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Microfluidics for Synthetic Biology: developing technologies for study of gene networks in single cells and large populations.

机译:用于合成生物学的微流控技术:开发用于研究单细胞和大种群中的基因网络的技术。

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摘要

Bottom-up approach in understanding and developing gene networks calls for study of cells on a single cell level. Microfluidic technology provides such necessary tools to examine single cells not only in static but even more importantly in dynamic environments. Here we present studies that focus on examining model organisms of Escherichia coli and Saccharomyces cerevisiae on single cell and colony level. First, we developed a microfluidic device for studying single cell response of Galactose network of S. cerevisiae in fluctuating carbon source environment. As part of the study we have developed a novel off-chip technology that allows for fast and dynamic control of extracellular environment. In addition, this microfluidic device allows for 8 independent single cell level experiments to be run simultaneously. Next, this technology was adapted to study protein expression on single-protein level in E. coli. Furthermore, we developed a microfluidic device to study and characterize a colony-coupled synthetic oscillator in E. coli. To study the diffusion characteristics of the coupling agent the scale of the devices was increased from nominal 100,000 cells to include over 50 million cells. Lastly, we combined the ability to generate a dynamic environment with a large-scale device to study long-term population dynamics of two competing S. cerevisiae strains.
机译:自下而上的理解和发展基因网络的方法要求在单个细胞水平上研究细胞。微流体技术提供了这样的必要工具,不仅可以在静态环境中检查单个细胞,而且在动态环境中甚至更重要。在这里,我们目前的研究集中在单细胞和菌落水平上检查大肠杆菌和酿酒酵母的模型生物。首先,我们开发了一种微流体装置,用于研究在碳源环境变化的情况下酿酒酵母半乳糖网络的单细胞反应。作为研究的一部分,我们开发了一种新颖的片外技术,可快速动态地控制细胞外环境。另外,这种微流体装置允许同时进行8个独立的单细胞水平实验。接下来,该技术适用于研究大肠杆菌中单蛋白水平的蛋白表达。此外,我们开发了一种微流体装置,用于研究和鉴定大肠杆菌中菌落耦合的合成振荡器。为了研究偶联剂的扩散特性,器件的规模从标称的100,000个单元增加到超过5000万个单元。最后,我们将生成动态环境的能力与大型设备相结合,以研究两种竞争酿酒酵母菌株的长期种群动态。

著录项

  • 作者单位

    University of California, San Diego.;

  • 授予单位 University of California, San Diego.;
  • 学科 Engineering Biomedical.;Biology Bioinformatics.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 205 p.
  • 总页数 205
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:40:43

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