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

Single-molecule detection of SARS-CoV-2 N protein on multilayered plasmonic nanotraps with surface-enhanced Raman spectroscopy

The spread of the SARS-CoV-2 virus has had an unprecedented impact, both by posing a serious risk to human health and by amplifying the burden on the global economy. The rapid identification of the SARS-CoV-2 virus has been crucial to preventing and controlling the spread of SARS-CoV-2 infections. In this study, we propose a multilayered plasmonic nanotrap (MPNT) device for the rapid identification of single particles of SARS-CoV-2 virus in ultra-high sensitivity by surface-enhanced Raman scattering (SERS). The MPNT device is composed of arrays of concentric cylindrical cavities with Ag/SiO2/Ag multilayers deposited on the top and at the bottom. By varying the diameter of the cylinders and the thickness of the multilayers, the resonant optical absorption and local electric field were optimized. The SERS enhancement factors of the proposed device are of the order of 108, which enable the rapid identification of SARS-CoV-2 N protein in concentrations as low as 1.25 × 10-15－12.5 × 10-15 g mL-1 within 1 min. The developed MPNT SERS device provides a label-free and rapid detection platform for SARS-CoV-2 virus. The general nature of the device makes it equally suitable to detect other infectious viruses.

Sensitivity-improved SERS detection of SARS-CoV-2 spike protein by Au NPs/COFs integrated with catalytic-hairpin-assembly amplification technology

BACKGROUND

The COVID-19 pandemic, caused by the novel coronavirus, has had a profound impact on global health and economies worldwide. This unprecedented crisis has affected individuals, communities, and nations in diverse manners. Developing simple and accurate diagnostic methods is an imperative task for frequent testing to mitigate the spread of the virus. Among these methods, SARS-CoV-2 antigen tests in clinical specimens have emerged as a promising diagnostic method for COVID-19 due to their sensitive and accurate detection of spike (S) protein, which plays a crucial role in viral infection initiation.

RESULTS

In this work, a dual-signal amplification surface enhanced Raman scattering (SERS)-based S protein biosensor was constructed based on Au NPs/COFs and enzyme-free catalytic hairpin assembly (CHA) amplification method. The approach relies on a released free DNA sequence (T), which is generated from the competition reaction between Aptamer/T and Aptamer/S protein, to trigger a CHA reaction. Due to the high binding affinity and selectivity between the S protein and its aptamer, CHA process was triggered with the maximum SERS tags (H2-conjugated Au@4-mercaptobenzonitrile@Ag) anchored onto Au NPs/COFs substrate surface. This SERS platform could detect the S protein at concentrations with high sensitivity (limit of detection = 3.0 × 10-16 g/mL), wide detection range (1 × 10-16 to 1 × 10-11 g/mL), acceptable reproducibility (relative standard deviation = 7.01 %) and excellent specificity. The biosensor was also employed to detect S protein in artificial human salivas.

SIGNIFICANCE

Thus, this study not only developed a novel Au NPs/COFs substrate exhibiting strong SERS enhancement ability and high reproducibility, but also proposed a promising dual-signal amplification SERS-based diagnostic method for COVID-19, holding immense potential for the detection of a wide range of antigens and infectious diseases in future applications.

Rapid Detection of SARS-CoV-2 Variants Using an Angiotensin-Converting Enzyme 2-Based Surface-Enhanced Raman Spectroscopy Sensor Enhanced by CoVari Deep Learning Algorithms

An integrated approach combining surface-enhanced Raman spectroscopy (SERS) with a specialized deep learning algorithm to rapidly and accurately detect and quantify SARS-CoV-2 variants is developed based on an angiotensin-converting enzyme 2 (ACE2)-functionalized AgNR@SiO2 array SERS sensor. SERS spectra with concentrations of different variants were collected using a portable Raman system. After appropriate spectral preprocessing, a deep learning algorithm, CoVari, is developed to predict both the viral variant species and concentrations. Using a 10-fold cross-validation strategy, the model achieves an average accuracy of 99.9% in discriminating between different virus variants and R2 values larger than 0.98 for quantifying viral concentrations of the three viruses, demonstrating the high quality of the detection. The limit of detection of the ACE2 SERS sensor is determined to be 10.472, 11.882, and 21.591 PFU/mL for SARS-CoV-2, SARS-CoV-2 B1, and CoV-NL63, respectively. The feature importance of virus classification and concentration regression in the CoVari algorithm are calculated based on a permutation algorithm, which showed a clear correlation to the biochemical origins of the spectra or spectral changes. In an unknown specimen test, classification accuracy can achieve >90% for concentrations larger than 781 PFU/mL, and the predicted concentrations consistently align with actual values, highlighting the robustness of the proposed algorithm. Based on the CoVari architecture and the output vector, this algorithm can be generalized to predict both viral variant species and concentrations simultaneously for a broader range of viruses. These results demonstrate that the SERS + CoVari strategy has the potential for rapid and quantitative detection of virus variants and potentially point-of-care diagnostic platforms.

