Water Research

The selection of appropriate viral indicators for evaluating wastewater treatment performance remains challenging because candidate markers have rarely been compared systematically within a unified analytical framework. Here, we collected influent and effluent samples monthly for one year from two wastewater treatment plants in Japan and conducted, to our knowledge, the first comprehensive comparison of 19 viral targets and one protozoan target using high-throughput quantitative PCR. Pepper mild mottle virus (PMMoV) was consistently detected at high concentrations, showed limited seasonal variability, and exhibited an approximately 1.0 log10 reduction, comparable to those observed for pathogenic viruses. In contrast, Carjivirus, formerly known as crAssphage, was present at the highest concentrations but showed significantly greater reduction than pathogenic viruses. Tomato brown rugose fruit virus (ToBRFV), despite its high abundance and emerging recognition as a potential marker, exhibited pronounced seasonal fluctuations. Other Tobamovirus species, such as cucumber green mottle mosaic virus and tobacco mild green mosaic virus, exhibited similar removal but lower prevalence compared with PMMoV. Overall, PMMoV demonstrated the most balanced performance in terms of abundance, stability, and removal behavior, supporting its use as a robust indicator for monitoring virus removal in wastewater treatment.

Wastewater treatment plants (WWTPs) are known reservoirs of antibiotic resistance genes (ARGs). Non-antibiotic compounds such as antidepressants may further promote ARG acquisition through horizontal gene transfer (HGT). Desvenlafaxine, a serotonin-norepinephrine reuptake inhibitor (SNRI) listed on the EU Surface Water Watch Lists, is among the most frequently detected antidepressants in WWTP effluents, yet its role in HGT has not been examined. Here, we detected desvenlafaxine at the highest concentrations among four antidepressants monitored across three municipal WWTPs in western New York. Using Acinetobacter baylyi ADP1 as a model recipient in natural transformation assays (n = 6), we found that desvenlafaxine significantly increased transformation frequency at 10 mg/L (1.74 {+/-} 0.33-fold) and 50 mg/L (1.49 {+/-} 0.19-fold; Padj < 0.05). Effects were independent of reactive oxygen species or membrane permeability stress, consistent with its very low toxicity (IC20 ~1353 mg/L). Instead, desvenlafaxine induced dose-dependent increases in membrane fluidity and shifts to less negative zeta potentials, suggesting that electrostatic interactions between its cationic amine group and the negatively charged membrane reduce surface repulsion and facilitate plasmid proximity during uptake. Non-targeted proteomics revealed a biphasic response: at 10 mg/L, competence-associated proteins (PilB, ComM) were upregulated and STRING analysis identified networks linked to membrane transport, transcriptional regulation, and envelope remodeling, while no connected network was recovered at 50 mg/L. Electron microscopy confirmed higher pili frequency at both doses. Together, these findings reveal an overlooked role of this non-antibiotic pharmaceutical in promoting ARG spread from wastewater environments.

Enteroviruses (EVs) are ubiquitous contaminants of surface waters, where they can remain infectious for long periods of time. Most methods used for EV monitoring are unable to distinguish between infectious and non-infectious particles or between EV types. Because different types exhibit both distinct environmental persistence and health implications, there is a need for type-resolved infectivity measurements. Here we developed Integrated Cell Culture-Nanopore Sequencing (ICC-NanoporeSeq), a method combining short-term cell culture amplification with Nanopore sequencing of the VP1 gene. The ICC approach was adapted from a previously described ICC-RTqPCR protocol, while the NanoporeSeq workflow was derived from a clinical EV typing protocol and optimized for environmentally circulating EV types. Using samples containing known concentrations of ten EV types, the NanoporeSeq method accurately and reproducibly recovered the original proportions of all EV types after correction of biases. Furthermore, type-specific calibration curves generated with ICC-NanoporeSeq enabled quantification of the infectious concentrations of six EV types, allowing a simultaneous and type-resolved assessment of infectivity in mixed samples. Overall, ICC-NanoporeSeq provides a scalable approach for the parallel analysis of multiple EV types. Compared with the predecessor ICC-RTqPCR method, it eliminates the need for multiple type-specific PCR primers and can therefore be readily expanded to include additional EV types. IMPORTANCECurrent methods used to detect EVs in environmental samples generally measure viral genome copies without determining whether viruses remain infectious, limiting their use in public health risk assessment or water quality monitoring. At the same time, available infectivity assays are often labor-intensive and cannot distinguish between different EV types. Here, we developed ICC-NanoporeSeq, a method combining cell culture and Nanopore sequencing to simultaneously quantify the infectious concentrations of multiple EV types in samples containing mixed EV populations. The method provides an efficient and scalable approach for studying EVs in complex environmental matrices. ICC-NanoporeSeq has potential applications in wastewater-based epidemiology, environmental surveillance, and disinfection studies, where understanding the persistence of different EV types simultaneously is crucial.

