Scipioni Lorenzo, Gratton Enrico, Diaspro Alberto, Lanzanò Luca
Nanoscopy, Nanophysics, Istituto Italiano di Tecnologia, Genoa, Italy; Department of Computer Science, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy.
Laboratory for Fluorescence Dynamics, Department of Biomedical Engineering, University of California, Irvine, Irvine, California.
Biophys J. 2016 Aug 9;111(3):619-629. doi: 10.1016/j.bpj.2016.06.029.
Organelles represent the scale of organization immediately below that of the cell itself, and their composition, size, and number are tailored to their function. Monitoring the size and number of organelles in live cells is relevant for many applications but can be challenging due to their highly heterogeneous properties. Image correlation spectroscopy is a well-established analysis method capable of extracting the average size and number of particles in images. However, when image correlation spectroscopy is applied to a highly heterogeneous system, it can fail to retrieve, from a single correlation function, the characteristic size and the relative amount associated to each subspecies. Here, we describe a fast, unbiased, and fit-free algorithm based on the phasor analysis of multiple local image correlation functions, capable of mapping the sizes of elements contained in a heterogeneous system. The method correctly provides the size and number of separate subspecies, which otherwise would be hidden in the average properties of a single correlation function. We apply the method to quantify the spatial and temporal heterogeneity in the size and number of intracellular vesicles formed after endocytosis in live cells.
细胞器代表了紧低于细胞本身的组织尺度,其组成、大小和数量都与其功能相适配。监测活细胞中细胞器的大小和数量在许多应用中都很重要,但由于其高度异质性,这可能具有挑战性。图像相关光谱法是一种成熟的分析方法,能够提取图像中粒子的平均大小和数量。然而,当将图像相关光谱法应用于高度异质的系统时,它可能无法从单个相关函数中检索出与每个亚群相关的特征大小和相对数量。在这里,我们描述了一种基于多个局部图像相关函数的相量分析的快速、无偏且无需拟合的算法,该算法能够绘制异质系统中所含元素的大小。该方法正确地提供了单独亚群的大小和数量,否则这些信息会隐藏在单个相关函数的平均特性中。我们应用该方法来量化活细胞内吞作用后形成的细胞内囊泡大小和数量的空间和时间异质性。