Water Research

A novel integrated pilot-scale A-stage high rate activated sludge, B-stage short-cut biological nitrogen removal and side-stream enhanced biological phosphorus removal (A/B-shortcut N- S2EBPR) process for treating municipal wastewater was demonstrated with the aim to achieve simultaneous and carbon- and energy-efficient N and P removal. In this studied period, an average of 7.62 {+/-} 2.17 mg-N/L nitrite accumulation was achieved through atypical partial nitrification without canonical known NOB out-selection. Network analysis confirms the central hub of microbial community as Nitrospira, which was one to two orders of magnitude higher than canonical aerobic oxidizing bacteria (AOB) in a B-stage nitrification tank. The contribution of comammox Nitrospira as AOB was evidenced by the increased amoB/nxr ratio and higher ammonia oxidation activity. Furthermore, oligotyping analysis of Nitrospira revealed two dominant sub-clusters (microdiveristy) within the Nitrospira. The relative abundance of oligotype II, which is phylogenetically close to Nitrospira_midas_s_31566, exhibited a positive correlation with nitrite accumulation in the same operational period, suggesting its role as comammox Nitrospira. Additionally, the phylogenetic investigation suggested that heterotrophic organisms from the family Comamonadacea and the order Rhodocyclaceae embedding ammonia monooxygenase and hydroxylamine oxidase may function as heterotrophic nitrifiers. This is the first study that elucidated the impact of integrating the S2EBPR on nitrifying populations with implications on short-cut N removal. The unique conditions in the side-stream reactor, such as low ORP, favorable VFA concentrations and composition, seemed to exert different selective forces on nitrifying populations from those in conventional biological nutrient removal processes. The results provide new insights for integrating EBPR with short-cut N removal process for mainstream wastewater treatment.

Tetrasphaera were recently identified based on the 16S rRNA gene as among the most abundant polyphosphate-accumulating organisms (PAOs) in global full-scale wastewater treatment plants (WWTPs) with enhanced biological phosphorus removal (EBPR). However, it is unclear how Tetrasphaera PAOs are selectively enriched in the context of the EBPR microbiome. In this study, an EBPR microbiome enriched with Tetrasphaera (accounting for 40% of 16S sequences on day 113) was built using a top-down design approach featuring multicarbon sources and a low dosage of allylthiourea. The microbiome showed enhanced nutrient removal (P removal ~85% and N removal ~80%) and increased P recovery (up to 23.2 times) compared with the seeding activated sludge from a local full-scale WWTP. The supply of 1 mg/L allylthiourea promoted the coselection of Tetrasphaera PAOs and Microlunatus PAOs and sharply reduced the relative abundance of both ammonia oxidizer Nitrosomonas and putative competitors Brevundimonas and Paracoccus, facilitating the establishment of the EBPR microbiome. Based on 16S rRNA gene analysis, a putative novel PAO species, EBPR-ASV0001, was identified with Tetrasphaera japonica as its closest relative. This study provides new knowledge on the establishment of a Tetrasphaera-enriched microbiome facilitated by allylthiourea, which can be further exploited to guide future process upgrading and optimization to achieve and/or enhance simultaneous biological phosphorus and nitrogen removal from high-concentration wastewater.

