Detection of microbial disturbances in a drinking water microbial community through continuous acquisition and advanced analysis of flow cytometry data

Online assessment of sand filter performance for bacterial removal in a full-scale drinking water treatment plant

“…FCM uses simultaneous light-scattering and fluorescence measurements coupled with dye staining for microbial counting and analysis; thus, bacterial counting using FCM is highly useful to measure microbial water quality. It has been validated for detecting variations in both intact and damaged bacterial cells for drinking water treatment systems and for distribution network (Props et al, 2018). FCM analysis has recently been automated with robotics for staining cells (Hammes et al, 2012;Besmer et al, 2014); providing further capabilities for online monitoring of bacterial counts.…”

Computational Surveillance of Microbial Water Quality With Online Flow Cytometry

“…The exact origin of this daily fluctuations is not known. The additional challenge of differentiating between the normal and intentional concentration increases was new compared to similar experiments where tap water was monitored by FCM in an online fashion and contaminated with axenic cultures and natural microbial communities (Besmer et al, 2017;Props et al, 2018).…”

“…Flow cytometric measurements do not only allow to derive the cell concentration in water samples, but also reveal bacteria community patterns which can be described by socalled cytometric fingerprints (Koch et al, 2014). Fingerprints summarize the bacteria distribution in the whole flow cytometric signal space and can be powerful tools to detect changes in the bacterial communities which are unnoticed when only the cell concentration is taken into account (Koch et al, 2013;Van Nevel et al, 2017a;Props et al, 2018;Schleich et al, 2019). An indepth analysis of the microbial communities in water processes could allow to distinguish between periods of high bacterial loads encountered during normal operating conditions and sudden bacterial increases caused by unwanted microbial perturbations.…”

“…Until recently, work discriminating water samples from different origins with cytometric fingerprints as well as the detection of changes in the microbial community was mainly done offline, meaning that the algorithms designed to identify intergroup characteristics were only applied after the whole data collection (De Roy et al, 2012;Koch et al, 2014;Van Nevel et al, 2017a;Buysschaert et al, 2018a;Props et al, 2018). De Roy et al (2012) developed a statistical analysis pipeline that could distinguish between different brands of bottled water and even detect microbial community changes caused by changing environmental factors.…”

“…De Roy et al (2012) developed a statistical analysis pipeline that could distinguish between different brands of bottled water and even detect microbial community changes caused by changing environmental factors. Koch et al (2014) identified microbial differences in electroactive biofilms grown under different substrate conditions using multiple fingerprint calculation approaches, and Props et al (2018) applied a cluster analysis on fingerprinting features to differentiate between natural freshwater microbial communities. In contrast, a recent study has developed an online processing method that was shown to be effective in drinking water quality monitoring (Favere et al, 2020).…”