A quorum-sensing factor in vegetative Dictyostelium discoideum cells revealed by quantitative migration analysis

Non-Gaussian Displacements in Active Transport on a Carpet of Motile Cells

We study the dynamics of micron-sized particles on a layer of motile cells. This cell carpet acts as an active bath that propels passive tracer particles via direct mechanical contact. The resulting nonequilibrium transport shows a crossover from superdiffusive to normal-diffusive dynamics. The particle displacement distribution is distinctly non-Gaussian even at macroscopic timescales exceeding the measurement time. We obtain the distribution of diffusion coefficients from the experimental data and introduce a model for the displacement distribution that matches the experimentally observed non-Gaussian statistics. We argue why similar transport properties are expected for many composite active matter systems.

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.

The aerotaxis of Dictyostelium discoideum is independent of mitochondria, nitric oxide and oxidative stress

Spatial and temporal variations of oxygen environments affect the behaviors of various cells and are involved in physiological and pathological events. Our previous studies with Dictyostelium discoideum as a model of cell motility have demonstrated that aerotaxis toward an oxygen-rich region occurs below 2% O₂. However, while the aerotaxis of Dictyostelium seems to be an effective strategy to search for what is essential for survival, the mechanism underlying this phenomenon is still largely unclear. One hypothesis is that an oxygen concentration gradient generates a secondary oxidative stress gradient that would direct cell migration towards higher oxygen concentration. Such mechanism was inferred but not fully demonstrated to explain the aerotaxis of human tumor cells. Here, we investigated the role on aerotaxis of flavohemoglobins, proteins that can both act as potential oxygen sensors and modulators of nitric oxide and oxidative stress. The migratory behaviors of Dictyostelium cells were observed under both self-generated and imposed oxygen gradients. Furthermore, their changes by chemicals generating or preventing oxidative stress were tested. The trajectories of the cells were then analyzed through time-lapse phase-contrast microscopic images. The results indicate that both oxidative and nitrosative stresses are not involved in the aerotaxis of Dictyostelium but cause cytotoxic effects that are enhanced upon hypoxia.

On the origin of the functional versatility of macrophages

Macrophages represent the most functionally versatile cells in the animal body. In addition to recognizing and destroying pathogens, macrophages remove senescent and exhausted cells, promote wound healing, and govern tissue and metabolic homeostasis. In addition, many specialized populations of tissue-resident macrophages exhibit highly specialized functions essential for the function of specific organs. Sometimes, however, macrophages cease to perform their protective function and their seemingly incomprehensible response to certain stimuli leads to pathology. In this study, we address the question of the origin of the functional versatility of macrophages. To this end, we have searched for the evolutionary origin of macrophages themselves and for the emergence of their characteristic properties. We hypothesize that many of the characteristic features of proinflammatory macrophages evolved in the unicellular ancestors of animals, and that the functional repertoire of macrophage-like amoebocytes further expanded with the evolution of multicellularity and the increasing complexity of tissues and organ systems. We suggest that the entire repertoire of macrophage functions evolved by repurposing and diversification of basic functions that evolved early in the evolution of metazoans under conditions barely comparable to that in tissues of multicellular organisms. We believe that by applying this perspective, we may find an explanation for the otherwise counterintuitive behavior of macrophages in many human pathologies.

Heterogeneous individual motility biases group composition in a model of aggregating cells

