FEMS Microbes

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.

Northern peatlands store large carbon stocks but are sensitive to disturbance. Hydrology, vegetation, herbivory and snow conditions may affect the soil microorganisms driving methane (CH) and nitrous oxide (N2O) cycling. We investigated how reindeer exclusion and snow depth (increased and reduced relative to ambient) manipulations (ongoing for three seasons) influenced archaeal and bacterial communities in a boreal rich fen. Metagenomic (MG) and metatranscriptomic (MT) sequencing were combined with pore-water chemistry and CH flux measurements to link the microbiome to ecosystem processes. Microbial communities differed between outside and inside the exclosure. However, these patterns primarily reflected underlying hydrological variation. Slightly wetter inside plots showed higher expression of denitrification genes (norB, nosZ) and lower (nirS+nirK)/nosZ ratios, indicating greater potential for complete denitrification to N2 instead of N2O. Methane dynamics were mainly associated with vegetation: plots associated with Carex rostrata exhibited lower pmoA/mcrA ratios and elevated CH fluxes. Snow manipulations had subtle effects: reduced snow depth decreased the expression of taxa dependent on microbial interactions, while the effect to the investigated metabolic marker genes was small. Overall hydrology, leading to variations in redox conditions and nutrient availability, together with vegetation appeared as the primary drivers on microbial greenhouse gas processes in this peatland.

Scalable soil microbiome monitoring requires sampling methods that are reproducible across operators, field sites, and logistical constraints. Here, we evaluated three key methodological choices that commonly limit comparability in agricultural rhizosphere studies: how the rhizosphere sampling unit is operationally defined, sample pooling strategies, and preservation methods. We introduce the RhizoCore, a standardized root-zone soil core defined by core diameter, depth, position relative to the plant, and subsample volume, as a practical proxy for traditional rhizosphere sampling. The RhizoCore method captured more than 92% of the sequencing depth found in traditional rhizosphere samples, with differences limited predominantly to low-abundance taxa. Preservation methods significantly affected bacterial communities, while sample pooling showed greater impact on fungal diversity and substantially reduced within-group variability across all treatments. Despite these effects, differential abundance analysis revealed minimal compositional changes, with only a small fraction of microbial taxa significantly affected by either pooling or preservation method. Our findings demonstrate that the RhizoCore method provides a reproducible, and scalable approach for rhizosphere sampling that balances scientific rigor with practical field implementation, offering a framework for large-scale soil microbiome monitoring programs and for improving comparability among agricultural microbiome studies across diverse environmental conditions.

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.

Pathogen cross-contamination during food production is primarily controlled through environmental sanitation. However, sanitizer efficacy is often studied in bench-scale experiments that poorly approximate the fluid dynamics of sanitization and limits our understanding of commercial sanitization efficacy. This study paired computational fluid dynamics (CFD) estimates of shear stress with experimental measurements of Listeria innocua reduction on stainless steel following treatment with 100 ppm hypochlorite sanitizer. At the pilot-scale, sanitizer spray manually applied by researchers achieved a 2.6 {+/-} 0.4 log CFU/surface reduction; however, microbial reduction from manual operation of sanitizer spray equipment differed significantly between researchers (p < 0.05). Microbial reduction varied by location following stationary, bench-scale spray application of sanitizer for 3 s. The greatest reduction was at the point of sanitizer spray impingement (7.5 {+/-} 0.5 log CFU/surface) and directly adjacent to the impingement point (6.4 {+/-} 0.7 log CFU/surface) where shear stress was the highest. Significantly less microbial reduction (0.4 {+/-} 0.1 log CFU/surface) occurred where shear stress was lowest in the fluid-film of sanitizer running down from the impingement point (p < 0.05). Static submersion of inoculated coupons in sanitizer for 3 s resulted in a log reduction of 2.3 {+/-} 0.1 log CFU/surface. Discrepancies between bench-scale spraying, pilot-scale spraying, and submerged coupons demonstrate the need for sanitizer efficacy testing under realistic conditions to better estimate the risk reduction achieved through sanitation programs. IMPORTANCESanitation is critical for controlling pathogen cross-contamination during food production. These findings highlight the limitations of traditional approaches to sanitizer efficacy testing, not because they are invalid, but because they do not reflect the level of microbial reduction typically achieved in application. We demonstrate that these differences in outcomes are attributable to fluid dynamics and exposure, which are not well approximated in submerged coupon experiments. Accurate estimation of microbial reduction from sanitizer application is needed to guide food safety policy decisions. For example, overestimation of the risk reduction conferred by sanitizer treatment may result in food safety policies that neglect other sources of microbial reduction within sanitation programs.

