Water Research

Nutrient-rich food-processing wastewaters represent valuable yet under-utilised side streams for sustainable protein production in the form of microbial biomass. Here we present an integrated dual-loop bioprocess that converts soybean-processing wastewater into microbial single-cell protein (SCP) while achieving substantial nutrient removal and product refinement. In the first loop, previously enriched microbial consortia were inoculated and cultivated in four parallel sequencing batch reactors (SBRs) for 44days at a hydraulic retention time (HRT) of 3days. This bioprocess configuration demonstrated features that support future scale-up while maintaining process stability, achieving a protein content of 33.3{+/-}3.2%, doubling the protein yield (15.32{+/-}3.49g dry weight per g soluble TKN) and quadrupling the production rate (0.29{+/-}0.06g dry weight L-1 d-1) compared to operating reactors without inoculation (HRT: 7.2days). Effluent treatment was stable, with 84% carbon and 78% nitrogen removal efficiencies, demonstrating efficient nutrient recovery. The SCP biomass was enriched in functional taxa, including Acidipropionibacterium, Lactococcus, Megasphaera, and Azospirillum, suggesting that reactor conditions and inoculum selection promoted a stable, protein-productive microbial community with potential probiotic benefits. In the second loop, bioreactor effluent was reused as aqueous matrix for heat treatment (60{degrees}C) of the SCP biomass, reducing the RNA content from 8.6% to 2.6%, with a 39% biomass loss accompanied by a 30% increase in total amino acid concentration. Hence, our valorisation approach integrates microbial biomass production, effluent reuse, and product refinement within a circular framework. The system provides a resource-efficient pathway for converting food-sector side streams into high-quality microbial community-based SCP, highlighting its potential scalability for sustainable nutrient and water management.

Surface waters in urban watersheds receive episodic inputs of wastewater, runoff, and road-salt residues during spring, yet the contribution of these short hydrological windows to antibiotic resistance gene (ARG) loading remains poorly resolved. Weekly samples were collected from offshore and nearshore sites in the Detroit River, a Great Lakes transboundary connecting channel, from February to December 2025. Five clinically relevant ARGs encoding resistance to carbapenems, methicillin, and colistin, alongside the fecal marker pepper mild mottle virus (PMMoV), were quantified by qPCR and paired with ten conventional water-quality variables. blaNDM, mcr-1, and blaVIM-7 were not detected while blaKPC occurred as discrete pulses. One week (5 May) accounted for 37.2% of annual offshore blaKPC loading, and three weeks in late April to early May accounted for 72.8%, with peak concentrations reaching 5.4 x 10E3 and 7.2 x 10E3 copies/L. mecA was detected in nearly all samples without a dominant pulse. PMMoV normalization showed blaKPC did not vary seasonally (Kruskal-Wallis p = 0.198), consistent with diluted wastewater during spring precipitation events rather than an emergent source. mecA/PMMoV varied seasonally (p = 0.003) and was lowest in spring, implicating non-wastewater inputs in summer and autumn. Seven water-quality variables were significantly elevated during blaKPC pulse weeks. PCA distinguished pulse from background conditions, explaining 81.3% of variance. A random forest classifier achieved leave-one-out AUC of 0.917; ROC AUC reached 0.943 for total phosphorus, 0.924 for chloride, and 0.974 for the multivariate model. These results demonstrate that blaKPC and mecA operate through distinct source pathways and that routine water-quality monitoring can flag elevated blaKPC risk without additional sampling infrastructure.

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.