Aggregative life cycles are characterized by alternating phases of unicellular growth and multicellular development. Their multiple, independent evolutionary emergence suggests that they may have coopted pervasive properties of single-celled ancestors. Primitive multicellular aggregates, where coordination mechanisms were less efficient than in extant aggregative microbes, must have faced high levels of conflict between different co-aggregating populations. Such conflicts within a multicellular body manifest in the differential reproductive output of cells of different types. Here, we study how heterogeneity in cell motility affects the aggregation process and creates a mismatch between the composition of the population and that of self-organized groups of active adhesive particles. We model cells as self-propelled particles and describe aggregation in a plane starting from a dispersed configuration. Inspired by the life cycle of aggregative model organisms such as Dictyostelium discoideum or Myxococcus xanthus, whose cells interact for a fixed duration before the onset of chimeric multicellular development, we study finite-time configurations for identical particles and in binary mixes. We show that co-aggregation results in three different types of frequency-dependent biases, one of which is associated to evolutionarily stable coexistence of particles with different motility. We propose a heuristic explanation of such observations, based on the competition between delayed aggregation of slower particles and detachment of faster particles. Unexpectedly, despite the complexity and non-linearity of the system, biases can be largely predicted from the behavior of the two corresponding homogenous populations. This model points to differential motility as a possibly important factor in driving the evolutionary emergence of facultatively multicellular life-cycles.

Aerotaxis and aerokinesis of Dictyostelium discoideum under hypoxic microenvironments

Although spatiotemporal changes of oxygen in a microenvironment are known to affect the cellular dynamics of various eukaryotes, the details are not fully understood. Here, we describe the aerotaxis and aerokinesis of Dictyostelium discoideum (Dd), which has long been employed as a model organism for eukaryotic cells. We developed a microfluidic device capable of time-lapse observation of cultured cells while controlling oxygen concentrations in microchannels. Migratory behaviors of Dd were observed and quantitatively evaluated under an oxygen concentration gradient from 0% to 21% O₂, as well as in various uniform oxygen conditions. In a hypoxic region within the oxygen concentration gradient, Dd migrated toward regions of higher oxygen concentration at increased velocity, which was independent of cell density. Observed under uniform oxygen concentrations of 1%, 2%, 3%, and 21%, the migration velocity of Dd increased significantly in hypoxic environments of 2% O₂ or less. Thus, Dd shows aerotaxis, directed by the oxygen concentration gradient, and simultaneously shows aerokinesis, changing the migration velocity according to the oxygen concentration itself.

Hypoxia triggers collective aerotactic migration in Dictyostelium discoideum

Using a self-generated hypoxic assay, we show that the amoeba Dictyostelium discoideum displays a remarkable collective aerotactic behavior. When a cell colony is covered, cells quickly consume the available oxygen (O₂) and form a dense ring moving outwards at constant speed and density. To decipher this collective process, we combined two technological developments: porphyrin-based O₂ -sensing films and microfluidic O₂ gradient generators. We showed that Dictyostelium cells exhibit aerotactic and aerokinetic response in a low range of O₂ concentration indicative of a very efficient detection mechanism. Cell behaviors under self-generated or imposed O₂ gradients were modeled using an in silico cellular Potts model built on experimental observations. This computational model was complemented with a parsimonious ‘Go or Grow’ partial differential equation (PDE) model. In both models, we found that the collective migration of a dense ring can be explained by the interplay between cell division and the modulation of aerotaxis.

Role of LrrkA in the Control of Phagocytosis and Cell Motility in Dictyostelium discoideum

LrrkA is a Dictyostelium discoideum kinase with leucine-rich repeats. LrrkA stimulates Kil2 and intra-phagosomal killing of ingested bacteria in response to folate. In this study, we show that genetic inactivation of lrrkA also causes a previously unnoticed phenotype: lrrkA KO cells exhibit enhanced phagocytosis and cell motility compared to parental cells. This phenotype is cell autonomous, is reversible upon re-expression of LrrkA, and is not due to an abnormal response to inhibitory quorum-sensing factors secreted by D. discoideum in its medium. In addition, folate increases motility in parental D. discoideum cells, but not in lrrkA KO cells, suggesting that LrrkA plays a pivotal role in the cellular response to folate. On the contrary, lrrkA KO cells regulate gene transcription in response to folate in a manner indistinguishable from parental cells. Overall, based on analysis of mutant phenotypes, we identify gene products that participate in the control of intracellular killing, cell motility, and gene transcription in response to folate. These observations reveal a mechanism by which D. discoideum encountering bacterially-secreted folate can migrate, engulf, and kill bacteria more efficiently.

