Environmental Science: Water Research & Technology

Wastewater contains a complex mixture of nucleic acids derived from human cells, microorganisms, diets, and agricultural or industrial inputs. Metatranscriptomics has the potential to broaden the understanding of wastewater viromes, but its utility is constrained by high-abundance RNA molecules that prevent the detection of lower-abundance signals, including human pathogens. Two major sources of this interfering background signal are ribosomal RNAs (rRNAs) from various organisms, and plant-infecting tobamoviruses from human diets, which are often the most abundant RNA viruses in wastewater. These rRNA molecules and RNA genomes can account for upwards of 95% of total RNA sequences, thereby obscuring the detection of lower-abundance viruses of public health importance. This study evaluated whether combined depletion of ribosomal RNAs and genomic RNA from abundant plant tobamoviruses can improve the recovery of underrepresented viral sequences from wastewater. RNA extracts from a large municipal wastewater treatment plant in Calgary, Canada, were processed with or without probe-based depletion of rRNAs and eight abundant tobamoviruses. Metatranscriptomes revealed that depletion reduced rRNA reads by 90%. Reads assigned to tobamoviruses, which accounted for up to 25% of viral reads in untreated samples, were reduced to <2% of viral reads after depletion. This decrease in undesired RNA signal led to an order of magnitude increase in viral read signals and improved assembled viral genome quality. Furthermore, the number of reads assigned to human and animal pathogens increased 42-fold after depletion, enabling the detection of important pathogens like influenza, RSV, and hepatitis A, which were undecteable in untreated samples. Together, these findings demonstrate that targeted depletion of abundant background RNAs improves the detection of low abundance viruses, and enhances the utility of metatranscriptomic approaches for wastewater viral surveillance.

Electrochemical advanced oxidation processes (EAOPs) are increasingly investigated for tertiary wastewater treatment, yet their short-term effects on real wastewater effluent remain poorly constrained. This study investigated real wastewater treatment plant (WWTP) effluent following short-term boron-doped diamond (BDD) electrochemical treatment using an interdigitated double-diamond electrode (iDDE), combined with hydrochemical, stable-isotope and shotgun metagenomic analyses. After 10 min at 7.0 V and 1.02 A, physicochemical parameters and bulk carbon pools remained largely unchanged. In contrast, d18O-DO decreased by 31.3 +/-0.28 permille alongside a small increase in dissolved oxygen (0.16 +/-0.03 mmol/L), indicating substantial oxygen consistent with electrochemical oxygen generation. Shotgun metagenomics revealed pronounced restructuring of the recovered microbial DNA pool, including increases in Comamonadaceae (~12.3% vs. ~25.1%) and Zoogloeaceae (~3.3% vs. ~8.4%), whereas the oxidative-stress-defence gene repertoire showed no coherent response. These taxonomic changes cannot be interpreted as selective survival, as metagenomics do not resolve viability or intra-/extracellular DNA contribution. Overall, short-term iDDE treatment affected the microbial component of real WWTP effluent despite comparatively limited changes in bulk chemistry, highlighting that EAOP effects extend beyond conventional disinfection.

Wastewater sequencing using probe-capture enrichment of public health-relevant viruses is a powerful, non-intrusive approach to monitor infectious diseases, but performance depends on sample type and processing approach. We compared two processing pipelines from wastewater influent samples collected at three timepoints across three wastewater treatment facilities. Each sample was split for parallel processing, with viruses concentrated (1) directly from whole influent using nano-sized affinity particles and (2) by settling and dewatering the solids fraction. Combined DNA/RNA extracts were prepared into libraries using a pre-commercial Illumina protocol, then probe-capture enrichment was performed with Illumina Viral Surveillance Panel (VSP) v1 (66 targets) and v2 (242 targets). Sequencing depth was increased for VSP v2 to accommodate the expanded target set. On average, 160 +/- 146 viral species were detected per sample, with wastewater fraction (sample type) explaining 19% of the variance in viral abundances. Solids contained a higher abundance of DNA viruses compared to RNA viruses, while influent exhibited the inverse. Metagenomic analysis of the VSP v2 sequencing data detected more viral species in influent (median 358) than in solids (median 184), but probe-capture enrichment produced more comparable target-virus readouts across fractions, supporting the use of either fraction for wastewater-based epidemiology.

