Polybrominated diphenyl ethers and polychlorinated biphenyls induced rice "diabetes" by disturbing the transport and decomposition of soluble sugars.

Halogenated flame retardants in farmlands were observed to inhibit the growth of exposed crops. This study aimed to elucidate the mechanism of inhibition on rice by employing four representative polybrominated diphenyl ethers (PBDEs) and polychlorinated biphenyls (PCBs). The exposure to these contaminants at 200 nM led to a decrease of 0.63-0.95 fold in rice below-ground biomass and 0.49-0.66 fold in yield, and a corresponding 4%-10% increase in soluble sugars in leaves. PBDEs and PCBs were found to significantly disrupt the synthesis, decomposition, and transport of sugars in leaves, the three pivotal determinants of crop growth. Notably, these compounds promoted a 1.41- to 7.60-fold upregulation of the triose phosphate translocator, significantly enhancing soluble sugar synthesis. Conversely, a 0.45-0.97 fold downregulation was observed for sucrose transporters, thus impeding the leaf-to-shoot efflux of soluble sugars. Furthermore, PBDEs and PCBs were favorably bound to fructose-1,6-bisphosphate aldolase (FBA), inducing its substrate-specific dysfunction in fructose-1,6-diphosphate decomposition (3%-14%). Overall, PBDE and PCB exposure promoted a notable intracellular accumulation of soluble sugars in rice leaves, a typical symptom of plant diabetes, since the intensified synthesis of soluble sugars in leaves and the repressed decomposition and transportation of soluble sugars to other storage organs, thus impeding crop growth. This study provided an insightful understanding of the toxic effects and molecular mechanisms of halogenated flame retardants, highlighting their role in abnormal sugar accumulation and growth inhibition in crops and offering vital information for the risk assessment and administration of these compounds to guarantee the safety of agricultural products.

Fluoranthene slow down sulfamethazine migration in soil via π-π interaction to increase the abundance of antibiotic resistance genes.

Sulfonamide antibiotics and polycyclic aromatic hydrocarbons (PAHs) often coexist in soil, leading to compound pollution through various pathways. This study focuses on sulfamethazine (SMZ) and PAHs (fluoranthene) as the subject for compound pollution research. Using a soil-groundwater simulation system, we investigated the migration characteristics of SMZ under coexistence with fluoranthene (Fla) and observed variations in the abundance of antibiotic resistance genes (ARGs). Through molecular docking simulations and isothermal adsorption experiments, we discovered that Fla bound with SMZ via π-π interactions, resulting in a 20.9% increase in the SMZ soil-water partition coefficient. Under compound conditions, the concentration of SMZ in surface soil could reach 1.4 times that of SMZ added alone, with an 13.4% extension in SMZ half-life. The deceleration of SMZ's vertical migration rate placed additional stress on surface soil microbiota, leading to a proliferation of ARGs by 66.3%-125.8%. Moreover, under compound pollution, certain potential hosts like Comamonadaceae and Gemmatimonas exhibited a significant positive correlation with resistance genes such as sul 1 and sul 2. These findings shed light on the impact of PAHs on sulfonamide antibiotic migration and the abundance of ARGs. They also provide theoretical insights for the development of technologies aimed at mitigating compound pollution in soil.

Unveiling the Mechanism and Kinetics of Pollutant Attenuation by Free Radicals Triggered from Goethite in Water Distribution Systems.

