Collective Cellular Behaviors Research Articles

ARHGEF3 Regulates Hair Follicle Morphogenesis.

During embryogenesis, cells arrange into precise patterns that enable tissues and organs to develop specialized functions. Despite its critical importance, the molecular choreography behind these collective cellular behaviors remains elusive, posing a major challenge in developmental biology and limiting advances in regenerative medicine. By using the mouse hair follicle as a mini-organ system to study the formation of bud-like structures during embryonic development, our work uncovers a crucial role for the Rho GTPase regulator ARHGEF3 in hair follicle morphogenesis. We demonstrate that Arhgef3 expression is upregulated at the onset of hair follicle placode formation. In Arhgef3 knockout animals, we observed defects in placode compaction, leading to impaired hair follicle downgrowth. Through cell culture models, we show that ARHGEF3 promotes F-actin accumulation at the cell cortex and P-cadherin enrichment at cell-cell junctions. Collectively, our study identifies ARHGEF3 as a new regulator of cell shape rearrangements during hair placode morphogenesis, warranting further exploration of its role in other epithelial appendages that arise from similar developmental processes.

Whole-body replacement of larval myofibers generates permanent adult myofibers in zebrafish

Drastic increases in myofiber number and size are essential to support vertebrate post-embryonic growth. However, the collective cellular behaviors that enable these increases have remained elusive. Here, we created the palmuscle myofiber tagging and tracking system for in toto monitoring of the growth and fates of ~5000 fast myofibers in developing zebrafish larvae. Through live tracking of individual myofibers within the same individuals over extended periods, we found that many larval myofibers readily dissolved during development, enabling the on-site addition of new and more myofibers. Remarkably, whole-body surveillance of multicolor-barcoded myofibers further unveiled a gradual yet extensive elimination of larval myofiber populations, resulting in near-total replacement by late juvenile stages. The subsequently emerging adult myofibers are not only long-lasting, but also morphologically and functionally distinct from the larval populations. Furthermore, we determined that the elimination-replacement process is dependent on and driven by the autophagy pathway. Altogether, we propose that the whole-body replacement of larval myofibers is an inherent yet previously unnoticed process driving organismic muscle growth during vertebrate post-embryonic development.

Emergence of Orchestrated and Dynamic Metabolism of Saccharomyces cerevisiae.

Microbial metabolism is a fundamental cellular process that involves many biochemical events and is distinguished by its emergent properties. While the molecular details of individual reactions have been increasingly elucidated, it is not well understood how these reactions are quantitatively orchestrated to produce collective cellular behaviors. Here we developed a coarse-grained, systems, and dynamic mathematical framework, which integrates metabolic reactions with signal transduction and gene regulation to dissect the emergent metabolic traits of Saccharomyces cerevisiae. Our framework mechanistically captures a set of characteristic cellular behaviors, including the Crabtree effect, diauxic shift, diauxic lag time, and differential growth under nutrient-altered environments. It also allows modular expansion for zooming in on specific pathways for detailed metabolic profiles. This study provides a systems mathematical framework for yeast metabolic behaviors, providing insights into yeast physiology and metabolic engineering.

Structure formation induced by non-reciprocal cell-cell interactions in a multicellular system.

Collective cellular behavior plays a crucial role in various biological processes, ranging from developmental morphogenesis to pathological processes such as cancer metastasis. Our previous research has revealed that a mutant cell of Dictyostelium discoideum exhibits collective cell migration, including chain migration and traveling band formation, driven by a unique tail-following behavior at contact sites, which we term "contact following locomotion" (CFL). Here, we uncover an imbalance of forces between the front and rear cells within cell chains, leading to an additional propulsion force in the rear cells. Drawing inspiration from this observation, we introduce a theoretical model that incorporates non-reciprocal cell-cell interactions. Our findings highlight that the non-reciprocal interaction, in conjunction with self-alignment interactions, significantly contributes to the emergence of the observed collective cell migrations. Furthermore, we present a comprehensive phase diagram, showing distinct phases at both low and intermediate cell densities. This phase diagram elucidates a specific regime that corresponds to the experimental system.

