IDENTIFICATION OF STAPHYLOCOCCI WITH A SELF-EDUCATING SYSTEM USING FATTY-ACID ANALYSIS AND BIOCHEMICAL TESTS

We characterized all of the 35 aerobic taxa of the genus Staphylococcu s by using an objective, self-learning system combining both whole-cel l fatty acid (FA) analysis and the results of 35 biochemical tests. Is olates were compared with the type strain for each taxon to generate a n FA profile library and a biochemical table of test responses. Isolat es were accepted into the system if they had a similarity index of gre ater than or equal to 0.6 for a taxon within the FA profile library an d if they were identified as the same taxon by a computer program usin g a probability matrix constructed from the biochemical data. These st ringent criteria led to acceptance of 1,117 strains assigned to legiti mate taxa. Additional FA groups were assembled from selected strains t hat did not meet the inclusion criteria based on the type strains and were added to the system as separate entries. Currently, 1,512 isolate s have been accepted into the system. This approach has resulted in a comprehensive table of biochemical test results and an FA profile libr ary, which together provide a practical system for valid identificatio ns.