Short- and long-term memory of moving amoeboid cells

Amoeboid cells constantly change shape and extend protrusions. The direction of movement is not random, but is correlated with the direction of movement in the preceding minutes. The basis of this correlation is an underlying memory of direction. The presence of memory in movement is known for many decades, but its molecular mechanism is still largely unknown. This study reports in detail on the information content of directional memory, the kinetics of learning and forgetting this information, and the molecular basis for memory using Dictyostelium mutants. Two types of memory were characterized. A short-term memory stores for ~20 seconds the position of the last pseudopod using a local modification of the branched F-actin inducer SCAR/WAVE, which enhances one new pseudopod to be formed at the position of the previous pseudopod. A long term memory stores for ~2 minutes the activity of the last ~10 pseudopods using a cGMP-binding protein that induces myosin filaments in the rear of the cell; this inhibits pseudopods in the rear and thereby enhances pseudopods in the global front. Similar types of memory were identified in human neutrophils and mesenchymal stem cells, the protist Dictyostelium and the fungus B.d. chytrid. The synergy of short- and long-term memory explains their role in persistent movement for enhanced cell dispersal, food seeking and chemotaxis.

From a discrete model of chemotaxis with volume-filling to a generalized Patlak-Keller-Segel model

We present a discrete model of chemotaxis whereby cells responding to a chemoattractant are seen as individual agents whose movement is described through a set of rules that result in a biased random walk. In order to take into account possible alterations in cellular motility observed at high cell densities (i.e. volume-filling), we let the probabilities of cell movement be modulated by a decaying function of the cell density. We formally show that a general form of the celebrated Patlak-Keller-Segel (PKS) model of chemotaxis can be formally derived as the appropriate continuum limit of this discrete model. The family of steady-state solutions of such a generalized PKS model are characterized and the conditions for the emergence of spatial patterns are studied via linear stability analysis. Moreover, we carry out a systematic quantitative comparison between numerical simulations of the discrete model and numerical solutions of the corresponding PKS model, both in one and in two spatial dimensions. The results obtained indicate that there is excellent quantitative agreement between the spatial patterns produced by the two models. Finally, we numerically show that the outcomes of the two models faithfully replicate those of the classical PKS model in a suitable asymptotic regime.

Collective regulation of cell motility using an accurate density-sensing system

The capacity of living cells to sense their population density and to migrate accordingly is essential for the regulation of many physiological processes. However, the mechanisms used to achieve such functions are poorly known. Here, based on the analysis of multiple trajectories of vegetative Dictyostelium discoideum cells, we investigate such a system extensively. We show that the cells secrete a high-molecular-weight quorum-sensing factor (QSF) in their medium. This extracellular signal induces, in turn, a reduction of the cell movements, in particular, through the downregulation of a mode of motility with high persistence time. This response appears independent of cAMP and involves a G-protein-dependent pathway. Using a mathematical analysis of the cells' response function, we evidence a negative feedback on the QSF secretion, which unveils a powerful generic mechanism for the cells to detect when they exceed a density threshold. Altogether, our results provide a comprehensive and dynamical view of this system enabling cells in a scattered population to adapt their motion to their neighbours without physical contact.

