A Dual-Modal Single-Antibody Plasmonic Spectro-Immunoassay for Detection of Small Molecules

Abstract

Small molecules play a pivotal role in regulating physiological processes and serve as biomarkers to uncover pathological conditions and effects of therapeutic treatments. However, it remains a significant challenge to detect small molecules given the size as compared to macromolecules. Recently, the newly emerging plasmonic immunoassays based on surface-enhanced Raman scattering (SERS) offer great promise to deliver extraordinary sensitivity. Nevertheless, they are limited by the intrinsic SERS intensity fluctuations associated with the SERS uncertainty principle. The single transducer that relies on the intensity change is also prone to false signals. Additionally, the prevailing sandwich immunoassay format proves less effective towards detecting small molecules. To circumvent these critical issues, herein, we developed a dual-modal single-antibody approach that synergized both the intensity and shift of peak-based immunoassay with Raman enhancement, coined as the INSPIRE assay, for small molecules detection. With two independent transduction mechanisms, it allows better prediction of analyte concentration and attenuation of signal artifacts, providing a new and robust strategy for molecular analysis. With proof-of-concept demonstrations for detection of free T4 and testosterone, we envision the INSPIRE assay could be expanded for a wide spectrum of applications in biomedical diagnosis, discovery of new biopharmaceuticals, food safety and environmental monitoring.

Graphical Abstract

A dual-modal single-antibody plasmonic spectro-immunoassay is developed for detection of small molecules. By harnessing both the intensity and frequency shift in surface-enhanced Raman scattering, the newly developed spectro-immunoassay allows better prediction of analyte concentration and attenuation of signal artifacts, providing a new and robust strategy for molecular analysis.

1. Introduction

Small molecules play a pivotal role in biology, physiology, and medicine. With a typical molecular weight of less than 900 Daltons, they possess a high cell and intestinal permeability. They can be used as excellent molecular probes to study physiological processes, and serve as biomarkers that can provide an important insight into the metabolic activities associated with pathological conditions and therapeutic treatments.^1–4 Identification and study of DNA- and protein-binding small molecules are also of paramount importance in genomics and the discovery of molecular medicines.^5–6 Despite their pivotal importance, it remains a significant challenge to detect small molecules given their small size (~ 1 nm), as compared to biomacromolecules.⁷ Conventionally, chromatography- and mass spectrometry-based techniques, particularly the coupled liquid chromatography–mass spectrometry (LC-MS), have been widely used for small-molecule detection.^8–14 With LC separating the analyte components and MS performing the structural identification and quantification, LC-MS features a high molecular specificity and detection sensitivity. By combining MS with laser desorption ionization (LDI), LDI-MS has also proven to be an attractive platform for profiling of biomolecules.^15–18 While efforts and great progresses have been made in miniaturization of LC-MS and optimization of the detection methods,^19–20 substantial sample pretreatment and accompanying labor costs, and lengthy experimental processes encountered in conventional mass spectrometric methods means that there remains a need for new technological platforms. Immunoassays, exemplified by the enzyme-linked immunosorbent assay (ELISA), represent a promising alternative, owing to the ease of operation, specificity, and high sensitivity towards many clinically important biomacromolecules.^21–22 Recently, the fusion of immunoassays with plasmon-enhanced spectroscopical methods, particularly surface enhanced Raman scattering (SERS), has greatly elevated the performance and utility of the newly emerging plasmonic immunoassays.^23–25 While relying on the highly specific antibody-antigen immunoreactions, the distinct plasmonic elements used, often in the form of SERS nanoprobes or a plasmonic substrate, allow the fingerprinting spectrum of Raman reporters to be enormously amplified that permit ultrasensitive analyte detection. Nevertheless, even the state-of-the art plasmonic immunoassays suffer from a few intrinsic drawbacks. First, the transduced signal based on SERS intensity fluctuates naturally owing to the SERS uncertainty principle that is associated with a variety of complicated dynamic processes at the interplay between Raman reporters and the plasmonic substrate, such as the molecular adsorption/desorption, diffusion, reorientation, and reconstruction of the metal surface.^26–28 Second, the single transducer that relies on the intensity change is prone to false signals, thus compromising the performance. Indeed, there is a strong incentive to explore innovative strategies to not only circumvent these critical issues, but also create a robust methodology for routine small-molecule analysis.

