ACS ES&T Water

Wastewater and environmental monitoring (WEM) was a critical public health surveillance tool for SARS-CoV-2 surveillance during the COVID-19 Pandemic. However, substantial methodological heterogeneity across laboratories continues to challenge the interpretation and thus compromise the actionability of resulting WEM measurements. This study quantifies interlaboratory concordance in SARS-CoV-2 WEM measurements using influent wastewater samples collected between September 2021 and January 2024 at a single wastewater treatment facility within the Ontario Wastewater Surveillance Initiative, analyzed independently by 12 laboratories using their routine methods. In the absence of a known true viral concentration, interlaboratory WEM measurements were evaluated against a facility-specific longitudinal benchmark derived from routine surveillance at the source facility and correlated to clinical surveillance metrics. Concordance was assessed across four WEM measurement units commonly used in practice: SARS-CoV-2 copies/mL, SARS-CoV-2 copies/copies of PMMoV, and their standardized counterpart wastewater viral activity level (WVAL) units of WVAL-standardized SARS-CoV-2 copies/mL and WVAL-standardized SARS-CoV-2 copies/copies of PMMoV. Measurements in each unit were analyzed using complementary analytical frameworks, including categorical concordance metrics, principal component analysis, and linear mixed-effects modelling. Across the study period, interlaboratory measurements consistently captured benchmark temporal dynamics, including major peaks and periods of low activity, but showed substantial variation in magnitude and public-health interpretation across laboratory methods. Concordance was strongest during epidemiological extremes and deteriorated during transitional periods, increasing the risk of misclassification with potentially implications for public health decision-making. To explore potential laboratory methodological drivers of agreement, associations between the benchmark concordance and the laboratory-specific concentration, extraction, and RT-qPCR analytical steps were assessed using Fishers exact tests, alongside extracted-mass threshold analyses. No single methodological factor showed a statistically significant association with benchmark concordance in this study; however, several parameters, including RNA template volume, total RT-qPCR reaction volume, and extracted mass of analyzed settled solids, may warrant further investigation in future studies.

Wastewater-based surveillance (WBS) is widely used to monitor respiratory viruses, yet uncertainties remain regarding how viral RNA concentrations in wastewater reflect infection dynamics. Specifically, diurnal variation in shedding and RNA losses during in-sewer transport can impact measured signals. We conducted a field study in a 5-km trunk sewer (travel time of one hour). Wastewater was sampled at the sewer inlet and outlet using autosamplers collecting time-proportional one-hour composite samples over 24 hours. The one-hour composite samples were analyzed for assessing intra-daily fluctuations, and 24-hour composites for signal change. Biofilms from the sewer-pipe walls were collected at three locations. Nucleic acids were extracted, and SARS-CoV-2, Influenza A/B, and Respiratory Syncytial Virus (RSV) RNA were quantified using a multiplex digital PCR assay. All viruses showed pronounced diurnal variation, with consistent morning load peaks. Viral RNA in the bulk liquid decreased during in-sewer transport, with modelled changes ranging from 15% to 72% across pathogens. Biofilms served as minor reservoirs of viral RNA; for SARS-CoV-2, sequencing revealed similarity between biofilm and bulk liquid RNA. Our study provides a full-scale assessment of in-sewer transport effects on viral RNA and highlights the need to account for complex in-sewer dynamics when interpreting WBS data.

Mass gatherings pose a concern for public health because they are associated with dense crowds, increased social interaction, and travel, all of which can facilitate the rapid transmission of infectious diseases. Wastewater and environmental surveillance (WES) were used for pathogen monitoring during the 2024 NFL Annual Player Selection Meeting (the Draft) in Detroit, MI, an event that drew an estimated 775,000 attendees. Wastewater and environmental samples were queried for respiratory viruses and clinically relevant antimicrobial resistance genes (ARG). WES did not detect an increase in the concentration of monitored respiratory viruses (SARS-CoV-2, IAV, IBV, and RSV) associated with the 2024 NFL Draft. In contrast, WES detected a transient increase in carbapenemase targets in wastewater, primarily driven by a fourfold increase in blaOXA-48. Resistome structure in wastewater was dominated by sampling site characteristics rather than changes associated with the event. The Draft weekend coincided with rainfall-driven combined sewer overflow (CSO), potentially allowing the dissemination of ARG to the environment. In surface waters receiving wastewater effluent, an increase in detection frequency and normalized concentrations for multiple ARG were observed following the Draft. WES provided an overview of pathogen prevalence before, during, and after a large-scale gathering, showing how it can warn of emerging health risks in near real time.

