Machine Learning-Driven SERS Nanoendoscopy and Optophysiology.

A frontier of analytical sciences is centered on the continuous measurement of molecules in or near cells, tissues, or organs, within the biological context in situ, where the molecular-level information is indicative of health status, therapeutic efficacy, and fundamental biochemical function of the host. Following the completion of the Human Genome Project, current research aims to link genes to functions of an organism and investigate how the environment modulates functional properties of organisms. New analytical methods have been developed to detect chemical changes with high spatial and temporal resolution, including minimally invasive surface-enhanced Raman scattering (SERS) nanofibers using the principles of endoscopy (SERS nanoendoscopy) or optical physiology (SERS optophysiology). Given the large spectral data sets generated from these experiments, SERS nanoendoscopy and optophysiology benefit from advances in data science and machine learning to extract chemical information from complex vibrational spectra measured by SERS. This review highlights new opportunities for intracellular, extracellular, and in vivo chemical measurements arising from the combination of SERS nanosensing and machine learning.

A portable surface plasmon resonance (SPR) sensor for the detection of immunoglobulin A in plasma.

BACKGROUND: A life-threatening anaphylactic shock can occur if a patient with undiagnosed immunoglobulin A (IgA) deficiency (i.e., IgA levels <500 ng/mL) receives IgA-containing blood, hence the need for a rapid, point-of-care (POC) method for IgA deficiency screening. Enzyme-linked immunosorbent assay (ELISA) is routinely used to detect IgA, but this method requires trained specialists and ≥24 h to obtain a result. We developed a surface plasmon resonance (SPR)-based protocol to identify IgA-deficient patients or donors within 1 h. MATERIALS AND METHODS: The SPR sensor relies on the detection of IgAs captured by primary antibodies adsorbed on the SPR chip and quantified with secondary antibodies. The sensor was calibrated from 0 to 2000 ng/mL in buffer, IgA-depleted human serum, and plasma samples from IgA-deficient individuals. A critical concentration of 500 ng/mL was set for IgA deficiency. The optimized sensor was then tested on eight plasma samples with known IgA status (determined by ELISA), including five with IgA deficiency and three with normal IgA levels. RESULTS: The limit of detection was estimated at 30 ng/mL in buffer and 400 ng/mL in diluted plasma. The results obtained fully agreed with ELISA among the eight plasma samples tested. The protocol distinguished IgA-deficient from normal samples, even for samples with an IgA concentration closer to critical concentration. DISCUSSION: In conclusion, we developed a reliable POC assay for the quantification of IgA in plasma. This test may permit POC testing at blood drives and centralized centers to maintain reserves of IgA-deficient blood and in-hospital testing of blood recipients.

Influence of bovine and human serum albumin on the binding kinetics of biomolecular interactions.

Bovine serum albumin (BSA) containing buffers are the standard blocking buffer in biosensing, yet human serum is the intended application for most clinical sensors. However, the effect of human serum albumin (HSA) on binding assays remains underexplored. A simple and well-studied assay (human IgG/goat anti-human IgG) was investigated with a surface plasmon resonance (SPR) sensor to address this fundamental question in sensing. Calibrations were performed with buffers containing various concentrations of bovine or human serum albumin, as well as full and diluted bovine or IgG-depleted human serum. It was found that HSA or human serum, but not BSA or bovine serum, significantly affected the SPR shift and binding constants of the assay. Interestingly, large differences were also observed depending on whether the animal or human antibody was immobilized on the SPR chip for detection, highlighting that matrix protein/analyte/receptor interactions play a significant role in the response. We find that the interaction of soluble HSA with human IgG interferes with the recognition region, affecting the binding constant, and thus results obtained in BSA are not necessarily applicable to clinical samples or in vivo conditions. We also clearly demonstrate why a minimum dilution of 1 : 10 is often required in SPR assays to remove most background effects. Taken together, these results show that: (1) BSA does not affect the binding constant between antibodies and thus serves its purpose well when only surface blocking is intended, (2) HSA is an adequate surrogate for human serum in assay optimization, and (3) blocking buffers should be prepared with HSA in the optimization steps of assays to be translated to human blood or serum.

Optoplasmonic Effects in Highly Curved Surfaces for Catalysis, Photothermal Heating, and SERS.

