Evaluation of a new automated viral RNA extraction platform for hepatitis A virus and human norovirus in testing of berries, lettuce, and oysters.

Fruits, vegetables, and shellfish are often associated with outbreaks of illness caused particularly by human norovirus (HuNoV) and hepatitis A virus (HAV), the leading causative agents of foodborne illness worldwide. The aim of this study was to evaluate a new automated nucleic acid extraction platform (EGENE-UP EASYPREP) for enteric viruses in several at-risk food matrices and to test its limit of detection in comparison to a semi-automated method (EGENE-UP) using Boom methodology for nucleic acid extraction as suggested in the reference method ISO 15216-2:2019. Fresh and frozen raspberries, frozen blackberries, romaine lettuce and oyster digestive glands were artificially contaminated with HAV, HuNoV GII.4 or HuNoV GI.7 at 102, 103 or 104 genome copies/sample. Virus was then recovered from the food matrix using the ISO method. Viral RNA extracted from frozen berry samples by the automated system was purified on a column for additional removal of RT-qPCR inhibitors. For fresh raspberry, oysters, and romaine lettuce, the two extraction platforms were deemed equivalent. For frozen raspberry, the automated platform appeared to be more efficient for viral recovery, particularly for HAV and HuNoV GI at lower concentrations. With frozen blackberries, the two platforms may be considered equivalent for all targeted viruses. However, the automated method led to less sample-associated inhibition of the PCR, 56.5 % of samples versus 95.0 % for the semi-automated. We thus found that the automated extraction can be performed easily by users while obtaining equivalent or even superior results to the ISO 15216-2:2019 method, and therefore appears to be suitable for routine sanitary monitoring in food processing and for tracing outbreaks of illness.

Concentration of foodborne viruses eluted from fresh and frozen produce: Applicability of ultrafiltration.

Foodborne illnesses involving raw and minimally processed foods are often caused by human noroviruses (HuNoV) and hepatitis A virus (HAV). Since food is contaminated usually with small numbers of virions, these must be eluted from the food surface and then concentrated for detection. The objective of this study was to optimize an ultrafiltration (UF) concentration method for HAV and HuNoVs present on various fresh and frozen produce. The detection range of the optimized method and its applicability to different food matrices was compared to the reference method ISO 15216-1:2017. Strawberry, raspberry, blackberry, lettuce, and green onion (25 g) were contaminated with HAV, HuNoV GI.7 and HuNoV GII.4 and then recovered therefrom by elution. A commercial benchtop UF device was used for the concentration step. Viral RNA was extracted and detected by RT-qPCR. From fresh strawberries, recovery of HAV loaded at 104 genome copies per sample was 30 ± 13 %, elution time had no significant impact, and UF membrane with an 80-100 kDa cut-off in combination with Tris-glycine elution buffer at pH 9.5 was found optimal. At lower copy numbers on fresh strawberry, at least 1 log lower numbers of HuNoV were detectable by the UF method (103 vs 104 GII.4 copies/sample and 101 vs 103 GI.7 copies/sample), while HAV was detected at 101 genome copies/sample by both methods. Except on raspberry, the UF method was usually equivalent to the ISO method regardless of the virus tested. The UF method makes rapid viral concentration possible, while supporting the filtration of large volume of sample. With fewer steps and shorter analysis time than the ISO method, this method could be suitable for routine analysis of viruses throughout the food production and surveillance chain.

Detection of Enteric Viruses on Strawberries and Raspberries Using Capture by Apolipoprotein H.

Human noroviruses (HuNoVs) and the hepatitis A virus (HAV) are the main viral causes of foodborne illness worldwide. These viruses are frequently transmitted via fresh and frozen berries, such as strawberries and raspberries. ISO 15216:1 (2017), currently the preferred method for their detection, involves several steps and is time-consuming. Apolipoprotein H (ApoH) has been shown to have a strong affinity for several microorganisms, including HuNoVs. In this article, we report an ApoH-based method of capturing the HAV and HuNoVs adherent to berries and concentrating them for assay. The limit of detection of both viruses suspended in a buffer was low. On strawberries, the HAV was detected down to 104 genome copies/25 g in 100% of cases and down to 103 genome copies/25 g on raspberries in 50% of cases. This sensitivity was not significantly different from that of the ISO method 15216:1 (2017). HuNoV GII.4 was more difficult to detect using the ApoH method. The ApoH CaptoVIR kit does, nevertheless, appear to be usable in the near future as a single-test, multiple-detection method for viruses on fresh and frozen berries.

Foodborne viruses: Detection, risk assessment, and control options in food processing.

In a recent report by risk assessment experts on the identification of food safety priorities using the Delphi technique, foodborne viruses were recognized among the top rated food safety priorities and have become a greater concern to the food industry over the past few years. Food safety experts agreed that control measures for viruses throughout the food chain are required. However, much still needs to be understood with regard to the effectiveness of these controls and how to properly validate their performance, whether it is personal hygiene of food handlers or the effects of processing of at risk foods or the interpretation and action required on positive virus test result. This manuscript provides a description of foodborne viruses and their characteristics, their responses to stress and technologies developed for viral detection and control. In addition, the gaps in knowledge and understanding, and future perspectives on the application of viral detection and control strategies for the food industry, along with suggestions on how the food industry could implement effective control strategies for viruses in foods. The current state of the science on epidemiology, public health burden, risk assessment and management options for viruses in food processing environments will be highlighted in this review.

High throughput multiple locus variable number of tandem repeat analysis (MLVA) of Staphylococcus aureus from human, animal and food sources.

Staphylococcus aureus is a major human pathogen, a relevant pathogen in veterinary medicine, and a major cause of food poisoning. Epidemiological investigation tools are needed to establish surveillance of S. aureus strains in humans, animals and food. In this study, we investigated 145 S. aureus isolates recovered from various animal species, disease conditions, food products and food poisoning events. Multiple Locus Variable Number of Tandem Repeat (VNTR) analysis (MLVA), known to be highly efficient for the genotyping of human S. aureus isolates, was used and shown to be equally well suited for the typing of animal S. aureus isolates. MLVA was improved by using sixteen VNTR loci amplified in two multiplex PCRs and analyzed by capillary electrophoresis ensuring a high throughput and high discriminatory power. The isolates were assigned to twelve known clonal complexes (CCs) and--a few singletons. Half of the test collection belonged to four CCs (CC9, CC97, CC133, CC398) previously described as mostly associated with animals. The remaining eight CCs (CC1, CC5, CC8, CC15, CC25, CC30, CC45, CC51), representing 46% of the animal isolates, are common in humans. Interestingly, isolates responsible for food poisoning show a CC distribution signature typical of human isolates and strikingly different from animal isolates, suggesting a predominantly human origin.