Fjord systems are susceptible to anthropogenic pressures, including discharges from wastewater treatment plants (WWTPs), which introduce micropollutants into coastal waters. We investigated the impact of micropollutants on bacteria and fungi within a fjord system adjacent to a significant petrochemical industry hub on the Swedish west coast. We characterised microbial assemblages along a land-to-sea transect, encompassing freshwater streams receiving agricultural and urban runoff, as well as the direct effluent from a WWTP. Our findings revealed elevated concentrations and a diverse array of micropollutants in the WWTP effluent and the stream running through the urban/industrial zone, highlighting these areas as major sources of pollution to the fjord. Bacterial and fungal communities inhabiting the WWTP effluent and the receiving marine waters near the marine outflow exhibited distinct structural compositions, indicating a selective pressure exerted in part by the micropollutant load. While freshwater sites generally displayed higher overall microbial diversity compared to marine sites, the WWTP effluent showed reduced diversity in both bacterial and fungal communities, likely due to the impact of micropollutants. Interestingly, marine sites far from the WWTP discharges exhibited a recovery in bacterial diversity, suggesting a potential response or adaptation. In contrast, fungal diversity remained comparable to that observed in other marine locations. Multivariate analyses identified physicochemical parameters and nutrients, alongside with summed fungicides and antibiotic stress as key factors driving the community dissimilarities across the fjord. Significant disruptions in potential bacterial metabolism and fungal ecological functions were evident at the WWTP discharge point, underscoring the ecological consequences of wastewater pollution. HighlightsO_LIWWTP discharge is the primary source of complex micropollutants in the fjord. C_LIO_LIAntibiotics and fungicides significantly shape bacterial and fungal communities. C_LIO_LIWastewater impacts reduce microbial diversity and disrupt functional potential. C_LIO_LIMarine sites show microbial recovery and enrichment away from discharge points. C_LIO_LIeDNA and toxic unit modeling link chemical stress to microbiome restructuring. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/711609v1_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@1751e5forg.highwire.dtl.DTLVardef@1d0d78org.highwire.dtl.DTLVardef@15f446aorg.highwire.dtl.DTLVardef@184bb0a_HPS_FORMAT_FIGEXP M_FIG C_FIG

Landfills are heterogeneous built environments embedded in natural freshwater systems. They pose increasing risks of groundwater contamination from metal-bearing leachates over time. The interlinked succession of waste decomposition processes, microbial community membership and metal cycling across a landfills lifespan have not been explored, reducing our ability to predict the long-term environmental impacts of landfills. Working with 1,647 metagenome-assembled genomes from a single landfill, from samples spanning over 39 years of waste decomposition, we identified changes in landfill biogeochemistry and connected these changes to shifts in microbial community composition and predicted functions over time. Comparing between Older (aged 31 - 39 years) and Newer (aged 3 - 20 years) waste cells identified significant shifts in the availability of labile carbon, redox-associated processes, and concentrations of mobile metals - all higher in Newer cells. Newer cells were dominated by chemoorganoheterotrophs, while Older cells contained higher proportions of chemolithoautotrophs and organisms with higher metabolic versatility. Metal resistance and metal cycling genes were significantly more abundant in Older cells. Using geochemistry data from time of filling to present and microbial membership across six landfill cells of different ages, we developed a conceptual model of landfill characteristics across time. This model connects redox conditions and metal fate, highlighting leachate recirculation as a key process impacting many geochemical parameters and defining site chemistry. Our work highlights the substantial changes occurring over the stabilization phase and provides a conceptual framework for understanding this critical, final stage in a landfills life cycle. ImportanceAging landfills pose significant risks to environmental stability and are currently poorly modeled beyond [~]20 years. Our examination of a single landfill across 39 years of waste degradation was a unique opportunity to examine the impact of time within a connected system. Our work connects geochemical data, microbial membership and predicted function, as well as physical processes (e.g., leachate recirculation). Our conceptual model interlinks these facets across the lifespan of a landfill, providing an empirical data-based model of landfill aging. Previous models were extrapolated from younger waste and did not include the microbial dimension - a critical facet of the landfill ecosystem. Our model clarifies processes taking place in older wastes (30+ years), including oxygen infiltration, that have important implications for methane emission and metal mobility and fate over the longer-term.