Power-to-Gas technologies are emerging as a key strategy to integrate surplus renewable electricity into energy systems, through the conversion of green hydrogen into methane. However, the practical implementation of biological in situ biomethanation is still constrained by operational and design requirements that are incompatible with most existing anaerobic digestion infrastructures. This study demonstrates a stable and efficient mesophilic (37{degrees}C) in situ biomethanation process driven by substrate-induced microbial selection rather than relying on continuous hydrogen supply. Anaerobic digesters co-digesting sewage sludge from a wastewater treatment plant with lipid-rich greases recovered from dairy wastewater developed a pre-adapted hydrogenotrophic consortium capable of effective CO2-H2 conversion under mesophilic conditions. Long-term operation confirmed the robustness and persistence of this microbial structure. Upon H2 addition, methane concentrations up to 82 % were achieved under atmospheric pressure, without biogas recirculation, with hydrogen-to-methane conversion efficiencies up to 90% and methane productivities of 1.64 NLCH4.L-1d-1. 16SrRNA-based microbial community analysis revealed that dairy grease co-digestion selectively enriched hydrogenotrophic methanogens, particularly Methanospirillum, together with syntrophic fatty-acid-degrading bacteria such as Syntrophomonas, promoting efficient interspecies hydrogen transfer. Importantly, the lipid co-substrate enabled the establishment and long-term stability of the hydrogenotrophic pathway independently of hydrogen availability, mitigating challenges associated with intermittent renewable energy supply. Overall, these findings challenge the common reliance on thermophilic conditions, continuous hydrogen input, pressurization, and gas recirculation in in situ biomethanation, demonstrating that substrate-driven microbial selection can replace conventional engineering requirements such as thermophilic operation or reactor modifications, providing a simpler and scalable strategy for mesophilic in situ biomethanation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/731101v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@c62086org.highwire.dtl.DTLVardef@1813ed6org.highwire.dtl.DTLVardef@4462bcorg.highwire.dtl.DTLVardef@1ae2cfb_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG Highlights- Lipid-assisted co-digestion promotes stable biogas and biomethane production - Dairy wastewater greases enable mesophilic in situ biomethanation - An enriched hydrogenotrophic methanogenic consortium yields >82% CH4 - 70-90% H2-to-CH4 conversion efficiency under mesophilic, unpressurized conditions - Substrate-driven microbial selection enables in situ biomethanation in WWTP digesters

Simultaneous removal of organic waste and industrial gypsum was assessed in continuous flow-through bioreactors that treat sulfate-rich sewage sludge. Metabolic fluxes, the composition of microbial communities, and profiles of organic matter in the presence of different organic loads were tracked over [~]190 days. The addition of a pre-enriched microbial community enhanced the rates of sulfate reduction during the establishment of the sludge blanket, but microbial diversity in established reactors depended primarily on organic loading. Organic removal rates were comparable to those in standard anaerobic digesters, but methane production accounted for [~]1% of electron flow compared to >70% in traditional systems. Stoichiometric analyses revealed that molar COD: sulfate ratios below [~]1 favored complete oxidation of acetate by sulfate-reducing bacteria (SRB) and those above [~]2.1 permitted either complete or incomplete oxidation, allowing sulfate reduction and methanogenesis to co-occur. Sequencing of the 16S rRNA confirmed these trends by revealing that the faster-growing SRB that do not oxidize acetate were more abundant at higher organic loads and during the establishment of the sludge blanket, whereas complete oxidizers became more abundant when the molar COD: sulfate ratio was [≤]3.2. In reactors that had been seeded with the pre-enriched communities, acetate-oxidizing SRB became prevalent over the incomplete oxidizers 25-50 days earlier. These results enable targeted design and control of microbial processes and bioreactors that remove waste organics and gypsum while producing less methane due to the competition for acetate between methanogenic archaea and SRB that oxidize acetate.

Methanogenic archaea, such as Methanothermobacter marburgensis, represent a powerful biological platform for carbon capture and valorization, directly converting carbon dioxide (CO2) and molecular hydrogen (H2) into proteinogenic amino acids (AAs). In this study, we present a controlled and scalable strategy for tailoring AA production (biosynthesis and secretion) in continuous gas fermentation. By applying various Design of Experiments (DOE) techniques, we systematically identified and optimized key process parameters governing AA biosynthesis and shaping a targeted AA secretion profile. A hybrid modeling framework combining experimental data with scale-independent parameters derived from computational fluid dynamics (CFD) enabled robust performance prediction across bioreactor scales. This model-driven approach successfully translated the process from 120 mL glass bottles via 2 L to 150 L reactors, corresponding to a reaction-volume scale-up factor of 2000. These findings set the foundation for a robust and predictive platform for sustainable AA production, positioning archaea as a high-potential alternative in industrial biotechnology.

