Single Chemicals Research Articles

Environmental levels of Zn do not protect embryos from Cu toxicity in three species of amphibians

Contaminants often occur as mixtures in the environment, but investigations into toxicity usually employ a single chemical. Metal contaminant mixtures from anthropogenic activities such as mining and coal combustion energy are widespread, yet relatively little research has been performed on effects of these mixtures on amphibians. Considering that amphibians tend to be highly sensitive to copper (Cu) and that metal contaminants often occur as mixtures in the environment, it is important to understand the interactive effects that may result from multiple metals. Interactive effects of Cu and zinc (Zn) on amphibians have been reported as antagonistic and, conversely, synergistic. The goal of our study was to investigate the role of Zn in Cu toxicity to amphibians throughout the embryonic developmental period. We also considered maternal effects and population differences by collecting multiple egg masses from contaminated and reference areas for use in four experiments across three species. We performed acute toxicity experiments with Cu concentrations that cause toxicity (10–200 μg/L) in the absence of other contaminants combined with sublethal concentrations of Zn (100 and 1000 μg/L). Our results suggest very few effects of Zn on Cu toxicity at these concentrations of Zn. As has been previously reported, we found that maternal effects and population history had significant influence on Cu toxicity. The explanation for a lack of interaction between Cu and Zn in this experiment is unknown but may be due to the use of sublethal Zn concentrations when previous experiments have used Zn concentrations associated with acute toxicity. Understanding the inconsistency of amphibian Cu/Zn mixture toxicity studies is an important research direction in order to create generalities that can be used to understand risk of contaminant mixtures in the environment.

Effects of Polycyclic Aromatic Hydrocarbon Mixtures on Degradation, Gene Expression, and Metabolite Production in Four Mycobacterium Species.

Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental contaminants that are hazardous to human health. It has been demonstrated that members of the Mycobacterium genus are among the most effective degraders of PAHs, but few studies have focused on the degradation of PAH mixtures. In this study, single and mixed PAH metabolism was investigated in four phylogenetically distinct Mycobacterium species with respect to (i) parent compound degradation, (ii) bacterial growth, (iii) catabolic gene expression, and (iv) metabolite production. Synergistic and antagonistic effects on four model PAH compounds (benzo[a]pyrene, pyrene, fluoranthene, and phenanthrene) characterized degradation of mixtures in a strain- and mixture-dependent manner. The mixture of pyrene and phenanthrene, in particular, resulted in antagonized degradation by three out of four bacterial species, and further studies were narrowed to investigate the degradation of this mixture. Antagonistic effects persisted over time and were correlated with reduced bacterial growth. Antagonized degradation of PAH was not caused by preferential degradation of secondary PAHs, nor were mixture compounds or concentrations toxic to cells growing on sugars. Reverse transcription-PCR (RT-PCR) studies of the characterized catabolic pathway of phenanthrene showed that in one organism, antagonism of mixture degradation was associated with downregulated gene expression. Metabolite profiling revealed that antagonism in mixture degradation was associated with the shunting of substrate through alternative pathways not used during the degradation of single PAHs. The results of this study demonstrate metabolic differences between single and mixed PAH degradation with consequences for risk assessment and bioremediation of PAH-contaminated sites. Mycobacterium species are promising organisms for environmental bioremediation because of their ubiquitous presence in soils and their ability to catabolize aromatic compounds. PAHs can be degraded effectively as single compounds, but mixed substrates often are subject to degradative inhibition, which may explain the persistence of these pollutants in soils. Single and mixed PAH degradation by diverse Mycobacterium species was compared, with associated bacterial growth, gene expression, and metabolite production. The results demonstrate that antagonism characterized degradation in a strain- and mixture-dependent manner. One strain that was versatile in its pathway use of single chemicals also efficiently degraded the mixture, whereas antagonism in other the strains was associated with altered metabolic profiles, indicating unusual pathway use. The impacts of this work on risk assessment and bioremediation modeling studies indicate the need to account for mixture-generated intermediates and to recognize mixture degradation as a property distinct from that of PAH substrate range.

