Environmental Science & Technology

2,4,6-Trinitrotoluene (TNT) is a recalcitrant and pervasive environmental pollutant. Although different environmental microbes have demonstrated their ability to degrade or transform TNT, the underlying genetic basis and cellular machinery remain unclear. In this study, we investigated bacterial strategies in response to TNT exposure in Pantoea sp. MT58 and P. putida KT2440 using proteomics and random barcode transposon-site sequencing (RB-TnSeq). Pantoea sp. MT58 was found to utilize TNT as a sole nitrogen source, whereas P. putida KT2440 exhibited only stress tolerance without assimilation. Pantoea sp. MT58 encodes multiple putative nitroreductases that were upregulated, yet deletion of these genes did not affect growth on TNT, revealing pathway redundancy. Furthermore, fitness profiling provided no evidence for genes involved in the canonical Meisenheimer-complex pathway associated with nitrite release. Instead, the data are most consistent with a sequential nitro-group reduction route in which nitrogen is ultimately recovered as ammonium, with nitrogen routed through the GS-GOGAT pathway with purine and urea pools as the candidate buffering architecture for TNT mineralization. Conversely, P. putida KT2440 relied on Ttg/RND efflux pumps and toluene tolerance proteins for survival without nitrogen assimilation from TNT. This work distinguishes routes for productive nitrogen assimilation from those involved in nitroaromatic tolerance, expanding the mechanistic understanding of anthropogenic compound metabolism to inform future bioremediation efforts.

Biological nitrification inhibition (BNI) is a plant-mediated process that suppresses nitrification and is widely considered beneficial for reducing nitrous oxide emissions. Here, we show that BNI compounds also inhibit methane oxidation by methanotrophic bacteria, revealing a previously unrecognized trade-off in greenhouse gas regulation. Across soil bioreactor systems and pure cultures of both Type I and Type II methanotrophs, BNI compounds consistently suppressed methane oxidation activity. Kinetic analyses indicated an uncompetitive-like inhibition pattern, characterized by concurrent decreases in Vmax and Km, while reversibility assays showed that inhibition was not associated with loss of cellular viability. Experiments under copper-replete and copper-depleted conditions further showed that inhibition is predominantly associated with particulate methane monooxygenase (pMMO). Transcriptomic analyses demonstrated compound-specific responses, including suppression of methane oxidation pathways and differential regulation of stress-associated genes. These findings suggest that BNI-mediated inhibition of methane oxidation may offset reductions in nitrous oxide emissions, with implications for predicting net greenhouse gas fluxes in agricultural and wetland ecosystems. Incorporating BNI effects into biogeochemical models will be critical for accurately evaluating their role in the global methane budget.

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.

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

The increasing discharge of treated wastewater effluent poses a growing threat to freshwater ecosystems. Although wastewater treatment plants reduce chemical pollution, they do not fully remove many biologically active compounds. Behavioural responses in aquatic organisms provide sensitive and ecologically relevant indicators of sublethal contaminant exposure, offering insight into underlying physiological disruption and potential ecological consequences. Here, we examined the behavioural and neurotoxic effects of a seven-day experimental exposure to treated wastewater effluent in the noble crayfish (Astacus astacus). We quantified four ecologically important behaviours: (1) shelter use, a key antipredator strategy, (2) food seeking, (3) the ability to detect and respond to wastewater-associated olfactory cues, and (4) locomotor activity was assessed across all behavioural contexts. Cholinesterase (ChE) activity was measured as a biomarker of neurotoxicity. Exposure to wastewater effluent significantly altered crayfish behaviour. Exposed individuals exhibited higher locomotor activity compared to controls, exposed crayfish avoided areas containing wastewater cues, spending less time near the effluent source. Similarly, ChE activity was significantly reduced in exposed crayfish, indicating neurotoxic effects. The concurrence of ChE inhibition and behavioural modification suggests that effluent-derived contaminants may interfere with neural signalling pathways underlying crayfish locomotion and habitat selection. Overall, our results demonstrate that short-term exposure to treated wastewater effluent can induce both neurochemical disruption and ecologically relevant behavioural changes in A. astacus. Such alterations may increase vulnerability to predation and influence population dynamics in effluent-receiving waters, highlighting the importance of integrating behavioural endpoints with mechanistic biomarkers in assessing sublethal impacts of wastewater contamination.

