A fast, ultrasensitive SERS immunoassay to detect SARS-CoV-2 in saliva

SERS-based microdevices for use as in vitro diagnostic biosensors

Advances in surface-enhanced Raman scattering (SERS) detection have helped to overcome the limitations of traditional in vitro diagnostic methods, such as fluorescence and chemiluminescence, owing to its high sensitivity and multiplex detection capability. However, for the implementation of SERS detection technology in disease diagnosis, a SERS-based assay platform capable of analyzing clinical samples is essential. Moreover, infectious diseases like COVID-19 require the development of point-of-care (POC) diagnostic technologies that can rapidly and accurately determine infection status. As an effective assay platform, SERS-based bioassays utilize SERS nanotags labeled with protein or DNA receptors on Au or Ag nanoparticles, serving as highly sensitive optical probes. Additionally, a microdevice is necessary as an interface between the target biomolecules and SERS nanotags. This review aims to introduce various microdevices developed for SERS detection, available for POC diagnostics, including LFA strips, microfluidic chips, and microarray chips. Furthermore, the article presents research findings reported in the last 20 years for the SERS-based bioassay of various diseases, such as cancer, cardiovascular diseases, and infectious diseases. Finally, the prospects of SERS bioassays are discussed concerning the integration of SERS-based microdevices and portable Raman readers into POC systems, along with the utilization of artificial intelligence technology.

Saliva-based detection of SARS-CoV-2: a bibliometric analysis of global research

Saliva has emerged as a promising noninvasive biofluid for the diagnosis of oral and systemic diseases, including viral infections. During the coronavirus disease 2019 (COVID-19) pandemic, a growing number of studies focused on saliva-based detection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Taking advantage of the WoS core collection (WoSCC) and CiteSpace, we retrieved 1021 articles related to saliva-based detection of SARS-CoV-2 and conducted a comprehensive bibliometric analysis. We analyzed countries, institutions, authors, cited authors, and cited journals to summarize their contribution and influence and analyzed keywords to explore research hotspots and trends. From 2020 to 2021, research focused on viral transmission via saliva and verification of saliva as a reliable specimen, whereas from 2021 to the present, the focus of research has switched to saliva-based biosensors for SARS-CoV-2 detection. By far, saliva has been verified as a reliable specimen for SARS-CoV-2 detection, although a standardized procedure for saliva sampling and processing is needed. Studies on saliva-based detection of SARS-CoV-2 will promote the development of saliva-based diagnostics and biosensors for viral detection. Collectively, our findings could provide valuable information to help scientists perceive the basic knowledge landscapes on saliva-based detection of SARS-CoV-2, the past and current research hotspots, and future opportunities.

Immunoassays: Analytical and Clinical Performance, Challenges, and Perspectives of SERS Detection in Comparison with Fluorescent Spectroscopic Detection

Immunoassays (IAs) with fluorescence-based detection are already well-established commercialized biosensing methods, such as enzyme-linked immunosorbent assay (ELISA) and lateral flow immunoassay (LFIA). Immunoassays with surface-enhanced Raman spectroscopy (SERS) detection have received significant attention from the research community for at least two decades, but so far they still lack a wide clinical commercial application. This review, unlike any other review that we have seen, performs a three-dimensional performance comparison of SERS IAs vs. fluorescence IAs. First, we compared the limit of detection (LOD) as a key performance parameter for 30 fluorescence and 30 SERS-based immunoassays reported in the literature. We also compared the clinical performances of a smaller number of available reports for SERS vs. fluorescence immunoassays (FIAs). We found that the median and geometric average LODs are about 1.5-2 orders of magnitude lower for SERS-based immunoassays in comparison to fluorescence-based immunoassays. For instance, the median LOD for SERS IA is 4.3 × 10-13 M, whereas for FIA, it is 1.5 × 10-11 M. However, there is no significant difference in average relative standard deviation (RSD)-both are about 5-6%. The analysis of sensitivity, selectivity, and accuracy reported for a limited number of the published clinical studies with SERS IA and FIA demonstrates an advantage of SERS IA over FIA, at least in terms of the median value for all three of those parameters. We discussed common and specific challenges to the performances of both SERS IA and FIA, while proposing some solutions to mitigate those challenges for both techniques. These challenges include non-specific protein binding, non-specific interactions in the immunoassays, sometimes insufficient reproducibility, relatively long assay times, photobleaching, etc. Overall, this review may be useful for a large number of researchers who would like to use immunoassays, but particularly for those who would like to make improvements and move forward in both SERS-based IAs and fluorescence-based IAs.

