Accurate and sensitive online detection tools would benefit both fundamental research and practical applications in aquatic microbiology. Here, we describe the development and testing of an online flow cytometer (FCM), with a specific use foreseen in the field of drinking water microbiology. The system incorporated fully automated sampling and fluorescent labeling of bacterial nucleic acids with analysis at 5‐min intervals for periods in excess of 24 h. The laboratory scale testing showed sensitive detection (< 5% error) of bacteria over a broad concentration range (1 × 103–1 × 106 cells mL−1) and particularly the ability to track both gradual changes and dramatic events in water samples. The system was tested with bacterial pure cultures as well as indigenous microbial communities from natural water samples. Moreover, we demonstrated the possibility of using either a single fluorescent dye (e.g., SYBR Green I) or a combination of two dyes (SYBR Green I and Propidium Iodide), thus broadening the application possibilities of the system. The online FCM approach described herein has considerable potential for routine and continuous monitoring of drinking water, optimization of specific drinking water processes such as biofiltration or disinfection, as well as aquatic microbiology research in general. © 2012 International Society for Advancement of Cytometry

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Process Analytical Technology (PAT) launched by the U.S. Food and Drug Administration (FDA) aims to ensure the quality of pharmaceutical products. One important tool to obtain a deeper process understanding is the use of modern real-time process sensors and analyzers. In this context an industrially accepted optical probe for turbidity measurement (Aquasant probe) has been adapted for on-line and real-time fluorescence measurement in (bio-)reactors. By tagging product proteins with fluorescent reporter molecules (e.g. GFP) it was possible to quantify product concentrations during a fermentation process with the new probe. The on-line obtained signal showed a high correlation to the off-line signal. This new method has remarkable advantages compared to classical off-line product lab analyses and can serve as a platform-independent quantification method of products to be used in either up- or downstream processing.