On-line monitoring of lipid storage in yeasts using impedance spectroscopy

Bioremediation technologies and many environmentally sound biosyntheses rely on the catalytic potential of whole cells. For analyzing and controlling such processes robust real-time indicators for the concentration of intact cells such as impedance are required. The conventional method measures the...

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Bibliographic Details
Published in:Journal of biotechnology 2008-05, Vol.135 (1), p.64-70
Main Authors: Maskow, Thomas, Röllich, Anita, Fetzer, Ingo, Ackermann, Jörg-Uwe, Harms, Hauke
Format: Article
Language:English
Subjects:
Algorithms
Arxula adeninivorans
Ascomycota - metabolism
Biological and medical sciences
Bioprocess control
Biotechnology
Electric Impedance
Fundamental and applied biological sciences. Psychology
Impedance spectroscopy
Lipid Metabolism - physiology
Lipids
Monitoring, Physiologic - methods
On-line monitoring
Online Systems
Reproducibility of Results
Sensitivity and Specificity
Spectrum Analysis - methods
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Summary:Bioremediation technologies and many environmentally sound biosyntheses rely on the catalytic potential of whole cells. For analyzing and controlling such processes robust real-time indicators for the concentration of intact cells such as impedance are required. The conventional method measures the capacitances of cell suspensions at one or two frequencies and correlates them with biomass concentrations. However, cell inclusions such as lipid droplets or overproduced enzymes may block intracellular ion paths, thereby possibly modifying the dielectric properties of the cells. To test the hypothesis that the total impedance spectrum into the analysis may provide useful information about cell inclusions, the impedance spectrum of a technical culture of the oleaginous yeast Arxula adeninivorans was measured and evaluated every 15 s. This yeast is a good test object since it stores the excess of assimilated carbon in experimentally controllable lipid droplets. Upon correction for possible impedance signal interferences, we derived different empirical methods suitable to indicate incipient lipid formation. The methods were designed to act on-line and are thus principally suited for real-time monitoring of cell inclusions. In search for optimised bioprocess monitoring we tested a heuristic spectrum analysis using integrative statistics (RDA). With this approach we were able to accurately detect the formation of cell inclusions, which is potentially valuable for future bioprocess control strategies.
ISSN:0168-1656
1873-4863
DOI:10.1016/j.jbiotec.2008.02.014