Detection of microbial disturbances in a drinking water microbial community through continuous acquisition and advanced analysis of flow cytometry data. (15th November 2018) - Props, Ruben; Rubbens, Peter; Besmer, Michael; Buysschaert, Benjamin; Sigrist, Jurg; Weilenmann, Hansueli; Waegeman, Willem; Boon, Nico; Hammes, Frederik
Abstract: Detecting disturbances in microbial communities is an important aspect of managing natural and engineered microbial communities. Here, we implemented a custom-built continuous staining device in combination with real-time flow cytometry (RT-FCM) data acquisition, which, combined with advanced FCM fingerprinting methods, presents a powerful new approach to track and quantify disturbances in aquatic microbial communities. Through this new approach we were able to resolve various natural community and single-species microbial contaminations in a flow-through drinking water reactor. Next to conventional FCM metrics, we applied metrics from a recently developed fingerprinting technique in order to gain additional insight into the microbial dynamics during these contamination events. Importantly, we found that multiple community FCM metrics based on different statistical approaches were required to fully characterize all contaminations. Furthermore we found that for accurate cell concentration measurements and accurate inference from the FCM metrics (coefficient of variation ≤ 5%), at least 1000 cells should be measured, which makes the achievable temporal resolution a function of the prevalent bacterial concentration in the system-of-interest. The integrated RT-FCM acquisition and analysis approach presented herein provides a considerable improvement in the temporal resolution by which microbial disturbances can be observed and simultaneously provides a multi-faceted toolset to characterize such disturbances. Graphical abstract: Image 1 Highlights: Real-time flow cytometry is combined with advanced flow cytometric fingerprinting data analysis. Conventional and advanced fingerprinting metrics grant complementary insights in microbial dynamics. Guidelines for data acquisition and analysis are proposed. RT-FCM and fingerprinting metrics extend toolset for studying microbial community disturbances.