Simultaneous and sensitive detection of SARS-CoV-2 proteins spike and nucleocapsid based on long-range SERS biosensor

BACKGROUND

Early diagnosis of SARS-CoV-2 infection is still critical to control COVID-19 outbreak. Traditional polymerase chain reaction, enzyme-linked immunosorbent assay or lateral flow immunoassay performed poorly on detection times, sample preparation process and accuracy. Surface-enhanced Raman scattering (SERS)-based detection has emerged as a powerful analytical technique, which overcomes the above limitations. However, due to the near-field effect of traditional substrate, it is difficult to monitor the binding event of aptamers with proteins. It is obvious that a novel SERS substrate thatsupportedextended and stronger electromagnetic fields was required to hold long-range effects and allow for binding event testing.

RESULTS

Driven by this challenge, we reported a long-range SERS-active substrate, which was built by inserting bowtie nanoaperture arrays in a refractive-index-symmetric environment and Au mirror surfaces, for SARS-CoV-2 protein binding event detection. Then, a double-π structure aptasensor was simply designed through the hybridization of spike (S) and nucleocapsid (N) proteins aptamers, and a corresponding complementary strand. This kind of double-π structure would dissociate when targets proteins S and N existed and led to the SERS responses decreased, which established the detection basis of our system. What's more, due to two Raman labels were involved, both proteins S and N can be sensed simultaneously. Our proposed method showed improved sensitivity with a low limit of detection for multiplex detection (1.6 × 10-16 g/mL for protein S and 1.0 × 10-16 g/mL for protein N) over a wide concentration range.

SIGNIFICANCE

This represents the first long-range SERS apatasensor platform for detection of S and N proteins simultaneously. Our method showed high sensitivity, selectivity, reproducibility, stability and remarkable recoveries in human in saliva and serum samples, which is particularly important for the early diagnostics of COVID as well as for future unknown coronavirus.

Rapid classification of SARS-CoV-2 variant strains using machine learning-based label-free SERS strategy

The spread of COVID-19 over the past three years is largely due to the continuous mutation of the virus, which has significantly impeded global efforts to prevent and control this epidemic. Specifically, mutations in the amino acid sequence of the surface spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have directly impacted its biological functions, leading to enhanced transmission and triggering an immune escape effect. Therefore, prompt identification of these mutations is crucial for formulating targeted treatment plans and implementing precise prevention and control measures. In this study, the label-free surface-enhanced Raman scattering (SERS) technology combined with machine learning (ML) algorithms provide a potential solution for accurate identification of SARS-CoV-2 variants. We establish a SERS spectral database of SARS-CoV-2 variants and demonstrate that a diagnostic classifier using a logistic regression (LR) algorithm can provide accurate results within 10 min. Our classifier achieves 100% accuracy for Beta (B.1.351/501Y.V2), Delta (B.1.617), Wuhan (COVID-19) and Omicron (BA.1) variants. In addition, our method achieves 100% accuracy in blind tests of positive and negative human nasal swabs based on the LR model. This method enables detection and classification of variants in complex biological samples. Therefore, ML-based SERS technology is expected to accurately discriminate various SARS-CoV-2 variants and may be used for rapid diagnosis and therapeutic decision-making.