Benzalkonium chloride (BAC) is widely used as a disinfectant in cleaning products and is frequently detected in indoor dust. In this study, we assessed dust samples, along with information on cleaning product use, from 24 pregnant participants. Dust samples were analyzed for BAC concentration and microbial tolerance. Different chain lengths of BAC (C12, C14, and C16) were quantified using LC-MS/MS, and bacterial isolates were tested for BAC tolerance using minimum inhibitory concentration (MIC) assays. BAC was ubiquitously detected, with C12 and C14 being dominant. Higher BAC concentrations were associated with reported disinfectant use and increased microbial tolerance. These findings suggest that indoor antimicrobial use may promote microbial resistance, highlighting potential exposure risks in indoor environments and the need for further investigation into health and ecological impacts.

Lifestyle, environmental and other exposures to exogenous mutagens generate somatic mutations in normal human cells in vivo and increase cancer risk. However, the global repertoire of exogenous mutagen exposures is uncertain. The mutational signatures of mutagens in normal tissues offer opportunities to detect such exposures and survey them at population level. Using single-molecule duplex sequencing of normal kidney (n=319) and blood (n=272) samples from 10 countries, we show that normal kidney cell genomes report an extensive repertoire of somatic mutational signatures. Microdissection of kidney structures revealed that proximal tubules exhibit higher mutation rates than other components of the nephron and most normal cell types despite low cell division rates. This is explained by marked enrichment of mutational signatures due to known exogenous carcinogenic mutagens including the plant-derived aristolochic acids, as well as several signatures of unknown causes including an unknown agent prevalent in Japan (SBS12), and signatures of uncertain origins (SBS40b and SBS40c). The results suggest the existence of multiple, common, systemically circulating mutagens affecting human populations and indicate that the genomes of kidney proximal tubule cells report such exposures with high sensitivity.

Per- and polyfluoroalkyl substances (PFAS) are highly resistant to enzymatic C-F bond cleavage, and hydrolytic defluorination of long-chain PFAS has rarely been demonstrated. Here, we report selective hydrolytic defluorination of branched perfluorooctanoic acid (PFOA) isomers by a haloacid dehalogenase (4A) from Delftia acidovorans strain D4B. A fluoride-specific riboswitch biosensor was used for initial substrate screening, followed by scaled-up assays in which fluoride release was quantified using a fluoride ion-selective electrode. Defluorination products were subsequently identified by liquid chromatography-mass spectrometry (LC-MS). Although purified 4A (10 M) readily catalyzed hydrolytic defluorination of fluoroacetic acid, incubation of PFOA (0.5 mM) with purified 4A resulted in a statistically significant increase in fluoride release at elevated enzyme loading (500 M). High-resolution LC-MS/MS analysis revealed that defluorination products originated from minor branched PFOA isomers rather than linear PFOA. Molecular docking analyses supported catalytically plausible binding geometries for branched PFOA isomers, positioning the substrate -carbon within [~]4 [A] of the catalytic aspartate residue. These findings demonstrate previously unrecognized hydrolytic reactivity of a haloacid dehalogenase toward branched PFAS isomers and expand the known catalytic scope of the haloacid dehalogenase family. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/719434v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1c12fb1org.highwire.dtl.DTLVardef@224ae3org.highwire.dtl.DTLVardef@16293b7org.highwire.dtl.DTLVardef@d014b7_HPS_FORMAT_FIGEXP M_FIG C_FIG SYNOPSISEnzymatic defluorination of PFAS is rarely observed in environmental systems. This study identifies hydrolytic defluorination of branched PFOA isomers, improving understanding of PFAS defluorination at the enzyme level.