Wastewater surveillance (WWS) is established as a vital tool for monitoring polio and SARS-CoV-2 with potential to improve surveillance for many other infectious diseases. This study evaluated the feasibility of detecting measles virus (MeV) RNA in wastewater as part of a national WS preparedness trial in Brisbane, Australia, from March to June 2025. Composite and passive sampling methods were employed in parallel at three wastewater treatment plants serving populations between 230,000 and 584,000. Nucleic acids were extracted and analyzed using RT-qPCR targeting MeV N and M genes to distinguish wild-type and vaccine strains. MeV RNA were detected in both 24-hour composite and passive samples on May 26 to 27, 2025 from the largest catchment of 584,000 which also included an international airport. No measles cases were reported in this city or region within 4 weeks of the WS detections. These were confirmed as vaccine-derived measles virus (MeVV) strain via specific RT-qPCR assay. Extraction recoveries varied (11.5% to 70.5%), with passive sampling showing higher efficiency. This is the first report of use of passive samples for detection of MeV. These findings are consistent with other studies reporting WWS results of both MeVV genotype A and wild type genotype B and/or D. It demonstrates the potential for sensitive MeV WWS with rapid differentiation of MeVV from wild type MeV shedding, including in airport transport hubs and with different sample types. Use of WWS could strengthen measles surveillance by enabling rapid detection of MeV RNA and supporting outbreak preparedness and response. This requires optimised methods which are specific to or differentiate wild-type MeV from MeVV. Furthermore, the successful detection of MeV using passive sampling in this study highlights its potential for deployment in diverse global contexts which may include non-sewered settings.

Robust early warning of emerging viruses requires sampling populations that drive spread coupled with assays capable of detecting new viral variants or species. Untargeted viral metagenomic sequencing can, in principle, detect any virus, including completely novel ones. Composite airplane wastewater enables monitoring long-distance travelers from central collection points; however, the performance of untargeted viral metagenomic sequencing in this sample type remains unknown. In municipal wastewater, abundant sewer-associated microbes and ribosomal RNA depress viral relative abundance, limiting metagenomic sensitivity. We compared untargeted viral metagenomic sequencing of composite airplane wastewater with time-matched municipal wastewater from the Greater Boston area. Human viruses and other human-associated taxa had consistently higher relative abundance in airplane samples than municipal samples, while most sewer-associated taxa had lower relative abundance. An increased relative abundance of human viruses lowers the sequencing depth required to detect emerging pathogens, suggesting that metagenomic sequencing of composite airplane wastewater is a cost-effective method for pathogen-agnostic surveillance. ImportanceLong-distance air travelers spread viral pathogens globally, making them an ideal sentinel population for pandemic surveillance systems. Testing composite airplane wastewater offers a practical, noninvasive approach to monitoring the traveler population. However, current surveillance systems rely on tests targeting specific known pathogens, missing novel threats. Untargeted metagenomic sequencing can detect viruses known or novel, but remains expensive to implement at scale; in municipal wastewater, sewer-derived microbes tend to overwhelm human viruses in sequencing data. We investigated whether a hypothesized reduced sewer microbial load in airplane wastewater would lower the sequencing effort required for viral detection. Understanding the performance of metagenomic sequencing in this context informs the design of cost-effective early-warning systems for emerging pandemics.

