Combining physicochemical properties and microbiome data to evaluate the water quality of South African drinking water production plants

Comparative microbial metagenomic analysis of drinking water plants and wastewater treatment plants in Istanbul

Introduction

Wastewater treatment plants (WWTPs) and drinking-water treatment plants (DWTPs) are critical for public health due to the potential risks posed by microorganisms that may persist after treatment. The aim of this study was to detect the microbiome profiles of waters from both DWTPs and WWTPs under the Istanbul Water and Sewerage Administration (ISKI), identify the antimicrobial resistance profiles in all these facilities, and observe the differences in the microbiome between the inlet and outlet of different WWTPs.

Methods

A total of 52 samples were examined, comprising 18 samples from DWTPs and 34 samples from WWTPs. All water samples underwent pre-isolation filtration. DNA isolation was conducted using filter material, followed by sequencing on a NovaSeq 6000 instrument. Kraken2 tools and R scripts were used for statistical analysis and data visualization.

Results

The microbial metagenomic analysis identified 71 phyla, 113 classes, 217 orders, 480 families, and 1,282 genera across all samples. There were unclassified microbes (53.14% vs. 58.75%), Eukaryota (3.64% vs. 3.5%), Archaea (0.08% vs. 0.03%), bacteria (42% vs. 36.25%), and viruses (0.02% vs. 0.04%) in the raw water and ozonation unit outlet of DWTPs. The inlet and outlet of WWTPs showed unclassified microbes (52.68% vs. 59.62%), Eukaryota (0.6% vs. 1.72%), Archaea (0.26% vs. 0.15%), bacteria (46.43% vs. 38.43%), and viruses (0.05% vs. 0.04%). No statistically significant results were found in the analysis of raw waters collected from DWTPs and samples taken from the ozonation unit outlet-from the phylum level to the genus level (p > 0.05). The inlet and outlet points of WWTPs showed no statistically significant results from the phylum to species levels (p > 0.05). The most detected genera were Desulfobacter (4.82%) in preliminary WWTPs, Thauera (1.93%) in biological WWTPs, Pseudomonas (1.44%) in advanced biological WWTPs, Acidovorax (1.85%) in biological package WWTPs, and Pseudomonas (11.55%) in plant-based WWTPs. No antimicrobial resistance gene markers were detected in water samples from raw water inlets and ozonation unit outlets from DWTPs, membrane wastewater recovery plants, or ultraviolet (UV) recycling facilities. The ANT(3″), Erm, and Sul resistance gene markers were detected in all raw WWTPs samples.

Discussion

There were no significant microbial risk differentiation between biological WWTPs and advanced biological WWTPs. The data could serve as preliminary information for future research. More extensive studies are needed, with multiple sample tracking in these facilities and their feeding basins.

Distribution of antibiotic resistance genes and antibiotic residues in drinking water production facilities: Links to bacterial community

There is a rapid spread of antibiotic resistance in the environment. However, the impact of antibiotic resistance in drinking water is relatively underexplored. Thus, this study aimed to quantify antibiotic resistance genes (ARGs) and antibiotic residues in two drinking water production facilities (NW-E and NW-C) in North West Province, South Africa and link these parameters to bacterial communities. Physicochemical and ARG levels were determined using standard procedures. Residues (antibiotics and fluconazole) and ARGs were quantified using ultra-high performance liquid chromatography (UHPLC) chemical analysis and real-time PCR, respectively. Bacterial community compositions were determined by high-throughput 16S rRNA sequencing. Data were analysed using redundancy analysis and pairwise correlation. Although some physicochemical levels were higher in treated than in raw water, drinking water in NW-E and NW-C was safe for human consumption using the South African Water Quality Guideline (SAWQG). ARGs were detected in raw and treated water. In NW-E, the concentrations of ARGs (sul1, intl1, EBC, FOX, ACC and DHA) were higher in treated water than in raw water. Regarding antimicrobial agents, antibiotic and fluconazole concentrations were higher in raw than in treated water. However, in NW-C, trimethoprim concentrations were higher in raw than in treated water. Redundancy analysis showed that bacterial communities were not significantly correlated (Monte Carlo simulations, p-value >0.05) with environmental factors. However, pairwise correlation showed significant differences (p-value <0.05) for Armatimonas, CL500-29 marine group, Clade III, Dickeya and Zymomonas genera with environmental factors. The presence of ARGs and antibiotic residues in the current study indicated that antibiotic resistance is not only a clinical phenomenon but also in environmental settings, particularly in drinking water niches. Consumption of NW-E and NW-C treated water may facilitate the spread of antibiotic resistance among consumers. Thus, regulating and monitoring ARGs and antibiotic residues in drinking water production facilities should be regarded as paramount.

