selectivity, and versatility in the interaction with various solid surfaces and other molecules [6]. The combination of peptides with gold nanoparticles (AuNPs) enhances biosensor performance even more due to the properties of the nanomaterial, e.g., high surface area, resulting in useful features such as high electroactivity, stability, and reproducibility [7,8]. In addition, this nanomaterial can be easily modified with peptides by exploring the interaction with thiols, amines, or even phosphate moieties of the biomolecules [9]. Furthermore, its biocompatibility has enabled applications as a drug carrier [10,11], and for detecting metal ions [12,13] and antigens/antibodies [14,15].

From this perspective, the present study aimed to develop an electrochemical immunosensor based on a solid-binding peptide (SBP) with affinity to gold nanoparticles as a simple diagnostic platform for viral diseases. The precise amino acid sequence plays an important role in SBP behavior along with the affinity between chemical groups within amino acid residues and solid surfaces, affording the conjugation of the antibody-binding site with specific support-binding residues [16]. Therefore, a gold-binding peptide was synthesized in fusion with a specific SARS-CoV-2 antigen. This virus was selected because COVID-19 is an emerging disease that still demands simple, fast, and easy-to-handle diagnostic platforms. Also, detecting antibodies is essential to complement antigen or molecular tests specially at later stages of infection, in which the viral load is reduced upon shedding and seroconversion. Furthermore, monitoring antibodies is a crucial tool to evaluate the postvaccination immune response of a population and even the effectiveness of vaccines [1,17,18].

2. Material and methods

2.1. Reagents and solutions

All reagents were of analytical grade and were used without any further purification. Chloroauric acid (HAuCl₄·3H₂O) and potassium ferricyanide (K₃[Fe(CN)₆]) were purchased from Sigma Aldrich, and sodium citrate (Na₃C₆H₅O₇) was purchased from Synth. Phosphate buffer saline (0.1 mol L⁻¹, pH 7.4) was prepared with sodium chloride (NaCl), potassium chloride (KCl), potassium phosphate monobasic (KH₂PO₄), and disodium hydrogen phosphate (Na₂HPO₄), all from Sigma Aldrich. Human serum was purchased from Sigma Aldrich. Bovine serum album (BSA) and the SARS-CoV-2 Anti-S antibody (15 mg mL⁻¹) were provided by the Molecular Biology Laboratory of the Bioprocess Engineering and Biotechnology Graduate Program of the Federal University of Paraná, Curitiba, PR, Brazil. Solutions were prepared with ultrapure water (Milli-Q®, Millipore) with resistivity higher than 18.2 MΩ cm.

2.2. In silico prediction

The reference genome used throughout this study is from the SARS-CoV 2 isolate Wuhan-Hu-1 (GenBank: MT126808.1) where we obtained S protein sequences (QIG55994.1), with these sequence we use the following tools for epitope prediction: Bepipred Linear Epitope Prediction 2.0 [19]. Surface, Accessibility, Antigenicity, Hydrophilicity available on BcePred (https://webs.iiitd.edu.in/raghava/bcepred) [20], Kolaskar & Tongaonkar Antigenicity [21]. Both prediction algorithms are available on the IEDB B cell prediction tool page IEDB Analysis Resource (http://tools.iedb.org/main/bcell) [[22], [23], [24]], ABCpred (webs.iiitd.edu.in/raghava/abcpred/) [25] and the software DNASTAR (Lasergene 14.1). With the values obtained by the different tools a Min-max normalization was carry out. The values obtained are separated into two categories, which will be assigned different weights, the first is physicochemical data weighs 33.3% and the second immunological data with 66.7% towards the final value. For each amino acid position were made average of value and multiplied by the weight of the category, to finally add up and get the final value for that position.

2.3. SPOT-synthesis and immunodetection

In base of the result of in silico prediction their sequences were spot-synthesized by overlapping peptides (15 residues) offset of four amino acids scanning. The Spot synthesis was performed on a cellulose membrane with Fmoc-protection using an automated spot peptide synthetizer (Intavis Bioanalytical Instruments, Nattermannallee, Germany) [26].

