Environmental Science: Water Research & Technology

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.

Methods to concentrate wastewater samples are essential for sensitive environmental surveillance of infectious diseases. We defined six main principles used to concentrate viral pathogens in wastewater and performed a systematic review and meta-analysis of their performance. PubMed and Web of Science were searched on 31 January 2025 using terms wastewater, sewage, concentration methods and wastewater surveillance. We included all studies comparing [≥]2 concentration methods for virus detection. Our search identified 49 eligible studies published since 2013 across seven continents. We ranked the performance of evaluated methods in each study and generated an overall performance metric for each method principle by virus group (enveloped vs. non-enveloped) using Plackett-Luce analysis. Precipitation and filtration methods were the most studied, while magnetic bead-based and centrifugation were least studied. Magnetic bead-based methods were more effective for concentrating enveloped viruses (63% of pairwise comparisons), whereas flocculation performed better for non-enveloped viruses (60%). However, no single method strongly dominated and method rankings were variable between studies. This study provides evidence-based guidance for selecting wastewater concentration methods to support environmental surveillance of viral pathogens.

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.

Respiratory infections caused by bacterial pathogens like Mycobacterium tuberculosis and Bordetella pertussis have increased since the COVID 19 pandemic, yet clinical surveillance of both suffers from underreporting and delayed diagnoses. Wastewater monitoring is a valuable public health surveillance tool that can help fill gaps in clinical data yet has rarely been applied to respiratory bacterial pathogens despite evidence of bacterial shedding via excretion types that enter wastewater. In this study, we investigated the possibility for wastewater monitoring of two bacterial respiratory diseases, tuberculosis and pertussis, using two case studies of wastewater monitoring for M. tuberculosis and B. pertussis. We retrospectively measured concentrations of these pathogens in wastewater samples collected longitudinally from communities with and without known outbreaks of these diseases. We designed and validated a novel B. pertussis specific assay for the NAD(P) gene; B. pertussis nucleic acids were detected sporadically in wastewater during an identified outbreak. We used a highly specific, established assay for M. tuberculosis nucleic acids, and found low concentrations of the marker in wastewater that were lag-correlated with clinical incidence rates 5 weeks later. Findings support the potential of wastewater monitoring for M. tuberculosis and B. pertussis to enable identification of communities with outbreaks of tuberculosis and pertussis and provide early warning for tuberculosis.

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.

Source-separated organics (SSO) are widely processed via anaerobic digestion to produce biogas, yet alternative conversion pathways could generate higher-value products. Here, we demonstrate long-term continuous production and recovery of medium-chain carboxylic acids (MCCAs) from SSO via microbial chain elongation using a bench-scale anaerobic bioreactor operated for 911 days. The reactor was fed with SSO samples collected from two full-scale municipal organics processing facilities in Toronto, Canada, capturing facility-specific and seasonal variability in SSO composition. MCCA production depended strongly on the availability of lactate as an electron donor, which varied with SSO preprocessing operations and outdoor collection temperatures. To mitigate product inhibition, an in-line extraction system using hollow-fiber polydimethylsiloxane (PDMS, also known as silicone) membranes was integrated with the anaerobic membrane bioreactor, providing a robust and solvent-free alternative to solvent-based extraction methods. Maximum MCCA yields reached 0.31 g MCCA/ g VSfeed, with notable octanoic acid production (up to 20% of total MCCA), and production rates up to 0.84 g L-1 d-1. Acidification of the alkaline extract produced a phase-separated MCCA-rich oil ([~]95% purity) without addition of downstream separation steps. Microbial community analysis of the reactor revealed enrichment of putative chain-elongating bacteria, including Eubacterium and Pseudoramibacter species, while shifts in SSO feedstock microbiomes influenced substrate availability and product spectra. These results demonstrate the feasibility of sustained MCCA production from municipal organic waste streams and highlight opportunities to integrate chain elongation with existing anaerobic digestion infrastructure.

