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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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Hop-resistance gene frequency on brewery surfaces and beers.(A) ddPCR detection of hitA, horA, horB, and horC on surfaces (detected as copies/cm2) and in beers (copies/ml). Bar height indicates cumulative log gene abundance; colors indicate relative gene frequencies superimposed on these bars. Two barrel bung (stopper) samples are depicted on the left, one has no detection. (B) Pearson product-moment correlation matrix between hop-resistance genes, Lactobacillales relative abundance by 16S rRNA gene sequencing, and relative abundance of the dominant lactic acid bacteria detected by LAB-TRFLP. The color and shape of correlation ellipses (lower-left) indicate Pearson's product-moment correlation coefficient (r) between intersecting variables, as depicted in the key to the right. Correlations with larger positive r values are depicted as darker blue with increasingly narrow, upward-pointing ellipses. Correlations with larger negative r values are depicted as darker red with increasingly narrow, downward-pointing ellipses. Weaker correlations are depicted as wider, lighter colored ellipses. The corresponding p values for all correlation tests are provided in the reflected intersection (top-right).DOI:http://dx.doi.org/10.7554/eLife.04634.011
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fig9: Hop-resistance gene frequency on brewery surfaces and beers.(A) ddPCR detection of hitA, horA, horB, and horC on surfaces (detected as copies/cm2) and in beers (copies/ml). Bar height indicates cumulative log gene abundance; colors indicate relative gene frequencies superimposed on these bars. Two barrel bung (stopper) samples are depicted on the left, one has no detection. (B) Pearson product-moment correlation matrix between hop-resistance genes, Lactobacillales relative abundance by 16S rRNA gene sequencing, and relative abundance of the dominant lactic acid bacteria detected by LAB-TRFLP. The color and shape of correlation ellipses (lower-left) indicate Pearson's product-moment correlation coefficient (r) between intersecting variables, as depicted in the key to the right. Correlations with larger positive r values are depicted as darker blue with increasingly narrow, upward-pointing ellipses. Correlations with larger negative r values are depicted as darker red with increasingly narrow, downward-pointing ellipses. Weaker correlations are depicted as wider, lighter colored ellipses. The corresponding p values for all correlation tests are provided in the reflected intersection (top-right).DOI:http://dx.doi.org/10.7554/eLife.04634.011

Mentions: Results demonstrate high gene frequencies on several surfaces within the brewery (Figure 9). Sour beer samples contained the highest counts, between 2.0 × 104–4.8 × 104 copies/µl of horC, but fermenter and packaging area surfaces (filler heads, below bottling line belt, and packaging sink) also registered between 2.8–7.8 × 102 copies/cm2. None of these alleles were detected on hop samples, keg samples, or one barrel bung (stopper) sample, though 1.1 × 103 total copies/cm2 were detected on a keg faucet used for attaching kegs to beer lines at the brewery. Among the genes analyzed, horC was the most abundant (Figure 9), which is interesting when considered in the context of previous work showing that presence of this gene correlates with increased hop-tolerance and beer-spoilage ability (Fujii et al., 2005; Iijima et al., 2006; Bergsveinson et al., 2012) and the plasmid carrying horC is the most important for supporting growth of Lactobacillus brevis in beer (Bergsveinson et al., 2015). The preferential expression of this gene observed in these previous studies and the relative increased abundance with which it was found in this study suggests horC is an important gene for facilitating beer-spoilage and is consequently selected for in the brewery environment, particularly in areas where sour beers are produced. The purported transcriptional regulator of horC, horB, was detected at stable ratios relative to horC in all samples, supporting this putative function (Iijima et al., 2006). The least frequently observed hop-resistance gene, hitA, is involved in manganese transport (Hayashi et al., 2001), supporting resistance against manganese depletion by iso-a-acids (Behr and Vogel, 2010). Other studies have observed similarly low frequencies of hitA presence and expression in LAB relative to the other hop-resistance genes (Haakensen and Ziola, 2008; Bergsveinson et al., 2012).10.7554/eLife.04634.011Figure 9.Hop-resistance gene frequency on brewery surfaces and beers.