The groundbreaking observation of SERS frequency shifts of antibody-conjugated Raman reporters after capturing antigens unveiled a novel mechanism that could be exploited for designing innovative plasmonic immunoassays.²⁹ Distinct from the SERS intensity change, the SERS frequency shift originates from the structural deformation of Raman reporters as a consequence of the binding events. With a gradually increased loading of antigens, the antibody-conjugated Raman reporters undergo an increasing deformation, which is manifested as a shifted SERS frequency that correlates with the number of captured antigens. As the deformation-induced frequency shift is independent of the magnitude of SERS intensity, it can be used as an independent and potentially more robust optical transducer in complementary to the prevailing intensity-based signal readout. Despite its promise, the SERS frequency shift-based strategy has been surprisingly underappreciated, with only a handful of proof-of-concept studies that were built on this method for detection of proteins,^30–32 circulating tumor DNA,³³ and serum microRNA.^34–35 Notably, these studied analytes using the SERS frequency shift method belong to the category of macromolecules rather than small molecules, presumably because of the limited structural deformation experienced by antibody-conjugated Raman reporters after capturing small molecules. More recently, a select few studies have sought to leverage SERS frequency shifts for detection of melamine in milk³⁶, for glucose detection with 4-MBPA functioning both as a Raman reporter and capture probe³⁷, and for enantioselective discrimination of alcohols³⁸. These recent reports hint at the potential of this general technique for developing innovative biosensing strategies for detection of analytes including and beyond macromolecules.

2. Results and Discussion

In this study, we developed a dual-modal single-antibody approach that synergized both the intensity and shift of peak-based immunoassay with Raman enhancement, which we coin as the INSPIRE assay, for ultrasensitive detection of small molecules. The INSPIRE assay relied on a two-step capturing process on a plasmonic gold nanopyramid array substrate, as schematically shown in Fig. 1. We used gold nanopyramid arrays as the plasmonic substrate for proof-of-concept demonstration of the INSPIRE assay. Such a plasmonic substrate was selected because of the well-established fabrication protocol based on the nanosphere lithography and its well-understood optical properties for plasmonic biosensing that have been detailed in our previous studies.^39–43 The fabricated gold nanopyramid array featured a sharp pyramidal geometry arranged hexagonally onto the quartz substrate (Fig. 2a). The sharp vertices and edges have been found to contribute to a significant local EM field enhancement for superior SERS applications.⁴⁴ Owing to the gold surface, thiolated Raman reporters (4-mercaptobenzoic acid, or MBA) were readily covalently functionalized via the Au-S bond onto the plasmonic substrate. Further through carboxylic groups of MBA, capture antibodies were also functionalized, as schematically shown in Fig. 1b.

Figure 1. Schematics of the INSPIRE assay.

(a) Synthesis of SERS nanoprobes. (b) Functionalization and compartmentalization using 3D printing of the captured antibody-functionalized gold nanopyramid array substrate. (c) Two-step capturing process for small molecule detection. In (c), each cell was dedicated to study a specific concentration, thus allowing studying multiple analytes at once.

Figure 2. Characterizations.

(a) SEM images for the fabricated gold nanopyramid arrays. (b) TEM images of gold nanostar-based SERS nanoprobes. (c) Normalized absorption spectra for gold nanostars (dashed blue), SERS nanoprobes (solid blue), and reflection spectrum for Au nanopyramid arrays (solid red).

After surface functionalization, we utilized 3D printing to compartmentalize the plasmonic substrate into 3 × 3 cells (Fig. 1b). The photographs of representative compartmentalized substrates were shown in Fig. S1. Conventionally, the same substrate was used for studying analytes with various concentrations through repeated analytes incubation and capturing processes. However, the irreversible capturing processes through either antibody-antigen interaction, streptavidin-biotin binding, enzymatic reaction, or DNA hybridization,^45–46 imposed a considerable interfering effect on subsequent measurements owing to the so-called SERS memory effect.⁴⁷ This could compromise SERS measurements over the time due to the changing surface conditions of the substrate. The repeated incubations are also time-consuming, hindering deployment of biosensor devices for rapid analytes screening. In contrast, the adopted substrate compartmentalization strategy using 3D printing allowed us to dedicate each cell to study a particular concentration without any interference from other cells or concentrations. Therefore, the compartmentalized substrate permitted incubating multiple analytes with different concentrations (depending on the number of printed cells) at once, as shown in Fig. 1c. Indeed, given the compatibility of 3D printing and 2D plasmonic substrates, the 3D-printed substrate enabled a creative, high-throughput, scalable, efficient, and cross-interference-free optical biosensing strategy, which is not otherwise possible using the conventional detection method where analytes are repeatedly incubated and captured on the same substrate.

