Correlation between cell morphology, tractions and motility of endothelial cells on compliant substrates
Alicia Izquierdo-Alvarez a, Alvaro Jorge-Peñas a, Diego A. Vargas a, Srilakshmi Ragunathan a, Hans Van Oosterwyck a, Ramesh Subramani b
a KU Leuven, Celestijnenlaan, Leuven, Belgium
b KU Leuven, Celestijnenlaan, Leuven, Belgium
Proceedings of New Advances in Probing Cell-ECM Interactions (CellMatrix)
Berlin, Germany, 2016 October 20th - 21st
Organizers: Ovijit Chaudhuri, Allen Liu and Sapun Parekh
Poster, Alicia Izquierdo-Alvarez, 057
Publication date: 25th July 2016

Angiogenesis is the formation of new vessels from the preexisting vasculature. It is an essential process not only in tissue regeneration but also in cardiovascular disease and cancer. Chemical regulation of this process has been studied for many years but how physical cues regulate angiogenesis is still poorly understood. We are investigating how substrate stiffness and adhesion properties affect cell morphology, tractions and motility of human umbilical vein endothelial cells (HUVECs) and how they correlate at the single cell level.

HUVECs were cultured on polyacrylamide substrates with different stiffness, functionalized with fibronectin or collagen and containing fluorescent beads for traction force microscopy (TFM). Time lapse TFM experiments were performed, using Free Form Deformation (FFD)-based image registration for substrate displacement calculation. We have previously demonstrated that this method leads to more accurate displacements and recovered tractions [2].

The migration parameters, speed and persistence time, were calculated from a fit of the MSD in accordance to the persistent random walk model described by Pei-Hsun et al [3]. A series of cell morphological features and the minimal distance between cells were measured from time lapse confocal fluorescence microscopy images. Correlation analyses are being performed by means of the software SAPHIRE [1], which uses principal component analysis (PCA) and hidden Markov models  to define a series of cellular states for each cell, incorporating temporal dependencies during model inference. This analysis provides a transition probability matrix that can be used to compare across conditions.

Our preliminary results showed that the total force exerted by cells increases with the substrate stiffness and its magnitude depends on the adhesion protein, being collagen the one promoting higher cellular tractions. Furthermore, the PCA analysis revealed the length of cells’ minor axis as the morphological parameter that describes most variability within a cell population. Surprisingly, distance to other cells showed no correlation with cellular state. Finally, hierarchical clustering of transition probability matrices shows potential to distinguish among cellular responses to different substrate stiffness. In summary, the resulting information is expected to provide a quantitative view of the cell-matrix mechanical interaction of HUVECs and leads to a better comprehension of cell mechanobiology in angiogenesis.

Acknowledgements: The research leading to these results has received funding from the European Research Council (FP7/2007-2013)/ ERC Grant Agreement n° 308223) and from the Research Foundation-Flanders (FWO – project number G.0821.13)

[1] Gordonov et al. (2016) Integrative Biology 8(1):73-90

[2] Jorge-Peñas A et al. (2015) PLoS ONE 10(12): e0144184.

[3] Pei-Hsun W et al. (2015) Nature Protocols 10, 517–527



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