Progress and perspectives in signal transduction, actin dynamics, and movement at the cell and tissue level: lessons from Dictyostelium

Exploring host-pathogen interactions in the Dictyostelium discoideum-Mycobacterium marinum infection model of tuberculosis

Mycobacterium tuberculosis is a pathogenic mycobacterium that causes tuberculosis. Tuberculosis is a significant global health concern that poses numerous clinical challenges, particularly in terms of finding effective treatments for patients. Throughout evolution, host immune cells have developed cell-autonomous defence strategies to restrain and eliminate mycobacteria. Concurrently, mycobacteria have evolved an array of virulence factors to counteract these host defences, resulting in a dynamic interaction between host and pathogen. Here, we review recent findings, including those arising from the use of the amoeba Dictyostelium discoideum as a model to investigate key mycobacterial infection pathways. D. discoideum serves as a scalable and genetically tractable model for human phagocytes, providing valuable insights into the intricate mechanisms of host-pathogen interactions. We also highlight certain similarities between M. tuberculosis and Mycobacterium marinum, and the use of M. marinum to more safely investigate mycobacteria in D. discoideum.

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.

A chemorepellent inhibits local Ras activation to inhibit pseudopod formation to bias cell movement away from the chemorepellent

The ability of cells to sense chemical gradients is essential during development, morphogenesis, and immune responses. Although much is known about chemoattraction, chemorepulsion remains poorly understood. Proliferating Dictyostelium cells secrete a chemorepellent protein called AprA. AprA prevents pseudopod formation at the region of the cell closest to the source of AprA, causing the random movement of cells to be biased away from the AprA. Activation of Ras proteins in a localized sector of a cell cortex helps to induce pseudopod formation, and Ras proteins are needed for AprA chemorepulsion. Here we show that AprA locally inhibits Ras cortical activation through the G protein–coupled receptor GrlH, the G protein subunits Gβ and Gα8, Ras protein RasG, protein kinase B, the p21-activated kinase PakD, and the extracellular signal–regulated kinase Erk1. Diffusion calculations and experiments indicate that in a colony of cells, high extracellular concentrations of AprA in the center can globally inhibit Ras activation, while a gradient of AprA that naturally forms at the edge of the colony allows cells to activate Ras at sectors of the cell other than the sector of the cell closest to the center of the colony, effectively inducing both repulsion from the colony and cell differentiation. Together, these results suggest that a pathway that inhibits local Ras activation can mediate chemorepulsion.

Moving the Research Forward: The Best of British Biology Using the Tractable Model System Dictyostelium discoideum

The social amoeba Dictyostelium discoideum provides an excellent model for research across a broad range of disciplines within biology. The organism diverged from the plant, yeast, fungi and animal kingdoms around 1 billion years ago but retains common aspects found in these kingdoms. Dictyostelium has a low level of genetic complexity and provides a range of molecular, cellular, biochemical and developmental biology experimental techniques, enabling multidisciplinary studies to be carried out in a wide range of areas, leading to research breakthroughs. Numerous laboratories within the United Kingdom employ Dictyostelium as their core research model. This review introduces Dictyostelium and then highlights research from several leading British research laboratories, covering their distinct areas of research, the benefits of using the model, and the breakthroughs that have arisen due to the use of Dictyostelium as a tractable model system.

Quantification of Myxococcus xanthus Aggregation and Rippling Behaviors: Deep-Learning Transformation of Phase-Contrast into Fluorescence Microscopy Images

Myxococcus xanthus bacteria are a model system for understanding pattern formation and collective cell behaviors. When starving, cells aggregate into fruiting bodies to form metabolically inert spores. During predation, cells self-organize into traveling cell-density waves termed ripples. Both phase-contrast and fluorescence microscopy are used to observe these patterns but each has its limitations. Phase-contrast images have higher contrast, but the resulting image intensities lose their correlation with cell density. The intensities of fluorescence microscopy images, on the other hand, are well-correlated with cell density, enabling better segmentation of aggregates and better visualization of streaming patterns in between aggregates; however, fluorescence microscopy requires the engineering of cells to express fluorescent proteins and can be phototoxic to cells. To combine the advantages of both imaging methodologies, we develop a generative adversarial network that converts phase-contrast into synthesized fluorescent images. By including an additional histogram-equalized output to the state-of-the-art pix2pixHD algorithm, our model generates accurate images of aggregates and streams, enabling the estimation of aggregate positions and sizes, but with small shifts of their boundaries. Further training on ripple patterns enables accurate estimation of the rippling wavelength. Our methods are thus applicable for many other phenotypic behaviors and pattern formation studies.