For immunodetection assay, the cellulose membrane was firstly blocked, for nonspecific binding, by overnight agitation with 3% (w/v) casein and 0.5% (w/v) sucrose dissolved in TBS-T (0.1% Tween 20 (v/v) in TBS) at 4 °C. Afterwards, the membrane was washed with TBS-T 0.1% for 10 min under agitation, and probed, for 90 min at 37 °C, with patients’ serum or negative control diluted 1:100 in blocking buffer (3% (w/v) casein, 0.5% (w/v) sucrose and TBS-T 0.1%). The membrane was washed again and incubated with biotin-labeled secondary antibody (1:40,000) diluted in blocking buffer for 60 min at 37 °C, followed by an incubation step with Streptavidin (1:10,000) diluted in blocking buffer for 60 min at 37 °C. After two washes, positive spots were visualizing by ECLTM system. To analyze and compared the generated images we used the imageJ software V.1.52n [27] with the plugin Protein array Analyzer are available on http://image.bio.methods.free.fr/ImageJ/?Protein-Array-Analyzer-for-ImageJ&lang=fr.

Membranes were evaluated for IgG. A regeneration process was carried out and checked for the membrane before using different antibodies, to ensure the removal of primary and secondary antibodies, and thus avoiding false positives during the assays. The regeneration of the membrane was carried out in two steps. In the first step the membranes were treated with the regeneration buffer I (solution 8 mol L⁻¹ of urea with 1% SDS, 2 times for 30 min). Then, they were treated with regeneration buffer II (solution of 100 mL of acetic acid, 500 mL of ethanol and 400 mL of water) for 30 min with a light agitation both at room temperature. Finally, they were washed at least five times with methanol and dried on air, the membrane was storage at −80 °C.

2.4. Synthesis and characterization of gold nanoparticles (AuNPs) and peptide-AuNPs (Pept/AuNP)

Gold nanoparticles were prepared by the Turkevich method [28]. Briefly, 5 mg of chloroauric acid were diluted in 95 mL of ultrapure water, and the solution was heated until boiling. Next, 5 mL of a 1% sodium citrate solution was added to the magnetically stirred gold solution, after which the solution turned grey-blue and then red. Boiling and stirring were kept for 1 h, after which the solution was cooled to room temperature and stored until use.

The peptide was designed to mimic a fragment of the SARS-CoV-2 spike-protein; therefore, it specifically interacts with the SARS-CoV-2 Anti-S antibodies. In addition, the peptide contained a specific sequence with affinity to gold (WALRRSIRRQSY). This peptide was chemically synthesized by the Molecular Biology Laboratory of the Bioprocess Engineering and Biotechnology Graduate Program of UFPR (Curitiba, PR, Brazil) using cleavable resin as a solid support, allowing the production of soluble peptides in aqueous buffer [29]. For that, a solid-phase peptide was synthesized using an automatic synthesizer (Intavis Bioanalytical Instruments, Nattermannallee, Germany) and using Fmoc-protected amino acids [30].

The nanoparticles were modified by mixing the peptide stock solution (1.109 mg mL⁻¹) and the gold nanoparticle solution in a 1:10 (v/v) ratio (peptide:AuNPs). Then, the solution was kept under stirring at 4 °C for 60 min, after which the peptide-gold nanoparticle (Pept/AuNP) solution was obtained.

The AuNPs size distribution was determined using transmission electron microscopy (TEM) images obtained using a JEOL JEM 1200 microscope operating at 120 kV. The software ImageJ was used to determine the diameter of particles. Scanning Electron Microscopy (SEM) images were obtained using a Quanta 450 ESEM FEG scanning electron microscope, and the elemental composition was estimated by energy dispersive spectroscopy (EDS) analyses using a spectroscope (Oxford) coupled to the scanning microscope. A BOMEN spectrophotometer was used for Fourier-transform infrared spectroscopy (FTIR) measurements (64 scans, from 4000 cm⁻¹ to 400 cm⁻¹).

2.5. Electrochemical measurements

Voltammetric measurements were performed using a Potentiostat/Galvanostat PGSTAT204 operated by the software NOVA 2.1.4. The biosensor construction steps were assessed by cyclic voltammetry (CV) using 1.0 mmol L⁻¹ K₃[Fe(CN)₆] in 0.1 mol L⁻¹ PBS as a redox probe (v = 50 mV s⁻¹). Differential pulse voltammetry (DPV) measurements were performed using a 5 mV step, a 150 mV amplitude, and a 0.5 s modulation time. All measurements were performed in triplicate.

