Thickness-Sensing Sandwiched Plasmonic Biosensors Enable Label-Free Naked-Eye Antibody Quantification

Abstract

Clinical serology assays for detecting the antibodies of the virus are time-consuming, are less sensitive/selective, or rely on sophisticated detection instruments. Here, we develop a sandwiched plasmonic biosensor (SPB) for supersensitive thickness-sensing via utilizing the distance-dependent electromagnetic coupling in sandwiched plasmonic nanostructures. SPBs quantitatively amplify the thickness changes on the nanoscale range (sensitivity: ~2% nm⁻¹) into macroscopically visible signals, thereby enabling the rapid, label-free, and naked-eye detection of targeted biomolecular species (via the thickness change caused by immunobinding events). As a proof of concept, this assay affords a broad dynamic range (7 orders of magnitude) and a low LOD (~0.3 pM), allowing for the extremely accurate SARS-CoV-2 antibody quantification (sensitivity/specificity: 100%/~99%, with a portable optical fiber device). This strategy is suitable for high-throughput multiplexed detection and smartphone-based sensing at the point-of-care, which can be expanded for various sensing applications beyond the fields of viral infections and vaccination.

Graphical Abstract

Viral infectious diseases such as coronavirus disease 2019 (COVID-19) have negatively affected the health and lives of individuals in all societies worldwide.^1–3 As such, it is imperative that methods for rapid and accurate biomolecular detection are being developed to monitor and control the spread of infectious diseases and thereby have attracted immense attention.^4–6 The antibody test is widely used to detect and quantify the amount of antibodies that is produced by the immune system following virus infection.^7–11 Several critical advantages are associated with the antibody test, such as the identification of infection stages, monitoring of immune dynamics, and evaluation of vaccination efficacy.^12–14 These are particularly useful in surveillance and prevalence studies. Specifically, the antibody test detects convalescent cases and helps in establishing epidemiological links between clusters.¹⁵ Neutralizing antibody titers help protect individuals from further infection and play a pivotal role in the evaluation of vaccine efficacy.¹⁶ Clinically, enzyme-linked immunosorbent assay (ELISA), chemiluminescent immunoassay (CLIA), and lateral flow immunoassay (LFIA) are most commonly conducted to detect antibodies.^17–19 Nevertheless, considerable concerns of either sensitivity/specificity, portability, or production costs of currently available detection methods hamper the effective screening and monitoring of infectious diseases.^20–22 Various existing state-of-the-art techniques involving efficient transducers have been used to address these limitations. Methods that involve the use of elaborate optical labels and electric sensing devices have been extensively investigated, greatly improving the clinical performance of biomarker detection.^23–36 Several versatile plasmonic sensors have also shown reasonable responses for the virus detection.^37–40 Although these critical advances have been made, a rapid, label-free, high-throughput detection method for the detection of biomolecular interactions with straightforward signal readout is still not available. This has also long been considered significantly important for the next-generation biosensors because it has huge potential in multiplexed diagnosis and accurate multiparametric analyses of clinical cases.

Herein, we report a sandwiched plasmonic biosensor (SPB) for supersensitive thickness detection by sandwiching a protein spacer between Au nanoparticles (AuNPs) and Au film. Since electromagnetic coupling is dependent upon the immunobinding of antibodies, the reflected visible light output signals are visible by the naked eye or using a smartphone that helps in further visually quantifying antibodies. This unique thickness-sensing transducing mechanism makes SPB immunoassay suitable for effective high-throughput antigen screening and rapid classification of samples. Here, clinical SARS-CoV-2 antibody detection was selected for the proof-of-concept demonstration. Detection with ~99% specificity with no false-negative cases can be supported by using a miniaturized optic fiber device or an optic-fiber-equipped microscope. The results can potentially provide a platform for the development of rapid multiplexed detection methods to diagnose various viral diseases.

