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：
8993954
负责人：
Lydia Freddolino
金额：
$ 24.87万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
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 2018-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8993954
关键词：
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 DNase I hypersensitive sites sequencing Data 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 Signal Transduction Site Source Staging Statistical Models Stimulus Systems Biology Technology Testing Time Tissue Differentiation Transcriptional Regulation Validation Vertebral column Work abstracting antimicrobial drug aqueous base chromatin immunoprecipitation computer framework computerized data processing computerized tools crosslink density directed evolution drug development extracellular follow-up genetic regulatory protein genome-wide improved information gathering insight metabolomics microbial community molecular modeling novel preference programs rapid technique research study resistance mechanism response rho termination factor tool transcription factor ultraviolet irradiation

项目摘要

Abstract 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 isolat- ing 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 sig- nal, 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 com- ponent, 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 transcrip- tional 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 net- works 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 Rho that improves cellular ﬁtness under a variety of conditions, and appears to be representative of a broad class of mutations to housekeep- ing 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 ex- act 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.

抽象的基因表达的调节在生物学的各个方面都起着关键作用，从细菌的方式来看对他们的环境响应较高的真核生物中组织的分化。在基因组时代，但是，蛋白质组学和代谢组学，生物学家仍然是一种通常适用于快速方法的方法确定在给定集中基因表达模式的基因表达模式的确定条件。这种逻辑在很大程度上源于转录因子（TF）的结合，这可以抑制或激活附近基因的表达。这里提出的K99/R00项目旨在贡献方法称为iPodhr，用于获得转录调节状态的全基因组快照细胞，通过提供生理下与基因组结合的所有转录因子的位置和身份状况。了解和定量对细菌细胞的调节网络进行建模都是至关重要的为了成功开发新的抗生素，以及对微生物群落的合理操纵例如人类肠道。 ipodhr与染色质免疫沉淀（CHIP）实验非常相似，但不是隔离 iPODHR与单个蛋白质（以及与之结合的任何DNA结合），将所有蛋白DNA复合物与交联的所有蛋白DNA复合物分离裂解物，使用这些复合物在苯酚 - 氯仿期间分配到有机水相间的事实萃取。高通量测序用于揭示DNA结合TF的位置。由此产生的sig- NAL代表整个基因组的总体蛋白质占用率，然后在数据处理中分裂为使用当前的计算方法，来自不同TF和其他DNA结合蛋白的贡献正在开发。与芯片不同，只需要一个实验来研究整个调节状态在给定条件下的单元格不需要相关TF的先验知识。目前，我正在进行的研究（包括奖励的修订阶段的计划）都集中在完成iPODHR框架的实验和计算方面。对于实验性com- 老板，似乎只有小规定才能进一步改善空间分辨率。验证实验然后将执行试点申请，以确保更改方法的敏感性和特定城市生理条件。分区iPodhr绑定程序所需的计算方法是同样在主动发展下，使用统计模型将iPodhr密度的峰分配给特定因素。在这些开发和验证实验的过程中，随访将针对TF结合位点以及从iPodhr数据推断但尚未详细描述的特定城市，进一步扩展了我们的知识大肠杆菌转录调节网络的范围通过揭示新的TF和相互作用。成功完成 iPodhr的应用将为社区提供一种变革性的新工具来衡量成绩单 - 细菌的构成调节逻辑，没有详细的先验了解所涉及的转录因子的知识。独立阶段计划的研究将集中于iPodhr的使用，以及其他已建立的细菌系统生物学中的方法，以完全了解如何重新布线转录网络工作可以使细胞适应新的条件，而无需获得新的酶促能力。我会最初专注于先前发现的终止因子Rho的突变，该突变改善了细胞舒适性在各种条件下，似乎代表了家政的广泛突变 - 在不断发展的细菌种群中发生的蛋白质。 ipodhr将允许测量更改转录逻辑产生以前观察到的自适应输出，从而提供了对ex的见解所研究的扰动改变了TF行为以引起观察到的ACT机制表型的变化。随着RHO突变使细胞在某种程度上具有对几类的抗性抗生素，将这种抗性的机制与其他已知路径进行比较将特别有用具有抗生素耐受性。如果提议的目标的进展非常快，那么在授予期适应的结束接近ipodhr 用于大肠杆菌以外的细菌也可以开始使用。该方法提供的大量信息范围，并且缺乏对目标生物的特定事先知识或操纵的任何需求，这意味着iPodhr 有望在理解不良研究的转录调节方面提供巨大的进步微生物。 iPodhr的这些应用将形成R01提案的骨干，以便在独立R00阶段的后期阶段。