Investigating the fate of persistent organic pollutants in water distribution systems (WDSs) is of great significance for preventing human health risks. The role of iron corrosion scales in the migration and transformation of organics in such systems remains unclear. Herein, we determined that hydroxyl (•OH), chlorine, and chlorine oxide radicals are generated by Fenton-like reactions due to the coexistence of oxygen vacancy-related Fe(II) on goethite (a major constituent of iron corrosion scales) and hypochlorous acid (HClO, the main reactive chlorine species of residual chlorine at pH ∼ 7.0). •OH contributed mostly to the decomposition of atrazine (ATZ, model compound) more than other radicals, producing a series of relatively low-toxicity small molecular intermediates. A simplified kinetic model consisting of mass transfer of ATZ and HClO, •OH generation, and ATZ oxidation by •OH on the goethite surface was developed to simulate iron corrosion scale-triggered residual chlorine oxidation of organic compounds in a WDS. The model was validated by comparing the fitting results to the experimental data. Moreover, the model was comprehensively applicable to cases in which various inorganic ions (Ca2+, Na+, HCO3-, and SO42-) and natural organic matter were present. With further optimization, the model may be employed to predict the migration and accumulation of persistent organic pollutants under real environmental conditions in the WDSs.

Prediction of BTEX volatilization in polluted soil based on the sorption potential energy theory.

Initial volatile concentration (Cs0) is a crucial parameter for the migration and diffusion of volatile organic pollutants (VOCs) from the soil to the atmosphere. The acquisition of Cs0 is, however, time-consuming and labor-intensive. This study developed a prediction model for Cs0 based on theoretical analysis and experimental simulations. The model was established by correlating the molecular kinetic and sorption potential energy. The pore structure and pore size distribution of the soil were analyzed based on the fractal theory of porous media, followed by calculating the sorption potential energy corresponding to each pore size. It was observed that the pore size distribution of soil influenced BTEX (benzene, toluene, ethylbenzene, and xylene) volatilization by impacting sorption potential energy. The soil parameters, such as organic matter and soil moisture content, and the initial concentration and physical properties of BTEX were coupled to the prediction model to ensure its practicability. Red soil was finally used to verify the accuracy and applicability of the model. The experimental and predicted values' maximum relative and root-mean-square errors were determined to be 24.2% and 11.7%, respectively. The model provides a simple, rapid, and accurate assessment of soil vapor emission content due to BTEX contamination. This study offers an economical and practical method for quantifying the amount of volatile BTEX in contaminated sites, providing a reference for its monitoring, control, and subsequent remediation.

Distribution, traceability, and risk assessment of organophosphate flame retardants in agricultural soils along the Yangtze River Delta in China.

Severe pollution threatens the ecosystem and human health in the Yangtze River Delta (YRD) in China because of the rapid development of industry in this area. This study examines the types, distribution, concentration, and origin of fourteen typical organophosphate flame retardants (OPFRs) in agricultural soils within the YRD region to offer insights for pollutant control and policy-making. The total concentration of OPFRs (ΣOPFRs) varied between 79.19 and 699.58 µg/kg dry weight (dw), averaging at 209.61 µg/kg dw. Among the OPFRs detected, tributoxyethyl phosphate (TBEP) was identified as the main congener, followed by tri-n-butyl phosphate (TnBP), tris(2-chloroisopropyl) phosphate (TCPP), and trimethyl phosphate (TMP). Source analysis, conducted through correlation coefficients and PCA, indicated that OPFRs in agricultural soils within the YRD region mainly originate from emissions related to plastic products and transportation. The health risk exposure to ΣOPFRs in agricultural soil was considered negligible for farmers, with values below 1.24 × 10-2 and 1.76 × 10-9 for noncarcinogenic and carcinogenic risks, respectively. However, the ecological risk of ΣOPFRs in all the samples ranged from 0.08-1.08, indicating a medium to high risk level. The results offer a comprehensive understanding of OPFR pollution in agricultural soils in the YRD region and can be useful for pollution control that mitigates ecological and health risks in this region.

The significance of environmentally bioavailable antimicrobials in driving antimicrobial resistance in soils.

