A platform for rapid characterization of metabolic disrupters in whole animals

描述（由申请人提供）：用于快速表征整个动物中代谢干扰物的平台越来越多的证据表明，来自环境的化学毒物可以干扰生物体的内部环境，产生化学应激，这可能对发育，行为和能量利用产生重大影响。特定的环境毒物破坏代谢体内平衡，产生全身脂肪积聚并最终导致肥胖。生物体所面临的大量环境条件使得很难确定“肥胖”生物学中的因果关系作为脂肪积累的指标 在整个动物中，表现影响的范围有限，时间线非常长。一个准确定义化合物致肥胖潜力的系统将极大地促进无处不在和令人担忧的环境污染物的检测和机理描述。在本RFA中，我们奋进以高通量方式筛选可疑的肥胖化合物文库，并与先前在C.优雅我们将利用我们在化学筛选方面的专业知识来开发描述各种致肥胖途径的新工具。通过这项研究获得的新指标，我们可以对剂量效应、合成肥胖剂相互作用进行自动化高通量筛选，并证明代谢致敏遗传背景对脂肪蓄积的影响。最终，我们将产生一个丰富的描述obesogen的影响，并建立一个预测的方法来评估未来的化学毒物的偏好，影响脂质代谢，诱导代谢综合征和/或产生胰岛素抵抗。

DESCRIPTION (provided by applicant): A platform for rapid characterization of metabolic disrupters in whole animals Mounting evidence suggest that chemical toxicants from the environment can disturb the internal milieu of the organism, creating chemical stress, which can have major consequences to development, behavior and energy utilization. Particular environmental toxicants disrupt metabolic homeostasis producing systemic fat accumulation and ultimately obesity. The vast number of environmental conditions presented to an organism makes it difficult to determine causality in "obesogen" biology as the metrics for fat accumulation in whole animals are scope limited and timelines extremely long to manifest affect. A system that accurately defines obesogenic potential of chemical compounds would greatly facilitate the detection and mechanistic description of ubiquitous and worrisome environmental pollutants. In this RFA we endeavor to screen through suspected obesogen compound libraries in a high throughput manner and make comparison to previously discovered metabolic disrupters in C. elegans. We will use our expertise in chemical screens to develop novel tools that describe the variety of obesogenic pathways. With new metrics derived from this study we can perform automated high throughput screens for dose effects, synthetic obesogen interactions and demonstrate the effect of metabolically sensitized genetic backgrounds on fat accumulation. Ultimately we will produce a rich description of obesogen effects and build a predictive methodology for evaluating future chemical toxicants predilection to affect lipid metabolism, induce metabolic syndrome and or generate insulin resistance.