Collaborative Research: Multidimensional single-cell phenotyping for elucidating genome to phenome relationships

这个项目的目的是开发方法并应用它们来更好地理解细胞如何同时最佳地执行多个任务，例如大量高效地生长和合成生物燃料。这些发现有望加速正在进行的利用生物系统作为工厂生产高价值化学品的努力，从而促进更可持续的生物经济。该项目还将为在科学领域缺乏代表性的高中生和本科生提供特殊的培训机会，重点是将物理和工程科学的数学严谨性转移到生物学上。此外，该项目是高度跨学科的，因此为研究生提供了特殊的培训机会，以解决多因素的社会需求。系统生物学极大地提高了我们对细胞进行编程以执行特定任务的能力。然而，随着所需任务数量的增加，生物系统的复杂性限制了我们编程或探索同时最佳执行多项任务的细胞基础的能力。该项目将通过单细胞分辨率的组合突变文库的转化微流控筛选来解决这一挑战。单细胞分辨率将使直接从生长培养中选择突变体以及量化细胞噪声成为可能。通过将所提出的方法应用于一个重要的生物燃料平台，并将实验结果与基因组尺度的代谢模型相结合，该项目将产生多维表型性状和细胞间表型异质性的全基因组起源的基础知识。该项目由MCB部门的系统和合成生物学集群以及刺激竞争研究的既定计划（EPSCoR）共同资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The aim of this project is to develop methods and apply them to better understand how cells can optimally perform more than one task simultaneously, such as to grow and to synthesize biofuels at high quantities and efficiently. These findings are expected to accelerate ongoing efforts that employ biological systems as factories to produce high-value chemicals, and, thus, contribute to a more sustainable bioeconomy. This project will also offer exceptional training opportunities to high school and undergraduate students underrepresented in science, with a focus on transferring the mathematical rigor of physical and engineering sciences to biology. Further, this project is highly interdisciplinary, thus offering exceptional training opportunities to graduate students towards professional careers that address multifactorial societal needs.Systems biology has greatly improved our ability to program cells to perform a specific task. As the number of desired tasks increases, however, the complexity of biological systems restricts our ability to program or explore the foundation of cells that optimally perform multiple tasks simultaneously. This project will address this challenge via transformative microfluidic screening of combinatorial mutant libraries with single-cell resolution. Single-cell resolution will critically enable the selection of mutants directly from growing cultures, as well as quantify cellular noise. By applying the proposed method to an important biofuel platform and by combining the experimental results with genome-scale metabolic models, the project will generate fundamental knowledge on the genome-wide origins of multidimensional phenotypic traits and cell-to-cell phenotypic heterogeneity. This project is jointly funded by Systems and Synthetic Biology Cluster of the MCB Division and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.