Taylor R J, Falconnet D, Niemistö A, Ramsey S A, Prinz S, Shmulevich I, Galitski T, Hansen C L
Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA.
Proc Natl Acad Sci U S A. 2009 Mar 10;106(10):3758-63. doi: 10.1073/pnas.0813416106. Epub 2009 Feb 17.
Cells have evolved biomolecular networks that process and respond to changing chemical environments. Understanding how complex protein interactions give rise to emergent network properties requires time-resolved analysis of cellular response under a large number of genetic perturbations and chemical environments. To date, the lack of technologies for scalable cell analysis under well-controlled and time-varying conditions has made such global studies either impossible or impractical. To address this need, we have developed a high-throughput microfluidic imaging platform for single-cell studies of network response under hundreds of combined genetic perturbations and time-varying stimulant sequences. Our platform combines programmable on-chip mixing and perfusion with high-throughput image acquisition and processing to perform 256 simultaneous time-lapse live-cell imaging experiments. Nonadherent cells are captured in an array of 2,048 microfluidic cell traps to allow for the imaging of eight different genotypes over 12 h and in response to 32 unique sequences of stimulation, generating a total of 49,000 images per run. Using 12 devices, we carried out >3,000 live-cell imaging experiments to investigate the mating pheromone response in Saccharomyces cerevisiae under combined genetic perturbations and changing environmental conditions. Comprehensive analysis of 11 deletion mutants reveals both distinct thresholds for morphological switching and new dynamic phenotypes that are not observed in static conditions. For example, kss1Delta, fus3Delta, msg5Delta, and ptp2Delta mutants exhibit distinctive stimulus-frequency-dependent signaling phenotypes, implicating their role in filtering and network memory. The combination of parallel microfluidic control with high-throughput imaging provides a powerful tool for systems-level studies of single-cell decision making.
细胞进化出了生物分子网络,用于处理和响应不断变化的化学环境。要理解复杂的蛋白质相互作用如何产生网络的涌现特性,需要在大量基因扰动和化学环境下对细胞反应进行时间分辨分析。迄今为止,缺乏在良好控制和时变条件下进行可扩展细胞分析的技术,使得此类全局研究要么无法进行,要么不切实际。为满足这一需求,我们开发了一种高通量微流控成像平台,用于在数百种组合基因扰动和时变刺激序列下对单细胞网络反应进行研究。我们的平台将可编程的芯片上混合和灌注与高通量图像采集和处理相结合,以进行256个同时的延时活细胞成像实验。非贴壁细胞被捕获在2048个微流控细胞阱阵列中,以便在12小时内对八种不同基因型进行成像,并响应32种独特的刺激序列,每次运行共生成49000张图像。使用12个设备,我们进行了3000多次活细胞成像实验,以研究酿酒酵母在组合基因扰动和变化环境条件下的交配信息素反应。对11个缺失突变体的综合分析揭示了形态转换的不同阈值以及在静态条件下未观察到的新动态表型。例如,kss1Delta、fus3Delta、msg5Delta和ptp2Delta突变体表现出独特的刺激频率依赖性信号表型,暗示它们在过滤和网络记忆中的作用。并行微流控控制与高通量成像的结合为单细胞决策的系统级研究提供了一个强大的工具。