Environmental Science & Technology Letters

Traditionally, studies have explored the impacts of individual water chemistry parameters on the persistence of Mycobacterium spp. and Legionella spp. in isolation with the underlying assumption that these associations are likely monotonic in nature. Yet chemical and microbiological changes are complex, and associations are likely highly combinatorial. In this study, we use interpretable machine learning models to disentangle the integrative and nonlinear associations between water chemistry and occurrence/abundance of Mycobacterium spp. and Legionella spp. Seasonal data from source water, point-of-entry and distribution systems of eight full-scale drinking water systems demonstrated that shifts in overall water chemistry were associated with the changes in microbial abundance during treatment and distribution. Machine learning models indicated moderate predictive ability of integrated water chemistry towards Legionella spp. abundance and towards the occurrence of both Legionella spp. and Mycobacterium spp., whereas predictive performance for Mycobacterium spp. abundance was limited. The association between nitrate and Legionella spp. abundance was disinfectant regimes dependent, while dissolved organic carbon exhibited a concentration dependent response type (i.e., positive and negative association). In chloraminated systems, Legionella spp. abundance was positively associated with ammonia and nitrate, highlighting the critical role of nitrification. Here, it appears that pH likely influences the initial colonization of Legionella spp. while ammonia governs its abundance in drinking water. Overall, this study demonstrates that integrated water chemistry and parameter-specific nonlinear effects collectively explain persistence of Mycobacterium spp. and Legionella spp. in drinking water systems.

Wastewater surveillance is increasingly used for antimicrobial resistance (AMR) monitoring in urban environments, but low-resource settings often lack a piped sewerage system. Instead, coprophagous flies--flies that ingest feces--may serve as composite samplers for monitoring fecal wastes present in terrestrial environments. We evaluated whether the class 1 integron-integrase gene intI1 was associated with genetic markers of AMR and fecal source tracking markers (FST) in coprophagous flies collected from latrine entrances and food preparation areas in low-income urban Maputo, Mozambique. We quantified intI1, an enteric 16S rRNA target (for normalization), three FST markers, and 30 ARG targets using qPCR. We normalized concentrations of intI1 and each target to enteric 16S rRNA. We fit linear mixed models with a random intercept for housing compound to estimate within-fly associations between log10 relative abundance of intI1 and log10 relative abundance of each target with and without adjustment for fly taxonomic group, capture location, and standardized fly mass. We also modeled per-fly unique ARG count (i.e., number of ARG targets detected) using Poisson regression. Of 188 flies assayed, 176 passed internal controls; intI1 and enteric 16S rRNA were detected in 95% and 96% of flies, respectively. Higher relative abundance of intI1 was positively associated with ARG and FST targets, with the strongest associations observed for sulfonamide-(sul1: {beta} = 0.87; 95% CI: 0.81, 0.94; sul2: {beta} = 0.81; 95% CI: 0.73, 0.89), tetracycline- (tetA: {beta} = 0.78; 95% CI: 0.70, 0.85; tetB: {beta} = 0.69; 95% CI: 0.60, 0.79), and trimethoprim-related (dfrA17: {beta} = 0.78; 95% CI: 0.70, 0.86) genes. Associations with FST markers were weaker (i.e., human mtDNA: {beta} = 0.46; 95% CI: 0.37, 0.55; human-associated Bacteroides: {beta} = 0.34; 95% CI: 0.25, 0.43). Higher relative abundance of intI1 was also associated with a greater number of ARGs detected: each 10-fold increase in intI1 was associated with an 8% higher expected unique ARG count (aRR=1.08, 95% CI: 1.04-1.12). These findings support the need for further research across different settings exploring intI1 carried by coprophagous flies as a potential standardized screening target for AMR surveillance in unsewered terrestrial environments.

