SERS-ELISA using silica-encapsulated Au core-satellite nanotags for sensitive detection of SARS-CoV-2.

The sensitive detection of viruses is key to preventing the spread of infectious diseases. In this study, we develop a silica-encapsulated Au core-satellite (CS@SiO2) nanotag, which produces a strong and reproducible surface-enhanced Raman scattering (SERS) signal. The combination of SERS from the CS@SiO2 nanotags with enzyme-linked immunosorbent assay (ELISA) achieves a highly sensitive detection of SARS-CoV-2. The CS@SiO2 nanotag is constructed by assembling 32 nm Au nanoparticles (AuNPs) on a 75 nm AuNP. Then the core-satellite particles are encapsulated with SiO2 for facile surface modification and stability. The SERS-ELISA technique using the CS@SiO2 nanotags provides a great sensitivity, yielding a detection limit of 8.81 PFU mL-1, which is 10 times better than conventional ELISA and 100 times better than lateral flow assay strip method. SERS-ELISA is applied to 30 SARS-CoV-2 clinical samples and achieved 100% and 55% sensitivities for 15 and 9 positive samples with cycle thresholds < 30 and > 30, respectively. This new CS@SiO2-SERS-ELISA method is an innovative technique that can significantly reduce the false-negative diagnostic rate for SARS-CoV-2 and thereby contribute to overcoming the current pandemic crisis.

Rapid Detection of SARS-CoV-2 RNA in Human Nasopharyngeal Specimens Using Surface-Enhanced Raman Spectroscopy and Deep Learning Algorithms.

A rapid and cost-effective method to detect the infection of SARS-CoV-2 is fundamental to mitigating the current COVID-19 pandemic. Herein, a surface-enhanced Raman spectroscopy (SERS) sensor with a deep learning algorithm has been developed for the rapid detection of SARS-CoV-2 RNA in human nasopharyngeal swab (HNS) specimens. The SERS sensor was prepared using a silver nanorod array (AgNR) substrate by assembling DNA probes to capture SARS-CoV-2 RNA. The SERS spectra of HNS specimens were collected after RNA hybridization, and the corresponding SERS peaks were identified. The RNA detection range was determined to be 103-109 copies/mL in saline sodium citrate buffer. A recurrent neural network (RNN)-based deep learning model was developed to classify 40 positive and 120 negative specimens with an overall accuracy of 98.9%. For the blind test of 72 specimens, the RNN model gave a 97.2% accuracy prediction for positive specimens and a 100% accuracy for negative specimens. All the detections were performed in 25 min. These results suggest that the DNA-functionalized AgNR array SERS sensor combined with a deep learning algorithm could serve as a potential rapid point-of-care COVID-19 diagnostic platform.

Model of the SARS-CoV-2 Virus for Development of a DNA-Modified, Surface-Enhanced Raman Spectroscopy Sensor with a Novel Hybrid Plasmonic Platform in Sandwich Mode.

The recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has posed a great challenge for the development of ultra-fast methods for virus identification based on sensor principles. We created a structure modeling surface and size of the SARS-CoV-2 virus and used it in comparison with the standard antigen SARS-CoV-2-the receptor-binding domain (RBD) of the S-protein of the envelope of the SARS-CoV-2 virus from the Wuhan strain-for the development of detection of coronaviruses using a DNA-modified, surface-enhanced Raman scattering (SERS)-based aptasensor in sandwich mode: a primary aptamer attached to the plasmonic surface-RBD-covered Ag nanoparticle-the Cy3-labeled secondary aptamer. Fabricated novel hybrid plasmonic structures based on "Ag mirror-SiO2-nanostructured Ag" demonstrate sensitivity for the detection of investigated analytes due to the combination of localized surface plasmons in nanostructured silver surface and the gap surface plasmons in a thin dielectric layer of SiO2 between silver layers. A specific SERS signal has been obtained from SERS-active compounds with RBD-specific DNA aptamers that selectively bind to the S protein of synthetic virion (dissociation constants of DNA-aptamer complexes with protein in the range of 10 nM). The purpose of the study is to systematically analyze the combination of components in an aptamer-based sandwich system. A developed virus size simulating silver particles adsorbed on an aptamer-coated sensor provided a signal different from free RBD. The data obtained are consistent with the theory of signal amplification depending on the distance of the active compound from the amplifying surface and the nature of such a compound. The ability to detect the target virus due to specific interaction with such DNA is quantitatively controlled by the degree of the quenching SERS signal from the labeled compound. Developed indicator sandwich-type systems demonstrate high stability. Such a platform does not require special permissions to work with viruses. Therefore, our approach creates the promising basis for fostering the practical application of ultra-fast, amplification-free methods for detecting coronaviruses based on SARS-CoV-2.

