Environmental Science: Water Research & Technology

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.

Wastewater surveillance (WS) offers a non-invasive means of tracking population-level circulation of infectious agents, including viruses linked to cancer. This study provides the first Australian assessment of oncogenic viruses in municipal wastewater by screening 76 influent samples collected over four months from six wastewater treatment plants in Southeast Queensland, Australia. Ten gene targets representing seven oncogenic viruses including Epstein-Barr virus (EBV), hepatitis B virus (HBV), hepatitis C virus (HCV), human herpesvirus 8 (HHV-8), human papillomavirus 16 and 18 (HPV-16 and -18), human T-lymphotropic virus type 1 (HTLV-1), and Merkel cell polyomavirus (MCPyV) were analysed using PCR-based methods. All viruses were detected in wastewater at least once, though with substantial variation in frequency. MCPyV was the most frequently detected virus, appearing in 97.3% of samples with concentrations ranging from 3.09-3.85 log10 gene copies (GC)/50 mL, indicating widespread population exposure. HBV (26.3%) and EBV (15.8%) were detected intermittently across multiple catchments, while HPV-16/18, HHV-8, HTLV-1, and HCV were detected at the lowest frequencies (<8%). This study reports the first baseline dataset for oncogenic viruses in Australian wastewater. More broadly, positive detection of all targeted oncogenic viruses including those associated with low prevalence infections in wastewater demonstrates the potential of WS to complement existing cancer surveillance systems in tracking community-level circulation of these infectious agents.

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.

Trace elements, such as iron, nickel, and cobalt are known to regulate methanogenic activity in anaerobic digestors used for waste valorisation, but the potential role of rare earth elements remains poorly understood. This study investigated the effects of lanthanum (La) supplementation on biogas production, methane generation, volatile fatty acid (VFA) formation, and carbohydrate utilisation in anaerobic digestion (AD). Biomethane potential (BMP) assays conducted under mesophilic conditions (37C) using methanogenic sludge granules, and glucose as substrate, were supplemented with 0.1, 1, 10, and 100 mg/L lanthanum chloride (LaCl3). Biogas production and composition was monitored over a 96-h incubation, while sacrificial, batch bioreactors were used to evaluate temporal VFA and carbohydrate profiles. La supplementation significantly enhanced biogas and methane production in a concentration-dependent manner. The highest cumulative biogas yield (478.9 mL, corresponding to 179.5 mL biogas/g COD) and methane production (285.7 mL, corresponding to 107.1 mL CH4/g COD) were observed with 100 mg/L LaCl3, corresponding to increases of 88.7% and 186%, respectively, compared with La-free controls. CO2 production also increased with La concentration, whereas hydrogen production remained comparatively low. Acetic and butyric acids represented the dominant fermentation products (80-88% of total VFAs), but profiles of accumulated VFA in the bioreactors diversified with La addition, including showing caproate production, indicating changed biodegradation dynamics in the methanogenic microbiome. These findings demonstrate that lanthanum can stimulate anaerobic digestion performance and methane generation, highlighting the potential as a novel trace element additive to enhance biogas production. Research is now required to elucidate the underlying microbial and biochemical mechanisms, and establish optimal dosing strategies for large-scale applications.

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.

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.

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.

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

The physicochemical controls governing metal acquisition, release, and redistribution across biological interfaces remain poorly understood. Biophytometallurgy--the microbially assisted release and recovery of plant-associated metals--was used to probe the directionality of the mechanisms controlling nickel and rare earth element (REE) release from Phytolacca during solid-liquid extraction. Bulk characterization did not support a dominant crystalline REE-phosphate-like host in hydroponically enriched shoots. Dissolution and rebinding experiments instead revealed chemically accessible nickel and REE pools, the latter of which had behaviors consistent with apparent equilibrium-like partitioning under mildly acidic conditions. During sulfur biooxidation, Acidithiobacillus ferrooxidans promoted REE release while providing a competing cell-associated REE sink. Consequently, aqueous REE concentrations reflected net redistribution among the separable plant, solution, and microbial phases instead of dissolution alone. These results establish a framework for studying metal partitioning across complex and coupled biological systems and support a route for aqueous REE recovery from plants without thermochemical conversion to ash.

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.

IntroductionGut microbiota are vulnerable to foreign chemicals (xenobiotics) including pharmaceuticals, environmental pollutants, and dietary contaminants such as aflatoxin B1 (AFB1) and fumonisin B1 (FB1). Assessing the effect of these xenobiotics in the laboratory requires their dissolution in a solvent vehicle, such as dimethyl sulfoxide (DMSO). While DMSO is typically used at low concentrations under the assumption of neutrality, its independent impact on microbial dynamics is a potential experimental confounder that has not been fully explored. MethodsHuman fecal microbiota were cultivated invitrofor 16 days, supplemented with 0, 10, 100, and 1000 ppb of the tested xenobiotics (AFB1 or FB1) in 0.05% DMSO (v/v), with a DMSO-free control included for comparison. Microbial community dynamics were characterized via full-length 16S rRNA gene sequencing, and metabolic activity was assessed by measuring production of short-chain fatty acids and gases. ResultsDMSO significantly altered microbial metabolism and drove the consistent enrichment of Desulfovibriodesulfuricans. This shift occurred across all AFB1 and FB1 treatment groups regardless of their concentrations, indicating that the biological impact of the DMSO vehicle overshadowed the specific effects of the xenobiotics. DiscussionThese findings demonstrate that DMSO can induce significant microbial shifts independent of the xenobiotics under study, potentially confounding biological interpretations. This highlights a critical need for rigorous vehicle validation and the identification of safe thresholds for solvents used in microbiota research.