Combined sewer overflows (CSOs) are a major pathway for untreated wastewater into urban streams, yet their role in shaping antimicrobial resistance (AMR) dynamics remains poorly understood. Here, we used high-frequency, time-resolved sampling during two storm-triggered CSO events across two monitoring locations and one stormwater-only control site in an urban stream to quantify how these disturbances affect microbial communities, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs) in an urban stream. CSO events caused rapid, up to two orders of magnitude, increases in bacterial, pathogen, and ARG abundance, with multiple transient peaks occurring within single overflow episodes. However, these increases were largely proportional to the total bacterial load, and most ARGs and MGEs did not change in relative abundance, indicating that CSOs primarily act as mass-transfer events rather than drivers of in situ selection. Downstream attenuation was governed by hydrological dilution despite additional CSO inputs: Both microbial and resistance signals largely returned to baseline within short time frames. This demonstrates that CSOs function as hydrologically driven pulse disturbances that generate acute but transient AMR exposure. Because CSO events lack the sustained pressure associated with continuous wastewater discharges, rapid washout prevents the long-term establishment of sewage-derived resistance. These findings highlight that AMR risk in CSO-impacted systems is driven primarily by short-term exposure rather than by persistent ecological transformation, with important implications for urban water management under increasingly extreme rainfall conditions.

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

Antimicrobial resistance (AMR) is an ever-increasing threat to population health. Industrial, environmental and societal factors are increasingly recognized as important contributors to AMR within communities. Here, we investigated the spatial distribution of AMR genes (ARGs) across Alberta, Canada and their association with socio-economic, immigration-related, and agro-industrial characteristics using municipal wastewater-based surveillance. We analyzed monthly wastewater metagenomes collected between March 2022 and March 2023 across eleven municipalities, representing 39% of Alberta's population. Integration with census data enabled multivariate analysis, revealing that municipal resistome profiles were strongly structured along income and immigration-related population gradients. ARGs spanning 14 resistance classes exhibited distinct distributional patterns across income and immigration gradients, including contrasting associations among beta-lactam, aminoglycoside, and macrolide-lincosamide-streptogramin ARGs, consistent with heterogeneous selection pressures across sub-populations. These findings demonstrate the capacity of longitudinal wastewater surveillance to identify persistent population-level resistome patterns and highlight the importance of incorporating sociodemographic context into AMR surveillance and mitigation strategies.

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 metagenomic sequencing (WW-MGS) enables simultaneous detection of hundreds of pathogens, but its use for quantitative pathogen tracking has not been robustly validated. Like wastewater PCR (WW-PCR), WW-MGS is affected by biases from variable fecal dilution and sample processing, but must additionally contend with the compositional structure of sequencing data, where a taxon's apparent abundance depends on the abundance of every other taxon in the sample. Simple summaries such as a pathogen's fraction of total reads may therefore be poorly suited to quantitative use. We retrospectively evaluated seven normalization approaches that attempt to control for these sources of bias against a baseline of total read relative abundance, using 1,425 samples from the CASPER consortium spanning 25 U.S. sites. Each approach was compared against WW-PCR and clinical data across eight total pathogens. Among the normalization strategies we evaluated, tobamovirus markers, diet-derived plant viruses abundant in human stool, performed best. Normalizing WW-MGS data by tobamovirus-genus counts improved median site concordance for 18 of 19 pathogen and comparison-source combinations. Gains were largest for year-round-circulating SARS-CoV-2 and norovirus and smaller for sharply seasonal pathogens such as influenza and respiratory syncytial virus, where baseline concordance was already high. Tobamovirus normalization rarely degraded concordance, with median gains roughly five times larger than median losses. Tobamovirus-normalized WW-MGS reached clinical concordance comparable to targeted WW-PCR, supporting its use as a quantitative trend-monitoring tool alongside pathogen-agnostic detection.

