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Volume 133, Issue 5

SIMCA Pattern Recognition in the Analysis of Streptomycete Fatty Acids Free

Abstract

Biomass from representative strains of and related taxa was degraded using an alkaline methanolysis procedure. The resultant fatty acid methyl esters were analysed by gas chromatography and the quantitative data examined using the SIMCA statistical package. The strains were recovered in two major clusters. The larger of these contained sixteen strains which had been previously classified as in a numerical phenetic survey. The remaining strains formed a heterogeneous aggregate cluster together with representatives of other streptomycete species. A third cluster encompassed a number of blue-spored streptomycetes from soil. Disjoint principal components analysis in conjunction with cross-validation analyses demonstrated that the group and the blue-spored soil isolates could be represented by statistically stable principal component models. The fact that the initial, numerically circumscribed, taxon was only partially recovered by the numerical analysis of fatty acid data supports the view that this taxon contains strains which are not entirely typical of the cluster, despite their high degree of similarity with other members. These preliminary findings suggest that models based on fatty acid data could be used for identifying unknown streptomycetes to established taxa and for the definition of novel streptomycetes.

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© Society for General Microbiology 1987
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1987-05-01
2024-04-20
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SIMCA Pattern Recognition in the Analysis of Streptomycete Fatty Acids
Microbiology 133, 1137 (1987); https://doi.org/10.1099/00221287-133-5-1137
/content/journal/micro/10.1099/00221287-133-5-1137
/content/journal/micro/10.1099/00221287-133-5-1137
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