Multicellular aligned bands disrupt global collective cell behavior.

Mechanical stress patterns emerging from collective cell behavior have been shown to play critical roles in morphogenesis, tissue repair, and cancer metastasis. In our previous work, we constrained valvular interstitial cell (VIC) monolayers on circular protein islands to study emergent behavior in a controlled manner and demonstrated that the general patterns of cell alignment, size, and apoptosis correlate with predicted mechanical stress fields if radially increasing stiffness or contractility are used in the computational models. However, these radially symmetric models did not predict the existence of local regions of dense aligned cells observed in seemingly random locations of individual aggregates. The goal of this study is to determine how the heterogeneities in cell behavior emerge over time and diverge from the predicted collective cell behavior. Cell-cell interactions in circular multicellular aggregates of VICs were studied with time-lapse imaging ranging from hours to days, and migration, proliferation, and traction stresses were measured. Our results indicate that elongated cells create strong local alignment within preconfluent cell populations on the microcontact printed protein islands. These cells influence the alignment of additional cells to create dense, locally aligned bands of cells which disrupt the predicted global behavior. Cells are highly elongated at the endpoints of the bands yet have decreased spread area in the middle and reduced mobility. Although traction stresses at the endpoints of bands are enhanced, even to the point of detaching aggregates from the culture surface, the cells in dense bands exhibit reduced proliferation, less nuclear YAP, and increased apoptotic rates indicating a low stress environment. These findings suggest that strong local cell-cell interactions between primary fibroblastic cells can disrupt the global collective cellular behavior leading to substantial heterogeneity of cell behaviors in constrained monolayers. This local emergent behavior within aggregated fibroblasts may play an important role in development and disease of connective tissues. STATEMENT OF SIGNIFICANCE: Mechanical stress patterns emerging from collective cell behavior play critical roles in morphogenesis, tissue repair, and cancer metastasis. Much has been learned of these collective behaviors by utilizing microcontact printing to constrain cell monolayers (aggregates) into specific shapes. Here we utilize these tools along with long-term video microscopy tracking of individual aggregates to determine how heterogeneous collective behaviors unique to primary fibroblastic cells emerge over time and diverge from computed stress fields. We find that dense multicellular bands form from local collective behavior and disrupt the global collective behavior resulting in heterogeneous patterns of migration, traction stresses, proliferation, and apoptosis. This local emergent behavior within aggregated fibroblasts may play an important role in development and disease of connective tissues.

A novel method for studying intercellular networks: quantifying cellular cooperativity and inferring the extracellular signals driving it

Abstract Objective: Develop an integrated experimental-computational approach to determine the functional role played by different cell subsets and extracellular communication signals in shaping the behavior of intercellular networks. Methods: We present a microwell-based experimental system, that allows isolating and culturing small groups (up to a few dozens) of cells over extended periods of time, while monitoring their interactions and states using fluorescence microscopy. In parallel, we present a computational framework that uses the data generated by this system for estimating the degree of intercellular cooperativity associated with observed behaviors of the interacting cells, and for inferring the contribution of measured extracellular signals in shaping these behaviors. Results: We used our approach to study the differentiation of mouse Th17 cells. We show that this process requires a relatively large number (> 10) of intermediate intercellular communication steps, in which information processing is carried out by a relatively small percentage (10–20%) of the interacting cells. We correctly predict a correlation between the time in which communication signals are expressed during differentiation, and the degree of intercellular cooperativity associated with their production. Furthermore, we show that we can accurately predict cell-level behaviors. In addition, we correctly identify previously-known effects of cytokines on cell survival, and further predict novel relations, which we validate experimentally. Conclusions: We present a new and general approach for the study of collective cellular behaviors, identifying the key cell subsets and extracellular communication signals driving them. This work was supported in part by National Human Genome Research Institute Centers of Excellence in Genomics Science P50 HG006193 (N.H.), by National Institutes of Health Grants P01 AI045757 and DP3 DK09768101 (J.C.L.) and by the U. S. Army Research Office through the Institute for Soldier Nanotechnologies, under contract number W911NF-13-D-0001 (J.C.L.). This work was also supported in part by the Koch Institute Support (core) Grant P30-CA14051 from the National Cancer Institute. J.C.L. is a Camille Dreyfus Teacher-Scholar.