Mass gatherings pose significant public health risks by facilitating the spread of infectious diseases. While wastewater-based surveillance (WBS) has been widely used to monitor pathogens in high-income settings, its use as a practical, multi-pathogen surveillance tool during mass gatherings in low- and middle-income countries remains limited. This study aimed to assess the operational feasibility, epidemiological significance, and public health utility of multi-pathogen WBS during the African Nations Championship (CHAN) football tournament in Uganda. Wastewater surveillance was conducted at Mandela National Stadium during eight match days in August 2025. Moore swabs were deployed at 38 manholes receiving wastewater from different toilet facilities across the stadium to capture representative wastewater samples. Samples were processed using Nanotrap(R) microbiome virus particles to concentrate pathogens, followed by nucleic acid extraction. Samples were analyzed for multiple enteric and respiratory pathogens, including Mpox, using quantitative PCR (qPCR). Descriptive analyses were performed to characterize pathogen detection patterns, positivity rates, and temporal distribution across surveillance sites. A total of 304 wastewater samples were collected and analyzed, of which 259 (85.2%) tested positive for at least one pathogen. Multiple pathogens were consistently detected across sampling days, with enteric pathogens predominating, particularly Shigella spp. (53.6%), Rotavirus A (35.9%) and Enterovirus (32.2%). The mpox virus was also detected in a notable proportion of samples (28.6%) across several sampling days. Respiratory pathogens, including SARS-CoV-2 (11.8%) and Influenza B (8.2%), were identified intermittently at lower frequencies. Pathogen diversity varied over time, with up to eight pathogens detected on a single day, and co-detection of multiple pathogens observed in the majority of positive samples. Cq value distributions further demonstrated variability in detected signal patterns across pathogens. Surveillance findings informed real-time public health interventions, including sanitation reinforcement, intensified hygiene promotion, environmental disinfection, and targeted risk communication, strengthened syndromic surveillance with on-site triage, and targeted environmental health assessments of food handling and wastewater infrastructure. These findings demonstrate the operational feasibility and public health utility of integrating multi-pathogen wastewater-based surveillance into mass-gathering preparedness and response frameworks in low-resource settings. By capturing diverse pathogen signals and informing targeted interventions during the CHAN football tournament, WBS can provide actionable population-level insights that can support outbreak preparedness and response. Scaling WBS within national preparedness systems could strengthen epidemic intelligence, enhance early warning capacity, and support data-driven public health decision-making during future mass gatherings and emerging infectious disease threats.

Respiratory Syncytial Virus (RSV) is responsible for a substantial health burden worldwide, particularly among children and older adults. In 2023, novel immunoprophylactic interventions for RSV were approved, underscoring the need to monitor circulating RSV lineages and detect mutations that could compromise intervention effectiveness. Here, we implemented wastewater-based genomic RSV surveillance by integrating digital PCR and amplicon-based sequencing within Switzerland's national wastewater monitoring program. We tracked RSV subtypes and individual mutations across the 2024-2025 peak season in six Swiss cities. RSV-A and RSV-B co-circulated nationwide, and both exhibited similar epidemiological dynamics estimated from their subtype-specific effective reproduction numbers. No previously reported F protein mutations relevant to prophylaxis efficacy were identified. Genetic diversity analysis of wastewater-derived sequences reflected patterns previously reported in clinical data, with higher diversity in RSV-A than RSV-B and greater variability in the G compared to the F gene. These findings demonstrate the potential of wastewater-based RSV surveillance for monitoring RSV dynamics and diversity and establish a national baseline for RSV evolution during the first season following vaccine implementation in Switzerland.

