Gene regulation in phage lambda: A real-time study with single-event resolution
Gene regulation in phage lambda: A real-time study with single-event resolution
批准号:
7668366
负责人:
Ido Golding
金额:
$31.7万
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-08-04 至 2010-07-31
关键词:
Active Biological TransportAffectBacteriaBacteriophage lambdaBacteriophagesBiochemicalBiochemistryBiologicalBiological ModelsCapsidCell AgingCell physiologyCell surfaceCellsCharacteristicsCommunitiesComplexComprehensionCytolysisCytoplasmDNA DamageDestinationsDetectionDevelopmentDiffusionEngineeringEpigenetic ProcessEscherichia coliEukaryotaEventFluorescence MicroscopyGene ExpressionGene Expression RegulationGeneticGenetic TranscriptionGenomeGoalsGrowthHandIn VitroIndividualInfectionKineticsKnowledgeLifeLife Cycle StagesLiteratureLocationLysogenyLyticLytic PhaseMaintenanceMeasurementMeasuresMessenger RNAMethodsMicroscopicModelingMotionNoiseOrganismOutcomePathway interactionsPhenotypePhysiologicalPopulationPositioning AttributePotential EnergyProcessProductionProkaryotic CellsPropertyProphagesReactionResearch PersonnelResolutionRoleScientistShapesSignal TransductionSourceSpatial DistributionStagingSystemSystems BiologyTheoretical modelTimeTime StudyTranscriptVirulentVirusbasebiological systemscell agecell injurychemical reactiondevelopmental geneticsin vivoinsightlambda repressormacromoleculemathematical modelmolecular scalenovelnovel strategiespublic health relevanceresponseself assemblyspatiotemporaltool
中文摘要
描述(申请人提供):由大肠杆菌及其病毒噬菌体lambda组成的系统是基因调控的许多方面的基本范例,范围从分子到有机体水平。在lambda系统中提出的问题通常会产生与“高等”真核系统相关的见解。使用遗传学和生物化学的传统工具对lambda系统进行了广泛的表征,使得能够根据细胞中的微观相互作用形成对所观察到的现象学的优雅且看似完整的叙述。然而,从量化科学家的角度来看,一方面遗传和生化知识与观察到的种群表型之间存在着巨大的理解差距。这一差距表现在系统的数学模型的预测能力很差。为了试图弥合这一知识鸿沟,需要通过在单个活细胞中实时研究组成这个生命周期的事件,以足够的分辨率量化细胞内的动力学来描述空间和时间上的个别事件,从而“解构”噬菌体lambda的生命周期。在这项建议中,我们建议表征lambda生命周期中的基因调控,主要集中在以下目标:(1)表征溶源/溶源开关在维持溶源(休眠)状态以及在细胞损伤后诱导裂解(毒力)途径的功能。(2)阐明影响生命周期的时空方面,例如裂解途径的不同阶段基因组复制、基因表达、衣壳自组装和裂解是如何在空间和时间上组织的。(3)在lambda生命周期中区分精确度和随机性,方法是将由不可控变异性的实际来源产生的“真实”随机性与由于我们自己无法检测和测量单个细胞之间的生理参数差异而产生的“表观”随机性分开。
公共卫生相关性:填补单一事件层面的知识空白将反过来使我们更接近从微观成分的角度对整个系统(有机体)特征的定量理解,而不是“系统生物学”。在像lambda这样的简单模型系统中实现这一目标之后,在高等生物体中也可以进行类似的努力。
英文摘要
DESCRIPTION (provided by applicant): The system comprised of the bacterium Escherichia coli and its virus, bacteriophage lambda, serves as the basic paradigm for many aspects of gene regulation, ranging in scale from the molecular to the organismic level. Questions asked within the lambda system often yield insights relevant to "higher" eukaryotic systems. The lambda system has been extensively characterized using the traditional tools of genetics and biochemistry, enabling the formation of an elegant and seemingly complete narrative of the observed phenomenology in terms of the microscopic interactions in the cell. However, from the point of view of a quantitative scientist there is an immense gap of understanding between the genetic and biochemical knowledge on the one hand, and the observed population phenotype on the other. This gap manifests itself in the poor predictive powers of mathematical models of the system. To try and bridge the knowledge gap it is required to "deconstruct" the life cycle of bacteriophage lambda by studying the events comprising this life cycle in real-time, in individual living cells, quantifying the intracellular dynamics with sufficient resolution to describe individual events in space and time. In this proposal we suggest to characterize gene regulation during the lambda life cycle, concentrating on the following aims: (1) Characterizing the function of the lysis/lysogeny switch during the maintenance of the lysogenic (dormant) state as well as the induction of the lytic (virulent) pathway following cell damage. (2) Elucidating spatiotemporal aspects affecting the life cycle, for example how the different stages of the lytic pathway genome replication, gene expression, capsid self-assembly and lysis are organized in space and time. (3) Distinguishing precision versus stochasticity in the lambda life cycle, by separating "real" stochasticity one resulting from actual sources of uncontrolled variability from "apparent" stochasticity, resulting from our own inability to detect and measure differences in physiological parameters between individual cells.
PUBLIC HEALTH RELEVANCE: Filling the knowledge gap at the single-event level will in turn bring us closer to a quantitative understanding of whole-system (organism) characteristics in terms of the microscopic constituents, in the vain of "systems biology". Achieving this goal in a simple model system such as lambda can then be followed by similar endeavors in higher organisms.
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