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.

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.

Photorhabdus bacteria are potent insect-killing microbes associated with entomopathogenic nematodes and offer opportunities for environmentally benign pest control. They can be applied as foliar sprays or soil drenches without their nematode vector, resulting in massive amounts of Photorhabdus cells and their (toxic) metabolites introduced into the soil. However, their effects beyond the target organisms are unknown. To fill this knowledge gap, we investigated the soil legacy effects of Photorhabdus cells and their metabolites on soil microbial communities, plant performance and resistance to herbivores. To this end, we first conditioned soils with i) mechanically killed (MK) or Photorhabdus-infected insect larvae, ii) aqueous extracts of MK or Photorhabdus-infected insect larvae, iii) cell-free Photorhabdus supernatants, iv) autoclaved soil complemented with live soil previously conditioned with MK or Photorhabdus-infected insect larvae. We then grew maize plants in these soils and measured plant biomass, profiled soil microbial communities and plant metabolites, and evaluated plant resistance against two pest insects Diabrotica balteata and Spodoptera frugiperda. We found that conditioned soils increased plant biomass by 10-26% relative to controls and significantly altered soil bacterial and nematode communities, and to a lesser extent, fungal communities. Re-inoculating conditioned soil microbiota into autoclaved soils recreated the plant growth-promoting effects, indicating microbial-mediated mechanisms. Additionally, plants grown in soils conditioned with Photorhabdus-infected insect cadavers were often more resistant to herbivorous insect attack, in a strain-specific manner. On average, D. balteata and S. frugiperda larvae gained 10-20% and 10-59% less weight, respectively, when fed on plants grown in conditioned soils than on plants grown in control soils. The plant metabolic profiles of plant leaves and roots also varied with resistance levels. We conclude that Photorhabdus metabolites modulate soil microbial communities towards a structure that enhances plant growth and triggers systemic responses against herbivores.

Acid mine drainage is a global pollution problem characterized by low pH and high concentrations of metals. Active remediation is often cost-prohibitive, but Fe(II) oxidizing microbes may be used for passive bioremediation. To leverage these species, we must understand the factors that control their distribution. Here, we examine the environmental and ecological factors that control these species with the aim of determining if microbial seeding is a viable remediation strategy. Although stochastic processes appear to control the distribution of majority of taxa inhabiting AMD ecosystems, the distribution of Fe(II) oxidizers is driven by environmental filtering and competition. The abundance of all the major Fe(II) oxidizing genera have significant relationships with pH, with pH explaining 10 - 38% of the variation in their abundance. The genera appear to have pH preferences with Acidithiobacillus and Leptospirillum preferring environments below pH 3, Gallionella, Sideroxydans, and Ferritrophicum preferring environments above pH 3.5, and Ferrovum preferring intermediate pH environments. Once the effect of pH is removed, genera that share pH preferences are negatively correlated, indicating that they are likely competing for the Fe(II) oxidizing niche in their preferred environments. Communities are also shaped by dispersal limitation, which suggests that microbial seeding is possible in these environments. Future seeding attempts should consider species interactions and ecology more generally to inform their efforts.

The extent that anaerobic digestate acts as a reservoir of antimicrobial resistance genes (ARGs) is likely underestimated as conventional metagenomics may underrepresent low-abundance determinants and lacks sufficient resolution to reliably link ARGs to mobile genetic elements (MGE). This study used hybrid assemblies to evaluate whether culture-enriched metagenomics (CEMG), with and without antimicrobial selectivity, improves detection of ARGs in digestate and characterization of ARG- MGE-host linkages. Culture enrichment substantially increased ARG recovery: mean ARG signal rose from 15.4 CPM in fresh digestate (FD; direct metagenomic samples) to 124 CPM in CEMG without antibiotics and 160.0 CPM in antibiotic-selective CEMG, corresponding to an approximately 10.4-fold increase over FD. While only 9 unique ARGs were detected in FD, enrichment recovered 112, including those of clinical importance such as those encoding for vancomycin resistance, extended-spectrum {beta}-lactamase, and linezolid resistance. Oxygen availability emerged as the strongest factor structuring enrichment, with aerobic and anaerobic samples forming distinct clusters and exhibiting shifts in dominant taxa and resistome composition. Antibiotic selection produced more targeted, class-specific shifts, with tetracycline resistance consistently enriched across treatments. Hybrid metagenomic assembly further resolved ARG-MGE-host linkages, revealing extensive co-localization of ARGs with MGEs and heavy metal resistance genes. Together, these findings demonstrate that antibiotic-selective culture enrichment enhances resistome surveillance by improving detection of low-abundance ARGs, while hybrid assembly provides critical genomic context to assess their mobility and host associations. IMPORTANCELivestock manure and its byproducts, such as anaerobic digestate, are recognized as important environmental reservoirs of antimicrobial resistance, yet current metagenomic approaches may underestimate this risk by failing to detect low abundance but clinically relevant resistance determinants. Here, we show that integrating culture enrichment with hybrid metagenomics improves the recovery of antimicrobial resistance genes and reveals their association with mobile genetic elements and bacterial hosts. This approach captures a cultivable and condition-responsive fraction of the resistome that is not readily accessible through direct metagenomic sequencing alone, providing a more informative framework for environmental AMR surveillance.

