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Dynamic analysis of MAPK signaling using a high-throughput microfluidic single-cell imaging platform

机译:使用高通量微流单细胞成像平台动态分析MAPK信号

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摘要

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, kss1Δ, fus3Δ, msg5Δ, and ptp2Δ 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.
机译:细胞已经进化出生物分子网络,可以处理和响应不断变化的化学环境。要了解复杂的蛋白质相互作用如何引起新兴的网络特性,需要在大量遗传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,由于缺乏在可控且随时间变化的条件下进行可扩展细胞分析的技术,使得这种全局性研究成为不可能或不切实际。为了满足这一需求,我们开发了一种高通量微流控成像平台,用于在数百种遗传扰动和时变刺激序列组合下对网络响应进行单细胞研究。我们的平台将可编程的片上混合和灌注与高通量图像采集和处理相结合,以执行256个同时进行的延时活细胞成像实验。非粘附细胞被捕获在2,048个微流体细胞捕获器阵列中,以允许在12小时内对八种不同的基因型成像,并响应32个独特的刺激序列,每次运行共生成49,000张图像。我们使用12种设备进行了超过3,000个活细胞成像实验,以研究在遗传干扰和环境条件变化共同作用下酿酒酵母中交配信息素的反应。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和在静态条件下未观察到的新动态表型。例如,kss1Δ,fus3Δ,msg5Δ和ptp2Δ突变体表现出独特的依赖于刺激频率的信号表型,暗示了它们在过滤和网络记忆中的作用。并行微流控与高通量成像的结合为系统级的单细胞决策研究提供了强大的工具。

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