Composition of active bacterial communities and presence of opportunistic pathogens in disinfected and non-disinfected drinking water distribution systems in Finland.

Many factors, including microbiome structure and activity in the drinking water distribution system (DWDS), affect the colonization potential of opportunistic pathogens. The present study aims to describe the dynamics of active bacterial communities in DWDS and identify the factors that shape the community structures and activity in the selected DWDSs. Large-volume drinking water and hot water, biofilm, and water meter deposit samples were collected from five DWDSs. Total nucleic acids were extracted, and RNA was further purified and transcribed into its cDNA from a total of 181 water and biofilm samples originating from the DWDS of two surface water supplies (disinfected with UV and chlorine), two artificially recharged groundwater supplies (non-disinfected), and a groundwater supply (disinfected with UV and chlorine). In chlorinated DWDSs, concentrations of <0.02-0.97 mg/l free chlorine were measured. Bacterial communities in the RNA and DNA fractions were analysed using Illumina MiSeq sequencing with primer pair 341F-785R targeted to the 16S rRNA gene. The sequence libraries were analysed using QIIME pipeline, Program R, and MicrobiomeAnalyst. Not all bacterial cells were active based on their 16S rRNA content, and species richness was lower in the RNA fraction (Chao1 mean value 490) than in the DNA fraction (710). Species richness was higher in the two DWDSs distributing non-disinfected artificial groundwater (Chao1 mean values of 990 and 1 000) as compared to the two disinfected DWDSs using surface water (Chao1 mean values 190 and 460) and disinfected DWDS using ground water as source water (170). The difference in community structures between non-disinfected and disinfected water was clear in the beta-diversity analysis. Distance from the waterworks also affected the beta diversity of community structures, especially in disinfected distribution systems. The two most abundant bacteria in the active part of the community (RNA) and total bacterial community (DNA) belonged to the classes Alphaproteobacteria (RNA 28 %, DNA 44 %) and Gammaproteobacteria (RNA 32 %, DNA 30 %). The third most abundant and active bacteria class was Vampirovibrionia (RNA 15 %), whereas in the total community it was Paceibacteria (DNA 11 %). Class Nitrospiria was more abundant and active in both cold and hot water in DWDS that used chloramine disinfection compared to non-chlorinated or chlorine-using DWDSs. Thirty-eight operational taxonomic units (OTU) of Legionella, 30 of Mycobacterium, and 10 of Pseudomonas were detected among the sequences. The (RT)-qPCR confirmed the presence of opportunistic pathogens in the DWDSs studied as Legionella spp. was detected in 85 % (mean value 4.5 × 104 gene copies/100 ml), Mycobacterium spp. in 95 % (mean value 8.3 × 106 gene copies/100 ml), and Pseudomonas spp. in 78 % (mean value 1.6 × 105 gene copies/100 ml) of the water and biofilm samples. Sampling point inside the system (distance from the waterworks and cold/hot system) affected the active bacterial community composition. Chloramine as a chlorination method resulted in a recognizable community composition, with high abundance of bacteria that benefit from the excess presence of nitrogen. The results presented here confirm that each DWDS is unique and that opportunistic pathogens are present even in conditions when water quality is considered excellent.

Assessing residential activity in a home plumbing system simulator: monitoring the occurrence and relationship of major opportunistic pathogens and phagocytic amoebas.