2.6. Screen-printed electrode modification and biosensor construction

Commercial screen-printed carbon electrodes (SPE, Metrohm DropSens 110) were used as a platform to construct the immunosensor (Fig. 1 ). For that, 5.0 μL of a Pept/AuNP solution (1,000x diluted in PBS) were dropped onto the working electrode, and the device was oven-dried (37 °C) until total solvent evaporation. After the recognition of layer formation, non-specific sites were blocked using 5.0 μL of a 1.0 mg mL⁻¹ BSA solution (incubation at 4 °C for 15 min). Then, the device was ready for the detection step, in which 5.0 μL of Anti-S solution were dropped onto the working electrode (incubation at 4 °C for 60 min). The electrode was gently washed with PBS solution (0.1 mol L⁻¹, pH 7.4) between every construction and detection step.

Fig. 1.

Scheme of the biosensor construction and detection steps: SPE was used as a platform to construct the device. For that, 5.0 μL of the Pept/AuNP solution was dropped onto the working electrode, and it was oven-dried at 37 °C until solvent evaporation. Then, 5.0 μL of BSA solution was dropped onto the electrode (incubation at 4 °C for 15 min). For the detection step, 5.0 μL of SARS-CoV-2 Anti-S antibody solutions were dropped onto the electrode (incubation at 4 °C for 60 min).

2.7. Evaluation of analytical parameters

The biosensor response was evaluated for SARS-CoV-2 Anti-S antibody concentrations ranging from 30 ng mL⁻¹ to 15 μg mL⁻¹ to establish the working range. For the trial in real sample, commercial human serum was diluted 10,000 times in PBS (0.1 mol L⁻¹, pH 7.4) and then spiked with 1.5 μg mL⁻¹ of the analyte. A non-fortified serum sample was also evaluated as a negative control. Selectivity was investigated by evaluating the biosensor response in the detection step to Anti-S (1.55 μg mL⁻¹), SARS-CoV-2 Anti-N antibodies (Anti-N, 1.32 μg mL⁻¹), Yellow-Fever antibodies (Anti-YF, 1.60 μg mL⁻¹), and a mixture of all antibodies.

3. Results and discussion

3.1. Peptide selection

The development of effective and reliable serological detection methods would play an important role in attending to these needs [31]. A proposal that we are addressing in this work is the development of serologic diagnostic test based in peptides identification by B-cell epitopes prediction, SPOT-synthesis and the incorporation of the peptide into the sensor base in graphite. Peptide selection based on spike protein of SARS-CoV-2 using silico B-cell epitope prediction and spot synthesis were schematically showed in Fig. S1A.

In silico prediction were identified four possible B-cell epitope regions with the potential of being core immunogenic, which are critical for antibody recognition, considering a cut-off 0.7. These regions corresponding to the region two regions in RBD, two regions in Monomer-Monomer Interaction (one in S1 and one S2) (Fig. S1B). We selected a region between 797 and 835 amino acid position of the protein S of SARS-CoV-2 with low variability, that is related to the binding mechanism of the RBD region with hACE2 [32,33], since the cleavage of this area is necessary to allow the RBD interaction with hACE2, which makes this region of greater interest. To optimize the size of the peptide, was made spot synthesis of the region selected (Fig. S1C), we detect five peptides with signal went we test with positive serum, and the peptide with the sequence PSKPSKRSFIEDLLF, the one that had the highest fluorescence in relation to the other peptides (Fig. S1C).

3.2. Characterization of AuNPs and Pept/AuNPs

TEM images were acquired for assessment of AuNPs morphology (Fig. S2). The particles showed a spherical-shape, agreeing with the morphology reported in the literature [34], and diameters ranging from 17 to 45 nm, with a mean diameter of 30 nm (n = 98). Whilst the unmodified SPE did not present any type of nanostructure (Fig. 2 A), gold nanoparticles with similar morphology and diameter were also visualized in the SEM images of the SPE modified with AuNPs (Fig. 2B). In addition, the EDS spectrum (Fig. S3) of the region indicated in Fig. 2B, for the modified SPE, indicated the existence of the Au element, showing that the AuNPs were successfully incorporated into the electrode.

