从定性到定量:植物合成生物学的现状和挑战

IF 0.6 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Chenfei Tian, Jianhua Li, Yong Wang
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引用次数: 0

摘要

蓬勃发展的植物科学促进了数据数量的爆炸式增长和工具包的扩展。植物合成生物学仍处于早期阶段,需要更多的定量和可预测的研究。尽管面临挑战,一些开创性的例子已经成功地在模式植物中得到了证明。随着越来越多的合成开关和电路被用于植物系统以及在植物底盘中生产的合成产品,植物合成生物学在农业和医学中站稳了坚实的脚跟。不断爆炸的数据也促进了该领域工具包的扩展。遗传部分文库和定量表征方法已经开发。然而,植物合成生物学仍处于起步阶段。选择生物部件来设计和构建具有可预测功能的遗传电路的考虑仍然是需要的。结果综述了近年来植物合成生物学领域的生物技术进展。讨论了遗传部件和遗传电路的装配标准化和定量化方法。我们还强调了将新性状引入植物的设计-构建-测试-学习迭代周期中的主要挑战。结论植物合成生物学有望为农业生产、人类健康和环境可持续性等诸多问题提供重要的解决方案。然而,这一领域存在着巨大的挑战。例如,遗传部分的定量表征是有限的;电路的正交性和传递函数是不可预测的;此外,数学建模辅助电路设计仍然需要提高可预测性和可靠性。随着人们对这一领域的兴趣日益浓厚,这些挑战有望在不久的将来得到解决。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From qualitative to quantitative: the state of the art and challenges for plant synthetic biology
The flourishing plant science promotes the exploding number of data and the expansion of toolkits. Plant synthetic biology is still in its early stages and requires more quantitative and predictable study. Despite the challenges, some pioneering examples have been successfully demonstrated in model plants. Backgrounds As an increasing number of synthetic switches and circuits have been created for plant systems and of synthetic products produced in plant chassis, plant synthetic biology is taking a strong foothold in agriculture and medicine. The ever‐exploding data has also promoted the expansion of toolkits in this field. Genetic parts libraries and quantitative characterization approaches have been developed. However, plant synthetic biology is still in its infancy. The considerations for selecting biological parts to design and construct genetic circuits with predictable functions remain desired. Results In this article, we review the current biotechnological progresses in field of plant synthetic biology. Assembly standardization and quantitative approaches of genetic parts and genetic circuits are discussed. We also highlight the main challenges in the iterative cycles of design‐build‐test‐learn for introducing novel traits into plants. Conclusion Plant synthetic biology promises to provide important solutions to many issues in agricultural production, human health care, and environmental sustainability. However, tremendous challenges exist in this field. For example, the quantitative characterization of genetic parts is limited; the orthogonality and the transfer functions of circuits are unpredictable; and also, the mathematical modeling‐assisted circuits design still needs to improve predictability and reliability. These challenges are expected to be resolved in the near future as interests in this field are intensifying.
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来源期刊
Quantitative Biology
Quantitative Biology MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
5.00
自引率
3.20%
发文量
264
期刊介绍: Quantitative Biology is an interdisciplinary journal that focuses on original research that uses quantitative approaches and technologies to analyze and integrate biological systems, construct and model engineered life systems, and gain a deeper understanding of the life sciences. It aims to provide a platform for not only the analysis but also the integration and construction of biological systems. It is a quarterly journal seeking to provide an inter- and multi-disciplinary forum for a broad blend of peer-reviewed academic papers in order to promote rapid communication and exchange between scientists in the East and the West. The content of Quantitative Biology will mainly focus on the two broad and related areas: ·bioinformatics and computational biology, which focuses on dealing with information technologies and computational methodologies that can efficiently and accurately manipulate –omics data and transform molecular information into biological knowledge. ·systems and synthetic biology, which focuses on complex interactions in biological systems and the emergent functional properties, and on the design and construction of new biological functions and systems. Its goal is to reflect the significant advances made in quantitatively investigating and modeling both natural and engineered life systems at the molecular and higher levels. The journal particularly encourages original papers that link novel theory with cutting-edge experiments, especially in the newly emerging and multi-disciplinary areas of research. The journal also welcomes high-quality reviews and perspective articles.
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