Gene Function and Pathway Analysis Using Systems Level Approaches in Prokaryotes

描述(由申请人提供)：我们解决了微生物学中的一个关键问题：如何将巨大的基因组库解密为细菌细胞特性的蓝图。目前，序列获取速度和功能信息之间的差异阻碍了我们基因组资源的利用。我们已经填补了这一空白。我们正在开发和实施高通量表型方法，以加快基因功能、途径及其相互联系的确定。因此，我们在系统分析和机械生物学之间发挥作用。我们已经证明，化学基因组图谱(对许多生长条件下完整基因缺失文库的适合性的定量图谱)和上位性图谱(E-map；在基因组水平上比较双突变和单突变表型)可以迅速加速发现大肠杆菌中的表型、途径和途径互连。这笔赠款中提议的工作极大地扩大了我们的努力。首先，在我们证明化学基因组图谱提供了孤儿(功能未描述的)基因和注释基因之间的高度相关性之后，我们现在将开发一条发现孤儿基因功能的管道。我们将通过描绘更多的化学空间来扩展和改进高相关性关联，评估与其他基本上不重叠的功能关联度量(例如蛋白质-蛋白质相互作用)的关联，并将我们的多变量数据集整合到每个潜在的孤儿-基因-注释基因相互作用的单个相互作用概率分数中。这一纲要将是一个强大的资源，既可以确定孤儿基因的功能，也可以评估哪些基因功能的度量对于功能表征来说是最具信息量和成本效益的。其次，我们将研究在我们的高通量筛选中确定的细胞分裂和肽聚糖合成之间难以捉摸的功能联系的分子基础。我们以前的工作表明，PBP1B双功能肽聚糖合成机与Tol-Pal在促进细胞分裂过程中的外膜收缩方面存在部分冗余。我们现在发现一种名为YbgF的孤儿蛋白质可能协调这两个机器，我们将寻求分子、生化和细胞生物学方法来探索协调是如何完成的。最后，我们将把我们的高通量表型方法扩展到枯草杆菌，枯草杆菌是革兰氏阳性的关键模式生物，也是人类肠道中普遍存在的两大门之一。我们将在枯草杆菌中进行化学基因组图谱和E-map分析，并利用它来剖析基因功能和途径连接。由于革兰氏阳性和革兰氏阴性生物在包膜结构、社会行为以及主要细胞过程的控制和执行方面存在差异，包括复制和新陈代谢，我们的开源数据集将包含丰富的新生物学。这项工作解决了阻碍基因组信息使用的“表型差距”，并展示了系统分析和机制研究在建立基因功能和过程之间更高阶联系方面的组合力量。

DESCRIPTION (provided by applicant): We address a pivotal issue in microbiology: how to decipher the vast reservoir of genomes into a blueprint for the cellular properties of bacteria. Currently, the disparity between speed of acquisition of sequence and functional information impedes utilization of our genomic resources. We have stepped into this gap. We are developing and implementing high throughput phenotyping approaches to accelerate determination of gene functions, pathways and their interconnections. Thus, we function at the interface between systems analysis and mechanistic biology. We have already shown that chemical-genomic profiling (quantitative profiling of the fitness of the complete gene deletion library under many growth conditions) and Epistasis MAPs (E- MAPs; comparison of double vs single mutant phenotypes on a genome level) rapidly accelerates discovery of phenotypes, pathways and pathway interconnections in E. coli. The work proposed in this grant significantly expands our efforts. First, following on our demonstration that chemical genomic profiling provides high correlation associations between orphan (functionally uncharacterized) genes and annotated genes, we will now develop a pipeline for discovery of orphan gene function. We will expand and improve the high correlation associations by profiling more chemical space, assess associations with other, largely non overlapping measures of functional association (e.g. protein-protein interactions) and integrate our multivariate data sets into a single interaction probability score for each potential orphan-gene-to-annotated gene interaction. This compendium will be a powerful resource both for determining orphan gene function, and for assessing which metrics of gene function are most informative and cost-effective for functional characterization. Second, we will investigate the molecular underpinnings of an elusive functional link between cell division and peptidoglycan synthesis identified in our high-throughput screens. Our previous work showed that the PBP1B bifunctional peptidoglycan synthesis machine is partially redundant with Tol-Pal in promoting outer membrane constriction during cell division. We now find that an orphan protein, YbgF, may coordinate both machines, and we will pursue molecular, biochemical and cell biological approaches to explore how coordination is accomplished. Finally, we will expand our high throughput phenotyping approaches to B. subtilis, the key gram-positive model organism and a member of the Firmicutes, one of two major phyla ubiquitously present in the human gut. We will implement chemical-genomic profiling and E-MAP analysis in B. subtilis and use it to dissect gene function and pathway connections. As Gram-positive and negative organisms differ in their envelope structures, social behaviors and control and execution of major cellular processes, including replication and metabolism, our open-source dataset will be rich in novel biology. This work addresses the "phenotype gap" impeding the use of genomic information and demonstrates the combined power of systems analyses and mechanistic studies in establishing gene function and higher-order connections between processes.