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We must rethink and test assumptions about relationships among biological research, security, and society

Legacy and current-use contaminants enter into and accumulate throughout the San Francisco Bay−Delta (Bay−Delta), and are present at concentrations with known effects on species important to this diverse watershed. There remains major uncertainty and a lack of focused research able to address and provide understanding of effects across multiple biological scales, despite previous and ongoing emphasis on the need for it. These needs are challenging specifically because of the established regulatory programs that often monitor on a chemical-by-chemical basis, or in which decisions are grounded in lethality-based endpoints. To best address issues of contaminants in the Bay−Delta, monitoring efforts should consider effects of environmentally relevant mixtures and sub-lethal impacts that can affect ecosystem health. These efforts need to consider the complex environment in the Bay−Delta including variable abiotic (e.g., temperature, salinity) and biotic (e.g., pathogens) factors. This calls for controlled and focused research, and the development of a multi-disciplinary contaminant monitoring and assessment program that provides information across biological scales. Information gained in this manner will contribute toward evaluating parameters that could alleviate ecologically detrimental outcomes. This review is a result of a Special Symposium convened at the University of California−Davis (UCD) on January 31, 2017 to address critical information needed on how contaminants affect the Bay−Delta. The UCD Symposium focused on new tools and approaches for assessing multiple stressor effects to freshwater and estuarine systems. Our approach is similar to the recently proposed framework laid out by the U.S. Environmental Protection Agency (USEPA) that uses weight of evidence to scale toxicological responses to chemical contaminants in a laboratory, and to guide the conservation of priority species and habitats. As such, we also aimed to recommend multiple endpoints that could be used to promote a multi-disciplinary understanding of contaminant risks in Bay−Delta while supporting management needs.

The Extreme Microbiome Project (XMP) is a project launched by the Association of Biomolecular Resource Facilities Metagenomics Research Group (ABRF MGRG) that focuses on whole genome shotgun sequencing of extreme and unique environments using a wide variety of biomolecular techniques. The goals are multifaceted, including development and refinement of new techniques for the following: 1) the detection and characterization of novel microbes, 2) the evaluation of nucleic acid techniques for extremophilic samples, and 3) the identification and implementation of the appropriate bioinformatics pipelines. Here, we highlight the different ongoing projects that we have been working on, as well as details on the various methods we use to characterize the microbiome and metagenome of these complex samples. In particular, we present data of a novel multienzyme extraction protocol that we developed, called Polyzyme or MetaPolyZyme. Presently, the XMP is characterizing sample sites around the world with the intent of discovering new species, genes, and gene clusters. Once a project site is complete, the resulting data will be publically available. Sites include Lake Hillier in Western Australia, the "Door to Hell" crater in Turkmenistan, deep ocean brine lakes of the Gulf of Mexico, deep ocean sediments from Greenland, permafrost tunnels in Alaska, ancient microbial biofilms from Antarctica, Blue Lagoon Iceland, Ethiopian toxic hot springs, and the acidic hypersaline ponds in Western Australia.

Interpretation of toxicogenomic experiments conducted with ovary tissue from asynchronous-spawning small fish species is complicated by background variation in the relative abundance and proportion of follicles at different stages within the ovary tissue sample. This study employed both real-time quantitative polymerase chain reaction and a 15,000 gene oligonucleotide microarray to examine variation in the fathead minnow (Pimephales promelas) ovarian transcriptional profile as a function of quantitative and qualitative differences in ovarian histology. The objectives were to provide data that could potentially aid interpretation of future toxicogenomics experiments, identify putative stage-related transcriptional markers, and generate insights into basic biological regulation of asynchronous oocyte development. Multiple lines of evidence from the present study indicate that variation in the transcriptional profile is primarily dependent on the relative abundance of previtellogenic versus vitellogenic follicles in the ovary. Due to the relatively small proportions of mature ovulated follicles or atretic follicles in the overall follicle population, few potential transcriptional markers of maturation, ovulation, or atresia could be identified. However, among the 460 differentially expressed genes identified in the present study, several targets, including HtrA serine peptidase 3 (htra3), tissue inhibitor of metalloproteinase 3 (timp3), aquaporin 8 (aqp8), transgelin 2 like (tagln2), Nedd4 family interacting protein 2 (ndfip2), chemokine ligand 12a (cxcl12a), midkine-related growth factor (mdka), and jagged 1b (jag 1b) exhibited responses and functional properties that support them as candidate molecular markers of significant shift in gross ovarian stage. Genes associated with a diversity of functions including cellular development, morphogenesis, coated vesicle transport, sexual reproduction, and neuron development, among others, were statistically enriched within the list of 460 genes differentially expressed among different ovarian classes. Overall, results of this study provide insights into background variation in ovary transcript profiles that should aid and enhance the interpretation of toxicogenomic data generated in experiments conducted with small, asynchronous-spawning fish species.