Extracellular vesicles (EVs) are evolutionarily conserved mediators of intercellular communication released by cells into biological fluids and the extracellular environment. Despite their growing relevance in biomedical and veterinary research, knowledge on EVs in marine bivalves remains limited. The aim of this study was to optimize tailored protocols for EV isolation from the hemolymph of the Manila clam (Ruditapes philippinarum) based on density gradient ultracentrifugation (dgUC) or size exclusion chromatography (SEC). EV-enriched fractions were identified through nanoparticle tracking analysis, protein quantification, transmission electron microscopy, and cryo-electron microscopy. Both methods successfully isolated small EVs (<200 nm). While dgUC yielded higher-purity preparations, SEC provided a higher recovery rate and compatibility with downstream metabolomic analyses. Metabolomics performed on SEC fractions and on hemolymph, revealed that EV-enriched fractions possessed a distinct metabolic signature including enrichment in metabolites associated with nucleotide metabolism, glycolysis, redox regulation, and energy metabolism. Furthermore, we performed a pilot investigation into the presence of EVs released into conditioned water by Manila clams. Using tangential flow filtration and ultrafiltration, EVs were successfully concentrated from water samples and characterized by nanoparticle tracking analysis, CONAN assay, atomic force microscopy, and electron microscopy. Our findings demonstrate the feasibility of isolating EVs both from Manila clam hemolymph and from conditioned water, providing the first evidence of water-derived EV recovery in aquatic animals. Although further methodological refinement is needed to improve the purity of EVs isolated from water, and additional characterization studies are required to better define the molecular composition of clam-derived EVs, these results establish a foundation for future investigations into the role of EVs in bivalve biology and their potential application as minimally invasive biomarkers for aquaculture, environmental monitoring, and ecosystem health assessment.

Sewer biofilms represent dynamic interfaces for exchange of bacteria and antibiotic resistance genes between biofilms and the overlying wastewater. Using inline, biofilm reactors, the movement of bacteria and 16S rRNA and carbapenemase genes (blaKPC, blaVIM, blaNDM, blaOXA-48-like, and blaIMP) between wastewater and sewer biofilms was investigated. Established, complex biofilms without these {beta}-lactamase (bla) genes, absorbed resistant bacteria within two minutes of exposure to high concentrations of resistant cultures in lab settings. Carbapenem-resistant organisms from these high-concentration source biofilms transferred to downstream biofilms over 60 minutes of representative sewer shear flows. Mass balances of bacteria and genes in biofilms versus wastewater under representative shear flow showed that biofilms exposed to resistant cultures contributed more to the wastewater than to the downstream biofilms. In field studies, established, complex biofilms without target carbapenem-resistant bacteria and genes from wastewater within hours and then stabilized between 2 to 15 days, not varying by more than 0.5 MPN/cm2 or 0.5 log gene copies (GC)/cm2. In contrast, metagenomic profiles of the bacterial community species continued to change up to 21 days. Established biofilms with resistant bacteria and genes exposed to tertiary-treated wastewater without target carbapenemase genes or meropenem antibiotics did not lose resistant genes or bacteria over nine days of exposure (i.e., < 1 log GC/cm2 reduction). Results show that sewer biofilms contribute to the resistance-gene signal found in sewer wastewater by absorbing and releasing bacteria and genes. Consideration of sewer biofilm dynamics is essential for more accurately interpreting wastewater bacterial concentrations in wastewater-based epidemiology studies. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/726639v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@19f6ce0org.highwire.dtl.DTLVardef@1a507c8org.highwire.dtl.DTLVardef@1a2013dorg.highwire.dtl.DTLVardef@ff8613_HPS_FORMAT_FIGEXP M_FIG C_FIG

