QSAR classification models for the screening of the endocrine-disrupting activity of perfluorinated compounds

Perfluorinated compounds (PFCs) are a class of emerging pollutants still widely used in different materials as non-adhesives, waterproof fabrics, fire-fighting foams, etc. Their toxic effects include potential for endocrine-disrupting activity, but the amount of experimental data available for these pollutants is limited. The use of predictive strategies such as quantitative structure-activity relationships (QSARs) is recommended under the REACH regulation, to fill data gaps and to screen and prioritize chemicals for further experimentation, with a consequent reduction of costs and number of tested animals. In this study, local classification models for PFCs were developed to predict their T4-TTR (thyroxin-transthyretin) competing potency. The best models were selected by maximizing the sensitivity and external predictive ability. These models, characterized by robustness, good predictive power and a defined applicability domain, were applied to predict the activity of 33 other PFCs of environmental concern. Finally, classification models recently published by our research group for T4-TTR binding of brominated flame retardants and for estrogenic and anti-androgenic activity were applied to the studied perfluorinated chemicals to compare results and to further evaluate the potential for these PFCs to cause endocrine disruption.     

Trends in the detection of pharmaceuticals and endocrine-disrupting compounds by Field-Effect Transistors (FETs)

Field-effect transistors (FETs) are one of the most widely-used electronic sensors for continuous monitoring and detection of contaminants such as pharmaceuticals and endocrine-disrupting compounds at low concentrations. FETs have been successfully utilized for the rapid analysis of these environmental pollutants due to their advantageous material properties like the disposability, rapid responses and simplicity. This paper presented an up-to-date overview of applied strategies with different bio-based materials in order to enhance the analytical performances of the designed sensors. Comparison and discussion were made between characteristics of recently engineered FET bio-sensors used for the detection of famous and selected pharmaceutical compounds in the literature. The recent progress in environmental research applications, comments on interesting trends, current challenge for future research in endocrine-disrupting chemicals’ (EDCs) detection using FETs biosensors were highlighted.     

An integrated "4-phase" approach for setting endocrine disruption screening priorities--phase I and II predictions of estrogen receptor binding affinity

Recent legislation mandates the US Environmental Protection Agency (EPA) to develop a screening and testing program for potential endocrine disrupting chemicals (EDCs), of which xenoestrogens figure prominently. Under the legislation, a large number of chemicals will undergo various in vitro and in vivo assays for their potential estrogenicity, as well as other hormonal activities. There is a crucial need for priority setting before this strategy can be effectively implemented. Here we report an integrated computational approach to priority setting using estrogen receptor (ER) binding as an example. This approach rationally integrates different predictive computational models into a "Four-Phase" scheme so that it can effectively identify potential estrogenic EDCs based on their predicted ER relative binding affinity (RBA). The system has been validated using an in-house ER binding assay dataset for 232 chemicals that was designed to have both broad structural diversity and a wide range of binding affinities. When applied to 58,000 chemicals identified by Walker et al. as candidates for endocrine disruption screening, some 9100 chemicals were predicted to bind to ER. Of these, only 3600 were expected to bind to ER at RBA values up to 100,000-fold less than that of 17beta-estradiol. The method ruled out 83% of the chemicals as non-binders with a very low rate of false negatives. We believe that the same integrated scheme will be equally applicable to endpoints of other endocrine disrupting mechanisms, e.g. androgen receptor binding.     

