Biology subjects

Shapeti, A.

Publications and source records attributed to Shapeti, A..

3 recordsLinked to original sources

bioRxiv2021

CCM2 deficient endothelial cells undergo a mechano-dependent reprogramming into senescence associated secretory phenotype used to recruit endothelial and immune cells.

Cerebral Cavernous Malformations (CCM) is a cerebrovascular disease in which stacks of dilated haemorrhagic capillaries form focally in the brain. Whether and how defective mechanotransduction, cellular mosaicism and inflammation interplay to sustain the progression of CCM diseases is unknown. Here, we reveal that CCM1- and CCM2-silenced endothelial cells enter into senescence associated with secretory phenotype (SASP) that they use to invade the extracellular matrix and attract surrounding wild-type endothelial and immune cells. Further, we demonstrate that this SASP is driven by the mechanical and molecular disorders provoked by ROCKs dysfunctions. By this, we identify CCM1/2 and ROCKs as parts of a scaffold controlling senescence, bringing new insights into the emerging field of the control of aging by cellular mechanics. This discovery reconciles the dysregulated traits of CCM1/2-deficient endothelial cells into a unique mechano-dependent endothelial fate that links perturbed mechanics to microenvironment remodelling and long-range activation of endothelial and immune cells.

cell biology↗

bioRxiv2020

TFMLAB: a MATLAB toolbox for 4D traction force microscopy

We present TFMLAB, a MATLAB software package for 4D (x;y;z;t) Traction Force Microscopy (TFM). While various TFM computational workflows are available in the literature, open-source programs that are easy to use by researchers with limited technical experience and that can analyze 4D in vitro systems do not exist. TFMLAB integrates all the computational steps to compute active cellular forces from confocal microscopy images, including image processing, cell segmentation, image alignment, matrix displacement measurement and force recovery. Moreover, TFMLAB eases usability by means of interactive graphical user interfaces. This work describes the package's functionalities and analyses its performance on a real TFM case.

bioengineering↗

bioRxiv2020

Advanced in silico validation framework forthree-dimensional Traction Force Microscopy andapplication to an in vitro model of sproutingangiogenesis

In the last decade, cellular forces in three-dimensional hydrogels that mimic the extracellular matrix have been calculated by means of Traction Force Microscopy (TFM). However, characterizing the accuracy limits of a traction recovery method is critical to avoid obscuring physiological information due to traction recovery errors. So far, 3D TFM algorithms have only been validated using simplified cell geometries, bypassing image processing steps or arbitrarily simulating focal adhesions. Moreover, it is still uncertain which of the two common traction recovery methods, i.e., forward and inverse, is more robust against the inherent challenges of 3D TFM. In this work, we established an advanced in silico validation framework that is applicable to any 3D TFM experimental setup and that can be used to correctly couple the experimental and computational aspects of 3D TFM. Advancements relate to the simultaneous incorporation of complex cell geometries, simulation of microscopy images of varying bead densities and different focal adhesion sizes and distributions. By measuring the traction recovery error with respect to ground truth solutions, we found that while highest traction recovery errors occur for cases with sparse and small focal adhesions, our implementation of the inverse method improves two-fold the accuracy with respect to the forward method (average error of 23% vs. 50%). This advantage was further supported by recovering cellular tractions around angiogenic sprouts in an in vitro model of angiogenesis. The inverse method recovered more realistic traction patterns than the forward method, showing higher traction peaks and a clearer pulling pattern at the sprout protrusion tips.

bioengineering↗