Occurrences and implications of pathogenic and antibiotic-resistant bacteria in different stages of drinking water treatment plants and distribution systems

Different stages of drinking water treatment plants (DWTPs) play specific roles in diverse contaminants' removal present in natural water sources. Although the stages are recorded to promote adequate treatment of water, the occurrence of pathogenic bacteria (PB) and antibiotic-resistant bacteria (ARB) in the treated water and the changes in their diversity and abundance as it passed down to the end users through the drinking water distribution systems (DWDSs), is a great concern, especially to human health. This could imply that the different stages and the distribution system provide a good microenvironment for their growth. Hence, it becomes pertinent to constantly monitor and document the diversity of PB and ARB present at each stage of the treatment and distribution system. This review aimed at documenting the occurrence of PB and ARB at different stages of treatment and distribution systems as well as the implication of their occurrence globally. An exhaustive literature search from Web of Science, Science-Direct database, Google Scholar, Academic Research Databases like the National Center for Biotechnology Information, Scopus, and SpringerLink was done. The obtained information showed that the different treatment stages and distribution systems influence the PB and ARB that proliferate. To minimize the human health risks associated with the occurrence of these PB, the present review, suggests the development of advanced technologies that can promote quick monitoring of PB/ARB at each treatment stage and distribution system as well as reduction of the cost of environomics analysis to promote better microbial analysis.

Characteristics of bacterial community and extracellular enzymes in response to atrazine application in black soil

The ecological functioning of black soil largely depends on the activities of various groups of microorganisms. However, little is known about how atrazine, a widely used herbicide with known harmful effects on the environment, influences the microbial ecology of black soil, and the extracellular enzymes related to the carbon, nitrogen and phosphorus cycles. Here, we evaluated the change in extracellular enzymes and bacterial community characteristics in black soil after exposure to various concentrations of atrazine. Low concentrations of applied atrazine (10 - 20 mg kg-1) were almost completely degraded after 120 days. At high concentrations (80 - 100 mg kg-1), about 95% of the applied atrazine was degraded over the same period. Additionally, linear fitting of data indicated that the total enzymatic activity index (TEI) and bacterial α-diversity index were negatively correlated with atrazine applied concentration. The atrazine had a greater effect on bacterial beta diversity after 120 days, which differentiated species clusters treated with low and high atrazine concentrations. Soil bacterial community structure and function were affected by atrazine, especially at high atrazine concentrations (80 - 100 mg kg-1). Key microorganisms such as Sphingomonas and Nocardioides were identified as biomarkers for atrazine dissipation. Functional prediction indicated that most metabolic pathways might be involved in atrazine dissipation. Overall, the findings enhance our understanding of the factors driving atrazine degradation in black soil and supports the use of biomarkers as indicators of atrazine dissipation.

In vitro genotoxic and mutagenic effects of water samples from Sapucaia and Esteio streams (Brazil) under the influence of different anthropogenic activities