Antimicrobial resistance (AMR) stands as an escalating public health crisis fueled by antimicrobial residues in the environment, particularly in soil, which acts as a reservoir for antimicrobial resistance genes (ARGs). Merely quantifying the total extractable concentration of antimicrobials, instead of bioavailable fractions, may substantially underestimate their minimal selection concentration for propagating ARGs. To shed light on the role of bioavailability in ARG abundance within soil, a systematic bioavailability assessment method was established for accurately quantifying the partitioning of multi-class antimicrobials in representative Chinese soils. Microcosm studies unveiled that antimicrobials persisting in the bioavailable fraction could potentially prolong their selection pressure duration to trigger AMR. Notably, the co-occurrence of pesticide or steroid hormone influenced the development trends of ARG subtypes, with fluoroquinolone resistance genes (RGs) being particularly susceptible. Partial least squares path model (PLS-PM) analysis uncovered potentially distinct induction mechanisms of antimicrobials: observable results suggested that extractable residual concentration may exert a direct selection pressure on the development of ARGs, while bioavailable concentration could potentially play a stepwise role in affecting the abundance of mobile genetic elements and initiating ARG dissemination. Such unprecedented scrutinization of the interplay between bioavailable antimicrobials in soils and ARG abundance provides valuable insights into strategizing regulatory policy or guidelines for soil remediation.

Dynamic migration and risk of cephalosporin antibiotic resistance genes: Move from pharmaceutical plants through wastewater treatment plants to coastal tidal flats sediments.

The migration and dissemination of antibiotics and their corresponding antibiotic resistance genes (ARGs) from pharmaceutical plants through wastewater treatment to the environment introduce exogenous ARGs, increasing the risk of antibiotic resistance. Cephalosporin antibiotics (Ceps) are among the most widely used antibiotics with the largest market scale today, and the issue of resistance is becoming increasingly severe. In this study, a cephalosporin pharmaceutical plant was selected and metagenomic analysis was employed to investigate the dissemination patterns of cephalosporin antibiotics (Ceps) and their ARGs (CepARGs) from the pharmaceutical plant through the wastewater treatment plant to tidal flats sediments. The findings revealed a significant reduction in the total concentration of Ceps by 90.32 % from the pharmaceutical plant's Pioneer Bio Reactor (PBR) to the effluent of the wastewater treatment plant, and a notable surge of 172.13 % in the relative abundance of CepARGs. It was observed that CepARGs originating from the PBR could migrate along the dissemination chain, contributing to 60 % of the CepARGs composition in tidal flats sediments. Microorganisms play a crucial role in the migration of CepARGs, with efflux-mediated CepARGs, as an intrinsic resistance mechanism, exhibiting a higher prospensity for migration due to their presence in multiple hosts. While Class I risk CepARGs are present at the pharmaceutical and wastewater plant stages, Class I ina-CepARGs are completely removed during wastewater treatment and do not migrate to the environment. This study reveals the dynamic migration characteristics and potential risk changes regarding Ceps and CepARGs in real dissemination chains, providing new theoretical evidence for the mitigation, control, and risk prevention of CepARGs.

Understanding the phytotoxic effects of organic contaminants on rice through predictive modeling with molecular descriptors: A data-driven analysis.

The widespread introduction of organic compounds into environments poses significant risks to ecosystems. Assessing the adverse effects of organic contaminants on crops is crucial for ensuring food safety. However, laboratory research is often time-consuming and costly, and machine learning (ML) methods can offer a viable solution to address these challenges. This study aimed at developing a ML model that incorporates chemical descriptors to predict the phytotoxicity of organic contaminants on rice. A dataset was compiled by gathering published experimental data on the phytotoxicity of 60 organic compounds, with a focus on morphological inhibition, photosynthesis perturbation, and oxidative stress. Four ML models (RF, SVM, GBM, ANN) were developed using chemical molecular descriptors (CMD) and the Molecular ACCess System (MACCS) keys. RF-MACCS model demonstrated the highest fitness, achieving an R2 value of 0.79 and an RMSE of 0.14. Feature importance analysis highlighted nAtom, HBA, logKow, and TPSA as the most influential CMDs in our model. Additionally, substructures containing oxygen atoms, carbonyl group and carbon chains with nitrogen and oxygen atoms were identified as significant factors associated with phytotoxicity. This data-driven study could aid in predicting the phytotoxicity of organic contaminants on crops and evaluating the potential risks of emerging contaminants in agroecosystems.