Wastewater-based surveillance (WBS) is increasingly used to monitor infectious disease dynamics, yet most evaluations focus on correlation or forecasting - neither of which directly assesses whether wastewater signals can identify the epidemiological events most relevant to public health decision-making. We argue that outbreak onset and epidemic peak detection are the operationally critical use cases of WBS, requiring a fundamentally different evaluation framework. We introduce a classification-based framework that treats WBS as an event-detection problem, defining outbreaks and peaks as discrete events, establishing detection intervals to account for timing uncertainty, and incorporating censoring and data completeness criteria for valid comparisons against imperfect clinical reference outcomes. Within this framework, we apply a Bayesian exponential growth model for outbreak detection - benchmarked against a standard reproductive number (Rt)-based method - and a rule-based algorithm for peak detection, evaluating performance via sensitivity and positive predictive value (PPV). Applied to county-level SARS-CoV-2 wastewater data from 281 U.S. counties (Biobot, 2021-2024), the exponential growth approach substantially outperforms the Rt-based baseline: sensitivity 0.82 and PPV 0.64 versus sensitivity 0.58 and PPV 0.19 for the best-performing Rt variant. Peak detection achieves sensitivity 0.84 and PPV 0.70 at the county level. Both peak and outbreak detection achieve strong and consistent performance against hospitalizations and deaths at the state level. Spatial aggregation yields a statistically significant improvement in peak detection PPV against a curated reference standard ($p < 0.001$), while outbreak detection improvements under aggregation are directionally consistent but not statistically significant. Wastewater leads case-defined outbreaks by 4-6 days but minimally leads epidemic peaks, consistent with wastewater approximating prevalence rather than incidence. These findings demonstrate that wastewater signals can reliably detect outbreak onset and epidemic peaks across spatial scales and clinical outcomes, and that the choice of detection method matters substantially in practice. The classification framework developed here provides a reusable and principled tool for evaluating any surveillance signal as an event-detection system, with direct relevance to how WBS is actually used in public health decision-making.