Recent advances in SERS-based immunochromatographic assay for pathogenic microorganism diagnosis: A review

Infectious diseases caused by bacteria, viruses, fungi, and other pathogenic microorganisms are among the most harmful public health problems in the world, causing tens of millions of deaths and incalculable economic losses every year. The establishment of rapid, simple, and highly sensitive diagnostic methods for pathogenic microorganisms is important for the prevention and control of infectious diseases, guidance of timely treatment, and the reduction of public safety risks. Lateral flow immunoassay (LFA) based on the colorimetric signal of colloidal gold is the most popular point-of-care testing technology at present, but it is limited by poor sensitivity and low throughput and hardly meets the needs of the highly sensitive screening of pathogenic microorganisms. In recent years, the combination of surface-enhanced Raman scattering (SERS) and LFA technology has developed into a novel analytical platform with high sensitivity and multiple detection capabilities and has shown great advantages in the detection of pathogenic microorganisms and infectious diseases. This review summarizes the working principle, design ideas, and application of the existing SERS-based LFA methods in pathogenic microorganism detection and further introduces the effect of new technologies such as Raman signal encoding, magnetic enrichment, novel membrane nanotags, and integrated Raman reading equipment on the performance of SERS-LFA. Finally, the main challenges and the future direction of development in this field of SERS-LFA are discussed.

An Investigation on the Use of Au@SiO2@Au Nanomatryoshkas as Gap-Enhanced Raman Tags

Gap-enhanced Raman tags are a new type of optical probe that have wide applications in sensing and detection. A gap-enhanced Raman tag is prepared by embedding Raman molecules inside a gap between two plasmonic metals such as an Au core and Au shell. Even though placing Raman molecules beneath an Au shell seems counter-intuitive, it has been shown that such systems produce a stronger surface-enhanced Raman scattering response due to the strong electric field inside the gap. While the theoretical support of the stronger electric field inside the gap was provided in the literature, a comprehensive understanding of how the electric field inside the gap compares with that of the outer surface of the particle was not readily available. We investigated Au@SiO2@Au nanoparticles with diameters ranging from 35 nm to 70 nm with varying shell (2.5-10 nm) and gap (2.5-15 nm) thicknesses and obtained both far-field and near-field spectra. The extinction spectra from these particles always have two peaks. The low-energy peak redshifts with the decreasing shell thickness. However, when the gap thickness decreases, the low-energy peaks first blueshift and then redshift, producing a C-shape in the peak position. For every system we investigated, the near-field enhancement spectra were stronger inside the gap than on the outer surface of the nanoparticle. We find that a thin shell combined with a thin gap will produce the greatest near-field enhancement inside the gap. Our work fills the knowledge gap between the exciting potential applications of gap-enhanced Raman tags and the fundamental knowledge of enhancement provided by the gap.

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.

Detection and analysis of rotavirus in clinical stool samples using silver nanoparticle functionalized paper as SERS substrate

Among the different analytical techniques, surface-enhanced Raman scattering (SERS) approach is a widely used technique for the detection and analysis of various chemicals and biological samples. Present study reports a low-cost, sensitive SERS substrate that has an ability to detect rotavirus in clinical stool samples. The proposed SERS substrate has been fabricated through drop-casting of silver nanoparticles (AgNPs) on a printing-grade paper. Rotavirus particles were extracted from clinical stool samples. The presence of rotavirus antigen in stool samples was confirmed using enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), and sequencing. The characteristic Raman peaks of rotavirus (RV) particles in solution were found to be significantly enhanced when Raman signals were recorded from the paper-based SERS substrates. Using the proposed SERS substrate, rotavirus samples with concentration as low as 1% could be reliably recorded by the Raman spectrometer. The paper SERS substrate reported herein is an extremely cost-efficient platform and may find applications in other research and clinical laboratories as well.

Diagnostics and analysis of SARS-CoV-2: current status, recent advances, challenges and perspectives

The disastrous spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has induced severe public healthcare issues and weakened the global economy significantly. Although SARS-CoV-2 infection is not as fatal as the initial outbreak, many infected victims suffer from long COVID. Therefore, rapid and large-scale testing is critical in managing patients and alleviating its transmission. Herein, we review the recent advances in techniques to detect SARS-CoV-2. The sensing principles are detailed together with their application domains and analytical performances. In addition, the advantages and limits of each method are discussed and analyzed. Besides molecular diagnostics and antigen and antibody tests, we also review neutralizing antibodies and emerging SARS-CoV-2 variants. Further, the characteristics of the mutational locations in the different variants with epidemiological features are summarized. Finally, the challenges and possible strategies are prospected to develop new assays to meet different diagnostic needs. Thus, this comprehensive and systematic review of SARS-CoV-2 detection technologies may provide insightful guidance and direction for developing tools for the diagnosis and analysis of SARS-CoV-2 to support public healthcare and effective long-term pandemic management and control.

