04.02.2014 Aufrufe

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Quantitative Microscopic Fingerprinting of<br />

Environmental Microbes<br />

Y. Kim #1 , P. Scherer 1<br />

1 Hamburg University of Applied <strong>Science</strong>s, Faculty <strong>Life</strong> <strong>Science</strong>s, Lohbruegger Kirchstr. 65, 21033<br />

Hamburg-Bergedorf, Germany<br />

# Corresponding Author: E-mail: yongsung.kim@haw-hamburg.de, Ph.: +49 (0)40 42875 6387 Fax:<br />

+49 (0)40 42875 6359<br />

Abstract<br />

The goal of this study was to find a new tool to evaluate the biological vitality of anaerobic<br />

digesters. Therefore, a simple microscopic method for quantification and morphological<br />

classification of microorganisms was developed. Cell counts and its morphology are<br />

supposed to be a direct indicator of a methanogenic habitate. Since environmental sample<br />

contains interfering fibrous material, an appropriate sample preparation is required such as<br />

an optimal visualizing stain, agent with its optimal viscosity for microscopic slide,<br />

homogenous distribution of sample on the slide as well as a proper image analysis algorithm.<br />

SYBR Green I was fo<strong>und</strong> to be the most sensitive dye for total cell counts in environmental<br />

samples with minimal backgro<strong>und</strong> fluorescence. For detection of methanogens,<br />

autofluorescence based on the typical methanogenic fluorescent coenzyme F 420 was used. A<br />

low viscosity methylcellulose was successfully applied as a fixing agent for microscopic slide.<br />

It showed a better adhering character and supplied more regular surface related to agar or<br />

gelatin. With the help of accompanying molecular analysis, morphological classification<br />

algorithms for methanogens could be established by the image analysis software Image Pro<br />

7. During analyzing one biogas plant sample for more than 26 weeks and several different<br />

anaerobic digesters for a shorter time, its reliability as a counting method was verified. The<br />

correctness of the counting by image analysis system was proven by Neubauer counting<br />

chamber and reference bacteria. The results showed a good congruence between<br />

quantitative image analysis and Neubauer counting chamber representing deviation of 0.2 –<br />

2.6 %.

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