Short-read amplicon sequencing is widely used for fungal surveys but can limit taxonomic resolution. Long-read sequencing enables recovery of the full internal transcribed spacer (ITS) region and may improve ecological and taxonomic inference. Here, we conducted a paired comparison of Illumina ITS2 and PacBio HiFi full-length ITS sequencing using identical DNA extracts from built-environmental air and surface samples (n = 68) collected across homes, a dormitory, and laboratories. Both datasets were taxonomically assigned using the same algorithm and reference database. We performed paired statistics, in-silico ITS2 trimming of long-read sequences, and cross-platform mapping at multiple identity thresholds. Full-length ITS provided higher taxonomic resolution, assigning a greater fraction of ASVs at the family (98% vs. 88%) and species (42% vs. 32%) ranks than ITS2 (paired Wilcoxon q = 0.002). Alpha-diversity comparisons showed similar Shannon diversity across pipelines, whereas richness metrics were consistently higher for full-length ITS. Beta-diversity analyses indicated broadly comparable community-level patterns, although full-length ITS revealed stronger sample-type- and location-associated structure (PERMANOVA R{superscript 2} [&ge;] 0.06, p = 0.0001). In-silico ITS2 trimming reduced these differences, indicating that amplicon length is a major contributor to enhanced taxonomic resolution and ecological inference. Cross-platform mapping further showed extensive one-to-many relationships between ITS2 and full-length ITS ASVs, consistent with increased sequence resolution in long-read data. Together, these results show that ITS2 sequencing provides robust community-level profiling, while full-length ITS enables improved richness estimates and finer ecological and taxonomic resolution. This paired, bias-aware framework provides a practical template for selecting fungal amplicon sequencing strategies in built-environment mycobiome studies. ImportanceFungal communities in built environments influence indoor air quality and human exposure, yet their characterization depends strongly on sequencing strategy. This study provides a controlled, paired comparison of short-read ITS2 and long-read full-length ITS sequencing, showing that differences in amplicon length substantially contribute to variation in taxonomic resolution and ecological inference. While both approaches yield comparable community-level patterns, full-length ITS improves richness estimates, species-level assignment, and environmental discrimination by resolving sequence variation collapsed in ITS2 surveys. By integrating paired diversity analyses, in-silico ITS2 trimming, and cross-platform ASV mapping, this work offers a bias-aware framework for evaluating fungal amplicon pipelines. Importantly, improved species-level resolution enables functional interpretation of indoor fungi, for example the identification of taxa associated with pathogenic traits, allergen production, or toxin synthesis, supporting the development of more informative exposure metrics and targeted assays relevant to human health in built environments.

2.Childhood atopic disease is linked to delayed gut microbiome development and metabolic dysfunction, however microbial drivers remain unclear. To explore microbial correlates of asthma risk during a time of active gut microbiome development, we analyzed stool from 6-month-old infants at high asthma risk (HR) or healthy controls (HC), using Genome-resolved metagenomics (HR=7; HC=12) and untargeted metabolomics (HR=11; HC=15). We recovered 82 bacterial species-level metagenomic-assembled genomes (MAGs). Global Taxonomic composition did not differ by asthma risk. Anticipating that key differences might associate with specific genomes, a machine-learning approach pinpointed Bacteroides cellulosilyticus, Hungatella effluvii, and Enterocloster aldenensis as linked with asthma risk status. All three species were more abundant in HC infants and the B. cellulosilyticus genome was enriched for carbohydrate metabolism genes relative to other MAGs. Metabolomic profiling revealed variance associated with asthma risk (PERMANOVA, R2 =0.069, p=0.016). HR fecal metabolomes were enriched in simple sugars, whereas HC contained more nitrogenous compounds. Integrative genome-metabolic modeling of compounds that significantly differentiate asthma-risk groups revealed risk-dependent interactions with community-encoded metabolic potential (CEP), for arabinose and agmatine, whose fecal concentrations are linked with B. cellulosilyticus and H. effluvii functional traits respectively. These findings suggest that microbial-influenced metabolic differences associate with asthma risk at 6 months, with B. cellulosilyticus and H. effluvii emerging as candidate bacteria influencing this observed metabolic remodeling. 3. Impact statementLeveraging a random forest classifier, we identified three bacterial species (Bacteroides cellulosilyticus, Hungatella effluvii, and Enterocloster aldenensis) as distinguishing features enriched in healthy 6-month old infant microbiomes compared to those at high risk of asthma development (HR). We developed an approach to integrate metabolomics and metagenomic-derived microbiome community encoded potential (CEP) with clinical outcomes to identify fecal metabolites whose concentrations are likely to be influenced by the microbiome. Fecal arabinose concentrations were positively associated with CEP in healthy infants, but not in HR subjects who exhibited elevated concentrations irrespective of CEP. These data implicate microbial activity as a contributor to the concentration of this metabolite in healthy but not HR infants. With a leave-one-out-cross-validation, we identified B. cellulosilyticus as a contributor to fecal arabinose concentrations. Our data indicate that microbial functional deficits in HR infants is associated with altered gut metabolic dysfunction during microbiome maturation. 4. Data summaryDurack et. al [1] is the source of the metabolomics data utilized in this study. The authors confirm that all other supporting data, code and protocols have been provided within the article or through supplementary data files.