Efek Sinergis Bahan Aktif Tanaman Obat Berbasiskan Jejaring dengan Protein Target

Medicinal plants contain inherently active ingredients. Such ingredients are beneficial to prevent and cure diseases, as well as to perform specific biological functions. In contrast to synthetic drugs, which is based on one single chemicals, medicinal plants exert their beneficial effects through the additive or synergistic action of several chemical compounds. Those chemical compound act on single or multiple targets (multicomponent therapeutic) associated with a physiological process. Active ingredients combinations show a synergistic effect. This means that the combinational effect of several active ingredients is greater than that of individual one acting separately. A network target can be used to identify synergistic effects of plants active ingredients. The method of NIMS (Network target-based Identification of Multicomponent Synergy) is a computational approach to identify the potential synergistics effect of active ingredients. It also assessess synergistic strength of any active ingradients at the molecular level by synergy scores. We investigate these synergistic on a Jamu formula for diabetes mellitus type 2. The Jamu formula is composed of four medicinal plants, namely Tinospora crispa , Zingiber officinale, Momordica charantia, and Blumea balsamivera. Our work succesfully demonstrates that the highest synergy scores on medicinal plants synergy can be seen in pairs of several active ingredients in Zingiber officinale. On the other hand, the synergy of pairs of active ingredients in Momordica charantia and Zingiber officinale posseses a relatively high score. The same occurs in Tinospora crispa and Zingiber officinale.

Efek Sinergis Bahan Aktif Tanaman Obat Berbasiskan Jejaring Dengan Protein Target

Medicinal plants contain inherently active ingredients. Such ingredients are beneficial to prevent and cure diseases, as well as to perform specific biological functions. In contrast to synthetic drugs, which is based on one single chemicals, medicinal plants exert their beneficial effects through the additive or synergistic action of several chemical compounds. Those chemical compound act on single or multiple targets (multicomponent therapeutic) associated with a physiological process. Active ingredients combinations show a synergistic effect. This means that the combinational effect of several active ingredients is greater than that of individual one acting separately. A network target can be used to identify synergistic effects of plants active ingredients. The method of NIMS (Network target-based Identification of Multicomponent Synergy) is a computational approach to identify the potential synergistics effect of active ingredients. It also assessess synergistic strength of any active ingradients at the molecular level by synergy scores. We investigate these synergistic on a Jamu formula for diabetes mellitus type 2. The Jamu formula is composed of four medicinal plants, namely Tinospora crispa , Zingiber officinale, Momordica charantia, and Blumea balsamivera. Our work succesfully demonstrates that the highest synergy scores on medicinal plants synergy can be seen in pairs of several active ingredients in Zingiber officinale. On the other hand, the synergy of pairs of active ingredients in Momordica charantia and Zingiber officinale posseses a relatively high score. The same occurs in Tinospora crispa and Zingiber officinale.

Prediction of mixture toxicity from the hormesis of a single chemical: A case study of combinations of antibiotics and quorum-sensing inhibitors with gram-negative bacteria

The 50% effect level of a single chemical in the real environment is almost impossible to determine at the low exposure concentration, and the prediction of the concentration of a mixture at the 50% effect level from the concentration of a single chemical at the low effect level is even more difficult. The current literature does not address this problem. Thus, to determine solutions for this question, single/mixture chronic toxicities of sulfonamides (SAs) and quorum-sensing inhibitors (QSIs) were determined using Gram-negative bacteria (Vibrio fischeri and E. coli.) and Gram-positive bacteria (B. subtilis) as the target organisms. The results showed that the joint effects of SAs and QSIs were primarily antagonistic responses. In addition, the toxicity mechanisms of mixtures of SAs and QSIs were investigated further, and the results revealed that the chronic joint effects were primarily an antagonistic response due to the QSI competing against acyl-homoserine lactones (AHL) for luxR in V. fischeri and SdiA in E. coli generated by the SAs, leading to negative effects exerted by the QSI-luxR or QSI-SdiA complexes on luxI in V. fischeri or FtsZ in E. coli. This phenomenon eventually weakened the stimulatory effect caused by the SAs. Based on the mixture toxicity mechanism, the relationship between the mixture toxicity and the simulation effect was formulated.