Wastewater treatment plants act as convergence zones for antibiotic residues, antibiotic-resistant bacteria (ARB), and antimicrobial resistance genes (ARGs), yet conventional processes are not designed to mitigate resistance dissemination from their effluents. While chemical disinfectants are generally effective, soluble quaternary ammonium compounds (QACs) can generate subinhibitory exposure gradients that promote resistance selection and co-selection both during treatment and after release into receiving waters. Here, we evaluate a contact-restricted alternative: benzyldimethyldodecyl ammonium chloride (BDMDAC) immobilised onto hydroxyapatite microparticles as a reusable and retainable post-treatment polishing strategy. Across single-strain assays, treated wastewater exposure, and experimental community evolution, immobilised BDMDAC-functionalised particles (BDMDAC-FPs) achieved concentration-dependent antimicrobial activity without detectable biocide leaching. Optimal exposure (200 mg/L, 4 h) resulted in a ~5.5 log reduction in total bacterial abundance and removal of clinically relevant ARGs. Antimicrobial efficacy was retained after one reuse cycle, supporting operational stability. Plasmid-borne QAC ARGs did not confer protection, and no enrichment of qac-associated or non-QAC ARGs was observed. Conjugation assays demonstrated suppression of horizontal gene transfer even under suboptimal exposure, and mobility-associated markers remained stable or declined during long-term community incubation. Collectively, the data support a contact-restricted mechanism in which antimicrobial pressure is spatially confined to the particle interface, generating high local lethality while limiting diffuse subinhibitory exposure. This spatial confinement decouples antimicrobial efficacy from classical disinfectant-driven resistance selection and mobility amplification. Immobilised BDMDAC-FPs therefore provide a mechanistically distinct and evolution-conscious framework for wastewater polishing technologies.

Mobile laboratories (MLs), whether vehicle mounted or portable, provide a versatile platform for on-site wastewater and environmental surveillance (WES) of pathogens, particularly in remote locations with limited laboratory infrastructure. However, molecular workflows intended for ML deployment require careful optimization to account for locally available equipment, consumables, infrastructure, workforce capacity, and operational constraints. In this study, we optimized an integrated ML workflow combining Oxford Nanopore Technologies (ONT) for shotgun metagenomics, multiplex metabarcoding for community level microbial analysis, and Biomeme based qPCR for targeted pathogen analysis. To further explore the potential of metagenomics for resistome assessment, we evaluated two whole metagenome enrichment approaches for their ability to improve detection of antimicrobial resistance genes. We introduce and validate a novel ONT based strategy for multiplexed sequencing small subunit (SSU) rRNA amplicon sequencing, enabling simultaneous profiling of bacteria, archaea, and microeukaryotes in complex microbial communities with multiplex metabarcoding. Sample pretreatment and nucleic acid (NA) extraction in this ML workflow were optimized using a combination chemical mechanical lysis approach followed by magnetic bead based NA purification. Workflow performance was verified using a mock community (ZymoBIOMICS Microbial Community Standard, Zymo Research, USA) and wastewater samples spiked with inactivated Mpox virus (MPXV), demonstrating accurate taxonomic representation and sensitive MPXV detection. Comparison with a commercial ZymoBIO bead beating kit for sediment sample showed ML NA extraction performed comparably. The time efficient multiplex metabarcoding workflow enabled simultaneous profiling of bacterial, archaeal, and eukaryotic diversity and produced results more concordant with qPCR based pathogen detection than the REPLIg Cell Whole Genome Amplification (WGA) & Whole Transcriptome amplification (WTA). The protocol for Mpox virus genome characterization was successfully validated for whole genome sequencing (WES) based detection and incorporated into the standard ML workflow. Across both high and low biomass environmental matrices, the Multiple Displacement Amplification (MDA) based metagenomic workflow, combined with the ML NA extraction procedure, reliably reproduced the expected composition of the Microbial Community Standard. Collectively, the integration of ONT technology with MDA metagenomics and mobile qPCR workflows provides an effective One Health approach for pathogen surveillance and outbreak response across heterogeneous environmental settings, which was later further enhanced by an offline bioinformatic and visualization pipeline enabling near real time detection of pathogens and AMR thus early risk assessment.