Antimicrobial resistance (AMR) is a major threat to modern medicine and an emerging environmental pollutant. Wastewater-based monitoring offers a scalable alternative to traditional surveillance by enabling population-level monitoring across One Health compartments. However, it remains unclear how well bacterial variants detected in wastewater reflect those causing clinical infections. Here, we assessed the prevalence of carbapenem-resistant Escherichia coli (CREC) in wastewater from Uppsala, Sweden, and compared wastewater isolates with clinical isolates from the same region and period. We observed partial overlap between wastewater and clinical CREC populations, but several common clinical variants were not detected in wastewater and vice versa. CREC prevalence was an order of magnitude higher in wastewater receiving hospital effluent, yet this did not improve concordance with clinical isolates, suggesting that hospital wastewater may artificially inflate CREC prevalence estimates. These findings indicate that wastewater CREC prevalence does not necessarily reflect the regional clinical burden. Furthermore, metagenomic sequencing of wastewater-derived E. coli populations rarely detected CREC resistance genes, suggesting that CREC abundance is below the detection limit of this approach and that targeted enrichment is required for reliable monitoring. Together, our results show that while wastewater-based monitoring can complement AMR surveillance, it should be interpreted cautiously when used as an indicator of clinical risk.

Wastewater-based epidemiology (WBE) has become a cornerstone of public health surveillance, yet routine regulatory monitoring remains largely focused on respiratory viruses and selecting antimicrobial resistant bacteria. Emerging foodborne parasites, such as Cyclospora cayetanensis, remain excluded from standard environmental surveillance panels despite increasing domestic outbreaks. This study presents a laboratory-based pilot protocol evaluating the feasibility of extracting and quantifying C. cayetanensis from urban wastewater across the Chicago metropolitan area. Using sample concentration via centrifugation and mechanical bead-beating, automated magnetic bead nucleic acid extraction, and digital PCR (dPCR), we demonstrate high-sensitivity detection in municipal influents and sewer nodes. These findings establish a proof-of-concept laboratory methodology to support the expansion of regulatory public health surveillance frameworks to include non-routine protozoan pathogens.

Antibiotic resistance genes (ARGs) travel from cities into rivers and coastal waters through wastewater treatment plants. Monitoring them normally requires metagenomic sequencing, which is sufficiently costly that most utilities can sample only occasionally. Weather and location data are freely available on a daily basis for virtually any location worldwide, making them attractive predictors for identifying where limited sequencing resources should be prioritized. However, whether such models generalize to previously unseen cities remains largely untested, as most published studies train and evaluate models within the same catchments, thereby assessing interpolation rather than geographic transferability. To address this gap, we paired 235 wastewater metagenomes collected from five European cities with 23 abiotic predictors spanning geospatial, meteorological, hydrological, radiative, and temporal domains. Model performance was evaluated using leave-one-group-out (LOGO) cross-validation, in which all samples from one city were withheld for testing while the remaining cities were used for training. CatBoost achieved a median LOGO ROC-AUC of 0.929 and a median F1-score of 0.750. Using freely available environmental reanalysis predictors (meteorological, hydrological, radiative, geospatial, and temporal) - without any metagenomic sequencing - CatBoost achieved a mean ROC-AUC of 0.722, recovering 78% of the predictive performance of the full omics-integrated model. Removing latitude and longitude reduced ROC-AUC by only 0.003, whereas replacing random cross-validation with city-wise validation reduced ROC-AUC by 0.052. Predictive performance varied across ARG classes, ranging from a ROC-AUC of 0.981 for {beta}-lactam resistance genes to 0.762 for glycopeptide resistance genes. These findings demonstrate that freely available environmental reanalysis predictors - spanning meteorological, hydrological, radiative, geospatial, and temporal domains - recover 78% of the predictive signal for antibiotic resistance gene occurrence in urban wastewater, allowing scarce sequencing capacity to be directed to the catchments where it changes a decision.

