A Synthetic-Biology Approach to Study Scaling Properties of Self-Organized Patterns

研究自组织模式尺度特性的合成生物学方法

• 批准号: 1412459
• 负责人: Lingchong You
• 金额: $ 67.71万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1412459&HistoricalAwards=false
• 关键词: Synthetic; Biology; Approach; Study; Scaling

Using engineered gene circuits as a model system, the proposed work aims to examine the scaling properties of self-organized patterns. It focuses on a unique property, scale invariance, or maintenance of constant relative size of an organ with respect to the whole body during animal development or between individuals. The project represents a transformative application of synthetic biology to address unresolved, fundamental questions in biology. The proposed computational and experimental framework provides a well-defined context for exploring design principles that underlie generation of self-organized pattern formation as well as the emergent scaling properties. In addition to offering new biological insights, the proposed engineered systems can serve as the foundation for future engineering endeavors, such as fabrication of novel biomaterials. Furthermore, experimental techniques and computational infrastructure arising from the proposed work will be applicable for analyzing both natural and synthetic biological networks. Both computational and experimental systems and tools will be made available to the broad research community. Equally important, the research in this project will provide opportunities for pre-college students, undergraduates, and graduate students with backgrounds in biology, engineering, mathematics, and physical sciences to become exposed to interdisciplinary research in bioengineering and synthetic biology. Modeling examples and experiments derived from the proposed research, along with other examples drawn from the literature, will be used to train these students. In addition, the course and curriculum development will facilitate dissemination of knowledge in Systems and Synthetic Biology both at and beyond Duke University. Finally, to support both short-term and long-term education goals, the proposed efforts include development of a textbook on systems and synthetic biology that targets upper-level undergraduate students and starting graduate students.Technical description: The project aims to use a combination of mathematical modeling and experimental analysis of synthetic gene circuits to explore the fundamental mechanisms underlying scaling properties of self-organized patterns. Scale invariance refers to maintenance of constant relative size of an organ with respect to the whole body during animal development or between individuals. A number of mechanisms have been proposed to explain scale invariance in biological pattern formation. Regardless of their specific molecular interactions, however, the vast majority of these mechanisms require morphogen gradients as the spatial cue, which are either predefined or generated as part of the patterning process. In preliminary work, using Escherichia coli programmed by a synthetic gene circuit, the investigator has demonstrated the generation of perfect scale invariance of ring size versus colony size in robust, self-organized ring patterns of gene expression in the absence of an apparent morphogen gradient. This observation raises a fundamental, unresolved question: How does scale invariance occur in self-organized patterns in the absence of a spatial morphogen gradient? To address this question, the investigator proposes to develop and optimize an experimental platform to examine scaling properties of self-organized pattern formation in engineered bacteria. This platform couples inkjet printing technology and synthetic gene circuitry to explore the role of morphogen as a temporal cue in the pattern formation process, guided by mechanistically based mathematical models.This award is funded jointly by the Systems and Synthetic Biology Program in MCB and the Biotechnology, Biochemical and Biomass Engineering Program in CBET.

使用工程基因电路作为模型系统，提出的工作旨在研究自组织模式的缩放特性。它侧重于一种独特的性质，规模不变性，或维持恒定的相对大小相对于整个身体在动物的发展过程中或个体之间。该项目代表了合成生物学的变革性应用，以解决生物学中尚未解决的基本问题。所提出的计算和实验框架为探索自组织模式形成以及紧急缩放特性的基础设计原则提供了一个定义良好的背景。除了提供新的生物学见解外，所提出的工程系统还可以作为未来工程努力的基础，例如制造新型生物材料。此外，实验技术和计算基础设施提出的工作将适用于分析自然和合成生物网络。计算和实验系统和工具将提供给广泛的研究界。同样重要的是，该项目的研究将为具有生物学、工程学、数学和物理科学背景的大学预科学生、本科生和研究生提供机会，让他们接触到生物工程和合成生物学的跨学科研究。从所提出的研究中得出的建模示例和实验，以及从文献中得出的其他示例，将用于培训这些学生。此外，课程和课程开发将促进杜克大学内外系统和合成生物学知识的传播。最后，为了支持短期和长期的教育目标，提议的努力包括开发一本针对高年级本科生和研究生的系统和合成生物学教科书。技术描述：本项目旨在将合成基因电路的数学建模与实验分析相结合，探索自组织模式标度特性的基本机制。尺度不变性是指在动物发育过程中或个体之间，相对于整个身体而言，一个器官的相对大小保持恒定。已经提出了许多机制来解释生物模式形成中的尺度不变性。然而，不管它们的特定分子相互作用如何，这些机制中的绝大多数都需要形态发生梯度作为空间线索，这要么是预定义的，要么是作为模式过程的一部分生成的。在初步工作中，研究者利用合成基因电路编程的大肠杆菌，证明了在没有明显形态因子梯度的情况下，在强大的、自组织的基因表达环模式中，环大小与菌落大小的完美尺度不变性。这一观察提出了一个基本的、尚未解决的问题：在没有空间形态发生梯度的情况下，尺度不变性是如何在自组织模式中发生的？为了解决这个问题，研究者建议开发和优化一个实验平台来检查工程细菌中自组织模式形成的缩放特性。该平台结合喷墨打印技术和合成基因电路，在基于机械的数学模型的指导下，探索形态因子在图案形成过程中作为时间线索的作用。该奖项由MCB的系统和合成生物学项目以及CBET的生物技术、生化和生物质工程项目共同资助。