How well can in vitro data predict in vivo effects of chemicals? Rodent carcinogenicity as a case study

A recent research article by the National Center for Computational Toxicology (NCCT) (Kleinstreuer et al., 2013), indicated that high throughput screening (HTS) data from assays linked to hallmarks and presumed pathways of carcinogenesis could be used to predict classification of pesticides as either (a) possible, probable or likely rodent carcinogens; or (b) not likely carcinogens or evidence of non-carcinogenicity. Using independently developed software to validate the computational results, we replicated the majority of the results reported. We also found that the prediction model correlating cancer pathway bioactivity scores with in vivo carcinogenic effects in rodents was not robust. A change of classification of a single chemical in the test set was capable of changing the overall study conclusion about the statistical significance of the correlation. Furthermore, in the subset of pesticide compounds used in model validation, the accuracy of prediction was no better than chance for about three quarters of the chemicals (those with fewer than 7 positive outcomes in HTS assays representing the 11 histopathological endpoints used in model development), suggesting that the prediction model was not adequate to predict cancer hazard for most of these chemicals. Although the utility of the model for humans is also unclear because a number of the rodent responses modeled (e.g., mouse liver tumors, rat thyroid tumors, rat testicular tumors, etc.) are not considered biologically relevant to human responses, the data examined imply the need for further research with HTS assays and improved models, which might help to predict classifications of in vivo carcinogenic responses in rodents for the pesticide considered, and thus reduce the need for testing in laboratory animals.

A Primary Screening and Applying of Plant Volatiles as Repellents to Control Whitefly Bemisia tabaci (Gennadius) on Tomato.

With the goal of finding a new way to reduce population densities of Bemisia tabaci biotype Q in greenhouses, seven repellent volatile chemicals and their combinations were screened. The mixture of DLCO (D-limonene, citral and olive oil (63:7:30)) had a better cost performance(SC50 = 22.59 mg/ml)to repel whiteflies from settling than the other mixtures or single chemicals. In the greenhouse, in both the choice test and the no-choice tests, the number of adult whiteflies that settled on 1% DLCO-treated tomato plants was significantly lower than those settling on the control plants for the different exposure periods (P < 0.01). In the choice test, the egg amount on the treated tomato plants was significantly lower (P < 0.01) than that on the control plants, but there was no significant difference (P > 0.05) between the number of eggs on treated and control plants in the no-choice test. Compared with the controls, 1% DLCO did not cause significantly statistic mortality rates (P > 0.05) out of different living stages of B. tabaci. The tests for evaluating the repellent efficacy, showed that a slow-releasing bottle containing the mixture had a period of efficacy of 29 days, and the application of this mixture plus a yellow board used as a push-pull strategy in the greenhouse was also effective.

Impact of in utero exposure to pollutants on metabolic health in adults

Obesity is a major public health problem because it is a risk factor for metabolic disorders including type 2 diabetes and cardiovascular disorders. Notably, pollutants endowed with endocrine disrupting activities have been charged to contribute to the etiology of obesity and type 2 diabetes, especially if exposure occurs during the early life shown to be a highly vulnerable window of time. An overview on endocrine disrupters in relation with the obesogen and metabolic disruption hypothesis is presented. Convincing data support the plausibility of such hypothesis. They also highlight the limits of the current threshold model used in risk assessment which focused on single chemicals and does not take into account potential effects of mixtures containing pollutants at environmental doses, e.g. the real life exposure. Certainly, the principle of precaution should guide the making of decisions especially when considering early life exposure.