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

The COVID-19 pandemic has emphasized the need for accurate, rapid, point-of-care diagnostics to control disease transmission. We have developed a simple, ultrasensitive single-particle surface-enhanced Raman spectroscopy (SERS) immunoassay to detect the SARS-CoV-2 spike protein in saliva. This assay relies on the use of single chain Fv (scFv) recombinant antibody expressed in E. coli to bind the SARS-CoV-2 spike protein. Recombinant scFv labeled with a SERS-active dye in solution is mixed with unlabeled scFv conjugated to gold-coated magnetic nanoparticles and a sample to be tested. In the presence of the SARS-CoV-2 spike protein, immunocomplexes form and concentrate the labeled scFv close to the gold surface of the nanoparticles, causing an increased SERS signal. The assay detects inactivated SARS-CoV-2 virus and spike protein in saliva at concentrations of 1.94 × 103 genomes mL-1 and 4.7 fg mL-1, respectively, making this direct detection antigen test only 2-3 times less sensitive than some qRT-PCR tests. All tested SARS-CoV-2 spike proteins, including those from alpha, beta, gamma, delta, and omicron variants, were detected without recognition of the closely related SARS and MERS spike proteins. This 30 min, no-wash assay requires only mixing, a magnetic separation step, and signal measurements using a hand-held, battery-powered Raman spectrometer, making this assay ideal for ultrasensitive detection of the SARS-CoV-2 virus at the point-of-care.

Innovative Application of SERS in Food Quality and Safety: A Brief Review of Recent Trends.

Innovative application of surface-enhanced Raman scattering (SERS) for rapid and nondestructive analyses has been gaining increasing attention for food safety and quality. SERS is based on inelastic scattering enhancement from molecules located near nanostructured metallic surfaces and has many advantages, including ultrasensitive detection and simple protocols. Current SERS-based quality analysis contains composition and structural information that can be used to establish an electronic file of the food samples for subsequent reference and traceability. SERS is a promising technique for the detection of chemical, biological, and harmful metal contaminants, as well as for food poisoning, and allergen identification using label-free or label-based methods, based on metals and semiconductors as substrates. Recognition elements, including immunosensors, aptasensors, or molecularly imprinted polymers, can be linked to SERS tags to specifically identify targeted contaminants and perform authenticity analysis. Herein, we highlight recent studies on SERS-based quality and safety analysis for different foods categories spanning the whole food chain, 'from farm to table' and processing, genetically modified food, and novel foods. Moreover, SERS detection is a potential tool that ensures food safety in an easy, rapid, reliable, and nondestructive manner during the COVID-19 pandemic.

Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min.

Population-wide surveillance of COVID-19 requires tests to be quick and accurate to minimize community transmissions. The detection of breath volatile organic compounds presents a promising option for COVID-19 surveillance but is currently limited by bulky instrumentation and inflexible analysis protocol. Here, we design a hand-held surface-enhanced Raman scattering-based breathalyzer to identify COVID-19 infected individuals in under 5 min, achieving >95% sensitivity and specificity across 501 participants regardless of their displayed symptoms. Our SERS-based breathalyzer harnesses key variations in vibrational fingerprints arising from interactions between breath metabolites and multiple molecular receptors to establish a robust partial least-squares discriminant analysis model for high throughput classifications. Crucially, spectral regions influencing classification show strong corroboration with reported potential COVID-19 breath biomarkers, both through experiment and in silico. Our strategy strives to spur the development of next-generation, noninvasive human breath diagnostic toolkits tailored for mass screening purposes.

