Category Archives: Earth Science

Individual Based Modelling of Cold Water Refuge Use in the Columbia River.

Anadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the advantages and disadvantages of spatially-distributed cold water refugia for adult migrating salmon and steelhead in the Columbia River. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss model development and the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River.

A Network of AOPs for reduced thyroid hormone synthesis derived from inhibition of Thyroperoxidase – A common Molecular Initiating Event Leading to Species-Specific Indices of Adversity.

This collection of 3 AOPs describe varying outcomes of adversity dependent upon species in response to inhibition of thyroperoxidase (TPO) during development. Chemical inhibition of TPO, the molecular-initiating event (MIE), results in decreased thyroid hormone (TH) synthesis, and subsequent reduction in circulating concentrations of THs. THs are essential for normal human brain development, metamorphorfic change from tadpole to frog in amphibians, and deficits in inflation of the anterior swim bladder in young fishes. Chemicals that interfere with TH synthesis have the potential to cause TH insufficiency that may result in adverse neurodevelopmental effects in offspring. The biochemistry of TPO and its essentiality for TH synthesis is well known across species. Although quantitative information at all levels of KERs is limited a number of applications of this AOP have been identified.

Neurodevelopment and Thyroid Hormone Synthesis Inhibition in the Rat: Quantitative Understanding Within the Adverse Outcome Pathway Framework

Adequate levels of thyroid hormones (TH) are needed for proper brain development, deficiencies may lead to adverse neurological outcomes in humans and animal models. Environmental chemicals have been linked to TH disruption, yet the relationship between developmental exposures and decline in serum TH resulting in neurodevelopmental impairment is poorly understood. The present study developed a quantitative adverse outcome pathway (qAOP) where serum thyroxin (T4) reduction following inhibition of thyroperoxidase in the thyroid gland are described and related to deficits in fetal brain TH and the development of a brain malformation, subcortical band heterotopia. Pregnant dams were exposed to 6-propylthiouracil (PTU 0, 0.1, 0.5, 1, 2, or 3 ppm) from gestational day 6-20, increasing PTU concentrations in maternal thyroid gland and serum as well as in fetal serum. Dams exposed to 0.5 ppm PTU and higher exhibited dose-dependent decreases in thyroidal T4. Serum T4 levels in the dam were significantly decreased with exposure to 2 and 3 ppm PTU. In the fetus, T4 decrements were first observed at a lower dose of 0.5 ppm PTU. Based on these data, fetal brain T4 levels were estimated from published literature sources, and quantitatively linked to increases in the size of the heterotopia present in the brains of offspring. These data show the potential of in vivo assessments and computational descriptions of biological responses to predict the development of this structural brain malformation and use of qAOP approach to evaluate brain deficits that may result from exposure to other TH disruptors.

Engineering human cell spheroids to model embryonic tissue fusion in vitro.

Epithelial-mesenchymal interactions drive embryonic fusion events during development and upon perturbation can result in birth defects. Cleft palate and neural tube defects can result from genetic defects or environmental exposures during development, yet very little is known about the effect of chemical exposures on fusion defects in humans because of the lack of relevant and robust human in vitro assays of developmental fusion behavior. Given the etiology and prevalence of cleft palate and the relatively simple architecture and composition of the embryonic palate, we sought to develop a three-dimensional culture system that could be used to study fusion behavior in vitro using human cells. We engineered human Wharton’s Jelly stromal cell (HWJSC) spheroids of defined size and established that 7 days of culture in osteogenesis differentiation medium was sufficient to promote an osteogenic phenotype consistent with embryonic palatal mesenchyme. HWJSC spheroids supported the attachment of human epidermal keratinocyte progenitor cells on the outer spheroid surface likely through deposition of collagens I and IV, fibronectin, and laminin, and co-cultured spheroids exhibited fusion behavior that was dependent on epidermal growth factor signaling and fibroblast growth factor signaling in agreement with palate fusion literature. The method described here may broadly apply to the generation of three-dimensional epithelial-mesenchymal co-cultures to study developmental fusion events in a format that is amenable to predictive toxicology applications.