Surface curvature can be used to focus light and alter optical processes. Here, we show that curved surfaces (spheres, cylinders, and cones) with a radius of around 5 µm lead to maximal optoplasmonic properties including surface-enhanced Raman scattering (SERS), photocatalysis, and photothermal processes. Glass microspheres, microfibers, pulled fibers, and control flat substrates were functionalized with well-dispersed and dense arrays of 45 nm Au NP using polystyrene-block-poly-4-vinylpyridine (PS-b-P4VP) and chemically modified with 4-mercaptobenzoic acid (4-MBA, SERS reporter), 4-nitrobenzenethiol (4-NBT, reactive to plasmonic catalysis), or 4-fluorophenyl isocyanide (FPIC, photothermal reporter). The various curved substrates enhanced the plasmonic properties by focusing the light in a photonic nanojet and providing a directional antenna to increase the collection efficacy of SERS photons. The optoplasmonic effects led to an increase of up to 1 order of magnitude of the SERS response, up to 5 times the photocatalytic conversion of 4-NBT to 4,4'-dimercaptoazobenzene when the diameter of the curved surfaces was about 5 µm and a small increase in photothermal effects. Taken together, the results provide evidence that curvature enhances plasmonic properties and that its effect is maximal for spherical objects around a few micrometers in diameter, in agreement with a theoretical framework based on geometrical optics. These enhanced plasmonic effects and the stationary-phase-like plasmonic substrates pave the way to the next generation of sensors, plasmonic photocatalysts, and photothermal devices.

Mode-Coupling Generation Using ITO Nanodisk Arrays with Au Substrate Enabling Narrow-Band Biosensing.

Plasmonic metal nanostructures have promising applications in biosensing due to their ability to facilitate light-matter interaction. However, the damping of noble metal leads to a wide full width at half maximum (FWHM) spectrum which restricts sensing capabilities. Herein, we present a novel non-full-metal nanostructure sensor, namely indium tin oxide (ITO)-Au nanodisk arrays consisting of periodic arrays of ITO nanodisk arrays and a continuous gold substrate. A narrow-band spectral feature under normal incidence emerges in the visible region, corresponding to the mode-coupling of surface plasmon modes, which are excited by lattice resonance at metal interfaces with magnetic resonance mode. The FWHM of our proposed nanostructure is barely 14 nm, which is one fifth of that of full-metal nanodisk arrays, and effectively improves the sensing performance. Furthermore, the thickness variation of nanodisks hardly affects the sensing performance of this ITO-based nanostructure, ensuring excellent tolerance during preparation. We fabricate the sensor ship using template transfer and vacuum deposition techniques to achieve large-area and low-cost nanostructure preparation. The sensing performance is used to detect immunoglobulin G (IgG) protein molecules, promoting the widespread application of plasmonic nanostructures in label-free biomedical studies and point-of-care diagnostics. The introduction of dielectric materials effectively reduces FWHM, but sacrifices sensitivity. Therefore, utilizing structural configurations or introducing other materials to generate mode-coupling and hybridization is an effective way to provide local field enhancement and effective regulation.

Interrelated Roles of Multiple Key Structure-Directing Agents in Seed-Mediated Growth of Monodisperse and Multibranched Au Nanoparticles.

Detailed mechanistic investigations of the interrelated roles of multiple key structure-directing agents in the growth solution of Au nanoparticles (AuNPs) is required for the optimization of synthetic protocols. Here, we report a robust seed-mediated growth strategy for synthesizing multibranched NPs (MB-AuNPs) with monodispersed size distribution, and investigate the roles of Ag ions and 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid (HEPES) based on an overgrowth synthesis approach. The intertwining roles of Ag+ , surface-capping stabilizers, and reducing agents were elucidated, and used to control the morphology of MB-AuNPs. The overgrowth of MB-AuNPs involves two distinct underlying pathways, namely, directional and anisotropic growth of Au branches on specific facets of Au seeds as well as an aggregation and growth mechanism governed by HEPES. In addition to Ag ions and HEPES, morphology tunability can also be achieved by pre-modification of the Au seeds with molecular probes. Optimized probe-containing MB-AuNPs prove to be excellent surface-enhanced Raman scattering (SERS) substrates and nanozymes. Taken together, the results of this work reveal the mechanistic evolution of nanocrystal growth which should stimulate the development of new synthetic strategies, improve the capabilities of tuning the optical, catalytic, and electronic properties of NPs, and further advance their applications in biolabeling, imaging, biosensing, and therapy.