Anthropogenic oil spills are a major source of hydrocarbon pollution, yet freshwater oil spills are studied less than marine once. We hypothesize that microorganisms from freshwater natural oil seeps are adapted to use oil as carbon source and could serve as a seedbank to accelerate degradation of anthropogenic oil spills. To test this, microcosms were set up using water and oil from a natural oil seep in Germany, while light oil and oil naive river water simulated an anthropogenic spill. Seven conditions combined different water types (adapted, naive) and oil types (heavy, light, mixed). Oil degradation was monitored over 81 days via reverse stable isotope labeling, and pH and microbial communities were analyzed by 16S rRNA gene amplicon sequencing at the start and end. Microcosms with adapted microbes exhibited higher oil mineralization rates. In mixed-oil incubations, simulating the application of a microbial seedbank, degradation rates were 0.26 mM/day with adapted microbes versus 0.15 mM/day in naive water. Applying seep-derived microbes to naive light-oil microcosms increased hydrocarbon mineralization by 32%. These results suggest that leveraging natural microbial seedbanks could accelerate oil weathering and reduce the environmental impact of freshwater oil spills, offering a promising strategy for spill mitigation if applied safely. ImportanceFreshwater oil spills remain poorly studied despite their substantial contribution to global hydrocarbon pollution. This study demonstrates that microbial communities from freshwater natural oil seeps are pre-adapted to degrade crude oil and can significantly enhance the breakdown of anthropogenic oil spills. Applying such microbial seedbanks increased hydrocarbon mineralization by over 30%, highlighting their potential as an effective and environmentally relevant tool for oil spill mitigation. These findings support the development of nature-based strategies to accelerate oil weathering and reduce the environmental impact of freshwater oil spills.

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

Mine tailings contribute to environmental heavy metal contamination through the formation of acid mine drainage (AMD). Microbially-mediated processes such as iron and sulfur redox cycling influence metal mobility. Here, we applied an integrated metagenomic and metaproteomic approach to profile microbial communities across vertical geochemical gradients in legacy copper/nickel tailings in Sudbury, Ontario, Canada. From 43 samples, we recovered 454 non-redundant metagenome-assembled genomes (MAGs), revealing diverse populations within the Actinobacteriota, Desulfobacterota, and uncultured lineages such as Candidatus Eremiobacterota and SZUA-79. Functional profiling identified 301 putative iron- and sulfur-cycling MAGs, including those within the Ca. Eremiobacterota and SZUA-79 phyla. Metal resistance genes were widespread and diverse, with abundances that did not correlate with measured metal concentrations. Proteomic data confirmed in situ expression of selected metal resistance genes and iron/sulfur metabolism genes, despite limited protein recovery from this challenging matrix. Our findings highlight both the depth of microbial diversity in metal resistance and metal biogeochemical cycling in mining waste, as well as the technical challenges that currently limit genomic and proteomic sequencing coverage in low-biomass, metal-rich matrices. This work also presents new protocols for multi-omics data capture and analysis from metal contaminated environments, including new protein extraction and bioinformatic gene annotation tools. HighlightsO_LIMetagenomics recovered 454 non-redundant MAGs from copper/nickel mine tailings, revealing high taxonomic novelty including uncultured Ca. Eremiobacterota and SZUA-79 lineages. C_LIO_LIA custom HMM-based pipeline targeting metal resistance genes uncovered a widespread and diverse set of metal resistance genes across MAGs in tailings, which did not correlate with metal concentrations. C_LIO_LIMetaproteomics validated in situ expression of both iron/sulfur cycling genes and metal resistance proteins, although low biomass and contamination limited proteomic sequencing coverage. C_LI

Influenza A viruses (IAV) remain a persistent One Health threat, and whole-genome sequencing from wastewater offers a promising surveillance tool. However, IAV is at low abundance in wastewater, making it difficult to sequence. We benchmarked four targeted enrichment methods suited for whole-genome sequencing including custom and off-the-shelf amplicon and probe-based methods. Our custom HA tiled-amplicon panel was sensitive, fast, and cost-effective, making it suitable for monitoring low-abundance seasonal variants of known subtypes. However, its reliance on conserved and intact primer-binding sites limited primer design to fewer subtypes. A previously published universal amplicon method targeted all IAV subtypes, but it performed poorly in wastewater due to its reliance on intact genome segments. Probe-capture methods were resilient to RNA degradation and mismatches, potentially enabling broader surveillance and detection of emerging strains. However, probes were costly, labor-intensive, and less sensitive than tiled-amplicon. When testing compatibility of sequencing methods with upstream virus concentration and extraction methods, ultrafiltration-based virus concentration outperformed large-volume direct extraction with all four sequencing methods. This set of benchmarking comparisons and custom panels provides needed information for the translation of IAV genomic sequencing into a routine component of wastewater surveillance.

