Development of a multiplex real-time PCR assay for the simultaneous detection of mpox virus and orthopoxvirus infections

Since May 2022, the multi-country outbreak of monkeypox (mpox) has raised a great concern worldwide. Early detection of mpox virus infection is recognized as an efficient way to prevent mpox transmission. Mpox specific detection methods reported up to now are based on the SNPs among mpox virus and other orthopoxviruses. We have therefore developed a real-time PCR based mpox detection method targeting mpox virus specific sequences (N3R and B18Rplus). We have also optimized an orthopoxvirus detection system which targets the highly conserved E9L and D6R genes. The mpox and orthopoxvirus real-time PCR assays have a high sensitivity (1 copy/reaction) and specificity. Mpox viral DNA and clinical samples from mpox patients are detected with the mpox detection system. Furthermore, we have established a multiplex real-time PCR detection system allowing simultaneous and efficient detection of mpox and orthopoxvirus infections.

Natural selection directing molecular evolution in vertebrate viral sensors

Diseases caused by pathogens contribute to molecular adaptations in host immunity. Variety of viral pathogens challenging animal immunity can drive positive selection diversifying receptors recognising the infections. However, whether distinct virus sensing systems differ across animals in their evolutionary modes remains unclear. Our review provides a comparative overview of natural selection shaping molecular evolution in vertebrate viral-binding pattern recognition receptors (PRRs). Despite prevailing negative selection arising from the functional constraints, multiple lines of evidence now suggest diversifying selection in the Toll-like receptors (TLRs), NOD-like receptors (NLRs), RIG-I-like receptors (RLRs) and oligoadenylate synthetases (OASs). In several cases, location of the positively selected sites in the ligand-binding regions suggests effects on viral detection although experimental support is lacking. Unfortunately, in most other PRR families including the AIM2-like receptor family, C-type lectin receptors (CLRs), and cyclic GMP-AMP synthetase studies characterising their molecular evolution are rare, preventing comparative insight. We indicate shared characteristics of the viral sensor evolution and highlight priorities for future research.

Investigation and characterization of rice dwarfing epidemic caused by southern rice black-streaked dwarf virus in Jiangsu in 2023

During the field surveys in Jiangsu Province, China, contiguous patches of rice plants with varying degrees of dwarfing, wax-white or dark brown enations at the base of stems, and abnormal heading symptoms were observed in the fields located in Jiangning District in Nanjing City, Jurong County in Zhenjiang City, and Zhangjiagang County in Suzhou City. Through molecular analyses, the presence of southern rice black-streaked dwarf virus was confirmed in symptomatic rice plants. The infections of other rice viruses that cause dwarfing were also ruled out. Additionally, Koch's postulates were fulfilled, further validating SRBSDV as the causal agent for the observed dwarfing disease epidemic. Furthermore, the phylogenetic analyses revealed that the SRBSDV prevalent in Jiangsu in 2023 may originate from multiple regions in Vietnam. Our study has documented the emergence of an SRBSDV epidemic in Jiangsu in 2023, marking the first incidence of southern rice black-streaked dwarf disease in this region.

Dual-Mode Virus Detection: Combining Electrochemical and Fluorescence Modalities for Enhanced Sensitivity and Reliability

This study introduces a dual-mode biosensor specifically designed for the quantitative detection of viruses in rapid analysis. The biosensor is unique in its use of both optical (fluorescence) and electrochemical (impedance) detection methods using the same nanocomposites, providing a dual confirmation system for virus (norovirus-like particles) quantification. The system is based on using two antibody-conjugated nanocomposites: CdSeS quantum dots and Au-N,S-GQD nanocomposites. For optical detection, the principle relies on the fluorescence quenching of CdSeS by Au-N,S-GQD in a sandwich structure with the target. Conversely, electrochemical detection is based on the change in impedance caused by the formation of the same sandwich structure. The biosensor demonstrated exceptional sensitivity, capable of detecting norovirus at concentrations of as low as femtomolar in the electrochemical method and picomolar in the optical method. In the dual-responsive concentration range from 10-13 to 10-10 M, the sensor is highly sensitive in both methods, creating significant changes in fluorescence intensity and impedance in the presence of virus. Furthermore, the biosensor exhibits a high degree of specificity, with a negligible response to nontarget proteins, even within complex test solutions. This work represents a significant advancement in the field of biosensor technology, offering a fast, accurate, and reliable method for diagnosing viral infections and diseases.

Trends and challenges in electroanalytical biosensing methodologies for infectious viral diseases

Viral pandemic diseases have disruptive global consequences leading to millions of deaths and a severe impact on the global economy. Inadequate preventative protocols have led to an overwhelming demand for intensive care leading to uncontrollable burdens and even breakdown of healthcare sectors across many countries. The rapid detection of viral disease helps in the understanding of the relevant intricacies, helping to tackle infection with improved guidelines. Portable biosensor devices offer promising solutions by facilitating on-site detection of viral pathogens. This review summarizes the latest innovative strategies reported using electroanalytical methods for the screening of viral antigens. The structural components of viruses and their categories are presented followed by the various recognition elements and transduction techniques involved in biosensors. Core sections focus on biosensors reported for viral genomic detection(DNA and RNA) and antigenic capsid protein. Strategies for addressing the challenges of electroanalytical biosensing of viral components are also presented. The advantages, and disadvantages of biorecognition elements and nanozymes for the detection of viral disease are highlighted. Such technical insights will help researchers working in chemistry, and biochemistry as well as clinicians working in medical diagnostics.

On the feasibility of Vis-NIR spectroscopy and machine learning for real time SARS-CoV-2 detection

The pandemic caused by Covid-19 is still present around the world. Despite advances in combating the disease, such as vaccine development, identifying infected individuals is still essential to optimize the control of human-to-human transmission of the virus. The main technique for detecting the virus is the RT-PCR method, which, despite its high relative cost, has a high accuracy in detecting the coronavirus. Given this, a method capable of performing the identification quickly, accurately, and inexpensively is necessary. Thus, this work aimed to analyze the feasibility of a new technique for identifying SARS-CoV-2 through the use of optical spectroscopy in the visible and near-infrared range (Vis-NIR) combined with machine learning algorithms. Spectral signals were obtained from nasopharyngeal swab samples previously analyzed using the RT-PCR method. The specimens were provided by the Molecular Diagnosis Laboratory of Covid-19 at Univasf. A total of 314 samples were analyzed, comprising 42 testing positive and 272 testing negative for Covid-19. Digital signal processing techniques, such as Savitzky-Golay filters and statistical methods were used to eliminate spurious elements from the original data and extract relevant features. Supervised machine learning algorithms such as SVM, Random Forest, and Naive Bayes classifiers were used to perform automatic sample identification. To evaluate the performance of the models, a 5-fold cross-validation technique was applied. With the proposed methodology, it was possible to achieve an accuracy of 75%, a sensitivity of 80%, and a specificity of 70%, in addition to an area under the ROC curve of 0.81, in the identification of nasopharyngeal swab samples from previously diagnosed individuals. From these results, it was possible to conclude that Vis-NIR spectroscopy is a promising, fast and relatively low cost technique to identify the SARS-CoV-2.