Ensuring safe drinking water is one of the top priorities in public health as waterborne diseases remain a global challenge. In China, microbial contamination in drinking water is of particular concern and comprehensive survey/monitoring of the drinking water microbiome is necessary. However, traditional culture-based microbial monitoring methods have significant limitations, and nationwide tap water survey/monitoring in China would require significant resources. Here, a cost-effective and culture-independent citizen science approach was developed to sample the microbiome in household drinking water (n = 50) from 19 provinces in China from December 2020 to August 2021, including a few opportunistic samples collected in situ right after extreme weather events such as the 2021 Henan Floods and Typhoon In-Fa Landfall. Using a protocol optimized for low-biomass samples, 22 out of 50 tap water samples were tested positive for microbial DNA. 16S rRNA gene metabarcoding were conducted on pooled samples, yielding 7,635 Amplicon Sequence Variants (ASVs), which revealed a diverse microbiome in household tap water. Alarmingly, pathogenic bacteria including Mycobacterium spp., Acinetobacter spp., and Legionella spp. were detected in all PCR positive samples. Despite the limited number of samples, a significant number of pathogenic species (e.g., Salmonella enterica) and/or toxin-producing cyanobacteria (e.g., Microcystis spp.) were detected in local tap water samples from Zhengzhou and Changzhou following the 2021 Henan Floods and Typhoon In-Fa Landfall, respectively. Overall, this study underscores the utility of citizen science in enhancing microbial monitoring and informs future public health strategies for water safety.

New long read sequencing technologies offer huge potential for effective recovery of complete, closed genomes from complex microbial communities. Using long read (MinION) obtained from an ensemble of activated sludge enrichment bioreactors, we 1) describe new methods for validating long read assembled genomes using their counterpart short read metagenome assembled genomes; 2) assess the influence of different correction procedures on genome quality and predicted gene quality and 3) contribute 21 new closed or complete genomes of community members, including several species known to play key functional roles in wastewater bioprocesses: specifically microbes known to exhibit the polyphosphate- and glycogen-accumulating organism phenotypes (namely Accumulibacter and Dechloromonas, and Micropruina and Defluviicoccus, respectively), and filamentous bacteria (Thiothrix) associated with the formation and stability of activated sludge flocs. Our findings further establish the feasibility of long read metagenome-assembled genome recovery, and demonstrate the utility of parallel sampling of moderately complex enrichments communities for recovery of genomes of key functional species relevant for the study of complex wastewater treatment bioprocesses.

Extracellular proteins are supposed to play crucial roles in the formation and structure of biofilms and aggregates. However, often little is known about these proteins, in particular for microbial communities. Here, we use two advanced metaproteomic approaches to study the extracellular proteome in a granular Candidatus Accumulibacter enrichment as a proxy for microbial communities that form solid microbial granules, such as used in biological wastewater treatment. Limited proteolysis of whole granules and metaproteome isolation from the cultures supernatant successfully identified over 50% of the protein biomass to be secreted. Moreover, structural and sequence-based classification identified 387 proteins, corresponding to over 50% of the secreted biomass, with characteristics that could aid the formation of aggregates, including filamentous, beta-barrel containing, and cell surface proteins. However, while most filamentous proteins originated from Ca. Accumulibacter, among others cell surface proteins did not. This suggests that not only a range of different proteins, but also multiple organisms contribute to granular biofilm formation. Therefore, the obtained extracellular metaproteome data from the granular Ca. Accumulibacter enrichment provides a resource for exploring proteins that potentially support the formation and stability of granular biofilms, whereas the demonstrated approaches can be applied to explore biofilms of microbial communities in general. SIGNIFICANCEBiofilm-forming microbial communities are widespread and pose both challenges and opportunities in various settings in life. Structure-providing, extracellular proteins likely play a crucial role in the formation of the biofilm matrix, but these proteins are challenging to characterise due to the dynamic and complex nature of these communities. We used two advanced metaproteomic approaches to enrich for the extracellular proteins in a granule-forming Candidatus Accumulibacter enrichment culture as a proxy for granule-forming communities present in wastewater treatment plants. The extracellular proteins were additionally classified using structure and sequence-based annotation tools, which identified multiple different protein categories that potentially aid in granule formation, but also may provide structure to the biofilm matrix. Interestingly, although the granules were highly enriched for Ca. Accumulibacter, several structure-providing protein categories originated from other organisms. The obtained metaproteomic data contribute to the understanding of proteins and processes that are potentially involved in granule formation. This could further help to optimise processes involving granular biofilms and identify candidates for the recovery of novel biopolymers for biotechnological applications.