Deriving Predicted No-Effect Concentrations in Diverse Geographies for use in eco-TTC Estimations

cological Thresholds for Toxicologic Concern (eco-TTC) employs an assessment of distributions of Predicted No-Effect Concentrations (PNECs) for compounds following chemical grouping. Grouping can be by mode of action, structural fragments, or by chemical functional use. Thus, eco-TTCs summarize the wealth of ecotoxicological information as probability distributions of PNECs and the 5th percentile lower value is chosen to represent the eco-TTC per se. Ecotoxicological hazards for untested chemicals, grouped using the same attributes, could be conservatively estimated. PNEC determinations vary fundamentally by regulatory jurisdiction. Application factors assigned to different levels of ecotoxicological data (species breadth, acute or chronic toxicity) result in different extrapolations for a potential “safe concentration” of a chemical. We compared PNECs derived by US and European environmental regulatory PNEC approaches in detail for ~5000 compounds and Japan and Canadian environmental PNEC approaches for a subset of these. Algorithms were written in R for US and Europe PNEC processes, then implemented into an eco-TTC web application as envisioned in Belanger et al. (2015). Cumulative PNEC probability distributions for European, Canadian, and Japan approaches are somewhat more conservative than the US approach driven principally by smaller assessment factors applied to data sets at earlier stages of hazard assessment. For example, the AF for the US when a full toxicity data set is available for all 3 trophic levels and a chronic test is available on the most sensitive acute species is 10; however, in other jurisdictions this may be as high as 100. On average, European PNECs were 11 times more conservative than US PNECs. PNEC distributions across geographies are driven by the large number of compounds that lack full chronic toxicity data. All assessments derive similar PNECs when full chronic toxicity data sets are available but this is only ~5% of cases encountered. The PNEC derivation logic, embedded in the eco-TTC web application, will be a useful tool to allow assessors to quickly and consistently compare hazard extrapolations across geographies minimizing animal testing requirements and maximizing use of existing information.

Ecological Threshold for Toxicological Concern (eco-TTC): exploring the importance of non-standard species

The Threshold for Toxicological Concern (TTC) is well-established for assessing human safety of indirect food-contact substances and has been applied to a variety of endpoints. Recently, we have proposed an extension to the human safety TTC concept for environmental applications, termed the ecological TTC (eco-TTC). The strengths and limitations of an eco-TTC approach are still being investigated. Algal tests are an important component of chemical environmental risk assessments and are the most sensitive taxon approximately 50% of the time. The complete eco-TTC database contains approximately 120,000 toxicological records (tests) employing some 2500 different species. Further, the eco-TTC database contains over 14,000 curated records from 300 unique algal species dominated by standard test species such as the green algal genera Pseudokirchneriella, Scenedesmus, and Desmodesmus, the marine Skeletonema and Phaeodactylum and the blue-green Microcystis and Anabaena. Here, we explore how hazard values for final PNEC derivation may change with the inclusion of standard and non-standard algal test species supported by analyses of eco-TTC and USEPA Web-ICE (Web-based Inter-species Correlation Estimation) applications. An eco-TTC derived hazard value will also be compared against an algal SSD for data rich chemicals such as cadmium chloride, triclosan, and a cationic surfactant. This work was performed with input from the HESI Animal Alternatives in ERA Technical Committee. * Disclaimer: The views, conclusions and recommendations expressed in this article are those of the author and do not necessarily represent views or policies of the US Environmental Protection Agency

Impaired swim bladder inflation in early-life stage fathead minnows exposed to a deiodinase inhibitor, iopanoic acid (article)