Fig. 2.

SEM images of (A) SPE, (B) SPE modified with AuNP, and (C) SPE modified with Pept/AuNP, with 30k times magnification; (D) FTIR spectra for AuNP and Pept/AuNP.

SEM images of the SPE modified with Pept/AuNP were also recorded (Fig. 2C), showing a larger density of spherical-shaped gold nanoparticles compared to the SPE modified with AuNPs only. The nanoparticle distribution over the electrode surface enhances with the presence of the peptide, probably due to the peptide structure, which prevents nanoparticle aggregation [35].

The FTIR spectrum (Fig. 2D) for the AuNPs shows some bands in the ranges of 3550–3200 cm⁻¹ (stretch of alcohol O–H bonds), 1760 cm⁻¹ (stretch of carboxylic acids C O), and 1440 cm⁻¹ (stretch of carboxylic acid O–H). These results can be related to sodium citrate, a reagent that acts as a stabilizer of gold nanoparticles. For the gold nanoparticles associated with the peptide (Pept/AuNP), bands were observed between 3500 and 3300 cm⁻¹. Moreover, the alcohol O–H bond can also indicate primary and secondary amines of the N–H bond. Secondary amine C O stretch, N–H deformation, and C–N stretch bands are observed in the 1680 cm⁻¹, 1650-1580 cm⁻¹, and 1250-1020 cm⁻¹ ranges, respectively. All these groups are part of the peptide bond, a structure that can be observed in protein formation by the bonding between amino and carboxylic groups from amino acids [36]. Therefore, these bands indicate the peptide-AuNPs association.

3.3. Immunosensor construction and optimization of experimental parameters

The potentiality of Pept/AuNPs as a selective layer to detect Anti-S was confirmed by evaluating the immunosensor construction steps considering the voltammetric behavior of the [Fe(CN)₆]^3-/4- probe. Cyclic voltammograms recorded after each device construction and detection step are presented in Fig. 3 A.

Fig. 3.

Cyclic voltammograms (A) and differential pulse voltammograms (B) for each construction and detection step of the biosensor (1.0 mmol L⁻¹ [Fe(CN)₆]^3-/4- in 0.1 mol L⁻¹ PBS, pH 7.4; CV: v = 50 mV s⁻¹; DPV: step = 5 mV, amplitude = 0.15 V, modulation time = 0.5 s, and interval time = 1 s); (C) Peak current response after several washes of the sensors assembled using Pept/AuNP and Pept as recognition layers.

First, the effect of Pept/AuNPs on the electrochemical response was investigated. Peak-to-peak separation (ΔE_p = E_ap – E_cp = 200 mV) decreased compared to the response obtained for unmodified SPE (ΔE_p = 310 mV), whereas the current peak for the anodic and cathodic processes increased. This behavior indicates that, regardless of the bonded-peptides, AuNPs enhance the electrochemical performance of the modified electrode due to their conductivity and high surface area, as reported in other studies [37]. CV measurements after the BSA step showed a decrease in both electrochemical signals and a less-reversible voltammetric profile. Therefore, adding a large and non-conductive molecule on the surface of the electrode hinders the probe redox processes, indicating the blockage of non-specific sites [38]. The detection of Anti-S antibodies was carried out by recording the CV measurement after the incubation step performed in the presence of the target. A decrease in probe peak currents was observed, indicating a blockage between the electrode and the electroactive species in solution. This effect can be attributed to antibodies bonded to the previously immobilized peptide and, therefore, the efficiency of the recognition layer.

Next, differential pulse voltammetry (DPV) was employed to diminish the influence of the capacitive current on probe response and improve analytical performance of immunosensors. Differential-pulse voltammograms (Fig. 3B) showed a response profile similar to CV: an increase in peak current after Pept/AuNPs immobilization followed by successive decreases for BSA and antibody detection steps. However, there was a suppression of the voltammetric signal around 20% when using DPV instead of 7% for CV measurements. Thus, DPV was employed so that a higher sensitivity could be achieved in the detection step, which leads to a more detectable signal when compared to the performance of the SPE modified only with the synthetic peptide (Fig. S4).

