Periodic traction in migrating large amoeba of Physarum polycephalum

Dynamics of centipede locomotion revealed by large-scale traction force microscopy

We present a novel approach to traction force microscopy (TFM) for studying the locomotion of 10 cm long walking centipedes on soft substrates. Leveraging the remarkable elasticity and ductility of kudzu starch gels, we use them as a deformable gel substrate, providing resilience against the centipedes' sharp leg tips. By optimizing fiducial marker size and density and fine-tuning imaging conditions, we enhance measurement accuracy. Our TFM investigation reveals traction forces along the centipede's longitudinal axis that effectively counterbalance inertial forces within the 0-10 mN range, providing the first report of non-vanishing inertia forces in TFM studies. Interestingly, we observe waves of forces propagating from the head to the tail of the centipede, corresponding to its locomotion speed. Furthermore, we discover a characteristic cycle of leg clusters engaging with the substrate: forward force (friction) upon leg tip contact, backward force (traction) as the leg pulls the substrate while stationary, and subsequent forward force as the leg tip detaches to reposition itself in the anterior direction. This work opens perspectives for TFM applications in ethology, tribology and robotics.

Random walk and cell morphology dynamics in Naegleria gruberi

Amoeboid cell movement and migration are wide-spread across various cell types and species. Microscopy-based analysis of the model systems Dictyostelium and neutrophils over the years have uncovered generality in their overall cell movement pattern. Under no directional cues, the centroid movement can be quantitatively characterized by their persistence to move in a straight line and the frequency of re-orientation. Mathematically, the cells essentially behave as a persistent random walker with memory of two characteristic time-scale. Such quantitative characterization is important from a cellular-level ethology point of view as it has direct connotation to their exploratory and foraging strategies. Interestingly, outside the amoebozoa and metazoa, there are largely uncharacterized species in the excavate taxon Heterolobosea including amoeboflagellate Naegleria. While classical works have shown that these cells indeed show typical amoeboid locomotion on an attached surface, their quantitative features are so far unexplored. Here, we analyzed the cell movement of Naegleria gruberi by employing long-time phase contrast imaging that automatically tracks individual cells. We show that the cells move as a persistent random walker with two time-scales that are close to those known in Dictyostelium and neutrophils. Similarities were also found in the shape dynamics which are characterized by the appearance, splitting and annihilation of the curvature waves along the cell edge. Our analysis based on the Fourier descriptor and a neural network classifier point to importance of morphology features unique to Naegleria including complex protrusions and the transient bipolar dumbbell morphologies.

Giant cells: multiple cells unite to survive

Multinucleated Giant Cells (MGCs) are specialized cells that develop from the fusion of multiple cells, and their presence is commonly observed in human cells during various infections. However, MGC formation is not restricted to infections alone but can also occur through different mechanisms, such as endoreplication and abortive cell cycle. These processes lead to the formation of polyploid cells, eventually resulting in the formation of MGCs. In Entamoeba, a protozoan parasite that causes amoebic dysentery and liver abscesses in humans, the formation of MGCs is a unique phenomenon and not been reported in any other protozoa. This organism is exposed to various hostile environmental conditions, including changes in temperature, pH, and nutrient availability, which can lead to stress and damage to its cells. The formation of MGCs in Entamoeba is thought to be a survival strategy to cope with these adverse conditions. This organism forms MGCs through cell aggregation and fusion in response to osmotic and heat stress. The MGCs in Entamoeba are thought to have increased resistance to various stresses and can survive longer than normal cells under adverse conditions. This increased survival could be due to the presence of multiple nuclei, which could provide redundancy in case of DNA damage or mutations. Additionally, MGCs may play a role in the virulence of Entamoeba as they are found in the inflammatory foci of amoebic liver abscesses and other infections caused by Entamoeba. The presence of MGCs in these infections suggests that they may contribute to the pathogenesis of the disease. Overall, this article offers valuable insights into the intriguing phenomenon of MGC formation in Entamoeba. By unraveling the mechanisms behind this process and examining its implications, researchers can gain a deeper understanding of the complex biology of Entamoeba and potentially identify new targets for therapeutic interventions. The study of MGCs in Entamoeba serves as a gateway to exploring the broader field of cell fusion in various organisms, providing a foundation for future investigations into related cellular processes and their significance in health and disease.

