Objective quantification of nanoscale protein distributions

Abstract

Nanoscale distribution of molecules within small subcellular compartments of neurons critically influences their functional roles. Although, numerous ways of analyzing the spatial arrangement of proteins have been described, a thorough comparison of their effectiveness is missing. Here we present an open source software, GoldExt, with a plethora of measures for quantification of the nanoscale distribution of proteins in subcellular compartments (e.g. synapses) of nerve cells. First, we compared the ability of five different measures to distinguish artificial uniform and clustered patterns from random point patterns. Then, the performance of a set of clustering algorithms was evaluated on simulated datasets with predefined number of clusters. Finally, we applied the best performing methods to experimental data, and analyzed the nanoscale distribution of different pre- and postsynaptic proteins, revealing random, uniform and clustered sub-synaptic distribution patterns. Our results reveal that application of a single measure is sufficient to distinguish between different distributions.

Distinct Nanoscale Calcium Channel and Synaptic Vesicle Topographies Contribute to the Diversity of Synaptic Function

“…To determine the number of gold particle clusters of Ca V 2.1 and Munc13-1 gold particles in SC boutons DBSCAN (Ester et al, 1996) was used, which is a density-based clustering algorithm. We used either MATLAB custom code or a Python-based open source software with a graphical user interface, GoldExt (Szoboszlay et al, 2017). The DBSCAN requires two user-defined parameters: ε (nm), which is the maximum distance between two localization points to be assigned to the same cluster, and the minimum number of localization points within a single cluster.…”

Activity-Dependent Remodeling of Synaptic Protein Organization Revealed by High Throughput Analysis of STED Nanoscopy Images

“…However, these metrics are sensitive to factors such as signal to noise ratio, labeling density, optical resolution, and signal intensity (Lagache et al, 2018). A further challenge is to determine whether the detected protein clusters are distributed in a spatially organized manner or are randomly distributed to each other (Helmuth et al, 2010;Szoboszlay et al, 2017;Lagache et al, 2018). To address these limitations, distance-based methods that statistically infer spatial association (coupling) between sub-cellular structures have been introduced (Helmuth et al, 2010;Lagache et al, 2013Lagache et al, , 2018.…”

Translocation of Epidermal Growth Factor (EGF) to the nucleus has distinct kinetics between adipose tissue-derived mesenchymal stem cells and a mesenchymal cancer cell lineage

“…On the other hand, light microscopy is a powerful approach to achieve protein intracellular localization and quantification, with recent advances in both aspects (Hamilton, 2009). Modern microscopes allows acquisition of higher resolution images than conventional confocal microscopy (Weisshart, 2014), and new image analysis methods are being developed to fulfill users requirements for protein quantifications (Coffman and Wu, 2012; Rizk et al, 2014; Szoboszlay et al, 2017). Although some approaches use live cells to track intracellular EGFR (Campos et al, 2011; Du et al, 2013), photobleaching and poor spatial and temporal resolution may affect the localization and quantification of proteins over time (Hamilton, 2009).…”