Non-enzymatic signal amplification-powered point-of-care SERS sensor for rapid and ultra-sensitive assay of SARS-CoV-2 RNA

Innovative Applications and Perspectives of Surface-Enhanced Raman Spectroscopy Technology in Biomedicine

Surface-enhanced Raman spectroscopy (SERS) has become a revolutionary technique in the biomedical field, providing unparalleled sensitivity for the detection and characterization of biological samples. In this review, recent SERS innovations are comprehensively discussed, including advanced substrate materials, different SERS detection strategies, and multimodal approaches that combine SERS with other biotechnologies. Among them, the role of SERS in the accurate diagnosis of tumors is highlighted, which has promoted accurate molecular analysis and real-time monitoring of treatment effects. In addition, the growing potential of SERS in the treatment of chronic diseases such as cardiovascular disease, diabetes, and neurodegenerative diseases is discussed. Moreover, the integration with microfluidic chip systems for precise single-cell analysis is presented. To give a forward-looking view, the key challenges faced by SERS technology are also proposed, and possible solutions to overcome these obstacles are provided.

Multiplex Detection and Quantification of Virus Co-Infections Using Label-free Surface-Enhanced Raman Spectroscopy and Deep Learning Algorithms

Multiple respiratory viruses can concurrently or sequentially infect the respiratory tract, making their identification crucial for diagnosis, treatment, and disease management. We present a label-free diagnostic platform integrating surface-enhanced Raman scattering (SERS) with deep learning for rapid, quantitative detection of respiratory virus coinfections. Using sensitive silica-coated silver nanorod array substrates, over 1.2 million SERS spectra are collected from 11 viruses, nine two-virus mixtures, and four three-virus mixtures at various concentrations in saliva. A deep learning model, MultiplexCR, is developed to simultaneously predict virus species and concentrations from SERS spectra. It achieves an impressive 98.6% accuracy in classifying virus coinfections and a mean absolute error of 0.028 for concentration regression. In blind tests, the model demonstrates consistent high accuracy and precise concentration predictions. This SERS-MultiplexCR platform completes the entire detection process in just 15 min, offering significant potential for rapid, point-of-care diagnostics in infection detection, as well as applications in food safety and environmental monitoring.

Factors that Affect Quantification in Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering (SERS) is an analytical technique capable of detecting trace amounts of specific species. The uniqueness of vibrational signatures is a major advantage of SERS. This combination of sensitivity and specificity has motivated researchers to develop diverse analytical methodologies leveraging SERS. However, even 50 years after its first observation, SERS is still perceived as an unreliable technique for quantification. This perception has precluded the application of SERS in laboratories that rely on consistent quantification (for regulatory purposes, for instance). In this review, we describe some of the aspects that lead to SERS intensity variations and how those challenges were addressed in the 50 years of the technique. The goal is to identify the sources of variations in SERS intensities and then demonstrate that, even with these pitfalls, the technique can be used for quantification when factors such as nature of the substrate, experimental conditions, sample preparation, surface chemistry, and data analysis are carefully considered and tailored for a particular application.

Recent Plasmonic Gold- and Silver-Assisted Raman Spectra for Advanced SARS-CoV-2 Detection

COVID-19 has become one of the deadliest epidemics in the past years. In efforts to combat the deadly disease besides vaccines, drug therapies, and facemasks, significant focus has been on designing specific methods for the sensitive and accurate detection of SARS-CoV-2. Of these, surface-enhanced Raman scattering (SERS) is an attractive analytical tool for the identification of SARS-CoV-2. SERS is the phenomenon of enhancement of Raman intensity signals from molecular analytes anchored onto the surfaces of roughened plasmonic nanomaterials. This work gives an updated summary of plasmonic gold nanomaterials (AuNMs) and silver nanomaterials (AgNMs)-based SERS technologies to identify SARS-CoV-2. Due to extreme "hot spots" promoting higher electromagnetic fields on their surfaces, different shapes of AuNMs and AgNMs combined with Raman probes have been reviewed for enhancing Raman signals of probe molecules for quantifying the virus. It also reviews progress made recently in the design of certain specific Raman probe molecules capable of imparting characteristic SERS response/tags for SARS-CoV-2 detection.

