Detection of SARS-CoV-2 and its S and N proteins using surface enhanced Raman spectroscopy

Label-free and liquid state SERS detection of multi-scaled bioanalytes via light-induced pinpoint colloidal assembly

Surface-enhanced Raman scattering (SERS) has been extensively applied to detect complex analytes due to its ability to enhance the fingerprint signals of molecules around nanostructured metallic surfaces. Thus, it is essential to design SERS-active nanostructures with abundant electromagnetic hotspots in a probed volume according to the dimensions of the analytes, as the analytes must be located in their hotspots for maximum signal enhancement. Herein, we demonstrate a simple method for detecting robust SERS signals from multi-scaled bioanalytes, regardless of their dimensions in the liquid state, through a photothermally driven co-assembly with colloidal plasmonic nanoparticles as signal enhancers. Under resonant light illumination, plasmonic nanoparticles and analytes in the solution quickly assemble at the focused surface area by convective movements induced by the photothermal heating of the plasmonic nanoparticles without any surface modification. Such collective assemblies of plasmonic nanoparticles and analytes were optimized by varying the optical density and surface charge of the nanoparticles, the viscosity of the solvent, and the light illumination time to maximize the SERS signals. Using these light-induced co-assemblies, the intrinsic SERS signals of small biomolecules can be detected down to nanomolar concentrations based on their fingerprint spectra. Furthermore, large-sized biomarkers, such as viruses and exosomes, were successfully detected without labels, and the complexity of the collected spectra was statistically analyzed using t-distributed stochastic neighbor embedding combined with support vector machine (t-SNE + SVM). The proposed method is expected to provide a robust and convenient method to sensitively detect biologically and environmentally relevant analytes at multiple scales in liquid samples.

Innovative and versatile surface-enhanced Raman spectroscopy-inspired approaches for viral detection leading to clinical applications: A review

The evolution of analytical techniques has opened the possibilities of accurate analyte detection through a straightforward method and short acquisition time, leading towards their applicability to identify medical conditions. Surface-enhanced Raman spectroscopy (SERS) has long been proven effective for rapid detection and relies on SERS spectra that are unique to each specific analyte. However, the complexity of viruses poses challenges to SERS and hinders further progress in its practical applications. The principle of SERS revolves around the interaction among substrate, analyte, and Raman laser, but most studies only emphasize the substrate, especially label-free methods, and the synergy among these factors is often ignored. Therefore, issues related to reproducibility and consistency of results, which are crucial for medical diagnosis and are the main highlights of this review, can be understood and largely addressed when considering these interactions. Viruses are composed of multiple surface components and can be detected by label-free SERS, but the presence of non-target molecules in clinical samples interferes with the detection process. Appropriate spectral data processing workflow also plays an important role in the interpretation of results. Furthermore, integrating machine learning into data processing can account for changes brought about by the presence of non-target molecules when analyzing spectral features to accurately group the data, for example, whether the sample corresponds to a positive or negative patient, and whether a virus variant or multiple viruses are present in the sample. Subsequently, advances in interdisciplinary fields can bring SERS closer to practical applications.

Focused ion beam-fabricated nanorod substrate for label-free surface-enhanced Raman spectroscopy and enabling dual virus detection

The COVID-19 pandemic presents global challenges, notably with co-infections in respiratory tract involving SARS-CoV-2 variants and influenza strains. Detecting multiple viruses simultaneously is crucial for accurate diagnosis, effective tracking infectious sources, and containment of the epidemic. This study uses a label-free surface-enhanced Raman spectroscopy (SERS) method using Au NPs/pZrO2 (250) and FIB-made Au NRs (100) to detect dual viruses, including SARS-CoV-2 Delta variant (D) and influenza A (A) or B (B) virus. Results demonstrate distinct peaks facilitating virus differentiation, especially between D and A or B, with clear disparities between substrates; specific peaks at 950 and 1337 cm-1 are pivotal for discerning viruses using Au NPs/pZrO2 (250), while those at 1050, 1394, and 1450 cm-1 and 1033, 1165, 1337, and 1378 cm-1 are key for validation using Au NRs (100). Differences in substrate surface morphology and spatial disposition of accommodating viruses significantly influence hotspot formation and Raman signal amplification efficiency, thereby affecting the ability to distinguish various viruses. Furthermore, both substrates offer insights, even in the presence of oxymetazoline hydrochloride (an interfering substance), with practical implications in viral diagnosis. The customized design and reproducibility underscore efficient Raman signal amplification, even in challenging environments, highlighting potential for widespread virus detection.

A biosensor based on magnetoelastic waves for detection of antibodies in human plasma for COVID-19 serodiagnosis

This study proposes a new efficient wireless biosensor based on magnetoelastic waves for antibody detection in human plasma, aiming at the serological diagnosis of COVID-19. The biosensor underwent functionalization with the N antigen - nucleocapsid phosphoprotein of the SARS-CoV-2 virus. Validation analyses by sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE), Western blotting (WB), atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) microanalysis and micro-Raman spectroscopy confirmed the selectivity and effective surface functionalization of the biosensor. The research successfully obtained, expressed and purified the recombinant antigen, while plasma samples from COVID-19 positive and negative patients were applied to test the performance of the biosensor. A performance comparison with the enzyme-linked immunosorbent assays (ELISA) method revealed equivalent diagnostic capacity. These results indicate the robustness of the biosensor in reliably differentiating between positive and negative samples, highlighting its potential as an efficient and low-cost tool for the serological diagnosis of COVID-19. In addition to being fast to execute and having the potential for automation in large-scale diagnostic studies, the biosensor fills a significant gap in existing SARS-CoV-2 detection approaches.

