ABSTRACT
With the recent global outbreaks of infectious diseases such as coronavirus disease 2019, developing a detection system capable of quickly and accurately diagnosing diseases on‐site has become a pressing need. The ability to diagnose patients in the field is crucial for the prompt isolation and treatment of infected individuals and the prevention of the spread of the disease. Our research group has recently developed a surface‐enhanced Raman scattering optofluidic system that enables rapid and accurate point‐of‐care diagnostics. This account will introduce the principle and configuration of the fluidic devices, such as lateral flow assay strips or microfluidic channels, and the portable Raman spectrometer. We will also highlight the challenges that must be addressed for using this system in clinical settings. Rapid and accurate diagnosis is critical for effective disease management and control, and developing this system can significantly improve our ability to respond to outbreaks of infectious diseases. [ FROM AUTHOR] Copyright of Bulletin of the Korean Chemical Society is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
In the macroscopic world, we can obtain some important information through the vibration of objects, that is, listening to the sound. Likewise, we can also get some information of the nanoparticles that we want to know by the means of "listening" in the microscopic world. In this review, we will introduce two sensing methods (cavity optomechanical sensing and surface-enhanced Raman scattering sensing) which can be used to detect the nanoparticles. The cavity optomechanical systems are mainly used to detect sub-gigahertz nanoparticle or cavity vibrations, while surface-enhanced Raman scattering is a well-known technique to detect molecular vibrations whose frequency generally exceeds terahertz. Therefore, the vibrational information of nanoparticles from low-frequency to high-frequency could be obtained by these two methods. The size of the viruses is at the nanoscale and we can regard it as a kind of nanoparticles. Rapid and ultrasensitive detection of the viruses is the key strategies to break the spread of the viruses in the community. Cavity optomechanical sensing enables rapid, ultrasensitive detection of nanoparticles through the interaction of light and mechanical oscillators and surface-enhanced Raman scattering is an attractive qualitatively analytical technique for chemical sensing and biomedical applications, which has been used to detect the SARS-CoV-2 infected. Hence, investigation in these two fields is of vital importance in preventing the spread of the virus from affecting human's life and health.
ABSTRACT
Although many approaches have been developed for the quick assessment of SARS-CoV-2 infection, few of them are devoted to the detection of the neutralizing antibody, which is essential for assessing the effectiveness of vaccines. Herein, we developed a tri-mode lateral flow immunoassay (LFIA) platform based on gold-silver alloy hollow nanoshells (Au-Ag HNSs) for the sensitive and accurate quantification of neutralizing antibodies. By tuning the shell-to-core ratio, the surface plasmon resonance (SPR) absorption band of the Au-Ag HNSs is located within the near infrared (NIR) region, endowing them with an excellent photothermal effect under the irradiation of optical maser at 808 nm. Further, the Raman reporter molecule 4-mercaptobenzoic acid (MBA) was immobilized on the gold-silver alloy nanoshell to obtain an enhanced SERS signal. Thus, these Au-Ag HNSs could provide colorimetric, photothermal and SERS signals, with which, tri-mode strips for SARS-CoV-2 neutralizing antibody detection were constructed by competitive immunoassay. Since these three kinds of signals could complement one another, a more accurate detection was achieved. The tri-mode LFIA achieved a quantitative detection with detection limit of 20 ng/mL. Moreover, it also successfully detected the serum samples from 98 vaccinated volunteers with 79 positive results, exhibiting great application value in neutralizing antibody detection.
Subject(s)
Antibodies, Neutralizing , COVID-19 , Immunoassay , Nanoshells , SARS-CoV-2 , Spectrum Analysis, Raman , Humans , Alloys , Antibodies, Neutralizing/immunology , Antibodies, Neutralizing/isolation & purification , Antibodies, Viral/immunology , Colorimetry/methods , COVID-19/diagnosis , COVID-19/immunology , Gold , Immunoassay/instrumentation , Immunoassay/methods , Metal Nanoparticles , SARS-CoV-2/immunology , Silver , Spectrum Analysis, Raman/methodsABSTRACT
The pandemic of COVID-19 creates an imperative need for sensitive and portable detection of SARS-CoV-2. We devised a SERS-read, CRISPR/Cas-powered nanobioassay, termed as OVER-SARS-CoV-2 (One-Vessel Enhanced RNA test on SARS-CoV-2), which enabled supersensitive, ultrafast, accurate and portable detection of SARS-CoV-2 in a single vessel in an amplification-free and anti-interference manner. The SERS nanoprobes were constructed by conjugating gold nanoparticles with Raman reporting molecular and single-stranded DNA (ssDNA) probes, whose aggregation-to-dispersion changes can be finely tuned by target-activated Cas12a though trans-cleavage of linker ssDNA. As such, the nucleic acid signals could be dexterously converted and amplified to SERS signals. By customizing an ingenious vessel, the steps of RNA reverse transcription, Cas12a trans-cleavage and SERS nanoprobes crosslinking can be integrated into a single and disposal vessel. It was proved that our proposed nanobioassay was able to detect SARS-CoV-2 as low as 200 copies/mL without any pre-amplification within 45 min. In addition, the proposed nanobioassay was confirmed by clinical swab samples and challenged for SARS-CoV-2 detection in simulated complex environmental and food samples. This work enriches the arsenal of CRISPR-based diagnostics (CRISPR-Dx) and provides a novel and robust platform for SARS-CoV-2 decentralized detection, which can be put into practice in the near future.
