Photo-Enhanced Toxicity in Amphibians: Synergistic Interactions of Solar Ultraviolet Radiation and Aquatic Contaminants

Amphibians experience a broad range of multiple environmental stressors that occur in natural systems. However, the impact of combinations of these stressors on amphibians are rarely examined. The effect of two stressors on amphibians, solar ultraviolet radiation (SUV) and environmental contamination, was investigated. To examine the interactive effects of SUV and environmental contaminants, Hyla venicolor and Rana sphenocephala were exposed in the laboratory to a carbamate insecticide and the water soluble fraction of a weathered petroleum in combination with various intensities of simulated solar radiation (SSR). The contaminants were tested at environmentally relevant concentrations. Synergistic interactions between SSR and these substances were observed during the exposures. Mortality of H. versicolor exposed to 2.51 mg/I carbaryl increased from 5% under control SSR conditions to 100% under low SSR irradiance (4 μ W/cm2). Exposure to a 10% solution of a water soluble fraction of petroleum under control SSR conditions was not lethal to R. sphenocephala; however under high SSR irradiance (17 μ W/cm2) a 5% water soluble fraction of petroleum was lethal. Relatively limited SSR irradiance is necessary to initiate photoenhanced toxicity, thus a range of amphibian habitats may be impacted by SUV. These studies indicate the importance of evaluating the interactive influence of environmental stressors present in amphibian habitats

Potential for Interspecies Toxicity Estimation in Soil Invertebrates

Interspecies correlation estimation (ICE) models are linear regressions that predict toxicity to a species with few data using a known toxicity value in a surrogate species. ICE models are well established for estimating toxicity to fish and aquatic invertebrates but have not been generally developed or applied to soil organisms. To facilitate the development of ICE models for soil invertebrates, a database of single chemical toxicity values was compiled from knowledgebases and reports that included 853 records encompassing 192 chemicals and 12 species. Most toxicity data for single chemicals tested in soil media were for species of earthworms, with only limited data for other species and taxa. ICE models were developed for eleven separate species pairs as least squares log-linear regressions of acute toxicity values of the same chemicals tested in both the surrogate and predicted species of soil organisms. Model uncertainty was assessed using leave one out cross-validation as the fold difference between a predicted and measured toxicity value. ICE models showed high accuracy within order (e.g., earthworm to earthworm), but less prediction accuracy in the two across-taxa models (Arthropoda to Annelida and the inverse). This study provides a proof-of-concept demonstration that ICE models can be developed for soil invertebrates

Temporal and Spatial Variation in Solar Radiation and Photo-Enhanced Toxicity Risks of Spilled Oil in Prince William Sound, Alaska, USA

Solar irradiance (W/m2) and downwelling diffuse attenuation coefficients (Kd; 1/m) were determined in several locations in Prince William Sound (AK, USA) between April 2003 and December 2005 to assess temporal and spatial variation in solar radiation and the risks of photo-enhanced toxicity from spilled oil.Weekly irradiance measurements of surface visible light, ultraviolet B (UVB), and ultraviolet A (UVA) radiation in Valdez (AK, USA) followed expected trends of maximum solar irradiance at each summer solstice and minimum values at each winter solstice. Variation from weekly maximum expected surface irradiances was attributed to large variations in environmental conditions over the 142-week monitoring period. Season and proximity to glacial meltwater were significant determinants of Kd, with 1% attenuation depths ranging from 0.4 to 15 m (UVB and UVA) and from 0.5 to 28 m (visible light). The probability of photo-enhanced toxicity risks estimated from UVA dosimetry decreased with increasing water depth, with higher risks during spring and summer and lower risks during fall and winter. These results demonstrate substantial temporal and spatial variation in solar radiation in Prince William Sound and the potential for significant season- and locationspecific photo-enhanced toxicity risks from spilled oil

Structure-Based Understanding of Binding Affinity and Mode of Estrogen Receptor α Agonists and Antagonists

<div><p>The flexible hydrophobic ligand binding pocket (LBP) of estrogen receptor α (ERα) allows the binding of a wide variety of endocrine disruptors. Upon ligand binding, the LBP reshapes around the contours of the ligand and stabilizes the complex by complementary hydrophobic interactions and specific hydrogen bonds with the ligand. Here we present a framework for quantitative analysis of the steric and electronic features of the human ERα-ligand complex using three dimensional (3D) protein-ligand interaction description combined with 3D-QSAR approach. An empirical hydrophobicity density field is applied to account for hydrophobic contacts of ligand within the LBP. The obtained 3D-QSAR model revealed that hydrophobic contacts primarily determine binding affinity and govern binding mode with hydrogen bonds. Several residues of the LBP appear to be quite flexible and adopt a spectrum of conformations in various ERα-ligand complexes, in particular His524. The 3D-QSAR was combined with molecular docking based on three receptor conformations to accommodate receptor flexibility. The model indicates that the dynamic character of the LBP allows accommodation and stable binding of structurally diverse ligands, and proper representation of the protein flexibility is critical for reasonable description of binding of the ligands. Our results provide a quantitative and mechanistic understanding of binding affinity and mode of <i>ER</i>α agonists and antagonists that may be applicable to other nuclear receptors.</p></div

Oil Characterization and Distribution in Florida Estuary Sediments Following the Deepwater Horizon Spill

