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利用合成生物学设计空间模式。

Using Synthetic Biology to Engineer Spatial Patterns.

作者信息

Santos-Moreno Javier, Schaerli Yolanda

机构信息

Department of Fundamental Microbiology, University of Lausanne, Biophore Building, 1015, Lausanne, Switzerland.

出版信息

Adv Biosyst. 2019 Apr;3(4):e1800280. doi: 10.1002/adbi.201800280. Epub 2018 Dec 17.

DOI:10.1002/adbi.201800280
PMID:32627430
Abstract

Synthetic biology has emerged as a multidisciplinary field that provides new tools and approaches to address longstanding problems in biology. It integrates knowledge from biology, engineering, mathematics, and biophysics to build-rather than to simply observe and perturb-biological systems that emulate natural counterparts or display novel properties. The interface between synthetic and developmental biology has greatly benefitted both fields and allowed to address questions that would remain challenging with classical approaches due to the intrinsic complexity and essentiality of developmental processes. This Progress Report provides an overview of how synthetic biology can help to understand a process that is crucial for the development of multicellular organisms: pattern formation. It reviews the major mechanisms of genetically encoded synthetic systems that have been engineered to establish spatial patterns at the population level. Limitations, challenges, applications, and potential opportunities of synthetic pattern formation are also discussed.

摘要

合成生物学已成为一个多学科领域,它提供了新的工具和方法来解决生物学中长期存在的问题。它整合了生物学、工程学、数学和生物物理学等多学科知识,旨在构建而非仅仅观察和扰动生物系统,这些生物系统能够模拟天然对应物或展现出新颖的特性。合成生物学与发育生物学之间的交叉融合极大地促进了这两个领域的发展,并使得人们能够解决一些因发育过程的内在复杂性和重要性而用传统方法仍具挑战性的问题。本进展报告概述了合成生物学如何有助于理解一个对多细胞生物体发育至关重要的过程:模式形成。报告回顾了已被设计用于在群体水平上建立空间模式的基因编码合成系统的主要机制。同时也讨论了合成模式形成的局限性、挑战、应用及潜在机遇。

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