System-wide Study of Transcriptional Control of Metabolism

代谢转录控制的全系统研究

基本信息

批准号：
7387471
负责人：
William S Hlavacek
金额：
$ 22.02万
依托单位：
LOS ALAMOS NAT SECTY-LOS ALAMOS NAT LAB
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-05-01 至 2010-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7387471
关键词：
Accounting Address Affect Affinity Algorithms Alzheimer&apos s Disease Animal Model Animals Architecture Autistic Disorder Automobile Driving B-Cell Lymphomas B-Lymphocytes Bacillus anthracis Bacterial Genome Beds Benchmarking Binding Biochemical Biochemical Pathway Biochemical Reaction Bioinformatics Biological Biological Assay Biological Process Biology Biomedical Computing Biomedical Research Cadherins Cell Adhesion Molecules Cell Separation Cell physiology Cell-Cell Adhesion Cells Chemicals Code Collaborations Commit Communities Complex Computational Biology Computational Technique Computational algorithm Computer Analysis Computer Simulation Computer software Computers Concentration measurement Condition Crystallography DNA Binding DNA-Protein Interaction Data Data Analyses Data Set Databases Development Discipline Disease Dissection Documentation Drug Formulations Drug Interactions Educational workshop Electrical Engineering Engineering Ensure Environment Enzyme Gene Enzymes Escherichia coli Family Gene Expression Gene Expression Profile Gene Proteins Generations Genes Genetic Genetic Determinism Genetic Transcription Genome Genomics Goals Growth Head Health Sciences Human Imagery Immune system In Vitro Informatics Institutes Institution Internet Java Joints Knowledge Laboratories Language Life Literature Machine Learning Mails Malignant Neoplasms Mammalian Cell Manuals Maps Mathematics Measurement Measures Mediating Metabolic Metabolic Control Metabolic Diseases Metabolism Methodology Methods Mission Modality Modeling Modification Molecular Molecular Profiling Molecular Structure Multimedia Nature Noise Online Systems Ontology Organism Pathway Analysis Pathway interactions Performance Personal Satisfaction Phenotype Phosphotransferases Physics Positioning Attribute Principal Investigator Process Prokaryotic Cells Property Protein Analysis Protein Family Proteins Proteome Publishing RNA Range Rate Reaction Research Research Activity Research Personnel Research Proposals Resolution Resources Sampling Semantics Sequence Analysis Services Signal Transduction Site Software Engineering Solutions Source Code Specific qualifier value Specificity Speed Structural Protein Structure Structure of germinal center of lymph node Students System Systems Biology Techniques Testing Time Tissues Training Transcriptional Regulation United States National Institutes of Health Universities Validation Virulence Visual Work base biocomputing biomedical informatics computer framework computer studies computerized tools concept data acquisition data mining data modeling design environmental change experience forging hazard improved innovation interest interoperability knowledge base member metabolomics microbial multidisciplinary nervous system disorder novel pathogen pathogenic bacteria professor programs protein protein interaction reconstruction research study response simulation size software development text searching tool transcription factor

