A Review on SERS-Based Detection of Human Virus Infections: Influenza and Coronavirus

Label-Free Detection of Virus-like Particles with Surface-Enhanced Raman Spectroscopy through Analyte Localization and Polymer-Enabled Capture

Virus detection is highly important; the last several years, since the onset of the SARS-CoV-2 pandemic, have highlighted a weakness in the field: the need for highly specialized and complex methodology for sensitive virus detection, which also manifests as sacrifices in limits of detection made to achieve simple and rapid sensing. Surface-enhanced Raman spectroscopy (SERS) has the potential to fill this gap, and two novel approaches to the development of a detection scheme are presented in this study. First, the physical entrapment of vesicular stomatitis virus (VSV) and additional virus-like particles through substrate design to localize virus analytes into SERS hotspots is explored. Then, the use of nonspecific linear polymers as affinity agents to facilitate polymer-enabled capture of the VSV for SERS detection is studied. Quantitative detection of the VSV is achieved down to 101 genetic copies per milliliter with an R2 of 0.987 using the optimized physical entrapment method. Physical entrapment of two more virus-like particles is demonstrated with electron microscopy, and distinctive SERS fingerprints are shown. This study shows great promise for the further exploration of label-free virus detection methods involving thoughtful substrate design and unconventional affinity agents.

Machine learning-driven SERS analysis platform for rapid and accurate detection of precancerous lesions of gastric cancer

A novel approach is proposed leveraging surface-enhanced Raman spectroscopy (SERS) combined with machine learning (ML) techniques, principal component analysis (PCA)-centroid displacement-based nearest neighbor (CDNN). This label-free approach can identify slight abnormalities between SERS spectra of gastric lesions at different stages, offering a promising avenue for detection and prevention of precancerous lesion of gastric cancer (PLGC). The agaric-shaped nanoarray substrate was prepared using gas-liquid interface self-assembly and reactive ion etching (RIE) technology to measure SERS spectra of serum from mice model with gastric lesions at different stages, and then a SERS spectral recognition model was trained and constructed using the PCA-CDNN algorithm. The results showed that the agaric-shaped nanoarray substrate has good uniformity, stability, cleanliness, and SERS enhancement effect. The trained PCA-CDNN model not only found the most important features of PLGC, but also achieved satisfactory classification results with accuracy, area under curve (AUC), sensitivity, and specificity up to 100%. This demonstrated the enormous potential of this analysis platform in the diagnosis of PLGC.

Potential of a deep eutectic solvent in silver nanoparticle fabrication for antibiotic residue detection

Deep eutectic solvents (DESs) have recently emerged as an alternative solvent for nanoparticle synthesis. There have been numerous advancements in the fabrication of silver nanoparticles (Ag NPs), but the potential of DESs in Ag NP synthesis was neither considered nor studied carefully. In this study, we present a novel strategy to fabricate Ag NPs in a DES (Ag NPs-DES). The DES composed of ᴅ-glucose, urea, and glycerol does not contain any anions to precipitate with Ag+ cations. Our Ag NPs-DES sample is used in a surface-enhanced Raman scattering (SERS) sensor. The two analytes for SERS quantitation are nitrofurantoin (NFT) and sulfadiazine (SDZ) whose residues can be traced down to 10-8 M. The highest enhancement factors (EFs) are competitive at 6.29 × 107 and 1.69 × 107 for NFT and SDZ, respectively. Besides, the linearity coefficients are extremely close to 1 in the range of 10-8 to 10-3 M of concentration, and the SERS substrate shows remarkable uniformity along with great selectivity. This powerful SERS performance indicates that DESs have tremendous potential in the synthesis of nanomaterials for biosensor substrate construction.

Machine Learning for COVID-19 Determination Using Surface-Enhanced Raman Spectroscopy

The rapid, low cost, and efficient detection of SARS-CoV-2 virus infection, especially in clinical samples, remains a major challenge. A promising solution to this problem is the combination of a spectroscopic technique: surface-enhanced Raman spectroscopy (SERS) with advanced chemometrics based on machine learning (ML) algorithms. In the present study, we conducted SERS investigations of saliva and nasopharyngeal swabs taken from a cohort of patients (saliva: 175; nasopharyngeal swabs: 114). Obtained SERS spectra were analyzed using a range of classifiers in which random forest (RF) achieved the best results, e.g., for saliva, the precision and recall equals 94.0% and 88.9%, respectively. The results demonstrate that even with a relatively small number of clinical samples, the combination of SERS and shallow machine learning can be used to identify SARS-CoV-2 virus in clinical practice.

Therapeutic Management with Repurposing Approaches: A Mystery During COVID-19 Outbreak

The ubiquitous pandemic that emerged due to COVID-19 affected the whole planet. People all over the globe became vulnerable to the unpredictable emergence of coronavirus. The sudden emergence of respiratory disease in coronavirus infected several patients. This affected human life drastically, from mild symptoms to severe illness, leading to mortality. COVID-19 is an exceptionally communicable disease caused by SARS-CoV-2. According to a genomic study, the viral spike RBD interactions with the host ACE2 protein from several coronavirus strains and the interaction between RBD and ACE2 highlighted the potential change in affinity from the virus causing the COVID-19 outbreak to a progenitor type of SARS-CoV-2. SARS-CoV-2, which could be the principal reservoir, is phylogenetically related to the SARS-like bat virus. Other research works reported that intermediary hosts for the transmission of viruses to humans could include cats, bats, snakes, pigs, ferrets, orangutans, and monkeys. Even with the arrival of vaccines and individuals getting vaccinated and treated with FDAapproved repurposed drugs like Remdesivir, the first and foremost steps aimed towards the possible control and minimization of community transmission of the virus include social distancing, self-realization, and self-health care. In this review paper, we discussed and summarized various approaches and methodologies adopted and proposed by researchers all over the globe to help with the management of this zoonotic outbreak by following repurposed approaches.

