title: Bifidobacteria identification based on 16S rRNA and pyruvate kinase partial gene sequence analysis.
abstract: The lack of a simple and rapid identification system for Bifidobacterium species makes them difficult to use in industrial applications. To obtain valuable discriminating factor, we studied different strains, and human isolates by two molecular taxonomy methods. First method was based on chrono-differentiation. A metabolic gene (pyruvate kinase) was chosen to be used as a systematic discriminating factor. A comparison of about 40 pyruvate kinase protein sequences allowed us to synthesize two oligonucleotides that were able to amplify a fragment of this corresponding gene in our strains. Based on these partial pyruvate kinase gene sequences, several clusters could be identified. The second method used in this study was based on 16S rRNA sequences analysis. We compared sequences present in GenBank database, and this allowed to separate bifidobacteria species into different clusters. They were different from those obtained with partial pyruvate kinase gene sequences analysis. So, by combining both methods, we were able to identify our isolates, when only 10% of them could be strictly identified using the 16S rRNA method. Moreover, pyruvate kinase analysis allowed to differentiate very ambivalent groups such as B. animalis/B. lactis or B. infantis/B. longum, but created different clusters for B. infantis species group, questioning on the homogeneity of this species.
authors.affiliation: Laboratoire de Bactériologie, Virologie et Microbiologie Industrielle, Faculté de Pharmacie, 31062 Toulouse cedex 4, France.
authors.forename: Laurence
authors.initials: L
authors.lastname: Vaugien
authors.forename: Fabien
authors.initials: F
authors.lastname: Prevots
authors.forename: Christine
authors.initials: C
authors.lastname: Roques