2.5D Traction Force Microscopy: Imaging three-dimensional cell forces at interfaces and biological applications

The forces that cells, tissues, and organisms exert on the surface of a soft substrate can be measured using Traction Force Microscopy (TFM), an important and well-established technique in Mechanobiology. The usual TFM technique (two-dimensional, 2D TFM) treats only the in-plane component of the traction forces and omits the out-of-plane forces at the substrate interfaces (2.5D) that turn out to be important in many biological processes such as tissue migration and tumour invasion. Here, we review the imaging, material, and analytical tools to perform "2.5D TFM" and explain how they are different from 2D TFM. Challenges in 2.5D TFM arise primarily from the need to work with a lower imaging resolution in the z-direction, track fiducial markers in three-dimensions, and reliably and efficiently reconstruct mechanical stress from substrate deformation fields. We also discuss how 2.5D TFM can be used to image, map, and understand the complete force vectors in various important biological events of various length-scales happening at two-dimensional interfaces, including focal adhesions forces, cell diapedesis across tissue monolayers, the formation of three-dimensional tissue structures, and the locomotion of large multicellular organisms. We close with future perspectives including the use of new materials, imaging and machine learning techniques to continuously improve the 2.5D TFM in terms of imaging resolution, speed, and faithfulness of the force reconstruction procedure.

Go with the flow - bulk transport by molecular motors

Cells are the smallest building blocks of all living eukaryotic organisms, usually ranging from a couple of micrometers (for example, platelets) to hundreds of micrometers (for example, neurons and oocytes) in size. In eukaryotic cells that are more than 100 µm in diameter, very often a self-organized large-scale movement of cytoplasmic contents, known as cytoplasmic streaming, occurs to compensate for the physical constraints of large cells. In this Review, we discuss cytoplasmic streaming in multiple cell types and the mechanisms driving this event. We particularly focus on the molecular motors responsible for cytoplasmic movements and the biological roles of cytoplasmic streaming in cells. Finally, we describe bulk intercellular flow that transports cytoplasmic materials to the oocyte from its sister germline cells to drive rapid oocyte growth.

Tracking Mechanical Stress and Cell Migration with Inexpensive Polymer Thin-Film Sensors

Polydiacetylene (PDA) Langmuir films are well known for their blue to red chromatic transitions in response to a variety of stimuli, including UV light, heat, bio-molecule bindings and mechanical stress. In this work, we detail the ability to tune PDA Langmuir films to exhibit discrete chromatic transitions in response to applied mechanical stress. Normal and shear-induced transitions were quantified using the Surface Forces Apparatus and established to be binary and tunable as a function of film formation conditions. Both monomer alkyl tail length and metal cations were used to manipulate the chromatic transition force threshold to enable discrete force sensing from ~50 to ~500 nN μm-2 for normal loading and ~2 to ~40 nN μm-2 for shear-induced transitions, which are appropriate for biological cells. The utility of PDA thin-film sensors was demonstrated with the slime mold Physarum polycephalum. The fluorescence readout of the films enabled: the area explored by Physarum to be visualized, the forces involved in locomotion to be quantified, and revealed novel puncta formation potentially associated with Physarum sampling its environment.

Emergence of behaviour in a self-organized living matter network

What is the origin of behaviour? Although typically associated with a nervous system, simple organisms also show complex behaviours. Among them, the slime mold Physarum polycephalum, a giant single cell, is ideally suited to study emergence of behaviour. Here, we show how locomotion and morphological adaptation behaviour emerge from self-organized patterns of rhythmic contractions of the actomyosin lining of the tubes making up the network-shaped organism. We quantify the spatio-temporal contraction dynamics by decomposing experimentally recorded contraction patterns into spatial contraction modes. Notably, we find a continuous spectrum of modes, as opposed to a few dominant modes. Our data suggests that the continuous spectrum of modes allows for dynamic transitions between a plethora of specific behaviours with transitions marked by highly irregular contraction states. By mapping specific behaviours to states of active contractions, we provide the basis to understand behaviour’s complexity as a function of biomechanical dynamics.

Encoding memory in tube diameter hierarchy of living flow network

The concept of memory is traditionally associated with organisms possessing a nervous system. However, even very simple organisms store information about past experiences to thrive in a complex environment-successfully exploiting nutrient sources, avoiding danger, and warding off predators. How can simple organisms encode information about their environment? We here follow how the giant unicellular slime mold Physarum polycephalum responds to a nutrient source. We find that the network-like body plan of the organism itself serves to encode the location of a nutrient source. The organism entirely consists of interlaced tubes of varying diameters. Now, we observe that these tubes grow and shrink in diameter in response to a nutrient source, thereby imprinting the nutrient's location in the tube diameter hierarchy. Combining theoretical model and experimental data, we reveal how memory is encoded: a nutrient source locally releases a softening agent that gets transported by the cytoplasmic flows within the tubular network. Tubes receiving a lot of softening agent grow in diameter at the expense of other tubes shrinking. Thereby, the tubes' capacities for flow-based transport get permanently upgraded toward the nutrient location, redirecting future decisions and migration. This demonstrates that nutrient location is stored in and retrieved from the networks' tube diameter hierarchy. Our findings explain how network-forming organisms like slime molds and fungi thrive in complex environments. We here identify a flow networks' version of associative memory-very likely of relevance for the plethora of living flow networks as well as for bioinspired design.