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

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

The 18S rRNA gene has emerged as the primary molecular marker for amplicon-based characterization of microalgal communities, including in wastewater treatment systems, yet trade-offs between short- and long-read approaches remain poorly defined. We systematically compared V8-V9 short-read sequencing (Illumina MiSeq), full-length long-read sequencing with ss5ss3 primers (PacBio Sequel II), and computationally extracted V8-V9 regions from long-read data. Both in silico and in vitro analyses confirmed V8-V9 captured broader taxonomic coverage than ss5ss3, though partial reference sequences and taxonomic mis-annotations biased in silico assessments. Long-reads taxonomic advantage was database-dependent, constrained by SILVA databases genus-level curation but fully realized when paired with the species-level-curated and eukaryotes-focused PR{superscript 2} (Protist Ribosomal Reference) database. Long-read sequencing uniquely identified amplicon sequence variants (ASVs) assigned to key phosphorus assimilators (Scenedesmus obliquus, Desmodesmus sp., and Acutodesmus sp.) at species level during successful phosphorus removal in a full-scale microalgal cultivation system, while V8-V9 short-read sequencing revealed ASVs assigned to algal-predatory (Leptophryidae) and bacterivorous (Choanoflagellata and Rhogostoma-lineage) protists when performance declined, suggesting grazing pressure on the phosphorus-removing community. Although both approaches performed comparably for operational monitoring, these complementary strengths support short-read sequencing for routine community profiling and long-read sequencing for detailed functional investigations of Chlorophyta.

Bullous pemphigoid (BP) is an autoimmune blistering disease with a growing incidence, and environmental factors are receiving increasing attention. Tetrabromobisphenol A (TBBPA), a widely used brominated flame retardant, is a significant environmental pollutant. However, the molecular mechanisms by which TBBPA contributes to BP pathogenesis remain unclear. This study integrated network toxicology, molecular docking, and molecular dynamics (MD) simulations to systematically investigate the molecular mechanisms of TBBPA-induced BP. Using network toxicology, we identified 797 potential targets of TBBPA and 446 BP-related targets. A Venn diagram analysis revealed 48 common targets. Protein-protein interaction (PPI) network and topological analyses further identified five core hub targets: TNF, CXCL8, MMP9, ICAM1, and ITGB1. Gene enrichment analysis indicated that these targets were significantly enriched in immune-inflammatory pathways, such as leukocyte migration, inflammatory responses, and the IL-17 signaling pathway, as well as in various pathogen infection and cancer-related pathways. Molecular docking revealed that TBBPA stably binds to all five core targets with binding energies [≤] -5 kcal/mol, driven primarily by hydrophobic interactions and {pi}-{pi} stacking. Subsequent MD simulations confirmed that TBBPA complexes with TNF, CXCL8, and MMP9 remained stable throughout the 100 ns simulation. The overall protein structures remained compact, and the ligands were effectively encapsulated within the binding pockets, forming stable networks of hydrogen bonds and hydrophobic interactions. In conclusion, this study, for the first time, proposes a systematic molecular framework using integrated computational biology. Our findings suggest that the environmental pollutant TBBPA may act as a potential risk factor in BP pathogenesis by targeting core proteins (TNF, CXCL8, and MMP9). These interactions potentially disrupt critical signaling pathways related to immune inflammation, cell migration, and tissue remodeling. This study offers a novel mechanistic hypothesis regarding environmental chemical exposure in autoimmune blistering diseases, although further experimental validation is required. HighlightsO_LINetwork toxicology identified 48 common targets linking Tetrabromobisphenol A(TBBPA) exposure to Bullous Pemphigoid (BP). C_LIO_LIFive core targets (TNF, CXCL8, MMP9, ICAM1, ITGB1) were screened as potential mediators. C_LIO_LITBBPA stably binds to TNF, CXCL8, and MMP9 with binding energies [≤] -5 kcal/mol. C_LIO_LIMolecular dynamics simulations confirm stable binding and structural integrity of complexes. C_LIO_LIThis study provides a mechanistic framework for TBBPA as an environmental risk factor in BP. C_LI