An integrated "4-phase" approach for setting endocrine disruption screening priorities--phase I and II predictions of estrogen receptor binding affinity

Recent legislation mandates the US Environmental Protection Agency (EPA) to develop a screening and testing program for potential endocrine disrupting chemicals (EDCs), of which xenoestrogens figure prominently. Under the legislation, a large number of chemicals will undergo various in vitro and in vivo assays for their potential estrogenicity, as well as other hormonal activities. There is a crucial need for priority setting before this strategy can be effectively implemented. Here we report an integrated computational approach to priority setting using estrogen receptor (ER) binding as an example. This approach rationally integrates different predictive computational models into a "Four-Phase" scheme so that it can effectively identify potential estrogenic EDCs based on their predicted ER relative binding affinity (RBA). The system has been validated using an in-house ER binding assay dataset for 232 chemicals that was designed to have both broad structural diversity and a wide range of binding affinities. When applied to 58,000 chemicals identified by Walker et al. as candidates for endocrine disruption screening, some 9100 chemicals were predicted to bind to ER. Of these, only 3600 were expected to bind to ER at RBA values up to 100,000-fold less than that of 17 g -estradiol. The method ruled out 83% of the chemicals as non-binders with a very low rate of false negatives. We believe that the same integrated scheme will be equally applicable to endpoints of other endocrine disrupting mechanisms, e.g. androgen receptor binding.     

冷冻干燥技术在环境水样有机新污染物前处理中的应用进展

有机新污染物是一类在先进分析技术帮助下新鉴定的、现有法规未管制的、人为源的有机污染物.有机新污染物主要包括药品与个人护理、农药、全氟化合物、内分泌干扰物等,其会产生内分泌干扰效应、诱发抗性基因传播,还对人类和野生生物的生存与发展构成潜在威胁,因此检测环境样品中的有机新污染物浓度对生态环境和人体健康具有重大意义.由于环境...     

Wastewater-based epidemiology to assess human exposure to personal care and household products – A review of biomarkers,analytical methods,and applications

Humans are nowadays exposed to numerous chemicals in our day-to-day life, including parabens, UV filters, phosphorous flame retardants/plasticizers, bisphenols, phthalates and alternative plasticizers, which can have different adverse effects to human health. Estimating human’s exposure to these potentially harmful substances is, therefore, of paramount importance. Human biomonitoring (HBM) is the existing approach to assess exposure to environmental contaminants, which relies on the analysis of specific human biomarkers (parent compounds and/or their metabolic products) in biological matrices from individuals. The main drawback is its implementation, which involves complex cohort studies. A novel approach, wastewater-based epidemiology (WBE), involves estimating exposure from the analysis of biomarkers in sewage (a pooled urine and feces sample of an entire population). One of the key challenges of WBE is the selection of biomarkers which are specific to human metabolism, excreted in sufficient amounts, and stable in sewage. So far, literature data on potential biomarkers for estimating exposure to these chemicals are scattered over numerous pharmacokinetic and HBM studies. Hence, this review provides a list of potential biomarkers of exposure to more than 30 widely used chemicals and report on their urinary excretion rates. Furthermore, the potential and challenges of WBE in this particular field is discussed through the review of pioneer WBE studies, which for the first time explored applicability of this novel approach to assess human exposure to environmental contaminants. In the future, WBE could be potentially applied as an “early warning system”, which could promptly identify communities with the highest exposure to environmental contaminants.     

Recent advances in analytical methodologies based on mass spectrometry for the environmental analysis of halogenated organic contaminants

Halogenated organic contaminants, including legislated and potential persistent organic pollutants and their precursors, represent a major environmental concern due to their hazardous effects in humans and wildlife as well as their ability to bioaccumulate through the food chain, their high resistance to environmental degradation, and their long-range atmospheric transport potential. The monitoring of these compounds in the environment at ultra-trace concentration levels requires highly selective and sensitive analytical methodologies. The lack of reference step-by-step methods led to a high number of reliable determinations depending on analytes, the complexity of the sample, and available instrumentation. Thus, this review article is mainly focused on the last advances in the analytical methodologies for the determination of halogenated organic contaminants. Methodologies regarding sample treatment, chromatographic separation, and mass spectrometry analysis have been reviewed to finally highlight the future perspectives for the improvement of the analytical determinations of these compounds and the throughput of environmental control laboratories in this field.     

