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Genome-wide measurement of bacterial transcriptional regulatory states

Genome-wide measurement of bacterial transcriptional regulatory states
细菌转录调控状态的全基因组测量
批准号:
8735166
负责人:
Lydia Freddolino
金额:
$3.0万
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-20 至 2014-12-31

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中文摘要
翻译
描述(申请人提供):基因表达调控在生物学的各个方面都发挥着关键作用,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在给定条件下细胞中基因表达模式背后的调控逻辑。这一逻辑在很大程度上源于转录因子(TF)的结合,转录因子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,通过提供在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。了解细菌细胞的调控网络并对其进行定量建模,对于成功开发新的抗生素以及合理操纵微生物群落(如人类肠道中的微生物群落)都是至关重要的。IPODHR表面上类似于染色质免疫沉淀(CHIP)实验,但不是分离单个蛋白质(以及与其结合的任何DNA),而是从交联的裂解物中分离所有蛋白质-DNA复合体,利用这些复合体在苯酚-氯仿提取过程中分配到有机-水相的事实。高通量测序用于揭示DNA结合的转录因子的位置。然后,利用目前正在开发的一种计算方法,在数据处理过程中,代表整个基因组的总蛋白质占有率的结果信号被分解为来自不同TF和其他DNA结合蛋白质的成分。因此,与芯片不同,只需要一次实验就可以研究给定条件下细胞的整个调节状态,并且不需要相关TF的先验知识。目前,我正在进行的研究(包括奖项指导阶段的计划)集中在完成IPODHR框架的实验和计算方面。对于实验部分,似乎只需进行微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结合图谱所需的计算方法也在积极开发中,使用统计模型将IPODHR密度中的峰值分配给特定因素。在这些开发和验证实验的过程中,后续将针对从IPODHR数据推断的TF结合位点和特异性,但尚未详细描述,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知识。IPODHR的成功完成和应用将为社区提供一个革命性的新工具,在不详细了解所涉及的转录因子的情况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使用IPODHR以及细菌系统生物学中的其他已有方法,以完全了解重新连接转录网络如何使细胞能够在不获得新的酶能力的情况下适应新的条件。我首先将重点放在先前发现的终止因子Rh的一个突变上,该突变可以在各种条件下改善细胞的适应性,并且似乎代表了在进化的细菌种群中发生的管家蛋白的一大类突变。IPODHR将允许测量转录逻辑中引起先前观察到的适应性输出的变化,从而提供对所研究的扰动改变TF行为以引起观察到的表型变化的确切机制的洞察。由于有问题的Rho突变使细胞对几类抗生素产生一定程度的抗药性,将这种抗药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, 在授权期接近尾声时,IPODHR用于除大肠杆菌以外的细菌的改造也可能开始。该方法提供的信息范围很广,而且不需要对目标生物体的特定先验知识或操纵,这意味着IPODHR有望在理解研究较少的微生物的转录调控方面取得巨大进展。IPODHR的这些应用将构成将在独立R00阶段后期阶段准备的R01提案的主干。
英文摘要
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.
期刊论文(3)
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科研奖励(0)
会议论文
DOI: 10.1021/acs.jpcb.6b12450
发表时间: 2017-05-25
期刊: The journal of physical chemistry. B
影响因子: --
作者: [Khabiri M, Freddolino PL]
通讯作者: Freddolino PL
DOI: 10.1021/acs.biochem.5b00586
发表时间: 2015-09-29
期刊: Biochemistry
影响因子: 2.9
作者: [Zisis T, Freddolino PL, Turunen P, van Teeseling MC, Rowan AE, Blank KG]
通讯作者: Blank KG
Bacteriophage Mu as Tool to Study Genome Organization in Bacteria and Eukaryotes
  • 批准号:
    10265837
  • 项目类别:
  • 资助金额:
    $44.71万
  • 财政年份:
    2021
  • 负责人:
    Lydia Freddolino
  • 依托单位:
Structure-based functional annotation of microbial genomes
Building a unified framework for understanding bacterial gene regulation and chromosomal architecture
Building a unified framework for understanding bacterial gene regulation and chromosomal architecture
海外基金