Department of Biological Sciences, National University of Singapore, 117543 Singapore, Singapore; Centre for BioImaging Sciences, National University of Singapore, 117557 Singapore, Singapore; Institute of Digital Molecular Analytics and Science, 117557 Singapore, Singapore; Department of Chemistry, National University of Singapore, 117543 Singapore, Singapore.
Department of Biological Sciences, National University of Singapore, 117543 Singapore, Singapore; Centre for BioImaging Sciences, National University of Singapore, 117557 Singapore, Singapore; Institute of Digital Molecular Analytics and Science, 117557 Singapore, Singapore.
Biochim Biophys Acta Gen Subj. 2024 Nov;1868(11):130716. doi: 10.1016/j.bbagen.2024.130716. Epub 2024 Sep 28.
Fluorescence Correlation Spectroscopy (FCS), invented more than 50 years ago is a widely used tool providing information on molecular processes in a variety of samples from materials to life sciences. In the last two decades FCS was multiplexed and ultimately made into an imaging technique that provided maps of molecular parameters over whole sample cross-section. However, it was still limited by a measurement time on the order of minutes. With the improvement of FCS time resolution to seconds using deep learning, we extend here FCS to so-called FCS videos that can provide information how the molecular parameters determined by Imaging FCS change in space and time. This opens up new possibilities for the investigation of molecular processes. Here, we demonstrate the feasibility of the approach and show FCS video applications to lipid bilayers and cell membranes.
荧光相关光谱(FCS)发明于 50 多年前,是一种广泛使用的工具,可提供从材料到生命科学等各种样品中分子过程的信息。在过去的二十年中,FCS 被多路复用,并最终发展成为一种成像技术,可提供整个样品横截面的分子参数图。然而,它仍然受到测量时间在几分钟左右的限制。通过深度学习将 FCS 的时间分辨率提高到秒级,我们将 FCS 扩展到所谓的 FCS 视频,该视频可以提供有关通过成像 FCS 确定的分子参数如何随时间和空间变化的信息。这为研究分子过程开辟了新的可能性。在这里,我们演示了该方法的可行性,并展示了 FCS 视频在脂质双层和细胞膜中的应用。