Water Research

The COVID-19 pandemic remains a global concern, partly due to the rapid mutation rate of SARS-CoV-2 and the emergence of new variants. Wastewater surveillance has proven effective in estimating infection incidence and detecting variants earlier than clinical testing. Its importance has grown as testing rates decline due to milder disease progression. However, current methods typically rely on the prior classification of SARS-CoV-2 lineages or their signature mutations, which may delay detection. We present an alternative method that identifies changes in the viral genetic population over time without requiring prior lineage classification. This population-based approach was applied to sequencing data from wastewater samples, which are generally noisier than clinical samples. We analyzed publicly available sequencing samples from wastewater plants covering Swiss catchments in Altenrhein, St. Gall, Geneva, and Zurich. To address noise, only samples with read depths above 40 and genome coverage of at least 90% were included. Genetic diversity within pooled populations over two time periods was compared to assess changes in viral composition. We demonstrate that SARS-CoV-2 variants can be detected in wastewater sequencing data without prior lineage classification. Our method successfully detected shifts in genetic populations that corresponded to the emergence of known variants of concern (VOCs) in the analyzed regions. Notably, it also revealed the rising prevalence during the first surges of the Omicron variant. Despite the increased noise in wastewater compared to clinical samples, our approach remains effective. However, achieving reliable predictions depends on high sequencing depth, broad genome coverage, and frequent sampling.

Mainstream anammox implementation for nitrogen removal is constrained by unstable nitrite supply and organic carbon requirements for nitrate byproduct removal. This study evaluated integrated fixed-film activated sludge (IFAS) biofilms to enhance anammox activity by coupling low-oxygen ammonium oxidation with volatile fatty acid (VFA)-driven nitrate reduction. Nanopore long-read metagenomic assembly recovered a high-quality, circular single-contig Candidatus Brocadia sapporoensis metagenome-assembled genome (MAG) from full-scale IFAS biofilms. This MAG encodes complete anammox metabolism, dissimilatory nitrate reduction to ammonium (DNRA) and acetate/propionate carbon transformation pathways. Metatranscriptomics showed that low dissolved oxygen (DO) upregulated Ca. B. sapporoensis genes involved in anammox, nitrate reduction, and carbon metabolism. Microaerobic assays established a DO level of 0.7 mg/L as optimal for sustaining near-maximal ammonium oxidation alongside anammox-driven total inorganic nitrogen (TIN) loss. Anoxic tests conducted in secondary effluent indicated that external acetate amendment promoted greater partial nitrate reduction and TIN loss than additional propionate amendment. Integrating this dissolved oxygen concentration with external acetate amendment in a two-stage microaerobic-anoxic system successfully achieved sequential ammonium oxidation, partial nitrate reduction, and anammox-mediated TIN removal. Stage-specific expression suggested Ca. B. sapporoensis could contribute to nitrite self-supplementation via nxrAB-mediated nitrate reduction. Overall, microaerobic ammonium oxidation and Ca. B. sapporoensis-driven partial nitrate reduction jointly sustain mainstream anammox activity. Furthermore, this study demonstrates that successful metabolic synergy depends fundamentally upon precise dissolved oxygen control and effective external acetate amendment.

Since the COVID-19 pandemic, wastewater-based surveillance (WBS) has emerged as a key approach to assess community-level health and the evolution of pathogens. To date, most established WBS systems focus on polymerase chain reaction (PCR) based detection and targeted sequencing of known pathogens because these approaches are well-accepted and include amplification of pathogen target sequences of interest thereby enabling lower limits of detection. Metagenomic next-generation sequencing (mNGS) is a promising approach to enable pathogen detection and surveillance beyond predefined pathogen lists, but its regular application to WBS has not been yet widely adopted because many key performance characteristics are not well-understood, including limit of detection (LOD) and false positive/negative rates. This paper describes a computational analysis to estimate the operational LOD of various sequencing approaches using a simplified model of a local wastewater (WW) system involving a military base. This paper also presents findings from two types of experiments: 1) laboratory-spiked, those for which Atlantibacter subterraneus (Asub) is introduced into real-world WW samples in a laboratory setting, and 2) system-spiked, those for which Asub is introduced at a source location of a real-world WW system. Findings indicate that mNGS detection performance varies with sequencing method and the data analysis process. In addition, findings indicate that site-specific method characterization should be used when implementing mNGS for WBS because sites can have different WW system configurations, background organisms and sequencing inhibitors.