Molybdenum Disulfide-Assisted Spontaneous Formation of Multistacked Gold Nanoparticles for Deep Learning-Integrated Surface-Enhanced Raman Scattering

Several fabrication methods have been developed for label-free detection in various fields. However, fabricating high-density and highly ordered nanoscale architectures by using soluble processes remains a challenge. Herein, we report a biosensing platform that integrates deep learning with surface-enhanced Raman scattering (SERS), featuring large-area, close-packed three-dimensional (3D) architectures of molybdenum disulfide (MoS2)-assisted gold nanoparticles (AuNPs) for the on-site screening of coronavirus disease (COVID-19) using human tears. Some AuNPs are spontaneously synthesized without a reducing agent because the electrons induced on the semiconductor surface reduce gold ions when the Fermi level of MoS2 and the gold electrolyte reach equilibrium. With the addition of polyvinylpyrrolidone, a two-dimensional large-area MoS2 layer assisted in the formation of close-packed 3D multistacked AuNP structures, resembling electroless plating. This platform, with a convolutional neural network-based deep learning model, achieved outstanding SERS performance at subterascale levels despite the microlevel irradiation power and millisecond-level acquisition time and accurately assessed susceptibility to COVID-19. These results suggest that our platform has the potential for rapid, low-damage, and high-throughput label-free detection of exceedingly low analyte concentrations.

Detection of SARS-CoV-2 N protein using AgNPs-modified aligned silicon nanowires BioSERS chip

The SARS-CoV-2 (COVID-19) pandemic had a strong impact on societies and economies worldwide and tests for high-performance detection of SARS-CoV-2 biomarkers are still needed for potential future outbreaks of the disease. In this paper, we present the different steps for the design of an aptamer-based surface-enhanced Raman scattering (BioSERS) sensing chip capable of detecting the coronavirus nucleocapsid protein (N protein) in spiked phosphate-buffered solutions and real samples of human blood serum. Optimization of the preparation steps in terms of the aptamer concentration used for the functionalization of the silver nanoparticles, time for affixing the aptamer, incubation time with target protein, and insulation of the silver active surface with cysteamine, led to a sensitive BioSERS chip, which was able to detect the N protein in the range from 1 to 75 ng mL-1 in spiked phosphate-buffered solutions with a detection limit of 1 ng mL-1 within 30 min. Furthermore, the BioSERS chip was used to detect the target protein in scarcely spiked human serum. This study demonstrates the possibility of a clinical application that can improve the detection limit and accuracy of the currently commercialized SARS-CoV-2 immunodiagnostic kit. Additionally, the system is modular and can be applied to detect other proteins by only changing the aptamer.

Photonic Crystal Surface Mode Real-Time Imaging of RAD51 DNA Repair Protein Interaction with the ssDNA Substrate

Photonic crystals (PCs) are promising tools for label-free sensing in drug discovery screening, diagnostics, and analysis of ligand-receptor interactions. Imaging of PC surface modes has emerged as a novel approach to the detection of multiple binding events at the sensor surface. PC surface modification and decoration with recognition units yield an interface providing the highly sensitive detection of cancer biomarkers, antibodies, and oligonucleotides. The RAD51 protein plays a central role in DNA repair via the homologous recombination pathway. This recombinase is essential for the genome stability and its overexpression is often correlated with aggressive cancer. RAD51 is therefore a potential target in the therapeutic strategy for cancer. Here, we report the designing of a PC-based array sensor for real-time monitoring of oligonucleotide-RAD51 recruitment by means of surface mode imaging and validation of the concept of this approach. Our data demonstrate that the designed biosensor ensures the highly sensitive multiplexed analysis of association-dissociation events and detection of the biomarker of DNA damage using a microfluidic PC array. The obtained results highlight the potential of the developed technique for testing the functionality of candidate drugs, discovering new molecular targets and drug entities. This paves the way to further adaption and bioanalytical use of the biosensor for high-content screening to identify new DNA repair inhibitor drugs targeting the RAD51 nucleoprotein filament or to discover new molecular targets.

Advances in nanobiosensors during the COVID-19 pandemic and future perspectives for the post-COVID era

The unprecedented threat of the highly contagious virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes exponentially increased infections of coronavirus disease 2019 (COVID-19), highlights the weak spots of the current diagnostic toolbox. In the midst of catastrophe, nanobiosensors offer a new opportunity as an alternative tool to fill a gap among molecular tests, rapid antigen tests, and serological tests. Nanobiosensors surpass the potential of antigen tests because of their enhanced sensitivity, thus enabling us to see antigens as stable and easy-to-access targets. During the first three years of the COVID-19 pandemic, a substantial number of studies have reported nanobiosensors for the detection of SARS-CoV-2 antigens. The number of articles on nanobiosensors and SARS-CoV-2 exceeds the amount of nanobiosensor research on detecting previous infectious diseases, from influenza to SARS-CoV and MERS-CoV. This unprecedented publishing pace also implies the significance of SARS-CoV-2 and the present pandemic. In this review, 158 studies reporting nanobiosensors for detecting SARS-CoV-2 antigens are collected to discuss the current challenges of nanobiosensors using the criteria of point-of-care (POC) diagnostics along with COVID-specific issues. These advances and lessons during the pandemic pave the way for preparing for the post-COVID era and potential upcoming infectious diseases.

Characterization and discrimination of spike protein in SARS-CoV-2 virus-like particles via surface-enhanced Raman spectroscopy

Non-infectious virus-like particles (VLPs) are excellent structures for development of many biomedical applications such as drug delivery systems, vaccine production platforms, and detection techniques for infectious diseases including SARS-CoV-2 VLPs. The characterization of biochemical and biophysical properties of purified VLPs is crucial for development of detection methods and therapeutics. The presence of spike (S) protein in their structure is especially important since S protein induces immunological response. In this study, development of a rapid, low-cost, and easy-to-use technique for both characterization and detection of S protein in the two VLPs, which are SARS-CoV-2 VLPs and HIV-based VLPs was achieved using surface-enhanced Raman spectroscopy (SERS). To analyze and classify datasets of SERS spectra obtained from the VLP groups, machine learning classification techniques including support vector machine (SVM), k-nearest neighbors (kNN), and random forest (RF) were utilized. Among them, the SVM classification algorithm demonstrated the best classification performance for SARS-CoV-2 VLPs and HIV-based VLPs groups with 87.5% and 92.5% accuracy, respectively. This study could be valuable for the rapid characterization of VLPs for the development of novel therapeutics or detection of structural proteins of viruses leading to a variety of infectious diseases.