Our proof-of-concept SPB comprises an AuNP monolayer on the top, a gold film at the bottom, and a sandwiched spacer (Figure 1a,b). The fabrication of such structures was enabled by transferring a poly(methyl methacrylate) (PMMA) membrane with embedded AuNPs onto a spacer-coated gold film following a wet transfer method (Figure S1). For practical use, the PMMA membranes can also be transferred onto a temporary substrate, allowing for the direct transfer of the AuNP monolayer to the target surface. To comprehensively understand and explore the properties of the sandwich system, the general structures were systematically enriched by tuning several basic parameters, including diameters and the density of the nanoparticles (Figure S2). We further applied a layer-by-layer (LbL) assembly technique to fabricate polymer spacer with well-controlled thicknesses (defined as “d”) in the range of 1.6–62.2 nm. Then, the optical properties of these fabricated chips with size-tunable AuNPs and polymer spacer were thoroughly investigated. SPBs showed distinct colors generated at various spacer thicknesses, and the overall reflectance dramatically decreased with an increase in the thickness of the LbL-assembled layers (Figure 1c,d and Figure S3). It is worth noting that continuously blue-shifted reflectance wavelength peaks were observed by subtracting the reference spectral profile (d = 0; “blank” spectrum) from the spectral profiles recorded in the presence of the polymer spacers (Figure S4). As shown in Figure S5a, the resonance modes of the SPB are divided into horizontal dipole mode and vertical dipole mode, corresponding to two plasmonic dipoles parallel and perpendicular to the Au surface. The reflectance difference could be attributed to the strong scattering of the p-polarized localized surface plasmonic resonance (LSPR) of the AuNPs (vertical dipole mode) present on the chip.⁴¹ Accordingly, the reflectance wavelength maxima were significantly affected by the distance-dependent plasmonic coupling between AuNPs and Au film. By eliminating induced opposite charges on the underlying Au film, weakened electromagnetic interactions substantially increase the restoring force applying to polarization charges, thus leading to an increased LSPR frequency.^42,43 Therefore, the p-polarized LSPR shifts to a shorter wavelength and eventually overlaps with the s-polarized LSPR signal with continuously increasing LbL circles. To further substantiate the coupling mechanism, we also performed the systematic finite-difference time-domain (FDTD) simulation of SPBs, which are described in the Supporting Information (Figure S5).

Figure 1.

The proof-of-concept sandwiched plasmonic biosensor (SPB) provides an unprecedented “thickness” sensitivity that utilizes plasmonic coupling. (a) Schematic representation of the sandwiched nanostructures. (b) Scanning electron micrograph (SEM) of the SPB with a polymeric spacer fabricated following the LbL (layer-by-layer) technique. The diameter of the AuNPs used was 84 nm. (c) Reflectance spectral profile recorded for the spacer-thickness-tuned SPBs fabricated following the LbL assembly technique. A remarkably highly sensitive reflectance response was achieved. The diameter of AuNPs used was 35 nm. (d) Images of SPBs recorded using microscopy for sandwiched polyelectrolyte spacer layers. (e) Reflectance as a function of effective protein thickness. (f) Plot of gray value versus effective protein thickness. The insets show the microscopy images of patterned SPBs (diameter: 1 mm) with protein thicknesses of 0.5 nm (left) and 4.5 nm (right). The diameter of the AuNPs used in (e) and (f) was 15 nm. Data in (e) and (f) are shown as the mean ± standard deviation (n = 3).

A single layer of the capture ligand (biotin-modified bovine serum albumin; bBSA) was next sandwiched between the SPB chips to evaluate the thickness sensitivity of protein samples. The sandwich model was investigated to obtain a general rule of signal transduction by protein adsorption. As the extent of surface coverage of the protein responsible for the increase in bBSA concentration increased, the effective thickness was quantitatively transduced to a high reflectance dip in the SPB spectral profile (Figure 1e and Figures S6 and S7a). SPB responded linearly with the protein thickness, attaining an unprecedented sensitivity as high as 1.94% nm⁻¹. The limit of detection (LOD) for a single protein interlayer was calculated to be 0.3 nm. Using a spectrometer that detects the minimum reflectance of <0.01%, the minimum resolution of ~5 pm was achieved. Simultaneously, to comprehensively understand the SPB transducer in this model, SPBs fabricated with different sizes of AuNPs were studied in detail (Figure S6). An optimal sensitivity of 2.24% nm⁻¹ could be achieved using the SPB fabricated with AuNPs having diameters of 35 nm. Notably, the as-demonstrated ultrahigh sensitivity of the SPBs enabled accurate quantification of protein thickness with a sensitivity of 1.75 nm⁻¹ using gray value analysis of microscopy images, which highlights their property of visibility with the naked eye (Figure 1f). Collectively, these results showed that SPBs quantitatively amplify the thickness changes in the nanoscale range to the macroscopic signal of reflectance to a visible wavelength.

