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Human noroviruses (HuNoV) are the leading cause of food borne disease in the U.S. Despite the fact that detection of HuNoV can be accomplished using molecular methods such as reverse transcription quantitative PCR (RT-qPCR), detection of contamination in food and environmental samples remains limited because of barriers such as large sample volumes in relation to small assay volume, low levels of contamination, and the presence of residual matrix components that inhibit molecular detection. For this reason, virus concentration and purification steps must be applied to samples prior to downstream detection. An additional concern is the inability of molecular amplification to discriminate infectious from non-infectious viruses. <P>The purpose of this project is to develop a sensitive, simple and relatively universal prototype method to detect infectious HuNoV from representative food and environmental samples. The approach capitalizes on recent findings that HuNoV bind to genetically determined host susceptibility factors associated with the histoblood group antigens (HBGA) and that HBGAs can be used as capture ligands in support of detection efforts. Other recent developments that inform the work include the introduction of recirculating magnetic capture units that facilitate large volume sample processing, and novel methods that can be used in conjunction with RT-qPCR to aid in discrimination of virus infectivity status. <P>Four major objectives are identified: (1) Investigate the efficacy of HBGA-bound magnetic beads for the capture of HuNoV; (2) Compare molecular-based approaches to discriminate infectious from non-infectious HuNoV; (3) Develop a prototype method for detection of infectious HuNoV in realistic samples sizes (>25 g); and (4) Validate the prototype method(s) using food and environmental samples artificially contaminated with representative virus strains. <P>Several different HuNoV strains, along with the cultivable surrogate murine norovirus (MNV-1), will be evaluated; molecular amplification and mammalian cell culture (when appropriate) will be used for virus quantification. The general methodological approach will involve initial evaluation of the efficacy of HBGA capture methods, alone or in combination, as applied to purified virus stock solutions. Similar studies will be done to identify the best method(s) to discriminate virus infectivity. <P>Optimal methods will then be applied to candidate food and environmental sample matrices and refined as appropriate, before being validated in spike and recovery experiments seeded with HuNoV at the low concentrations anticipated for naturally contaminated samples. Successful completion this project will result in improved methods to detect HuNoV across the farm-to-fork chain. <P>These methods can be used in (i) the epidemiological investigation of food borne viral disease outbreaks; (ii) for the tracking of HuNoV contamination and transmission; and (iii) to evaluate the efficacy of proposed mitigation strategies. The long term outcome will be improvements to the safety of the nation's food supply as evidenced by reduction in the burden of disease associated with HuNoV.
Non-Technical Summary: Human noroviruses (HuNoV) are a significant cause of food borne disease in the U.S., responsible for over 50% of outbreaks of confirmed etiology reported to the CDC in 2006. These and other viruses are also likely to be responsible for a large proportion of food borne disease of unknown etiology. Although HuNoV cause what is usually considered a short-lived gastrointestinal disease, severe disease has been documented in some individuals. Only a few infectious particles are necessary to cause illness and these viruses are considered highly transmissible. The development of methods to detect HuNoV has lagged behind similar efforts for bacterial food borne pathogens. Even though HuNoV can now be detected using molecular methods such as reverse transcription quantitative PCR (RT-qPCR), foods and environmental samples remain challenging because (i) these viruses cannot be cultured outside of humans; (ii) they are likely to be present in very low numbers or intermittently in contaminated food and environmental samples; and (ii) these sorts of samples can be inhibitory of molecular-based detection. Therefore, virus concentration and purification steps must be applied before detection but these tend to be cumbersome and vary by sample matrix. A further complication is the inability of molecular methods to tell us whether viruses are infectious (can actually cause disease) or are simply inactivated. The lack of detection methods means that it is very difficult to understand the true significance of viral food borne disease or to test whether candidate control methods actually work to reduce or eliminate contamination and hence disease risk. The purpose of this work is to develop better ways to detect infectious HuNoV from representative food and environmental samples. Using a panel of viruses and advanced molecular and mammalian cell culture methods, the project will seek to come up with ways to (i) efficiently recover these viruses from various sample types; (ii) assure that they can be reliably detected even when only a few viruses are present in the sample; and (iii) assure that what is being detected actually presents a disease risk. The availability of these improved detection methods will allow us to track HuNoV contamination and transmission along the food chain and to develop scientifically valid control methods to prevent contamination. The long term outcome will be improvements to the safety of the U.S. food supply as evidenced by reduction in food borne disease caused by HuNoV. <P> Approach: In this project, we will use candidate genogroup I and II HuNoV strains obtained from outbreaks and human challenge studies, as well as the cultivable surrogate murine norovirus (MNV-1). The former will be detected/enumerated using broadly reactive RT-qPCR primers and probes; the latter by both RT-qPCR and infectivity assay using RAW 264.7 cells. The first two objectives focus on identification of the best approaches to capture-concentrate HuNoV and monitor their infectivity; these will be applied to pure virus suspensions. Four different ligand-magnetic bead complexes will be evaluated, i.e., magnetic beads conjugated to (i) synthetic histo-blood group antigen (HBGA) oligosaccharides; (ii) porcine gastric mucin; (iii) antibodies against HBGAs; and (iv) genogroup-specific HuNoV antibodies. In Objective 1 experiments, we will identify which combinations of magnetic bead-bound ligands result in high capture efficiency (>75%) with broad applicability to multiple HuNoV strains. In Objective 2, we will compare four methods for discriminating virus infectivity: three estimating capsid integrity (pre-treatment with DNA intercalating agents, proteinase-RNase digestion, and ligand/antibody capture) and one method to evaluate genome integrity (whole genome amplification). These approaches will be applied to representative HuNoV strains and MNV-1 exposed to a panel of physical and/or chemical insults having different mechanisms of virus inactivation. Capitalizing on the results of Objectives 1 and 2, the latter two objectives focus on developing a prototype method for detection of infectious HuNoV in realistic sample sizes (>25 g). These methods will be developed for one representative product from each of three different food matrices [i.e., oyster diverticula, strawberry, and deli-sliced turkey] and one environmental sample matrix (stainless steel surface swabs). Products/surfaces will be artificially contaminated with HuNoV or MNV-1 at relatively high concentrations with subsequent virus elution. Given that fact that food-derived eluates are likely to need pre-treatment prior to virus capture, this will be accomplished using combinations of enzymes (pectinase and/or proteinase) and solvent extraction. After pre-treatment, the samples are processed for virus concentration using ligand-bound bead suspensions in a recirculating magnetic capture unit. Modification of methods to improve virus recoveries will be made as necessary. In the final objective, the performance of the prototype methods will be evaluated using sample matrices seeded with HuNoV at the low concentrations anticipated for naturally contaminated samples. Homologous internal amplification controls will be included in RT-qPCR assays as amplification inhibition controls; MNV-1 will be used as a process control. Method performance measures will include assay sensitivity, specificity and LOD50 (i.e., virus load per sample in which 50% of tests are positive). Assays will also be evaluated for inclusivity (sensitivity) and exclusivity (specificity) using a diverse HuNoV panel and other non-HuNoV enteric viruses.