The Label-Free Detection and Identification of SARS-CoV-2 Using Surface-Enhanced Raman Spectroscopy and Principal Component Analysis

The World Health Organization (WHO) declared in a May 2023 announcement that the COVID-19 illness is no longer categorized as a Public Health Emergency of International Concern (PHEIC); nevertheless, it is still considered an actual threat to world health, social welfare and economic stability. Consequently, the development of a convenient, reliable and affordable approach for detecting and identifying SARS-CoV-2 and its emerging new variants is crucial. The fingerprint and signal amplification characteristics of surface-enhanced Raman spectroscopy (SERS) could serve as an assay scheme for SARS-CoV-2. Here, we report a machine learning-based label-free SERS technique for the rapid and accurate detection and identification of SARS-CoV-2. The SERS spectra collected from samples of four types of coronaviruses on gold nanoparticles film, fabricated using a Langmuir-Blodgett self-assembly, can provide more spectroscopic signatures of the viruses and exhibit low limits of detection (<100 TCID50/mL or even <10 TCID50/mL). Furthermore, the key Raman bands of the SERS spectra were systematically captured by principal component analysis (PCA), which effectively distinguished SARS-CoV-2 and its variant from other coronaviruses. These results demonstrate that the combined use of SERS technology and PCA analysis has great potential for the rapid analysis and discrimination of multiple viruses and even newly emerging viruses without the need for a virus-specific probe.

Diagnosing COVID-19 in nasopharyngeal secretion through Raman spectroscopy: a feasibility study

Since the beginning of the COVID-19 pandemic, the scientific community has sought to develop fast and accurate techniques for detecting the SARS-CoV-2 virus. Raman spectroscopy is a promising technique for diagnosing COVID-19 through serum samples. In the present study, the diagnosis of COVID-19 through nasopharyngeal secretion has been proposed. Raman spectra from nasopharyngeal secretion samples (15 Control, negative and 12 COVID-19, positive, assayed by immunofluorescence antigen test) were obtained in triplicate in a dispersive Raman spectrometer (830 nm, 350 mW), accounting for a total of 80 spectra. Using principal component analysis (PCA) the main spectral differences between the Control and COVID-19 samples were attributed to N and S proteins from the virus in the COVID-19 group. Features assigned to mucin (serine, threonine and proline amino acids) were observed in the Control group. A binary model based on partial least squares discriminant analysis (PLS-DA) differentiated COVID-19 versus Control samples with accuracy of 91%, sensitivity of 80% and specificity of 100%. Raman spectroscopy has a great potential for becoming a technique of choice for rapid and label-free evaluation of nasopharyngeal secretion for COVID-19 diagnosis.

SARS-CoV-2 Virus-like Particles with Plasmonic Au Cores and S1-Spike Protein Coronas

The COVID-19 pandemic has stimulated the scientific world to intensify virus-related studies aimed at the development of quick and safe ways of detecting viruses in the human body, studying the virus-antibody and virus-cell interactions, and designing nanocarriers for targeted antiviral therapies. However, research on dangerous viruses can only be performed in certified laboratories that follow strict safety procedures. Thus, developing deactivated virus constructs or safe-to-use virus-like objects, which imitate real viruses and allow performing virus-related studies in any research laboratory, constitutes an important scientific challenge. Such species, called virus-like particles (VLPs), contain instead of capsids with viral DNA/RNA empty or synthetic cores with real virus proteins attached to them. We have developed a method for the preparation of VLPs imitating the virus responsible for the COVID-19 disease: the SARS-CoV-2. The particles have Au cores surrounded by "coronas" of S1 domains of the virus's spike protein. Importantly, they are safe to use and specifically interact with SARS-CoV-2 antibodies. Moreover, Au cores exhibit localized surface plasmon resonance (LSPR), which makes the synthesized VLPs suitable for biosensing applications. During the studies, the effect allowed us to visualize the interaction between the VLPs and the antibodies and identify the characteristic vibrational signals. What is more, additional functionalization of the particles with a fluorescent label revealed their potential in studying specific virus-related interactions. Notably, the universal character of the developed synthesis method makes it potentially applicable for fabricating VLPs imitating other life-threatening viruses.

Analysis of SARS-CoV-2 spike RBD binding to ACE2 and its inhibition by fungal cohaerin C using surface enhanced Raman spectroscopy

The structure of the SARS-CoV-2 spike RBD and human ACE2 as well as changes in the structure due to binding activities were analysed using surface enhanced Raman spectroscopy. The inhibitor cohaerin C was applied to inhibit the binding between spike RBD and ACE2. Differences and changes in the Raman spectra were determined using deconvolution of the amide bands and principal component analysis. We thus demonstrate a fast and label-free analysis of the protein structures and the differentiation between bound and unbound states. The approach is suitable for sensing and screening and might be relevant to investigate other protein systems as well.

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.