To demonstrate the feasibility of the SPB platform for antibody quantifications, we next explored clinical sensing performance of the SPBs by performing SARS-CoV-2 antibody detection in serum samples. Assays using SPBs were established by incubating 40–60 μL of serum samples on an antigen-printed Au/glass substrate and subsequently covering it with a layer of AuNPs. The SPB assay affords accurate quantification of the exact thickness of nanometers-thick proteins (Figure 2a). The spatial expansion attributable to the specific binding of antibodies results in weakened electromagnetic coupling,⁴⁴ thereby resulting in a blueshift in the reflectance dip originating from the p-polarized LSPR of the AuNPs. Atomic force microscopy (AFM) was used to confirm the increase in the thickness of bound protein layers (Figure S7b). Since increasing concentrations of bound antibody significantly affected the extent of SPB surface coverage, a decrease in the reflectance in the visible spectrum was typically observed (instead of a shift in the wavelength). Therefore, when an antigen-coated SPB was incubated with targeted antibody solutions of increasing concentrations, a graduated color change was observed (Figure 2b). Similarly, spots with a darker color, which represent a positive signal, could accordingly be observed via standard microscopy (Figure 2d). Multiplexed sensing was compatibly supported by a microarray printer in the absence of a secondary antibody and labels. Various types of capture antigens were successfully incorporated into a single sensing element of dimensions 7 mm × 7 mm. A chip of 25 mm × 75 mm could be used to conduct 10 assays.

Figure 2.

Principle and performance of the SARS-CoV-2 antibody assay conducted using the SPB platform. (a) Schematic depicting the SPB fabrication steps and the principle underlying the assay. A thickness sensing transducer was employed. (b) Photographs of the SPB incubated with solutions of antibodies against SARS-CoV-2 having various concentrations (100 μg mL⁻¹, 50 μg mL⁻¹, 40 μg mL⁻¹, 30 μg mL⁻¹, 20 μg mL⁻¹, 10 μg mL⁻¹, 5 μg mL⁻¹, and 2 μg mL⁻¹; the bottom two spots correspond to a concentration of 0 μg mL⁻¹) in the dry (left) and wet state (right). Amino acid peptides were used as the capture antigen. Scale bars: 2 cm. (c) Schematic representation of the printing layout and photograph of the corresponding printed Au film (top, scale bar: 1 cm). Anti-IgG, bovine serum albumin, and phosphate buffered saline (PBS) were used as controls. S1 subunit and receptor-binding domain (RBD), obtained from two different vendors, and an amino acid peptide were printed. (d) Several typical patterns (microscopy images) of RBD #1 and anti-IgG (used as a normalizer) were generated using the PCR-positive and healthy samples. The patient IDs are represented by the digits. The diameter of each antigen spot (in each panel) is ~300 μm. (e) Gray value plot profiles from three PCR-positive and healthy samples. (f) Comparison of the signals generated by PCR-positive and healthy groups. A gray value analysis method was used to compare the data, and significant differences were observed. The horizontal solid lines indicate the mean values. (g) ROC curves generated using SPB SARS-CoV-2 antibody assays and the table presenting the sensitivity and specificity of SPBs with the two different sized AuNPs. (h) Signals measured using SPBs with AuNPs of different sizes as the top layer and correlation between the data. Moderate data fitness was achieved. Data obtained from PCR-positive and healthy serum samples are displayed in orange and blue, respectively. The dashed lines represent cutoff values (determined by the ROC curve analysis) of the two types of sensors. All data presented in panels (f)–(h) are derived from 74 healthy and 25 PCR-positive human serum samples.

The antigens were first screened to optimize the sensing method in order to achieve enhanced sensing performance. The S1 subunit and receptor-binding domain (RBD) (from two different vendors, see Supporting Information) within the SARS CoV-2 spike glycoprotein were evaluated. In addition to these common antigens, we also used a 20-amino-acid peptide that was derived from the SARS CoV-2 spike glycoprotein. A goat anti-rabbit IgG, used as a normalizer, was also printed simultaneously. It was assumed that the size of the goat anti-rabbit IgG could be maintained during the assays to eliminate the effects of batch-to-batch variations and nonuniform distributions of the AuNPs.

