Comprehensive investigation and risk assessment of organic contaminants in Yellow River Estuary using suspect and nontarget screening strategies

Ubiquitous nanocolloids suppress the conjugative transfer of plasmid-mediated antibiotic resistance in aqueous environment

Nanocolloids (Nc) are widespread in natural water environment, whereas the potential effects of Nc on dissemination of antibiotic resistance remain largely unknown. In this study, Nc collected from the Yellow River in Henan province was tested for its ability to influence the conjugative transfer of resistant plasmid in aqueous environment. The results revealed that the conjugative transfer of RP4 plasmid between Escherichia coli was down-regulated by 52%-91% upon exposure to 1-10 mg/L Nc and the reduction became constant when the dose became higher (20-200 mg/L). Despite the exposure of Nc activated the anti-oxidation and SOS response in bacteria through up-regulating genes involved in glutathione biosynthesis and DNA recombination, the inhibition on the synthesis and secretion of extracellular polysaccharide induced the prevention of cell-cell contact, leading to the reduction of plasmid transfer. This was evidenced by the decreased bacterial adhesion and lowered levels of genes and metabolites relevant to transmembrane transport and D-glucose phosphorylation, as clarified in phenotypic, transcriptomics and metabolomics analysis of E. coli. The significant down-regulation of glycolysis/gluconeogenesis and TCA cycle was associated with the shortage of ATP induced by Nc. The up-regulation of global regulatory genes (korA and trbA) and the reduction of plasmid genes (trfAp, trbBp, and traG) expression also contributed to the suppressed conjugation of RP4 plasmid. The obtained findings remind that the role of ubiquitous colloidal particles is nonnegligible when practically and comprehensively assessing the risk of antibiotic resistance in the environment.

Ecological implications and drivers of emerging contaminants in Dongting Lake of Yangtze River Basin, China: A multi-substance risk analysis

Emerging contaminants (ECs) are increasingly recognized as a global threat to biodiversity and ecosystem health. However, the cumulative risks posed by ECs to aquatic organisms and ecosystems, as well as the influence of anthropogenic activities and natural factors on these risks, remain poorly understood. This study assessed the mixed risks of ECs in Dongting Lake, a Ramsar Convention-classified Typically Changing Wetland, to elucidate the major EC classes, key risk drivers, and magnitude of anthropogenic and natural impacts. Results revealed that ECs pose non-negligible acute (30% probability) and chronic (70% probability) mixed risks to aquatic organisms in the freshwater lake ecosystem, with imidacloprid identified as the primary pollutant stressor. Redundancy analysis (RDA) and structural equation modeling (SEM) indicated that cropland and precipitation were major drivers of EC contamination levels and ecological risk. Cropland was positively associated with EC concentrations, while precipitation exhibited a dilution effect. These findings provide critical insights into the ecological risk status and key risk drivers in a typical freshwater lake ecosystem, offering data-driven support for the control and management of ECs in China.

Plastic protective nets: A significant but neglected "reservoir" for priority chemicals as revealed by composition analysis

As chemical-intensive products, plastics are potential sources of emerging contaminants and pose risks to the ecosystem. However, knowledge on the inventory and emissions of chemicals in plastics remains scarce, prohibiting the lifecycle assessment of their environmental exposure. Herein, full compositions of plastic protective nets (PPNs, one globally used plastics) were analyzed via nontarget screening with mass spectrometry, optical emission spectrometry, infrared spectroscopy and thermogravimetric analysis. Nontarget screening identified 861 non-polymeric organic chemicals, which were classified by network-like similarity analysis into 9 communities, dominated by phthalates (PAEs), aliphatic/oxalic esters and branched alkanes. Notably, around 80.8% (696) of the chemicals were first observed in plastics, suggesting aplenty plastic additives have previously been overlooked. Quantification results indicated PPNs contained higher levels of priority chemicals, including detrimental lead (1.17 × 104 ng/g), benzotriazoles ultraviolet stabilizers (6.66 × 103 ng/g) and PAEs (1.87 × 104 ng/g) than other plastics commonly reported. Emission projections revealed that dibutyl phthalate in PPNs had an annual release (1.83 × 103 kg) comparable to that from greenhouse films in China. These findings suggest PPNs are a significant but neglected "reservoir" for priority chemicals, which could inform future research on resolving plastic compositions, so as to promote sound chemical management.

