One-step duplex RT-droplet digital PCR assay for the detection of norovirus GI and GII in lettuce and strawberry

An international inter-laboratory study to compare digital PCR with ISO standardized qPCR assays for the detection of norovirus GI and GII in oyster tissue

An optimized digital RT-PCR (RT-dPCR) assay for the detection of human norovirus GI and GII RNA was compared with ISO 15216-conform quantitative real-time RT-PCR (RT-qPCR) assays in an interlaboratory study (ILS) among eight laboratories. A duplex GI/GII RT-dPCR assay, based on the ISO 15216-oligonucleotides, was used on a Bio-Rad QX200 platform by six laboratories. Adapted assays for Qiagen Qiacuity or ThermoFisher QuantStudio 3D were used by one laboratory each. The ILS comprised quantification of norovirus RNA in the absence of matrix and in oyster tissue samples. On average, results of the RT-dPCR assays were very similar to those obtained by RT-qPCR assays. The coefficient of variation (CV%) of norovirus GI results was, however, much lower for RT-dPCR than for RT-qPCR in intra-laboratory replicates (eight runs) and between the eight laboratories. The CV% of norovirus GII results was in the same range for both detection formats. Had in-house prepared dsDNA standards been used, the CV% of norovirus GII could have been in favor of the RT-dPCR assay. The ratio between RT-dPCR and RT-qPCR results varied per laboratory, despite using the distributed RT-qPCR dsDNA standards. The study indicates that the RT-dPCR assay is likely to increase uniformity of quantitative results between laboratories.

Improving the Detection and Understanding of Infectious Human Norovirus in Food and Water Matrices: A Review of Methods and Emerging Models

Human norovirus (HuNoV) is a leading global cause of viral gastroenteritis, contributing to numerous outbreaks and illnesses annually. However, conventional cell culture systems cannot support the cultivation of infectious HuNoV, making its detection and study in food and water matrices particularly challenging. Recent advancements in HuNoV research, including the emergence of models such as human intestinal enteroids (HIEs) and zebrafish larvae/embryo, have significantly enhanced our understanding of HuNoV pathogenesis. This review provides an overview of current methods employed for HuNoV detection in food and water, along with their associated limitations. Furthermore, it explores the potential applications of the HIE and zebrafish larvae/embryo models in detecting infectious HuNoV within food and water matrices. Finally, this review also highlights the need for further optimization and exploration of these models and detection methods to improve our understanding of HuNoV and its presence in different matrices, ultimately contributing to improved intervention strategies and public health outcomes.

A review of nucleic acid-based detection methods for foodborne viruses: Sample pretreatment and detection techniques

Viruses are major pathogens that cause food poisoning when ingested via contaminated food and water. Therefore, the development of foodborne virus detection technologies that can be applied throughout the food distribution chain is essential for food safety. A common nucleic acid-based detection method is polymerase chain reaction (PCR), which has become the gold standard for monitoring food contamination by viruses due to its high sensitivity, and availability of commercial kits. However, PCR-based methods are labor intensive and time consuming, and are vulnerable to inhibitors that may be present in food samples. In addition, the methods are restricted with regard to site of analysis due to the requirement of expensive and large equipment for sophisticated temperature regulation and signal analysis procedures. To overcome these limitations, optical and electrical readout biosensors based on nucleic acid isothermal amplification technology and nanomaterials have emerged as alternatives for nucleic acid-based detection of foodborne viruses. Biosensors are promising portable detection tools owing to their easy integration into compact platforms and ability to be operated on-site. However, the complexity of food components necessitates the inclusion of tedious preprocessing steps, and the lack of stability studies on residual food components further restricts the practical application of biosensors as a universal detection method. Here, we summarize the latest advances in nucleic acid-based strategies for the detection of foodborne viruses, including PCR-based and isothermal amplification-based methods, gene amplification-free methods, as well as food pretreatment methods. The principles, strengths/disadvantages, and performance of each method, problems to be solved, and future prospects for the development of a universal detection method are discussed.

Risk assessment of norovirus and hepatitis A virus in strawberries imported into China

Norovirus (NoV) and hepatitis A virus (HAV) pose a considerable health risk worldwide. In recent years, many cases of virus infection caused by virus-contaminated strawberries have occurred worldwide. This study applied a critical control point system to analyze the main hazards during the production and marketing of strawberries imported into China and explore the key control points in the whole process. To further evaluate the risks in the supply chain, the established quantitative microbial risk assessment (QMRA) was used to determine the probability that residents would be infected with viruses after consuming imported strawberries. It was found that the risk of virus contamination from imported strawberries was low, and the virus contamination mainly results from water resources and personnel. This research helps the regulatory authorities formulate strategies to ensure the long-term microbial safety of imported strawberries. In addition, the methods may prove useful in evaluating the risks of other agricultural produce.