Towards cellular digital twins of in vivo tumors.

To this day, cancer remains an insufficiently understood disease plaguing humanity. In particular, the mechanisms driving tumor invasion still require extensive study. Current investigations address collective cellular behavior within tumors, which leads to solid or fluid tissue dynamics. Furthermore, the extracellular matrix (ECM) has come into focus as a driving force facilitating invasion. Large scale tumor simulations at subcellular resolution represent a promising computational tool to complement the experimental studies, and advances in computational power within HPC systems have enabled the simulation of such macroscopic tissue arrangements. We hereby present our work using Cells in Silico (CiS), a high performance framework for large-scale tissue simulation previously developed by us. Combining a cellular Potts model and an agent-based layer, CiS is capable of simulating tissues composed of tens of millions of cells, while accurately representing many physical and biological properties. However, in order to realistically represent tumor dynamics, CiS needs to be parameterized. We present strategies and pitfalls in investigating multiple experimental data sources for this task. In particular, we highlight recent success utilizing a feature-extraction based deviation score method for the comparison of simulated and experimental tumor spheroids.

Acquired chemoresistance drives spatial heterogeneity, chemoprotection and collective migration in pancreatic tumor spheroids.

Tumors display rich cellular heterogeneity and typically consist of multiple co-existing clones with distinct genotypic and phenotypic characteristics. The acquisition of resistance to chemotherapy has been shown to contribute to the development of aggressive cancer traits, such as increased migration, invasion and stemness. It has been hypothesized that collective cellular behavior and cooperation of cancer cell populations may directly contribute to disease progression and lack of response to treatment. Here we show that the spontaneous emergence of chemoresistance in a cancer cell population exposed to the selective pressure of a chemotherapeutic agent can result in the emergence of collective cell behavior, including cell-sorting, chemoprotection and collective migration. We derived several gemcitabine resistant subclones from the human pancreatic cancer cell line BxPC3 and determined that the observed chemoresistance was driven of a focal amplification of the chr11p15.4 genomic region, resulting in over-expression of the ribonucleotide reductase (RNR) subunit RRM1. Interestingly, these subclones display a rich cell-sorting behavior when cultured as mixed tumor spheroids. Furthermore, we show that chemoresistant cells are able to exert a chemoprotective effect on non-resistant cells in spheroid co-culture, whereas no protective effect is seen in conventional 2D culture. We also demonstrate that the co-culture of resistant and non-resistant cells leads to collective migration where resistant cells enable migration of otherwise non-migratory cells.

Multicellularity: Amoebae follow the leader to food

Multicellular fruiting body formation through aggregation of individual cells has been known in Fonticla alba since the original description of the organism. A new study reveals the existence of a second transient collective cellular behavior separate from fruiting body formation.

Computational modeling and analysis of the morphogenetic domain signaling networks regulating C. elegans embryogenesis