A strategy for ranking environmentally occurring chemicals. Part VI. QSARs for the mutagenic effects of halogenated aliphatics.

A strategy for the systematic analysis and priority ranking of environmental chemicals has been applied to a class of 58 halogenated aliphatic hydrocarbons. A training set of ten compounds representing this class, was selected by statistical design. The training set compounds were then subjected to biological testing in the Salmonella typhimurium reverse mutation assay (Ames test). The measured biological data, recorded as dose-response curves, were analyzed to determine the mutagenic potency (slope of the initial portion) and the mutagen dose (MD 50) required to increase the number of revertants above the background by 50%. For each compound, four mutagenic potency estimates and four MD 50 values were determined, all originating from the tester strains TA 100 and TA 1535 with and without metabolic activation. The obtained responses were analyzed with multivariate techniques to give QSAR models relating the mutagenic potency data to the physico-chemical properties of the compounds. Finally, the derived QSARs were used to predict the mutagenic potencies and the MD 50S for the non-tested compounds in the class.     

Towards the development of molecularly imprinted artificial receptors for the screening of estrogenic chemicals.

Molecularly imprinted polymers are prepared using various steroid compounds as the templates. The imprinted polymers can selectively re-bind the original print molecules, which leads to versatile potential applications. The feasibility of using these artificial receptors to replace their biological counterparts for preliminary screening of a chemical library is demonstrated. A steroid library composed of 22 closely related compounds is screened with an estrogen specific polymer. The print molecule is identified with accuracy and structural similarities of other members are correlated with normalized retention indices. Molecularly imprinted artificial receptors are envisioned as being useful for screening purposes in drug discovery or for identifying endocrine-disrupting chemicals.     

In silico prediction of receptor-mediated environmental toxic phenomena-application to endocrine disruption

It is an objective of our institution to establish a virtual laboratory allowing for a reliable in silico estimation of the harmful effects triggered by drugs, chemicals and their metabolites. In the recent past, we have developed the underlying technology (Multi-dimensional QSAR: Quasar and Raptor) and compiled a pilot system including the 3D models of three receptors known to mediate endocrine-disrupting effects (the aryl hydrocarbon receptor, the estrogen receptor and the androgen receptor, respectively) and validated them against 310 compounds (drugs, chemicals, toxins). Within this set up we could demonstrate that our concepts are able to both recognize toxic compounds substantially different from those used in the training set as well as to classify harmless compounds clearly as being non-toxic. This suggests that our approach can be used for the prediction of adverse effects of drug molecules and chemicals.     

Improving confidence in (Q)SAR predictions under Canada’s Chemicals Management Plan – a chemical space approach$

Abstract

One of the key challenges of Canada’s Chemicals Management Plan (CMP) is assessing chemicals with limited/no empirical hazard data for their risk to human health. In some instances, these chemicals have not been tested broadly for their toxicological potency; as such, limited information exists on their potential to induce human health effects following exposure. Although (quantitative) structure activity relationship ((Q)SAR) models are able to generate predictions to address data gaps for certain toxicological endpoints, the confidence in predictions also needs to be addressed. One way to address this issue is to apply a chemical space approach. This approach uses international toxicological databases, for example, those available in the Organisation for Economic Co-operation and Development (OECD) QSAR Toolbox. The approach,assesses a model’s ability to predict the potential hazards of chemicals that have limited hazard data that require assessment under the CMP when compared to a larger, data-rich chemical space that is structurally similar to chemicals of interest. This evaluation of a model’s predictive ability makes (Q)SAR analysis more transparent and increases confidence in the application of these predictions in a risk-assessment context. Using this approach, predictions for such chemicals obtained from four (Q)SAR models were successfully classified into high, medium and low confidence levels to better inform their use in decision-making.     

