Department of Chemistry and Biochemistry, University of Colorado , Boulder, Colorado 80303, United States.
BioFrontiers Institute, University of Colorado , Boulder, Colorado 80303, United States.
Anal Chem. 2017 Sep 5;89(17):9601-9608. doi: 10.1021/acs.analchem.7b02933. Epub 2017 Aug 16.
Genetically encoded sensors based on fluorescence resonance energy transfer (FRET) are powerful tools for quantifying and visualizing analytes in living cells, and when targeted to organelles have the potential to define distribution of analytes in different parts of the cell. However, quantitative estimates of analyte distribution require rigorous and systematic analysis of sensor functionality in different locations. In this work, we establish methods to critically evaluate sensor performance in different organelles and carry out a side-by-side comparison of three different genetically encoded sensor platforms for quantifying cellular zinc ions (Zn). Calibration conditions are optimized for high dynamic range and stable FRET signals. Using a combination of single-cell microscopy and a novel microfluidic platform capable of screening thousands of cells in a few hours, we observe differential performance of these sensors in the cytosol compared to the ER of HeLa cells, and identify the formation of oxidative oligomers of the sensors in the ER. Finally, we use new methodology to re-evaluate the binding parameters of these sensors both in the test tube and in living cells. Ultimately, we demonstrate that sensor responses can be affected by different cellular environments, and provide a framework for evaluating future generations of organelle-targeted sensors.
基于荧光共振能量转移(FRET)的基因编码传感器是定量和可视化活细胞内分析物的强大工具,当靶向细胞器时,它们有可能定义分析物在细胞不同部位的分布。然而,分析物分布的定量估计需要对传感器在不同位置的功能进行严格和系统的分析。在这项工作中,我们建立了方法来批判性地评估不同细胞器中传感器的性能,并对用于定量细胞内锌离子(Zn)的三种不同基因编码传感器平台进行并排比较。我们优化了校准条件以实现高动态范围和稳定的 FRET 信号。使用单细胞显微镜和一种新的微流控平台的组合,该平台能够在几个小时内筛选数千个细胞,我们观察到这些传感器在细胞质中的性能与 HeLa 细胞内质网中的性能存在差异,并确定了传感器在 ER 中形成氧化寡聚物。最后,我们使用新的方法学在试管中和活细胞中重新评估这些传感器的结合参数。最终,我们证明传感器的响应可能会受到不同细胞环境的影响,并为评估下一代细胞器靶向传感器提供了框架。