@article{22956, abstract = {Tissue regeneration requires de novo patterning, which has been proposed to be facilitated by cellular heterogeneity. Yet how such heterogeneities are integrated with the mechanochemical state of the tissue and stabilized at the chromatin level into stable, spatially organized fates remains poorly understood. Using in vivo mouse intestinal regeneration models and organoids, we identify a critical density regime that produces a permissive window for heterogeneity in the mechanosensor Yes-associated protein 1 (YAP1). We show that YAP1 heterogeneity is coupled to lineage-biased chromatin accessibility and is decoded through FOXA1, which integrates the permissive chromatin state to Delta-Notch supracellular feedback and lineage commitment. This circuit generates fate bistability and preserves a memory of transient YAP1 activity, thereby maintaining spatial patterning as tissues return to homeostasis after injury. Together, our findings establish a multiscale framework in which tissue-scale mechanics tune single-cell competence and, through FOXA1-mediated bistability, convert transient heterogeneity into stable and self-organized tissue architecture.}, author = {Schwayer, Cornelia and Barbiero, Silvia and Brückner, David and Oost, Koen C. and Baader, Clara and Repina, Nicole A. and Kim, Jinse and Diaz, Oscar E. and Uccelli, Isa and Capolupo, Laura and Meylan, Ludivine Challet and Kalck, Veronique and Moos, Franziska and Suppinger, Simon and Yang, Qiutan and Schnabl, Jakob and Kilik, Umut and Bourdon, Matthieu and Camp, J. Gray and Stockinger, Brigitta and Ferrari, Alessandra and Bühler, Marc and Stadler, Michael B. and Hannezo, Edouard B and Liberali, Prisca}, issn = {1097-4172}, journal = {Cell}, keywords = {tissue patterning, heterogeneity, mechanics, intestinal regeneration, epigenetic competence, multiscale integration, modeling, organoids, image-based phenotyping, Yap1}, number = {17}, pages = {5266--5282.e17}, publisher = {Cell Press}, title = {{Multiscale integration of tissue and chromatin context converts cell heterogeneity into stable intestinal patterning}}, doi = {10.1016/j.cell.2026.06.009}, volume = {189}, year = {2026}, } @article{20056, abstract = {Theoretical studies have shown that stochasticity can affect the dynamics of ecosystems in counterintuitive ways. However, without knowing the equations governing the dynamics of populations or ecosystems, it is difficult to ascertain the role of stochasticity in real datasets. Therefore, the inverse problem of inferring the governing stochastic equations from datasets is important. Here, we present an equation discovery methodology that takes time series data of state variables as input and outputs a stochastic differential equation. We achieve this by combining traditional approaches from stochastic calculus with the equation discovery techniques. We demonstrate the generality of the method via several applications. First, we deliberately choose various stochastic models with fundamentally different governing equations, yet they produce nearly identical steady-state distributions. We show that we can recover the correct underlying equations, and thus infer the structure of their stability, accurately from the analysis of time series data alone. We demonstrate our method on two real-world datasets—fish schooling and single-cell migration—that have vastly different spatiotemporal scales and dynamics. We illustrate various limitations and potential pitfalls of the method and how to overcome them via diagnostic measures. Finally, we provide our open-source code via a package named PyDaDDy (Python Library for Data-Driven Dynamics).}, author = {Nabeel, Arshed and Karichannavar, Ashwin and Palathingal, Shuaib and Jhawar, Jitesh and Brückner, David and Raj M, Danny and Guttal, Vishwesha}, issn = {1537-5323}, journal = {The American Naturalist}, number = {4}, pages = {E100--E117}, publisher = {University of Chicago Press}, title = {{Discovering stochastic dynamical equations from ecological time series data}}, doi = {10.1086/734083}, volume = {205}, year = {2025}, } @article{20259, abstract = {Cell migration in narrow microenvironments occurs in numerous physiological processes. It involves successive cycles of confinement and release that drive important morphological changes. However, it remains unclear whether migrating cells can retain a memory of their past morphological states that could potentially facilitate their navigation through confined spaces. We demonstrate that local geometry governs a switch between two cell morphologies, thereby facilitating cell passage through long and narrow gaps. We combined cell migration assays on standardized microsystems with biophysical modelling and biochemical perturbations to show that migrating cells have a long-term memory of past confinement events. The morphological cell states correlate across transitions through actin cortex remodelling. These findings indicate that mechanical memory in migrating cells plays an active role in their migratory potential in confined environments.