权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Genome-wide measurement of bacterial transcriptional regulatory states

细菌转录调控状态的全基因组测量

基本信息

批准号：
8735166
负责人：
Lydia Freddolino
金额：
$ 3万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-20 至 2014-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8735166
关键词：
Affinity Antibiotics Award Bacteria Bacterial Genome Behavior Binding Binding Sites Biology Carbon Cell Communication Cells Chloroform Communities Complex Computing Methodologies DNA DNA Binding DNA-Binding Proteins Data Deoxyribonucleases Detection Development Environment Environmental Hazards Escherichia coli Eukaryota Evaluation Evolution Exclusion Gene Expression Gene Expression Profile Gene Expression Regulation Genes Genetic Genetic Transcription Genome Genomics Goals Grant Heart High-Throughput Nucleotide Sequencing Housekeeping Human Individual Interphase Knowledge Life Link Location Logic Maps Measurement Measures Mentors Messenger RNA Methods Microbe Modeling Molecular Models Mutation Organism Output Phase Phenols Phenotype Physiological Play Population Process Proteins Proteomics Regulatory Element Research Resistance Resolution Role Sensitivity and Specificity Signal Transduction Site Source Specificity Staging Statistical Models Stimulus Systems Biology Technology Testing Time Tissue Differentiation Transcriptional Regulation Validation Vertebral column antimicrobial drug aqueous base chromatin immunoprecipitation computer framework computerized data processing computerized tools crosslink density directed evolution drug development extracellular fitness follow-up genetic regulatory protein genome-wide improved information gathering insight metabolomics microbial community molecular modeling novel preference programs public health relevance rapid technique research study resistance mechanism response rho termination factor tool transcription factor ultraviolet irradiation

项目摘要

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.

描述（由申请人提供）：基因表达的调节在生物学的各个方面都起着关键作用，从细菌对其环境的反应方式到高等真核生物中组织的分化。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（TF）的结合，这些转录因子可以抑制或激活附近基因的表达。这里提出的K99/R 00项目的目的是贡献一种方法，称为IPODHR，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。了解和定量建模细菌细胞的调控网络对于成功开发新抗生素和合理操纵微生物群落（如人类肠道中的微生物群落）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），而是利用苯酚-氯仿提取期间这些复合物分配到有机-水界面的事实，从交联裂解物中分离所有蛋白质-DNA复合物。高通量测序用于揭示DNA结合的TF的位置。然后，使用目前正在开发的计算方法，在数据处理期间将代表整个基因组的总体蛋白质占用的所得信号分成来自不同TF和其他DNA结合蛋白的贡献。因此，与ChIP不同，只需要一个实验来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（包括该奖项的指导阶段的计划）的重点是完成IPODHR框架的实验和计算方面。对于实验部分，只有小的改进似乎是必要的，以进一步提高空间分辨率，验证实验和试点应用，然后将进行确认的灵敏度和特异性的方法，以改变生理条件。分区IPODHR结合概况所需的计算方法也在积极发展中，使用统计模型将IPODHR密度中的峰分配给特定因素。在这些开发和验证实验的过程中，后续工作将针对从IPODHR数据推断但尚未详细表征的TF结合位点和特异性，进一步扩展我们对E.大肠杆菌转录调控网络，揭示新的转录因子和相互作用。IPODHR的成功完成和应用将为社区提供一个变革性的新工具，以测量细菌的转录调控逻辑，而无需详细了解所涉及的转录因子。计划在独立阶段进行的研究将侧重于使用IPODHR以及细菌系统生物学中其他已建立的方法，以全面了解如何重新布线转录网络，使细胞能够适应新的条件，而无需获得新的酶能力。我将首先关注先前发现的终止因子Rh的突变，该突变在各种条件下改善细胞适应性，并且似乎代表了发生在进化细菌群体中的管家蛋白的广泛类别的突变。IPODHR将允许测量导致先前观察到的适应性输出的转录逻辑变化，从而深入了解所研究的扰动改变TF行为以引起观察到的表型变化的确切机制。由于所讨论的rho突变使细胞对几类抗生素具有一定的耐药性，因此将这种耐药性的机制与其他已知的抗生素耐受性途径进行比较将特别有用。如果拟议目标的进展足够迅速，在接近授权期结束时，IPODHR的适应性用于除E.大肠杆菌也可以开始。该方法提供的大量信息，以及缺乏对靶生物的特定先验知识或操作的任何需要，意味着IPODHR有希望在了解研究不足的微生物的转录调控方面提供巨大的进步。IPODHR的这些应用将构成R 01提案的主干，该提案将在独立R 00阶段的后期阶段编制。