Ecotoxicogenomics: Microarray interlaboratory comparability

Perspectives on transcriptomics in animal physiology studies

Reductionist approaches in physiology and biochemistry are essential for understanding how animals cope and adapt to their environments. Transcriptomics is no longer restricted to a select few, and accessibility and affordability continue to facilitate its rapid growth as a science. More than 6000 publications (a conservative estimate) over the past decade quantify the response of the transcriptome to a wide breadth of questions in animal physiology. Transcriptomes have been quantified under conditions of hypoxia, climate change, salinity, drought, environmental pollution, and ultraviolet radiation among others; these studies have greatly improved understanding of the molecular machinery required for organismal adaptation. These "snapshots in time" however are never complete as the transcriptome is exquisitely sensitive to an individual's current physiologic state. Animal physiologists new to the field must recognize limitations of transcriptome technologies and consider experimental designs that strengthen physiologic interpretation. Current estimates suggest that a sample size of 6 or more are required for RNA-seq experiments in order to capture the majority of differentially expressed genes confidently. "Outside-the-box" approaches for statistical analyses of data derived from RNA-seq should be explored, as studies continue to point out that high false discoveries rates are pervasive with RNA-seq studies, reminiscent of the early days of microarrays. Incorporating biological variability, rather than reducing it (i.e. pooling strategies), into experimental designs is essential. Moreover, real-time PCR must not be viewed as a "validation step" to justify low samples sizes, but rather an orthogonal method to strengthen biological interpretation. The use of proper experimental controls in transcriptomics studies (i.e. spike-in controls and technical replication) are recommended and there is a pressing need for inter-laboratory tests (round robin experiments) to quantify repeatability and to identify sources of transcriptome variation within the context of animal physiology. Testing the reproducibility of transcriptome experiments in light of physiology in non-model organisms would be a significant contribution to the community. Single cell transcriptomics and multiplexing barcoding strategies such as decode-seq are poised to further advance the reductionist view of animal physiology; researchers are encouraged to consult literature herein and elsewhere for guidance on best practices and limitations of transcriptome technologies when studying the physiology of animals.

Omics Advances in Ecotoxicology

Toxic substances in the environment generate adverse effects at all levels of biological organization from the molecular level to community and ecosystem. Given this complexity, it is not surprising that ecotoxicologists have struggled to address the full consequences of toxic substance release at ecosystem level, due to the limits of observational and experimental tools to reveal the changes in deep structure at different levels of organization. -Omics technologies, consisting of genomics and ecogenomics, have the power to reveal, in unprecedented detail, the cellular processes of an individual or biodiversity of a community in response to environmental change with high sample/observation throughput. This represents a historic opportunity to transform the way we study toxic substances in ecosystems, through direct linkage of ecological effects with the systems biology of organisms. Three recent examples of -omics advance in the assessment of toxic substances are explored here: (1) the use of functional genomics in the discovery of novel molecular mechanisms of toxicity of chemicals in the environment; (2) the development of laboratory pipelines of dose-dependent, reduced transcriptomics to support high-throughput chemical testing at the biological pathway level; and (3) the use of eDNA metabarcoding approaches for assessing chemical effects on biological communities in mesocosm experiments and through direct observation in field monitoring. -Omics advances in ecotoxicological studies not only generate new knowledge regarding mechanisms of toxicity and environmental effect, improving the relevance and immediacy of laboratory toxicological assessment, but can provide a wholly new paradigm for ecotoxicology by linking ecological models to mechanism-based, systems biology approaches.