Aiming for Maximized and Reproducible Enhancements in the Obstacle Race of SERS

Surface enhanced Raman scattering (SERS), since its discovery in the mid-1970s, has taken on many roles in the world of analytical measurement science. From identifying known and unknown chemicals in mixtures such as pharmaceutical and environmental samples to enabling qualitative and quantitative analysis of biomolecules and biomedical disease markers (or biomarkers), furthermore expanding to tracking nanostructures in vivo for medical diagnosis and therapy. This is because SERS combines the inherent power of Raman scattering capable of molecular species identification, topped with tremendous amplification in the Raman signal intensity when the molecule of interest is positioned near plasmonic nanostructures. The higher the SERS signal amplification, the lower the limit of detection (LOD) that could be achieved for the above applications. Therefore, improving SERS sensing efficiencies is vital. The signal reproducibility and SERS enhancement factor (EF) heavily rely on plasmonic nanostructure design, which has led to tremendous work in the field. But SERS signal and EF reproducibility remain key limitations for its wider market usability. This Review will scrutinize factors, some recognized and some often overlooked, that dictate the SERS signal and are of utmost importance to enable reproducible SERS EFs. Most of the factors pertain to colloidal labeled SERS. Some critically reviewed factors include the nanostructure's surface area as a limiting factor, SERS hot-spots including optimizing the SERS EF within the hot-spot volume and positioning labels, properties of label molecules governing molecule orientation in hot-spots, and resonance effects. A better understanding of these factors will enable improved optimization and control of the experimental SERS, enabling extremely sensitive LODs without overestimating the SERS EFs. These are crucial steps toward identification and reproducible quantification in SERS sensing.

Recent Development and Applications of Stretchable SERS Substrates

Surface-enhanced Raman scattering (SERS) is a cutting-edge technique for highly sensitive analysis of chemicals and molecules. Traditional SERS-active nanostructures are constructed on rigid substrates where the nanogaps providing hot-spots of Raman signals are fixed, and sample loading is unsatisfactory due to the unconformable attachment of substrates on irregular sample surfaces. A flexible SERS substrate enables conformable sample loading and, thus, highly sensitive Raman detection but still with limited detection capabilities. Stretchable SERS substrates with flexible sample loading structures and controllable hot-spot size provide a new strategy for improving the sample loading efficiency and SERS detection sensitivity. This review summarizes and discusses recent development and applications of the newly conceptual stretchable SERS substrates. A roadmap of the development of SERS substrates is reviewed, and fabrication techniques of stretchable SERS substrates are summarized, followed by an exhibition of the applications of these stretchable SERS substrates. Finally, challenges and perspectives of the stretchable SERS substrates are presented. This review provides an overview of the development of SERS substrates and sheds light on the design, fabrication, and application of stretchable SERS systems.

Recent Advances in DNA Nanotechnology-Enabled Biosensors for Virus Detection

Virus-related infectious diseases are serious threats to humans, which makes virus detection of great importance. Traditional virus-detection methods usually suffer from low sensitivity and specificity, are time-consuming, have a high cost, etc. Recently, DNA biosensors based on DNA nanotechnology have shown great potential in virus detection. DNA nanotechnology, specifically DNA tiles and DNA aptamers, has achieved atomic precision in nanostructure construction. Exploiting the programmable nature of DNA nanostructures, researchers have developed DNA nanobiosensors that outperform traditional virus-detection methods. This paper reviews the history of DNA tiles and DNA aptamers, and it briefly describes the Baltimore classification of virology. Moreover, the advance of virus detection by using DNA nanobiosensors is discussed in detail and compared with traditional virus-detection methods. Finally, challenges faced by DNA nanobiosensors in virus detection are summarized, and a perspective on the future development of DNA nanobiosensors in virus detection is also provided.

SERS immuno- and apta-assays in biosensing/bio-detection: Performance comparison, clinical applications, challenges

Surface Enhanced Raman Spectroscopy is increasingly used as a sensitive bioanalytical tool for detection of variety of analytes ranging from viruses and bacteria to cancer biomarkers and toxins, etc. This comprehensive review describes principles of operation and compares the performance of immunoassays and aptamer assays with Surface Enhanced Raman scattering (SERS) detection to each other and to some other bioassay methods, including ELISA and fluorescence assays. Both immuno- and aptamer-based assays are categorized into assay on solid substrates, assays with magnetic nanoparticles and assays in laminar flow or/and strip assays. The best performing and recent examples of assays in each category are described in the text and illustrated in the figures. The average performance, particularly, limit of detection (LOD) for each of those methods reflected in 9 tables of the manuscript and average LODs are calculated and compared. We found out that, on average, there is some advantage in terms of LOD for SERS immunoassays (0.5 pM median LOD of 88 papers) vs SERS aptamer-based assays (1.7 pM median LOD of 51 papers). We also tabulated and analyzed the clinical performance of SERS immune and aptamer assays, where selectivity, specificity, and accuracy are reported, we summarized the best examples. We also reviewed challenges to SERS bioassay performance and real-life application, including non-specific protein binding, nanoparticle aggregation, limited nanotag stability, sometimes, relatively long time to results, etc. The proposed solutions to those challenges are also discussed in the review. Overall, this review may be interesting not only to bioanalytical chemist, but to medical and life science researchers who are interested in improvement of bioanalyte detection and diagnostics.