Background Following the end of a public health emergency of international concern, divergence emerged between reported coronavirus disease 2019 (COVID-19) cases and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater. Exploring viral, clinical, patient, and surveillance-related factors underlying this divergence, we developed models to predict clinically confirmed infections, hospitalizations, and severe cases. Methods In this observational study, we analyzed ~2 years of data from January 2022 in Kanagawa Prefecture, Japan, assessing associations between wastewater SARS-CoV-2 RNA concentrations and confirmed, hospitalized, and severe cases, adjusting for wave and variant effects. Findings Our models based on wastewater viral RNA concentrations showed high predictive accuracy (R^2 = 0.8199-0.9961), closely tracking confirmed, hospitalized, and severe cases. Models derived from earlier waves were applied to subsequent waves with residual correction based on prior prediction errors and maintained good predictive performance (root mean square error = 0.0665-0.2065). Divergence between wastewater viral RNA concentrations and reported cases was not explained by changes in viral shedding. Declines in patients' healthcare-seeking behavior and testing were associated with trends in confirmed cases, whereas milder clinical presentation was associated with severe case trends. The lineages XBB.1.9.2 and BA.2.86 were identified as candidates associated with reduced virulence. Interpretation By incorporating understanding of viral, clinical, and surveillance-related mechanisms, wastewater surveillance may enable prediction of case trends approximately one week earlier than official reporting and inform healthcare capacity planning.

Antimicrobial resistance (AMR) is a significant and growing threat to human, plant and animal health, the global economy, and food security. The One Health approach to AMR recognises the role of the environment in the evolution, emergence, and dissemination of AMR. In part, this is due to anthropogenic pollution that releases AMR organisms alongside cocktails of compounds that may select for AMR in situ, which then pose an exposure risk to humans and animals. This has spurred growing interest from cross-sectoral stakeholders in environmental risk assessment (ERA) of antibiotics, with regards to their selective potential. Many different experimental and modelling approaches have been used to determine the lowest concentration of an antibiotic that may select for AMR. Debates continue regarding which individual approach, if any, may be best for determining concentrations of antibiotics that may select for AMR, for ERA purposes. This paper contributes to this ongoing discourse by refining and using a previously published method SELECT (SELection Endpoints in Communities of bacTeria) to rapidly generate predicted no effect concentrations for resistance (PNECRs) for 32 antibiotics on the premise that reduction in growth of complex community of bacteria correlates with selection for AMR resistance genes. The database of PNECRs of antibiotics presented here is the largest generated using a single experimental, empirical approach that will aid future efforts towards creating a standardised test. PNECR data were used to conduct ERAs using measured environmental concentrations of antibiotics to rank antibiotics by potential selection risk in different environments. The experimental approach and statistical code have been made open access, with online tutorials available to facilitate other laboratories using the SELECT 2.0 method. Finally, we discuss the limitations of this approach and how these could be addressed in future studies.

Microbial fuel cells (MFCs) represent a promising technology for the simultaneous treatment of wastewater and bioelectricity generation. In this study, the MFCs are conceived as functional modules to be integrated into hydroponic cultivation systems, acting as a prosthetic rhizosphere capable of coupling wastewater treatment and bioelectrochemical activity with plant nutrition improvement. We compared the electrochemical performance of different microbial consortia comprising the electroactive bacterium Shewanella oneidensis, the plant growth promoting rhizobacterium (PGPR) Pseudomonas putida, and the plant biomass-degrading fungus Ophiostoma piceae, along with the supplementation with the quorum sensing (QS) analogue molecule 1{square} dodecanol. These microbial consortia are tested in MFCs fed with wastewater and root exudates to analyze enhanced feedstock assimilation, electricity production, and the generation of plant growth-promoting substances (PGPS). From an electrochemical perspective, we evaluated planktonic growth, anode adhesion, substrate consumption, and the production of redox-active molecules and PGPS such as flavins and siderophores respectively alongside key electrical production parameters, including current output and power. Among the different microbial configurations tested, the consortium combining S. oneidensis, P. putida, and O. piceae exhibited the highest electrical production potential. Moreover, within this framework, we detected the extracellular production of siderophores in MFCs containing P. putida, suggesting a potential role supporting hydroponic crop growth. Furthermore, the addition of 1-dodecanol led to an improvement of the bioelectrochemical parameters. These results highlight the potential of synthetic microbial consortia in MFC-based systems not only to enhance electricity generation from wastewater but also to provide added value in integrated hydroponic applications through rhizosphere-like functions.