Bacterial membrane vesicles (BMVs) have emerged as important contributors to the dissemination of antibiotic resistance genes (ARGs) in the environment. Here, we developed a high-performance immunomagnetic isolation method that improves the purity and selectivity of BMV recovery from wastewater, minimizes contamination from eDNA and viruses, and enables differentiation of BMVs originating from Gram-positive versus Gram-negative bacteria with minimal cross-reactivity. Using this approach, we found that ARGs such as the kanamycin resistance gene (kanR) was highly abundant in BMVs from both raw and treated wastewater, exhibited persistence following treatment, and retained the ability to generate antibiotic-resistant bacteria via transformation. Metagenomic sequencing further revealed that tetracycline resistance genes were the most abundant ARG class across all wastewater samples, while the composition of BMV-associated ARGs differed from the bulk ARG profile. These findings highlight the critical yet underrecognized role of BMVs in the spread of antimicrobial resistance and underscore the need to address BMV-mediated pathways within a One Health framework linking environmental and human health.

BackgroundBenzene, toluene, ethylbenzene, and xylene (BTEX) are volatile aromatic hydrocarbons that are widespread environmental pollutants arising from petroleum processing, fuel combustion, and other industrial activities. Persistent BTEX contamination poses substantial risks to human health and ecosystems, underscoring the need for effective long term remediation strategies. Microbial bioremediation is a promising and sustainable approach for BTEX removal, but development of these approaches requires accurate detection of the genes and pathways responsible for substrate specific degradation. Although profile hidden Markov model (HMM) databases are widely used for functional annotation, existing annotation resources lack the substrate-specific resolution needed to distinguish between closely-related BTEX-degrading enzymes with different catalytic specificities. ResultsWe developed BTEXgenie as a sensitive annotation tool that uses custom HMMs built from alignments of experimentally validated BTEX degradation proteins to identify genes involved in the initial steps of aerobic and anaerobic BTEX degradation. BTEXgenie improved detection of anaerobic BTEX degradation genes that were absent from KOfam annotations. In benchmarking against the KEGG KOfam HMM database, BTEXgenie achieved 17.73%higher overall sensitivity while maintaining comparable specificity at 97.02%across genes involved in BTEX degradation pathways. When applied to environmental metagenomes, BTEXgenie recovered pathway patterns consistent with reported site characteristics and known degradation potential. In addition to gene annotation, BTEXgenie supports downstream interpretation through KEGG pathway-based visualization of detected functions and Circos-based visualization of genomic hit distributions. ConclusionsBTEXgenie is a substrate-specific annotation tool built from custom HMMs for detecting genes involved in BTEX degradation. By integrating gene annotation with pathway and genome-level visualizations, BTEXgenie facilitates characterization of microbial BTEX degradation potential in environmental and comparative genomic studies.

Coastal marine environments are increasingly recognised as reservoirs of antimicrobial-resistant (AMR) pathogens. However, it remains challenging to recover high-quality genomes of clinically relevant bacteria present at low abundance from complex natural systems. Here, we applied culture-enriched metagenomics to systematically track the diversity and dynamics of major AMR pathogens within the coastal marine system of St. Johns Island, Singapore, as a model ecosystem for pathogen surveillance. Selective media-based enrichment recovered 773 metagenome-assembled genomes (MAGs) from 92 multi-matrix environmental samples, which includes coastal water, sediment, and seaweed, capturing diverse AMR ESKAPE and Vibrio species. Distinct bacterial signatures and dispersal patterns were observed in each niche, for example, microbes that signal human impact was detected at the beach, while fish-associated pathogens were present at the aquaculture facility outlet. Notably, the high-quality MAGs enabled subspecies-level identification and supported the AMR gene detection across six distinct coastal habitats. Detailed differences in the recovery of specific pathogens across enrichment media were also identified, demonstrating the methods efficacy in finding media suitable for surveillance of specific organisms, such as deciding between liquid or solid formulations. MAGs recovered from culture-enriched metagenomics were highly similar to genomes obtained from pure isolates, as demonstrated for Klebsiella pneumoniae. The preserved culture-enriched stocks were capable of recovering organisms of interest when individual isolates were required for further study. Overall, our findings highlight the utility of culture-enriched metagenomics as a cost-effective, sensitive approach to uncovering the genomic landscape of pathogens with environmental reservoirs, with implications for AMR surveillance and ecological risk assessment.