Hospital-based wastewater surveillance may complement community and clinical surveillance data in important ways, and may be useful in jurisdictions without community-based wastewater surveillance. From May 2024-April 2026, we analyzed weekly samples (n=190) from three hospitals in New York City using digital PCR to evaluate the sensitivity, specificity, and positive predictive value (PPV) of wastewater viral detection against facility SARS-CoV-2 and influenza A/B inpatient caseloads. Sensitivity was 38-42% for SARS-CoV-2 and 36-49% for influenza A/B, while specificity exceeded 72% for all pathogens. During respiratory seasons, sensitivity reached 81% for SARS-CoV-2 and 81% for influenza A; both had 100% sensitivity during peak case weeks. Notably, off-peak influenza detections occurred in hospital wastewater at all three hospitals in summer 2024 without corresponding hospital case detection, suggesting the presence of undiagnosed cases. These findings underscore the potential utility of hospital-based wastewater monitoring for tracking respiratory virus activity.

Multi-stage continuous bioprocessing can increase volumetric productivity, operational consistency, and process throughput, but its design is complicated by coupling among dilution rate, reactor volume, feed allocation, and cellular physiology. Here, we present ContiDesigner, available at https://chemnettools.anc.univie.ac.at/ContiDesigner/, a mechanistic steady-state framework and interactive web tool for the system-level design of continuous fermentation cascades. Comparing one- and two-stage configurations at equal total reactor volume and outlet flow, ContiDesigner reveals how internal flow and reactor volume allocation shape space-time yield and identifies productivity-maximizing operating conditions. Compared with one-stage processes, two-stage cascades favor lower over-all dilution rates, thereby preserving residence time in the production stage. The first-stage dilution rate approaches the corresponding one-stage productivity optimum, but the cascade optimum occurs earlier, reflecting a system-level compromise between biomass generation and production-stage residence time. However, two-stage operation outperforms optimized one-stage operation only when non-growth-associated production in the second stage is sufficiently strong, whereas increasing growth coupling favors one-stage operation. Two case studies demonstrate both the potential and limits of process intensification. An optimized two-stage design is predicted to achieve a more than 1.5 fold increase in space-time yield for poly-R-3-hydroxybutyrate (PHB) production compared with a published experimental five-stage cascade, whereas the lactic acid case study identifies conditions under which staging offers no advantage. ContiDesigner translates these design principles into an accessible workflow to explore feasible operating regions and prioritize cascade designs for experimental evaluation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/743657v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@ef58faorg.highwire.dtl.DTLVardef@1ba88a4org.highwire.dtl.DTLVardef@160edd3org.highwire.dtl.DTLVardef@9dda34_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIContiDesigner enables system-level design of continuous fermentation cascades C_LIO_LIHigh stage-one dilution supports biomass generation C_LIO_LILow stage-two dilution preserves productive residence time C_LIO_LIYet two-stage cascades favor lower overall dilution than one-stage systems C_LIO_LITwo-stage advantage requires strong non-growth-associated production in stage two C_LI

Newly established freshwater aquaria rely on development of biofilter nitrifying populations to prevent ammonia and nitrite accumulation that can negatively impact fish health. Although initial fish loads impact water chemistry of new aquaria, little is known about the corresponding impact on microbial community succession within freshwater aquarium biofilters. To address this gap, fourteen home aquarium systems were established, stocked with a range of fish loads, and maintained for eight months. Aquaria were sampled regularly to monitor nitrogen species, microbial community composition (16S rRNA gene sequencing), and the abundance of nitrifiers (qPCR). Aquaria with higher fish loads developed microbial communities that were compositionally distinct from those with lower fish loads, and were dominated by Pseudomonas, Rhodobacter, and Planctomycetes. These patterns are consistent with increased nutrient availability supporting biofilm development, whereas lower fish loads may delay biofilm maturation. Increasing the number of fish in an aquarium significantly increased maximum ammonia and nitrite concentrations, although both were ultimately depleted within similar timeframes across treatments. Comammox Nitrospira were among the most abundant biofilter nitrifiers and were present in all biofilter samples regardless of fish load. Ammonia-oxidizing bacteria were detected at relatively low abundance but showed increases in relative abundance within high fish load aquarium filters. Ammonia-oxidizing archaea were below sequencing detection limits and detected only at low levels by qPCR, suggesting that their establishment in aquarium biofilters may require higher initial inoculation or longer timeframes. Overall, these results demonstrate that fish load shapes microbial community development in newly established aquarium biofilters, and that comammox Nitrospira dominate among nitrifiers during early biofilter establishment.