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.

Microbial communities play a central role in compost-bedded pack (CBP) systems by driving organic matter decomposition and nutrient cycling. The objective of this study was to characterize and compare the bacterial community structure of CBP from two dairy farms in Cordoba, Argentina, using 16S rRNA gene sequencing. Two CBP systems were evaluated: Martin Bono (MB; 30 months in operation) and Angela Teresa (AT; 20 months). The MB system was established on natural soil without bedding addition and included concrete feed alleys, whereas AT was initiated with peanut shell bedding and lacked concrete alleys. In both systems, compost was tilled twice daily. Two samples per farm were collected at a depth of 30 cm during winter 2019. Raw Illumina reads were processed using the DADA2 pipeline, including quality filtering, error modeling, denoising, and chimera removal. A total of four samples yielded 2,503 amplicon sequence variants (ASVs), with approximately 76% of reads retained after filtering and chimera removal, indicating high-quality sequencing data. Taxonomic analysis revealed that bacterial communities in both systems were dominated by phyla typically associated with compost environments, including Actinobacteriota, Proteobacteria, and Firmicutes. Differences in relative abundance between systems suggested shifts in community composition associated with management conditions.

Industrial waste containing hydrophobic pollutants, like oils and hydrocarbons, is toxic and difficult to degrade, posing both ecological and human health risks. Biosurfactants are eco-friendly surface-active compounds produced by microorganisms, known for their ability to lower surface and interfacial tension, enhancing the solubility and bioavailability of hydrophobic compounds, facilitating their breakdown. The current study focuses on isolating biosurfactant-producing bacteria from industrial waste sources near Dhaka, Bangladesh, and characterizing their properties, determining potential usage. Using diesel-enriched nutrient agar, bacterial strains were isolated and screened for biosurfactant production by oil displacement, emulsification index (E24%), and drop collapse assay. The most promising isolates were characterized according to their biochemical activities and 16S rRNA amplicon-based sequencing. Isolation and characterization of the surfactants have been carried out using chromatographic techniques. The identified bacteria passed the drop collapse and oil displacement tests. CTAB agar assay, indicates their anionic nature, showing an emulsification index ranging 10-41%. The potential biosurfactant producers belong to Bacillus, Pseudomonas, Acinetobacter, and Enterobacterium genera. The surfactants showed antibacterial, antifungal, and plant growth promotion activity and have been characterized in terms of pH stability, salinity, adhesion, and temperature tolerance. The study successfully identified and characterized potential biosurfactant-producing bacteria from industrial waste, highlighting their efficiency in breaking down hydrophobic pollutants and hydrocarbons. These microorganisms provide a green and economical substitute for synthetic surfactants due to their biodegradability and lower toxicity. Upon further research and scaling, these bacteria can be a good source of biosurfactants for potential applications in industrial, agricultural, and biomedical fields. IMPORTANCEThe study carries high significance as it creates multi-disciplinary scopes for utilizing these environmentally adapted biosurfactant-producing bacteria in industry, agriculture, and medicine. Since the bacterial isolates have hydrocarbon degradation ability, upon optimization for higher production, industrial usage in oil refinery and other industries can be adopted. Due to their biodegradable nature, usage in wound healing bandages and as antimicrobial agents in medicine will be noteworthy. The isolates have plant growth promotion ability and utilizing them as biofertilizer will reduce the dependency on chemical fertilizers. This is the first detailed report on biosurfactant-producing bacteria from this industrial waste-polluted Turag River of Dhaka City. Moreover, it compiles detailed screening protocols and methods for analyzing such environmentally friendly microbes. Such characterization also opens the scope for optimizing the production of the surfactant compounds on a large scale and utilizing them commercially.

