Unlock unprecedented accuracy in viral detection with Virusure: A Smartphone integrated sensor empowered by Trailing Moving Average algorithm

Background and Aims: Australian certification programs that provide high-health planting material depend on accurate virus detection methods. The reliability of enzyme-linked immunosorbent assays (ELISAs) and reverse transcription-polymerase chain reaction (RT-PCR) tests for virus detection was compared in Australian conditions. Methods and Results: Replicate trials were established in a hot climate and a cool climate with grapevines that were uninoculated or inoculated with Grapevine virus A, Grapevine fleck virus, Grapevine leafroll-associated virus (GLRaV)-2 and GLRaV-3. Grapevines were tested monthly for virus during 3 years. RT-PCR detected viruses more frequently than ELISA, and the reliability of both tests increased after 12 months and up to 3 years post-inoculation in both climates. Conclusions: Viruses may not be consistently detected until 12 months after an infection event. RT-PCR is more reliable than ELISA for virus detection during spring and summer. However, detection of viruses was rarely 100% efficient, and retesting of grapevines is recommended to improve the rate of detection. Significance of the Study: Validated diagnostic procedures were developed to improve the reliability of grapevine virus detection in Australia.

Plants can be infected by a wide range of viruses that often cause important agronomic, economic and social impacts. Detection of viruses at premature stages of infection is crucial to allow control viral diseases and reduce economic losses. For that reason, the use of rapid, sensitive and accurate detection methods is recommended. Molecular techniques have revolutionized the way of plant virus detection and identification. Retrotranscription (RT)-polymerase chain reaction (PCR) is the 'gold standard' method for virus detection in most laboratories worldwide because of its sensitivity, specificity, simplicity and rapidity. Since its discovery, many versions and continuous improvements of PCR have been developed. Nested and co-operational RT-PCR achieve high sensitivity, decreasing contamination risks and multiplex RT-PCR offer the possibility to detect several targets in one assay. The development of real-time RT-PCR completely revolutionized the way of virus detection and quantitation, contributing enormously to the control of plant virus diseases. Some novel molecular methods such as nucleic acids arrays, isothermal amplification, massive sequencing and biosensors could be applied in the future in most diagnostic laboratories. However, the use of validated and integrated protocols that include molecular techniques combined with serological or biological methods will increase the accuracy and reliability of virus detection. In this review, the main RT-PCR-based methods used for plant virus detection are described and the advantages and drawbacks of each of them are discussed.

Respiratory viruses are a common cause of respiratory tract infection (RTI), particularly in neonates and children. Rapid and accurate diagnosis of viral infections could improve clinical outcomes and reduce the use of antibiotics and treatment sessions. Advances in diagnostic technology contribute to the accurate detection of viruses. We performed a multiplex real-time polymerase chain reaction (PCR) to investigate the viral etiology in pediatric patients and compared the detection rates with those determined using traditional antigen tests and virus cultures. Fifteen respiratory viruses were included in our investigation: respiratory syncytial virus A/B (RSV), influenza virus A (FluA) and influenza virus B (FluB), human metapneumovirus (MPV), enterovirus (EV), human parainfluenza virus (PIV) types 1–4, human rhinovirus (RV), human coronavirus OC43, NL63, and 229E, human adenovirus (ADV), and human bocavirus (Boca). In total, 474 specimens were collected and tested. Respiratory viruses were detected more frequently by PCR (357, 75.3%) than they were by traditional tests (229, 49.3%). The leading pathogens were RSV (113, 23.8%), RV (72, 15.2%), PIV3 (53, 11.2%), FluA (51, 10.8%), and ADV (48, 10.1%). For children younger than 5 years, RSV and RV were most prevalent; for children older than 5 years, FluA and ADV were the most frequently detected. Of the specimens, 25.8% (92/357) were coinfected with two or more viruses. RV, Boca, PIV2, FluB, and PIV4 had higher rates of coinfection; MPV and PIV1 had the lowest rates of coinfection (9.1% and 5.3%). To conclude, the detection power of PCR was better than that of traditional antigen tests and virus cultures when considering the detection of respiratory viruses. RSV and RV were the leading viral pathogens identified in the respiratory specimens. One-quarter of the positive specimens were coinfected with two or more viruses. In the future, further application of PCR may contribute to the rapid and accurate diagnosis of respiratory viruses and could improve patient outcomes.

