Subgrouping of Pseudomonas cepacia by cellular fatty acid composition

Abstract

The cellular fatty acid compositions were determined for 42 strains of Pseudomonas cepacia from five cystic fibrosis centers in North America. All isolates contained significant (20%) amounts of hexadecanoic (C16:0), and cis-9 hexadecenoic (Cl6:1 cis9) acids and an isomer of octadecenoic acid (Cl8,:). None had hydroxy acids containing fewer than 14 carbon atoms. The quantitative data from the fatty acid analysis were highly reproducible and provided a basis for numerical analysis. Five subgroups comprising all the strains were obtained by cluster analysis and further characterized by principal-component analysis. With minor exceptions, the predominant subgroup identified in each center was different from that identified in other centers and accounted for one-half of the isolates within each center. Cellular fatty acid composition is a useful adjunct to biochemical characterization for the identification of P. cepacia isolated from cystic fibrosis patients. Numerical analysis of the fatty acid data can separate P. cepacia into subgroups, which may provide useful epidemiologic information or a basis for further analysis by more complex techniques such as DNA probe analysis.

Grouping of some clinically relevant Gram‐positive rods by automated fatty acid analysis

“…Finally, principal component analysis (1 1) reflected the grouping and sequence of organisms provided in Tables 1 to 4. Reproducibility, checked on 24 randomly selected strains, resembled that observed by others (23).…”

Analysis of saturated free fatty acids from pollen by HPLC with fluorescence detection

“…Therefore, derivatization of these analytes with labeling reagents has been widely adopted, since HPLC with UV or fluorescence detection has a higher sensitivity. The easily detectable fatty acid derivatives after methyl esterification, with GC or GC/ MS, have been reported [2][3][4]. In contrast, with GC, use of HPLC allows the fatty acids to be converted to a large number of different derivatives.…”

Cellular fatty acid profiles for the differentiation of Penicillium species

“…To make visible some of the smaller di¡erences between the analyzed samples (samples may be in other directions and therefore not seen in the plot), a stepwise principal component computation was carried out on samples which are located close to- 1 The Principal Components Analysis is a classic tool used to analyze data matrices. In this study the data matrix is composed of 18 rows (fungi) and 16 columns (fatty acids).…”