Numerical phenetic classification of clinically significant aerobic sporoactinomycetes and related organisms

Antonie Van Leeuwenhoek. 2003;84(1):39-68. doi: 10.1023/a:1024401004258.

Abstract

Clinically significant aerobic sporoactinomycetes, notably agents of mycetoma, were examined for a balanced set of unit characters and the resultant data analysed using standard numerical taxonomic procedures. All save two of the one hundred and seventy three tested strains were assigned to three multimembered cluster-groups, which encompassed sixteen major (4-7 strains), ten minor (2-3 strains) and forty single membered clusters, in an analysis based on the simple matching coefficient and unweighted pair group method with arithmetic averages algorithm. The three cluster-groups were equated with the genus Actinomadura (including Actinocorallia and Streptomyces somaliensis strains), and the genera Nocardiopsis and Streptomyces, and Thermobifida and Thermomonospora, respectively. In a corresponding principal co-ordinates analysis four multimembered groups corresponding to the genera Actinomadura, Nocardiopsis, Streptomyces, and Thermobifida and Thermomonospora were recognised. The causal agents of actinomycetoma were not only assigned to established taxa, notably, to Actinomadura latina, Actinomadura madurae, Actinomadura pelletieri and Streptomyces somaliensis, but also to additional centres of taxonomic variation which were equated with the rank of species. Most of the streptomycetes isolated from clinical material were assigned to clusters equated with the species Streptomyces albus and Streptomyces anulatus. The numerical taxonomic data were used to generate a frequency matrix designed to facilitate the identification of clinically significant Actinomadura, Nocardiopsis and Streptomyces strains to the species level; rapid enzyme tests accounted for eleven out of the twenty-one diagnostic tests.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Actinomycetales / classification*
  • Actinomycetales / physiology
  • Actinomycetales Infections / diagnosis
  • Cluster Analysis
  • Data Interpretation, Statistical
  • Humans
  • Phenotype
  • Phylogeny*