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Raw milk and fecal microbiota of commercial Alpine dairy cows varies with herd, fat content and diet.


ABSTRACT: The factors that influence the diversity and composition of raw milk and fecal microbiota in healthy commercial dairy herds are not fully understood, partially because the majority of metataxonomic studies involve experimental farms and/or single factors. We analyzed the raw milk and fecal microbiota of 100 healthy cows from 10 commercial alpine farms from the Province of Trento, Italy, using metataxonomics and applied statistical modelling to investigate which extrinsic and intrinsic parameters (e.g. herd, diet and milk characteristics) correlated with microbiota richness and composition in these relatively small traditional farms. We confirmed that Firmicutes, Ruminococcaceae and Lachnospiraceae families dominated the fecal and milk samples of these dairy cows, but in addition, we found an association between the number of observed OTUs and Shannon entropy on each farm that indicates higher microbiota richness is associated with increased microbiota stability. Modelling showed that herd was the most significant factor affecting the variation in both milk and fecal microbiota composition. Furthermore, the most important predictors explaining the variation of microbiota richness were milk characteristics (i.e. percentage fat) and diet for milk and fecal samples, respectively. We discuss how high intra-herd variation could affect the development of treatments based on microbiota manipulation.

SUBMITTER: Albonico F 

PROVIDER: S-EPMC7410245 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The factors that influence the diversity and composition of raw milk and fecal microbiota in healthy commercial dairy herds are not fully understood, partially because the majority of metataxonomic studies involve experimental farms and/or single factors. We analyzed the raw milk and fecal microbiota of 100 healthy cows from 10 commercial alpine farms from the Province of Trento, Italy, using metataxonomics and applied statistical modelling to investigate which extrinsic and intrinsic parameters  ...[more]

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