Sulfonamide-induced DNA hypomethylation disturbed sugar metabolism in rice (Oryza sativa L.).

DNA methylation is well-accepted as a bridge to unravel the complex interplay between genome and environmental exposures, and its alteration regulated the cellular metabolic responses towards pollutants. However, the mechanism underlying site-specific aberrant DNA methylation and metabolic disorders under pollutant stresses remained elusive. Herein, the multilevel omics interferences of sulfonamides (i.e., sulfadiazine and sulfamerazine), a group of antibiotics pervasive in farmland soils, towards rice in 14 days of 1 mg/L hydroponic exposure were systematically evaluated. Metabolome and transcriptome analyses showed that 57.1-71.4 % of mono- and disaccharides were accumulated, and the differentially expressed genes were involved in the promotion of sugar hydrolysis, as well as the detoxification of sulfonamides. Most differentially methylated regions (DMRs) were hypomethylated ones (accounting for 87-95 %), and 92 % of which were located in the CHH context (H = A, C, or T base). KEGG enrichment analysis revealed that CHH-DMRs in the promoter regions were enriched in sugar metabolism. To reveal the significant hypomethylation of CHH, multi-spectroscopic and thermodynamic approaches, combined with molecular simulation were conducted to investigate the molecular interaction between sulfonamides and DNA in different sequence contexts, and the result demonstrated that sulfonamides would insert into the minor grooves of DNA, and exhibited a stronger affinity with the CHH contexts of DNA compared to CG or CHG contexts. Computational modeling of DNA 3D structures further confirmed that the binding led to a pitch increase of 0.1 Å and a 3.8° decrease in the twist angle of DNA in the CHH context. This specific interaction and the downregulation of methyltransferase CMT2 (log2FC = -4.04) inhibited the DNA methylation. These results indicated that DNA methylation-based assessment was useful for metabolic toxicity prediction and health risk assessment.

Polybrominated diphenyl ethers (PBDEs) decreased the protein quality of rice grains by disturbing amino acid metabolism.

Polybrominated diphenyl ethers (PBDEs) in soils posed potential risks to crop growth and food safety due to their prevalence and persistence. PBDEs were capable of being absorbed and accumulated into crops, impacting their growth, whereas the interference on metabolic components and nutritional composition deserves further elucidation. This study integrated a combined non-targeted and targeted metabolomics method to explore the influences of 2,2',4,4'-tetrabromodiphenyl ether (BDE-47), 2,2',4,4',5-pentabromodiphenyl ether (BDE-99) and decabromodiphenyl ether (BDE-209) on the metabolic responses of rice (Oryza sativa). Metabolic pathways, which were associated with sugars, organic acids, and amino acids, were significantly disturbed under PBDE stresses. Particularly, 75% of the marked altered pathways belonged to amino acid metabolism, with alanine/aspartate/glutamate metabolism being commonly enhanced. The degradation of aspartic acid promoted the formation of downstream amino acids, among which the levels of lysine, methionine, isoleucine, and asparagine were increased by 1.31-3.15 folds compared to the control. Thus, the antioxidant capacity in rice plants was enhanced, particularly through the significant promotion of ascorbic acid-glutathione (AsA-GSH) cycle in rice leaves. The amino acids were promoted to resist reactive oxygen species (ROS) efficiently, thus were deficient for nutrient storage. When exposed to 4 µmol/kg PBDEs, the contents of amino acids and proteins in grains decreased by 9.1-32.1% and 8.6-34.8%, respectively. In particular, glutelin level was decreased by 5.6-41.2%, resulting in a decline in nutritional quality. This study demonstrated that PBDEs deteriorated the protein nutrition in rice grains by affecting amino acid metabolism, providing a new perspective for evaluating the ecological risks of PBDEs and securing agricultural products.