Are we closer to the vision? A proposed framework for incorporating omics into environmental assessments

Environmental science has benefited a great deal from omics-based technologies. High-throughput toxicology has defined adverse outcome pathways (AOPs), prioritized chemicals of concern, and identified novel actions of environmental chemicals. While many of these approaches are conducted under rigorous laboratory conditions, a significant challenge has been the interpretation of omics data in "real-world" exposure scenarios. Clarity in the interpretation of these data limits their use in environmental monitoring programs. In recent years, one overarching objective of many has been to address fundamental questions concerning experimental design and the robustness of data collected under the broad umbrella of environmental genomics. These questions include: (1) the likelihood that molecular profiles return to a predefined baseline level following remediation efforts, (2) how reference site selection in an urban environment influences interpretation of omics data and (3) what is the most appropriate species to monitor in the environment from an omics point of view. In addition, inter-genomics studies have been conducted to assess transcriptome reproducibility in toxicology studies. One lesson learned from inter-genomics studies is that there are core molecular networks that can be identified by multiple laboratories using the same platform. This supports the idea that "omics-networks" defined a priori may be a viable approach moving forward for evaluating environmental impacts over time. Both spatial and temporal variability in ecosystem structure is expected to influence molecular responses to environmental stressors, and it is important to recognize how these variables, as well as individual factor (i.e. sex, age, maturation), may confound interpretation of network responses to chemicals. This mini-review synthesizes the progress made towards adopting these tools into environmental monitoring and identifies future challenges to be addressed, as we move into the next era of high throughput sequencing. A conceptual framework for validating and incorporating molecular networks into environmental monitoring programs is proposed. As AOPs become more defined and their potential in environmental monitoring assessments becomes more recognized, the AOP framework may prove to be the conduit between omics and penultimate ecological responses for environmental risk assessments.

The Transcriptome of the Zebrafish Embryo After Chemical Exposure: A Meta-Analysis

Numerous studies have been published in the past years investigating the transcriptome of the zebrafish embryo (ZFE) upon being subjected to chemical stress. Aiming at a more mechanistic understanding of the results of such studies, knowledge about commonalities of transcript regulation in response to chemical stress is needed. Thus, our goal in this study was to identify and interpret genes and gene sets constituting a general response to chemical exposure. Therefore, we aggregated and reanalyzed published toxicogenomics data obtained with the ZFE. We found that overlap of differentially transcribed genes in response to chemical stress across independent studies is generally low and the most commonly differentially transcribed genes appear in less than 50% of all treatments across studies. However, effect size analysis revealed several genes showing a common trend of differential expression, among which genes related to calcium homeostasis emerged as key, especially in exposure settings up to 24 h post-fertilization. Additionally, we found that these and other downregulated genes are often linked to anatomical regions developing during the respective exposure period. Genes showing a trend of increased expression were, among others, linked to signaling pathways (e.g., Wnt, Fgf) as well as lysosomal structures and apoptosis. The findings of this study help to increase the understanding of chemical stress responses in the developing zebrafish embryo and provide a starting point to improve experimental designs for this model system. In future, improved time- and concentration-resolved experiments should offer better understanding of stress response patterns and access to mechanistic information.

Transcriptome analysis reveals novel insights into the response to Pb exposure in Phanerochaete chrysosporium

Metals released into the environment continue to be of concern for human health. Using white-rot fungi as biosorbents for heavy metals removal is an attractive alternative owing to its good performance and low cost. However, the molecular mechanism underlying heavy metal tolerance in white-rot fungi has not yet been fully elucidated. This study identified and analyzed the lead (Pb)-induced transcriptional changes in Phanerochaete chrysosporium, a well-known heavy metal hyperaccumulating white-rot fungus. The results confirmed its outstanding ability in Pb tolerance and effective defense system. By comparative analysis of gene expression profiles obtained from cDNA-amplified fragment length polymorphism (cDNA-AFLP), we isolated 43 transcript-derived fragments (TDFs) differentially regulated by Pb exposure in P. chrysosporium, and 23 TDFs presented significant similarities to genes encoding known or putative proteins which belong to different functional categories involving ion binding, energy and carbohydrate metabolism, and signal transduction. The detailed characterization of these Pb-responsive genes was presented and the expression patterns of some interesting genes were validated by quantitative RT-PCR. This work provides the first evidence of Pb-responsive genes along with their putatively functional annotations in P. chrysosporium, which may help to understand the mechanism underlying heavy metal accumulation and tolerance in P. chrysosporium.