Harmful algal blooms have important implications for the health, functioning and services of aquatic ecosystems. Our ability to detect and monitor these events is often challenged by the lack of rapid and cost-effective methods to identify bloom-forming organisms and their potential for toxin production, Here, we developed and applied a combination of DNA barcoding and Next Generation Sequencing (NGS) for the rapid assessment of phytoplankton community composition with focus on two important indicators of ecosystem health: toxigenic bloom-forming cyanobacteria and impaired planktonic biodiversity. To develop this molecular toolset for identification of cyanobacterial and algal species present in HABs (Harmful Algal Blooms), hereafter called HAB-ID, we optimized NGS protocols, applied a newly developed bioinformatics pipeline and constructed a BOLD (Barcode of Life Data System) 16S reference database from cultures of 203 cyanobacterial and algal strains representing 101 species with particular focus on bloom and toxin producing taxa. Using the new reference database of 16S rDNA sequences and constructed mock communities of mixed strains for protocol validation we developed new NGS primer set which can recover 16S from both cyanobacteria and eukaryotic algal chloroplasts. We also developed DNA extraction protocols for cultured algal strains and environmental samples, which match commercial kit performance and offer a cost-efficient solution for large scale ecological assessments of harmful blooms while giving benefits of reproducibility and increased accessibility. Our bioinformatics pipeline was designed to handle low taxonomic resolution for problematic genera of cyanobacteria such as the Anabaena-Aphanizomenon-Dolichospermum species complex, two clusters of Anabaena (I and II), Planktothrix and Microcystis. This newly developed HAB-ID toolset was further validated by applying it to assess cyanobacterial and algal composition in field samples from waterbodies with recurrent HABs events.

Anaerobic ammonium-oxidizing bacteria (AnAOB) play important roles in both artificial wastewater treatment systems and natural ecosystems. To date, AnAOB pure cultures are not available and they tend to coexist with various microbial species. However, anammox community characteristics including the relationships between AnAOB and their companion bacteria at the global perspective and their impacts on anammox metabolism remain unclear. Here, we systematically analyzed the characteristics of anammox communities and the stable relationships concerning AnAOB using a global dataset containing 619 anammox-related amplicons. Different anammox systems showed significant differences in alpha and beta diversity, but shared some core taxa of interest. A total of 89 and 55 core genera and species were identified respectively across anammox communities worldwide, which formed the backbone of artificial anammox systems. Through the analysis of co-abundance networks derived from four distinct artificial anammox systems--biofilm, granular sludge, flocculent sludge, and planktonic cells--we identified 208 stable and 92 limited stable relationships associated with AnAOB. Functional analysis suggested that stable positively-correlated companion bacteria may provide essential cofactors (e.g., molybdenum cofactor, tetrahydrofolate, and coenzyme A) to AnAOB. The companion bacteria which showed limited stable positive correlations with AnAOB in the anammox attachment-growth systems, may mutualize with AnAOB via type pili. This study deepens the understanding of anammox communities, anammox core microbiome, and AnAOB symbiotic relationships. These (limited) stable companion bacteria and corresponding cofactors can potentially guide the development and application of bioaugmentation methods, synthetic anammox communities, and deterioration biomarkers for engineered anammox systems.

