Supracellular organization confers directionality and mechanical potency to migrating pairs of cardiopharyngeal progenitor cells

Physiological and pathological morphogenetic events involve a wide array of collective movements, suggesting that multicellular arrangements confer biochemical and biomechanical properties contributing to tissue-scale organization. The Ciona cardiopharyngeal progenitors provide the simplest model of collective cell migration, with cohesive bilateral cell pairs polarized along the leader-trailer migration path while moving between the ventral epidermis and trunk endoderm. We use the Cellular Potts Model to computationally probe the distributions of forces consistent with shapes and collective polarity of migrating cell pairs. Combining computational modeling, confocal microscopy, and molecular perturbations, we identify cardiopharyngeal progenitors as the simplest cell collective maintaining supracellular polarity with differential distributions of protrusive forces, cell-matrix adhesion, and myosin-based retraction forces along the leader-trailer axis. 4D simulations and experimental observations suggest that cell-cell communication helps establish a hierarchy to align collective polarity with the direction of migration, as observed with three or more cells in silico and in vivo. Our approach reveals emerging properties of the migrating collective: cell pairs are more persistent, migrating longer distances, and presumably with higher accuracy. Simulations suggest that cell pairs can overcome mechanical resistance of the trunk endoderm more effectively when they are polarized collectively. We propose that polarized supracellular organization of cardiopharyngeal progenitors confers emergent physical properties that determine mechanical interactions with their environment during morphogenesis.publishedVersio

Data from: Inferring single cell behavior from large-scale epithelial sheet migration patterns

Cell migration plays an important role in a wide variety of biological processes and can incorporate both individual cell motion and collective behavior. The emergent properties of collective migration are receiving increasing attention as collective motion’s role in diseases such as metastatic cancer becomes clear. Yet, how individual cell behavior influences large-scale, multi-cell collective motion remains unclear. In our study, we provided insight into the mechanisms behind collective migration by studying cell migration in a spreading monolayer of epithelial MCF10A cells. We quantify migration using particle image velocimetry and find that cell groups have features of motion that span multiple length scales. Comparing our experimental results to a model of collective cell migration, we find that cell migration within the monolayer can be affected in qualitatively different ways by cell motion at the boundary, yet it is not necessary to introduce leader cells at the boundary or specify other large-scale features to recapitulate this large-scale phenotype in simulations. Instead, in our model, collective motion can be enhanced by increasing the overall activity of the cells or by giving the cells a stronger coupling between their motion and polarity. This suggests that investigating the activity and polarity persistence of individual cells will add insight into the collective migration phenotypes observed during development and disease. This dataset provides microscopy images and analysis to support the article in the Journal of the Royal Society Interface (doi 10.1098/rsif.2017.0147) describing these migration behaviors.This work was carried out with financial support to RML and WL from a NSF-Physics of Living Systems grant (PHY1205965). RML was additionally supported by the JCM Foundation through an ARCS/MWC Scholar Award. WJR and HY were supported by NIH Grant No. P01 GM078586 and NSF Grant No. DMS 1309542. The raw images analyzed in this work have been described previously [1] and were collected with funding and support from the Intramural Research Program of the Center for Cancer Research, NCI, National Institutes of Health. [1] Lee RM, Kelley DH, Nordstrom KN, Ouellette NT, Losert W. Quantifying stretching and rearrangement in epithelial sheet migration. New J Phys. 2013;15(2):25036

Study the mechanical effect in collective movement of two cells using Cellular Potts Model

Collective cell movement is closely related to normal development and cancer metastasis and scientists are studying it from different points of view, on different scales and using different biological systems. We would like to study its mechanism focusing on the mechanical and morphological effects using Cellular Potts Model. Our model is based on the experiments on the trunk ventral cells (TVCs) in Ciona cardiopharyngeal progenitors which include only two migratory cells so that it is the simplest case for collective cell movement. The observation in the experiment tells us that these two cells are polarized as leader and trailer cells with different morphological properties. So, we apply different mechanical properties for these two cells, such as adhesion, surface tension, protruding and retracting forces, to study their effects on cell shape, moving speed, and persistence in direction. We hope to see in what way two cells behave better than one.Non UBCUnreviewedAuthor affiliation: NYUPostdoctora

Models to study the mechanism of single and collective cell migration

Cell migration plays a vital role in many biological processes and the mechanism for both single cell and collective cell migration remains unclear. It is a complex multi-step procedure, including signal receiving, signal processing, force generation and when considering multicell migration, cell-cell interaction. Thus it inspires many scientists in biology as well as interdisciplinary areas to study this topic. This dissertation includes the study of cell migration from different aspects and on different scales, using quantitative models. I write them with a sequence from the smallest scale to the largest. In Chapter 2, I study the kinetics of the activation of G-protein-coupled receptors used in chemotaxis trying to explain the two activation rates observed in the experiments. In Chapter 3, I study single cell chemotaxis, focusing on the signaling networks to explain the memory effect observed in the experiments. In Chapter 4, I study the collective cell chemotaxis taking cell-cell communication into consideration, trying to find the possible minimal network topologies for the signal processing. Finally, in Chapter 5, I study multi-cell migration on a much larger scale with thousands of cells and use a simplified model which focuses on the different kinds of forces applied on the cells to study the relation between single cell properties and large scale behaviors shown in the multi-cell migration. All these works provide some new knowledge on part of the mechanism controlling cell migration

Minimal Network Topologies for Signal Processing during Collective Cell Chemotaxis.

