Altered Larval Yellow Perch Swimming Behavior Due to Methylmercury and PCB126 Detected Using Hidden Markov Chain Models.

Fish swimming behavior is a commonly measured response in aquatic ecotoxicology because behavior is considered a whole organism-level effect that integrates many sensory systems. Recent advancements in animal behavior models, such as hidden Markov chain models (HMM), suggest an improved analytical approach for toxicology. Using both new and traditional approaches, we examined the sublethal effects of PCB126 and methylmercury on yellow perch (YP) larvae (Perca flavescens) using three doses. Both approaches indicate larvae increase activity after exposure to either chemical. The middle methylmercury-dosed larvae showed multiple altered behavior patterns. First, larvae had a general increase in activity, typically performing more behavior states, more time swimming, and more swimming bouts per second. Second, when larvae were in a slow or medium swimming state, these larvae tended to switch between these states more often. Third, larvae swam slower during the swimming bouts. The upper PCB126-dosed larvae exhibited a higher proportion and a fast swimming state, but the total time spent swimming fast decreased. The middle PCB126-dosed larvae transitioned from fast to slow swimming states less often than the control larvae. These results indicate that developmental exposure to very low doses of these neurotoxicants alters YP larvae overall swimming behaviors, suggesting neurodevelopment alteration.

Chronic aquatic toxicity of perfluorooctane sulfonic acid (PFOS) to Ceriodaphnia dubia, Chironomus dilutus, Danio rerio, and Hyalella azteca.

Perfluorooctane sulfonic acid (PFOS) is a ubiquitous and persistent contaminant in aquatic ecosystems. Chronic toxicity information for aquatic organisms is limited, therefore we conducted chronic PFOS toxicity tests for four model organisms commonly used for freshwater toxicology assays: Chironomus dilutus (midge), Ceriodaphnia dubia (water flea), Hyalella azteca (amphipod) and Danio rerio (zebrafish). The 16-day survival test with C. dilutus resulted in the lowest PFOS exposure concentrations to cause significant impacts, with reduced survival at 1 µg/L, a LC50 of 7.5 µg/L, and a growth EC10 of 1.5 µg/L. D. rerio was the next most sensitive species, with a 30-day LC50 of 490 µg/L and reduced growth at 260 µg/L. Effects for C. dubia and H. azteca occurred at concentrations a thousand-fold higher than for C. dilutus. H. azteca had a 42-day LC50 of 15 mg/L, an EC50 of 3.8 mg/L for reproduction (neonates per female) and an EC50 of 4.7 mg/L for growth. C. dubia was similarly tolerant of PFOS, with a 6-day LC50 of 20 mg/L for survival and an EC50 of 7 mg/L for reproduction (neonates per adult). H. azteca, C. dubia, and, to a lesser extent, D. rerio, appear tolerant of PFOS concentrations typically found in the environment. However, in agreement with previous studies, C. dilutus was particularly sensitive to PFOS exposure, with lethal and sublethal effects occurring at concentration levels present at highly contaminated sites.

Building biosecurity for synthetic biology.

The fast-paced field of synthetic biology is fundamentally changing the global biosecurity framework. Current biosecurity regulations and strategies are based on previous governance paradigms for pathogen-oriented security, recombinant DNA research, and broader concerns related to genetically modified organisms (GMOs). Many scholarly discussions and biosecurity practitioners are therefore concerned that synthetic biology outpaces established biosafety and biosecurity measures to prevent deliberate and malicious or inadvertent and accidental misuse of synthetic biology's processes or products. This commentary proposes three strategies to improve biosecurity: Security must be treated as an investment in the future applicability of the technology; social scientists and policy makers should be engaged early in technology development and forecasting; and coordination among global stakeholders is necessary to ensure acceptable levels of risk.

Regulation of endocrine systems by the microbiome: Perspectives from comparative animal models.

