Quantitative Determination of Cellular-and Neurite Motility Speed in Dense Cell Cultures.

Andreas W Henkel,Zoran B Redzic,Mohammed S Al-Qallaf,Lulwa A A D Al-Abdullah

doi:10.3389/fninf.2019.00015

Abstract

Mobility quantification of single cells and cellular processes in dense cultures is a challenge, because single cell tracking is impossible. We developed a software for cell structure segmentation and implemented 2 algorithms to measure motility speed. Complex algorithms were tested to separate cells and cellular components, an important prerequisite for the acquisition of meaningful motility data. Plasma membrane segmentation was performed to measure membrane contraction dynamics and organelle trafficking. The discriminative performance and sensitivity of the algorithms were tested on different cell types and calibrated on computer-simulated cells to obtain absolute values for cellular velocity. Both motility algorithms had advantages in different experimental setups, depending on the complexity of the cellular movement. The correlation algorithm (COPRAMove) performed best under most tested conditions and appeared less sensitive to variable cell densities, brightness and focus changes than the differentiation algorithm (DiffMove). In summary, our software can be used successfully to analyze and quantify cellular and subcellular movements in dense cell cultures.

Highlights

Analysis of changes in cellular motility, shape changes and movements of subcellular particles plays an important role in exploring cell biology phenomena
Animals were supplied by the Animal Resource Center (ARC), Health Science Centre (HSC), Kuwait University
Verification and quantitative performance of the motility algorithms were analyzed by means of cell motility simulations, conducted by SynoQuant’s movement simulator module “CellSimulator.” Since the translocation velocity of randomly moving cells was directly defined in units of [pixels/frame], a linear function could be derived to calibrate the COPRAMove velocity descriptor in SynoQuant’s mobility analysis module

Summary

Introduction

Analysis of changes in cellular motility, shape changes and movements of subcellular particles plays an important role in exploring cell biology phenomena. Cells show often highly dynamic morphological changes and large translocations after application of drugs and chemicals that affect the cytoskeleton or organelle trafficking inside the cytoplasm (Paluch et al, 2005; Krause and Gautreau, 2014) Though these morphodynamic effects are very obvious upon visual inspection, they could be difficult to quantify, because few software tools exist that could measure nonlinear movements of cellular objects and structures (Myers, 2012; Barry et al, 2015). The existing programs we found so far, do all require dye-stained preparation and cannot be used in low- quality phase contrast images without major manual intervention to select the structures of interest (Rodriguez et al, 2008; Jacquemet et al, 2017; Urbancic et al, 2017) One strategy, addressing this problem was the development of particle image velocimetry (PIV) (Vig et al, 2016).

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Discussion

Conclusion