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Drinking water enters buildings with a given microbiological community composition. Within premise plumbing systems, the drinking water is subject to very different conditions and temperatures. Whereas part of the water stays cold, another part is heated to provide hot water. In this study, drinking water samples were taken at different locations in four buildings that had central heating circles and that were equipped with ultrafiltration modules. The latter were intended to keep bacterial numbers low. When studying the increase in bacterial concentrations in these water samples using regrowth tests at different incubation temperatures, a temperature-dependence could be observed. Bacteria in cold water samples propagated best when incubated at 22°C, but often poorly at 36°C and not at all at 50°C. Bacteria in hot water samples showed the reverse behavior and grew best when incubated at 50°C, whereas growth at 22°C was poor or associated with a long growth lag. Water samples from distal taps in periphery locations used for retrieving both cold and hot water showed intermediate growth behaviors. Results suggest the existence of different temperature-adapted bacterial populations within domestic drinking water systems. The finding was supported by sequence data revealing distinct differences in the microbiomes between cold and hot water samples. Abundant bacterial groups in hot water included Deinococci, Kryptonia, Ignavibacteria, Nitrospiria, Gemmatimonadetes and different genera of Gammaproteobacteria. Stagnation of hot water at 50°C, 55°C, or 60°C furthermore shaped the microbiome in different ways indicating that small temperature differences can have a substantial impact on the bacterial communities.

Abstract Limiting microbial growth during drinking water distribution is achieved either by maintaining a disinfectant residual or through nutrient limitation without using a disinfectant. The impact of these contrasting approaches on the drinking water microbiome is not systematically understood. We use genome-resolved metagenomics to compare the structure, metabolic traits, and population genomes of drinking water microbiome samples from bulk drinking water across multiple full-scale disinfected and non-disinfected drinking water systems. Microbial communities cluster at the structural- and functional potential-level based on the presence/absence of a disinfectant residual. Disinfectant residual alone explained 17 and 6.5% of the variance in structure and functional potential of the drinking water microbiome, respectively, despite including multiple drinking water systems with variable source waters and source water communities and treatment strategies. The drinking water microbiome is structurally and functionally less diverse and variable across disinfected compared to non-disinfected systems. While bacteria were the most abundant domain, archaea and eukaryota were more abundant in non-disinfected and disinfected systems, respectively. Community-level differences in functional potential were driven by enrichment of genes associated with carbon and nitrogen fixation in non-disinfected systems and γ-aminobutyrate metabolism in disinfected systems likely associated with the recycling of amino acids. Genome-level analyses for a subset of phylogenetically-related microorganisms suggests that disinfection selects for microorganisms capable of using fatty acids, presumably from microbial decay products, via the glyoxylate cycle. Overall, we find that disinfection exhibits systematic selective pressures on the drinking water microbiome and may select for microorganisms able to utilize microbial decay products originating from disinfection-inactivated microorganisms. Video abstract

In drinking water distribution systems (DWDSs), pipe material and water temperature are some of the critical factors affecting the microbial flora of water. Six model DWDSs consisting of three pipe materials (galvanized steel, copper, and PEX) were constructed. The temperature in three systems was maintained at 22 °C and the other 3 at 32 °C to study microbial and elemental contaminants in a 6-week survey using 16S rRNA next-generation sequencing (NGS) and inductively coupled plasma-optical emission spectrometry (ICP-OES). Pipe material and temperature were preferentially linked with the composition of trace elements and the microbiome of the DWDSs, respectively. Proteobacteria was the most dominant phylum across all water samples ranging from 60.9% to 91.1%. Species richness (alpha diversity) ranking was PEX < steel ≤ copper system and elevated temperature resulted in decreased alpha diversity. Legionellaceae were omni-prevalent, while Mycobacteriaceae were more prevalent at 32 °C (100% vs. 58.6%) and Pseudomonadaceae at 22 °C (53.3% vs. 62.9%). Heterogeneity between communities was disproportionately driven by the pipe material and water temperature. The elevated temperature resulted in well-defined microbial clusters (high pseudo-F index) in all systems, with the highest impact in PEX (10.928) followed by copper (9.696) and steel (5.448). Legionellaceae and Mycobacteriaceae are preferentially prevalent in warmer waters. The results suggest that the water temperature has a higher magnitude of impact on the microbiome than the pipe material.

Advanced treatment facilities for potable water reuse of wastewater are designed to achieve high removal levels of specific pathogens, as well as many other constituents. However, changes to the microbial community throughout treatment, storage, and distribution of this water have not been well characterized. We applied high-throughput amplicon sequencing, read-based, assembly-based, and genome-resolved metagenomics, and flow cytometry to investigate the microbial communities present in a pilot-scale advanced water treatment facility. Advanced treatment of secondary-treated wastewater consisted of ozonation, chloramination, microfiltration, reverse osmosis (RO), advanced oxidation (UV/H2O2), granular activated carbon (GAC) filtration, and chlorination. Treated water was fed into bench-scale simulated distribution systems (SDS). Cell counts and microbial diversity in bulk water decreased until GAC filtration, and the bacterial communities were significantly different following each treatment step. Bacteria grew within GAC media and contributed to a consistent microbial community in the filtrate, which included members of the Rhizobiales and Mycobacteriaceae. After chlorination, some of the GAC filtrate community was maintained within the SDS, and community shifts were associated with stagnation. Putative antibiotic resistance genes and potential opportunistic pathogens were identified before RO and after advanced oxidation, although few if any members of the wastewater microbial community passed through these treatment steps. These findings can contribute to improved design of advanced treatment trains and management of microbial communities in post-treatment steps.

While safe and of high quality, drinking water can host an astounding biodiversity of microorganisms, dismantling the belief of its “biological simplicity.” During the very few years, we are witnessing an exponential growth in scientific publications, exploring the ecology hidden in drinking water treatment plants (DWTPs) and drinking water distribution system (DWDS). We focused on what happens to the microbial communities from source water (groundwater) throughout the main steps of the potabilization process of a DWTP, located in an urbanized area in Northern Italy. Samples were processed by a stringent water filtration to retain even the smallest environmental bacteria and then analyzed with High-Throughput DNA Sequencing (HTS) techniques. We showed that carbon filters harbored a microbial community seeding and shaping water microbiota downstream, introducing a significant variation on incoming (groundwater) microbial community. Chlorination did not instantly affect the altered microbiota. We were also able to correctly predict (through machine learning analysis) samples belonging to groundwater (overall accuracy was 0.71), but the assignation was not reliable with carbon filter samples, which were incorrectly predicted as chlorination samples. The presence and abundance of specific microorganisms allowed us to hypothesize their role as indicators. In particular, Candidatus Adlerbacteria (Parcubacteria), together with microorganisms belonging to Alphaproteobacteria and Gammaproteobacteria, characterized treated water, but not raw water. An exception, confirming our hypothesis, is given by the samples downstream the filters renewal, which had a composition resembling groundwater. Volatility analysis illustrated how carbon filters represented an ecosystem that is stable over time, probably bearing the environmental conditions that promote the survival and growth of this peculiar microbial community.