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Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
ID
4250577
Author(s)
Besmer, Michael D.; Epting, Jannis; Page, Rebecca M.; Sigrist, Jurg A.; Huggenberger, Peter; Hammes, Frederik
Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment
Journal
Scientific Reports
Volume
6
Pages / Article-Number
38462
Mesh terms
Bacteria, isolation & purification; Drinking Water, microbiology; Environmental Monitoring; Flow Cytometry; Groundwater, microbiology; Humans; Water Microbiology; Water Pollution; Water Quality
Abstract
Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality - particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells mu L-1. The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems.
