High-throughput tracking of single yeast cells in a microfluidic imaging matrix.
High-throughput tracking of single yeast cells in a microfluidic imaging matrix.
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DOI：
10.1039/c0lc00228c
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发表时间：
2011-02-07
期刊：
影响因子：
6.1
通讯作者：
Hansen CL
中科院分区：
文献类型：
--
作者：
Falconnet D;Niemistö A;Taylor RJ;Ricicova M;Galitski T;Shmulevich I;Hansen CL
延时活细胞成像是研究信号网络动力学和复杂性的强大工具，并且特别适合于响应动力学，噪声和遗传差异的单细胞研究。虽然传统的成像格式具有这种研究所需的时间和空间分辨率，但它们不能同时提供细胞跟踪、实验通量和精确化学控制的优点。这对于使用非粘附模式生物如酵母的系统水平研究尤其成问题，其中细胞的运动使跟踪复杂化，并且期望在各种遗传和化学扰动下进行大规模分析。我们在这里提出了一个高通量的微流控成像系统，能够在128个可编程和精确的化学控制的同时实验中跟踪多代单细胞。高分辨率成像和强大的细胞跟踪是通过使用机械夹持和琼脂糖凝胶聚合相结合的酵母细胞的固定实现的。我们的设备的通道和阀门架构允许形成128个集成琼脂糖凝胶垫的矩阵，每个都允许通过扩散进行完全可编程的介质交换的独立成像实验。我们证明了我们的系统在8种基因型和16种条件下的酵母信息素信号转导反应的组合和定量分析，并表明谱系依赖性效应有助于观察到的变异性在刺激条件下接近细胞决策的临界阈值。
Time-lapse live cell imaging is a powerful tool for studying signaling network dynamics and complexity and is uniquely suited to single cell studies of response dynamics, noise, and heritable differences. Although conventional imaging formats have the temporal and spatial resolution needed for such studies, they do not provide the simultaneous advantages of cell tracking, experimental throughput, and precise chemical control. This is particularly problematic for systems-level studies using non-adherent model organisms such as yeast, where the motion of cells complicates tracking and where large-scale analysis under a variety of genetic and chemical perturbations is desired. We present here a high-throughput microfluidic imaging system capable of tracking single cells over multiple generations in 128 simultaneous experiments with programmable and precise chemical control. High-resolution imaging and robust cell tracking is achieved through immobilization of yeast cells using a combination of mechanical clamping and polymerization in an agarose gel. The channel and valve architecture of our device allows for the formation of a matrix of 128 integrated agarose gel pads, each allowing for an independent imaging experiment with fully programmable medium exchange via diffusion. We demonstrate our system in the combinatorial and quantitative analysis of the yeast pheromone signaling response across 8 genotypes and 16 conditions, and show that lineage-dependent effects contribute to observed variability at stimulation conditions near the critical threshold for cellular decision making.
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