Non-target analysis for water characterization: wastewater treatment impact and selection of relevant features

Non-target analyses were conducted to characterize and compare the molecular profiles (UHPLC-HRMS fingerprint) of water samples from a wastewater treatment plant (WWTP). Inlet and outlet samples were collected from three campaigns spaced 6 months apart in order to highlight common trends. A significant impact of the treatment on the sample fingerprints was shown, with a 65-70% abatement of the number of features detected in the effluent, and more polar, smaller and less intense molecules found overall compared to those in WWTP influent waters. Multivariate analysis (PCA) associated with variations of the features between inlets and outlets showed that features appearing or increasing were correlated with effluents while those disappearing or decreasing were correlated with influents. Finally, effluent features considered as relevant to a potentially adverse effect on aqueous media (i.e. those which appeared or increased or slightly varied from the influent) were highlighted. Three hundred seventy-five features common with the 3 campaigns were thus selected and further characterized. For most of them, elementary composition was found to be C, H, N, O (42%) and C, H, N, O, P (18%). Considering the MS2 spectra and several reference MS2 databases, annotations were proposed for 35 of these relevant features. They include synthetic products, pharmaceuticals and metabolites.

Association between co-exposure to phenols, phthalates, and polycyclic aromatic hydrocarbons with the risk of frailty

The phenomenon of population aging has brought forth the challenge of frailty. Nevertheless, the contribution of environmental exposure to frailty remains ambiguous. Our objective was to investigate the association between phenols, phthalates (PAEs), and polycyclic aromatic hydrocarbons (PAHs) with frailty. We constructed a 48-item frailty index using data from the National Health and Nutrition Examination Survey (NHANES). The exposure levels of 20 organic contaminants were obtained from the survey circle between 2005 and 2016. The association between individual organic contaminants and the frailty index was assessed using negative binomial regression models. The combined effect of organic contaminants was examined using weighted quantile sum (WQS) regression. Dose-response patterns were modeled using generalized additive models (GAMs). Additionally, an interpretable machine learning approach was employed to develop a predictive model for the frailty index. A total of 1566 participants were included in the analysis. Positive associations were observed between exposure to MIB, P02, ECP, MBP, MHH, MOH, MZP, MC1, and P01 with the frailty index. WQS regression analysis revealed a significant increase in the frailty index with higher levels of the mixture of organic contaminants (aOR, 1.12; 95% CI, 1.05-1.20; p < 0.001), with MIB, ECP, COP, MBP, P02, and P01 identified as the major contributors. Dose-response relationships were observed between MIB, ECP, MBP, P02, and P01 exposure with an increased risk of frailty (both with p < 0.05). The developed predictive model based on organic contaminants exposure demonstrated high performance, with an R2 of 0.9634 and 0.9611 in the training and testing sets, respectively. Furthermore, the predictive model suggested potential synergistic effects in the MIB-MBP and P01-P02 pairs. Taken together, these findings suggest a significant association between exposure to phthalates and PAHs with an increased susceptibility to frailty.

Priority control sequence of 34 typical pollutants in effluents of Chinese wastewater treatment plants

The identification of the priority control sequence of pollutants in effluents of wastewater treatment plants (WWTPs) has important implications for the management of water quality. This study chose 34 typical pollutants based on their representativeness and detection rates in municipal wastewater. The occurrence frequency and concentration of these pollutants in 168 Chinese WWTP effluents were measured at the national level. The data on in vitro toxicity (67 assays) and in vivo toxicity (216 species) for target pollutants were obtained from the public toxicity database and our experimental data. An environmental health prioritization index (EHPi) method was proposed to integrate the occurrence frequency, concentration, removal rate, and in vitro and in vivo toxicity to determine the priority control sequence of target pollutants. Ethynyl estradiol, 17β-estradiol, estrone, diclofenac, and atrazine were the top 5 pollutants identified by the EHPi score. Several pollutants with high EHPi scores showed spatial differences. Besides the EHPi method which was from the single pollutant perspective, the combined toxicity of pollutants (300 pairs of binary combinations) was also measured based on in vitro toxicity assays to evaluate the key pollutants from the pollutant-pollutant interacting perspective. The pollutants (such as ofloxacin and acetaminophen) that could have significant synergetic effects with many other pollutants are worthy of prior attention. This study shed new light on the identification of the priority control sequence of pollutants in WWTP effluents. The results provide meaningful data for the effective management and control of wastewater water quality.