Lipid-water partition coefficients and correlations with uptakes by algae of organic compounds

Polyparameter Linear Free Energy Relationships for Partitioning of Neutral Organic Compounds to Storage Lipids

Storage lipids are an important compartment in the bioaccumulation of neutral organic compounds. Reliable models for predicting storage lipid-water and storage lipid-air partition coefficients (Kislip/w and Kislip/a), as well as their temperature dependence, are considered useful. Polyparameter linear free energy relationships (PP-LFERs) are accurate, general, and mechanistically clear models for predicting partitioning-related physicochemical quantities. About a decade ago, PP-LFERs were calibrated for Kislip/w at the physiological temperature of 37 °C. However, to date, a comprehensive collection and sufficiently reliable PP-LFERs for Kislip/w and Kislip/a at the most common standard temperature of 25 °C are still lacking. In this study, experimentally based Kislip/w and/or Kislip/a values at 25 °C for 278 compounds were extensively collected or converted from the literature. Subsequently, PP-LFERs were calibrated for Kislip/w and Kislip/a at 25 °C, performing well over 10 orders of magnitude with root-mean-square errors of 0.17-0.21 log units for compounds with reliable descriptors. Furthermore, standard internal energy changes of transfer from water or air to storage lipids for 158 compounds were derived and used to calibrate PP-LFERs for estimating the temperature dependence of Kislip/w or Kislip/a. Additionally, using PP-LFERs, low-density polyethylene was confirmed to be a better storage lipid analogue than silicone and polyoxymethylene in the equilibrium passive sampling of nonpolar and H-bond acceptor polar compounds.

Mitigation of Triclocarban Inhibition in Microbial Electrolysis Cell-Assisted Anaerobic Digestion

Triclocarban (TCC), as a widely used antimicrobial agent, is accumulated in waste activated sludge at a high level and inhibits the subsequent anaerobic digestion of sludge. This study, for the first time, investigated the effectiveness of microbial electrolysis cell-assisted anaerobic digestion (MEC-AD) in mitigating the inhibition of TCC to methane production. Experimental results showed that 20 mg/L TCC inhibited sludge disintegration, hydrolysis, acidogenesis, and methanogenesis processes and finally reduced methane production from traditional sludge anaerobic digestion by 19.1%. Molecular docking revealed the potential inactivation of binding of TCC to key enzymes in these processes. However, MEC-AD with 0.6 and 0.8 V external voltages achieved much higher methane production and controlled the TCC inhibition to less than 5.8%. TCC in the MEC-AD systems was adsorbed by humic substances and degraded to dichlorocarbanilide, leading to a certain detoxification effect. Methanogenic activities were increased in MEC-AD systems, accompanied by complete VFA consumption. Moreover, the applied voltage promoted cell apoptosis and sludge disintegration to release biodegradable organics. Metagenomic analysis revealed that the applied voltage increased the resistance of electrode biofilms to TCC by enriching functional microorganisms (syntrophic VFA-oxidizing and electroactive bacteria and hydrogenotrophic methanogens), acidification and methanogenesis pathways, multidrug efflux pumps, and SOS response.

Novel aminothiazoximone-corbelled ethoxycarbonylpyrimidones with antibiofilm activity to conquer Gram-negative bacteria through potential multitargeting effects

The emergence of drug-resistant microorganisms threatens human health, and it is usually exacerbated by the formation of biofilm, which forces the development of new antibacterial agents with antibiofilm activity. In this work, a novel category of aminothiazoximone-corbelled ethoxycarbonylpyrimidones (ACEs) was designed and synthesized, and some of the prepared ACEs showed potent bioactivity against the tested bacteria. In particular, imidazolyl ACE 6c showed better inhibitory activity towards Acinetobacter baumannii and Escherichia coli with MIC values both of 0.0066 mmol/L than norfloxacin. It was also revealed that imidazolyl ACE 6c not only possessed inconspicuous hemolytic rate and cytotoxicity, low drug resistance and no risk of penetrating the blood-brain barrier, but also exhibited obvious biofilm inhibition and eradication activities. The preliminary mechanism research suggested that imidazolyl ACE 6c could induce metabolic dysfunction by deactivating lactate dehydrogenase and promote the accumulation of reactive oxygen species to decrease the reduced glutathione and ultimately cause oxidative damage in bacteria. Furthermore, ACE 6c was also found that could insert into DNA to form the supramolecular complex of 6c-DNA and trigger cell death. The multidimensional effect might promote bacterial cell rupture, leading to the leakage of intracellular content. These findings manifested that novel imidazolyl ACE 6c as a potential multitargeting antibacterial agent with potent antibiofilm activity could provide new possibility for the treatment of refractory biofilm-intensified bacterial infections.