Optical biosensors for diagnosis of COVID-19: nanomaterial-enabled particle strategies for post pandemic era

The COVID-19 pandemic underlines the need for effective strategies for controlling virus spread and ensuring sensitive detection of SARS-CoV-2. This review presents the potential of nanomaterial-enabled optical biosensors for rapid and low-cost detection of SARS-CoV-2 biomarkers, demonstrating a comprehensive analysis including colorimetric, fluorescence, surface-enhanced Raman scattering, and surface plasmon resonance detection methods. Nanomaterials including metal-based nanomaterials, metal-organic frame-based nanoparticles, nanorods, nanoporous materials, nanoshell materials, and magnetic nanoparticles employed in the production of optical biosensors are presented in detail. This review also discusses the detection principles, fabrication methods, nanomaterial synthesis, and their applications for the detection of SARS-CoV-2 in four categories: antibody-based, antigen-based, nucleic acid-based, and aptamer-based biosensors. This critical review includes reports published in the literature between the years 2021 and 2024. In addition, the review offers critical insights into optical nanobiosensors for the diagnosis of COVID-19. The integration of artificial intelligence and machine learning technologies with optical nanomaterial-enabled biosensors is proposed to improve the efficiency of optical diagnostic systems for future pandemic scenarios.

Delayed Collagen Production without Myofibroblast Formation Contributes to Reduced Scarring in Adult Skin Microwounds

In adult mammals, wound healing predominantly follows a fibrotic pathway, culminating in scar formation. However, cutaneous microwounds generated through fractional photothermolysis, a modality that produces a constellation of microthermal zones, exhibit a markedly different healing trajectory. Our study delineates the cellular attributes of these microthermal zones, underscoring a temporally limited, subclinical inflammatory milieu concomitant with rapid re-epithelialization within 24 hours. This wound closure is facilitated by the activation of genes associated with keratinocyte migration and differentiation. In contrast to macrothermal wounds, which predominantly heal through a robust myofibroblast-mediated collagen deposition, microthermal zones are characterized by absence of wound contraction and feature delayed collagen remodeling, initiating 5-6 weeks after injury. This distinct wound healing is characterized by a rapid re-epithelialization process and a muted inflammatory response, which collectively serve to mitigate excessive myofibroblast activation. Furthermore, we identify an initial reparative phase characterized by a heterogeneous extracellular matrix protein composition, which precedes the delayed collagen remodeling. These findings extend our understanding of cutaneous wound healing and may have significant implications for the optimization of therapeutic strategies aimed at mitigating scar formation.

Afterglow Nanoprobe-Enabled Quantitative Lateral Flow Immunoassay by a Palm-Size Device for Household Healthcare

Lateral flow immunoassay (LFIA), a classical point-of-care testing (POCT) technique, plays an important role in disease screening and healthcare monitoring. However, traditional LFIA is either designed for qualitative analysis or requires expensive equipment for quantification, limiting its use in household diagnosis. In this study, we proposed a new generation of LFIA for household health monitoring by using ultralong organic phosphorescence (UOP) nanomaterials as afterglow nanoprobes with a self-developed palm-size sensing device. The UOP nanoprobes exhibit a phosphorescence signal with a second-level lifetime, which completely avoids the interference from excitation light and biological background fluorescence. Therefore, an ultraminiaturized and low-cost UOP nanosensor was successfully designed by eliminating the complex optical path and filtering systems. We chose an inflammatory factor, C-reactive protein (CRP), for household POCT validation. The whole analysis was completed within 9 min. A limit of detection (LOD) of 0.54 ng/mL of CRP antigen was achieved with high stability and good specificity, which is comparable to laboratory instruments and fully satisfying the clinical diagnosis requirement.