Background Pseudomonas aeruginosa is a major cause of healthcare-associated infections in paediatric settings, where its persistence in moist environments such as hospital water and wastewater systems poses a particular risk to neonates and immunocompromised children. Aim The aim of this study was to showcase the long-term survival and transmission of P. aeruginosa in a large tertiary children's hospital in England which is crucial to develop strategies for water-safe care. Methods Environmental P. aeruginosa isolates were collected from taps, sinks, showers, and baths in augmented care areas of a 330-bed tertiary children's hospital built to NHS water-safety standards. Clinical isolates were classified as invasive (blood, cerebrospinal fluid, and bronchoalveolar lavage) or non-invasive (respiratory, urine, ear, abdominal, and rectal surveillance). Variable number tandem repeat (VNTR) profiles and metadata were extracted from PDF reports, de-identified, deduplicated, and curated using Python and R. Findings This retrospective study analysed nine-locus VNTR profiles of 457 P. aeruginosa isolates submitted to the UK Health Security Agency from a large tertiary children's hospital, identifying 56 isolate clusters (each with [≥]2 isolates), of which 19 (34%) contained at least one invasive isolate. The most persistent cluster (Cluster 1, n=20) spanned from July 2016 to September 2024, containing environmental and clinical (invasive and non-invasive) isolates. Conclusion These findings demonstrate long-term persistence of certain genotypes and temporal overlap between environmental and clinical isolates, highlighting the difficulty in detecting and eradicating P. aeruginosa in hospital water and wastewater systems and reinforcing the need for continuous rigorous water system controls.

Nowadays N95 facial mask has gain huge attention due to COVID19 pandemic situation and it serves as the prime PPE. Though the microbes can be restricted to get inside the human body due to the presence of mask temporarily, but over the time, bacteria and other microbes may get entrapped into the threads of the mask itself and thus acting as a storage chamber of microbes. It is necessary to eliminate them from the mask surface. To do so different floral structured Nano-ZnO with variable oriented arrangement of petals were fabricated on the surface of the N95 mask and further characterized through instrumentations including XRD, FTIR,UV-Vis, Fluorescence-Spectroscopy, SEM, DLS. The average crystallite size calculated for synthesized four different ZnO nanoflower were 25.19 nm, 23.46 nm, 27.27 nm and 31.78 nm (for glycerol, PEG, EDTA, Chitosan assisted) respectively. The antimicrobial activity was investigated by standard microbial broth dilution assay and Kirby-Bauer test which assured the inhibition of the bacterial growth. The MIC-MBC value of ZnO nanoflowers for E.coli and B. subtilis were found to be effective at dilution of 250 {micro}g/ml and 100 {micro}g/ml. Additionally a modified Kirby-Bauer assay has been designed to investigate the killing efficiency of the bacteria (E.coli). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=145 SRC="FIGDIR/small/719592v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@48e5ecorg.highwire.dtl.DTLVardef@1ef03c5org.highwire.dtl.DTLVardef@e089ddorg.highwire.dtl.DTLVardef@17b2850_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. - Graphical AbstractC_FLOATNO C_FIG

1.Etiological diagnosis of lower respiratory tract infections (LRTIs) relies on sputum or bronchoalveolar lavage (BAL), which may be difficult to obtain or invasive. Exhaled breath aerosol (XBA) sampling offers a non-invasive alternative for pathogen detection. We evaluated the performance of the AveloMask, a face mask-based device designed to capture XBAs for molecular testing. In this prospective paired-sample study, hospitalized adults with pneumonia at three hospitals in Switzerland and Georgia provided an XBA sample using the AveloMask and a lower respiratory tract (LRT) specimen (sputum or BAL). XBA samples were analyzed by multiplex PCR using the Roche LightMix(R) panel and LRT samples were tested using the BioFire(R) FilmArray(R) Pneumonia Panel. Concordance between XBA and LRT samples was assessed using positive percent agreement (PPA), negative percent agreement (NPA), and overall percent agreement (OPA). Ninety-three participants were enrolled and 63 participants provided paired samples. AveloMask sampling identified the dominant pathogen (lowest Ct value in the LRT sample) in 40/47 LRT-positive cases (85.1%). Across all targets, PPA was 61% (95%CI, 50-72%), NPA was 100% (95%CI, 99-100%), and OPA was 95% (95% CI, 92-96%). PPA was higher for bacteria than for viruses and lower PPA was largely driven by reduced detection of low-abundance or co-infecting pathogens. In a subset analysis, AveloMask results showed substantial overlap with standard-of-care testing and could have supported antimicrobial de-escalation. Breath aerosol sampling using the AveloMask enabled non-invasive molecular detection of LRT pathogens in pneumonia cases and may complement conventional standard-of-care testing, particularly when sputum is unavailable.