Dual-clamped One-Pot SERS-based Biosensors for Rapid and Sensitive Detection of SARS-CoV-2 Using Portable Raman Spectrometer

Rapid and sensitive diagnostics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of utmost importance to control the widespread coronavirus disease 2019 (COVID-19) upsurge. This study demonstrated a novel one-pot surface-enhanced Raman scattering (SERS) based immunoassay to detect SARS-CoV-2, without any washing process using a portable Raman spectrometer. The SERS-immune assay was designed using a regular digital versatile disk (DVD) substrate integrated with Raman reporter labeled silver nanoparticles for double clamping effects. The disks were molded to form nanopillar arrays and coated with silver film to enhance the sensitivity of immunoassay. The SERS platform demonstrated a limit of detection (LoD) up to 50 pg mL^-1 for SARS-CoV-2 spike protein and virus-like-particle (VLP) protein in phosphate buffer saline within a turnaround time of 20 minutes. Moreover, VLP protein spiked in untreated saliva achieved an LoD of 400 pg mL^-1, providing a cycle threshold (Ct) value range of 30-32, closer to reverse transcription-polymerase chain reaction (RT-PCR) results (35-40) and higher than the commercial rapid antigen tests, ranging from 25-28. Therefore, the developed one-pot SERS based biosensor exhibited highly sensitive and rapid detection of SARS-CoV-2, which could be a potential point-of-care platform for early and cost-effective diagnosis of the COVID-19 virus.

Simple, Fast and Convenient Magnetic Bead-Based Sample Preparation for Detecting Viruses via Raman-Spectroscopy

We introduce a magnetic bead-based sample preparation scheme for enabling the Raman spectroscopic differentiation of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2)-positive and -negative samples. The beads were functionalized with the angiotensin-converting enzyme 2 (ACE2) receptor protein, which is used as a recognition element to selectively enrich SARS-CoV-2 on the surface of the magnetic beads. The subsequent Raman measurements directly enable discriminating SARS-CoV-2-positive and -negative samples. The proposed approach is also applicable for other virus species when the specific recognition element is exchanged. A series of Raman spectra were measured on three types of samples, namely SARS-CoV-2, Influenza A H1N1 virus and a negative control. For each sample type, eight independent replicates were considered. All of the spectra are dominated by the magnetic bead substrate and no obvious differences between the sample types are apparent. In order to address the subtle differences in the spectra, we calculated different correlation coefficients, namely the Pearson coefficient and the Normalized cross correlation coefficient. By comparing the correlation with the negative control, differentiating between SARS-CoV-2 and Influenza A virus is possible. This study provides a first step towards the detection and potential classification of different viruses with the use of conventional Raman spectroscopy.

Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection

Viral infections can pose a major threat to public health by causing serious illness, leading to pandemics, and burdening healthcare systems. The global spread of such infections causes disruptions to every aspect of life including business, education, and social life. Fast and accurate diagnosis of viral infections has significant implications for saving lives, preventing the spread of the diseases, and minimizing social and economic damages. Polymerase chain reaction (PCR)-based techniques are commonly used to detect viruses in the clinic. However, PCR has several drawbacks, as highlighted during the recent COVID-19 pandemic, such as long processing times and the requirement for sophisticated laboratory instruments. Therefore, there is an urgent need for fast and accurate techniques for virus detection. For this purpose, a variety of biosensor systems are being developed to provide rapid, sensitive, and high-throughput viral diagnostic platforms, enabling quick diagnosis and efficient control of the virus's spread. Optical devices, in particular, are of great interest due to their advantages such as high sensitivity and direct readout. The current review discusses solid-phase optical sensing techniques for virus detection, including fluorescence-based sensors, surface plasmon resonance (SPR), surface-enhanced Raman scattering (SERS), optical resonators, and interferometry-based platforms. Then, we focus on an interferometric biosensor developed by our group, the single-particle interferometric reflectance imaging sensor (SP-IRIS), which has the capability to visualize single nanoparticles, to demonstrate its application for digital virus detection.

A Direct Immunoassay Based on Surface-Enhanced Spectroscopy Using AuNP/PS-b-P2VP Nanocomposites

A biosensor was developed for directly detecting human immunoglobulin G (IgG) and adenosine triphosphate (ATP) based on stable and reproducible gold nanoparticles/polystyrene-b-poly(2-vinylpyridine) (AuNP/PS-b-P2VP) nanocomposites. The substrates were functionalized with carboxylic acid groups for the covalent binding of anti-IgG and anti-ATP and the detection of IgG and ATP (1 to 150 μg/mL). SEM images of the nanocomposite show 17 ± 2 nm AuNP clusters adsorbed over a continuous porous PS-b-P2VP thin film. UV–VIS and SERS were used to characterize each step of the substrate functionalization and the specific interaction between anti-IgG and the targeted IgG analyte. The UV–VIS results show a redshift of the LSPR band as the AuNP surface was functionalized and SERS measurements showed consistent changes in the spectral features. Principal component analysis (PCA) was used to discriminate between samples before and after the affinity tests. Moreover, the designed biosensor proved to be sensitive to different concentrations of IgG with a limit-of-detection (LOD) down to 1 μg/mL. Moreover, the selectivity to IgG was confirmed using standard solutions of IgM as a control. Finally, ATP direct immunoassay (LOD = 1 μg/mL) has demonstrated that this nanocomposite platform can be used to detect different types of biomolecules after proper functionalization.