Harnessing Motile Amoeboid Cells as Trucks for Microtransport and -Assembly

Cell-driven microtransport is one of the most prominent applications in the emerging field of biohybrid systems. While bacterial cells have been successfully employed to drive the swimming motion of micrometer-sized cargo particles, the transport capacities of motile adherent cells remain largely unexplored. Here, it is demonstrated that motile amoeboid cells can act as efficient and versatile trucks to transport microcargo. When incubated together with microparticles, cells of the social amoeba Dictyostelium discoideum readily pick up and move the cargo particles. Relying on the unspecific adhesive properties of the amoeba, a wide range of different cargo materials can be used. The cell-driven transport can be directionally guided based on the chemotactic responses of amoeba to chemoattractant gradients. On the one hand, the cargo can be assembled into clusters in a self-organized fashion, relying on the developmentally induced chemotactic aggregation of cells. On the other hand, chemoattractant gradients can be externally imposed to guide the cellular microtrucks to a desired location. Finally, larger cargo particles of different shapes that exceed the size of a single cell by more than an order of magnitude, can also be transported by the collective effort of large numbers of motile cells.

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.

Biased continuous-time random walks for ordinary and equilibrium cases: facilitation of diffusion, ergodicity breaking and ageing

We examine renewal processes with power-law waiting time distributions (WTDs) and non-zero drift via computing analytically and by computer simulations their ensemble and time averaged spreading characteristics. All possible values of the scaling exponent α are considered for the WTD ψ(t) ∼ 1/t1+α. We treat continuous-time random walks (CTRWs) with 0 < α < 1 for which the mean waiting time diverges, and investigate the behaviour of the process for both ordinary and equilibrium CTRWs for 1 < α < 2 and α > 2. We demonstrate that in the presence of a drift CTRWs with α < 1 are ageing and non-ergodic in the sense of the non-equivalence of their ensemble and time averaged displacement characteristics in the limit of lag times much shorter than the trajectory length. In the sense of the equivalence of ensemble and time averages, CTRW processes with 1 < α < 2 are ergodic for the equilibrium and non-ergodic for the ordinary situation. Lastly, CTRW renewal processes with α > 2-both for the equilibrium and ordinary situation-are always ergodic. For the situations 1 < α < 2 and α > 2 the variance of the diffusion process, however, depends on the initial ensemble. For biased CTRWs with α > 1 we also investigate the behaviour of the ergodicity breaking parameter. In addition, we demonstrate that for biased CTRWs the Einstein relation is valid on the level of the ensemble and time averaged displacements, in the entire range of the WTD exponent α.

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?

Synthetic quorum sensing in model microcapsule colonies

Biological quorum sensing refers to the ability of cells to gauge their population density and collectively initiate a new behavior once a critical density is reached. Designing synthetic materials systems that exhibit quorum sensing-like behavior could enable the fabrication of devices with both self-recognition and self-regulating functionality. Herein, we develop models for a colony of synthetic microcapsules that communicate by producing and releasing signaling molecules. Production of the chemicals is regulated by a biomimetic negative feedback loop, the "repressilator" network. Through theory and simulation, we show that the chemical behavior of such capsules is sensitive to both the density and number of capsules in the colony. For example, decreasing the spacing between a fixed number of capsules can trigger a transition in chemical activity from the steady, repressed state to large-amplitude oscillations in chemical production. Alternatively, for a fixed density, an increase in the number of capsules in the colony can also promote a transition into the oscillatory state. This configuration-dependent behavior of the capsule colony exemplifies quorum-sensing behavior. Using our theoretical model, we predict the transitions from the steady state to oscillatory behavior as a function of the colony size and capsule density.

Generalized run-and-turn motions: From bacteria to Lévy walks

Swimming bacteria exhibit a repertoire of motility patterns, in which persistent motion is interrupted by turning events. What are the statistical properties of such random walks? If some particular instances have long been studied, the general case where turning times do not follow a Poisson process has remained unsolved. We present a generic extension of the continuous time random walks formalism relying on operators and noncommutative calculus. The approach is first applied to a unimodal model of bacterial motion. We examine the existence of a minimum in velocity correlation function and discuss the maximum of diffusivity at an optimal value of rotational diffusion. The model is then extended to bimodal patterns and includes as particular cases all swimming strategies: run-and-tumble, run-stop, run-reverse and run-reverse-flick. We characterize their velocity correlation functions and investigate how bimodality affects diffusivity. Finally, the wider applicability of the method is illustrated by considering curved trajectories and Lévy walks. Our results are relevant for intermittent motion of living beings, be they swimming micro-organisms or crawling cells.