IntroductionDrowning risk begins with water exposure, yet population-water relationships have rarely been quantified at scale using environmental measures. This study explored whether satellite-derived data was associated with subnational drowning mortality and whether associations differed by country income level. MethodsWe linked Global Burden of Disease (GBD 2021) age-standardised drowning mortality rates to satellite-derived exposures for 212 subnational regions across 12 countries (2006-2021; 3,392 region-years). Exposures were extracted via Google Earth Engine and standardised. Gamma-log generalised linear mixed models included region random intercepts and year fixed effects. Income-stratified models were estimated separately. Supplementary models assessed maritime vessel activity. ResultsNear-water population percentage was the strongest correlate of drowning (IRR 1.40; 95% CI 1.33-1.47). Permanent water coverage was protective (IRR 0.80; 0.73-0.88), as were nighttime lights (IRR 0.96; 0.95-0.97) and hot days [≥]30{degrees}C (IRR 0.95; 0.92-0.99). Mean temperature (IRR 1.17; 1.11-1.23) and precipitation (IRR 1.03; 1.01-1.04) were positively associated. Near-water effects were consistent across income strata (LIC 1.25; MIC 1.31; HIC 1.24), while other predictors showed weak or inconsistent within-strata associations. Vessel activity was modestly associated with drowning in Global Fishing Watch models (IRR 1.05; 1.01-1.09) but not in Synthetic Aperture Radar models. DiscussionSatellite-derived indicators can characterise drowning risk at scale, with population proximity to water emerging as a robust cross-context correlate. Protective associations for permanent water suggest landscape configuration may shape risk beyond proximity alone, highlighting geospatial datas value for targeting prevention where surveillance is limited.

Background Polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs) are combustion-derived pollutants linked to cardiovascular disease. Prior NHANES analyses have evaluated these chemicals individually, failing to capture the correlated co-exposure structures that characterize real-world environmental burden, thereby underscoring the need for application. In this study, we applied an unsupervised machine learning pipeline to urinary biomarker data to identify multi-chemical exposure clusters and quantify their differential cardiovascular risk profiles in a nationally representative US sample. Methods We analyzed 2,979 participants from NHANES between 2017-2018, representing an estimated 36.8 million US adults after complex survey weighting. Twenty-five urinary biomarkers (6 PAH, 19 VOC metabolites) were log-transformed, imputed using Multivariate Imputation by Chained Equations (MICE), and standardized. Uniform Manifold Approximation and Projection (UMAP) was used for dimensionality reduction, followed by Gaussian Mixture Model (GMM) clustering. Survey-weighted prevalence estimates with 95% confidence intervals (CIs) were calculated for hypertension and high total cholesterol within each cluster. Weighted multivariable logistic regression was used to estimate odds ratios (OR) for hypertension, adjusting for age, sex, race/ethnicity, and income. Results Four exposure clusters were identified with a mean assignment probability of 0.948. The High combustion cluster (n=370; estimated 5.1 million US adults) exhibited the highest multi-chemical burden and a weighted hypertension prevalence of 39.3% (95% CI 37.2-41.4%), compared to 28.7% (95% CI 21.9-35.5%) in the Low exposure reference group. After demographic adjustment, High combustion cluster membership was independently associated with 38.4% higher odds of prevalent hypertension (OR 1.38). The prediction model achieved a cross-validated area under the receiver operating characteristic curve (AUC) of 0.849 (SD 0.017). Non-Hispanic Black participants constituted approximately 40% of the High combustion cluster, exceeding their representation in lower-risk clusters. Conclusions Multi-chemical exposome profiling identifies four cardiovascularly distinct subpopulations in the US adult population. Membership in the High combustion exposure cluster was associated with higher odds of prevalent hypertension and disproportionately affected Non-Hispanic Black participants. These findings support the use of multichemical approaches over single-pollutant analyses and highlight the relevance of environmental exposure patterns for making policy and targeted cardiovascular risk stratification.