Coastal waters often experience fecal contamination from human (e.g., septic systems, wastewater treatment catchments and outfalls) and non-human (e.g., wildlife, domesticated pets, and livestock) origins, posing human health risks through contaminated fisheries and recreational waters. Quantitative PCR (qPCR) methods can identify and quantify fecal origins for their management by targeting Bacteroides, a dominant group of gastrointestinal bacteria with high host specificity. This study identified major contributors and drivers of fecal contamination to Mobile Bay, Alabama, an urbanized estuary in the southern United States. We utilized a multi-species qPCR source tracking approach targeting total Bacteroides and human-, pig-, dog-, cow-, and fowl-associated Bacteroides. Water samples and environmental parameters were collected over one year from 13 sites that represent a range of potential fecal inputs common to coastal waters. Human-associated feces were a consistent major contributor to the system (positive in 82% of samples), with localized inputs from pig (wild or domestic) and dog. Freshwater discharge and nitrogen constituents were good predictors of Bacteroides concentrations in this system, while areas with impervious surfaces and developed land cover may be contributing elevated fecal indicator levels. The multi-species qPCR source tracking approach described in this study can be implemented in other watersheds to support the development of better detection, identification, and fecal management strategies for community health of coastal areas.

The anaerobic biotransformation of lindane ({gamma}-hexachlorocyclohexane), a persistent legacy pesticide and challenging subsurface contaminant was modelled using an integrated Monod biokinetics framework. Calibrated against batch experimental data, this model accounted for the dissolution of solid phase lindane and the thermodynamics of reactions involved. The study focused on a methanogenic, lindane-degrading enrichment culture (GT2) that used ethanol as the electron donor, where ethanol fermentation supplied hydrogen to support reductive dechlorination of lindane. A Dehalobacter strain was identified as the lindane-degrading organism, while a member of bacterial order Geobacterales carried out ethanol fermentation. First-order decay constants for lindane-degrading Dehalobacter were estimated from experimental data and showed variation across different growth conditions. The biokinetics model captured interactions among key microbial processes, namely lindane dechlorination, ethanol fermentation, hydrogenotrophic methanogenesis, and acetoclastic methanogenesis. Thirteen biokinetics parameters including maximum substrate utilization rates (k), half-velocity constants (Ks), and decay constants for these microbial processes were estimated through a Bayesian optimization approach. Global sensitivity analysis showed that eight parameters, primarily k and Ks, had significant linear impact on the model output, whereas responses to decay constants were more variable and potentially non-linear. This study proposed an effective modelling approach for characterizing syntrophic microbial growth within enrichment cultures and provides valuable biokinetics parameters estimates for real-world applications of anaerobic lindane bioremediation.

Groundwater contamination by lead and nitrate exceeding the permissible limits of the World Health Organization (WHO) and the Bureau of Indian Standards (BIS) of 10 ppb lead and 45 to 50 ppm nitrate poses a severe health risk of systemic toxicity in humans and animals. Microbial nitrate reduction coupled with microbiologically induced calcite precipitation (MICP) proved to be a novel bioremediation strategy to transform soluble lead nitrate into insoluble lead biominerals. This study presents statistical optimization of operational parameters for nitrate reduction and co-precipitation of biogenic lead carbonate-calcium carbonate by nitrate-reducing bacterial consortia. The SEM, TEM with SEAD, and XRD analysis of the biomineral confirmed lead carbonate co-precipitation with CaCO3. A two-level factorial design was applied to screen significant variables and interactive factors that influence nitrate reduction and biomineral precipitation. The highest nitrate reduction, maximum ammonia production, and biogenic Pb-mineralization efficiency of > 90% were obtained at the optimum conditions (initial nitrate requirement of 600 ppm, temperature 37 oC, pH 8, and carbon content of 5.5 g/L) compared to those obtained under the common process parameters. ANOVA with a high correlation coefficient (R2 > 0.99) corroborated the linear model for the biogenic mineralization process. This study on the biogenic removal of Pb by nitrate-reducing bacterial consortia revealed possible opportunities for large-scale treatment of Pb-contaminated surface and subsurface water bodies.

