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.
Bacteriophage control of harmful or pathogenic bacteria has aroused growing interest, largely due to the rise of antibiotic resistance. The objective of this study was to test phages as potential ...agents for the biocontrol of an opportunistic pathogen Pseudomonas aeruginosa in water. Two P. aeruginosa bacteriophages (vB_PaeM_V523 and vB_PaeM_V524) were isolated from wastewater and characterized physically and functionally. Genomic and morphological characterization showed that both were myoviruses within the Pbunavirus genus. Both had a similar latent period (50–55 min) and burst size (124–134 PFU/infected cell), whereas there was variation in the host range. In addition to these environmental phages, a commercial Pseudomonas phage, JG003 (DSM 19870), was also used in the biocontrol experiments. The biocontrol potential of the three phages in water was tested separately and together as a cocktail against two P. aeruginosa strains; PAO1 and the environmental strain 17V1507. With PAO1, all phages initially reduced the numbers of the bacterial host, with phage V523 being the most efficient (>2.4 log10 reduction). For the environmental P. aeruginosa strain (17V1507), only the phage JG003 caused a reduction (1.2 log10) compared to the control. The cocktail of three phages showed a slightly higher decrease in the level of the hosts compared to the use of individual phages. Although no synergistic effect was observed in the host reduction with the use of the phage cocktail, the cocktail-treated hosts did not appear to acquire resistance as rapidly as hosts treated with a single phage. The results of this study provide a significant step in the development of bacteriophage preparations for the control of pathogens and harmful microbes in water environments.
In this study, we evaluated the use of RT-qPCR assays targeting rRNA gene sequences for the detection of fecal bacteria in water samples. We challenged the RT-qPCR assays against RNA extracted from ...sewage effluent (n = 14), surface water (n = 30), and treated source water (n = 15) samples. Additionally, we applied the same assays using DNA as the qPCR template. The targeted fecal bacteria were present in most of the samples tested, although in several cases, the detection frequency increased when RNA was used as the template. For example, the majority of samples that tested positive for E. coli and Campylobacter spp. in surface waters, and for human-specific Bacteroidales, E. coli, and Enterococcus spp. in treated source waters were only detected when rRNA was used as the original template. The difference in detection frequency using rRNA or rDNA (rRNA gene) was sample- and assay-dependent, suggesting that the abundance of active and nonactive populations differed between samples. Statistical analyses for each population exhibiting multiple quantifiable results showed that the rRNA copy numbers were significantly higher than the rDNA counterparts (p < 0.05). Moreover, the detection frequency of rRNA-based assays were in better agreement with the culture-based results of E. coli, intestinal enterococci, and thermotolerant Campylobacter spp. in surface waters than that of rDNA-based assays, suggesting that rRNA signals were associated to active bacterial populations. Our data show that using rRNA-based approaches significantly increases detection sensitivity for common fecal bacteria in environmental waters. These findings have important implications for microbial water quality monitoring and public health risk assessments.
Abstract
Background
Rivers and lakes are used for multiple purposes such as for drinking water (DW) production, recreation, and as recipients of wastewater from various sources. The deterioration of ...surface water quality with wastewater is well-known, but less is known about the bacterial community dynamics in the affected surface waters. Understanding the bacterial community characteristics —from the source of contamination, through the watershed to the DW production process—may help safeguard human health and the environment.
Results
The spatial and seasonal dynamics of bacterial communities, their predicted functions, and potential health-related bacterial (PHRB) reads within the Kokemäenjoki River watershed in southwest Finland were analyzed with the 16S rRNA-gene amplicon sequencing method. Water samples were collected from various sampling points of the watershed, from its major pollution sources (sewage influent and effluent, industrial effluent, mine runoff) and different stages of the DW treatment process (pre-treatment, groundwater observation well, DW production well) by using the river water as raw water with an artificial groundwater recharge (AGR).
The beta-diversity analysis revealed that bacterial communities were highly varied among sample groups (R = 0.92,
p
< 0.001, ANOSIM). The species richness and evenness indices were highest in surface water (Chao1; 920 ± 10) among sample groups and gradually decreased during the DW treatment process (DW production well; Chao1: 320 ± 20). Although the phylum
Proteobacteria
was omnipresent, its relative abundance was higher in sewage and industrial effluents (66–80%) than in surface water (55%). Phyla
Firmicutes
and
Fusobacteria
were only detected in sewage samples.