To understand the utility of healthcare facility-level wastewater surveillance (WWS) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it is important to correlate wastewater SARS-CoV-2 RNA detection with the number of clinical infections. WWS for SARS-CoV-2 was performed at three skilled nursing facilities (SNFs) over 25 weeks. Electronegative membrane filtration (enMF) and Nanotrap(R) Magnetic Virus Particles (NP) virus concentration methods were compared. Extracts were tested by droplet digital polymerase chain reaction. Spearman's correlations ({rho}) between wastewater virus RNA concentrations and infection counts were calculated. From split wastewater samples, enMF recovered higher SARS-CoV-2 RNA concentrations than NP. Combining data from all facilities, the median concentrations were 53.0 versus 38.6 gc/100 mL for enMF and NP, respectively (p=0.001). Using enMF, correlations were moderate to strong at SNF A ({rho} ranged 0.67 to 0.86, all p-values <0.001). Weak to moderate correlations can be explained by the sampled manhole not representing the entire facility (SNF B, {rho} ranged 0.47 to 0.72, p-values ranged <0.001 to 0.12) and longitudinal data gaps from summer heat and equipment maintenance (SNF C, {rho} ranged 0.14 to 0.59, p-values ranged 0.52 to <0.01). WWS can be a valuable tool for tracking dynamics of SARS-CoV-2 infections in healthcare facilities.

The Pamir Plateau is a transboundary water tower whose source lakes serve as critical biogeochemical hubs with implications for downstream freshwater security. However, it remains unclear how environmental shifts in these high-altitude lakes reshape the microbial communities that drive ecosystem functioning and water safety. Here, we conducted a multi-omics survey across 20 lakes spanning Chinese and Tajikistani Pamir. Our results revealed that prokaryotes exhibited lower diversity but higher among-lake connectivity in China, while eukaryotes showed higher diversity but stronger dispersal limitation. These contrasting biogeographic responses triggered profound rewiring of microbial associations. Under intensified anthropogenic pressures, Chinese cross-kingdom networks decoupled from environmental constraints and became more centralized and complex. Conversely, Tajikistani lakes maintained more modular networks governed by hydrochemical filtering. Critically, this rewiring mediated a trade-off between multifunctionality and potential biosafety risk, with higher element cycling abundances in Chinese lakes, whereas Tajikistani lakes harbored larger biosafety burden dominated by virulence, pathogen, and toxic-algae potential. Incorporating network topology also substantially improved the prediction of these ecological consequences. These findings highlight the importance of network-informed monitoring and management strategies to safeguard ecosystem sustainability in transboundary Pamir lakes under global change.

Sequencing-based wastewater surveillance is emerging as an important tool in pathogen-agnostic threat detection, potentially enabling early identification before capture through clinical surveillance systems. However, virus sequences of human pathogens are typically low in abundance in wastewater while much of the data is unclassifiable at the read level. This presents a challenge because genomes may not assemble well for novel pathogens of interest, but read-based methods cannot currently separate novel from previously seen unclassified sequences. Using ultra-deep untargeted sequencing of the wastewater RNA virome performed by the CASPER consortium (321 samples), we constructed a wastewater virus genome database (WVDB) with the goal of expanding the set of available high-quality non-redundant reference genomes. The first version of this database contains 21,015 near-complete viral genomes, of which the majority are ssRNA bacteriophage (79%). We additionally recovered genomes for putative plant and vertebrate-infecting viruses, human enteric viruses, and viruses whose host could not be predicted. Fewer than 4000 genomes had matches in previously published virus genome databases, and WVDB captured around one fifth of the reads that could not be classified by Kraken2. Further expansion of WVDB will provide a comprehensive resource of RNA virus genomes for characterization of viral diversity and dynamics in wastewater across space and time.