Point-of-care dengue detection: polydopamine-modified electrode for rapid NS1 protein testing for clinical samples

Early diagnosis of dengue infection by detecting the dengue virus non-structural protein 1 (DENV-NS1) is important to the patients to initiate speedy treatment. Enzyme-linked immunosorbent assay (ELISA)-based NS1 detection and RT-PCR are time-consuming and too complex to be employed in remote areas of dengue-endemic countries. Meanwhile, those of NS1 rapid test by lateral flow assay suffer from low detection limit. Electrochemical-based biosensors using screen-printed gold electrodes (SPGEs) have become a reliable detection method to convey both ELISA's high sensitivity and rapid test portability. In this research, we developed an electrochemical biosensor for DENV-NS1 detection by employing polydopamine (PDA)-modified SPGE. The electrodeposition of PDA on the surface of SPGE serves as a bioconjugation avenue for anti-NS1 antibody through a simple and low-cost immobilization procedure. The biosensor performance was evaluated to detect DENV-NS1 protein in PBS and human serum through a differential pulse voltammetric (DPV) technique. The developed sensing platform displayed a low limit of detection (LOD) of 1.63 pg mL-1 and a wide linear range of 10 pg mL-1 to 1 ng mL-1 (R2 ∼ 0.969). The sensing platform also detected DEV-NS1 from four different serotypes in the clinical samples collected from dengue patients in India and Indonesia, with acceptable sensitivity, specificity, and accuracy values of 90.00%, 80.95%, and 87.65%, respectively. This result showcased the facile and versatile method of PDA coating onto the surface of screen-printed gold electrodes for a miniaturized point-of-care (PoC) detection device.

Food and Environmental Virology: Use of Passive Sampling to Characterize the Presence of SARS-CoV-2 and Other Viruses in Wastewater

Fecal shedding of SARS-CoV-2 leads to a renaissance of wastewater-based epidemiology (WBE) as additional tool to follow epidemiological trends in the catchment of treatment plants. As alternative to the most commonly used composite samples in surveillance programs, passive sampling is increasingly studied. However, the many sorbent materials in different reports hamper the comparison of results and a standardization of the approach is necessary. Here, we compared different cost-effective sorption materials (cheesecloths, gauze swabs, electronegative filters, glass wool, and tampons) in torpedo-style housings with composite samples. Despite a remarkable variability of the concentration of SARS-CoV-2-specific gene copies, analysis of parallel-deposited passive samplers in the sewer demonstrated highest rate of positive samples and highest number of copies by using cheesecloths. Using this sorption material, monitoring of wastewater of three small catchments in the City of Dresden resulted in a rate of positive samples of 50% in comparison with composite samples (98%). During the investigation period, incidence of reported cases of SARS-CoV-2 in the catchments ranged between 16 and 170 per 100,000 persons and showed no correlation with the measured concentrations of E gene in wastewater. In contrast, constantly higher numbers of gene copies in passive vs. composite samples were found for human adenovirus and crAssphage indicating strong differences of efficacy of methods concerning the species investigated. Influenza virus A and B were sporadically detected allowing no comparison of results. The study contributes to the further understanding of possibilities and limits of passive sampling approaches in WBE.

Signal-Amplified Nanobiosensors for Virus Detection Using Advanced Nanomaterials

Rapid diagnosis and treatment of infectious illnesses are crucial for clinical outcomes and public health. Biosensing developments enhance diagnostics at the point of care. This is superior to traditional procedures, which need centralized lab facilities, specialized personnel, and large equipment. The emerging coronavirus epidemic threatens global health and economic security. Increasing viral surveillance and regulatory actions against disease transmission necessitate rapid, sensitive testing tools for viruses. Due to their sensitivity and specificity, biosensors offer a possible reliable and quantifiable viral detection method. Current advances in genetic engineering, such as genetic alteration and material engineering, have provided several opportunities to enhance biosensors' sensitivity, selectivity, and recognition efficiency. This chapter explains biosensing techniques, biosensor varieties, and signal amplification technologies. Challenges and potential developments for viral microorganisms based on biosensors and signal amplification were also investigated.

Lateral flow immunoassay (LFIA) for dengue diagnosis: Recent progress and prospect

Dengue is one of the most widespread and fatal arboviral infections in the world. Early detection of dengue virus (DENV) is essential to prevent the spread of the disease and provide an immediate response. The lateral flow immunoassay (LFIA) systems are low-cost, rapid, sensitive, targeted, and straightforward detection, which is an ideal early detection candidate for point-of-care testing (POCT) in dengue-affected areas. However, current commercial LFIA kits cannot fully satisfy the sensitivity, specificity, serotype differentiation, and multiplex detection requirements. Therefore, various strategies have been applied to optimize the LFIA for DENV detection, including label material improvement, optical enhancement and novel structure design. In this review, we comprehensively presented the snapshot of dengue, the principle of LFIA, and recent progress in the LFIA optimization for dengue diagnoses. Furthermore, this review also discusses insights into the prospect of LFIA dengue diagnostic methods, such as microfluidics, multiplex design, nucleic acid-typed probes and smartphone-assisted result analysis.

High-throughput characterization and phenotyping of resistance and tolerance to virus infection in sweetpotato

Breeders have made important efforts to develop genotypes able to resist virus attacks in sweetpotato, a major crop providing food security and poverty alleviation to smallholder farmers in many regions of Sub-Saharan Africa, Asia and Latin America. However, a lack of accurate objective quantitative methods for this selection target in sweetpotato prevents a consistent and extensive assessment of large breeding populations. In this study, an approach to characterize and classify resistance in sweetpotato was established by assessing total yield loss and virus load after the infection of the three most common viruses (SPFMV, SPCSV, SPLCV). Twelve sweetpotato genotypes with contrasting reactions to virus infection were grown in the field under three different treatments: pre-infected by the three viruses, un-infected and protected from re-infection, and un-infected but exposed to natural infection. Virus loads were assessed using ELISA, (RT-)qPCR, and loop-mediated isothermal amplification (LAMP) methods, and also through multispectral reflectance and canopy temperature collected using an unmanned aerial vehicle. Total yield reduction compared to control and the arithmetic sum of (RT-)qPCR relative expression ratios were used to classify genotypes into four categories: resistant, tolerant, susceptible, and sensitives. Using 14 remote sensing predictors, machine learning algorithms were trained to classify all plots under the said categories. The study found that remotely sensed predictors were effective in discriminating the different virus response categories. The results suggest that using machine learning and remotely sensed data, further complemented by fast and sensitive LAMP assays to confirm results of predicted classifications could be used as a high throughput approach to support virus resistance phenotyping in sweetpotato breeding.

Development and evaluation of RT-qPCR assays for two neglected orthobunyaviruses: Oya virus and Ebinur Lake virus

OBJECTIVES

Oya virus (OYAV) and Ebinur lake virus (EBIV) belong to the genus Orthobunyavirus within the Peribunyaviridae family, and both are recognized as the novel virus with potential threat to the animal or public health. Given their potential to cause outbreaks and their detection in diverse samples across different regions, the need for a reliable and efficient molecular detection method for OYAV and EBIV becomes imperative.

METHODS

The S-segment of OYAV and EBIV was used for designing specific primer and probe sets, which were employed in a real-time reverse transcription quantitative PCR (RT-qPCR) assay. The analytical performance of these assays, encompassing specificity, sensitivity, reproducibility, and fitness for purpose, was thoroughly evaluated across various sample matrices.

RESULTS

The developed RT-qPCR assays were very specific to their respective targets. Both assays were highly reproducible (%CV<3) and sensitive with the 95% limit of detection (LOD) of 0.80 PFU/mL for OYAV primer probe set and 0.37 PFU/mL for EBIV primer probe set. Furthermore, the assays fitness for purpose was good as it could detect the specific viruses in virus-spiked serum samples, virus-inoculated mosquito samples, field caught mosquitoes and biting midge samples.

CONCLUSIONS

Our study has successfully developed specific, sensitive, and reliable RT-qPCR assays for the detection of OYAV and EBIV. These assays hold great promise for their potential application in clinical and field samples in the future.

Computational Pipeline for the Detection of Plant RNA Viruses Using High-Throughput Sequencing

In this chapter, we describe a computational pipeline for the in silico detection of plant viruses by high-throughput sequencing (HTS) from total RNA samples. The pipeline is designed for the analysis of short reads generated using an Illumina platform and free-available software tools. First, we provide advice for high-quality total RNA purification, library preparation, and sequencing. The bioinformatics pipeline begins with the raw reads obtained from the sequencing machine and performs some curation steps to obtain long contigs. Contigs are blasted against a local database of reference nucleotide viral sequences to identify the viruses in the samples. Then, the search is refined by applying specific filters. We also provide the code to re-map the short reads against the viruses found to get information on sequencing depth and read coverage for each virus. No previous bioinformatics background is required, but basic knowledge of the Unix command line and R language is recommended.