Current mechanical and chemical recycling strategies address less than 10% of global plastic waste, necessitating alternative valorization routes. Biological upcycling via enzymatic depolymerization combined with microbial conversion of the resulting monomers offers a promising pathway to transform mixed plastic waste into valuable alternatives. Here, we employed a single engineered Pseudomonas putida KT2440 for simultaneous co-utilization of five plastic monomers including ethylene glycol, terephthalic acid, adipic acid, 1,4-butanediol, and L-lactic acid, which can be derived from enzymatic hydrolysis of polyethylene terephthalate (PET), polybutylene adipate-co-terephthalate (PBAT), polyester-polyurethanes (PUs), and polylactic acid (PLA). Continuous fermentation over 21 days with alternating mixed-monomer feeds achieved steady state growth and complete substrate depletion, yielding adaptive mutations that informed iterative strain improvement. Further engineering enabled the biosynthesis of (R)-3-hydroxybutyrate (R-3HB), and 0.70 g L-1 R-3HB was produced directly from enzymatic hydrolysates of blended PET, PBAT, and TPU. These results establish a viable bio-based approach for upcycling realistic mixed plastics into value-added bioproducts.

A compact, in-house developed ultraviolet germicidal irradiation (UVGI) system adaptable to static, mobile, or robotic platforms was developed for the effective sterilization of bacteria and fungi using a wireless mode of operation. Under controlled laboratory conditions, its efficacy was evaluated against three representative biofilm-forming pathogens: Bacillus subtilis (Gram-positive, spore-forming, motile bacterium), Escherichia coli K12 (Gram-negative, non-spore-forming, non-motile bacterium), and Candida albicans M-207 (multi-drug-resistant, clinical yeast isolate). Microbial viability following UVGI exposure was assessed using colony-forming unit (CFU) and MTT assays, and morphological alterations were characterized by scanning electron microscopy (SEM). Cultures were exposed to UV-C radiation at distances of 1-5 m for 15-90 min. CFU assay demonstrated 100% kill of all tested organisms at 1 m and 15 min, corresponding to doses of 600.3, 576 & 697.5 mJ/cm{superscript 2}. Although MTT assays indicated residual metabolic activity under the same conditions, CFU results confirmed that surviving cells were unable to proliferate, highlighting the robustness of UV treatment for long-term inactivation. SEM confirmed distinct morphological alterations such as complete destruction of extracellular matrix & reduction in number of cells indicating cell death with increase in UV dose as compared to controls. A dose & time-dependent inactivation of biofilm-forming bacteria & fungi was observed on exposure to UVGI. Therefore, this pilot study validates the effectiveness of the newly developed UVGI surface sterilizer against biofilm-forming bacterial and fungal pathogens. Overall, the system demonstrates proof-of-concept efficacy under laboratory conditions and holds strong potential for future development and validation in hospitals and other contaminated public spaces. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/715580v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@150cefcorg.highwire.dtl.DTLVardef@450831org.highwire.dtl.DTLVardef@1cfd6borg.highwire.dtl.DTLVardef@1419ba8_HPS_FORMAT_FIGEXP M_FIG C_FIG IMPORTANCEMicroorganisms that form biofilms on surfaces are difficult to eliminate and contribute to the spread of infections in healthcare and indoor environments. There is a need for practical, easy-to-use disinfection technologies that can effectively reduce such contamination. In this study, we developed a compact, in-house, wireless UV-C disinfection system designed for flexible operation across different surface types. The system was evaluated under controlled laboratory conditions using representative biofilm-forming bacterial and fungal pathogens. Our findings show that the system can effectively reduce microbial contamination, demonstrating proof-of-concept efficacy. This work highlights the potential of accessible, non-chemical UV-based technologies and supports their further validation for applications in real-world disinfection settings.

