4.8 Article

Multichannel Synchronous Hydrodynamic Gating Coupling with Concentration Gradient Generator for High-Throughput Probing Dynamic Signaling of Single Cells

期刊

ANALYTICAL CHEMISTRY
卷 92, 期 17, 页码 12062-12070

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AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.0c02746

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资金

  1. National Natural Science Foundation of China [31700746, 21775049]
  2. Fundamental Research Fund for the Central Universities [2020kfyXJJS034]

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Cell signaling greatly affected by complicated and temporally dynamic extracellular microenvironments controls most of the physiological functions in vivo. To reconstruct or simulate such microenvironments in vitro represents a fundamental approach for revealing the underlying mechanisms of those sophisticated processes. Recent advances in microfluidics have added a new dimension to cell signaling analysis, for example, concentration gradient generators (amplitude aspect) or hydrodynamic gating strategy (frequency aspect), but it is still challengeable to capture single-cell dynamic signaling in response to a mimicked extracellular microenvironment with varied stimuli waveforms of different amplitude and frequency in a high-throughput manner. In this article, we proposed a novel microfluidic strategy coupling multichannel synchronous hydrodynamic gating with microfluidic concentration gradient generators (mu MHG-CGG) to probe dynamic signaling of single cells with high throughput. The mu MHG-CGG allows rapid delivery of dynamic chemical signals in both high frequency (as high as 670 mHz) and multiple amplitude domains at the same time and simultaneously high-throughput probing cell dynamics at single-cell resolution in real time. By applying the proposed system, the mechanisms for encoding/decoding systems (termed frequency coding or amplitude coding) via GPCRs-mediated signaling pathways responding to histamine (HA) and adenosine triphosphate (ATP) in single HeLa cells were investigated. The optimal drug concentrations of single cells responses to HA and ATP individually or in combination were also successfully discussed, allowing us to obtain both single-cell heterogeneity and statistics from the cell population.

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