Microbial community assembly and its impact on functions in water filtration processes

Abstract

Water filters, extensively employed in the modern drinking water treatment plants (DWTPs), are populated by a high diversity of bacteria. Little is known about what forces determine the structure of those bacterial communities and how their assembly affects the quality of the final potable water. Two contrasting ecological theories explain how natural microbial communities assemble, shaped by environmental deterministic factors (Niche based theory) or merely stochastic forces (Neutral community model-NCM). Moreover, no simple and standardized culture-independent method that allows direct cell quantification in filter media samples, free from biases introduced by simplifying assumptions or technical method limitations, is currently available. The aim of this work was to further the understanding of the factors involved in the assembly of microbial communities in water filters and develop a new method for their quantification using flowcytometry. The shaping effect of two contrasting drinking water filter materials (quartz sand and granular activated carbon) was studied in laboratory-scale columns, while, the role played by neutral dynamics was tested by applying an explicit model of neutral assembly to the community compositions of distinct full scale filters. Results suggested that filter medium has the potential of shaping different filter microbial communities whose different compositions affect the quality of the post-filtration in terms of pathogens presence and Triahalomethanes (THMs) formation potential. Stochastic forces play a weak role in the assembly of lab-scale water filters with contrasting materials, but they seem to play a more prominent role in driving the assembly of full-scale systems as suggested by the agreement between the experimental data and the model. An accurate and highly reproducible method for enumerating cells on sand grains using flowcytometry has been developed and tested against other culture-independent quantification approaches typically used for such samples