Advances and Future Trends in Nanozyme-Based SERS Sensors for Food Safety, Environmental and Biomedical Applications

Nanozymes, a kind of nanoparticles with enzyme-mimicking activities, have attracted considerable attention due to their robust catalytic properties, ease of preparation, and resistance to harsh conditions. By combining nanozymes with surface-enhanced Raman spectroscopy (SERS) technology, highly sensitive and selective sensors have been developed. These sensors are capable of detecting a wide range of analytes, such as foodborne toxins, environmental pollutants, and biomedical markers. This review provides an overview of recent advancements in the synthesis and surface modification of nanozymes, highlighting their ability to mimic multiple enzymes and enhance catalytic performance. In addition, we explore the development and applications of nanozyme-based SERS sensors in food contaminants, environmental pollutants, and biomedical markers. The review concludes with perspectives and challenges facing the field, involving the need for deeper understanding of nanozyme principles and mechanisms, development of standardized systems for characterization, and the engineering of nanozymes with tailored properties for specific applications. Finally, we discuss the potential for integrating various techniques with nanozymes to create multi-modal detection platforms, paving the way for the next generation of analytical tools in the fields of food safety, environmental monitoring, and biomedical diagnostics.

In the flow of molecular miniaturized fungal diagnosis

The diagnosis of fungal infections presents several challenges and limitations, stemming from the similarities in symptomatology, diversity of underlying pathogenic species, complexity of fungal biology, and scarcity of rapid, affordable, and point-of-care approaches. In this review, we assess technological advances enabling the conversion of cutting-edge laboratory molecular diagnostic methods to cost-effective microfluidic devices. The most promising strategies toward the design of DNA sequence-based fungal diagnostic systems, capable of capturing and deciphering the highly informative DNA of the pathogen and adapted for resource-limited settings, are discussed, bridging fungal biology, molecular genetics, microfluidics, and biosensors.

CRISPR/Cas13a Trans-Cleavage and Catalytic Hairpin Assembly Cascaded Signal Amplification Powered SERS Aptasensor for Ultrasensitive Detection of Gastric Cancer-Derived Exosomes

Cancer-derived exosomes carry a large number of specific molecular profiles from cancer cells and have emerged as ideal biomarkers for early cancer diagnosis. Accurate detection of ultralow-abundance exosomes in complex biological samples remains a great challenge. Herein, a novel SERS aptasensor powered by cascaded signal amplification of CRISPR/Cas13a trans-cleavage and catalytic hairpin assembly (CHA) was proposed for ultrasensitive detection of gastric cancer-derived exosomes, which included hairpin-structured recognition aptamers (MUC1-apt), cascaded signal amplification (i.e., CRISPR/Cas13a trans-cleavage and CHA), SERS tags, and silver nanorods (AgNRs) sensing chip. In the presence of SGC-7901 cell-derived exosomes, MUC1-apt specifically bound to MUC1 proteins highly expressed on exosomes via its contained MUC1 aptamer with its exposed RNA fragments activating the CRISPR/Cas13a trans-cleavage to cleave the uracil-modified hairpin reporter, and the cleavage products further triggered the downstream CHA reaction to form numerous duplexes, which can, in turn, capture a large number of SERS tags onto the AgNRs sensing chip to generate a significantly enhanced Raman signal. The proposed SERS aptasensor exhibits good performance on analysis of exosomes, i.e., rapid response within 60 min, single-particle sensitive detection from a 2 μL biological sample, good specificity in distinguishing SGC-7901 cell-derived exosomes against other exosomes, good uniformity, excellent repeatability, and satisfactory recoveries in human serum, and good universality to expand the detection of multiplex exosomes, which indicates that the SERS aptasensor provides a valuable reference for clinical diagnosis of early cancer.

