Biology subjects

Graedel, B.

Publications and source records attributed to Graedel, B..

3 recordsLinked to original sources

bioRxiv2025

Interplay between Rac1/RhoA and actin waves in giant epithelial cells : experiment and theory

The acto-myosin cytoskeleton is a key driver of cellular shape changes in vivo and in vitro. Acto-myosin organization results from actin assembly and interactions between actin and myosin, which are both regulated by small Rho GTPases like Rac1 and RhoA. To uncover principles governing cytoskeletal organization, we analyzed actin patterns using live microscopy and theory. In giant Madin-Darby Canine Kidney (MDCK) epithelial cells and REF52 fibroblasts, we observed acto-myosin stress fibres and propagating waves. Stress fibres were stationary and correlated with homogeneous distributions of Rac and RhoA activity. Waves propagated at {approx} 1m/min and were associated with density variations of actin, Rac and active RhoA. Some waves transported cellular components or generated protrusions at the cell edge. Essential features of wave propagation are captured by a polar reaction-diffusion system for actin and Rac. Notably, two colliding waves annihilate each other. In cells, myosin activity was not required for the emergence of waves, but tended to suppress them. Consistently, local activation of RhoA slowed down or stopped and broke waves. These results highlight how the coupling between acto-myosin and Rho GTPase generates a variety of cytoskeletal structures and dynamics. O_TEXTBOXSIGNIFICANCEThe cytoskeleton shapes cells in vitro and in vivo. Its molecular mechanisms have been extensively documented, but the mesoscopic structures resulting from the interplay between the activator and the motor activity have been poorly characterized. Here we show that two structures are conserved in two systems, stress fibres with RhoA activity and diffusion actin waves regulated by Rac1. The annihilation of waves and the alteration of the wave dynamics are reproduced by a minimal model based on a polar reaction-diffusion model. This approach could pave the way to a generic description of regulated active gels in cells with potential biological functions, such as stress generation for fibres and probing of space and homogenization of the cortex by actin waves. C_TEXTBOX

biophysics↗

bioRxiv2025

Teach your microscope how to print: Low-cost and rapid-iteration microfabrication for biology

The application of traditional microfabrication techniques to biological research is hindered by their reliance on clean rooms, expensive or toxic materials, and slow iteration cycles. We present an accessible microfabrication workflow that addresses these challenges by integrating consumer 3D printing techniques and repurposing standard fluorescence microscopes equipped with DMDs for maskless photolithography. Our method achieves micrometer-scale precision across centimeter-sized areas without clean room infrastructure, using affordable and readily available consumables. We demonstrate the versatility of this approach through four biological applications: inducing cytoskeletal protrusions via 1 m-resolution surface topographies; micropatterning to standardize cell and tissue morphology; fabricating multilayer microfluidic devices for confined cell migration studies; imprinting agar chambers for long-time tracking of C. elegans. Our protocol drastically reduces material costs compared to conventional methods and enables design-to-device turnaround within a day. By leveraging open-source microscope control software and existing lab equipment, our workflow lowers the entry barrier to micro-fabrication, enabling labs to prototype custom solutions for diverse experimental needs while maintaining compatibility with soft lithography and downstream biological assays.

cell biology↗

bioRxiv2024

Convpaint - Universal framework for interactive pixel classification using pretrained neural networks

We develop Convpaint, a universal computational framework for interactive pixel classification. Convpaint utilizes pretrained convolutional neural networks (CNNs) or vision transformers (ViTs) for feature extraction and enables easy segmentation across a wide variety of tasks. Available within the Python-based napari software ecosystem, Convpaint integrates seamlessly with other plugins into image processing pipelines, which we demonstrate with three workflows across different data modalities.

bioinformatics↗