Quantitative 3D analysis of complex single border cell behaviors in coordinated collective cell migration

Finishing the egg

Gamete development is a fundamental process that is highly conserved from early eukaryotes to mammals. As germ cells develop, they must coordinate a dynamic series of cellular processes that support growth, cell specification, patterning, the loading of maternal factors (RNAs, proteins, and nutrients), differentiation of structures to enable fertilization and ensure embryonic survival, and other processes that make a functional oocyte. To achieve these goals, germ cells integrate a complex milieu of environmental and developmental signals to produce fertilizable eggs. Over the past 50 years, Drosophila oogenesis has risen to the forefront as a system to interrogate the sophisticated mechanisms that drive oocyte development. Studies in Drosophila have defined mechanisms in germ cells that control meiosis, protect genome integrity, facilitate mRNA trafficking, and support the maternal loading of nutrients. Work in this system has provided key insights into the mechanisms that establish egg chamber polarity and patterning as well as the mechanisms that drive ovulation and egg activation. Using the power of Drosophila genetics, the field has begun to define the molecular mechanisms that coordinate environmental stresses and nutrient availability with oocyte development. Importantly, the majority of these reproductive mechanisms are highly conserved throughout evolution, and many play critical roles in the development of somatic tissues as well. In this chapter, we summarize the recent progress in several key areas that impact egg chamber development and ovulation. First, we discuss the mechanisms that drive nutrient storage and trafficking during oocyte maturation and vitellogenesis. Second, we examine the processes that regulate follicle cell patterning and how that patterning impacts the construction of the egg shell and the establishment of embryonic polarity. Finally, we examine regulatory factors that control ovulation, egg activation, and successful fertilization.

Constriction imposed by basement membrane regulates developmental cell migration

The basement membrane (BM) is a specialized extracellular matrix (ECM), which underlies or encases developing tissues. Mechanical properties of encasing BMs have been shown to profoundly influence the shaping of associated tissues. Here, we use the migration of the border cells (BCs) of the Drosophila egg chamber to unravel a new role of encasing BMs in cell migration. BCs move between a group of cells, the nurse cells (NCs), that are enclosed by a monolayer of follicle cells (FCs), which is, in turn, surrounded by a BM, the follicle BM. We show that increasing or reducing the stiffness of the follicle BM, by altering laminins or type IV collagen levels, conversely affects BC migration speed and alters migration mode and dynamics. Follicle BM stiffness also controls pairwise NC and FC cortical tension. We propose that constraints imposed by the follicle BM influence NC and FC cortical tension, which, in turn, regulate BC migration. Encasing BMs emerge as key players in the regulation of collective cell migration during morphogenesis.

Quantitative Image Analysis of Dynamic Cell Behaviors During Border Cell Migration

Drosophila border cells have emerged as a genetically tractable model to investigate dynamic collective cell migration within the context of a developing organ. Studies of live border cell cluster migration have revealed similarities with other migrating collectives, including formation and restriction of cellular protrusions to the front of the cluster, supracellular actomyosin contractility of the entire collective, and intra-collective cell motility. Here, we describe protocols to prepare ex vivo cultures of stage 9 egg chambers followed by live time-lapse imaging of fluorescently labeled border cells to image dynamic cell behaviors. We provide options to perform live imaging using either a widefield epifluorescent microscope or a confocal microscope. We further outline steps to quantify various cellular behaviors and protein dynamics of live migrating border cells using the Fiji image processing package of ImageJ. These methods can be adapted to other migrating cell collectives in cultured tissues and organs.

Adaptive tracking algorithm for trajectory analysis of cells and layer-by-layer assessment of motility dynamics

