The purpose of this research is to unravel the substrate specificity and kinetic properties of an insect arylalkylamine N-acyltransferase from Bombyx mori (Bm-iAANAT) and to determine if this enzyme will catalyze the formation of long chain N-acylarylalkylamides in vitro. However, the determination of substrates and products for Bm-iAANAT in vitro is no guarantee that these same molecules are substrates and products for the enzyme in the organism. Therefore, RT-PCR was performed to detect the Bm-iAANAT transcripts and liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QToF-MS) analysis was performed on purified lipid extracts from B. mori larvae (fourth instar, Bmi4) to determine if long chain fatty acid amides are produced in B. mori. Ultimately, we found that recombinant Bm-iAANAT will utilize long-chain acyl-CoA thioesters as substrates and identified Bm-iAANAT transcripts and long-chain fatty acid amides in Bmi4. Together, these data show Bm-iAANAT will catalyze the formation of long-chain N-acylarylalkylamides in vitro and provide evidence demonstrating that Bm-iAANAT has a role in fatty acid amide biosynthesis in B. mori, as well.

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The US Environmental Protection Agency's ToxCast program has generated toxicity data for thousands of chemicals but does not adequately assess potential neurotoxicity. Networks of neurons grown on microelectrode arrays (MEAs) offer an efficient approach to screen compounds for neuroactivity and distinguish between compound effects on firing, bursting, and connectivity patterns. Previously, single concentrations of the ToxCast Phase II library were screened for effects on mean firing rate (MFR) in rat primary cortical networks. Here, we expand this approach by retesting 384 of those compounds (including 222 active in the previous screen) in concentration-response across 43 network activity parameters to evaluate neural network function. Using hierarchical clustering and machine learning methods on the full suite of chemicalparameter response data, we identified 15 network activity parameters crucial in characterizing activity of 237 compounds that were response actives ("hits"). Recognized neurotoxic compounds in this network function assay were often more potent compared to other ToxCast assays. Of these chemical-parameter responses, we identified three k-means clusters of chemical-parameter activity (i.e., multivariate MEA response patterns). Next, we evaluated the MEA clusters for enrichment of

Exposure to endocrine-disrupting chemicals (EDCs) is linked to myriad disorders, characterized by the disruption of the complex endocrine signaling pathways that govern development, physiology, and even behavior across the entire body. The mechanisms of endocrine disruption involve a complex system of pathways that communicate across the body to stimulate specific receptors that bind DNA and regulate the expression of a suite of genes. These mechanisms, including gene regulation, DNA binding, and protein binding, can be tied to differences in individual susceptibility across a genetically diverse population. In this review, we posit that EDCs causing such differential responses may be identified by looking for a signal of population variability after exposure. We begin by summarizing how the biology of EDCs has implications for genetically diverse populations. We then describe how gene-environment interactions (GxE) across the complex pathways of endocrine signaling could lead to differences in susceptibility. We survey examples in the literature of individual susceptibility differences to EDCs, pointing to a need for research in this area, especially regarding the exceedingly complex thyroid pathway. Following a discussion of experimental designs to better identify and study GxE across EDCs, we present a case study of a high-throughput screening signal of putative GxE within known endocrine disruptors. We conclude with a call for further, deeper analysis of the EDCs, particularly the thyroid disruptors, to identify if these chemicals participate in GxE leading to differences in susceptibility.

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