Until recently, single‐molecule localization microscopy (SMLM) was constrained to the study of fixed cells, limiting analysis to the structural characterization of cell anatomy. The extension of SMLM to live‐cell imaging enables the dynamic visualization of molecular organization, paving the way for more functional studies. If associated with novel quantification tools such as presented here, it has the potential to provide a unique insight into cellular machinery at the nanoscale. While cluster analysis for conventional SMLM data sets is relatively well established, the extension of SMLM to live‐cell imaging lacks the required analytical tools. Here, a Bayesian‐based cluster analysis strategy is presented for live‐cell SMLM that allows the dynamics of nanoscale molecular clusters to be analyzed for the first time, generating functional information otherwise lost in fixed cell studies. The method is validated on simulations as well as on experimental data sets derived from naive CD4⁺ T‐cell synapses.

中文翻译：

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活细胞单分子定位显微镜数据集的动态贝叶斯聚类分析

直到最近，单分子定位显微镜（SMLM）还局限于固定细胞的研究，而将分析局限于细胞解剖结构的表征。SMLM扩展到活细胞成像可以实现分子组织的动态可视化，为更多的功能研究铺平了道路。如果与此处介绍的新型定量工具相关联，则它有可能提供对纳米级细胞机械的独特见解。尽管对常规SMLM数据集的聚类分析已相对完善，但将SMLM扩展到活细胞成像尚缺乏所需的分析工具。在此，我们提出了一种针对活细胞SMLM的基于贝叶斯的聚类分析策略，该策略允许首次分析纳米级分子簇的动力学，生成功能性信息，否则这些信息会在固定细胞研究中丢失 该方法在模拟以及从原始CD4衍生的实验数据集上均得到了验证⁺ T细胞突触。