The present study investigated whether inhibition of deiodinase, the enzyme which converts thyroxine (T4) to the more biologically-active form, 3,5,3′-triiodothyronine (T3), would impact inflation of the posterior and/or anterior chamber of the swim bladder, processes previously demonstrated to be thyroid-hormone regulated. Two experiments were conducted using a model deiodinase inhibitor, iopanoic acid (IOP). In the first study, fathead minnow (Pimephales promelas) embryos were exposed to 0.6, 1.9, or 6.0 mg IOP/L or control water in a flow-through system until reaching 6 days post-fertilization (dpf) at which time posterior swim bladder inflation was assessed. To examine effects on anterior swim bladder inflation, a second study was conducted with 6 dpf larvae exposed to the same IOP concentrations until reaching 21 dpf. Fish from both studies were sampled for T4/T3 measurements, gene transcription analyses, and thyroid histopathology. In the embryo study, incidence and length of inflated posterior swim bladders were significantly reduced in the 6.0 mg/L treatment at 6 dpf. Incidence of inflation and length of anterior swim bladder in larval fish were significantly reduced in all IOP treatments at 14 dpf, but inflation recovered by 18 dpf. Throughout the larval study, whole body T4 concentrations were significantly increased and T3 concentrations were significantly decreased in all IOP treatments. Consistent with hypothesized compensatory responses, significant up-regulation of deiodinase-2 mRNA was observed in the larval study, and down-regulation of thyroperoxidase mRNA was observed in all IOP treatments in both studies. Taken together, these results support the hypothesized adverse outcome pathways linking inhibition of deiodinase activity to impaired swim bladder inflation.

Extrapolation of mammalian-based ToxCast assay results to non-mammalian species to evaluate endocrine disruption

In vitro high-throughput screening (HTS) and in silico technologies have emerged as 21st century tools for chemical hazard identification. In 2007 the U.S. Environmental Protection Agency (EPA) launched the ToxCast Program, which has screened thousands of chemicals in hundreds of (primarily) mammalian-based HTS assays for biological activity suggestive of potential toxic effects. Data generated through this effort are being used to prioritize toxicity testing on chemicals most likely to lead to adverse health effects. To realize the full potential of the ToxCast data for predicting adverse effects to both humans and wildlife, it is necessary to understand how broadly these data may plausibly be extrapolated across species. Therefore, the U.S. EPA Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was used to assess conservation of the 460 protein targets represented in the ToxCast assay suite. The SeqAPASS query sequence was selected based on the model organism used in the ToxCast assay (e.g., human, cattle, chimpanzee, guinea pig, rabbit, rat, mouse, pig, or sheep). Similarity of primary amino acid sequences and sequences from appropriate functional domains were compared across species to understand conservation of each assay target across taxa and probe questions of species extrapolation. To demonstrate the applicability of the SeqAPASS data for extrapolation of ToxCast targets, we developed case studies focused on the extrapolation of targets being evaluated as a component of the Endocrine Disruptor Screening Program, including the androgen receptor, enzymes involved in steroidogenesis, and proteins in thyroid axis function. These case studies demonstrate the utility of SeqAPASS for informing the extrapolation of HTS data and identification of model organisms likely to be suitable for follow-up or complementary in vivo toxicity tests.

SeqAPASS: Predicting chemical susceptibility to threatened/endangered species

Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS; application was developed to simplify, streamline, and quantitatively assess protein sequence/structural similarity across taxonomic groups as a means to predict relative intrinsic susceptibility. The intent of the tool is to allow for evaluation of any potential protein target while remaining amenable to variable degrees of protein characterization, in the context of available information about the chemical/protein interaction and the molecular target itself. To accommodate this flexibility in the analysis, three levels of evaluation were developed. The first level of the SeqAPASS analysis compares primary amino acid sequences to a query sequence, calculating a metric for sequence similarity (including detection of orthologs); the second level evaluates sequence similarity within selected functional domains (e.g., ligand-binding domain); and the third level of analysis compares individual amino acid residue positions of importance for protein conformation and/or interaction with the chemical upon binding. Each level of the SeqAPASS analysis provides additional evidence to apply toward rapid, screening-level assessments of probable cross species susceptibility. Such analysis can provide valuable insights as to the potential chemical susceptibility of such species lacking empirical toxicity test data such as the case with threatened and endangered species. To better understand the potential for chemicals to act on threatened and endangered species, a case study was developed demonstrating how SeqAPASS can be used to evaluate the potential susceptibility of endangered butterfly to molt-accelerating compounds.

