Genome-wide measurement of bacterial transcriptional regulatory states

描述（由申请人提供）：基因表达的调控在生物学的各个方面都起着关键作用，从细菌对环境的反应方式到高等真核生物组织的分化。然而，在基因组学、蛋白质组学和代谢组学的时代，生物学家仍然缺乏一种普遍适用的方法来快速确定给定条件下细胞中基因表达模式的调控逻辑。这种逻辑在很大程度上源于转录因子（TFs）的结合，它可以抑制或激活附近基因的表达。这里提出的K99/R00项目旨在提供一种称为IPODHR的方法，通过提供生理条件下与基因组结合的所有转录因子的位置和身份，获得细胞转录调控状态的全基因组快照。理解和定量模拟细菌细胞的调控网络对于新抗生素的成功开发以及对微生物群落（如人类肠道中的微生物群落）的合理操纵至关重要。IPODHR表面上类似于染色质免疫沉淀（ChIP）实验，但IPODHR不是分离单个蛋白质（以及与之结合的任何DNA），而是从交联裂解物中分离所有蛋白质-DNA复合物，利用这些复合物在苯酚-氯仿提取过程中分裂到有机-水间相的事实。高通量测序用于揭示dna结合tf的位置。由此产生的信号，代表了整个基因组的整体蛋白质占用，然后在数据处理过程中被分成来自不同tf和其他DNA结合蛋白的贡献，使用目前正在开发的计算方法。因此，与ChIP不同的是，只需要一个实验就可以研究给定条件下细胞的整个调控状态，并且不需要预先了解相关的tf。目前，我正在进行的研究（包括奖项指导阶段的计划）主要集中在完成IPODHR框架的实验和计算方面。对于实验组件，只需要进行小的改进就可以进一步提高空间分辨率；然后将进行验证实验和试点应用，以确认该方法对不断变化的生理条件的敏感性和特异性。划分IPODHR结合谱所需的计算方法也在积极开发中，使用统计模型将IPODHR密度的峰值分配给特定因素。在这些开发和验证实验的过程中，后续研究将针对从IPODHR数据推断但尚未详细表征的TF结合位点和特异性，通过揭示新的TF和相互作用，进一步扩大我们对大肠杆菌转录调控网络的认识。IPODHR的成功完成和应用将为科学界提供一种革命性的新工具，可以在不详细了解所涉及的转录因子的前提下测量细菌的转录调控逻辑。计划在独立阶段进行的研究将集中在IPODHR的使用上，以及细菌系统生物学中其他已建立的方法，以全面了解重新布线的转录网络如何允许细胞在不获得新的酶能力的情况下适应新的条件。我将首先关注先前发现的终止因子Rh的突变，它在各种条件下改善细胞适应性，并且似乎是在进化的细菌种群中发生的管家蛋白突变的广泛类别的代表。IPODHR将允许测量转录逻辑的变化，从而产生先前观察到的适应性输出，从而深入了解所研究的扰动改变TF行为从而引起观察到的表型变化的确切机制。由于所讨论的rho突变使细胞对几种抗生素具有一定的抗性，因此将这种抗性的机制与其他已知的抗生素耐受途径进行比较将特别有用。如果拟议目标的进展足够迅速，

DESCRIPTION (provided by applicant): The regulation of gene expression plays a pivotal role in all aspects of biology, from the manner in which bacteria respond to their environment to the differentiation of tissues in higher eukaryotes. In the era of genomics, proteomics, and metabolomics, however, biologists are still bereft of a generally applicable method for rapid determination of the regulatory logic underlying the pattern of gene expression in a cell under a given set of conditions. This logic arises in large part from the binding of transcription factors (TFs) which can either repress or activate expression of nearby genes. The K99/R00 project proposed here aims to contribute a method, termed IPODHR, for obtaining a genome-wide snapshot of the transcriptional regulatory state of the cell, by providing the locations and identities of all transcription factors bound to the genome under physiological conditions. Understanding and quantitatively modeling the regulatory networks of bacterial cells is crucial both for the successful development of new antibiotics, and for the rational manipulation of microbial communities such as that in the human gut. IPODHR is superficially similar to chromatin immunoprecipitation (ChIP) experiments, but instead of isolating a single protein (and any DNA bound to it), IPODHR isolates all protein-DNA complexes from crosslinked lysates, using the fact that these complexes partition to the organic-aqueous interphase during phenol-chloroform extraction. High throughput sequencing is used to reveal the locations of DNA-bound TFs. The resulting signal, representing overall protein occupancy throughout the genome, is then split during data processing into contributions from different TFs and other DNA binding proteins, using a computational method that is currently under development. Thus, unlike ChIP, only one experiment is required to study the entire regulatory state of the cell under a given condition, and prior knowledge of the relevant TFs is not required. At present, my ongoing research (including plans for the mentored phase of the award) is focused on completing the experimental and computational aspects of the IPODHR framework. For the experimental component, only small refinements appear necessary to improve spatial resolution further; validation experiments and pilot applications will then be performed to confirm the sensitivity and specificity of the method to changing physiological conditions. The computational methods required for partitioning the IPODHR binding profile are also under active development, using a statistical model to assign peaks in the IPODHR density to particular factors. In the process of these development and validation experiments, follow-ups will target TF binding sites and specificities inferred from IPODHR data but not yet characterized in detail, further expanding our knowledge of the E. coli transcriptional regulatory network by revealing new TFs and interactions. Successful completion and application of IPODHR will provide the community with a transformative new tool to measure the transcriptional regulatory logic of bacteria without detailed prior knowledge of the transcription factors involved. Research planned for the independent phase will focus on the use of IPODHR, alongside other established methods in bacterial systems biology, to obtain a complete understanding of how rewiring transcriptional networks can allow cells to adapt to novel conditions without the acquisition of new enzymatic capacities. I will focus initially on a previously discovered mutation of the termination factor Rh that improves cellular fitness under a variety of conditions, and appears to be representative of a broad class of mutations to housekeeping proteins that occur in evolving bacterial populations. IPODHR will allow measurement of the changes in transcriptional logic giving rise to previously observed adaptive outputs, and thus provide insight into the exact mechanisms through which the perturbations under study alter TF behavior to give rise to the observed changes in phenotype. As the rho mutation in question renders cells somewhat resistant to several classes of antibiotics, it will be particularly useful to compare the mechanisms of this resistance with other known paths to antibiotic tolerance. If progress on the proposed aims is sufficiently rapid, near the end of the grant period adaptation of IPODHR for use in bacteria other than E. coli may also begin. The massive scope of information provided by the method, and lack of any need for specific prior knowledge or manipulation of the target organism, mean that IPODHR has the promise to provide a huge advance in the understanding of transcriptional regulation in poorly studied microbes. These applications of IPODHR will form the backbone of an R01 proposal to be prepared during the late stages of the independent R00 phase.