Bayesian Refinement of the Permeability-Limited Physiologically Based Pharmacokinetic Model for Perfluorooctanoic Acid in Male Rats.

Physiologically based pharmacokinetic (PBPK) modeling is a powerful technique to inform risk assessment of xenobiotic substances such as perfluorooctanoic acid (PFOA). In our previous study, a permeability-limited PBPK model was developed to simulate the toxicokinetics and tissue distribution of PFOA in male rats. However, due to limited information on some key model parameters (e.g., protein binding and active transport rates), the uncertainty of the permeability-limited PBPK model was quite high. To address this issue, a hierarchical Bayesian analysis with Markov chain Monte Carlo (MCMC) was applied to reduce the uncertainty of parameters and improve the performance of the PBPK model. With the optimized posterior parameters, the PBPK model was evaluated by comparing its prediction with experimental data from three different studies. The results show that the uncertainties of the posterior model parameters were reduced substantially. In addition, most of the PBPK model predictions were improved: with the posterior parameters, most of the predicted plasma toxicokinetics (e.g., half-life) and tissue distribution fell well within a factor of 2.0 of the experimental data. Finally, the Bayesian framework could provide insights into the molecular mechanisms driving PFOA toxicokinetics: PFOA-protein binding, membrane permeability, and active transport.

Perfluoroalkyl Acid Binding with Peroxisome Proliferator-Activated Receptors α, γ, and δ, and Fatty Acid Binding Proteins by Equilibrium Dialysis with a Comparison of Methods.

The biological impacts of per- and polyfluorinated alkyl substances (PFAS) are linked to their protein interactions. Existing research has largely focused on serum albumin and liver fatty acid binding protein, and binding affinities determined with a variety of methods show high variability. Moreover, few data exist for short-chain PFAS, though their prevalence in the environment is increasing. We used molecular dynamics (MD) to screen PFAS binding to liver and intestinal fatty acid binding proteins (L- and I-FABPs) and peroxisome proliferator activated nuclear receptors (PPAR-α, -δ and -γ) with six perfluoroalkyl carboxylates (PFCAs) and three perfluoroalkyl sulfonates (PFSAs). Equilibrium dissociation constants, KDs, were experimentally determined via equilibrium dialysis (EqD) with liquid chromatography tandem mass spectrometry for protein-PFAS pairs. A comparison was made between KDs derived from EqD, both here and in literature, and other in vitro approaches (e.g., fluorescence) from literature. EqD indicated strong binding between PPAR-δ and perfluorobutanoate (0.044 ± 0.013 µM) and perfluorohexane sulfonate (0.035 ± 0.0020 µM), and between PPAR-α and perfluorohexanoate (0.097 ± 0.070 µM). Unlike binding affinities for L-FABP, which increase with chain length, KDs for PPARs showed little chain length dependence by either MD simulation or EqD. Compared with other in vitro approaches, EqD-based KDs consistently indicated higher affinity across different proteins. This is the first study to report PPARs binding with short-chain PFAS with KDs in the sub-micromolar range.

Integrative Computational Approaches to Inform Relative Bioaccumulation Potential of Per- and Polyfluoroalkyl Substances Across Species.

Predictive toxicology is increasingly reliant on innovative computational methods to address pressing questions in chemicals assessment. Of importance is the evaluation of contaminant impact differences across species to inform ecosystem protection and identify appropriate model species for human toxicity studies. Here we evaluated 2 complementary tools to predict cross-species differences in binding affinity between per- and polyfluoroalkyl substances (PFAS) and the liver fatty acid-binding protein (LFABP): the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool and molecular dynamics (MD). SeqAPASS determined that the structure of human LFABP, a key determinant of PFAS bioaccumulation, was conserved in the majority of vertebrate species, indicating these species would have similar PFAS bioaccumulation potentials. Level 3 SeqAPASS evaluation identified several potentially destabilizing amino acid differences across species, which were generally supported by DUET stability change predictions. Nine single-residue mutations and 7 whole species sequences were selected for MD evaluation. One mutation (F50V for PFNA) showed a statistically significant difference with stronger affinity than wild-type human LFABP. Predicted binding affinities for 9 different PFAS across 7 species showed human, rat, chicken, and rainbow trout had similar binding affinities to one another for each PFAS, whereas Japanese medaka and fathead minnow had significantly weaker LFABP-binding affinity for some PFAS. Based on these analyses, the combined use of SeqAPASS and MD provides rapid screening for potential species differences with deeper structural insight. This approach can be easily extended to other important biological receptors and potential ligands.