Raman spectroscopy for viral diagnostics

Raman spectroscopy offers the potential for fingerprinting biological molecules at ultra-low concentration and therefore has potential for the detection of viruses. Here we review various Raman techniques employed for the investigation of viruses. Different Raman techniques are discussed including conventional Raman spectroscopy, surface-enhanced Raman spectroscopy, Raman tweezer, tip-enhanced Raman Spectroscopy, and coherent anti-Stokes Raman scattering. Surface-enhanced Raman scattering can play an essential role in viral detection by multiplexing nanotechnology, microfluidics, and machine learning for ensuring spectral reproducibility and efficient workflow in sample processing and detection. The application of these techniques to diagnose the SARS-CoV-2 virus is also reviewed.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-023-01059-4.

SERS-based immunomagnetic bead for rapid detection of H5N1 influenza virus

The surface-enhanced Raman scattering (SERS) has recently drawn attention in the detection of respiratory viruses, but there have been few reports of the direct detection of viruses. In this study, a sandwich immunomagnetic bead SERS was established for the rapid diagnosis of the H5N1 influenza virus. The detection limit was estimated to be 5.0 × 10-6 TCID50/ml. The method showed excellent specificity with no cross-reaction with H1N1, H5N6 or H9N2. The H5N1 influenza virus detection accuracy of the SERS method was 100% in chicken embryos. The results hold great promise for the utilization of SERS as an innovative approach in the diagnosis of influenza virus.

New, fast, and precise method of COVID-19 detection in nasopharyngeal and tracheal aspirate samples combining optical spectroscopy and machine learning

Fast, precise, and low-cost diagnostic testing to identify persons infected with SARS-CoV-2 virus is pivotal to control the global pandemic of COVID-19 that began in late 2019. The gold standard method of diagnostic recommended is the RT-qPCR test. However, this method is not universally available, and is time-consuming and requires specialized personnel, as well as sophisticated laboratories. Currently, machine learning is a useful predictive tool for biomedical applications, being able to classify data from diverse nature. Relying on the artificial intelligence learning process, spectroscopic data from nasopharyngeal swab and tracheal aspirate samples can be used to leverage characteristic patterns and nuances in healthy and infected body fluids, which allows to identify infection regardless of symptoms or any other clinical or laboratorial tests. Hence, when new measurements are performed on samples of unknown status and the corresponding data is submitted to such an algorithm, it will be possible to predict whether the source individual is infected or not. This work presents a new methodology for rapid and precise label-free diagnosing of SARS-CoV-2 infection in clinical samples, which combines spectroscopic data acquisition and analysis via artificial intelligence algorithms. Our results show an accuracy of 85% for detection of SARS-CoV-2 in nasopharyngeal swab samples collected from asymptomatic patients or with mild symptoms, as well as an accuracy of 97% in tracheal aspirate samples collected from critically ill COVID-19 patients under mechanical ventilation. Moreover, the acquisition and processing of the information is fast, simple, and cheaper than traditional approaches, suggesting this methodology as a promising tool for biomedical diagnosis vis-à-vis the emerging and re-emerging viral SARS-CoV-2 variant threats in the future.

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool for applications in biology and medicine owing to its ease-of-use, non-destructive, and label-free approach. Advances in plasmonics and instrumentation have enabled the realization of SERS's full potential for the trace detection of biomolecules, disease diagnostics, and monitoring. We provide a brief review on the recent developments in the SERS technique for biosensing applications, with a particular focus on machine learning techniques used for the same. Initially, the article discusses the need for plasmonic sensors in biology and the advantage of SERS over existing techniques. In the later sections, the applications are organized as SERS-based biosensing for disease diagnosis focusing on cancer identification and respiratory diseases, including the recent SARS-CoV-2 detection. We then discuss progress in sensing microorganisms, such as bacteria, with a particular focus on plasmonic sensors for detecting biohazardous materials in view of homeland security. At the end of the article, we focus on machine learning techniques for the (a) identification, (b) classification, and (c) quantification in SERS for biology applications. The review covers the work from 2010 onwards, and the language is simplified to suit the needs of the interdisciplinary audience.

Electrochemical Synthesis, Magnetic and Optical Characterisation of FePd Dense and Mesoporous Nanowires

Dense and mesoporous FePd nanowires (NWs) with 45 to 60 at.% Pd content were successfully fabricated by template- and micelle-assisted pulsed potentiostatic electrodeposition using nanoporous anodic alumina and polycarbonate templates of varying pore sizes. An FePd electrolyte was utilized for obtaining dense NWs while a block copolymer, P-123, was added to this electrolyte as the micelle-forming surfactant to produce mesoporous NWs. The structural and magnetic properties of the NWs were investigated by electron microscopy, X-ray diffraction, and vibrating sample magnetometry. The as-prepared NWs were single phase with a face-centered cubic structure exhibiting 3.1 µm to 7.1 µm of length. Mesoporous NWs revealed a core-shell structure where the porosity was only witnessed in the internal volume of the NW while the outer surface remained non-porous. Magnetic measurements revealed that the samples displayed a soft ferromagnetic behavior that depended on the shape anisotropy and the interwire dipolar interactions. The mesoporous core and dense shell structure of the NWs were seen to be slightly affecting the magnetic properties. Moreover, mesoporous NWs performed excellently as SERS substrates for the detection of 4,4'-bipyridine, showing a low detection limit of 10^-12 M. The signal enhancement can be attributed to the mesoporous morphology as well as the close proximity of the embedded NWs being conducive to localized surface plasmon resonance.