Detection of live SARS-CoV-2 virus and its variants by specially designed SERS-active substrates and spectroscopic analyses

A method using label-free surface enhanced Raman spectroscopy (SERS) based on substrate design is provided for an early detection and differentiation of spike glycoprotein mutation sites in live SARS-CoV-2 variants. Two SERS-active substrates, Au nanocavities (Au NCs) and Au NPs on porous ZrO₂ (Au NPs/pZrO₂), were used to identify specific peaks of A.3, Alpha, and Delta variants at different concentrations and demonstrated the ability to provide their SERS spectra with detection limits of 0.1–1.0% (or 10⁴⁻⁵ copies/mL). Variant identification can be achieved by cross-examining reference spectra and analyzing the substrate-analyte relationship between the suitability of the analyte upon the hotspot(s) formed at high concentrations and the effective detection distance at low concentrations. Mutation sites on the S1 chain of the spike glycoprotein for each variant may be related and distinguishable. This method does not require sample preprocessing and therefore allows for fast screening, which is of high value for more comprehensive and specific studies to distinguish upcoming variants.

Recent development of surface-enhanced Raman scattering for biosensing

Surface-Enhanced Raman Scattering (SERS) technology, as a powerful tool to identify molecular species by collecting molecular spectral signals at the single-molecule level, has achieved substantial progresses in the fields of environmental science, medical diagnosis, food safety, and biological analysis. As deepening research is delved into SERS sensing, more and more high-performance or multifunctional SERS substrate materials emerge, which are expected to push Raman sensing into more application fields. Especially in the field of biological analysis, intrinsic and extrinsic SERS sensing schemes have been widely used and explored due to their fast, sensitive and reliable advantages. Herein, recent developments of SERS substrates and their applications in biomolecular detection (SARS-CoV-2 virus, tumor etc.), biological imaging and pesticide detection are summarized. The SERS concepts (including its basic theory and sensing mechanism) and the important strategies (extending from nanomaterials with tunable shapes and nanostructures to surface bio-functionalization by modifying affinity groups or specific biomolecules) for improving SERS biosensing performance are comprehensively discussed. For data analysis and identification, the applications of machine learning methods and software acquisition sources in SERS biosensing and diagnosing are discussed in detail. In conclusion, the challenges and perspectives of SERS biosensing in the future are presented.

Challenges and opportunities for SERS in the infrared: materials and methods

In the wake of a global, heightened interest towards biomarker and disease detection prompted by the SARS-CoV-2 pandemic, surface enhanced Raman spectroscopy (SERS) positions itself again at the forefront of biosensing innovation. But is it ready to move from the laboratory to the clinic? This review presents the challenges associated with the application of SERS to the biomedical field, and thus, to the use of excitation sources in the near infrared, where biological windows allow for cell and through-tissue measurements. Two main tackling strategies will be discussed: (1) acting on the design of the enhancing substrate, which includes manipulation of nanoparticle shape, material, and supramolecular architecture, and (2) acting on the spectral collection set-up. A final perspective highlights the upcoming scientific and technological bets that need to be won in order for SERS to stably transition from benchtop to bedside.

Ultrasensitive detection of SARS-CoV-2 antigen using surface-enhanced Raman spectroscopy-based lateral flow immunosensor

The fast spread and transmission of the coronavirus 2019 (COVID-19) has become one of serious global public health problems. Herein, a surface enhanced Raman spectroscopy-based lateral flow immunoassay (LFA) was developed for the detection of SARS-CoV-2 antigen. Using uniquely designed core-shell nanoparticle with embedded Raman probe molecules as the indicator to reveal the concentration of target protein, excellent quantitative performance with a limit of detection (LOD) of 0.03 ng/mL and detection range of 10-1000 ng/mL can be achieved within 15 min. Besides, the detection of spiked virus protein in human saliva was also performed with a portable Raman spectrometer, proposing the feasibility of the method in practical applications. This easy-to-use, rapid and accurate method would provide a point-of-care testing way as the ideal alternative for current detection requirement of virus-related biomarkers.

Perspective Chapter: Novel Diagnostics Methods for SARS-CoV-2

A novel coronavirus of zoonotic origin (SARS-CoV-2) has recently been recognized in patients with acute respiratory disease. COVID-19 causative agent is structurally and genetically similar to SARS and bat SARS-like coronaviruses. The drastic increase in the number of coronavirus and its genome sequence has given us an unprecedented opportunity to perform bioinformatics and genomics analysis on this class of viruses. Clinical tests such as PCR and ELISA for rapid detection of this virus are urgently needed for early identification of infected patients. However, these techniques are expensive and not readily available for point-of-care (POC) applications. Currently, lack of any rapid, available, and reliable POC detection method gives rise to the progression of COVID-19 as a horrible global problem. To solve the negative features of clinical investigation, we provide a brief introduction of the various novel diagnostics methods including SERS, SPR, electrochemical, magnetic detection of SARS-CoV-2. All sensing and biosensing methods based on nanotechnology developed for the determination of various classes of coronaviruses are useful to recognize the newly immerged coronavirus, i.e., SARS-CoV-2. Also, the introduction of sensing and biosensing methods sheds light on the way of designing a proper screening system.

Identify the Virus-like Models for COVID-19 as Bio-Threats: Combining Phage Display, Spectral Detection and Algorithms Analysis

The rapid identification and recognition of COVID-19 have been challenging since its outbreak. Multiple methods were developed to realize fast monitoring early to prevent and control the pandemic. In addition, it is difficult and unrealistic to apply the actual virus to study and research because of the highly infectious and pathogenic SARS-CoV-2. In this study, the virus-like models were designed and produced to replace the original virus as bio-threats. Three-dimensional excitation-emission matrix fluorescence and Raman spectroscopy were employed for differentiation and recognition among the produced bio-threats and other viruses, proteins, and bacteria. Combined with PCA and LDA analysis, the identification of the models for SARS-CoV-2 was achieved, reaching a correction of 88.9% and 96.3% after cross-validation, respectively. This idea might provide a possible pattern for detecting and controlling SARS-CoV-2 from the perspective of combining optics and algorithms, which could be applied in the early-warning system against COVID-19 or other bio-threats in the future.