The microbiome regulates endocrine systems and influences many aspects of hormone signaling. Using examples from different animal taxa, we highlight the state of the science in microbiome research as it relates to endocrinology and endocrine disruption research. Using a comparative approach discussing fish, birds, and mammals, we demonstrate the bidirectional interaction between microbiota and hormone systems, presenting concepts that include (1) gastrointestinal microbiome regulation of the neuroendocrine feeding axis; (2) stress hormones and microbial communities; (3) the role of site-specific microbiota in animal reproduction; (4) microbiome effects on the neuroendocrine systems and behavior; and (5) novel mechanisms of endocrine disruption through the microbiome. This mini-review demonstrates that hormones can directly affect the richness and diversity of microbiota and conversely, microbiota can influence hormone production and mediate their functions in animals. In addition, microbiota can influence the action of a diverse range of neurotransmitters and neuropeptides in the central nervous system, which can lead to behavioral disruptions. As many animals have species-specific reproductive behaviors, it is important to understand how shifts in the microbiota relate to these complex interactions between sexes. This is especially important for captive animals on specialized diets, and there are significant implications for microbiome research in conservation and reproductive biology. For example, microbial metabolites may modify motility of gametes or modulate hormone-receptor interactions in reproductive tissues. Thus, efforts to incorporate metabolomics into the science of microbiome-endocrine relationships, both those produced by the host and those generated from microbial metabolism, are increasingly needed. These concepts have fostered an exciting emerging era in comparative endocrinology.

Predicting the Probability that a Chemical Causes Steatosis Using Adverse Outcome Pathway Bayesian Networks (AOPBNs).

Adverse outcome pathway Bayesian networks (AOPBNs) are a promising avenue for developing predictive toxicology and risk assessment tools based on adverse outcome pathways (AOPs). Here, we describe a process for developing AOPBNs. AOPBNs use causal networks and Bayesian statistics to integrate evidence across key events. In this article, we use our AOPBN to predict the occurrence of steatosis under different chemical exposures. Since it is an expert-driven model, we use external data (i.e., data not used for modeling) from the literature to validate predictions of the AOPBN model. The AOPBN accurately predicts steatosis for the chemicals from our external data. In addition, we demonstrate how end users can utilize the model to simulate the confidence (based on posterior probability) associated with predicting steatosis. We demonstrate how the network topology impacts predictions across the AOPBN, and how the AOPBN helps us identify the most informative key events that should be monitored for predicting steatosis. We close with a discussion of how the model can be used to predict potential effects of mixtures and how to model susceptible populations (e.g., where a mutation or stressor may change the conditional probability tables in the AOPBN). Using this approach for developing expert AOPBNs will facilitate the prediction of chemical toxicity, facilitate the identification of assay batteries, and greatly improve chemical hazard screening strategies.

Keanu: a novel visualization tool to explore biodiversity in metagenomes.

BACKGROUND: One of the main challenges when analyzing complex metagenomics data is the fact that large amounts of information need to be presented in a comprehensive and easy-to-navigate way. In the process of analyzing FASTQ sequencing data, visualizing which organisms are present in the data can be useful, especially with metagenomics data or data suspected to be contaminated. Here, we describe the development and application of a command-line tool, Keanu, for visualizing and exploring sample content in metagenomics data. We developed Keanu as an interactive tool to make viewing complex data easier. RESULTS: Keanu, a tool for exploring sequence content, helps a user to understand the presence and abundance of organisms in a sample by analyzing alignments against a database that contains taxonomy data and displaying them in an interactive web page. The content of a sample can be presented either as a collapsible tree, with node size indicating abundance, or as a bilevel partition graph, with arc size indicating abundance. Here, we illustrate how Keanu works by exploring shotgun metagenomics data from a sample collected from a bluff that contained paleosols and a krotovina in an alpine site in Ft. Greely, Alaska. CONCLUSIONS: Keanu provides a simple means by which researchers can explore and visualize species present in sequence data generated from complex communities and environments. Keanu is written in Python and is freely available at https://github.com/IGBB/keanu .

Development of Adverse Outcome Pathway for PPARγ Antagonism Leading to Pulmonary Fibrosis and Chemical Selection for Its Validation: ToxCast Database and a Deep Learning Artificial Neural Network Model-Based Approach.

Exposure to certain chemicals such as disinfectants through inhalation is suspected to be involved in the development of pulmonary fibrosis, a lung disease in which lung tissue becomes damaged and scarred. Pulmonary fibrosis is known to be regulated by transforming growth factor ß (TGF-ß) and peroxisome proliferator-activated receptor gamma (PPARγ). Here, we developed an adverse outcome pathway (AOP) to better define the linkage of PPARγ antagonism to the adverse outcome of pulmonary fibrosis. We then conducted a systematic analysis to identify potential chemicals involved in this AOP, using the ToxCast database and deep learning artificial neural network models. We identified chemicals bearing a potential inhalation hazard and exposure hazards from the database that could be related to this AOP. For chemicals that were not present in the ToxCast database, multilayer perceptron models were developed based on the ToxCast assays related to the AOP. The reactivity of ToxCast untested chemicals was then predicted using these deep learning models. Both approaches identified a set of chemicals that could be used to validate the AOP. This study suggests that chemicals categorized using an existing database such as ToxCast can be used to validate an AOP and that deep learning approaches can be used to characterize a range of potential active chemicals for an AOP of interest.

Exploring current read-across applications and needs among selected U.S. Federal Agencies.

Read-across is a well-established data gap-filling technique applied for regulatory purposes. In US Environmental Protection Agency's New Chemicals Program under TSCA, read-across has been used extensively for decades, however the extent of application and acceptance of read-across among U.S. federal agencies is less clear. In an effort to build read-across capacity, raise awareness of the state of the science, and work towards a harmonization of read-across approaches across U.S. agencies, a new read-across workgroup was established under the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM). This is one of several ad hoc groups ICCVAM has convened to implement the ICCVAM Strategic Roadmap. In this article, we outline the charge and scope of the workgroup and summarize the current applications, tools used, and needs of the agencies represented on the workgroup for read-across. Of the agencies surveyed, the Environmental Protection Agency had the greatest experience in using read-across whereas other agencies indicated that they would benefit from gaining a perspective of the landscape of the tools and available guidance. Two practical case studies are also described to illustrate how the read-across approaches applied by two agencies vary on account of decision context.

The clandestine organs of the endocrine system.

This review analyzes what could be regarded as the "clandestine organs" of the endocrine system: the gut microbiome, the immune system, and the stress system. The immune system is very closely related to the endocrine system, with many intertwined processes and signals. Many researchers now consider the microbiome as an 'organ' that affects the organism at many different levels. While stress is certainly not an organ, it affects so many processes, including endocrine-related processes, that the stress response system deserved a special section in this review. Understanding the connections, effects, and feedback mechanisms between the different "clandestine organs" and the endocrine system will provide us with a better understanding of how an organism functions, as well as reinforce the idea that there are no independent organs or systems, but a complex, interacting network of molecules, cells, tissues, signaling pathways, and mechanisms that constitute an individual.

Estrogen signaling through both membrane and nuclear receptors in the liver of fathead minnow.

Estradiol is a potent sex steroid hormone that controls reproduction and other cellular pathways in fish. It is known to regulate important proteins such as vitellogenin, the egg yolk precursor protein, and zona radiata proteins that form the eggshell for fish eggs. These proteins are made in the liver and transported out into the blood from where they are taken up into the ovary during oogenesis. Estradiol can exert its influence directly through soluble nuclear receptors (there are three in fish) or indirectly through membrane receptors and a phosphorylation cascade. Often there is coordination through both genomic and non-genomic pathways. We have used a toxicogenomics approach to determine the contribution of genomic and non-genomic regulation in the liver of fathead minnows exposed to 5ng ethinylestradiol per liter or to a mixture of 5ng ethinylestradiol and 100ng ZM189,154 (ZM) per liter. ZM has previously been shown to be a "perfect" antagonist for the fish nuclear estrogen receptors but has displayed agonistic activities for membrane receptors. We find that both nuclear and membrane receptors contribute to the biosynthesis of vitellogenin 1 and estrogen receptor one (Esr1), among others. In addition, lipid metabolism pathways appear to require both activities.

Prioritization of Contaminants of Emerging Concern in Wastewater Treatment Plant Discharges Using Chemical:Gene Interactions in Caged Fish.

We examined whether contaminants present in surface waters could be prioritized for further assessment by linking the presence of specific chemicals to gene expression changes in exposed fish. Fathead minnows were deployed in cages for 2, 4, or 8 days at three locations near two different wastewater treatment plant discharge sites in the Saint Louis Bay, Duluth, MN and one upstream reference site. The biological impact of 51 chemicals detected in the surface water of 133 targeted chemicals was determined using biochemical endpoints, exposure activity ratios for biological and estrogenic responses, known chemical:gene interactions from biological pathways and knowledge bases, and analysis of the covariance of ovary gene expression with surface water chemistry. Thirty-two chemicals were significantly linked by covariance with expressed genes. No estrogenic impact on biochemical endpoints was observed in male or female minnows. However, bisphenol A (BPA) was identified by chemical:gene covariation as the most impactful estrogenic chemical across all exposure sites. This was consistent with identification of estrogenic effects on gene expression, high BPA exposure activity ratios across all test sites, and historical analysis of the study area. Gene expression analysis also indicated the presence of nontargeted chemicals including chemotherapeutics consistent with a local hospital waste stream. Overall impacts on gene expression appeared to be related to changes in treatment plant function during rain events. This approach appears useful in examining the impacts of complex mixtures on fish and offers a potential route in linking chemical exposure to adverse outcomes that may reduce population sustainability.

Rapid effects of the aromatase inhibitor fadrozole on steroid production and gene expression in the ovary of female fathead minnows (Pimephales promelas).

Cytochrome P450 aromatase catalyzes conversion of C19 androgens to C18 estrogens and is critical for normal reproduction in female vertebrates. Fadrozole is a model aromatase inhibitor that has been shown to suppress estrogen production in the ovaries of fish. However, little is known about the early impacts of aromatase inhibition on steroid production and gene expression in fish. Adult female fathead minnows (Pimephales promelas) were exposed via water to 0, 5, or 50µg fadrozole/L for a time-course of 0.5, 1, 2, 4, and 6h, or 0 or 50µg fadrozole/L for a time-course of 6, 12, and 24h. We examined ex vivo ovarian 17ß-estradiol (E2) and testosterone (T) production, and plasma E2 concentrations from each study. Expression profiles of genes known or hypothesized to be impacted by fadrozole including aromatase (cytochrome P450 [cyp] 19a1a), steriodogenic acute regulatory protein (star), cytochrome P450 side-chain cleavage (cyp11a), cytochrome P450 17 alpha hydroxylase/17,20 lyase (cyp17), and follicle stimulating hormone receptor (fshr) were measured in the ovaries by quantitative real-time polymerase chain reaction (QPCR). In addition, broader ovarian gene expression was examined using a 15k fathead minnow microarray. The 5µg/L exposure significantly reduced ex vivo E2 production by 6h. In the 50µg/L treatment, ex vivo E2 production was significantly reduced after just 2h of exposure and remained depressed at all time-points examined through 24h. Plasma E2 concentrations were significantly reduced as early as 4h after initiation of exposure to either 5 or 50µg fadrozole/L and remained depressed throughout 24h in the 50µg/L exposure. Ex vivo T concentrations remained unchanged throughout the time-course. Expression of transcripts involved in steroidogenesis increased within the first 24h suggesting rapid induction of a mechanism to compensate for fadrozole inhibition of aromatase. Microarray results also showed fadrozole exposure caused concentration- and time-dependent changes in gene expression profiles in many HPG-axis pathways as early as 4h. This study provides insights into the very rapid effects of aromatase inhibition on steroidogenic processes in fish.

Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles.

BACKGROUND: A very large and rapidly growing collection of transcriptomic profiles in public repositories is potentially of great value to developing data-driven bioinformatics applications for toxicology/ecotoxicology. Modeled on human connectivity mapping (Cmap) in biomedical research, this study was undertaken to investigate the utility of an analogous Cmap approach in ecotoxicology. Over 3500 zebrafish (Danio rerio) and fathead minnow (Pimephales promelas) transcriptomic profiles, each associated with one of several dozen chemical treatment conditions, were compiled into three distinct collections of rank-ordered gene lists (ROGLs) by species and microarray platforms. Individual query signatures, each consisting of multiple gene probes differentially expressed in a chemical condition, were used to interrogate the reference ROGLs. RESULTS: Informative connections were established at high success rates within species when, as defined by their mechanisms of action (MOAs), both query signatures and ROGLs were associated with the same or similar chemicals. Thus, a simple query signature functioned effectively as an exposure biomarker without need for a time-consuming process of development and validation. More importantly, a large reference database of ROGLs also enabled a query signature to cross-interrogate other chemical conditions with overlapping MOAs, leading to novel groupings and subgroupings of seemingly unrelated chemicals at a finer resolution. This approach confirmed the identities of several estrogenic chemicals, as well as a polycyclic aromatic hydrocarbon and a neuro-toxin, in the largely uncharacterized water samples near several waste water treatment plants, and thus demonstrates its future potential utility in real world applications. CONCLUSIONS: The power of Cmap should grow as chemical coverages of ROGLs increase, making it a framework easily scalable in the future. The feasibility of toxicity extrapolation across fish species using Cmap needs more study, however, as more gene expression profiles linked to chemical conditions common to multiple fish species are needed.

