Chapter 7 : Rethinking Virus Detection in Food

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Well over 100 different enteric viruses are liable to be found as food contaminants; however, with few exceptions most well-characterized food-borne viral outbreaks are restricted to calicivirus, essentially norovirus (NoV) and hepatitis A virus (HAV), which in consequence are the main targets for virus detection in food. Nucleic acid amplification techniques are currently the most widely used methods for detection of viruses in food. Although nucleic acid sequence based amplification and loop-mediated isothermal amplification techniques have been reported to be highly sensitive and specific, respectively, reverse transcription-polymerase chain reaction (RT-PCR) remains the current “gold standard” for virus detection in food. A wide variety of foodstuffs may become contaminated by viruses during the farm-to-fork chain, during either the preharvest or postharvest stages. Among the foods at risk of preharvest contamination are bivalve shellfish, fresh produce, and water. Prospective virological analysis of food is envisaged to ensure the safety of the foodstuff before public consumption. A sensible prospective food safety approach is to identify and prevent hazards that could cause food-borne illnesses rather than relying on spot checks of the manufacturing processes and random sampling of finished products to ensure safety. The advent of standardized molecular techniques allowing the detection and quantification of viruses in foodstuffs is a major breakthrough in food safety.

Citation: Pintó R, Bosch A. 2008. Rethinking Virus Detection in Food, p 171-188. In Koopmans M, Cliver D, Bosch A, Doyle M (ed), Food-Borne Viruses. ASM Press, Washington, DC. doi: 10.1128/9781555815738.ch7
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Figure 1

Secondary structure of the 5′NCR RNA of HAV strain HM175. (Reprinted from reference with permission.)

Citation: Pintó R, Bosch A. 2008. Rethinking Virus Detection in Food, p 171-188. In Koopmans M, Cliver D, Bosch A, Doyle M (ed), Food-Borne Viruses. ASM Press, Washington, DC. doi: 10.1128/9781555815738.ch7
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Figure 2

Analysis of the variability of full-length NoV genomes of genogroup I (A) and genogroup II (B) strains. The locations of the ORFs are noted. Thick lines depict the most highly conserved regions. The average similarity score within each genogroup is represented as a dotted line. (Reprinted from reference with permission.)

Citation: Pintó R, Bosch A. 2008. Rethinking Virus Detection in Food, p 171-188. In Koopmans M, Cliver D, Bosch A, Doyle M (ed), Food-Borne Viruses. ASM Press, Washington, DC. doi: 10.1128/9781555815738.ch7
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Figure 3

Proposed standardized procedure for an accurate estimation of the number of viral genome copies in food. (Reprinted from reference with permission.)

Citation: Pintó R, Bosch A. 2008. Rethinking Virus Detection in Food, p 171-188. In Koopmans M, Cliver D, Bosch A, Doyle M (ed), Food-Borne Viruses. ASM Press, Washington, DC. doi: 10.1128/9781555815738.ch7
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Table 1

Examples of documented NoV and HAV food-borne outbreaks.

Citation: Pintó R, Bosch A. 2008. Rethinking Virus Detection in Food, p 171-188. In Koopmans M, Cliver D, Bosch A, Doyle M (ed), Food-Borne Viruses. ASM Press, Washington, DC. doi: 10.1128/9781555815738.ch7
Generic image for table
Table 2

QC measures for real-time RT-PCR-based analysis of food

Citation: Pintó R, Bosch A. 2008. Rethinking Virus Detection in Food, p 171-188. In Koopmans M, Cliver D, Bosch A, Doyle M (ed), Food-Borne Viruses. ASM Press, Washington, DC. doi: 10.1128/9781555815738.ch7

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