Laboratoire d'Optique Biomédicale, École Polytechnique Fédérale de Lausanne, STI-IBI, CH-1015, Lausanne, Switzerland.
Department of Radioelectronics, FEE, Czech Technical University in Prague, 166 27, Prague, Czech Republic.
Nat Commun. 2017 Nov 23;8(1):1731. doi: 10.1038/s41467-017-01857-x.
Quantitative approaches for characterizing molecular organization of cell membrane molecules under physiological and pathological conditions profit from recently developed super-resolution imaging techniques. Current tools employ statistical algorithms to determine clusters of molecules based on single-molecule localization microscopy (SMLM) data. These approaches are limited by the ability of SMLM techniques to identify and localize molecules in densely populated areas and experimental conditions of sample preparation and image acquisition. We have developed a robust, model-free, quantitative clustering analysis to determine the distribution of membrane molecules that excels in densely labeled areas and is tolerant to various experimental conditions, i.e. multiple-blinking or high blinking rates. The method is based on a TIRF microscope followed by a super-resolution optical fluctuation imaging (SOFI) analysis. The effectiveness and robustness of the method is validated using simulated and experimental data investigating nanoscale distribution of CD4 glycoprotein mutants in the plasma membrane of T cells.
在生理和病理条件下，定量方法可用于描述细胞膜分子的分子组织，这得益于最近开发的超分辨率成像技术。目前的工具利用统计算法，根据单分子定位显微镜 (SMLM) 数据确定分子簇。这些方法受到 SMLM 技术在密集区域识别和定位分子的能力以及样品制备和图像采集的实验条件的限制。我们开发了一种稳健、无模型、定量聚类分析方法，用于确定膜分子的分布，该方法在标记密集区域表现出色，并且能够耐受各种实验条件，例如多次闪烁或高闪烁率。该方法基于 TIRF 显微镜，随后进行超分辨率光学波动成像 (SOFI) 分析。使用模拟和实验数据验证了该方法的有效性和稳健性，这些数据用于研究 T 细胞质膜中 CD4 糖蛋白突变体的纳米级分布。