项目摘要

DESCRIPTION (provided by applicant): This proposal is in response to the NIH call for Exploratory Collaborations with National Centers for Biomedical Computing, PAR-06-223, and it will involve a collaboration between Columbia University's MAGNet NCBC and a team at Los Alamos National Laboratory. The aim of the proposal is a system-wide tudy of integrated transcriptional and metabolic networks in Eschericia coli K-12 strain, aiming at a similar analysis of a pathogen, Bacillus anthracis, at a later date. LANL hosts an experimental research program on bacterial metabolomics. Metabolites serve several functions. The most common one is being the precursors to various cellular components. They are also regulators of cellular functions by means of modulating metabolic reactions or binding to transcription factors and subsequently regulating gene expression. Conversely, the genes regulated by a transcription factor often encode enzymes, modulating the speed of metabolic reactions. Thus, to understand and ultimately predict the cellular response to an environmental change of interest (e.g., pathogen entry into its host environment), we must integrate the analysis of the transcriptome and metabolome. To address this need, we will work with the laboratories of Pat Unkefer and John Dunbar, which will produce data sets of about 300 joint metabolic/transcriptional profiles of E.coli under different steady-state growth conditions. The resources of MAGnet NCBC, specifically the algorithms within the geWorkbench bioinformatics platform produced by the center, will be leveraged to reconstruct cellular networks. Specifically, we expect that ARACNE, an algorithm originally developed by MAGNet for high-fidelity analysis of transcriptional networks in mammalian cells, is well positioned for reconstruction of metabolic networks from high throughput system-wide metabolic activity data, provide that appropriate modifications to deal with the specifics of the metabolic data are made. We will also adapt the algorithm to discover modulated interactions, that is, metabolic interactions that are conditional on the activity of a modulator gene (enzyme), or transcriptional interactions that require the presence of a metabolite to proceed. Such integrated genome/metabolome analysis has not been attempted yet. It will be a giant leap towards a complete understanding of cellular processes in an important organism. Because of the comparatively small size of bacterial genomes and metabolomes, it will be possible to perform system-wide analyses of interactions for the entire integrated genome and metabolome. While important in its own right, especially in view of the pathogenic nature of B. anthracis, this research would also represent an important test bed for a subsequent study of metabolic diseases in higher animals, including humans.

描述（由申请人提供）：该提案是对NIH呼吁与国家生物医学计算中心进行探索性合作的回应，PAR-06-223，它将涉及哥伦比亚大学磁铁NCBC与洛斯阿拉莫斯国家实验室的团队之间的合作。该提案的目的是在大肠杆菌K-12菌株中的整体转录和代谢网络的系统范围的延期，旨在在以后对病原体（病原体）的类似分析。 LANL举办了一项有关细菌代谢组学的实验研究计划。代谢物具有多种功能。最常见的是各种细胞成分的前体。它们还通过调节代谢反应或与转录因子的结合并随后调节基因表达来调节细胞功能。相反，受转录因子调节的基因通常编码酶，从而调节代谢反应的速度。因此，为了理解并最终预测对环境变化的细胞反应（例如，病原体进入其宿主环境），我们必须整合转录组和代谢组的分析。为了满足这一需求，我们将与Pat Unkefer和John Dunbar的实验室合作，该实验室将在不同的稳态生长条件下生成大约300个E.Coli的300个联合代谢/转录概况的数据集。磁铁NCBC的资源，特别是该中心生产的Geworkbench生物信息学平台中的算法，将利用用于重建蜂窝网络。具体而言，我们预计，Aracne是一种最初是由磁铁开发的算法，用于对哺乳动物细胞中转录网络进行高保真分析，对从高吞吐量系统范围内代谢性数据进行重建的重建良好，提供了适当的修改以处理代谢数据的具体内容。我们还将调整算法以发现调制相互作用，即以调节剂基因（酶）的活性为条件的代谢相互作用或需要代谢物进行进行进行的转录相互作用。这种综合基因组/代谢组分析尚未尝试。这将是对重要生物体中细胞过程的完全理解的巨大飞跃。由于细菌基因组和代谢组的大小相对较小，因此可以对整个综合基因组和代谢组进行全系统范围的相互作用分析。虽然本身很重要，尤其是鉴于炭疽芽孢杆菌的致病性质，但这项研究也将代表一个重要的测试床，用于随后研究包括人类在内的高等动物的代谢疾病。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Mass conservation and inference of metabolic networks from high-throughput mass spectrometry data.

从高通量质谱数据中进行质量守恒和代谢网络的推断。

DOI：
10.1089/cmb.2010.0222
发表时间：
2011
期刊：
Journal of computational biology : a journal of computational molecular cell biology
影响因子：
0
作者：
Bandaru,Pradeep;Bansal,Mukesh;Nemenman,Ilya
通讯作者：
Nemenman,Ilya

Using sequence-specific chemical and structural properties of DNA to predict transcription factor binding sites.