Understanding how airborne particulates disrupt the human alveolar barrier requires in vitro systems that accurately replicate its composition and function. We present a biodegradable lung alveoli-on-a-chip that reproduces the architecture and physiology of the human air-blood interface using a porous poly(lactic-co-glycolic acid) (PLGA) membrane positioned between epithelium and endothelium under air-liquid interface (ALI) culture. The membrane, fabricated by porogen-assisted nonsolvent-induced phase separation, exhibited >50 % porosity, [~]2 {micro}m thickness, and mechanical compliance over 100-fold higher than conventional Transwell inserts, closely resembling the native interstitium. During co-culture, gradual PLGA degradation was compensated by cell-secreted extracellular-matrix (ECM) proteins such as collagen IV and laminin, forming a self-remodeling barrier that maintained integrity for at least 11 days. The platform supported stable epithelial-endothelial co-culture, high transepithelial electrical resistance, and physiologically relevant permeability. To demonstrate its utility, the chip was used to assess pulmonary toxicity of four types of waste-combustion-derived particulates, including rubber, plastic bags, plastic bottles, and textile fibers, delivered apically under ALI conditions. All combustion products reduced cell viability, increased hydrogen-peroxide release, and elevated {gamma}-H2AX expression, indicating oxidative and genotoxic stress, while disrupting barrier permeability. Rubber combustion particles elicited the most severe toxicity, causing the greatest loss of viability, accumulation of reactive oxygen species, and formation of DNA double-strand breaks. Together, these results establish a biodegradable, ECM-remodeling lung alveoli-on-a-chip as a physiologically relevant platform for investigating source-specific particulate toxicity and alveolar-barrier pathophysiology. By bridging environmental exposure models with human-relevant lung biology, this system provides a quantitative and translatable tool for evaluating respiratory risks and therapeutic interventions.

BackgroundHigh-content assays (HCAs) have problems distinguishing biologically significant effects from the incidental effects of non-repeatable technical factors. Non-repeatable results are attributed to variations in the cell culture environment and the numerous, heterogeneous descriptors evaluated. The aim here was to determine whether preprocessing operations impacted the reproducibility of class assignments of experimental data. MethodsBatch effects that could affect reproducibility, i.e., signal/noise ratio, instrumental conditions, and segmentation, were controlled variables. The remaining batch effects, variations in materials, personnel, and culture environment could not be controlled. Descriptors values were measured directly from images. Exploratory factor analysis was used to solve the identifiable and interpretable feature, factor 4. In each of five trials, one sample was treated with the same chemical mixture (EXP) and another with the solvent vehicle alone (CON). ResultsRepeated CON and EXP samples showed significant differences among factor 4 means in data regularized within each trial. The mean of Trial 3 CON differed significantly from all other CON samples. These differences disappeared upon regularization to comprehensive databases. Among repeated EXPs, the Trial 2 mean differed from three other EXPs, but regularization to comprehensive databases had little effect. However, classification patterns were unchanged after regularization to any comprehensive database derived by the same protocol. After regularization to datasets derived by two different protocols, the classification pattern differed but only reflected elevation of differences that had been marginal to statistical significance. Outlier removal was deleterious. Even with the most sparing definition of outliers, over 3% of a single samples contents were removed from most trials. Elimination based on the overall within-trial distributions caused type I and type II errors. ConclusionsNon-repeatable factor 4 means in repeated trials had negligible influence on classification outcomes, so repeatability may not be a good indicator of assay quality. Irreducible batch effects, combined with small sample sizes and skewed distributions of descriptors values, may account for non-repeatability. As the current results are based on real-world data, they suggest that non-repeatability is an uncorrectable feature of these assays. Classification patterns are not affected by several irreducible technical factors, namely materials, personnel, and non-repeatable environmental variables.