Opportunistic premise plumbing pathogens (OPPPs) have been detected in buildings' plumbing systems causing waterborne disease outbreaks in the United States. In this study, we monitored the occurrence of OPPPs along with free-living amoeba (FLA) and investigated the effects of residential activities in a simulated home plumbing system (HPS). Water samples were collected from various locations in the HPS and analyzed for three major OPPPs: Legionella pneumophila, nontuberculous mycobacterial species (e.g., Mycobacterium avium, M. intracellulare, and M. abscessus), and Pseudomonas aeruginosa along with two groups of amoebas (Acanthamoeba and Vermamoeba vermiformis). A metagenomic approach was also used to further characterize the microbial communities. Results show that the microbial community is highly diverse with evidence of spatial and temporal structuring influenced by environmental conditions. L. pneumophila was the most prevalent pathogen (86% of samples), followed by M. intracellulare (66%) and P. aeruginosa (21%). Interestingly, M. avium and M. abscessus were not detected in any samples. The data revealed a relatively low prevalence of Acanthamoeba spp. (4%), while V. vermiformis was widely detected (81%) across all the sampling locations within the HPS. Locations with a high concentration of L. pneumophila and M. intracellulare coincided with the highest detection of V. vermiformis, suggesting the potential growth of both populations within FLA and additional protection in drinking water. After a period of stagnation lasting at least 2-weeks, the concentrations of OPPPs and amoeba immediately increased and then decreased gradually back to the baseline. Furthermore, monitoring the microbial population after drainage of the hot water tank and partial drainage of the entire HPS demonstrated no significant mitigation of the selected OPPPs. This study demonstrates that these organisms can adjust to their environment during such events and may survive in biofilms and/or grow within FLA, protecting them from stressors in the supplied water.

A comparative analysis employing a gene- and genome-centric metagenomic approach reveals changes in composition, function, and activity in waterworks with different treatment processes and source water in Finland.

The emergence and development of next-generation sequencing technologies (NGS) has made the analysis of the water microbiome in drinking water distribution systems (DWDSs) more accessible and opened new perspectives in microbial ecology studies. The current study focused on the characterization of the water microbiome employing a gene- and genome-centric metagenomic approach to five waterworks in Finland with different raw water sources, treatment methods, and disinfectant. The microbial communities exhibit a distribution pattern of a few dominant taxa and a large representation of low-abundance bacterial species. Changes in the community structure may correspond to the presence or absence and type of disinfectant residual which indicates that these conditions exert selective pressure on the microbial community. The Archaea domain represented a small fraction (up to 2.5%) and seemed to be effectively controlled by the disinfection of water. Their role particularly in non-disinfected DWDS may be more important than previously considered. In general, non-disinfected DWDSs harbor higher microbial richness and maintaining disinfectant residual is significantly important for ensuring low microbial numbers and diversity. Metagenomic binning recovered 139 (138 bacterial and 1 archaeal) metagenome-assembled genomes (MAGs) that had a >50% completeness and <10% contamination consisting of 20 class representatives in 12 phyla. The presence and occurrence of nitrite-oxidizing bacteria (NOB)-like microorganisms have significant implications for nitrogen biotransformation in drinking water systems. The metabolic and functional complexity of the microbiome is evident in DWDSs ecosystems. A comparative analysis found a set of differentially abundant taxonomic groups and functional traits in the active community. The broader set of transcribed genes may indicate an active and diverse community regardless of the treatment methods applied to water. The results indicate a highly dynamic and diverse microbial community and confirm that every DWDS is unique, and the community reflects the selection pressures exerted at the community structure, but also at the levels of functional properties and metabolic potential.

Comprehensive characterization of aerobic groundwater biotreatment media.

Aerobic biotreatment systems can treat multiple reduced inorganic contaminants in groundwater, including ammonia (NH3), arsenic (As), iron (Fe), and manganese (Mn). While individual systems treating multiple contaminants simultaneously have been characterized and several systems treating one contaminant have been compared, a comparison of systems treating co-occurring contaminants is lacking. This study assessed the treatment performance and microbial communities within 7 pilot- and full-scale groundwater biotreatment systems in the United States that treated waters with pH 5.6-7.8, 0.1-2.0 mg/L dissolved oxygen, 75-376 mg CaCO3/L alkalinity, < 0.03-3.79 mg NH3-N/L, < 4-31 µg As/L, < 0.01-9.37 mg Fe/L, 2-1220 µg Mn/L, and 0.1-5.6 mg/L total organic carbon (TOC). Different reactor configurations and media types were represented, allowing for a broad assessment of linkages between water quality and microbial communities via microscopy, biofilm quantification, and molecular methods. Influent NH3, TOC, and pH contributed to differences in the microbial communities. Mn oxidase gene copy numbers were slightly negatively correlated with the influent Mn concentration, but no significant relationships between gene copy number and influent concentration were observed for the other contaminants. Extracellular enzyme activities, community composition, and carbon transformation pathways suggested heterotrophic bacteria may be important in nitrifying biofilters. Aerobic groundwater biofilters are complex, and improved understanding could lead to engineering enhancements.

