A comparison of flow cytometry and conventional microbiology in the study of biofilms.

JIAN, Xiangrong. (2002). A comparison of flow cytometry and conventional microbiology in the study of biofilms. Doctoral, Sheffield Hallam University (United Kingdom).. [Thesis]

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Abstract
A comprehensive study on the application of flow cytometry (FCM) for the analysis of biofilms has been undertaken and the results presented in this thesis have shown that flow cytometry can been successfully used to enumerate, sort and image the bacteria and amoebae in biofilms and water distribution systems as a rapid and sensitive semiautomated technique compared with conventional microbiology.It has been shown that the results of flow cytometric analysis of total Legionella pneumophila cells have a strong statistical correlation with the numbers of Legionella cfu by BCYE plate counting (BCYE PC) methods for biofilms and planktonic phases. There are also strong statistical correlations between flow cytometric analysis and epifluorescent microscopic (EFM) analysis (direct counting) for determination of bacteria, including Legionella, Escherichia coli, Salmonella, Pseudomonas and amoebae, and total and viable cells in pure cultures, water distribution systems and biofilms.The flow cytometric protocols have been set up and optimised for the analysis of environmental microorganisms. The novel fluorescent dyes and immunofluorescence antibodies from the most current commercial dyes also have been screened and the staining protocols have been optimised and adopted for flow cytometric analysis and direct counting by epifluorescent microscopy. The tap water biofilms and river water biofilms were analysed by the flow cytometer and direct counting methods as well as by conventional microbiological methods (plate counting). The bacterial populations in real water distribution systems have been fully investigated and the total, viable bacteria were determined by the above methods.The findings of this work have practical implications with respect to the rapid and automatic detection and predictions of Legionella spp. and the risk assessment from biofilms and water environments.
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