Updates on the Biofunctionalization of Gold Nanoparticles for the Rapid and Sensitive Multiplatform Diagnosis of SARS-CoV-2 Virus and Its Proteins: From Computational Models to Validation in Human Samples

Since the outbreak of the pandemic respiratory virus SARS-CoV-2 (COVID-19), academic communities and governments/private companies have used several detection techniques based on gold nanoparticles (AuNPs). In this emergency context, colloidal AuNPs are highly valuable easy-to-synthesize biocompatible materials that can be used for different functionalization strategies and rapid viral immunodiagnosis. In this review, the latest multidisciplinary developments in the bioconjugation of AuNPs for the detection of SARS-CoV-2 virus and its proteins in (spiked) real samples are discussed for the first time, with reference to the optimal parameters provided by three approaches: one theoretical, via computational prediction, and two experimental, using dry and wet chemistry based on single/multistep protocols. Overall, to achieve high specificity and low detection limits for the target viral biomolecules, optimal running buffers for bioreagent dilutions and nanostructure washes should be validated before conducting optical, electrochemical, and acoustic biosensing investigations. Indeed, there is plenty of room for improvement in using gold nanomaterials as stable platforms for ultrasensitive and simultaneous "in vitro" detection by the untrained public of the whole SARS-CoV-2 virus, its proteins, and specific developed IgA/IgM/IgG antibodies (Ab) in bodily fluids. Hence, the lateral flow assay (LFA) approach is a quick and judicious solution to combating the pandemic. In this context, the author classifies LFAs according to four generations to guide readers in the future development of multifunctional biosensing platforms. Undoubtedly, the LFA kit market will continue to improve, adapting researchers' multidetection platforms for smartphones with easy-to-analyze results, and establishing user-friendly tools for more effective preventive and medical treatments.

Can DFT Calculations Provide Useful Information for SERS Applications?

Density functional theory (DFT) calculations allow us to reproduce the SERS (surface-enhanced Raman scattering) spectra of molecules adsorbed on nanostructured metal surfaces and extract the most information this spectroscopy is potentially able to provide. The latter point mainly concerns the anchoring mechanism and the bond strength between molecule and metal as well as the structural and electronic modifications of the adsorbed molecule. These findings are of fundamental importance for the application of this spectroscopic technique. This review presents and discusses some SERS-DFT studies carried out in Italy as a collaboration between the universities of Modena and Reggio-Emilia and of Florence, giving an overview of the information that we can extract with a combination of experimental SERS spectra and DFT modeling. In addition, a selection of the most recent studies and advancements on the DFT approach to SERS spectroscopy is reported with commentary.

Isolation of SARS-CoV-2-blocking recombinant antibody fragments and characterisation of their binding to variant spike proteins

COVID-19 is a severe acute respiratory disease caused by SARS-CoV-2. From its initial appearance in Wuhan, China in 2019, it developed rapidly into a global pandemic. In addition to vaccines, therapeutic antibodies play an important role in immediately treating susceptible individuals to lessen severity of the disease. In this study, phage display technology was utilised to isolate human scFv antibody fragments that bind the receptor-binding domain (RBD) of SARS-CoV-2 Wuhan-Hu-1 spike protein. Of eight RBD-binding scFvs isolated, two inhibited interaction of RBD with ACE2 protein on VeroE6 cells. Both scFvs also exhibited binding to SARS-CoV-2 Delta variant spike protein but not to Omicron variant spike protein in a Raman spectroscopy immunotest. The study demonstrates the potential of recombinant antibody approaches to rapidly isolate antibody moieties with virus neutralisation potential.