Biology subjects

Elgeti, J.

Publications and source records attributed to Elgeti, J..

6 recordsLinked to original sources

bioRxiv2026

Mechanics and fate stochasticity shape stem cell distribution in tissues

Balancing cellular loss in tissues requires fine balance of cell proliferation and differentiation. In differentiated tissues consisting of a single cell type, a mechanical regulation of proliferation has been proposed to underlie growth-control and homeostatic steady-states. Yet, how tissues containing different cell types with distinct proliferation rates, mechanical interactions, and spatial self-organization retain robust homeostasis of cell proportions remains poorly understood. Here, we combine particle-based mechanical models of proliferative tissues with a classical hierarchy of stem, progenitor, and differentiated cells, undergoing stochastic fate choices, and show that mechanical feedback alone is sufficient to stabilize populations. We derive analytically and computationally a phase diagram of possible stable states, in particular those maintained either via slow and rare stem cells with short-lived progenitors or no stem cells and long-lived progenitors. Our simulations uncover that mechanical control of growth is sufficient, in the absence of any codes of adhesion or extrinsic niche signals, to cause stable spatial structures, with small stem cell clusters forming and maintaining dynamical renewal units. Our results demonstrate how complex spatial structures can emerge in minimal stochastic and mechanical simulations with impact to understand the homeostasis of multi-cellular systems.

biophysics↗

bioRxiv2023

Membrane potential mediates an ancient mechano-transduction mechanism for multi-cellular homeostasis

Mechanical forces have been shown to influence cellular decisions to grow, die, or differentiate, through largely mysterious mechanisms. Separately, changes in resting membrane potential have been observed in development, differentiation, regeneration, and cancer. We now demonstrate that membrane potential is the central mediator of cellular response to mechanical pressure. We show that mechanical forces acting on the cell change cellular biomass density, which in turn alters membrane potential. Membrane potential then regulates cell number density in epithelia by controlling cell growth, proliferation, and cell elimination. Mechanistically, we show that changes in membrane potential control signaling through the Hippo and MAPK pathways, and potentially other signaling pathways that originate at the cell membrane. While many molecular interactions are known to affect Hippo signaling, the upstream signal that activates the canonical Hippo pathway at the membrane has previously been elusive. Our results establish membrane potential as a central regulator of growth and tissue homeostasis.

cell biology↗

bioRxiv2023

Cell wall fluidization by mechano-endopeptidases sets up a turgor-mediated volumetric pacemaker

The cell wall is an essential cellular component of bacteria and the target of many antibiotics. However, how bacteria regulate the rate of cell wall biosynthesis as growth rates change remains unresolved. In E. coli, cell wall growth was thought to proceed independently from turgor pressure1, the osmotic pressure that the cytoplasm exerts on the cell wall. Here, we uncover a striking increase of turgor pressure with growth rate. Modulating turgor pressure and measuring cell wall biosynthesis, we find that turgor pressure is directly controls the rate of cell wall biosynthesis. The picture that emerges is that turgor pressure is largely generated by counterions of negatively charged cellular biomass. The increase in turgor pressure with growth rates results from more ribosomes and therefore higher concentrations of negatively charged ribosomal RNA. Elegantly, the coupling between biomass composition, turgor pressure and cell wall biosynthesis simultaneously explains how bacteria achieve homeostasis of cytoplasmic crowding and how they regulate the rate of cell wall biosynthesis across growth rates.

microbiology↗

bioRxiv2022

Chiral and nematic phases of flexible active filaments

The emergence of large-scale order in self-organized systems relies on local interactions between individual components. During bacterial cell division, the tubulin-homolog FtsZ polymerizes into treadmilling filaments that further assemble into a cytoskeletal ring. Although minimal in vitro assays have shown the striking self-organization capacity of FtsZ filaments, such as dynamic chiral assemblies, how these large-scale structures emerge and relate to individual filament properties remains poorly understood. To understand this quantitatively, we combined minimal chiral active matter simulations with biochemical reconstitution experiments. Using STED and TIRF microscopy as well as high-speed AFM, we imaged the behavior of FtsZ filaments on different spatial scales. Simulations and experiments revealed that filament density and flexibility define the local and global order of the system: At intermediate densities, flexible filaments organize into chiral rings and polar bands, while an effectively nematic organization dominates for high filament densities and for mutant filaments with increased rigidity. Our predicted phase diagram captured these features quantitatively, demonstrating how filament flexibility, density and chirality cooperate with activity to give rise to a large repertoire of collective behaviors. These properties are likely important for the dynamic organization of soft chiral matter, including that of treadmilling FtsZ filaments during bacterial cell division.

