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Appl Environ Microbiol. 2007 Mar;73(6):1882-91. Epub 2007 Jan 26.

Monitoring bacterial communities in raw milk and cheese by culture-dependent and -independent 16S rRNA gene-based analyses.

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INRA, Unité de Recherches Fromagères, 36 rue de Salers, F-15000 Aurillac, France.


The diversity and dynamics of bacterial populations in Saint-Nectaire, a raw-milk, semihard cheese, were investigated using a dual culture-dependent and direct molecular approach combining single-strand conformation polymorphism (SSCP) fingerprinting and sequencing of 16S rRNA genes. The dominant clones, among 125 16S rRNA genes isolated from milk, belonged to members of the Firmicutes (58% of the total clones) affiliated mainly with the orders Clostridiales and the Lactobacillales, followed by the phyla Proteobacteria (21.6%), Actinobacteria (16.8%), and Bacteroidetes (4%). Sequencing the 16S rRNA genes of 126 milk isolates collected from four culture media revealed the presence of 36 different species showing a wider diversity in the Gammaproteobacteria phylum and Staphylococcus genus than that found among clones. In cheese, a total of 21 species were obtained from 170 isolates, with dominant species belonging to the Lactobacillales and subdominant species affiliated with the Actinobacteria, Bacteroidetes (Chryseobacterium sp.), or Gammaproteobacteria (Stenotrophomonas sp.). Fingerprinting DNA isolated from milk by SSCP analysis yielded complex patterns, whereas analyzing DNA isolated from cheese resulted in patterns composed of a single peak which corresponded to that of lactic acid bacteria. SSCP fingerprinting of mixtures of all colonies harvested from plate count agar supplemented with crystal violet and vancomycin showed good potential for monitoring the subdominant Proteobacteria and Bacteroidetes (Flavobacteria) organisms in milk and cheese. Likewise, analyzing culturable subcommunities from cheese-ripening bacterial medium permitted assessment of the diversity of halotolerant Actinobacteria and Staphylococcus organisms. Direct and culture-dependent approaches produced complementary information, thus generating a more accurate view of milk and cheese microbial ecology.

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