Using Machine Learning to Classify Bioactivity for 3486 Per- and Polyfluoroalkyl Substances (PFASs) from the OECD List.

A recent OECD report estimated that more than 4000 per- and polyfluorinated alkyl substances (PFASs) have been produced and used in a broad range of industrial and consumer applications. However, little is known about the potential hazards (e.g., bioactivity, bioaccumulation, and toxicity) of most PFASs. Here, we built machine-learning-based quantitative structure-activity relationship (QSAR) models to predict the bioactivity of those PFASs. By examining a number of available molecular data sets, we constructed the first PFAS-specific database that contains the bioactivity information on 1012 PFASs for 26 bioassays. On the basis of the collected PFAS data set, we trained 5 different machine learning models that cover a variety of conventional models (e.g., random forest and multitask neural network (MNN)) and advanced graph-based models (e.g., graph convolutional network). Those models were evaluated based on the validation data set. Both MNN and graph-based models demonstrated the best performance. The average of the best area-under-the-curve score for each bioassay is 0.916. For predictions on the OECD list, most of the biologically active PFASs have perfluoroalkyl chain lengths less than 12 and are categorized into fluorotelomer-related compounds and perfluoroalkyl acids and their precursors.

Predicting Relative Protein Affinity of Novel Per- and Polyfluoroalkyl Substances (PFASs) by An Efficient Molecular Dynamics Approach.

With the phasing out of long-chain per- and polyfluoroalkyl substances (PFASs), production of a wide variety of alternative PFASs has increased to meet market demand. However, little is known about the bioaccumulation potential of these replacement compounds. Here, we developed a modeling workflow that combines molecular docking and molecular dynamics simulation techniques to estimate the relative binding affinity of a total of 15 legacy and replacement PFASs for human and rat liver-type fatty acid binding protein (hLFABP and rLFABP). The predicted results were compared with experimental data extracted from three different studies. There was good correlation between predicted free energies of binding and measured binding affinities, with correlation coefficients of 0.97, 0.79, and 0.96, respectively. With respect to replacement PFASs, our results suggest that EEA and ADONA are at least as strongly bound to rLFABP as perfluoroheptanoic acid (PFHpA), and as strongly bound to hLFABP as perfluorooctanoic acid (PFOA). For F-53 and F-53B, both have similar or stronger binding affinities than perfluorooctanesulfonate (PFOS). Given that interactions of PFASs with proteins (e.g., LFABPs) are important determinants of bioaccumulation potential in organisms, these alternatives could be as bioaccumulative as legacy PFASs, and are therefore not necessarily safer alternatives to long-chain PFASs.

Fate of antibiotic and metal resistance genes during two-phase anaerobic digestion of residue sludge revealed by metagenomic approach.

The prevalence and persistence of antibiotic resistance genes in wastewater treatment plants (WWTPs) is of growing interest, and residual sludge is among the main sources for the release of antibiotic resistance genes (ARGs). Moreover, heavy metals concentrated in dense microbial communities of sludge could potentially favor co-selection of ARGs and metal resistance genes (MRGs). Residual sludge treatment is needed to limit the spread of resistance from WWTPs into the environment. This study aimed to explore the fate of ARGs and MRGs during thermophilic two-phase (acidogenic/methanogenic phase) anaerobic digestion by metagenomic analysis. The occurrence and abundance of mobile genetic elements were also determined based on the SEED database. Among the 27 major ARG subtypes detected in feed sludge, large reductions (> 50%) in 6 ARG subtypes were achieved by acidogenic phase (AP), while 63.0% of the ARG subtypes proliferated in the following methanogenic phase (MP). In contrast, a 2.8-fold increase in total MRG abundance was found in AP, while the total abundance during MP decreased to the same order of magnitude as in feed sludge. The distinct dynamics of ARGs and MRGs during the two-phase anaerobic digestion are noteworthy, and more specific treatments are required to limit their proliferation in the environment.