Plasmonic nanoparticle sensors: current progress, challenges, and future prospects

Plasmonic nanoparticles (NPs) have played a significant role in the evolution of modern nanoscience and nanotechnology in terms of colloidal synthesis, general understanding of nanocrystal growth mechanisms, and their impact in a wide range of applications. They exhibit strong visible colors due to localized surface plasmon resonance (LSPR) that depends on their size, shape, composition, and the surrounding dielectric environment. Under resonant excitation, the LSPR of plasmonic NPs leads to a strong field enhancement near their surfaces and thus enhances various light-matter interactions. These unique optical properties of plasmonic NPs have been used to design chemical and biological sensors. Over the last few decades, colloidal plasmonic NPs have been greatly exploited in sensing applications through LSPR shifts (colorimetry), surface-enhanced Raman scattering, surface-enhanced fluorescence, and chiroptical activity. Although colloidal plasmonic NPs have emerged at the forefront of nanobiosensors, there are still several important challenges to be addressed for the realization of plasmonic NP-based sensor kits for routine use in daily life. In this comprehensive review, researchers of different disciplines (colloidal and analytical chemistry, biology, physics, and medicine) have joined together to summarize the past, present, and future of plasmonic NP-based sensors in terms of different sensing platforms, understanding of the sensing mechanisms, different chemical and biological analytes, and the expected future technologies. This review is expected to guide the researchers currently working in this field and inspire future generations of scientists to join this compelling research field and its branches.

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.

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.

Bilateral efforts to improve SERS detection efficiency of exosomes by Au/Na7PMo11O39 Combined with Phospholipid Epitope Imprinting

Detection of cancer-related exosomes in body fluids has become a revolutionary strategy for early cancer diagnosis and prognosis prediction. We have developed a two-step targeting detection method, termed PS-MIPs-NELISA SERS, for rapid and highly sensitive exosomes detection. In the first step, a phospholipid polar site imprinting strategy was employed using magnetic PS-MIPs (phospholipids-molecularly imprinted polymers) to selectively isolate and enrich all exosomes from urine samples. In the second step, a nanozyme-linked immunosorbent assay (NELISA) technique was utilized. We constructed Au/Na7PMo11O39 nanoparticles (NPs) with both surface-enhanced Raman scattering (SERS) property and peroxidase catalytic activity, followed by the immobilization of CD9 antibodies on the surface of Au/Na7PMo11O39 NPs. The Au/Na7PMo11O39-CD9 antibody complexes were then used to recognize CD9 proteins on the surface of exosomes enriched by magnetic PS-MIPs. Lastly, the high sensitivity detection of exosomes was achieved indirectly via the SERS activity and peroxidase-like activity of Au/Na7PMo11O39 NPs. The quantity of exosomes in urine samples from pancreatic cancer patients obtained by the PS-MIPs-NELISA SERS technique showed a linear relationship with the SERS intensity in the range of 6.21 × 107-2.81 × 108 particles/mL, with a limit of detection (LOD) of 5.82 × 107 particles/mL. The SERS signal intensity of exosomes in urine samples from pancreatic cancer patients was higher than that of healthy volunteers. This bidirectional MIPs-NELISA-SERS approach enables noninvasive, highly sensitive, and rapid detection of cancer, facilitating the monitoring of disease progression during treatment and opening up a new avenue for rapid early cancer screening.