Quaternary ammonium compounds (QACs) are high production volume biocidal compounds increasingly scrutinized for their potential to promote antimicrobial resistance spread. This study compared the release of QACs, QAC resistance indicator genes (qacE/qacE{Delta}1), and QAC tolerant bacteria from livestock and human waste streams into the environment. Five livestock farms with on-farm biogas plants (BGPs), a rural and an urban municipal wastewater treatment plant (WWTP) were studied in parallel. In WWTPs, <1% of incoming QACs were discharged with treated wastewater but 10-20% were transferred to sewage sludge. QAC concentrations in sewage sludge far exceeded those in raw and digested manure. The qacE/qacE{Delta}1 genes were detected in all samples with a higher relative abundance in solid than liquid samples. Relative abundances of QAC tolerant fast growing heterotrophic bacteria cultivated under high nutrient conditions at 37{degrees}C were higher in human than livestock waste streams. Providencia and Pseudomonas dominated the cultivated QAC tolerant bacteria in both systems but showed higher QAC tolerance when originating from human waste streams. Additionally, Enterobacteriaceae with higher QAC tolerance were cultivated from human waste streams. Most QAC tolerant strains carried antibiotic resistances without strong system differences. Only few strains carried the qacE/qacE{Delta}1 gene indicating that other mechanisms must be responsible for the increased QAC tolerance. In conclusion, QACs, qacE/qacE{Delta}1, and viable QAC tolerant bacteria including potential pathogenic bacteria were released from livestock and human waste streams into the environment with highest abundances in a post-pandemic sewage sludge sample. Highlights- QACs most abundant in human waste streams, especially biosolids - Higher relative abundance of QAC tolerant bacteria in human waste streams - Pseudomonas and Providencia dominated QAC tolerant bacteria in both waste streams - Enterobacteriaceae with higher QAC tolerance abundant in human waste streams - Most QAC tolerant strains carried additional antibiotic resistances Environmental implicationMunicipal wastewater treatment plants (WWTPs) and livestock farms are hotspots for antimicrobial resistance (AMR) propagation. We compared the simultaneous occurrence of quaternary ammonium compounds (QACs), resistance genes (RGs), QAC-tolerant bacteria, and their multidrug-resistance status in livestock and human waste streams. QACs, indicators of QAC tolerance and AMR occurred in both systems but were higher in WWTPs, especially sewage sludge. Our findings highlight the need for prudent disinfectant use and enhanced waste treatments to reduce the risks of spreading micropollutants, pathogens, and AMR via organic fertilizers or treated wastewater recycled in circular agricultural practice.

Salmonella is a major zoonotic foodborne pathogen, and antimicrobial resistance (AMR) in Salmonella presents a significant public health challenge. Whole-genome sequencing (WGS) offers a more rapid and comprehensive method for AMR characterization compared to conventional antimicrobial susceptibility testing (AST), supporting antimicrobial therapy and surveillance efforts. In this study, Oxford Nanopore Technology (ONT)-based WGS was performed on 1,490 Salmonella isolates collected through nationwide surveillance in Taiwan in 2025. Genotypic resistance inferred from WGS data was compared with phenotypic AST results to assess the performance of ONT-WGS. Overall, WGS-inferred resistance showed high concordance with phenotypic resistance for most antimicrobials. However, major genotype- phenotype discordance was observed, attributed to four categories: (i) breakpoint-dependent classification, (ii) reduced or absent phenotypic expression of resistance genes, (iii) MIC modulation by ramAp, and (iv) absence of known AMR determinants. Notable discrepancies included tigecycline resistance without known genetic determinants, nalidixic acid resistance linked to ramAp-mediated MIC elevation, and a high prevalence of colistin resistance (35.4%) in S. Enteritidis without identifiable AMR determinants. Additionally, a significant proportion of ESBL- and AmpC-producing isolates were classified as susceptible or intermediate to cefotaxime and ceftazidime under CLSI criteria, highlighting the potential for misclassification and treatment failure. These findings demonstrate that ONT-WGS enables accurate, comprehensive AMR characterization, offering direct identification of AMR determinants and minimizing misclassification due to breakpoint-based AST interpretations. When interpreted appropriately, WGS can support better antimicrobial selection and serve as a valuable alternative to conventional susceptibility testing.