Enumeration of the heterotrophic plate counts of culturable microorganisms (HPC) is used for the assessment of water quality before, during and after the drinking water treatment processes and monitoring of integrity of the drinking water distribution systems. Any substantial change in HPC is a warning of potential contamination, treatment failure, or intrusion. This study produced data for international standardization of Reasoners 2 Agar (R2A) method. Interlaboratory studies were applied to find out which inoculation technique, spread plate or pour plate, is more applicable, and what is the acceptable transport and storage time between the sampling and initiation of the analysis. Based on the produced interlaboratory data, spread plate inoculation followed by incubation for 7 days at 22 {degrees}C was selected as the standard method, and it is recommended to analyse samples as soon as possible, but the samples may be kept at (5 {+/-} 3) {degrees}C for up to 24 hours after the sampling prior to examination. Performance characteristics of the method were determined in a single laboratory according to ISO 13843:2017 by using process water from waterworks, bottled water, chlorinated and non-chlorinated tap water, and well water intended for human consumption. For quality assurance of the R2A medium, the use of control strains of Bacillus subtilis subsp. spizizenii, Pseudomonas fluorescens and an additional strain of Sphingomonas paucimobilis was verified during the work. The R2A method is especially suitable for determination of micro-organisms forming colonies after a prolonged incubation time, enabling HPC enumeration from biostable waters with low nutrient levels and low temperature. Such waters usually produce zero counts when nutrient-rich formulations of culture media with short incubation times are employed. Further, the nutrient limited conditions of R2A minimize the colony size and overgrowth in all kinds of water providing improvement to the HPC determinations.

Uranium (U) and arsenic (As) are both ubiquitous contaminants in the American southwest, posing risks to humans, animals, and the environment. Depleted uraniums (DU) chronic effects and mechanisms of toxicity are incompletely understood. Differential gene expression of concomitant exposures to identify markers of toxicity have not been undertaken until now. Continuous low-dose, high-dose, and concomitant exposures are investigated using the larval zebrafish (Danio rerio), with exposure paradigms lasting from embryo collection until sampling at 5 days post fertilization (dpf). Herein, we describe overall differential gene expression with counts and pathway enrichment statistics using both gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The raw dataset has been deposited in NCBIs Gene Expression Omnibus (GEO) repository [1] under the accession number GSE319292 [2]. O_TBL View this table: org.highwire.dtl.DTLVardef@9b121aorg.highwire.dtl.DTLVardef@c17073org.highwire.dtl.DTLVardef@1bdc2b9org.highwire.dtl.DTLVardef@13b130aorg.highwire.dtl.DTLVardef@15f1d22_HPS_FORMAT_FIGEXP M_TBL C_TBL VALUE OF THE DATAO_LIUranyl nitrate (UN), a water-soluble depleted uranium species, and sodium arsenite (As) are both ubiquitous contaminants in the American southwest, posing risks to humans, animals, and the environment. The United States Environmental Protection Agency (EPA) has set maximum contaminant limits (MCL) of 30 ppb U atoms and 10 ppb As atoms, respectively. C_LIO_LIThese data show differentially expressed genes (DEGs) from larval zebrafish exposed to 1 or 10 {micro}M As, 30 or 300 {micro}g/L UN, or 1 {micro}M As and 30 {micro}g/L UN in combination. Concentrations were specifically chosen based on environmental relevance. C_LIO_LIGene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of up- and down-regulated DEGs are provided to understand the molecular mechanisms of uranium toxicity and inform future studies. C_LIO_LIThese data should be used for biomarker identification and mechanistic interrogation of single and combinatorial exposures of environmentally relevant compounds at realistic exposure levels. C_LI

