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ME: Strategies for Metabolic Engineering of Environmental Microorganisms - Applications to Degradation of Organophosphate Contaminants

ME: Strategies for Metabolic Engineering of Environmental Microorganisms - Applications to Degradation of Organophosphate Contaminants
ME:环境微生物代谢工程策略 - 在有机磷污染物降解中的应用
批准号:
9814088
负责人:
Jay Keasling
金额:
$26.5万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1998
资助国家:
美国
项目状态:
已结题
起止时间:
1998-12-01 至 2001-11-30

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中文摘要
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英文摘要
This proposal seeks to develop the experimental and theoretical methods to introduce multiple, heterologous, biodegradation pathways into a single organism and optimize the flux through those pathways for the remediation of toxic or recalcitrant organic contaminants. The project will focus the biodegradation of parathion as a model compound since: (1) it has been widely used as a pesticide; (2) it could potentially serve as a source for carbon, phosphorus, and sulfur for cell growth; (3) no single organism has been isolated that can use parathion as a sole carbon and phosphorus source; and (4) it is similar in structure to a number of other important environmental contaminants, such as nerve agents and other pesticides. An engineered form of Pseudomonas putida will be used as a model organism.
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FMRG: Digital Light Manufacturing for the Circular Economy
  • 批准号:
    2036849
  • 项目类别:
    Standard Grant
  • 资助金额:
    $370.61万
  • 财政年份:
    2020
  • 负责人:
    Jay Keasling
  • 依托单位:
Physical regulation of cellular respiration by membrane lipid composition
  • 批准号:
    1715681
  • 项目类别:
    Standard Grant
  • 资助金额:
    $62.53万
  • 财政年份:
    2017
  • 负责人:
    Jay Keasling
  • 依托单位:
Indo-US Workshop on "Cell Factories" to be held in Mumbai, India
  • 批准号:
    1630180
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.59万
  • 财政年份:
    2016
  • 负责人:
    Jay Keasling
  • 依托单位:
Design Principles for Engineering Biology - Hyatt Regency, Tysons, VA - November 11 & 12, 2015
  • 批准号:
    1565318
  • 项目类别:
    Standard Grant
  • 资助金额:
    $7.54万
  • 财政年份:
    2015
  • 负责人:
    Jay Keasling
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis