Later Life Consequences of Subteratogenic Exposure to a Complex PAH Mixture in the Atlantic Killifish (Fundulus heteroclitus)

Subteratogenic and other low-level chronic exposures to toxicant mixtures are an understudied threat to environmental and human health. It is especially important to understand the effects of these exposures for contaminants, such as polycyclic aromatic hydrocarbons (PAHs) a large group of more than 100 individual compounds, which are important environmental (including aquatic) contaminants. Aquatic sediments constitute a major sink for hydrophobic pollutants, and studies show PAHs can persist in sediments over time. Furthermore, estuarine systems (namely breeding grounds) are of particular concern, as they are highly impacted by a wide variety of pollutants, and estuarine fishes are often exposed to some of the highest levels of contaminants of any vertebrate taxon. Acute embryonic exposure to PAHs results in cardiac teratogenesis in fish, and early life exposure to certain individual PAHs and PAH mixtures cause heart alterations with decreased swimming capacity in adult fish. Consequently, the heart and cardiorespiratory system are thought to be targets of PAH mixture exposure. While many studies have investigated acute, teratogenic PAH exposures, few studies have longitudinally examined the impacts of subtle, subteratogenic PAH mixture exposures, which are arguably more broadly applicable to environmental contamination scenarios. The goal of this dissertation was to highlight the later-life consequences of early-life exposure to subteratogenic concentrations of a complex, environmentally relevant PAH mixture.

A unique population of Fundulus heteroclitus (the Atlantic killifish or mummichog, hereafter referred to as killifish), has adapted to creosote-based polycyclic aromatic hydrocarbons (PAHs) found at the Atlantic Wood Industries (AW) Superfund site in the southern branch of the Elizabeth River, VA, USA. This killifish population survives in a site heavily contaminated with a mixture of PAHs from former creosote operations. They have developed resistance to the acute toxicity and teratogenic effects caused by the mixture of PAHs in sediment from the site. The primary goal of this dissertation was to compare and contrast later-life outcomes of early-life, subteratogenic PAH mixture exposure in both the Atlantic Wood killifish (AW) and a naïve reference population of killifish from King’s Creek (KC; a relatively uncontaminated tributary of the Severn River, VA). Killifish from both populations were exposed to subteratogenic concentrations of a complex PAH-sediment extract, Elizabeth River Sediment Extract (ERSE), made by collecting sediment from the AW site. Fish were reared over a 5-month period in the laboratory, during which they were examined for a variety of molecular, physiological and behavioral responses.

The central aims of my dissertation were to determine alterations to embryonic gene expression, larval swimming activity, adult behavior, heart structure, enzyme activity, and swimming/cardiorespiratory performance following subteratogenic exposure to ERSE. I hypothesized that subteratogenic exposure to ERSE would impair cardiac ontogenic processes in a way that would be detectable via gene expression in embryos, and that the misregulation of cardiac genes would help to explain activity changes, behavioral deficits, and later-life swimming deficiencies. I also hypothesized that fish heart structure would be altered. In addition, I hypothesized that the AW killifish population would be resistant to developmental exposures and perform normally in later life challenges. To investigate these hypotheses, a series of experiments were carried out in PAH-adapted killifish from Elizabeth River and in reference killifish. As an ancillary project to the primary aims of the dissertation, I examined the toxicity of weaker aryl hydrocarbon receptor (AHR) agonists in combination with fluoranthene (FL), an inhibitor of cytochrome P4501A1 (CYP1A1). This side project was conducted in both Danio rerio (zebrafish) and the KC and AW killifish.

Embryonic gene expression was measured in both killifish populations over an ERSE dose response with multiple time points (12, 24, 48, and 144 hours post exposure). Genes known to play critical roles in cardiac structure/development, cardiac function, and angiogenesis were elevated, indicating cardiac damage and activation of cardiovascular repair mechanisms. These data helped to inform later-life swimming performance and cardiac histology studies. Behavior was assessed during light and dark cycles in larvae of both populations following developmental exposure to ERSE. While KC killifish showed activity differences following exposure, AW killifish showed no significant changes even at concentrations that would cause overt cardiac toxicity in KC killifish. Juvenile behavior experiments demonstrated hyperactivity following ERSE exposure in KC killifish, but no significant behavioral changes in AW killifish. Adult swimming performance via prolonged critical swimming capacity (Ucrit) demonstrated performance costs in the AW killifish. Furthermore, swimming performance decline was observed in KC killifish following exposure to increasing dilutions of ERSE. Lastly, cardiac histology suggested that early-life exposure to ERSE could result in cardiac structural alteration and extravasation of blood into the pericardial cavity.

Responses to AHR agonists resulted in a ranking of relative potency for agonists, and determined which agonists, when combined with FL, caused cardiac teratogenesis. These experiments showed interesting species differences for zebrafish and killifish. To probe mechanisms responsible for cardiotoxicity, a CYP1A-morpholino and a AHR2-morpholino were used to mimic FL effects or attempt to rescue cardiac deformities respectively. Findings suggested that the cardiac toxicity elicited by weak agonist + FL exposure was likely driven by AHR-independent mechanisms. These studies stand in contrast to previous research from our lab showing that moderate AHR agonist + FL caused cardiac toxicity that can be partially rescued by AHR-morpholino knockdown.

My findings will form better characterization of mechanisms of PAH toxicity, and advance our understanding of how subteratogenic mixtures of PAHs exert their toxic action in naïve killifish. Furthermore, these studies will provide a framework for investigating how subteratogenic exposures to PAH mixtures can impact aquatic organismal health and performance. Most importantly, these experiments have the potential to help inform risk assessment in fish, mammals, and potentially humans. Ultimately, this research will help protect populations exposed to subtle PAH-contamination.

