Combinatorial Engineering of Essentiality

基因突变以许多不同的方式影响它们的功能。任何生物体的基因组中都有数以千计的基因，因此破译每个基因的作用是一个重大挑战。该项目的重点是建立一个新的、更高效的技术平台，使研究人员能够有效地了解基因突变如何影响该基因编码的功能。这个使用合成生物学工具的平台将使研究人员能够更快地发展这种理解。这些努力是应用科学和基础科学中广泛应用的核心。它可能有助于开发用于生产药用蛋白质、酶、化学品或燃料的新菌株。它还将有助于开发对生物工程的未来至关重要的前沿工程范例。在这一平台的开发中，调查人员还将培训多名研究生和本科生，掌握尖端科学、技术、工程和数学(STEM)方法和技术。这些学生将在实验和计算方法、科学研究的设计、执行和报告以及知识产权的产生方面培养专业知识。合成生物学的一个基本目标是为生物系统的正向工程开发新的范例。典型的正向工程过程包括设计、构建、测试和学习(DBTL)阶段，理想情况下，这些阶段以循环和高度并行的方式执行，从而建立知识库、编码化设计规则和优化设计。在生物努力中，“DBTL”战略历来是通过“序列-活性关系(SAR)”突变图谱实现的，这种突变图谱传统上仅限于处理最小的生物系统。然而，DNA合成和测序技术的进步为扩展到基因组规模的新的大规模并行SAR方法铺平了道路。已经开发的几项技术将在一个普遍可访问的框架中进行优化，以供更大的合成生物学社区使用。这样的框架将使新的向前DBTL类型的工程战略在规模上比目前可用的方法先进一个数量级。这个项目的研究人员选择将他们的努力集中在模式细菌大肠杆菌中基因重要性的全面图谱上，因为这个模式系统不仅是展示他们的平台的理想之选，而且还将使他们能够解决关于重要性、进化性、上位性和适合性的基本问题。这将对遗传学、合成生物学和生物技术产生广泛的影响。

Mutations in genes affect their function in many different ways. There are thousands of genes in the genome of any organism, so it is a major challenge to decipher the role of each gene. The focus of this project is to build a new and more efficient technology platform that will enable researchers to efficiently understand how mutations in a gene affect the function encoded by that gene. This platform which uses the tools of synthetic biology will allow researchers to develop such understanding much more rapidly. Such efforts are central to a broad range of applications in both applied and basic science. It may help with the development of new strains for the production of pharmaceutical proteins, enzymes, chemicals, or fuels. It will also help to develop forward engineering paradigms central to the future of bioengineering. In the development of this platform, the investigators will also train multiple graduate and undergraduate students in cutting edge science, technology, engineering and mathematical (STEM) approaches and technologies. These students will develop expertise in experimental and computational methods, the design, execution, and reporting of scientific research, and the generation of intellectual property. A fundamental goal of synthetic biology is to develop new paradigms for the forward engineering of biological systems. The prototypical forward engineering process involves design, build, test, and learn (DBTL) stages, which ideally are performed in a cyclical and highly parallel fashion leading to the build up of knowledge bases, codified design rules, and optimized designs. In biological endeavors, the "DBTL" strategy has historically been realized through "sequence to activity relationship (SAR)" mutational mapping, which has traditionally been limited in throughput to addressing only the smallest of biological systems. Advances in DNA synthesis and sequencing technologies however, have paved the way for new massively parallel approaches to SAR that extend to the genome scale. Several technologies that have been developed will be optimized in a generally accessible framework for use by the larger synthetic biology community. Such a framework will enable new forward DBTL-type engineering strategies at scales that are orders of magnitude more advanced than methods currently available. The investigators in this project have chosen to focus their efforts on the comprehensive mapping of gene essentiality in the model bacterium Escherichia coli because this model system is not only ideal for demonstrating their platform but also will allow them to address foundational questions concerning essentiality, evolvability, epistasis and fitness. This will have broad implications across genetics, synthetic biology and biotechnology.