Codeployment of Passive Samplers and Mussels Reveals Major Source of Ongoing PCB Inputs to the Anacostia River in Washington, DC

Remedial investigations of sites contaminated with legacy pollutants like polychlorinated biphenyls (PCBs) have traditionally focused on mapping sediment contamination to develop a site conceptual model and select remedy options. Ignoring dissolved concentrations that drive transport and bioaccumulation often leads to an incomplete assessment of ongoing inputs to the water column and overestimation of potential effectiveness of sediment remediation. Here, we demonstrate the utility of codeployment of passive equilibrium samplers and freshwater mussels as dual lines of evidence to identify ongoing sources of PCBs from eight main tributaries of the Anacostia River in Washington, DC, that has been historically polluted from industrial and other human activities. The freely dissolved PCB concentrations measured using passive samplers tracked well with the accumulation in mussels and allowed predictions of biouptake within a factor of 2 for total PCBs and a factor of 4 for most congeners. One tributary was identified as the primary source of PCBs to the water column and became a focus of additional ongoing investigations. Codeployment of passive samplers and mussels provides strong lines of evidence to refine site conceptual models and identify ongoing sources critical to control to achieve river water quality standards and reduce bioaccumulation in the aquatic food web.

Exploring the role of octanol-water partition coefficient and Henry's law constant in predicting the lipid-water partition coefficients of organic chemicals

Partition coefficients for storage lipid-water (logKlw) and phospholipid-water (logKpw) phases are key parameters to understand the bioaccumulation and toxicity of organic contaminants. However, the published experimental databases of these properties are dwarfs and current estimation approaches are cumbersome. Here, we present partition models that exploit the correlations of logKlw, and of logKpw with the linear combinations of the octanol-water partition coefficient (logKow) and the dimensionless Henry's law constant (air-water partition coefficient, logKaw). The calibrated partition models successfully describe the variations in logKlw data (n = 305, R2 = 0.971, root-mean-square-error (rmse) = 0.375), and in logKpw data (n = 131, R2 = 0.953, rmse = 0.413). With the inputs of logKow and logKaw estimated from the U.S. EPA's EPI Suite, our models of logKlw and logKpw have exhibited rmse = 0.52 with respect to experimental values indicating suitability of these models for inclusion in the EPI Suite. Our models perform similar to or better than the previously reported models such as one parameter partition models, Abraham solvation models, and models based on quantum-chemical calculations. Taken together, our models are robust, easy-to-use, and provide insight into variations of logKlw and logKpw in terms of hydrophobicity and volatility trait of chemicals.

Predicting crop root concentration factors of organic contaminants with machine learning models

Accurate prediction of uptake and accumulation of organic contaminants by crops from soils is essential to assessing human exposure via the food chain. However, traditional empirical or mechanistic models frequently show variable performance due to complex interactions among contaminants, soils, and plants. Thus, in this study different machine learning algorithms were compared and applied to predict root concentration factors (RCFs) based on a dataset comprising 57 chemicals and 11 crops, followed by comparison with a traditional linear regression model as the benchmark. The RCF patterns and predictions were investigated by unsupervised t-distributed stochastic neighbor embedding and four supervised machine learning models including Random Forest, Gradient Boosting Regression Tree, Fully Connected Neural Network, and Supporting Vector Regression based on 15 property descriptors. The Fully Connected Neural Network demonstrated superior prediction performance for RCFs (R² =0.79, mean absolute error [MAE] = 0.22) over other machine learning models (R² =0.68-0.76, MAE = 0.23-0.26). All four machine learning models performed better than the traditional linear regression model (R² =0.62, MAE = 0.29). Four key property descriptors were identified in predicting RCFs. Specifically, increasing root lipid content and decreasing soil organic matter content increased RCFs, while increasing excess molar refractivity and molecular volume of contaminants decreased RCFs. These results show that machine learning models can improve prediction accuracy by learning nonlinear relationships between RCFs and properties of contaminants, soils, and plants.

