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Mapping microbial ecosystems and spoilage-gene flow in breweries highlights patterns of contamination and resistance.

Bokulich NA, Bergsveinson J, Ziola B, Mills DA - Elife (2015)

Bottom Line: Physically mapping microbial populations over time illustrates patterns of dispersal and identifies potential contaminant reservoirs within this environment.Habitual exposure to beer is associated with increased abundance of spoilage genes, predicting greater contamination risk.Elucidating the genetic landscapes of indoor environments poses important practical implications for food-production systems and these concepts are translatable to other built environments.

View Article: PubMed Central - PubMed

Affiliation: Department of Food Science and Technology, University of California, Davis, Davis, United States.

ABSTRACT
Distinct microbial ecosystems have evolved to meet the challenges of indoor environments, shaping the microbial communities that interact most with modern human activities. Microbial transmission in food-processing facilities has an enormous impact on the qualities and healthfulness of foods, beneficially or detrimentally interacting with food products. To explore modes of microbial transmission and spoilage-gene frequency in a commercial food-production scenario, we profiled hop-resistance gene frequencies and bacterial and fungal communities in a brewery. We employed a Bayesian approach for predicting routes of contamination, revealing critical control points for microbial management. Physically mapping microbial populations over time illustrates patterns of dispersal and identifies potential contaminant reservoirs within this environment. Habitual exposure to beer is associated with increased abundance of spoilage genes, predicting greater contamination risk. Elucidating the genetic landscapes of indoor environments poses important practical implications for food-production systems and these concepts are translatable to other built environments.

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Related in: MedlinePlus

Spatial distribution heatmaps of bacteria in brewery environments across seasons (part 2).Plots indicate relative abundance of bacterial taxa detected by 16S rRNA gene sequence reads across brewery surfaces at different times: Autumn (left), Spring (center), and Summer (right). Scales on right represent relative abundance scale (maximum 1.0) for each row of plots. See Figure 1 for a floorplan key and description of surfaces. Note that the floorplans change between seasons as some samples were only collected as specific timepoints and the wild brewing facility was built and opened during the Spring sampling time.DOI:http://dx.doi.org/10.7554/eLife.04634.009
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fig7: Spatial distribution heatmaps of bacteria in brewery environments across seasons (part 2).Plots indicate relative abundance of bacterial taxa detected by 16S rRNA gene sequence reads across brewery surfaces at different times: Autumn (left), Spring (center), and Summer (right). Scales on right represent relative abundance scale (maximum 1.0) for each row of plots. See Figure 1 for a floorplan key and description of surfaces. Note that the floorplans change between seasons as some samples were only collected as specific timepoints and the wild brewing facility was built and opened during the Spring sampling time.DOI:http://dx.doi.org/10.7554/eLife.04634.009

Mentions: The spoilage genes horA, horB, and horC all display high degrees of intercorrelation (Pearson's r = 0.83–1.0, p < 0.01) and significant but lesser correlation to hitA (r = 0.48–0.64, p ≤ 0.04). All spoilage genes except for hitA demonstrate significant correlation with bulk detection of Lactobacillales via 16S rRNA gene sequencing (r = 0.53–0.74, p ≤ 0.03), while bulk Lactobacillales and all spoilage genes but horA correlate significantly with L. lindneri detection via LAB-TRFLP (r = 0.48–0.77, p ≤ 0.04). The only gene correlated with Pediococcus abundance via LAB-TRFLP was horA (r = 0.57, p = 0.01), consistent with previous observations that horA is the primary known hop-resistance gene observed in Pediococcus spp. (Haakensen and Ziola, 2008). Interestingly, no resistance genes correlated with L. brevis, strains of which are among the most common brewery contaminants and most commonly positive for hop-resistance genes (Haakensen and Ziola, 2008). This likely reflects the strains detected in this brewery only, and L. brevis was only a minor constituent of sour beers and processing surfaces (Figure 7).


