Biology subjects

Vasilevich, A. S.

Publications and source records attributed to Vasilevich, A. S..

3 recordsLinked to original sources

bioRxiv2020

Tendon-derived biomimetic surface topographies induce phenotypic maintenance of tenocytes in vitro

The tenocyte niche contains biochemical and biophysical signals that are needed for tendon homeostasis. The tenocyte phenotype is correlated with cell shape in vivo and in vitro, and shape-modifying cues are needed for tenocyte phenotypical maintenance. Indeed, cell shape changes from elongated to spread when cultured on a flat surface, and rat tenocytes lose the expression of phenotypical markers throughout five passages. We hypothesized that tendon gene expression can be preserved by culturing cells in the native tendon shape. To this end, we reproduced the tendon topographical landscape into tissue culture polystyrene, using imprinting technology. We confirmed that the imprints forced the cells into a more elongated shape, which correlated with the level of Scleraxis expression. When we cultured the tenocytes for seven days on flat surfaces and tendon imprints, we observed a decline in tenogenic marker expression on flat but not on imprints. This research demonstrates that native tendon topography is an important factor contributing to the tenocyte phenotype. Tendon imprints therefore provide a powerful platform to explore the effect of instructive cues originating from native tendon topography on guiding cell shape, phenotype and function of tendon-related cells.

bioengineering↗

bioRxiv2020

Evolutionary design of optimal surface topographies for biomaterials

Natural evolution tackles optimization by producing many genetic variants and exposing these variants to selective pressure, resulting in the survival of the fittest. We use high throughput screening of large libraries of materials with differing surface topographies to probe the interactions of implantable device coatings with cells and tissues. However, the vast size of possible parameter design space precludes a brute force approach to screening all topographical possibilities. Here, we took inspiration from Nature to optimize materials surface topographies using evolutionary algorithms. We show that successive cycles of material design, production, fitness assessment, selection, and mutation results in optimization of biomaterials designs. Starting from a small selection of topographically designed surfaces that upregulate expression of an osteogenic marker, we used genetic crossover and random mutagenesis to generate new generations of topographies.

bioinformatics↗

bioRxiv2020

On the correlation between material-induced cell shape and phenotypical response of human mesenchymal stem cells

Learning rules by which cell shape impacts cell function would enable control of cell physiology and fate in medical applications, particularly, on the interface of cells and material of the implants. We defined the phenotypic response of human bone marrow-derived mesenchymal stem cells (hMSCs) to 2176 randomly generated surface topographies by probing basic functions such as migration, proliferation, protein synthesis, apoptosis, and differentiation using quantitative image analysis. Clustering the surfaces into 28 archetypical cell shapes, we found a very strict correlation between cell shape and physiological response and selected seven cell shapes to describe the molecular mechanism leading to phenotypic diversity. Transcriptomics analysis revealed a tight link between cell shape, molecular signatures, and phenotype. For instance, proliferation is strongly reduced in cells with limited spreading, resulting in down-regulation of genes involved in the G2/M cycle and subsequent quiescence, whereas cells with large filopodia are related to activation of early response genes and inhibition of the osteogenic process. Thus, we have started to unravel the open question of how cell function follows cell shape. This will allow designing implants that can actively regulate cellular, molecular signalling through cell shape. Here we are proposing an approach to tackle this question.

bioinformatics↗