Tracking biological objects such as cells or subcellular components imaged with time-lapse microscopy enables us to understand the molecular principles about the dynamics of cell behaviors. However, automatic object detection, segmentation and extracting trajectories remain as a rate-limiting step due to intrinsic challenges of video processing. This paper presents an adaptive tracking algorithm (Adtari) that automatically finds the optimum search radius and cell linkages to determine trajectories in consecutive frames. A critical assumption in most tracking studies is that displacement remains unchanged throughout the movie and cells in a few frames are usually analyzed to determine its magnitude. Tracking errors and inaccurate association of cells may occur if the user does not correctly evaluate the value or prior knowledge is not present on cell movement. The key novelty of our method is that minimum intercellular distance and maximum displacement of cells between frames are dynamically computed and used to determine the threshold distance. Since the space between cells is highly variable in a given frame, our software recursively alters the magnitude to determine all plausible matches in the trajectory analysis. Our method therefore eliminates a major preprocessing step where a constant distance was used to determine the neighbor cells in tracking methods. Cells having multiple overlaps and splitting events were further evaluated by using the shape attributes including perimeter, area, ellipticity and distance. The features were applied to determine the closest matches by minimizing the difference in their magnitudes. Finally, reporting section of our software were used to generate instant maps by overlaying cell features and trajectories. Adtari was validated by using videos with variable signal-to-noise, contrast ratio and cell density. We compared the adaptive tracking with constant distance and other methods to evaluate performance and its efficiency. Our algorithm yields reduced mismatch ratio, increased ratio of whole cell track, higher frame tracking efficiency and allows layer-by-layer assessment of motility to characterize single-cells. Adaptive tracking provides a reliable, accurate, time efficient and user-friendly open source software that is well suited for analysis of 2D fluorescence microscopy video datasets.

Live imaging of delamination in Drosophila shows epithelial cell motility and invasiveness are independently regulated

Delaminating cells undergo complex, precisely regulated changes in cell–cell adhesion, motility, polarity, invasiveness, and other cellular properties. Delamination occurs during development and in pathogenic conditions such as cancer metastasis. We analyzed the requirements for epithelial delamination in Drosophila ovary border cells, which detach from the structured epithelial layer and begin to migrate collectively. We used live imaging to examine cellular dynamics, particularly epithelial cells’ acquisition of motility and invasiveness, in delamination-defective mutants during the time period in which delamination occurs in the wild-type ovary. We found that border cells in slow border cells (slbo), a delamination-defective mutant, lacked invasive cellular protrusions but acquired basic cellular motility, while JAK/STAT-inhibited border cells lost both invasiveness and motility. Our results indicate that invasiveness and motility, which are cooperatively required for delamination, are regulated independently. Our reconstruction experiments also showed that motility is not a prerequisite for acquiring invasiveness.

DMNet: Dual-Stream Marker Guided Deep Network for Dense Cell Segmentation and Lineage Tracking

Accurate segmentation and tracking of cells in microscopy image sequences is extremely beneficial in clinical diagnostic applications and biomedical research. A continuing challenge is the segmentation of dense touching cells and deforming cells with indistinct boundaries, in low signal-to-noise-ratio images. In this paper, we present a dual-stream marker-guided network (DMNet) for segmentation of touching cells in microscopy videos of many cell types. DMNet uses an explicit cell marker-detection stream, with a separate mask-prediction stream using a distance map penalty function, which enables supervised training to focus attention on touching and nearby cells. For multi-object cell tracking we use M2Track tracking-by-detection approach with multi-step data association. Our M2Track with mask overlap includes short term track-to-cell association followed by track-to-track association to re-link tracklets with missing segmentation masks over a short sequence of frames. Our combined detection, segmentation and tracking algorithm has proven its potential on the IEEE ISBI 2021 6th Cell Tracking Challenge (CTC-6) where we achieved multiple top three rankings for diverse cell types. Our team name is MU-Ba-US, and the implementation of DMNet is available at, http://celltrackingchallenge.net/participants/MU-Ba-US/.

Directional Persistence of Cell Migration in Schizophrenia Patient-Derived Olfactory Cells

Cell migration is critical for brain development and linked to several neurodevelopmental disorders, including schizophrenia. We have shown previously that cell migration is dysregulated in olfactory neural stem cells from people with schizophrenia. Although they moved faster than control cells on plastic substrates, patient cells were insensitive to regulation by extracellular matrix proteins, which increase the speeds of control cells. As well as speed, cell migration is also described by directional persistence, the straightness of movement. The aim of this study was to determine whether directional persistence is dysregulated in schizophrenia patient cells and whether it is modified on extracellular matrix proteins. Directional persistence in patient-derived and control-derived olfactory cells was quantified from automated live-cell imaging of migrating cells. On plastic substrates, patient cells were more persistent than control cells, with straighter trajectories and smaller turn angles. On most extracellular matrix proteins, persistence increased in patient and control cells in a concentration-dependent manner, but patient cells remained more persistent. Patient cells therefore have a subtle but complex phenotype in migration speed and persistence on most extracellular matrix protein substrates compared to control cells. If present in the developing brain, this could lead to altered brain development in schizophrenia.