Targeted Gene Expression in Zebrafish Exposed to Chlorpyrifos-Oxon Confirms Phenotype-Specific Mechanisms Leading to Adverse Outcomes.

Zebrafish models for mild, moderate, and severe acute organophosphorus poisoning were previously developed by exposing zebrafish larvae to chlopyrifos-oxon. The phenotype of these models was characterized at several levels of biological organization. Oxidative stress and mitochondrial dysfunction were found to be involved in the development of the more severe phenotype. Here we used targeted gene expression to understand the dose-responsiveness of those two pathways and their involvement on generating the different zebrafish models. As the severe phenotype is irreversible after only 3 h of exposure, we also analyzed the response of the oxidative stress pathway at 3 and 24 h. Some of the genes related to oxidative stress were already differentially expressed at 3 h. There was an increase in differentially expressed genes related to both oxidative stress and mitochondrial function from the more mild to the more severe phenotype, suggesting the involvement of these mechanisms in increasing phenotype severity. Temporal data suggest that peroxynitrite leading to lipid peroxidation might be involved in phenotype transition and irreversibility.

Are adverse outcome pathways here to stay?

Social pressure to minimize the use of animal testing and the ever-increasing concern on animal welfare, together with the need for more human-relevant and more predictive toxicity tests, are some of the drivers for new approaches to chemical screening. These approaches must also be able to accelerate the screening and assessment of the thousands of chemicals that are currently in use and in development for potential hazards to human and ecological health. Ideally, approaches are needed that decrease (or eliminate) animal testing while increasing predictivity. Efforts in many countries have focused on a toxicological pathway-based vision for human health assessments relying on in vitro systems and predictive models,1 vision equally applicable to ecological risk assessment.2 A pathway-based analysis of chemical effects opens numerous opportunities to apply nontraditional approaches for understanding the risks of chemical exposure. Conservation of molecular initiating and key events leading to adverse outcomes of regulatory concern provide a defensible framework for extrapolating chemical effects across species, even if the specific adverse outcomes differ between them.3.

Using transcriptomic tools to evaluate biological effects across effluent gradients at a diverse set of study sites in Minnesota, USA.

The aim of this study was to explore the utility of "omics" approaches in monitoring aquatic environments where complex, often unknown stressors make chemical-specific risk assessment untenable. We examined changes in the fathead minnow (Pimephales promelas) ovarian transcriptome following 4-day exposures conducted at three sites in Minnesota (MN, USA). Within each site, fish were exposed to water from three locations along a spatial gradient relative to a wastewater treatment plant (WWTP) discharge. After exposure, site-specific impacts on gene expression in ovaries were assessed. Using an intragradient point of comparison, biological responses specifically associated with the WWTP effluent were identified using functional enrichment analyses. Fish exposed to water from locations downstream of the effluent discharges exhibited many transcriptomic responses in common with those exposed to the effluent, indicating that effects of the discharge do not fully dissipate downstream. Functional analyses showed a range of biological pathways impacted through effluent exposure at all three sites. Several of those impacted pathways at each site could be linked to potential adverse reproductive outcomes associated with the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows, specifically signaling pathways associated with oocyte meiosis, TGF-beta signaling, gonadotropin-releasing hormone (GnRH) and epidermal growth factor receptor family (ErbB), and gene sets associated with cyclin B-1 and metalloproteinase. The utility of this approach comes from the ability to identify biological responses to pollutant exposure, particularly those that can be tied to adverse outcomes at the population level and those that identify molecular targets for future studies.

Differential effects and potential adverse outcomes of ionic silver and silver nanoparticles in vivo and in vitro.