Determination of phthalate esters in vegetable oils using direct immersion solid-phase microextraction and fast gas chromatography coupled with triple quadrupole mass spectrometry

Phthalates are a group of synthetic compounds mainly used as plasticizers, which have been classified as endocrine-disrupting chemicals and potential human-cancer causing agents. They can be found in high amounts in foods, deriving mainly from plastic packaging. The analytical determination of these compounds is very challenging since they are ubiquitous. Therefore, minimization of sample manipulation is highly desirable.     

Effect-directed analysis of endocrine-disrupting compounds in multi-contaminated sediment: identification of novel ligands of estrogen and pregnane X receptors

Effect-directed analysis (EDA)-based strategies have been increasingly used in order to identify the causative link between adverse (eco-)toxic effects and chemical contaminants. In this study, we report the development and use of an EDA approach to identify endocrine-disrupting chemicals (EDCs) in a multi-contaminated river sediment. The battery of in vitro reporter cell-based bioassays, measuring estrogenic, (anti)androgenic, dioxin-like, and pregnane X receptor (PXR)-like activities, revealed multi-contamination profiles. To isolate active compounds of a wide polarity range, we established a multi-step fractionation procedure combining: (1) a primary fractionation step using normal phase-based solid-phase extraction (SPE), validated with a mixture of 12 non-polar to polar standard EDCs; (2) a secondary fractionation using reversed-phase-based high-performance liquid chromatography (RP-HPLC) calibrated with 33 standard EDCs; and (3) a purification step using a recombinant estrogen receptor (ER) affinity column. In vitro SPE and HPLC profiles revealed that ER and PXR activities were mainly due to polar to mid-polar compounds, while dioxin-like and anti-androgenic activities were in the less polar fractions. The overall procedure allowed final isolation and identification of new environmental PXR (e.g., di-iso-octylphthalate) and ER (e.g., 2,4-di-tert-butylphenol and 2,6-di-tert-butyl-α-methoxy-p-cresol) ligands by using gas chromatography coupled with mass spectrometry with full-scan mode acquisition in mid-polar fractions. In vitro biological activity of these chemicals was further confirmed using commercial standards, with di-iso-octylphthalate identified for the first time as a potent hPXR environmental agonist.     

Analytical methods for personal-care products in environmental waters

Personal-care products (PCPs) are organic chemicals widely used in human life daily. Among the most recently studied PCPs, we can find ultraviolet filters, preservatives, antimicrobials, musk fragrances, insect repellents and siloxanes. PCPs are increasingly important emerging organic contaminants due to their presence in environmental waters.We present a review of the most important extraction and chromatographic techniques used to determine PCPs in waters. We also review data regarding the occurrence of these compounds in different kinds of environmental waters and the removal of these compounds in sewage-treatment plants.     

Considerations involved with the use of semipermeable membrane devices for monitoring environmental contaminants

Semipermeable membrane devices (SPMDs) are used with increasing frequency, and throughout the world as samplers of organic contaminants. The devices can be used to detect a variety of lipophilic chemicals in water, sediment/soil, and air. SPMDs are designed to sample nonpolar, hydrophobic chemicals. The maximum concentration factor achievable for a particular chemical is proportional to its octanol-water partition coefficient. Techniques used for cleanup of SPMD extracts for targeted analytes and for general screening by full-scan mass spectrometry do not differ greatly from techniques used for extracts of other matrices. However, SPMD extracts contain potential interferences that are specific to the membrane-lipid matrix. Procedures have been developed or modified to alleviate these potential interferences. The SPMD approach has been demonstrated to be applicable to sequestering and analyzing a wide array of environmental contaminants including organochlorine pesticides, polychlorinated biphenyls, polycyclic aromatic hydrocarbons, polychlorinated dioxins and dibenzofurans, selected organophosphate pesticides and pyrethroid insecticides, and other nonpolar organic chemicals. We present herein an overview of effective procedural steps for analyzing exposed SPMDs for trace to ultra-trace levels of contaminants sequestered from environmental matrices.