Mechanical plasticity in collective cell migration

Collective cell migration is crucial to maintain epithelium integrity during developmental and repair processes. It requires a tight regulation of mechanical coordination between neighboring cells. This coordination embraces different features including mechanical self-propulsion of individual cells within cellular colonies and large-scale force transmission through cell-cell junctions. This review discusses how the plasticity of biomechanical interactions at cell-cell contacts could help cellular systems to perform coordinated motions and adapt to the properties of the external environment.

Tissue topography steers migrating Drosophila border cells

Moving cells can sense and respond to physical features of the microenvironment; however, in vivo, the significance of tissue topography is mostly unknown. Here, we used Drosophila border cells, an established model for in vivo cell migration, to study how chemical and physical information influences path selection. Although chemical cues were thought to be sufficient, live imaging, genetics, modeling, and simulations show that microtopography is also important. Chemoattractants promote predominantly posterior movement, whereas tissue architecture presents orthogonal information, a path of least resistance concentrated near the center of the egg chamber. E-cadherin supplies a permissive haptotactic cue. Our results provide insight into how cells integrate and prioritize topographical, adhesive, and chemoattractant cues to choose one path among many.

An Integrative and Modular Framework to Recapitulate Emergent Behavior in Cell Migration

Cell migration has been a subject of study in a broad variety of biological systems, from morphogenetic events during development to cancer progression. In this work, we describe single-cell movement in a modular framework from which we simulate the collective behavior of glioblastoma cells, the most prevalent and malignant primary brain tumor. We used the U87 cell line, which can be grown as a monolayer or spatially closely packed and organized in 3D structures called spheroids. Our integrative model considers the most relevant mechanisms involved in cell migration: chemotaxis of attractant factor, mechanical interactions and random movement. The effect of each mechanism is integrated into the overall probability of the cells to move in a particular direction, in an automaton-like approach. Our simulations fit and reproduced the emergent behavior of the spheroids in a set of migration assays where single-cell trajectories were tracked. We also predicted the effect of migration inhibition on the colonies from simple experimental characterization of single treated cell tracks. The development of tools that allow complementing molecular knowledge in migratory cell behavior is relevant for understanding essential cellular processes, both physiological (such as organ formation, tissue regeneration among others) and pathological perspectives. Overall, this is a versatile tool that has been proven to predict individual and collective behavior in U87 cells, but that can be applied to a broad variety of scenarios.

Diversity of collective migration patterns of invasive breast cancer cells emerging during microtrack invasion

Understanding the mechanisms underlying the diversity of tumor invasion dynamics, including single-cell migration, multicellular streaming, and the emergence of various collective migration patterns, is a long-standing problem in cancer research. Here we have designed and fabricated a series of microchips containing high-throughput microscale tracks using protein repelling coating technology, which were then covered with a thin Matrigel layer. By varying the geometrical confinement (track width) and microenvironment factors (Matrigel concentration), we have reproduced a diversity of collective migration patterns in the chips, which were also observed in vivo. We have further classified the collective patterns and quantified the emergence probability of each class of patterns as a function of microtrack width and Matrigel concentration to devise a quantitive "collective pattern diagram." To elucidate the mechanisms behind the emergence of various collective patterns, we employed cellular automaton simulations, incorporating the effects of both direct cell-cell interactions and microenvironment factors (e.g., chemical gradient and extracellular matrix degradation). Our simulations suggest that tumor cell phenotype heterogeneity, and the associated dynamic selection of a favorable phenotype via cell-microenivronment interactions, are key to the emergence of the observed collective patterns in vitro.