Role of SpdA in Cell Spreading and Phagocytosis in Dictyostelium

Dictyostelium discoideum is a widely used model to study molecular mechanisms controlling cell adhesion, cell spreading on a surface, and phagocytosis. In this study we isolated and characterize a new mutant created by insertion of a mutagenic vector in the heretofore uncharacterized spdA gene. SpdA-ins mutant cells produce an altered, slightly shortened version of the SpdA protein. They spread more efficiently than WT cells when allowed to adhere to a glass substrate, and phagocytose particles more efficiently. On the contrary, a functional spdA knockout mutant where a large segment of the gene was deleted phagocytosed less efficiently and spread less efficiently on a substrate. These phenotypes were highly dependent on the cellular density, and were most visible at high cell densities, where secreted quorum-sensing factors inhibiting cell motility, spreading and phagocytosis are most active. These results identify the involvement of SpdA in the control of cell spreading and phagocytosis. The underlying molecular mechanisms, as well as the exact link between SpdA and cell spreading, remain to be established.

Actin flows mediate a universal coupling between cell speed and cell persistence

Cell movement has essential functions in development, immunity, and cancer. Various cell migration patterns have been reported, but no general rule has emerged so far. Here, we show on the basis of experimental data in vitro and in vivo that cell persistence, which quantifies the straightness of trajectories, is robustly coupled to cell migration speed. We suggest that this universal coupling constitutes a generic law of cell migration, which originates in the advection of polarity cues by an actin cytoskeleton undergoing flows at the cellular scale. Our analysis relies on a theoretical model that we validate by measuring the persistence of cells upon modulation of actin flow speeds and upon optogenetic manipulation of the binding of an actin regulator to actin filaments. Beyond the quantitative prediction of the coupling, the model yields a generic phase diagram of cellular trajectories, which recapitulates the full range of observed migration patterns.

Optimal cooperative searching using purely repulsive interactions

Foraging, either solitarily or collectively, is a necessary behavior for survival that is demonstrated by many organisms. Foraging can be collectively optimized by utilizing communication between the organisms. Examples of such communication range from high level strategic foraging by animal groups to rudimentary signaling among unicellular organisms. Here we systematically study the simplest form of communication via long range repulsive interactions between multiple diffusing Brownian searchers on a one-dimensional lattice. We show that the mean first passage time for any one of them to reach a fixed target depends non-monotonically on the range of the interaction and can be optimized for a repulsive range that is comparable to the average spacing between searchers. Our results suggest that even the most rudimentary form of collective searching does in fact lower the search time for the foragers suggesting robust mechanisms for search optimization in cellular communities.

Temperature limitation may explain the containment of the trophozoites in the cornea during Acanthamoeba castellanii keratitis

Acanthamoeba keratitis is a serious sight-threatening disease. The relatively low temperature of the cornea may explain why amoebic infections usually are localized in this tissue and rarely spread to other parts of the eye. In this study, the growth rate of the amoeba Acanthamoeba castellanii was examined at different temperatures. The aim was to establish the optimal growth temperature for A. castellanii and to examine the growth within the vicinity of the core body temperature. The growth rates of four clinical and two environmental strains of A. castellanii were estimated at different temperatures, and temperature limitations for the trophozoite stage was established. Movements influenced by temperature gradients were monitored for two clinical strains of A. castellanii. The highest growth rate for each of the six amoebic strains tested was found to be close to 32 °C. The growth of the trophozoites of all examined strains was greatly reduced or completely halted at temperatures above 36 °C and encysted at the elevated temperature. Thus, the optimal growth temperature for the four strains of A. castellanii is close to the surface temperature of the human cornea, while the higher body core-temperature induced encysting of the amoebae. This may explain why most amoebic eye infections are confined to the cornea.