Caenorhabditiselegans, often referred to as the ‘roundworm’, provides a powerful model for studying cell autonomous and cell–cell interactions through the direct observation of embryonic development in vivo. By leveraging the precisely mapped cell lineage at single cell resolution, we are able to study at a systems level how early embryonic cells communicate across morphogenetic domains for the coordinated processes of gene expressions and collective cellular behaviors that regulate tissue morphogenesis. In this study, we developed a computational framework for the exploration of the morphogenetic domain cell signaling networks that may regulate C. elegans gastrulation and embryonic organogenesis. We demonstrated its utility by producing the following results, i) established a virtual reference model of developing C. elegans embryos through the spatiotemporal alignment of individual embryo cell nuclear imaging samples; ii) integrated the single cell spatiotemporal gene expression profile with the established virtual embryo model by data pooling; iii) trained a Machine Learning model (Random Forest Regression), which predicts accurately the spatial positions of the cells given their gene expression profiles for a given developmental time (e.g. total cell number of the embryo); iv) enabled virtual 4-dimensional tomographic graphical modeling of single cell data; v) inferred the biology signaling pathways that act in each of morphogenetic domains by meta-data analysis. It is intriguing that the morphogenetic domain cell signaling network seems to involve some crosstalk of multiple biology signaling pathways during the formation of tissue boundary pattern. Lastly, we developed the Software tool ‘Embryo aligner version 1.0’ and provided it as an Open Source program to the research community for virtual embryo modeling, and phenotype perturbation analyses (https://github.com/csniuben/embryo_aligner/wiki and https://bioinfo89.github.io/C.elegansEmbryonicOrganogenesisweb/).

Microswimming in viscoelastic fluids

The locomotion of microorganisms and spermatozoa in complex viscoelastic fluids is of critical importance in many biological processes such as fertilization, infection, and biofilm formation. Depending on their propulsion mechanisms, microswimmers display various responses to a complex fluid environment: increasing or decreasing their swimming speed and efficiency, modifying their propulsion kinematics and swimming gaits, and experiencing different hydrodynamic interactions with their surroundings. In this article, we review the fundamental physics of locomotion of biological and synthetic microswimmers in complex viscoelastic fluids. Starting from a continuum framework, we describe the main theoretical approaches developed to model microswimming in viscoelastic fluids, which typically rely on asymptotically-small dimensionless parameters. We then summarize recent progress on the mobility of single cells propelled by cilia, waving flagella and rotating helical flagella in unbounded viscoelastic fluids. We next briefly discuss the impact of other physical factors, including the micro-scale heterogeneity of complex biological fluids, the role of Brownian fluctuations of the microswimmers, the effect of polymer entanglement and the influence of shear-thinning viscosity. In particular, for solution of long polymer chains whose sizes are comparable to the radius of flagella, continuum models cannot be used and instead Brownian Dynamics for the polymers can predict the swimming dynamics. Finally, we discuss the effect of viscoelasticity on the dynamics of microswimmers in the presence of surfaces or external flows and its impact on collective cellular behavior.

Xylella fastidiosa subsp. pauca Strains Fb7 and 9a5c from Citrus Display Differential Behavior, Secretome, and Plant Virulence.

Xylella fastidiosa colonizes the xylem of various cultivated and native plants worldwide. Citrus production in Brazil has been seriously affected, and major commercial varieties remain susceptible to Citrus Variegated Chlorosis (CVC). Collective cellular behaviors such as biofilm formation influence virulence and insect transmission of X. fastidiosa. The reference strain 9a5c produces a robust biofilm compared to Fb7 that remains mostly planktonic, and both were isolated from symptomatic citrus trees. This work deepens our understanding of these distinct behaviors at the molecular level, by comparing the cellular and secreted proteomes of these two CVC strains. Out of 1017 identified proteins, 128 showed differential abundance between the two strains. Different protein families were represented such as proteases, hemolysin-like proteins, and lipase/esterases, among others. Here we show that the lipase/esterase LesA is among the most abundant secreted proteins of CVC strains as well, and demonstrate its functionality by complementary activity assays. More severe symptoms were observed in Nicotiana tabacum inoculated with strain Fb7 compared to 9a5c. Our results support that systemic symptom development can be accelerated by strains that invest less in biofilm formation and more in plant colonization. This has potential application in modulating the bacterial-plant interaction and reducing disease severity.

The Role of Tricellulin in Epithelial Jamming and Unjamming via Segmentation of Tricellular Junctions.