Triangular gold nanoplates/two-dimensional nano mica platelets with a 3D lightning-rod effect as flexible nanohybrid substrates for SERS bacterial detection

Triangular gold nanoplates (TAuNPs) were prepared by a one-step rapid growth method and then reduced and stabilized on two-dimensional nano mica nanoplatelets (NMPs). We also prepared TAuNP/NMP nanohybrids with a three-dimensional lightning-rod effect by oxidative etching. The surface of the delaminated NMPs (only 1 nm thick) is highly charged and can provide a large specific surface area; thus, it can be used as a substrate for the stable growth of gold nanoplates. In addition, by controlling relevant synthesis parameters, the edge length of the TAuNPs can be easily adjusted in the range of 30-90 nm. During reduction of the TAuNPs, the cationic surfactant cetyltrimethylammonium chloride was added as a protective agent to surround the TAuNPs; consequently, the surface was positively charged, which facilitates adsorption for detecting molecules with negative charges. When nanohybrids were used in surface-enhanced Raman spectroscopy (SERS) to detect adenine molecules, the limit of detection concentration was 10^-9 M. The Raman enhancement factor was 5.7 × 10⁷, and the relative standard deviation (RSD) was 9.8%. Finally, this method was applied to the biological detection of Staphylococcus aureus, and the surface charge and hydrophilic properties of the material significantly improved the SERS signal of S. aureus. The limit of detection concentration was 10² CFU mL^-1, and the RSD was 11.2%. The TAuNP/NMP nanohybrids can provide very rapid and sensitive SERS detection of biomolecules.

Detection of A and B Influenza Viruses by Surface-Enhanced Raman Scattering Spectroscopy and Machine Learning

We demonstrate the possibility of applying surface-enhanced Raman spectroscopy (SERS) combined with machine learning technology to detect and differentiate influenza type A and B viruses in a buffer environment. The SERS spectra of the influenza viruses do not possess specific peaks that allow for their straight classification and detection. Machine learning technologies (particularly, the support vector machine method) enabled the differentiation of samples containing influenza A and B viruses using SERS with an accuracy of 93% at a concentration of 200 μg/mL. The minimum detectable concentration of the virus in the sample using the proposed approach was ~0.05 μg/mL of protein (according to the Lowry protein assay), and the detection accuracy of a sample with this pathogen concentration was 84%.

Spectroscopic methods for COVID-19 detection and early diagnosis

The coronavirus pandemic is a worldwide hazard that poses a threat to millions of individuals throughout the world. This pandemic is caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which was initially identified in Wuhan, China's Hubei provincial capital, and has since spread throughout the world. According to the World Health Organization's Weekly Epidemiological Update, there were more than 250 million documented cases of coronavirus infections globally, with five million fatalities. Early detection of coronavirus does not only reduce the spread of the virus, but it also increases the chance of curing the infection. Spectroscopic techniques have been widely used in the early detection and diagnosis of COVID-19 using Raman, Infrared, mass spectrometry and fluorescence spectroscopy. In this review, the reported spectroscopic methods for COVID-19 detection were discussed with emphasis on the practical aspects, limitations and applications.

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 CRISPR-Cas12a integrated SERS nanoplatform with chimeric DNA/RNA hairpin guide for ultrasensitive nucleic acid detection

Background: CRISPR-Cas12a has been integrated with nanomaterial-based optical techniques, such as surface-enhanced Raman scattering (SERS), to formulate a powerful amplification-free nucleic acid detection system. However, nanomaterials impose steric hindrance to limit the accessibility of CRISPR-Cas12a to the narrow gaps (SERS hot spots) among nanoparticles (NPs) for producing a significant change in signals after nucleic acid detection. Methods: To overcome this restriction, we specifically design chimeric DNA/RNA hairpins (displacers) that can be destabilized by activated CRISPR-Cas12a in the presence of target DNA, liberating excessive RNA that can disintegrate a core-satellite nanocluster via toehold-mediated strand displacement for orchestrating a promising "on-off" nucleic acid biosensor. The core-satellite nanocluster comprises a large gold nanoparticle (AuNP) core surrounded by small AuNPs with Raman tags via DNA hybridization as an ultrabright Raman reporter, and its disassembly leads to a drastic decrease of SERS intensity as signal readouts. We further introduce a magnetic core to the large AuNPs that can facilitate their separation from the disassembled nanostructures to suppress the background for improving detection sensitivity. Results: As a proof-of-concept study, our findings showed that the application of displacers was more effective in decreasing the SERS intensity of the system and attained a better limit of detection (LOD, 10 aM) than that by directly using activated CRISPR-Cas12a, with high selectivity and stability for nucleic acid detection. Introducing magnetic-responsive functionality to our system further improves the LOD to 1 aM. Conclusion: Our work not only offers a platform to sensitively and selectively probe nucleic acids without pre-amplification but also provides new insights into the design of the CRISPR-Cas12a/SERS integrated system to resolve the steric hindrance of nanomaterials for constructing biosensors.

Specific intracellular signature of SARS-CoV-2 infection using confocal Raman microscopy

SARS-CoV-2 infection remains spread worldwide and requires a better understanding of virus-host interactions. Here, we analyzed biochemical modifications due to SARS-CoV-2 infection in cells by confocal Raman microscopy. Obtained results were compared with the infection with another RNA virus, the measles virus. Our results have demonstrated a virus-specific Raman molecular signature, reflecting intracellular modification during each infection. Advanced data analysis has been used to distinguish non-infected versus infected cells for two RNA viruses. Further, classification between non-infected and SARS-CoV-2 and measles virus-infected cells yielded an accuracy of 98.9 and 97.2 respectively, with a significant increase of the essential amino-acid tryptophan in SARS-CoV-2-infected cells. These results present proof of concept for the application of Raman spectroscopy to study virus-host interaction and to identify factors that contribute to the efficient SARS-CoV-2 infection and may thus provide novel insights on viral pathogenesis, targets of therapeutic intervention and development of new COVID-19 biomarkers.