Navigating the tmdl process: sediment toxicity

A key step in the development of Total Maximum Daily Load (TMDL) allocations for water bodies impaired due to sediment toxicity is the identification of chemicals responsible for toxicity. Sediment toxicity identification evaluation procedures (TIEs) are one of the primary tools used in this process. This project evaluated standardized and recently developed sediment TIE methods developed by the US EPA and others, to determine their utility for identifying chemicals responsible for toxicity. In this study, formulated sediments were spiked with five chemicals: copper, fluoranthene, tetrachlorobenzene, nonylphenol and ammonia. Experiments were conducted using sediments spiked with single chemicals and chemical mixtures. Toxicity tests used the estuarine amphipod Eohaustorius estuarius and the freshwater amphipod Hyalella azteca. TIEs were conducted using solid-phase (whole sediment) and sediment interstitial waters. Our results indicate that the TIE methods are sufficient to characterize and identify toxicity due to single and multiple chemicals using spiked sediments. One key finding from the spiked sediment experiments is that methods to elute chemicals from extraction media used in solid-phase and interstitial water TIEs require further refinement to ensure complete and consistent elution of sorbed chemicals. An additional finding is that both solid-phase and interstitial water TIE procedures provide useful lines of evidence and that both approaches should be used in a weight-of-evidence approach in the sediment TIE process. In the final phase of this project, we evaluated the TIE procedures using ambient samples collected from three marine sites and three freshwater sites. Marine sediments were collected from Switzer Creek in San Diego Bay, Upper Newport Bay in Newport Beach, and Consolidated Slip, in Long Beach Harbor, all of which are sites in southern California. Freshwater sediments were collected from two additional sites in California: San Diego Creek, in Newport Beach, and Alisal Slough, in Salinas. The final freshwater sediment was collected from a site in Indiana Harbor. Multiple solid-phase and interstitial water TIEs were conducted on each sediment and results of these were combined with chemical analyses and other lines-of-evidence to evaluate the methods. The results indicate that sediment TIE methods are sufficiently developed to characterize toxicity due to general classes of chemicals such as cationic metals, organic chemicals, and ammonia. Methods to improve extraction and elution of metal and organic chemicals in highly toxic sediments require further refinement in order to allow identification of specific chemicals responsible for toxicity as part of the Phase II TIE process. These refinements include determining the appropriate masses of solid-phase extraction media to allow complete removal of toxic chemicals from sediments and interstitial waters. In addition, we recommend that additional studies be designed to determine optimal equilibration periods to maximize removal of toxic chemicals using resin amendments in solid-phase sediment TIEs. As in the spiked-sediment TIEs, we observed inconsistent elution of toxic chemicals from extraction media used in solid-phase and interstitial water Phase II TIEs with the ambient samples. These procedures require additional work to ensure that chemicals responsible for toxicity are completely eluted from extraction media. Improvement of the Phase II TIE elution and solvent handling steps should facilitate better identification of chemicals responsible for toxicity, particularly in situations where toxicity is due to highly insoluble chemicals. When these considerations are satisfactorily addressed, the methods evaluated are capable of providing useful lines of evidence that can be combined to successfully identify sediment toxicants. This title belongs to WERF Research Report Series ISBN: 9781843397663 (Print) ISBN: 9781780403786 (eBook)

Defining the Schistosoma haematobium kinome enables the prediction of essential kinases as anti-schistosome drug targets.

The blood fluke Schistosoma haematobium causes urogenital schistosomiasis, a neglected tropical disease (NTD) that affects more than 110 million people. Treating this disease by targeted or mass administration with a single chemical, praziquantel, carries the risk that drug resistance will develop in this pathogen. Therefore, there is an imperative to search for new drug targets in S. haematobium and other schistosomes. In this regard, protein kinases have potential, given their essential roles in biological processes and as targets for drugs already approved by the US Food and Drug Administration (FDA) for use in humans. In this context, we defined here the kinome of S. haematobium using a refined bioinformatic pipeline. We classified, curated and annotated predicted kinases, and assessed the developmental transcription profiles of kinase genes. Then, we prioritised a panel of kinases as potential drug targets and inferred chemicals that bind to them using an integrated bioinformatic pipeline. Most kinases of S. haematobium are very similar to those of its congener, S. mansoni, offering the prospect of designing chemicals that kill both species. Overall, this study provides a global insight into the kinome of S. haematobium and should assist the repurposing or discovery of drugs against schistosomiasis.