Elevated concentrations of ammonium and methane in groundwater can cause severe problems during drinking water production. To avoid their accumulation, raw water in the Netherlands, and many other countries, is purified by sand filtration. These drinking water filtration systems select for microbial communities that mediate the biodegradation of organic and inorganic compounds. In this study, the active layers and wall biofilm of a Dutch drinking water treatment plant (DWTP) were sampled at different locations along the filtration units of the plant over three years. We used high-throughput sequencing in combination with differential coverage and sequence composition-based binning to recover 56 near-complete metagenome-assembled genomes (MAGs) with an estimated completion of [≥]70% and with [≤]10% redundancy. These MAGs were used to characterize the microbial communities involved in the conversion of ammonia and methane. The methanotrophic microbial communities colonizing the wall biofilm (WB) and the granular material of the primary rapid sand filter (P-RSF) were dominated by members of the Methylococcaceae and Methylophilaceae. The abundance of these bacteria drastically decreased in the secondary rapid sand filter (S-RSF) samples. In all samples, complete ammonia-oxidizing (comammox) Nitrospira were the most abundant nitrifying guild. Clade A comammox Nitrospira dominated the P-RSF, while clade B was most abundant in WB and S-RSF, where ammonium concentrations were much lower. In conclusion, the knowledge obtained in this study contributes to understanding the role of microorganisms in the removal of carbon and nitrogen compounds during drinking water production. We furthermore found that drinking water treatment plants represent valuable model systems to study microbial community function and interaction. HighlightsO_LIMicrobial distribution was mainly influenced by sampling location within the DWTP C_LIO_LIClade A comammox Nitrospira were the dominant nitrifiers in the primary sand filter C_LIO_LIClade B was most abundant in samples from wall biofilm and the secondary filter C_LIO_LIA novel Methylophilaceae-affiliated methanotroph dominated the primary sand filter C_LI

Shifting from ammonia removal to recovery is the current strategy in wastewater treatment management. We recently developed a microaerophilic activated sludge (MAS) system for retaining ammonia while removing organic carbon with minimal N2O emissions. A comprehensive understanding of nitrogen metabolisms in the MAS system is essential to optimize system performance. Here, we employed metagenomics and metatranscriptomics analyses to characterize the microbial community structure and activity during the transition from a microaerophilic to an aerobic condition. A hybrid approach of high-quality Illumina short reads and Nanopore long reads recovered medium-to high-quality 98 non-redundant metagenome-assembled genomes (MAGs) from the MAS communities. The suppressed bacterial ammonia monooxygenase (amoA) expression was upregulated after shifting from a microaerophilic to an aerobic condition. The 73 MAGs (>74% of the total) from 11 bacterial phyla harbored genes encoding proteins involved in nitrate respiration; 39 MAGs ([~]53%) carried N2O reductase (nosZ) genes with the predominance of clade II nosZ (31 MAGs), and 24 MAGs ([~]33%) possessed nitrite reductase (ammonia forming) genes (nrfA). Clade II nosZ and nrfA genes exhibited the highest and second-highest expressions among nitrogen metabolism genes, indicating robust N2O consumption and ammonification. Non-denitrifying clade II nosZ bacteria, Cloacibacterium spp., in the most abundant and active phylum Bacteroioda, were likely major N2O sinks. Elevated dissolved oxygen (DO) concentration inhibited clade II nosZ expression but not nrfA expression, potentially switching phenotypes from N2O reduction to ammonification. Collectively, the multi-omics analysis illuminated vital bacteria responsible for N2O reduction and ammonification in microaerophilic and aerobic conditions, facilitating high-performance ammonia recovery.

RNA viruses are widely recognized for their roles in causing human diseases and shaping Earths biodiversity. Wastewater treatment plants (WWTPs) are eco-friendly biotechnological systems where the roles of RNA viruses in process engineering and sanitation remain unclear. This study analyzed RNA sequencing dataset (> 3.8 Tb) from global WWTPs to examine the diversity, host associations, and auxiliary metabolic functions of RNA viruses. We identified 11,414 RNA virus operational taxonomic units (vOTUs), expanding the known diversity of RNA viruses in WWTPs by 67%. The RNA viral community in WWTPs was dominated by prokaryotic viruses, including both established RNA phage lineages and novel clades with broad ecological distributions, highlighting their underestimated diversity and broad niche breadths. Notably, a vOTU from the base-Howeltoviricetes phage clade was associated with the pathogenic bacterium Aliarcobacter cryaerophilus, suggesting potential applications in RNA phage therapy. Furthermore, the examined distribution and fate of human RNA viruses emphasized the utility of quantitative metatranscriptomics-based wastewater surveillance for public health monitoring. The discovery of auxiliary metabolic genes encoded by RNA viruses further revealed their involvement in critical host metabolic pathways such as translation and cellular respiration. These findings underscore the multifaceted roles of RNA viruses in the critical engineered systems.