Background SARS-CoV-2 genomic surveillance data remain limited in most low and middle-income countries (LMICs), resulting in significant gaps in the understanding of variant circulation and evolution. Wastewater-based epidemiology (WBE) presents a non-invasive, cost-effective, and population-representative surveillance approach that can complement clinical testing, particularly in densely populated urban informal settlements with limited healthcare access. This study aimed to pilot wastewater-based genomic surveillance as a multifaceted public health tool in Kenya. Methods A prospective study was conducted using wastewater samples collected from two WHO-validated environmental surveillance sites -- Eastleigh A (Kamukunji sub-county) and Mathare (Starehe sub-county) -- in Nairobi, Kenya, between December 2022 and October 2023. A total of 272 samples were collected using Moore swabs at a frequency of two to three times per week. Samples were concentrated using Nanotrap(R) Magnetic Virus Particles, and nucleic acid was extracted using the Qiagen QIAamp Viral RNA Mini Kit. SARS-CoV-2 was detected using RT-PCR (TaqPath COVID-19 CE-IVD RT-PCR Kit). Library preparation for whole-genome sequencing was performed using the Illumina COVIDSeq kit, and sequencing was conducted on the Illumina MiSeq platform. Bioinformatic analysis was performed using Terra.bio and RStudio, and phylogenetic analysis included sequences abstracted from GISAID. Results Of 272 samples, 238 (87.5%) tested positive with a cycle threshold (Ct) value of less than 36. Genomic analysis of 181 sequences identified Omicron as the predominant circulating variant, detected in 59% of samples. Other variants included XBB (16%), XBB.2.3(10%), XBB.1.9.X (5%), and additional minor variants. These findings were concordant with clinical sequencing data from Kenya over the same period. Conclusions Wastewater-based genomic surveillance reliably reflected SARS-CoV-2 variant trends observed in clinical data. This approach provides early signals of variant emergence and evolution, offering a cost-effective complement to clinical surveillance in resource-limited settings.

Rapid urbanisation has profoundly shaped microbial diversity across different ecosystems. Freshwater microbiomes are particularly affected by urbanisation activities, such as eutrophication, pollution, runoff, and sewage. This is of significant concern as marginalised communities often depend on waterbodies for their livelihood. Freshwater bodies play a crucial role in maintaining both human and ecological health at population level. Currently, we lack a systematic understanding of the global impacts of urbanisation on freshwater microbiomes in relation to human health, ecosystem functioning, and sustainability. We identified 90 eligible papers from the last 25 years after screening based on the inclusion exclusion criteria. We extracted data that examined changes in the functional traits such as antimicrobial resistance (AMR), nutrient cycling of the microbiome in urban waterbodies and several other factors. Data were extracted by a thematic analysis followed by a narrative synthesis on specific functional traits. This systematic review presents a comprehensive analysis on the changes and challenges brought about by urbanisation on freshwater bodies. Our results indicate that urbanisation leads to reduced bacterial diversity of urban waterbodies, with a striking increase in reporting of Proteobacteria, Cyanobacteria and Coliform bacteria. These insights will help inform public health strategies and sustainable urban planning. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/715732v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@18db38dorg.highwire.dtl.DTLVardef@70a79org.highwire.dtl.DTLVardef@40aaaborg.highwire.dtl.DTLVardef@184ecca_HPS_FORMAT_FIGEXP M_FIG C_FIG Waterbodies in urban areas function as convergence platforms for anthropogenic and environmental microbiomes. Runoffs, wastewater and effluents contain antimicrobial resistance genes and other pathogens that survive in water due to inadequate treatment. Disposal, use, and overflow of wastewater cause restructuration of microbial communities, proliferation of opportunistic microorganisms, and spread of antimicrobial resistance in aquatic ecosystems.