Solvatochromic probes undergo an emission shift when the hydration level of the membrane environment increases and are commonly used to distinguish between solid-ordered and liquid-disordered phases in artificial membrane bilayers. This emission shift is currently limited in unraveling the broad spectrum of membrane phases of natural cell membranes and their spatial organization. Spectrally resolved fluorescence lifetime imaging can provide pixel-resolved multiparametric information about the biophysical state of the membranes, like membrane hydration, microviscosity and the partition coefficient of the probe. Here, we introduce a clustering based analysis that, leveraging the multiparametric content of spectrally resolved lifetime images, allows us to classify through an unsupervised learning approach multiple membrane phases with sub-micrometric resolution. This method extends the spectrum of detectable membrane phases allowing to dissect and characterize up to six different phases, and to study real-time phase transitions in cultured cells and tissues undergoing different treatments. We applied this method to investigate membrane remodeling induced by high glucose on PC-12 neuronal cells, associated with the development of diabetic neuropathy. Due to its wide applicability, this method provides a new paradigm in the analysis of environmentally sensitive fluorescent probes.

中文翻译：

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多参数荧光图像的无监督聚类扩展了具有亚微米分辨率的可检测细胞膜相的光谱


当膜环境的水合水平增加时，溶剂致变色探针会发生发射变化，通常用于区分人工膜双层中的固相有序相和液相无序相。这种发射变化目前在揭示天然细胞膜的广谱膜相及其空间组织方面受到限制。光谱分辨荧光寿命成像可以提供有关膜生物物理状态的像素分辨多参数信息，例如膜水合、微粘度和探针的分配系数。在这里，我们介绍了一种基于聚类的分析，利用光谱解析寿命图像的多参数内容，使我们能够通过无监督学习方法对具有亚微米分辨率的多个膜相进行分类。该方法扩展了可检测膜相的范围，允许解剖和表征多达六个不同的相，并研究经过不同处理的培养细胞和组织的实时相变。我们应用这种方法来研究高葡萄糖诱导的 PC-12 神经元细胞膜重塑，这与糖尿病神经病变的发展相关。由于其广泛的适用性，该方法为环境敏感荧光探针的分析提供了新的范例。