Space, time, and chemical risk assessment

Exposure to manufactured chemicals is a fact of contemporary life for both humans and wildlife. In many cases, these exposures occur at safe environmental concentrations. However, spectacular exceptions have occurred (e.g., DDT and eggshell thinning, monocrotophos and Swainson’s Hawk mortality). USEPA is responsible for ensuring that regulated chemicals used in accordance with their labeling will not pose risks to humans or wildlife. This is done through a process called Ecological Risk Assessment. I will describe how USEPA conducts Ecological Risk Assessment for birds potentially exposed to pesticides, focusing on spatio-temporal considerations in the Risk Assessment process. I will also describe recent research on new ecological models for population-level risk assessment at USEPA.

Simultaneous analysis of fourteen endogenous steroid hormones by liquid chromatography tandem mass spectrometry with atmospheric pressure photoionization

Product Description: To understand how some chemicals affect the endocrine system, controlled lab experiments often monitor how chemicals impact natural steroid hormones in fish. Current methods can target only one or two hormones in a single sample, limiting the information that can be obtained. A new method was developed to identify fourteen steroid hormones in a single sample. Using this method in toxicity testing will aid our understanding of how chemicals induce toxic effects along the endocrine axis of vertebrates.
Abstract: Exposure to endocrine active chemicals can lead to perturbations of the hypothalamic-pituitary-gonadal (HPG) axis, ultimately leading to adverse reproductive or developmental effects. To evaluate potential effects, studies with possible HPG-active chemicals often rely on radioimmunoassay (RIA) for determination of biologically-active steroids and their precursors in biological matrices. While RIAs provide high sensitivity, there is potential for cross reactivity of antibodies, and assays are limited to a single steroid. To address these limitations, in the present study analytical methods were developed for the simultaneous analysis of fourteen steroid hormones including androgens, estrogens, progestogens, and glucocorticoids by liquid chromatography tandem mass spectrometry (LC-MS/MS). Atmospheric pressure photoionization (APPI) with a toluene dopant was utilized to allow ionization of all compounds in positive ionization mode without the need for derivatization. This method was applied to the analysis of fathead minnow (Pimephales promelas) plasma and exposure tank water from zebrafish (Danio rerio) experiments. Application to tank water analysis during flow-through chemical exposures provides a possible non-invasive endpoint for time-course experiments. The method demonstrated high sensitivity in both matrices with detection limits of most steroids at low µg/L in plasma and sub ng/L in water. Application of this method to aquatic vertebrate toxicity testing will lead to better understanding of specific mechanisms of HPG axis disruption and inform development of adverse outcome pathways (AOPs). The contents of this presentation neither constitute nor necessarily reflect US EPA policy.

From conceptual diagram to regulatory model. Is the science the easy part?

Many, if not most, ecological models developed for chemical risk assessment have not been (and will never be?) adopted for routine use by public agencies. There may be many valid reasons for this: 1) models are often published as “case studies” giving little insight into how they could be routinely applied under varying conditions, 2) model complexity is not commensurate with either the objectives of a specific regulatory risk assessment or available data, 3) lack of guidance about uncertainties associated with decisions made using the proposed model, 4) model output is not provided in a format that is useful for risk assessment, 5) time and expertise required for adoption and use of the model by a regulatory agency is greater than the perceived value added through model use. Nevertheless, calls for the adoption and use of population models in ecological risk assessment have been ongoing for many decades. We will explore some of the reasons why population models have been rarely used in ecological risk assessment at USEPA. Using the MCnest model as an example, we will also explore the factors that led to its formal adoption as a tool for avian population-level ecological risk assessment by the Office of Pesticide Programs at USEPA, a process that took at least 12 years from inception to adoption. Our goal is to initiate an ongoing discussion about the types of collaboration that lead to successful adoption of models as tools for regulatory risk assessment.

