Cell shape dynamics: from waves to migration

Emergence of multiple collective motility modes in a physical model of cell chains

Collective cell migration is central to processes like development and cancer metastasis. While mechanisms of collective motility are increasingly understood, their classification remains incomplete. Here, we study the migration of small cell chains, namely cohesive pairs. Experiments with Dictyostelium discoideum (Dd) revealed two motility modes: the individual contributor (IC) mode, where each cell generates its own traction dipole, and the supracellular (S) mode, characterized by a single dipole. Dd pairs favored the IC mode, while Madin-Darby canine kidney (MDCK) doublets predominantly used the S mode. A 2D biophysical model recapitulated many experimental observations; the IC mode emerged naturally in ameboid Dd doublets when both cells exerted similar traction stresses, while the S mode dominated with stronger leaders. Contrary to amebas, MDCK-like cell chains showed a bias towards the IC mode when increasing cell-cell adhesion. Extending the model to longer chains, we show its potential for understanding emergent migration patterns across cell types and scales.

Suppressing collective cell motion with bidirectional guidance cues

In natural environments, cells move in the presence of multiple physical and chemical guidance cues. Using a model system for such guided cell migration, Dictyostelium discoideum (Dicty), we investigate how chemical and physical signals compete in guiding the motion of cell groups. In Dicty cells, chemical signals can lead to collective streaming behavior, in which cells follow one another head-to-tail and aggregate into clusters of ∼10^{5} cells. We use experiments and numerical simulations to show that streaming and aggregation can be suppressed by the addition of a physical guidance cue of comparable strength to the chemical signals, parallel nanoridges. The bidirectional character of physical guidance by ridges is a determining factor in the suppression of streaming and aggregation. Thus, combining multiple types of guidance cues is a powerful approach to trigger or explain a broad range of collective cell behaviors.

Facile Physicochemical Reprogramming of PEG-Dithiolane Microgels

Granular biomaterials have found widespread applications in tissue engineering, in part because of their inherent porosity, tunable properties, injectability, and 3D printability. However, the assembly of granular hydrogels typically relies on spherical microparticles and more complex particle geometries have been limited in scope, often requiring templating of individual microgels by microfluidics or in-mold polymerization. Here, we use dithiolane-functionalized synthetic macromolecules to fabricate photopolymerized microgels via batch emulsion, and then harness the dynamic disulfide crosslinks to rearrange the network. Through unconfined compression between parallel plates in the presence of photoinitiated radicals, we transform the isotropic microgels are transformed into disks. Characterizing this process, we find that the areas of the microgel surface in contact with the compressive plates are flattened while the curvature of the uncompressed microgel boundaries increases. When cultured with C2C12 myoblasts, cells localize to regions of higher curvature on the disk-shaped microgel surfaces. This altered localization affects cell-driven construction of large supraparticle scaffold assemblies, with spherical particles assembling without specific junction structure while disk microgels assemble preferentially on their curved surfaces. These results represent a unique spatiotemporal process for rapid reprocessing of microgels into anisotropic shapes, providing new opportunities to study shape-driven mechanobiological cues during and after granular hydrogel assembly.

Imaging Dissolution Dynamics of Individual NaCl Nanoparticles during Deliquescence with In Situ Transmission Electron Microscopy

Water vapor condensation on hygroscopic aerosol particles plays an important role in cloud formation, climate change, secondary aerosol formation, and aerosol aging. Conventional understanding considers deliquescence of nanosized hygroscopic aerosol particles a nearly instantaneous solid to liquid phase transition. However, the nanoscale dynamics of water condensation and aerosol particle dissolution prior to and during deliquescence remain obscure due to a lack of high spatial and temporal resolution single particle measurements. Here we use real time in situ transmission electron microscopy (TEM) imaging of individual sodium chloride (NaCl) nanoparticles to demonstrate that water adsorption and aerosol particle dissolution prior to and during deliquescence is a multistep dynamic process. Water condensation and aerosol particle dissolution was investigated for lab generated NaCl aerosols and found to occur in three distinct stages as a function of increasing relative humidity (RH). First, a < 100 nm water layer adsorbed on the NaCl cubes and caused sharp corners to dissolve and truncate. The water layer grew to several hundred nanometers with increasing RH and was rapidly saturated with solute, as evidenced by halting of particle dissolution. Adjacent cube corners displayed second-scale curvature fluctuations with no net particle dissolution or water layer thickness change. We propose that droplet solute concentration fluctuations drove NaCl transport from regions of high local curvature to regions of low curvature. Finally, we observed coexistence of a liquid water droplet and aerosol particle immediately prior to deliquescence. Particles dissolved discretely along single crystallographic directions, separated by few second lag times with no dissolution. This work demonstrates that deliquescence of simple pure salt particles with sizes in the range of 100 nm to several microns is not an instantaneous phase transition and instead involves a range of complex dissolution and water condensation dynamics.

Active nuclear positioning and actomyosin contractility maintain leader cell integrity during gonadogenesis

Proper distribution of organelles can play an important role in a moving cell's performance. During C. elegans gonad morphogenesis, the nucleus of the leading distal tip cell (DTC) is always found at the front, yet the significance of this localization is unknown. Here, we identified the molecular mechanism that keeps the nucleus at the front, despite a frictional force that pushes it backward. The Klarsicht/ANC-1/Syne homology (KASH) domain protein UNC-83 links the nucleus to the motor protein kinesin-1 that moves along a polarized acentrosomal microtubule network. Interestingly, disrupting nuclear positioning on its own did not affect gonad morphogenesis. However, reducing actomyosin contractility on top of nuclear mispositioning led to a dramatic phenotype: DTC splitting and gonad bifurcation. Long-term live imaging of the double knockdown revealed that, while the gonad attempted to perform a planned U-turn, the DTC was stretched due to the lagging nucleus until it fragmented into a nucleated cell and an enucleated cytoplast, each leading an independent gonadal arm. Remarkably, the enucleated cytoplast had polarity and invaded, but it could only temporarily support germ cell proliferation. Based on a qualitative biophysical model, we conclude that the leader cell employs two complementary mechanical approaches to preserve its integrity and ensure proper organ morphogenesis while navigating through a complex 3D environment: active nuclear positioning by microtubule motors and actomyosin-driven cortical contractility.

Nuclear curvature determines Yes-associated protein localization and differentiation of mesenchymal stem cells

Controlling mesenchymal stem cell (MSC) differentiation remains a critical challenge in MSCs' therapeutic application. Numerous biophysical and mechanical stimuli influence stem cell fate; however, their relative efficacy and specificity in mechanically directed differentiation remain unclear. Yes-associated protein (YAP) is one key mechanosensitive protein that controls MSC differentiation. Previous studies have related nuclear mechanics with YAP activity, but we still lack an understanding of what nuclear deformation specifically regulates YAP and its relationship with mechanical stimuli. Here, we report that maximum nuclear curvature is the most precise biophysical determinant for YAP mechanotransduction-mediated MSC differentiation and is a relevant parameter for stem cell-based therapies. We employed traction force microscopy and confocal microscopy to characterize the causal relationships between contractility and nuclear deformation in regulating YAP activity in MSCs. We observed that an increase in contractility compresses nuclei anisotropically, whereby the degree of asymmetric compression increased the bending curvature of the nuclear membrane. We then examined membrane curvature and tension using thin micropatterned adhesive substrate lines and an FRET-based tension sensor, revealing the direct role of curvature in YAP activity driven by both active and passive nuclear import. Finally, we employed micropatterned lines to control nuclear curvature and precisely direct MSC differentiation. This work illustrates that nuclear curvature subsumes other biophysical aspects to control YAP-mediated differentiation in MSCs and may provide a deterministic solution to some of the challenges in mesenchymal stem cell therapies.