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.

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.

Wastewater sequencing is an increasingly valuable tool in tracking the spread of infectious disease agents across space and time in areas of dense human settlement. Among pathogens that can be readily detected by this approach is influenza A, which follows predictable patterns of prevalence through the winter months in North America. Here, we leverage routine surveillance of a municipal wastewater treatment plant in Northern California to describe an atypical, off-season spike in influenza A concentrations that rivals that of the winter respiratory virus season. Drawing upon metagenomic data generated through hybrid-capture sequencing, we assemble and subsequently characterize fragments of divergent influenza genomes that appear to derive predominantly from the avian H16 clade. These strains exhibit close evolutionary relationships to influenza isolated from migratory shorebirds, hinting at potential host species and mechanisms of geographic spread. Analysis of read abundances suggest that these avian strains dominate the pool of influenza circulating during the summer months, when typical human-infecting strains are essentially absent. Together, our results expand the value of wastewater sequencing to encompass sensitive tracking of outbreaks within animals in interface regions where human settlement abuts wildlands, increasing overall pandemic preparedness.

Hydrocarbons are recalcitrant organic matter that are released into the environment via natural and anthropogenic activities. We hypothesized that abiotic and biotic factors, including salinity, temperature, seasonality, microbial interactions, and functional redundancy, influence the abundance and activity of potential hydrocarbon degraders in the Delaware and Chesapeake Bays. We identified key genes in hydrocarbon degradation pathways in metagenomes, metatranscriptomes, and metagenome assembled genomes (MAGs) from these estuaries. Aerobic aromatic and alkane degradation pathways predominated in both estuaries, with higher gene abundances observed in low-salinity spring and summer samples. Hydrocarbon degrading MAG abundance were significantly structured by salinity, temperature, nitrate, and silicate concentrations. Metatranscriptomic analyses revealed consistently higher expression of aerobic alkane and aromatic degradation genes in the Delaware compared to the Chesapeake Bay, with the highest occurring under low-salinity spring conditions in the former. Catechol degradation pathways exhibited high functional redundancy, whereas the naphthalene degradation pathway showed restricted distribution. Co-expression analysis revealed that Burkholderiales displayed condition dependent metabolic coupling while Pseudomonadales integrated hydrocarbon degradation with fermentation and central metabolism, demonstrating complementary strategies that support multi-scale ecosystem resilience. In conclusion, environmental gradients and taxon-specific metabolic strategies together govern hydrocarbon degradation potential in these estuaries, with implications for predicting ecosystem responses to hydrocarbon inputs under changing conditions. ImportanceCoastal estuaries are among the most contaminated aquatic environments on Earth, receiving continuous hydrocarbon inputs from industrial activity, urban runoff, and natural sources. Microorganisms are the primary agents of hydrocarbon breakdown in these systems yet predicting when and where this capacity is active and how resilient it is to environmental change remains a major challenge. Using paired genomic and transcriptomic data from microbial genomes across two major mid-Atlantic estuaries, we show that hydrocarbon degradation capacity is not uniformly distributed but is instead shaped by salinity, nutrients, and seasonality in pathway-specific ways. Critically, dominant degrader taxa employ fundamentally different metabolic strategies to sustain this function across fluctuating conditions, providing a form of community-level insurance against environmental disturbance. These findings advance our ability to predict microbial hydrocarbon degradation in coastal systems and inform nature-based approaches to bioremediation under increasing climate and anthropogenic pressures.

