Biological Switches: Past and Future Milestones of Transcription Factor-Based Biosensors.

IF 3.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
ACS Synthetic Biology Pub Date : 2025-01-17 Epub Date: 2024-12-22 DOI:10.1021/acssynbio.4c00689
Brecht De Paepe, Marjan De Mey
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引用次数: 0

Abstract

Since the description of the lac operon in 1961 by Jacob and Monod, transcriptional regulation in prokaryotes has been studied extensively and has led to the development of transcription factor-based biosensors. Due to the broad variety of detectable small molecules and their various applications across biotechnology, biosensor research and development have increased exponentially over the past decades. Throughout this period, key milestones in fundamental knowledge, synthetic biology, analytical tools, and computational learning have led to an immense expansion of the biosensor repertoire and its application portfolio. Over the years, biosensor engineering became a more multidisciplinary discipline, combining high-throughput analytical tools, DNA randomization strategies, forward engineering, and advanced protein engineering workflows. Despite these advances, many obstacles remain to fully unlock the potential of biosensor technology. This review analyzes the timeline of key milestones on fundamental research (1960s to 2000s) and engineering strategies (2000s onward), on both the DNA and protein level of biosensors. Moreover, insights into the future perspectives, remaining hurdles, and unexplored opportunities of this promising field are discussed.

生物开关:过去和未来的里程碑转录因子为基础的生物传感器。
自1961年Jacob和Monod描述lac操纵子以来,原核生物的转录调控得到了广泛的研究,并导致了基于转录因子的生物传感器的发展。由于各种可检测的小分子及其在生物技术中的各种应用,生物传感器的研究和发展在过去几十年中呈指数级增长。在此期间,基础知识、合成生物学、分析工具和计算学习方面的关键里程碑导致了生物传感器曲目及其应用组合的巨大扩展。多年来,生物传感器工程成为一个多学科的学科,结合了高通量分析工具,DNA随机化策略,正向工程和先进的蛋白质工程工作流程。尽管取得了这些进步,但要充分释放生物传感器技术的潜力,仍存在许多障碍。本文分析了生物传感器在DNA和蛋白质水平上的基础研究(20世纪60年代至21世纪初)和工程策略(21世纪初以后)的关键里程碑的时间表。此外,本文还讨论了该领域的未来前景、存在的障碍和未开发的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.00
自引率
10.60%
发文量
380
审稿时长
6-12 weeks
期刊介绍: The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.
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