Drosophila TMEM63 and mouse TMEM63A are lysosomal mechanosensory ion channels

Cells sense physical forces and convert them into electrical or chemical signals, a process known as mechanotransduction. Whereas extensive studies focus on mechanotransduction at the plasma membrane, little is known about whether and how intracellular organelles sense mechanical force and the physiological functions of organellar mechanosensing. Here we identify the Drosophila TMEM63 (DmTMEM63) ion channel as an intrinsic mechanosensor of the lysosome, a major degradative organelle. Endogenous DmTMEM63 proteins localize to lysosomes, mediate lysosomal mechanosensitivity and modulate lysosomal morphology and function. Tmem63 mutant flies exhibit impaired lysosomal degradation, synaptic loss, progressive motor deficits and early death, with some of these mutant phenotypes recapitulating symptoms of TMEM63-associated human diseases. Importantly, mouse TMEM63A mediates lysosomal mechanosensitivity in Neuro-2a cells, indicative of functional conservation in mammals. Our findings reveal DmTMEM63 channel function in lysosomes and its physiological roles in vivo and provide a molecular basis to explore the mechanosensitive process in subcellular organelles.

Cargo Size Limits and Forces of Cell-Driven Microtransport

The integration of motile cells into biohybrid microrobots offers unique properties such as sensitive responses to external stimuli, resilience, and intrinsic energy supply. Here, biohybrid cell-cargo systems that are driven by amoeboid Dictyostelium discoideum cells are studied and how the cargo speed and the resulting viscous drag force scales with increasing radius of the spherical cargo particle are explored. Using a simplified geometrical model of the cell-cargo interaction, the findings toward larger cargo sizes, which are not accessible with the experimental setup, are extrapolated and a maximal cargo size is predicted beyond which active cell-driven movements will stall. The active forces exerted by the cells to move a cargo show mechanoresponsive adaptation and increase dramatically when challenged by an external pulling force, a mechanism that may become relevant when navigating cargo through complex heterogeneous environments.

Three-component contour dynamics model to simulate and analyze amoeboid cell motility in two dimensions

Amoeboid cell motility is relevant in a wide variety of biomedical processes such as wound healing, cancer metastasis, and embryonic morphogenesis. It is characterized by pronounced changes of the cell shape associated with expansions and retractions of the cell membrane, which result in a crawling kind of locomotion. Despite existing computational models of amoeboid motion, the inference of expansion and retraction components of individual cells, the corresponding classification of cells, and the a priori specification of the parameter regime to achieve a specific motility behavior remain challenging open problems. We propose a novel model of the spatio-temporal evolution of two-dimensional cell contours comprising three biophysiologically motivated components: a stochastic term accounting for membrane protrusions and two deterministic terms accounting for membrane retractions by regularizing the shape and area of the contour. Mathematically, these correspond to the intensity of a self-exciting Poisson point process, the area-preserving curve-shortening flow, and an area adjustment flow. The model is used to generate contour data for a variety of qualitatively different, e.g., polarized and non-polarized, cell tracks that visually resemble experimental data very closely. In application to experimental cell tracks, we inferred the protrusion component and examined its correlation to common biomarkers: the F-actin density close to the membrane and its local motion. Due to the low model complexity, parameter estimation is fast, straightforward, and offers a simple way to classify contour dynamics based on two locomotion types: the amoeboid and a so-called fan-shaped type. For both types, we use cell tracks segmented from fluorescence imaging data of the model organism Dictyostelium discoideum. An implementation of the model is provided within the open-source software package AmoePy, a Python-based toolbox for analyzing and simulating amoeboid cell motility.

Scanning ion conductance microscopy revealed cisplatin-induced morphological changes related to apoptosis in single adenocarcinoma cells

The studies of drug-induced apoptosis play a vital role in the identification of potential drugs that could treat diseases such as cancer. Alterations in the native morphology of cancer cells following treatment with anticancer drugs serve as one of the indicators that reveal drug efficacy. Various techniques such as optical microscopy, electron microscopy (EM), and atomic force microscopy (AFM) have been used to map the three dimensional (3D) morphological changes in cells induced with drugs. However, caution should be exercised when interpreting morphological data from techniques that might alter the native morphology of cells, caused by phototoxicity, electron beam invasiveness, intrusive sample preparation, and cell membrane deformation. Herein, we have used scanning ion conductance microscopy (SICM) to study the 3D morphology and roughness of A549 adenocarcinoma cells under physiological conditions before and after cisplatin induced apoptosis, where we observed an increase in height, overall shrinkage of the cells, and irregular features form on the cell membrane. Tracking the morphology of the same single A549 cells exposed to cisplatin unveiled heterogeneity in response to the drug, formation of membrane blebs, and an increase in membrane roughness. We have also demonstrated the use of SICM for studying the effect of cisplatin on the dynamic changes in the volume of A549 cells over days. SICM is demonstrated as a technique for studying the effect of drug induced apoptosis in the same cells over time, and for multiple different single cells.

A Hands-on Guide to AmoePy - a Python-Based Software Package to Analyze Cell Migration Data

Amoeboid cell motility is fundamental for a multitude of biological processes such as embryogenesis, immune responses, wound healing, and cancer metastasis. It is characterized by specific cell shape changes: the extension and retraction of membrane protrusions, known as pseudopodia. A common approach to investigate the mechanisms underlying this type of cell motility is to study phenotypic differences in the locomotion of mutant cell lines. To characterize such differences, methods are required to quantify the contour dynamics of migrating cells. AmoePy is a Python-based software package that provides tools for cell segmentation, contour detection as well as analyzing and simulating contour dynamics. First, a digital representation of the cell contour as a chain of nodes is extracted from each frame of a time-lapse microscopy recording of a moving cell. Then, the dynamics of these nodes-referred to as virtual markers-are tracked as the cell contour evolves over time. From these data, various quantities can be calculated that characterize the contour dynamics, such as the displacement of the virtual markers or the local stretching rate of the marker chain. Their dynamics is typically visualized in space-time plots, the so-called kymographs, where the temporal evolution is displayed for the different locations along the cell contour. Using AmoePy, you can straightforwardly create kymograph plots and videos from stacks of experimental bright-field or fluorescent images of motile cells. A hands-on guide on how to install and use AmoePy is provided in this chapter.

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.

Sensing their plasma membrane curvature allows migrating cells to circumvent obstacles

To navigate through diverse tissues, migrating cells must balance persistent self-propelled motion with adaptive behaviors to circumvent obstacles. We identify a curvature-sensing mechanism underlying obstacle evasion in immune-like cells. Specifically, we propose that actin polymerization at the advancing edge of migrating cells is inhibited by the curvature-sensitive BAR domain protein Snx33 in regions with inward plasma membrane curvature. The genetic perturbation of this machinery reduces the cells' capacity to evade obstructions combined with faster and more persistent cell migration in obstacle-free environments. Our results show how cells can read out their surface topography and utilize actin and plasma membrane biophysics to interpret their environment, allowing them to adaptively decide if they should move ahead or turn away. On the basis of our findings, we propose that the natural diversity of BAR domain proteins may allow cells to tune their curvature sensing machinery to match the shape characteristics in their environment.