Antibiotic resistance genes (ARGs) circulating among clinically relevant bacteria pose serious challenges to public health. Given the ancient and environmental bacterial origins of ARGs, a better understanding of the carriers of ARGs beyond the clinically most relevant species is urgently needed for more farsighted resistance monitoring and intervention measures. While the risks of emerging ARGs from environmental sources have been recognized, the identification bottlenecks stem from the limitations of shotgun metagenomic sequencing and bioinformatic methods. Here, we used long-read metagenomic sequencing and bacteria-specific methylation profiles to re-establish the links between established (well-described) or latent (absent in databases) ARGs and their bacterial and genetic contexts in wastewater. The base modification data produced by PacBio SMRT sequencing was analyzed by an in-house pipeline utilizing position weight matrices and UMAP visualizations. The approach was validated by a synthetic community with known bacterial composition. Our analysis revealed several previously unreported ARGs and their hosts with varying risk levels defined by their potential as emerging public health threats. For instance, Arcobacter, as one of the prevalent taxa in influent wastewater, was shown to carry a latent beta-lactamase gene with high predicted mobility potential. Of the other emerging beta-lactamases, we provided a real-life example of ongoing pdif module-mediated genetic reshuffling of the blaMCA gene occurring at least within Acinetobacter hosts in our samples. Additionally, we identified Simplicispira, Phycisphaerae, and environmental groups of the Bacteroidales order as the carriers of established, clinically important ARGs. These findings support the intermediate host roles of strictly environmental bacteria for the further dissemination of mobilized ARGs, highlighting the importance of exploring the uncultivated, or non-pathogenic, carriers of ARGs for the early detection of newly arising ARGs and mobility mechanisms.

Antimicrobial resistance (AMR) is a growing global public health threat projected to cause up to 10 million deaths annually by 2050 if no immediate action is taken. While misuse and overuse of antibiotics are the main drivers of increasing AMR, the eco-evolutionary dynamics of AMR in the environment - particularly across the urban-rural continuum - remain poorly understood. Using shotgun sequencing, we investigated urban, farm, and rural water sources in the Berlin-Brandenburg region to explore the distinctness or overlap of their antibiotic resistance gene (ARG) profiles and the potential impact of wastewater treatment plants (WWTP). ARGs were identified using multiple databases and five bioinformatic tools, combining sequence-based alignment and deep learning approaches. This multi-tool approach allowed for the detection of up to 18 AMR classes--more than any single tool alone. The multi-tool screening approach for ARGs, combined with the ABRicate algorithm, was superior to all single ARG tools and databases, detecting more AMR classes, allowing for biocide and metal resistance detection, while less sensitive for detection of aminocoumarin resistance genes. ARG diversity was higher in urban lake sediments, urban waters, and wastewater compared to rural lake sediments and water. Among all environments, urban lake water showed the highest overall ARG abundance, second only to wastewater, and this pattern held across all AMR classes, except for aminoglycoside resistance, which was most prevalent in rural lake sediments. The WWTP was unable to remove the circulating pool of ARGs, despite a decrease in unique ARGs in the outflow.

Aquaculture practices generate nutrient-rich effluents with associated microbiological hazards, such as pathogens and antimicrobial resistance genes (ARGs). Despite their growing popularity as nature-based solutions, little is known about how constructed wetlands (CWs) affect the dynamics of microbial communities at the field scale. By combining flow cytometry, 16S rRNA gene sequencing, shotgun metagenomics, and metabolic potential assays, we investigated the structural and functional responses of the aquatic microbial community following the recurrent exposure to CW-treated effluents from an intensive marine fish farm (Orbetello lagoon, Italy). While the CW promoted abundant, metabolically active, and functionally redundant microbial communities, the phylogenetic composition diverged primarily between water and sediments. Microbial profiles in CW outlet waters converged towards those of the lagoon baselines, suggesting gradual ecological recovery. The CW attenuated the occurrence of potential pathogens (e.g., Francisella spp., Campylobacter spp.) and limited ARG dissemination, though sediments remained reservoirs of microbial and genetic signatures. Functional profiles, dominated by chemoheterotrophy, denitrification, and sulfur respiration, remained stable across environments, reflecting microbial resilience. Our results highlight CWs as effective, field-proven solutions to mitigate aquaculture wastewater impacts while preserving core ecosystem services.

