alexa Use of biochemical kinetic data to determine strain relatedness among Salmonella enterica subsp. enterica isolates.


Clinical Microbiology: Open Access

Author(s): de la Torre E, Tello M, Mateu EM, Torre E

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Abstract Classical biotyping characterizes strains by creating biotype profiles that consider only positive and negative results for a predefined set of biochemical tests. This method allows Salmonella subspecies to be distinguished but does not allow serotypes and phage types to be distinguished. The objective of this study was to determine the relatedness of isolates belonging to distinct Salmonella enterica subsp. enterica serotypes by using a refined biotyping process that considers the kinetics at which biochemical reactions take place. Using a Vitek GNI+ card for the identification of gram-negative organisms, we determined the biochemical kinetic reactions (28 biochemical tests) of 135 Salmonella enterica subsp. enterica strains of pig origin collected in Spain from 1997 to 2002 (59 Salmonella serotype Typhimurium strains, 25 Salmonella serotype Typhimurium monophasic variant strains, 25 Salmonella serotype Anatum strains, 12 Salmonella serotype Tilburg strains, 7 Salmonella serotype Virchow strains, 6 Salmonella serotype Choleraesuis strains, and 1 Salmonella enterica serotype 4,5,12:-:- strain). The results were expressed as the colorimetric and turbidimetric changes (in percent) and were used to enhance the classical biotype profile by adding kinetic categories. A hierarchical cluster analysis was performed by using the enhanced profiles and resulted in 14 clusters. Six major clusters grouped 94\% of all isolates with a similarity of > or =95\% within any given cluster, and eight clusters contained a single isolate. The six major clusters grouped not only serotypes of the same type but also phenotypic serotype variations into individual clusters. This suggests that metabolic kinetic reaction data from the biochemical tests commonly used for classic Salmonella enterica subsp. enterica biotyping can possibly be used to determine the relatedness between isolates in an easy and timely manner.
This article was published in J Clin Microbiol and referenced in Clinical Microbiology: Open Access

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