Collective cellular behavior in confluent monolayers supports physiological and pathological processes of epithelial development, regeneration, and carcinogenesis. Here, the attainment of a mature and static tissue configuration or the local reactivation of cell motility involve a dynamic regulation of the junctions established between neighboring cells. Tricellular junctions (tTJs), established at vertexes where three cells meet, are ideally located to control cellular shape and coordinate multicellular movements. However, their function in epithelial tissue dynamic remains poorly defined. To investigate the role of tTJs establishment and maturation in the jamming and unjamming transitions of epithelial monolayers, a semi‐automatic image‐processing pipeline is developed and validated enabling the unbiased and spatially resolved determination of the tTJ maturity state based on the localization of fluorescent reporters. The software resolves the variation of tTJ maturity accompanying collective transitions during tissue maturation, wound healing, and upon the adaptation to osmolarity changes. Altogether, this work establishes junctional maturity at tricellular contacts as a novel biological descriptor of collective responses in epithelial monolayers.

Characterization and Analysis of Collective Cellular Behaviors in 3D Dextran Hydrogels with Homogenous and Clustered RGD Compositions.

The interactions between substrate materials and cells usually play an important role in the hydrogel-based 3D cell cultures. However, the hydrogels that are usually used could not be parametrically regulated, especially for quantitatively regulating the spatial distribution of the adhesion sites for cells in 3D. Here, we employed the semisynthetic hydrogel consisting of maleimide-dextran, Arg-Gly-Asp (RGD) peptides, and cell degradable crosslinkers to biochemically characterize the evolutionary behaviors of NIH–3T3 fibroblasts and C2C12 cells in 3D. Moreover, by comparing the cell-adhesive efficacy of 3D dextran hydrogels with four different RGD clustering rates, we explored the underlying regulation law of C2C12 connections and 3T3 aggregations. The results showed that mal-dextran hydrogel could promise cells stable viability and continuous proliferation, and induce more self-organized multicellular structures relative to 2D culture. More importantly, we found that RGD-clustered mal-dextran hydrogel has the advantage of enhancing C2C12 cell elongation and the breadthwise-aggregated connection, and promoting the 3T3 cell aggregating degree compared to that with homogenous RGD. Further, the advantages of RGD clustering hydrogel could be amplified by appropriately reducing RGD concentration. Such RGD-composition controllable mal-dextran hydrogel can function as a regulator of the collective cellular behaviors, which provides useful information for quantitatively designing the tailored hydrogel system and exploiting advanced biomaterials.

Novel inverse finite-element formulation for reconstruction of relative local stiffness in heterogeneous extra-cellular matrix and traction forces on active cells

Accurately resolving the traction forces on active cells in 3D extra-cellular matrix (ECM) is crucial to understanding stress homeostasis in cellularized ECM systems and the resulting collective cellular behavior. The majority of 3D traction force microscopy techniques, which compute the stress distribution in ECM as well as cellular traction forces from experimentally measured deformation field in the ECM using dispersed tracing particles or fluorescently-tagged matrix proteins, have assumed a spatially homogeneous ECM with constant material properties at every location in the system. Recent studies have shown that ECM can exhibit significant heterogeneity due to the disordered nature of collagen network as well as cell remodeling. In this paper, we develop a novel inverse finite-element formulation for accurately resolving the cellular traction forces by explicitly reconstructing the relative local elastic modulus values of the heterogeneous ECM containing an arbitrary shaped cell from a measured displacement field in the ECM. Our formulation does not require any a priori knowledge of the boundary conditions, and simultaneously results in the distribution of the heterogeneous modulus values and stress field in the ECM, as well as the traction forces on the cell, given experimentally measured average modulus of the ECM. We first validate our procedure in artifical model cell-ECM systems, and then employ the procedure to compute the distribution of elastic modulus in a heterogeneous type-I collagen gel as well as the traction force on a rounded breast cancer cell in the gel, based on the deformation field data obtained via 3D reflectance force microscopy. Our results indicate that the majority part of the cell is in a tensile state, while a local region on the cell is in a tri-axial compressive state, indicating the possible development of a local protrusion in this region. This is further verified by tracking the subsequent evolution of the cell morphology.