A Permeability-Limited Physiologically Based Pharmacokinetic (PBPK) Model for Perfluorooctanoic acid (PFOA) in Male Rats.

Physiologically based pharmacokinetic (PBPK) modeling is a powerful in silico tool that can be used to simulate the toxicokinetics and tissue distribution of xenobiotic substances, such as perfluorooctanoic acid (PFOA), in organisms. However, most existing PBPK models have been based on the flow-limited assumption and largely rely on in vivo data for parametrization. In this study, we propose a permeability-limited PBPK model to estimate the toxicokinetics and tissue distribution of PFOA in male rats. Our model considers the cellular uptake and efflux of PFOA via both passive diffusion and transport facilitated by various membrane transporters, association with serum albumin in circulatory and extracellular spaces, and association with intracellular proteins in liver and kidney. Model performance is assessed using seven experimental data sets extracted from three different studies. Comparing model predictions with these experimental data, our model successfully predicts the toxicokinetics and tissue distribution of PFOA in rats following exposure via both IV and oral routes. More importantly, rather than requiring in vivo data fitting, all PFOA-related parameters were obtained from in vitro assays. Our model thus provides an effective framework to test in vitro-in vivo extrapolation and holds great promise for predicting toxicokinetics of per- and polyfluorinated alkyl substances in humans.

Prevalence of bacterial resistance within an eco-agricultural system in Hangzhou, China.

The wide use of antibiotics in the animal husbandry and the relevant sustainable industries may promote the emergence of antibiotic-resistant bacteria (ARB), which constitutes a growing threat to human health. The objective of this study was to determine the abundance and diversity of sulfonamide- and tetracycline-resistant bacteria within an eco-agricultural system (EAS) in Hangzhou, China. We investigated samples at every link in the EAS, from livestock manure, to biogas residues and biogas slurry, to vegetable and ryegrass fields, to a fish pond. A combination of culture-based and 16S rRNA gene-based sequencing method was used in this study. Within the studied system, the average rate of bacterial resistance to sulfonamide (46.19 %) was much higher than that of tetracycline (8.51 %) (p < 0.01). There were 224 isolates that were enumerated and sequenced, 108 of which were identified to species level. The genera comprising the sulfamethoxazole-resistant (SMXr) bacteria were generally different from those of tetracycline-resistant (TCr) bacteria. Staphylococcus and Acinetobacter were the most dominant genera of SMXr bacteria (19.30 % of the total resistant bacteria) and TCr bacteria (14.04 % of the total resistant bacteria), respectively. Several strains of resistant opportunistic pathogens (e.g., Pantoea agglomerans) were detected in edible vegetable samples, which may exert a potential threat to both pig production and human health. In general, this study indicates that the EAS is an important reservoir of antibiotic-resistant bacteria, some of which may be pathogenic.

Influence of two-phase anaerobic digestion on fate of selected antibiotic resistance genes and class I integrons in municipal wastewater sludge.

The response of representative antibiotic resistance genes (ARGs) to lab-scale two-phase (acidogenic/methanogenic phase) anaerobic digestion processes under thermophilic and mesophilic conditions was explored. The associated microbial communities and bacterial pathogens were characterized by 16S rRNA gene sequencing. A two-phase thermophilic digestion reduced the presence of tetA, tetG, tetX, sul1, ermB, dfrA1, dfrA12 and intI1 exhibiting 0.1-0.72 log unit removal; in contrast, tetO, tetW, sul3, ermF and blaTEM even increased relative to the feed, and sul2 showed no significant decrease. The acidogenic phase of thermophilic digestion was primarily responsible for reducing the quantity of these genes, while the subsequent methanogenic phase caused a rebound in their quantity. In contrast, a two-phase mesophilic digestion process did not result in reducing the quantity of all ARGs and intI1 except for ermB and blaTEM. ARGs patterns were correlated with Proteobacteria and Actinobacteria during the two-phase anaerobic digestion.