A minimal cell model for lamellipodia-based cellular dynamics and migration

One ubiquitous cellular structure for performing various tasks, such as spreading and migration over external surfaces, is the sheet-like protrusion called a lamellipodium, which propels the leading edge of the cell. Despite the detailed knowledge about the many components of this cellular structure, it is not yet fully understood how these components self-organize spatiotemporally to form lamellipodia. We review here recent theoretical works where we have demonstrated that membrane-bound protein complexes that have intrinsic curvature and recruit the protrusive forces of the cytoskeleton result in a simple, yet highly robust, organizing feedback mechanism that organizes the cytoskeleton and the membrane. This self-organization mechanism accounts for the formation of flat lamellipodia at the leading edge of cells spreading over adhesive substrates, allowing for the emergence of a polarized, motile 'minimal cell' model. The same mechanism describes how lamellipodia organize to drive robust engulfment of particles during phagocytosis and explains in simple physical terms the spreading and migration of cells over fibers and other curved surfaces. This Review highlights that despite the complexity of cellular composition, there might be simple general physical principles that are utilized by the cell to drive cellular shape dynamics.

From actin waves to mechanism and back: How theory aids biological understanding

Actin dynamics in cell motility, division, and phagocytosis is regulated by complex factors with multiple feedback loops, often leading to emergent dynamic patterns in the form of propagating waves of actin polymerization activity that are poorly understood. Many in the actin wave community have attempted to discern the underlying mechanisms using experiments and/or mathematical models and theory. Here, we survey methods and hypotheses for actin waves based on signaling networks, mechano-chemical effects, and transport characteristics, with examples drawn from Dictyostelium discoideum, human neutrophils, Caenorhabditis elegans, and Xenopus laevis oocytes. While experimentalists focus on the details of molecular components, theorists pose a central question of universality: Are there generic, model-independent, underlying principles, or just boundless cell-specific details? We argue that mathematical methods are equally important for understanding the emergence, evolution, and persistence of actin waves and conclude with a few challenges for future studies.

Decoding Natural Astrocyte Rhythms: Dynamic Actin Waves Result from Environmental Sensing by Primary Rodent Astrocytes

Astrocytes are key regulators of brain homeostasis, equilibrating ion, water, and neurotransmitter concentrations and maintaining essential conditions for proper cognitive function. Recently, it has been shown that the excitability of the actin cytoskeleton manifests in second-scale dynamic fluctuations and acts as a sensor of chemophysical environmental cues. However, it is not known whether the cytoskeleton is excitable in astrocytes and how the homeostatic function of astrocytes is linked to the dynamics of the cytoskeleton. Here it is shown that homeostatic regulation involves the excitable dynamics of actin in certain subcellular regions of astrocytes, especially near the cell boundary. The results further indicate that actin dynamics concentrate into "hotspot" regions that selectively respond to certain chemophysical stimuli, specifically the homeostatic challenges of ion or water concentration increases. Substrate topography makes the actin dynamics of astrocytes weaker. Super-resolution images demonstrate that surface topography is also associated with the predominant perpendicular alignment of actin filaments near the cell boundary, whereas flat substrates result in an actin cortex mainly parallel to the cell boundary. Additionally, coculture with neurons increases both the probability of actin dynamics and the strength of hotspots. The excitable systems character of actin thus makes astrocytes direct participants in neural cell network dynamics.

Polarized branched Actin modulates cortical mechanics to produce unequal-size daughters during asymmetric division

The control of cell shape during cytokinesis requires a precise regulation of mechanical properties of the cell cortex. Only few studies have addressed the mechanisms underlying the robust production of unequal-sized daughters during asymmetric cell division. Here we report that unequal daughter-cell sizes resulting from asymmetric sensory organ precursor divisions in Drosophila are controlled by the relative amount of cortical branched Actin between the two cell poles. We demonstrate this by mistargeting the machinery for branched Actin dynamics using nanobodies and optogenetics. We can thereby engineer the cell shape with temporal precision and thus the daughter-cell size at different stages of cytokinesis. Most strikingly, inverting cortical Actin asymmetry causes an inversion of daughter-cell sizes. Our findings uncover the physical mechanism by which the sensory organ precursor mother cell controls relative daughter-cell size: polarized cortical Actin modulates the cortical bending rigidity to set the cell surface curvature, stabilize the division and ultimately lead to unequal daughter-cell size.

Spontaneous transitions between amoeboid and keratocyte-like modes of migration

The motility of adherent eukaryotic cells is driven by the dynamics of the actin cytoskeleton. Despite the common force-generating actin machinery, different cell types often show diverse modes of locomotion that differ in their shape dynamics, speed, and persistence of motion. Recently, experiments in Dictyostelium discoideum have revealed that different motility modes can be induced in this model organism, depending on genetic modifications, developmental conditions, and synthetic changes of intracellular signaling. Here, we report experimental evidence that in a mutated D. discoideum cell line with increased Ras activity, switches between two distinct migratory modes, the amoeboid and fan-shaped type of locomotion, can even spontaneously occur within the same cell. We observed and characterized repeated and reversible switchings between the two modes of locomotion, suggesting that they are distinct behavioral traits that coexist within the same cell. We adapted an established phenomenological motility model that combines a reaction-diffusion system for the intracellular dynamics with a dynamic phase field to account for our experimental findings.

ATP levels influence cell movement during the mound phase in Dictyostelium discoideum as revealed by ATP visualization and simulation

Cell migration plays an important role in multicellular organism development. The cellular slime mold Dictyostelium discoideum is a useful model organism for the study of cell migration during development. Although cellular ATP levels are known to determine cell fate during development, the underlying mechanism remains unclear. Here, we report that ATP-rich cells efficiently move to the central tip region of the mound against rotational movement during the mound phase. A simulation analysis based on an agent-based model reproduces the movement of ATP-rich cells observed in the experiments. These findings indicate that ATP-rich cells have the ability to move against the bulk flow of cells, suggesting a mechanism by which high ATP levels determine the cell fate of differentiation.

Combined Effect of Matrix Topography and Stiffness on Neutrophil Shape and Motility

The crawling behavior of leukocytes is driven by the cell morphology transition, which is a direct manifestation of molecular motor machinery. The topographical anisotropy and mechanical stiffness of the substrates are the main physical cues that affect leukocytes' shape generation and migratory responses. However, their combined effects on the cell morphology and motility have been poorly understood, particularly for neutrophils, which are the fastest reacting leukocytes against infections and wounds. Here, spatiotemporally correlated physical parameters are shown, which determine the neutrophil shape change during migratory processes, in response to surface topography and elasticity. Guided crawling and shape generation of individual neutrophils, activated by a uniform concentration of a chemoattractant, are analyzed by adopting elasticity-tunable micropatterning and live cell imaging techniques. Whole cell-level image analysis is performed based on a planar geometric quantification of cell shape and motility. The findings show that the pattern anisotropy and elastic modulus of the substrate induce synergic effects on the shape anisotropy, deformability, and polarization/alignment of crawling neutrophils. How the morphology-motility relationship is affected by different surface microstructures and stiffness is demonstrated. These results imply that the neutrophil shape-motility correlations can be utilized for controlling the immune cell functions with predefined physical microenvironments.