Isolation of Double-Stranded RNAs by Lithium Chloride Fractionation

This procedure provides a comprehensive method for isolating double-stranded RNA (dsRNA) that relies on the different solubility of various nucleic acids in lithium chloride (LiC1). The approach offers several notable advantages including simplicity, avoidance of enzymatic treatments, and the ability to obtain relatively high yields of undegraded dsRNA over other conventional techniques. Moreover, it allows for the separation of different groups of cellular and viral nucleic acids from a single tissue sample. This method was further improved to increase the purity of dsRNA using plant tissues infected by RNA viruses.

Label-free detection of virus based on surface-enhanced Raman scattering

Due to the background interference from biological samples, detecting viruses using surface-enhanced Raman scattering (SERS) in clinical samples is challenging. This study is based on SERS by reducing sodium borohydride and aggregating silver nanoparticles to develop suitable virus detection "hot spot." The monkeypox virus and human papillomavirus fingerprints were quickly obtained, tested, and identified in serum and artificial vaginal discharge, respectively, by combining the principal component analysis method. Therefore, these viruses were successfully identified in the biological background. In addition, the lowest detection limit was 100 copies/mL showing good reproducibility and signal-to-noise ratio. The concentration-dependent curve of the monkeypox virus had a good linear relationship. This method helps solve the SERS signal interference problem in complex biological samples, with low detection limits and high selectivity in virus characterization and quantitative analysis. Therefore, this method has a reasonable prospect of clinical application.

Microfluidic Enrichment of Intact SARS-CoV-2 Viral Particles by Stoichiometric Balanced DNA Computation

Health diagnostic tools for community safety and environmental monitoring require selective and quantitatively accurate active viral load assessment. Herein, we report a microfluidic enrichment strategy to separate intact SARS-CoV-2 particles by AND logic gate with inputs of cholesterol oligonucleotides for the envelope and aptamers for the spike viral proteins. Considering the unequal quantity of endogenous spikes and lipid membranes on SARS-CoV-2, a dual-domain binding strategy, with two aptamers targeting different spike domains, was applied to balance the spike-envelope stoichiometric ratio. By balancing the stoichiometric with DNA computation and promoting microscale mass transfer of the herringbone chip, the developed strategy enabled high sensitivity detection of pseudotyped SARS-CoV-2 with a limit of detection as low as 37 active virions/μL while distinguishing it from inactive counterparts, other nontarget viruses, and free spike protein. Moreover, the captured viral particles can be released through DNase I treatment with up to 90% efficiency, which is fully compatible with virus culture and sequencing. Overall, the developed strategy not only identified SARS-CoV-2-infected patients (n = 14) with 100% identification from healthy donors (n = 8) but also provided a fresh perspective on the regulation of stoichiometric ratio to achieve a more biologically relevant DNA computation.

A universal all-in-one RPA-Cas12a strategy with de novo autodesigner and its application in on-site ultrasensitive detection of DNA and RNA viruses

Revolutionary all-in-one RPA-CRISPR assays are rapidly becoming the most sought-after tools for point-of-care testing (POCT) due to their high sensitivity and ease of use. Despite the availability of one-pot methods for specific targets, the development of more efficient methods for new targets remains a significant challenge. In this study, we present a rapid and universal approach to establishing an all-in-one RPA-Cas12a method CORDSv2 based on rational balancing amplification and Cas12a cleavage, which achieves ultrasensitive detection of several targets, including SARS-CoV-2, ASFV, HPV16, and HPV18. CORDSv2 demonstrates a limit of detection (LOD) of 0.6 cp/μL and 100% sensitivity for SARS-CoV-2, comparable to qPCR. Combining with our portable device(hippo-CORDS), it has a visual detection LOD of 6 cp/μL and a sensitivity up to 100% for SARS-CoV-2 and 97% for Ct<35 ASFV samples, surpassing most one-pot visual methods. To simplify and accelerate the process for new targets, we also develop a de novo autodesigner by which the optimal couples of primers and crRNA can be selected rapidly. As a universal all-in-one RPA-CRISPR method for on-site testing, CORDSv2 becomes an attractive choice for rapid and accurate diagnosis in resource-limited settings.

Rapid and reliable ultrasensitive detection of pathogenic H9N2 viruses through virus-binding phage nanofibers decorated with gold nanoparticles

The rapid and sensitive detection of pathogenic viruses is important for controlling pandemics. Herein, a rapid, ultrasensitive, optical biosensing scheme was developed to detect avian influenza virus H9N2 using a genetically engineered filamentous M13 phage probe. The M13 phage was genetically engineered to bear an H9N2-binding peptide (H9N2BP) at the tip and a gold nanoparticle (AuNP)-binding peptide (AuBP) on the sidewall to form an engineered phage nanofiber, M13@H9N2BP@AuBP. Simulated modelling showed that M13@H9N2BP@AuBP enabled a 40-fold enhancement of the electric field enhancement in surface plasmon resonance (SPR) compared to conventional AuNPs. Experimentally, this signal enhancement scheme was employed for detecting H9N2 particles with a sensitivity down to 6.3 copies/mL (1.04 × 10-5 fM). The phage-based SPR scheme can detect H9N2 viruses in real allantoic samples within 10 min, even at very low concentrations beyond the detection limit of quantitative polymerase chain reaction (qPCR). Moreover, after capturing the H9N2 viruses on the sensor chip, the H9N2-binding phage nanofibers can be quantitatively converted into plaques that are visible to the naked eye for further quantification, thereby allowing us to enumerate the H9N2 virus particles through a second mode to cross-validate the SPR results. This novel phage-based biosensing strategy can be employed to detect other pathogens because the H9N2-binding peptides can be easily switched with other pathogen-binding peptides using phage display technology.

Evaluation of rRNA depletion methods for capturing the RNA virome from environmental surfaces

OBJECTIVE

Metatranscriptomic analysis of RNA viromes on built-environment surfaces is hampered by low RNA yields and high abundance of rRNA. Therefore, we evaluated the quality of libraries, efficiency of rRNA depletion, and viral detection sensitivity using a mock community and a melamine-coated table surface RNA with levels below those required (< 5 ng) with a library preparation kit (NEBNext Ultra II Directional RNA Library Prep Kit).

RESULTS

Good-quality RNA libraries were obtained from 0.1 ng of mock community and table surface RNA by changing the adapter concentration and number of PCR cycles. Differences in the target species of the rRNA depletion method affected the community composition and sensitivity of virus detection. The percentage of viral occupancy in two replicates was 0.259 and 0.290% in both human and bacterial rRNA-depleted samples, a 3.4 and 3.8-fold increase compared with that for only bacterial rRNA-depleted samples. Comparison of SARS-CoV-2 spiked-in human rRNA and bacterial rRNA-depleted samples suggested that more SARS-CoV-2 reads were detected in bacterial rRNA-depleted samples. We demonstrated that metatranscriptome analysis of RNA viromes is possible from RNA isolated from an indoor surface (representing a built-environment surface) using a standard library preparation kit.

Polarimetric imaging for the detection of synthetic models of SARS-CoV-2: A proof of concept

OBJECTIVE

To conduct a proof-of-concept study of the detection of two synthetic models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polarimetric imaging.

APPROACH

Two SARS-CoV-2 models were prepared as engineered lentiviruses pseudotyped with the G protein of the vesicular stomatitis virus, and with the characteristic Spike protein of SARS-CoV-2. Samples were prepared in two biofluids (saline solution and artificial saliva), in four concentrations, and deposited as 5-µL droplets on a supporting plate. The angles of maximal degree of linear polarization (DLP) of light diffusely scattered from dry residues were determined using Mueller polarimetry from87 samples at 405 nm and 514 nm. A polarimetric camera was used for imaging several samples under 380-420 nm illumination at angles similar to those of maximal DLP. Per-pixel image analysis included quantification and combination of polarization feature descriptors in 475 samples.