Risk advantages of platform technologies for biorenewable chemical production

Recent investments in bio-based chemical development are financing the construction of commercial production facilities, often designed to produce a single biorenewable chemical. Investments in technologies targeting a single biorenewable chemical are subject to significant technological and market risks. Platform technologies that can convert biomass into a range of related biorenewable chemicals can reduce these risks significantly. Researchers are now developing platform technologies that combine bio-and chemical-catalysis, such as a process of converting glucose into fatty alcohols of specific carbon chain length. The financial risk and profitability of investments in platform technology producing fatty alcohol of different chain length were analyzed. A techno-economic model to evaluate single- and platform technologies was developed. A platform technology that can produce two products: 1-decanol and a blend of dodecanol and 1-tetradecanol reduces financial risk of investment by 23% and increases profitability by 55% compared to production via single-product technologies. This financial advantage of two-product technology is eliminated as the cost of switching between products rises above $4MM for a 14MT/yr plant. Investments in technologies that can produce a larger number of products provide higher returns lower risk. Other less quantifiable risk advantages of platform technologies that nonetheless important are also discussed.

From single chemicals to mixtures—Reproductive effects of levonorgestrel and ethinylestradiol on the fathead minnow

The aquatic environment is polluted with thousands of chemicals. It is currently unclear which of these pose a significant threat to aquatic biota. The typical exposure scenario is now represented by a widespread blanket of contamination composed of myriads of individual pollutants—each typically present at a low concentration. The synthetic steroids, 17α-ethinylestradiol and levonorgestrel, have been widely reported to be present in the aquatic environment in the low ng to sub-ng/l range. They are widely used in contraceptive formulations, both individually and in combination. Our research employed the fathead minnow (Pimephales promelas) 21 day ‘pair-breeding’ assay to assess reproductive output when pairs of fish were exposed to the single chemicals at low environmentally relevant concentrations, and then to a binary mixture of them. A variety of endpoints were assessed, including egg production, which was inhibited in a concentration-dependent manner by both the individual chemicals and the mixture. Significant, sex specific effects were also seen with both chemicals, at differing levels of biological organisation. Plasma concentrations of EE2 and levonorgestrel were predicted and in the case of levonorgestrel measured, and compared with the human therapeutic plasma concentrations (Read-Across approach) to support the interpretation of the results. A novel quantitative method was developed for the data analysis, which ensured a suitable endpoint for the comparative mixture assessment. This approach compares the reproductive performance from individual pairs of fish during chemical exposure to its pre-treatment performance. The responses from the empirical mixture study were compared to predictions derived from the single substance data. We hypothesised combined responses which were best described by the concept of concentration addition, and found no clear indications against this additivity expectation. However, the effect profiles support the current knowledge that both compounds act in different ways to reduce egg production in fish, and suggest that probably response addition (also called Independent action) is the more appropriate mixture model in this case.

QSAR models and their corresponding toxicity mechanism for mixture toxicity of organic pollutants

Environmental contaminants are frequently encountered as mixtures rather than single chemicals. However, current environmental quality standards and ecological risk assessments are mainly based on single toxicities, and pay little attention to the potential hazards of mixture exposure. The study of mixture toxicity is therefore not only of theoretical value, but also of deep practical significance. This review mainly focuses on quantitative structure-activity relationship (QSAR) models for mixture toxicities of organic pollutants and the corresponding toxicity mechanisms. The organic pollutants are classified as non-polar narcosis chemicals, polar narcosis chemicals, and reactive chemicals, according to their modes of action. QSAR models of the three types of chemical are described based on their toxicity mechanisms respectively. QSAR models of non-polar narcosis chemicals are described. The QSAR models of the mixture toxicities of non-polar narcosis chemicals are the simplest. The toxicity only depends on the total hydrophobicity of the mixture and can be predicted using a uniform model. QSAR models for polar narcosis chemicals are summarized. The toxicities of narcosis chemicals are determined not only by the total hydrophobicity but also by hydrogen-bonding effects. QSAR models for reactive chemicals are described in detail. There is no uniform model, because the toxicity mechanisms of the reactive chemicals are complicated. However, three aspects of the latest research on quantitative prediction methods for toxicities of mixtures containing reactive chemicals are summarized: the factors affecting multicomponent mixtures containing reactive chemicals; the interactions among the single chemicals in the mixture; and the interactions between the chemicals and the target protein. It is pointed out that identifying the molecular biological mechanisms of chemicals using advanced experimental methods (such as genomics and metabolomics) and formulating a common prediction model based on these mechanisms should be the direction of future developments.