Addressing species diversity in biotransformation: Variability in expressed transcripts of Phase I and II hepatic enzymes among fishes

The ability of an organism to metabolize a pollutant is critical to understanding the risk the chemical poses to the organism. In the environment, fish are uniquely exposed to pollutants found in agricultural runoff and discharges from industry and wastewater treatment plants. Most research on chemical toxicity in fish rely on a few model fish species, like the zebrafish. For other fish, scientists make predictions of pollutant effects based on the model species. However, fish are extremely diverse. There is already good evidence that fish possess very different metabolizing enzymes which act on specific types of pollutants, making predictions of chemical toxicity challenging. This study examines the variability in metabolizing enzymes found among diverse fish species, including: model species, endangered species (e.g., American eel), species which have changed very little over time (e.g., sturgeon), and the most highly-evolved species (e.g., pufferfish). There is increasing evidence that diverse xenobiotic metabolizing enzymes exist among fishes, potentially resulting in different chemical sensitivities and accumulation, but this has never been systematically evaluated. One concern is that model test species such as rainbow trout, zebrafish and fathead minnows may not adequately represent the xenobiotic metabolizing capacity of other fish species. Our current study mined available fish liver transcriptome data and performed full-transcript, isoform sequencing on liver samples from two dozen phylogenetically diverse fish species. This novel RNAseq approach eliminated the need for transcriptome reconstruction resulting in reference genomes of the highest precision, allowing for detection of enzyme isoform orthologs among the species, as well as the nuclear receptors that control expression of the enzymes. Species were selected for broad phylogenetic coverage, as well as economic, research, and conservation importance, and included: sea lamprey (Petromyzon marinus), lake sturgeon (Acipenser fluvenscens), American eel (Anguilla rostrate), alligator gar (Atractosteus spatula), paddlefish (Polyodon spathula), rainbow trout (Oncorhynchus mykiss), rainbow smelt (Osmerus mordax), fathead minnow (Pimephales promelas), Antarctic icefish (Trematomus loennbergii), common carp (Cyprinus carpio), and channel catfish (Ictalurus punctatus). In addition to comparing information across fish species, the resolved isoforms were compared to human xenobiotic metabolizing enzymes. This comparison aids in evaluating the utility of human-based biotransformation tools such as ToxCast chemical screening assays or metabolism prediction software for potential relevance in fish. The content of this presentation neither constitute nor necessarily reflect US EPA policy..

Can avian reproductive outcomes estimated with MCnest be made more robust using stochastic parameterizations?

The Markov chain nest productivity model, or MCnest, is a set of algorithms for integrating the results of avian toxicity tests with reproductive life-history data to project the relative magnitude of chemical effects on avian reproduction. The mathematical foundation of MCnest is in the analysis of Markov chains, which provides a flexible template for modeling the variation in avian breeding cycles among species. MCnest quantitatively estimates the relative change in the number of successfully fledged broods per female per year of avian species exposed to a specific pesticide application scenario. The relative change in the number of successful broods is estimated by comparing model results based on a defined pesticide application scenario with a no-pesticide scenario. MCnest requires data from avian toxicity tests, avian species life-history profiles and a pesticide-use scenario that defines the timing and temporal pattern of exposures. In addition, MCnest uses algorithms from the USEPA Office of Pesticide Programs Terrestrial Residue EXposure model or T-REX to translate the application rate (expressed as pounds AI/acre) into doses (expressed as mg/kg body wt./day) for both adult and juveniles taking into account the species typical diet. Under ideal circumstances, McNest estimates would be reflected in similar real world occurrences in terms of species reproductive outcomes following pesticide exposures. Validation of model estimated outcomes versus empirical data can however be difficult, particularly in light of the use of deterministic input of sensitive parameters. The goal of the current analysis is to employ a stochastic approach to model parameterization in terms of toxicity endpoints, life history variability, exposure timing and magnitude in order to present a robust profile of avian reproductive outcomes as a function of variability in selected sensitive input parameters.