The comparison between the results of antigen screening indicated that the most significant difference in the signals generated during the test of healthy and PCR-positive groups was achieved using the RBD #1 antigen, suggesting that RBD #1 was the optimal capture ligand (Figure S8). Analysis of the images recorded using microscopy and the signals obtained using gray value analysis verified that the SPBs exhibited excellent detection abilities (Figure 2c–f). Subsequently, 25 PCR-positive samples were collected from patients 8–31 days after COVID-19 symptom onset (Table S1). Using AuNPs with diameters of 35 nm and 67 nm, sensitivities of 96% and 92% along with specificities of 95% and 89%, respectively, were obtained by analyzing each corresponding receiver operating characteristic (ROC) curve (Figure 2g). Detailed results from gray value analysis conducted to detect antibodies are also shown (Figure S9). A positive correlation (R² = 0.55) was observed among the data collected using AuNPs of different diameters, thereby demonstrating that different nanoparticle sizes do not cause differences in clinical interpretation (Figure 2h).

The data obtained by analyzing the patterns on the chip surface revealed that the chips could be effectively integrated into a miniaturized readout device, thus allowing for the transformation into rapid high-throughput point-of-care tests (POCTs). The sensitivity and specificity achieved 100% and 98.9%, respectively, when a portable optical fiber device was used (Figure 3). Of the 120 samples tested, 119 samples could be accurately analyzed with only one false-positive case (accuracy: 99.2%). As expected, a strong correlation was also observed between the detected antibody levels against S1 and RBD antigens (Figure 3e,f).¹⁸ Notably, a dose-dependent optical signal was observed across all serum concentrations tested (Figure 3g). BSA does not specifically interact with any elements in the serum samples, thereby leading to the generation of constant signals. Some positive samples can still generate signals above the cutoff value even with 100-fold dilution, indicating a strong immunological response in the PCR-positive individuals. To determine assay variation, we characterized a set of serum samples from 5 PCR-positive patients and 16 healthy individuals through three independent experiments (Figure 3h). We observed average interassay coefficients of variations (CVs) of 3–15% (PCR-positive samples, 3%; 19 samples with a signal value of >0.1, 9%; all 21 samples, 15%), which indicates that high reproducibility could be achieved. In addition, high levels of the antibodies against the peptide were detected in 9 of the 25 PCR-positive individuals (5 strongly positive cases), whereas increased signals were not observed in the case of samples from the healthy group (Figure S9c,d). In conclusion, these results suggested that the developed platform can also be used in resource-limited settings, thus enabling the high sensitivity and specificity of antibody tests using a low-cost and portable optical reader.

Figure 3.

SPB immunoassays for SARS-CoV-2 antibody quantification using the portable spectrometer. (a, b) Schematic (a) and images (b) of the portable optic fiber device, which consists of a visible light source, reflection probe, and miniaturized detector. (c) Plot of optical outputs obtained by conducting the SPB antibody assays with AuNP monolayers (AuNP diameter: 35 nm) (tests were conducted with 30 PCR-positive and 90 healthy serum samples). Corresponding ROC curves (inset) show the significant difference between the positive and negative groups. A sensitivity and specificity of 100% and 98.9% were achieved, respectively. The horizontal solid lines indicate the mean values. (d) Detailed results in the form of a histogram from optical analysis were conducted to detect antibodies against RBD #1. The SPB immunoassays were conducted with AuNP monolayers (diameters: 35 nm). (e, f) Correlation plots of antibody levels using RBD #1 and RBD #2 antigens (e) and RBD #1 and S1 #1 antigens (spectral analysis) (f). (g) Optical signals obtained by conducting SPB antibody immunoassays for the original or diluted samples using an optic fiber device. Data in this plot correspond to the serum samples obtained from patients #22 (peptide), #23 (BSA, RBD #2), and #24 (S1 #1, RBD #1). (h) Levels of antibody against SARS-CoV-2 were measured in human serum samples obtained from 5 PCR-positive patients and 16 healthy individuals through three independent experiments (spectral analysis). Reproducible optical readouts were achieved. Data in (d)–(h) are shown as the mean ± standard deviation (n = 3).

SPB produces signals by reflecting visible light. Hence, not only is it compatible with various signal readout devices, but this type of configuration also allows for a rapid high-throughput multiplexed detection with the naked eye. Indeed, we recorded pictures using smartphones to check the capability of naked-eye observations using our SPB-based immunoassay. Representative results obtained by conducting the normal (Figure 4b–e) and five-plexed (Figure 4f,g) SPB immunoassays to detect SARS-CoV-2 antibodies are shown in Figure 4. Here, PCR-positive samples can be easily distinguished by the naked eye using smartphone images. To increase the robustness and accuracy of our smartphone-based SPB immunoassays, we used image-processing software to conduct the gray value analysis. Of the 30 samples, 28 had gray value signals above the cutoff value, indicating a 93% assay sensitivity. The specificity was calculated to be 97% (87/90). The signals collected by the spectrometer and registered by the smartphone also show a strong correlation (R² = 0.85), thereby demonstrating that comparable accuracy can be achieved by using the smartphone as the readout device. These results revealed that the method could be used to directly analyze the samples from patients infected with SARS-CoV-2 by visualizing the microarray spots.