Clustered cell migration: Modeling the model system of Drosophila border cells

In diverse developmental contexts, certain cells must migrate to fulfill their roles. Many questions remain unanswered about the genetic and physical properties that govern cell migration. While the simplest case of a single cell moving alone has been well-studied, additional complexities arise in considering how cohorts of cells move together. Significant differences exist between models of collectively migrating cells. We explore the experimental model of migratory border cell clusters in Drosophila melanogaster egg chambers, which are amenable to direct observation and precise genetic manipulations. This system involves two special characteristics that are worthy of attention: border cell clusters contain a limited number of both migratory and non-migratory cells that require coordination, and they navigate through a heterogeneous three-dimensional microenvironment. First, we review how clusters of motile border cells are specified and guided in their migration by chemical signals and the physical impact of adjacent tissue interactions. In the second part, we examine questions around the 3D structure of the motile cluster and surrounding microenvironment in understanding the limits to cluster size and speed of movement through the egg chamber. Mathematical models have identified sufficient gene regulatory networks for specification, the key forces that capture emergent behaviors observed in vivo, the minimal regulatory topologies for signaling, and the distribution of key signaling cues that direct cell behaviors. This interdisciplinary approach to studying border cells is likely to reveal governing principles that apply to different types of cell migration events.

Adjustable viscoelasticity allows for efficient collective cell migration

Cell migration is essential for a wide range of biological processes such as embryo morphogenesis, wound healing, regeneration, and also in pathological conditions, such as cancer. In such contexts, cells are required to migrate as individual entities or as highly coordinated collectives, both of which requiring cells to respond to molecular and mechanical cues from their environment. However, whilst the function of chemical cues in cell migration is comparatively well understood, the role of tissue mechanics on cell migration is just starting to be studied. Recent studies suggest that the dynamic tuning of the viscoelasticity within a migratory cluster of cells, and the adequate elastic properties of its surrounding tissues, are essential to allow efficient collective cell migration in vivo. In this review we focus on the role of viscoelasticity in the control of collective cell migration in various cellular systems, mentioning briefly some aspects of single cell migration. We aim to provide details on how viscoelasticity of collectively migrating groups of cells and their surroundings is adjusted to ensure correct morphogenesis, wound healing, and metastasis. Finally, we attempt to show that environmental viscoelasticity triggers molecular changes within migrating clusters and that these new molecular setups modify clusters' viscoelasticity, ultimately allowing them to migrate across the challenging geometries of their microenvironment.

Coordination of protrusion dynamics within and between collectively migrating border cells by myosin II

Collective cell migration is emerging as a major driver of embryonic development, organogenesis, tissue homeostasis, and tumor dissemination. In contrast to individually migrating cells, collectively migrating cells maintain cell–cell adhesions and coordinate direction-sensing as they move. While nonmuscle myosin II has been studied extensively in the context of cells migrating individually in vitro, its roles in cells migrating collectively in three-dimensional, native environments are not fully understood. Here we use genetics, Airyscan microscopy, live imaging, optogenetics, and Förster resonance energy transfer to probe the localization, dynamics, and functions of myosin II in migrating border cells of the Drosophila ovary. We find that myosin accumulates transiently at the base of protrusions, where it functions to retract them. E-cadherin and myosin colocalize at border cell-border cell contacts and cooperate to transmit directional information. A phosphomimetic form of myosin is sufficient to convert border cells to a round morphology and blebbing migration mode. Together these studies demonstrate that distinct and dynamic pools of myosin II regulate protrusion dynamics within and between collectively migrating cells and suggest a new model for the role of protrusions in collective direction sensing in vivo.

Imaging, Visualization, and Computation in Developmental Biology

Embryonic development is highly complex and dynamic, requiring the coordination of numerous molecular and cellular events at precise times and places. Advances in imaging technology have made it possible to follow developmental processes at cellular, tissue, and organ levels over time as they take place in the intact embryo. Parallel innovations of in vivo probes permit imaging to report on molecular, physiological, and anatomical events of embryogenesis, but the resulting multidimensional data sets pose significant challenges for extracting knowledge. In this review, we discuss recent and emerging advances in imaging technologies, in vivo labeling, and data processing that offer the greatest potential for jointly deciphering the intricate cellular dynamics and the underlying molecular mechanisms. Our discussion of the emerging area of “image-omics” highlights both the challenges of data analysis and the promise of more fully embracing computation and data science for rapidly advancing our understanding of biology.