Disagreement between molecular and culture-based assays for Legionella pneumophila detection is widely reported, yet comparisons have largely been based on direct assay-derived concentrations or binary positive/negative outcomes. However, it remains unclear whether molecular-culture disagreement reflects concentration-level incompatibility or unaccounted methodological and physiological differences related to DNA recovery and cell culturability. In this study, we observed substantial disagreement between molecular and Legiolert assays in source and finished drinking water samples collected from eight full-scale drinking water systems across the United States. Molecular thresholds adjusted for DNA recovery and cell culturability only partially resolved these discrepancies. We therefore developed a probabilistic Monte Carlo framework that incorporates sample-specific DNA recovery and cell culturability to evaluate the quantitative consistency of culturable L. pneumophila concentrations estimated by molecular and Legiolert assays. Quantitatively consistent and inconsistent samples occurred across both binary concordant and discordant classifications, demonstrating that positive/negative agreement poorly reflects concentration-level comparability. Overall, molecular and Legiolert assays showed strong quantitative consistency once sample-specific DNA recovery and cell culturability were considered. A small proportion of persistent inconsistencies at specific sampling sites, coupled with atypical microbial indicators, suggest that sample heterogeneity likely contributed to the remaining discrepancies. These findings demonstrate that integrating DNA recovery and cell culturability enhanced quantitative consistency between molecular and Legiolert assays and supports the use of molecular methods as rapid quantitative tools to complement culture-based L. pneumophila monitoring.

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.

Inshore coastal waters are almost invariably supersaturated with respect to methane and are thereby sources of methane to the atmosphere. We investigated floating algal mats and surface waters of four contrasting inshore habitats and quantified methane concentrations, sea-to-air emissions, and microbial community composition of surface waters over a seasonal cycle to determine the potential for in-situ microbial methane production in shallow oxygen-saturated surface waters with floating algal biomass. 16S rDNA sequencing indicated that Archaea belonging to the genera Methanocorpusculum, Methanosarcina, Candidatus Methanomethylophilus, and some genera from order Methanobacteriales occurred in the floating algal mats. qPCR of the genes encoding the methyl coenzyme M reductase mcrA revealed the highest expression levels during the warmest sampling periods supporting active methane production directly in surface water. Co-occurrence of the Archaea sequences and sequences belonging to the cyanobacterium strain Nodularia PCC 9350 suggests a structural relationship. Our study underscores the significant, yet underexplored impact of methane production on the surface in aggregates of floating algal material. While Nodularia and methanogens can exist independently in surface waters, their co-occurrence in algal mats reveals where the layered mat structure creates distinct microenvironments that facilitate direct metabolic exchange and provide physical stability for both groups, thereby potentially enhancing methane production in these shallow coastal systems.

Background: Helicobacter pylori is a major global pathogen with recognized potential for waterborne transmission. Intermittent water supply affects over one billion worldwide and may promote H. pylori contamination of municipal sources. Whether water supply discontinuity contributes to population-level H. pylori burden has not been examined globally. Materials and Methods: We conducted a cross-sectional ecological analysis of 79 countries with matched utility-level water infrastructure data and country-level H. pylori prevalence estimates from a published global meta-analysis. The primary exposure was continuity of water supply (hours/day). Secondary exposures included non-revenue water percentage (NRW %), pipe breaks per utility, and operating cost coverage ratio. Unadjusted and adjusted linear regression models with heteroscedasticity-consistent standard errors were estimated, controlling for basic sanitation coverage and log-transformed population density. A sensitivity analysis used a population-based measure of water availability on demand. Results: Greater water supply continuity was independently associated with lower H. pylori prevalence in both unadjusted ({beta} = -0.987, 95% CI -1.669 to -0.305, p = 0.005) and adjusted models ({beta} = -1.125, 95% CI -1.876 to -0.375, p = 0.004). Higher NRW % and lower operating cost coverage were each associated with higher H. pylori prevalence after adjustment. Pipe breaks were not significant in regression models though the Spearman correlation was in the expected direction. Sensitivity analysis produced consistent findings. Conclusion: IWS and broader water infrastructure deterioration are associated with higher H. pylori prevalence at the country level. These findings implicate water supply continuity as a potentially relevant environmental determinant of H. pylori transmission and suggest a role for water system investment within long-term gastric cancer prevention strategies.