Omics tools: New challenges in aquatic nanotoxicology?

In recent years, the implication of genomics into ecotoxicological studies has been studied closely to allow a better understanding of organism's responses to environmental contaminants including engineering nanomaterials (ENMs). ENMs are increasingly produced for various applications including cosmetics, electronics, sports equipment, biomedicine and agriculture. Because of their small size, ENMs possess chemical or physical characteristics improved compared to the corresponding macro-sized material. As their application expend, the release of manufactured ENMs into the environment is likely to increase and concern over impacts for the aquatic ecosystem is growing. Several studies reported deleterious effect of ENMs to aquatic organisms, but there is little information about the molecular mechanisms of toxicity. The development of ecotoxicogenomic approaches will improve the characterization of cellular and molecular modes of action of ENMs to aquatic organisms and allow a better prediction of contaminants toxicity. This paper presents an overview of transciptomic/proteomic studies in freshwater and marine organisms exposed to ENMs. Overall, induction of gene expression in relations to defense mechanisms, immune responses, growth and reproduction were measured after ENMs exposures of organisms, but with different patterns depending on exposure duration and concentrations used. In addition, some studies reported a positive correlation between gene expression and cellular modifications, but not at the individual level.

Estrogen-responsive gene networks in the teleost liver: What are the key molecular indicators?

An overarching goal of environmental genomics is to leverage sensitive suites of markers that are robust and reliable to assess biological responses in a range of species inhabiting variable environments. The objective of this study was to identify core groups of transcripts and molecular signaling pathways that respond to 17alpha-ethylinestadiol (EE2), a ubiquitous estrogenic contaminant, using transcriptome datasets generated from six independent laboratories. We sought to determine which biomarkers and gene networks were those most robust and reliably detected in multiple laboratories. Six laboratories conducted microarray analysis in pieces of the same liver from male fathead minnows exposed to ∼15ng/L EE2 for 96h. There were common transcriptional networks identified in every dataset. These included down-regulation of gene networks associated with blood clotting, complement activation, triglyceride storage, and xenobiotic metabolism. Noteworthy was that more than ∼85% of the gene networks were suppressed by EE2. Leveraging both these data and those mined from the Comparative Toxicogenomics Database (CTD), we narrowed in on an EE2-responsive transcriptional network. All transcripts in this network responded ∼±5-fold or more to EE2, increasing reliability of detection. This network included estrogen receptor alpha, transferrin, myeloid cell leukemia 1, insulin like growth factor 1, insulin like growth factor binding protein 2, and methionine adenosyltransferase 2A. This estrogen-responsive interactome has the advantage over single markers (e.g. vitellogenin) in that these entities are directly connected to each other based upon evidence of expression regulation and protein binding. Thus, it represents an interacting functional suite of estrogenic markers. Vitellogenin, the gold standard for estrogenic exposures, can show high individual variability in its response to estrogens, and the use of a multi-gene approach for estrogenic chemicals is expected to improve sensitivity. In our case, the coefficient of variation was significantly lowered by the gene network (∼67%) compared to Vtg alone, supporting the use of this transcriptional network as a sensitive alternative for detecting estrogenic effluents and chemicals. We propose that screening chemicals for estrogenicity using interacting genes within a defined expression network will improve sensitivity, accuracy, and reduce the number of animals required for endocrine disruption assessments.

How consistent are we? Interlaboratory comparison study in fathead minnows using the model estrogen 17α-ethinylestradiol to develop recommendations for environmental transcriptomics

