Biology subjects

Ardaseva, A.

Publications and source records attributed to Ardaseva, A..

3 recordsLinked to original sources

bioRxiv2024

Mechanical stresses govern myoblast fusion and myotube growth

Myoblast fusion into multinucleated myotubes is essential for skeletal muscle development and repair, yet how tissue-scale mechanics contributes to this process remains poorly understood. Here, we show that primary myoblasts behave as an evolving active nematic system in which actomyosin-dependent stresses, extracellular-matrix (ECM) remodeling and fusion-driven myotube growth are dynamically coupled. As myoblasts fuse into elongated myotubes, orientational order increases and the nematic field is progressively reshaped. We identify a strong coupling between cellular and ECM nematic organization, whereby cytoskeleton-dependent ECM remodeling stabilizes topological defects and reinforces their associated stress patterns. Fusion events preferentially accumulate near comet-shaped +1/2 defects, which correspond to regions of high compressive stress predicted by our theoretical model. Our findings support a model in which the intrinsic fusion machinery provides fusion competence, while ECM-stabilized nematic stress patterns spatially bias the localization of fusion events. Fusion-driven myotube growth then feeds back on the mechanical landscape, increasing nematogen length and stress magnitude. Together, these results reveal a self-reinforcing biomechanical mechanism that contributes to the organization of myoblast fusion and myotube growth, with potential relevance for developmental and regenerative morphogenesis.

biophysics↗

bioRxiv2019

A mathematical dissection of the adaptation of cell populations to fluctuating oxygen levels

The disordered network of blood vessels that arises from tumour angiogenesis results in variations in the delivery of oxygen into the tumour tissue. This brings about regions of chronic hypoxia (i.e. sustained low oxygen levels) and regions with alternating phases of low and relatively higher oxygen levels within vascularised tumours, and makes it necessary for cancer cells to adapt to fluctuating environmental conditions. We use a phenotype-structured model to dissect the evolutionary dynamics of cell populations exposed to fluctuating oxygen levels. In this model, the phenotypic state of every cell is described by a continuous variable that provides a simple representation of its metabolic phenotype, ranging from fully oxidative to fully glycolytic, and cells are grouped into two competing populations that undergo heritable, spontaneous phenotypic variations at different rates. Model simulations indicate that, depending on the rate at which oxygen is consumed by the cells, nonlinear dynamic interactions between cells and oxygen can stimulate chronic hypoxia and cycling hypoxia. Moreover, the model supports the idea that under chronic-hypoxic conditions lower rates of phenotypic variation lead to a competitive advantage, whereas higher rates of phenotypic variation can confer a competitive advantage under cycling-hypoxic conditions. In the latter case, the numerical results obtained show that bet-hedging evolutionary strategies, whereby cells switch between oxidative and glycolytic phenotypes, can spontaneously emerge. We explain how these results can shed light on the evolutionary process that may underpin the emergence of phenotypic heterogeneity in vascularised tumours.

cancer biology↗

bioRxiv2018

Evolutionary exploitation of PD-L1 expression in hormone receptor positive breast cancer

Based on clinical data from hormone positive breast cancer patients, we determined that there is a potential tradeoff between reducing tumor burden and altering metastatic potential when administering combination therapy of aromatase inhibitors and immune checkpoint inhibitors. While hormone-deprivation therapies serve to reduce tumor size in the neoadjuvant setting pre-surgery, they may induce tumors to change expression patterns towards a metastatic phenotype. We used mathematical modeling to explore how the timing of the therapies affects tumor burden and metastatic potential with an eye toward developing a dynamic prognostic score and reducing both tumor size and risk of metastasis.

cancer biology↗