Subject(s)
COVID-19 , Metal Nanoparticles , Humans , SARS-CoV-2/genetics , COVID-19/diagnosis , CRISPR-Cas Systems , Gold , Biological Assay , RNA , Nucleic Acid Amplification TechniquesABSTRACT
Nanoscale plasmonic hotspots play a critical role in the enhancement of molecular Raman signals, enabling the sensitive and reliable trace analysis of biomedical molecules via surface-enhanced Raman spectroscopy (SERS). However, effective and label-free SERS diagnoses in practical fields remain challenging because of clinical samples' random adsorption and size mismatch with the nanoscale hotspots. Herein, we suggest a novel SERS strategy for interior hotspots templated with protein@Au core-shell nanostructures prepared via electrochemical one-pot Au deposition. The cytochrome c and lysates of SARS-CoV-2 (SLs) embedded in the interior hotspots were successfully functionalized to confine the electric fields and generate their optical fingerprint signals, respectively. Highly linear quantitative sensitivity was observed with the limit-of-detection value of 10-1 PFU/ mL. The feasibility of detecting the targets in a bodily fluidic environment was also confirmed using the proposed templates with SLs in human saliva and nasopharyngeal swabs. These interior hotspots templated with the target analytes are highly desirable for early and on-site SERS diagnoses of infectious diseases without any labeling processes.
ABSTRACT
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.
ABSTRACT
Non-metallic materials have emerged as a new family of active substrates for surface-enhanced Raman scattering (SERS), with unique advantages over their metal counterparts. However, owing to their inefficient interaction with the incident wavelength, the Raman enhancement achieved with non-metallic materials is considerably lower with respect to the metallic ones. Herein, we propose colourful semiconductor-based SERS substrates for the first time by utilizing a Fabry-Pérot cavity, which realize a large freedom in manipulating light. Owing to the delicate adjustment of the absorption in terms of both frequency and intensity, resonant absorption can be achieved with a variety of non-metal SERS substrates, with the sensitivity further enhanced by ≈100â times. As a typical example, by introducing a Fabry-Pérot-type substrate fabricated with SiO2 /Si, a rather low detection limit of 10-16 â M for the SARS-CoV-2S protein is achieved on SnS2 . This study provides a realistic strategy for increasing SERS sensitivity when semiconductors are employed as SERS substrates.
ABSTRACT
COVID-19 has devastated the entire world for the past couple of years. Timely and efficient detection and identification of a virus are crucial in preventing the wider virus spread. By using intelligent sensors based on Surface-Enhanced Raman Scattering (SERS), it is possible to detect and identify virus automatically. In this study, we successfully applied the XGBoost Algorithm (Supervised Machine Learning) to classify the type of the virus using the SERS sensor data. The supervised approach has a limitation when a new type of virus arises, whose shape is different from the previously known samples. To tackle this problem, we investigated the unsupervised learning approaches that can cluster the virus data into different groups without labeled data. The unsupervised approach presented in this paper is called k-Shape Clustering. This technique compares the cross-correlation between different samples and then clusters them into similar or different groups. If a subvariant of a virus emerges, it would be clustered into the existing virus groups;if a new type of virus is found, it would be clustered into a new group. Both of the approaches have shown very promising results based on extensive evaluations. © 2022 IEEE.
ABSTRACT
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.
Subject(s)
COVID-19 , Deep Learning , Humans , SARS-CoV-2/genetics , COVID-19/diagnosis , RNA, Viral/genetics , Spectrum Analysis, Raman/methods , Pandemics , NasopharynxABSTRACT
In early 2022, the number of people infected with the highly contagious mutant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), called Omicron, was increasing worldwide. Therefore, several countries approved the lateral flow assay (LFA) strip as a diagnostic method for confirming SARS-CoV-2 instead of reverse transcription-polymerase chain reaction (RT-PCR), which takes a long time to generate the results. However, owing to the limitation of detection sensitivity, commercial LFA strips have high false-negative diagnosis rates for patients with low virus concentrations. Therefore, in this study, we developed a portable surface-enhanced Raman scattering (SERS)-LFA reader based on localized surface plasmon effects to solve the sensitivity problem of the commercial LFA strip. We tested 54 clinical samples using this portable SERS-LFA reader, which generated 49 positive and 5 negative results. Out of the 49 positive results, SERS-LFA classified only 2 as false negative, while the commercial LFA classified 21 as false negative. This confirmed that the false-negative rate had significantly improved compared to that of commercial LFA strips. We believe that the proposed SERS-LFA system can be utilized as a point-of-care diagnostic system to quickly and accurately determine a virus infection that could spread significantly within a short period.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Spectrum Analysis, Raman/methods , COVID-19/diagnosis , Point-of-Care Systems , Biological AssayABSTRACT
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.