Biomechanics of Collective Cell Migration in Cancer Progression: Experimental and Computational Methods

Cell migration is essential for regulating many biological processes in physiological or pathological conditions, including embryonic development and cancer invasion. In vitro and in silico studies suggest that collective cell migration is associated with some biomechanical particularities such as restructuring of extracellular matrix (ECM), stress and force distribution profiles, and reorganization of the cytoskeleton. Therefore, the phenomenon could be understood by an in-depth study of cells' behavior determinants, including but not limited to mechanical cues from the environment and from fellow "travelers". This review article aims to cover the recent development of experimental and computational methods for studying the biomechanics of collective cell migration during cancer progression and invasion. We also summarized the tested hypotheses regarding the mechanism underlying collective cell migration enabled by these methods. Together, the paper enables a broad overview on the methods and tools currently available to unravel the biophysical mechanisms pertinent to cell collective migration as well as providing perspectives on future development toward eventually deciphering the key mechanisms behind the most lethal feature of cancer.

A novel generic dictionary-based denoising method for improving noisy and densely packed nuclei segmentation in 3D time-lapse fluorescence microscopy images

Time-lapse fluorescence microscopy is an essential technique for quantifying various characteristics of cellular processes, i.e. cell survival, migration, and differentiation. To perform high-throughput quantification of cellular processes, nuclei segmentation and tracking should be performed in an automated manner. Nevertheless, nuclei segmentation and tracking are challenging tasks due to embedded noise, intensity inhomogeneity, shape variation as well as a weak boundary of nuclei. Although several nuclei segmentation approaches have been reported in the literature, dealing with embedded noise remains the most challenging part of any segmentation algorithm. We propose a novel denoising algorithm, based on sparse coding, that can both enhance very faint and noisy nuclei signal but simultaneously detect nuclei position accurately. Furthermore our method is based on a limited number of parameters, with only one being critical, which is the approximate size of the objects of interest. We also show that our denoising method coupled with classical segmentation method works properly in the context of the most challenging cases. To evaluate the performance of the proposed method, we tested our method on two datasets from the cell tracking challenge. Across all datasets, the proposed method achieved satisfactory results with 96:96% recall for the C. elegans dataset. Besides, in the Drosophila dataset, our method achieved very high recall (99:3%).

Frustration-induced phases in migrating cell clusters

Certain malignant cancer cells form clusters in a chemoattractant gradient, which can spontaneously show three different phases of motion: translational, rotational, and random. Guided by our experiments on the motion of two-dimensional clusters in vitro, we developed an agent-based model in which the cells form a cohesive cluster due to attractive and alignment interactions. We find that when cells at the cluster rim are more motile, all three phases of motion coexist, in agreement with our observations. Using the model, we show that the transitions between different phases are driven by competition between an ordered rim and a disordered core accompanied by the creation and annihilation of topological defects in the velocity field. The model makes specific predictions, which we verify with our experimental data. Our results suggest that heterogeneous behavior of individuals, based on local environment, can lead to novel, experimentally observed phases of collective motion.

Collective gradient sensing and chemotaxis: modeling and recent developments

Cells measure a vast variety of signals, from their environment's stiffness to chemical concentrations and gradients; physical principles strongly limit how accurately they can do this. However, when many cells work together, they can cooperate to exceed the accuracy of any single cell. In this topical review, I will discuss the experimental evidence showing that cells collectively sense gradients of many signal types, and the models and physical principles involved. I also propose new routes by which experiments and theory can expand our understanding of these problems.

TASI: A software tool for spatial-temporal quantification of tumor spheroid dynamics

Spheroid cultures derived from explanted cancer specimens are an increasingly utilized resource for studying complex biological processes like tumor cell invasion and metastasis, representing an important bridge between the simplicity and practicality of 2-dimensional monolayer cultures and the complexity and realism of in vivo animal models. Temporal imaging of spheroids can capture the dynamics of cell behaviors and microenvironments, and when combined with quantitative image analysis methods, enables deep interrogation of biological mechanisms. This paper presents a comprehensive open-source software framework for Temporal Analysis of Spheroid Imaging (TASI) that allows investigators to objectively characterize spheroid growth and invasion dynamics. TASI performs spatiotemporal segmentation of spheroid cultures, extraction of features describing spheroid morpho-phenotypes, mathematical modeling of spheroid dynamics, and statistical comparisons of experimental conditions. We demonstrate the utility of this tool in an analysis of non-small cell lung cancer spheroids that exhibit variability in metastatic and proliferative behaviors.