Nanoparticles are of concern because of widespread use, but it is unclear if metal nanoparticles cause effects directly or indirectly. We explored whether polyvinylpyrrolidone-coated silver nanoparticles (PVP-AgNPs) cause effects through intact nanoparticles or dissolved silver. Females of the model species fathead minnow (Pimephales promelas) were exposed to either 4.8 µg/L of AgNO3 or 61.4 µg/L of PVP-AgNPs for 96h. Microarray analyses were used to identify impacted receptors and toxicity pathways in liver and brain tissues that were confirmed using in vitro mammalian assays. AgNO3 and PVP-AgNP exposed fish had common and distinct effects consistent with both intact nanoparticles and dissolved silver causing effects. PVP-AgNPs and AgNO3 both affected pathways involved in Na(+), K(+), and H(+) homeostasis and oxidative stress but different neurotoxicity pathways. In vivo effects were supported by PVP-AgNP activation of five in vitro nuclear receptor assays and inhibition of ligand binding to the dopamine receptor. AgNO3 inhibited ligand binding to adrenergic receptors α1 and α2 and cannabinoid receptor CB1, but had no effect in nuclear receptor assays. PVP-AgNPs have the potential to cause effects both through intact nanoparticles and metal ions, each interacting with different initiating events. Since the in vitro and in vivo assays examined here are commonly used in human and ecological hazard screening, this work suggests that environmental health assessments should consider effects of intact nanoparticles in addition to dissolved metals.

Endocrinology: advances through omics and related technologies.

The rapid development of new omics technologies to measure changes at genetic, transcriptomic, proteomic, and metabolomics levels together with the evolution of methods to analyze and integrate the data at a systems level are revolutionizing the study of biological processes. Here we discuss how new approaches using omics technologies have expanded our knowledge especially in nontraditional models. Our increasing knowledge of these interactions and evolutionary pathway conservation facilitates the use of nontraditional species, both invertebrate and vertebrate, as new model species for biological and endocrinology research. The increasing availability of technology to create organisms overexpressing key genes in endocrine function allows manipulation of complex regulatory networks such as growth hormone (GH) in transgenic fish where disregulation of GH production to produce larger fish has also permitted exploration of the role that GH plays in testis development, suggesting that it does so through interactions with insulin-like growth factors. The availability of omics tools to monitor changes at nearly any level in any organism, manipulate gene expression and behavior, and integrate data across biological levels, provides novel opportunities to explore endocrine function across many species and understand the complex roles that key genes play in different aspects of the endocrine function.

Integrated approach to explore the mechanisms of aromatase inhibition and recovery in fathead minnows (Pimephales promelas).

Aromatase, a member of the cytochrome P450 superfamily, is a key enzyme in estradiol synthesis that catalyzes the aromatization of androgens into estrogens in ovaries. Here, we used an integrated approach to assess the mechanistic basis of the direct effects of aromatase inhibition, as well as adaptation and recovery processes in fish. We exposed female fathead minnows (Pimephales promelas) via the water to 30 µg/L of a model aromatase inhibitor, fadrozole, during 8 days (exposure phase). Fish were then held in clean water for 8 more days (recovery phase). Samples were collected at 1, 2, 4, and 8 days of both the exposure and the recovery phases. Transcriptomics, metabolomics, and network inference were used to understand changes and infer connections at the transcript and metabolite level in the ovary. Apical endpoints directly indicative of endocrine function, such as plasma estradiol, testosterone, and vitellogenin levels were also measured. An integrated analysis of the data revealed changes in gene expression consistent with increased testosterone in fadrozole-exposed ovaries. Metabolites such as glycogen and taurine were strongly correlated with increased testosterone levels. Comparison of in vivo and ex vivo steroidogenesis data suggested the accumulation of steroidogenic enzymes, including aromatase, as a mechanism to compensate for aromatase inhibition.

Applying Adverse Outcome Pathways (AOPs) to support Integrated Approaches to Testing and Assessment (IATA).

Chemical regulation is challenged by the large number of chemicals requiring assessment for potential human health and environmental impacts. Current approaches are too resource intensive in terms of time, money and animal use to evaluate all chemicals under development or already on the market. The need for timely and robust decision making demands that regulatory toxicity testing becomes more cost-effective and efficient. One way to realize this goal is by being more strategic in directing testing resources; focusing on chemicals of highest concern, limiting testing to the most probable hazards, or targeting the most vulnerable species. Hypothesis driven Integrated Approaches to Testing and Assessment (IATA) have been proposed as practical solutions to such strategic testing. In parallel, the development of the Adverse Outcome Pathway (AOP) framework, which provides information on the causal links between a molecular initiating event (MIE), intermediate key events (KEs) and an adverse outcome (AO) of regulatory concern, offers the biological context to facilitate development of IATA for regulatory decision making. This manuscript summarizes discussions at the Workshop entitled "Advancing AOPs for Integrated Toxicology and Regulatory Applications" with particular focus on the role AOPs play in informing the development of IATA for different regulatory purposes.