Wastewater-based epidemiology uses both targeted and non-targeted bioanalytical approaches to detect and track disease-causing microbes in wastewater. Targeted approaches such as quantitative polymerase chain reaction (qPCR) remain widely used while sequencing-based approaches have slowly gained popularity. However, concordance between established targeted molecular assays and sequencing approaches remains incompletely characterized. To assess the validity of sequencing as an alternative to qPCR, we compared outcomes of both methods targeting five respiratory viruses in wastewater samples collected across 16 Texas cities over 4 years (May 2022-July 2026) of continuous sampling. We found positive correlations between qPCR and sequencing measurements, with both methods independently correlating with statewide clinical emergency department visits. qPCR positivity also increased with genomic sequencing coverage, and sequencing demonstrated greater potential than qPCR as an early respiratory virus outbreak detection method. Our findings support metagenomic sequencing as a sensitive and highly specific alternative to targeted qPCR for wastewater surveillance, and reinforce its utility towards long-term longitudinal monitoring of respiratory viruses.

Biological filtration in newly established aquaria depends on the establishment of nitrifying microorganisms that prevent accumulation of toxic ammonia and nitrite. Many aquarists use commercial nitrifying supplements to accelerate biofilter establishment and reduce ammonia and nitrite accumulation. However, the microbial composition and in situ efficacy of these products remain poorly characterized. We evaluated the ability of enrichment cultures containing comammox Nitrospira (CX) and the ammonia-oxidizing archaeon Ca. Nitrosotenuis aquarius (AQ) to serve as aquarium nitrifying supplements, tested alongside a conventional supplement (CS) containing ammonia-oxidizing bacteria. Inoculation of new aquaria containing zebrafish (Danio rerio) with nitrifying supplements resulted in distinct nitrifier profiles within biofilters of each treatment group corresponding with significant reductions in peak ammonia and nitrite concentrations, which were most evident when applied at the maximum tested supplement dose. Treating aquaria with CX, AQ, or CS maintained ammonia and nitrite at low concentrations, and CX effectively prevented ammonia and nitrite accumulation through all stages of aquarium operation and biofilter establishment. After removing all fish from the aquaria, ammonia "spike-in" experiments demonstrated biofilters treated with CX and AQ conferred long-term protection against nitrite accumulation following acute ammonia loading events. Whereas 16S rRNA gene sequences associated with CS were rarely detected within biofilter profiles, those associated with CX and AQ established early and persisted temporally. Overall, results demonstrate how nitrifiers might be differentially adapted to home aquarium conditions and the potential of AOA and comammox Nitrospira to improve biofilter establishment and maintaining safe water quality in newly established freshwater aquaria.

