Numerous viruses of human or animal origin can spread in the environment and infect people via water and food, mostly through ingestion and occasionally through skin contact. These viruses are released into the environment by various routes including water run-offs and aerosols. Furthermore, zoonotic viruses may infect humans exposed to contaminated surface waters. Foodstuffs of animal origin can be contaminated, and their consumption may cause human infection if the viruses are not inactivated during food processing. Molecular epidemiology and surveillance of environmental samples are necessary to elucidate the public health hazards associated with exposure to environmental viruses. Whereas monitoring of viral nucleic acids by PCR methods is relatively straightforward and well documented, detection of infectious virus particles is technically more demanding and not always possible (e.g. human norovirus or hepatitis E virus). The human pathogenic viruses that are most relevant in this context are nonenveloped and belong to the families of the Caliciviridae, Adenoviridae, Hepeviridae, Picornaviridae and Reoviridae. Sampling methods and strategies, first-choice detection methods and evaluation criteria are reviewed.

We developed and assessed real-time PCR (RTi-PCR) assays for the detection and quantification of the foodborne pathogen Listeria monocytogenes and the closely related nonpathogenic species L. innocua. The target genes were hly and iap for L. monocytogenes and lin02483 for L. innocua. The assays were 100% specific, as determined with 100 Listeria strains and 45 non-Listeria strains, and highly sensitive, with detection limits of one target molecule in 11 to 56% of the reactions with purified DNA and 3 CFU in 56 to 89% of the reactions with bacterial suspensions. Quantification was possible over a 5-log dynamic range, with a limit of 15 target molecules and R 2 values of >0.996. There was an excellent correspondence between the predicted and the actual numbers of CFU in the samples (deviations of <23%). The hly-based assay accurately quantified L. monocytogenes in all of the samples tested. The iap-based assay, in contrast, was unsuitable for quantification purposes, underestimating the bacterial counts by 3 to 4 log units in a significant proportion of the samples due to serovar-related target sequence variability. The combination of the two assays enabled us to classify L. monocytogenes isolates into one of the two major phylogenetic divisions of the species, I and II. We also assessed the new AmpliFluor technology for the quantitative detection of L. monocytogenes by RTi-PCR. The performance of this system was similar to that of the TaqMan system, although the former system was slightly less sensitive (detection limit of 15 molecules in 45% of the reactions) and had a higher quantification limit (60 molecules). Bacteria of the facultative anaerobic gram-positive genusListeria are widely distributed in the environment, particularly the closely related species Listeria monocytogenes and L. innocua. Both of these Listeria spp. are frequently found in food products, where they can grow over a pH range of 4.39 to 9.40, even at refrigeration temperatures. Ingestion of foods contaminated with L. monocytogenes can result in listeriosis, a severe infectious disease characterized by meningoencephalitis, abortion, septicemia, and a high fatality rate (30%). Listeriosis predominantly affects certain risk groups, including pregnant women, newborns, elderly people, and immunocompromised patients. L. innocua, in contrast, is nonpathogenic, and its presence in foods is no hazard to human health (20,25,35,37,41). Human listeriosis outbreaks are most often associated with ready-to-eat food products that are consumed without prior cooking (8, 36). To err on the side of caution, food safety regulations have tended to adopt a zero-tolerance attitude for L. monocytogenes in these products (9). However, as clinical cases of listeriosis are usually associated with high loads of L. monocytogenes (6,8) and as it is difficult to eradicate listeriae from the environment of food-processing plants (11), the International Commission on Microbiological Specification for Foods concluded that 100 CFU of L. monocytogenes per g of food is accepta...

Processing does not substantially abate endogenous virus.