As toxicology shifts towards non-animal testing, quantitative models are essential to predict adverse health effects from molecular or cellular perturbations. Quantitative Adverse Outcome Pathways (qAOPs) represent such models, building on mechanistic knowledge and quantifying the Key Event Relationships (KERs) described in AOPs. Despite the recognized need, the number of qAOPs remains limited. Bayesian-based approaches are often chosen for developing qAOP for their flexibility, but most use discretized variables, limiting their predictive power. In addition, these models are mainly built from newly generated data, underexploiting the large amount of information available. This study successfully leverages data from public literature and presents an innovative framework based on continuous variables to develop a Bayesian-based quantitative model for a central KER towards liver fibrosis. The model predicts the probability of the expression fold change for two key markers of hepatic stellate cell activation (aSMA and COL1A1), given the effects on tissue injury, using in vitro data from 9 chemicals. We propose a newly developed workflow to assist in knowledge identification, organization, and extraction from scientific literature and chemical databases. Based on in vitro data and in vivo information from the Open TG-GATEs (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System) database, we estimate a biologically relevant range in COL1A1 fold change that indicates an activated state of stellate cells and high liver fibrosis odds ratios. Our study provides a case example of integrating published data and continuous variables to build a Bayesian-based model, which constitutes an essential step for predicting liver fibrosis from in vitro data.

Isoprenoid quinones are ubiquitous redox lipids that mediate electron transfer in various cellular processes across all domains of life. These molecules also serve as taxonomic and metabolic markers, facilitating the characterisation of microbial communities. However, their structural diversity and extreme hydrophobicity pose challenges for comprehensive detection and quantification in complex biological matrices. In this study, we present a semi-quantitative HPLC-MS/MS method that enables the sensitive analysis of the widest range of quinones reported to date. Using a 16-quinone standard mixture, we optimized separation within a 14-minute HPLC gradient and achieved femtomole-level sensitivity in targeted analyses. When applied to sewage sludges sampled weekly over three weeks, our method detected 57 distinct quinones, revealing stage-specific quinone profiles that reflect shifts in bacterial communities during wastewater treatment. This rapid and sensitive workflow provides a robust tool for accurate quinone profiling in complex samples, opening avenues for the discovery of novel quinones through untargeted approaches. By pushing the boundaries of quinone profiling, our method holds significant promise for advancing microbial ecology, environmental monitoring, and biotechnological applications. HighlightsO_LIuHPLC-Orbitrap method for the semi-quantitative profiling of isoprenoid quinones C_LIO_LIAnalysis of the widest range of isoprenoid quinones to date C_LIO_LIFemtomole-level sensitivity in just 14 minutes of chromatographic separation C_LIO_LIDetection of 57 quinones in complex wastewater sludge matrices C_LIO_LIMost comprehensive set of quinone standards including microbially-purified quinones C_LI

Reducing the cost and environmental impact of cell culture media is an important goal for cultivated meat, the process of generating meat in vitro using proliferating animal cells. While prior approaches have demonstrated the use of microbial lysates to replace expensive animal-based fetal bovine serum (FBS) in media, these formulations still rely on large quantities of growth factors such as fibroblast-like growth factor 2 (FGF2). Here, we demonstrate the use of FGF2-expressing Vibrio natriegens to create whole-cell lysates that replace both FBS and FGF2 in cell culture media for cultivated meat applications. This medium, named "VN40FGF", supports rapid proliferation of immortalized bovine muscle satellite cells (iBSCs) in the absence of supplemented FGF2. Cells grown in VN40FGF maintain phenotype and differentiation capacity. We also demonstrate that engineered V. natriegens can grow in spent cell culture media, further improving sustainability and economics, and reducing potential eutrophication concerns associated with waste disposal. Our approach combines multiple strategies for reducing the total number of media inputs, demonstrating opportunities for more economical and sustainable cell culture, especially for cultivated meats.

Accelerating the development of enzymatic degradation of polyesters such as poly(ethylene terephthalate) (PET) and poly(butylene terephthalate) (PBT) requires a rapid and parallelizable detection method. We developed a protein-based biosensor for the fast and accurate quantification of the PET and PBT degradation product, terephthalate (TPA), which we named TPAsense. Engineering TPAsense required overcoming low thermal stability and aggregation of the initial construct by introducing stabilizing mutations without disrupting the binding affinity to TPA. The sensor performance was validated by screening for the PBT degrading activity of a Leaf-branch Compost Cutinase (LCC) mutant library and comparing with liquid chromatography data. TPAsense detects nanomolar concentrations of TPA enabling shorter incubation times for screening workflows. In addition, a comparative analysis of PETase and PBTase kinetics was performed with TPAsense. Finally, we demonstrated the detection of PET microplastic in samples from a wastewater treatment plant by combining the biosensor and a PETase. TPAsense offers a platform to accelerate PETase and PBTase development for plastic waste recycling and detection of microplastic in the environment.

