Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5542451 | Journal of Dairy Science | 2017 | 8 Pages |
Abstract
Bacteriological examination of milk samples is a prerequisite for pathogen-specific therapy and aids in limiting antimicrobial resistance. The aims of this study were to establish a standardized scheme for reliable Streptococcus uberis identification in routine diagnosis and to evaluate the accuracy of conventional tests and growing patterns of Strep. uberis on a selective medium (modified Rambach agar medium, MRAM) using 16S rRNA gene sequencing analysis as a reference method. We obtained isolates of presumptive Strep. uberis (n = 336) from quarter milk samples of dairy cows with intramammary infections and classified the isolates into 2 clusters using biochemical characterization. In cluster 1 (n = 280), cocci grew as non-hemolytic colonies, hydrolyzing esculin, carrying no Lancefield antigen (A/B/C/D/G) or Christie Atkins Munch-Petersen factor, and their growth was inhibited on an Enterococcus agar. Production of β-d-galactosidase on MRAM was shown by 257 of the cluster 1 isolates (91.79%), and 16S rRNA gene sequencing verified 271 (96.79%) of the isolates to be Strep. uberis. In 264 isolates (94.29%), MRAM agreed with the sequencing results. In cluster 2 (n = 56), isolates showed different characteristics: 37 (66.07%) were β-d-galactosidase-positive, and based on 16S sequencing results, 36 (64.29%) were identified correctly as Strep. uberis using biochemical methods. Identification success in this group differed significantly between routine diagnosis and MRAM application: MRAM agreed with sequencing results in 47 isolates (83.93%). To identify Strep. uberis and differentiate it from other lactic acid bacteria in routine diagnosis, we suggest using catalase reaction, hemolysis, esculin hydrolysis, and growth on enterococci agar. Isolates that show a typical biochemical profile can be identified satisfactorily with these tests. For Strep. uberis isolates with divergent patterns, application of MRAM as a follow-up test increased the diagnostic accuracy to 94.64%.
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Authors
Regina Wald, Martina Baumgartner, Verena Urbantke, Beatrix Stessl, Thomas Wittek,