Finite mixture distributions, sequential likelihood and the EM algorithm

A popular way to account for unobserved heterogeneity is to assume that the data are drawn from a finite mixture distribution. A barrier to using finite mixture models is that parameters that could previously be estimated in stages must now be estimated jointly: using mixture distributions destroys any additive separability of the log-likelihood function. We show, however, that an extension of the EM algorithm reintroduces additive separability, thus allowing one to estimate parameters sequentially during each maximization step. In establishing this result, we develop a broad class of estimators for mixture models. Returning to the likelihood problem, we show that, relative to full information maximum likelihood, our sequential estimator can generate large computational savings with little loss of efficiency.

Uncovering compounds by synergy of cluster expansion and high-throughput methods.

Predicting from first-principles calculations whether mixed metallic elements phase-separate or form ordered structures is a major challenge of current materials research. It can be partially addressed in cases where experiments suggest the underlying lattice is conserved, using cluster expansion (CE) and a variety of exhaustive evaluation or genetic search algorithms. Evolutionary algorithms have been recently introduced to search for stable off-lattice structures at fixed mixture compositions. The general off-lattice problem is still unsolved. We present an integrated approach of CE and high-throughput ab initio calculations (HT) applicable to the full range of compositions in binary systems where the constituent elements or the intermediate ordered structures have different lattice types. The HT method replaces the search algorithms by direct calculation of a moderate number of naturally occurring prototypes representing all crystal systems and guides CE calculations of derivative structures. This synergy achieves the precision of the CE and the guiding strengths of the HT. Its application to poorly characterized binary Hf systems, believed to be phase-separating, defines three classes of alloys where CE and HT complement each other to uncover new ordered structures.

Robust test method for time-course microarray experiments.

BACKGROUND: In a time-course microarray experiment, the expression level for each gene is observed across a number of time-points in order to characterize the temporal trajectories of the gene-expression profiles. For many of these experiments, the scientific aim is the identification of genes for which the trajectories depend on an experimental or phenotypic factor. There is an extensive recent body of literature on statistical methodology for addressing this analytical problem. Most of the existing methods are based on estimating the time-course trajectories using parametric or non-parametric mean regression methods. The sensitivity of these regression methods to outliers, an issue that is well documented in the statistical literature, should be of concern when analyzing microarray data. RESULTS: In this paper, we propose a robust testing method for identifying genes whose expression time profiles depend on a factor. Furthermore, we propose a multiple testing procedure to adjust for multiplicity. CONCLUSIONS: Through an extensive simulation study, we will illustrate the performance of our method. Finally, we will report the results from applying our method to a case study and discussing potential extensions.

Adaptive Mixture Modelling Metropolis Methods for Bayesian Analysis of Non-linear State-Space Models.

We describe a strategy for Markov chain Monte Carlo analysis of non-linear, non-Gaussian state-space models involving batch analysis for inference on dynamic, latent state variables and fixed model parameters. The key innovation is a Metropolis-Hastings method for the time series of state variables based on sequential approximation of filtering and smoothing densities using normal mixtures. These mixtures are propagated through the non-linearities using an accurate, local mixture approximation method, and we use a regenerating procedure to deal with potential degeneracy of mixture components. This provides accurate, direct approximations to sequential filtering and retrospective smoothing distributions, and hence a useful construction of global Metropolis proposal distributions for simulation of posteriors for the set of states. This analysis is embedded within a Gibbs sampler to include uncertain fixed parameters. We give an example motivated by an application in systems biology. Supplemental materials provide an example based on a stochastic volatility model as well as MATLAB code.

Task-driven adaptive statistical compressive sensing of gaussian mixture models

A framework for adaptive and non-adaptive statistical compressive sensing is developed, where a statistical model replaces the standard sparsity model of classical compressive sensing. We propose within this framework optimal task-specific sensing protocols specifically and jointly designed for classification and reconstruction. A two-step adaptive sensing paradigm is developed, where online sensing is applied to detect the signal class in the first step, followed by a reconstruction step adapted to the detected class and the observed samples. The approach is based on information theory, here tailored for Gaussian mixture models (GMMs), where an information-theoretic objective relationship between the sensed signals and a representation of the specific task of interest is maximized. Experimental results using synthetic signals, Landsat satellite attributes, and natural images of different sizes and with different noise levels show the improvements achieved using the proposed framework when compared to more standard sensing protocols. The underlying formulation can be applied beyond GMMs, at the price of higher mathematical and computational complexity. © 1991-2012 IEEE.

Overview of FEED, the feeding experiments end-user database.

The Feeding Experiments End-user Database (FEED) is a research tool developed by the Mammalian Feeding Working Group at the National Evolutionary Synthesis Center that permits synthetic, evolutionary analyses of the physiology of mammalian feeding. The tasks of the Working Group are to compile physiologic data sets into a uniform digital format stored at a central source, develop a standardized terminology for describing and organizing the data, and carry out a set of novel analyses using FEED. FEED contains raw physiologic data linked to extensive metadata. It serves as an archive for a large number of existing data sets and a repository for future data sets. The metadata are stored as text and images that describe experimental protocols, research subjects, and anatomical information. The metadata incorporate controlled vocabularies to allow consistent use of the terms used to describe and organize the physiologic data. The planned analyses address long-standing questions concerning the phylogenetic distribution of phenotypes involving muscle anatomy and feeding physiology among mammals, the presence and nature of motor pattern conservation in the mammalian feeding muscles, and the extent to which suckling constrains the evolution of feeding behavior in adult mammals. We expect FEED to be a growing digital archive that will facilitate new research into understanding the evolution of feeding anatomy.