Microplastics are pervasive environmental pollutants that pose a growing concern for human health. Oral ingestion is a common route of human microplastic exposure, yet the proteomic response of the gut epithelium to microplastics remains unclear. This study aimed to investigate the cellular effects of pristine and artificially digested microplastic exposure in primary rat duodenal epithelial cells using untargeted proteomics. Cells were exposed to pristine or digested 0.5 um polystyrene microplastics at 10 or 100 ug/mL for 72 hours and were then analyzed by tandem liquid chromatography and mass spectrometry (LC-MS). Proteins that were both significantly different in intensity compared to controls, with a threshold change of 1.3 or greater, were considered to be differentially expressed. This criterion identified 41 differentially expressed proteins after 100 ug/mL pristine MP exposure, with 19 downregulated and 21 upregulated. Following exposure to 100 ug/mL digested MP, only 3 differentially expressed proteins were upregulated and 7 were down regulated, demonstrating the impact of microplastic physicochemistry. FGSEA pathway analysis revealed that 270 Reactome pathways were significantly altered following microplastic exposure in either condition at both concentrations. These pathways contributed to functional domains including protein synthesis, DNA replication, cell cycle control and aerobic respiration. Overall, microplastic exposure was associated with upregulated mitochondrial respiration, and downregulation of nuclear-related processes including DNA synthesis, transcription and cell proliferation. This study provides targets for future investigation (mitochondria and nucleus) and emphasizes the need to consider biological and environmental conditions for in vitro models of microplastic exposure.

Cyclosporiasis is a foodborne illness caused by the parasite Cyclospora cayetanensis. Clinical surveillance often lags infection by weeks because diagnosis depends on a clinician ordering a test that is not part of routine parasite panels. Wastewater metagenomic sequencing does not depend on care seeking, which may be useful for early detection and community monitoring. We designed 1,670 31-mers from C. cayetanensis mature ribosomal RNA and retained 1,464 without an exact non-target match in the 28 July 2025 NCBI core_nt release. By analyzing 293 public wastewater metagenomes, we selected a threshold of 24 distinct diagnostic 31-mers on one read. Applying that threshold to 2,333 public runs from BioProject PRJNA1247874 yielded putative C. cayetanensis reads in 81 runs, or 3.5%, and in 24 of the 30 longitudinally sampled sewersheds. Detections rose through the summer in two consecutive years, matching the known seasonality of cyclosporiasis. The most parsimonious explanation is that these reads come from parasites shed into wastewater, although undescribed Cyclospora species absent from reference databases cannot be excluded. The same approach can be applied to other pathogens in existing wastewater sequencing data.

Respiratory viruses pose a major threat to human health. Environmental virus persistence in respiratory secretions is essential for successful spread, yet studies have focused largely on a select few viruses in non-physiological matrices. Here, we compared the stability of structurally distinct human respiratory viruses, adenovirus, influenza virus, and rhinovirus, in deposited particles of pooled human saliva under indoor-relevant relative humidity (RH) conditions. Adenovirus exhibited <2.2-log10 decay over 6 h regardless of RH, while rhinovirus exhibited significantly greater degradation (>3.8-log10, at 50% and 80% RH). Influenza virus showed minimal decay at 20% and 50% RH but degraded significantly more (3-log10) at 80% RH. To distinguish aspects of human saliva that are key determinants in driving virus decay, we recapitulated saliva composition using the inorganic solute and protein concentrations determined via ion-coupled plasma mass spectrometry and proteomics, respectively. Rhinovirus was significantly more stable in simulated saliva than in human saliva at 50% RH, while influenza virus and adenovirus behaved similarly in both matrices. These findings emphasize virus-specific environmental persistence and highlight limitations of relying on a single virus and particle matrix for defining public health strategies. Ultimately, these insights will contribute to approaches for mitigating environmental transmission of distinct respiratory pathogens.

Eutrophication-driven hypoxia and harmful algal blooms are an expanding threat to water quality in estuaries. Engineered aeration is a technology used in freshwater and, to a lesser extent, estuarine systems to mitigate both hypoxia and algal blooms. However, the efficacy of engineered aeration has not been well studied within estuarine ecosystems and very little is known about the impact of aeration on microbial communities in either estuarine or freshwater environments. Here we present a time series investigation of microbial community response to aeration and cessation of aeration in a eutrophic estuary. Samples for 16S rRNA gene analysis were collected over about a month-long period during which time the aerators transitioned from being "on" to "off" to "on" again. Cessation of aeration selected for the dominance of a eukaryotic algae similar to Heterosigma akashiwo. After the resumption of aeration, H. akashiwo dominance decreased rapidly. Cessation of aeration also shifted the structure of the entire microbial community, where diversity decreased and the structure of microbial communities at the surface diverged from those from the bottom of the water column. These changes did not occur at non-aerated control sites. Distinct groups of taxa responded to the disruption in a successional pattern through time, with most taxa never returning to their pre-aeration-cessation abundance during the observational period. These findings demonstrate the complex community response to anthropogenic interventions and provide support for bloom suppression through aeration.