T cell morphodynamics reveal periodic shape oscillations in three-dimensional migration

T cells use sophisticated shape dynamics (morphodynamics) to migrate towards and neutralize infected and cancerous cells. However, there is limited quantitative understanding of the migration process in three-dimensional extracellular matrices (ECMs) and across timescales. Here, we leveraged recent advances in lattice light-sheet microscopy to quantitatively explore the three-dimensional morphodynamics of migrating T cells at high spatio-temporal resolution. We first developed a new shape descriptor based on spherical harmonics, incorporating key polarization information of the uropod. We found that the shape space of T cells is low-dimensional. At the behavioural level, run-and-stop migration modes emerge at approximately 150 s, and we mapped the morphodynamic composition of each mode using multiscale wavelet analysis, finding 'stereotyped' motifs. Focusing on the run mode, we found morphodynamics oscillating periodically (every approx. 100 s) that can be broken down into a biphasic process: front-widening with retraction of the uropod, followed by a rearward surface motion and forward extension, where intercalation with the ECM in both of these steps likely facilitates forward motion. Further application of these methods may enable the comparison of T cell migration across different conditions (e.g. differentiation, activation, tissues and drug treatments) and improve the precision of immunotherapeutic development.

Actin Dynamics as a Multiscale Integrator of Cellular Guidance Cues

Migrating cells must integrate multiple, competing external guidance cues. However, it is not well understood how cells prioritize among these cues. We investigate external cue integration by monitoring the response of wave-like, actin-polymerization dynamics, the driver of cell motility, to combinations of nanotopographies and electric fields in neutrophil-like cells. The electric fields provide a global guidance cue, and approximate conditions at wound sites in vivo. The nanotopographies have dimensions similar to those of collagen fibers, and act as a local esotactic guidance cue. We find that cells prioritize guidance cues, with electric fields dominating long-term motility by introducing a unidirectional bias in the locations at which actin waves nucleate. That bias competes successfully with the wave guidance provided by the bidirectional nanotopographies.

Cortical softening elicits zygotic contractility during mouse preimplantation development

Actomyosin contractility is a major engine of preimplantation morphogenesis, which starts at the 8-cell stage during mouse embryonic development. Contractility becomes first visible with the appearance of periodic cortical waves of contraction (PeCoWaCo), which travel around blastomeres in an oscillatory fashion. How contractility of the mouse embryo becomes active remains unknown. We have taken advantage of PeCoWaCo to study the awakening of contractility during preimplantation development. We find that PeCoWaCo become detectable in most embryos only after the second cleavage and gradually increase their oscillation frequency with each successive cleavage. To test the influence of cell size reduction during cleavage divisions, we use cell fusion and fragmentation to manipulate cell size across a 20- to 60-μm range. We find that the stepwise reduction in cell size caused by cleavage divisions does not explain the presence of PeCoWaCo or their accelerating rhythm. Instead, we discover that blastomeres gradually decrease their surface tensions until the 8-cell stage and that artificially softening cells enhances PeCoWaCo prematurely. We further identify the programmed down-regulation of the formin Fmnl3 as a required event to soften the cortex and expose PeCoWaCo. Therefore, during cleavage stages, cortical softening, mediated by Fmnl3 down-regulation, awakens zygotic contractility before preimplantation morphogenesis.

During preimplantation morphogenesis, the mouse embryo relies on forces generated by the actomyosin cytoskeleton. This study uncovers how periodic actomyosin contractions increase in frequency during cleavage stages as blastomeres soften with each cleavage division.

Genetic characterization of carrot root shape and size using genome-wide association analysis and genomic-estimated breeding values

The principal phenotypic determinants of market class in carrot-the size and shape of the root-are under primarily additive, but also highly polygenic, genetic control. The size and shape of carrot roots are the primary determinants not only of yield, but also market class. These quantitative phenotypes have historically been challenging to objectively evaluate, and thus subjective visual assessment of market class remains the primary method by which selection for these traits is performed. However, advancements in digital image analysis have recently made possible the high-throughput quantification of size and shape attributes. It is therefore now feasible to utilize modern methods of genetic analysis to investigate the genetic control of root morphology. To this end, this study utilized both genome wide association analysis (GWAS) and genomic-estimated breeding values (GEBVs) and demonstrated that the components of market class are highly polygenic traits, likely under the influence of many small effect QTL. Relatively large proportions of additive genetic variance for many of the component phenotypes support high predictive ability of GEBVs; average prediction ability across underlying market class traits was 0.67. GWAS identified multiple QTL for four of the phenotypes which compose market class: length, aspect ratio, maximum width, and root fill, a previously uncharacterized trait which represents the size-independent portion of carrot root shape. By combining digital image analysis with GWAS and GEBVs, this study represents a novel advance in our understanding of the genetic control of market class in carrot. The immediate practical utility and viability of genomic selection for carrot market class is also described, and concrete guidelines for the design of training populations are provided.

Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows

Amoeboid cell motility is essential for a wide range of biological processes including wound healing, embryonic morphogenesis, and cancer metastasis. It relies on complex dynamical patterns of cell shape changes that pose long-standing challenges to mathematical modeling and raise a need for automated and reproducible approaches to extract quantitative morphological features from image sequences. Here, we introduce a theoretical framework and a computational method for obtaining smooth representations of the spatiotemporal contour dynamics from stacks of segmented microscopy images. Based on a Gaussian process regression we propose a one-parameter family of regularized contour flows that allows us to continuously track reference points (virtual markers) between successive cell contours. We use this approach to define a coordinate system on the moving cell boundary and to represent different local geometric quantities in this frame of reference. In particular, we introduce the local marker dispersion as a measure to identify localized membrane expansions and provide a fully automated way to extract the properties of such expansions, including their area and growth time. The methods are available as an open-source software package called AmoePy, a Python-based toolbox for analyzing amoeboid cell motility (based on time-lapse microscopy data), including a graphical user interface and detailed documentation. Due to the mathematical rigor of our framework, we envision it to be of use for the development of novel cell motility models. We mainly use experimental data of the social amoeba Dictyostelium discoideum to illustrate and validate our approach.

Amoeboid motion is a crawling-like cell migration that plays an important key role in multiple biological processes such as wound healing and cancer metastasis. This type of cell motility results from expanding and simultaneously contracting parts of the cell membrane. From fluorescence images, we obtain a sequence of points, representing the cell membrane, for each time step. By using regression analysis on these sequences, we derive smooth representations, so-called contours, of the membrane. Since the number of measurements is discrete and often limited, the question is raised of how to link consecutive contours with each other. In this work, we present a novel mathematical framework in which these links are described by regularized flows allowing a certain degree of concentration or stretching of neighboring reference points on the same contour. This stretching rate, the so-called local dispersion, is used to identify expansions and contractions of the cell membrane providing a fully automated way of extracting properties of these cell shape changes. We applied our methods to time-lapse microscopy data of the social amoeba Dictyostelium discoideum.

