0000000000072836
AUTHOR
Roberto Zoncu
Fuzzy temporal random sets with an application to cell biology
Total Internal Reflection Fluorescence Microscopy (TIRFM) greatly facilitates to imaging the first steps of endocytosis, a process whereby cells traffic cargo from the cell surface to endosomes. Using TIRFM, fluorescent-tagged endocytic proteins are observed as overlapped areas forming random clumps of different sizes, shapes and durations. A common procedure to segment these objects consists of thresholding the original gray-level images to produce binary sequences in which a pixel is covered or not by a given fluorescent-tagged protein. This binary logic is not appropriate because it leaves a free tuning parameter to be set by the user which can influence on the conclusions of the statist…
Loss of endocytic clathrin-coated pits upon acute depletion of phosphatidylinositol 4,5-bisphosphate.
Phosphatidylinositol 4,5-bisphosphate [PI(4,5) P 2 ], a phosphoinositide concentrated predominantly in the plasma membrane, binds endocytic clathrin adaptors, many of their accessory factors, and a variety of actin-regulatory proteins. Here we have used fluorescent fusion proteins and total internal reflection fluorescence microscopy to investigate the effect of acute PI(4,5) P 2 breakdown on the dynamics of endocytic clathrin-coated pit components and of the actin regulatory complex, Arp2/3. PI(4,5) P 2 breakdown was achieved by the inducible recruitment to the plasma membrane of an inositol 5-phosphatase module through the rapamycin/FRB/FKBP system or by treatment with ionomycin. PI(4,5)…
Measuring Spatiotemporal Dependencies in Bivariate Temporal Random Sets with Applications to Cell Biology
Analyzing spatiotemporal dependencies between different types of events is highly relevant to many biological phenomena (e.g., signaling and trafficking), especially as advances in probes and microscopy have facilitated the imaging of dynamic processes in living cells. For many types of events, the segmented areas can overlap spatially and temporally, forming random clumps. In this paper, we model the binary image sequences of two different event types as a realization of a bivariate temporal random set and propose a nonparametric approach to quantify spatial and spatiotemporal interrelations using the pair correlation, cross-covariance, and the Ripley K functions. Based on these summary st…
Studying endocytosis in space and time by means of temporal Boolean models
Endocytosis is a process by which cells carry traffic from the extracellular space into various intracellular compartments. Visualization of fluorescently tagged clathrin proteins (mediators of endocytosis) allows us to image endocytosis in real time. When imaging the plasma membrane, areas of fluorescence generated by different endocytic processes overlap spatially and temporally, forming random clumps. Here, a sequence of segmented clathrin spots is considered a realization of a non-isotropic 3D Boolean model. Estimates of the intensity, the mean perimeter and the density function of the durations of endocytic events are obtained.
Analyzing Protein-Protein Spatial-Temporal Dependencies from Image Sequences Using Fuzzy Temporal Random Sets
Total Internal Reflection Fluorescence Microscopy (TIRFM) allows us to image fluorescenttagged proteins near the plasma membrane of living cells with high spatial-temporal resolution. Using TIRFM imaging of GFP-tagged clathrin endocytic proteins, areas of fluorescence are observed as overlapping spots of different sizes and durations. Standard procedures to measure protein-protein colocalization of dual labeled samples threshold the original graylevel images to segment areas covered by different proteins. This binary logic is not appropriate as it leaves a free tuning parameter which can influence the conclusions. Moreover, these procedures rely on simple statistical analysis based on corre…
Analysis of Spatially and Temporally Overlapping Events with Application to Image Sequences
Counting spatially and temporally overlapping events in image sequences and estimating their shape-size and duration features are important issues in some applications. We propose a stochastic model, a particular case of the nonisotropic 3D Boolean model, for performing this analysis: the temporal Boolean model. Some probabilistic properties are derived and a methodology for parameter estimation from time-lapse image sequences is proposed using an explicit treatment of the temporal dimension. We estimate the mean number of germs per unit area and time, the mean grain size and the duration distribution. A wide simulation study in order to assess the proposed estimators showed promising resul…