Direct Prediction of Bioaccumulation of Organic Contaminants in Plant Roots from Soils with Machine Learning Models Based on Molecular Structures

Root concentration factor (RCF) is an important characterization parameter to describe accumulation of organic contaminants in plants from soils in life cycle impact assessment (LCIA) and phytoremediation potential assessment. However, building robust predictive models remains challenging due to the complex interactions among chemical-soil-plant root systems. Here we developed end-to-end machine learning models to devolve the complex molecular structure relationship with RCF by training on a unified RCF data set with 341 data points covering 72 chemicals. We demonstrate the efficacy of the proposed gradient boosting regression tree (GBRT) model based on the extended connectivity fingerprints (ECFP) by predicting RCF values and achieved prediction performance with R-squared of 0.77 and mean absolute error (MAE) of 0.22 using 5-fold cross validation. In addition, our results reveal nonlinear relationships among properties of chemical, soil, and plant. Further in-depth analyses identify the key chemical topological substructures (e.g., -O, -Cl, aromatic rings and large conjugated π systems) related to RCF. Stemming from its simplicity and universality, the GBRT-ECFP model provides a valuable tool for LCIA and other environmental assessments to better characterize chemical risks to human health and ecosystems.

Weak interaction-alleviated toxicity of aromatic compounds in EPS matrices: Quantifying the noncovalent bonding-to-EPS ecoservice chain

Extracellular polymeric substances (EPSs) constitute a largely global carbon pool that could participate in geochemical process of organic chemicals. Besides the chemical hydrolysis and redox of chemicals exerted by the EPS, weakly noncovalent interactions with dispersive EPS control the toxicity of numerous organic compounds. Nevertheless, there has been a lack of in-depth research on this issue. This work quantified a chain of links from bonding to detoxification using natural biofilms to explore the control behavior of fragile noncovalent bonding to the ecotoxicity of aromatic compounds. Such bonding decreases cell absorbability of m-phenylenediamine, 2-naphthol, and phenanthrene by 5.3-53.6%, resultantly increasing the indices of microbial diversity by 122.2-279.5%. Herein, the 60 kDa chaperonin in EPS acts as the most important contributor (16.4% of the top 20 proteins) to noncovalent interactions. Hydrophilic carboxyl groups in EPS bind with hydroxyl and amino groups of m-phenylenediamine and 2-naphthol via H-bonds, respectively. Methylene and carboxyl groups combine with hydrophobic phenanthrene via CH···π and H-bonding, respectively. A quantified chain was consequently established that weak interaction linearly controls ecotoxicity of aromatic compounds via the above suppressive cell absorbability of aromatic compounds (R² =0.82). Considering ubiquitous EPS and prevailing aromatic compounds, our findings revealed a previously unnoticed phenomenon in which seemingly fragile noncovalent bonding profoundly alleviates the ecotoxicity of aromatic compounds in Earth's surface system.

Comparative study on the toxicity and removal of bisphenol S in two typical freshwater algae

