Multiscale kinetic analysis of Cu/Zn efflux in Halobacterium sp. NRC-1

盐杆菌属铜/锌流出的多尺度动力学分析。

• 批准号: 7676970
• 负责人: Wyming Lee Pang
• 金额: $ 5.01万
• 依托单位: INSTITUTE FOR SYSTEMS BIOLOGY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-12-01 至 2011-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7676970
• 关键词: Address; Adverse drug effect; Affect; Architecture; Behavior; Cell physiology; Cells; Chemicals; Complex; Copper; Data; Disease; Environment; Equation; Exhibits; Feedback; Gene Combinations; Gene Expression; Gene Expression Regulation; Genes; Genome; Halobacterium; Halobacterium salinarium; Homeostasis; Hybrids; Ions; Kinetics; Metals; Microfluidic Microchips; Modeling; Molecular Profiling; Nutrient; Pathway interactions; Property; Pump; Regulation; Reporter; Statistical Models; Stimulus; System; Techniques; Time; Uncertainty; Zinc; base; cell type; cost; efflux pump; halobacteria; insight; interest; knockout gene; predictive modeling; response; shear stress; transcription factor

DESCRIPTION (provided by applicant): All cell types endure changes to their environments, and thus, have evolved remarkable ways to react to complex stimuli. Importantly, separate cell functions may combine directly or indirectly to handle such environmental perturbations. Accurate prediction of cellular behavior requires knowing how these functions are coordinated by gene regulation. Moreover, understanding how dynamic cross-talk affects these responses will provide important insights into the causes and appropriate treatments for adverse disease and drug side effects. The ways to do so vary greatly based on scales of interest. In small systems of few genes, models are typically formal chemical equations that offer great dynamical accuracy. Alternately, statistical approaches are more feasible to predict larger, more complex, global networks due to limited parameter data, high dimensionality, and nonlinearity. Hence, quantitative dynamic predictions are typically unavailable at the large scale, creating uncertainty in how small changes to underlying components affect global dynamics. I will address this issue using a multiscale approach that integrates a dynamic model of a small regulatory subcircuit into a statistically inferred, predictive, model of global gene regulation. I will study the copper (Cu) efflux pathway in H. salinarum NRC-1. Based on its regulatory architecture, the subcircuit is potentially bistable in expression of the Cu specific efflux pump yvgX. Yet, such bistability is not readily observed. Notably, H. salinarum NRC-1 also uses a multispecific efflux pump, zntA, to export Cu, which may explain the lack of bistability. I hypothesize that zntA regulation uses many of the same control-points (transcription factors, metallochaperone complexes, etc.) as yvgX and such regulatory sharing offers robust/rapid expression dynamics, but at the cost of regulatory cross-talk. Specifically, additional feedback from zntA forces transient yvgX expression to a high "ON" state in high Cu concentrations and a low "OFF" state in low/homeostatic amounts, avoiding bistability which is detrimental to the cell. However, cross-talk from zntA's sensitivity to other metal ions, namely zinc (Zn), disrupts Cu homeostasis, forcing the system closer to bistability. Moreover, by combining small and large scale modeling techniques, I should be able to predict system wide gene expression perturbations as a result of this cross-talk.

描述（由申请人提供）：所有类型的细胞都能忍受环境的变化，因此，它们已经进化出对复杂刺激做出反应的显着方式。重要的是，独立的细胞功能可以直接或间接地联合收割机来处理这种环境扰动。准确预测细胞行为需要知道这些功能是如何通过基因调控来协调的。此外，了解动态串扰如何影响这些反应将为不良疾病和药物副作用的原因和适当治疗提供重要见解。这样做的方式根据感兴趣的尺度而有很大的不同。在只有少量基因的小系统中，模型通常是形式化的化学方程，具有很高的动力学精度。另外，由于有限的参数数据、高维数和非线性，统计方法更适合预测更大、更复杂的全局网络。因此，通常无法在大尺度上进行定量动态预测，从而造成了基本组成部分的微小变化如何影响全球动态的不确定性。我将使用多尺度方法来解决这个问题，该方法将一个小的调控子回路的动态模型集成到一个统计推断的、预测的全局基因调控模型中。我将研究H. Salinarum NRC-1.基于其调节结构，该子回路可能在Cu特异性外排泵yvgX的表达中被抑制。然而，这样的双稳态是不容易观察到的。值得注意的是，H. salinarum NRC-1还使用多特异性外排泵zntA来输出Cu，这可以解释双稳态的缺乏。我假设zntA调节使用许多相同的控制点（转录因子，金属伴侣复合物等）。因为yvgX和这种调控共享提供了稳健/快速的表达动力学，但以调控串扰为代价。具体地，来自zntA的额外反馈迫使瞬时yvgX表达在高Cu浓度下处于高“开启”状态，并且在低/稳态量下处于低“关闭”状态，从而避免对细胞有害的双稳态。然而，zntA对其他金属离子（即锌（Zn））的敏感性产生的串扰会破坏铜的稳态，迫使系统更接近双稳态。此外，通过结合小规模和大规模的建模技术，我应该能够预测系统范围内的基因表达扰动作为这种串扰的结果。