Depth profiles of biological aerated contactors: Characterizing microbial activity treating reduced contaminants.

The biological treatment process consisting of an aerated contactor and filter is effective for groundwaters containing elevated ammonia and other reduced contaminants, including iron, manganese, arsenic, and methane. Depth profiles characterizing microbial activity across aerated contactors are lacking. A 1-year pilot study comparing gravel- and ceramic-packed contactors was conducted, and media depth profile samples were collected at the conclusion of the study. Media and water samples also were collected from pilot-scale aerated contactors at 4 other water systems. Water quality, media surface metals concentrations, and a suite of biofilm parameters were analyzed. Media surface metals concentrations were greatest at the influent end. ATP concentrations, extracellular polymeric substances, and extracellular enzyme activities tended to be similar across depth. Bacteria and functional genes involved in contaminant oxidation co-occurred and tended to decrease across depth, but were not correlated to the media metals concentration. Microbial community composition changed with depth, and the diversity either decreased or remained similar. The microbial activity profiles through aerated contactors differed from what is typically reported for groundwater biofilters, suggesting that the different reactor flow and dissolved oxygen profiles impacted the microbial community.

Metagenomic Profile of Microbial Communities in a Drinking Water Storage Tank Sediment after Sequential Exposure to Monochloramine, Free Chlorine, and Monochloramine.

Sediment accumulation in drinking water storage facilities may lead to water quality degradation, including biological growth and disinfectant decay. The current research evaluated the microbiome present in a sediment after sequential exposure to monochloramine, free chlorine, and monochloramine. Chemical profiles within the sediment based on microelectrodes showed evidence of nitrification, and monochloramine slowly penetrated the sediment but was not measurable at lower depths. A metagenomic approach was used to characterize the microbial communities and functional potential of top (0-1 cm) and bottom (1-2 cm) layers in sediment cores. Differential abundance analysis revealed both an enrichment and depletion associated with depth of microbial populations. We assembled 30 metagenome-assembled genomes (MAGs) representing bacterial and archaeal microorganisms. Most metabolic functions were represented in both layers, suggesting the capability of the microbiomes to respond to environmental fluctuations. However, niche-specific abundance differences were identified in biotransformation processes (e.g., nitrogen). Metagenome-level analyses indicated that nitrification and denitrification can potentially occur simultaneously in the sediments, but the exact location of their occurrence within the sediment will depend on the localized physicochemical conditions. Even though monochloramine was maintained in the bulk water there was limited penetration into the sediment, and the microbial community remained functionally diverse and active.

Closed Genome and Plasmid Sequences of Legionella pneumophila AW-13-4, Isolated from a Hot Water Loop System of a Large Occupational Building.

Unused water in unoccupied buildings can become stagnant, with reductions in temperature and levels of disinfectant resulting in increased microbial growth. We report the closed and complete genome and plasmid of Legionella pneumophila strain AW-13-4 (serogroup 1), which was isolated from a hot water loop system of a large building.

Bacterial Genes Encoding Resistance Against Antibiotics and Metals in Well-Maintained Drinking Water Distribution Systems in Finland.