Tracking the emergence of new SARS-CoV-2 variants is important for a comprehensive understanding of the pandemics progression. However, it remains challenging due to the low variant prevalence in the early stage of an outbreak. Here, we present an integrated framework that combines three key components: early variant detection in wastewater, validation through clinical genome sequencing, and transmissibility assessment using mathematical modeling. Using the SARS-CoV-2 Omicron variant as a proof of concept, we developed a novel nested allele-specific RT-qPCR assay (NAS-PCR) for wastewater surveillance. Our framework detected Omicron in Greater Boston wastewater samples starting from September 2021, over two months before the first U.S. clinical case. We validated these findings by analyzing GISAID clinical sequence data, which revealed 172 previously unreported Omicron genomes predating its official identification in South Africa. To assess transmissibility, we developed a Susceptible-Infected-Viral load model using quantified wastewater concentrations, which estimated Omicrons basic reproduction number (R0) between 2.36 and 3.09, showing robust consistency across varying population sizes, data points, and viral shedding rates. This integrated approach unifies molecular diagnostics, wastewater epidemiology, and mathematical modeling for comprehensive variant surveillance. Our framework provides a systematic solution for early warning and risk assessment of emerging variants, which can strengthen public health preparedness for future viral threats.

Granular sludge intensifies the removal of nutrients from wastewater. Granules structured by extracellular polymeric substances (EPS) can be recovered as biomaterial. Links between microbial selection and EPS formation during granulation need to get uncovered. We inoculated anaerobic-aerobic sequencing batch reactors with either flocs or granules to study the relationships between microbial selection, bioaggregation, exopolymer formation, and EPS composition. Selection for slow-growing organisms like the model polyphosphate- accumulating organism "Candidatus Accumulibacter" (max. 83% vs. amplicon sequencing read counts) and glycogen-accumulating organism "Ca. Competibacter" (max. 45%) sustained granulation. Gel-forming exopolymers were produced as high as above 40% of the volatile solids of the biomass by stepwise increase of the organic loading rate (0.3 to 2.0 g CODAc d-1 LR-1). Confocal laser scanning microscopy, FT-IR spectroscopy, and HPAE-PAD chromatography revealed the complex and dynamic chemical compositions of the structural EPS in relation to microbial population shifts along reactor regimes. The analysis of 20 representative genomes of "Ca. Accumulibacter" and "Ca. Competibacter" recovered from public databases revealed their functional potential to produce EPS among other representative wastewater microorganisms. The more than 40 functional gene categories annotated highlight the complexity of EPS metabolic networks from monomers processing to assembly, export, and epimerizations. The combination of ecological engineering principles and systems microbiology will help unravel and direct the production of EPS from wastewater, valorizing residual granular sludge into beneficial biomaterials for the circular economy. HighlightsO_LISelection for slow-growing organisms like PAOs and GAOs fostered a robust granulation. C_LIO_LIStructural EPS were produced above 40% of biomass volatile content under high loading. C_LIO_LIChemical composition of EPS evolved together with the microbial community composition. C_LIO_LIGenomic insights highlighted the genetic potential of PAOs and GAOs for EPS formation. C_LIO_LIMicrobial communities are complex; further are their EPS compositions and metabolisms. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/534144v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@a163e2org.highwire.dtl.DTLVardef@1a4ab94org.highwire.dtl.DTLVardef@1fc93d4org.highwire.dtl.DTLVardef@14d4b7f_HPS_FORMAT_FIGEXP M_FIG C_FIG

