A platform for rapid characterization of metabolic disrupters in whole animals

描述(由申请人提供)：一个快速描述整个动物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扰乱生物体的内部环境，产生化学应激，这可能对发育、行为和能量利用产生重大后果。特殊的环境毒物会破坏新陈代谢的动态平衡，导致全身脂肪堆积，最终导致肥胖。呈现给生物体的大量环境条件使得很难确定“肥胖”生物学中作为脂肪积累衡量标准的因果关系。 总体而言，动物的范围有限，表现情感的时间线非常长。一个准确定义化合物致肥胖潜力的系统将极大地促进对普遍存在的令人担忧的环境污染物的检测和机理描述。在这个RFA中，我们努力以高通量的方式筛选可疑的肥胖原化合物文库，并与以前在线虫中发现的代谢干扰物进行比较。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肥胖途径的新型工具。利用这项研究得出的新指标，我们可以对剂量效应、合成肥胖原相互作用进行自动化高通量筛选，并展示代谢敏化遗传背景对脂肪积累的影响。最终，我们将对肥胖的影响进行丰富的描述，并建立一种预测方法，以评估未来化学毒物倾向于影响脂肪代谢、诱导代谢综合征和或产生胰岛素抵抗的倾向。

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.