Wastewater-based epidemiology (WBE) has emerged as a powerful population-level surveillance tool, but its coverage is structurally concentrated in in-network urban areas, potentially leaving rural populations underrepresented. Routine human movement between sewered (in-network) and unsewered (off-network) areas may, however, cause wastewater treatment plant (WWTP) measurements to reflect infectious disease dynamics beyond sewer boundaries. We evaluated this hypothesis using daily clinical COVID-19 testing data (January 2021-April 2022) across New York State excluding New York City (NYC). We disaggregated weekly cases and tests into in-network (WWTP catchment area) and off-network (outside WWTP catchment area) components applied to two geographic frameworks: administrative counties (N = 53 mixed-coverage) and mobility-defined communities identified through Walktrap community detection applied to census tract-level movement networks (N = 32 mixed-coverage). In/off-network COVID-19 trends were strongly correlated under both frameworks. County-level statewide aggregate correlations were high (incidence r = 0.994, positivity r = 0.996), as were individual county correlations (median r = 0.909 and 0.932, respectively). Mobility-defined community-level statewide correlations were similarly strong (r = 0.990 and 0.992), with comparable unit-level medians (r = 0.877 and 0.894). The mobility-defined community framework provided better population balance between in-network and off-network strata (87.5% vs. 69.8% in balanced range) and a higher floor on representativeness (minimum r = 0.440 vs. 0.177). Population size was the dominant predictor of in-network/off-network alignment at both scales; wastewater infrastructure density and off-network signal variability provided additional explanatory power at the mobility-defined community level. WWTPs broadly represent COVID-19 dynamics in surrounding off-network populations, supporting their use as sentinel surveillance sites. Representativeness weakens in smaller, more rural communities, and mobility-defined communities provide a complementary framework for identifying where this occurs.

While the suppression of toxic cyanobacteria by aquatic plants has long been recognized, few studies have clearly differentiated between the allelopathic effects of the plant itself and the inhibitory influence of its associated microbiome. This study aimed to clarify the primary inhibitory agent by pre-culturing Myriophyllum spicatum (Eurasian watermilfoil) under three conditions: (1) BG11 medium, (2) live Microcystis aeruginosa KW culture, and (3) a Microcystis-symbiotic microbiome (excluding Microcystis cells). After a 7-day pre-culture, Myriophyllum shoots were transferred to fresh Microcystis culture. The Myriophyllum pre-cultured in Microcystis culture exhibited rapid inhibition against Microcystis (84% within day 1), whereas the Myriophyllum pre-cultured in BG11 medium showed delayed responses (89% by day 7). In contrast, inhibition remained below 50% in the Myriophyllum pre-cultured with the Microcystis-symbiotic microbiome. Notably, plant-derived soluble compounds exhibited weak inhibitory effects, whereas the microbiome showed stronger inhibitory activity, indicating that the plant-associated microbiome plays a more dominant role than the plant itself. Exposure to Microcystis triggered significant shifts in plant-symbiotic microbial community composition, leading to rapid enhancement of inhibitory activity in the Myriophyllum microbiome. Microbial community analysis identified 28 bacterial taxa closely associated with the inhibitory response, including strains involved in organic matter degradation, adhesion, biofilm formation, and predatory behavior. Meta-transcriptomic analysis further confirmed increased expression of genes related to bacterial adhesion, biofilm formation, and carbohydrate metabolism following Microcystis exposure, highlighting functional adaptations linked to cyanobacterial suppression. These findings underline the role of microbiome-mediated cyanobactericidal mechanisms, providing new insights into a nature-based solution for mitigating Microcystis-dominated harmful algal blooms.