Abstract Background Interpreting proteomic and genomic data is a major challenge in predictive ecotoxicology that can be addressed by a systems biology approach. Mathematical modeling provides an organizational platform to consolidate protein dynamics with possible genomic regulation. Here, a model of ovarian steroidogenesis in the fathead minnow, Pimephales promelas, (FHM) is developed to evaluate possible transcriptional regulation of steroid production observed in microarray studies. Results The model was developed from literature sources, integrating key signaling components (G-protein and PKA activation) with their ensuing effect on steroid production. The model properly predicted trajectory behavior of estradiol and testosterone when fish were exposed to fadrozole, a specific aromatase inhibitor, but failed to predict the steroid hormone behavior occurring one week post-exposure as well as the increase in steroid levels when the stressor was removed. In vivo microarray data implicated three modes of regulation which may account for over-production of steroids during a depuration phase (when the stressor is removed): P450 enzyme up-regulation, inhibin down-regulation, and luteinizing hormone receptor up-regulation. Simulation studies and sensitivity analysis were used to evaluate each case as possible source of compensation to endocrine stress. Conclusions Simulation studies of the testosterone and estradiol response to regulation observed in microarray data supported the hypothesis that the FHM steroidogenesis network compensated for endocrine stress by modulating the sensitivity of the ovarian network to global cues coming from the hypothalamus and pituitary. Model predictions of luteinizing hormone receptor regulation were consistent with depuration and in vitro data. These results challenge the traditional approach to network elucidation in systems biology. Generally, the most sensitive interactions in a network are targeted for further elucidation but microarray evidence shows that homeostatic regulation of the steroidogenic network is likely maintained by a mildly sensitive interaction. We hypothesize that effective network elucidation must consider both the sensitivity of the target as well as the target's robustness to biological noise (in this case, to cross-talk) when identifying possible points of regulation.

Neurotransmitters such as dopamine play an important role in reproductive behaviors and signaling. Neuroendocrine-active chemicals in the environment have potential to interfere with and/or alter these processes. A companion study with the dopamine 2 receptor antagonist, haloperidol, found no evidence of a direct effect of the chemical on fish reproduction. This study considered haloperidol's potential effects on behavior and ovarian gene expression. Male fathead minnows exposed to 50 microg haloperidol/L for 96 h were found to be significantly more dominant than control males. In terms of molecular signaling, investigated using oligonucleotide microarrays, there was little similarity in the identity and functions of genes differentially expressed in the ovaries of fathead minnows (Pimephales promelas) versus zebrafish (Danio rerio) exposed under the same conditions. Results suggest that non-lethal concentrations of haloperidol do not induce ovarian molecular responses that could serve as biomarkers of exposure to D2R antagonists, but may impact behavior.

Neurotransmitters such as dopamine play an important role in regulating fish reproduction. However, the potential for neuroendocrine active chemicals to disrupt fish reproduction has not been well studied, despite emerging evidence of their discharge into aquatic environments. This study is the first to apply the fathead minnow 21 d reproduction assay developed for the US Endocrine Disruptor Screening Program to evaluate the reproductive toxicity of a model neuroendocrine active chemical, the dopamine 2 receptor antagonist, haloperidol. Continuous exposure to up to 20 imcrog haloperidol/L had no significant effects on fathead minnow fecundity, secondary sex characteristics, gonad histology, or plasma steroid and vitellogenin concentrations. The only significant effect observed was an increase in gonadotropin-releasing hormone (cGnRH) transcripts in the male brain. Results suggest that non-lethal concentrations of haloperidol do not directly impair fish reproduction. Potential effects of haloperidol on reproductive behaviors and gene expression were examined in a companion study.