Analytical approximations for the speed of pacemaker-generated waves

In oscillatory media, waves can be generated by pacemaker regions which oscillate faster than their surroundings. In many chemical and biological systems, such waves can synchronize the whole medium and as such they are a means of transmitting information at a fixed speed over large distances. In this paper, we apply analytical tools to investigate the factors that determine the speed of these waves. More precisely, we apply singular perturbation and phase reduction methods to two types of negative-feedback oscillators, one built on underlying bistability and one including a time delay in the negative feedback. In both systems, we investigate the influence of time-scale separation on the resulting wave speed, as well as the effect of size and frequency of the pacemaker region. We compare our analytical estimates to numerical simulations which we described previously [J. Rombouts and L. Gelens, Phys. Rev. Research 2, 043038 (2020)2643-156410.1103/PhysRevResearch.2.043038].

Mathematical modeling of chemotaxis guided amoeboid cell swimming

Cells and microorganisms adopt various strategies to migrate in response to different environmental stimuli. To date, many modeling research has focused on the crawling-basedDictyostelium discoideum(Dd) cells migration induced by chemotaxis, yet recent experimental results reveal that even without adhesion or contact to a substrate, Dd cells can still swim to follow chemoattractant signals. In this paper, we develop a modeling framework to investigate the chemotaxis induced amoeboid cell swimming dynamics. A minimal swimming system consists of one deformable Dd amoeboid cell and a dilute suspension of bacteria, and the bacteria produce chemoattractant signals that attract the Dd cell. We use themathematical amoeba modelto generate Dd cell deformation and solve the resulting low Reynolds number flows, and use a moving mesh based finite volume method to solve the reaction-diffusion-convection equation. Using the computational model, we show that chemotaxis guides a swimming Dd cell to follow and catch bacteria, while on the other hand, bacterial rheotaxis may help the bacteria to escape from the predator Dd cell.

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.

Mathematical modelling in cell migration: tackling biochemistry in changing geometries

Directed cell migration poses a rich set of theoretical challenges. Broadly, these are concerned with (1) how cells sense external signal gradients and adapt; (2) how actin polymerisation is localised to drive the leading cell edge and Myosin-II molecular motors retract the cell rear; and (3) how the combined action of cellular forces and cell adhesion results in cell shape changes and net migration. Reaction-diffusion models for biological pattern formation going back to Turing have long been used to explain generic principles of gradient sensing and cell polarisation in simple, static geometries like a circle. In this minireview, we focus on recent research which aims at coupling the biochemistry with cellular mechanics and modelling cell shape changes. In particular, we want to contrast two principal modelling approaches: (1) interface tracking where the cell membrane, interfacing cell interior and exterior, is explicitly represented by a set of moving points in 2D or 3D space and (2) interface capturing. In interface capturing, the membrane is implicitly modelled analogously to a level line in a hilly landscape whose topology changes according to forces acting on the membrane. With the increased availability of high-quality 3D microscopy data of complex cell shapes, such methods will become increasingly important in data-driven, image-based modelling to better understand the mechanochemistry underpinning cell motion.

