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Intensifying urbanization and human activities have dramatically increased global wastewater generation, creating complex microbial ecosystems that significantly impact environmental and public health. This study presents the first large-scale, comprehensive characterization of bacterial and viral communities in wastewater treatment systems worldwide. By analyzing samples from diverse geographical, climatic, and socioeconomic contexts, we reveal how wastewater microbiomes serve as microbial fingerprints of human society, reflecting regional characteristics while maintaining functional conservation. Our findings demonstrate that these communities function as ecological extensions of human gut microbiota in the external environment, with important implications for the spread of antibiotic resistance and pathogens. The identification of viruses as key metabolic regulators in these systems provides new perspectives on microbial community dynamics. This global-scale analysis advances our understanding of wastewater microbiology and offers valuable insights for improving wastewater management, enhancing environmental monitoring systems, and strengthening public health surveillance through wastewater-based epidemiology.

Background The interconnectivities of built and natural environments can serve as conduits for the proliferation and dissemination of antibiotic resistance genes (ARGs). Several studies have compared the broad spectrum of ARGs (i.e., “resistomes”) in various environmental compartments, but there is a need to identify unique ARG occurrence patterns (i.e., “discriminatory ARGs”), characteristic of each environment. Such an approach will help to identify factors influencing ARG proliferation, facilitate development of relative comparisons of the ARGs distinguishing various environments, and help pave the way towards ranking environments based on their likelihood of contributing to the spread of clinically relevant antibiotic resistance. Here we formulate and demonstrate an approach using an extremely randomized tree (ERT) algorithm combined with a Bayesian optimization technique to capture ARG variability in environmental samples and identify the discriminatory ARGs. The potential of ERT for identifying discriminatory ARGs was first evaluated using in silico metagenomic datasets (simulated metagenomic Illumina sequencing data) with known variability. The application of ERT was then demonstrated through analyses using publicly available and in-house metagenomic datasets associated with (1) different aquatic habitats (e.g., river, wastewater influent, hospital effluent, and dairy farm effluent) to compare resistomes between distinct environments and (2) different river samples (i.e., Amazon, Kalamas, and Cam Rivers) to compare resistome characteristics of similar environments. Results The approach was found to readily identify discriminatory ARGs in the in silico datasets. Also, it was not found to be biased towards ARGs with high relative abundance, which is a common limitation of feature projection methods, and instead only captured those ARGs that elicited significant profiles. Analyses of publicly available metagenomic datasets further demonstrated that the ERT approach can effectively differentiate real-world environmental samples and identify discriminatory ARGs based on pre-defined categorizing schemes. Conclusions Here a new methodology was formulated to characterize and compare variances in ARG profiles between metagenomic data sets derived from similar/dissimilar environments. Specifically, identification of discriminatory ARGs among samples representing various environments can be identified based on factors of interest. The methodology could prove to be a particularly useful tool for ARG surveillance and the assessment of the effectiveness of strategies for mitigating the spread of antibiotic resistance. The python package is hosted in the Git repository: https://github.com/gaarangoa/ExtrARG

This study emphasizes the critical role of wastewater treatment plants (WWTPs) in facilitating the horizontal transfer of ARGs through biosolids. As biosolids are routinely applied to agricultural soils, their load of clinically relevant ARG content and transferability pose risks to animal and human health through plant-associated bacteria or surface water. By identifying conserved ARG-MGE associations across diverse plasmid types and WWTPs, this work highlights the global and persistent nature of resistance dissemination. These findings underscore the urgent need for sustainable management practices to limit the spread of antimicrobial-resistant bacteria (ARB) and associated ARGs in agricultural ecosystems. Ensuring safe biosolid use will contribute to combating antimicrobial resistance gene connectivity from environmental to human- or animal-associated bacteria globally.

Microbial communities are responsible for biological wastewater treatment, but our knowledge of their diversity and function is still poor. Here, we sequence more than 5 million high-quality, full-length 16S rRNA gene sequences from 740 wastewater treatment plants (WWTPs) across the world and use the sequences to construct the ‘MiDAS 4’ database. MiDAS 4 is an amplicon sequence variant resolved, full-length 16S rRNA gene reference database with a comprehensive taxonomy from domain to species level for all sequences. We use an independent dataset (269 WWTPs) to show that MiDAS 4, compared to commonly used universal reference databases, provides a better coverage for WWTP bacteria and an improved rate of genus and species level classification. Taking advantage of MiDAS 4, we carry out an amplicon-based, global-scale microbial community profiling of activated sludge plants using two common sets of primers targeting regions of the 16S rRNA gene, revealing how environmental conditions and biogeography shape the activated sludge microbiota. We also identify core and conditionally rare or abundant taxa, encompassing 966 genera and 1530 species that represent approximately 80% and 50% of the accumulated read abundance, respectively. Finally, we show that for well-studied functional guilds, such as nitrifiers or polyphosphate-accumulating organisms, the same genera are prevalent worldwide, with only a few abundant species in each genus. Microbial communities are responsible for biological wastewater treatment. Here, Dueholm et al. generate more than 5 million high-quality, full-length 16S rRNA gene sequences from wastewater treatment plants across the world to construct a database with a comprehensive taxonomy, providing insights into diversity and function of these microbial communities.