The search for antimicrobials with a low propensity to select resistance has intensified in response to the global antimicrobial resistance crisis. Norway spruce resin (Picea abies) has long been used in Northern European wound care traditions and has shown broad antimicrobial activity in earlier microbiological studies. In the present study, we evaluated whether prolonged exposure to medical-grade spruce resin promotes reduced susceptibility in clinically relevant bacterial species. A 20-day serial-passage experiment was performed with Staphylococcus aureus, Pseudomonas aeruginosa, and Enterococcus faecalis using sub-inhibitory resin concentrations and broth microdilution readouts at baseline, day 10, and day 20. Resistance development was predefined as a [&ge;]4-fold increase in inhibitory concentration. Baseline inhibitory concentrations were 1.25% for S. aureus, 5.0% for P. aeruginosa, and 2.5% for E. faecalis. After 20 days, inhibitory concentrations were 2.5%, 10.0%, and 2.5%, respectively, corresponding to at most 2-fold changes and remaining below the predefined threshold for resistance development. Validation and vehicle-control arms indicated that these shifts were not attributable to medium transfer or solvent-related bias. These findings suggest that medical-grade Norway spruce resin has a low short-term tendency to select for reduced susceptibility under serial-passage conditions. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/723837v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@160479forg.highwire.dtl.DTLVardef@1fe1e95org.highwire.dtl.DTLVardef@89dec3org.highwire.dtl.DTLVardef@17ff134_HPS_FORMAT_FIGEXP M_FIG C_FIG

Silver has been used as a biocide for centuries, mostly in health-oriented applications. However, as a biocide, silver is toxic not only to its intended targets, mainly bacteria and fungi, but also to all living cells. Because of this toxicity, it is desirable to use forms of silver that maximize the required biocidal activity while minimizing the amount of silver that will be released in the environment at the end of life of the product. Silver nano objects are a good compromise for such requirements. The high surface to volume ratio allows for good reactivity and thus good biocidal activity, while the small amount of silver present in nano objects allows for a limited environmental release at the product end of life. In this work, we tested three types of silver nano objects. The first type, polyvinylpyrrolidone-coated silver nanoparticles (nAg-PVP) were used as a control nanoparticle, as this type of nanoparticle is now widespread. We also manufactured and tested maltodextrin-coated silver nanoparticles (nAg-MD) and micrometric (20 {micro}m in two dimensions and a few nanometers in the third one) silver flakes ({micro}AgSF). For these three silver nano objects, we investigated the biocidal activity by stringent tests using both Staphylococcus aureus and Escherichia coli as target bacteria. In addition, we investigated toxicity on mammalian macrophages or keratinocytes cell lines, as well as on an insect hemocyte cell line. Our results showed that the two innovative silver nano objects (nAg-MD and even more {micro}AgSF), showed both a better bactericidal activity and a lesser toxicity than the reference nAg-PVP nanoparticles. In addition, we also checked that beyond toxicity, the silver nano objects did not induce an inflammatory reaction, making them safer to use.