Comparative mapping of crawling-cell morphodynamics in deep learning-based feature space

Navigation of fast migrating cells such as amoeba Dictyostelium and immune cells are tightly associated with their morphologies that range from steady polarized forms that support high directionality to those more complex and variable when making frequent turns. Model simulations are essential for quantitative understanding of these features and their origins, however systematic comparisons with real data are underdeveloped. Here, by employing deep-learning-based feature extraction combined with phase-field modeling framework, we show that a low dimensional feature space for 2D migrating cell morphologies obtained from the shape stereotype of keratocytes, Dictyostelium and neutrophils can be fully mapped by an interlinked signaling network of cell-polarization and protrusion dynamics. Our analysis links the data-driven shape analysis to the underlying causalities by identifying key parameters critical for migratory morphologies both normal and aberrant under genetic and pharmacological perturbations. The results underscore the importance of deciphering self-organizing states and their interplay when characterizing morphological phenotypes.

Migratory cells that move by crawling do so by extending and retracting their plasma membrane. When and where these events take place determine the cell shape, and this is directly linked to the movement patterns. Understanding how the highly plastic and interconvertible morphologies appear from their underlying dynamics remains a challenge partly because their inherent complexity makes quantitatively comparison against the outputs of mathematical models difficult. To this end, we employed machine-learning based classification to extract features that characterize the basic migrating morphologies. The obtained features were then used to compare real cell data with outputs of a conceptual model that we introduced which describes coupling via feedback between local protrusive dynamics and polarity. The feature mapping showed that the model successfully recapitulates the shape dynamics that were not covered by previous related models and also hints at the critical parameters underlying state transitions. The ability of the present approach to compare model outputs with real cell data systematically and objectively is important as it allows outputs of future mathematical models to be quantitatively tested in an accessible and common reference frame.

Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells

During the last decade, a consensus has emerged that the stochastic triggering of an excitable system drives pseudopod formation and subsequent migration of amoeboid cells. The presence of chemoattractant stimuli alters the threshold for triggering this activity and can bias the direction of migration. Though noise plays an important role in these behaviors, mathematical models have typically ignored its origin and merely introduced it as an external signal into a series of reaction-diffusion equations. Here we consider a more realistic description based on a reaction-diffusion master equation formalism to implement these networks. In this scheme, noise arises naturally from a stochastic description of the various reaction and diffusion terms. Working on a three-dimensional geometry in which separate compartments are divided into a tetrahedral mesh, we implement a modular description of the system, consisting of G-protein coupled receptor signaling (GPCR), a local excitation-global inhibition mechanism (LEGI), and signal transduction excitable network (STEN). Our models implement detailed biochemical descriptions whenever this information is available, such as in the GPCR and G-protein interactions. In contrast, where the biochemical entities are less certain, such as the LEGI mechanism, we consider various possible schemes and highlight the differences between them. Our simulations show that even when the LEGI mechanism displays perfect adaptation in terms of the mean level of proteins, the variance shows a dose-dependence. This differs between the various models considered, suggesting a possible means for determining experimentally among the various potential networks. Overall, our simulations recreate temporal and spatial patterns observed experimentally in both wild-type and perturbed cells, providing further evidence for the excitable system paradigm. Moreover, because of the overall importance and ubiquity of the modules we consider, including GPCR signaling and adaptation, our results will be of interest beyond the field of directed migration.

Though the term noise usually carries negative connotations, it can also contribute positively to the characteristic dynamics of a system. In biological systems, where noise arises from the stochastic interactions between molecules, its study is usually confined to genetic regulatory systems in which copy numbers are small and fluctuations large. However, noise can have important roles when the number of signaling molecules is large. The extension of pseudopods and the subsequent motion of amoeboid cells arises from the noise-induced trigger of an excitable system. Chemoattractant signals bias this triggering thereby directing cell motion. To date, this paradigm has not been tested by mathematical models that account accurately for the noise that arises in the corresponding reactions. In this study, we employ a reaction-diffusion master equation approach to investigate the effects of noise. Using a modular approach and a three-dimensional cell model with specific subdomains attributed to the cell membrane and cortex, we explore the spatiotemporal dynamics of the system. Our simulations recreate many experimentally-observed cell behaviors thereby supporting the biased-excitable network hypothesis.

An optogenetic model reveals cell shape regulation through FAK and fascin

Cell shape regulation is important, but the mechanisms that govern shape are not fully understood, in part due to limited experimental models in which cell shape changes and underlying molecular processes can be rapidly and non-invasively monitored in real time. Here, we used an optogenetic tool to activate RhoA in the middle of mononucleated macrophages to induce contraction, resulting in a side with the nucleus that retained its shape and a non-nucleated side that was unable to maintain its shape and collapsed. In cells overexpressing focal adhesion kinase (FAK; also known as PTK2), the non-nucleated side exhibited a wide flat morphology and was similar in adhesion area to the nucleated side. In cells overexpressing fascin, an actin-bundling protein, the non-nucleated side assumed a spherical shape and was similar in height to the nucleated side. This effect of fascin was also observed in fibroblasts even without inducing furrow formation. Based on these results, we conclude that FAK and fascin work together to maintain cell shape by regulating adhesion area and height, respectively, in different cell types. This article has an associated First Person interview with the first author of the paper.

A Digital Image-Based Phenotyping Platform for Analyzing Root Shape Attributes in Carrot

Root shape in carrot (Daucus carota subsp. sativus), which ranges from long and tapered to short and blunt, has been used for at least several centuries to classify carrot cultivars. The subjectivity involved in determining market class hinders the establishment of metric-based standards and is ill-suited to dissecting the genetic basis of such quantitative phenotypes. Advances in digital image acquisition and analysis has enabled new methods for quantifying sizes of plant structures and shapes, but in order to dissect the genetic control of the shape features that define market class in carrot, a tool is required that quantifies the specific shape features used by humans in distinguishing between classes. This study reports the construction and demonstration of the first such platform, which facilitates rapid phenotyping of traits that are measurable by hand, such as length and width, as well as principal component analysis (PCA) of the root contour and its curvature. This latter approach is of particular interest, as it enabled the detection of a novel and significant quantitative trait, defined here as root fill, which accounts for 85% of the variation in root shape. Curvature analysis was demonstrated to be an effective method for precise measurement of the broadness of the carrot shoulder, and degree of tip fill; the first principal component of the respective curvature profiles captured 87% and 84% of the total variance. This platform's performance was validated in two experimental panels. First, a diverse, global collection of germplasm was used to assess its capacity to identify market classes through clustering analysis. Second, a diallel mating design between inbred breeding lines of differing market classes was used to estimate the heritability of the key phenotypes that define market class, which revealed significant variation in the narrow-sense heritability of size and shape traits, ranging from 0.14 for total root size, to 0.84 for aspect ratio. These results demonstrate the value of high-throughput digital phenotyping in characterizing the genetic control of complex quantitative phenotypes.