Population-scale pathogen surveillance is limited worldwide, particularly in resource-constrained settings, where clinical systems only monitor select priority pathogens and reach only those who can access healthcare. Wastewater-based epidemiology addresses many of these gaps, offering cost-effective surveillance that is adaptable across diverse implementation contexts. In Lagos, Nigeria, a high enteric pathogen burden coincides with a complex sanitation landscape. However, circulating pathogen diversity in Lagos is largely uncharacterised outside of outbreak contexts. Here we characterize human-associated pathogen diversity in Lagos with virus-enriched metagenomic and metatranscriptomic sequencing of untreated wastewater sampled from open drainage canals from July-August 2024. We detected a diverse human-associated virome dominated by enteric adenoviruses, astroviruses and caliciviruses. We recovered numerous partial and near-complete genomes from pathogens of public health concern, including noroviruses, enteroviruses and sapoviruses. Although our enrichment targeted viruses, we detected diverse bacterial pathogens, including recurrent detection of Vibrio cholerae, other enteric bacteria, and zoonotic pathogens such as Streptococcus suis. We also detected antimicrobial resistance genes, including aminoglycoside, beta-lactam and fluoroquinolone resistance and clinically important genes such as mcr. Together, these results establish a regional baseline of pathogen diversity and demonstrate the utility of virus-enriched sequencing for integrated wastewater surveillance.

Enteric viruses are important contaminants of surface waters and a significant burden on public health. In aquatic ecosystems, the stability of these pathogens is differentially impacted by abiotic and biotic stressors, which can exert inactivating effects. Here, we investigated the fate of two enteroviruses, echovirus 11 (E11) and coxsackievirus B5 (CVB5), and one adenovirus, human adenovirus 2 (HAdV2), in lakewater and explored the mechanisms underlying their microbial inactivation. By combining infectivity assays, genome quantification, and capsid integrity analysis, we characterized virus-specific inactivation kinetics and mechanisms and examined the relationship between infectivity loss and capsid structural integrity. We observed rapid, intermediate, and negligible decay for HAdV2, E11, and CVB5, respectively, and confirmed that microbial proteases contribute to their inactivation. In addition, we revealed that loss of capsid structural integrity drives E11 inactivation, but not HAdV2 inactivation. Genome decay did not consistently correlate with loss of infectivity, highlighting the limitations of genome-based detection for assessing the presence of infectious viruses. These findings provide new insights into the mechanisms governing virus inactivation in aquatic environments and emphasize the importance of understanding viral fate when interpreting molecular detection data to assess virus-associated microbial risks.

The unprecedented rise in greenhouse gases such as carbon dioxide (CO2), and their detrimental effects on the atmosphere have intensified the current climate emergency. This challenge has inspired the development of novel carbon capture and utilisation (CCU) technologies, specifically microbial electrosynthesis (MES), for the bioelectrochemical fixation of CO2 into commodity chemical compounds (CCCs) using microbial biocatalysts. In this study, we systematically enriched and maintained robust mixed microbial communities of electroactive bacteria (EAB) from wastewater treatment sludge to serve as biocatalysts for MES. The MES performance of these biocatalysts under different operational conditions in bioelectrochemical systems (BES) reactors were investigated. BES reactors with enriched biocatalysts incubated and maintained under controlled conditions produced higher CCCs yields than those developed at ambient temperatures, while strict anaerobic operations further improved the MES efficiency compared to aerobic conditions. At an applied potential of -1000 mV vs Ag/AgCl, CO2 conversion reached up to 88.11%, significantly outperforming the lower potential (-600 mV) operation. These findings underscore the importance of systematic development of robust and stable biocatalysts, as well as maintaining strict anaerobic conditions, for achieving efficient MES performance, thereby demonstrating the potential of our approach for scalable industrial CCU applications.