MAIN RESULTS

The angles (from sample surface) of maximal DLP were 3° for 405 nm and 6° for 514 nm. Similar viral particles that differed only in the characteristic spike protein of the SARS-CoV-2, their corresponding negative controls, fluids, and the sample holder were discerned at 10-degree and 15-degree configurations.

SIGNIFICANCE

Polarimetric imaging in the visible spectrum may help improve fast, non-contact detection and identification of viral particles, and/or other microbes such as tuberculosis, in multiple dry fluid samples simultaneously, particularly when combined with other imaging modalities. Further analysis including realistic concentrations of real SARS-CoV-2 viral particles in relevant human fluids is required. Polarimetric imaging under visible light may contribute to a fast, cost-effective screening of SARS-CoV-2 and other pathogens when combined with other imaging modalities.

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

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

High-throughput microbead assay system with a portable, cost-effective Wi-Fi imaging module, and disposable multi-layered microfluidic cartridges for virus and microparticle detection, and tracking

In recent years biomedical scientific community has been working towards the development of high-throughput devices that allow a reliable, rapid and parallel detection of several strains of virus or microparticles simultaneously. One of the complexities of this problem lies on the rapid prototyping of new devices and wireless rapid detection of small particles and virus alike. By reducing the complexity of microfluidics microfabrication and using economic materials along with makerspace tools (Kundu et al. 2018) it is possible to provide an affordable solution to both the problems of high-throughput devices and detection technologies. We present the development of a wireless, standalone device and disposable microfluidics chips that rapidly generate parallel readouts for selected, possible virus variants from a nasal or saliva sample, based on motorized and non-motorized microbeads detection, and imaging processing of the motion tracks of these beads in micrometers. Microbeads and SARS-CoV-2 COVID-19 Delta variant were tested as proof-of-concept for testing the microfluidic cartridges and wireless imaging module. The Microbead Assay (MA) system kit consists of a Wi-Fi readout module, a microfluidic chip, and a sample collection/processing sub-system. Here, we focus on the fabrication and characterization of the microfluidic chip to multiplex various micrometer-sized beads for economic, disposable, and simultaneous detection of up to six different viruses, microparticles or variants in a single test, and data collection using a commercially available, Wi-Fi-capable, and camera integrated device (Fig. 1).

Tunable nanochannel resistive pulse sensing device using a novel multi-module self-assembly

Nanochannel-based resistive pulse sensing (nano-RPS) system is widely used for the high-sensitive measurement and characterization of nanoscale biological particles and biomolecules due to its high surface to volume ratio. However, the geometric dimensions and surface properties of nanochannel are usually fixed, which limit the detections within particular ranges or types of nanoparticles. In order to improve the flexibility of nano-RPS system, it is of great significance to develop nanochannels with tunable dimensions and surface properties. In this work, we proposed a novel multi-module self-assembly (MS) strategy which allows to shrink the geometric dimensions and tune surface properties of the nanochannels simultaneously. The MS-tuned nano-RPS device exhibits an enhanced signal-to-noise ratio (SNR) for nanoparticle detections after shrunk the geometric dimensions by MS strategy. Meanwhile, by tuning the surface charge, an enhanced resolution for viral particles detection was achieved with the MS-tuned nano-RPS devices by analyzing the variation of pulse width due the tuned surface charge. The proposed MS strategy is versatile for various types of surface materials and can be potentially applied for nanoscale surface reconfiguration in various nanofluidic devices.

A multiplex real-time RT-PCR assay for the detection of H1, H2 and H3 subtype avian influenza viruses

Avian influenza viruses (AIVs) are influenza A viruses, of which subtypes H1, H2 and H3 are highly transmissible in poultry and have the risk of transmission to human as well. It is important to establish an accurate, sensitive and convenient means of virus detection. In this study, we developed a multiplex real-time RT-PCR assay based on conserved sequences of the virus hemagglutinin and matrix, and designed primers and probes for the simultaneous and rapid detection of AIV subtypes H1, H2 and H3. We used different subtypes of AIVs and other avian respiratory viruses for evaluation of the specificity of this method. The results showed good sensitivity, specificity and reproducibility. The detection limit was 10-100 copies per reaction. The method also achieved good concordance with the virus isolation method when compared to 81 poultry samples evaluated. It provides a new method for detecting mixed infections of AIVs.

First report of Alstroemeria necrotic streak virus infecting greenhouse bell pepper (Capsicum annuum) in Canada

Alstroemeria necrotic streak virus (ANSV) is an Orthotospovirus that has been isolated from symptomatic Alstroemeria plant in 2010 (Hassani-Mehraban et al. 2010). It has been shown to infect crops of bell pepper (Capsicum annuum) and tomato (Solanum lycopersicum) (Olaya et al. 2017) which are two of the three biggest greenhouse crops in Canada in terms of production volume and value (Statistic Canada. 2020). In July of 2022, the entire production of bell pepper (all plants) from a greenhouse in Québec was presenting necrotic rings and discoloration in fruit and seemingly healthy leaves. Samples from these infected bell pepper were found to be negative for twenty two common viruses infecting bell pepper by ELISA immunoassay by the Laboratoire d'expertise et de diagnostic en phytoprotection (LEDP) (Québec, Canada). To identify the causal agent, double-stranded RNA was extracted from leaf and fruit of one plant to form two separate samples (leaf and fruit) and used for cDNA library preparations with Nextera XT DNA Sample Prep kit (Illumina, USA). The libraries were sequenced using Illumina Miseq (Fall et al. 2020). The same dsRNA were also sequenced with MinION nanopore sequencing method as described previously (Javaran et al. 2021; Javaran et al. 2023). The obtained raw FASTQ data were processed following the methodology described in Fall et al. 2020 and Javaran et al. 2023. The Miseq sequencing yielded over 2 million reads per sample with a percentage of mapped viral reads ranging from 26.92 to 47.29% of the total number of reads. The leaf samples were positive to Bell pepper endornavirus (BPEV) with the full genome covered 16713 times and Alstroemeria necrotic streak virus (ANSV) with 98% of the genome covered 4929 times. The MinION sequencing yielded 1,028,460 reads and the same viruses were detected with 1288 long reads (mean length of 745bp) assigned to ANSV genome. Both viruses were detected in the leaf and fruit samples. The complete ANSV genome comprising three segments (L, M, and S) was assembled and deposited in GenBank: (OQ261731-OQ261733). These L, M and S segments shown 99% nt identity with an isolate from the Columbia (GenBank: MF469036, MF469037, MF469038). It is interesting that read coverage at near the 2000th position of the S segment, was very low. This phenomenon may suggest a cleavage site nearby by a viral or host factor. ANSV was mainly found in leaf samples and very low numbers of reads in fruit samples. The presence of ANSV was confirmed by RT-PCR using the primers specific to the ANSV nucleocapsid gene Tospo_S_F (5'- CAG AAT CAG GCT GCA TTT AAT TTC C-3') and Tospo_S_R (5'-CAA CGC TTC CTT TAG CAT TAG G-3') (Gallo et al. 2019). The sequences of ∼600 bp amplicons were determined using Sanger sequencing and showed 100% nt identity with Miseq-derived sequences of ANSV. The virus has previously been detected in Colombia (Hassani-Mehraban et al. 2010) and then in California in 2018 (Tian et al. 2020). This is to our knowledge the first detection of ANSV in Canada. Bell pepper is one of the most important crops in Canada and the ANSV vector, the western flower thrips (Frankliniella occidentalis), known to spread the tomato spotted wilt virus (TSWV) is established in Canada (Allen et al. 1986). The detection of ANSV in Canada is line with the hypothesis of an international spread of this virus (Tian et al. 2020) as is it not known to spread through seeds.