Production of monoclonal antibodies for detection of Citrus leprosis virus C in enzyme-linked immuno-assays and immunocapture reverse transcription-polymerase chain reaction

Plants infected by a wide range of viruses often cause important agronomic and economic losses worldwide. Detection of plant viruses is becoming more challenging as globalisation of trade, particularly the ornamental plants, and the potential effects of climate change facilitate movement of viruses and their vectors, thereby transforming the diagnostic landscape. Under such circumstances, detection of viruses at premature stages of infection by use of rapid, sensitive and accurate detection methods seems crucial to ensure safe and sustainable agriculture and as such reduces economic losses. For proper identification, detection technique needs to be rapid, most accurate and inexpensive, as it forms the key step in developing appropriate practical solutions to manage plant virus diseases that pose continuous threats to the viability of certain horticultural and agricultural industries. This review is concerned with the advancement in techniques in the diagnosis of viruses in plants.

Detection and quantification of four viruses in Prunus pollen: Implications for biosecurity

Comprehensive SummaryThe prevalence and spread of viral infectious diseases pose a grave threat to global public health, particularly resulting in a significant number of casualties. To curb the spread of infectious diseases, virus testing is one of the efficient and economical means, among which nucleic acid detection has the advantage of detecting viral infections at an early stage, even before symptoms appear. Rolling circle replication is a representative of enzyme‐mediated nucleic acid isothermal amplification technology, which is characterized by its mild reaction conditions, no need for temperature control equipment, and high efficiency. This review provides a conceptual overview of the latest advances of rolling circle replication (RCR) and their applications in viral detection, focusing on the molecular design principles in different application scenarios. The first part briefly describes the significance and advantages of RCR in virus detection. The second part elaborates on the design principle and preparation strategy of RCR and its derivative technologies. The third part focuses on the various application scenarios in virus detection. In the end, we provide a perspective on the innovation of RCR in improving the accuracy and specificity of virus detection to cope with the challenges of infectious diseases that may arise in the future.

All biological products are required to demonstrate the absence of adventitious viruses (AVs), which may be inadvertently introduced at different steps involved in the manufacturing process. The currently recommended in vitro and in vivo virus detection assays have limitations for broad detection and are lengthy and laborious. Additionally, the use of animals is discouraged by the global 3 R's initiative for replacement, reduction, and refinement. High-throughput or next-generation sequencing (HTS/NGS) technologies can rapidly detect known and novel viruses in biological materials. There are, however, challenges for HTS detection of AVs due to differential abundance of viral sequences in public databases, which led to the creation of a non-redundant, Reference Viral Database (RVDB) containing all viral, viral-like, and viral-related sequences, with a reduced cellular sequence content. In this paper, we describe improvements in RVDB, which include the transition of RVDB production scripts from the original Python 2 to Python 3 codebase, updating the semantic pipeline to remove misannotated non-viral sequences and irrelevant viral sequences, use of taxonomy for the removal of phages, and inclusion of a quality-check step for SARS-CoV-2 genomes to exclude low-quality sequences. Additionally, RVDB website updates include search tools for exploring the database sequences and implementation of an automatic pipeline for providing annotation information to distinguish non-viral and viral sequences in the database. These updates for refining RVDB are expected to enhance HTS bioinformatics by reducing the computational time and increasing the accuracy for virus detection.IMPORTANCEHigh-throughput sequencing (HTS) has emerged as an advanced technology for demonstrating the safety of biological products. HTS can be used as an alternative adventitious virus detection method for replacing the currently recommended in vivo and PCR assays and supplementing or replacing the in vitro cell culture assays. However, HTS bioinformatics analysis for broad virus detection, including both known and novel viruses, depends on using a comprehensive and accurately annotated database. In this study, we have refined our original comprehensive Reference Virus Database (RVDB) for greater accuracy of virus detection with a reduced computational burden. Additionally, the production script for automating the generation of RVDB was updated to facilitate reliable database production and timely availability.