BackgroundCase-based infectious disease surveillance is subject to ascertainment bias when testing intensity varies across time and population subgroups. We previously developed a regression-based test adjustment methodology using Standardized Testing Ratios (STRs) to correct for differential testing patterns in COVID-19 surveillance data. Wastewater-based surveillance (WWS) measures viral burden in the community independently of diagnostic testing behavior, making it a valuable external validation tool for test-adjusted case estimates. MethodsWe analyzed 111 weeks of paired wastewater and case surveillance data from Ontario, Canada (July 19, 2020 to August 28, 2022). Wastewater SARS-CoV-2 signals from 107 sewersheds across 34 public health units were normalized within sewersheds and aggregated using population-weighted averages. We compared wastewater correlations with crude reported and test-adjusted case counts using Spearman rank correlations, linear regression, and negative binomial distributed lag nonlinear models (DLNM), stratified by epidemic period. ResultsTest-adjusted cases correlated substantially more strongly with wastewater signals than crude reported cases overall (Spearman {rho} = 0.849 vs. 0.679; linear R{superscript 2} = 0.609 vs. 0.191). The advantage of test adjustment was greatest during the Omicron wave, when population-level diagnostic testing contracted sharply following PCR eligibility restrictions ({rho} = 0.924 vs. 0.604; R{superscript 2} = 0.815 vs. 0.470). DLNM incorporating the wastewater signal explained substantially more variance in test-adjusted than crude reported cases (McFadden pseudo-R{superscript 2} 0.898 vs. 0.776), despite similar lag-response structure for both outcomes. ConclusionsWastewater surveillance provides compelling independent validation of a previously described test adjustment methodology for COVID-19 case surveillance. The agreement between wastewater signals and test-adjusted cases was strongest precisely when testing scarcity was most severe, supporting the use of test adjustment to recover accurate infection dynamics from case surveillance data during periods of changing testing access and policy.

Numerous studies have shown that the abundance of antibiotic-resistant bacteria (ARBs) or antibiotic-resistance genes (ARGs) in soil increases after irrigation with wastewater. However, it is unclear whether this increase is due to the selection effects of pharmaceutical residues in the irrigation water or the continuous introduction of ARBs and ARGs with the wastewater. Further, it is unclear how the binding of antibiotics to natural colloids (1-1000 nm) affects their biological effects compared to truly dissolved substances (< 1 nm). We conducted competition experiments with resistant and susceptible Acinetobacter baylyi BD413 strains in wastewater, as well as in colloidal and truly dissolved extracts of soils irrigated with wastewater. Although the concentrations of our six target antibiotics were far below the measured minimum selective concentrations of the tested strains, we demonstrate that the resistant strain was favored in the wastewater and the colloidal extracts. In contrast, the truly dissolved fractions exhibited weaker and more variable selective effects. A non-targeted analysis revealed the presence of 82 additional substances in our extracts, including further antibiotics, pesticides, and different non-antibiotic drugs that may influence the selection of our resistant A. baylyi BD413 strain. Our findings suggest that antibiotic resistance is selected for in wastewater and wastewater-irrigated soils. This cannot be explained by antibiotic concentrations alone, but may also arise from the effects of complex mixtures of co-occurring contaminants, particularly those associated with colloidal particles.

