Applications of genetically-encoded biosensors for the construction and control of biosynthetic pathways.
Applications of genetically-encoded biosensors for the construction and control of biosynthetic pathways.
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DOI：
10.1016/j.ymben.2011.09.004
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发表时间：
2012-05
影响因子：
8.4
通讯作者：
Smolke, Christina D.
中科院分区：
文献类型：
--
作者：
Michener, Joshua K.;Thodey, Kate;Liang, Joe C.;Smolke, Christina D.
细胞中充满了生物传感器和分子系统，它们可以测量细胞的状态，并通过调节宿主的过程做出反应。就像工程师监控化学反应器一样，细胞使用这些传感器来监控细胞内环境的变化，并在环境变化的情况下产生一致的行为。虽然自然系统从途径调节中获得了明显的好处，但过去在工程细胞代谢方面的研究工作主要集中在引入新的途径和消除现有的途径调节。合成生物学是一个快速发展的领域，专注于开发支持生物系统设计、构建和优化的新工具。近年来，遗传编码生物传感器的设计以及这类分子工具在优化和调节异源通路方面的应用取得了新的进展。细胞代谢物的生物传感器可以直接从自然系统中获取，从自然传感器中工程化，或者完全在体外构建。当与报告者（如抗生素耐药性标记物）连接时，这些代谢物传感器可用于报告途径生产力，从而允许高通量筛选途径优化。未来的方向将集中在应用生物传感器将反馈控制引入代谢途径，提供动态控制策略，以提高细胞资源的有效利用和途径的可靠性。
Cells are filled with biosensors, molecular systems that measure the state of the cell and respond by regulating host processes. In much the same way that an engineer would monitor a chemical reactor, the cell uses these sensors to monitor changing intracellular environments and produce consistent behavior despite the variable environment. While natural systems derive a clear benefit from pathway regulation, past research efforts in engineering cellular metabolism have focused on introducing new pathways and removing existing pathway regulation. Synthetic biology is a rapidly growing field that focuses on the development of new tools that support the design, construction, and optimization of biological systems. Recent advances have been made in the design of genetically-encoded biosensors and the application of this class of molecular tools for optimizing and regulating heterologous pathways. Biosensors to cellular metabolites can be taken directly from natural systems, engineered from natural sensors, or constructed entirely in vitro. When linked to reporters, such as antibiotic resistance markers, these metabolite sensors can be used to report on pathway productivity, allowing high-throughput screening for pathway optimization. Future directions will focus on the application of biosensors to introduce feedback control into metabolic pathways, providing dynamic control strategies to increase the efficient use of cellular resources and pathway reliability.
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影响因子：
14.9
作者：
Edwards WR;Busse K;Allemann RK;Jones DD
通讯作者：
Jones DD
DOI：
10.1073/pnas.142089199
发表时间：
2002-07-23
影响因子：
11.1
作者：
Fehr, M;Frommer, WB;Lalonde, S
通讯作者：
Lalonde, S
影响因子：
15
作者：
FAMULOK, M
通讯作者：
FAMULOK, M
DOI：
10.1073/pnas.262420099
发表时间：
2002-12-24
影响因子：
11.1
作者：
Baker, K;Bleczinski, C;Cornish, VW
通讯作者：
Cornish, VW
影响因子：
4.8
作者：
Fehr, M;Lalonde, S;Frommer, WB
通讯作者：
Frommer, WB