Pollution characteristics and source apportionment of heavy metal(loid)s in soil and groundwater of a retired industrial park.

Heavy metal(loid)s (HMs) pollution has become a common and complex problem in industrial parks due to rapid industrialization and urbanization. Here, soil and groundwater were sampled from a retired industrial park to investigate the pollution characteristics of HMs. Results show that Ni, Pb, Cr, Zn, Cd, and Cu were the typical HMs in the soil. Source analysis with the positive matrix factorization model indicates that HMs in the topsoil stemmed from industrial activities, traffic emission, and natural source, and the groundwater HMs originated from industrial activities, groundwater-soil interaction, groundwater-rock interaction, and atmosphere deposition. The sequential extraction of soil HMs reveals that As and Hg were mainly distributed in the residue fraction, while Ni, Pb, Cr, Zn, Cd, and Cu mainly existed in the mobile fraction. Most HMs either in the total concentration or in the bioavailable fraction preferred to retain in soil as indicated by their high soil-water partitioning coefficients (Kd), and the Kd values were correlated with soil pH, groundwater redox potential, and dissolved oxygen. The relative stable soil-groundwater circumstance and the low active fraction contents limited the vertical migration of soil HMs and their release to groundwater. These findings increase our knowledge about HMs pollution characteristics of traditional industrial parks and provide a protocol for HMs pollution scrutinizing in large zones.

Insights into CO2 and N2O emissions driven by applying biochar and nitrogen fertilizers in upland soil.

Biochar and soil carbon sequestration hold promise in mitigating global warming by storing carbon in the soil. However, the interaction between biochar properties, soil carbon-nitrogen cycling, and nitrogen fertilizer application's impact on soil carbon-nitrogen balance remained unclear. Herein, we conducted batch experiments to study the effects and mechanisms of rice straw biochar application (produced at 300, 500, and 700 °C) on net greenhouse gas emissions (CO2, N2O, CH4) in upland soils under different forms of nitrogen fertilizers. The findings revealed that (NH4)2SO4 and urea significantly elevated soil carbon dioxide equivalent emissions, ranging from 28 to 61.7 kg CO2e/ha and 8.2 to 37.7 kg CO2e/ha, respectively. Conversely, KNO3 reduced soil CO2e emissions, ranging from 2.2 to 13.6 kg CO2e/ha. However, none of these three nitrogen forms exhibited a significant effect on CH4 emissions. The pyrolysis temperature of biochar was found negatively correlated with soil CO2 and N2O emissions. The alkaline substances presented in biochar pyrolyzed at 500-700 °C raised soil pH, increased the ratio of Gram-negative to Gram-positive bacteria, and enhanced the relative abundance of Sphingomonadaceae. Moreover, the co-application of KNO3 based nitrogen fertilizer and biochar increased the total carbon/inorganic nitrogen ratio and reduces the relative abundance of Nitrospirae. This series of reactions led to a significant increase in soil DOC content, meanwhile reduced soil CO2 emissions, and inhibited the nitrification process and decreased the emission of soil N2O. This study provided a scientific basis for the rational application of biochar in soil.

Field-based investigation reveals selective enrichment of companion microbes in vegetables leading to specific accumulation of antibiotic resistance genes.

Vegetables capture antibiotic resistance genes (ARGs) from the soil and then pass them on to consumers through the delivery chain and food chain, and are therefore the key node that may increase the risk of human exposure to ARGs. This study investigates the patterns and driving forces behind the transmission of ARGs from soil to vegetables by the commonly planted cash crops in the coastal region of southern China, i.e. broccoli, pumpkin, and broad bean, to investigate. The study used metagenomic data to reveal the microbial and ARGs profiles of various vegetables and the soil they are grown. The results indicate significant differences in the accumulation of ARGs among different vegetables harvested in the same area at the same time frame, and the ARGs accumulation ability of the three vegetables was in the order of broccoli, broad bean, and pumpkin. In addition, broccoli collected the highest number of ARGs in types (n = 14), while pumpkin (n = 13) does not obtain trimethoprim resistance genes and broad beans (n = 10) do not obtain chloramphenicol, fosmidomycin, quinolone, rifamycin, or trimethoprim resistance genes. Host tracking analysis shows a strong positive correlation (|rho| > 0.8, p < 0.05) between enriched ARGs and plant companion microbes. Enrichment analysis of metabolic pathways of companion microbes shows that vegetables exhibit a discernible enrichment of companion microbes, with significant differences among vegetables. This phenomenon is primarily due to the screening of carbohydrate metabolism capabilities among companion microbes and leads varied patterns of ARGs that spread from the soil to vegetables. This offers a novel insight into the intervention of foodborne transmission of ARGs.