An ultrasensitive electrochemical sensor for detecting porcine epidemic diarrhea virus based on a Prussian blue-reduced graphene oxide modified glassy carbon electrode

This study developed a novel, ultrasensitive sandwich-type electrochemical immunosensor for detecting the porcine epidemic diarrhea virus (PEDV). By electrochemical co-deposition of graphene and Prussian blue, a Prussian blue-reduced graphene oxide-modified glassy carbon electrode was made, further modified with PEDV-monoclonal antibodies (mAbs) to create a new PEDV immunosensor using the double antibody sandwich technique. The electrochemical characteristics of several modified electrodes were investigated using cyclic voltammetry (CV). We optimized the pH levels and scan rate. Additionally, we examined specificity, reproducibility, repeatability, accuracy, and stability. The study indicates that the immunosensor has good performance in the concentration range of 1 × 10^1.88 to 1 × 10^5.38 TCID₅₀/mL of PEDV, with a detection limit of 1 × 10^1.93 TCID₅₀/mL at a signal-to-noise ratio of 3σ. The composite membranes produced via co-deposition of graphene and Prussian blue effectively increased electron transport to the glassy carbon electrode, boosted response signals, and increased the sensitivity, specificity, and stability of the immunosensor. The immunosensor could accurately detect PEDV, with results comparable to real-time quantitative PCR. This technique was applied to PEDV detection and served as a model for developing additional immunosensors for detecting hazardous chemicals and pathogenic microbes.

Batteryless wireless magnetostrictive Fe30Co70/Ni clad plate for human coronavirus 229E detection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been garnered increasing for its rapid worldwide spread. Each country had implemented city-wide lockdowns and immigration regulations to prevent the spread of the infection, resulting in severe economic consequences. Materials and technologies that monitor environmental conditions and wirelessly communicate such information to people are thus gaining considerable attention as a countermeasure. This study investigated the dynamic characteristics of batteryless magnetostrictive alloys for energy harvesting to detect human coronavirus 229E (HCoV-229E). Light and thin magnetostrictive Fe-Co/Ni clad plate with rectification, direct current (DC) voltage storage capacitor, and wireless information transmission circuits were developed for this purpose. The power consumption was reduced by improving the energy storage circuit, and the magnetostrictive clad plate under bending vibration stored a DC voltage of 1.9 V and wirelessly transmitted a signal to a personal computer once every 5 min and 10 s under bias magnetic fields of 0 and 10 mT, respectively. Then, on the clad plate surface, a novel CD13 biorecognition layer was immobilized using a self-assembled monolayer of -COOH groups, thus forming an amide bond with -NH₂ groups for the detection of HCoV-229E. A bending vibration test demonstrated the resonance frequency changes because of HCoV-229E binding. The fluorescence signal demonstrated that HCoV-229E could be successfully detected. Thus, because HCoV-229E changed the dynamic characteristics of this plate, the CD13-modified magnetostrictive clad plate could detect HCoV-229E from the interval of wireless communication time. Therefore, a monitoring system that transmits/detects the presence of human coronavirus without batteries will be realized soon.

CRISPR-Based Diagnostics and Microfluidics for COVID-19 Point-of-Care Testing: A Review of Main Applications

An ongoing pandemic of coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). So far, there have been various approaches for SARS-CoV-2 detection, each having its pros and cons. The current gold-standard method for SARS-CoV-2 detection, which offers acceptable specificity and sensitivity, is the quantitative reverse transcription-PCR (qRT-PCR). However, this method requires considerable cost and time to transport samples to specialized laboratories and extract, amplify, and detect the viral genome. On the other hand, antigen and antibody testing approaches that bring rapidity and affordability into play have lower sensitivity and specificity during the early stages of COVID-19. Moreover, the immune response is variable depending on the individual. Methods based on clustered regularly interspaced short palindromic repeats (CRISPR) can be used as an alternative approach to controlling the spread of disease by a high-sensitive, specific, and low-cost molecular diagnostic system. CRISPR-based detection systems (CRISPR-Dx) target the desired sequences by specific CRISPR-RNA (crRNA)-pairing on a pre-amplified sample and a subsequent collateral cleavage. In the present article, we have reviewed different CRISPR-Dx methods and presented their benefits and drawbacks for point-of-care testing (POCT) of suspected SARS-CoV-2 infections at home or in small clinics.

Identification of an emerging cucumber virus in Taiwan using Oxford nanopore sequencing technology

BACKGROUND

In June 2020, severe symptoms of leaf mosaic and fruit malformation were observed on greenhouse-grown cucumber plants in Xizhou Township of Changhua County, Taiwan. An unknown virus, designated CX-2, was isolated from a diseased cucumber sample by single lesion isolation on Chenopodium quinoa leaves. Identification of CX-2 was performed. Moreover, the incidence of cucumber viruses in Taiwan was also investigated.

METHODS

Transmission electron microscopy was performed to examine virion morphology. The portable MinION sequencer released by Oxford Nanopore Technologies was used to detect viral sequences in dsRNA of CX-2-infected leaf tissue. The whole genome sequence of CX-2 was completed by Sanger sequencing and analyzed. Reverse transcription-polymerase chain reaction (RT-PCR) with species-specific primers and indirect enzyme-linked immunosorbent assay (ELISA) with anti-coat protein antisera were developed for virus detection in the field [see Additional file 1].

RESULTS

Icosahedral particles about 30 nm in diameter were observed in the crud leaf sap of CX-2-infected C. quinoa plant. The complete genome sequence of CX-2 was determined as 4577 nt long and shared 97.0-97.2% of nucleotide identity with that of two cucumber Bulgarian latent virus (CBLV) isolates in Iran and Bulgaria. Therefore, CX-2 was renamed CBLV-TW. In 2020-2022 field surveys, melon yellow spot virus (MYSV) had the highest detection rate of 74.7%, followed by cucurbit chlorotic yellows virus (CCYV) (32.0%), papaya ringspot virus virus watermelon type (PRSV-W) (10.7%), squash leaf curl Philippines virus (SLCuPV) (9.3%), CBLV (8.0%) and watermelon silver mottle virus (WSMoV) (4.0%). Co-infection of CBLV and MYSV could be detected in field cucumbers.

CONCLUSION

The emerging CBLV-TW was identified by nanopore sequencing. Whole genome sequence analysis revealed that CBLV-TW is closely related, but phylogenetically distinct, to two known CBLV isolates in Bulgaria and Iran. Detection methods including RT-PCR and indirect ELISA have been developed to detect CBLV and to investigate cucumber viruses in central Taiwan. The 2020-2022 field survey results showed that MYSV and CCYV were the main threats to cucumbers, with CBLV, SLCuPV and WSMoV were occasionally occurring.

Recent trends and advancements in electrochemiluminescence biosensors for human virus detection

Researchers are constantly looking to find new techniques of virus detection that are sensitive, cost-effective, and accurate. Additionally, they can be used as a point-of-care (POC) tool due to the fact that the populace is growing at a quick tempo, and epidemics are materializing greater often than ever. Electrochemiluminescence-based (ECL) biosensors for the detection of viruses have become one of the most quickly developing sensors in this field. Thus, we here focus on recent trends and developments of these sensors with regard to virus detection. Also, quantitative analysis of various viruses (e.g., Influenza virus, SARS-CoV-2, HIV, HPV, Hepatitis virus, and Zika virus) with a specific interest in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was introduced from the perspective of the biomarker and the biological receptor immobilized on the ECL-based sensors, such as nucleic acids-based, immunosensors, and other affinity ECL biosensors.

Loop-Mediated Isothermal Amplification-Based Microfluidic Platforms for the Detection of Viral Infections

Purpose of Review

Easy-to-use, fast, and accurate virus detection method is essential for patient management and epidemic surveillance, especially during severe pandemics. Loop-mediated isothermal amplification (LAMP) on a microfluidic platform is suitable for detecting infectious viruses, regardless of the availability of medical resources. The purpose of this review is to introduce LAMP-based microfluidic devices for virus detection, including their detection principles, methods, and application.

