Synthetic Genetic Regulatory Networks to Study Emergent Properties of Development

用于研究发展的新兴特性的合成遗传调控网络

• 批准号: 1413044
• 负责人: Gregory Reeves
• 金额: $ 79.8万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1413044&HistoricalAwards=false
• 关键词: Synthetic; Genetic; Regulatory; Networks; Study

The award, funded by the Systems and Synthetic Biology Program in MCB and the Biotechnology, Biochemical and Biomass Engineering Program in the CBET, uses synthetic biology to address the properties of gene networks. Regulation of gene expression is crucial in many areas of biology, including differentiation, stem cell biology, and proper maintenance of tissues. To ensure proper gene expression, multiple genes regulate each other in a complex web of interactions called gene regulatory networks. One approach to understanding the function of a gene regulatory network is to try to construct that network using synthetic circuits, and then directly examine how the construction of the synthetic network impacts the stability and robustness of gene expression. In this project, investigators explore these concepts of stability and robustness, as well as sharpness in patterns of gene expression in the model organism, Drosophila melanogaster (the fruit fly). In order to create synthetic circuits in the fruit fly, the investigators will first develop new synthetic biology tools for controlling gene expression in a complex organism, such that these synthetic gene regulatory networks can be created. This work should lead to both new tools in synthetic biology for complex organisms as well as new understanding of gene regulatory network properties associated with pattern formation in the fruit fly. The investigators will also work with Science House, a North Carolina State University organization that oversees K-12 outreach to engage both high school students and teachers in the use of engineering principles in the study of biology, with a goal of enhancing participant?s appreciation and comfort with the use of quantitative tools in the study of biology.Technical description: Gene regulatory networks (GRNs), complex webs of genetic interactions, are hypothesized to explain emergent properties of developing tissues, such as the robustness and sharpness of gene expression. However, hypotheses of how these properties emerge from specific GRN motifs are difficult to verify, partly due to the high degree of complexity found in native GRNs. To overcome this difficulty, an alternative approach is proposed in which simpler, synthetic GRNs are designed to directly test these hypotheses. In this project, investigators will first develop tunable gene expression tools in Drosophila, including the use of ribozymes and other RNA expression control devices, as well as predictive tools for the design of such expression control devices. They will then investigate the robustness of gene expression when controlled by a negative feedback motif, as well as the sharpness of gene expression when controlled by a mutual repression motif. Previous studies of emergent properties of GRNs have produced as-yet untested hypotheses from computational models. This work will first develop standardized tools to tune gene expression levels in Drosophila, with expected applicability to other multicellular model organisms. The work will also test how specific GRN motifs result in the desired emergent properties of robustness and sharpness of gene expression boundaries. The work has broad applicability due to its focus on network motifs rather than specific systems or signaling pathways.

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资助，利用合成生物学来研究基因网络的特性。基因表达的调控在生物学的许多领域都是至关重要的，包括分化、干细胞生物学和组织的适当维护。为了确保正确的基因表达，多个基因在一个复杂的相互作用网络中相互调节，称为基因调节网络。了解基因调控网络功能的一种方法是尝试使用合成电路构建该网络，然后直接检查合成网络的构建如何影响基因表达的稳定性和鲁棒性。在这个项目中，研究人员探索了这些概念的稳定性和稳健性，以及在模式生物，果蝇（果蝇）的基因表达模式的清晰度。为了在果蝇中创建合成电路，研究人员将首先开发新的合成生物学工具来控制复杂生物体中的基因表达，这样就可以创建这些合成基因调控网络。这项工作将为复杂生物体的合成生物学提供新的工具，并为果蝇模式形成相关的基因调控网络特性提供新的认识。研究人员还将与北卡罗莱纳州立大学（North Carolina State University）的科学之家（Science House）合作，该组织负责监督K-12的推广工作，让高中生和教师在生物学研究中运用工程原理，目的是提高参与者的参与度。对在生物学研究中使用定量工具的赞赏和适应。技术描述：基因调控网络（grn），基因相互作用的复杂网络，被假设用来解释发育组织的紧急特性，如基因表达的稳健性和清晰度。然而，这些特性如何从特定的GRN基元中产生的假设很难验证，部分原因是在天然GRN中发现的高度复杂性。为了克服这一困难，提出了一种替代方法，即设计更简单的合成grn来直接测试这些假设。在本项目中，研究人员将首先在果蝇中开发可调基因表达工具，包括使用核酶和其他RNA表达控制装置，以及设计这种表达控制装置的预测工具。然后，他们将研究在负反馈基序控制下基因表达的稳健性，以及在相互抑制基序控制下基因表达的清晰度。以前对grn涌现特性的研究已经从计算模型中产生了尚未验证的假设。这项工作将首先开发标准化的工具来调整果蝇的基因表达水平，预计将适用于其他多细胞模式生物。这项工作还将测试特定的GRN基元如何导致基因表达边界的鲁棒性和清晰度的期望涌现特性。这项工作具有广泛的适用性，因为它关注的是网络基序，而不是特定的系统或信号通路。