Highly Sensitive Flexible SERS-Based Sensing Platform for Detection of COVID-19

COVID-19 continues to spread and has been declared a global emergency. Individuals with current or past infection should be identified as soon as possible to prevent the spread of disease. Surface-enhanced Raman spectroscopy (SERS) is an analytical technique that has the potential to be used to detect viruses at the site of therapy. In this context, SERS is an exciting technique because it provides a fingerprint for any material. It has been used with many COVID-19 virus subtypes, including Deltacron and Omicron, a novel coronavirus. Moreover, flexible SERS substrates, due to their unique advantages of sensitivity and flexibility, have recently attracted growing research interest in real-world applications such as medicine. Reviewing the latest flexible SERS-substrate developments is crucial for the further development of quality detection platforms. This article discusses the ultra-responsive detection methods used by flexible SERS substrate. Multiplex assays that combine ultra-responsive detection methods with their unique biomarkers and/or biomarkers for secondary diseases triggered by the development of infection are critical, according to this study. In addition, we discuss how flexible SERS-substrate-based ultrasensitive detection methods could transform disease diagnosis, control, and surveillance in the future. This study is believed to help researchers design and manufacture flexible SERS substrates with higher performance and lower cost, and ultimately better understand practical applications.

Recent Advances in Inflammatory Diagnosis with Graphene Quantum Dots Enhanced SERS Detection

Inflammatory diseases are some of the most common diseases in different parts of the world. So far, most attention has been paid to the role of environmental factors in the inflammatory process. The diagnosis of inflammatory changes is an important goal for the timely diagnosis and treatment of various metastatic, autoimmune, and infectious diseases. Graphene quantum dots (GQDs) can be used for the diagnosis of inflammation due to their excellent properties, such as high biocompatibility, low toxicity, high stability, and specific surface area. Additionally, surface-enhanced Raman spectroscopy (SERS) allows the very sensitive structural detection of analytes at low concentrations by amplifying electromagnetic fields generated by the excitation of localized surface plasmons. In recent years, the use of graphene quantum dots amplified by SERS has increased for the diagnosis of inflammation. The known advantages of graphene quantum dots SERS include non-destructive analysis methods, sensitivity and specificity, and the generation of narrow spectral bands characteristic of the molecular components present, which have led to their increased application. In this article, we review recent advances in the diagnosis of inflammation using graphene quantum dots and their improved detection of SERS. In this review study, the graphene quantum dots synthesis method, bioactivation method, inflammatory biomarkers, plasma synthesis of GQDs and SERS GQD are investigated. Finally, the detection mechanisms of SERS and the detection of inflammation are presented.

Advancements in Testing Strategies for COVID-19

The SARS-CoV-2 coronavirus, also known as the disease-causing agent for COVID-19, is a virulent pathogen that may infect people and certain animals. The global spread of COVID-19 and its emerging variation necessitates the development of rapid, reliable, simple, and low-cost diagnostic tools. Many methodologies and devices have been developed for the highly sensitive, selective, cost-effective, and rapid diagnosis of COVID-19. This review organizes the diagnosis platforms into four groups: imaging, molecular-based detection, serological testing, and biosensors. Each platform's principle, advancement, utilization, and challenges for monitoring SARS-CoV-2 are discussed in detail. In addition, an overview of the impact of variants on detection, commercially available kits, and readout signal analysis has been presented. This review will expand our understanding of developing advanced diagnostic approaches to evolve into susceptible, precise, and reproducible technologies to combat any future outbreak.

How Surface-Enhanced Raman Spectroscopy Could Contribute to Medical Diagnoses

In the last decade, there has been a rapid increase in the number of surface-enhanced Raman scattering (SERS) spectroscopy applications in medical research. In this article we review some recent, and in our opinion, most interesting and promising applications of SERS spectroscopy in medical diagnostics, including those that permit multiplexing within the range important for clinical samples. We focus on the SERS-based detection of markers of various diseases (or those whose presence significantly increases the chance of developing a given disease), and on drug monitoring. We present selected examples of the SERS detection of particular fragments of DNA or RNA, or of bacteria, viruses, and disease-related proteins. We also describe a very promising and elegant ‘lab-on-chip’ approach used to carry out practical SERS measurements via a pad whose action is similar to that of a pregnancy test. The fundamental theoretical background of SERS spectroscopy, which should allow a better understanding of the operation of the sensors described, is also briefly outlined. We hope that this review article will be useful for researchers planning to enter this fascinating field.

Surface-enhanced Raman scattering-based immunoassay for severe acute respiratory syndrome coronavirus 2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected humans worldwide for over a year now. Although various tests have been developed for the detection of SARS-CoV-2, advanced sensing methods are required for the diagnosis, screening, and surveillance of coronavirus disease 2019 (COVID-19). Here, we report a surface-enhanced Raman scattering (SERS)-based immunoassay involving an antibody pair, SERS-active hollow Au nanoparticles (NPs), and magnetic beads for the detection of SARS-CoV-2. The selected antibody pair against the SARS-CoV-2 antigen, along with the magnetic beads, facilitates the accurate direct detection of the virus. The hollow Au NPs exhibit strong, reproducible SERS signals, allowing sensitive quantitative detection of SARS-CoV-2. This assay had detection limits of 2.56 fg/mL for the SARS-CoV-2 antigen and 3.4 plaque-forming units/mL for the SARS-CoV-2 lysates. Furthermore, it facilitated the identification of SARS-CoV-2 in human nasopharyngeal aspirates and diagnosis of COVID-19 within 30 min using a portable Raman device. Thus, this assay can be potentially used for the diagnosis and prevention of COVID-19.