SERS-based lateral flow immunoassay for sensitive and simultaneous detection of anti-SARS-CoV-2 IgM and IgG antibodies by using gap-enhanced Raman nanotags.

The lateral flow immunoassay (LFIA) has played a crucial role in early diagnosis during the current COVID-19 pandemic owing to its simplicity, speed and affordability for coronavirus antibody detection. However, the sensitivity of the commercially available LFIAs needs to be improved to better prevent the spread of the infection. Here, we developed an ultra-sensitive surface-enhanced Raman scattering-based lateral flow immunoassay (SERS-based LFIA) strip for simultaneous detection of anti-SARS-CoV-2 IgM and IgG by using gap-enhanced Raman nanotags (GERTs). The GERTs with a 1 nm gap between the core and shell were used to produce the "hot spots", which provided about 30-fold enhancement as compared to conventional nanotags. The COVID-19 recombinant antigens were conjugated on GERTs surfaces and replaced the traditional colloidal gold for the Raman sensitive detection of human IgM and IgG. The LODs of IgM and IgG were found to be 1 ng/mL and 0.1 ng/mL (about 100 times decrease was observed as compared to commercially available LFIA strips), respectively. Moreover, under the condition of common nano-surface antigen, precise SERS signals proved the unreliability of quantitation because of the interference effect of IgM on IgG.

Ultra-fast and onsite interrogation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in waters via surface enhanced Raman scattering (SERS).

The outbreak of coronavirus infectious disease-2019 (COVID-19) pneumonia challenges the rapid interrogation of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in human and environmental samples. In this study, we developed an assay using surface enhanced Raman scattering (SERS) coupled with multivariate analysis to detect SARS-CoV-2 in an ultra-fast manner without any pretreatment (e.g., RNA extraction). Using silver-nanorod SERS array functionalized with cellular receptor angiotensin-converting enzyme 2 (ACE2), we obtained strong SERS signals of ACE2 at 1032, 1051, 1089, 1189, 1447 and 1527 cm-1. The recognition and binding of receptor binding domain (RBD) of SARS-CoV-2 spike protein on SERS assay significantly quenched the spectral intensities of most peaks and exhibited a shift from 1189 to 1182 cm-1. On-site tests on 23 water samples with a portable Raman spectrometer proved its accuracy and easy-operation for spot detection of SARS-CoV-2 to evaluate disinfection performance, explore viral survival in environmental media, assess viral decay in wastewater treatment plant and track SARS-CoV-2 in pipe network. Our findings raise a state-of-the-art spectroscopic tool to screen and interrogate viruses with RBD for human cell entry, proving its feasibility and potential as an ultra-fast detection tool for wastewater-based epidemiology.

Recent advances in sensitive surface-enhanced Raman scattering-based lateral flow assay platforms for point-of-care diagnostics of infectious diseases.

This review reports the recent advances in surface-enhanced Raman scattering (SERS)-based lateral flow assay (LFA) platforms for the diagnosis of infectious diseases. As observed through the recent infection outbreaks of COVID-19 worldwide, a timely diagnosis of the disease is critical for preventing the spread of a disease and to ensure epidemic preparedness. In this regard, an innovative point-of-care diagnostic method is essential. Recently, SERS-based assay platforms have received increasing attention in medical communities owing to their high sensitivity and multiplex detection capability. In contrast, LFAs provide a user-friendly and easily accessible sensing platform. Thus, the combination of LFAs with a SERS detection system provides a new diagnostic modality for accurate and rapid diagnoses of infectious diseases. In this context, we briefly discuss the recent application of LFA platforms for the POC diagnosis of SARS-CoV-2. Thereafter, we focus on the recent advances in SERS-based LFA platforms for the early diagnosis of infectious diseases and their applicability for the rapid diagnosis of SARS-CoV-2. Finally, the key issues that need to be addressed to accelerate the clinical translation of SERS-based LFA platforms from the research laboratory to the bedside are discussed.