Active poroelastic two-phase model for the motion of physarum microplasmodia

The onset of self-organized motion is studied in a poroelastic two-phase model with free boundaries for Physarum microplasmodia (MP). In the model, an active gel phase is assumed to be interpenetrated by a passive fluid phase on small length scales. A feedback loop between calcium kinetics, mechanical deformations, and induced fluid flow gives rise to pattern formation and the establishment of an axis of polarity. Altogether, we find that the calcium kinetics that breaks the conservation of the total calcium concentration in the model and a nonlinear friction between MP and substrate are both necessary ingredients to obtain an oscillatory movement with net motion of the MP. By numerical simulations in one spatial dimension, we find two different types of oscillations with net motion as well as modes with time-periodic or irregular switching of the axis of polarity. The more frequent type of net motion is characterized by mechano-chemical waves traveling from the front towards the rear. The second type is characterized by mechano-chemical waves that appear alternating from the front and the back. While both types exhibit oscillatory forward and backward movement with net motion in each cycle, the trajectory and gel flow pattern of the second type are also similar to recent experimental measurements of peristaltic MP motion. We found moving MPs in extended regions of experimentally accessible parameters, such as length, period and substrate friction strength. Simulations of the model show that the net speed increases with the length, provided that MPs are longer than a critical length of ≈ 120 μm. Both predictions are in line with recent experimental observations.

A lumped parameter model of endoplasm flow in Physarum polycephalum explains migration and polarization-induced asymmetry during the onset of locomotion

The plasmodial slime mold Physarum polycephalum exhibits strong, periodic flow of cytoplasm through the veins of its network. In the special case of mesoplasmodia, a newly described starvation-induced, shape-constant morphotype, this periodic endoplasm streaming is the basis of locomotion. Furthermore, we presume that cytoplasm flow is also involved in signal transmission and signal processing. Mesoplasmodia motility resembles amoeboid locomotion. In contrast to other amoebae, however, mesoplasmodia move without extending pseudopods and retain a coherent, fan-shaped morphology throughout their steady locomotion. Attaining sizes of up to 2 mm², mesoplasmodia are also much bigger than other amoebae. We characterize this particular type of locomotion and identify patterns of movement. By using the analogy between pulsatile fluid flow through a network of elastic tubes and electrical circuits, we build a lumped model that explains observed fluid flow patterns. Essentially, the mesoplasmodium acts as a low-pass filter, permitting only low-frequency oscillations to propagate from back to front. This frequency selection serves to optimize flow and reduces power dissipation. Furthermore, we introduce a distributed element into the lumped model to explain cell polarization during the onset of chemotaxis: Biochemical cues (internal or external) lead to a local softening of the actin cortex, which in turn causes an increased flow of cytoplasm into that area and, thus, a net forward movement. We conclude that the internal actin-enclosed vein network gives the slime mold a high measure of control over fluid transport, especially by softening or hardening, which in turn leads to polarization and net movement.

Oscillatory fluid flow drives scaling of contraction wave with system size

Flows over remarkably long distances are crucial to the functioning of many organisms, across all kingdoms of life. Coordinated flows are fundamental to power deformations, required for migration or development, or to spread resources and signals. A ubiquitous mechanism to generate flows, particularly prominent in animals and amoebas, is actomyosin cortex-driven mechanical deformations that pump the fluid enclosed by the cortex. However, it is unclear how cortex dynamics can self-organize to give rise to coordinated flows across the largely varying scales of biological systems. Here, we develop a mechanochemical model of actomyosin cortex mechanics coupled to a contraction-triggering, soluble chemical. The chemical itself is advected with the flows generated by the cortex-driven deformations of the tubular-shaped cell. The theoretical model predicts a dynamic instability giving rise to stable patterns of cortex contraction waves and oscillatory flows. Surprisingly, simulated patterns extend beyond the intrinsic length scale of the dynamic instability-scaling with system size instead. Patterns appear randomly but can be robustly generated in a growing system or by flow-generating boundary conditions. We identify oscillatory flows as the key for the scaling of contraction waves with system size. Our work shows the importance of active flows in biophysical models of patterning, not only as a regulating input or an emergent output, but also as a full part of a self-organized machinery. Contractions and fluid flows are observed in all kinds of organisms, so this concept is likely to be relevant for a broad class of systems.