Recent Findings

Facing the uncontrolled spread of viruses, the large-scale deployment of LAMP-based microfluidic platforms at the grassroots level can help expand the coverage of nucleic acid testing and shorten the time to obtain test reports. Microfluidic chip technology is highly integrated and miniaturized, enabling precise fluid control for effective virus detection. Performing LAMP on miniaturized systems can reduce analysis time, reagent consumption and risk of sample contamination, and improve analytical performance.

Summary

Compared to traditional benchtop protocols, LAMP-based microfluidic devices reduce the testing time, reagent consumption, and the risk of sample contamination. In addition to simultaneous detection of multiple target genes by special channel design, microfluidic chips can also integrate digital LAMP to achieve absolute quantification of target genes.

Rapid and quantitative detection of respiratory viruses using surface-enhanced Raman spectroscopy and machine learning

Rapid and sensitive pathogen detection is important for prevention and control of disease. Here, we report a label-free diagnostic platform that combines surface-enhanced Raman scattering (SERS) and machine learning for the rapid and accurate detection of thirteen respiratory virus species including SARS-CoV-2, common human coronaviruses, influenza viruses, and others. Virus detection and measurement have been performed using highly sensitive SiO₂ coated silver nanorod array substrates, allowing for detection and identification of their characteristic SERS peaks. Using appropriate spectral processing procedures and machine learning algorithms (MLAs) including support vector machine (SVM), k-nearest neighbor, and random forest, the virus species as well as strains and variants have been differentiated and classified and a differentiation accuracy of >99% has been obtained. Utilizing SVM-based regression, quantitative calibration curves have been constructed to accurately estimate the unknown virus concentrations in buffer and saliva. This study shows that using a combination of SERS, MLA, and regression, it is possible to classify and quantify the virus in saliva, which could aid medical diagnosis and therapeutic intervention.

Engineering carbon nanotubes for sensitive viral detection

Viral infections have been proven a severe threat to human beings, and the pandemic of Coronavirus Disease 2019 (COVID-19) has become a societal health concern, including mental distress and morbidity. Therefore, the early diagnosis and differentiation of viral infections are the prerequisite for curbing the local and global spread of viruses. To this end, carbon nanotubes (CNTs) based virus detection strategies are developed that provide feasible alternatives to conventional diagnostic techniques. Here in this review, an overview of the design and engineering of CNTs-based sensors for virus detection is summarized, followed by the nano-bio interactions used in developing biosensors. Then, we classify the viral sensors into covalently engineered CNTs, non-covalently engineered CNTs, and size-tunable CNTs arrays for viral detection, based on the type of CNTs-based nano-bio interfaces. Finally, the current challenges and prospects of CNTs-based sensors for virus detection are discussed.

Development of a dual RT-RPA detection for Sweet potato feathery mottle virus and Sweet potato chlorotic stuntvirus

The disease co-infected by Sweet potato feathery mottle virus (SPFMV) and Sweet potato chlorotic stunt virus (SPCSV) is devastating in sweet potato, as it would give rise to the serious losses in both production and quality. Consequently, it is conducive for preventing and controlling this disease to detect these two viruses accurately and timely. Here we developed and optimized a dual reverse transcription recombinase polymerase amplification (RT-RPA) for rapid and accurate detection of SPFMV and SPCSV. Four special primers were designed based on the conserved sequences of SPFMV and SPCSV, respectively. The sensitivity of dual RT-RPA for SPFMV and SPCSV was 10^-4 ng/μL at the optimal conditions in which the primer ratio between SPFMV and SPCSV was 2:1, and the reaction incubated for 25 min at a temperature of 39 °C. Both 61 sweet potato samples and 5 morning glory samples collected from China were tested using the dual RT-RPA successfully. Therefore, the dual RT-RPA is a reliable, rapid, sensitive method to detect these two viruses in sweet potato. It is the RT-RPA that was used for detection of SPFMV and SPCSV simultaneously firstly. This dual RT-RPA, as a convenient and powerful tool, will be useful to diagnose SPFMV and SPCSV.

A novel enhanced substrate for label-free detection of SARS-CoV-2 based on surface-enhanced Raman scattering

Accurate and sensitive detection of SARS-CoV-2 is an effective strategy for preventing the COVID-19 pandemic in the current absence of specific drug therapy. This study presents a novel enhanced substrate for label-free detection of respiratory viruses using surface-enhanced Raman Scattering. Sodium borohydride reduces silver ions to clustered silver nanoparticles to eliminate the disorganized peak signal of the traditional citrate reducing agent. Meanwhile, the study obtained the fingerprints and concentration-dependent curves of many respiratory viruses, including SARS-CoV-2, human adenovirus type 7, and H1N1 virus, with good linear relationships. The three viruses were also identified in serum and saliva within two minutes, combined with linear discriminant diagnostic analysis. Therefore, establishing this enhanced substrate is greatly valuable for the global response to the COVID-19 pandemic.

Sensor System Based on a Piezoelectric Resonator with a Lateral Electric Field for Virus Diagnostics

A sensor system based on a piezoelectric resonator with a lateral electric field in the frequency range 6-7 MHz of the electric field for virus detection is described. Through use of the transmissible virus causing gastroenteritis in pigs and specific antibodies, the possibility of detecting the virus in suspension in real time was determined. It was found that the frequency dependence of the real and imaginary parts of the electrical impedance of such a resonator loaded with a virus suspension changes significantly after the addition of specific antibodies to the suspension. No changes are observed if the antibodies are not specific. Thus, the results obtained illustrate the possibility of detecting viruses in situ, directly in the liquid phase, if the change in the real or imaginary parts of the electrical impedance after the addition of antibodies is used as an analytical signal. The possibility of virus detection in the presence of foreign viral particles has been illustrated.

First report of bean common mosaic virus naturally infecting yam bean (Pachyrhizus erosus) in China

Yam bean (Pachyrhizus erosus), a high-yielding leguminous root crop with good nutritional value, is widely cultivated in southern China. In 2020, P. erosus (cv. Mumashan) plants exhibiting irregular yellow leaves and malformed seed pods (Supplementary Fig S1) were observed at Ningbo city, Zhejiang Province, China. To determine the causal agent(s) of the disease, symptomatic leaves (n=4) were collected for electron microscopy negative staining. Virus particles with a length of about 700nm, similar to viruses in the genus Potyvirus, were observed via transmission electron microscope (TEM), suggesting the presence a potyvirus(es). To further confirm which potyvirus(es) infected yam bean, total RNA was extracted from leaf samples of a total of six plants, including four symptomatic plants and two asymptomatic plants using TRIzol reagent (Invitrogen Carlsbad, CA, USA) according to the manufacturer's instructions. RNA was reverse-transcribed into cDNA with M4-T as the 3'-anchoring primer by ReverTra Ace® kit (Toyobo, Japan). Sprimer/M4 Potyviridae specific primers (Chen et al., 2001) were used for PCR analysis. A ~1,700-bp-long product was amplified from four symptomatic plants using KOD FX enzyme (Toyobo, Japan). No such band was amplified from the two asymptomatic plants. The PCR product (~1.7kb) amplified from a single symptomatic plant was ligated into the pEASY®-Blunt Zero vector (TransGen Bio, Beijing, China) and sequenced (Sangon Bio, Shanghai, China). The amplicon showed 99% nucleotide sequence identities with bean common mosaic virus (BCMV) isolate NKY021 (KJ807819). Subsequently, the complete nucleotide sequences of this BCMV isolate (referred as BCMV-NB) was amplified by overlapping RT-PCR and rapid amplification of cDNA ends with primers (Supplementary Table S1) designed from the sequence of BCMV isolate NKY021. The BCMV-NB full genome (Accession No. OL871237) consists of 10,053 nucleotides excluding the poly(A) tail and contains a large open reading frame encoding a polyprotein of 3222 amino acids. BLASTn analysis showed that BCMV-NB shared a sequence identity of 96.4% with BCMV isolate HZZB011 (KJ807815). Phylogenetic tree generated by Neighbour-Joining method revealing the BCMV-NB isolate was grouped together with Chinese isolates from Glycine max (Supplementary Fig S1). To test the infectivity of BCMV-NB, virus-free yam bean (cv. Mumashan) and Nicotiana benthamiana seedlings were mechanically inoculated with sap extracted from the symptomatic leaves of a BCMV-NB-infected yam bean plant. The inoculated yam bean plants developed typical BCMV mosaic and chlorotic symptoms at 16 days post inoculation (dpi), while Nicotiana benthamiana had no obvious symptoms at 10 or 20 dpi (Supplementary Fig S1). BCMV infections were confirmed in yam bean plants (infection rate 6/6) and N. benthamiana plants (infection rate 8/8) by RT-PCR at 16 dpi and 10 dpi, respectively. Twelve further P. erosus plants (cv. Mumashan) were collected from a field in Ningbo city and tested by RT-PCR with BCMV-specific primer pair BCMV CP (+)/(-) (Supplementary Table 1). Eight out of the 12 samples tested positive for BCMV by PCR-gel electrophoresis (Supplementary Fig S1) and Sanger sequencing, suggesting a high incidence of BCMV infection in this field. BCMV infection in yam bean has been reported from Indonesia (Damayanti et al., 2008) and Peru (Fuentes et al., 2012). To the best of our knowledge, this is the first report of BCMV naturally infecting yam bean in China. Thus, special attention and appropriate management strategies are needed to minimize the damage caused by BCMV to yam bean crops in China.