Transcriptional responses in male Japanese medaka exposed to antiandrogens and antiandrogen/androgen mixtures.

The occurrence of androgenic endocrine disrupting chemicals (EDCs) in water is thought to be linked to deviation from normal male developmental and reproductive functions in exposed aquatic organisms. Because aquatic environments represent a chemically complex medium, the combined effects of androgenic EDCs require urgent attention. In the present study, the effects of two model androgen receptor (AR) antagonists, flutamide (FLU), and vinclozolin (VIN), were first determined individually in male Japanese medaka using the transcriptional response for genes associated with the hypothalamic-pituitary-gonadal axis. The fish were further exposed to binary mixtures of VIN and 17β-trenbolone (TRE, AR agonist) to confirm the theoretical opposing effects of the AR antagonist and agonist. The results showed that exposure to FLU or VIN alone induced very similar transcriptional responses, demonstrating that gene transcription analysis could be successfully employed in identifying the action of single chemicals. For example, both exposures increased the transcription of cyp17b but decreased that of cyp19b in the gonad, demonstrating the compensatory response for AR blockage. However, in the case of exposure to mixtures, although the joint antagonistic action of TRE and VIN affected the most genes, the transcription profiles after exposure to mixtures were not consistent with expectations based on the results for individual chemicals, such as hepatic vtg, and star or cyp19a in gonads. Therefore, the limitation of gene transcription analyses in exposures to mixtures, as well as the potential for the extrapolation of single chemicals, should be considered in future studies. © 2015 Wiley Periodicals, Inc. Environ Toxicol 31: 1591-1599, 2016.

A Dose-Response Modeling Approach Shows That Effects From Mixture Exposure to the Skin Sensitizers Isoeugenol and Cinnamal Are in Line With Dose Addition and Not With Synergism.

Currently, hazard characterization of skin sensitizers is based on data obtained from studies examining single chemicals. Many consumer products, however, contain mixtures of sensitizers that might interact in such a way that the response induced by a substance is higher than predicted in the hazard assessment. To assess interaction of skin sensitizers in a mixture, a dose-response modeling approach is applied. With this approach, it is possible to assess whether or not responses from mixtures of sensitizers can be predicted from the dose-response information obtained from individual chemicals using dose addition. We selected the skin sensitizers isoeugenol and cinnamal, frequently occurring together in consumer products, to be examined in an adjusted local lymph node assay (LLNA). Cell number and cytokine production (IL-10 and IFN-γ) of the auricular lymph nodes were measured as hallmarks of the skin sensitization response. We found that dose addition for these 2 skin sensitizers closely predicted the effects from mixtures of both chemicals across the broad dose range tested. Hence, isoeugenol and cinnamal show no synergistic effects in the LLNA. Therefore, hazard assessment and risk assessment of these substances can be performed without taking into account mixture exposure.