}, author = {Kalukula, Yohalie and Luciano, Marine and Simanov, Gleb and Charras, Guillaume and Brückner, David and Gabriele, Sylvain}, issn = {1745-2481}, journal = {Nature Physics}, pages = {1451--1461}, publisher = {Springer Nature}, title = {{The actin cortex acts as a mechanical memory of morphology in confined migrating cells}}, doi = {10.1038/s41567-025-02980-z}, volume = {21}, year = {2025}, } @article{20431, abstract = {Haptotaxis is the process of directed cell migration along gradients of extracellular matrix density and is central to morphogenesis, immune responses and cancer invasion. It is commonly assumed that cells respond to these gradients by migrating directionally towards the regions of highest ligand density. In contrast with this view, here we show that cells exposed to micropatterned fibronectin gradients exhibit a wide range of complex trajectories, including directed haptotactic migration up the gradient but also linear oscillations and circles with extended periods of migration down the gradient. To explain this behaviour, we developed a biophysical model of haptotactic cell migration based on a coarse-grained molecular clutch model coupled to persistent stochastic polarity dynamics. Although initial haptotactic migration is explained by the differential friction at the front and back of the cell, the observed complex trajectories over longer timescales arise from the interplay between differential friction, persistence and physical confinement. Overall, our study reveals that confinement and persistence modulate the ability of cells to sense and respond to haptotactic cues and provides a framework for understanding how cells navigate complex environments.}, author = {Fortunato, Isabela Corina and Brückner, David and Grosser, Steffen and Nautiyal, Rohit and Rossetti, Leone and Bosch-Padrós, Miquel and Trebicka, Jonel and Roca-Cusachs, Pere and Sunyer, Raimon and Hannezo, Edouard B and Trepat, Xavier}, issn = {1745-2481}, journal = {Nature Physics}, pages = {1638--1647}, publisher = {Springer Nature}, title = {{Single-cell migration along and against confined haptotactic gradients}}, doi = {10.1038/s41567-025-03015-3}, volume = {21}, year = {2025}, } @article{18960, abstract = {The importance of physical forces in the morphogenesis, homeostatic function, and pathological dysfunction of multicellular tissues is being increasingly characterized, both theoretically and experimentally. Analogies between biological systems and inert materials such as foams, gels, and liquid crystals have provided striking insights into the core design principles underlying multicellular organization. However, these connections can seem surprising given that a key feature of multicellular systems is their ability to constantly consume energy, providing an active origin for the forces that they produce. Key emerging questions are, therefore, to understand whether and how this activity grants tissues novel properties that do not have counterparts in classical materials, as well as their consequences for biological function. Here, we review recent discoveries at the intersection of active matter and tissue biology, with an emphasis on how modeling and experiments can be combined to understand the dynamics of multicellular systems. These approaches suggest that a number of key biological tissue-scale phenomena, such as morphogenetic shape changes, collective migration, or fate decisions, share unifying design principles that can be described by physical models of tissue active matter.}, author = {Brückner, David and Hannezo, Edouard B}, issn = {1943-0264}, journal = {Cold Spring Harbor Perspectives in Biology}, number = {4}, publisher = {Cold Spring Harbor Laboratory Press}, title = {{Tissue active matter: Integrating mechanics and signaling into dynamical models}}, doi = {10.1101/cshperspect.a041653}, volume = {17}, year = {2025}, } @article{19404, abstract = {Cell migration is a fundamental process during embryonic development. Most studies in vivo have focused on the migration of cells using the extracellular matrix (ECM) as their substrate for migration. In contrast, much less is known about how cells migrate on other cells, as found in early embryos when the ECM has not yet formed. Here, we show that lateral mesendoderm (LME) cells in the early zebrafish gastrula use the ectoderm as their substrate for migration. We show that the lateral ectoderm is permissive for the animal-pole-directed migration of LME cells, while the ectoderm at the animal pole halts it. These differences in permissiveness depend on the lateral ectoderm being more cohesive than the animal ectoderm, a property controlled by bone morphogenetic protein (BMP) signaling within the ectoderm. Collectively, these findings identify ectoderm tissue cohesion as one critical factor in regulating LME migration during zebrafish gastrulation.