Nucleic Acid-Based Nanobiosensor (NAB) Used for Salmonella Detection in Foods: A Systematic Review

Salmonella bacteria is a foodborne pathogen found mainly in food products causing severe symptoms in the individual, such as diarrhea, fever, and abdominal cramps after consuming the infected food, which can be fatal in some severe cases. Rapid and selective methods to detect Salmonella bacteria can prevent outbreaks when ingesting contaminated food. Nanobiosensors are a highly sensitive, simple, faster, and lower cost method for the rapid detection of Salmonella, an alternative to conventional enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) techniques. This study systematically searched and analyzed literature data related to nucleic acid-based nanobiosensors (NABs) with nanomaterials to detect Salmonella in food, retrieved from three databases, published between 2010 and 2021. We extracted data and critically analyzed the effect of nanomaterial functionalized with aptamer or DNA at the limit of detection (LOD). Among the nanomaterials, gold nanoparticles (AuNPs) were the most used nanomaterial in studies due to their unique optical properties of the metal, followed by magnetic nanoparticles (MNPs) of Fe₃O₄, copper nanoparticles (CuNPs), and also hybrid nanomaterials multiwalled carbon nanotubes (c-MWCNT/AuNP), QD/UCNP-MB (quantum dotes upconverting nanoparticle of magnetic beads), and cadmium telluride quantum dots (CdTe QDs@MNPs) showed excellent LOD values. The transducers used for detection also varied from electrochemical, fluorescent, surface-enhanced Raman spectroscopy (SERS), RAMAN spectroscopy, and mainly colorimetric due to the possibility of visualizing the detection result with the naked eye. Furthermore, we show the magnetic separation system capable of detecting the target amplification of the genetic material. Finally, we present perspectives, future research, and opportunities to use point-of-care (POC) diagnostic devices as a faster and lower cost approach for detecting Salmonella in food as they prove to be viable for resource-constrained environments such as field-based or economically limited conditions.

Magnetic-Responsive Surface-Enhanced Raman Scattering Platform with Tunable Hot Spot for Ultrasensitive Virus Nucleic Acid Detection

Surface-enhanced Raman scattering (SERS)-based biosensors are promising tools for virus nucleic acid detection. However, it remains challenging for SERS-based biosensors using a sandwiching strategy to detect long-chain nucleic acids such as nucleocapsid (N) gene of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) because the extension of the coupling distance (CD) between the two tethered metallic nanostructures weakens electric field and SERS signals. Herein, we report a magnetic-responsive substrate consisting of heteoronanostructures that controls the CD for ultrasensitive and highly selective detection of the N gene of SARS-CoV-2. Significantly, our findings show that this platform reversibly shortens the CD and enhances SERS signals with a 10-fold increase in the detection limit from 1 fM to 100 aM, compared to those without magnetic modulation. The optical simulation that emulates the CD shortening process confirms the CD-dependent electric field strength and further supports the experimental results. Our study provides new insights into designing a stimuli-responsive SERS-based platform with tunable hot spots for long-chain nucleic acid detection.

Diagnostic biosensors for coronaviruses and recent developments

Coronaviruses are well known airborne viruses that infect humans, other mammals, and birds. COVID-19 is the disease caused by the last emerging type of corona viruses; SARS-CoV-2 which resulted in the ongoing pandemic. Since its first identification, SARS-CoV-2 has spread globally causing significant morbidity and mortality. Fast and reliable diagnostic methods are crucial to control the virus outbreak. In this chapter, we summarize the traditional methods used to detect corona viruses. Various biosensors used for the detection of the virus antibodies and antigens were briefly discussed. Different biosensing approaches for the detection of corona viruses were presented with special emphasis on the reported biosensors for the detection of SARS-CoV-2. Major advancements in the biosensors area for corona viruses such as the use of cotton, magnetic nanoparticles, graphene, gold nanoparticles, and portable devices are highlighted. The challenges and future perspectives in the biosensors for the detection of corona viruses are discussed.

Carbon nanotubes in COVID-19: A critical review and prospects

The rapid spread of Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) around the world has ravaged both global health and economy. This unprecedented situation has thus garnered attention globally. This further necessitated the deployment of an effective strategy for rapid and patient-compliant identification and isolation of patients tested positive for SARS-CoV-2. Following this, several companies and institutions across the globe are striving hard to develop real-time methods, like biosensors for the detection of various viral components including antibodies, antigens, ribonucleic acid (RNA), or the whole virus. This article attempts to review the various, mechanisms, advantages and limitations of the common biosensors currently being employed for detection. Additionally, it also summarizes recent advancements in various walks of fighting COVID-19, including its prevention, diagnosis and treatment.

Recent advances in plasmonic Prussian blue-based SERS nanotags for biological application

The reliability and reproducibility of surface-enhanced Raman scattering (SERS) technology is still a great challenge in bio-related analysis. Prussian blue (PB)-based SERS tags have attracted increasing interest for improving these deficiencies due to its unique Raman band (near 2156 cm-1) in the Raman-silent region, providing zero-background bio-Raman labels without interference from endogenous biomolecules. Moreover, the stable PB shell consisting of multiple layers of CN- reporters ensure a stable and strong Raman signal output, avoiding the desorption of the Raman reporter from the plasmonic region by the competitive adsorption of the analyte. More importantly, they possess outstanding multiplexing potential in biological analysis owing to the adjustable Raman shift with unique narrow spectral widths. Despite more attention having been attracted to the structure and preparation of PB-based SERS tags for their better biological applications over the past five years, there is still a great challenge for SERS suitable for applications in the actual environment. The biological applications of PB-based SERS tags are comprehensively recounted in this minireview, mainly focusing on quantification analysis, multiple-spectral analysis and cell-imaging joint phototherapy. The prospects of PB-based SERS tags in clinical diagnosis and treatment are also discussed. This review aims to draw attention to the importance of SERS tags and provide a reference for the design and application of PB-based SERS tags in future bio-applications.