The stability of the modification was investigated using SPE modified with the synthetic peptide combined with AuNPs (Pept/AuNP). The biosensor was assembled, successively washed with distilled water and the probe signal was recorded after every wash (Fig. 3C, red bars). The results highlighted the effectiveness of Pept/AuNP immobilization on the working electrode, suggesting no leaching of recognition sites. The voltammograms shows barely no profile change in terms of potential anodic and cathodic peaks and a relative standard deviation of 3.6% in the anodic peak current. As a comparative, a device was assembled using only the peptide as the recognition layer and its stability was investigated. In this case, the probe signal showed a significant variation after consecutive washes (Fig. 3C, blue bars), indicating that the peptide itself was not stably immobilized over the electrode surface. Consequently, immunocomplex formation did not properly occur, and there was no difference in the response after antibody incubation compared to the previous step [39]. Therefore, the design proposed for sensor construction exploring the gold-binding peptide as a selective layer for Anti-S detection was successful considering electrode stability and reproducibility. This approach has the advantage of requiring only two steps for device construction, resulting in simple labor and reduced time consumption.

3.4. Evaluation of analytical performance

Anti-S concentrations ranging from 30 ng mL⁻¹ to 15 μg mL⁻¹ were investigated to evaluate the analytical performance of the biosensor. The response of [Fe(CN)₆]^3-/4- decreased as the Anti-S concentration increased, as shown in Fig. 4 A, and a linear relationship was established between the logarithm of Anti-S concentration and ΔI_p (ΔI_p = I_p(BSA) – I_p(Anti-S)) in the range from 75 ng mL⁻¹ to 15 μg mL⁻¹, with 1.059 μA dec⁻¹ sensitivity and R² = 0.984 (Fig. 4B).

Fig. 4.

DP voltammograms (A) and Calibration curve (B) obtained for the proposed biosensor: probe differential current peak intensity versus the Anti-S concentration logarithm.

Concentration level of 75 ng mL⁻¹ was not included in the biosensor linear working range; however, the device was still able to detect antibodies against SARS-CoV-2 in this condition. Because of that, this level was established as the limit of detection (LOD) of the proposed methodology. Additionally, even though not many concentration levels were included in the linear working range, the primary function of the biosensor was achieved, that is, it was successfully used to detect different analyte concentrations. Also, the performance of the gold-binding peptide biosensor obtained in this study is comparable to other results reported in the literature, which use peptides associated with gold-based (nano)materials to detect antigens or antibodies (Table 1 ). Furthermore, even though the detection of SARS-CoV-2 antigens using a peptide/gold-modified biosensor platform has been already reported [40], this is the first study, as far as we know, to use this sort of platform to detect antibodies against the virus. Therefore, the developed platform contributes to monitoring the current exposure, disease progression, and even vaccine efficiency and the human body post-vaccination response.

• [a]Time for peptide-analyte interaction
• [b]Lowest concentration of the linear working range or lowest concentration reported in the study
• [c]Gold electrode as a platform for biosensor construction

Table 1.

Peptides associated with gold/gold nanoparticles as recognition sites for antigen or antibody detection: analytes, techniques, assay time, and lowest detectable values.

Target	Detection technique	Assay time[a]	Lowest detectable value[b]	Ref.
Gliadin antibodies	UV–Vis	30 min	2000 ng mL−1	[41]
Carcinoembryonic antigen	SPR	Overnight	0.1 ng mL−1	[42]
BSA antibodies	DFM	60 min	10 nmol L−1	[43]
SARS-CoV-2 spike protein	EIS	15 min	18.2 ng mL−1	[40][c]
SARS-CoV-2 antibodies	DPV	60 min	30 ng mL−1	This study

DFM: darkfield microscopy; DPV: differential pulse voltammetry; EIS: electrochemical impedance spectroscopy; SPR: surface plasmon resonance; UV–Vis: ultraviolet–visible spectroscopy.