Ocean warming is currently leading to distributional shifts of species and an alternation of coastal communities. Vulnerable species that are most sensitive to ocean warming are able to use several acclimation mechanisms, with one of the fastest being a shift in and shuffling of their partnerships with symbiotic microorganisms. Assessing symbiosis-focused mechanisms of acclimation and adaptation in response to ocean warming is a technical challenge due to the difficulty of accurately simulating the de novo formation of coastal communities. Here, we use the Kiel Outdoor Benthocosm facility to assess which sponges species are experimentally recruited and whether they exhibit symbiosis-focused mechanisms of acclimation following selection to ocean warming. We observed one sponge species (Haliclona sp.) and found that this sponge exhibited significant shifts in the membership and composition of its associated microbiome in response to ocean warming, with much of this being attributed to the rare microbiota. Moreover, Haliclona sp. maintained the diversity and dominance of its microbiome members. Four bacteria taxa were differentially abundant at elevated temperatures, with two being a Francisella sp. that is a suspected pathogen and an uncultured Francisellaceae that is most closely related to sulfur-oxidizing endosymbionts. Changes to the Haliclona sp. microbiome are largely consistent with a limited acclimation response, which could indicate that this sponge may use microbial symbionts as part of a mechanism to acclimate and adapt to a warmer future ocean.

The increasing use of microbial biopesticides in sustainable agriculture requires a deeper understanding of their potential impact on non-target pollinators. Although biocontrol agents are generally considered safer than synthetic pesticides, they may still cause subtle but ecologically relevant adverse effects on non-target organisms, especially when exposed to multiple stressors that are often overlooked in current risk assessment frameworks. Among these, nutritional stress, caused by habitat loss, fragmentation and reduced floral diversity, is becoming increasingly widespread. In this study, we investigated the lethal and sublethal effects of the bacterial biopesticide Bacillus velezensis (formerly B. amyloliquefaciens) strain QST713 at field-relevant concentrations on two key pollinators: Apis mellifera and Bombus terrestris. For the first time for a biopesticide, oral toxicity was assessed under environmental stress represented by diets with varying sugar concentrations (optimal and suboptimal) to identify potential synergistic effects on bee health. Sublethal effects were examined by studying learning performance and memory retention through a conditioning experiment under laboratory conditions. The results showed marked species-specific differences. While B. velezensis did not impact bee survival under realistic nutritional conditions, we observed a synergistic lethal effect in B. terrestris when biopesticide exposure was coupled with extreme nutritional stress (sugar deprivation). Similar species-specific differences emerged at the behavioral level: unlike A. mellifera, B. terrestris showed impaired visual learning and early long-term memory recall. Taken together, these results show that sublethal cognitive endpoints and multi-stressor contexts may reveal vulnerabilities not immediately evident through mortality-based assessments alone. Our findings also highlight the importance of including multiple pollinator species in risk assessment, as sensitivity to biopesticides might greatly vary among species.

AO_SCPLOWBSTRACTC_SCPLOWSpatially resolved characterization of nanomaterial (NM) distribution within cellular ultrastructure is essential for understanding NM fate and activity in biological systems. Volume electron microscopy (vEM) is uniquely positioned to address this challenge, yet fully documented quantitative pipelines that simultaneously segment NMs and cellular structures remain scarce. Here, an end-to-end analytical pipeline is presented based on the example of serial block-face scanning electron microscopy (SBF-SEM) data of tumor spheroids containing nanoparticles (NPs). A hybrid segmentation strategy is adopted: a fine-tuned Cellpose-SAM model for cells and nuclei, and an empirical Bayes approach for AuNPs. The fine-tuned model outperforms both the pre-trained baseline and benchmark experiments in Amira, and shows good generalization to 2D EM datasets of varying sample types, suggesting potential as a general-purpose segmentation model for electron microscopy. Full 3D reconstruction of NP distributions reveals preferential clustering in the perinuclear region, with a median nucleus-to-NP distance of 2.57 {micro}m and NM uptake spanning several orders of magnitude across cells. Furthermore, morphological analysis of segmented cells and nuclei using 3D shape descriptors and local curvature metrics provides quantitative access to features inaccessible from single sections. Together, these results establish a reproducible, open framework for the joint quantitative analysis of NM distribution and cellular morphology in vEM data.