Recent advances in carbon quantum dots for virus detection, as well as inhibition and treatment of viral infection

In the last decade, carbon quantum dots (CQDs), as a novel class of carbon-based nanomaterials, have received increasing attention due to their distinct properties. CQDs are ultimately small nanoparticles with an average size below 10 nm, possessing high water solubility, alluring photoluminescence, photostability, excellent biocompatibility, low/none toxicity, environmental friendliness, and high sustainability, etc. In history, there are intermittent threats from viruses to humans, animals and plants worldwide, resulting in enormous crises and impacts on our life, environment, economy and society. Some recent studies have unveiled that certain types of CQDs exhibited high and potent antiviral activities against various viruses such as human coronavirus, arterivirus, norovirus and herpesvirus. Moreover, they have been successfully explored and developed for different virus detections including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This article exclusively overviews and discusses the recent progress of designing, synthesizing, modifying/functionalizing and developing CQDs towards effective virus detection as well as the inhibition and treatment of viral infection. Their mechanisms and applications against various pathogenic viruses are addressed. The latest outcomes for combating the coronavirus disease 2019 (COVID-19) utilizing CQDs are also highlighted. It can be envisaged that CQDs could further benefit the development of virus detectors and antiviral agents with added broad-spectrum activity and cost-effective production.

SARS-CoV-2 Detection in air samples from inside heating, ventilation, and air conditioning (HVAC) systems- COVID surveillance in student dorms

Background

The COVID-19 pandemic affected universities and institutions and caused campus shutdowns with a transition to online teaching models. To detect infections that might spread on campus, we pursued research towards detecting SARS-CoV-2 in air samples inside student dorms.

Methods

We sampled air in 2 large dormitories for 3.5 months and a separate isolation suite containing a student who had tested positive for COVID-19. We developed novel techniques employing 4 methods to collect air samples: Filter Cassettes, Button Sampler, BioSampler, and AerosolSense sampler combined with direct qRT-PCR SARS-CoV-2 analysis.

Results

For the 2 large dorms with the normal student population, we detected SARS-CoV-2 in 11 samples. When compared with student nasal swab qRT-PCR testing, we detected SARS-CoV-2 in air samples when a PCR positive COVID-19 student was living on the same floor of the sampling location with a detection rate of 75%. For the isolation dorm, we had a 100% SARS-CoV-2 detection rate with AerosolSense sampler.

Conclusions

Our data suggest air sampling may be an important SARS-CoV-2 surveillance technique, especially for buildings with congregant living settings (dorms, correctional facilities, barracks). Future building designs and public health policies should consider implementation of Heating, Ventilation, and Air Conditioning surveillance.

viralFlye: assembling viruses and identifying their hosts from long-read metagenomics data

Although the use of long-read sequencing improves the contiguity of assembled viral genomes compared to short-read methods, assembling complex viral communities remains an open problem. We describe the viralFlye tool for identification and analysis of metagenome-assembled viruses in long-read assemblies. We show it significantly improves viral assemblies and demonstrate that long-reads result in a much larger array of predicted virus-host associations as compared to short-read assemblies. We demonstrate that the identification of novel CRISPR arrays in bacterial genomes from a newly assembled metagenomic sample provides information for predicting novel hosts for novel viruses.

NIRVANA for Simultaneous Detection and Mutation Surveillance of SARS-CoV-2 and Co-infections of Multiple Respiratory Viruses

Detection and mutation surveillance of SARS-CoV-2 are crucial for combating the COVID-19 pandemic. Here we describe a lab-based method for multiplex isothermal amplification-based sequencing and real-time analysis of multiple viral genomes. It can simultaneously detect SARS-CoV-2, influenza A, human adenovirus, and human coronavirus and monitor mutations for up to 96 samples in real time. The method proved to be rapid and sensitive (limit of detection: 29 viral RNA copies/μL of extracted nucleic acid) in detecting SARS-CoV-2 in clinical samples. We expect it to offer a promising solution for rapid field-deployable detection and mutational surveillance of pandemic viruses.

A multiplex real-time RT-PCR method for detecting H5, H7 and H9 subtype avian influenza viruses in field and clinical samples

In recent years, H5 and H7 subtypes of highly pathogenic avian influenza viruses (HPAIVs) have been identified in poultry worldwide, resulting in large economic losses to poultry production. Furthermore, H9N2 low pathogenic AIVs are reported to provide internal genes for generating novel reassortant AIVs, leading to potential pandemic risks. To establish an accurate, sensitive and convenient diagnostic method for H5, H7 and H9 subtype AIVs in Eurasian lineage, four groups of specific primers and probes were designed based on the conserved fragments of M, H5, H7 and H9 genes, and a multiplex real-time RT-PCR (RRT-PCR) method was established. High sensitivity was achieved for the multiplex RRT-PCR approach, with a detection limit of 1-10 copies (plasmid DNA) per reaction. The specificity of the method was evaluated using diverse subtypes of AIVs and other avian respiratory viruses isolated in eastern China over the last 9 years. Compared with virus isolation, a higher consistency was achieved when assessing 135 field samples and 126 clinical samples. The results showed that the multiplex RRT-PCR method is a fast, convenient and practical method for AIV clinical detection and epidemiological analysis.

CRISPR-Cas based virus detection: Recent advances and perspectives

Viral infections are one of the most intimidating threats to human beings. One convincing example is the coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2. Rapid, sensitive, specific and field-deployable identification of causal viruses is critical for disease surveillance, control and treatment. The shortcomings of current methods create an impending need for developing novel biosensing platforms. CRISPR-Cas systems, especially CRISPR-Cas12a and CRISPR-Cas13a, characterized by their sensitivity, specificity, high base resolution and programmability upon nucleic acid recognition, have been repurposed for molecular diagnostics, surging a new path forward in biosensing. They, as the core of some robust diagnostic tools, are revolutionizing the way that virus can be detected. This review focuses on recent advances in virus detection with CRISPR-Cas systems especially CRISPR-Cas12a/Cas13a. We started with a short introduction to CRISPR-Cas systems and the properties of Cas12a and Cas13a effectors, and continued with reviewing the current advances of virus detection utilizing CRISPR-Cas systems. The significance and advantages of such methods were then discussed. Finally, the challenges and perspectives were proposed. We tried to provide readers with a concise profile of emerging and fast-expanding CRISPR-Cas based biosensing technology, and highlighted its potential applications in a range of scenarios with regard to virus detection.