BackgroundCloud water harbors diverse microbial communities despite its extreme oligotrophic conditions. However, the ecological and evolutionary dynamics of viruses in these transient atmospheric habitats remain poorly understood. Clouds have traditionally been regarded primarily as passive carriers of microorganisms rather than as active ecological environments supporting microbial interactions. In this study, cloud water was sampled at Mount Verde, Cape Verde Islands (744 m a.s.l.). We performed metagenomic analyses of iron-flocculated cloud water alongside genome analyses of a bacterial isolate and metagenome-assembled genomes using established bioinformatic approaches. Viral diversity, virus-host interactions, metabolic functions, genetic adaptations, and viral population dynamics across cloud events were investigated. In addition, UV-B resistance experiments were conducted for a novel cloud-water isolate. ResultsWe isolated 24 cloud water bacteria, including four novel species lineages, and recovered 62 high-quality metagenome-assembled genomes, including 10 novel species lineages. We identified 458 viral operational taxonomic units and 237 virus-host linkages across diverse prokaryotic hosts, revealing active viral predation across diverse bacterial taxa. In addition, CRISPR spacer matches from isolates of novel bacterial lineages such as Deinococcus nubigenus MPC36 were found. Viruses carried genes involved in host adaptation to environmental stressors, including cold-shock response, UV radiation resistance, and osmotic stress. In addition, viral populations exhibited SNP-level microdiversity and shifts in single-nucleotide variant composition across temporally proximate cloud events, indicating rapid population turnover. Experimental characterization of the cloud isolate Curtobacterium nubigenum MPC39 further revealed pronounced resistance to UV-B radiation and the presence of an inducible prophage, Curtobacterium phage vB_CnuS_Cirrus1 assigned to the new viral family Nebulaviridae, which could be validated in transmission electron microscopy. Reconstructed genomes from cloud-associated bacteria encoded carbon monoxide dehydrogenase genes and UV resistance genes, suggesting trace gas metabolism and enhanced UV protection as survival strategies in oligotrophic cloud droplets. In silico replication rates estimated using iRep were consistent with active bacterial replication at the time of sampling. ConclusionsTogether, these findings demonstrate that clouds are not merely passive carriers of microorganisms, but dynamic atmospheric ecosystems in which virus-host interactions shape microbial diversity and contribute to microbial turnover, atmospheric dispersal, and cloud-water biogeochemistry.

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

BackgroundWhether the lung microbiome represents a stable microbial colonization or a transient ecosystem shaped by continuous microbial turnover and controlled by host immunity remains unresolved. The murine lung microbiome largely consists of species from the former Lactobacillus genus with Ligilactobacillus murinus as a dominant species, bacterial genera such as Streptococcus, Staphylococcus, Mammaliicoccus, Enterococcus and other less frequently detected bacteria. Here, we directly addressed the question of persistence and host interaction of a dominant murine lung commensal in vivo and focused on the host immune response towards lung commensal bacteria. ResultsWe developed a transformation strategy for stable genomic integration of a green fluorescent protein (GFP)-encoding gene to track the fate of a lung bacterium. Following intranasal administration of GFP-labeled L. murinus in mice, bacteria were readily detected in the lungs at early time points but declined rapidly and became undetectable after 72 hours, as determined by quantification of viable bacteria and qPCR. Flow cytometry and fluorescence imaging revealed efficient uptake of GFP-labeled bacteria by lung phagocytes. These findings indicate that even dominant members of the murine pulmonary microbiota normally detected at low abundances are transiently present in the lungs without causing infection. We further analyzed the effects of moderate and high bacterial concentrations. While moderate bacterial loads were efficiently controlled without clinical effects, high concentrations induced severe lethargy, indicating a threshold-dependent host response. Finally, we demonstrated that pulmonary commensals such as L. murinus, Staphylococcus xylosus, and Mammaliicoccus sciuri, as well as conidia of the opportunistic lung pathogen Aspergillus fumigatus, are phagocytosed at comparable rates in macrophage assays. ConclusionsOur data demonstrate that even lung-adapted bacterial species fail to establish stable colonization and are instead subject to rapid immune-mediated elimination contributing to the maintenance of a low microbial burden in the lungs. While this homeostatic balance supports health, elevated bacterial loads trigger immune activation and, at high levels, lead to health deterioration. Together, these results support a model of a highly dynamic and transient lung microbiome, maintained by continual microbial immigration rather than long-term colonization. Accounting for the lung microbiome dynamics is essential for understanding host-microbiota interactions and respiratory health.