Surface-Enhanced Raman Scattering-Active Gold-Decorated Silicon Nanowire Substrates for Label-Free Detection of Bilirubin

Bilirubin (BR) is a product of hemoglobin breakdown, and its increasing levels in the blood may indicate liver disorders and lead to jaundice. Kernicterus is most dangerous in newborns when the unconjugated BR concentration can quickly rise to toxic levels, causing neurological damage and even death. The development of an accurate, fast, and sensitive sensor for BR detection will help reduce diagnostic time and ensure successful treatment. In this study, we propose a new method for creating a surface-enhanced Raman scattering (SERS)-active substrate based on gold-decorated silicon nanowires (Au@SiNWs) for sensitive label-free BR detection. Gold-assisted chemical etching of crystalline silicon wafers was used to synthesize SiNWs, the tops of which were then additionally decorated with gold nanoparticles. The low detection limit of model analyte 4-mercaptopyridine down to the concentration of 10^-8 M demonstrated the excellent sensitivity of the obtained substrates for SERS application. The theoretical full-wave electromagnetic simulations of Raman scattering in the Au@SiNW substrates showed that the major contribution to the total SERS signal comes from the analyte molecules located on the SiNW surface near the gold nanoparticles. Therefore, for efficient BR adsorption and SERS detection, the surface of the SiNWs was modified with amino groups. Label-free detection of BR using amino modified Au@SiNWs with high point-to-point, scan-to-scan, and batch-to-batch reproducibility with a detection limit of 10^-6 M has been demonstrated. Artificial urine, mimicking human urine samples, was used as the matrix to get insights into the influence of different parameters such as matrix complexity on the overall BR SERS signal. The signal stability was demonstrated for 7 days after adsorption of BR with a concentration of 5 × 10^-5 M, which is the required sensitivity for clinical applications.

Development and Characterization of Magnetic SARS-CoV-2 Peptide-Imprinted Polymers

The development of new methods for the rapid, sensitive, and selective detection of SARS-CoV-2 is a key factor in overcoming the global pandemic that we have been facing for over a year. In this work, we focused on the preparation of magnetic molecularly imprinted polymers (MMIPs) based on the self-polymerization of dopamine at the surface of magnetic nanoparticles (MNPs). Instead of using the whole SARS-CoV-2 virion as a template, a peptide of the viral spike protein, which is present at the viral surface, was innovatively used for the imprinting step. Thus, problems associated with the infectious nature of the virus along with its potential instability when used as a template and under the polymerization conditions were avoided. Dopamine was selected as a functional monomer following a rational computational screening approach that revealed not only a high binding energy of the dopamine–peptide complex but also multi-point interactions across the entire peptide template surface as opposed to other monomers with similar binding affinity. Moreover, variables affecting the imprinting efficiency including polymerization time and amount of peptide and dopamine were experimentally evaluated. Finally, the selectivity of the prepared MMIPs vs. other peptide sequences (i.e., from Zika virus) was evaluated, demonstrating that the developed MMIPs were only specific for the target SARS-CoV-2 peptide.

Plasmonic Metasurfaces Based on Pyramidal Nanoholes for High-Efficiency SERS Biosensing

An inverted pyramidal metasurface was designed, fabricated, and studied at the nanoscale level for the development of a label-free pathogen detection on a chip platform that merges nanotechnology and surface-enhanced Raman scattering (SERS). Based on the integration and synergy of these ingredients, a virus immunoassay was proposed as a relevant proof of concept for very sensitive detection of hepatitis A virus, for the first time to our best knowledge, in a very small volume (2 μL), without complex signal amplification, allowing to detect a minimal virus concentration of 13 pg/mL. The proposed work aims to develop a high-flux and high-accuracy surface-enhanced Raman spectroscopy (SERS) nanobiosensor for the detection of pathogens to provide an effective method for early and easy water monitoring, which can be fast and convenient.

Novel approaches for COVID-19 diagnosis and treatment: a nonsystematic review

Since COVID-19 pandemic has been continuously rising and spreading, several original contributions and review articles on COVID-19 started to appear in the literature. The review articles are mainly focus on the current status of the pandemic along with current status of the corona diagnosis and treatment process. Due to some disadvantages of the currently used methods, the improvement on the novel promising diagnosis and treatment methods of corona virus is very important issue. In this review, after briefly discussing the status of current diagnosis and treatment methods, we present to the scientific community, novel promising methods in the diagnosis and treatment of COVID-19. As with other novel approaches, first, the diagnosis potential of mass spectroscopy and optical spectroscopic methods such as UV/visible, infrared, and Raman spectroscopy coupled with chemometrics will be discussed for the corona virus infected samples based on the relevant literature. In vibrational spectroscopy studies, due to complexity of the data, multivariate analysis methods are also applied to data. The application of multivariate analysis tools that can be used to extract useful information from the data for diagnostic and characterisation purposes is also included in this review. The reviewed methods include hierarchical cluster analysis, principal component analysis, linear and quadratic discriminant analysis, support vector machine algorithm, and one form of neural networks namely deep learning method. Second, novel treatment methods such as photodynamic therapy and the use of nanoparticles in the in-corona virus therapy will be discussed. Finally, the advantages of novel promising diagnosis and treatment methods in COVID-19, over standard methods will be discussed. One of the main aims of this paper is to encourage the scientific community to explore the potential of this novel tools for their use in corona virus characterization, diagnosis, and treatment.