Quantitative Risk Assessment of Five Foodborne Viruses in Shellfish Based on Multiplex qPCR

Foodborne diseases are currently the most critical food safety issue in the world. There are not many hazard identification and exposure assessments for foodborne viruses (Norovirus GI, GII, Hepatitis A Virus, Rotavirus, Adenovirus) in shellfish. Multiplex qPCR for the simultaneous detection of five foodborne viruses was established and used to assess infection risk based on a 1-year pathogenesis study. The sensitivity, specificity and reproducibility of the multiplex qPCR method are consistent with that of conventional qPCR, which saves more time and effort. Overall, 37.86% of shellfish samples had one or more foodborne viruses. Risk assessment formulae and matrices were used to develop risk assessments for different age groups, different seasons and different shellfish. The annual probability of contracting a foodborne virus infection from shellfish is greater than 1.6 × 10-1 for all populations, and even for infants aged 0-4 years, it is greater than 1.5 × 10-2, which is much higher than the risk thresholds recommended by WHO (10-6) and the US EPA (10-4). High risk (level IV) is associated with springtime, and medium risk (level III) is associated with Mussel consumption. This study provides a basis for the risk of foodborne viral infections in people of different ages, in different seasons, and by consuming different shellfish.

Use of bentonite-coated activated carbon for improving the sensitivity of RT-qPCR detection of norovirus from vegetables and fruits: The ISO 15216-1:2017 standard method extension

Produce-related foodborne outbreaks are becoming increasingly prevalent worldwide. In plant tissues, various compounds, including polysaccharides, phenolic compounds, and chlorophyll, can inhibit RT-PCR detection of viruses. In this study, we developed a highly sensitive RT-qPCR in combination with the bentonite-coated activated carbon (BCAC) assay for detection of norovirus from fruits and vegetables, which could be completed within 7 h and was about 10-100 fold more sensitive than the standard procedures (ISO 15216-1:2017). The extraction efficiencies of three surrogate viruses (MS2, MNV-1, and TV) from five fresh produce (lettuce, cherry tomato, blueberry, strawberry, and spinach) were higher with BCAC treatment than those of control groups, ranging from 17.82% to 98.60%. The average detection limit of these viruses using the BCAC-RT-qPCR method was stable at an average of 102 PFU/g or GC/g. Finally, this BCAC-RT-qPCR method was applied for detection of human norovirus GII.4 spiked onto lettuce and cherry tomato. The viral extraction efficiencies were up to 53.43% and 95.56%, respectively, which is almost four and seven times better than those without BCAC. Therefore, the BCAC-RT-qPCR method can be used to detect low levels of foodborne viruses from produce.

A “peptide-target-aptamer” electrochemical biosensor for norovirus detection using a black phosphorous nanosheet@Ti3C2-Mxene nanohybrid and magnetic covalent organic framework

Norovirus (NoV) is a major foodborne pathogen responsible for acute gastroenteritis epidemics, and establishing a robust detection method for the timely identification and monitoring of NoV contamination is of great significance. In this study, a peptide-target-aptamer sandwich electrochemical biosensor for NoV was fabricated using Au@BP@Ti₃C₂-MXene and magnetic Au@ZnFe₂O₄@COF nanocomposites. The response currents of the electrochemical biosensor were proportional to the NoV concentrations ranging from 0.01-10⁵ copies/mL with a detection limit (LOD) of 0.003 copies/mL (S/N = 3). To our best knowledge, this LOD was the lowest among published assays to date, due to the specific recognition of the affinity peptide and aptamer for NoV and the outstanding catalytic activity of nanomaterials. Furthermore, the biosensor showed excellent selectivity, anti-interference performance, and satisfactory stability. The NoV concentrations in simulative food matrixes were successfully detected using the constructed biosensor. Meanwhile, NoV in stool samples was also successfully quantified without complex pretreatment. The designed biosensor had the potential to detect NoV (even at a low level) in foods, clinical samples, and environmental samples, providing a new method for NoV detection in food safety and diagnosing foodborne pathogens.

CRISPR-Cas systems mediated biosensing and applications in food safety detection

Food safety, closely related to economic development of food industry and public health, has become a global concern and gained increasing attention worldwide. Effective detection technology is of great importance to guarantee food safety. Although several classical detection methods have been developed, they have some limitations in portability, selectivity, and sensitivity. The emerging CRISPR-Cas systems, uniquely integrating target recognition specificity, signal transduction, and efficient signal amplification abilities, possess superior specificity and sensitivity, showing huge potential to address aforementioned challenges and develop next-generation techniques for food safety detection. In this review, we focus on recent progress of CRISPR-Cas mediated biosensing and their applications in food safety monitoring. The properties and principles of commonly used CRISPR-Cas systems are highlighted. Notably, the frequently coupled nucleic acid amplification strategies to enhance their selectivity and sensitivity, especially isothermal amplification methods, as well as various signal output modes are also systematically summarized. Meanwhile, the application of CRISPR-Cas systems-based biosensors in food safety detection including foodborne virus, foodborne bacteria, food fraud, genetically modified organisms (GMOs), toxins, heavy metal ions, antibiotic residues, and pesticide residues is comprehensively described. Furthermore, the current challenges and future prospects in this field are tentatively discussed.