Water Quality Verification Through Optical Detection of Bacteria

Contamination in water supplies can occur and it results in the distribution of inappropriate water, affecting greatly the community well-being. Monitoring water utilities is key to avoiding possible health problems from this scenario. A conventional parameter to evaluate the quality of water is the concentration of Escherichia coli, a bacteria commonly present in sewage. Nowadays, the standard procedures for the counting of such micro-organisms are reliable but very laborious and time-consuming. Therefore they are not suitable for the demands of fast evaluation, which is necessary to circumvent any potential distribution of contaminated water. This masters thesis proposes to improve and automate the operation of a sensor system developed by Acreo ICT to monitor the water quality in water facilities. This sensor uses a quantum dot-based immunoassay for targeting the E. coli present in the water, and flow cytometry as a technique to detect and transform the obtained fluorescent signals into an estimated concentration value of the E. coli. First, immunoassay was performed by using IgY-conjugated quantum dots and IgY-conjugated organic fluorophore, which are used to label E. coli from lab strain and from sewage. The immunoassay was subjected to different solutions. Results of these immunoassay tests showed that the antibody-antigen reaction needs to take place in a saline environment for stronger binding. Furthermore, the combination of Triton X-100, BSA and EDTA in this system improved the specificity of the immunoassay and increased the signal strength. The increase of temperature up to 40°C accelerated the reaction rate, reducing the necessary time for the binding reaction. The sensor system was automated by the implementation of a proposed design of a mixing structure based on continuous flow. Furthermore, an improvement in the flow cytometry was made by replacing the former flow cell made of plastic to one made of quartz, which also has a smaller optical path. Lastly, tests using tap water and sewage showed that the final assembled sensor can be used to detect contamination of drinking water with sewage. With these improvements, the sensor system is, at the time of publication of this thesis, being subject to in situ tests in water facilities in Jerusalem and Zürich