Fundamental questions remain about the application of omics in environmental risk assessments, such as the consistency of data across laboratories. The objective of the present study was to determine the congruence of transcript data across 6 independent laboratories. Male fathead minnows were exposed to a measured concentration of 15.8 ng/L 17α-ethinylestradiol (EE2) for 96 h. Livers were divided equally and sent to the participating laboratories for transcriptomic analysis using the same fathead minnow microarray. Each laboratory was free to apply bioinformatics pipelines of its choice. There were 12 491 transcripts that were identified by one or more of the laboratories as responsive to EE2. Of these, 587 transcripts (4.7%) were detected by all laboratories. Mean overlap for differentially expressed genes among laboratories was approximately 50%, which improved to approximately 59.0% using a standardized analysis pipeline. The dynamic range of fold change estimates was variable between laboratories, but ranking transcripts by their relative fold difference resulted in a positive relationship for comparisons between any 2 laboratories (mean R²  > 0.9, p < 0.001). Ten estrogen-responsive genes encompassing a fold change range from dramatic (>20-fold; e.g., vitellogenin) to subtle (∼2-fold; i.e., block of proliferation 1) were identified as differentially expressed, suggesting that laboratories can consistently identify transcripts that are known a priori to be perturbed by a chemical stressor. Thus, attention should turn toward identifying core transcriptional networks using focused arrays for specific chemicals. In addition, agreed-on bioinformatics pipelines and the ranking of genes based on fold change (as opposed to p value) should be considered in environmental risk assessment. These recommendations are expected to improve comparisons across laboratories and advance the use of omics in regulations. Environ Toxicol Chem 2017;36:2593-2601. © 2017 SETAC.

Evolutionary toxicology in an omics world

Evolutionary toxicology is a young field that has grown rapidly in the past two decades. The potential of this field comes from the ability to link chemical contamination to multigenerational and population-wide effects in various species. The advancements and rapidly decreasing costs of -omic tools are improving the power and resolution of evolutionary toxicology studies. In this manuscript, we aim to address the trajectories and perspectives for conducting evolutionary toxicology studies with -omic approaches. We discuss the complementarity of using multiple -omic tools (genomics, eDNA, transcriptomics, proteomics, and metabolomics) for utility in understanding the toxicological relevance of adaptive responses in populations. In addition, we discuss phenotypic plasticity and its relevance to transcriptomic studies in toxicology. As evolutionary toxicology grows and expands its capacity to link toxicology with population-wide end points, we emphasize the applications of such studies in answering questions about ecological and population health, as well as future applicability to regulation. Thus, we aim to emphasize the enormous potential for evolutionary toxicology in an -omics world and give perspectives on the directions of future investigations.

From the exposome to mechanistic understanding of chemical-induced adverse effects

The exposome encompasses an individual's exposure to exogenous chemicals, as well as endogenous chemicals that are produced or altered in response to external stressors. While the exposome concept has been established for human health, its principles can be extended to include broader ecological issues. The assessment of exposure is tightly interlinked with hazard assessment. Here, we explore if mechanistic understanding of the causal links between exposure and adverse effects on human health and the environment can be improved by integrating the exposome approach with the adverse outcome pathway (AOP) concept that structures and organizes the sequence of biological events from an initial molecular interaction of a chemical with a biological target to an adverse outcome. Complementing exposome research with the AOP concept may facilitate a mechanistic understanding of stress-induced adverse effects, examine the relative contributions from various components of the exposome, determine the primary risk drivers in complex mixtures, and promote an integrative assessment of chemical risks for both human and environmental health.

Spotlight on environmental omics and toxicology: a long way in a short time

The applications for high throughput omics technologies in environmental science have increased dramatically in recent years. Transcriptomics, proteomics, and metabolomics have been used to study how chemicals in our environment affect both aquatic and terrestrial organisms, and the characterization of molecular initiating events is a significant goal in toxicology to better predict adverse responses to toxicants. This special journal edition demonstrates the scope of the science that leverages omics-based methods in both laboratory and wild populations within the context of environmental toxicology, ranging from fish to mammals. It is important to recognize that the environment comprises one axis of the One Health concept - the idea that human health is unequivocally intertwined to our environment and to the organisms that inhabit that environment. We have much to learn from a comparative approach, and studies that integrate the transcriptome, proteome, and the metabolome are expected to offer the most detailed mechanism-based adverse outcome pathways that are applicable for use in both environmental monitoring and risk assessment.