Wastewater surveillance offers an objective, comprehensive, and cost-effective means of monitoring the prevalence and genomic heterogeneity of pathogens circulating in a community. Here, a novel two-step extraction procedure for the direct capture of SARS-CoV-2 RNA from raw wastewater is presented. Combined with reverse transcription-droplet digital polymerase chain reaction (RT-ddPCR) detection, the method provides a fast and sensitive method for measuring viral RNA concentrations in wastewater. The method was used to measure the concentration of SARS-CoV-2 RNA in daily samples of wastewater entering a major metropolitan wastewater treatment plant over the course of 32 months, from November 2020 through June 2023. In addition, targeted mutation assays were used with RT-ddPCR to characterize the evolving presence and prevalence of specific SARS-CoV-2 variant sub-lineages in the wastewater stream over time. The results demonstrate the utility of these methods to accurately measure the total load of SARS-CoV-2 RNA, and chronicle its evolving variant composition, in wastewater treatment plant influent, providing near-real-time characterization of COVID-19 disease prevalence and trends in the served community. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/24311866v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1789a8aorg.highwire.dtl.DTLVardef@e9ec37org.highwire.dtl.DTLVardef@1933133org.highwire.dtl.DTLVardef@831134_HPS_FORMAT_FIGEXP M_FIG C_FIG

Nitrous oxide (N2O), a potent greenhouse gas and ozone-depleting agent, was detected at high concentrations in the anoxic bottom-waters of a monomictic eutrophic lake basin in Switzerland (Lake Lugano). The observed high site-specific nitrogen (N) isotope preference (SP), was inconsistent with bacterial denitrification, which typically exhibits low SP, thereby challenging its role as the primary N2O source. This pointed to chemo-denitrification and/or fungal denitrification, both characterized by high SP, as possible alternative pathways. We conducted incubation experiments with sediment and bottom-water samples to assess N2O production and reduction dynamics and associated natural-abundance stable isotope signatures. We demonstrate that N2O accumulation predominantly originated from sedimentary production, and that elevated SP values in the bottom water reflected fractional bacterial N2O reduction. Using an isotope mass balance mixing model, we identified bacterial denitrification as the dominant sedimentary process ([~]75%), followed by chemo-denitrification ([~]20%), and fungal denitrification ([~]5%). Additional 15N tracer incubation experiments, combined with selective inhibitors to quantify isolated pathways, confirmed model-estimated contributions. These findings validate the use of literature-based SP values in mixing models, and provide evidence for non-canonical N2O production via chemo- and fungal denitrification, highlighting the need to broaden our understanding of N2O cycling in lakes beyond classical bacterial pathways. SYNOPSISEutrophic lake conditions significantly enhance nitrous oxide production through diverse microbial processes, including non-traditional pathways beyond classical nitrification and denitrification. This study highlights the importance of incorporating chemo- and fungal denitrification when investigating aquatic nitrous oxide cycling. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/670496v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@808806org.highwire.dtl.DTLVardef@626820org.highwire.dtl.DTLVardef@a22bd8org.highwire.dtl.DTLVardef@eca378_HPS_FORMAT_FIGEXP M_FIG C_FIG