Recent advances of Au@Ag core-shell SERS-based biosensors

The methodological advancements in surface-enhanced Raman scattering (SERS) technique with nanoscale materials based on noble metals, Au, Ag, and their bimetallic alloy Au-Ag, has enabled the highly efficient sensing of chemical and biological molecules at very low concentration values. By employing the innovative various type of Au, Ag nanoparticles and especially, high efficiency Au@Ag alloy nanomaterials as substrate in SERS based biosensors have revolutionized the detection of biological components including; proteins, antigens antibodies complex, circulating tumor cells, DNA, and RNA (miRNA), etc. This review is about SERS-based Au/Ag bimetallic biosensors and their Raman enhanced activity by focusing on different factors related to them. The emphasis of this research is to describe the recent developments in this field and conceptual advancements behind them. Furthermore, in this article we apex the understanding of impact by variation in basic features like effects of size, shape varying lengths, thickness of core-shell and their influence of large-scale magnitude and morphology. Moreover, the detailed information about recent biological applications based on these core-shell noble metals, importantly detection of receptor binding domain (RBD) protein of COVID-19 is provided.

Classification of Coronavirus Spike Proteins by Deep-Learning-Based Raman Spectroscopy and its Interpretative Analysis

The outbreak of COVID-19 has spread worldwide, causing great damage to the global economy. Raman spectroscopy is expected to become a rapid and accurate method for the detection of coronavirus. A classification method of coronavirus spike proteins by Raman spectroscopy based on deep learning was implemented. A Raman spectra dataset of the spike proteins of five coronaviruses (including MERS-CoV, SARS-CoV, SARS-CoV-2, HCoVHKU1, and HCoV-OC43) was generated to establish the neural network model for classification. Even for rapidly acquired spectra with a low signal-to-noise ratio, the average accuracy exceeded 97%. An interpretive analysis of the classification results of the neural network was performed, which indicated that the differences in spectral characteristics captured by the neural network were consistent with the experimental analysis. The interpretative analysis method provided a valuable reference for identifying complex Raman spectra using deep-learning techniques. Our approach exhibited the potential to be applied in clinical practice to identify COVID-19 and other coronaviruses, and it can also be applied to other identification problems such as the identification of viruses or chemical agents, as well as in industrial areas such as oil and gas exploration.

Plasmonic nanostructure-enhanced Raman scattering for detection of SARS-CoV-2 nucleocapsid protein and spike protein variants

Epidemiological control and public health monitoring during the outbreaks of infectious viral diseases rely on the ability to detect viral pathogens. Here we demonstrate a rapid, sensitive, and selective nanotechnology-enhanced severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection based on the surface-enhanced Raman scattering (SERS) responses from the plasma-engineered, variant-specific antibody-functionalized silver microplasma-engineered nanoassemblies (AgMEN) interacting with the SARS-CoV-2 spike (S) and nucleocapsid (N) proteins. The three-dimensional (3D) porous AgMEN with plasmonic-active nanostructures provide a high sensitivity to virus detection via the remarkable SERS signal collection. Moreover, the variant-specific antibody-functionalization on the SERS-active AgMEN enabled the high selectivity of the SARS-CoV-2 S variants, including wild-type, Alpha, Delta, and Omicron, under the simulated human saliva conditions. The exceptional ultrahigh sensitivity of our SERS biosensor was demonstrated via SARS-CoV-2 S and N proteins at the detection limit of 1 fg mL^-1 and 0.1 pg mL^-1, respectively. Our work demonstrates a versatile SERS-based detection platform can be applied for the ultrasensitive detection of virus variants, infectious diseases, and cancer biomarkers.

SARS-CoV-2 proteins monitored by long-range surface plasmon field-enhanced Raman scattering with hybrid bowtie nanoaperture arrays and nanocavities

The identification of biomacromolecules by using surface-enhanced Raman scattering (SERS) remains a challenge because of the near-field effect of traditional substrates. Long-range surface plasmon resonance (LRSPR) is a special type of surface optical phenomenon that provides higher electromagnetic field enhancement and longer penetration depth than conventional surface plasmon resonance. To break the limit of SERS detection distance and obtain a SERS substrate with increased enhancement ability, a bowtie nanoaperture array was sandwiched between two symmetric dielectric environments. Then, an Au mirror was inserted to form a metal-insulator-metal configuration. Finite-difference time-domain simulations revealed that numerous hybrid modes can be provided by this novel configuration (denoted as long-range SERS [LR-SERS] substrate). In particular, the LRSPR mode can be excited and reach the maximum value through the regulation of the polarizations of the incident light and the geometrical parameters of the LR-SERS substrate. The optimized LR-SERS substrate was then applied to detect SARS-CoV-2 spike (S) and nucleocapsid (N) proteins. This substrate displayed ultralow detection limits of ∼9.2 and ∼11.3 pg mL^-1 for the S and N proteins, respectively. Moreover, with the help of principal component analysis and receiver operating characteristic methods, our fabricated sensors exhibited excellent selectivity and hold great potential for the diagnosis of SARS-CoV-2 proteins in real samples.

Recent Advances of Representative Optical Biosensors for Rapid and Sensitive Diagnostics of SARS-CoV-2

The outbreak of Corona Virus Disease 2019 (COVID-19) has again emphasized the significance of developing rapid and highly sensitive testing tools for quickly identifying infected patients. Although the current reverse transcription polymerase chain reaction (RT-PCR) diagnostic techniques can satisfy the required sensitivity and specificity, the inherent disadvantages with time-consuming, sophisticated equipment and professional operators limit its application scopes. Compared with traditional detection techniques, optical biosensors based on nanomaterials/nanostructures have received much interest in the detection of SARS-CoV-2 due to the high sensitivity, high accuracy, and fast response. In this review, the research progress on optical biosensors in SARS-CoV-2 diagnosis, including fluorescence biosensors, colorimetric biosensors, Surface Enhancement Raman Scattering (SERS) biosensors, and Surface Plasmon Resonance (SPR) biosensors, was comprehensively summarized. Further, promising strategies to improve optical biosensors are also explained. Optical biosensors can not only realize the rapid detection of SARS-CoV-2 but also be applied to judge the infectiousness of the virus and guide the choice of SARS-CoV-2 vaccines, showing enormous potential to become point-of-care detection tools for the timely control of the pandemic.