Actinobacteria
was more abundant in the surface water (≥13%) than in other groups (≤3%).
Acidobacteria
was more abundant in the DW treatment process (≥13%) than in others (≤2%). In total, the share of PHRB reads was higher in sewage and surface water than in the DW treatment samples. The seasonal effect in bacterial communities was observed only on surface water samples, with the lowest diversity during summer.
Conclusions
The low bacterial diversity and absence of PHRB read in the DW samples indicate AGR can produce biologically stable and microbiologically safe drinking water. Furthermore, the significantly different bacterial communities at the pollution sources compared to surface water and DW samples highlight the importance of effective wastewater treatment for protecting the environment and human health.
Eukaryotes are ubiquitous in natural environments such as soil and freshwater. Little is known of their presence in drinking water distribution systems (DWDSs) or of the environmental conditions that ...affect their activity and survival.
Eukaryotes were characterized by Illumina high-throughput sequencing targeting 18S rRNA gene (DNA) that estimates the total community and the 18S rRNA gene transcript (RNA) that is more representative of the active part of the community. DWDS cold water (N = 124), hot water (N = 40), and biofilm (N = 16) samples were collected from four cities in Finland. The sampled DWDSs were from two waterworks A-B with non-disinfected, recharged groundwater as source water and from three waterworks utilizing chlorinated water (two DWDSs of surface waterworks C-D and one of ground waterworks E). In each DWDS, samples were collected from three locations during four seasons of 1 year.
A beta-diversity analysis revealed that the main driver shaping the eukaryotic communities was the DWDS (A-E) (R = 0.73, P < 0.001, ANOSIM). The kingdoms Chloroplastida (green plants and algae), Metazoa (animals: rotifers, nematodes), Fungi (e.g., Cryptomycota), Alveolata (ciliates, dinoflagellates), and Stramenopiles (algae Ochrophyta) were well represented and active-judging based on the rRNA gene transcripts-depending on the surrounding conditions. The unchlorinated cold water of systems (A-B) contained a higher estimated total number of taxa (Chao1, average 380-480) than chlorinated cold water in systems C-E (Chao1 ≤ 210). Within each DWDS, unique eukaryotic communities were identified at different locations as was the case also for cold water, hot water, and biofilms. A season did not have a consistent impact on the eukaryotic community among DWDSs.
This study comprehensively characterized the eukaryotic community members within the DWDS of well-maintained ground and surface waterworks providing good quality water. The study gives an indication that each DWDS houses a unique eukaryotic community, mainly dependent on the raw water source and water treatment processes in place at the corresponding waterworks. In particular, disinfection as well as hot water temperature seemed to represent a strong selection pressure that controlled the number of active eukaryotic species.
•Archaea-specific primers in high-throughput sequencing found archaea reads.•Archaea community with DNA-based analysis was different from RNA-based analysis.•Archaea are a natural part of microbiomes ...in drinking water distribution systems.•Active archaea reads were high in non-disinfected and cold distribution systems.
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The knowledge about the members of active archaea communities in DWDS is limited. The current understanding is based on high-throughput 16S ribosomal RNA gene (DNA-based) amplicon sequencing that reveals the diversity of active, dormant, and dead members of the prokaryote (bacteria, archaea) communities. The sequencing primers optimized for bacteria community analysis may underestimate the share of the archaea community. This study characterized archaea communities at five full-scale drinking water distribution systems (DWDS), representing a variety of drinking water production units (A-E); A&B use artificially recharged non-disinfected groundwater (ARG), the other DWDS's supplied water disinfected by using ultraviolet (UV) light and chlorine compounds, C&D were surface waterworks and E was a ground waterworks. For the first time for archaea community analyses, this study employed the archaea-specific high-throughput sequencing primers for 16S ribosomal RNA (rRNA) as a target (reverse-transcribed cDNA; an RNA-based approach) in addition to the previously used 16S rRNA gene target (rDNA; a DNA-based approach) to reveal the active fraction of the archaea present in DWDS. The archaea community structure in varying environmental conditions in the water and biofilm of the five DWDSs were investigated by taking into consideration the system properties (cold or hot water system) and water age (distance from the treatment plants) in samples from each season of one year.