Although natural forests sequester carbon, this function may decline under chronic herbivory by abundant ungulates (hereafter overbrowsing). Specifically, overbrowsing alters stand structure, potentially impair carbon exchanges related to the vegetation. Further, overbrowsing may also accelerate soil erosion, especially in heavy-rainfall regions like Monsoon Asia. We quantified these impacts by estimating net ecosystem carbon balance (NECB; g C m-2 yr-1) by subtracting heterotrophic respiration (Rh) and lateral carbon export via erosion (Se) from net primary production (Pn) in southern Kyushu, Japan. Here, about 40-years of overbrowsing by sika deer (Cervus nippon) altered mixed broadleaf-conifer stands with presence of understory (PU) into stands with no understory (NU), then further altered into stands dominated by unpalatable shrublands (SR) or stands with canopy gaps (CG). The PU maintained a positive NECB (plot mean = 307.0 g C m-2 yr-1) because high Pn (721.9) exceeded the sum of Rh (175.4) and Se (239.5). Alteration from PU into NU converted NECB to negative (-98.2 g C m-2 yr-1). This was because the suppressed Pn (400.2 g C m-2 yr-1) could not offset the sum of Rh (170.6) and Se (327.7). Further degradation into CG caused a profound negative NECB (-894.4 g C m-2 yr-1), where Pn (71.9) offset only 7% of the sum of surging Rh (464.8) and Se (501.5). Alteration into SR showed a partially recovered NECB (97.3 g C m-2 yr-1), driven by shrub growth (Pn; 554.5, Rh; 175.4, Se; 239.5). However, this recovery is still limited given that lowered shrub biomass and prior topsoil loss via erosion. Our results validate previous findings that stand alteration from PU to SR or CG through NU leads to up to a 49% loss of ecosystem carbon stocks. Preventing stand alteration and soil erosion are key countermeasures against chronic overbrowsing and subsequent erosion. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/719128v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@12f833forg.highwire.dtl.DTLVardef@51a1cforg.highwire.dtl.DTLVardef@1562461org.highwire.dtl.DTLVardef@6e652b_HPS_FORMAT_FIGEXP M_FIG C_FIG We reported that over 40 years of sika deer overbrowsing and subsequent soil erosion severely degraded the net ecosystem carbon balance (NECB) of mountain forests in Japan. The loss of understory vegetation drove the transition of intact stands into degraded states (no-understory, shrub-dominated, or canopy gaps). Based on field measurements, we quantified that this structural alteration suppressed net primary production (Pn) while increased both heterotrophic respiration (Rh) and lateral carbon loss via soil erosion (Se). Consequently, the forest shifted from a net carbon sink (+307 g C m-{superscript 2} yr-{superscript 1}) to a source (up to -894 g C m-{superscript 2} yr-{superscript 1}). These findings provide compelling empirical evidence that increasing ungulate populations, compounded by the rising frequency of heavy rainfall, may severely undermine the carbon sequestration functions traditionally expected of natural forests.

Indo-Pacific humpback dolphin (Sousa chinensis) and finless porpoise (Neophocaena phocaenoides) are increasingly threatened across their native range, yet the relative influence of multiple stressors in shaping their population dynamics remains unclear. Current conservation strategies for both species are limited by incomplete data and limited assessment of affecting factors. Here, we integrated eDNA metabarcoding with Joint Species Distribution Modeling (JSDM) to assess how environmental gradients, pollution, and trophic associations interactively influence cetacean distributions in Hong Kong waters. We show that degraded water quality and intensified human activity negatively associated with cetacean occurrence, with clear species-specific responses to different stressors. S. chinensis covaried most strongly with Secchi disc depth, and presence of vessels, while N. phocaenoides was negatively associated with nitrate nitrogen and microbial pollution (sewage). The JSDM variance partitioning analysis highlighted that the occurrence of S. chinensis was primarily associated with anthropogenic disturbances (30.04%), followed by water physical properties (26.63%), whereas N. phocaenoides was more strongly associated with physical (40.9%) and anthropogenic disturbances (35.2%). By integrating eDNA and JSDM, our approach provides fine-scale diagnostics of species-specific vulnerabilities, supporting adaptive conservation strategies and guiding the realignment of protected areas to mitigate biodiversity loss in urbanized marine ecosystems. Environmental ImplicationOur study demonstrates that hazardous water pollutants, including microbial contamination, nutrient enrichment, and chemical stressors, vessel pressure, show strong, species-specific impacts on resident cetaceans in Hong Kong. By integrating eDNA metabarcoding with joint species distribution models, we provide a diagnostic framework that directly links pollutant profiles to ecological risk. These findings highlight that conventional conservation strategies overlooking pollution drivers are insufficient for marine megafauna persistence. Our approach offers an early-warning system for monitoring hazardous pollutants in coastal ecosystems and supports adaptive management strategies to mitigate biodiversity loss in urbanized seascapes.