Hierarchical Nanobiosensors at the End of the SARS-CoV-2 Pandemic

Nanostructures have played a key role in the development of different techniques to attack severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Some applications include masks, vaccines, and biosensors. The latter are of great interest for detecting diseases since some of their features allowed us to find specific markers in secretion samples such as saliva, blood, and even tears. Herein, we highlight how hierarchical nanoparticles integrated into two or more low-dimensional materials present outstanding advantages that are attractive for photonic biosensing using their nanoscale functions. The potential of nanohybrids with their superlative mechanical characteristics together with their optical and optoelectronic properties is discussed. The progress in the scientific research focused on using nanoparticles for biosensing a variety of viruses has become a medical milestone in recent years, and has laid the groundwork for future disease treatments. This perspective analyzes the crucial information about the use of hierarchical nanostructures in biosensing for the prevention, treatment, and mitigation of SARS-CoV-2 effects.

Wearable Plasmonic Sensors Engineered via Active-Site Maximization of TiVC MXene for Universal Physiological Monitoring at the Molecular Level

Two-dimensional transition metal carbon/nitrides (MXenes) are promising candidates to revolutionize next-generation wearable sensors as high-performance surface-enhanced Raman scattering (SERS) substrates. However, low sensitivity of pure MXene nanosheets and weak binding force or uncontrolled in situ growth of plasmonic nanoparticles on hybrid MXene composites limit their progress toward universal and reliable sensors. Herein, we designed and manufactured a highly sensitive, structurally stable wearable SERS sensor by in situ fabrication of plasmonic nanostructures on the flexible TiVC membranes via the maximization of chemically reducing sites using alkaline treatment. DFT calculations and experimental characterization demonstrated that the hydroxyl functional groups on the surface of MXenes can facilitate the reduction of metal precursors and the nucleation of gold nanoparticles (AuNPs) and can be covalently attached to AuNPs. Thus, the fabricated flexible TiVC-OH-Au sensor satisfied the rigorous mechanical requirements for wearable sensors. In addition, combining the electromagnetic (EM) enhancement from dense AuNPs formed by the activation of nucleation sites and charge transfer (CT) between target molecule and substrate induced by the abundant DOS near the Fermi level of TiVC, the fabricated sensor exhibits ultrasensitivity, long-term stability, good signal repeatability, and excellent mechanical durability. Moreover, the proof-of-concept application of the wearable SERS sensor in sweat sensing was demonstrated to monitor the content of nicotine, methotrexate, nikethamide, and 6-acetylmorphine in sweat at the molecular level, which was an important step toward the universality and practicality of the wearable sensing technology.

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

BACKGROUND

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

RESULTS

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

SIGNIFICANCE

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

Plasmon resonance biosensor for interleukin-1β point-of-care determination: A tool for early periodontitis diagnosis

Among pro-inflammatory cytokines, Interleukin-1β is crucially involved in several inflammatory-based diseases and even cancer. Increased Interleukin-1β levels in oral fluids have been proposed as an early marker of periodontitis, a broadly diffused chronic inflammatory condition of periodontal-supporting tissues, leading eventually to tooth loss. We describe the development of a portable surface-plasmon-resonance-based optical fiber probe suitably coated with an anti-Interleukin-1β antibody monolayer. A pico-nanomolar linear range of determination was obtained in both buffer solution and saliva with a rapid (3 min) incubation and high selectivity in presence of interferents. Higher Interleukin-1β concentration in the saliva of a periodontitis patient compared to a healthy control was determined. These measurements were validated by an automated ELISA system. Our results sustain the potential applicability of the proposed SPR-POF as diagnostic point-of-care device for real-time monitoring of salivary Interleukin-1β, that can support early detection of oral inflammatory-based pathologies and rapid and timely therapeutic decisions.