Development of a reverse-transcription loop-mediated isothermal amplification assay for the detection of Tobacco mild green mosaic virus (TMGMV)

Tobacco mild green mosaic virus (TMGMV), a member species of the genus Tobamovirus, infects pepper (Capsicum annuum) and a number of other economically important species in the Solanaceae family. TMGMV infections had seriously impacted pepper production worldwide, including China. A reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assay was developed to detect TMGMV in pepper field samples and seed. This assay was based on four primers that matched to six sequences in the C-terminal region of the TMGMV genome. RT-LAMP assay could detect the presence of the virus in 3.0 × 10-7 µg of total RNA extract from pepper leaves, which was ten times more sensitive than the corresponding reverse-transcription polymerase chain reaction (RT-PCR) assay. This method specifically detected TMGMV but not the closely related species of the same genus Pepper mild mottle virus, Cucumber green mottle mosaic virus and Tomato mosaic virus. In addition, the use of SYBR Green I facilitated the detection of the TMGMV RT-LAMP products by the naked eye. These results indicated that the RT-LAMP assay was a simple, sensitive, specific and affordable diagnostic tool that has the potential to detect and monitor TMGMV infection in field samples.

Carbon dots for virus detection and therapy

Recent experience with the COVID-19 pandemic should be a lesson learnt with respect to the effort we have to invest in the development of new strategies for the treatment of viral diseases, along with their cheap, easy, sensitive, and selective detection. Since we live in a globalized world where just hours can play a crucial role in the spread of a virus, its detection must be as quick as possible. Thanks to their chemical stability, photostability, and superior biocompatibility, carbon dots are a kind of nanomaterial showing great potential in both the detection of various virus strains and a broad-spectrum antiviral therapy. The biosensing and antiviral properties of carbon dots can be tuned by the selection of synthesis precursors as well as by easy post-synthetic functionalization. In this review, we will first summarize current options of virus detection utilizing carbon dots by either electrochemical or optical biosensing approaches. Secondly, we will cover and share the up-to-date knowledge of carbon dots' antiviral properties, which showed promising activity against various types of viruses including SARS-CoV-2. The mechanisms of their antiviral actions will be further adressed as well. Finally, we will discuss the advantages and distadvantages of the use of carbon dots in the tangled battle against viral infections in order to provide valuable informations for further research and development of new virus biosensors and antiviral therapeutics.

Paper-based analytical devices for virus detection: Recent strategies for current and future pandemics

The importance of user-friendly, inexpensive, sensitive, and selective detection of viruses has been highlighted again due to the recent Coronavirus disease 2019 (COVID-19) pandemic. Among the analytical tools, paper-based devices (PADs) have become a leading alternative for point-of-care (POC) testing. In this review, we discuss the recent development strategies and applications in nucleic acid-based, antibody/antigen-based and other affinity-based PADs using optical and electrochemical detection methods for sensing viruses. In addition, advantages and drawbacks of presented PADs are identified. Current state and insights towards future perspectives are presented regarding developing POC diagnosis platform for COVID-19. This review considers state-of-the-art technologies for further development and improvement in PADs performance for virus detection.

Conventional and microfluidic methods for airborne virus isolation and detection

With the COVID-19 pandemic, the threat of infectious diseases to public health and safety has become much more apparent. Viral, bacterial and fungal diseases have led to the loss of millions of lives, especially in the developing world. Diseases caused by airborne viruses like SARS-CoV-2 are difficult to control, as these viruses are easily transmissible and can circulate in the air for hours. To contain outbreaks of viruses such as SARS-CoV-2 and institute targeted precautions, it is important to detect them in air and understand how they infect their targets. Point-of-care (PoC) diagnostics and point-of-need (PoN) detection methods are necessary to rapidly test patient and environmental samples, so precautions can immediately be applied. Traditional benchtop detection methods such as ELISA, PCR and culture are not suitable for PoC and PoN monitoring, because they can take hours to days and require specialized equipment. Microfluidic devices can be made at low cost to perform such assays rapidly and at the PoN. They can also be integrated with air- and liquid-based sampling technologies to capture and analyze viruses from air and body fluids. Here, conventional and microfluidic virus detection methods are reviewed and compared. The use of air sampling devices to capture and concentrate viruses is discussed first, followed by a review of analysis methods such as immunoassays, RT-PCR and isothermal amplification in conventional and microfluidic platforms. This review provides an overview of the capabilities of microfluidics in virus handling and detection, which will be useful to infectious disease researchers, biomedical engineers, and public health agencies.

Capacity of existing wastewater treatment plants to treat SARS-CoV-2. A review

Water is one of many viral transmission routes, and the presence of Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) in wastewater has brought attention to its treatment. SARS CoV-2 primarily transmits in the air but the persistence of the virus in the water possibly can serve as a secondary source even though current studies do not show this. In this paper, an evaluation of the current literature with regards to the treatment of SARS-CoV-2 in wastewater treatment plant (WWTP) effluents and biosolids is presented. Treatment efficiencies of WWTPs are compared for viral load reduction on the basis of publicly available data. The results of this evaluation indicate that existing WWTPs are effectively removing 1-6 log₁₀ viable SARS-CoV-2. However, sludge and biosolids provide an umbrella of protection from treatment and inactivation to the virus. Hence, sludge treatment factors like high temperature, pH changes, and predatory microorganisms can effectively inactivate SARS-CoV-2.

Design and finite element simulation of metal-core piezoelectric fiber/epoxy matrix composites for virus detection

Undoubtedly, the coronavirus disease 2019 (COVID-19) has received the greatest concern with a global impact, and this situation will continue for a long period of time. Looking back in history, airborne transimission diseases have caused huge casualties several times. COVID-19 as a typical airborne disease caught our attention and reminded us of the importance of preventing such diseases. Therefore, this study focuses on finding a new way to guard against the spread of these diseases such as COVID-19. This paper studies the dynamic electromechanical response of metal-core piezoelectric fiber/epoxy matrix composites, designed as mass load sensors for virus detection, by numerical modelling. The dynamic electromechanical response is simulated by applying an alternating current (AC) electric field to make the composite vibrate. Furthermore, both concentrated and distributed loads are considered to assess the sensitivity of the biosensor during modelling of the combination of both biomarker and viruses. The design parameters of this sensor, such as the resonant frequency, the position and size of the biomarker, will be studied and optimized as the key values to determine the sensitivity of detection. The novelty of this work is to propose functional composites that can detect the viruses from changes of the output voltage instead of the resonant frequency change using piezoelectric sensor and piezoelectric actuator. The contribution of this detection method will significantly shorten the detection time as it avoids fast Fourier transform (FFT) or discrete Fourier transform (DFT). The outcome of this research offers a reliable numerical model to optimize the design of the proposed biosensor for virus detection, which will contribute to the production of high-performance piezoelectric biosensors in the future.

A review on plasmonic and metamaterial based biosensing platforms for virus detection

Due to changes in our climate and constant loss of habitat for animals, new pathogens for humans are constantly erupting. SARS-CoV-2 virus, become so infectious and deadly that they put new challenge to the whole technological advancement of healthcare. Within this very decade, several other deadly virus outbreaks were witnessed by humans such as Zika virus, Ebola virus, MERS-coronavirus etc. and there might be even more infectious and deadlier diseases in the horizon. Though conventional techniques have succeeded in detecting these viruses to some extent, these techniques are time-consuming, costly, and require trained human-resources. Plasmonic metamaterial based biosensors might pave the way to low-cost rapid virus detection. So this review discusses in details, the latest development in plasmonics and metamaterial based biosensors for virus, viral particles and antigen detection and the future direction of research in this field.