Pollution of aquatic ecosystems is associated with the discharge of mainly industrial and urban effluents, which may cause damage to public health. This study aims to evaluate the cytotoxic, genotoxic, and mutagenic potential of surface water samples under the influence of different anthropogenic effluents in a human-derived liver cell line (HepG2). Samples were collected in Esteio and Sapucaia streams (Rio Grande do Sul; Brazil), which flow into the Sinos River, a source of water supply for more than one million people. Physicochemical and microbiological analyses were performed as well as an analysis of inorganic elements using the PIXE technique (Particle-Induced X-Ray Emission). The presence of pharmaceutical compounds and caffeine was evaluated by gas chromatography coupled to mass spectrometry. The cytotoxicity, genotoxicity, and mutagenicity of the samples were evaluated in HepG2 cells by cell viability assays, alkaline Comet Assay and Cytokinesis-block micronucleus (CBMN) assay. We verified alterations in the physicochemical and microbiological parameters and detected caffeine, diethyltoluamide, and different inorganic elements that corresponded to elements from domestic and industrial effluents and agricultural runoff. Although the samples in the concentration used were not cytotoxic, water samples from all sites induced DNA damage. However, it is difficult to attribute these damages to a specific substance since the factors are a complex mixture of different compounds. Despite this, it is observed that both urban and industrial contributions had a similar effect in the cells evaluated. Such results demonstrate the need to perform biomonitoring of surface waters under anthropogenic influence, especially those that flow into rivers that are a source of public supply water. We also highlight the need for research into emerging pollutants in these aquatic environments.

Clean and Safe Drinking Water Systems via Metagenomics Data and Artificial Intelligence: State-of-the-Art and Future Perspective

The use of next-generation sequencing technologies in drinking water distribution systems (DWDS) has shed insight into the microbial communities' composition, and interaction in the drinking water microbiome. For the past two decades, various studies have been conducted in which metagenomics data have been collected over extended periods and analyzed spatially and temporally to understand the dynamics of microbial communities in DWDS. In this literature review, we outline the findings which were reported in the literature on what kind of occupancy-abundance patterns are exhibited in the drinking water microbiome, how the drinking water microbiome dynamically evolves spatially and temporally in the distribution networks, how different microbial communities co-exist, and what kind of clusters exist in the drinking water ecosystem. While data analysis in the current literature concerns mainly with confirmatory and exploratory questions pertaining to the use of metagenomics data for the analysis of DWDS microbiome, we present also future perspectives and the potential role of artificial intelligence (AI) and mechanistic models to address the predictive and mechanistic questions. The integration of meta-omics, AI, and mechanistic models transcends metagenomics into functional metagenomics, enabling deterministic understanding and control of DWDS for clean and safe drinking water systems of the future.

Metagenomic analysis of bacterial communities of Wadi Namar Lake, Riyadh, Saudi Arabia

Wadi Namar lake is a new touristic attraction area in the south of Riyadh. Human activities around the lake may lead to changes in water quality with subsequent changes in microenvironment components including microbial diversity. The current study was designed to assess possible changes in bacterial communities of the water at Wadi Namar Lake. Therefore, water samples were collected from three different locations along the lake: L1 (no human activities, no plants), L2 (no human activity, some plants) and L3 (human activities, municipal wastes and some plants). The total DNA of the samples was extracted and subjected to 16S rDNA sequencing and metagenomic analysis; water pH, electrical conductivity (EC), total dissolved solids (TDS) as well as the concentration of Na+1, K+1, Cl-1 and total N were analysed. Metagenomic analysis showed variations in relative abundance of 17 phyla, 31 families, 43 genera and 19 species of bacteria between the locations. Proteobacteria was the most abundant phylum in all locations; however, its highest abundance was in L1. Planctomycete phylum was highly abundant in L1 and L3, while its abundance in L2 was low. The phyla Acidobacteria, Candidatus Saccharibacteria, Nitrospirae and Chloroflexi were associated with high TDS, EC, K+1 and Cl-1 concentrations in L3; various human activities around this location had possibly affected microbial diversity. Current study results help in recognising the structure of bacterial communities at Wadi Namar Lake in relation to their surroundings for planning to environment protection and future restoration of affected ecosystems.