Occurrence and removal of antibiotics and the corresponding resistance genes in wastewater treatment plants: effluents' influence to downstream water environment.

In this study, the occurrence of 8 antibiotics [3 tetracyclines (TCs), 4 sulfonamides, and 1 trimethoprim (TMP)], 12 antibiotic resistance genes (ARGs) (10 tet, 2 sul), 4 types of bacteria [no antibiotics, anti-TC, anti-sulfamethoxazole (SMX), and anti-double], and intI1 in two wastewater treatment plants (WWTPs) were assessed and their influences in downstream lake were investigated. Both WWTPs' effluent demonstrated some similarities, but the abundance and removal rate varied significantly. Results revealed that biological treatment mainly removed antibiotics and ARGs, whereas physical techniques were found to eliminate antibiotic resistance bacteria (ARBs) abundance (about 1 log for each one). UV disinfection did not significantly enhance the removal efficiency, and the release of the abundantly available target contaminants from the excess sludge may pose threats to human and the environment. Different antibiotics showed diverse influences on the downstream lake, and the concentrations of sulfamethazine (SM2) and SMX were observed to increase enormously. The total ARG abundance ascended about 0.1 log and some ARGs (e.g., tetC, intI1, tetA) increased due to the high input of the effluent. In addition, the abundance of ARB variation in the lake also changed, but the abundance of four types of bacteria remained stable in the downstream sampling sites.

Behavior of antibiotics and antibiotic resistance genes in eco-agricultural system: A case study.

This study aims to determine abundance and persistence of antibiotics and antibiotic resistance genes (ARGs) in eco-agricultural system (EAS), which starts from swine feces to anaerobic digestion products, then application of anaerobic digestion solid residue (ADSR) and anaerobic digestion liquid residue (ADLR) to the soil to grow ryegrass, one of swine feed. Oxytetracycline had the highest concentration in manure reaching up to 138.7 mg/kg. Most of antibiotics could be effectively eliminated by anaerobic digestion and removal rates ranged from 11% to 86%. ARGs abundance fluctuated within EAS. TetQ had the highest relative abundance and the relative abundance of tetG had the least variation within the system, which indicates that tetG is persistent in the agricultural environment and requires more attention. Compared to the relative abundance in manure, tetC and tetM increased in biogas residue while three ribosomal protection proteins genes (tetO, tetQ, tetW) decreased (p<0.05), with other genes showing no significant change after anaerobic fermentation (p>0.05). Most ARGs in downstream components (soils and fishpond) of EAS showed significantly higher relative abundance than the control agricultural system (p<0.05), except for tetG and sulI.

Antibiotic-resistant genes and antibiotic-resistant bacteria in the effluent of urban residential areas, hospitals, and a municipal wastewater treatment plant system.

In this study, we determined the abundance of 8 antibiotics (3 tetracyclines, 4 sulfonamides, and 1 trimethoprim), 12 antibiotic-resistant genes (10 tet, 2 sul), 4 antibiotic-resistant bacteria (tetracycline, sulfamethoxazole, and combined resistance), and class 1 integron integrase gene (intI1) in the effluent of residential areas, hospitals, and municipal wastewater treatment plant (WWTP) systems. The concentrations of total/individual targets (antibiotics, genes, and bacteria) varied remarkably among different samples, but the hospital samples generally had a lower abundance than the residential area samples. The WWTP demonstrated removal efficiencies of 50.8% tetracyclines, 66.8% sulfonamides, 0.5 logs to 2.5 logs tet genes, and less than 1 log of sul and intI1 genes, as well as 0.5 log to 1 log removal for target bacteria. Except for the total tetracycline concentration and the proportion of tetracycline-resistant bacteria (R (2) = 0.330, P < 0.05), there was no significant correlation between antibiotics and the corresponding resistant bacteria (P > 0.05). In contrast, various relationships were identified between antibiotics and antibiotic resistance genes (P < 0.05). Tet (A) and tet (B) displayed noticeable relationships with both tetracycline and combined antibiotic-resistant bacteria (P < 0.01).