Military aviation training noise remains understudied despite its widespread impacts across urban, rural, and wilderness areas. The predominance of low-frequency noise and repetitive training can create pervasive noise pollution, yet past research often fails to capture the full range of health and quality-of-life effects. This study analyzed two complaint datasets related to Whidbey Island Naval Air Station noise: U.S. Navy records (2017-2020) and Quiet Skies Over San Juan County data (2021-2023). We analyzed and mapped sentiment intensity from noise complaints relative to modeled annual noise exposure, developed a typology to classify impacts, and modeled the environmental and operational factors influencing complaints. Findings revealed widespread negative sentiment and anger, often beyond the bounds of estimated noise contours, suggesting that annual cumulative noise models inadequately estimate community impacts. Complaints consistently highlighted sleep disturbance, hearing and health concerns, and compromised home environments due to shaking, vibration, and disruption of daily life. Residents also reported significant social, recreational, and work disruptions, along with feelings of fear, helplessness, and concern for children's well-being. The number of complaints were strongly associated with training schedules, with late-night sessions being the strongest predictor. A delayed response pattern suggests residents reach a frustration threshold before filing complaints. Overall, our findings demonstrate persistent negative sentiment and diverse impacts from military aviation noise. Results highlight the need for improved noise metrics, modeling and operational adjustments to mitigate the most disruptive effects.

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.

Per- and polyfluoroalkyl substances (PFAS) are chemicals linked to obesity and metabolic dysfunction, but their role in bariatric surgery remains poorly understood. This prospective pilot study examined correlations between plasma PFAS concentrations, body composition, and glycemic measures in adults undergoing bariatric surgery. Thirty-two patients (91% female; 66% Black; mean age 43 years) were enrolled preoperatively; twenty-two completed follow-up at a mean 8.6 months post-surgery. Three PFAS (PFHxS, PFNA, and PFOS) were quantified by plasma liquid chromatography-mass spectrometry; body composition and insulin sensitivity were assessed by dual-energy X-ray absorptiometry and intravenous glucose tolerance testing. At baseline, higher plasma PFNA and PFOS concentrations tracked with lower total lean mass ({rho}s = -0.46 and -0.48, respectively) and lean mass index ({rho}s = -0.46 and -0.42), and PFNA was inversely correlated with body weight ({rho}s = -0.40). No baseline associations were observed with adiposity or glycemic indices. Postoperatively, PFHxS concentrations decreased (median = -1.103 ng/mL, p < 0.001), whereas PFNA and PFOS did not change. Average PFNA was positively correlated with postoperative changes in HOMA-IR ({rho}s = 0.51) and total lean mass ({rho}s = 0.49). No significant associations were observed for average PFHxS or PFOS. These findings suggest that PFNA and PFOS may be linked to reduced lean tissue at baseline, and that PFNA burden modestly tracks with attenuated metabolic and body composition recovery. In an ANCOVA, baseline PFNA was not significantly associated with postoperative HOMA-IR or total lean mass. Larger, longitudinal studies are needed to clarify how PFAS influence these associations.

Cable bacteria are filamentous microbes that couple sulfide oxidation to oxygen reduction over centimeter distances via long-distance electron transport. While their activity creates characteristic biogeochemical gradients that shape sediment ecology, the study of cable bacteria has been constrained by the chemical and physical heterogeneity of the natural sediments they inhabit. To date, laboratory cultivation efforts have relied on these undefined environmental matrices. Here, we established a reproducible enrichment and cultivation platform using an artificial sediment matrix coupled with chemically defined media. This matrix successfully supported the growth of both freshwater and marine cable bacteria and enabled serial propagation over multiple transfers. Microsensor profiling confirmed that the incubations recapitulated hallmark geochemical signatures, including the sulfide, oxygen and pH gradients associated with electrogenic sulfur oxidation. Scanning electron microscopy confirmed the presence of cable bacteria, while 16S rRNA sequencing confirmed enrichment of the cable bacteria together with a stable co-enriched community that included taxa associated with sulfur and iron cycling as well as cellulose decomposition. This defined cultivation system eliminates the variability inherent to natural samples, providing a controlled platform for dissecting the physiology, genetics, and microbial interactions of cable bacteria.