Accurate and reliable surface-enhanced Raman spectroscopy assay for early detection of SARS-CoV-2 RNA with exceptional sensitivity

This research proposes a highly sensitive and simple surface-enhanced Raman spectroscopy (SERS) assay for the detection of SARS-CoV-2 RNA using suitably designed probes specific for RdRp and N viral genes attached to a Raman marker. The sensitivity of the assay was optimized through precise adjustments to the conditions of immobilization and hybridization processes of the target RNA, including modifications to factors such as time and temperature. The assay achieved a remarkable sensitivity down to 58.39 copies/mL, comparable to or lower than the sensitivities reported for commercial fluorescent polymerase chain reaction (PCR) based methods. It has good selectivity in discriminating SARS-CoV-2 RNA against other respiratory viruses, respiratory syncytial virus (RSV), and influenza A virus. The reliability of the assay was validated by testing 24 clinical samples, including 12 positive samples with varying cycle threshold (Ct) values and 12 negative samples previously tested using real-time PCR. The assay consistently predicted true results that were in line with the PCR results for all samples. Furthermore, the assay demonstrated a notable limit of detection (LOD) of Ct (38 for RdRp gene and 37.5 for N-gene), indicating its capability to detect low concentrations of the target analyte and potentially facilitating early detection of the pathogen.

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.

Synergistic photoinduced charge transfer resonance from porous ZIF-67 decorated violet phosphorus array for SERS immunoassay of SARS-CoV-2 spike protein

As a rapid, highly sensitive, and user-friendly technique, surface-enhanced Raman scattering (SERS) has an extraordinary appeal to home self-test of COVID-19 during the post pandemic era. However, most of the existing SERS substrates have been still criticized in stability, repeatability, and sample enrichment. To address these obstacles, a novel non-metallic SERS substrate with porous surfaces and array geometry was developed by in-situ growing ZIF-67 particles on two-dimensional violet phosphorus (VP) matrix. Chemical enhancement was prominently promoted by the synergistic photoinduced charge transfer resonance in the hybrid band structure of the ZIF-67@VP substrate, facilitating a noble metal-similar enhancement factor of 6.11 × 107. The biocompatible ZIF-67@VP porous array with attractive enhancement capability and high anchoring efficiency was further utilized to monitoring SARS-CoV-2 spike protein in practical saliva samples based on a sandwich immunostructure, achieving a limit of detection of 1.7 ng/mL assisted by black phosphorus nanosheets. This nonmetallic immunoassay strategy with exceptional sensitivity and specificity is predicted to extend the utilization of SERS obstacle in daily infectious disease screening.

Deciphering biomolecular complexities: the indispensable role of surface-enhanced Raman spectroscopy in modern bioanalytical research

Surface-enhanced Raman spectroscopy (SERS) has emerged as an indispensable analytical tool in biomolecular research, providing unmatched sensitivity critical for the elucidation of biomolecular structures. This review presents a thorough examination of SERS, outlining its fundamental principles, cataloging its varied applications within the biomolecular sphere, and contemplating its future developmental trajectories. We begin with a detailed analysis of SERS's mechanistic principles, emphasizing both the phenomena of surface enhancement and the complexities inherent in Raman scattering spectroscopy. Subsequently, we delve into the pivotal role of SERS in the structural analysis of diverse biomolecules, including proteins, nucleic acids, lipids, carbohydrates, and biochromes. The remarkable capabilities of SERS extend beyond mere detection, offering profound insights into biomolecular configurations and interactions, thereby enriching our comprehension of intricate biological processes. This review also sheds light on the application of SERS in real-time monitoring of various bio-relevant compounds, from enzymes and coenzymes to metal ion-chelate complexes and cellular organelles, thereby providing a holistic view and empowering researchers to unravel the complexities of biological systems. We also address the current challenges faced by SERS, such as enhancing sensitivity and resolution, developing stable and reproducible substrates, and conducting thorough analyses in complex biological matrices. Nonetheless, the continual advancements in nanotechnology and spectroscopy solidify the standing of SERS as a formidable force in biomolecular research. In conclusion, the versatility and robustness of SERS not only deepen our understanding of biomolecular intricacies but also pave the way for significant developments in medical research, therapeutic innovation, and diagnostic approaches.