Redox potential model for guiding moderate oxidation of polycyclic aromatic hydrocarbons in soils.

In-situ chemical oxidation is an important approach to remediate soils contaminated with persistent organic pollutants, e.g., polycyclic aromatic hydrocarbons (PAHs). However, massive oxidants are added into soils without an explicit model for predicting the redox potential (Eh) during soil remediation, and overdosed oxidants would pose secondary damage by disturbing soil organic matter and acidity. Here, a soil redox potential (Eh) model was first established to quantify the relationship among oxidation parameters, crucial soil properties, and pollutant elimination. The impacts of oxidant types and doses, soil pH, and soil organic carbon contents on soil Eh were systematically clarified in four commonly used oxidation systems (i.e., KMnO4, H2O2, fenton, and persulfate). The relative error of preliminary Eh model was increased from 48-62% to 4-16% after being modified with the soil texture and dissolved organic carbon, and this high accuracy was verified by 12 actual PAHs contaminated soils. Combining the discovered critical oxidation potential (COP) of PAHs, the moderate oxidation process could be regulated by the guidance of the soil Eh model in different soil conditions. Moreover, the product analysis revealed that the hydroxylation of PAHs occurred most frequently when the soil Eh reached their COP, providing a foundation for further microorganism remediation. These results provide a feasible strategy for selecting oxidants and controlling their doses toward moderate oxidation of contaminated soils, which will reduce the consumption of soil organic matter and protect the main structure and function of soil for future utilization. ENVIRONMENTAL IMPLICATIONS: This study provides a novel insight into the moderate chemical oxidation by the Eh model and largely reduces the secondary risks of excessive oxidation and oxidant residual in ISCO. The moderate oxidation of PAHs could be a first step to decrease their toxicity and increase their bioaccessibility, favoring the microbial degradation of PAHs. Controlling the soil Eh with the established model here could be a promising approach to couple moderate oxidation of organic contaminants with microbial degradation. Such an effective and green soil remediation will largely preserve the soil's functional structure and favor the subsequent utilization of remediated soil.

Predicting removal efficiency of organic pollutants by soil vapor extraction based on an optimized machine learning method.

Soil vapor extraction (SVE) was a cost-effective technology for remediating volatile and semi-volatile organic contaminated soils. Many factors, including SVE parameters, soil properties, and contaminant characteristics, significantly influenced the remediation efficiency of SVE. The optimal conditions for organic pollutants removal efficiency were site-specific and varied among studies. Therefore, a generalized model was needed to predict the remediation efficiency of SVE in organic contaminated soils. This study employed machine learning to predict the removal efficiency of organic pollutants by SVE. The model's development was based on a trainset, and its predictive capabilities were evaluated using a testset. An XGBoost (XGB) model was derived from literature data (R2 = 0.9728). Time, pollutant type, and temperature were identified as the three most important features affecting SVE remediation efficiency. The accuracy (R2 = 0.9799) and universality of the model were enhanced through an optimization scheme. The developed XGB model demonstrated the ability to predict the removal efficiency of organic pollutants by considering all collected influential factors. The mechanism of multi-factor interaction on remediation efficiency was clarified. Overall, this study would contribute to evaluating the remediation potential of SVE for specific organic contaminated soils, aiding in maximizing the removal efficiency of organic pollutants under optimal conditions.