}, author = {Tavano, Ste and Brückner, David and Tasciyan, Saren and Tong, Xin and Kardos, Roland and Schauer, Alexandra and Hauschild, Robert and Heisenberg, Carl-Philipp J}, issn = {2211-1247}, journal = {Cell Reports}, number = {3}, publisher = {Cell Press}, title = {{BMP-dependent patterning of ectoderm tissue material properties modulates lateral mesendoderm cell migration during early zebrafish gastrulation}}, doi = {10.1016/j.celrep.2025.115387}, volume = {44}, year = {2025}, } @article{15315, abstract = {Single and collective cell migration are fundamental processes critical for physiological phenomena ranging from embryonic development and immune response to wound healing and cancer metastasis. To understand cell migration from a physical perspective, a broad variety of models for the underlying physical mechanisms that govern cell motility have been developed. A key challenge in the development of such models is how to connect them to experimental observations, which often exhibit complex stochastic behaviours. In this review, we discuss recent advances in data-driven theoretical approaches that directly connect with experimental data to infer dynamical models of stochastic cell migration. Leveraging advances in nanofabrication, image analysis, and tracking technology, experimental studies now provide unprecedented large datasets on cellular dynamics. In parallel, theoretical efforts have been directed towards integrating such datasets into physical models from the single cell to the tissue scale with the aim of conceptualising the emergent behaviour of cells. We first review how this inference problem has been addressed in both freely migrating and confined cells. Next, we discuss why these dynamics typically take the form of underdamped stochastic equations of motion, and how such equations can be inferred from data. We then review applications of data-driven inference and machine learning approaches to heterogeneity in cell behaviour, subcellular degrees of freedom, and to the collective dynamics of multicellular systems. Across these applications, we emphasise how data-driven methods can be integrated with physical active matter models of migrating cells, and help reveal how underlying molecular mechanisms control cell behaviour. Together, these data-driven approaches are a promising avenue for building physical models of cell migration directly from experimental data, and for providing conceptual links between different length-scales of description.}, author = {Brückner, David and Broedersz, Chase P.}, issn = {1361-6633}, journal = {Reports on Progress in Physics}, number = {5}, publisher = {IOP Publishing}, title = {{Learning dynamical models of single and collective cell migration: a review}}, doi = {10.1088/1361-6633/ad36d2}, volume = {87}, year = {2024}, } @article{17123, abstract = {A key feature of many developmental systems is their ability to self-organize spatial patterns of functionally distinct cell fates. To ensure proper biological function, such patterns must be established reproducibly, by controlling and even harnessing intrinsic and extrinsic fluctuations. While the relevant molecular processes are increasingly well understood, we lack a principled framework to quantify the performance of such stochastic self-organizing systems. To that end, we introduce an information-theoretic measure for self-organized fate specification during embryonic development. We show that the proposed measure assesses the total information content of fate patterns and decomposes it into interpretable contributions corresponding to the positional and correlational information. By optimizing the proposed measure, our framework provides a normative theory for developmental circuits, which we demonstrate on lateral inhibition, cell type proportioning, and reaction–diffusion models of self-organization. This paves a way toward a classification of developmental systems based on a common information-theoretic language, thereby organizing the zoo of implicated chemical and mechanical signaling processes.