High Accuracy of Clinical Verification of Electrohydrodynamic-Driven Nanobox-on-Mirror Platform for Molecular Identification of Respiratory Viruses

The molecular detection of multiple respiratory viruses provides evidence for the rational use of drugs and effective health management. Herein, we developed and tested the clinical performance of an electrohydrodynamic-driven nanobox-on-mirror platform (E-NoM) for the parallel, accurate, and sensitive detection of four respiratory viral antigens. The E-NoM platform uses gold-silver alloy nanoboxes as the core material with the deposition of a silver layer as a shell on the core surfaces to amplify and enable a reproducible Raman signal readout that facilitates accurate detection. Additionally, the E-NoM platform employs gold microelectrode arrays as the mirror with electrohydrodynamics to manipulate the fluid flow and enhance molecular interactions for an improved biosensing response. The presence of viral antigens binds the nanobox-based core-shell nanostructure on the gold microelectrode and creates the nanocavity with extremely strong "hot spots" to benefit sensitive analysis. Significantly, in a large clinical cohort with 227 patients, the designed E-NoM platform demonstrates the capability of screening respiratory infection with achieved clinical specificity, sensitivity, and accuracy of 100.0, 96.48, and 96.91%, respectively. It is anticipated that the E-NoM platform can find a position in clinical usage for respiratory disease diagnosis.

Engineered aptamers for molecular imaging

Molecular imaging, including quantification and molecular interaction studies, plays a crucial role in visualizing and analysing molecular events occurring within cells or organisms, thus facilitating the understanding of biological processes. Moreover, molecular imaging offers promising applications for early disease diagnosis and therapeutic evaluation. Aptamers are oligonucleotides that can recognize targets with a high affinity and specificity by folding themselves into various three-dimensional structures, thus serving as ideal molecular recognition elements in molecular imaging. This review summarizes the commonly employed aptamers in molecular imaging and outlines the prevalent design approaches for their applications. Furthermore, it highlights the successful application of aptamers to a wide range of targets and imaging modalities. Finally, the review concludes with a forward-looking perspective on future advancements in aptamer-based molecular imaging.

A non-enzymatic test for SARS-CoV-2 RNA using DNA nanoswitches

The emergence of a highly contagious novel coronavirus in 2019 led to an unprecedented need for large scale diagnostic testing. The associated challenges including reagent shortages, cost, deployment delays, and turnaround time have all highlighted the need for an alternative suite of low-cost tests. Here, we demonstrate a diagnostic test for SARS-CoV-2 RNA that provides direct detection of viral RNA and eliminates the need for costly enzymes. We employ DNA nanoswitches that respond to segments of the viral RNA by a change in shape that is readable by gel electrophoresis. A new multi-targeting approach samples 120 different viral regions to improve the limit of detection and provide robust detection of viral variants. We apply our approach to a cohort of clinical samples, positively identifying a subset of samples with high viral loads. Since our method directly detects multiple regions of viral RNA without amplification, it eliminates the risk of amplicon contamination and renders the method less susceptible to false positives. This new tool can benefit the COVID-19 pandemic and future emerging outbreaks, providing a third option between amplification-based RNA detection and protein antigen detection. Ultimately, we believe this tool can be adapted both for low-resource onsite testing as well as for monitoring viral loads in recovering patients.

Nanotechnology-Assisted Biosensors for the Detection of Viral Nucleic Acids: An Overview

The accurate and rapid diagnosis of viral diseases has garnered increasing attention in the field of biosensors. The development of highly sensitive, selective, and accessible biosensors is crucial for early disease detection and preventing mortality. However, developing biosensors optimized for viral disease diagnosis has several limitations, including the accurate detection of mutations. For decades, nanotechnology has been applied in numerous biological fields such as biosensors, bioelectronics, and regenerative medicine. Nanotechnology offers a promising strategy to address the current limitations of conventional viral nucleic acid-based biosensors. The implementation of nanotechnologies, such as functional nanomaterials, nanoplatform-fabrication techniques, and surface nanoengineering, to biosensors has not only improved the performance of biosensors but has also expanded the range of sensing targets. Therefore, a deep understanding of the combination of nanotechnologies and biosensors is required to prepare for sanitary emergencies such as the recent COVID-19 pandemic. In this review, we provide interdisciplinary information on nanotechnology-assisted biosensors. First, representative nanotechnologies for biosensors are discussed, after which this review summarizes various nanotechnology-assisted viral nucleic acid biosensors. Therefore, we expect that this review will provide a valuable basis for the development of novel viral nucleic acid biosensors.