Air Pollution and Insulin Resistance: Do All Roads Lead to Rome?

The World Health Organization estimates that worldwide in 2012, nearly 7 million deaths occurred prematurely due to air pollution (1). In addition to respiratory and cardiovascular diseases, air pollution exposure is also linked to increased incidence of diabetes (2). Notably, the prevalence of diabetes and dyslipidemia escalated exponentially in the latter half of the 20th century coincident with the manufacture, use, and release of massive amounts of chemicals and pollution. The increase in the prevalence of these chronic conditions also coincides with an increase in sedentary lifestyles, calorie-rich diets, and human stress. Together, these factors contribute to metabolic disease. This complex tapestry suggests that many elements, including air pollution, are likely involved in an interactive manner to increase the risk of certain health cond1t1ons. Determining how air pollution might be linked to diabetes is useful not only in understanding how environmental factors contribute to the pathogenesis of this disease but also for identifying molecular targets for potential therapeutic strategies. Improved understanding of this dynamic also provides further rationale for improving air quality standards and public health.Ozone is produced in the air by photochemical reaction of components of anthropogenic emissions, and it contributes substantially to the societal burden of respiratory and cardiovascular disease. The pulmonary effects of ozone have been studied for decades (3), with recent attention turning to the metabolic and cardiovascular effects of this exposure.

NSF-funded scientists to present on long-term ecological research findings at AGU fall meeting

A salt marsh

Find related stories on NSF’s Long-Term Ecological Research Program at this link.

Hurricanes Harvey, Irma and Maria this fall. Wildfires that raged across California and British Columbia this summer. Unseasonable cold snaps in South Florida in past winters. How do such events shape and re-shape ecosystems?

And how do events from past decades affect the ways in which

More at

This is an NSF News item.


Epidemiological and experimental data suggest that obesity exacerbates the health effects of air pollutants such as ozone (O3). Maternal inactivity and calorically rich diets lead to offspring that show signs of obesity. Exacerbated O3 susceptibility of offspring could thus be manifested by maternal obesity. Thirty-day old female Long-Evans rats were fed a control (CD) or high fat (HF) (60% calories) diet for 6 wks and then bred. GD1 rats were then housed with a running wheel (RW) or without a wheel (SED) until parturition, creating 4 groups of offspring: CD-SED, CD-RW, HF-SED, and HF-RW. HF diet was terminated at PND 35 and all offspring were placed on CD. Body weight and %fat of dams were greatest in order; HF-SED>HF-RW>CD-SED>CD-RW. Adult offspring were exposed to O3 for 2 consecutive days (0.8 ppm, 4 hr/day). Glucose tolerance tests (GTT), ventilatory parameters (plethysmography), and bronchoalveolar fluid (BALF) cell counts and protein biomarkers were performed to assess response to O3. Exercise and diet altered body weight and %fat of young offspring. GTT, ventilation, and BALF cell counts were exacerbated by O3 with responses markedly exacerbated in males. HF diet and O3 led to significant exacerbation of several BALF parameters: Total cell count, neutrophils, and lymphocytes were increased in male HF-SED vs. CD-SED. Males were hyperglycemic after O3 exposure and exhibited exacerbated GTT responses. Ventilatory dysfunction was also exacerbated in males. Maternal exercise had minimal effects on O3 response. The results of this exploratory study suggest a link between maternal obesity and susceptibility to O3 in their adult offspring in a sex-specific manner.