Fecal material in the environment is a primary source of pathogens that cause waterborne diseases and affect over a billion people worldwide. Microbial source tracking (MST) assays based on single genes (e.g., 16S rRNA) do not always provide the resolution needed to attribute fecal contamination sources. In this work, we used dialysis bag mesocosms simulating a freshwater habitat that were spiked separately with cow, pig, or human feces to monitor the decay of host-specific fecal signals over time with metagenomics, traditional qPCR, and culture-based methods. Sequencing of the host fecal communities used as inocula recovered 79 non-redundant metagenome-assembled genomes (MAGs) whose abundance patterns showed that the majority of the fecal community signal was not detectable in the mesocosm metagenomes after four days. Several MAGs showed high host specificity, and thus are promising candidates for biomarkers for their respective host type. Traditional qPCR methods varied in their correlation with MAG decay kinetics. Notably, the human-specific Bacteroides assay, HF183/BFDRev, consistently under-estimated fecal pollution due to not being present in all hosts and/or primer mismatches. This work provides new insights on the persistence and decay kinetics of host-specific gut microbes in the environment and identifies several MAGs as putative biomarkers for improved MST. SYNOPSISWe track cow, pig, and human fecal pollution in lake water over time with metagenomics and benchmark these novel protocols against standard culture-based and qPCR tests for water quality monitoring.

This study focused on the development of machine-learning- (ML) based strategies for mitigating nitrous oxide (N2O) emissions from various wastewater treatment systems in the United States measured using a benchmark USEPA-endorsed protocol. Results revealed that in general, poor process performance correlated with higher N2O emissions. Specifically, local variables including zone-specific dissolved oxygen, ammonia, and nitrite concentrations and global variables including effluent nitrite and nitrate concentrations contributed positively towards N2O emissions from both aerobic and anoxic zones of the process bioreactors. The optimal operational conditions identified for minimizing N2O emissions included operation of aerobic and anoxic zones at DO < 4 mg O2 L-1 and < 1 mg O2 L-1, respectively, coupled with appropriate solids retention times (SRTs) that maximize process performance. Accordingly, our results strongly underscore the utility of ML models in combination with bioprocess fundamentals for predicting and mitigating N2O emissions, while concomitantly optimizing wastewater treatment operations.

Antimicrobial resistance (AMR) is a growing problem, with annual deaths set to pass 10 million by 2050 if current trends continue. Wastewater surveillance has been proposed as a strategy to understand population-level resistance, and water reclamation facilities (WRFs) have been identified as a control point for environmental dissemination of resistant bacteria. Understanding dynamics of AMR across WRFs requires advanced molecular tools that elucidate host bacteria, especially for mobile resistance carried on plasmids. To that end, influent, activated sludge, and effluent were collected from three WRFs in North Carolina, Texas, and California during three weeks of Spring 2024. Samples were analyzed using Hi-C proximity ligation sequencing to identify the AMR host range for chromosomal and plasmid-based resistance. A total of 1,868 hits for 244 unique resistance genes were observed, with seven resistance genes identified in all samples. Resistance genes were more likely to be carried on a microbial plasmid in influent, but more likely to be in a chromosome in activated sludge. Seventeen total microbial hosts for resistance genes were identified in effluent, suggesting WRF effluents may be sources of resistant bacteria to receiving surface waters. A high proportion of all identified host relationships were confined to just four bacterial families. Hi-C contact mapping is a critical tool to more fully describe the AMR host range in complex matrices, particularly for plasmid-based resistance genes. ImportanceAntimicrobial resistance (AMR) threatens modern medicine. Water reclamation facilities receive a complex mixture of antibiotics and rely on active microbial communities for treatment, thereby acting as critical systems to prevent environmental spread of resistance. However, AMR dynamics are difficult to discern in complex wastewater environments due to antibiotic resistance genes (ARGs) being frequently carried on mobile pieces of DNA that are difficult to link to specific bacteria using conventional shotgun sequencing. Novel proximity ligation sample preparation techniques like Hi-C physically link co-located sequences of DNA before shotgun sequencing. This allows sequencing to elucidate the bacterial hosts for both stable and mobile ARGs. In the current study, Hi-C sequencing was carried out on influent, activated sludge, and effluent collected from water reclamation facilities in California, Texas, and North Carolina to assess the resistome host range across treatment. 5 Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/26346186v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1e4620eorg.highwire.dtl.DTLVardef@e1c3a7org.highwire.dtl.DTLVardef@1f40964org.highwire.dtl.DTLVardef@94b886_HPS_FORMAT_FIGEXP M_FIG C_FIG