Metagenomic sequencing is increasingly applied to wastewater to characterize the diversity, dynamics, and relative abundance of human and animal viruses. Among these sequencing approaches are those that enrich viral nucleic acids from the wastewater matrix, aiming to increase the viral read fraction for analysis. However, the feasibility of scaling targeted viral sequencing to diverse sewersheds across large geographic scales is currently unknown. In this study, we apply hybrid capture metagenomic sequencing to nearly 450 weekly wastewater samples collected during the respiratory virus season in the United States and evaluate sequencing performance for generating public health-relevant data. Analysis of data from 15 wastewater treatment plants demonstrates that our approach enabled efficient capture of pathogens of interest, achieving a median viral read fraction over 19%. Importantly, relative abundance estimates of common pathogens correlated with direct quantification of viral targets using RT-ddPCR. Together, our results demonstrate that hybrid capture sequencing of wastewater is a viable tool to monitor both common and rare pathogens across geographically diverse sewersheds.

Antibiotic residues exceeding selective concentrations for antibiotic-resistant bacteria have been detected in various environments, including manure, wastewater, and effluents from wastewater treatment plants. When these residues come into contact with soils, for instance, due to wastewater irrigation or fertilization with manure, they interact with soil constituents. Soil colloids (1-1000 nm), such as montmorillonite, have been observed to adsorb pharmaceuticals, including antibiotics. We investigated the effect of colloids on the bioavailability of ciprofloxacin and found, that added to bacterial growth medium, montmorillonite reduces, but does not completely prevent, the growth-inhibitory effect of the antibiotic. The bacteria were able to grow at up to roughly double the concentration of ciprofloxacin in the presence of montmorillonite. We show that the incomplete deactivation of ciprofloxacin was most probably caused by medium components that decreased the adsorption of ciprofloxacin to montmorillonite. We conclude that a selective potential of this highly active antibiotic in contaminated soils, which also contain nutrients enabling bacterial growth, cannot be ruled out. Environmental implicationAntibiotics such as ciprofloxacin are frequently detected in water bodies and soils due to wastewater irrigation or manure application. These residues raise concerns about environmental toxicity and antibiotic resistance. This study demonstrates that montmorillonite, a common clay mineral in soils, significantly reduces the antimicrobial efficacy of environmental ciprofloxacin concentrations by sorption. The findings reveal a natural attenuation mechanism that may influence the environmental fate and bioavailability of antibiotics. Understanding such interactions is critical for predicting antibiotic behavior in terrestrial systems and for designing more accurate environmental risk assessments.

Microbial colonization is a major cause of deterioration in paintings, leading to discoloration, pigment degradation, and loss of structural integrity. While biodeterioration of artworks has been studied in temperate climates, tropical environments remain underexplored despite their high humidity and temperature, which promote microbial growth. This study assessed the microbiological deterioration of two eighteenth-century oil paintings, La Muerte de San Jose and Virgen de Guadalupe, located in Orosis Colonial Church and Religious Art Museum, Costa Rica. Microorganisms were isolated and identified using VITEK(R) 2, microscopy, and MALDI-ToF analysis, and their biofilm-forming capacity was evaluated. Additionally, the antimicrobial activity of six essential oil components was tested using direct and indirect contact assays. Twenty-three bacterial species and fifteen fungal genera were identified, with Bacillus, Staphylococcus, Cladosporium, and Aspergillus among the most common. Notably, La Virgen de Guadalupe displayed the highest microbial diversity, reflected in a high Shannon index, indicative of a more complex microbial community. Several isolates displayed strong biofilm formation, particularly Bacillus subtilis/amyloliquefaciens/vallismortis and Staphylococcus saprophyticus. Linalool exhibited the strongest inhibitory activity, achieving complete bacterial growth inhibition in non-contact assays. Environmental monitoring revealed persistently elevated relative humidity and CO2 levels during the study period. Together, these results reveal the complex microbial ecology of tropical heritage paintings and demonstrate that volatile essential oil components can serve as candidates for low-impact antimicrobial strategies in preventive conservation. ImportanceUnderstanding the microbiological deterioration of cultural heritage in tropical environments is crucial for designing sustainable conservation strategies. While microbial colonization of artworks has been widely studied in temperate regions, data from tropical climates remain limited despite inherently favorable conditions for microbial proliferation. This study integrates microbiological, environmental, and physicochemical analyses to characterize microbial communities colonizing eighteenth-century oil paintings in Orosi, Costa Rica. By combining microbial identification, biofilm quantification, and essential oil biocide testing, it bridges applied microbiology and cultural heritage conservation. The finding that volatile components such as linalool inhibit biofilm-forming bacteria without direct contact highlights their potential as eco-friendly, noninvasive antimicrobial alternatives to conventional biocides. These results expand the understanding of biodeterioration dynamics under tropical conditions and offer a practical framework for developing sustainable, evidence-based conservation protocols that protect both heritage materials and the environment. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=171 SRC="FIGDIR/small/723565v1_ufig1.gif" ALT="Figure 1"> View larger version (98K): org.highwire.dtl.DTLVardef@16cd608org.highwire.dtl.DTLVardef@57aa00org.highwire.dtl.DTLVardef@159fcbeorg.highwire.dtl.DTLVardef@e0363b_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 0.C_FLOATNO Artistic visualization of the geographical context of the studied artworks and the multidisciplinary analytical approaches applied, highlighting the diversity of microorganisms identified (illustration by Keylin Urena-Alvarado). C_FIG

