Identification of staphylococci with a self-educating system using fatty acid analysis and biochemical tests

Abstract

We characterized all of the 35 aerobic taxa of the genus Staphylococcus by using an objective, self-learning system combining both whole-cell fatty acid (FA) analysis and the results of 35 biochemical tests. Isolates were compared with the type strain for each taxon to generate an FA profile library and a biochemical table of test responses. Isolates were accepted into the system if they had a similarity index of > or = 0.6 for a taxon within the FA profile library and if they were identified as the same taxon by a computer program using a probability matrix constructed from the biochemical data. These stringent criteria led to acceptance of 1,117 strains assigned to legitimate taxa. Additional FA groups were assembled from selected strains that did not meet the inclusion criteria based on the type strains and were added to the system as separate entries. Currently, 1,512 isolates have bee accepted into the system. This approach has resulted in a comprehensive table of biochemical test results and a FA profile library, which together provide a practical system for valid identifications.