Logic integration of mRNA signals by an RNAi-based molecular computer.
Logic integration of mRNA signals by an RNAi-based molecular computer.
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DOI：
10.1093/nar/gkq117
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发表时间：
2010-05
影响因子：
14.9
通讯作者：
Benenson Y
中科院分区：
文献类型：
--
作者：
Xie Z;Liu SJ;Bleris L;Benenson Y
合成的体内分子“计算机”可以通过在分子信号和生物反应之间建立可编程的非天然途径来重新连接生物过程。多个分子计算机原型已被证明可以在简单的缓冲溶液中工作。这些原型中的许多是由DNA链组成的，并使用退火消化或链置换的循环进行计算。我们之前已经介绍了基于RNA干扰（RNAi）的计算作为在体内实现复杂分子逻辑的一种方式。因为它也依赖于核酸的运作，RNAi计算可以从为DNA系统开发的工具中受益。然而，这些工具必须被利用来生产生物活性成分，并适应反映体内条件的恶劣操作环境。在实现这一目标的一步，我们报告的建设和实施的生物传感器，'生物活性，小干扰RNA分子的mRNA水平通过RNA链交换在无细胞果蝇胚胎裂解液，一步超越简单的缓冲环境。我们进一步将传感器与我们的RNAi“计算”模块集成，以评估mRNA浓度的双输入逻辑函数。我们的研究结果显示了RNA链交换如何扩大RNAi计算的效用，并指出了在天然生物环境中使用链交换的可能性。
Synthetic in vivo molecular ‘computers’ could rewire biological processes by establishing programmable, non-native pathways between molecular signals and biological responses. Multiple molecular computer prototypes have been shown to work in simple buffered solutions. Many of those prototypes were made of DNA strands and performed computations using cycles of annealing-digestion or strand displacement. We have previously introduced RNA interference (RNAi)-based computing as a way of implementing complex molecular logic in vivo. Because it also relies on nucleic acids for its operation, RNAi computing could benefit from the tools developed for DNA systems. However, these tools must be harnessed to produce bioactive components and be adapted for harsh operating environments that reflect in vivo conditions. In a step toward this goal, we report the construction and implementation of biosensors that ‘transduce’ mRNA levels into bioactive, small interfering RNA molecules via RNA strand exchange in a cell-free Drosophila embryo lysate, a step beyond simple buffered environments. We further integrate the sensors with our RNAi ‘computational’ module to evaluate two-input logic functions on mRNA concentrations. Our results show how RNA strand exchange can expand the utility of RNAi computing and point toward the possibility of using strand exchange in a native biological setting.
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影响因子：
11.4
作者：
Elbashir, SM;Martinez, J;Tuschl, T
通讯作者：
Tuschl, T
影响因子：
14.9
作者：
Bartlett DW;Davis ME
通讯作者：
Davis ME
影响因子：
56.9
作者：
LIPTON, RJ
通讯作者：
LIPTON, RJ
DOI：
10.1073/pnas.0404443101
发表时间：
2004-08-03
影响因子：
11.1
作者：
Golding, I;Cox, EC
通讯作者：
Cox, EC
影响因子：
1.6
作者：
Head, T;Rozenberg, G;Spaink, HP
通讯作者：
Spaink, HP