Municipal wastewaters contain a multitude of organic trace pollutants. Often, their biodegradability by activated sludge microorganisms is decisive for their elimination during wastewater treatment. Since the amounts of micropollutants seem too low to serve as growth substrate, cometabolism is supposed to be the dominating biodegradation process. Nevertheless, as many biodegradation studies were performed without the intention to discriminate between metabolic and cometabolic processes, the specific contribution of the latter to substance transformations is often not clarified. This minireview summarizes current knowledge about the cometabolic degradation of organic trace pollutants by activated sludge and sludge-inherent microorganisms. Due to their relevance for communal wastewater contamination, the focus is laid on pharmaceuticals, personal care products, antibiotics, estrogens, and nonylphenols. Wherever possible, reference is made to the molecular process level, i.e., cometabolic pathways, involved enzymes, and formed transformation products. Particular cometabolic capabilities of different activated sludge consortia and various microbial species are highlighted. Process conditions favoring cometabolic activities are emphasized. Finally, knowledge gaps are identified, and research perspectives are outlined.

Sulfamethoxazole (SMX) is one of the most widely applied sulfonamide antibiotics in the world, which is becoming a ubiquitous pollutant in the environment. In this mini-review, the microbial degradation of SMX was briefly reviewed. The performance of the conventional wastewater treatment plants in removing SMX was provided. The microorganisms capable of degrading SMX, including mixed cultures and pure cultures, were presented. The effects of environmental conditions such as temperature, pH, initial SMX concentration, and additional carbon sources on the biodegradation of SMX were discussed. The metabolic pathways of SMX degradation were summarized. Finally, the suggestions were made for further studies.

Microorganisms play crucial roles in water recycling, pollution removal and resource recovery in the wastewater industry. The structure of these microbial communities is increasingly understood based on 16S rRNA amplicon sequencing data. However, such data cannot be linked to functional potential in the absence of high-quality metagenome-assembled genomes (MAGs) for nearly all species. Here, we use long-read and short-read sequencing to recover 1083 high-quality MAGs, including 57 closed circular genomes, from 23 Danish full-scale wastewater treatment plants. The MAGs account for ~30% of the community based on relative abundance, and meet the stringent MIMAG high-quality draft requirements including full-length rRNA genes. We use the information provided by these MAGs in combination with >13 years of 16S rRNA amplicon sequencing data, as well as Raman microspectroscopy and fluorescence in situ hybridisation, to uncover abundant undescribed lineages belonging to important functional groups. Microbes play key roles in wastewater treatment. Here, Singleton et al. use long-read and short-read sequencing to recover 1083 high-quality metagenome-assembled genomes from 23 wastewater treatment plants, and combine this information with amplicon data, Raman microspectroscopy and FISH to reveal functionally important lineages.

Wastewater, tourism, and trade are moving microbes around the globe at an unprecedented scale For several billion years, microorganisms and the genes they carry have mainly been moved by physical forces such as air and water currents. These forces generated biogeographic patterns for microorganisms that are similar to those of animals and plants ( 1 ). In the past 100 years, humans have changed these dynamics by transporting large numbers of cells to new locations through waste disposal, tourism, and global transport and by modifying selection pressures at those locations. As a consequence, we are in the midst of a substantial alteration to microbial biogeography. This has the potential to change ecosystem services and biogeochemistry in unpredictable ways.

Wastewater treatment plants (WWTPs) are implicated as hotspots for the dissemination of antibacterial resistance into the environment. However, the in situ processes governing removal, persistence, and evolution of resistance genes during wastewater treatment remain poorly understood. Here, we used quantitative metagenomic and metatranscriptomic approaches to achieve a broad-spectrum view of the flow and expression of genes related to antibacterial resistance to over 20 classes of antibiotics, 65 biocides, and 22 metals. All compartments of 12 WWTPs share persistent resistance genes with detectable transcriptional activities that were comparatively higher in the secondary effluent, where mobility genes also show higher relative abundance and expression ratios. The richness and abundance of resistance genes vary greatly across metagenomes from different treatment compartments, and their relative and absolute abundances correlate with bacterial community composition and biomass concentration. No strong drivers of resistome composition could be identified among the chemical stressors analyzed, although the sub-inhibitory concentration (hundreds of ng/L) of macrolide antibiotics in wastewater correlates with macrolide and vancomycin resistance genes. Contig-based analysis shows considerable co-localization between resistance and mobility genes and implies a history of substantial horizontal resistance transfer involving human bacterial pathogens. Based on these findings, we propose future inclusion of mobility incidence (M%) and host pathogenicity of antibiotic resistance genes in their quantitative health risk ranking models with an ultimate goal to assess the biological significance of wastewater resistomes with regard to disease control in humans or domestic livestock.

Biological conversion of sulfide, acetate, and nitrate to, respectively, elemental sulfur (S⁰), carbon dioxide, and nitrogen-containing gas (such as N₂) at NaCl concentration of 35–70 g/L was achieved in an expanded granular sludge bed (EGSB) reactor. A C/N ratio of 1:1 was noted to achieve high sulfide removal and S⁰ conversion rate at high salinity. The extracellular polymeric substance (EPS) quantities were increased with NaCl concentration, being 11.4-mg/g volatile-suspended solids at 70 mg/L NaCl. The denitrifying sulfide removal (DSR) consortium incorporated Thauera sp. and Halomonas sp. as the heterotrophs and Azoarcus sp. being the autotrophs at high salinity condition. Halomonas sp. correlates with the enhanced DSR performance at high salinity.