Biology subjects

Dimitracopoulos, A.

Publications and source records attributed to Dimitracopoulos, A..

4 recordsLinked to original sources

bioRxiv2024

Substrate stiffness regulates neuronal maturation via Piezo1-mediated TTR activity

During brain development, neurons extend axons to connect to their target cells while initiating a maturation process during which neurons start expressing voltage-gated ion channels, form synapses, express synaptic transmitters and receptors, and start communicating via action potentials. Little is known about external factors regulating this process. Here, we identified environmental mechanics as an important regulator of neuronal maturation, and a molecular pathway linking tissue stiffness to this process. Using patch clamp electrophysiology, calcium imaging and immunofluorescence, we found that neurons cultured on stiffer substrates showed a delay in voltage-gated ion channel activity, spontaneous and evoked action potentials, and synapse formation. RNA sequencing and CRISPR/Cas9 knockdown revealed that the mechanosensitive ion channel Piezo1 supresses transthyretin (TTR) expression on stiffer substrates, slowing down synapse formation and consequently electrical maturation. In agreement, the stiffness of developing Xenopus laevis brain negatively correlated with local synapse densities, and stiffening of brain tissue resulted in a significant delay of synaptic activity in vivo. Our data indicate that environmental stiffness represents a fundamental regulator of neuronal maturation, which is important for the development of normal circuitry in the brain, and potentially for neurodevelopmental disorders. Furthermore, the mechanical regulation of TTR downstream of Piezo1 may be found in many other biological systems.

developmental biology↗

bioRxiv2021

Effective Cell Membrane Tension is Independent of Substrate Stiffness

Most animal cells are surrounded by a cell membrane and an underlying actomyosin cortex. Both structures are linked, and they are under tension. In-plane membrane tension and cortical tension both influence many cellular processes, including cell migration, division, and endocytosis. However, while actomyosin tension is regulated by substrate stiffness, how membrane tension responds to mechanical substrate properties is currently poorly understood. Here, we probed the effective membrane tension of neurons and fibroblasts cultured on glass and polyacrylamide substrates of varying stiffness using optical tweezers. In contrast to actomyosin-based traction forces, both peak forces and steady state tether forces of cells cultured on hydrogels were independent of substrate stiffness and did not change after blocking myosin II activity using blebbistatin, indicating that tether and traction forces are not directly linked. Peak forces in fibroblasts on hydrogels were about twice as high as those in neurons, indicating stronger membrane-cortex adhesion in fibroblasts. Steady state tether forces were generally higher in cells cultured on hydrogels than on glass, which we explain by a mechanical model. Our results provide new insights into the complex regulation of effective membrane tension and pave the way for a deeper understanding of the biological processes it instructs.

biophysics↗

bioRxiv2019

Cortical cell stiffness is independent of substrate mechanics

Cortical stiffness is an important cellular property that changes during migration, adhesion, and growth. Previous atomic force microscopy (AFM) indentation measurements of cells cultured on deformable substrates suggested that cells adapt their stiffness to that of their surroundings. Here we show that the force applied by AFM onto cells results in a significant deformation of the underlying substrate if it is softer than the cells. This soft substrate effect leads to an underestimation of a cells elastic modulus when analyzing data using a standard Hertz model, as confirmed by finite element modelling (FEM) and AFM measurements of calibrated polyacrylamide beads, microglial cells, and fibroblasts. To account for this substrate deformation, we developed the composite cell-substrate model (CoCS model). Correcting for the substrate indentation revealed that cortical cell stiffness is largely independent of substrate mechanics, which has significant implications for our interpretation of many physiological and pathological processes.

biophysics↗

bioRxiv2018

KymoButler: A deep learning software for automated kymograph tracing and analysis

Kymographs are graphical representations of spatial position over time, which are often used in biology to visualise the motion of fluorescent particles, molecules, vesicles, or organelles moving along a predictable path. Although in kymographs tracks of individual particles are qualitatively easily distinguished, their automated quantitative analysis is much more challenging. Kymographs often exhibit low signal-to-noise-ratios (SNRs), and available tools that automate their analysis usually require manual supervision. Here we developed KymoButler, a Deep Learning-based software to automatically track dynamic processes in kymographs. We demonstrate that KymoButler performs as well as expert manual data analysis on kymographs with complex particle trajectories from a variety of different biological systems. The software was packaged in a web-based \"one-click\" application for use by the wider scientific community. Our approach significantly speeds up data analysis, avoids unconscious bias, and represents another step towards the widespread adaptation of Machine Learning techniques in biological data analysis.

cell biology↗