Label-free laser spectroscopy for respiratory virus detection: A review

Infectious diseases are among the most severe threats to modern society. Current methods of virus infection detection based on genome tests need reagents and specialized laboratories. The desired characteristics of new virus detection methods are noninvasiveness, simplicity of implementation, real-time, low cost and label-free detection. There are two groups of methods for molecular biomarkers' detection and analysis: (i) a sample physical separation into individual molecular components and their identification, and (ii) sample content analysis by laser spectroscopy. Variations in the spectral data are typically minor. It requires the use of sophisticated analytical methods like machine learning. This review examines the current technological level of laser spectroscopy and machine learning methods in applications for virus infection detection.

In Situ Surface-Enhanced Raman Scattering Detection of a SARS-CoV-2 Biomarker Using Flexible and Transparent Polydimethylsiloxane Films with Embedded Au Nanoplates

Coronavirus disease 2019 (COVID-19) remains an ongoing issue worldwide and continues to disrupt daily life. Transmission of infection primarily occurs through secretions when in contact with infected individuals, but more recent evidence has shown that fomites are also a source of virus transmission, especially in cold-chain logistics. Traditional nucleic acid testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contamination in cold-chain logistics is time-consuming and inaccurate because of the multiplex sampling sites. Surface-enhanced Raman spectroscopy (SERS) provides a rapid, sensitive, and label-free detection route for various molecules, including viruses, through the identification of the characteristic peaks of their outer membrane proteins. In this study, we embedded arbitrarily orientated gold nanoplates (Au NPLs) in polydimethylsiloxane (PDMS) elastomer and used it as biosensor for the ultrasensitive detection of the SARS-CoV-2 spike protein in cold-chain logistics. This transparent and flexible substrate can be wrapped onto arbitrary surfaces and permits light penetration into the underlying contact surface, enabling in situ and point-of-care SERS diagnostics. The developed assay displayed high reproducibility (8.7%) and a low detection limit of 6.8 × 10-9 g mL-1, indicating its potential to serve as a promising approach with increased accuracy and sensitivity for the detection of the S protein.

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.

Understanding the Excitation Wavelength Dependence and Thermal Stability of the SARS-CoV-2 Receptor-Binding Domain Using Surface-Enhanced Raman Scattering and Machine Learning

COVID-19 has cost millions of lives worldwide. The constant mutation of SARS-CoV-2 calls for thorough research to facilitate the development of variant surveillance. In this work, we studied the fundamental properties related to the optical identification of the receptor-binding domain (RBD) of SARS-CoV-2 spike protein, a key component of viral infection. The Raman modes of the SARS-CoV-2 RBD were captured by surface-enhanced Raman spectroscopy (SERS) using gold nanoparticles (AuNPs). The observed Raman enhancement strongly depends on the excitation wavelength as a result of the aggregation of AuNPs. The characteristic Raman spectra of RBDs from SARS-CoV-2 and MERS-CoV were analyzed by principal component analysis that reveals the role of secondary structures in the SERS process, which is corroborated with the thermal stability under laser heating. We can easily distinguish the Raman spectra of two RBDs using machine learning algorithms with accuracy, precision, recall, and F1 scores all over 95%. Our work provides an in-depth understanding of the SARS-CoV-2 RBD and paves the way toward rapid analysis and discrimination of complex proteins of infectious viruses and other biomolecules.

High-sensitivity and point-of-care detection of SARS-CoV-2 from nasal and throat swabs by magnetic SERS biosensor

The outbreak of COVID-19 caused by SARS-CoV-2 urges the development of rapidly and accurately diagnostic methods. Here, one high-sensitivity and point-of-care detection method based on magnetic SERS biosensor composed of Fe₃O₄-Au nanocomposite and Au nanoneedles array was developed to detect SARS-CoV-2 directly. Among, the magnetic Fe₃O₄-Au nanocomposite is applied to capture and separate virus from nasal and throat swabs and enhance the Raman signals of SARS-CoV-2. The magnetic SERS biosensor possessed high sensitivity by optimizing the Fe₃O₄-Au nanocomposite. More significantly, the on-site detection of inactivated SARS-CoV-2 virus was achieved based on the magnetic SERS biosensor with ultra-low limit of detection of 100 copies/mL during 15 mins. Furthermore, the contaminated nasal and throat swabs samples were identified by support vector machine, and the diagnostic accuracy of 100% was obtained. The magnetic SERS biosensor combined with support vector machine provides giant potential as the point-of-care detection tool for SARS-CoV-2.

Probing the mutation independent interaction of DNA probes with SARS-CoV-2 variants through a combination of surface-enhanced Raman scattering and machine learning

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 ∼100% sensitivity and ∼90% 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.

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.

Ultrafast Detection of SARS-CoV-2 Spike Protein (S) and Receptor-Binding Domain (RBD) in Saliva Using Surface-Enhanced Raman Spectroscopy

Controlling contagious diseases necessitates using diagnostic techniques that can detect infection in the early stages. Although different diagnostic tools exist, there are still challenges related to accuracy, rapidity, cost-effectiveness, and ease of use. Surface-enhanced Raman spectroscopy (SERS) is a rapid, simple, less expensive, and accurate method. We continue our previous work published on SERS detection of the SARS-CoV-2 receptor-binding domain (RBD) in water. In this work, we replace water with saliva to detect SARS-CoV-2 proteins at very low concentrations and during a very short time. We prepared a very low concentration of 10−9 M SARS-CoV-2 spike protein (S) and SARS-CoV-2 receptor-binding domain (RBD) in saliva to mimic a real case scenario. Then, we drop them on a SERS substrate. Using modified SERS measurements on the control and the sample containing the biomolecules, confirmed the sensitivity of the target identification. This technique provides different diagnostic solutions that are fast, simple, non-destructive and ultrasensitive. Simulation of the real-world of silicon wire covered with silver and gold, were performed using an effective and accurate tool, COMSOL Multiphysics software, for the enhancement properties study.