Characterization of Cell Membrane Extensions and Studying Their Roles in Cancer Cell Adhesion Dynamics

The cell membrane's extension repertoire modulates various malignant behaviors of cancer cells, including their adhesive and migratory potentials. The ability to accurately classify and quantify cell extensions and measure the effect on a cell's adhesive capacity is critical to determining how cell-signaling events impact cancer cell behavior and aggressiveness. Here, we describe the in vitro design and use of a cell extension quantification method in conjunction with an adhesion capacity assay in an established in vitro model for adrenocortical carcinoma (ACC). Specifically, we test the effects of DKK3, a putative tumor suppressor and a pro-differentiation factor, on the membrane extension phenotype of the ACC cell line, SW-13. We propose these assays to provide relatively simple, reliable, and easily interpretable metrics to measures these characteristics under various experimental conditions.

Dancing Styles of Collective Cell Migration: Image-Based Computational Analysis of JRAB/MICAL-L2

Collective cell migration is observed during morphogenesis, angiogenesis, and wound healing, and this type of cell migration also contributes to efficient metastasis in some kinds of cancers. Because collectively migrating cells are much better organized than a random assemblage of individual cells, there seems to be a kind of order in migrating clusters. Extensive research has identified a large number of molecules involved in collective cell migration, and these factors have been analyzed using dramatic advances in imaging technology. To date, however, it remains unclear how myriad cells are integrated as a single unit. Recently, we observed unbalanced collective cell migrations that can be likened to either precision dancing or awa-odori, Japanese traditional dancing similar to the style at Rio Carnival, caused by the impairment of the conformational change of JRAB/MICAL-L2. This review begins with a brief history of image-based computational analyses on cell migration, explains why quantitative analysis of the stylization of collective cell behavior is difficult, and finally introduces our recent work on JRAB/MICAL-L2 as a successful example of the multidisciplinary approach combining cell biology, live imaging, and computational biology. In combination, these methods have enabled quantitative evaluations of the “dancing style” of collective cell migration.

Perspective on Circulating Tumor Cell Clusters: Why It Takes a Village to Metastasize

Circulating tumor cell (CTC) clusters may represent one of the key mechanisms initiating the metastasis process. However, the series of pathophysiologic events by which CTC clusters originate, enter the circulation, and reach the distant sites remain to be identified. The cellular and molecular mechanisms that provide survival advantage for CTC clusters during the transit in the blood stream are also still largely unknown. Understanding the biology of CTC clusters is critical to assess this unified scheme employed by cancer and to device strategies to overcome key pathways responsible for their improved metastatic potential. CTC clusters remain an underdeveloped area of research begging the attention of multidisciplinary cancer research teams. Here, we provide insight on existing preclinical evidence on the potential mechanisms leading to CTC cluster formation and dissemination and on processes that may offer survival advantage. We also offer our perspective on future directions to delineate the role of CTC clusters in metastatic cascade and discuss their clinical significance. Cancer Res; 78(4); 845-52. ©2018 AACR.

An objective comparison of cell-tracking algorithms

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

Leaders in collective migration: are front cells really endowed with a particular set of skills?

Collective cell migration is the coordinated movement emerging from the interaction of at least two cells. In multicellular organisms, collective cell migration is ubiquitous. During development, embryonic cells often travel in numbers, whereas in adults, epithelial cells close wounds collectively. There is often a division of labour and two categories of cells have been proposed: leaders and followers. These two terms imply that followers are subordinated to leaders whose proposed broad range of actions significantly biases the direction of the group of cells towards a specific target. These two terms are also tied to topology. Leaders are at the front while followers are located behind them. Here, we review recent work on some of the main experimental models for collective cell migration, concluding that leader-follower terminology may not be the most appropriate. It appears that not all collectively migrating groups are driven by cells located at the front. Moreover, the qualities that define leaders (pathfinding, traction forces and matrix remodelling) are not specific to front cells. These observations indicate that the terms leaders and followers are not suited to every case. We think that it would be more accurate to dissociate the function of a cell from its position in the group. The position of cells can be precisely defined with respect to the direction of movement by purely topological terms such as “front” or “rear” cells. In addition, we propose the more ample and strictly functional definition of “steering cells” which are able to determine the directionality of movement for the entire group. In this context, a leader cell represents only a specific case in which a steering cell is positioned at the front of the group.