For the capturing process, analytes of interest with a range of concentrations were first dispensed into each cell and incubated at 37 °C for 20 min for antibody-antigen interactions. After unbound antigens were washed away, SERS nanoprobes in excess were dispensed into all the cells and incubated for another 20 min at 37 °C (Fig. 1c). The SERS nanoprobes were rationally customized in this study, as shown in Fig. 1a. The surface of the SERS nanoprobes was coated with a layer of BSA-conjugated antigens which were the same as those from the analytes, following a previously reported method.⁴⁸ Inside the SERS nanoprobe featured a gold nanostar as the core encapsulated by an IR-775 chloride dye-doped silica shell, approximately 2 ~ 15 nm in thickness, a representative transmission electron microscopy (TEM) image of which was shown in Fig. 2b. The interplay between the spiky tips and the spherical core of the gold nanostar could modulate its optical response and allow the plasmonic resonance to be tuned near 785 nm.⁴⁹ When combined with the resonant Raman molecule IR-775 chloride, the nanoprobes not only allowed an optimal SERS performance, but also transduced an independent SERS spectrum in complementary to that of MBA (Fig. S2), which could also be exploited as an independent signal transducer. Owing to the coated antigens on the surface, the SERS nanoprobes ended up being captured by the remaining unoccupied binding sites on the substrate. Resultantly, all the antibody binding sites were occupied by either the antigens from the analytes or the SERS nanoprobes (Fig. 1c).

Given the inverse relationship between the antigen concentration in the analytes and the number of remaining binding sites occupied by the SERS nanoprobes, a larger number of nanoprobes would be captured in the cells where lower concentrations of analytes were dispensed. In other words, at the lower analyte concentration end, the nanoprobes would induce a higher SERS intensity and a larger shifted SERS peak owing to a higher loading of SERS nanoprobes. By correlating the intensity change and the shift of the SERS peak with the analyte concentration, two linear regression curves based on two distinct types of signal transduction mechanisms were expected to be obtained. Such two independent transduction mechanisms, and, therefore, two independent levers at arriving at the analyte concentration, allow cross-checking the signal outputs, eliminating false signals, and enabling an accurate and robust analyte detection. The single antibody used for two-step capturing of antigens and SERS nanoprobes also helps overcome the ineffective binding of small molecules by the traditional sandwich immunoassay format.

To provide a proof-of-concept demonstration of the INSPIRE assay for detection of small molecules, we selected free T4 and testosterone as two model small-molecule analytes. They have a molecular weight of approximately 777 Daltons for the former and 228 Daltons for the latter. To perform free T4 detection, the gold nanopyramid array substrate was functionalized with free T4 antibodies via the carboxylic groups of MBA. In the meanwhile, the surface of SERS nanoprobes were conjugated with free T4 antigens. The functionalized substrate was subsequently compartmentalized into a 3 × 3 cells using 3D printing prior to the two-step incubation and capturing processes as described in Fig. 1c. For each cell, Raman mapping was performed over an area of 0.5 mm × 0.5 mm with a pixel size about 45 μm and a total of 11 × 11 spectra collected for each studied concentration. The averaged SERS spectra together with the standard deviation (indicated by the shades) for free T4 with a range of concentrations were shown in Fig. 3a. We observed that, at the lower free T4 concentration end, the detected SERS spectra displayed a higher intensity, which was attributed to a larger number of captured SERS nanoprobes. These SERS nanoprobes not only produced independent SERS peaks, dominated by the ones between 500 ~ 600 cm⁻¹ from IR-775 chloride, but also further amplified the SERS peaks at 1075 cm⁻¹ and 1580 cm⁻¹, which are respectively assigned to the C-S stretching and C-C breathing modes of MBA.²⁹ The signal amplification for MBA was believed to originate from the plasmonic coupling between the encapsulated gold nanostar and gold nanopyramid array, as will be elaborated by optical modeling below. The unique position of MBA, i.e., lying at the deep-subwavelength gap between the gold nanostar and the gold nanopyramid array, allowed itself to experience the largest possible SERS enhancement from the plasmonic coupling effects. Mapping of the SERS peak intensity at 1075 cm⁻¹ and 1580 cm⁻¹ provided a qualitative view of the correlation between the transduced SERS intensity and the corresponding logarithmic concentration of free T4 (Fig. 3b). Regression analysis established a quantitative picture of the performance of the INSPIRE assay towards free T4 detection with a R² of 0.90 and 0.88 based on the 1075 cm⁻¹ and 1580 cm⁻¹ peak, respectively (Fig. 3c). The calculated coefficient of variation also confirmed a marginal signal variation around or below 10% that is crucial and desired for translational applications.

