Growth of Alcaligenes eutrophus JMP134 on 2,4-dichlorophenoxyacetate requires a 2,4-dichlorophenol hydroxylase encoded by gene tfdB. Catabolism of either 2,4-dichlorophenoxyacetate or 3-chlorobenzoate involves enzymes encoded by the chlorocatechol oxidative operon consisting of tfdCDEF, which converts 3-chloro-and 3,5-dichlorocatechol to maleylacetate and chloromaleylacetate, respectively. Transposon mutagenesis has localized tfdB and t.fdCDEF to EcoRI fragment B of plasmid pJP4 (R. H. Don, A. J. Wieghtman, H.-J. Knackmuss, and K. N. Timmis, J. Bacteriol. 161:85-90, 1985). We present the complete nucleotide sequence of tfdB and tfdCDEF contained within a 7,954-base-pair HindIII-SstI fragment from EcoRI fragment B. Sequence and expression analysis of tfdB in Escherichia coli suggested that 2,4-dichlorophenol hydroxylase consists of a single subunit of 65 kilodaltons. The amino acid sequences of proteins encoded by tfdD and tfdE were found to be 63 and 53% identical to those of functionally similar enzymes encoded by clcB and ckD, respectively, from plasmid pAC27 of Pseudomonas putida. P. putida(pAC27) can utilize 3-chlorocatechol but not dichlorinated catechols. A region of DNA adjacent to clcD in pAC27 was found to be 47% identical in amino acid sequence to tfdiF, a gene important in catabolizing dichlorocatechols. The region in pAC27 does not appear to encode a protein, suggesting that the absence of a functional trans-chlorodienelactone isomerase may prevent P. putida(pAC27) from utilizing 3,5-dichlorocatechol.Bacteria play a crucial role in the dissimilation of environmental pollutants. In general, the catabolism of aromatic compounds is channeled through catechol intermediates (33). Hence, the ability of an organism to form and catabolize catechols or their derivatives can play a major part in the utilization of an aromatic compound. Comparison of the degradative pathways of different aromatics may help in understanding the evolution of growth substrate specificity.Chlorinated aromatics, such as 2,4-dichlorophenoxyacetic acid (2,4D) and 3-chlorobenzoate (3CBA), are catabolized via a modified ortho pathway (11,12,20,28,34,35; for a review, see reference 33). Pseudomonas putida plasmid pAC27, a deletion derivative of pAC25, confers catabolism of 3CBA (5), whereas Alcaligenes eutrophus JMP134 plasmid pJP4 enables degradation of both 2,4D and 3CBA (10, 11). In both cases, 3CBA appears to be degraded to 3-chlorocatechol by enzymes encoded by chromosomal genes. 2,4D is catabolized by A. eutrophus JMP134 to 2,4-dichlorophenol (2,4DCP) by 2,4D monooxygenase. 2,4DCP is then hydroxylated by 2,4DCP hydroxylase to form 3,5-dichlorocatechol (11; Fig. 1).3-Chlorocatechol is oxidized to maleylacetic acid by enzymes encoded by the clcABD operon in pAC27 (13) and by the tfdCDEF operon of pJP4 (11). The maleylacetic acid is then catabolized by chromosomally encoded enzymes (21). Enzymes involved in this transformation are chlorocatechol 1,2-dioxygenase (catechol 1,2-dioxygenase II or pyrocatechase II; EC 1.13.11.1), encoded b...

Toxicogenomics has provided innovative approaches to chemical screening, risk assessment, and predictive toxicology. If applied to ecotoxicology, genomics tools could greatly enhance the ability to understand the modes of toxicity in environmentally relevant organisms. Daphnia magna, a small aquatic crustacean, is considered a "keystone" species in ecological food webs and is an indicator species for toxicant exposure. Our objective was to demonstrate the potential utility of gene expression profiling in ecotoxicology by identifying novel biomarkers and uncovering potential modes of action in D. magna. Using a custom D. magna cDNA microarray, we identified distinct expression profiles in response to sublethal copper, cadmium, and zinc exposures and discovered specific biomarkers of exposure including two probable metallothioneins, and a ferritin mRNA with a functional IRE. The gene expression patterns support known mechanisms of metal toxicity and reveal novel modes of action including zinc inhibition of chitinase activity. By integrating gene expression profiling into an environmentally important organism, this study provides experimental support for the utility of ecotoxicogenomics.

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A quantitative adverse outcome pathway (qAOP) consists of one or more biologically based, computational models describing key event relationships linking a molecular initiating event (MIE) to an adverse outcome. A qAOP provides quantitative, dose-response, and time-course predictions that can support regulatory decision-making. Herein we describe several facets of qAOPs, including (a) motivation for development, (b) technical considerations, (c) evaluation of confidence, and (d) potential applications. The qAOP used as an illustrative example for these points describes the linkage between inhibition of cytochrome P450 19A aromatase (the MIE) and population-level decreases in the fathead minnow (FHM; Pimephales promelas). The qAOP consists of three linked computational models for the following: (a) the hypothalamic-pitutitary-gonadal axis in female FHMs, where aromatase inhibition decreases the conversion of testosterone to 17β-estradiol (E2), thereby reducing E2-dependent vitellogenin (VTG; egg yolk protein precursor) synthesis, (b) VTG-dependent egg development and spawning (fecundity), and (c) fecundity-dependent population trajectory. While development of the example qAOP was based on experiments with FHMs exposed to the aromatase inhibitor fadrozole, we also show how a toxic equivalence (TEQ) calculation allows use of the qAOP to predict effects of another, untested aromatase inhibitor, iprodione. While qAOP development can be resource-intensive, the quantitative predictions obtained, and TEQ-based application to multiple chemicals, may be sufficient to justify the cost for some applications in regulatory decision-making.