Bisphenol S (BPS), one of the most widely used bisphenol A substitutes, has recently received more attention because of its high detection in water and potential toxicity. In the present study, the toxicity and removal of BPS in typical freshwater algae Navicula sp. were investigated under laboratory conditions and the comparative study with Chlorella vulgaris was also explored. BPS was more toxic to Navicula sp. than C. vulgaris with their 120-h EC₅₀ values of 3.89 and 25.19 mg/L, respectively. It may be mainly ascribed to the high tolerance of C. vulgaris to BPS. For instance, the superoxide dismutase (SOD) and catalase (CAT) activities of C. vulgaris were increased under the exposure of 20 mg BPS/L, whereas they were increased in Navicula sp. at 1 mg BPS/L. It is implied that the detoxification mechanism of C. vulgaris was activated until BPS concentration reach to 20 mg L^-1. Moreover, the results had demonstrated that both algae had promoted the removal of BPS at 0.5 mg/L, but the removal could be inhibited as BPS concentration increased. Navicula sp. presented a better removal of BPS because of their higher accumulation, implying that they may be good materials for the removal of BPS. In addition, the sharp increase of BCF value at 72 h in Navicula sp. under the exposure of environmental-related BPS concentration (0.5 mg/L) may indicate a high risk of BPS to aquatic ecosystem. These findings will provide a reference for the risk assessment of BPS in natural waters.

In vitro methods for predicting the bioconcentration of xenobiotics in aquatic organisms

The accumulation of anthropogenic chemical substances in aquatic organisms is an immensely important issue from the point of view of environmental protection. In the context of the increasing number and variety of compounds that may potentially enter the environment, there is a need for efficient and reliable solutions to assess the risks. However, the classic approach of testing with fish or other animals is not sufficient. Due to very high costs, significant time and labour intensity, as well as ethical concerns, in vivo methods need to be replaced by new laboratory-based tools. So far, many models have been developed to estimate the bioconcentration potential of chemicals. However, most of them are not sufficiently reliable and their predictions are based on limited input data, often obtained with doubtful quality. The octanol-water partition coefficient is still often used as the main laboratory tool for estimating bioconcentration. However, according to current knowledge, this method can lead to very unreliable results, both for neutral species and, above all, for ionic compounds. It is therefore essential to start using new, more advanced and credible solutions on a large scale. Over the last years, many in vitro methods have been newly developed or improved, allowing for a much more adequate estimation of the bioconcentration potential. Therefore, the aim of this work was to review the most recent laboratory methods for assessing the bioconcentration potential and to evaluate their applicability in further research.

Adjusting the lipid-water distribution coefficient of iridium(III) complexes to enhance the cellular penetration and treatment efficacy to antagonize cisplatin resistance in cervical cancer

The effective design of metal complexes to manipulate their lipid-water distribution coefficient is an appealing strategy for improving their cellular penetration and treatment efficacy. Here, we conveniently synthesized three iridium (Ir) complexes with red fluorescence via the simple non-conjugate modification of the side arm of the ligand. Bio-evaluation revealed that upon adding non-conjugate selenium (Se) arene derivatives, the lipid-water distribution coefficient of Ir-Se was found to be suitable, not only decreasing the toxic side effects of complexes to normal cells, but also effectively improving their anticancer activity via enhancing their penetration into tumor cells. Moreover, mechanistic investigations demonstrated that Ir-Se entered R-HeLa cells through endocytosis, and triggered apoptosis via the down-regulation of the mitochondrial membrane potential and excessive production of singlet oxygen, thereby possessing a highly effective cytotoxicity to antagonize cisplatin resistance. Therefore, we developed a convenient strategy to derive functional metal complexes and revealed that the introduction of Se on the side arm of the ligand provided the complexes with the capacity to reverse multidrug resistance.

Integrated Assessment of Bioconcentration, Toxicity, and Hazards of Chlorobenzenes in the Aquatic Environment

The evaluation of bioconcentration, toxicity, and hazard (BTH) of persistent lipophilic organic compounds (LOCs) are generally performed as separate rather than integrated assessments. There are adequate data sets in the literature for chlorobenzenes (CBs) consisting of (a) concentrations in aquatic biota (C_B) and water (C_w) in the natural environment, (b) laboratory-derived bioconcentration factors (K_B) and field concentration ratios (CR), the field equivalent factor of K_B, (c) measured internal lethal concentrations (ILC₅₀) and model estimated ILC₅₀ calculated from K_B and lethal concentrations (LC₅₀), and (d) calculated hazard quotients in aquatic biota (HQ_B) and in water (HQ_W). However, there have been no integrated studies of those parameter values based on the respective lipid-based parameters (C_BL, K_BL, CR_L, ILC_50L, HQ_BL) performed. This study utilized the lipid-based parameters for CBs; a group of widely occuring, bioaccumulative, and toxic LOCs, and integrated those parameters into a bioconcentration-toxicity-hazard (BTH_L) index. The values of the parameters were obtained from selected literature with known lipid contents of the aquatic biota. The results showed that the laboratory derived bioconcentration factors, K_BLs, were comparable to the corresponding field based factors, CR_Ls, and the measured internal lethal concentrations, ILC_50L, showed comparable values with the estimated ones. The integrated BTH_L index was less than an order of magnitude or moderately acceptable for the assessment of variability, uncertainty, and predictive power of the index. This integrated assessment can be used to support decision making dealing with CBs in specific and LOCs in general, both in regional and global aquatic environments.