Figure 3. Free T4 detection using the INSPIRE assay based on the SERS peak intensity change.

(a) The detected SERS spectra from the INSPIRE assay with an increase of free T4 concentrations as specified in the figure. Each spectrum was averaged from 11 × 11 spectra collected by Raman mapping over an area of 0.5 mm × 0.5 mm inside the 3D printed cell with the standard deviation depicted by the shades. Y-axis was intentionally offset for easy visualization of the spectral change. The blue-shaded 1075 cm⁻¹ and red-shaded 1580 cm⁻¹ peaks from the Raman reporter MBA were subsequently used for regression analysis. (b) Mapping of the SERS peak intensity at 1075 cm⁻¹ (upper panel) and 1580 cm⁻¹ (lower panel) with various free T4 concentrations as specified. (c) and (d) Regression analysis based on the SERS peak intensity at 1075 cm⁻¹ and 1580 cm⁻¹. (e) Calculated coefficient of variation for (c) and (d).

In addition to the SERS peak intensity, the shift of the peak at about 1580 cm⁻¹ from MBA was also exploited for free T4 detection. Although subtle, the 1580 cm⁻¹ peak would undergo a robust vibrational frequency change when subjected to an increasing deformation owing to the gradually captured SERS nanoprobes. By reconstructing using the heat map of the peak position for each Raman scanned pixel from Fig. 3b (lower panel), we also provided a quantitative view of the Raman vibrational frequency change, as shown in Fig. 4a. At the lower free T4 concentration end, because a larger number of SERS nanoprobes were captured, the 1580 cm⁻¹ peak underwent a blue shift towards the smaller wavenumber direction. The increase of free T4 concentration was accompanied by a gradual red shift towards the larger wavenumber direction, owing to the reduced number of SERS nanoprobes captured. The relative Raman vibrational frequency shift for the 1580 cm⁻¹ peak, which was defined as $\Delta \nu ={\nu }_c-{\nu }_0$, where ${\nu }_c$ is the peak position detected for free T4 with a concentration of $c$ and ${\nu }_0$ is the peak position detected for zero free T4 concentration, was found to be well correlated with the logarithmic concentration of free T4 with a R² of 0.92, as shown in Fig. 4b. Establishment of the shift of the SERS peak based regression curve provided a second and mechanistically distinct transducer for free T4 detection.

Figure 4. Free T4 detection using the INSPIRE assay based on the shift of the SERS peak at 1580 cm-1.

(a) Mapping of the wavenumber of the SERS peak at about 1580 cm⁻¹ with various free T4 concentrations as specified. (b) Regression analysis based on the shift of peak from (a). The relative shift of the peak is defined as $\Delta \nu ={\nu }_c-{\nu }_0$, where ${\nu }_c$ is the peak position detected for free T4 with a concentration of $c,{\nu }_0$ is the peak position detected for zero free T4 concentration.

The INSPIRE assay was expanded for testosterone detection, as shown in Fig. S4-S5. We observed a similar correlation between both the SERS spectral intensity and shift of the peak with the logarithmic concentration of testosterone. Together, this proved the concept of the INSPIRE assay for detection of small molecules. Further comparison with other prevailing fluorescence and SERS-based methods (as shown in Table S1) underscores the promise of our INSPIRE method for detection of small molecules.

