Abstract
ABSTRACTBacterial communities migrate continuously from the drinking water treatment plant through the drinking water distribution system and into our built environment. Understanding bacterial dynamics in the distribution system is critical to ensuring that safe drinking water is being supplied to customers. We present a 15-month survey of bacterial community dynamics in the drinking water system of Ann Arbor, MI. By sampling the water leaving the treatment plant and at nine points in the distribution system, we show that the bacterial community spatial dynamics of distance decay and dispersivity conform to the layout of the drinking water distribution system. However, the patterns in spatial dynamics were weaker than those for the temporal trends, which exhibited seasonal cycling correlating with temperature and source water use patterns and also demonstrated reproducibility on an annual time scale. The temporal trends were driven by two seasonal bacterial clusters consisting of multiple taxa with different networks of association within the larger drinking water bacterial community. Finally, we show that the Ann Arbor data set robustly conforms to previously described interspecific occupancy abundance models that link the relative abundance of a taxon to the frequency of its detection. Relying on these insights, we propose a predictive framework for microbial management in drinking water systems. Further, we recommend that long-term microbial observatories that collect high-resolution, spatially distributed, multiyear time series of community composition and environmental variables be established to enable the development and testing of the predictive framework.
Highlights
Bacterial communities migrate continuously from the drinking water treatment plant through the drinking water distribution system and into our built environment
We demonstrate that the bacterial community in the DWDS (i) clusters closely with the DW treatment plant (DWTP) community while exhibiting small localized DWDS effects, (ii) exhibits spatial patterns that conform to the layout of the DWDS, (iii) displays temporal trends that indicate annual reproducibility, (iv) is driven by two seasonal clusters with distinct cluster-level network characteristics, and (v) exhibits robust interspecific occupancy-abundance relationships that utilize data from all detected taxa, linking detection frequency of taxa to their observed relative abundance
Water samples were collected from the clean water reservoir at the DWTP and at nine different locations in three sectors (S1, S2, and S3) of the DWDS of Ann Arbor, MI (Fig. 1), for a period of 15 months
Summary
Bacterial communities migrate continuously from the drinking water treatment plant through the drinking water distribution system and into our built environment. We demonstrate that the bacterial community in the DWDS (i) clusters closely with the DWTP community while exhibiting small localized DWDS effects, (ii) exhibits spatial patterns (distance decay and dispersivity) that conform to the layout of the DWDS, (iii) displays temporal trends that indicate annual reproducibility, (iv) is driven by two seasonal clusters with distinct cluster-level network characteristics, and (v) exhibits robust interspecific occupancy-abundance relationships that utilize data from all detected taxa, linking detection frequency of taxa to their observed relative abundance Based on these five major findings, we suggest that the collection of fine-scale spatial and temporal data through the establishment of long-term DW ecological observatories should allow the forecasting of the DW microbiome. The ability to predict the DW bacterial community has the potential to impart significant cost savings to the water industry by improving the efficiency of water quality monitoring, reduce risk to public health by helping to eliminate microbial risks before they are manifested, and pave the way toward exploiting the multiple benefits that a functionally diverse and structurally robust microbial community offers
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