Predicting thermal desorption efficiency of PAHs in contaminated sites based on an optimized machine learning approach.

Thermal desorption (TD) remediation of polycyclic aromatic hydrocarbon (PAH)-contaminated sites is known for its high energy consumption and cost implications. The key to solving this issue lies in analyzing the PAHs desorption process, defining remediation endpoints, and developing prediction models to prevent excessive remediation. Establishing an accurate prediction model for remediation efficiency, which involves a systematic consideration of soil properties, TD parameters, and PAH characteristics, poses a significant challenge. This study employed a machine learning approach for predicting the remediation efficiency based on batch experiment results. The results revealed that the extreme gradient boosting (XGB) model yielded the most accurate predictions (R2 = 0.9832). The importance of features in the prediction process was quantified. A model optimization scheme was proposed, which involved integrating features based on their relevance, importance, and partial dependence. This integration not only reduced the number of input features but also enhanced prediction accuracy (R2 = 0.9867) without eliminating any features. The optimized XGB model was validated using soils from sites, demonstrating a prediction error of less than 30%. The optimized XGB model aids in identifying the most optimal conditions for thermal desorption to maximize the remediation efficiency of PAH-contaminated sites under relative cost and energy-saving conditions.

The intracellular concentrations of fluoroquinolones determined the antibiotic resistance response of Escherichia coli.

The extensive consumption of antibiotics has been reported to significantly promote the generation of antibiotic resistance (ABR), however, a quantitative causal relationship between antibiotic exposure and ABR response is absent. This study aimed to pinpoint the accurate regulatory concentration of fluoroquinolones (FQs) and to understand the biochemical mechanism of the mutual action between FQ exposure and FQ resistance response. Highly sensitive analytical methods were developed by using UPLC-MS/MS to determine the total residual, extracellular residual, total intracellular, intracellular residual and intracellular degraded concentration of three representative FQs, including ciprofloxacin (CIP), ofloxacin (OFL) and norfloxacin (NOR), with detection limits in the range of 0.002-0.057 µg/L, and recoveries in the range of 80-93%. The MICs of Escherichia coli (E. coli) were 7.0-31.4-fold of the respective MIC0 after 40-day FQ exposure, and significant negative associations were discovered between the intracellular (residual, degraded or the sum) FQ concentrations and FQ resistance. Transcriptional expression and whole-genome sequencing results indicated that reduced membrane permeability and enhanced multi-drug efflux pumps contributed to the decreasing intracellular concentration. These results unveiled the pivotal role of intracellular concentration in triggering FQ resistance, providing important information to understand the dose-response relationship between FQ exposure and FQ resistance response, and ascertain the target dose metric of FQs for eliminating FQ resistance crisis.

Mutation-driven resistance development in wastewater E. coli upon low-level cephalosporins: Pharmacophore contribution and novel mechanism.

Cephalosporins have been widely applied in clinical and veterinary settings and detected at increasing concentrations in water environments. They potentially induce high-level antibiotic resistance at environmental concentrations. This study characterized how typical wastewater bacteria developed heritable antibiotic resistance under exposure to different cephalosporins, including pharmacophore-resistance correlation, resistance mechanism, and occurrence of resistance-relevant mutations in different water environments. Wastewater-isolated E. coli JX1 was exposed to eight cephalosporins individually at 25 µg/L for 60 days. Multidrug resistance developed and diverse mutations arose in selected mutants, where a single mutation in ATP phosphoribosyltransferase encoding gene (hisG) resulted in up to 128-fold increase in resistance to meropenem. Molprint2D pharma RQSAR analysis revealed that hydrogen-bond acceptors and hydrophobic groups in the R1 and R2 substituents of cephalosporins contributed positively to antibiotic resistance. Some of these pharmacophores may persist during bio- or photo-degradation in the environment. hisG mutation confers a novel resistance mechanism by inhibiting fatty acid degradation, and its variants were more abundant in water-related E. coli (especially in the effluent of wastewater treatment plants) compared with those in non-water environments. These results suggest that specific degradation of particular pharmacophores in cephalosporins could be useful for controlling resistance development, and mutations in previously unreported resistance genes (e.g., hisG) can lead to overlooked antibiotic resistance risks in water environments.

