Typing of unknown microorganisms based on quantitative analysis of fatty acids by mass spectrometry and hierarchical clustering

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• 作者：Tingting Li ; Ling Dai ; Lun Li ; Xuejiao Hu ; Linjie Dong ; Jianjian Li ; Sule Khalfan Salim ; Jieying Fu ; Hongying Zhong
• 关键词：Microorganism identification ; Fatty acids ; Hierarchical clustering ; Mass spectrometry ; Stable isotope labeling
• 刊名：Analytica Chimica Acta
• 出版年：2011
• 出版时间：17 January 2011
• 年：2011
• 卷：684
• 期：1-2
• 页码：112-120
• 全文大小：723 K

文摘

Rapid identification of unknown microorganisms of clinical and agricultural importance is not only critical for accurate diagnosis of infections but also essential for appropriate and prompt treatment. We describe here a rapid method for microorganisms typing based on quantitative analysis of fatty acids by iFAT approach (Isotope-coded Fatty Acid Transmethylation). In this work, lyophilized cell lysates were directly mixed with 0.5 M NaOH solution in d3-methanol and n-hexane. After 1 min of ultrasonication, the top n-hexane layer was combined with a mixture of standard d0-methanol derived fatty acid methylesters with known concentration. Measurement of intensity ratios of d3/d0 labeled fragment ion and molecular ion pairs at the corresponding target fatty acids provides a quantitative basis for hierarchical clustering. In the resultant dendrogram, the Euclidean distance between unknown species and known species quantitatively reveals their differences or shared similarities in fatty acid related pathways. It is of particular interest to apply this method for typing fungal species because fungi has distinguished lipid biosynthetic pathways that have been targeted for lots of drugs or fungicides compared with bacteria and animals. The proposed method has no dependence on the availability of genome or proteome databases. Therefore, it is can be applicable for a broad range of unknown microorganisms or mutant species.