Interplay of mesoscale physics and agent-like behaviors in the parallel evolution of aggregative multicellularity

Myxobacteria and dictyostelids are prokaryotic and eukaryotic multicellular lineages, respectively, that after nutrient depletion aggregate and develop into structures called fruiting bodies. The developmental processes and resulting morphological outcomes resemble one another to a remarkable extent despite their independent origins, the evolutionary distance between them and the lack of traceable homology in molecular mechanisms. We hypothesize that the morphological parallelism between the two lineages arises as the consequence of the interplay within multicellular aggregates between generic processes, physical and physicochemical processes operating similarly in living and non-living matter at the mesoscale (~10^-3-10^-1 m) and agent-like behaviors, unique to living systems and characteristic of the constituent cells, considered as autonomous entities acting according to internal rules in a shared environment. Here, we analyze the contributions of generic and agent-like determinants in myxobacteria and dictyostelid development and their roles in the generation of their common traits. Consequent to aggregation, collective cell-cell contacts mediate the emergence of liquid-like properties, making nascent multicellular masses subject to novel patterning and morphogenetic processes. In both lineages, this leads to behaviors such as streaming, rippling, and rounding-up, as seen in non-living fluids. Later the aggregates solidify, leading them to exhibit additional generic properties and motifs. Computational models suggest that the morphological phenotypes of the multicellular masses deviate from the predictions of generic physics due to the contribution of agent-like behaviors of cells such as directed migration, quiescence, and oscillatory signal transduction mediated by responses to external cues. These employ signaling mechanisms that reflect the evolutionary histories of the respective organisms. We propose that the similar developmental trajectories of myxobacteria and dictyostelids are more due to shared generic physical processes in coordination with analogous agent-type behaviors than to convergent evolution under parallel selection regimes. Insights from the biology of these aggregative forms may enable a unified understanding of developmental evolution, including that of animals and plants.

Interactions at engineered graft-tissue interfaces: A review

The interactions at the graft-tissue interfaces are critical for the results of engraftments post-implantation. To improve the success rate of the implantations, as well as the quality of the patients' life, understanding the possible reactions between artificial materials and the host tissues is helpful in designing new generations of material-based grafts aiming at inducing specific responses from surrounding tissues for their own reparation and regeneration. To help researchers understand the complicated interactions that occur after implantations and to promote the development of better-designed grafts with improved biocompatibility and patient responses, in this review, the topics will be discussed from the basic reactions that occur chronologically at the graft-tissue interfaces after implantations to the existing and potential applications of the mechanisms of such reactions in designing of grafts. It offers a chance to bring up-to-date advances in the field and new strategies of controlling the graft-tissue interfaces.

Legionella pneumophila Infection Rewires the Acanthamoeba castellanii Transcriptome, Highlighting a Class of Sirtuin Genes

Legionella pneumophila is an environmental bacterium that has evolved to survive predation by soil and water amoebae such as Acanthamoeba castellanii, and this has inadvertently led to the ability of L. pneumophila to survive and replicate in human cells. L. pneumophila causes Legionnaire's Disease, with human exposure occurring via the inhalation of water aerosols containing both amoebae and the bacteria. These aerosols originate from aquatic biofilms found in artifical water sources, such as air-conditioning cooling towers and humidifiers. In these man-made environments, A. castellanii supports L. pneumophila intracellular replication, thereby promoting persistence and dissemination of the bacteria and providing protection from external stress. Despite this close evolutionary relationship, very little is known about how A. castellanii responds to L. pneumophila infection. In this study, we examined the global transcriptional response of A. castellanii to L. pneumophila infection. We compared A. castellanii infected with wild type L. pneumophila to A. castellanii infected with an isogenic ΔdotA mutant strain, which is unable to replicate intracellularly. We showed that A. castellanii underwent clear morphological and transcriptional rewiring over the course of L. pneumophila infection. Through improved annotation of the A. castellanii genome, we determined that these transcriptional changes primarily involved biological processes utilizing small GTPases, including cellular transport, signaling, metabolism and replication. In addition, a number of sirtuin-encoding genes in A. castellanii were found to be conserved and upregulated during L. pneumophila infection. Silencing of sirtuin gene, sir6f (ACA1_153540) resulted in the inhibition of A. castellanii cell proliferation during infection and reduced L. pneumophila replication. Overall our findings identified several biological pathways in amoebae that may support L. pneumophila replication and A. castellanii proliferation in environmental conditions.