The RNA-based archaea amplicon reads were obtained mostly from cold water samples from DWDSs (A–B) distributing water without disinfection where the DNA-based and RNA-based analysis created separate clusters in a weighted beta-diversity analysis. The season and location in DWDS A further affected the diversity of these archaea communities as was seen by different clusters in beta-diversity plots. The recovery of archaea reads was not adequate for analysis in any of the disinfected samples in DWDSs C–E or non-disinfected hot water in DWDSs A–B when utilizing RNA-based template. The metabolically active archaea community of DWDSs thus seemed to be effectively controlled by disinfection of water and in the hot water systems by the temperature. All biofilms regardless of DWDS showed lower species richness values (mainly Nitrososphaeria class) than non-disinfected water from DWDSs A–B where several archaea classes occurred (e.g. Woesearchaeia, Nitrososphaeria, Micrarchaeia, Methanomicrobia, Iairchaeia, Bathyarchaeia) indicating only part of the archaea members were able to survive in biofilms. Thus, Archaea has been shown as a significant part of normal DWDS biota, and their role especially in non-disinfected DWDS may be more important than previously considered.
Failures in the drinking water distribution system cause gastrointestinal outbreaks with multiple pathogens. A water distribution pipe breakage caused a community-wide waterborne outbreak in Vuorela, ...Finland, July 2012. We investigated this outbreak with advanced epidemiological and microbiological methods. A total of 473/2931 inhabitants (16%) responded to a web-based questionnaire. Water and patient samples were subjected to analysis of multiple microbial targets, molecular typing and microbial community analysis. Spatial analysis on the water distribution network was done and we applied a spatial logistic regression model. The course of the illness was mild. Drinking untreated tap water from the defined outbreak area was significantly associated with illness (RR 5.6, 95% CI 1.9-16.4) increasing in a dose response manner. The closer a person lived to the water distribution breakage point, the higher the risk of becoming ill. Sapovirus, enterovirus, single Campylobacter jejuni and EHEC O157:H7 findings as well as virulence genes for EPEC, EAEC and EHEC pathogroups were detected by molecular or culture methods from the faecal samples of the patients. EPEC, EAEC and EHEC virulence genes and faecal indicator bacteria were also detected in water samples. Microbial community sequencing of contaminated tap water revealed abundance of Arcobacter species. The polyphasic approach improved the understanding of the source of the infections, and aided to define the extent and magnitude of this outbreak.
•Each of the five waterworks harbors a distinct and diverse microbiome.•Occurrence and type of disinfectant exert selective pressure on the microbiome.•The archaea domain represents a small fraction ...of the prokaryote community.•Variable proportions of metabolic processes suggest different living strategies.•Broad set of transcribed genes and functional traits indicate an active community.
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.
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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 × 10
gene copies/100 ml), Mycobacterium spp. in 95 % (mean value 8.3 × 10
gene copies/100 ml), and Pseudomonas spp. in 78 % (mean value 1.6 × 10
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.
Waterborne disease outbreaks are a persistent and serious threat to public health according to reported incidents across the globe. Online drinking water quality monitoring technologies have evolved ...substantially and have become more accurate and accessible. However, using online measurements alone is unsuitable for detecting microbial regrowth, potentially including harmful species, ahead of time in the distribution systems. Alternatively, observational data could be collected periodically, e.g. once per week or once per month and it could include a representative set of variables: physicochemical water characteristics, disinfectant concentrations, and bacterial abundances, which would be a valuable source of knowledge for predictive modelling that aims to reveal pathogen-related threats. In this study, we utilised data collected from a pilot-scale drinking water distribution system. A data-driven random forest model was used for predictive modelling and was trained for nowcasting and forecasting abundances of bacterial groups. In all the experiments, we followed the realistic crossline scenario, which means that when training and testing the models the data is collected from different pipelines. In spite of the more accurate results of the nowcasting, the 1-week forecasting still provided accurate predictions of the most abundant bacteria, their rapid increase and decrease. In the future predictive modelling might be used as a tool in designing control measures for opportunistic pathogens which are able to multiply in the favourable conditions in drinking water distribution systems (DWDS). Eventually, the forecasting information will be able to produce practically helpful data for controlling the DWDS regrowth.
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•Data was collected in a pilot-scale drinking water distribution system.•Random forest regression was trained to predict abundances of bacterial groups.•The pipe material and disinfection matter when selecting samples for modelling.•In 1-week forecasting, Rhizobiales and Pseudanabaenales were accurately predicted.•Water pH, temperature, and copper concentration were the most important predictors.
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