Biodiversity and Ecosystem Informatics - BDEI -Bioinformatic Prediction of Functions of Unculturable Microbes in Ecosystems
Biodiversity and Ecosystem Informatics - BDEI -Bioinformatic Prediction of Functions of Unculturable Microbes in Ecosystems
批准号:
0131899
负责人:
Allan Dickerman
金额:
$10.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-10-01 至 2003-09-30
中文摘要
迪克森、阿兰维吉尼亚理工学院和州立大学SUMMARYCells经常执行复杂的计算任务,使它们能够控制数千个基因的编排,并与其他细胞进行交流,以表现出生长和分化等紧急特性。理解和设计细胞复杂计算机制的算法应该对科学和技术,特别是生物技术、生物计算和医学产生重大影响。最近几个值得注意的报告表明,在大肠杆菌中设计和构建简单的去核遗传电路是可能的。这项工作还揭示了,即使是最简单的电路在体内的实现也需要对通常知之甚少的DNA-相互作用、mRNA和蛋白质稳定性进行繁琐的优化。在其他参数中,我们建议开发高效的进化设计策略来构建功能从头开始的遗传电路。我们将应用分子进化的方法,这些方法已经被证明在设计具有改进或改变性质的蛋白质方面非常成功,并应用于涉及多个抑制子、操作符和启动子的复杂遗传系统。我们相信进化将被证明普遍适用于优化单个设备以及复杂的遗传电路,我们的目标是展示如何最好地执行进化搜索以建立设备库并将它们组装成功能电路。
英文摘要
EIA-0131899Dickerson, AllanVirginia Polytechnic Institute and State UniversitySUMMARYCells routinely perform complex computational tasks that enable them to control the orchestrationof thousands of genes and communicate with other cells to manifest emergent properties such as growthand differentiation.Understanding and engineering the algorithms underlying the complex computationalmachinery of cells should have significant impact in science and technology,particularly biotechnology,biocomputation and medicine.Several notable recent reports demonstrate that it is possible to design and construct simple denovo genetic circuits such as a switch and an oscillator in Escherichia coli .This work also revealed thatimplementation of even the most simple circuits in vivo requires tedious optimization of often poorly-understood protein-DNA interactions and mRNA and protein stabilities,among other parameters.Wepropose to develop efficient,evolutionary design strategies for constructing functional de novo geneticcircuits.We will apply methods of molecular evolution,which have proven highly successful forengineering proteins with improved or altered properties,to complex genetic systems involving multiplerepressors,operators,and promoters.We believe that evolution will prove to be generally applicable foroptimizing individual devices as well as complex genetic circuits,and our goal will be to demonstratehow evolutionary searches are best performed in order to build libraries of devices and assemble theminto functional circuits.
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