The peptide used in this study was synthetized in fusion with a specific SARS-CoV-2-antibody binding site - S protein. The response selectivity of the proposed sensor was evaluated against SARS-CoV-2 antibodies - N protein (Anti-N, 1.3 μg mL⁻¹), yellow-fever antibodies (Anti-YF, 1.6 μg mL⁻¹), and a mixture of Anti-S, Anti-N, and Anti-YF. The results obtained are showed as relative values in Fig. 5 . Regarding the results, no significant difference at a 95% significance level was observed in the detection step in the presence of Anti-YF (t_calculated = 1.42 < t_{critical(0.025; 2)} = 4.303) and Anti-N (t_calculated = 1.21 < t_{critical(0.025; 2)} = 4.303). On the other hand, a significant decrease in peak current was obtained after incubation in the presence of an Anti-S target (t_calculated = 4.49 > t_{critical(0.025; 3)} = 3.18) and the mixture containing Anti-S, Anti-N, and Anti-YF (t_calculated = 5.12 > t_{critical(0.025; 2)} = 4.303). Therefore, the biosensor showed excellent selectivity in the presence of concomitant species.

Fig. 5.

Responses for detection of Anti-S, Yellow-Fever antibody, SARS-CoV-2 Anti-N antibody, and a mixture of them.

The analytical performance of the immunosensor proposed in real samples was evaluated against positive and negative serum samples (10,000x diluted in PBS). For the negative serum sample, as shown in Fig. 6 A, no difference in peak current was observed for the detection step, indicating no interaction of non-specific species of the serum with the biosensor. On the other hand, the positive serum sample showed a clear signal differentiation in the detection step (Fig. 6B) due to the specific interaction of Anti-S antibodies with the recognition layer. This signal suppression was approximately 33% smaller than the one obtained in the absence of the matrix, suggesting a sensitivity loss related to other components present in the serum matrix. However, this response is still valid since the immunosensor was able to significantly differentiate between negative and positive serum samples (t_calculated = 12.02 > t_{critical(0.025; 2)} = 4.303 at a 95% confidence level), as shown in Fig. 6C.

Fig. 6.

Differential pulse voltammograms for the detection of a (A) Negative serum sample and a (B) Positive serum sample (1.0 mmol L⁻¹ [Fe(CN)₆]^3-/4- in 0.1 mol L⁻¹ PBS, pH 7.4, step = 5 mV, amplitude = 0.15 V, modulation time = 0.5 s, and interval time = 1 s); (C) Signal variation for the detection of negative and positive serum samples.

4. Conclusions

The gold-binding peptide was suitable for application as a selective layer to detect SARS-CoV-2 antibodies (Anti-S). The synthetic peptide was able to interact with gold nanoparticles, allowing the development of an electrochemical immunosensor by means of a very simple procedure. This approach provided highly stable and selective responses using an immunosensor prepared directly with a dispersion of AuNPs/Pept. In addition, the use of preincubated peptide-AuNPs reduces drastically the assembly time of immunosensor. Analyses of positive and negative serum samples were carried out and provided excellent results. In addition, screen-printed electrodes were very good platforms to construct portable and low-cost immunosensors. Therefore, antibodies can be determined using simple construction and detection approaches, which is helpful to verify disease progression.

Credit author statement

Beatriz A. Braz: Conceptualization, Formal analysis, Investigation, Methodology, Validation, Writing – review & editing. Manuel H. Santiani: Conceptualization, Methodology. Gustavo Martins: Conceptualization, Investigation, Methodology, Validation, Writing – review & editing. Jeferson L. Gogola: Investigation, Validation, Writing – review & editing. Marcia G. P. Valenga: Formal analysis, Writing – original draft. Breno C. B. Beirão: Conceptualization, Resources, Funding acquisition, Supervision, Writing – review & editing. Márcio F. Bergamini: Conceptualization, Resources, Funding acquisition, Supervision, Writing – review & editing. Luiz H. Marcolino-Junior: Conceptualization, Resources, Funding acquisition, Supervision, Writing – review & editing. Vanete Thomaz-Soccol: Conceptualization, Resources, Funding acquisition, Supervision, Writing – review & editing. Carlos R. Soccol: Conceptualization, Resources, Funding acquisition, Supervision, Writing – review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Handling Editor: J.-M. Kauffmann

Appendix A. Supplementary data

The following is the Supplementary data to this article.

Data availability

No data was used for the research described in the article.