Label-Free Detection of the Receptor-Binding Domain of the SARS-CoV-2 Spike Glycoprotein at Physiologically Relevant Concentrations Using Surface-Enhanced Raman Spectroscopy

Surface-enhanced Raman scattering (SERS) spectroscopy is a surface- or cavity-enhanced variant of Raman scattering spectroscopy that allows the detection of analytes with a sensitivity down to single molecules. This method involves the use of SERS-active surfaces or cavities capable of concentrating incident radiation into small mode volumes containing the analyte. Here, we have engineered an ultranarrow metal-dielectric nano-cavity out of a film of the receptor-binding domain (RBD) of SARS-CoV-2 spike (S) glycoprotein and a silver surface, held together by interaction between reduced protein sulfhydryl groups and silver. The concentration of light in this nano-cavity allows the label-free recording of the characteristic Raman spectra of protein samples smaller than 1 pg. This is sufficient for the ultrasensitive detection of viral protein antigens at physiologically relevant levels. Moreover, the protein SERS signal can be increased by several orders of magnitude by coating the RBD film with a nanometer-thick silver shell, thereby raising the cavity Q-factor. This ensures a sub-femtogram sensitivity of the viral antigen detection. A simple theoretical model explaining the observed additional enhancement of the SERS signal from the silver-coated protein is proposed. Our study is the first to obtain the characteristic Raman and SERS spectra of the RBD of S glycoprotein, the key SARS-CoV-2 viral antigen, directly, without the use of Raman-reporter molecules. Thus, our approach allows label-free recording of the characteristic spectra of viral antigens at concentrations orders of magnitude lower than those required for detecting the whole virus in biological media. This makes it possible to develop a high-performance optical detection method and conformational analysis of the pathogen and its variants.

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.

Investigation of mammalian cells expressing SARS-CoV-2 proteins by surface-enhanced Raman scattering and multivariate analysis

COVID-19 has caused millions of cases and deaths all over the world since late 2019. Rapid detection of the virus is crucial for controlling its spread through a population. COVID-19 is currently detected by nucleic acid-based tests and serological tests. However, these methods have limitations such as the requirement of high-cost reagents, false negative results and being time consuming. Surface-enhanced Raman scattering (SERS), which is a powerful technique that enhances the Raman signals of molecules using plasmonic nanostructures, can overcome these disadvantages. In this study, we developed a virus-infected cell model and analyzed this model by SERS combined with Principal Component Analysis (PCA). HEK293 cells were transfected with plasmids encoding the nucleocapsid (N), membrane (M) and envelope (E) proteins of SARS-CoV-2 via polyethyleneimine (PEI). Non-plasmid transfected HEK293 cells were used as the control group. Cellular uptake was optimized with green fluorescence protein (GFP) plasmids and evaluated by fluorescence microscopy and flow cytometry. The transfection efficiency was found to be around 60%. The expression of M, N, and E proteins was demonstrated by western blotting. The SERS spectra of the total proteins of transfected cells were obtained using a gold nanoparticle-based SERS substrate. Proteins of the transfected cells have peak positions at 646, 680, 713, 768, 780, 953, 1014, 1046, 1213, 1243, 1424, 2102, and 2124 cm^-1. To reveal spectral differences between plasmid transfected cells and non-transfected control cells, PCA was applied to the spectra. The results demonstrated that SERS coupled with PCA might be a favorable and reliable way to develop a rapid, low-cost, and promising technique for the detection of COVID-19.

Insight into prognostics, diagnostics, and management strategies for SARS CoV-2

The foremost challenge in countering infectious diseases is the shortage of effective therapeutics. The emergence of coronavirus disease (COVID-19) outbreak has posed a great menace to the public health system globally, prompting unprecedented endeavors to contain the virus. Many countries have organized research programs for therapeutics and management development. However, the longstanding process has forced authorities to implement widespread infrastructures for detailed prognostic and diagnostics study of severe acute respiratory syndrome (SARS CoV-2). This review discussed nearly all the globally developed diagnostic methodologies reported for SARS CoV-2 detection. We have highlighted in detail the approaches for evaluating COVID-19 biomarkers along with the most employed nucleic acid- and protein-based detection methodologies and the causes of their severe downfall and rejection. As the variable variants of SARS CoV-2 came into the picture, we captured the breadth of newly integrated digital sensing prototypes comprised of plasmonic and field-effect transistor-based sensors along with commercially available food and drug administration (FDA) approved detection kits. However, more efforts are required to exploit the available resources to manufacture cheap and robust diagnostic methodologies. Likewise, the visualization and characterization tools along with the current challenges associated with waste-water surveillance, food security, contact tracing, and their role during this intense period of the pandemic have also been discussed. We expect that the integrated data will be supportive and aid in the evaluation of sensing technologies not only in current but also future pandemics.

Spectroscopy: a versatile sensing tool for cost-effective and rapid detection of novel coronavirus (COVID-19)

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).