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)

Hop-resistance gene frequency on brewery surfaces and beers.(A) ddPCR detection of hitA, horA, horB, and horC on surfaces (detected as copies/cm2) and in beers (copies/ml). Bar height indicates cumulative log gene abundance; colors indicate relative gene frequencies superimposed on these bars. Two barrel bung (stopper) samples are depicted on the left, one has no detection. (B) Pearson product-moment correlation matrix between hop-resistance genes, Lactobacillales relative abundance by 16S rRNA gene sequencing, and relative abundance of the dominant lactic acid bacteria detected by LAB-TRFLP. The color and shape of correlation ellipses (lower-left) indicate Pearson's product-moment correlation coefficient (r) between intersecting variables, as depicted in the key to the right. Correlations with larger positive r values are depicted as darker blue with increasingly narrow, upward-pointing ellipses. Correlations with larger negative r values are depicted as darker red with increasingly narrow, downward-pointing ellipses. Weaker correlations are depicted as wider, lighter colored ellipses. The corresponding p values for all correlation tests are provided in the reflected intersection (top-right).DOI:http://dx.doi.org/10.7554/eLife.04634.011
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fig9: Hop-resistance gene frequency on brewery surfaces and beers.(A) ddPCR detection of hitA, horA, horB, and horC on surfaces (detected as copies/cm2) and in beers (copies/ml). Bar height indicates cumulative log gene abundance; colors indicate relative gene frequencies superimposed on these bars. Two barrel bung (stopper) samples are depicted on the left, one has no detection. (B) Pearson product-moment correlation matrix between hop-resistance genes, Lactobacillales relative abundance by 16S rRNA gene sequencing, and relative abundance of the dominant lactic acid bacteria detected by LAB-TRFLP. The color and shape of correlation ellipses (lower-left) indicate Pearson's product-moment correlation coefficient (r) between intersecting variables, as depicted in the key to the right. Correlations with larger positive r values are depicted as darker blue with increasingly narrow, upward-pointing ellipses. Correlations with larger negative r values are depicted as darker red with increasingly narrow, downward-pointing ellipses. Weaker correlations are depicted as wider, lighter colored ellipses. The corresponding p values for all correlation tests are provided in the reflected intersection (top-right).DOI:http://dx.doi.org/10.7554/eLife.04634.011
Mentions: Results demonstrate high gene frequencies on several surfaces within the brewery (Figure 9). Sour beer samples contained the highest counts, between 2.0 × 104–4.8 × 104 copies/µl of horC, but fermenter and packaging area surfaces (filler heads, below bottling line belt, and packaging sink) also registered between 2.8–7.8 × 102 copies/cm2. None of these alleles were detected on hop samples, keg samples, or one barrel bung (stopper) sample, though 1.1 × 103 total copies/cm2 were detected on a keg faucet used for attaching kegs to beer lines at the brewery. Among the genes analyzed, horC was the most abundant (Figure 9), which is interesting when considered in the context of previous work showing that presence of this gene correlates with increased hop-tolerance and beer-spoilage ability (Fujii et al., 2005; Iijima et al., 2006; Bergsveinson et al., 2012) and the plasmid carrying horC is the most important for supporting growth of Lactobacillus brevis in beer (Bergsveinson et al., 2015). The preferential expression of this gene observed in these previous studies and the relative increased abundance with which it was found in this study suggests horC is an important gene for facilitating beer-spoilage and is consequently selected for in the brewery environment, particularly in areas where sour beers are produced. The purported transcriptional regulator of horC, horB, was detected at stable ratios relative to horC in all samples, supporting this putative function (Iijima et al., 2006). The least frequently observed hop-resistance gene, hitA, is involved in manganese transport (Hayashi et al., 2001), supporting resistance against manganese depletion by iso-a-acids (Behr and Vogel, 2010). Other studies have observed similarly low frequencies of hitA presence and expression in LAB relative to the other hop-resistance genes (Haakensen and Ziola, 2008; Bergsveinson et al., 2012).10.7554/eLife.04634.011Figure 9.Hop-resistance gene frequency on brewery surfaces and beers.

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