To gain a mechanistic understanding of how the two prominent SERS peaks of MBA at 1075 cm⁻¹ and 1580 cm⁻¹ benefited from the plasmonic coupling, we performed finite-difference time-domain (FDTD) simulations to uncover the SERS enhancement factors (EF) for each individual element as well as their hybrid construct. The SERS EF was calculated by $\raisebox{1ex}{${\left|E\right|}^4$}\!\left/ \!\raisebox{-1ex}{${{|E}_0|}^4$}\right.$ at an excitation and emission wavelength of 785 nm. The Stokes shift was neglected owing to the broad plasmonic resonance bands. For a single gold nanopyramid, the calculated SERS EF at the cross section, as indicated by the dashed triangle in Fig. 5a, was shown in Fig. 5b. It displayed intense plasmonic vertex and edge modes, but its surface was barely plasmonically active. The SERS nanoprobe was modelled as a gold star@SiO₂ nanoparticle (inset in Fig. 5c). Owing to the spiky tips, the gold star@SiO₂ nanoparticle exhibited strong SERS enhancements at each tip (Fig. 5c). As in a practical setting, the SERS nanoprobes would most likely couple with the edge or surface of a gold nanopyramid rather than with its vertex, we thus calculated the gap-dependent SERS EF for a gold star@SiO₂ nanoparticle coupling with the edge and surface areas of a gold nanopyramid, as schematically shown in Fig. 5d. Given a lateral dimension of ~10 nm for an antibody, we varied the gap from 0 to 20 nm. The calculated SERS EF for a gap of 10 nm was shown in Fig. 5e. The observed large SERS EF at the studied four gaps, as indicated by A, B (edge coupling) and C, D (surface coupling) confirmed the intense plasmonic coupling between the SERS nanoprobes and the gold nanopyramid arrays. The calculated gap-dependent SERS EF was shown in Fig. 5f. A larger SERS EF was seen for a gap of 0 ~ 20 nm than the control which corresponds to the SERS EF at the indicated four points (A, B, C, D) in Fig. 5b for a single gold nanopyramid. It was noted that despite the minimal SERS EF at the surface area of a single gold nanopyramid, upon coupling with the SERS nanoprobes, a large SERS EF was activated. As the most probable coupling occurs at the surface area of a gold nanopyramid, the SERS nanoprobe-activated SERS enhancement underscores the distinct advantage of the very design of the INSPIRE assay.

Figure 5. FDTD simulations.

(a) Schematic of a single gold nanopyramid, featuring sharp vertices, edges, and planar surfaces. Enclosed by the dashed lines is the cross section where the SERS EF was displayed in (b) and (e). The SERS EF for (b) a single gold nanopyramid and (c) a single Au star@SiO₂ nanoparticle. (d) Schematic and (e) the SERS EF for gold star@SiO₂ nanoparticles coupling with the gold nanopyramid at the edge and surface areas as indicated by A, B, and C, D. The gap between a gold star@SiO₂ nanoparticle and the gold nanopyramid is 10 nm. (f) Dependence of the SERS EF on the gap size for gold star@SiO₂ nanoparticles coupling with the different areas of the gold nanopyramid as indicated by A, B, C, and D. The control is for the single gold nanopyramid as shown in (b). All the excitation wavelengths were fixed at 785 nm. The incident polarizations were indicated by the yellow double arrows. The SERS EF is calculated by $\raisebox{1ex}{${\left|E\right|}^4$}\!\left/ \!\raisebox{-1ex}{${{|E}_0|}^4$}\right.$. Log₁₀ scale of the SERS EF was used for the color bars in (b), (c), and (e), in consistent with (f).

3. Conclusion

In conclusion, we have developed an innovative INSPIRE assay for detection of small molecules based on two independent transduction mechanisms, that is the SERS peak intensity and the shift of the peak. By combining with 3D printing to compartmentalize the plasmonic substrate, the INSPIRE assay provided a high-throughput, scalable, efficient, and cross-interference-free optical biosensing strategy. The dual modalities also enabled cross-checking signal output and eliminating false signals, a prevailing problem commonly encountered in biosensing devices that rely on a single transducer. The performance of the INSPIRE assay was systematically studied and validated using free T4 and testosterone as two model small molecules. Success in detecting free T4 and testosterone demonstrates the utility of an innovative INSPIRE method for testing thyroid function and showcases its promise for future serum assays for accurate disease screening. Given its superior sensitivity, simplicity, and compatibility with existing 3D printing and nanofabrication facilities, the INPIRE assay provided an excellent approach for detection of important small molecules in complementary to existing ELISA, PCR, and mass spectrometry-based detection methods. We envision that the potential of the INSPIRE assay could be further expanded for drug discovery, antimicrobial susceptibility testing, clinical diagnostics, food and environmental safety monitoring, among others.