Early time-point cell morphology classifiers successfully predict human bone marrow stromal cell differentiation modulated by fiber density in nanofiber scaffolds

Nanofiber scaffolds can induce osteogenic differentiation and cell morphology alterations of human bone marrow stromal cells (hBMSCs) without introduction of chemical cues. In this study, we investigate the predictive power of day 1 cell morphology, quantified by a machine learning based method, as an indicator of osteogenic differentiation modulated by nanofiber density. Nanofiber scaffolds are fabricated via electrospinning. Microscopy, quantitative image processing and clustering analysis are used to systematically quantify scaffold properties as a function of fiber density. hBMSC osteogenic differentiation potential is evaluated after 14 days using osteogenic marker gene expression and after 50 days using calcium mineralization, showing enhanced osteogenic differentiation with an increase in nanofiber density. Cell morphology measurements at day 1 successfully predict differentiation potential when analyzed with the support vector machine (SVM)/supercell tools previously developed and trained on cells from a different donor. A correlation is observed between differentiation potential and cell morphology, demonstrating sensitivity of the morphology measurement to varying degrees of differentiation potential. To further understand how nanofiber density determines hBMSC morphology, both full 3-D morphology measurements as well as other measurements of the 2-D projected morphology are investigated in this study. To achieve predictive power on hBMSC osteogenic differentiation, at least two morphology metrics need to be considered together for each cell, with the majority of metric pairs including one 3-D morphology metric. Analysis of the local nanofiber structure surrounding each cell reveals a correlation with single-cell morphology and indicates that the osteogenic differentiation phenotype may be predictive at the single-cell level.

The Roles of Signaling in Cytoskeletal Changes, Random Movement, Direction-Sensing and Polarization of Eukaryotic Cells

Movement of cells and tissues is essential at various stages during the lifetime of an organism, including morphogenesis in early development, in the immune response to pathogens, and during wound-healing and tissue regeneration. Individual cells are able to move in a variety of microenvironments (MEs) (A glossary of the acronyms used herein is given at the end) by suitably adapting both their shape and how they transmit force to the ME, but how cells translate environmental signals into the forces that shape them and enable them to move is poorly understood. While many of the networks involved in signal detection, transduction and movement have been characterized, how intracellular signals control re-building of the cyctoskeleton to enable movement is not understood. In this review we discuss recent advances in our understanding of signal transduction networks related to direction-sensing and movement, and some of the problems that remain to be solved.

Cellular locomotion using environmental topography

Eukaryotic cells migrate by coupling the intracellular force of the actin cytoskeleton to the environment. While force coupling is usually mediated by transmembrane adhesion receptors, especially those of the integrin family, amoeboid cells such as leukocytes can migrate extremely fast despite very low adhesive forces¹. Here we show that leukocytes cannot only migrate under low adhesion but can also transmit forces in the complete absence of transmembrane force coupling. When confined within three-dimensional environments, they use the topographical features of the substrate to propel themselves. Here the retrograde flow of the actin cytoskeleton follows the texture of the substrate, creating retrograde shear forces that are sufficient to drive the cell body forwards. Notably, adhesion-dependent and adhesion-independent migration are not mutually exclusive, but rather are variants of the same principle of coupling retrograde actin flow to the environment and thus can potentially operate interchangeably and simultaneously. As adhesion-free migration is independent of the chemical composition of the environment, it renders cells completely autonomous in their locomotive behaviour.

Motility and morphodynamics of confined cells

We introduce a minimal hydrodynamic model of polarization, migration, and deformation of a biological cell confined between two parallel surfaces. In our model, the cell is driven out of equilibrium by an active cytsokeleton force that acts on the membrane. The cell cytoplasm, described as a viscous droplet in the Darcy flow regime, contains a diffusive solute that actively transduces the applied cytoskeleton force. While fairly simple and analytically tractable, this quasi-two-dimensional model predicts a range of compelling dynamic behaviours. A linear stability analysis of the system reveals that solute activity first destabilizes a global polarization-translation mode, prompting cell motility through spontaneous symmetry breaking. At higher activity, the system crosses a series of Hopf bifurcations leading to coupled oscillations of droplet shape and solute concentration profiles. At the nonlinear level, we find traveling-wave solutions associated with unique polarized shapes that resemble experimental observations. Altogether, this model offers an analytical paradigm of active deformable systems in which viscous hydrodynamics are coupled to diffusive force transducers.

Modulation of the mechanosensing of mesenchymal stem cells by laser-induced patterning for the acceleration of tissue reconstruction through the Wnt/β-catenin signaling pathway activation

Growing evidence suggests that the physical microenvironment can guide cell fate. However, cells sense cues from the adjacent physical microenvironment over a limited distance. In the present study, murine mesenchymal stem cells (MSCs) and murine preosteoblastic cells (MC3T3-E1) behaviors are regulated by the cell-material interface using ordered-micro and disordered-nano patterned structures on Ti implants. The optimal bone formation structure is a stable wave (horizontal direction: ridge, 2.7 µm; grooves, 5.3 µm; and vertical direction: distance, 700 µm) with the appropriate density of nano-branches (6.0 per µm²). The repeated waves provide cells with directional guidance, and the disordered branches influence cell geometry by providing different spacing and density nanostructure. And micro-nano patterned structure can provide biophysical cues to direct cell phenotype development, including cell size, shape, and orientation, to influence cellular processes including survival, growth, and differentiation. Thus, the overlaid isotropic and anisotropic cues, ordered-micro and disordered-nano patterned structures, could transfer further and alter cell shape and induce nuclear orientation by activating Wnt/β-catenin signaling to promote integrin α5, integrin β1, cadherin 2, Runx2, Opn, and Ocn. That canonical Wnt signaling inhibitor dickkopf1 further demonstrates osteogenic differentiation induced by ordered-micro and disordered-nano patterned structures, which is related to Wnt/β-catenin signaling. Our findings show the role of ordered microstructures and disordered nanostructures in modulating stem cell differentiation with potential medical applications. STATEMENT OF SIGNIFICANCE: It remains a challenge to modify poor osteogenic and osteoconductive properties of titanium alloy bases on the inherent poverty of titanium. We demonstrate that ordered microtopography and disordered nano topography pattern structure could lead to osteogenic differentiation in vitro and bone regeneration in vivo. Furthermore, the pattern structure is created through selective laser melting and alkali heat. And the structure only takes advantage of titanium itself and does not bring in active film, such as hydroxyapatite. On the other hand, we find that cell shape and orientation show angle-orientation tendency due to the polarity, which involves with mechanical signal created via patterned structure. Meanwhile, the Wnt/Ca²⁺ signaling pathway is activated.

Substrate composition directs slime molds behavior

Cells, including unicellulars, are highly sensitive to external constraints from their environment. Amoeboid cells change their cell shape during locomotion and in response to external stimuli. Physarum polycephalum is a large multinucleated amoeboid cell that extends and develops pseudopods. In this paper, changes in cell behavior and shape were measured during the exploration of homogenous and non-homogenous environments that presented neutral, and nutritive and/or adverse substances. In the first place, we developed a fully automated image analysis method to measure quantitatively changes in both migration and shape. Then we measured various metrics that describe the area covered, the exploration dynamics, the migration rate and the slime mold shape. Our results show that: (1) Not only the nature, but also the spatial distribution of chemical substances affect the exploration behavior of slime molds; (2) Nutritive and adverse substances both slow down the exploration and prevent the formation of pseudopods; and (3) Slime mold placed in an adverse environment preferentially occupies previously explored areas rather than unexplored areas using mucus secretion as a buffer. Our results also show that slime molds migrate at a rate governed by the substrate up until they get within a critical distance to chemical substances.

Cell Migration: Making the Waves

Coordinated changes of cell shape are often the result of the excitable, wave-like dynamics of the actin cytoskeleton. New work shows that, in migrating cells, protrusion waves arise from mechanochemical crosstalk between adhesion sites, membrane tension and the actin protrusive machinery.

