Bacterial composition in Swedish raw drinking water reveals three major interacting ubiquitous metacommunities

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.

Upstream land use with microbial downstream consequences: Iron and humic substances link to Legionella spp

Intensified land use can disturb water quality, potentially increasing the abundance of bacterial pathogens, threatening public access to clean water. This threat involves both direct contamination of faecal bacteria as well as indirect factors, such as disturbed water chemistry and microbiota, which can lead to contamination. While direct contamination has been well described, the impact of indirect factors is less explored, despite the potential of severe downstream consequences on water supply. To assess direct and indirect downstream effects of buildings, farms, pastures and fields on potential water sources, we studied five Swedish lakes and their inflows. We analysed a total of 160 samples in a gradient of anthropogenic activity spanning four time points, including faecal and water-quality indicators. Through species distribution modelling, Random Forest and network analysis using 16S rRNA amplicon sequencing data, our findings highlight that land use indirectly impacts lakes via inflows. Land use impacted approximately one third of inflow microbiota taxa, in turn impacting ∼20-50 % of lake taxa. Indirect effects via inflows were also suggested by causal links between e.g. water colour and lake bacterial taxa, where this influenced the abundance of several freshwater bacteria, such as Polynucleobacter and Limnohabitans. However, it was not possible to identify direct effects on the lakes based on analysis of physiochemical- or microbial parameters. To avoid potential downstream consequences on water supply, it is thus important to consider possible indirect effects from upstream land use and inflows, even when no direct effects can be observed on lakes. Legionella (a genus containing bacterial pathogens) illustrated potential consequences, since the genus was particularly abundant in inflows and was shown to increase by the presence of pastures, fields, and farms. The approach presented here could be used to assess the suitability of lakes as alternative raw water sources or help to mitigate contaminations in important water catchments. Continued broad investigations of stressors on the microbial network can identify indirect effects, avoid enrichment of pathogens, and help secure water accessibility.