Figure 4.

Visible patterns of SARS-CoV-2 binding generated during performance of SPB-based immunoassays. (a) Image of the portable smartphone readout device. (b) Several images of typical SPB-based immunoassays for the detection of SARS-CoV-2 antibody captured using the smartphone. Chips were in the wet state. The schematic diagram presents the corresponding assay layout. The patient IDs are represented by the digits. “T” and “C” represents “test spots” and “control spots”, respectively. (c) Detailed gray value signal levels of the 30 PCR-positive and 90 healthy samples by performing SPB immunoassay with a smartphone as readout device. (d) Plots of gray value signals for PCR-positive and healthy groups by using a smartphone as readout device and the corresponding ROC curves (inset). The horizontal solid lines indicate the mean values. (e) Signals measured by a spectrometer and a smartphone and correlation between the data collected using the two kinds of readout devices. Data obtained from PCR-positive and healthy serum samples are displayed in orange and blue, respectively. The dashed lines represent cutoff values (determined by the ROC curve analysis) of the two different methods. (f) Several images of five-plexed SPB-based immunoassays for the detection of SARS-CoV-2 antibody captured using the smartphone. Chips were in the wet state. (g) Detailed gray value signal levels of the 4 PCR-positive and 3 healthy samples by performing the smartphone-based multiplexed SPB immunoassay. All data were obtained by performing an SPB immunoassay with 35 nm AuNP monolayers. Scheme in (a) was created with BioRender.com.

To comprehensively understand main factors affecting clinical sensing performance of the SPB immunoassays, streptavidin (SA)/biotin system was next used as a high-affinity ligand–receptor pair to maximize the clinical potential of the SPB platform. The efficiency was studied in the presence of printed bBSA and variable concentrations of SA. SPBs with a relatively high density of AuNPs (diameter: 35 nm) exhibited the best sensing performance (Figure S10). Using a portable optic fiber system, a broad dynamic range (7 orders of magnitude) and a LOD value of 262 fM were obtained when this platform was used in the bBSA/SA system (Figure 5a). A similar calibration curve was obtained when the peptide/SARS-CoV-2 antibody pairs were tested (Figure 5b). The extremely low LOD value of 44.8 pg mL⁻¹ (~0.3 pM) essentially provided a crucial contributing factor for the high sensitivity and specificity of the SPBs. The value also indicated that apart from the detection of the SARS-CoV-2-specific antibody, which is present in high concentrations in highly positive samples, the system can be potentially used for the accurate POCT of a large number of trace biomarkers present in a complex biological medium. We compared the efficiency of the developed SPB with state-of-the-art techniques to determine the sensitivity of the developed device (Figure 5c).¹⁸ Under the same experimental conditions, the developed SPB was more sensitive than the general and enhanced immunofluorescence assay (IFA) platforms. Notably, the broad dynamic range achieved using the developed SPB makes it a suitable system that can be used to detect various disease models with varying cutoff values. The specificity of the SPB platform were extensively studied (Figure 5d). SPBs printed with the SARS-CoV-2 peptide did not cross-react with several off-target biomarkers, such as the hepatitis B virus (HBV) antigen, HBV antibody, C-reactive protein (CRP), CRP antibody, and procalcitonin. Similarly, the SARS-CoV-2 antibody molecule also only reacts with correct capture ligands, which shows the marginal cross-reactivities with the SPB platform (Figure S11). Furthermore, we studied the effects of incubation time and temperature during SPB-based immunoassays (Figure S12). Signals reached >50% of the maximum values within 10 min and >40% of the maximum value within 5 min. The fabricated SPB can be potentially used to achieve a rapid diagnosis (5–10 min) with a reduced sensitivity. Changes in temperature exerted little effect on the performance of the SPB immunoassays in the peptide/SARS-CoV-2 antibody model. These data were reproducible under different experimental conditions in practical clinical settings.

Figure 5.