Wastewater systems are increasingly recognized as important environmental reservoirs of antimicrobial resistance (AMR), acting as interfaces where resistant bacteria, antimicrobial resistance genes (ARGs), and mobile genetic elements (MGEs) converge and potentially disseminate. Wastewater samples were collected from hospital and community sites, including municipal medical centers, household wastewater outlets, and open drainage systems. Genomic DNA was extracted using the ZymoBIOMICS DNA/RNA Miniprep Kit and sequenced on the Oxford Nanopore Technologies MinION MK1D platform using the Native Barcoding Kit (SQK-NBD114.24, V14). Sequencing data were processed through a custom Snakemake workflow integrating quality control, taxonomic profiling, resistome characterization, mobilome analysis, and genome-resolved metagenomics. A total of 489 unique ARGs conferring resistance to 29 antibiotic classes were identified through metagenomic analysis. The resistome was dominated by genes conferring resistance to {beta}-lactams (including cephalosporins and carbapenems), aminoglycosides, tetracyclines, macrolides, and fluoroquinolones. Clinically important resistance determinants, including blaOXA, blaTEM, blaGES, blaCARB, cfxA, tet, qnr, sul, dfrA, erm, msrE, and aminoglycoside-modifying enzyme genes such as aac(3) and ant(3'') were detected across both hospital and community wastewater samples. Resistance mechanisms were predominantly driven by antibiotic inactivation, followed by efflux and target protection. Several priority bacterial pathogens were detected, including Escherichia coli, Klebsiella pneumoniae, Enterobacter cloacae, Pseudomonas aeruginosa, and Acinetobacter baumannii. Integration/excision elements were the predominant category of MGEs, followed by transfer-associated elements and replication/recombination/repair functions. Plasmid analysis further identified diverse incompatibility groups, predominantly IncP6, IncC, IncF, and IncR replicons, supporting the widespread occurrence of plasmid-mediated horizontal gene transfer in both settings. These findings reveal a substantial burden of clinically relevant ARGs, mobile genetic elements, and potential bacterial pathogens in hospital and community wastewater in Conakry. This study provides the first metagenomic baseline for environmental AMR surveillance in Guinea and highlights the urgent need for integrated One Health strategies to mitigate the environmental dissemination of antimicrobial resistance.

Microbial fuel cells (MFCs) have been widely investigated as decentralized bioelectrochemical systems capable of converting organic substrates into electricity. However, their long-term autonomous operation is constrained by substrate depletion in the anode compartment, leading to metabolic starvation of electroactive biofilms and a decline in power output. Conventional MFC design treats substrate crossover through the membrane separator as a parasitic loss that reduces coulombic efficiency. In this work, we propose a conceptual inversion of this paradigm by considering controlled cathodic-to-anodic substrate crossover as a passive mechanism to sustain basal microbial metabolism during periods of substrate scarcity. A transport-reaction framework is developed to quantify the balance between membrane-mediated substrate flux and microbial maintenance demand within the anode biofilm. Based on this balance, a dimensionless maintenance crossover Damkohler number (Dam) is introduced to define three operational regimes: starvation-dominated (Dam >> 1), balanced autonomous (Dam {approx} 1), and crossover-dominated (Dam << 1). The framework integrates membrane transport theory with biofilm kinetics to evaluate the effects of separator properties, substrate gradients, and current-dependent electro-osmotic transport on system stability. Order-of-magnitude analysis indicates that achievable crossover fluxes span several orders of magnitude depending on separator characteristics, suggesting that membrane properties critically influence system behavior. This perspective reframes substrate crossover from a loss mechanism to a potential design variable, offering a conceptual tool for enhancing resilience and guiding separator selection in MFCs intended for long-duration, and low-maintenance operation. HighlightsO_LIControlled crossover can sustain microbial metabolism in MFCs C_LIO_LIIntroduces maintenance crossover Damkohler number (Dam) C_LIO_LIIdentifies regimes for autonomous and starvation operation C_LIO_LILinks membrane properties to long-term system stability C_LIO_LIReframes crossover as a design variable, not only a loss C_LI

