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. 2021 Dec 23;10(1):17.
doi: 10.3390/microorganisms10010017.

Bacterial Complexity of Traditional Mountain Butter Is Affected by the Malga-Farm of Production

Affiliations

Bacterial Complexity of Traditional Mountain Butter Is Affected by the Malga-Farm of Production

Silvia Schiavon et al. Microorganisms. .

Abstract

Bacteria can play different roles affecting flavors and food characteristics. Few studies have described the bacterial microbiota of butter. In the present paper, next-generation sequencing was used to determine bacterial diversity, together with aromatic characteristics, in raw cow milk butter processed by traditional fermentation, in fourteen small farms called "Malga", located in the Trentino province (Alpine region, North-East of Italy). The physicochemical and aromatic characterization of traditional mountain butter (TMB) showed a low moisture level depending on the Malga producing the butter. Counts of lactic acid bacteria, Staphylococci, and coliforms, as well as diacetyl/acetoin concentrations exhibited changes according to the geographical origin of Malga and the residual humidity of butter. MiSeq Illumina data analysis revealed that the relative abundance of Lactococcus was higher in TMB samples with the highest values of acetoin (acetoin higher than 10 mg/kg). The traditional mountain butter bacterial community was characterized by a "core dominance" of psychrotrophic genera, mainly Acinetobacter and Pseudomonas, but according to ANCOM analysis, a complex bacterial population emerged and specific bacterial genera were able to characterize the TMB bacteria community, with their high abundance, based on the Malga producing the butter.

Keywords: Illumina MiSeq; Lactococcus; Malga; acetoin; bacterial counts; butter; raw milk.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Relative abundances (%) of the main taxa groups (genus level or above) of bacterial sequences from different TMB samples using Illumina MiSeq. Each bar is the mean value of 3 samples collected in different Mfarms located in the Trentino province (for the interpretation of the references to color in this figure legend, the reader is referred to the web version of this article).
Figure 2
Figure 2
Box plot of the relative abundances (%) of Acidobacteria, Chryseobacterium, other Bacteroidetes, Xanthomonadaceae, other Proteobacteria, and the concentration of diacetyl/acetoin measured in the TMB of the two valleys in Trentino (Val di Sole, n = 17; Valsugana n = 25). Significance level: * p ≤ 0.05 significant; ** p ≤ 0.01 very significant; *** p ≤ 0.001 highly significant.
Figure 3
Figure 3
Plots of loadings and scores for principal components 1 and 2 (PC1 and PC2) obtained by principal component analysis (PCA).
Figure 4
Figure 4
Partial least squares regression (PLSR) analysis results: VIP (variable importance in prediction) scores and correlation plots between actual and predicted values of (A) diacetyl and (B) acetoin. Note: MB: Methanobrevibacter; AB: Acidobacteria; MC: Micrococcaceae; OA: other Actinobacteria; CB: Chryseobacterium; CyB: Cyanobacteria; OB: other Bacteroidetes; SC: Staphylococcus; LN: Leuconostoc; LC: Lactococcus; StC: Streptococcus; OF: other Firmicutes; EB: Enterobacteriaceae; AcB: Acinetobacter; EnB: Enhydrobacter; PM: Pseudomonas; XM: Xanthomonadaceae; and OP: other Proteobacteria. Significance level: * p ≤ 0.05 significant.
Figure 5
Figure 5
Correlation plots between the actual and predicted values of (A) diacetyl and (B) acetoin with a polynomial function of the second order.

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