Label-Free SERS for Rapid Differentiation of SARS-CoV-2-Induced Serum Metabolic Profiles in Non-Hospitalized Adults.

COVID-19 represents a multi-system infectious disease with broad-spectrum manifestations, including changes in host metabolic processes connected to the disease pathogenesis. Understanding biochemical dysregulation patterns as a consequence of COVID-19 illness promises to be crucial for tracking disease course and clinical outcomes. Surface-enhanced Raman scattering (SERS) has attracted considerable interest in biomedical diagnostics for the sensitive detection of intrinsic profiles of unique fingerprints of serum biomolecules indicative of SARS-CoV-2 infection in a label-free format. Here, we applied label-free SERS and chemometrics for rapid interrogation of temporal metabolic dynamics in longitudinal sera of mildly infected non-hospitalized patients (n = 22), at 4 and 16 weeks post PCR-positive diagnosis, and compared them with negative controls (n = 8). SERS spectral markers revealed distinct metabolic profiles in patient sera that significantly deviated from the healthy metabolic state at the two sampling time intervals. Multivariate and univariate analyses of the spectral data identified abundance dynamics in amino acids, lipids, and protein vibrations as the key spectral features underlying the metabolic differences detected in convalescent samples and perhaps associated with patient recovery progression. A validation study performed using spontaneous Raman spectroscopy yielded spectral data results that corroborated SERS spectral findings and confirmed the detected disease-specific molecular phenotypes in clinical samples. Label-free SERS promises to be a valuable analytical technique for rapid screening of the metabolic phenotype induced by SARS-CoV-2 infection to allow appropriate healthcare intervention.

Machine learning for nanoplasmonics.

Plasmonic nanomaterials have outstanding optoelectronic properties potentially enabling the next generation of catalysts, sensors, lasers and photothermal devices. Owing to optical and electron techniques, modern nanoplasmonics research generates large datasets characterizing features across length scales. Furthermore, optimizing syntheses leading to specific nanostructures requires time-consuming multiparametric approaches. These complex datasets and trial-and-error practices make nanoplasmonics research ripe for the application of machine learning (ML) and advanced data processing methods. ML algorithms capture relationships between synthesis, structure and performance in a way that far exceeds conventional simulation and theory approaches, enabling effective performance optimization. For example, neural networks can tailor the nanostructure morphology to target desired properties, identify synthetic conditions and extract quantitative information from complex data. Here we discuss the nascent field of ML for nanoplasmonics, describe the opportunities and limitations of ML in nanoplasmonic research, and conclude that ML is potentially transformative, especially if the community curates and shares its big data.

Robustness enhancement of dynamic spectroscopic ellipsometry by compensating temperature dependency of the monolithic polarizing interferometer.

This paper describes a robust dynamic spectroscopic ellipsometer that can provide a highly accurate and reliable real-time spectroscopic polarization measurement capability for various in-line nanoscale measurement applications. The robustness of dynamic spectroscopic ellipsometry is enhanced significantly by employing a compensation channel that removes the temperature dependency of the monolithic polarizing interferometric module, and it results in highly accurate dynamic spectral ellipsometric measurements. We present how the monolithic interferometer is affected by external disturbances and show experimentally that the proposed scheme can provide a few hundreds of times long-term stability enhancement compared with a single-channel-based dynamic spectroscopic ellipsometer scheme.

Combining multilayered wrinkled polymer SERS substrates and spectral data processing for low concentration analyte detection.

A series of thermally shrinkable polymer surface-enhanced Raman scattering (SERS) substrates were prepared with bimetallic Au and Ag (oxidized or not) films and with Au nanoparticles (AuNPs) located at different places in the layered structure to evaluate the synergistic effect of different known SERS amplification methods to enhance the Raman signal for low concentration dopamine detection. A bimetallic Au and Ag layered structure improved the Raman signal by 5 and 2 times compared to the single-layered Au and Ag films. Oxidizing the Ag layer prior to deposition of Au further improved the signal by a factor of 2, while adding AuNP on wrinkled films increased another 10 times the intensity of the Raman signal. It was found that the enhancement was another 10 times stronger when using AuNPs in combination with other means of enhancement such as with a silver underlayer or surface wrinkling. Wrinkling alone only gave a few-fold increase compared to a flat film, but the combination of wrinkling with AuNPs and a silver underlayer improved the SERS intensity by more than 3 orders of magnitude, showing the synergistic effect of these enhancement methods. The optimized sensors were then tested in dynamic SERS with low concentration dopamine solutions, where the signal showed characteristics of a digital SERS response. Raman spectra preprocessing and sorting software was developed to triage the SERS-active spectra from the null spectra, to count the detection events such as the ones observed in single molecule experiments.

