NUMERICAL CLASSIFICATION AND IDENTIFICATION OF ACINETOBACTER GENOMIC SPECIES

A total of 211 Acinetobacter strains (representing all currently recog nized genomic species) were tested for 329 biochemical characters. Ove rall similarities of all strains were determined for 145 characters by numerical taxonomic techniques, the UPGMA algorithm and the S(SM) and the S(J) coefficients as measures of similarity. Seven clusters (two or more strains) and three unclustered strains were recovered at a sim ilarity level of 80.0% (S(SM)). At this level a complete correspondenc e between phenotypic cluster and genomic species was found only for ge nomic species 12 (Ac. radioresistens). At higher similarity levels (84 .0% to 84-6% (S(SM))), however, several subclusters were found, each r epresenting a single genomic species. An exception were the strains be longing to the genetically closely related species of the Acinetobacte r calcoaceticus-baumannii complex. these were recovered scattered in s everal subclusters. The degree of genomic relatedness between some DNA groups correlated with phenotypic similarities, especially for DNA gr oup 8 (Ac. lwoffii) and 15 of Tjernberg and Ursing, and for DNA group 4 (Ac. haemolyticus) and 6. For the majority of genomic species, two i dentification matrices were constructed consisting of 22 and 10 diagno stic characters, respectively. The correct identification rates for th e matrices were 98.0% (22 tests) and 90.8% (10 tests) taking a Willcox probability > 0.9. For unambiguous identification of some genomic spe cies, however, additional methods (preferably DNA-DNA hybridization or ribotyping) should be used.