Drowning remains a major global public health challenge, yet how built environment characteristics shape population-level drowning risk remains poorly understood. This study linked satellite-derived built environment data to subnational drowning mortality estimates across 203 regions in 12 countries from 2006-2021. It found that built environment associations with drowning mortality are complex, non-linear, and shaped by development context. Urban extent was strongly protective, while built area near water showed protection overall but increased risk when combined with high population crowding. Almost all drowning mortality variance occurred between regions rather than within regions over time, indicating risk is predominantly determined by place-based characteristics. Income-stratified analyses revealed profound heterogeneity: crowding was protective in low-to middle-income settings but near-null in high-income regions, while waterfront development captured very different realities across contexts. These findings highlight the importance of tailoring drowning prevention strategies to local built environment configurations and development contexts.

Hypotheses concerning the ecology and evolution of bacteria commonly relate to the presence and abundance of species in various settings and conditions. Shotgun metagenomics may address these hypotheses, which previously relied on PCR or culture. However, the problem of determining the presence/absence of a given species of interest is not trivial, particularly when closely related species are present in the reference database or metagenomic sample. Reference-based methods to detect species-level taxa mostly rely on thresholding of aligned reads or mapped k-mers or derivative metrics like genomic coverage, and create a trade-off between recall/completeness and precision/purity. New methods for species-level profiling (YACHT, metapresence and sylph) have recently been published. Here we test the performance of these methods, along with Kraken2/bracken and MetaPhlAn4, to detect related species of interest using simulated metagenomic samples from genomes in the families Mycobacteriaceae and Neisseriaceae, which contain closely related genomes. Among methods tested, metapresence, when used with an alignment quality filter, and sylph offer the best overall performance. Sylph maintains high precision but requires a depth of coverage greater than approximately 0.1x to reliably detect a genomes presence. Metapresence has a lower limit of detection of hundreds of reads but this is balanced against relatively lower precision. Both methods are relatively robust to the presence of reads from genomes outside the groups of interest. We demonstrate the application of these methods in two real-world datasets: a mycobacterial community in a drinking water system and the community of Neisseriaceae present in the human oral cavity. ImportanceDetecting which bacterial species of interest are present in a given sample is fundamental to studies of microbial ecology and evolution, and to applied microbiology (e.g. clinical diagnostics). Culture-dependent and independent (e.g. PCR) approaches are increasingly complemented by metagenomic approaches, but methods to accurately identify specific low-abundance species-level genomes in a shotgun metagenomic sample are still being refined. Here we comprehensively test YACHT, Kraken2/bracken, metapresence, MetaPhlAn4, and sylph using two simulated datasets of bacterial families, Mycobacteriaceae and Neisseriaceae that contain closely related species. Our simulations exploit natural genomic diversity to create a challenging benchmark. We demonstrate that metapresence and sylph perform best, with the former being well-suited to low-biomass host-associated datasets, and the latter with environmental metagenomic samples. This study is the first extensive benchmark of these methods for this use case, and demonstrates these methods can accurately identify closely related species of interest.

