4.7 Article

Detection of volatile metabolites of Escherichia coli by multi capillary column coupled ion mobility spectrometry

期刊

ANALYTICAL AND BIOANALYTICAL CHEMISTRY
卷 394, 期 3, 页码 791-800

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s00216-009-2758-0

关键词

Volatile metabolites; MVOC; Escherichia coli; Acetone; Heptan-2-one; Nonan-2-one; Metabolism; Metabolic network

资金

  1. Ministerium fur Innovation, Wissenschaft
  2. Forschung und Technologies des Landes Nordrhein-Westfalen
  3. Bundesministerium fur Bildung und Forschung

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Detection and immediate quantification of microbial metabolic activities is of high interest in fields as diverse as biotechnology and infection biology. Interestingly, the most direct signals of microbial metabolism, the evolution of volatile metabolites, is largely ignored in the literature, and rather, metabolite concentrations in the microbial surrounding or even disruptive methods for intracellular metabolite measurements (i.e., metabolome analysis) are favored. Here, the development of a multi capillary column coupled ion mobility spectrometer (MCC-IMS) was described for the detection of volatile organic compounds from microbes and the MCC-IMS was used for characterization of metabolic activity of growing Escherichia coli. The MCC-IMS chromatogram of the microbial culture off-gas of the acetone-producing E. coli strain BL21 pLB4 revealed four analytes that positively correlated with growth, which were identified as ethanol, propanone (acetone), heptan-2-one, and nonan-2-one. The occurrence of these analytes was cross-validated by solid-phase micro-extraction coupled with gas chromatography mass spectrometry analysis. With this information in hand, the dynamic relationship between the E. coli biomass concentration and the metabolite concentrations in the headspace was measured. The results suggest that the metabolic pathways of heptan-2-one and nonan-2-one synthesis are regulated independent of each other. It is shown that the MCC-IMS in-line off-gas analysis is a simple method for real-time detection of microbial metabolic activity and discussed its potential for application in metabolic engineering, bioprocess control, and health care.

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