Barrier islands of Northwest Florida were heavily oiled during the Deepwater Horizon spill, but less is known about the impacts to the shorelines of the associated estuaries. Shoreline sediment oiling was investigated at 18 sites within the Pensacola Bay, Florida system prior to impact, during peak oiling, and post-wellhead capping. Only two locations closest to the Gulf of Mexico had elevated levels of total petroleum hydrocarbons (TPH) and total polycyclic aromatic hydrocarbons (PAHs). These samples showed a clear weathered crude oil signature, pattern of depletion of C9 to C19 alkanes and C0 to C4 naphthalenes, and geochemical biomarker ratios in concordance with weathered Macondo crude oil. All other locations and sample times showed only trace petroleum contamination. The results of this study are consistent with available satellite imagery and visual shoreline survey data showing heavy shoreline oiling limited to sandy beaches near the entrance to Pensacola Bay and shorelines of Santa Rosa Island

Advancing Fifth Percentile Hazard Concentration Estimation Using Toxicity-Normalized Species Sensitivity Distributions

The species sensitivity distribution (SSD) is an internationally accepted approach to hazard estimation using the probability distribution of toxicity values that is representative of the sensitivity of a group of species to a chemical. Application of SSDs in ecological risk assessment has been limited by insufficient taxonomic diversity of species to estimate a statistically robust fifth percentile hazard concentration (HC5). We used the toxicity-normalized SSD (SSDn) approach, (Lambert, F. N.; Raimondo, S.; Barron, M. G. Environ. Sci. Technol.2022,56, 8278–8289), modified to include all possible normalizing species, to estimate HC5 values for acute toxicity data for groups of carbamate and organophosphorous insecticides. We computed mean and variance of single chemical HC5 values for each chemical using leave-one-out (LOO) variance estimation and compared them to SSDn and conventionally estimated HC5 values. SSDn-estimated HC5 values showed low uncertainty and high accuracy compared to single-chemical SSDs when including all possible combinations of normalizing species within the chemical-taxa grouping (carbamate-all species, carbamate-fish, organophosphate-fish, and organophosphate-invertebrate). The SSDn approach is recommended for estimating HC5 values for compounds with insufficient species diversity for HC5 computation or high uncertainty in estimated single-chemical HC5 values. Furthermore, the LOO variance approach provides SSD practitioners with a simple computational method to estimate confidence intervals around an HC5 estimate that is nearly identical to the conventionally estimated HC5

Advancing Fifth Percentile Hazard Concentration Estimation Using Toxicity-Normalized Species Sensitivity Distributions

The species sensitivity distribution (SSD) is an internationally accepted approach to hazard estimation using the probability distribution of toxicity values that is representative of the sensitivity of a group of species to a chemical. Application of SSDs in ecological risk assessment has been limited by insufficient taxonomic diversity of species to estimate a statistically robust fifth percentile hazard concentration (HC5). We used the toxicity-normalized SSD (SSDn) approach, (Lambert, F. N.; Raimondo, S.; Barron, M. G. Environ. Sci. Technol.2022,56, 8278–8289), modified to include all possible normalizing species, to estimate HC5 values for acute toxicity data for groups of carbamate and organophosphorous insecticides. We computed mean and variance of single chemical HC5 values for each chemical using leave-one-out (LOO) variance estimation and compared them to SSDn and conventionally estimated HC5 values. SSDn-estimated HC5 values showed low uncertainty and high accuracy compared to single-chemical SSDs when including all possible combinations of normalizing species within the chemical-taxa grouping (carbamate-all species, carbamate-fish, organophosphate-fish, and organophosphate-invertebrate). The SSDn approach is recommended for estimating HC5 values for compounds with insufficient species diversity for HC5 computation or high uncertainty in estimated single-chemical HC5 values. Furthermore, the LOO variance approach provides SSD practitioners with a simple computational method to estimate confidence intervals around an HC5 estimate that is nearly identical to the conventionally estimated HC5

Advancing Fifth Percentile Hazard Concentration Estimation Using Toxicity-Normalized Species Sensitivity Distributions

The species sensitivity distribution (SSD) is an internationally accepted approach to hazard estimation using the probability distribution of toxicity values that is representative of the sensitivity of a group of species to a chemical. Application of SSDs in ecological risk assessment has been limited by insufficient taxonomic diversity of species to estimate a statistically robust fifth percentile hazard concentration (HC5). We used the toxicity-normalized SSD (SSDn) approach, (Lambert, F. N.; Raimondo, S.; Barron, M. G. Environ. Sci. Technol.2022,56, 8278–8289), modified to include all possible normalizing species, to estimate HC5 values for acute toxicity data for groups of carbamate and organophosphorous insecticides. We computed mean and variance of single chemical HC5 values for each chemical using leave-one-out (LOO) variance estimation and compared them to SSDn and conventionally estimated HC5 values. SSDn-estimated HC5 values showed low uncertainty and high accuracy compared to single-chemical SSDs when including all possible combinations of normalizing species within the chemical-taxa grouping (carbamate-all species, carbamate-fish, organophosphate-fish, and organophosphate-invertebrate). The SSDn approach is recommended for estimating HC5 values for compounds with insufficient species diversity for HC5 computation or high uncertainty in estimated single-chemical HC5 values. Furthermore, the LOO variance approach provides SSD practitioners with a simple computational method to estimate confidence intervals around an HC5 estimate that is nearly identical to the conventionally estimated HC5

Prediction of RBA of 17β-estradiol derivatives based on protein-ligand complex structures from crystal structure modification (blue bars) or molecular docking (red bars).

<p>RBA is described by contributions from hydrophobic contacts (rectangle bars) and hydrogen bonds (hexagon bars). Black dots represent the experimental log RBA.</p