MacMillan: Project 2; Technology and Research Development Project 2: FUSION (Macmillian)

摘要：天然产物和植物药领域的一个紧迫挑战是生物学特性 纯化合物、混合物和协同关系的研究。虽然发现的速度 有趣的新代谢物是高使用表型方法，目标识别的难度， 核查是一个难以克服的瓶颈。为了充分利用这个巨大的水库， 生物活性小分子需要开发高通量方法， 注释化学收藏品。对于植物药，通常有轶事证据证明它们的使用，在一些情况下， 临床评价的主体。然而，许多人没有很好地注释其分子和细胞 交互.我们已经开发出一种方法，用于对人体细胞中的天然产物进行广泛的分类， 通过采用信息丰富的内源性报告基因表达平台， 对遗传和化学扰动的细胞反应的辨别。在概念验证中， 表达驱动的功能标签被用作跨平台表型鉴别器， 对1124种遗传和1186种天然产物扰动的一致细胞反应，提供功能性 签名的本体（融合）地图，使我们能够预测的作用机制的天然产物。在 根据这项建议，我们将扩大化学品的覆盖范围，包括植物、海洋无脊椎动物和微生物。 提取物、级分和纯化合物以及商业纯化合物文库。我们还将扩大 我们的生物学覆盖范围包括超过20，000个siRNA，在正常人类细胞，非小细胞， 肺癌细胞系和免疫细胞。重要的是，我们将使用实验和 生物信息学方法用于选择一组优化的高性能报告基因， 我们将使用的不同细胞类型的背景。

Abstract: A pressing challenge in the field of natural products and botanicals is the biological characterization of pure compounds, mixtures and the study of synergistic relationships. Although the rate of discovery of interesting new metabolites is high using phenotypic approaches, the difficulty of target identification and verification is a bottleneck that is difficult to overcome. To fully take advantage of this vast reservoir of biologically active small molecules requires the development of high-throughput methods to mechanistically annotate chemical collections. For botanicals, there is generally anecdotal evidence for their use and in some cases a body of clinical evaluation. However many are not well annotated for their molecular and cellular interactions. We have developed a method for the broad-scale classification of natural products in human cells, by employing an information-rich, endogenous reporter gene expression platform that allows quantitative discrimination of cellular responses to genetic and chemical perturbations. In a proof-of-concept, gene expression-driven functional signatures were employed as cross-platform phenotypic discriminators to link concordant cellular responses to 1124 genetic and 1186 natural product perturbations, providing Functional Signature of Ontology (FUSION) maps, allowing us to predict the mechanism of action of natural products. In this proposal, we will expand both our chemical coverage to include plant, marine invertebrate and microbial extracts, fractions and pure compounds as well as commercial pure compound libraries. We will also expand our biological coverage to include over 20,000 siRNAs in the context of normal human cells, non-small cell lung cancer cell lines and immune cells. Importantly, we will use a combination of experimental and bioinformatic approaches for the selection of an optimized set of high performance reporter genes tuned to the context of the different cell types we will utilize.