Data-driven soft sensors can estimate fermentation product concentrations from routinely recorded process variables, but strong performance during normal operation does not establish reliability during process deviations. This study evaluated current-time penicillin-concentration estimation using 100 simulated IndPenSim batches comprising 90 normal-operation batches and ten documented deviation batches, with 113,935 observations in total. Initial normal-trained models and five follow-up experiments examined complete-batch validation, dependence on batch-progress features, phase-specific error, model-family comparisons, early out-of-distribution warnings and empirical prediction ranges. These analyses motivated a matched comparison between normal-only and fault-inclusive HistGradientBoosting regressors using 36 current and causal history-based inputs. Normal performance was evaluated in five regime-balanced complete-batch folds, and deviation performance by leave-one-fault-batch-out evaluation; every tested deviation batch was excluded from its own model fit. Batch-balanced sample weights were used, with a factor of three assigned to permitted deviation batches in fault-inclusive fitting. On held-out deviation batches, pooled RMSE decreased from 3.195 to 2.564 g/L, a reduction of 19.73%, while MAE decreased from 2.076 to 1.441 g/L and R2 increased from 0.8580 to 0.9085. Normal-operation RMSE was nearly unchanged at 1.981 and 1.983 g/L. Eight of ten deviation batches improved. The mean paired fault-batch RMSE difference was -0.7063 g/L, with a descriptive 95% batch-bootstrap interval of -1.2844 to -0.2194 g/L. Improvement was largest within the first-to-last recorded fault-reference window, but late-stage errors persisted. Batch 100 remained poorly predicted, with fault-inclusive RMSE of 6.631 g/L and R2 of -2.4837. A fault-risk classifier, Isolation Forest OOD detector and empirical error ranges offered incomplete reliability information. Fault-inclusive training therefore improved this benchmark on average, but did not establish generalization to unseen fault mechanisms, calibrated safety warnings or deployment in physical fermentation.

Paper-based colorimetric sensors offer a low-cost and accessible platform for point-of-care (POC) analysis, but enzyme activity loss during coating and drying can weaken analytical signals and require high enzyme loadings or complex immobilization procedures. Although surfactants are widely used to improve wettability in paper-based assays, their potential contribution to colorimetric performance beyond these effects remains unclear. Here, we investigated surfactant-assisted colorimetric signal enhancement in a glucose assay implemented on a 96-puddle paper plate (96-PPP) and identified Tween 20 as the most effective surfactant. Its effect on detection performance became more pronounced as glucose oxidase (GOx) loading decreased; at 0.1 mg/mL GOx, Tween 20 lowered the limit of detection (LoD) from 0.113 to 0.034 mg/mL (approximately 3.3-fold) over a working range of 0-5 mg/mL, despite no statistically significant change in the measured contact angle at this loading. Tween 20 had no appreciable effect on the reaction in solution but preserved 95% of the apparent reaction rate constant after drying, compared with 11% without it, and atomic force microscopy (AFM) revealed a more dispersed dried enzyme morphology on mica. Tween 20-containing sensors also showed slower signal decay during repeated wetting-drying cycles and thermal stress, retained 77% (vs 26%) of the response at 400 mM NaCl, and exhibited within-PPP and between-batch coefficients of variation (CVs) below 10% (vs 12.3-19.5%), while maintaining glucose selectivity over potentially interfering molecules. These results indicate that Tween 20 enhances paper-based glucose sensing beyond wettability, in part by retaining enzyme cascade activity during drying, although the contributions of the individual enzymes and the underlying mechanism remain to be established.