What is the Difference between Conventional Drinking Water, Potable Reuse Water, and Nonpotable Reuse Water? A Microbiome Perspective.

As water reuse applications expand, there is a need for more comprehensive means to assess water quality. Microbiome analysis could provide the ability to supplement fecal indicators and pathogen profiling toward defining a "healthy" drinking water microbiota while also providing insight into the impact of treatment and distribution. Here, we utilized 16S rRNA gene amplicon sequencing to identify signature features in the composition of microbiota across a wide spectrum of water types (potable conventional, potable reuse, and nonpotable reuse). A clear distinction was found in the composition of microbiota as a function of intended water use (e.g., potable vs nonpotable) across a very broad range of U.S. water systems at both the point of compliance (Betadisper p > 0.01; ANOSIM p < 0.01, r-stat = 0.71) and point of use (Betadisper p > 0.01; ANOSIM p < 0.01, r-stat = 0.41). Core and discriminatory analysis further served in identifying distinct differences between potable and nonpotable water microbiomes. Taxa were identified at both the phylum (Desulfobacterota, Patescibacteria, and Myxococcota) and genus (Aeromonas and NS11.12_marine_group) levels that effectively discriminated between potable and nonpotable waters, with the most discriminatory taxa being core/abundant in nonpotable waters (with few exceptions, such as Ralstonia being abundant in potable conventional waters). The approach and findings open the door to the possibility of microbial community signature profiling as a water quality monitoring approach for assessing efficacy of treatments and suitability of water for intended use/reuse application.

Relating microbial community composition to treatment performance in an ozone-biologically active carbon filtration potable reuse treatment train.

Treatment trains that couple ozone (O3) with biologically active carbon (BAC) filtration are of interest as a lower cost, more sustainable, membrane-free approach to water reuse. However, little is known about the microbial communities that are the fundamental drivers of O3-BAC treatment. The objective of this study was to demonstrate microbial community profiling as a diagnostic tool for assessing the functionality, biological stability, and resilience of coupled physical, chemical, advanced oxidative and biological processes employed in water reuse treatment. We utilized 16S rRNA gene amplicon sequencing to profile the bacterial microbiota over time throughout a potable reuse train employing coagulation, flocculation, sedimentation, ozonation, BAC filtration, granular activated carbon (GAC) adsorption, and UV disinfection. A distinct baseline microbiota was associated with each stage of treatment (ANOSIM, p < 0.05, r-stat = 0.52), each undergoing succession with time and operational shifts. Ozonation resulted in the sharpest shifts (i.e., 83.3 % average change in Genus level relative abundances, when adjusted O3:TOC ratio > 1), and also variance, in microbial community composition. Adjustment in O3:TOC ratios, temperature, filter-aid polymer, monochloramine quenching agent, and empty-bed contact time also resulted in measurable changes in the baseline microbial community composition of individual processes, but to a lesser degree. Of these, supplementation of nitrogen and phosphorus resulted in the strongest bifurcation, especially in the microbial communities inhabiting the BAC (ANOSIM: p < 0.05, BAC5 r-stat = 0.32; BAC10 r-stat = 0.54) and GAC (ANOSIM: p < 0.05, GAC10 r-stat = 0.54; GAC20 r-stat = 0.63) units. Additionally, we found that the BAC microbial community was responsive to an inoculation of microbially active media, which resulted in improved TOC removal. The findings of this study improve understanding of bacterial dynamics occurring in advanced water treatment trains and can inform improved system design and operation.

Demonstrating a Comprehensive Wastewater-Based Surveillance Approach That Differentiates Globally Sourced Resistomes.

Wastewater-based surveillance (WBS) for disease monitoring is highly promising but requires consistent methodologies that incorporate predetermined objectives, targets, and metrics. Herein, we describe a comprehensive metagenomics-based approach for global surveillance of antibiotic resistance in sewage that enables assessment of 1) which antibiotic resistance genes (ARGs) are shared across regions/communities; 2) which ARGs are discriminatory; and 3) factors associated with overall trends in ARGs, such as antibiotic concentrations. Across an internationally sourced transect of sewage samples collected using a centralized, standardized protocol, ARG relative abundances (16S rRNA gene-normalized) were highest in Hong Kong and India and lowest in Sweden and Switzerland, reflecting national policy, measured antibiotic concentrations, and metal resistance genes. Asian versus European/US resistomes were distinct, with macrolide-lincosamide-streptogramin, phenicol, quinolone, and tetracycline versus multidrug resistance ARGs being discriminatory, respectively. Regional trends in measured antibiotic concentrations differed from trends expected from public sales data. This could reflect unaccounted uses, captured only by the WBS approach. If properly benchmarked, antibiotic WBS might complement public sales and consumption statistics in the future. The WBS approach defined herein demonstrates multisite comparability and sensitivity to local/regional factors.