A systematic methodology for optimal mixture design in an integrated biorefinery

Biomass is a sustainable source of energy which can be utilised to produce value-added products such as biochemical products and biomaterials. In order to produce a sustainable supply of such value-added products, an integrated biorefinery is required. An integrated biorefinery is a processing facility that integrates multiple biomass conversion pathways to produce value-added products. To date, various biomass conversion pathways are available to convert biomass into a wide range of products. Due to the large number of available pathways, various systematic screening tools have been developed to address the process design aspect of an integrated biorefinery. Process design however, is often inter-linked with product design as it is important to identify the optimal molecule (based on desired product properties) prior to designing its optimal production routes. In cases where the desired product properties cannot be met by a single component chemical product, a mixture of chemicals would be required. In this respect, product and process design decisions would be a challenging task for an integrated biorefinery. In this work, a novel two-stage optimisation approach is developed to identify the optimal conversion pathways in an integrated biorefinery to convert biomass into the optimal mixtures in terms of target product properties. In the first stage, the optimal mixture is designed via computer-aided molecular design (CAMD) technique. CAMD technique is a reverse engineering approach which predicts the molecules with optimal properties using property prediction models. Different classes of property models such as group contribution (GC) models and quantitative structure property relationship (QSPR) are adapted in this work. The main component of the mixture is first determined from the target product properties. This is followed by the identifying of additive components to form an optimal mixture with the main component based on the desired product properties. Once the optimal mixture is determined, the second stage identifies the optimal conversion pathways via superstructural mathematical optimisation approach. With such approach, the optimal conversion pathways can be determined based on different optimisation objectives (e.g. highest product yield, lowest environmental impact etc.). To illustrate the proposed methodology, a case study on the design of fuel additives as a mixture of different molecules from palm-based biomass is presented. With the developed methodology, optimal fuel additives are designed based on optimal target properties. Once the optimal fuel additives are designed, the optimal conversion pathways in terms of highest product yield and economic performance that convert biomass into the optimal fuel additives are identified.

Exploring the Potential Interference of Estuarine Sediment Contaminants with the DNA Repair Capacity of Human Hepatoma Cells

Estuaries may be reservoirs of a wide variety of pollutants, including mutagenic and carcinogenic substances that may impact on the ecosystem and human health. A previous study showed that exposure of human hepatoma (HepG2) cells to extracts from sediment samples collected in two areas (urban/industrial and riverine/agricultural) of an impacted estuary (Sado, Portugal), produced differential cytotoxic and genotoxic effects. Those effects were found to be consistent with levels and nature of sediment contamination. The present study aimed at evaluating whether the mixtures of contaminants contained in those extracts were able to modulate DNA repair capacity of HepG2 cells. The residual level of DNA damage was measured by the comet assay in cells exposed for 24 or 48 h to different extracts, after a short preexposure to a challenging concentration range of ethyl methanesulfonate (EMS), as a model alkylating agent. The results suggested that the mixture of contaminants present in the tested samples, besides a potential direct effect on the DNA molecule, may also interfere with DNA repair mechanisms in HepG2 cells, thus impairing their ability to deal with genotoxic stress and, possibly, facilitating accumulation of mutations. Humans are environmentally/occupationally exposed to mixtures rather than to single chemicals. Thus, the observation that estuarine contaminants induce direct and indirect DNA strand breakage in human cells, the latter through the impairment of DNA repair, raises additional concerns regarding potential hazards from exposure and the need to further explore these endpoints in the context of environmental risk assessment.

Assessing Human Variability in Kinetics for Exposures to Multiple Environmental Chemicals: A Physiologically Based Pharmacokinetic Modeling Case Study with Dichloromethane, Benzene, Toluene, Ethylbenzene, and m-Xylene