Improved prediction of the bioconcentration factors of organic contaminants from soils into plant/crop roots by related physicochemical parameters

There has been an on-going pursuit for relations between the levels of chemicals in plants/crops and the source levels in soil or water in order to address impacts of toxic substances on human health and ecological quality. In this research, we applied the quasi-equilibrium partition model to analyze the relations for nonionic organic contaminants between plant/crop roots and external soil/water media. The model relates the in-situ root concentration factors of chemicals from external water into plant/crop roots (RCF(water)) with the system physicochemical parameters and the chemical quasi-equilibrium states with plant/crop roots (αpt, ≤1). With known RCF(water) values, root lipid contents (flip), and octanol-water Kow's, the chemical-plant αpt values and their ranges of variation at given flipKow could be calculated. Because of the inherent relation between αpt and flipKow, a highly distinct correlation emerges between log RCF(water) and log flipKow (R2 = 0.825; n = 368), with the supporting data drawn from 19 disparate soil-plant studies covering some 6 orders of magnitude in flipKow and 4 orders of magnitude in RCF(water). This correlation performs far better than any relationship previously developed for predicting the contamination levels of pesticides and toxic organic chemicals in plant/crop roots for assessing risks on food safety.

SSP silicone-, lipid- and SPMD-water partition coefficients of seventy hydrophobic organic contaminants and evaluation of the water concentration calculator for SPMD

Passive sampling is increasingly applied for monitoring neutral hydrophobic compounds (HOC) in various environmental media like water, sediment, air and also soft biota tissue. Passive samplers for HOC are often constructed from permeable polymers like silicone and polyethylene (PE), while also SPMD are often applied. Their HOC uptake can be converted to freely dissolved or equivalent lipid-based concentrations using appropriate partition coefficients with or without the use of kinetic uptake models to adjust for non-equilibrium. To facilitate such conversions for seventy HOC partition coefficients are derived by combining polymer-water for Altesil™ silicone and PE, with new and earlier published polymer-polymer, polymer-lipid partition coefficients. Derived SSP silicone-water, lipid-water (K_lip/w), and SPMD-water (K_spmd/w) partition coefficients demonstrate good agreement with literature data, except for K_spmd/w. For SPMD, this work demonstrates a linear K_spmd/w - K_ow relationship (R² = 0.99) in contrast to the parabolic K_spmd/w - K_ow relationship utilized in the USGS "SPMD Water Concentrations Calculator". Following a thorough evaluation of this Calculator it is recommended that in combination with revised K_spmd/w, a radical different model approach should be used for obtaining accurate water concentrations from passive sampling with SPMD.

Biosorption and Biodegradation of the Environmental Hormone Nonylphenol By Four Marine Microalgae

Microalgae are the most abundant microorganisms in aquatic environments, and many possess the ability to remove organic contaminants. The presence of endocrine disruption compounds (EDCs) in many coastal marine systems and their associated risks have elicited great concern, especially in the case of nonylphenol (NP), which is classified as a priority contaminate by the U.S. EPA. In this context, batch experiments were conducted to investigate the intracellular absorption, extracellular adsorption and biodegradation of NP by four species of marine microalgae: Phaeocystis globosa, Nannochloropsis oculata, Dunaliella salina and Platymonas subcordiformis. The results showed a sharp reduction of NP in medium containing the four microalgal species during the first 24 h of incubation, and the four species exhibited the greatest capacity for NP adsorption and absorption within 24 h of culture. However, the amount of NP absorbed and adsorbed by all four microalgae decreased with increasing time in culture, and intracellular absorption was greater than extracellular adsorption. After 120 h of exposure to NP, the four species could biodegrade most of the NP in the medium, with efficiencies ranging from 43.43 to 90.94%. In sum, we found that the four microalgae have high biodegradation percentages and can thus improve the bioremediation of NP-contaminated water.