BackgroundTransposable elements (TEs) are repetitive genetic elements that can jump to new loci causing genome expansions, structural rearrangements, and can, ultimately, propel the evolution of genomes. Despite their significance, the role of TEs in the evolution of genomes and phylogenetic groups remains largely understudied in early diverging lineages. Further, the extent to which TE content varies across species is still an open question. Medusozoa, a group within Cnidaria encompassing jellyfish and hydroids, exhibits an exceptional diversity of life history strategies, body plans, and physiological capabilities. These characteristics, along with its early-diverging phylogenetic position, establish Medusozoa as an ideal system for investigating the composition and evolutionary history of TEs within the group. ResultsWe generated a custom repeat library built from annotations of 25 Medusozoan genomes and used it to characterize TEs, aiming to identify lineage-specific TE content and activity that may correlate with the diversity observed within the group. We found that repetitive element percentage and genome size varied considerably, with Hydrozoa exhibiting the most variation among classes in both respects. DNA transposons were the most prevalent TE classification in all but two genomes, averaging 28% of all genomes. Intra-genus comparisons revealed a surprising degree of differences in TE content. In the genus Aurelia, the expansion of a single DNA transposon superfamily accounted for much of the difference in repetitive element percentage between two species, whereas in the genus Turritopsis, a similar divergence resulted from the proliferation of multiple superfamilies. Interestingly, most genomes showed evidence of recent TE expansions, suggesting ongoing activity in many medusozoan species. ConclusionWe present the first comparative analysis of TEs across all medusozoan classes. Our results reveal class-specific TE dynamics and highlight cases of TE proliferations as lineages diverge. This research provides data on TE activity and diversity that can be used as a resource for future study and fills important gaps in our understanding of TEs in early diverging animal lineages.

This report identifies a bidirectional signaling axis connecting lipid metabolism to nuclear mechanotransduction, with the potential to control fatty acid/triglyceride metabolism. The sterol regulatory element-binding (SREBP) family of transcription factors control fatty acid, triglyceride and cholesterol synthesis and metabolism. The family consists of three members: SREBP1a, SREBP1c, and SREBP2, that are regulated by intracellular cholesterol levels and insulin signaling. The SREBP2-dependent control of the LDL receptor gene is a well-established target for cholesterol-lowering therapeutics and the activity of SREBP1c is an attractive target in metabolic disease. In the current report, we identify SYNE4 (nesprin-4), a component of the Linker of Nucleoskeleton and Cytoskeleton (LINC) complex, as a direct target of the SREBP family of transcription factors, and show that nesprin-4 in turn supports SREBP1c function. We identify functional SREBP binding sites in the human SYNE4 promoter and demonstrate that these are required for the sterol- and SREBP-dependent regulation of the promoter. Furthermore, we show that the endogenous SYNE4 gene is also regulated by SREBP1/2 and intracellular sterol levels. Interestingly, SREBP2 is responsible for the sterol regulation of the SYNE4 gene in HepG2 cells, while SREBP1 is the major regulator in MCF7 cells, demonstrating that diberent cell types use diberent SREBP paralogs to regulate the same promoter/gene. Importantly, we find that nesprin-4 is a positive regulator of SREBP1c expression and function in HepG2 cells and during the diberentiation of human adipose-derived stem cells. In summary, the current report identifies a novel regulatory interaction between lipid metabolism and the LINC complex. Importantly, we demonstrate that this signaling axis is bidirectional, forming a closed loop that has the potential to control SREBP1c activity and thereby fatty acid and triglyceride synthesis/metabolism. Based on our data, we propose that the nesprin-4-dependent regulation of SREBP1c could represent a novel therapeutic target in metabolic disease.

Toxoplasma gondii is a widespread human pathogen that has multiple, clinically relevant stages in its complex life cycle, including fast-replicating tachyzoites and latent bradyzoites. Bradyzoite differentiation is triggered by stress responses that lead to changes in transcription, translation, and metabolism. Two aspects of this process are addressed in this report: first, whether proteins that play roles in bradyzoite differentiation are specific to T. gondii and other bradyzoite-forming parasites of the Sarcocystidae family, and second, whether new bradyzoite differentiation proteins can be identified in T. gondii. To answer these questions, a phylogenetic approach was used, comparing proteomes of select members of the Sarcocystidae family that form morphologically different bradyzoite cysts and members of the Eimeriidae family that do not form cysts. This approach resulted in 8 distinct clusters of T. gondii proteins that reflected different conservation patterns; for example, one cluster showed conservation among all organisms, while another showed conservation in bradyzoite cyst-forming organisms. Known T. gondii proteins involved in bradyzoite differentiation were found in all clusters, indicating that this process uses both highly conserved pathways as well as bradyzoite-specific pathways. Importantly, the cluster containing proteins that are conserved in bradyzoite-forming organisms contained several known regulators of bradyzoites, and will be a source for identifying novel T. gondii proteins that are involved in bradyzoite differentiation.