Quantitative and unbiased analysis of directional persistence in cell migration

The mechanism by which cells control directional persistence during migration is a major question. However, the common index measuring directional persistence, namely the ratio of displacement to trajectory length, is biased, particularly by cell speed. An unbiased method is to calculate direction autocorrelation as a function of time. This function depends only on the angles of the vectors tangent to the trajectory. This method has not been widely used, because it is more difficult to compute. Here we discuss biases of the classical index and introduce a custom-made open-source computer program, DiPer, which calculates direction autocorrelation. In addition, DiPer also plots and calculates other essential parameters to analyze cell migration in two dimensions: it displays cell trajectories individually and collectively, and it calculates average speed and mean square displacements (MSDs) to assess the area explored by cells over time. This user-friendly program is executable through Microsoft Excel, and it generates plots of publication-level quality. The protocol takes ∼15 min to complete. We have recently used DiPer to analyze cell migration of three different mammalian cell types in 2D cultures: the mammary carcinoma cell line MDA-MB-231, the motile amoeba Dictyostelium discoideum and fish-scale keratocytes. DiPer can potentially be used not only for random migration in 2D but also for directed migration and for migration in 3D (direction autocorrelation only). Moreover, it can be used for any types of tracked particles: cellular organelles, bacteria and whole organisms.

Spontaneous emergence of large-scale cell cycle synchronization in amoeba colonies

Unicellular eukaryotic amoebae Dictyostelium discoideum are generally believed to grow in their vegetative state as single cells until starvation, when their collective aspect emerges and they differentiate to form a multicellular slime mold. While major efforts continue to be aimed at their starvation-induced social aspect, our understanding of population dynamics and cell cycle in the vegetative growth phase has remained incomplete. Here we show that cell populations grown on a substrate spontaneously synchronize their cell cycles within several hours. These collective population-wide cell cycle oscillations span millimeter length scales and can be completely suppressed by washing away putative cell-secreted signals, implying signaling by means of a diffusible growth factor or mitogen. These observations give strong evidence for collective proliferation behavior in the vegetative state.

Differential adhesion between moving particles as a mechanism for the evolution of social groups

The evolutionary stability of cooperative traits, that are beneficial to other individuals but costly to their carrier, is considered possible only through the establishment of a sufficient degree of assortment between cooperators. Chimeric microbial populations, characterized by simple interactions between unrelated individuals, restrain the applicability of standard mechanisms generating such assortment, in particular when cells disperse between successive reproductive events such as happens in Dicyostelids and Myxobacteria. In this paper, we address the evolutionary dynamics of a costly trait that enhances attachment to others as well as group cohesion. By modeling cells as self-propelled particles moving on a plane according to local interaction forces and undergoing cycles of aggregation, reproduction and dispersal, we show that blind differential adhesion provides a basis for assortment in the process of group formation. When reproductive performance depends on the social context of players, evolution by natural selection can lead to the success of the social trait, and to the concomitant emergence of sizeable groups. We point out the conditions on the microscopic properties of motion and interaction that make such evolutionary outcome possible, stressing that the advent of sociality by differential adhesion is restricted to specific ecological contexts. Moreover, we show that the aggregation process naturally implies the existence of non-aggregated particles, and highlight their crucial evolutionary role despite being largely neglected in theoretical models for the evolution of sociality.