Information on the co-occurrence of antibiotic resistance genes (ARGs) and metal resistance genes (MRGs) among bacterial communities in drinking water distribution systems (DWDSs) is scarce. This study characterized ARGs and MRGs in five well-maintained DWDSs in Finland. The studied DWDSs had different raw water sources and treatment methods. Two of the waterworks employed artificially recharged groundwater (ARGW) and used no disinfection in the treatment process. The other three waterworks (two surface and one groundwater source) used UV light and chlorine during the treatment process. Ten bulk water samples (two from each DWDS) were collected, and environmental DNA was extracted and then sequenced using the Illumina HiSeq platform for high-throughput shotgun metagenome sequencing. A total of 430 ARGs were characterized among all samples with the highest diversity of ARGs identified from samples collected from non-disinfected DWDSs. Furthermore, non-disinfected DWDSs contained the highest diversity of bacterial communities. However, samples from DWDSs using disinfectants contained over double the ratio of ARG reads to 16S rRNA gene reads and most of the MRG (namely mercury and arsenic resistance genes). The total reads and types of ARGs conferring genes associated with antibiotic groups namely multidrug resistance, and bacitracin, beta-lactam, and aminoglycoside and mercury resistance genes increased in waterworks treating surface water with disinfection. The findings of this study contribute toward a comprehensive understanding of ARGs and MRGs in DWDSs. The occurrence of bacteria carrying antibiotic or metal resistance genes in drinking water causes direct exposure to people, and thus, more systematic investigation is needed to decipher the potential effect of these resistomes on human health.

Monitoring of Nitrification in Chloraminated Drinking Water Distribution Systems With Microbiome Bioindicators Using Supervised Machine Learning.

Many drinking water utilities in the United States using chloramine as disinfectant treatment in their drinking water distribution systems (DWDS) have experienced nitrification episodes, which detrimentally impact the water quality. Identification of potential predictors of nitrification in DWDS may be used to optimize current nitrification monitoring plans and ultimately helps to safeguard drinking water and public health. In this study, we explored the water microbiome from a chloraminated DWDS simulator operated through successive operational schemes of stable and nitrification events and utilized the 16S rRNA gene dataset to generate high-resolution taxonomic profiles for bioindicator discovery. Analysis of the microbiome revealed both an enrichment and depletion of various bacterial populations associated with nitrification. A supervised machine learning approach (naïve Bayes classifier) trained with bioindicator profiles (membership and structure) were used to classify water samples. Performance of each model was examined using the area under the curve (AUC) from the receiver-operating characteristic (ROC) and precision-recall (PR) curves. The ROC- and PR-AUC gradually increased to 0.778 and 0.775 when genus-level membership (i.e., presence and absence) was used in the model and increased significantly using structure (i.e., distribution) dataset (AUCs = 1.000, p < 0.01). Community structure significantly improved the predictive ability of the model beyond that of membership only regardless of the type of data (sequence- or taxonomy-based model) we used to represent the microbiome. In comparison, an ATP-based model (bulk biomass) generated a lower AUCs of 0.477 and 0.553 (ROC and PR, respectively), which is equivalent to a random classification. A combination of eight bioindicators was able to correctly classify 85% of instances (nitrification or stable events) with an AUC of 0.825 (sensitivity: 0.729, specificity: 0.894) on a full-scale DWDS test set. Abiotic-based model using total Chlorine/NH2Cl and NH3 generated AUCs of 0.740 and 0.861 (ROC and PR, respectively), corresponding to a sensitivity of 0.250 and a specificity of 0.957. The AUCs increased to > 0.946 with the addition of NO2 - concentration, which is indicative of nitrification in the DWDS. This research provides evidence of the feasibility of using bioindicators to predict operational failures in the system (e.g., nitrification).

Legionella Diversity and Spatiotemporal Variation in The Occurrence of Opportunistic Pathogens within a Large Building Water System.