Mapping microbial ecosystems and spoilage-gene flow in breweries highlights patterns of contamination and resistance.

Bokulich NA, Bergsveinson J, Ziola B, Mills DA - Elife (2015)

Spatial distribution heatmaps of bacteria in brewery environments across seasons (part 2).Plots indicate relative abundance of bacterial taxa detected by 16S rRNA gene sequence reads across brewery surfaces at different times: Autumn (left), Spring (center), and Summer (right). Scales on right represent relative abundance scale (maximum 1.0) for each row of plots. See Figure 1 for a floorplan key and description of surfaces. Note that the floorplans change between seasons as some samples were only collected as specific timepoints and the wild brewing facility was built and opened during the Spring sampling time.DOI:http://dx.doi.org/10.7554/eLife.04634.009
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4352708&req=5

fig7: Spatial distribution heatmaps of bacteria in brewery environments across seasons (part 2).Plots indicate relative abundance of bacterial taxa detected by 16S rRNA gene sequence reads across brewery surfaces at different times: Autumn (left), Spring (center), and Summer (right). Scales on right represent relative abundance scale (maximum 1.0) for each row of plots. See Figure 1 for a floorplan key and description of surfaces. Note that the floorplans change between seasons as some samples were only collected as specific timepoints and the wild brewing facility was built and opened during the Spring sampling time.DOI:http://dx.doi.org/10.7554/eLife.04634.009
Mentions: The spoilage genes horA, horB, and horC all display high degrees of intercorrelation (Pearson's r = 0.83–1.0, p < 0.01) and significant but lesser correlation to hitA (r = 0.48–0.64, p ≤ 0.04). All spoilage genes except for hitA demonstrate significant correlation with bulk detection of Lactobacillales via 16S rRNA gene sequencing (r = 0.53–0.74, p ≤ 0.03), while bulk Lactobacillales and all spoilage genes but horA correlate significantly with L. lindneri detection via LAB-TRFLP (r = 0.48–0.77, p ≤ 0.04). The only gene correlated with Pediococcus abundance via LAB-TRFLP was horA (r = 0.57, p = 0.01), consistent with previous observations that horA is the primary known hop-resistance gene observed in Pediococcus spp. (Haakensen and Ziola, 2008). Interestingly, no resistance genes correlated with L. brevis, strains of which are among the most common brewery contaminants and most commonly positive for hop-resistance genes (Haakensen and Ziola, 2008). This likely reflects the strains detected in this brewery only, and L. brevis was only a minor constituent of sour beers and processing surfaces (Figure 7).

Bottom Line: Physically mapping microbial populations over time illustrates patterns of dispersal and identifies potential contaminant reservoirs within this environment.Habitual exposure to beer is associated with increased abundance of spoilage genes, predicting greater contamination risk.Elucidating the genetic landscapes of indoor environments poses important practical implications for food-production systems and these concepts are translatable to other built environments.

View Article: PubMed Central - PubMed

Affiliation: Department of Food Science and Technology, University of California, Davis, Davis, United States.

ABSTRACT
Distinct microbial ecosystems have evolved to meet the challenges of indoor environments, shaping the microbial communities that interact most with modern human activities. Microbial transmission in food-processing facilities has an enormous impact on the qualities and healthfulness of foods, beneficially or detrimentally interacting with food products. To explore modes of microbial transmission and spoilage-gene frequency in a commercial food-production scenario, we profiled hop-resistance gene frequencies and bacterial and fungal communities in a brewery. We employed a Bayesian approach for predicting routes of contamination, revealing critical control points for microbial management. Physically mapping microbial populations over time illustrates patterns of dispersal and identifies potential contaminant reservoirs within this environment. Habitual exposure to beer is associated with increased abundance of spoilage genes, predicting greater contamination risk. Elucidating the genetic landscapes of indoor environments poses important practical implications for food-production systems and these concepts are translatable to other built environments.

Show MeSH
Related in: MedlinePlus