Biology subjects

Gerum, R.

Publications and source records attributed to Gerum, R..

7 recordsLinked to original sources

bioRxiv2026

Mechanochemical synchronization of force oscillations in connective tissue models

Cells in a tissue coordinate their behavior collectively by mechanical and chemical feedback with their surroundings. To study how such feedback mechanisms interact, we embed multicellular spheroids from mouse and primary human fibroblasts of different origin in 3D collagen matrices. Immediately after embedding, spheroids apply steadily increasing, radially symmetric, inward-directed forces to the surrounding matrix. Typically, within a few hours, collective force oscillations emerge with an average time interval of {approx}30 min. Similar force oscillations also arise in engineered, parallel-aligned microtissues attached to flexible pillars. Force oscillations propagate between neighboring cells as a mechanical wave, accompanied by calcium waves that travel at comparable speeds of several hundred m/min. Blocking gap junctions or mechanosensitive Piezo1 channels impairs these oscillations, indicating that calcium signaling contributes to their propagation. Their amplitude and frequency are regulated by integrin-mediated feedback in actin-rich protrusions and by ERK signaling, which also controls collective invasion into the surrounding matrix. Neighboring spheroids mechanically synchronize their force oscillations in phase and frequency over distances of up to {approx}2 mm without direct contact. Together, our results show that oscillatory mechanochemical feedback enables multicellular systems to coordinate force generation and invasive migration across cellular and millimeter length scales in 3D matrices.

biophysics↗

bioRxiv2023

Fiber alignment in 3D collagen networks as a biophysical marker for cell contractility

Cells cultured in 3D fibrous biopolymer matrices exert traction forces on their environment that induce deformations and remodeling of the fiber network. By measuring these deformations, the traction forces can be reconstructed if the mechanical properties of the matrix and the force-free matrix configuration are known. These requirements severely limit the applicability of traction force reconstruction in practice. In this study, we test whether force-induced matrix remodeling can instead be used as a proxy for cellular traction forces. We measure the traction forces of hepatic stellate cells and different glioblastoma cell lines and quantify matrix remodeling by measuring the fiber orientation and fiber density around these cells. In agreement with simulated fiber networks, we demonstrate that changes in local fiber orientation and density are directly related to cell forces. By resolving Rho-kinase (ROCK) Inhibitor-induced changes of traction forces and fiber alignment and density in hepatic stellate cells, we show that the method is suitable for drug screening assays. We conclude that differences in local fiber orientation and density, which are easily measurable, can be used as a qualitative proxy for changes in traction forces. The method is available as an open-source Python package with a graphical user interface.

biophysics↗

bioRxiv2023

Immune cells employ traction forces to overcome steric hindrance in 3D biopolymer networks

To reach targets outside the bloodstream, immune cells can extravasate and migrate through connective tissue. During tissue infiltration, immune cells migrate in an amoeboid fashion, characterized by weak matrix adhesions and low traction forces, that allows them to achieve high migration speeds of up to 10 {micro}m/min. How immune cells reconcile amoeboid migration with the need to overcome steric hindrance in dense matrices is currently not understood. Here we show that NK92 (natural killer) cells can switch from their default amoeboid migration mode to a contractile, mesenchymal-like migration mode when moving through fibrous human amniotic membrane (HAM) tissue. We subsequently study immune cell migration in reconstituted 3D collagen networks with known mechanical properties and pore sizes and apply time-lapse confocal reflection microscopy to obtain simultaneous measurements of migration speed, directional persistence, and cell contractility. We find that NK92 cells are highly mechanoresponsive and exert substantial acto-myosin driven, integrin-mediated contractile forces of up to 100 nN on the extracellular matrix during short contractile phases. This burst-like contractile behavior is also found in primary B, T, NK cells, neutrophils, and monocytes, and is tightly related to the fraction of cells that appear to become stuck in narrow pores of the surrounding matrix. Our results demonstrate that steric hindrance guides the rapid regulation of integrin-mediated adhesion to the ECM in a large number of immune cell subtypes.

biophysics↗

bioRxiv2022

Dynamic traction force measurements of migrating immune cells in 3D matrices

Immune cells such as natural killer (NK) cells migrate with high speeds of several {micro}m/min through dense tissue, but the traction forces are unknown. We present a method to measure dynamic traction forces of fast migrating cells in non-linear biopolymer matrices. The method accounts for the mechanical non-linearity of the 3D tissue matrix and can be applied to time series of confocal or bright-field image stacks. The method is highly sensitive over a large range of forces and object sizes, from [~]1 nN for axon growth cones up to [~]10 {micro}N for mouse intestinal organoids. We find that NK cells display bursts of large traction forces that increase with matrix stiffness and facilitate migration through tight constrictions.