Realizations of highly heterogeneous collagen networks via stochastic reconstruction for micromechanical analysis of tumor cell invasion.

Three-dimensional (3D) collective cell migration in a collagen-based extracellular matrix (ECM) is among one of the most significant topics in developmental biology, cancer progression, tissue regeneration, and immune response. Recent studies have suggested that collagen-fiber mediated force transmission in cellularized ECM plays an important role in stress homeostasis and regulation of collective cellular behaviors. Motivated by the recent in vitro observation that oriented collagen can significantly enhance the penetration of migrating breast cancer cells into dense Matrigel which mimics the intravasation process in vivo [Han et al. Proc. Natl. Acad. Sci. USA 113, 11208 (2016)PNASA60027-842410.1073/pnas.1610347113], we devise a procedure for generating realizations of highly heterogeneous 3D collagen networks with prescribed microstructural statistics via stochastic optimization. Specifically, a collagen network is represented via the graph (node-bond) model and the microstructural statistics considered include the cross-link (node) density, valence distribution, fiber (bond) length distribution, as well as fiber orientation distribution. An optimization problem is formulated in which the objective function is defined as the squared difference between a set of target microstructural statistics and the corresponding statistics for the simulated network. Simulated annealing is employed to solve the optimization problem by evolving an initial network via random perturbations to generate realizations of homogeneous networks with randomly oriented fibers, homogeneous networks with aligned fibers, heterogeneous networks with a continuous variation of fiber orientation along a prescribed direction, as well as a binary system containing a collagen region with aligned fibers and a dense Matrigel region with randomly oriented fibers. The generation and propagation of active forces in the simulated networks due to polarized contraction of an embedded ellipsoidal cell and a small group of cells are analyzed by considering a nonlinear fiber model incorporating strain hardening upon large stretching and buckling upon compression. Our analysis shows that oriented fibers can significantly enhance long-range force transmission in the network. Moreover, in the oriented-collagen-Matrigel system, the forces generated by a polarized cell in collagen can penetrate deeply into the Matrigel region. The stressed Matrigel fibers could provide contact guidance for the migrating cell cells, and thus enhance their penetration into Matrigel. This suggests a possible mechanism for the observed enhanced intravasation by oriented collagen.

Determining the impact of cell mixing on signaling during development.

Cell movement and intercellular signaling occur simultaneously to organize morphogenesis during embryonic development. Cell movement can cause relative positional changes between neighboring cells. When intercellular signals are local such cell mixing may affect signaling, changing the flow of information in developing tissues. Little is known about the effect of cell mixing on intercellular signaling in collective cellular behaviors and methods to quantify its impact are lacking. Here we discuss how to determine the impact of cell mixing on cell signaling drawing an example from vertebrate embryogenesis: the segmentation clock, a collective rhythm of interacting genetic oscillators. We argue that comparing cell mixing and signaling timescales is key to determining the influence of mixing. A signaling timescale can be estimated by combining theoretical models with cell signaling perturbation experiments. A mixing timescale can be obtained by analysis of cell trajectories from live imaging. After comparing cell movement analyses in different experimental settings, we highlight challenges in quantifying cell mixing from embryonic timelapse experiments, especially a reference frame problem due to embryonic motions and shape changes. We propose statistical observables characterizing cell mixing that do not depend on the choice of reference frames. Finally, we consider situations in which both cell mixing and signaling involve multiple timescales, precluding a direct comparison between single characteristic timescales. In such situations, physical models based on observables of cell mixing and signaling can simulate the flow of information in tissues and reveal the impact of observed cell mixing on signaling.

Computational Model of Secondary Palate Fusion and Disruption.

