Reflektometrische Interferenzspektroskopie (RIfS) zur Detektion ganzer Legionella pneumophila-Zellen und Entwicklung regenerierbarer funktionaler Oberflächen für Anwendungen in der Biosensorik.

Verlässliche und effiziente Methoden der Legionellen-Detektion sind für den Bereich der Hygiene in öffentlichen Gebäuden überaus wichtig. Die Legionellose ist eine der häufigsten Todesursachen infolge von nosokomial erworbenen Infektionen. Die etablierten Legionellentests liefern erst nach 3-7 Tage...

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Bibliographic Details
Main Author: Merkl, Stefan
Contributors: Keusgen, Michael (Prof. Dr.) (Thesis advisor)
Format: Doctoral Thesis
Language:German
Published: Philipps-Universität Marburg 2015
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Reliable and efficient methods for the detection of Legionella pneumophila germs are of utmost importance for maintenance of hygienic standards in public buildings. Legionellosis is one of the most frequent causes of death as a result of nosocomial infections. Established tests for Legionella yield reliable results within 3 to 7 days at the earliest. Faster methods are urgently required. Biosensors are an often used tool in a wide range of analytics. However, only one experiment can be conducted on one appropriate sensor-chip, a limitation that is costly in material an money. According to this study the RIfS method is appropriate for the detection of whole cells of Legionella pneumophila. The lower detection limit is between 1000000 and 10000000 cells/100 ml. A quantification of cells turned out to be problematic because the cell concentrations did not reliably correlate with the net signals at the end of the dissociation phase. The reason may be that the cells on the surface do not form a well-defined layer in the physical sense. Using REM a lot of cell-free areas were found on the surface as well as many overlappings of individual cells. The correlation of cell concentrations and the slopes in the initial binding phase seem to be more reliable since overlappings do not impinge on the signal development at the beginning of the experiment.