Sensitivity, specificity, and stability of the SPB immunoassay. (a, b) Calibration curves generated for biotin-modified bovine serum albumin (bBSA)/streptavidin (SA) (a) and peptide/SARS-CoV-2 antibody pairs (b). The LOD values were calculated to be 262 fM and 44.8 pg mL⁻¹, respectively. SD represents standard deviation. (c) Comparison of the detection sensitivity of the SPB platform, ordinary IFA, and enhanced IFA in the presence of a nanoplasmonic substrate. The curves were generated under the same experimental conditions (bBSA was coated by the incubation method) and a condition where the microarray printer was used for general IFA and enhanced IFA (see Materials and Methods, Supporting Information). SA was labeled with IRDye-800CW, and the degree of labeling was 2.55 ± 0.08. Refl. Diff. represents reflectance difference. (d) Microscopy images and corresponding quantitative outputs of the SPBs loaded with different proteins (concentration: 50 μg mL⁻¹). Analysis of images reveals that SARS-CoV-2 antibodies exclusively interact with peptides. (e) Calibration curves of the SPB immunoassays carried out in the presence of a secondary antibody in the peptide/SARS-CoV-2 antibody model. The diameter of the AuNPs used in this experiment was 67 nm. Scheme in (e) was created with BioRender.com. Data in all panels are shown as the mean ± standard deviation (n = 3).

Another feature of this method is that the signals produced using SPBs are stable for ≥80 days at room temperature (Figure S13). In contrast, the signals generated using commonly used techniques such as IFA, ELISA, and CLIA degraded over such time frame. Moreover, SPB immunoassays in the presence of a secondary antibody were also performed (Figure 5e). The use of a secondary antibody increases the final thickness of the specifically adsorbed protein layer and thus results in an even higher sensitivity. These results also demonstrated that increasing the molecular dimensions of the analyte was an efficient approach to further improving the sensing performance of the SPB platform. Collectively, these nanoplasmonic sensing chips could be used for multiple POCTs in hospitals, clinics, roadside triage sites, and homes. Importantly, these sensors can help achieve a low-cost method for the COVID-19 surveillance and prevalence studies via using a label-free and naked-eye readout route.

Our investigations demonstrated a sensitive and specific multiplexed assay for rapid, low-cost, high-throughput, label-free, and naked-eye detection of antibodies against SARS-CoV-2 using a sandwiched plasmonic nanostructure. As discussed above, compared with conventional plasmonic sensors, which place considerable emphasis on refractive index changes on the surface of SPR materials, the SPB platform adopts a revolutionary thickness-sensing mechanism. Thus, these assays provide extremely high sensitivity and specificity (100% and ~99%), largely exceeding those values of commercially available SARS-CoV-2 antibody test kits.^15,17,23,45 Figure S14 shows the sensitivity and specificity comparison between the SPB and several reported biosensors (most of them are based on labeled quantitative techniques) available to date. The SPB assay also provides a short assay time of 20−40 min, whereas widely used quantitative techniques typically take hours to perform (ELISA, >1.5 h; sandwich ELISA, several hours).^25,46 Notably, the facile transfer of the AuNP monolayer can be completed within minutes, and this makes SPB a ready-to-use tool that can be used for efficient sensing (Figure S15). We also established a brief assay procedure of a SPB kit, demonstrating its facile operation that is possibly performed in resource-limited settings (Figure S16).

Apart from addressing the current clinical needs for COVID-19 control and surveillance, we believe that this technology will facilitate multiplexed detection of diverse biomarkers using highly integrated microarray chips.⁴⁷ The results obtained from the SARS-CoV-2 antigen screening experiments revealed that the SPB transducer can replace fluorescence labels and facilitate the development of high-throughput screening technologies, such as the protein microarray technology.⁴⁸ Another feature of this method is that signals can be collected by various readout devices with optional signal processing methods for a wide array of sensing applications. As discussed above, signal processing methods directly affect the sensitivity and specificity of the SPB immunoassay. For instance, the LOD values obtained using the gray value estimation method were higher (60.2 pg mL⁻¹) than those obtained using the spectral analysis method (44.8 pg mL⁻¹) when the peptide/SARS-CoV-2 antibody model was used (Figure S17).

Finally, the density, distribution, shape, and size of the nanoparticles can theoretically affect the sensitivity of the sensor. Future in-depth studies with highly reproducible optimized nanostructures should substantially improve the effectiveness of the SPB platform in clinical settings.