Automated systems for identification of heterotrophic marine bacteria on the basis of their Fatty Acid composition

Abstract

The fatty acid methyl ester composition of a total of 71 marine strains representing the genera Alteromonas, Deleya, Oceanospirillum, and Vibrio was determined by gas-liquid chromatographic analysis. Over 70 different fatty acids were found. The predominant fatty acids were 16:0, 16:1 cis 9, summed-in-feature (SIF) 4 (15:0 iso 2OH and/or 16:1 trans 9) and SIF 7 (18:1 cis 11, 18:1 trans 9, and/or 18:1 trans 6) for all the strains considered, but minor quantitative variations could be used to distinguish the different genera. In addition to a conventional statistical processing method to analyze the data and draw comparison between species and genera, an approach involving neutral network-based elaboration is applied. The statistical analysis and dendrogram representation gave a comparison of the species considered, while the neural network computation provided a more accurate assignment of species to their genera. Moreover, by using neural networks, it was possible to conclude that only 22 fatty acids were important for the identification of the marine genera considered. A database of Alteromonas, Deleya, Oceanospirillum, and Vibrio fatty acid methyl ester profiles was generated and is now routinely used to identify fresh marine isolates.