Ecotoxicogenomic approaches to environmental monitoring provide holistic information, offer insight into modes of action, and help to assess the causal agents and potential toxicity of effluents beyond the traditional end points of death and reproduction. Recent investigations of toxicant exposure indicate dose-dependent changes are a key issue in interpreting genomic studies. Additionally, there is interest in developing methods to integrate gene expression studies in environmental monitoring and regulation, and the No Observed Transcriptional Effect Level (NOTEL) has been proposed as a means for screening effluents and unknown chemicals for toxicity. However, computational methods to determine the NOTEL have yet to be established. Therefore, we examined effects on gene expression in Daphnia magna following exposure to Cu, Cd, and Zn over a range of concentrations including a tolerated, a sublethal, and a nearly acutely toxic concentration. Each concentration produced a distinct gene expression profile. We observed differential expression of a very few genes at tolerated concentrations that were distinct from the expression profiles observed at concentrations associated with toxicity. These results suggest that gene expression analysis may offer a strategy for distinguishing toxic and nontoxic concentrations of metals in the environment and provide support for a NOTEL for metal exposure in D. magna. Mechanistic insights could be inferred from the concentration-dependent gene expression profiles including metal specific effects on disparate metabolic processes such as digestion, immune response, development and reproduction, and less specific stress responses at higher concentrations.

In conjunction with the second International Environmental Omics Symposium (iEOS) conference, held at the University of Liverpool (United Kingdom) in September 2014, a workshop was held to bring together experts in toxicology and regulatory science from academia, government and industry. The purpose of the workshop was to review the specific roles that high-content omics datasets (eg, transcriptomics, metabolomics, lipidomics, and proteomics) can hold within the adverse outcome pathway (AOP) framework for supporting ecological and human health risk assessments. In light of the growing number of examples of the application of omics data in the context of ecological risk assessment, we considered how omics datasets might continue to support the AOP framework. In particular, the role of omics in identifying potential AOP molecular initiating events and providing supportive evidence of key events at different levels of biological organization and across taxonomic groups was discussed. Areas with potential for short and medium-term breakthroughs were also discussed, such as providing mechanistic evidence to support chemical read-across, providing weight of evidence information for mode of action assignment, understanding biological networks, and developing robust extrapolations of species-sensitivity. Key challenges that need to be addressed were considered, including the need for a cohesive approach towards experimental design, the lack of a mutually agreed framework to quantitatively link genes and pathways to key events, and the need for better interpretation of chemically induced changes at the molecular level. This article was developed to provide an overview of ecological risk assessment process and a perspective on how high content molecular-level datasets can support the future of assessment procedures through the AOP framework.

Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework provides a systematic approach for organizing knowledge that may support such inference. Likewise, computational models of biological systems at various scales provide another means and platform to integrate current biological understanding to facilitate inference and extrapolation. We argue that the systematic organization of knowledge into AOP frameworks can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment. This concept was explored as part of a workshop on AOP-Informed Predictive Modeling Approaches for Regulatory Toxicology held September 24–25, 2015. Examples of AOP-informed model development and its application to the assessment of chemicals for skin sensitization and multiple modes of endocrine disruption are provided. The role of problem formulation, not only as a critical phase of risk assessment, but also as guide for both AOP and complementary model development is described. Finally, a proposal for actively engaging the modeling community in AOP-informed computational model development is made. The contents serve as a vision for how AOPs can be leveraged to facilitate development of computational prediction models needed to support the next generation of chemical safety assessment.

There is increasing demand for the implementation of effectsbased monitoring and surveillance (EBMS) approaches in the Great Lakes Basin to complement traditional chemical monitoring. Herein, we describe an ongoing multiagency effort to develop and implement EBMS tools, particularly with regard to monitoring potentially toxic chemicals and assessing Areas of Concern (AOCs), as envisioned by the Great Lakes Restoration Initiative (GLRI). Our strategy includes use of both targeted and open-ended/discovery techniques, as appropriate to the amount of information available, to guide a priori end point and/or assay selection. Specifically, a combination of in vivo and in vitro tools is employed by using both wild and caged fish (in vivo), and a variety of receptor-and cell-based assays (in vitro). We employ a work flow that progressively emphasizes in vitro tools for long-term or high-intensity monitoring because of their greater practicality (e.g., lower cost, labor) and relying on in vivo assays for initial surveillance and verification. Our strategy takes advantage of the strengths of a diversity of tools, balancing the depth, breadth, and specificity of information they provide against their costs, transferability, and practicality. Finally, a series of illustrative scenarios is examined that align EBMS options with management goals to illustrate the adaptability and scaling of EBMS approaches and how they can be used in management decisions. Environmental Practice 15:409-426 (2013)