Subject(s)
Aptamers, Nucleotide , Biosensing Techniques , COVID-19 , Metal Nanoparticles , Aptamers, Nucleotide/chemistry , Biosensing Techniques/methods , COVID-19/diagnosis , DNA/chemistry , Humans , Metal Nanoparticles/chemistry , SARS-CoV-2 , Silicon Dioxide , Silver/chemistry , Spectrum Analysis, Raman/methodsABSTRACT
Aspergillus flavus and Aflatoxins in grain crops give rise to a serious threat to food security and cause huge economic losses. In particular, aflatoxin B1 has been identified as a Class I carcinogen to humans by the International Agency for Research on Cancer (IARC). Compared with conventional methods, Surface-Enhanced Raman Scattering (SERS) has paved the way for the detection of Aspergillus flavus and Aflatoxins in grain crops as it is a rapid, nondestructive, and sensitive analytical method. In this work, the rapid detection of Aspergillus flavus and quantification of Aflatoxin B1 in grain crops were performed by using a portable Raman spectrometer combined with colloidal Au nanoparticles (AuNPs). With the increase of the concentration of Aspergillus flavus spore suspension in the range of 102-108 CFU/mL, the better the combination of Aspergillus flavus spores and AuNPs, the better the enhancement effect of AuNPs solution on the Aspergillus flavus. A series of different concentrations of aflatoxin B1 methanol solution combined with AuNPs were determined based on SERS and their spectra were similar to that of solid powder. Moreover, the characteristic peak increased gradually with the increase of concentration in the range of 0.0005-0.01 mg/L and the determination limit was 0.0005 mg/L, which was verified by HPLC in ppM concentration. This rapid detection method can greatly shorten the detection time from several hours or even tens of hours to a few minutes, which can help to take effective measures to avoid causing large economic losses.
Subject(s)
Aflatoxins , Metal Nanoparticles , Aflatoxin B1 , Aflatoxins/analysis , Aspergillus flavus , Edible Grain/chemistry , Gold/pharmacology , HumansABSTRACT
The COVID-19 outbreak spreads around world, accumulated to more than 27 million confirmed cases and 800k deaths. Polymerase Chain Reaction (PCR), a gold-standard diagnostic method, were labor intensive, time-consuming and costly, which restricted its application to widespread screening. Herein, this study purposes a one-pot and non-washing method to rapidly detect virus by dual-clamped surface-enhanced Raman scattering (SERS) mechanism. COVID Antigens were captured by SERS nanoparticles and novel SERS substrate simultaneously to achieve 6 order enhancements within 20 minutes. The dual-SERS sensors have reached a detection limit of 1 ng/ml in clinical samples for recognizing nucleocapsid & Spike proteins of COVID-19, which is comparable with PCR results. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.
ABSTRACT
Since COVID-19 and flu have similar symptoms, they are difficult to distinguish without an accurate diagnosis. Therefore, it is critical to quickly and accurately determine which virus was infected and take appropriate treatments when a person has an infection. This study developed a dual-mode surface-enhanced Raman scattering (SERS)-based LFA strip that can diagnose SARS-CoV-2 and influenza A virus with high accuracy to reduce the false-negative problem of the commercial colorimetric LFA strip. Furthermore, using a single strip, it is feasible to detect SARS-CoV-2 and influenza A virus simultaneously. A clinical test was performed on 39 patient samples (28 SARS-CoV-2 positives, 6 influenza A virus positives, and 5 negatives), evaluating the clinical efficacy of the proposed dual-mode SERS-LFA strip. Our assay results for clinical samples show that the dual-mode LFA strip significantly reduced the false-negative rate for both SARS-CoV-2 and influenza A virus.
ABSTRACT
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.
Subject(s)
COVID-19 , Single-Chain Antibodies , COVID-19/diagnosis , Escherichia coli , Gold , Humans , Immunoassay , Pandemics , SARS-CoV-2 , Saliva/chemistry , Spike Glycoprotein, CoronavirusABSTRACT
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.