Naphthenic acids are amphipathic compounds whose toxicity has primarily been attributed to narcosis toxicity to cell membranes. However, few methods exist that specifically study the membrane disruption and toxicity of this complex family of cyclic, polycyclic and acyclic alkyl-substituted carboxylic acids. Here we describe a whole cell biosensor approach that relies on the ability of Pseudomonas aeruginosa, a ubiquitous environmental organism and opportunistic pathogen, to sense membrane damage (narcosis) and induce protective genes to repair and protect the outer membrane. Many classes of membrane disrupting antimicrobials induce the expression of two operons that encode protective defense systems against outer membrane (OM) damage, including antimicrobial peptides, chelators, and detergents. We demonstrate that the pmrF and spdE2 transcriptional lux reporters are induced by exposure to individual NA compounds with diverse structures, as well as mixtures and naphthenic acid fraction compounds (NAFCs). To further support the narcosis hypothesis, we demonstrated that NA permeabilizes the outer membrane to assist in lysozyme killing, and disrupts the inner membrane integrity, allowing uptake of the DNA binding dye propidium iodide. The conventional OM permeability assay that measures NPN fluorescence is not applicable to study NAs, because they stimulate NPN fluorescence in the absence of cells. This narcosis biosensor approach constitutes a rapid and simple method to measure narcosis and could be developed as a novel toxicity indicator of oil sands tailings.

In todays world, point-of-care nucleic acid detection still remains extensively constrained and limited by the heavy dependence on centralized urban instrumentation facilities and complex assay workflows. Here, we elucidate a glucometer-based analytical platform that enables label-free detection of nucleic acids and the nucleic acid amplification products through a simple redox-mediated mechanism. The approach leverages the potassium ferricyanide (K3[Fe(CN)6])/ potassium ferrocyanide (K4[Fe(CN)6]), redox system, which is intrinsic to commercial glucometers, complementing with interactions between methylene blue (MB) and nucleic acids. These interactions transduce concentration differences in nucleic acids into quantifiable electrochemical signal readouts. Distinct varied signal outputs are observed between single-stranded and double-stranded DNA, enabling the direct detection as well as integration with nucleic acid amplification tests (NAATs), including polymerase chain reaction, rolling circle amplification, and loop-mediated isothermal amplification. Optimization of reaction parameters and conditions leads to enhancement of the overall signal discrimination and sensitivity across various assay formats. This innovation repurposes widely available off-the-shelf glucometers as a low-cost, portable nucleic acid detectors, thus eliminating the need for any specialized instrumentation. Our results enumerate and establish a generalized and scalable strategy for nucleic acid sensing. The platform thus supports sustainable and environmentally responsible point-of-care testing, thereby enabling improved accessibility and public health monitoring at resource-limited and remote settings.

Micro- and nanoplastics (MNPs) are now recognized as ubiquitous dietary and environmental contaminants, yet practical strategies to reduce gastrointestinal exposure remain limited. This study evaluated whether Qi601, a heat-inactivated Limosilactobacillus fermentum biofilm-derived postbiotic, could bind plastic particles and reduce intestinal epithelial plastic burden. Prior probiotic studies have demonstrated live bacterial adsorption of MNPs and mitigation of MNP-associated toxicity in vivo; here, we evaluate whether a nonviable postbiotic preparation can produce analogous MNP-binding and epithelial-protective effects. Qi601 durably bound polystyrene nanoplastics under in vitro simulated digestion conditions. In Caco-2 intestinal epithelial monolayers, Qi601 reduced surface-associated and intracellular nanoplastic burden in both protection and rescue models, indicating decreased epithelial particle interaction both before and after established nanoplastic exposure. Multimodal imaging, including confocal microscopy, atomic force microscopy, and scanning electron microscopy, confirmed close physical association between Qi601 and nanoplastics. Finally, a first-in-human proof-of-concept chewing-gum study showed Qi601 binding in the human mouth to heterogeneous gum-derived microplastic fragments released during mastication. Together, these findings support the concept of postbiotic intervention for gastrointestinal epithelial protection against ingested MNPs.