Infectious disease forecasts can inform public health decision-making. Wastewater monitoring is a relatively new epidemiological data source with multiple potential applications, including forecasting. Incorporating wastewater data into epidemiological forecasting models is challenging, and relatively few studies have assessed whether this improves forecast performance. We present and evaluate a semi-mechanistic wastewater-informed forecasting model. The model forecasts COVID-19 hospital admissions at the state and territorial levels in the United States, based on incident hospital admissions data and, optionally, SARS-CoV-2 wastewater concentration data from multiple wastewater sampling sites. From February through April 2024, we produced real-time wastewater-informed COVID-19 forecasts using development versions of the model and submitted them to the United States COVID-19 Forecast Hub ("the Hub"). We then published an open-source R package, wwinference, that implements the model with or without wastewater as an input. Using proper scoring rules and measures of model calibration, we assess both our real-time submissions to the Hub and retrospective hypothetical forecasts from wwinference made with and without wastewater data. While the models performed similarly with and without the wastewater signal included, there was substantial heterogeneity for individual locations and dates where wastewater data meaningfully improved or degraded the models forecast performance. Compared to other models submitted to the Hub during the period spanned by our submissions, the real-time wastewater-informed version of our model ranked fourth of 10 models, with the hospital admissions-only version of our model ranking second out of 10 models. Across the 2023-2024 winter epidemic wave, retrospective forecasts from wwinference would have performed similarly with and without the wastewater signal included: fifth and fourth out of 10 models, respectively. To better understand the drivers of differential forecast performance with and without wastewater, we performed an exploratory analysis investigating the relationship between characteristics of the input data and improved and reduced performance in our model. Based on that analysis, we identify and discuss key areas for further model development. To our knowledge, this is the first work that conducts an evaluation of real-time and retrospective infectious disease forecasts across the United States both with and without wastewater data and compared to other forecasting models. Author SummaryWastewater-based epidemiology, in combination with clinical surveillance, has the potential to improve situational awareness and inform outbreak responses. We developed a model that uses data on the pathogen concentration in wastewater from one or more wastewater treatment plants in combination with hospital admissions to produce short-term forecasts of hospital admissions. We produced and submitted forecasts of 28-day ahead COVID-19 hospital admissions from this model to the U.S. COVID-19 Forecast Hub during the spring of 2024 and found that it performed well in comparison to other models during that limited time period. To assess the added value of incorporating wastewater data into the model and to investigate how it would have performed had we submitted it during the entire 2023-2024 winter epidemic wave, we performed a retrospective analysis in which we produced forecasts from the model with and without including wastewater data, using data that would have been available in real-time as of each forecast date. Both versions of the model would have been median overall performers had they been submitted to the Hub throughout the season. When comparing the models performance with and without wastewater data included, we found that overall forecast performance was very similar, with wastewater data slightly reducing overall average forecast performance. Within this result, there was significant heterogeneity, with clear instances of wastewater data improving and detracting from forecast performance. We used trends in the observed data to generate hypotheses as to the drivers of improved and reduced relative forecast performance within our model. We conclude by suggesting future work to improve the model and more broadly the application of wastewater-based epidemiology to forecasting.

Interactions between viruses and filter-feeding zooplankton can alter viral persistence in surface waters, with direct implications for water quality and public health risk. However, data on virus-zooplankton interactions and the environmental factors that influence them are still limited. This study evaluated the impact of filter feeding, in the dark and under simulated sunlight, on a bacteriophage (MS2) and a human virus (echovirus11; E11) in the presence of a ciliate (Tetrahymena pyriformis) and rotifer (Brachionus calyciflorus). Dark experiments established organism-dependent baseline removal for each virus, and rotifers showed greater removal of both viruses in comparison to ciliates. Under simulated sunlight, in contrast, experiments with ciliates resulted in greater virus removal compared to experiments with rotifers over a similar timespan (4.2 vs. 2.7 log MS2 in 53-58 h; 3.5 vs. 3.0 log E11 in 24-25 h). Analysis of decay rate constants reveals species-specific shifts in virus removal between dark and light that, depending on viral type and zooplankton species, either accelerate viral attenuation or protect viruses and prolong infectivity. T. pyriformis increases removal under sunlight relative to dark conditions and acts synergistically with sunlight inactivation, whereas rotifers impede sunlight inactivation.

