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Chapter 37 : Food Microbiomes: A New Paradigm for Food and Food Ecology

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Abstract:

This chapter takes a brief look at the new frontier of microbiological food safety, nutrition, and immunology. With the use of metagenomic profiles of food and food ecologies, we can now better describe risk factors for contamination by human pathogens along the farm-to-fork continuum. We have also begun to organize data that may also improve our understanding of the more comprehensive prebiotic, probiotic, and antibiotic impact of food on the human microbiomes and how this may be relevant to nutrition, immunology, and chronic disease. We describe case studies with fresh produce such as tomatoes, sprouts, and leafy greens and highlight new approaches to pathogen detection using quasimetagenomics.

Citation: Ottesen A, Ramachandran P. 2019. Food Microbiomes: A New Paradigm for Food and Food Ecology, p 963-970. In Doyle M, Diez-Gonzalez F, Hill C (ed), Food Microbiology: Fundamentals and Frontiers, 5th Edition. ASM Press, Washington, DC. doi: 10.1128/9781555819972.ch37
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Figures

Image of Figure 37.1
Figure 37.1

Microbial food pyramid. This graphic is designed to highlight the fact that healthy diets must consider not only foods themselves, but also the microbial content of foods. Even if a food is completely devoid of microbes, the food matrix itself will interact with the human microbiome in some manner that will impact nutrition and health.

Citation: Ottesen A, Ramachandran P. 2019. Food Microbiomes: A New Paradigm for Food and Food Ecology, p 963-970. In Doyle M, Diez-Gonzalez F, Hill C (ed), Food Microbiology: Fundamentals and Frontiers, 5th Edition. ASM Press, Washington, DC. doi: 10.1128/9781555819972.ch37
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Image of Figure 37.2
Figure 37.2

Quasimetagenomic survey of the FDA, USDA, and ISO enrichments for the recovery of from ice cream. B, buffered enrichment broth (FDA BAM method); U, University of Vermont modified broth with Fraser broth (USDA method); H, half-Fraser broth with transfer to Fraser broth (ISO method). All methods performed equally well for recovery of . Exciting source tracking utility was documented as early as hours 20 and 28, when genomic data for could be used to subtype strains with the same precision as WGS methods, in half the time ( ). Adapted from reference .

Citation: Ottesen A, Ramachandran P. 2019. Food Microbiomes: A New Paradigm for Food and Food Ecology, p 963-970. In Doyle M, Diez-Gonzalez F, Hill C (ed), Food Microbiology: Fundamentals and Frontiers, 5th Edition. ASM Press, Washington, DC. doi: 10.1128/9781555819972.ch37
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Image of Figure 37.3
Figure 37.3

Using the NCBI data for the 2015 Blue Bell ice cream outbreak (abbreviated collection shown here) to assess the phylogenetic utility of a quasimetagenomic approach to source tracking, we show that single-nucleotide-polymorphism and MLST data from quasimetagenomic data of enrichments can be used to infer the same phylogenetic source attribution information that was achieved with WGS strains (data in purple are from hours 20, 36, and 40 of enrichments). This approach took half the time of traditional WGS and thus holds great promise as a method to reduce the time needed to source track pathogens from foods ( ). .

Citation: Ottesen A, Ramachandran P. 2019. Food Microbiomes: A New Paradigm for Food and Food Ecology, p 963-970. In Doyle M, Diez-Gonzalez F, Hill C (ed), Food Microbiology: Fundamentals and Frontiers, 5th Edition. ASM Press, Washington, DC. doi: 10.1128/9781555819972.ch37
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References

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