BackgroundZebrafish (Danio rerio) are a powerful vertebrate model for developmental toxicology and chemical safety assessment, yet large-scale transcriptomics in zebrafish remains limited by cost and data heterogeneity. Targeted transcriptomics offers a cost-effective alternative, but gene extrapolation methods tailored to zebrafish have not been systematically developed or evaluated. ObjectivesWhile the S1500+ platform is widely used for toxicogenomics research with rat, mouse, and human cell lines as model systems, its use in zebrafish has been limited due to data scarcity and lack of suitable bioinformatics approaches for analysis of such data. To that end, we sought to (i) curate a large zebrafish transcriptomic training data resource, and (ii) evaluate multiple machine learning strategies for reconstructing unmeasured transcriptome-wide expression profiles for data originating from the zebrafish-specific reduced representation gene set ("Zf S1500+"). MethodsWe assembled 14,924 zebrafish RNA-Seq samples covering 21,930 genes across 1,246 studies. Using the Zf S1500+ gene subset (3,062 genes), we trained and tested three extrapolation approaches: principal components regression (PCR), a locally weighted extension of PCR (PCR+), and a neural network mixture-of-experts model (NN-MoE). Model performance was assessed using mean absolute error (MAE), mean squared regression error (MSRE), and weighted variants of these metrics. ResultsExtrapolation performance using the baseline approach was strongly influenced by tissue and developmental context, with within-tissue models outperforming cross-tissue models. Errors were lowest when training and testing were conducted within the same tissue or between developmentally related tissues. Both PCR+ and NN-MoE improved upon the baseline PCR approach, with NN-MoE reducing average MAE by [~]20% and MSRE by [~]17%. Importantly, extrapolation remained reliable for the majority of genes, even when limiting output to high-confidence predictions using an empirical MAE threshold. ConclusionsWe demonstrate that targeted transcriptomics can be effectively extended to zebrafish, enabling robust transcriptome-wide extrapolation at reduced cost. The NN-MoE method provided the most substantial gains, highlighting the value of non-linear and ensemble modeling in heterogeneous datasets. These results establish a scalable framework for zebrafish toxicogenomics and suggest that accuracy will continue to improve with larger, better-annotated datasets, paving the way for broader application in chemical safety assessments.

NicA2 is a flavin-bound amine dehydrogenase from Pseudomonas putida S16 that converts nicotine to the pharmacologically inactive N-methylmyosmine. In animal models of nicotine addiction, injection of NicA2 can decrease nicotine-seeking behavior 10-fold. Accordingly, NicA2-related enzymes have been investigated as smoking-cessation therapeutics. However, efficient catalysis by NicA2 in Pseudomonas putida relies on electron transfer to CycN, a cytochrome c, and not directly to O2. Impractically high amounts of NicA2 are thus necessary to achieve a pharmacological effect in the absence of CycN. Directed evolution has improved the ambient-O2 value of kcat from 0.007 s-1 to 1 s-1 for NicA2, but further improvements have been challenging. Here, we identify a strain of Peribacillus frigoritolerans NIC8 which encodes two flavin amine oxidoreductases, Ncox and Pnox. In the presence of oxygen, Ncox and Pnox act on nicotine and pseudooxynicotine respectively with apparent kcat values of 7.7 s-1 and 3.9 s-1. Transient kinetics establishes bimolecular rate constants of 51100 M-1s-1 and 81000 M-1s-1 for the half-reactions between Ncox and O2 and between Pnox and O2 respectively, consistent with Ncox and Pnox being bona-fide oxidases. Transcriptomics shows enhanced expression of Ncox and Pnox under nicotine-dependent growth as well as supporting the identification of downstream enzymes. Phylogenetic analysis suggests that Ncox and Pnox arose out of repurposing of homologous enzymes found in Bacillus species. The enzymes we describe may be useful for the development of nicotine addiction therapeutics and for bioconversion of nicotine in waste streams.