BackgroundRising global temperatures and eutrophication are increasing the intensity and frequency of cyanobacterial harmful algal blooms that release toxins including microcystin-LR (MC-LR). MC-LR inhibits protein phosphatases in the human liver and brain, but its accumulation in the placenta is unclear. Placental transporter expression varies across pregnancy and is influenced by physiological cues, such as low oxygen concentrations which activate HIF1A, and trophoblast cell fusion forming syncytiotrophoblasts that engage CREB-driven transcription. This study examined whether MC-LR accumulates in placental cells, which transporters mediate uptake, and how these transporters are regulated by HIF1A and CREB. MethodsIntracellular accumulation of MC-LR (0.1-10 {micro}M, 3 hour) was measured in human cytotrophoblasts (JAR, BeWo) and extravillous trophoblasts (HTR-8/SVneo) by western blotting for MC-LR-adducted proteins. Organic anion transporting polypeptide (OATP) involvement was tested using cyclosporin A (10 {micro}M), an OATP inhibitor, before exposure to the OATP substrate or MC-LR. Cells were also cultured under 3%, 8%, or 20% O2 to induce hypoxic responses or treated with forskolin (a potent intracellular cAMP inducer) to stimulate cell fusion before MC-LR exposure. ResultsMC-LR accumulated in all three placenta cell lines in a concentration-dependent manner. Cyclosporin A reduced MC-LR uptake by 57% in JAR cells, confirming OATP-mediated transport. Low O2 increased OATP4A1 expression and function but reduced protein phosphatase expression, decreasing MC-LR-bound proteins by 52-72%. Forskolin increased OATP4A1 expression and enhanced MC-LR uptake >2.5-fold. ConclusionMC-LR enters placental trophoblasts via active OATP transport, likely OATP4A1, and uptake increases under hypoxia and trophoblast fusion.

Natural freshwater streams harbor diverse microbial communities that support ecosystem functioning. Due to their great biodiversity and geomorphological characteristics, these ecosystems are often very attractive ecotourism destinations, which makes them highly vulnerable to anthropogenic disturbances. The Agua Azul Waterfalls (Cascadas de Agua Azul, in Spanish), a major tourist destination located in indigenous territories of southeastern Mexico (Chiapas, Mexico), offer a unique setting to investigate how sustained human activity influences microbial diversity and quality of water and sediments. To determine the ecological sensitivity of this freshwater stream to tourism pressure, we sampled sites spanning gradients of tourist activity and conducted an integrated analysis of water and sediment physicochemistry, elemental composition, and the composition of microbial communities (bacteria, archaea, and fungi). Areas associated with ecotourism activities showed notable changes in physicochemical parameters and microbial community composition, indicating localized impacts on this ecosystem. Furthermore, evidence of effective management by local Indigenous communities suggests a partial mitigation of anthropogenic disturbances through ecotourism activities. Our findings highlight the potential of microbial diversity in combination with physicochemical parameters as a tool to detect early stages of human impacts on freshwater ecosystems and establish a basis for future monitoring and conservation efforts. The distinctive characteristics of this site position it as a promising model for advancing our understanding of microbial diversity and the dynamics of freshwater stream ecosystems. ImportanceThis study shows evidence that ecotourism is already impacting the biodiversity and water quality of Agua Azul Waterfalls, a freshwater stream located within a protected natural area in southeastern Mexico. While the water still meets basic quality standards, areas with higher tourist activity show early signs of nutrient enrichment and measurable changes in the types of microbes present and the roles they play in this ecosystem. As the first analysis of microbial diversity in this ecosystem, our work highlights the value of microbes as early and sensitive indicators of human impact. By directly comparing tourist and non-tourist areas, we provide evidence of how recreational pressure is transforming this freshwater environment. We expect that our findings will help guide local communities and policymakers in creating more sustainable tourism practices to preserve the cultural and economic value of this ecosystem before irreversible damage occurs.