Inferring microbiota functions from taxonomic genes: a review

Deciphering microbiota functions is crucial to predict ecosystem sustainability in response to global change. High-throughput sequencing at the individual or community level has revolutionized our understanding of microbial ecology, leading to the big data era and improving our ability to link microbial diversity with microbial functions. Recent advances in bioinformatics have been key for developing functional prediction tools based on DNA metabarcoding data and using taxonomic gene information. This cheaper approach in every aspect serves as an alternative to shotgun sequencing. Although these tools are increasingly used by ecologists, an objective evaluation of their modularity, portability, and robustness is lacking. Here, we reviewed 100 scientific papers on functional inference and ecological trait assignment to rank the advantages, specificities, and drawbacks of these tools, using a scientific benchmarking. To date, inference tools have been mainly devoted to bacterial functions, and ecological trait assignment tools, to fungal functions. A major limitation is the lack of reference genomes-compared with the human microbiota-especially for complex ecosystems such as soils. Finally, we explore applied research prospects. These tools are promising and already provide relevant information on ecosystem functioning, but standardized indicators and corresponding repositories are still lacking that would enable them to be used for operational diagnosis.

Soil bacterial community dynamics following bioaugmentation with Paenarthrobacter sp. W11 in atrazine-contaminated soil

Atrazine is one of the most widely used herbicides, however it and its metabolites cause widespread contamination in soil and ground water. Bioaugmentation is an effective method for remediation of environmental organic pollutants. High-throughput sequencing provides an important tool for understanding the changes of microbial community and function in response to pollutants degradation based on bioaugmentation. In this study, the effect of biodegradation with Paenarthrobacter sp. W11 and the change of microbial community during atrazine degradation were investigated. The results showed that bioaugmentation significantly accelerated the degradation rate of atrazine in soil and reduced the toxic effect of atrazine residues on wheat growth. The extra available NH₄⁺ through atrazine mineralization could serve as a nitrogen source to increase microbial numbers. High-throughput sequencing further revealed that the microbial community restored a new balance. The function of microbial community predicted by PICRUSt2 suggested that the biodegradation process of atrazine affected not only the atrazine degradation pathway, but also the nitrogen metabolism pathway. Methylobacillus and Pseudomonas were considered as the most important indigenous atrazine-degrading microorganisms, because their relative abundances were positively correlated with the relative abundance of Paenarthrobacter and atrazine degradation pathway. This study provides insight into the cooperation between indigenous microorganisms and external inoculums on atrazine degradation process.

Impact of the aquatic pathobiome in low-income and middle-income countries (LMICs) quest for safe water and sanitation practices

Microbial contamination of surface waters is of particular relevance in low-income and middle-income countries (LMICs) since they often represent the only available source of water for drinking and domestic use. In the recent years, a growing urbanization, profound demographic shifts and drastic climate events have greatly affected LMICs capacity to reach access to safe drinking water and sanitation practices, and to protect citizens' health from risks associated to the exposure and use of contaminated water. Detailed phylogenetic and microbiological information on the exact composition of pathogenic organisms in urban and peri-urban water is scarce, especially in rapidly changing settings of sub-Saharan Africa. In this review we aim to highlight how large-scale water pathobiome studies can support the LMICs challenge to global access to safe water and sanitation practices.

Environmental antimicrobial resistance is associated with faecal pollution in Central Thailand's coastal aquaculture region

We assessed antimicrobial resistance (AMR) potential to seven major classes of antibiotics in Central Thailand's coastal aquaculture region using high-throughput qPCR targeting 295 antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs). In parallel, we used MinION next generation sequencing (NGS) of 16S rRNA gene amplicons, qPCR of faecal pollution makers, and conventional plate count methods for the comprehensive characterization of environmental microbiomes. We tested the hypothesis that aquaculture increases environmental AMR by comparing ARGs and MGEs in water and sediment samples from five aquaculture sites and their associated canals. There was no evidence from the ARG and MGE data that aquaculture is a major driver of environmental AMR in Central Thailand. Instead, the highest relative prevalence of resistance traits was found in Hua Krabue canal water influenced by urban pollution from Bangkok at the inland edge of the coastal aquaculture region. The sum of ARGs and MGEs, relative to 16S rRNA genes used as markers for overall bacterial abundance, was between 0.495 ± 0.011 and 0.498 ± 0.013 in Hua Krabue canal water, compared with at most 0.132 ± 0.005 in all the other environmental samples. Corresponding patterns were observed for most faecal pollution markers, which were also elevated in Hua Krabue canal water.