Predicting Partitioning and Diffusion Properties of Nonpolar Chemicals in Biotic Media and Passive Sampler Phases by GC × GC

The chemical parameters needed to explain and predict bioavailability, biodynamics, and baseline toxicity are not readily available for most nonpolar chemicals detected in the environment. Here, we demonstrate that comprehensive two-dimensional gas chromatography (GC × GC) retention times can be used to predict 26 relevant properties for nonpolar chemicals, specifically: partition coefficients for diverse biotic media and passive sampler phases; aquatic baseline toxicity; and relevant diffusion coefficients. The considered biotic and passive sampler phases include membrane and storage lipids, serum and muscle proteins, carbohydrates, algae, mussels, polydimethylsiloxane, polyethylene, polyoxymethylene, polyacrylate, polyurethane, and semipermeable membrane devices. GC × GC-based chemical property predictions are validated with a compilation of 1038 experimental property data collected from the literature. As an example application, we overlay a map of baseline toxicity to fathead minnows onto the separated analyte signal of a polychlorinated alkanes (chlorinated paraffins) technical mixture that contains 7820 congeners. In a second application, GC × GC-estimated properties are used to parametrize multiphase partitioning models for mammalian tissues and organs. In a third example, we estimate chemical depuration kinetics for mussels. Finally, we illustrate an approach to screen the GC × GC chromatogram for nonpolar chemicals of potentially high concern, defined based on their GC × GC-estimated biopartitioning properties, diffusion properties, and baseline toxicity.

Equations for water-triolein partition coefficients for neutral species; comparison with other water-solvent partitions, and environmental and toxicological processes

Linear free energy relationships, LFERs, have been constructed for water-triolein partition coefficients for neutral species. It is shown that separate equations are required for wet and dry triolein. From a comparison of the equation coefficients for water-wet triolein with those for 52 other water-solvent systems it is shown that there is little correspondence between triolein and any of the 52 other solvents - only the water-isopropyl myristate system is close to the water-wet triolen system. A comparison of equation coefficients for the water-wet triolein system with LFER coefficients of 16 environmentally important processes shows that wet triolein is not a suitable model for any of the processes, although a number of other water-solvent systems are possible models for some of the environmental processes. A comparison of LFER coefficients with those of 17 aqueous toxicological processes reveals that most of the water-solvent systems, including water-wet triolein, will be poor models for any of the toxicological systems, but the water-lower alcohol systems show promise as models for a number of the toxicological systems. Our method of comparison of coefficients for LFERs that have exactly the same independent variables can be extended to various other types of system.

In situ investigation of the mechanisms of the transport to tissues of polycyclic aromatic hydrocarbons adsorbed onto the root surface of Kandelia obovata seedlings

A novel method for in situ determination of the polycyclic aromatic hydrocarbons (PAHs) adsorbed onto the root surface of Kandelia obovata seedlings was established using laser-induced time-resolved nanosecond fluorescence spectroscopy (LITRF). The linear dynamic ranges for the established method were 1.5-1240ng/spot for phenanthrene, 1.0-1360ng/spot for pyrene and 5.0-1220ng/spot for benzo[a]pyrene. Then, the mechanisms of PAHs transport from the Ko root surface to tissues were investigated. The three-phase model including fast, slow and very slow fractions was superior to the single or dual-phase model to describe the PAHs transport processes. Moreover, the fast fraction of PAHs transport process was mainly due to passive movement, while the slow and very slow fractions were not. Passive movement was the main process of B[a]P adsorbed onto Ko root surface transport to tissues. In addition, the extent of the PAHs transport to Ko root tissues at different salinity were evaluated.