Background: Beaches are popular summertime destinations in Canada. However, they can be affected by specific fecal pollution sources, increasing the risk of recreational water illness. Objectives: This study was conducted to determine the risks of acute gastrointestinal illness (AGI) among Canadian beachgoers and to evaluate the influence of different fecal indicator bacteria (FIB) and other water quality measures on assessing these risks. Methods: In a prospective cohort design, beachgoers were recruited at sites across Canada from 2023 to 2025. Sociodemographic characteristics and exposures were determined through an on-site survey, with a 7-day follow-up survey to determine risks of AGI. Bayesian mixed-effects logistic regression models were fitted to evaluate the effects of an ordinal water contact variable (no contact, minimal contact, body immersion, and swallowed water) on the incident risk of AGI, with an interaction included for water quality indicators. The levels of six FIB and water quality measures were assessed: Escherichia coli, enterococci DNA, three microbial source tracking DNA markers (human HF183/BacR287, human mitochondria, seagull Gull4), and turbidity. Results: A total of 4085 participants were recruited, with 67.6% completing the follow-up survey. The overall incident risk of AGI was 2.6%. Both swallowing water and body immersion increased AGI risks compared to no water contact: median of 20 excess cases (95% Credible Interval [CrI]: 4, 64) and 5 excess cases (95% CrI: 1, 19) of AGI predicted per 1000 beachgoers, respectively. Escherichia coli and seagull DNA marker levels were associated with AGI among those who had water contact, particularly among those who reported swallowing water. Discussion: While the overall burden of AGI due to beach water contact in Canada was low, increased risks are associated with E. coli levels particularly among those who swallow water. This could be related to fecal contamination from seagulls. However, there is substantial uncertainty in the predicted effect sizes.

The 18S rRNA gene has emerged as the primary molecular marker for amplicon-based characterization of microalgal communities, including in wastewater treatment systems, yet trade-offs between short- and long-read approaches remain poorly defined. We systematically compared V8-V9 short-read sequencing (Illumina MiSeq), full-length long-read sequencing with ss5ss3 primers (PacBio Sequel II), and computationally extracted V8-V9 regions from long-read data. Both in silico and in vitro analyses confirmed V8-V9 captured broader taxonomic coverage than ss5ss3, though partial reference sequences and taxonomic mis-annotations biased in silico assessments. Long-reads taxonomic advantage was database-dependent, constrained by SILVA databases genus-level curation but fully realized when paired with the species-level-curated and eukaryotes-focused PR{superscript 2} (Protist Ribosomal Reference) database. Long-read sequencing uniquely identified amplicon sequence variants (ASVs) assigned to key phosphorus assimilators (Scenedesmus obliquus, Desmodesmus sp., and Acutodesmus sp.) at species level during successful phosphorus removal in a full-scale microalgal cultivation system, while V8-V9 short-read sequencing revealed ASVs assigned to algal-predatory (Leptophryidae) and bacterivorous (Choanoflagellata and Rhogostoma-lineage) protists when performance declined, suggesting grazing pressure on the phosphorus-removing community. Although both approaches performed comparably for operational monitoring, these complementary strengths support short-read sequencing for routine community profiling and long-read sequencing for detailed functional investigations of Chlorophyta.

Water-miscible metalworking fluids are widely used in industrial processes. Despite the fact that they contain biocides, they are almost always colonized by microorganisms, which degrade different components of the liquid, may clog machines due to biofilm formation and might pose a health risk to workers. In this study, samples from four metalworking machines operated with the same metalworking concentrate from two different locations, were analyzed with respect to microbial growth. Twenty-seven bacterial species and one fungus were identified. From these, twenty species were not observed before as colonizers of metalworking fluids. Growth of microorganisms, resulting health risks, putative contamination pathways and metabolic pathways involved in biodegradation are analyzed and discussed in this study. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/712622v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@16164e6org.highwire.dtl.DTLVardef@1273ee6org.highwire.dtl.DTLVardef@192aa20org.highwire.dtl.DTLVardef@1df4df2_HPS_FORMAT_FIGEXP M_FIG C_FIG