biophysics↗

bioRxiv2022

Deep learning based decoding of local field potential events

How is information processed in the cerebral cortex? To answer this question a lot of effort has been undertaken to create novel and to further develop existing neuroimaging techniques. Thus, a high spatial resolution of fMRI devices was the key to exactly localize cognitive processes. Furthermore, an increase in time-resolution and number of recording channels of electro-physiological setups has opened the door to investigate the exact timing of neural activity. However, in most cases the recorded signal is averaged over many (stimulus) repetitions, which erases the fine-structure of the neural signal. Here, we show that an unsupervised machine learning approach can be used to extract meaningful information from electro-physiological recordings on a single-trial base. We use an auto-encoder network to reduce the dimensions of single local field potential (LFP) events to create interpretable clusters of different neural activity patterns. Strikingly, certain LFP shapes correspond to latency differences in different recording channels. Hence, LFP shapes can be used to determine the direction of information flux in the cerebral cortex. Furthermore, after clustering, we decoded the cluster centroids to reverse-engineer the underlying prototypical LFP event shapes. To evaluate our approach, we applied it to both neural extra-cellular recordings in rodents, and intra-cranial EEG recordings in humans. Finally, we find that single channel LFP event shapes during spontaneous activity sample from the realm of possible stimulus evoked event shapes. A finding which so far has only been demonstrated for multi-channel population coding.

neuroscience↗

bioRxiv2020

Intrinsic noise improves speech recognition in a computational model of the auditory pathway

Noise is generally considered to harm information processing performance. However, in the context of stochastic resonance, noise has been shown to improve signal detection of weak subthreshold signals, and it has been proposed that the brain might actively exploit this phenomenon. Especially within the auditory system, recent studies suggest that intrinsic noise plays a key role in signal processing and might even correspond to increased spontaneous neuronal firing rates observed in early processing stages of the auditory brain stem and cortex after hearing loss. Here we present a computational model of the auditory pathway based on a deep neural network, trained on speech recognition. We simulate different levels of hearing loss and investigate the effect of intrinsic noise. Remarkably, speech recognition after hearing loss actually improves with additional intrinsic noise. This surprising result indicates that intrinsic noise might not only play a crucial role in human auditory processing, but might even be beneficial for contemporary machine learning approaches.

neuroscience↗

bioRxiv2019

High-force magnetic tweezers with hysteresis-free force feedback

Magnetic tweezers based on solenoids with iron alloy cores are widely used to apply large forces (~100 nN) onto micron-sized (~5 m) superparamagnetic particles for mechanical manipulation or microrheological measurements at the cellular and molecular level. The precision of magnetic tweezers, however, is limited by the magnetic hysteresis of the core material, especially for time-varying force protocols. Here, we eliminate magnetic hysteresis by a feedback control of the magnetic induction, which we measure with a Hall sensor mounted to the distal end of the solenoid core. We find that the generated force depends on the induction according to a power-law relationship, and on the bead-tip distance according to a stretched exponential relationship. Together, both relationships allow for an accurate force calibration and precise force feedback with only 3 calibration parameters. We apply our method to measure the force-dependence of the viscoelastic and plastic properties of fibroblasts using a protocol with stepwise increasing and decreasing forces. We find that soft cells show an increasing stiffness but decreasing plasticity at higher forces, indicating a pronounced stress stiffening of the cytoskeleton. By contrast, stiff cells show no stress stiffening but an increasing plasticity at higher forces. These findings indicate profound differences between soft and stiff cells regarding their protection mechanisms against external mechanical stress. In summary, our method increases the precision, simplifies the handling and extends the applicability of magnetic tweezers. SIGNIFICANCEMagnetic tweezers are widely used, versatile tools to investigate the mechanical behavior of cells or to measure the strength of receptor-ligand bonds. A limitation of existing high-force magnetic tweezer setups, however, is caused by the magnetic hysteresis of the tweezer core material. This magnetic hysteresis requires that the tweezer core must be de-magnetized (de-Gaussed) prior to each measurement, and that flexible force protocols with decreasing forces are not possible. We describe how these limitations can be overcome with a force feedback though direct magnetic field measurement. We demonstrate the applicability of our setup by investigating the visco-elastic and plastic deformations of fibroblasts to forces of different amplitudes.

biophysics↗