Schneider Falk, Waithe Dominic, Lagerholm B Christoffer, Shrestha Dilip, Sezgin Erdinc, Eggeling Christian, Fritzsche Marco
Institute of Applied Optics, Friedrich-Schiller-University and Leibniz Institute of Photonic Technology, Helmholtzweg 4 , 07743 Jena , Germany.
Kennedy Institute for Rheumatology , University of Oxford , Roosevelt Drive , Oxford OX3 7LF , United Kingdom.
ACS Nano. 2018 Aug 28;12(8):8540-8546. doi: 10.1021/acsnano.8b04080. Epub 2018 Jul 26.
Cells rely on versatile diffusion dynamics in their plasma membrane. Quantification of this often heterogeneous diffusion is essential to the understanding of cell regulation and function. Yet such measurements remain a major challenge in cell biology, usually due to low sampling throughput, a necessity for dedicated equipment, sophisticated fluorescent label strategies, and limited sensitivity. Here, we introduce a robust, broadly applicable statistical analysis pipeline for large scanning fluorescence correlation spectroscopy data sets, which uncovers the nanoscale heterogeneity of the plasma membrane in living cells by differentiating free from hindered diffusion modes of fluorescent lipid and protein analogues.
细胞依赖其质膜中多样的扩散动力学。对这种通常具有异质性的扩散进行量化，对于理解细胞调节和功能至关重要。然而，此类测量在细胞生物学中仍然是一项重大挑战，这通常是由于采样通量低、需要专用设备、复杂的荧光标记策略以及灵敏度有限。在这里，我们为大型扫描荧光相关光谱数据集引入了一种强大且广泛适用的统计分析流程，该流程通过区分荧光脂质和蛋白质类似物的自由扩散模式与受阻扩散模式，揭示活细胞中质膜的纳米级异质性。