Transformation process and phytotoxicity of sulfamethoxazole and N4-acetyl-sulfamethoxazole in rice.

Sulfonamide antibiotics, extensively used in human and veterinary therapy, accumulate in agroecosystem soils through livestock manure and sewage irrigation. However, the interaction between sulfonamides and rice plants remains unclear. This study investigated the transformation behavior and toxicity of sulfamethoxazole (SMX) and its main metabolite, N4-acetyl-sulfamethoxazole (NASMX) in rice. SMX and NASMX were rapidly taken up by roots and translocated acropetally. NASMX showed higher accumulating capacity, with NASMX concentrations up to 20.36 ± 1.98 µg/g (roots) and 5.62 ± 1.17 µg/g (shoots), and with SMX concentrations up to 15.97 ± 2.53 µg/g (roots) and 3.22 ± 0.789 µg/g (shoots). A total of 18 intermediate transformation products of SMX were identified by nontarget screening using Orbitrap-HRMS, revealing pathways such as deamination, hydroxylation, acetylation, formylation, and glycosylation. Notably, NASMX transformed back into SMX in rice, a novel finding. Transcriptomic analysis highlights the involvements of cytochrome P450 (CYP450), acetyltransferase (ACEs) and glycosyltransferases (GTs) in these biotransformation pathways. Moreover, exposure to SMX and NASMX disrupts TCA cycle, amino acid, linoleic acid, nucleotide metabolism, and phenylpropanoid biosynthesis pathways of rice, with NASMX exerting a stronger impact on metabolic networks. These findings elucidate the sulfonamides' metabolism, phytotoxicity mechanisms, and contribute to assessing food safety and human exposure risk amid antibiotic pollution.

Photosynthetic mechanisms of carbon fixation reduction in rice by cadmium and polycyclic aromatic hydrocarbons.

Environmental pollutants interfere with plant photosynthesis, thus reduce the crop yield and carbon storage capacity of farmland. This study comparatively explored the effects and mechanisms of polycyclic aromatic hydrocarbons (PAHs, e.g., phenanthrene, pyrene, and benzo[a]pyrene) and cadmium (Cd) on the carbon fixation capacity of rice throughout the growth period. Cd posed severer inhibition on the net carbon fixation of rice than PAHs, with the inhibition rates of 1.40-14.8-fold over PAHs at the concentrations of 0.5 or 5 mg/kg soil. Ribulose diphosphate carboxylase/oxygenase (Rubisco) involved in the Calvin cycle was identified as the common target of these pollutants to inhibit the photosynthetic carbon fixation. Further investigation demonstrated that the different inhibitory effects of Cd and PAHs was resulted from their different interference on the dual catalysis function (carboxylation and oxygenation) of Rubisco. Cd disturbed the balance of the intercellular CO2/O2, thus promoting the oxygenation and inhibiting the carboxylation of the substrate of Rubisco. Under the stress of Cd, the downstream metabolites (e.g. glycolate, glyoxylate, and serine) of Rubisco oxygenation were upregulated by over 2.01-3.24-fold, whereas the carboxylation efficiency (Vcmax) was decreased by 5.58-29.3%. Comparatively, PAHs inhibited both the carboxylation and oxygenation by down-regulating the expression of Rubisco coding gene (OsRBCS2, Log2FC < -2). This study broadens the understanding of the mechanisms of different environmental pollutants on the carbon fixation, providing valuable information for the quantitative estimation of their impacts on the farmland carbon sink. The results would be constructive to develop strategies for eliminating the adverse effects of contaminants and assist the carbon-neutral programs.