The theory of island biogeography and its trophic extensions predict that both species richness and food-web complexity should increase with increasing ecosystem surface area. Accordingly, Species-Area Relationships (SARs) and Network-Area Relationships (NARs) are often observed to be positively-sloped, an observation that came to be considered as a law, and on which rest many area-based conservation plans for biodiversity. However, our mechanistic understanding of the driving mechanisms of SARs and NARs slopes remains limited, undermining our ability to predict how biodiversity will respond to habitat gain or loss. We show in 180 rural ponds sampled across five years that invasive alien predators reversed the SAR and NARs from positive in invader-free ponds, to negative in invaded ponds. Relationship reversal resulted from a higher prevalence of invasive alien predators driving magnified prey extinctions and simplified food webs in larger ponds. The ability of invasive alien predators to reverse SAR and NARs presumably reflected disproportionately high predation rates combined with a low sensitivity to prey extinction conferred by a wide trophic generalism. In a world where virtually all ecosystems face biological invasions, omnipresent invasive alien predators stress the pivotal role played by predation in shaping biocomplexity-area relationships, and highlight a growing need to preserve small ecosystems where invasive alien predators are less prevalent.

Cellular organelle content is fairly constant within a given cell type. This is accomplished in part by ensuring equitable organelle partitioning during division. Much of our understanding of organelle inheritance has come from investigating cells that divide in half producing two daughter cells. However, more elaborate division strategies that give rise to multiple daughters are not uncommon in nature. Here, we present the first characterization of organelle inheritance in a fungus that grows by multi-budding, producing several (2-20) daughter cells in a single cell cycle. We find that some organelles (mitochondria and ER) are evenly delivered to all growing buds, while others (vacuole and peroxisomes) are more variably inherited. We discuss the implications of even and uneven inheritance for this polyextremotolerant fungus capable of growing in dynamic, and diverse, environments.

Diabetes mellitus is characterized by chronic hyperglycemia and loss of pancreatic {beta}-cell function and mass. Current therapies focus on {beta}-cell protection and regeneration, led by GLP-1 receptor agonists. The G protein -subunit (Gs) acts as a key signaling node downstream of numerous GPCRs, integrating diverse signals that impact {beta}-cell mass and function. Elucidating the integrative role of pancreatic Gs signaling is thus crucial for understanding {beta}-cell biology. Our map of the pancreatic Gs-coupled GPCR landscape reveals sophisticated, cell-type-specific networks, positioning Gs as a central hub for intra-pancreatic communication. Previous studies in mice with {beta}-cell-specific or whole-pancreatic Gs deletion demonstrated reduced {beta}-cell mass, impaired insulin secretion, and glucose intolerance. The stronger phenotype in the whole-pancreas model--marked by -cell expansion and abnormal distribution--points to a crucial role for Gs in differential control of postnatal - and {beta}-cell proliferation. Here, we analyze the organ-wide consequences of Gs deletion using pancreas-specific Gs knockout mice (PGsKO). Consistent with prior findings, PGsKO mice exhibit reduced weight gain from four weeks and severe diabetes due to decreased {beta}-cell mass and concomitant -cell expansion. Furthermore, Gs loss induces profound architectural and functional defects in the exocrine pancreas, linked to YAP reactivation in acinar cells. Importantly, we observed attempted {beta}-cell regeneration in PGsKO mice. Although insufficient to reverse diabetes, our results delineate the full pancreatic phenotype that may facilitate these regenerative efforts and suggest that strategically biasing GPCR signaling network away from Gs could be a viable strategy to promote {beta}-cell regeneration from other pancreatic cell types. ARTICLE HIGHLIGHTSO_LIGs is a central signaling hub that integrates diverse GPCR inputs across pancreatic cell types, yet its organ-wide role remained poorly defined. C_LIO_LIWe addressed how pancreas-wide Gs deletion disrupts both endocrine and exocrine compartments, and whether regenerative programs are engaged. C_LIO_LIGs loss caused severe diabetes through {beta}-cell loss and -cell expansion, induced profound exocrine defects with YAP reactivation, and triggered attempted {beta}-cell regeneration from ducts and potentially other cell types. C_LIO_LIOur findings suggest that strategically biasing GPCR signaling away from Gs could promote regeneration from non-{beta}-cell sources, offering new therapeutic avenues for diabetes. C_LI