Identifying the mechanism for superdiffusivity in mouse fibroblast motility

We seek to characterize the motility of mouse fibroblasts on 2D substrates. Utilizing automated tracking techniques, we find that cell trajectories are super-diffusive, where displacements scale faster than t1/2 in all directions. Two mechanisms have been proposed to explain such statistics in other cell types: run and tumble behavior with Lévy-distributed run times, and ensembles of cells with heterogeneous speed and rotational noise. We develop an automated toolkit that directly compares cell trajectories to the predictions of each model and demonstrate that ensemble-averaged quantities such as the mean-squared displacements and velocity autocorrelation functions are equally well-fit by either model. However, neither model correctly captures the short-timescale behavior quantified by the displacement probability distribution or the turning angle distribution. We develop a hybrid model that includes both run and tumble behavior and heterogeneous noise during the runs, which correctly matches the short-timescale behaviors and indicates that the run times are not Lévy distributed. The analysis tools developed here should be broadly useful for distinguishing between mechanisms for superdiffusivity in other cells types and environments.

Statistical and Mathematical Modeling of Spatiotemporal Dynamics of Stem Cells

Statistical and mathematical modeling are crucial to describe, interpret, compare, and predict the behavior of complex biological systems including the organization of hematopoietic stem and progenitor cells in the bone marrow environment. The current prominence of high-resolution and live-cell imaging data provides an unprecedented opportunity to study the spatiotemporal dynamics of these cells within their stem cell niche and learn more about aberrant, but also unperturbed, normal hematopoiesis. However, this requires careful quantitative statistical analysis of the spatial and temporal behavior of cells and the interaction with their microenvironment. Moreover, such quantification is a prerequisite for the construction of hypothesis-driven mathematical models that can provide mechanistic explanations by generating spatiotemporal dynamics that can be directly compared to experimental observations. Here, we provide a brief overview of statistical methods in analyzing spatial distribution of cells, cell motility, cell shapes, and cellular genealogies. We also describe cell-based modeling formalisms that allow researchers to simulate emergent behavior in a multicellular system based on a set of hypothesized mechanisms. Together, these methods provide a quantitative workflow for the analytic and synthetic study of the spatiotemporal behavior of hematopoietic stem and progenitor cells.

Adhesion strategies of Dictyostelium discoideum- a force spectroscopy study

Biological adhesion is essential for all motile cells and generally limits locomotion to suitably functionalized substrates displaying a compatible surface chemistry. However, organisms that face vastly varying environmental challenges require a different strategy. The model organism Dictyostelium discoideum (D.d.), a slime mould dwelling in the soil, faces the challenge of overcoming variable chemistry by employing the fundamental forces of colloid science. To understand the origin of D.d. adhesion, we realized and modified a variety of conditions for the amoeba comprising the absence and presence of the specific adhesion protein Substrate Adhesion A (sadA), glycolytic degradation, ionic strength, surface hydrophobicity and strength of van der Waals interactions by generating tailored model substrates. By employing AFM-based single cell force spectroscopy we could show that experimental force curves upon retraction exhibit two regimes. The first part up to the critical adhesion force can be described in terms of a continuum model, while the second regime of the curve beyond the critical adhesion force is governed by stochastic unbinding of individual binding partners and bond clusters. We found that D.d. relies on adhesive interactions based on EDL-DLVO (Electrical Double Layer-Derjaguin-Landau-Verwey-Overbeek) forces and contributions from the glycocalix and specialized adhesion molecules like sadA. This versatile mechanism allows the cells to adhere to a large variety of natural surfaces under various conditions.

Modeling random crawling, membrane deformation and intracellular polarity of motile amoeboid cells

Amoeboid movement is one of the most widespread forms of cell motility that plays a key role in numerous biological contexts. While many aspects of this process are well investigated, the large cell-to-cell variability in the motile characteristics of an otherwise uniform population remains an open question that was largely ignored by previous models. In this article, we present a mathematical model of amoeboid motility that combines noisy bistable kinetics with a dynamic phase field for the cell shape. To capture cell-to-cell variability, we introduce a single parameter for tuning the balance between polarity formation and intracellular noise. We compare numerical simulations of our model to experiments with the social amoeba Dictyostelium discoideum. Despite the simple structure of our model, we found close agreement with the experimental results for the center-of-mass motion as well as for the evolution of the cell shape and the overall intracellular patterns. We thus conjecture that the building blocks of our model capture essential features of amoeboid motility and may serve as a starting point for more detailed descriptions of cell motion in chemical gradients and confined environments.

Intravital microscopy of collective invasion plasticity in breast cancer

Cancer invasion programs are adaptive by switching between metastatic collective and single-cell dissemination; however, current intravital microscopy models for epithelial cancer in mice fail to reliably recreate such invasion plasticity. Using microimplantation of breast cancer spheroids into the murine mammary fat pad and live-cell monitoring, we show microenvironmental conditions and cytoskeletal adaptation during collective to single-cell transition in vivo E-cadherin-expressing 4T1 and E-cadherin-negative MMT tumors both initiated collective invasion along stromal structures, reflecting invasion patterns in 3D organotypic culture and human primary ductal and lobular carcinoma. Collectively invading cells developed weakly oscillatory actin dynamics, yet provided zones for single-cell transitions with accentuated, more chaotic actin fluctuations. This identifies collective invasion in vivo as a dynamic niche and efficient source for single-cell release.

Chemokines and integrins independently tune actin flow and substrate friction during intranodal migration of T cells

Although much is known about the physiological framework of T cell motility, and numerous rate-limiting molecules have been identified through loss-of-function approaches, an integrated functional concept of T cell motility is lacking. Here, we used in vivo precision morphometry together with analysis of cytoskeletal dynamics in vitro to deconstruct the basic mechanisms of T cell migration within lymphatic organs. We show that the contributions of the integrin LFA-1 and the chemokine receptor CCR7 are complementary rather than positioned in a linear pathway, as they are during leukocyte extravasation from the blood vasculature. Our data demonstrate that CCR7 controls cortical actin flows, whereas integrins mediate substrate friction that is sufficient to drive locomotion in the absence of considerable surface adhesions and plasma membrane flux.

Morphometrics of complex cell shapes: lobe contribution elliptic Fourier analysis (LOCO-EFA)

Quantifying cell morphology is fundamental to the statistical study of cell populations, and can help unravel mechanisms underlying cell and tissue morphogenesis. Current methods, however, require extensive human intervention, are highly parameter sensitive, or produce metrics that are difficult to interpret biologically. We therefore developed a method, lobe contribution elliptical Fourier analysis (LOCO-EFA), which generates from digitalised two-dimensional cell outlines meaningful descriptors that can be directly matched to morphological features. This is shown by studying well-defined geometric shapes as well as actual biological cells from plant and animal tissues. LOCO-EFA provides a tool to phenotype efficiently and objectively populations of cells, here demonstrated by applying it to the complex shaped pavement cells of Arabidopsis thaliana wild-type and speechless leaves, and Drosophila amnioserosa cells. To validate our method's applicability to large populations, we analysed computer-generated tissues. By controlling in silico cell shape, we explored the potential impact of cell packing on individual cell shape, quantifying through LOCO-EFA deviations between the specified shape of single cells in isolation and the resultant shape when they interact within a confluent tissue.