Understanding Legionella survival mechanisms within building water systems (BWSs) is challenging due to varying engineering, operational, and water quality characteristics unique to each system. This study aimed to evaluate Legionella, mycobacteria, and free-living amoebae occurrence within a BWS over 18-28 months at six locations differing in plumbing material and potable water age, quality, and usage. A total of 114 bulk water and 57 biofilm samples were analyzed. Legionella culturability fluctuated seasonally with most culture-positive samples being collected during the winter compared to the spring, summer, and fall months. Positive and negative correlations between Legionella and L. pneumophila occurrence and other physiochemical and microbial water quality parameters varied between location and sample types. Whole genome sequencing of 19 presumptive Legionella isolates, from four locations across three time points, identified nine isolates as L. pneumophila serogroup (sg) 1 sequence-type (ST) 1; three as L. pneumophila sg5 ST1950 and ST2037; six as L. feeleii; and one as Ochrobactrum. Results showed the presence of a diverse Legionella population with consistent and sporadic occurrence at four and two locations, respectively. Viewed collectively with similar studies, this information will enable a better understanding of the engineering, operational, and water quality parameters supporting Legionella growth within BWSs.

Whole-Genome Sequencing of Four Campylobacter Strains Isolated from Gull Excreta Collected from Hobie Beach (Oxnard, CA, USA).

Campylobacter spp. are commensal organisms in avian species and are one of the leading causes of bacterial foodborne human diarrheal disease worldwide. We report the draft genome sequences of Campylobacter volucris, C. lari, and C. jejuni strains isolated from California gull (Larus californicus) excreta collected from a California beach.

Draft Genome Sequences of Antibiotic-Resistant Escherichia coli Isolates from U.S. Wastewater Treatment Plants.

The spread of antibiotic-resistant microorganisms is a major public health concern. Here, we report the draft genome sequences of three Escherichia coli isolates from primary effluent collected from geographically dispersed U.S. wastewater treatment plants (WWTPs). Genomic analysis confirms the presence of genes encoding resistance to a broad spectrum of antibiotics.

Draft Genome Sequences of Seven Legionella pneumophila Isolates from a Hot Water System of a Large Building.

Public health data show that a significant fraction of the nation's waterborne disease outbreaks are attributable to premise plumbing. We report the draft genome sequences of seven Legionella pneumophila serogroup 1 isolates from hot water lines of a large building. Genomic analysis identified the isolates as belonging to sequence type 1.

History of EPI Suite™ and future perspectives on chemical property estimation in US Toxic Substances Control Act new chemical risk assessments.

Chemical property estimation is a key component in many industrial, academic, and regulatory activities, including in the risk assessment associated with the approximately 1000 new chemical pre-manufacture notices the United States Environmental Protection Agency (US EPA) receives annually. The US EPA evaluates fate, exposure and toxicity under the 1976 Toxic Substances Control Act (amended by the 2016 Frank R. Lautenberg Chemical Safety for the 21st Century Act), which does not require test data with new chemical applications. Though the submission of data is not required, the US EPA has, over the past 40 years, occasionally received chemical-specific data with pre-manufacture notices. The US EPA has been actively using this and publicly available data to develop and refine predictive computerized models, most of which are housed in EPI Suite™, to estimate chemical properties used in the risk assessment of new chemicals. The US EPA develops and uses models based on (quantitative) structure-activity relationships ([Q]SARs) to estimate critical parameters. As in any evolving field, (Q)SARs have experienced successes, suffered failures, and responded to emerging trends. Correlations of a chemical structure with its properties or biological activity were first demonstrated in the late 19th century and today have been encapsulated in a myriad of quantitative and qualitative SARs. The development and proliferation of the personal computer in the late 20th century gave rise to a quickly increasing number of property estimation models, and continually improved computing power and connectivity among researchers via the internet are enabling the development of increasingly complex models.

Draft Genome Sequence of Mycobacterium chimaera Type Strain Fl-0169.

We report here the draft genome sequence of the type strain Mycobacterium chimaera Fl-0169, a member of the Mycobacterium avium complex (MAC). M. chimaera Fl-0169T was isolated from a patient in Italy and is highly similar to strains of M. chimaera isolated in Ireland, although Fl-0169T possesses unique virulence genes.