The objective of this study was to compare the magnitude of interindividual variability in internal dose for inhalation exposure to single versus multiple chemicals. Physiologically based pharmacokinetic models for adults (AD), neonates (NEO), toddlers (TODD), and pregnant women (PW) were used to simulate inhalation exposure to “low” (RfC-like) or “high” (AEGL-like) air concentrations of benzene (Bz) or dichloromethane (DCM), along with various levels of toluene alone or toluene with ethylbenzene and xylene. Monte Carlo simulations were performed and distributions of relevant internal dose metrics of either Bz or DCM were computed. Area under the blood concentration of parent compound versus time curve (AUC)-based variability in AD, TODD, and PW rose for Bz when concomitant “low” exposure to mixtures of increasing complexities occurred (coefficient of variation (CV) = 16–24%, vs. 12–15% for Bz alone), but remained unchanged considering DCM. Conversely, AUC-based CV in NEO fell (15 to 5% for Bz; 12 to 6% for DCM). Comparable trends were observed considering production of metabolites (AMET), except for NEO’s CYP2E1-mediated metabolites of Bz, where an increased CV was observed (20 to 71%). For “high” exposure scenarios, Cmax-based variability of Bz and DCM remained unchanged in AD and PW, but decreased in NEO (CV= 11–16% to 2–6%) and TODD (CV= 12–13% to 7–9%). Conversely, AMET-based variability for both substrates rose in every subpopulation. This study analyzed for the first time the impact of multiple exposures on interindividual variability in toxicokinetics. Evidence indicates that this impact depends upon chemical concentrations and biochemical properties, as well as the subpopulation and internal dose metrics considered.

A novel biomarker for anti-androgenic activity in placenta reveals risks of urogenital malformations.

It has been hypothesized that the rise in male reproductive disorders over recent decades may at least be partially attributable to environmental factors, including chemical exposures, but observed associations with single chemicals were rather weak. The aim of this case-control study was to explore the relationship between exposure to mixtures of (anti-)androgenic chemicals during pregnancy and the risk of cryptorchidism and/or hypospadias in offspring, using the total effective xenobiotic burden of anti-androgens (TEXB-AA) as a biomarker. A subsample of 29 cases (16 of cryptorchidism, 12 of hypospadias, and one of both disorders) and 60 healthy controls was nested in a cohort of male newborns recruited between October 2000 and July 2002. The (anti-)androgenic activity of placenta samples collected at delivery was assessed using TEXB-AA biomarker, combined with a bioassay-directed fractionation protocol that separated endogenous hormones from most (anti-)androgenic chemicals by normal-phase HPLC. The bioassay measures the androgen-induced luciferase activity and the inhibition of this pathway by (anti-)androgens. First, we collected 27 HPLC fractions in each placenta extract, which were all tested in the bioassay. The multivariable statistical analyses indicated a statistically significant positive dose-response association between the potent anti-androgenic activity of the HPLC fraction collected during minutes 1-2 (F2) and the risk of malformations (odds ratio: 2.33, 95% CI: 1.04-5.23). This study represents a novel approach for the estimation of combined effects of the total anti-androgenic load and the associations suggest an effect of environmental pollutants on the development of fetal reproductive tract.Free Spanish abstract: A Spanish translation of this abstract is freely available at http://www.reproduction-online.org/content/149/6/605/suppl/DC1.

Multiple stressor effects in Chlamydomonas reinhardtii – Toward understanding mechanisms of interaction between effects of ultraviolet radiation and chemical pollutants

The effects of chemical pollutants and environmental stressors, such as ultraviolet radiation (UVR), can interact when organisms are simultaneously exposed, resulting in higher (synergistic) or lower (antagonistic) multiple stressor effects than expected based on the effects of single stressors. Current understanding of interactive effects is limited due to a lack of mechanism-based multiple stressor studies. It has been hypothesized that effect interactions may generally occur if chemical and non-chemical stressors cause similar physiological effects in the organism. To test this hypothesis, we exposed the model green alga Chlamydomonas reinhardtii to combinations of UVR and single chemicals displaying modes of action (MOA) similar or dissimilar to the impact of UVR on photosynthesis. Stressor interactions were analyzed based on the independent action model. Effect interactions were found to depend on the MOA of the chemicals, and also on their concentrations, the exposure time and the measured endpoint. Indeed, only chemicals assumed to cause effects on photosynthesis similar to UVR showed interactions with UVR on photosynthetic yield: synergistic in case of Cd(II) and paraquat and antagonistic in case of diuron. No interaction on photosynthesis was observed for S-metolachlor, which acts dissimilarly to UVR. However, combined effects of S-metolachlor and UVR on algal reproduction were synergistic, highlighting the importance of considering additional MOA of UVR. Possible mechanisms of stressor effect interactions are discussed.