QSB: Metabolic Engineering of Quorum Circuitry - A Systems Approach

QSB：群体回路的代谢工程 - 系统方法

• 批准号: 0222687
• 负责人: William Bentley
• 金额: $ 48.89万
• 依托单位: University of Maryland Biotechnology Institute
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-01 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0222687&HistoricalAwards=false
• 关键词: QSB; Metabolic; Engineering; Quorum; Circuitry

The long range goal of this project is to develop a computational formalism, built on stochastic Petri nets (SPN) that will enable accurate and dynamic calculation of all system variables and their variances. In particular, computational models of two Escherichia coli genetic circuits (emergence and decay of heat shock transcription factor, s?32, upon heat shock, and cell-to-cell communication or "quorum sensing") will be constructed, validated, and combined, suggesting the incremental assembly of predictive models that will ultimately predict system-wide behavior. Quorum sensing is known to determine the virulence of Pseudomonas aeruginosa (causative agent for cystic fibrosis), E. coli O157:H7 (Enterohemorrhagic E. coli), and Salmonella typhimurium (food poisoning). The focus is on the identification of signature genes that contribute to the synthesis and perception of autoinducer-2 (the signal molecule for quorum sensing), as well as the interplay between this circuit and the ?s32 circuit. By assembling combined circuits and by creating an optimization formalism that captures the stochastic variance, the Principal Investigators (PIs) will create an approach by which phenotype can be predicted, manipulated, and ultimately optimized. The specific optimization objective for the proposed work is to streamline the synthesis process of biologically active recombinant proteins in E. coli and it provides significant motivation for this work. It is expected that stochastic variance information is important in understanding these circuits. However, the approach is intended to evaluate this assertion at each stage of the work.

该项目的长期目标是开发一种基于随机Petri网（SPN）的计算形式，使所有系统变量及其方差的准确和动态计算成为可能。特别是，两个大肠杆菌遗传回路的计算模型(热休克转录因子的出现和衰变，s？根据热休克和细胞间通信（“群体感应”），将构建、验证和组合，表明预测模型的增量组装将最终预测系统范围的行为。已知群体感应可以确定铜绿假单胞菌（囊性纤维化的病原体）、大肠杆菌O157:H7（肠出血性大肠杆菌）和鼠伤寒沙门氏菌（食物中毒）的毒力。重点是识别有助于自动诱导-2（群体感应的信号分子）的合成和感知的特征基因，以及该电路与？s32电路。通过组装组合电路并创建捕获随机方差的优化形式，首席研究员（pi）将创建一种可以预测、操纵并最终优化表型的方法。该优化的具体目标是简化大肠杆菌中具有生物活性的重组蛋白的合成过程，这为该工作提供了重要的动力。预计随机方差信息在理解这些电路中是重要的。然而，该方法旨在在工作的每个阶段评估这一断言。