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Pathway engineering via quorum sensing and sRNA riboregulators-interconnected networks and controllers.

机译:通过群体感应和sRNA核糖调节剂-互连的网络和控制器进行路径工程设计。

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The advent of genetic engineering has elevated our level of comprehension of cellular processes and functions. A natural progression of these findings is determining not only how these processes function within individual cells but also within a community. Bacterial cells monitor the conditions and microorganisms in their vicinity by producing, releasing and sensing chemical-signaling molecules. When a specific cell-density threshold is reached, a quorum is perceived, gene expression profiles are altered and the community orchestrates activities that are more effective en masse. This communication mechanism, in the language of autoinducers (AI), is referred to as quorum sensing (QS). It has become increasingly evident that while scientists attempt to decipher the intricacies of cellular communication and quorum sensing networks, we must remain conscious of the broader context of how a cell may identify itself in the environment and how this also impacts QS. Importantly, these phenomena span time and length scales by several orders in magnitude. Though the revelation of small RNAs, as both sensing and regulatory elements participating in the quorum sensing cascade, has connected new pieces of the puzzle, it has also added a new tier of uncertainty. The complexity of quorum sensing networks makes resolution of its diverse mechanisms difficult. The ability to design simpler networks with defined, more predictable or even "modular" elements will help elucidate these actions. Because it embraces innovative concepts of biological design accommodating the many length and time scales at play, synthetic biology serves as one of the most promising platforms for describing QS phenomena as well as enabling novel implementation strategies for biotechnological application.
机译:基因工程的出现提高了我们对细胞过程和功能的理解水平。这些发现的自然发展不仅决定了这些过程如何在单个细胞内起作用,而且还决定了在社区内的作用。细菌细胞通过产生,释放和感测化学信号分子来监测周围环境和微生物。当达到特定的细胞密度阈值时,将达到法定人数,基因表达谱将发生改变,并且社区将组织更有效的活动。用自动感应器(AI)语言表示的这种通信机制称为仲裁感应(QS)。越来越明显的是,尽管科学家试图破译蜂窝通信和群体感应网络的复杂性,但我们必须始终意识到细胞如何在环境中自我识别以及这如何影响QS的广阔背景。重要的是,这些现象跨越时间和长度尺度达几个数量级。尽管作为参与群体感应级联的感应元件和调节元件的小RNA的揭示连接了新的难题,但它也增加了新的不确定性。群体感应网络的复杂性使其解决各种机制变得困难。设计具有定义,更可预测甚至“模块化”元素的简单网络的能力将有助于阐明这些动作。由于合成生物学包含适应多种长度和时间尺度的生物学设计创新概念,因此合成生物学是描述QS现象以及实现生物技术应用新实施策略的最有希望的平台之一。

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