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Identifying the connections between molecular and physiological processes underlying the diversity of drought stress responses in plants is key for basic and applied science. Drought stress response involves a large number of molecular pathways and subsequent physiological processes. Therefore, it constitutes an archetypical systems biology model. We first inferred a gene-phenotype network exploiting differences in drought responses of eight sunflower (Helianthus annuus) genotypes to two drought stress scenarios. Large transcriptomic data were obtained with the sunflower Affymetrix microarray, comprising 32423 probesets, and were associated to nine morpho-physiological traits (integrated transpired water, leaf transpiration rate, osmotic potential, relative water content, leaf mass per area, carbon isotope discrimination, plant height, number of leaves and collar diameter) using sPLS regression. Overall, we could associate the expression patterns of 1263 probesets to six phenotypic traits and identify if correlations were due to treatment, genotype and/or their interaction. We also identified genes whose expression is affected at moderate and/or intense drought stress together with genes whose expression variation could explain phenotypic and drought tolerance variability among our genetic material. We then used the network model to study phenotypic changes in less tractable agronomical conditions, i.e. sunflower hybrids subjected to different watering regimes in field trials. Mapping this new dataset in the gene-phenotype network allowed us to identify genes whose expression was robustly affected by water deprivation in both controlled and field conditions. The enrichment in genes correlated to relative water content and osmotic potential provides evidence of the importance of these traits in agronomical conditions.

Potential ways to address the issues that relate to the techniques for analyzing food and environmental samples for the presence of enteric viruses are discussed. It is not the authors' remit to produce or recommend standard or reference methods but to address specific issues in the analytical procedures. Foods of primary importance are bivalve molluscs, particularly, oysters, clams, and mussels; salad crops such as lettuce, green onions and other greens; and soft fruits such as raspberries and strawberries. All types of water, not only drinking water but also recreational water (fresh, marine, and swimming pool), river water (irrigation water), raw and treated sewage are potential vehicles for virus transmission. Well over 100 different enteric viruses could be food or water contaminants; however, with few exceptions, most well-characterized foodborne or waterborne viral outbreaks are restricted to hepatitis A virus (HAV) and calicivirus, essentially norovirus (NoV). Target viruses for analytical methods include, in addition to NoV and HAV, hepatitis E virus (HEV), enteroviruses (e.g., poliovirus), adenovirus, rotavirus, astrovirus, and any other relevant virus likely to be transmitted by food or water. A survey of the currently available methods for detection of viruses in food and environmental matrices was conducted, gathering information on protocols for extraction of viruses from various matrices and on the various specific detection techniques for each virus type.

Human sewage from Florianopolis (Santa Catarina, Brazil) was analyzed for severe acute respiratory syndrome coronavirus-2 (SARS-CoV2) from October 2019 until March 2020. Twenty five ml of sewage samples were clarified and viruses concentrated using a glycine buffer method coupled with polyethylene glycol precipitation, and viral RNA extracted using a commercial kit. SARS-CoV-2 RNA was detected by RT-qPCR using oligonucleotides targeting N1, S and two RdRp regions. The results of all positive samples were further confirmed by a different RT-qPCR system in an independent laboratory. S and RdRp amplicons were sequenced to confirm identity with SARS-CoV-2. Genome sequencing was performed using two strategies; a sequence-independent single-primer amplification (SISPA) approach, and by direct metagenomics using Illumina's NGS. SARS-CoV-2 RNA was detected on 27th November 2019 (5.49 ± 0.02 log 10 SARS-CoV-2 genome copies (GC) L −1 ), detection being confirmed by an independent laboratory and genome sequencing analysis. The samples in the subsequent three events were positive by all RT-qPCR assays; these positive results were also confirmed by an independent laboratory. The average load was 5.83 ± 0.12 log 10 SARS-CoV-2 GC L −1 , ranging from 5.49 ± 0.02 log 10 GC L −1 (27th November 2019) to 6.68 ± 0.02 log 10 GC L −1 (4th March 2020). Our findings demonstrate that SARS-CoV-2 was likely circulating undetected in the community in Brazil since November 2019, earlier than the first reported case in the Americas (21st January 2020).