Abstract
In this study, we co-analyze all available 16S rRNA gene sequencing studies from bulk drinking water samples in full-scale drinking water distribution systems.
Highlights
Microbial communities in drinking water systems can mediate wide-ranging impacts from biofiltration for pollutant removal to public health risks
The transport of drinking water (DW) through the Drinking water distribution systems (DWDSs) is accompanied by a mass migration of the microbial communities that are an inevitable component of this ecosystem and controlling their growth is paramount to the provision of safe DW
Biofilms are extremely spatially heterogeneous[31] and are likely to develop over time-scales that are much longer than the residence time of water within a given DWDS
Summary
Microbial communities in drinking water systems can mediate wide-ranging impacts from biofiltration for pollutant removal to public health risks. Studies have reported differences in the dominance of these classes depending on a range of factors, including but not limited to seasons[7,17] and disinfection strategy.[6,12,20,21] Despite this emerging consensus about the composition of the DW microbiome, the bacterial community, to our knowledge there has been no study that attempts a collective analysis (i.e. meta-analysis) of all publicly available DW datasets Such efforts are critical, as the study of the DW microbiome with high-throughput sequencing methods is nascent, compared to efforts to characterize microbiomes associated with other environments, e.g. human gut[22] and even another engineered aquatic system, i.e. the wastewater/activated sludge system.[23,24] Such an early-stage meta-analysis effort can reveal conserved features across DW systems and help identify targeted research questions and highlight opportunities to improve future DW microbiome studies. The objectives of this study were to: (1) identify microbial populations that are detected across all publicly available bulk DW datasets; (2) evaluate the variation in the occurrence and relative abundance of target microbial groups, at the phylum/class and operational taxonomic unit (OTU) level, (3) evaluate the relationship between occurrence and relative abundance of taxa across systems, (4) determine the association between disinfection strategy and microbial community, and (5) provide insights into their functional potential across all samples and within disinfection strategy type, to the extent possible
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