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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

Taxon abundance heatmaps depict family-level relative abundance of bacteria across sampling sites detected by marker-gene sequencing.The relative abundances of each genus (columns) within each sample (rows) are indicated by the color of the intersecting tile. Sample types are indicated by colored bars to the left of each row, classified according to the location within the brewery (Figure 1) or the type of substrate (grain, wort, hops, beer). Dendrograms represent Bray–Curtis dissimilarity between samples (vertical trees) and shared-niche similarity between taxa (horizontal trees), respectively indicating taxonomic composition similarities and taxon co-occurrence patterns. Only taxa ≥0.05 relative abundance in at least one sample are shown.DOI:http://dx.doi.org/10.7554/eLife.04634.005
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fig3: Taxon abundance heatmaps depict family-level relative abundance of bacteria across sampling sites detected by marker-gene sequencing.The relative abundances of each genus (columns) within each sample (rows) are indicated by the color of the intersecting tile. Sample types are indicated by colored bars to the left of each row, classified according to the location within the brewery (Figure 1) or the type of substrate (grain, wort, hops, beer). Dendrograms represent Bray–Curtis dissimilarity between samples (vertical trees) and shared-niche similarity between taxa (horizontal trees), respectively indicating taxonomic composition similarities and taxon co-occurrence patterns. Only taxa ≥0.05 relative abundance in at least one sample are shown.DOI:http://dx.doi.org/10.7554/eLife.04634.005

Mentions: Short-amplicon marker-gene sequencing was employed to survey the bacterial and fungal consortia inhabiting the entire brewery environment. A total of 501 samples were collected during three seasons, representing the main processing surfaces and equipment used throughout the brewing process (Figure 1). Beta-diversity (between sample) comparisons provide useful assessments of the taxonomic similarity between different sites. Bray–Curtis dissimilarity of complete microbial profiles reveals that many samples cluster by processing room and substrate type regardless of season (Figures 2–3). Thus, fermenter samples cluster, associated with Bacillaceae; cellar production areas, associated with Micrococcaceae (including the beer-spoiling genera Kocuria and Micrococcus); wort, malt, and hotside (wort-preparation) surfaces, associated with Enterobacteriaceae, Leuconostocaceae, Candida santamariae, Pichia, and Rhodotorula; barrel-room floor samples, associated with Staphylococcaceae and Carnobacteriaceae; and beer samples, associated with Lactobacillaceae and Enterobacteriaceae. Barrels cluster, associated with Aspergillus, Eurotium, and Penicillium; coolship and barrel-room samples with Cryptococcus and Cladosporium. These taxonomic trends each demonstrate significant site associations (Kruskal–Wallis Bonferroni-corrected p < 0.05). S. cerevisiae was common throughout the brewery, but especially in the fermentation cellar. LAB and acetic acid bacteria were found sporadically at different sites and times, including on and near packaging equipment and fermenters inoculated with LAB (Figure 3).10.7554/eLife.04634.003Figure 1.Brewery map and simplified brewing process diagrams.


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)

Taxon abundance heatmaps depict family-level relative abundance of bacteria across sampling sites detected by marker-gene sequencing.The relative abundances of each genus (columns) within each sample (rows) are indicated by the color of the intersecting tile. Sample types are indicated by colored bars to the left of each row, classified according to the location within the brewery (Figure 1) or the type of substrate (grain, wort, hops, beer). Dendrograms represent Bray–Curtis dissimilarity between samples (vertical trees) and shared-niche similarity between taxa (horizontal trees), respectively indicating taxonomic composition similarities and taxon co-occurrence patterns. Only taxa ≥0.05 relative abundance in at least one sample are shown.DOI:http://dx.doi.org/10.7554/eLife.04634.005
© Copyright Policy
Related In: Results  -  Collection

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

fig3: Taxon abundance heatmaps depict family-level relative abundance of bacteria across sampling sites detected by marker-gene sequencing.The relative abundances of each genus (columns) within each sample (rows) are indicated by the color of the intersecting tile. Sample types are indicated by colored bars to the left of each row, classified according to the location within the brewery (Figure 1) or the type of substrate (grain, wort, hops, beer). Dendrograms represent Bray–Curtis dissimilarity between samples (vertical trees) and shared-niche similarity between taxa (horizontal trees), respectively indicating taxonomic composition similarities and taxon co-occurrence patterns. Only taxa ≥0.05 relative abundance in at least one sample are shown.DOI:http://dx.doi.org/10.7554/eLife.04634.005
Mentions: Short-amplicon marker-gene sequencing was employed to survey the bacterial and fungal consortia inhabiting the entire brewery environment. A total of 501 samples were collected during three seasons, representing the main processing surfaces and equipment used throughout the brewing process (Figure 1). Beta-diversity (between sample) comparisons provide useful assessments of the taxonomic similarity between different sites. Bray–Curtis dissimilarity of complete microbial profiles reveals that many samples cluster by processing room and substrate type regardless of season (Figures 2–3). Thus, fermenter samples cluster, associated with Bacillaceae; cellar production areas, associated with Micrococcaceae (including the beer-spoiling genera Kocuria and Micrococcus); wort, malt, and hotside (wort-preparation) surfaces, associated with Enterobacteriaceae, Leuconostocaceae, Candida santamariae, Pichia, and Rhodotorula; barrel-room floor samples, associated with Staphylococcaceae and Carnobacteriaceae; and beer samples, associated with Lactobacillaceae and Enterobacteriaceae. Barrels cluster, associated with Aspergillus, Eurotium, and Penicillium; coolship and barrel-room samples with Cryptococcus and Cladosporium. These taxonomic trends each demonstrate significant site associations (Kruskal–Wallis Bonferroni-corrected p < 0.05). S. cerevisiae was common throughout the brewery, but especially in the fermentation cellar. LAB and acetic acid bacteria were found sporadically at different sites and times, including on and near packaging equipment and fermenters inoculated with LAB (Figure 3).10.7554/eLife.04634.003Figure 1.Brewery map and simplified brewing process diagrams.

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