Staphylococcus aureus (S. aureus) is the most common pathogen associated with skin infections worldwide. Significant efforts have been made to identify and develop innovative therapeutic strategies against S. aureus as alternatives to conventional antibiotics. Physical plasma has a broad range of potential uses, with non-destructive disinfection being one of its earliest applications. Although the literature emphasizes the antibacterial properties of cold atmospheric plasma (CAP), the effect of plasma on S. aureus on damaged skin susceptible to S. aureus invasion through the itch-scratch cycle has not been studied to date. Thus, we examined the effectiveness of CAP treatment on S. aureus bacteria in atopic dermatitis lesions using floating electrode dielectric barrier discharge devices, as well as helium and argon plasma jets. Heat distribution on the skin target, ultraviolet C radiation, and ozone generation of plasma jets for the operator of plasma sources were evaluated. Microbial tests confirmed the presence of S. aureus on the lesions of the groups before treatment. The groups exposed to plasma treatment showed a notable reduction in bacterial population compared to the model group (p<0.05). Furthermore, our investigation indicated that plasma treatment reduced pruritus behavior. The findings suggest that cold atmospheric plasma treatment may potentially target skin infections caused by S. aureus in addition to conventional therapies.

Microbiome science is increasingly important in modern biology education because microbial communities influence human health, ecosystems, and environmental processes. However, undergraduate microbiome instruction is often limited by the high cost and technical complexity of sequencing-based workflows, restricting opportunities for authentic student-driven research. To address this challenge, we developed a low-cost, inquiry-based curriculum that enables undergraduate students to conduct complete microbiome studies using 16S rRNA gene sequencing. The module integrates project design, environmental sample collection, microbial cell processing, PCR amplification, sequencing, and bioinformatic analysis using open-source tools such as QIIME 2. Cost-reduction strategies included centrifugation-based cell collection and a surfactant-assisted direct PCR workflow that eliminated the need for commercial DNA extraction kits. Students designed independent research projects investigating microbial communities in local environments, including campus water sources and gym equipment surfaces. Assessment data from post-course surveys, knowledge checks, and student research products demonstrated strong learning gains in microbiome concepts, molecular biology techniques, scientific communication, and computational analysis. Students reported high confidence in PCR, experimental design, and microbiome interpretation, while also identifying bioinformatics as the most challenging yet rewarding component of the curriculum. All participants expressed increased interest in future research in microbiology or bioinformatics. Overall, this curriculum provides an accessible, scalable framework for integrating next-generation sequencing into undergraduate education while promoting inquiry-driven learning, student ownership, and engagement in authentic scientific research.