Although pervasive in the living world, collective behavior is a puzzle for evolutionary biology. The genetic traits that sustain it are costly for their carriers and make them vulnerable to the exploitation of asocial “free-riders” that benefit from the group without contributing to its cohesion. This paradox has spawned an extensive literature mainly concerned with elaborate cooperative behaviors that might be inoperant for simple biological entities such as microbes. We model successive life cycles of aggregation, reproduction and dispersal in a biological population combining a statistical physics approach to mimic the group formation process and an evolutionary game theory approach to account for the conflict between individual competition and collective success. Our results show a parsimonious way to the advent of sociality based on differential physical adhesion in organisms deprived of complex cognitive abilities. We also stress the key role of ungrouped individuals and specify the conditions on motion properties that make sociality possible. In detailing a mechanism akin to promote social behavior in microbes in the absence of genealogical relatedness, our work might shed light on both the maintenance of facultative multicellular lifestyles and the evolutionary origins of multicellularity.

Modeling and measuring signal relay in noisy directed migration of cell groups

We develop a coarse-grained stochastic model for the influence of signal relay on the collective behavior of migrating Dictyostelium discoideum cells. In the experiment, cells display a range of collective migration patterns, including uncorrelated motion, formation of partially localized streams, and clumping, depending on the type of cell and the strength of the external, linear concentration gradient of the signaling molecule cyclic adenosine monophosphate (cAMP). From our model, we find that the pattern of migration can be quantitatively described by the competition of two processes, the secretion rate of cAMP by the cells and the degradation rate of cAMP in the gradient chamber. Model simulations are compared to experiments for a wide range of strengths of an external linear-gradient signal. With degradation, the model secreting cells form streams and efficiently transverse the gradient, but without degradation, we find that model secreting cells form clumps without streaming. This indicates that the observed effective collective migration in streams requires not only signal relay but also degradation of the signal. In addition, our model allows us to detect and quantify precursors of correlated motion, even when cells do not exhibit obvious streaming.

Collective cell migration is observed in various biological processes including angiogenesis, gastrulation, fruiting body formation, and wound healing. Dictyostelium discoideum, for example, exhibits highly dynamic patterns such as streams and clumps during its early phases of collective motion and has served as a model organism for the study of collective migration. In this study, facilitated by experiments, we develop a conceptual, minimalistic, computational model to analyze the dynamical processes leading to the emergence of collective patterns and the associated dependence on the external injection of a cAMP signal, the intercellular cAMP secretion rate, and the cAMP degradation rate. We demonstrate that degradation is necessary to reproduce the experimentally observed collective migration patterns, and show how our model can be utilized to uncover basic dependences of migration modes on cell characteristics. Our numerical observations elucidate the different possible types of motion and quantify the onset of collective motion. Thus, the model allows us to distinguish noisy motion guided by the external signal from weakly correlated motion.

A tapered channel microfluidic device for comprehensive cell adhesion analysis, using measurements of detachment kinetics and shear stress-dependent motion

We have developed a method for studying cellular adhesion by using a custom-designed microfluidic device with parallel non-connected tapered channels. The design enables investigation of cellular responses to a large range of shear stress (ratio of 25) with a single input flow-rate. For each shear stress, a large number of cells are analyzed (500-1500 cells), providing statistically relevant data within a single experiment. Besides adhesion strength measurements, the microsystem presented in this paper enables in-depth analysis of cell detachment kinetics by real-time videomicroscopy. It offers the possibility to analyze adhesion-associated processes, such as migration or cell shape change, within the same experiment. To show the versatility of our device, we examined quantitatively cell adhesion by analyzing kinetics, adhesive strength and migration behaviour or cell shape modifications of the unicellular model cell organism Dictyostelium discoideum at 21 °C and of the human breast cancer cell line MDA-MB-231 at 37 °C. For both cell types, we found that the threshold stresses, which are necessary to detach the cells, follow lognormal distributions, and that the detachment process follows first order kinetics. In addition, for particular conditions' cells are found to exhibit similar adhesion threshold stresses, but very different detachment kinetics, revealing the importance of dynamics analysis to fully describe cell adhesion. With its rapid implementation and potential for parallel sample processing, such microsystem offers a highly controllable platform for exploring cell adhesion characteristics in a large set of environmental conditions and cell types, and could have wide applications across cell biology, tissue engineering, and cell screening.