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发挥着关键作用，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，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。了解细菌细胞的调节网络并对其进行定量建模对于成功开发新抗生素以及合理操纵微生物群落（例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（以及与其结合的任何 DNA），而是从交联裂解物中分离所有蛋白质-DNA 复合物，利用这些复合物分配到有机-苯酚-氯仿萃取过程中的水相。高通量测序用于揭示 DNA 结合 TF 的位置。所产生的信号代表整个基因组中蛋白质的总体占据情况，然后在数据处理过程中使用目前正在开发的计算方法将其分解为来自不同 TF 和其他 DNA 结合蛋白的贡献。因此，与 ChIP 不同，只需要一次实验即可研究给定条件下细胞的整个调控状态，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）重点是完成 IPODHR 框架的实验和计算方面。对于实验组件，似乎只需要进行小的改进即可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，进一步扩展我们对大肠杆菌转录调控网络的了解。 IPODHR 的成功完成和应用将为业界提供一种变革性的新工具来测量细菌的转录调控逻辑，而无需事先详细了解所涉及的转录因子。独立阶段计划的研究将重点关注 IPODHR 的使用以及细菌系统生物学中其他已建立的方法，以全面了解转录网络的重新布线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。我将首先关注先前发现的终止因子 Rh 的突变，该突变可改善多种条件下的细胞适应性，并且似乎代表了进化细菌群体中发生的一类管家蛋白突变。 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产生一定的耐药性，因此将这种耐药性的机制与其他已知的抗生素耐受途径进行比较将特别有用。如果拟议目标的进展足够快，在授权期即将结束时，IPODHR 也可能开始适应用于大肠杆菌以外的细菌。该方法提供的大量信息，并且不需要任何特定的先验知识或对目标生物体的操作，意味着IPODHR有望在了解研究不足的微生物的转录调控方面取得巨大进展。 IPODHR 的这些应用将构成在独立 R00 阶段后期准备的 R01 提案的支柱。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Distinct heterochromatin-like domains promote transcriptional memory and silence parasitic genetic elements in bacteria.

独特的异染色质样结构域促进转录记忆并沉默细菌中的寄生遗传元件。

DOI：
发表时间：
2022-02-01
期刊：
影响因子：
0
作者：
Amemiya, Haley M;Goss, Thomas J;Nye, Taylor M;Hurto, Rebecca L;Simmons, Lyle A;Freddolino, Peter L
通讯作者：
Freddolino, Peter L

Deficiencies in Molecular Dynamics Simulation-Based Prediction of Protein-DNA Binding Free Energy Landscapes.

基于分子动力学模拟的蛋白质-DNA 结合自由能景观预测的缺陷。