Microbial communities regulate carbon and nitrogen (N) cycling, yet their long-term responses to chronic global changes remain unclear. Using 12 years of grassland litter samples from the Loma Ridge Global Change Experiment in Irvine, California, we tested whether interactions between experimental drought and N deposition, and previously observed temporal variability are driven by background climatic conditions, including precipitation and temperature. Consistent with short-term studies, drought and N addition had relatively small effects on bacterial community composition compared to pronounced seasonal and interannual variability, with drought-by-year interactions explaining more variation than drought alone. Seasonal shifts were largely driven by short-term fluctuations in rainfall and temperature, whereas the substantial interannual variability in community composition was not captured by site-level climate metrics. Contrary to expectations, drought effects were influenced more by background temperature than precipitation, with the strongest effects observed in cooler years. Lastly, a bacterial taxons sensitivity to climate variability under ambient conditions did not predict its response to chronic drought. Together, our findings show that bacterial responses to drought are temporally dynamic and influenced by background temperature, underscoring the need for long-term longitudinal studies of soil microbial communities to better predict microbial responses under future global change. ImportanceMicrobial responses to global change, particularly drought and nitrogen addition, are often inferred from short-term studies (< 2 years), yet natural temporal variability may overshadow experimental effects. Using a 12-year dataset of grassland leaf litter communities, we show that temporal variability, both seasonal and interannual, exert a stronger influence on bacterial community composition than chronic drought or nitrogen deposition. These findings challenge assumptions about the magnitude of drought effects, particularly in naturally drought-affected ecosystem such as California grasslands and highlight the importance of long-term datasets for predicting microbial responses to climate change. By demonstrating that bacterial communities are strongly shaped by background climatic variability (baseline precipitation and temperature independent of imposed chronic treatments) and may be buffered to sustained drought, this work improves forecasts of ecosystem responses and informs the design of global change experiments and restoration strategies in future research studies.

BackgroundThe female lower reproductive tract harbors a complex microbiome that plays a critical role in reproductive health. A vaginal microbiome dominated by Lactobacillus crispatus (LC; Community State Type (CST) I) supports vaginal health, whereas a microbiome enriched with anaerobic species, such as Gardnerella vaginalis (GV) and Mobiluncus mulieris (MM) (CST IV) is linked to bacterial vaginosis (BV) and adverse outcomes, including sexually transmitted infections, infertility, and preterm birth. Although antibiotics such as metronidazole and clindamycin are commonly prescribed to treat BV, recurrence rates remain high, and the impact of these treatments on bacterial extracellular vesicles (bEVs), critical mediators of host-microbe interactions, is poorly understood. ResultWe investigated how antibiotic treatment at a dose below minimum inhibitory concentration alters the production and immunomodulatory function of bEVs derived from GV, MM, and LC. Using nanoparticle tracking analysis, cytokine profiling, and TLR pathway analyses, we found that antibiotic treatment significantly enhanced the inflammatory properties of bEVs in a species- and antibiotic-specific manner. Notably, bEVs from antibiotic-exposed GV and MM cultures induced elevated cytokine responses in epithelial and immune cells, primarily through TLR2 activation for GV bEVs, and through both TLR2 and TLR5 activation for MM bEVs. While LC bEVs are typically non-inflammatory, exposure to metronidazole, even at a lower dose than what is used clinically, rendered them immunostimulatory, suggesting a potential unintended proinflammatory consequence of treatment on beneficial microbes. We also detected bEVs in human vaginal swabs, including vaginolysin-positive bEVs, even in CST I microbiomes, indicating that low-abundance microbes, including pathogens, remain transcriptionally active. ConclusionsThese findings suggest that antibiotics not only reduce microbial load but also reshape bacterial communication via bEVs, potentially contributing to inflammation, epithelial barrier disruption, persistent dysbiosis, and recurrent infections. This work underscores the need for precision antimicrobial strategies that eliminate pathogens while preserving beneficial bacteria and their functional bEVs. Future therapies may benefit from considering the ecosystem-wide effects of antibiotics on the vaginal microbiome and its bEV-mediated signaling network.