Rapidly converting viral genome information into deployable molecular tests remains a major challenge in outbreak preparedness. We developed CONAN-SWIFT (Simple Workflow for Isothermal Field Testing), a sequence-to-test platform that integrates computational assay design, reverse-transcription loop-mediated isothermal amplification, CRISPR-Cas3 detection, reagent lyophilization and lateral-flow readout. Sequence-guided assays for Andes virus and Bundibugyo virus were established within approximately three weeks and extended to four additional filoviruses. A web-based designer supported crRNA selection, and systematic RT-LAMP primer optimization improved amplification performance. Recombinant Escherichia coli-expressed Cascade enabled standardized preparation of lyophilized Cas3-detection reagents, which were combined with a battery-operated isothermal device. The portable system detected as few as 10 input RNA copies per reaction within approximately 40 min. It also detected viral RNA and biologically contained, replication-incompetent Ebola virus in spiked human blood and concentrated wastewater. These findings establish the analytical feasibility of a rapidly adaptable CRISPR-Cas3 engineering framework for decentralized detection of emerging RNA viruses.

Polycyclic aromatic hydrocarbons (PAHs) are hazardous organic contaminants for which microbial bioaugmentation is a promising remediation strategy, but poor persistence of introduced microorganisms can limit efficacy. Encapsulation may improve persistence, yet the influence of capsule design, microbial species, and environmental conditions on performance remains poorly understood. We evaluated alginate encapsulation of the PAH-degrading bacteria Pseudomonas putida and Novosphingobium aromaticivorans across nutrient conditions and capsule formulations. Encapsulation effects varied by species and medium, influencing growth rate, maximum cell density, overall growth, and lag time; notably, encapsulation shortened lag time of N. aromaticivorans in sRB15 medium (36.9 h to 3.9-5.3 h). Enumeration methods also affected apparent cell recovery. After 8 weeks, encapsulation had no significant effect on P. putida but resulted in increased concentrations of N. aromaticivorans relative to planktonic cultures (1.22 x 10; vs. 2.05 x 10; CFU/mL). Capsule composition further influenced cell retention: increasing alginate approximately doubled capsule-associated cell concentrations, while chitosan coatings reduced cell concentrations within capsules without affecting external concentrations. These findings demonstrate that the benefits of encapsulation are species- and environment-dependent and that capsule formulation can be tuned to influence bacterial persistence and release, informing the design of encapsulated inoculants for bioaugmentation applications.

Background: Autonomous ultraviolet-C (UV-C) disinfection systems are increasingly used to supplement manual environmental cleaning, yet evidence-based guidance defining pathogen-specific UV-C dose requirements across representative surfaces remains limited. Aim: To characterize operational UV-C dose requirements for clinically relevant pathogens across diverse high-touch and healthcare surfaces and determine how experimentally derived microbial inactivation can inform operational exposure parameters. Methods: SARS-CoV-2, adenovirus, Pseudomonas aeruginosa, Staphylococcus aureus, Klebsiella pneumoniae, Enterococcus faecalis, Candida auris, and Clostridioides difficile spores were exposed to defined UV-C doses on representative high-touch materials or stainless steel under standardized conditions, including a 10% fetal bovine serum organic soil challenge. Microbial inactivation was quantified by viable recovery. Dose-response analysis and operational modelling were used where supported by the experimental data. Findings: UV-C exposure significantly reduced viable recovery of all pathogens, with substantial differences in the exposure conditions associated with microbial inactivation. SARS-CoV-2 exhibited substantial inactivation at doses as low as 2.6 mJ/cm2, whereas the highest evaluated doses were 1,800 mJ/cm2 for C. difficile spores and 3600 mJ/cm2 for C. auris. For C. auris, multi-dose data estimated that approximately 1,410 mJ/cm2 was associated with a 2-log10 reference reduction, enabling distance-dependent exposure-time predictions. Conclusion: Experimentally quantified UV-C exposures produced substantial microbial inactivation across diverse pathogen classes and surfaces. Integrating delivered dose with microbial reduction provides a quantitative framework for translating laboratory efficacy into operational parameters for autonomous UV-C disinfection.

