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PMID: 3183021 Published · ppublish English Comparative Study Journal Article

Optimal data processing procedure for automatic bacterial identification by gas-liquid chromatography of cellular fatty acids.

Journal of clinical microbiology ·Vol. 26 ·No. 9 ·1988-09-00 ·Pages 1745-53

Eerola E, Lehtonen OP

Abstract

Gas-liquid chromatography of cellular fatty acids was used in automatic identification of clinical bacterial isolates. The intraspecies variation in the occurrence of fatty acids and the variation in the relative gas-liquid chromatography peak areas of different fatty acids were evaluated and compared with the relative peak areas of these acids. A new chromatogram comparison method involving the use of an exponential function was developed to adjust to data variation optimally. This method was compared with several previously published methods of correlation analysis with data from representative clinical bacteriological isolates. The efficacies of the methods in separating different bacterial species into distinct clusters were compared. The new exponential function method was superior to the others both in its ability to separate species into different clusters and in giving a greater degree of identity to strains within a proper cluster. The results indicate that the gas-liquid chromatography of bacterial cellular fatty acids can be used effectively in the identification of clinically isolated bacteria. However, the usefulness of the analysis depends on the comparison method used and on its ability to cope with data variations.

MeSH Terms
Bacteria/analysis,classification,isolation & purification Chromatography, Gas Electronic Data Processing Fatty Acids/analysis Microcomputers
Chemicals
Fatty Acids
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Eerola E
Department of Medical Microbiology, Turku University, Finland.
Lehtonen O P
References (8)
8 references, click to expand
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Article Info
Journal
Journal of clinical microbiology
Abbr.
J Clin Microbiol
ISSN
0095-1137
Published
1988-09-00
Pages
1745-53
Language
English
Region
United States
NLM ID
7505564
PMCID
PMC266709
Subset
IM
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