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

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

Ultrasensitive detection of SARS-CoV-2 S protein with aptamers biosensor based on surface-enhanced Raman scattering

A rapid and accurate diagnostic modality is essential to prevent the spread of SARS-CoV-2. In this study, we proposed a SARS-CoV-2 detection sensor based on surface-enhanced Raman scattering (SERS) to achieve rapid and ultrasensitive detection. The sensor utilized spike protein deoxyribonucleic acid aptamers with strong affinity as the recognition entity to achieve high specificity. The spherical cocktail aptamers-gold nanoparticles (SCAP) SERS substrate was used as the base and Au nanoparticles modified with the Raman reporter molecule that resonates with the excitation light and spike protein aptamers were used as the SERS nanoprobe. The SCAP substrate and SERS nanoprobes were used to target and capture the SARS-CoV-2 S protein to form a sandwich structure on the Au film substrate, which can generate ultra-strong "hot spots" to achieve ultrasensitive detection. Analysis of SARS-CoV-2 S protein was performed by monitoring changes in SERS peak intensity on a SCAP SERS substrate-based detection platform. This assay detects S protein with a LOD of less than 0.7 fg mL^-1 and pseudovirus as low as 0.8 TU mL^-1 in about 12 min. The results of the simulated oropharyngeal swab system in this study indicated the possibility of it being used for clinical detection, providing a potential option for rapid and accurate diagnosis and more effective control of SARS-CoV-2 transmission.

Needs, Challenges and Countermeasures of SARS-CoV-2 Surveillance in Cold-Chain Foods and Packaging to Prevent Possible COVID-19 Resurgence: A Perspective from Advanced Detections

The pandemic caused by SARS-CoV-2 has a huge impact on the global economy. SARS-CoV-2 could possibly and potentially be transmitted to humans through cold-chain foods and packaging (namely good-to-human), although it mainly depends on a human-to-human route. It is imperative to develop countermeasures to cope with the spread of viruses and fulfil effective surveillance of cold-chain foods and packaging. This review outlined SARS-CoV-2-related cold-chain food incidents and current methods for detecting SARS-CoV-2. Then the needs, challenges and practicable countermeasures for SARS-CoV-2 detection, specifically for cold-chain foods and packaging, were underlined. In fact, currently established detection methods for SARS-CoV-2 are mostly used for humans; thus, these may not be ideally applied to cold-chain foods directly. Therefore, it creates a need to develop novel methods and low-cost, automatic, mini-sized devices specifically for cold-chain foods and packaging. The review intended to draw people's attention to the possible spread of SARS-CoV-2 with cold-chain foods and proposed perspectives for futuristic cold-chain foods monitoring during the pandemic.

Recent Development in Plasmonic Nanobiosensors for Viral DNA/RNA Biomarkers

Recently, due to the coronavirus pandemic, the need for early diagnosis of infectious diseases, including viruses, is emerging. Though early diagnosis is essential to prevent infection and progression to severe illness, there are few technologies that accurately measure low concentrations of biomarkers. Plasmonic nanomaterials are attracting materials that can effectively amplify various signals, including fluorescence, Raman, and other optical and electromagnetic output. In this review, we introduce recently developed plasmonic nanobiosensors for measuring viral DNA/RNA as potential biomarkers of viral diseases. In addition, we discuss the future perspective of plasmonic nanobiosensors for DNA/RNA detection. This review is expected to help the early diagnosis and pathological interpretation of viruses and other diseases.