African swine fever virus (ASFV) poses a major transboundary threat to global swine production, underscoring the need for rapid and field-deployable diagnostic tools. Although quantitative polymerase chain reaction (qPCR)-based assays are the standard molecular assay for ASFV detection, their reliance on centralized laboratory infrastructure, multi-step sample preparation, and trained personnel limit their utility for timely decision-making at the point of need (PON). Here, we report a portable molecular diagnostic platform that enables colorimetric quantitative loop-mediated isothermal amplification (qLAMP) directly from diluted whole blood on microfluidic paper-based analytical devices ({micro}PADs). The assay targets the conserved ASFV viral protein 72 (VP72) and topoisomerase II (TOPII) genes and incorporates objective image-based colorimetric signal analysis to reduce user-dependent interpretation. Using plasmid DNA spiked into whole blood diluted to 5% (v/v) in 5% D-mannitol, the {micro}PAD-LAMP assay achieved a limit of detection (LOD) of 25 copies per reaction (67 copies/{micro}L of whole blood sample) for VP72 targets with no observed cross-reactivity against nine common swine pathogens, demonstrating 100% analytical sensitivity and specificity during in-house testing and 90% and 92% analytical sensitivity and specificity respectively in an external laboratory evaluation. The complete assay was performed within 60 minutes using a portable heating and imaging platform. Together, these results demonstrate a simple, DNA extraction-free molecular diagnostic approach that enables rapid and reliable ASFV detection from whole blood applicable to field-relevant conditions.

Wastewater is a key reservoir and transmission route for antibiotic resistance genes (ARGs), enabling their spread from influent to effluent and into receiving environments. However, how combined selective pressures (antibiotics, biocides, heavy metals, pharmaceuticals) influence resistant bacteria and ARG persistence over space and time remains poorly understood. Likewise, the role of the wastewater microbiome in ARG dynamics is still unclear, as few studies integrate microbiome shifts with chemical and environmental drivers. Here, we investigated how microbiome dynamics, chemical exposures, and environmental conditions shape clinically relevant ARG dynamics from sewage to receiving environments in Guadeloupe, French Caribbean. We analysed data collected from three wastewater continuums, (hospital-based, domestic, touristic) over four campaigns (September 2021-February 2023). We characterised ARG and microbiome composition spatiotemporal patterns and used a mixed-effect model to investigate ARG associations with potential drivers, including exposome factors, microbiome dissimilarity and environmental factors. Several ARGs were negatively associated with microbiome dissimilarity (Bray-Curtis distances) (aac(6)-Ib, aph(3)-III, blaSHV, blaTEM, intI1, qnrS, sul1 and tetM). Negative associations were also observed between upstream-downstream differences in anti-inflammatory drug concentrations and the abundance of aac(6)-Ib, aph(3)-III, blaCTX-M, ermB, intI1, and tetM. In contrast, ARG relative abundance was positively associated with upstream-downstream differences in antibiotic concentrations, suggesting selection along the continuum. These findings indicate that ARG dissemination along wastewater-to-coastal pathways is shaped by opposing processes, with microbiome turnover potentially limiting ARG persistence while chemical gradients promote specific gene enrichment. The outcome is ARG-specific, with implications for antimicrobial resistance risks associated with recreational waters, seafood consumption, and coastal ecosystem interactions.