Summary Background: Wastewater and environmental surveillance (WES) enables community-level monitoring of infectious diseases. Most progress has focused on sewer-based surveillance, yet nearly half of the global population relies on non-sewered sanitation. In non-sewered settings, urban drainage channels have been used for poliovirus environmental surveillance, but their potential for a multi-pathogen WES with spatially defined catchments, and comparability to sewer-based surveillance, remains under-explored. Methods: Ten drainage channel sampling points with delineated micro-catchments (0.95-3.83 km2 with 12,885-44,146 people) were selected within Kampala. A total of 255 drainage channel and 54 wastewater treatment plant (WWTP) influent samples were collected during two campaigns in March and September-October 2025. A multi-target panel was quantified by digital PCR, including enteric viruses (Norovirus GI and GII, Rotavirus), respiratory viruses (SARS-CoV-2, Influenza A and B viruses, Respiratory Syncytial Virus (RSV)), non-O1/O139 Vibrio cholerae (V. cholerae), and Pepper Mild Mottle Virus (PMMoV) as a fecal indicator. Findings: Enteric viruses, non-O1/O139 V. cholerae, and PMMoV were consistently detected across all drainage channels and WWTP influents. Concentrations were generally lower in drainage than WWTP influents, except for non-O1/O139 V. cholerae. When normalized by PMMoV, concentrations across most drainage channels were comparable to WWTP influents, although comparability varied by target and location. Both concentrations and PMMoV-normalized concentrations varied across sampling locations. Trends between campaigns varied by pathogen target and were not explained by any single micro-catchment characteristic. Influenza A virus was the most frequently detected respiratory virus (8-23% in drainage channels; 3-10% in WWTP influents), while SARS-CoV-2, Influenza B, and RSV were rarely detected. Interpretation: PMMoV-normalized concentrations across most micro-catchments were comparable to WWTP influents, with spatial heterogeneity implying neighborhood-level differences in disease prevalence. Catchment-delineated drainage surveillance has potential to offer spatially resolved public health information in non-sewered settings comparable to sewer-based wastewater monitoring. Funding: Eawag Discretionary Funding

Passive sampling is the deployment of a collection material in the environment to continuously capture environmental DNA (eDNA) over time, offering the potential to integrate biodiversity signals while reducing the need for repeated active water collection. However, the mechanisms governing eDNA capture and retention on passive samplers remain poorly understood, limiting the interpretation of passive eDNA signals and their broader application. Here, we investigated the mechanistic performance of glass fibre passive samplers using controlled mesocosm experiments with three invasive freshwater bivalves: zebra mussels (Dreissena polymorpha), quagga mussels (Dreissena bugensis), and Asian clams (Corbicula fluminea). Specifically, we quantified eDNA accumulation dynamics, evaluated the contribution of different eDNA states, tested the persistence of captured eDNA, and compared passive sampler signals with conventional active sampling. Passive samplers rapidly accumulated target eDNA within hours of deployment, after which concentrations either plateaued or continued to increase depending on species. Sequential transfer of passive samplers between mesocosms containing different species showed that previously captured eDNA declined while new target eDNA accumulated to concentrations comparable to freshly deployed samplers, demonstrating continual turnover rather than permanent retention. Dissolved eDNA showed little evidence of accumulation beyond the concentration retained in the pore water within the membrane, suggesting that it is unlikely to be the dominant contributor to long-term passive sampler signals. Instead, the observed variability among replicate samplers, together with the physical properties of glass fibre membranes, suggests that membrane-bound and particulate eDNA are the primary contributors to passive eDNA capture. Collectively, these findings support a model in which glass fibre passive sampler signals reflect a dynamic equilibrium between ongoing eDNA capture and concurrent loss processes rather than cumulative accumulation over time. This mechanistic framework provides a foundation for interpreting passive eDNA data and informs the future development of passive sampling materials, deployment strategies, and biodiversity monitoring applications.

Full-length 16S rRNA gene sequencing using Oxford Nanopore Technologies has emerged as a promising approach to improve species-level resolution in microbiota studies. However, the accuracy of taxonomic assignment remains highly dependent on the bioinformatics s used to process Nanopore long-read data. Therefore, the only way to ensure a good level of certainty in obtained results is to use positive controls in the form of mock communities in the experimental designs. In this study, we compared the performance of Epi2Me 16S (using Minimap2 or Kraken2) workflows provided by Oxford Nanopore Technologies and an EMU workflow for full-length 16S rRNA gene analysis. Using a commercial mock community sequenced across multiple Nanopore runs, taxonomic assignment accuracy and reproducibility was evaluated. Epi2Me-Kraken2 exhibited 18 % of incorrect genus-level assignments and failed to identify 3 species present in the mock community. While Epi2Me-Minimap2 achieved an excellent genus-level classification, reporting 9 % of sequences assigned to a genus not in the mock community, species-level assignments were inconsistent for several community members such as Listeria. In contrast, EMU provided accurate and consistent species-level taxonomic profiles, with all species correctly identified while keeping the number of genus absent from the mock community at 1.2%. ImportanceThese results highlight that Epi2Me integrated workflows are not the best option for specie-level taxonomic assignation. More importantly, this paper underscores the importance of routine inclusion of positive controls for microbiota studies, in the form of mock communities, as a critical safeguard for accurate data interpretation. Without the use of a mock community, a paper published would be at risk of reporting wrong observations and inaccurate conclusions.