Effect of temperature and colonization of Legionella pneumophila and Vermamoeba vermiformis on bacterial community composition of copper drinking water biofilms.

It is unclear how the water-based pathogen, Legionella pneumophila (Lp), and associated free-living amoeba (FLA) hosts change or are changed by the microbial composition of drinking water (DW) biofilm communities. Thus, this study characterized the bacterial community structure over a 7-month period within mature (> 600-day-old) copper DW biofilms in reactors simulating premise plumbing and assessed the impact of temperature and introduction of Lp and its FLA host, Vermamoeba vermiformis (Vv), co-cultures (LpVv). Sequence and quantitative PCR (qPCR) analyses indicated a correlation between LpVv introduction and increases in Legionella spp. levels at room temperature (RT), while at 37°C, Lp became the dominant Legionella spp. qPCR analysis suggested Vv presence may not be directly associated with Lp biofilm growth at RT and 37°C, but may contribute to or be associated with non-Lp legionellae persistence at RT. Two-way PERMANOVA and PCoA revealed that temperature was a major driver of microbiome diversity. Biofilm community composition also changed over the seven-month period and could be associated with significant shifts in dissolved oxygen, alkalinity and various metals in the influent DW. Hence, temperature, biofilm age, DW quality and transient intrusions/amplification of pathogens and FLA hosts may significantly impact biofilm microbiomes and modulate pathogen levels over extended periods.

Draft Genome Sequence of Two Sphingopyxis sp. Strains, Dominant Members of the Bacterial Community Associated with a Drinking Water Distribution System Simulator.

We report the draft genomes of twoSphingopyxissp. strains isolated from a chloraminated drinking water distribution system simulator. Both strains are ubiquitous residents and early colonizers of water distribution systems. Genomic annotation identified a class 1 integron (intI1) gene associated with sulfonamide (sul1) and puromycin (pac) antibiotic resistance genes.

Draft Genome Sequences of Six Mycobacterium immunogenum Strains Obtained from a Chloraminated Drinking Water Distribution System Simulator.

We report here the draft genome sequences of six Mycobacterium immunogenum strains isolated from a chloraminated drinking water distribution system simulator subjected to changes in operational parameters. M. immunogenum, a rapidly growing mycobacterium previously reported to be the cause of hypersensitivity pneumonitis from contaminated metalworking fluid aerosols, is becoming a public health concern.

Whole-Genome Sequences of Four Strains Closely Related to Members of the Mycobacterium chelonae Group, Isolated from Biofilms in a Drinking Water Distribution System Simulator.

We report here the draft genome sequences of four Mycobacterium chelonae strains from biofilms subjected to a "chlorine burn" in a chloraminated drinking water distribution system simulator. These opportunistic pathogens have been detected in hospital and municipal water distribution systems, in which biofilms have been recognized as an important factor for their persistence.

Bacterial composition in a metropolitan drinking water distribution system utilizing different source waters.

We investigated the bacterial composition of water samples from two service areas within a drinking water distribution system (DWDS), each associated with a different primary source of water (groundwater, GW; surface water, SW) and different treatment process. Community analysis based on 16S rRNA gene clone libraries indicated that Actinobacteria (Mycobacterium spp.) and α-Proteobacteria represented nearly 43 and 38% of the total sequences, respectively. Sequences closely related to Legionella, Pseudomonas, and Vibrio spp. were also identified. In spite of the high number of sequences (71%) shared in both areas, multivariable analysis revealed significant differences between the GW and SW areas. While the dominant phylotypes where not significantly contributing in the ordination of samples, the populations associated with the core of phylotypes (1-10% in each sample) significantly contributed to the differences between both service areas. Diversity indices indicate that the microbial community inhabiting the SW area is more diverse and contains more distantly related species coexisting with local assemblages as compared with the GW area. The bacterial community structure of SW and GW service areas were dissimilar, suggesting that their respective source water and/or water quality parameters shaped by the treatment processes may contribute to the differences in community structure observed.