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.

Topotaxis of active Brownian particles

Recent experimental studies have demonstrated that cellular motion can be directed by topographical gradients, such as those resulting from spatial variations in the features of a micropatterned substrate. This phenomenon, known as topotaxis, has been extensively studied for topographical gradients at the subcellular scale, but can also occur in the presence of a spatially varying density of cell-sized features. Such a large-scale topotaxis has recently been observed in highly motile cells that persistently crawl within an array of obstacles with smoothly varying lattice spacing. We introduce a toy model of large-scale topotaxis, based on active Brownian particles. Using numerical simulations and analytical arguments, we demonstrate that topographical gradients introduce a spatial modulation of the particles' persistence, leading to directed motion toward regions of higher persistence. Our results demonstrate that persistent motion alone is sufficient to drive large-scale topotaxis and could serve as a starting point for more detailed studies on self-propelled particles and cells.

Germ cell migration-Evolutionary issues and current understanding

In many organisms, primordial germ cells (PGCs) are specified at a different location than where the gonad forms, meaning that PGCs must migrate toward the gonad within the early developing embryo. Following species-specific paths, PGCs can be passively carried by surrounding tissues and also perform active migration. When PGCs actively migrate through and along a variety of embryonic structures in different organisms, they adopt an ancestral robust migration mode termed "amoeboid motility", which allows cells to migrate within diverse environments. In this review, we discuss the possible significance of the PGC migration process in facilitating the evolution of animal body shape. In addition, we summarize the latest findings relevant for the molecular and cellular mechanisms controlling the movement and the directed migration of PGCs in different species.

Emergence of collective oscillations in adaptive cells

Collective oscillations of cells in a population appear under diverse biological contexts. Here, we establish a set of common principles by categorising the response of individual cells against a time-varying signal. A positive intracellular signal relay of sufficient gain from participating cells is required to sustain the oscillations, together with phase matching. The two conditions yield quantitative predictions for the onset cell density and frequency in terms of measured single-cell and signal response functions. Through mathematical constructions, we show that cells that adapt to a constant stimulus fulfil the phase requirement by developing a leading phase in an active frequency window that enables cell-to-signal energy flow. Analysis of dynamical quorum sensing in several cellular systems with increasing biological complexity reaffirms the pivotal role of adaptation in powering oscillations in an otherwise dissipative cell-to-cell communication channel. The physical conditions identified also apply to synthetic oscillatory systems.

There are many examples of cell populations exhibiting density-dependent collective oscillatory behaviour. Here, the authors show that sustained collective oscillations emerge when cells anticipate variation in signal and attempt to amplify it, a property that can be linked to adaptation.

Dictyostelium: An Important Source of Structural and Functional Diversity in Drug Discovery

The cellular slime mold Dictyostelium discoideum is an excellent model organism for the study of cell and developmental biology because of its simple life cycle and ease of use. Recent findings suggest that Dictyostelium and possibly other genera of cellular slime molds, are potential sources of novel lead compounds for pharmacological and medical research. In this review, we present supporting evidence that cellular slime molds are an untapped source of lead compounds by examining the discovery and functions of polyketide differentiation-inducing factor-1, a compound that was originally isolated as an inducer of stalk-cell differentiation in D. discoideum and, together with its derivatives, is now a promising lead compound for drug discovery in several areas. We also review other novel compounds, including secondary metabolites, that have been isolated from cellular slime molds.