biophysics↗

bioRxiv2020

The role of thickness inhomogeneities in hierarchical cortical folding

The morphology of the mammalian brain cortex is highly folded. For long it has been known that specific patterns of folding are necessary for an optimally functioning brain. On the extremes, lissencephaly, a lack of folds in humans, and polymicrogyria, an overly folded brain, can lead to severe mental retardation, short life expectancy, epileptic seizures, and tetraplegia. The construction of a quantitative model on how and why these folds appear during the development of the brain is the first step in understanding the cause of these conditions. In recent years, there have been various attempts to understand and model the mechanisms of brain folding. Previous works have shown that mechanical instabilities play a crucial role in the formation of brain folds, and that the geometry of the fetal brain is one of the main factors in dictating the folding characteristics. However, modeling higher-order folding, one of the main characteristics of the highly gyrencephalic brain, has not been fully tackled. The effects of thickness inhomogeneity in the gyrogenesis of the mammalian brain are studied in silico. Finite-element simulations of rectangular slabs are performed. The slabs are divided into two distinct regions, where the outer layer mimics the gray matter, and the inner layer the underlying white matter. Differential growth is introduced by growing the top layer tangentially, while keeping the underlying layer untouched. The brain tissue is modeled as a neo-Hookean hyperelastic material. Simulations are performed with both, homogeneous and inhomogeneous cortical thickness. The homogeneous cortex is shown to fold into a single wavelength, as is common for bilayered materials, while the inhomogeneous cortex folds into more complex conformations. In the early stages of development of the inhomogeneous cortex, structures reminiscent of the deep sulci in the brain are obtained. As the cortex continues to develop, secondary undulations, which are shallower and more variable than the structures obtained in earlier gyrification stage emerge, reproducing well-known characteristics of higher-order folding in the mammalian, and particularly the human, brain.

neuroscience↗

bioRxiv2019

Tissue evolution: Mechanical interplay of adhesion, pressure, and heterogeneity

The evolution of various competing cell types in tissues, and the resulting persistent tissue population, is studied numerically and analytically in a particle-based model of active tissues. Mutations change the properties of cells in various ways, including their mechanical properties. Each mutation results in an advantage or disadvantage to grow in the competition between different cell types. While changes in signaling processes and biochemistry play an important role, we focus on changes in the mechanical properties by studying the result of variation of growth force and adhesive cross-interactions between cell types. For independent mutations of growth force and adhesion strength, the tissue evolves towards cell types with high growth force and low internal adhesion strength, as both increase the homeostatic pressure. Motivated by biological evidence, we postulate a coupling between both parameters, such that an increased growth force comes at the cost of a higher internal adhesion strength or vice versa. This tradeoff controls the evolution of the tissue, ranging from unidirectional evolution to very heterogeneous and dynamic populations. The special case of two competing cell types reveals three distinct parameter regimes: Two in which one cell type outcompetes the other, and one in which both cell types coexist in a highly mixed state. Interestingly, a single mutated cell alone suffices to reach the mixed state, while a finite mutation rate affects the results only weakly. Finally, the coupling between changes in growth force and adhesion strength reveals a mechanical explanation for the evolution towards intra-tumor heterogeneity, in which multiple species coexist even under a constant evolutianary pressure.\n\nAuthor summaryThe evolution of cell populations in growing tissues is due to mutations during cell division, and subsequent competition through various biochemical and mechanical factors. Cancer represents an example of such an evolution on a short time scale. It is a multistep process, where several mutations are needed in order for a tumor to develop and become malignant. Furthermore, cell types in a tumor are often found to be very heterogeneous. We employ computer simulations of a particle-based model of growing tissues to study the competition of various cell types through variations of the mechanical cell properties. Unconstraint evolution drives the tissue towards cell types with stronger growth force and reduced adhesion. However, growth force and adhesion are not independent. Motivated by biologcal evidence, we consider a tissue, where enhanced growth force is coupled to increased adhesion. In a regime around a balanced tradeoff, multiple cell types coexist in a tissue, providing a tentative explanation for tumor heterogeneity. The special case of a competition between two cell types facilitates the study of the underlying competition mechanism. For example, we find that the number fraction of mutated cells is nearly independent of the mutation rate km, as long as km is much smaller than the apoptosis rate ka.

biophysics↗