Morphogenetic events are driven by cell-generated physical forces and complex cellular dynamics. To improve our capacity to predict developmental effects from chemical-induced cellular alterations, we built a multicellular agent-based model in CompuCell3D that recapitulates the cellular networks and collective cell behavior underlying growth and fusion of the mammalian secondary palate. The model incorporated multiple signaling pathways (TGFβ, BMP, FGF, EGF, and SHH) in a biological framework to recapitulate morphogenetic events from palatal outgrowth through midline fusion. It effectively simulated higher-level phenotypes (e.g., midline contact, medial edge seam (MES) breakdown, mesenchymal confluence, and fusion defects) in response to genetic or environmental perturbations. Perturbation analysis of various control features revealed model functionality with respect to cell signaling systems and feedback loops for growth and fusion, diverse individual cell behaviors and collective cellular behavior leading to physical contact and midline fusion, and quantitative analysis of the TGF/EGF switch that controls MES breakdown-a key event in morphogenetic fusion. The virtual palate model was then executed with theoretical chemical perturbation scenarios to simulate switch behavior leading to a disruption of fusion following chronic (e.g., dioxin) and acute (e.g., retinoic acid) chemical exposures. This computer model adds to similar systems models toward an integrative "virtual embryo" for simulation and quantitative prediction of adverse developmental outcomes following genetic perturbation and/or environmental disruption.

Abstract A62: Unjamming and spreading of a cellular aggregate as a model of breast cancer migration

Abstract Traditional understanding holds that metastasis begins as tumor cells undergo epithelial-to-mesenchymal transition (EMT) to migrate and escape. Recent studies suggest that EMT is not necessary for metastasis, however. Tumor cells may retain their epithelial phenotype to migrate collectively during metastasis. But if EMT is not the crucial permissive step, what is? Our group recently discovered cellular jamming; a process by which an epithelial layer is dormant, non-migratory, and solid-like, corresponding to the jammed state, but in other circumstances becomes active, migratory, and fluid-like, corresponding to the unjammed state. Therefore, based on this phenomenon, do breast cancer cells unjam before they can collectively migrate and metastasize? Spheroidal aggregates of MCF10A and MDA-MB-231 cells spreading on collagen-coated polyacrylamide gels, modeling normal and malignant breast epithelium, respectively, were used to investigate cell jamming, cell-matrix adhesion, and associated traction forces. Compared with MCF10A spheroids, MDA-MB-231 spheroids permeated more rapidly onto gels, generated largely localized traction forces, and dissociated to spread more rapidly outwards. These results suggest MDA-MB-231 cells are more susceptible to unjamming and collective migration. This work will provide a new framework by which to explain collective cellular behavior of normal and malignant breast epithelium. Citation Format: Karin Wang, Jeffrey J. Fredberg. Unjamming and spreading of a cellular aggregate as a model of breast cancer migration. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A62.

Targeting extracellular matrix remodeling in disease: Could resveratrol be a potential candidate?

Disturbances of extracellular matrix homeostasis are associated with a number of pathological conditions. The ability of extracellular matrix to provide contextual information and hence control the individual or collective cellular behavior is increasingly being recognized. Hence, newer therapeutic approaches targeting extracellular matrix remodeling are widely investigated. We reviewed the current literature showing the effects of resveratrol on various aspects of extracellular matrix remodeling. This review presents a summary of the effects of resveratrol on extracellular matrix deposition and breakdown. Mechanisms of action of resveratrol in extracellular matrix deposition involving growth factors and their signaling pathways are discussed. Involvement of phosphoinositol-3-kinase/Akt and mitogen-activated protein kinase pathways and role of transcription factors and sirtuins on the effects of resveratrol on extracellular matrix homeostasis are summarized. It is evident from the literature presented in this review that resveratrol has significant effects on both the synthesis and breakdown of extracellular matrix. The major molecular targets of the action of resveratrol are growth factors and their signaling pathways, phosphoinositol-3-kinase/Akt and mitogen-activated protein kinase pathways, transcription factors, and SIRT-1. The effects of resveratrol on extracellular matrix and the molecular targets appear to be related to experimental models, experimental environment as well as the doses.