Acanthamoeba and Dictyostelium as Cellular Models for Legionella Infection

Environmental bacteria of the genus Legionella naturally parasitize free-living amoebae. Upon inhalation of bacteria-laden aerosols, the opportunistic pathogens grow intracellularly in alveolar macrophages and can cause a life-threatening pneumonia termed Legionnaires' disease. Intracellular replication in amoebae and macrophages takes place in a unique membrane-bound compartment, the Legionella-containing vacuole (LCV). LCV formation requires the bacterial Icm/Dot type IV secretion system, which translocates literally hundreds of "effector" proteins into host cells, where they modulate crucial cellular processes for the pathogen's benefit. The mechanism of LCV formation appears to be evolutionarily conserved, and therefore, amoebae are not only ecologically significant niches for Legionella spp., but also useful cellular models for eukaryotic phagocytes. In particular, Acanthamoeba castellanii and Dictyostelium discoideum emerged over the last years as versatile and powerful models. Using genetic, biochemical and cell biological approaches, molecular interactions between amoebae and Legionella pneumophila have recently been investigated in detail with a focus on the role of phosphoinositide lipids, small and large GTPases, autophagy components and the retromer complex, as well as on bacterial effectors targeting these host factors.

Revealing chiral cell motility by 3D Riesz transform-differential interference contrast microscopy and computational kinematic analysis

Left–right asymmetry is a fundamental feature of body plans, but its formation mechanisms and roles in functional lateralization remain unclear. Accumulating evidence suggests that left–right asymmetry originates in the cellular chirality. However, cell chirality has not yet been quantitatively investigated, mainly due to the absence of appropriate methods. Here we combine 3D Riesz transform-differential interference contrast (RT-DIC) microscopy and computational kinematic analysis to characterize chiral cellular morphology and motility. We reveal that filopodia of neuronal growth cones exhibit 3D left-helical motion with retraction and right-screw rotation. We next apply the methods to amoeba Dictyostelium discoideum and discover right-handed clockwise cell migration on a 2D substrate and right-screw rotation of subcellular protrusions along the radial axis in a 3D substrate. Thus, RT-DIC microscopy and the computational kinematic analysis are useful and versatile tools to reveal the mechanisms of left–right asymmetry formation and the emergence of lateralized functions.

The lack of an appropriate method has hampered quantitative measurements of cell chirality. Here, the authors combine Riesz transform-differential interference contrast microscopy and computational kinematic analysis to reveal chiral cell motility of neuronal growth cone filopodia and cellular slime mold.

Modelling the collective response of heterogeneous cell populations to stationary gradients and chemical signal relay

The directed motion of cell aggregates toward a chemical source occurs in many relevant biological processes. Understanding the mechanisms that control this complex behavior is of great relevance for our understanding of developmental biological processes and many diseases. In this paper, we consider a self-propelled particle model for the movement of heterogeneous subpopulations of chemically interacting cells towards an imposed stable chemical gradient. Our simulations show explicitly how self-organisation of cell populations (which could lead to engulfment or complete cell segregation) can arise from the heterogeneity of chemotactic responses alone. This new result complements current theoretical and experimental studies that emphasise the role of differential cell-cell adhesion on self-organisation and spatial structure of cellular aggregates. We also investigate how the speed of individual cell aggregations increases with the chemotactic sensitivity of the cells, and decreases with the number of cells inside the aggregates.

Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development

Collective cell movement is critical to the emergent properties of many multicellular systems, including microbial self-organization in biofilms, embryogenesis, wound healing, and cancer metastasis. However, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Known for its social developmental cycle, the bacterium Myxococcus xanthus uses coordinated movement to generate three-dimensional aggregates called fruiting bodies. Despite extensive progress in identifying genes controlling fruiting body development, cell behaviors and cell-cell communication mechanisms that mediate aggregation are largely unknown. We developed an approach to examine emergent behaviors that couples fluorescent cell tracking with data-driven models. A unique feature of this approach is the ability to identify cell behaviors affecting the observed aggregation dynamics without full knowledge of the underlying biological mechanisms. The fluorescent cell tracking revealed large deviations in the behavior of individual cells. Our modeling method indicated that decreased cell motility inside the aggregates, a biased walk toward aggregate centroids, and alignment among neighboring cells in a radial direction to the nearest aggregate are behaviors that enhance aggregation dynamics. Our modeling method also revealed that aggregation is generally robust to perturbations in these behaviors and identified possible compensatory mechanisms. The resulting approach of directly combining behavior quantification with data-driven simulations can be applied to more complex systems of collective cell movement without prior knowledge of the cellular machinery and behavioral cues.