Fluid flows shaping organism morphology

A dynamic self-organized morphology is the hallmark of network-shaped organisms like slime moulds and fungi. Organisms continuously reorganize their flexible, undifferentiated body plans to forage for food. Among these organisms the slime mould Physarum polycephalum has emerged as a model to investigate how an organism can self-organize their extensive networks and act as a coordinated whole. Cytoplasmic fluid flows flowing through the tubular networks have been identified as the key driver of morphological dynamics. Inquiring how fluid flows can shape living matter from small to large scales opens up many new avenues for research. This article is part of the theme issue 'Self-organization in cell biology'.

Self-organized mechano-chemical dynamics in amoeboid locomotion of Physarum fragments

The aim of this work is to quantify the spatio-temporal dynamics of flow-driven amoeboid locomotion in small (~100 µm) fragments of the true slime mold Physarum polycephalum. In this model organism, cellular contraction drives intracellular flows, and these flows transport the chemical signals that regulate contraction in the first place. As a consequence of these non-linear interactions, a diversity of migratory behaviors can be observed in migrating Physarum fragments. To study these dynamics, we measure the spatio-temporal distributions of the velocities of the endoplasm and ectoplasm of each migrating fragment, the traction stresses it generates on the substratum, and the concentration of free intracellular calcium. Using these unprecedented experimental data, we classify migrating Physarum fragments according to their dynamics, finding that they often exhibit spontaneously coordinated waves of flow, contractility and chemical signaling. We show that Physarum fragments exhibiting symmetric spatio-temporal patterns of endoplasmic flow migrate significantly slower than fragments with asymmetric patterns. In addition, our joint measurements of ectoplasm velocity and traction stress at the substratum suggest that forward motion of the ectoplasm is enabled by a succession of stick-slip transitions, which we conjecture are also organized in the form of waves. Combining our experiments with a simplified convection-diffusion model, we show that the convective transport of calcium ions may be key for establishing and maintaining the spatiotemporal patterns of calcium concentration that regulate the generation of contractile forces.

Mechanism of signal propagation in Physarum polycephalum

Complex behaviors are typically associated with animals, but the capacity to integrate information and function as a coordinated individual is also a ubiquitous but poorly understood feature of organisms such as slime molds and fungi. Plasmodial slime molds grow as networks and use flexible, undifferentiated body plans to forage for food. How an individual communicates across its network remains a puzzle, but Physarum polycephalum has emerged as a novel model used to explore emergent dynamics. Within P. polycephalum, cytoplasm is shuttled in a peristaltic wave driven by cross-sectional contractions of tubes. We first track P. polycephalum's response to a localized nutrient stimulus and observe a front of increased contraction. The front propagates with a velocity comparable to the flow-driven dispersion of particles. We build a mathematical model based on these data and in the aggregate experiments and model identify the mechanism of signal propagation across a body: The nutrient stimulus triggers the release of a signaling molecule. The molecule is advected by fluid flows but simultaneously hijacks flow generation by causing local increases in contraction amplitude as it travels. The molecule is initiating a feedback loop to enable its own movement. This mechanism explains previously puzzling phenomena, including the adaptation of the peristaltic wave to organism size and P. polycephalum's ability to find the shortest route between food sources. A simple feedback seems to give rise to P. polycephalum's complex behaviors, and the same mechanism is likely to function in the thousands of additional species with similar behaviors.

Coordination of contractility, adhesion and flow in migrating Physarum amoebae

This work examines the relationship between spatio-temporal coordination of intracellular flow and traction stress and the speed of amoeboid locomotion of microplasmodia of Physarum polycephalum. We simultaneously perform particle image velocimetry and traction stress microscopy to measure the velocity of cytoplasmic flow and the stresses applied to the substrate by migrating Physarum microamoebae. In parallel, we develop a mathematical model of a motile cell which includes forces from the viscous cytosol, a poro-elastic, contractile cytoskeleton and adhesive interactions with the substrate. Our experiments show that flow and traction stress exhibit back-to-front-directed waves with a distinct phase difference. The model demonstrates that the direction and speed of locomotion are determined by this coordination between contraction, flow and adhesion. Using the model, we identify forms of coordination that generate model predictions consistent with experiments. We demonstrate that this coordination produces near optimal migration speed and is insensitive to heterogeneity in substrate adhesiveness. While it is generally thought that amoeboid motility is robust to changes in extracellular geometry and the nature of extracellular adhesion, our results demonstrate that coordination of adhesive forces is essential to producing robust migration.