Virus-based human infectious diseases have a significant negative impact on people's health and social development. The need for quick, accurate, and early viral infection detection in preventive medicine is expanding. A microfluidic control is particularly suitable for point-of-care-testing virus diagnosis due to its advantages of low sample consumption, quick detection speed, simple operation, multi-functional integration, small size, and easy portability. It is also thought to have significant development potential and a wide range of application prospects in the research on virus detection technology. In an effort to aid researchers in creating novel microfluidic tools for virus detection, this review highlights recent developments of droplet-based microfluidics in virus detection research and also discusses the challenges and opportunities for rapid virus detection.

The impact of viral diseases on human health is becoming increasingly prevalent globally with the burden of disease being shared between resource-rich and poor areas. As seen in the global pandemic caused by SARS-CoV-2, there is a need to establish viral detection techniques applicable to resource-limited areas that provide sensitive and specific testing with a logistically conscious mindset. Herein, we describe a direct-to-PCR technology utilizing mechanical homogenization prior to viral PCR detection, which allows the user to bypass traditional RNA extraction techniques for accurate detection of human coronavirus. This methodology was validated in vitro, utilizing human coronavirus 229E (HCoV-229E), and then clinically, utilizing patient samples to test for SARS-CoV-2 infection. In this manuscript, we describe in detail the protocol utilized to determine the limit of detection for this methodology with in vitro testing of HCoV-229E.

Infectious pathogens cause severe human illnesses and great deaths per year worldwide. Rapid, sensitive, and accurate detection of pathogens is of great importance for preventing infectious diseases caused by pathogens and optimizing medical healthcare systems. Inspired by a microbial defense system (i.e., CRISPR/ CRISPR-associated proteins (Cas) system, an adaptive immune system for protecting microorganisms from being attacked by invading species), a great many new biosensors have been successfully developed and widely applied in the detection of infectious viruses and pathogenic bacteria. Moreover, advanced nanotechnologies have also been integrated into these biosensors to improve their detection stability, sensitivity, and accuracy. In this review, the recent advance in CRISPR/Cas systems-based nano/biosensors and their applications in the detection of infectious viruses and pathogenic bacteria are comprehensively reviewed. First of all, the categories and working principles of CRISPR/Cas systems for establishing the nano/biosensors are simply introduced. Then, the design and construction of CRISPR/Cas systems-based nano/biosensors are comprehensively discussed. In the end, attentions are focused on the applications of CRISPR/Cas systems-based nano/biosensors in the detection of infectious viruses and pathogenic bacteria. Impressively, the remaining opportunities and challenges for the further design and development of CRISPR/Cas system-based nano/biosensors and their promising applications are proposed.

This study was performed to develop real-time PCR (qPCR) for detection of human seasonal and avian influenza viruses in duplex format. First duplex qPCR detects haemagglutinin (HA) gene of influenza virus A(H1N1)pdm09 and HA gene of influenza virus A(H3N2), the second reaction detects neuraminidase (NA) gene of influenza virus A(H3N2) and NA gene of influenza virus A(H1N1)pdm09 and A(H5N1), and the third reaction detects HA gene of influenza A(H5N1) and nonstructural protein gene of influenza B virus. Primers and probes were designed using multiple alignments of target gene sequences of different reference strains. Assays were optimised for identical thermocycling conditions. Their specificity was confirmed by conventional PCR and monoplex qPCR with nucleic acids isolated from different influenza viruses and other respiratory pathogens. Plasmid constructs with a fragment of specific gene were used to assess sensitivity of the assay. The limit of detection ranged from 27 to 96 cDNA copies/reaction. Clinical specimens (n = 107) have been tested using new assays, immunofluorescence and monoplex qRT-PCR. It has been shown that developed assays have been capable of rapid and accurate simultaneous detection and differentiation of influenza viruses. They are more sensitive than immunofluorescence and at least as sensitive as monoplex qRT-PCR.

