Quantitative fluorescence fluctuation spectroscopy from optical microscopy datasets is a very powerful tool to resolve multiple spatiotemporal cellular and subcellular processes at the molecular level. In particular, raster image correlation spectroscopy (RICS) and number and brightness analyses (N&B) yield molecular mobility and clustering dynamic information extracted from real-time cellular processes. This quantitative information can be inferred in a highly flexible and detailed manner, i.e. 1) at the localisation level: from full-frame datasets and multiple regions of interest within; and 2) at the temporal level: not only from full-frame and multiple regions, but also intermediate temporal events. Here we build on previous research in deciphering the molecular dynamics of paxillin, a main component of focal adhesions. Cells use focal adhesions to attach to the extracellular matrix and interact with their local environment. Through focal adhesions and other adhesion structures, cells sense their local environment and respond accordingly; due to this continuous communication, these structures can be highly dynamic depending on the extracellular characteristics. By using a previously well-characterised model like paxillin, we examine the powerful sensitivity and some limitations of RICS and N&B analyses. We show that cells upon contact to different surfaces show differential self-assembly dynamics in terms of molecular diffusion and oligomerisation. In addition, single-cell studies show that these dynamics change gradually following an antero-posterior gradient.

中文翻译：

---

通过荧光波动光谱方法剖析单细胞分子时空迁移率和偏振细胞中焦点粘附的聚集

光学显微镜数据集的定量荧光波动光谱是在分子水平上解决多个时空细胞和亚细胞过程的非常强大的工具。特别是，光栅图像相关光谱 (RICS) 以及数量和亮度分析 (N&B) 产生从实时细胞过程中提取的分子迁移率和聚类动态信息。该定量信息可以以高度灵活和详细的方式推断，即 1) 在本地化级别：从全帧数据集和其中的多个感兴趣区域；2）时间层面：不仅来自全帧和多个区域，还来自中间时间事件。在这里，我们以先前的研究为基础，破译桩蛋白（粘着斑的主要成分）的分子动力学。细胞利用粘着斑附着在细胞外基质上并与其局部环境相互作用。通过粘着斑和其他粘附结构，细胞感知其局部环​​境并做出相应反应；由于这种持续的通讯，这些结构可以根据细胞外特性而高度动态。通过使用先前已充分表征的模型（如桩蛋白），我们检查了 RICS 和 N&B 分析的强大灵敏度和一些局限性。我们表明，细胞在接触不同表面时在分子扩散和寡聚方面表现出不同的自组装动力学。此外，单细胞研究表明这些动态按照前后梯度逐渐变化。