Assessment of the longitudinal humoral response in non-hospitalized SARS-CoV-2-positive individuals at decentralized sites: Outcomes and concordance.

Introduction: Early in the COVID-19 pandemic, reagent availability was not uniform, and infrastructure had to be urgently adapted to undertake COVID-19 surveillance. Methods: Before the validation of centralized testing, two enzyme-linked immunosorbent assays (ELISA) were established independently at two decentralized sites using different reagents and instrumentation. We compared the results of these assays to assess the longitudinal humoral response of SARS-CoV-2-positive (i.e., PCR-confirmed), non-hospitalized individuals with mild to moderate symptoms, who had contracted SARSCoV-2 prior to the appearance of variants of concern in Québec, Canada. Results: The two assays exhibited a high degree of concordance to identify seropositive individuals, thus validating the robustness of the methods. The results also confirmed that serum immunoglobulins persist ≥ 6 months post-infection among non-hospitalized adults and that the antibodies elicited by infection cross-reacted with the antigens from P.1 (Gamma) and B.1.617.2 (Delta) variants of concern. Discussion: Together, these results demonstrate that immune surveillance assays can be rapidly and reliably established when centralized testing is not available or not yet validated, allowing for robust immune surveillance.

Cross-reactivity of antibodies from non-hospitalized COVID-19 positive individuals against the native, B.1.351, B.1.617.2, and P.1 SARS-CoV-2 spike proteins.

SARS-CoV-2 variants of concern (VOCs) have emerged worldwide, with implications on the spread of the pandemic. Characterizing the cross-reactivity of antibodies against these VOCs is necessary to understand the humoral response of non-hospitalized individuals previously infected with SARS-CoV-2, a population that remains understudied. Thirty-two SARS-CoV-2-positive (PCR-confirmed) and non-hospitalized Canadian adults were enrolled 14-21 days post-diagnosis in 2020, before the emergence of the B.1.351 (also known as Beta), B.1.617.2 (Delta) and P.1 (Gamma) VOCs. Sera were collected 4 and 16 weeks post-diagnosis. Antibody levels and pseudo-neutralization of the ectodomain of SARS-CoV-2 spike protein/human ACE-2 receptor interaction were analyzed with native, B.1.351, B.1.617.2 and P.1 variant spike proteins. Despite a lower response observed for the variant spike proteins, we report evidence of a sustained humoral response against native, B.1.351, B.1.617.2 and P.1 variant spike proteins among non-hospitalized Canadian adults. Furthermore, this response inhibited the interaction between the spike proteins from the different VOCs and ACE-2 receptor for ≥ 16 weeks post-diagnosis, except for individuals aged 18-49 years who showed no inhibition of the interaction between B.1.617.1 or B.1.617.2 spike and ACE-2. Interestingly, the affinity (KD) measured between the spike proteins (native, B.1.351, B.1.617.2 and P.1) and antibodies elicited in sera of infected and vaccinated (BNT162b2 and ChAdOx1 nCoV-19) individuals was invariant. Relative to sera from vaccine-naïve (and previously infected) individuals, sera from vaccinated individuals had higher antibody levels (as measured with label-free SPR) and more efficiently inhibited the spike-ACE-2 interactions, even among individuals aged 18-49 years, showing the effectiveness of vaccination.

Cross-validation of ELISA and a portable surface plasmon resonance instrument for IgG antibody serology with SARS-CoV-2 positive individuals.

