title: Numerical classification and identification of Aeromonas genospecies.
abstract: A total of 176 Aeromonas strains representing all currently characterized genospecies were tested for 329 biochemical characters. Overall similarities of all strains were determined by numerical taxonomic techniques, the UPGMA algorithm and the SSM and the SJ coefficients as measures of similarity. Sixteen clusters (two or more strains) and seven unclustered strains were recovered at the 93.5% similarity level (SSM). Genospecies 1, 4, 5, 6, 7, 9, 12 and 13 were largely represented by single phena, whereas strains of genospecies 2 and 3 were found in closely-related phena. Strains belonging to genospecies 8 formed two distinct biotypes. Strains belonging to genospecies 11 formed a subcluster within a cluster representing different genospecies. In general, similar groupings were obtained with the Jaccard coefficient at a similarity level of 80.0% (SJ) with minor changes in the definition of clusters. The phenetic data showed good correlation with the taxa defined by DNA/DNA hybridization and those obtained by multilocus enzyme analysis. For all genospecies (independent from cluster assignment) 30 diagnostic characters were selected to construct a matrix for probabilistic identification. The correct identification rate of the matrix was 71.51% taking a Willcox probability greater than 0.99, and 83.7% taking a Willcox probability greater than 0.9 as identification threshold levels.
authors.affiliation: Fachgebiet Hygiene, Technischen Universität Berlin, Germany.
authors.forename: P
authors.initials: P
authors.lastname: Kämpfer
authors.forename: M
authors.initials: M
authors.lastname: Altwegg
mesh_terms: D000333:Aeromonas / Q000145:classification* / Q000254:growth & development / Q000378:metabolism; D015373:Bacterial Typing Techniques; D011336:Probability