Stochastic Partitioning and Degradation of Macromolecules

大分子的随机分配和降解

基本信息

批准号：
8501571
负责人：
Johan Paulsson
金额：
$ 30.79万
依托单位：
HARVARD MEDICAL SCHOOL
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-07-01 至 2015-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8501571
关键词：
Accounting Address Affect Antibiotic Resistance Area Biological Models Cell Cycle Cell division Cell physiology Cells Clinical DNA Daughter Disease Outbreaks Drug resistance Escherichia coli Fission Yeast Gene Activation Gene Expression Genes Genetic Transcription Health Heterogeneity Human Individual Information Theory Investigation Kinetics Libraries Life Mathematics Measures Messenger RNA Methods Modeling Molecular Monitor Noise Organism Physics Plant Roots Plasmids Play Process Proteins Proteolysis Randomized Reaction Role Shapes Signal Transduction Source Surveys System Testing Time Toy Translations Untranslated Regions Virulence biological systems cell growth clinically relevant design enzyme substrate genetic manipulation interest macromolecule mathematical model mathematical theory microbial non-genetic pathogenic bacteria prevent research study response segregation statistics tool transmission process

项目摘要

DESCRIPTION (provided by applicant): Many genes, RNAs and proteins are present in such extremely low numbers that random collisions between individual molecules create fluctuations in abundances between otherwise identical cells. The sources and dynamics of such 'noise' have been analyzed in detail, for example showing how variances respond to changes in transcription and translation as expected from models of stochastic gene expression. Preliminary mathematical theory surprisingly suggests a very different explanation, showing that almost all such results are equally consistent with fluctuations that instead originate due to unequal partitioning of molecules at cell division. Other mathematical results suggest that random partitioning of molecules indeed could contribute at least as much as gene expression to the overall heterogeneity. These results motivate a broad experimental investigation of segregation, comparing stochastic partitioning for different types of macromolecules: in-depth analyses of active segregation mechanisms of plasmids in Escherichia coli, a quantification of proteolysis in E. coli, and an mRNA and protein survey in Schizosaccharomyces pombe. Each system was chosen because of the key principles illustrated, because of the central roles they play biologically and threats they pose clinically, and because new experimental approaches developed in the lab make it possible to analyze them much more quantitatively. The experimental analyses go hand-in-hand with both analytical toy models of basic principles, general nonlinear mathematical theory that collectively addresses classes of cyclic random processes. In addition to analyzing and comparing central biological systems in molecular and kinetic detail, this ambitious proposal could produce a substantial shift in the quantitative perspective on fluctuations in cellular constituents, and will provide several enabling mathematical and experimental methods. The processes studied are also relevant to human health both by studying a central principle important to all cell growth and division, and by focusing on specific systems of clinical relevance, such as the genes responsible for the majority of antibiotic resistance outbreaks, and the protective responses of pathogenic bacteria.

描述（由申请人提供）：许多基因，RNA和蛋白质的数量非常低，以至于单个分子之间的随机碰撞在其他相同的细胞之间会导致丰富的波动。例如，已经对这种“噪声”的来源和动力学进行了详细分析，例如，表明方差如何响应转录和转换的变化，如随机基因表达模型所期望的。初步数学理论令人惊讶地提出了一个非常不同的解释，这表明几乎所有这些结果与波动同样是由于细胞分裂分子分配不平等而起源的波动。其他数学结果表明，分子的随机分配确实可以至少与基因表达相同，对整体异质性。 These results motivate a broad experimental investigation of segregation, comparing stochastic partitioning for different types of macromolecules: in-depth analyses of active segregation mechanisms of plasmids in Escherichia coli, a quantification of proteolysis in E. coli, and an mRNA and protein survey in Schizosaccharomyces pombe.选择每个系统是因为所说明的关键原理，因为它们在生物学上扮演的主要角色并在临床上构成威胁，并且由于实验室中开发的新实验方法使得可以更定量地分析它们。实验分析与基本原理的两个分析玩具模型（一般的非线性数学理论）并存，共同解决了环状随机过程的类别。除了在分子和动力学细节中分析和比较中央生物系统外，这一雄心勃勃的建议还可以在细胞成分波动的定量观点上产生实质性的转变，并将提供几种有灵感的数学和实验方法。研究的过程也与人类健康有关，既通过研究对所有细胞生长和分裂重要的中心原理，以及专注于临床相关性的特定系统，例如负责大多数抗生素耐药性暴发的基因以及致病细菌的保护反应。