Phytophthora species are globally significant soilborne oomycetes responsible for widespread ecosystem decline. Standard soil sampling protocols, originally developed for qualitative baiting assays, typically require collecting substantial soil volumes in order to capture viable propagules. While effective for culture-based detection, these protocols are labour-intensive and can damage the shallow root systems of sensitive host species such as New Zealand kauri (Agathis australis). Phytophthora agathidicida (PA), the pathogen associated with kauri dieback disease, is routinely surveyed using these methods. However, quantitative data describing the vertical distribution of PA in natural forest soils are lacking. Consequently, it remains unclear whether extensive depth sampling is necessary to ensure consistent molecular detection. In this study, we applied a quantitative oospore DNA (oDNA) qPCR assay to characterise the fine-scale vertical distribution of PA across four soil depth increments (0-5, 5-10, 10-15, 15-20 cm) from 12 kauri trees representing a range of disease stages. Results revealed distinct vertical stratification, with PA DNA concentrations peaking within the upper 0-10 cm of soil in non-symptomatic and possibly symptomatic trees. In symptomatic trees, the absolute peak occasionally reached 10-15 cm, while pathogen signals remained consistently detectable within the top 10 cm. Field validation from an additional eight trees confirmed that targeted 0-10 cm "shallow" sampling yielded higher PA concentrations than deeper sampling protocols. These findings provide a data-driven basis for refining soil sampling strategies, enabling more sensitive molecular detection while minimising disturbance and logistical effort in fragile ecosystems. IMPORTANCEPhytophthora species are among the most destructive soilborne pathogens globally, requiring robust diagnostic protocols for both agricultural and conservation settings. Traditional sampling frameworks were established to meet the biological requirements of baiting assays, which often necessitate collecting large soil volumes from broad depth profiles to ensure the capture of viable, infectious propagules. However, these extensive requirements are labour-intensive and can cause significant soil disturbance in sensitive forest ecosystems. Using P. agathidicida as a model, this study provides a high-resolution quantitative assessment of how pathogen DNA is distributed vertically across different disease stages. We demonstrate that while absolute peak abundance can shift within the 0-15 cm range as infection progresses, the pathogen signal remains consistently detectable within the top 10 cm. This evidence-based approach suggests that targeted, shallow sampling enhances sensitivity by reducing signal dilution, offering a lower-impact path for monitoring soilborne oomycetes worldwide.

Hospital-acquired infections driven by ESKAPEE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli) are highly prevalent. Premise plumbing, sinks and drains, seeds these organisms into patient environments via aerosolization and subsequent surface contamination. We measured viable ESKAPEE pathogens and overall microbial communities in and around sinks in two high-burden hospitals in La Paz, Bolivia, using culture and 16S rDNA sequencing. In a prospective observational study (May-August 2025), we collected 233 surface swabs and 39 air samples across four sink-related surface categories and in room air. Samples were plated on selective media for ESKAPEE identification and quantified as colony-forming units (CFU) normalized to 100 cm2 or 6000 L. DNA was extracted, and the full 16S rDNA gene was sequenced on PacBio Revio, analyzed via DADA2/QIIME2 and R. We detected viable presumptive ESKAPEE pathogens in 74.7% surface swabs and 74.4% air samples. Sink basins were most contaminated (mean 31CFU/100 cm2, 95 % CI16-46); concentrations declined with distance from the drain. Klebsiella/Enterobacter spp. showed the highest mean concentration across samples; S. aureus was most frequently detected (54.4% of samples). Hospital-specific differences were evident in culture positivity (Hospital A 85% vs. Hospital B 66.9%) and community composition (PERMANOVA P = 0.001; sample location explained 21.9% vs. 11.7% of variation). 16S profiling confirmed elevated relative abundances of Klebsiella, Enterococcus, and Enterobacter in basins relative to distant surfaces and air. The hospitals studied had high levels of ESKAPEE pathogens, underscoring the need for control measures.

BackgroundBuilt environment microbiome studies have identified numerous factors that shape indoor microbiomes, yet the reproducibility of these findings across buildings, timepoints, and research groups remains unclear. Differences in sequencing protocols, sampling design, and environments pose major challenges for cross-study comparisons, particularly in low-biomass environments where technical variation can obscure biological signal. To address this gap, we constructed a simple ontology which groups samples into one of three categories: hand, hand-associated surfaces, and floor then applied it to four publicly available 16S rRNA gene datasets: a hospital, university dormitory, Air Force dormitory, and private residential houses. ResultsWe identified strong and reproducible separation between floors and surfaces with frequent human contact. We found that floors consistently harbored soil-associated taxa, including KD4-96, 67-14, Skermanella, and Sphingobacterium, whereas hands and hand-associated surfaces were enriched with skin-associated genera, such as Lawsonella and Cutibacterium. Within studies, these results were generally consistent across timepoints. Across studies, mixed-model PERMANOVA analysis revealed significant clustering by sample type, with modest effects of study, suggesting that biological signal outweighed differences in laboratory or sequencing methods. Leave-one-study-out random forest models achieved high AUCs for hand vs. floor comparisons (0.865 to 0.921), moderate AUCs for hand-associated vs. floor comparisons, and weaker performance for hand vs. hand-associated comparisons. Application of the batch-correction method DEBIAS-M did not improve effect sizes or classification performance, indicating that reproducible structure was already discernible without batch adjustment. ConclusionsDespite substantial temporal and environmental heterogeneity among studies, we found that the built environment microbiome has a reproducible bacterial signal. There was consistent enrichment of soil-derived taxa on floors and human-associated taxa on hands and hand-associated surfaces suggesting a stable microbiome despite differences in building type, occupancy, and methodology. These findings establish an important foundation for future studies, suggesting cross-study comparability, the accuracy of ecological inference, and the ability to support the development of predictive applications in indoor microbiome research.

