小分子生物传感器的工程技术现状及其在代谢工程中的应用。

IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS
Patarasuda Chaisupa , R. Clay Wright
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引用次数: 0

摘要

基因编码的生物传感器对于增强我们对分子如何调节生物系统的理解至关重要。特别是小分子生物传感器,可以帮助我们了解化学物质和生物过程之间的相互作用。它们还通过增加筛选量和消除通过传统化学分析制备样品的需要来加速代谢工程。此外,它们在细胞分析物测量中提供了显著更高的空间和时间分辨率。在这篇综述中,我们讨论了代谢工程中体内生物传感器和控制系统中基于生物传感器的控制器的最新进展。我们还专门探索了基于蛋白质的生物传感器,与更普遍的转录因子和变构调节机制相比,这些传感器利用了不太常用的信号机制,如蛋白质稳定性和诱导降解。我们提出,这些较少使用的机制将对工程真核系统和生长较慢的原核系统具有重要意义,在这些系统中,蛋白质周转可能有助于更快速可靠地测量和调节当前细胞状态。最后,我们强调在基于蛋白质的生物传感器的开发中利用尖端和最先进的技术,通过合理设计、定向进化和协作方法实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering

Genetically encoded biosensors are crucial for enhancing our understanding of how molecules regulate biological systems. Small molecule biosensors, in particular, help us understand the interaction between chemicals and biological processes. They also accelerate metabolic engineering by increasing screening throughput and eliminating the need for sample preparation through traditional chemical analysis. Additionally, they offer significantly higher spatial and temporal resolution in cellular analyte measurements. In this review, we discuss recent progress in in vivo biosensors and control systems—biosensor-based controllers—for metabolic engineering. We also specifically explore protein-based biosensors that utilize less commonly exploited signaling mechanisms, such as protein stability and induced degradation, compared to more prevalent transcription factor and allosteric regulation mechanism. We propose that these lesser-used mechanisms will be significant for engineering eukaryotic systems and slower-growing prokaryotic systems where protein turnover may facilitate more rapid and reliable measurement and regulation of the current cellular state. Lastly, we emphasize the utilization of cutting-edge and state-of-the-art techniques in the development of protein-based biosensors, achieved through rational design, directed evolution, and collaborative approaches.

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来源期刊
SLAS Technology
SLAS Technology Computer Science-Computer Science Applications
CiteScore
6.30
自引率
7.40%
发文量
47
审稿时长
106 days
期刊介绍: SLAS Technology emphasizes scientific and technical advances that enable and improve life sciences research and development; drug-delivery; diagnostics; biomedical and molecular imaging; and personalized and precision medicine. This includes high-throughput and other laboratory automation technologies; micro/nanotechnologies; analytical, separation and quantitative techniques; synthetic chemistry and biology; informatics (data analysis, statistics, bio, genomic and chemoinformatics); and more.
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