Genetic Toggle Switch in Plants

IF 3.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Tessema K. Kassaw, Wenlong Xu, Christopher S. Zalewski, Katherine Kiwimagi, Ron Weiss, Mauricio S. Antunes, Ashok Prasad* and June I. Medford*, 
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引用次数: 0

Abstract

In synthetic biology, genetic components are assembled to make transcriptional units, and transcriptional units are assembled into circuits to perform specific and predictable functions of a genetic device. Genetic devices have been described in bacteria, mammalian cell cultures, and small organoids, yet the development of programmable genetic circuits for devices in plants has lagged. Programmable genetic devices require defining the component’s quantitative functions. Because plants have long life spans, studies often use transient analysis to define quantitative functions, while verification in stably engineered plants is often neglected and largely unknown. This raises the question if unique attributes of plants, such as environmental sensitivity, developmental plasticity, or alternation of generations, adversely impact predictability of plant genetic circuits and devices. Alternatively, it is also possible that genetic elements to produce predictable genetic devices for plants require rigorous characterization with detailed mathematical modeling. Here, we use plant genetic elements with quantitatively characterized transfer functions and developed in silico models to guide their assembly into a genetic device: a toggle switch or a mutually inhibitory gene-regulatory device. Our approach allows for computational selection of plant genetic components and iterative refinement of the circuit if the desired genetic functions are not initially achieved. We show that our computationally selected genetic circuit functions as predicted in stably engineered plants, including through tissue and organ differentiation. Developing abilities to produce predictable and programmable plant genetic devices opens the prospect of predictably engineering plant’s unique abilities in sustainable human and environmental systems.

植物的基因开关
在合成生物学中,遗传成分被组装成转录单位,转录单位被组装成电路,以执行遗传装置的特定和可预测的功能。遗传装置已经在细菌、哺乳动物细胞培养物和小型类器官中得到了描述,但用于植物装置的可编程遗传电路的发展滞后。可编程遗传设备需要定义组件的定量功能。由于植物的寿命很长,研究经常使用瞬态分析来定义定量函数,而在稳定工程植物中的验证往往被忽视,而且在很大程度上是未知的。这就提出了一个问题,即植物的独特属性,如环境敏感性、发育可塑性或世代交替,是否会对植物遗传回路和装置的可预测性产生不利影响。另一种可能是,为植物产生可预测的遗传装置的遗传元素需要用详细的数学模型进行严格的表征。在这里,我们使用具有定量特征传递函数的植物遗传元件,并开发了硅模型来指导它们组装成一个遗传装置:一个拨动开关或一个相互抑制的基因调控装置。如果期望的遗传功能最初没有实现,我们的方法允许植物遗传成分的计算选择和电路的迭代改进。我们表明,计算选择的遗传回路在稳定工程植物中发挥着预测的作用,包括通过组织和器官分化。发展生产可预测和可编程植物遗传设备的能力,为可预测的工程植物在可持续的人类和环境系统中的独特能力开辟了前景。
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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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