Synergistic surface-enhanced Raman scattering effect to distinguish live SARS-CoV-2 S pseudovirus

The COVID-19 pandemic negatively affected the economy and health security on a global scale, causing a drastic change on lifestyle, calling a need to mitigate further transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Surface-enhanced Raman spectroscopy (SERS) has shown great potential in the sensitive and rapid detection of various molecules including viruses, through the identification of characteristic peaks of their outer membrane proteins. Accurate detection can be developed through the synergistic integration effect among SERS-active substrate, the appropriate laser wavelength, and the target analyte. In this study, gold nanocavities (Au NC) and Au nanoparticles upon ZrO2 nano-bowls (Au NPs/pZrO2) were tested and used as SERS-active substrates in detecting SARS-CoV-2 pseudovirus containing S protein as a surface capsid glycoprotein (SARS-CoV-2 S pseudovirus) and vesicular stomatitis virus G (VSV-G) pseudo-type lentivirus (VSV-G pseudovirus) to demonstrate their virus detection capability. The optimized Au NCs and Au NPs/pZrO2 substrates were then verified by examining the repetition of measurement, reproducibility, and detection limit. Due to the difference in geometry and composition of the substrates, the characteristic peak-positions of live SARS-CoV-2 S and VSV-G pseudoviruses in the obtained Raman spectra vary, which were also compared with those of inactivated ones. Based on the experimental results, SERS mechanism of each substrate to detect virus is proposed. The formation of hot spots brought by the synergistic integration effect among substrate, analyte, and laser induction may result differences in the obtained SERS spectra.

Determination of the denaturation temperature of the Spike protein S1 of SARS-CoV-2 (2019 nCoV) by Raman spectroscopy

In the present work the temperature response of the constitutive S1 segment of the SARS-CoV-2 Spike Glycoprotein (GPS) has been studied. The intensity of the Raman bands remained almost constant before reaching a temperature of 133 °C. At this temperature a significant reduction of peak intensities was observed. Above 144 °C the spectra ceased to show any recognizable feature as that of the GPS S1, indicating that it had transformed after the denaturation process that it was subjected. The GPS S1 change is irreversible. Hence, Raman Spectroscopy (RS) provides a precision method to determine the denaturation temperature (T_D) of dry powder GPS S1. The ability of RS was calibrated through the reproduction of T_D of other well studied proteins as well as those of the decomposition temperature of some amino acids (AA). Through this study we established a T_D of 139 ± 3 °C for powder GPS S1 of SARS-CoV-2.

Raman Scattering-Based Biosensing: New Prospects and Opportunities

The growing interest in the development of new platforms for the application of Raman spectroscopy techniques in biosensor technologies is driven by the potential of these techniques in identifying chemical compounds, as well as structural and functional features of biomolecules. The effect of Raman scattering is a result of inelastic light scattering processes, which lead to the emission of scattered light with a different frequency associated with molecular vibrations of the identified molecule. Spontaneous Raman scattering is usually weak, resulting in complexities with the separation of weak inelastically scattered light and intense Rayleigh scattering. These limitations have led to the development of various techniques for enhancing Raman scattering, including resonance Raman spectroscopy (RRS) and nonlinear Raman spectroscopy (coherent anti-Stokes Raman spectroscopy and stimulated Raman spectroscopy). Furthermore, the discovery of the phenomenon of enhanced Raman scattering near metallic nanostructures gave impetus to the development of the surface-enhanced Raman spectroscopy (SERS) as well as its combination with resonance Raman spectroscopy and nonlinear Raman spectroscopic techniques. The combination of nonlinear and resonant optical effects with metal substrates or nanoparticles can be used to increase speed, spatial resolution, and signal amplification in Raman spectroscopy, making these techniques promising for the analysis and characterization of biological samples. This review provides the main provisions of the listed Raman techniques and the advantages and limitations present when applied to life sciences research. The recent advances in SERS and SERS-combined techniques are summarized, such as SERRS, SE-CARS, and SE-SRS for bioimaging and the biosensing of molecules, which form the basis for potential future applications of these techniques in biosensor technology. In addition, an overview is given of the main tools for success in the development of biosensors based on Raman spectroscopy techniques, which can be achieved by choosing one or a combination of the following approaches: (i) fabrication of a reproducible SERS substrate, (ii) synthesis of the SERS nanotag, and (iii) implementation of new platforms for on-site testing.

Ultra-sensitive and fast optical detection of the spike protein of the SARS-CoV-2 using AgNPs/SiNWs nanohybrid based sensors

Severe acute respiratory syndrome SARS-CoV-2 virus led to notable challenges amongst researchers in view of development of new and fast detecting techniques. In this regard, surface-enhanced Raman spectroscopy (SERS) technique, providing a fingerprint characteristic for each material, would be an interesting approach. The current study encompasses the fabrication of a SERS sensor to study the SARS-CoV-2 S1 (RBD) spike protein of the SARS-CoV-2 virus family. The SERS sensor consists of a silicon nanowires (SiNWs) substrate decorated with plasmonic silver nanoparticles (AgNPs). Both SiNWs fabrication and AgNPs decoration were achieved by a relatively simple wet chemical processing method. The study deliberately projects the factors that influence the growth of silicon nanowires, uniform decoration of AgNPs onto the SiNWs matrix along with detection of Rhodamine-6G (R6G) to optimize the best conditions for enhanced sensing of the spike protein. Increasing the time period of etching process resulted in enhanced SiNWs' length from 0.55 to 7.34 µm. Furthermore, the variation of the immersion time in the decoration process of AgNPs onto SiNWs ensued the optimum time period for the enhancement in the sensitivity of detection. Tremendous increase in sensitivity of R6G detection was perceived on SiNWs etched for 2 min (length=0.90 µm), followed by 30s of immersion time for their optimal decoration by AgNPs. These SiNWs/AgNPs SERS-based sensors were able to detect the spike protein at a concentration down to 9.3 × 10^-12 M. Strong and dominant peaks at 1280, 1404, 1495, 1541 and 1609 cm^-1 were spotted at a fraction of a minute. Moreover, direct, ultra-fast, facile, and affordable optoelectronic SiNWs/AgNPs sensors tuned to function as a biosensor for detecting the spike protein even at a trace level (pico molar concentration). The current findings hold great promise for the utilization of SERS as an innovative approach in the diagnosis domain of infections at very early stages.