CAREER: Artificial Pattern Formation with Synthetic Gene Networks

职业：利用合成基因网络形成人工模式

• 批准号: 0448244
• 负责人: Ron Weiss
• 金额: $ 58.3万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-05-01 至 2010-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0448244&HistoricalAwards=false
• 关键词: CAREER; Artificial; Pattern; Formation; Synthetic

Biological pattern formation is an elaborate process that requires spatiotemporal coordination of cellular activities. To-date, research has focused on studying naturally occurring patterns either by devising abstract models that explain the formation of these patterns or by characterizing relevant genetic circuits and biochemical interactions. The knowledge gained from understanding how cells form patterns has practical applications in tissue engineering, biosensing, and biomaterial fabrication. However, to fully realize the potential of these applications one must be able to form arbitrary patterns, e.g. tissues with new arrangements of cells. Existing efforts to coerce cells to form particular patterns have largely focused on setting up scaffolds and appropriate environmental conditions, but such efforts are limited because they rely on the cells' existing genetic circuitry. The approach in this project is fundamentally different: the focus is to engineer de novo patterns by building synthetic gene networks and in the process gain a greater understanding of pattern formation. The project strives to create a new engineering discipline for generating user-specified artificial differentiation patterns. The main component of this discipline is the tight integration of modeling tools with experimental work. Based on these models, novel genetic circuits will be built and validated experimentally. These circuits will direct cells to form stable and dynamic spatiotemporal gene expression patterns - lines, standing waves, Turing Patterns, Conway's Game of Life, and branched structures. Results from the project will serve as the basis for a pattern formation toolkit that will be used to engineer more complex patterns, enable future applications, and elucidate the underlying principles governing natural pattern formation. The research outlined here will have a broad impact both in academia and industry. This project will advance knowledge in a number of important areas in systems biology including the understanding of robust gene networks, noise in gene expression, gene regulation, cell-cell communications, in addition to providing mathematical models for intracellular and intercellular systems. Research in multicellular pattern formation is not only fundamental to understanding organism development and coordinated cell behavior, but also has practical applications. For example, micro-pattern formation will benefit nanotechnology where such patterns could be used for bacterial nano-fabrication. Also, the ability to construct synthetic patterns will contribute to the field of tissue engineering, where such patterns could be utilized to differentiate stem cells into tissues and organs. In the long term, knowledge gained from this research into the coordination of cell behaviors will be applicable to areas outside of biology, including the design of robust multi-agent systems such as computer networks. Perhaps the most important contribution will be through the multidisciplinary education of students and future leaders in the field. This will be accomplished through various activities including the Burroughs Wellcome Fund and the Synthetic Biology Summer Program, where the focus is on recruiting and providing specific funding for underrepresented minorities and women.

生物模式的形成是一个复杂的过程，需要细胞活动的时空协调。迄今为止，研究的重点是研究自然发生的模式，要么通过设计抽象的模型来解释这些模式的形成，要么通过表征相关的遗传电路和生化相互作用。从理解细胞如何形成图案中获得的知识在组织工程、生物传感和生物材料制造中具有实际应用。然而，为了充分实现这些应用的潜力，必须能够形成任意图案，例如具有新细胞排列的组织。现有的迫使细胞形成特定模式的努力主要集中在建立支架和适当的环境条件上，但这种努力是有限的，因为它们依赖于细胞现有的遗传电路。这个项目的方法是根本不同的：重点是通过构建合成基因网络来设计从头模式，并在此过程中获得对模式形成的更好理解。该项目致力于创建一个新的工程学科，用于生成用户指定的人工分化模式。该学科的主要组成部分是建模工具与实验工作的紧密集成。基于这些模型，新型的遗传电路将被建立和实验验证。 这些回路将指导细胞形成稳定和动态的时空基因表达模式-线条，驻波，图灵模式，康威的生命游戏和分支结构。 该项目的结果将作为模式形成工具包的基础，该工具包将用于设计更复杂的模式，使未来的应用成为可能，并阐明自然模式形成的基本原理。 这里概述的研究将在学术界和工业界产生广泛的影响。 该项目将推进系统生物学许多重要领域的知识，包括对强大基因网络、基因表达噪音、基因调控、细胞间通讯的理解，以及为细胞内和细胞间系统提供数学模型。多细胞模式形成的研究不仅是理解生物体发育和协调细胞行为的基础，而且具有实际应用价值。例如，微图案的形成将有利于纳米技术，其中这种图案可用于细菌纳米制造。此外，构建合成模式的能力将有助于组织工程领域，其中这种模式可用于将干细胞分化为组织和器官。从长远来看，从细胞行为协调研究中获得的知识将适用于生物学以外的领域，包括设计强大的多智能体系统，如计算机网络。也许最重要的贡献将是通过对学生和该领域未来领导人的多学科教育。这将通过各种活动来实现，包括Burroughs Wellcome基金和合成生物学暑期项目，重点是为代表性不足的少数民族和妇女招聘和提供具体资金。