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

Microbial-mediated plastic degradation has the potential to address the persistent global problems of plastic waste and pollution. Previous work has shown that soils can harbour microbes capable of plastic degradation, but we expect there is a broader diversity of soil microbes capable of metabolizing plastics than identified to date using more traditional cultivation-based screening methods. Here we demonstrate a novel approach to identify putative plastic degrading microbes in soil. We paired in situ, real-time measurements of microbial plastic degradation on conductive sensors with subsequent microbial community profiling of the sensor-associated biofilms exhibiting appreciable degradation. To illustrate the utility of our approach, we focus on microbial degradation of the bioplastic polymer PHBV, poly(3-hydroxybutuyrate-co-3-hydroxyvalerate). We screened a range of soils with the in situ sensors to identify a subset of five soils with high PHBV degradation rates, and confirmed that PHBV degradation was due to microbial activity. We then extracted DNA directly from sensors placed in soils with high measured rates of PHBV degradation and used marker gene sequencing to identify the bacterial and fungal taxa associated with the observed PHBV degradation. We confirmed via in vitro culturing that microbes isolated from the sensors have a demonstrated capacity for PHBV metabolism. Together, these results highlight the benefit and feasibility of using low-cost, in-soil sensors to simultaneously collect real-time data on plastic degradation rates in soil and identify previously unrecognized microbial taxa capable of degrading and metabolizing plastic polymers in situ.

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.

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.

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.

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.

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

Karst groundwater supplies in Virginia are relied on to varying degrees for domestic, agricultural, and municipal water supplies. Further, Virginian caves harbor an estimated 200 endemic invertebrate species. The microbial occupants of Virginias karst aquifers are largely undescribed; characterizing them promises to inform both the scientific description of these systems and the management of a critical water resource. Karst aquifers are heterogeneous, and much of the water moving through them cannot be reached directly; we profiled cave waters both because cave passages offer direct access to active groundwater and because cave water specifically is relied upon by endemic invertebrate species living in caves. Using 16S rRNA sequencing, we characterized aquatic microbial communities in eight Virginia caves, across Virginias four major karst regions. We identified 3,899 unique amplicon sequence variants (ASVs) and found that caves hosted diverse microbial assemblages that differed markedly among sampled sites. These baseline data provide a starting point for future work to understand how seasonal cycles, weather events, and surface disturbances affect the microbial communities present in cave waters and the cave-endemic invertebrates that depend on these waters.

O_LIEnvironmental DNA (eDNA) methods are developing rapidly for ecological surveys, and passive eDNA sampling has emerged as a promising approach for integrating DNA signals over deployment time. However, how deployment duration affects the amount of detectable DNA retained by a sampler remains poorly understood. C_LIO_LIHere, an analytical model was developed to examine how DNA input, degradation, finite substrate capacity and residual retention of degraded DNA shape passive eDNA accumulation. The model distinguishes detectable adsorbed DNA from degraded, non-detectable DNA that may remain on the substrate and continue to occupy capacity. The residual-retention parameter,{theta} , represents the fraction of degraded DNA that remains capacity-occupying, with{theta} = 0 corresponding to complete replacement and{theta} = 1 to complete non-replacement. C_LIO_LIThe model predicts three key behaviours. First, when degraded DNA does not occupy substrate capacity ({theta} = 0), detectable eDNA accumulates monotonically towards equilibrium, but equilibrium recovery increases less than proportionally with DNA input. Thus, passive-sampler measurements can compress quantitative differences in environmental DNA supply. Second, when degraded DNA remains capacity-occupying ({theta} > 0), detectable eDNA can reach a finite peak and subsequently decline. Higher DNA input increases peak yield but shifts the peak earlier, whereas greater substrate capacity increases peak yield and delays the peak. Third, under prolonged deployment with{theta} > 0, a higher-input condition can yield less detectable eDNA than a lower-input condition, reversing the expected input-rate ranking. C_LIO_LIThese results show that passive eDNA recovery can follow saturating, unimodal or intermediate dynamics depending on substrate capacity and post-adsorption DNA fate. Thus, retrieval time cannot be optimised by adjusting deployment duration alone. Although investigators can choose deployment duration and sampler design, including substrate capacity, optimisation also requires calibration or explicit assumptions about ambient DNA supply, DNA degradation rate and residual retention of degraded DNA. C_LI