Revolutionizing SARS-CoV-2 omicron variant detection: Towards faster and more reliable methods

The emergence of the highly contagious Omicron variant of SARS-CoV-2 has inflicted significant damage during the ongoing COVID-19 pandemic. This new variant's significant sequence changes and mutations in both proteins and RNA have rendered many existing rapid detection methods ineffective in identifying it accurately. As the world races to control the spread of the virus, researchers are urgently exploring new diagnostic strategies to specifically detect Omicron variants with high accuracy and sensitivity. In response to this challenge, we have compiled a comprehensive overview of the latest reported rapid detection techniques. These techniques include strategies for the simultaneous detection of multiple SARS-CoV-2 variants and methods for selectively distinguishing Omicron variants. By categorizing these diagnostic techniques based on their targets, which encompass protein antigens and nucleic acids, we aim to offer a comprehensive understanding of the utilization of various recognition elements in identifying these targets. We also highlight the advantages and limitations of each approach. Our work is crucial in providing a more nuanced understanding of the challenges and opportunities in detecting Omicron variants and emerging variants.

Nanomaterial-based biosensors for avian influenza virus: A new way forward

Avian influenza virus (AIV) is a zoonotic virus that can be transmitted from animals to humans. Although human infections are rare, the virus has a high mortality rate when contracted. Appropriate detection methods are thus crucial for combatting this pathogen. There is a growing demand for rapid, selective, and accurate methods of identifying the virus. Numerous biosensors have been designed and commercialized to detect AIV. However, they all have considerable shortcomings. Nanotechnology offers a new way forward. Nanomaterials produce more eco-friendly, rapid, and portable diagnostic systems. They also exhibit high sensitivity and selectivity while achieving a low detection limit (LOD). This paper reviews state-of-the-art nanomaterial-based biosensors for AIV detection, such as those composed of quantum dots, gold, silver, carbon, silica, nanodiamond, and other nanoparticles. It also offers insight into potential trial protocols for creating more effective methods of identifying AIV and discusses key issues associated with developing nanomaterial-based biosensors.

Antibody- and aptamer-free SERS substrate for ultrasensitive and anti-interference detection of SARS-CoV-2 spike protein in untreated saliva

Sensitive and anti-interference detection of targeted signal(s) in body fluids is one of the paramount tasks in biosensing. Overcoming the complication and high cost of antibody/aptamer-modification, surface-enhanced Raman spectroscopy (SERS) based on antibody/aptamer-free (AAF) substrates has shown great promise, yet with rather limited detection sensitivity. Herein, we report ultrasensitive and anti-interference detection of SARS-CoV-2 spike protein in untreated saliva by an AAF SERS substrate, applying the evanescent field induced by the high-order waveguide modes of well-defined nanorods for SERS for the first time. A detection limit of 3.6 × 10-17 M and 1.6 × 10-16 M are obtained in phosphate buffered saline and untreated saliva, respectively; the detection limits are three orders of magnitude improved than the best records from AAF substrates. This work unlocks an exciting path to design AAF SERS substrates for ultrasensitive biosensing, not limited to detection of viral antigens.

Biopanning of specific peptide for SARS-CoV-2 nucleocapsid protein and enzyme-linked immunosorbent assay-based antigen assay

The ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread worldwide which triggered serious public health issues. The search for rapid and accurate diagnosis, effective prevention, and treatment is urgent. The nucleocapsid protein (NP) of SARS-CoV-2 is one of the main structural proteins expressed and most abundant in the virus, and is considered a diagnostic marker for the accurate and sensitive detection of SARS-CoV-2. Herein, we report the screening of specific peptides from the pIII phage library that bind to SARS-CoV-2 NP. The phage monoclone expressing cyclic peptide N1 (peptide sequence, ACGTKPTKFC, with C&C bridged by disulfide bonding) specifically recognizes SARS-CoV-2 NP. Molecular docking studies reveal that the identified peptide is bound to the "pocket" region on the SARS-CoV-2 NP N-terminal domain mainly by forming a hydrogen bonding network and through hydrophobic interaction. Peptide N1 with the C-terminal linker was synthesized as the capture probe for SARS-CoV-2 NP in ELISA. The peptide-based ELISA was capable of assaying SARS-CoV-2 NP at concentrations as low as 61 pg/mL (∼1.2 pM). Furthermore, the as-proposed method could detect the SARS-CoV-2 virus at limits as low as 50 TCID₅₀ (median tissue culture infective dose)/mL. This study demonstrates that selected peptides are powerful biomolecular tools for SARS-CoV-2 detection, providing a new and inexpensive method of rapidly screening infections as well as rapidly diagnosing coronavirus disease 2019 patients.

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

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

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.

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.