Illumina sequencing-based analyses of bacterial communities during short-chain fatty-acid production from food waste and sewage sludge fermentation at different pH values.

Short-chain fatty acids (SCFAs) can be produced by primary and waste activated sludge anaerobic fermentation. The yield and product spectrum distribution of SCFAs can be significantly affected by different initial pH values. However, most studies have focused on the physical and chemical aspects of SCFA production by waste activated sludge fermentation at different pH values. Information on the bacterial community structures during acidogenic fermentation is limited. In this study, comparisons of the bacterial communities during the co-substrate fermentation of food wastes and sewage sludge at different pH values were performed using the barcoded Illumina paired-end sequencing method. The results showed that different pH environments harbored a characteristic bacterial community, including sequences related to Lactobacillus, Prevotella, Mitsuokella, Treponema, Clostridium, and Ureibacillus. The most abundant bacterial operational taxonomic units in the different pH environments were those related to carbohydrate-degrading bacteria, which are associated with constituents of co-substrate fermentation. Further analyses showed that during organic matter fermentation, a core microbiota composed of Firmicutes, Proteobacteria, and Bacteroidetes existed. Comparison analyses revealed that the bacterial community during fermentation was significantly affected by the pH, and that the diverse product distribution was related to the shift in bacterial communities.

Abundance and persistence of antibiotic resistance genes in livestock farms: a comprehensive investigation in eastern China.

Increases of antibiotic resistance genes in the environment may pose a threat to public health. The purpose of this study was to investigate the abundance and diversity of tetracycline (tet) and sulfonamide (sul) resistance genes in eight livestock farms in Hangzhou, eastern China. Ten tet genes (tetA, tetB, tetC, tetG, tetL, tetM, tetO, tetQ, tetW, and tetX), two sul genes (sulI and sulII), and one genetic element associated with mobile antibiotic resistance genes [class 1 integron (intI1)] were quantified by real-time polymerase chain reaction. No significant difference was found in the abundance of the tet and sul genes in various scales of pig, chicken, and duck farms (P>0.05). The average abundance of ribosomal protection protein genes (tetQ, tetM, tetW, and tetO) in the manure and wastewater samples was higher than most of the efflux pump genes (tetA, tetB, tetC, and tetL) and enzymatic modification gene (tetX) (P<0.05), except for efflux pump gene tetG, which was abundant and showed no difference from tetM. Most ARGs had higher relative abundance in the wastewater lagoon than in manures even after treatment. Although the three ribosomal protection protein genes (tetQ, tetW, and tetO) had higher relative abundance, numbers were reduced during the complete wastewater treatment process in pig farms (P<0.05). The relative abundance of tetG, sulI, and sulII increased after the wastewater treatment and the removal of these three genes exhibited significant positive correlations with the intI1 gene (tetG: R(2)=0.60, P<0.05; sulI: R(2)=0.72, P<0.05; sulII: R(2)=0.62, P<0.05), suggesting that intI1 may be involved in their proliferation. As for tetM and sulII genes, a highly significant difference was found in manure samples between pig farms and duck farms (P<0.001). Phylogenetic analysis showed that tetM was more diverse in duck farms than in pig farms. Additionally, sulII sequence was conserved both in pig and duck farms. This is the first comprehensive study to detail the relative abundance of specific ARGs in animal manures and agricultural wastewater treatment systems, potentially providing knowledge for managing antibiotic resistance emanating from agricultural activities.