Given the current global environmental challenges, waste biomass is an attractive renewable resource for circular economies. Gasification of biomass yields syngas (CO, CO2, and H2) that is a suitable feedstock for gas fermentation in biomanufacturing of fuels and chemicals using acetogen microbes. While it is generally known that syngas composition influences both acetogen growth and process performance, we are lacking a consistent dataset quantifying these effects under controlled fermentation conditions. Here, we mapped the metabolic response of the model-acetogen Clostridium autoethanogenum to seven synthetic syngas mixtures during exponential batch growth in bioreactor fermentations. Notably, distinct gas compositions resulted in different fermentation profiles, affecting both growth and metabolite production. Maximum specific growth rates ranged within 0.05 0.13 h-1, with slower growth for low-CO mixtures. While acetate and ethanol production yields varied between 20-133 and 76-353 mmol per gram dry cell weight, respectively, minor production of 2,3-butanediol was detected. All syngas mixtures supported co-utilization of CO and H2, though gas uptake stoichiometry only moderately correlated with syngas content. Importantly, gas uptake stoichiometry strongly influenced carbon partitioning, with higher relative H2 uptake reducing CO2 loss or even realizing CO2 fixation together with increasing carbon flow towards metabolites. Interestingly, higher syngas H2 content favored ethanol and 2,3-butanediol production, while higher H2:CO uptake ratios increased total flux through the Wood-Ljungdahl pathway rather than selectively favoring reduced by-products. Our results are valuable for a better understanding of syngas composition effects on the acetogen biocatalyst and for process engineering towards optimizing gas fermentation performance. HighlightsO_LISyngas composition affects acetogen growth, gas uptake, and carbon distribution C_LIO_LIHigher H2:CO uptake ratios increase carbon flow through the Wood-Ljungdahl pathway C_LIO_LIHigher relative H2 uptake reduces CO2 loss and increases metabolite production C_LI

Hospital wastewater (WW) and wastewater biofilms (WWB) are increasingly recognized as important reservoirs of carbapenemase-producing Enterobacterales (CPE), yet their long-term ecological dynamics and relationship with contemporaneous clinical isolates remain poorly understood. Here, we performed longitudinal CPE surveillance of WW and WWB over a 17-month period, combining culture-based screening and comparative whole-genome sequencing of environmental isolates with CPE isolates recovered from patients hospitalized in the same hospital building. A total of 42 environmental and 21 clinical CPE isolates were characterized. Environmental CPE populations underwent a marked ecological shift, with blaOXA-48 -producing Citrobacter spp. progressively replaced by blaVIM-4-producing Serratia nevei. In contrast, clinical isolates remained taxonomically diverse throughout the study period, with a range of betalactamases including blaOXA-48, blaVIM-4, and blaNDM, with no comparable temporal replacement. Comparative genomic analyses revealed a strong association between resistance genes and mobile genetic elements (MGEs), with MGE dynamics largely following those of their hosts. blaOXA-48 was predominantly associated with highly conserved IncL/M plasmid backbones shared across environmental and clinical compartments, whereas blaVIM-4 was consistently embedded within conserved class 1 integron-associated genetic contexts on IncHI2A-rep1088 plasmids. In contrast, blaNDM displayed heterogeneous genomic organizations involving multiple plasmid backgrounds and frequent chromosomal integration. Together, our findings show that bacterial hosts and carbapenemase-carrying genetic elements follow distinct ecological trajectories within hospital WW ecosystems. Integrating longitudinal environmental surveillance with comparative genomics provides new insights into the persistence of clinically important carbapenemases across interconnected environmental and clinical reservoirs.