High-throughput sequencing (HTS) technologies and bioinformatic analyses are of growing interest to be used as a routine diagnostic tool in the field of plant viruses. The reliability of HTS workflows from sample preparation to data analysis and results interpretation for plant virus detection and identification must be evaluated (verified and validated) to approve this tool for diagnostics. Many different extraction methods, library preparation protocols, and sequence and bioinformatic pipelines are available for virus sequence detection. To assess the performance of plant virology diagnostic laboratories in using the HTS of ribosomal RNA depleted total RNA (ribodepleted totRNA) as a diagnostic tool, we carried out an interlaboratory comparison study in which eight participants were required to use the same samples, (RNA) extraction kit, ribosomal RNA depletion kit, and commercial sequencing provider, but also their own bioinformatics pipeline, for analysis. The accuracy of virus detection ranged from 65% to 100%. The false-positive detection rate was very low and was related to the misinterpretation of results as well as to possible cross-contaminations in the lab or sequencing provider. The bioinformatic pipeline used by each laboratory influenced the correct detection of the viruses of this study. The main difficulty was the detection of a novel virus as its sequence was not available in a publicly accessible database at the time. The raw data were reanalysed using Virtool to assess its ability for virus detection. All virus sequences were detected using Virtool in the different pools. This study revealed that the ribodepletion target enrichment for sample preparation is a reliable approach for the detection of plant viruses with different genomes. A significant level of virology expertise is needed to correctly interpret the results. It is also important to improve and complete the reference data.

Existing antivirus products employ diverse types of techniques to detect malware or any suspicious activities. The majority of such techniques rely on signature-based detection algorithms. However, the speed of such detection algorithms may adversely impact the performance of the antivirus products (e.g., if used for online virus scanning). In this paper, we review existing research that proposed fast and efficient signature-based algorithms to dynamically improve the time and accuracy of virus detection. We classify and discuss the different algorithms according to the type of analysis they perform (i.e., static, dynamic or hybrid). In addition, we evaluate existing virus detection algorithms using different design issues and performance criteria, namely (a) memory cost, (b) time complexity, and (c) detection rates. In addition, we discuss how certain design choices of signature-based approaches can only apply to specific virus detection circumstances. Finally, we present the current research challenges of using signature-based algorithms for investigating cybercrime activities.

ABSTRACTAdventitious agent detection during the production of vaccines and biotechnology-based medicines is of critical importance to ensure the final product is free from any possible viral contamination. Increasing the speed and accuracy of viral detection is beneficial as a means to accelerate development timelines and to ensure patient safety. Here, several rapid viral metagenomics approaches were tested on simulated next-generation sequencing (NGS) data sets and existing data sets from virus spike-in studies done in CHO-K1 and HeLa cell lines. It was observed that these rapid methods had comparable sensitivity to full-read alignment methods used for NGS viral detection for these data sets, but their specificity could be improved. A method that first filters host reads using KrakenUniq and then selects the virus classification tool based on the number of remaining reads is suggested as the preferred approach among those tested to detect nonlatent and nonendogenous viruses. Such an approach shows reasonable sensitivity and specificity for the data sets examined and requires less time and memory as full-read alignment methods.IMPORTANCE Next-generation sequencing (NGS) has been proposed as a complementary method to detect adventitious viruses in the production of biotherapeutics and vaccines to current in vivo and in vitro methods. Before NGS can be established in industry as a main viral detection technology, further investigation into the various aspects of bioinformatics analyses required to identify and classify viral NGS reads is needed. In this study, the ability of rapid metagenomics tools to detect viruses in biopharmaceutical relevant samples is tested and compared to recommend an efficient approach. The results showed that KrakenUniq can quickly and accurately filter host sequences and classify viral reads and had comparable sensitivity and specificity to slower full read alignment approaches, such as BLASTn, for the data sets examined.