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.

Water scarcity is an increasing constraint on agricultural productivity and demands scalable strategies that improve crop performance under reduced irrigation. As soil microorganisms regulate key processes at the soil-plant interface, microbial inoculants may help sustain plant growth and physiological function during water limitation. Here, we assembled five functionally diverse microbial consortia containing taxa selected to support rhizosphere colonization, soil structural stabilization, and fungal-mediated nutrient and water foraging. These consortia were evaluated in greenhouse trials with lettuce and spinach grown under full irrigation or a 30% deficit irrigation regime (70% of crop water requirement). Crop responses were assessed using yield, harvest delay, root length, wilting incidence, chlorophyll content, and Water Band Index (WBI). Across both crops, microbial consortium treatments improved performance under deficit irrigation relative to untreated water-stressed controls. In lettuce, yield increased by 3-9%, while in spinach yield increased by 4-13%, with several treatments restoring performance to levels not significantly different from the fully irrigated control. Microbial treatments also reduced harvest delay by an average of three to four days, improved root length, lowered wilting incidence, and reduced WBI, indicating reduced plant water stress. In several cases, these physiological responses approached those observed under full irrigation despite 30% lower water input. Higher application rates (500 vs 250 g h-1) generally produced stronger responses, although this trend was not always statistically significant. Together, these results show that complex microbial consortia can buffer the negative effects of deficit irrigation and improve crop performance in leafy greens. These findings support the development of microbial inoculants as biologically based tools to enhance agricultural resilience under increasing water scarcity. TeaserMicrobial soil inoculants help crops maintain yield and harvest synchrony under reduced irrigation.

Bacterial interactions-whether positive or negative - are crucial for the functioning of microbial communities. Though bacterial interactions are mainly expected to be negative, the sign and strength of interactions are predicted to be context dependent, with interactions typically being more positive in more stressful and nutrient-poor conditions. However, systematic studies investigating how the environment affects interactions between multiple taxa are lacking. Here, we determine if interactions between a panel of natural soil isolates change in response to the environment in which they are grown, with two different artificial media used (one simple and one complex) and a more ecologically relevant soil wash. To maximise natural variation in interactions, we collected multiple isolates from multiple sites: co-occurring (sympatric) isolates were predicted to show more negative interactions than allopatric isolates because of greater overlap in resource use. Pairwise interactions were in general negative, but more negative when grown in a complex lab-derived medium (Tryptic Soy Broth). Mutually beneficial interactions were most common in a simple resource medium (M9 minimal media) and exploitative interactions were most frequent in a soil broth. These patterns were independent of whether species originated from the same or a different site. The study supports the prediction that nutrient rich environments promote more negative interactions, and that measuring interactions of soil isolates in standard lab media is likely to misrepresent interactions occurring in natural environments.

Arctic winters are long and cold and have traditionally been considered a period of limited biological activity. However, the seasonal dynamics of microbial community composition and functional potential during winter remain poorly understood. Here, we investigated taxonomic (bacteria, fungi, archaea) and functional (fungal guilds and nitrogen cycling genes) dynamics throughout a full year at two Arctic tundra heath sites with contrasting snow regimes. A steep drop in microbial abundances in early to mid-winter, likely linked to freeze-thaw events, coincided with shifts in soil pH and elevated community turnover. Saprotrophic and root-associated fungi were more abundant in the cold-season, while inorganic nitrogen cycling groups were more abundant in summer and declined toward winter despite high bacterial abundance. This indicates sustained organic matter cycling during the winter and expanded inorganic nitrogen cycling in the summer. Functional gene ratios further suggested a higher early-winter nitrogen loss potential via nitrous oxide and greater late-winter nitrogen retention. Site-specific differences in snow regime altered the timing and magnitude of these dynamics. Together, our results demonstrate that winter represents a critical and dynamic period for microbial community restructuring with important implications for nitrogen turnover in Arctic tundra soils.

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.

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.