ABSTRACT
The SARS-CoV-2 outbreaks highlighted the need for effective, reliable, fast, easy-to-do and cheap diagnostics procedures. We pragmatically experienced that an early positive-case detection, inevitably coupled with a mass vaccination campaign, is a milestone to control the COVID-19 pandemic. Gold nanoparticles (AuNPs) can indeed play a crucial role in this context, as their physicochemical, optics and electronics properties are being extensively used in photothermal therapy (PTT), radiation therapy (RT), drug delivery and diagnostic. AuNPs can be synthesized by several approaches to obtain different sizes and shapes that can be easily functionalized with many kinds of molecules such as antibodies, proteins, probes, and lipids. In addition, AuNPs showed high biocompatibility making them useful tool in medicine field. We thus reviewed here the most relevant evidence on AuNPs as effective way to detect the presence of SARS-CoV-2 antigens. We trust future diagnostic efforts must take this 'old-fashioned' nanotechnology tool into consideration for the development and commercialization of reliable and feasible detection kits.
ABSTRACT
Surface-enhanced Raman scattering (SERS)-based assays have been recently developed to overcome the low detection sensitivity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SERS-based assays using magnetic beads in microtubes slightly improved the limit of detection (LoD) for SARS-CoV-2. However, the sensitivity and reproducibility of the method are still insufficient for reliable SARS-CoV-2 detection. In this study, we developed a SERS-based microdroplet sensor to dramatically improve the LoD and reproducibility of SARS-CoV-2 detection. Raman signals were measured for SERS nanotags in 140 droplets passing through a laser focal volume fixed at the center of the channel for 15 s. A comparison of the Raman signals of SERS nanotags measured in a microtube with those measured for multiple droplets in the microfluidic channel revealed that the LoD and coefficient of variation significantly improved from 36 to 0.22 PFU/mL and 21.2% to 1.79%, respectively. This improvement resulted from the ensemble average effects because the signals were measured for SERS nanotags in multiple droplets. Moreover, the total assay time decreased from 30 to 10 min. A clinical test was performed on patient samples to evaluate the clinical efficacy of the SERS-based microdroplet sensor. The assay results agreed well with those measured by the reverse transcription-polymerase chain reaction (RT-PCR) method. The proposed SERS-based microdroplet sensor is expected to be used as a new point-of-care diagnostic platform for quick and accurate detection of SARS-CoV-2 in the field.
ABSTRACT
The deadly novel coronavirus SARS-CoV-2 is responsible for COVID-19, which was first recognized in Wuhan, China, in December 2019. Rapid identification at primary stage of the novel coronavirus, SARS-CoV-2, is important to restrict it and prevent the pandemic. Real-time RT-PCR assays are the best diagnostic tests presently available for SARS-CoV-2 detection, which are highly sensitive, even though expensive equipment and trained technicians are necessary. Furthermore, the method has moderately long time bound. This deadly viral infection can also be detected by applying various spectroscopic techniques as spectroscopy can provide fast, precise identification and monitoring, leading to the overall understanding of its mutation rates, which will further facilitate antiviral drug development as well as vaccine development. It is an innovative and non-invasive technique for combating the spread of novel coronavirus. This review article demonstrates the application of various spectroscopic techniques to detect COVID-19 rapidly. Different spectroscopy-based detection protocols and additional development of new, novel sensors and biosensors along with diagnostic kits had been described here stressing the status of sensitive diagnostic systems to handle with the COVID-19 outbreak. Graphical abstract: Spectroscopy: A versatile sensing tool for cost-effective and rapid detection of novel Coronavirus (COVID-19).
ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution has been characterized by the emergence of sets of mutations impacting the virus characteristics, such as transmissibility and antigenicity, presumably in response to the changing immune profile of the human population. The presence of mutations in the SARS-CoV-2 virus can potentially impact therapeutic and diagnostic test performances. We design and develop here a unique set of DNA probes i.e., antisense oligonucleotides (ASOs) which can interact with genetic sequences of the virus irrespective of its ongoing mutations. The probes, developed herein, target a specific segment of the nucleocapsid phosphoprotein (N) gene of SARS-CoV-2 with high binding efficiency which do not mutate among the known variants. Further probing into the interaction profile of the ASOs reveals that the ASO-RNA hybridization remains unaltered even for a hypothetical single point mutation at the target RNA site and diminished only in case of the hypothetical double or triple point mutations. The mechanism of interaction among the ASOs and SARS-CoV-2 RNA is then explored with a combination of surface-enhanced Raman scattering (SERS) and machine learning techniques. It has been observed that the technique, described herein, could efficiently discriminate between clinically positive and negative samples with â¼100% sensitivity and â¼90% specificity up to 63 copies/mL of SARS-CoV-2 RNA concentration. Thus, this study establishes N gene targeted ASOs as the fundamental machinery to efficiently detect all the current SARS-CoV-2 variants regardless of their mutations.