}, author = {Brückner, David and Tkačik, Gašper}, issn = {1091-6490}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, number = {23}, publisher = {National Academy of Sciences}, title = {{Information content and optimization of self-organized developmental systems}}, doi = {10.1073/pnas.2322326121}, volume = {121}, year = {2024}, } @article{17269, abstract = {The directed migration of epithelial cell collectives through coordinated movements plays a crucial role in various physiological processes and is increasingly understood at the level of large confluent monolayers. However, numerous processes rely on the migration of small groups of polarized epithelial clusters in complex environments, and their responses to external geometries remain poorly understood. To address this, we cultivate primary epithelial keratocyte tissues on adhesive microstripes to create autonomous epithelial clusters with well-defined geometries. We show that their migration efficiency is strongly influenced by the contact geometry and the orientation of cell–cell contacts with respect to the direction of migration. A combination of velocity and polarity alignment with contact regulation of locomotion in an active matter model captures quantitatively the experimental data. Furthermore, we predict that this combination of rules enables efficient navigation in complex geometries, which we confirm experimentally. Altogether, our findings provide a conceptual framework for extracting the interaction rules of active systems from their interaction with physical boundaries, as well as design principles for collective navigation in complex microenvironments.}, author = {Vercruysse, Eléonore and Brückner, David and Gómez-González, Manuel and Remson, Alexandre and Luciano, Marine and Kalukula, Yohalie and Rossetti, Leone and Trepat, Xavier and Hannezo, Edouard B and Gabriele, Sylvain}, issn = {1745-2481}, journal = {Nature Physics}, pages = {1492--1500}, publisher = {Springer Nature}, title = {{Geometry-driven migration efficiency of autonomous epithelial cell clusters}}, doi = {10.1038/s41567-024-02532-x}, volume = {20}, year = {2024}, } @article{13261, abstract = {Chromosomes in the eukaryotic nucleus are highly compacted. However, for many functional processes, including transcription initiation, the pairwise motion of distal chromosomal elements such as enhancers and promoters is essential and necessitates dynamic fluidity. Here, we used a live-imaging assay to simultaneously measure the positions of pairs of enhancers and promoters and their transcriptional output while systematically varying the genomic separation between these two DNA loci. Our analysis reveals the coexistence of a compact globular organization and fast subdiffusive dynamics. These combined features cause an anomalous scaling of polymer relaxation times with genomic separation leading to long-ranged correlations. Thus, encounter times of DNA loci are much less dependent on genomic distance than predicted by existing polymer models, with potential consequences for eukaryotic gene expression.}, author = {Brückner, David and Chen, Hongtao and Barinov, Lev and Zoller, Benjamin and Gregor, Thomas}, issn = {1095-9203}, journal = {Science}, number = {6652}, pages = {1357--1362}, publisher = {American Association for the Advancement of Science}, title = {{Stochastic motion and transcriptional dynamics of pairs of distal DNA loci on a compacted chromosome}}, doi = {10.1126/science.adf5568}, volume = {380}, year = {2023}, } @article{14827, abstract = {Understanding complex living systems, which are fundamentally constrained by physical phenomena, requires combining experimental data with theoretical physical and mathematical models. To develop such models, collaborations between experimental cell biologists and theoreticians are increasingly important but these two groups often face challenges achieving mutual understanding. To help navigate these challenges, this Perspective discusses different modelling approaches, including bottom-up hypothesis-driven and top-down data-driven models, and highlights their strengths and applications. Using cell mechanics as an example, we explore the integration of specific physical models with experimental data from the molecular, cellular and tissue level up to multiscale input. We also emphasize the importance of constraining model complexity and outline strategies for crosstalk between experimental design and model development. Furthermore, we highlight how physical models can provide conceptual insights and produce unifying and generalizable frameworks for biological phenomena. Overall, this Perspective aims to promote fruitful collaborations that advance our understanding of complex biological systems.}, author = {Schwayer, Cornelia and Brückner, David}, issn = {1477-9137}, journal = {Journal of Cell Science}, keywords = {Cell Biology}, number = {24}, publisher = {The Company of Biologists}, title = {{Connecting theory and experiment in cell and tissue mechanics}}, doi = {10.1242/jcs.261515}, volume = {136}, year = {2023}, }