Genome-resolved insights into the structure and function of the drinking water microbiome can advance the effective management of drinking water quality. To enable this, we constructed and curated thousands of metagenome-assembled and isolate genomes from drinking water distribution systems globally to develop a Drinking Water Genome Catalog (DWGC). The current DWGC disproportionately represents disinfected drinking water systems due to a paucity of metagenomes from nondisinfected systems. Using the DWGC, we identify core genera of the drinking water microbiome including a genus (UBA4765) within the order Rhizobiales that is frequently detected and highly abundant in disinfected drinking water systems. We demonstrate that this genus has been widely detected but incorrectly classified in previous amplicon sequencing-based investigations of the drinking water microbiome. Further, we show that a single genome variant (genomovar) within this genus is detected in 75% of drinking water systems included in this study. We propose a name for this uncultured bacterium as \"Raskinella chloraquaticus\" and describe the genus as \"Raskinella\" (endorsed by SeqCode). Metabolic annotation and modeling-based predictions indicate that this bacterium is capable of necrotrophic growth, is able to metabolize halogenated compounds, proliferates in a biofilm-based environment, and shows clear indications of disinfection-mediated selection.

Increases in phosphate availability in drinking water distribution systems (DWDSs) from the use of phosphate-based corrosion control strategies may result in nutrient and microbial community composition shifts in the DWDS. This study assessed the year-long impacts of full-scale DWDS orthophosphate addition on both the microbial ecology and density of drinking-water-associated pathogens that infect the immunocompromised (DWPIs). Using 16S rRNA gene amplicon sequencing and droplet digital PCR, drinking water microbial community composition and DWPI density were examined. Microbial community composition analysis suggested significant compositional changes after the orthophosphate addition. Significant increases in total bacterial density were observed after orthophosphate addition, likely driven by a 2 log 10 increase in nontuberculous mycobacteria (NTM). Linear effect models confirmed the importance of phosphate addition with phosphorus concentration explaining 17% and 12% of the variance in NTM and L. pneumophila density, respectively. To elucidate the impact of phosphate on NTM aggregation, a comparison of planktonic and aggregate fractions of NTM cultures grown at varying phosphate concentrations was conducted. Aggregation assay results suggested that higher phosphate concentrations cause more disaggregation, and the interaction between phosphate and NTM is species specific. This work reveals new insight into the consequences of orthophosphate application on the DWDS microbiome and highlights the importance of proactively monitoring the DWDS for DWPIs.

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.

The biogeography of eukaryotes in drinking water systems is poorly understood relative to that of prokaryotes or viruses, limiting the understanding of their role and management. A challenge with studying complex eukaryotic communities is that metagenomic analysis workflows are currently not as mature as those that focus on prokaryotes or viruses. In this study, we benchmarked different strategies to recover eukaryotic sequences and genomes from metagenomic data and applied the best-performing workflow to explore the factors affecting the relative abundance and diversity of eukaryotic communities in drinking water distribution systems (DWDSs). We developed an ensemble approach exploiting k-mer- and reference-based strategies to improve eukaryotic sequence identification and identified MetaBAT2 as the best-performing binning approach for their clustering. Applying this workflow to the DWDS metagenomes showed that eukaryotic sequences typically constituted small proportions (i.e., <1%) of the overall metagenomic data with higher relative abundances in surface water-fed or chlorinated systems with high residuals. The α and β diversities of eukaryotes were correlated with those of prokaryotic and viral communities, highlighting the common role of environmental/management factors. Finally, a co-occurrence analysis highlighted clusters of eukaryotes whose members\' presence and abundance in DWDSs were affected by disinfection strategies, climate conditions, and source water types.

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.

[This corrects the article DOI: 10.3389/fmicb.2019.00993.].

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.