We report on the development of surface plasmon resonance (SPR) sensors and matching ELISAs for the detection of nucleocapsid and spike antibodies specific against the novel coronavirus 2019 (SARS-CoV-2) in human serum, plasma and dried blood spots (DBS). When exposed to SARS-CoV-2 or a vaccine against SARS-CoV-2, the immune system responds by expressing antibodies at levels that can be detected and monitored to identify the fraction of the population potentially immunized against SARS-CoV-2 and support efforts to deploy a vaccine strategically. A SPR sensor coated with a peptide monolayer and functionalized with various sources of SARS-CoV-2 recombinant proteins expressed in different cell lines detected human anti-SARS-CoV-2 IgG antibodies in clinical samples. Nucleocapsid expressed in different cell lines did not significantly change the sensitivity of the assays, whereas the use of a CHO cell line to express spike ectodomain led to excellent performance. This bioassay was performed on a portable SPR instrument capable of measuring 4 biological samples within 30 minutes of sample/sensor contact and the chip could be regenerated at least 9 times. Multi-site validation was then performed with in-house and commercial ELISA, which revealed excellent cross-correlations with Pearson's coefficients exceeding 0.85 in all cases, for measurements in DBS and plasma. This strategy paves the way to point-of-care and rapid testing for antibodies in the context of viral infection and vaccine efficacy monitoring.

Surface-Enhanced Raman Scattering Optophysiology Nanofibers for the Detection of Heavy Metals in Single Breast Cancer Cells.

Mercury(II) ions (Hg2+) and silver ions (Ag+) are two of the most hazardous pollutants causing serious damage to human health. Here, we constructed surface-enhanced Raman scattering (SERS)-active nanofibers covered with 4-mercaptopyridine (4-Mpy)-modified gold nanoparticles to detect Hg2+ and Ag+. Experimental evidence suggests that the observed spectral changes originate from the combined effect of (i) the coordination between the nitrogen on 4-Mpy and the metal ions and (ii) the 4-Mpy molecular orientation (from flatter to more perpendicular with respect to the metal surface). The relative intensity of a pair of characteristic Raman peaks (at ∼428 and ∼708 cm-1) was used to quantify the metal ion concentration, greatly increasing the reproducibility of the measurement compared to signal-on or signal-off detection based on a single SERS peak. The detection limit of this method for Hg2+ is lower than that for the Ag+ (5 vs 100 nM), which can be explained by the stronger interaction energy between Hg2+ and N compared to Ag+ and N, as demonstrated by density functional theory calculations. The Hg2+ and Ag+ ions can be masked by adding ethylenediaminetetraacetate and Cl-, respectively, to the Hg2+ and Ag+ samples. The good sensitivity, high reproducibility, and excellent selectivity of these nanosensors were also demonstrated. Furthermore, detection of Hg2+ in living breast cancer cells at the subcellular level is possible, thanks to the nanometric size of the herein described SERS nanosensors, allowing high spatial resolution and minimal cell damage.

Multiplexed SERS Detection of Microcystins with Aptamer-Driven Core-Satellite Assemblies.

We describe surface-enhanced Raman spectroscopy (SERS) aptasensors that can indirectly detect MC-LR and MC-RR, individually or simultaneously, in natural water and in algal culture. The sensor is constructed from nanoparticles composed of successive layers of Au core-SERS label-silver shell-gold shell (Au@label@Ag@Au NPs), functionalized on the outer Au surface by MC-LR and/or MC-RR aptamers. These NPs are immobilized on asymmetric Au nanoflowers (AuNFs) dispersed on planar silicon substrates through DNA hybridization of the aptamers and capture DNA sequences with which the AuNFs are functionalized, thereby forming core-satellite nanostructures on the substrates. This construction led to greater electromagnetic (EM) field enhancement of the Raman label-modified region, as supported by finite-difference time-domain (FDTD) simulations of the core-satellite assembly. In the presence of MC-LR and/or MC-RR, the aptamer-functionalized NPs dissociate from the AuNFs because of the stronger affinity of the aptamers with the MCs, which decreases the SERS signal, thus allowing indirect detection of the MCs. The improved SERS sensitivity significantly decreased the limit of detection (LOD) for separate MC-LR detection (0.8 pM) and for multiplex detection (1.5 pM for MC-LR and 1.3 pM for MC-RR), compared with other recently reported SERS-based methods for MC-LR detection. The aptasensors show excellent selectivity to MC-LR/MC-RR and excellent recoveries (96-105%). The use of these SERS aptasensors to monitor MC-LR production over 1 week in a culture medium of M. aeruginosa cells demonstrates the applicability of the sensors in a realistic environment.