Cell-cell communication plays an important role in collective cell migration. However, it remains unclear how cells in a group cooperatively process external signals to determine the groups direction of motion. Although the topology of signaling pathways is vitally important in single-cell chemotaxis, the signaling topology for collective chemotaxis has not been systematically studied. Here, we combine mathematical analysis and simulations to find minimal network topologies for multicellular signal processing in collective chemotaxis. We focus on border cell cluster chemotaxis in the Drosophila egg chamber, in which responses to several experimental perturbations of the signaling network are known. Our minimal signaling network includes only four elements: a chemoattractant, the protein Rac (indicating cell activation), cell protrusion, and a hypothesized global factor responsible for cell-cell interaction. Experimental data on cell protrusion statistics allows us to systematically narrow the number of possible topologies from more than 40,000,000 to only six minimal topologies with six interactions between the four elements. This analysis does not require a specific functional form of the interactions, and only qualitative features are needed; it is thus robust to many modeling choices. Simulations of a stochastic biochemical model of border cell chemotaxis show that the qualitative selection procedure accurately determines which topologies are consistent with the experiment. We fit our model for all six proposed topologies; each produces results that are consistent with all experimentally available data. Finally, we suggest experiments to further discriminate possible pathway topologies

Correlation between Oncogenic Mutations and Parameter Sensitivity of the Apoptosis Pathway Model

<div><p>One of the major breakthroughs in oncogenesis research in recent years is the discovery that, in most patients, oncogenic mutations are concentrated in a few core biological functional pathways. This discovery indicates that oncogenic mechanisms are highly related to the dynamics of biologic regulatory networks, which govern the behaviour of functional pathways. Here, we propose that oncogenic mutations found in different biological functional pathways are closely related to parameter sensitivity of the corresponding networks. To test this hypothesis, we focus on the DNA damage-induced apoptotic pathway—the most important safeguard against oncogenesis. We first built the regulatory network that governs the apoptosis pathway, and then translated the network into dynamics equations. Using sensitivity analysis of the network parameters and comparing the results with cancer gene mutation spectra, we found that parameters that significantly affect the bifurcation point correspond to high-frequency oncogenic mutations. This result shows that the position of the bifurcation point is a better measure of the functionality of a biological network than gene expression levels of certain key proteins. It further demonstrates the suitability of applying systems-level analysis to biological networks as opposed to studying genes or proteins in isolation.</p></div

Inferring single-cell behaviour from large-scale epithelial sheet migration patterns.

Cell migration plays an important role in a wide variety of biological processes and can incorporate both individual cell motion and collective behaviour. The emergent properties of collective migration are receiving increasing attention as collective motions role in diseases such as metastatic cancer becomes clear. Yet, how individual cell behaviour influences large-scale, multi-cell collective motion remains unclear. In this study, we provide insight into the mechanisms behind collective migration by studying cell migration in a spreading monolayer of epithelial MCF10A cells. We quantify migration using particle image velocimetry and find that cell groups have features of motion that span multiple length scales. Comparing our experimental results to a model of collective cell migration, we find that cell migration within the monolayer can be affected in qualitatively different ways by cell motion at the boundary, yet it is not necessary to introduce leader cells at the boundary or specify other large-scale features to recapitulate this large-scale phenotype in simulations. Instead, in our model, collective motion can be enhanced by increasing the overall activity of the cells or by giving the cells a stronger coupling between their motion and polarity. This suggests that investigating the activity and polarity persistence of individual cells will add insight into the collective migration phenotypes observed during development and disease

Parameter sensitivity analysis.

<p>(A) The change of the saddle-node bifurcation point in response to a 20% increase or decrease in each parameter of the apoptosis pathway. (B) The change in the steady-state concentration of caspase3 in response to a 20% increase or decrease in each parameter of the apoptosis pathway.</p

Parameter sensitivity analysis and its correspondence with mutations in the extended pathway.

<p>(A) The change in the saddle-node bifurcation point in response to a 20% increase or decrease of each parameter of the extended apoptosis pathway. Yellow and green bars indicate parameters that cause a large or small percentage change in the bifurcation points, respectively. (B) The change in the steady-state concentration of caspase-3 in response to a 20% increase or decrease in each parameter of the extended apoptosis pathway. Magenta and blue bars indicate parameters that cause a large or small change in the steady-state concentration of caspase3, respectively. (C) The correspondence between parameters linked to sensitivity of the bifurcation point (yellow bar) or caspase3 (blue bar) and high-frequency mutation genes. (D) The correspondence between insensitive parameters and low-frequency mutation genes. (E) The inconsistency between parameter sensitivity and gene mutation frequency. The numbers in the frame indicate the number of occurrences in the mutation spectrum of the gene that relates to the corresponding parameters.</p