Nociceptive interneurons control modular motor pathways to promote escape behavior in Drosophila

Rapid and efficient escape behaviors in response to noxious sensory stimuli are essential for protection and survival. Yet, how noxious stimuli are transformed to coordinated escape behaviors remains poorly understood. In Drosophila larvae, noxious stimuli trigger sequential body bending and corkscrew-like rolling behavior. We identified a population of interneurons in the nerve cord of Drosophila, termed Down-and-Back (DnB) neurons, that are activated by noxious heat, promote nociceptive behavior, and are required for robust escape responses to noxious stimuli. Electron microscopic circuit reconstruction shows that DnBs are targets of nociceptive and mechanosensory neurons, are directly presynaptic to pre-motor circuits, and link indirectly to Goro rolling command-like neurons. DnB activation promotes activity in Goro neurons, and coincident inactivation of Goro neurons prevents the rolling sequence but leaves intact body bending motor responses. Thus, activity from nociceptors to DnB interneurons coordinates modular elements of nociceptive escape behavior.

Non-Gaussianity, population heterogeneity, and transient superdiffusion in the spreading dynamics of amoeboid cells

What is the underlying diffusion process governing the spreading dynamics and search strategies employed by amoeboid cells?

Extracting microtentacle dynamics of tumor cells in a non-adherent environment

During metastasis, tumor cells dynamically change their cytoskeleton to traverse through a variety of non-adherent microenvironments, including the vasculature or lymphatics. Due to the challenges of imaging drift in non-adhered tumor cells, the dynamic cytoskeletal phenotypes are poorly understood. We present a new approach to analyze the dynamic cytoskeletal phenotypes of non-adhered cells that support microtentacles (McTNs), which are cell surface projections implicated in metastatic reattachment. Combining a recently-developed cell tethering method with a novel image analysis framework allowed McTN attribute extraction. Full cell outlines, number of McTNs, and distance of McTN tips from the cell body boundary were calculated by integrating a rotating anisotropic filtering method for identifying thin features with retinal segmentation and active contour algorithms. Tethered cells behave like free-floating cells; however tethering reduces cell drift and improves the accuracy of McTN measurements. Tethering cells does not significantly alter McTN number, but rather allows better visualization of existing McTNs. In drug treatment experiments, stabilizing tubulin with paclitaxel significantly increases McTN length, while destabilizing tubulin with colchicine significantly decreases McTN length. Finally, we quantify McTN dynamics by computing the time delay autocorrelations of 2 composite phenotype metrics (cumulative McTN tip distance, cell perimeter:cell body ratio). Our automated analysis demonstrates that treatment with paclitaxel increases total McTN amount and colchicine reduces total McTN amount, while paclitaxel also reduces McTN dynamics. This analysis method enables rapid quantitative measurement of tumor cell drug responses within non-adherent microenvironments, using the small numbers of tumor cells that would be available from patient samples.

Cell protrusion and retraction driven by fluctuations in actin polymerization: A two-dimensional model

Animal cells that spread onto a surface often rely on actin-rich lamellipodial extensions to execute protrusion. Many cell types recently adhered on a two-dimensional substrate exhibit protrusion and retraction of their lamellipodia, even though the cell is not translating. Travelling waves of protrusion have also been observed, similar to those observed in crawling cells. These regular patterns of protrusion and retraction allow quantitative analysis for comparison to mathematical models. The periodic fluctuations in leading edge position of XTC cells have been linked to excitable actin dynamics using a one-dimensional model of actin dynamics, as a function of arc-length along the cell. In this work we extend this earlier model of actin dynamics into two dimensions (along the arc-length and radial directions of the cell) and include a model membrane that protrudes and retracts in response to the changing number of free barbed ends of actin filaments near the membrane. We show that if the polymerization rate at the barbed ends changes in response to changes in their local concentration at the leading edge and/or the opposing force from the cell membrane, the model can reproduce the patterns of membrane protrusion and retraction seen in experiment. We investigate both Brownian ratchet and switch-like force-velocity relationships between the membrane load forces and actin polymerization rate. The switch-like polymerization dynamics recover the observed patterns of protrusion and retraction as well as the fluctuations in F-actin concentration profiles. The model generates predictions for the behavior of cells after local membrane tension perturbations.

Live-single-cell phenotypic cancer biomarkers-future role in precision oncology?

The promise of precision and personalized medicine is rooted in accurate, highly sensitive, and specific disease biomarkers. This is particularly true for cancer-a disease characterized by marked tumor heterogeneity and diverse molecular signatures. Although thousands of biomarkers have been described, only a very small number have been successfully translated into clinical use. Undoubtedly, there is need for rapid, quantitative, and more cost effective biomarkers for tumor diagnosis and prognosis, to allow for better risk stratification and aid clinicians in making personalized treatment decisions. This is particularly true for cancers where specific biomarkers are either not available (e.g., renal cell carcinoma) or where current biomarkers tend to classify individuals into broad risk categories unable to accurately assess individual tumor aggressiveness and adverse pathology potential (e.g., prostate cancer), thereby leading to problems of over-diagnosis and over-treatment of indolent cancer and under-treatment of aggressive cancer. This perspective highlights an emerging class of cancer biomarkers-live-single-cell phenotypic biomarkers, as compared to genomic biomarkers, and their potential application for cancer diagnosis, risk-stratification, and prognosis.

The microfluidic lighthouse: an omnidirectional gradient generator

Studies of chemotactic cell migration rely heavily on various assay systems designed to evaluate the ability of cells to move in response to attractant molecules. In particular, the development of microfluidics-based devices in recent years has made it possible to spatially distribute attractant molecules in graded profiles that are sufficiently stable and precise to test theoretical predictions regarding the accuracy and efficiency of chemotaxis and the underlying mechanism of stimulus perception. However, because the gradient is fixed in a direction orthogonal to the laminar flow and thus the chamber geometry, conventional devices are limited for the study of cell re-orientation to gradients that move or change directions. Here, we describe the development of a simple radially symmetric microfluidics device that can deliver laminar flow in 360°. A stimulant introduced either from the central inlet or by photo uncaging is focused into the laminar flow in a direction determined by the relative rate of regulated flow from multiple side channels. Schemes for flow regulation and an extended duplexed device were designed to generate and move gradients in desired orientations and speed, and then tested to steer cell migration of Dictyostelium and neutrophil-like HL60 cells. The device provided a high degree of freedom in the positioning and orientation of attractant gradients, and thus may serve as a versatile platform for studying cell migration, re-orientation, and steering.

Curvature-induced expulsion of actomyosin bundles during cytokinetic ring contraction

Many eukaryotes assemble a ring-shaped actomyosin network that contracts to drive cytokinesis. Unlike actomyosin in sarcomeres, which cycles through contraction and relaxation, the cytokinetic ring disassembles during contraction through an unknown mechanism. Here we find in Schizosaccharomyces japonicus and Schizosaccharomyces pombe that, during actomyosin ring contraction, actin filaments associated with actomyosin rings are expelled as micron-scale bundles containing multiple actomyosin ring proteins. Using functional isolated actomyosin rings we show that expulsion of actin bundles does not require continuous presence of cytoplasm. Strikingly, mechanical compression of actomyosin rings results in expulsion of bundles predominantly at regions of high curvature. Our work unprecedentedly reveals that the increased curvature of the ring itself promotes its disassembly. It is likely that such a curvature-induced mechanism may operate in disassembly of other contractile networks.

DOI:http://dx.doi.org/10.7554/eLife.21383.001