Adhesion-Based Self-Organization in Tissue Patterning

Mechanical state transitions in the regulation of tissue form and function

From embryonic development, postnatal growth and adult homeostasis to reparative and disease states, cells and tissues undergo constant changes in genome activity, cell fate, proliferation, movement, metabolism and growth. Importantly, these biological state transitions are coupled to changes in the mechanical and material properties of cells and tissues, termed mechanical state transitions. These mechanical states share features with physical states of matter, liquids and solids. Tissues can switch between mechanical states by changing behavioural dynamics or connectivity between cells. Conversely, these changes in tissue mechanical properties are known to control cell and tissue function, most importantly the ability of cells to move or tissues to deform. Thus, tissue mechanical state transitions are implicated in transmitting information across biological length and time scales, especially during processes of early development, wound healing and diseases such as cancer. This Review will focus on the biological basis of tissue-scale mechanical state transitions, how they emerge from molecular and cellular interactions, and their roles in organismal development, homeostasis, regeneration and disease.

Building better habitats: Spatiotemporal signaling cues in 3D biointerfaces for tailored cellular functionality

A promising research direction in the field of biological engineering is the design and functional programming of three-dimensional (3D) biointerfaces designed to support living cell functionality and growth in vitro, offering a route to precisely regulate cellular behaviors and phenotypes for addressing therapeutic challenges. While traditional two-dimensional (2D) biointerfaces have provided valuable insights, incorporating specific signaling cues into a 3D biointeractive microenvironment at the right locations and time is now recognized as crucial for accurately programming cellular decision-making and communication processes. This approach aims to engineer cell-centric microenvironments with the potential to recapitulate complex biological functions into a finite set of growing cellular organizations. Additionally, they provide insights into the hierarchical logic governing the relationship between molecular components and higher-order multicellular functionality. The functional live cell-based microenvironment engineered through such innovative biointerfaces has the potential to be used as an in vitro model system for expanding our understanding of cellular behaviors or as a therapeutic habitat where cellular functions can be reprogrammed.

Linking discrete and continuous models of cell birth and migration

Self-organization of individuals within large collectives occurs throughout biology. Mathematical models can help elucidate the individual-level mechanisms behind these dynamics, but analytical tractability often comes at the cost of biological intuition. Discrete models provide straightforward interpretations by tracking each individual yet can be computationally expensive. Alternatively, continuous models supply a large-scale perspective by representing the 'effective' dynamics of infinite agents, but their results are often difficult to translate into experimentally relevant insights. We address this challenge by quantitatively linking spatio-temporal dynamics of continuous models and individual-based data in settings with biologically realistic, time-varying cell numbers. Specifically, we introduce and fit scaling parameters in continuous models to account for discrepancies that can arise from low cell numbers and localized interactions. We illustrate our approach on an example motivated by zebrafish-skin pattern formation, in which we create a continuous framework describing the movement and proliferation of a single cell population by upscaling rules from a discrete model. Our resulting continuous models accurately depict ensemble average agent-based solutions when migration or proliferation act alone. Interestingly, the same parameters are not optimal when both processes act simultaneously, highlighting a rich difference in how combining migration and proliferation affects discrete and continuous dynamics.

A mismatch in the expression of cell surface molecules induces tissue-intrinsic defense against aberrant cells

Tissue-intrinsic error correction enables epithelial cells to detect abnormal neighboring cells and facilitate their removal from the tissue. One of these pathways, "interface surveillance," is triggered by cells with aberrant developmental and cell-fate-patterning pathways. It remains unknown which molecular mechanisms provide cells with the ability to compare fate between neighboring cells. We demonstrate that Drosophila imaginal discs express an array of cell surface molecules previously implicated in neuronal axon guidance processes. They include members of the Robo, Teneurin, Ephrin, Toll-like, or atypical cadherin families. Importantly, a mismatch in expression levels of these cell surface molecules between adjacent cells is sufficient to induce interface surveillance, indicating that differences in expression levels between neighboring cells, rather than their absolute expression levels, are crucial. Specifically, a mismatch in Robo2 and Robo3, but not Robo1, induces enrichment of actin, myosin II, and Ena/Vasp, as well as activation of JNK and apoptosis at clonal interfaces. Moreover, Robo2 can induce interface surveillance independently of its cytosolic domain and without the need for the Robo-ligand Slit. The expression of Robo2 and other cell surface molecules, such as Teneurins or the Ephrin receptor is regulated by fate-patterning pathways intrinsic and extrinsic to the wing disc, as well as by expression of oncogenic RasV12. Combined, we demonstrate that neighboring cells respond to a mismatch in surface code patterns mediated by specific transmembrane proteins and reveal a novel function for these cell surface proteins in cell fate recognition and removal of aberrant cells during development and homeostasis of epithelial tissues.

Measurement of adhesion and traction of cells at high yield (MATCHY) reveals an energetic ratchet driving nephron condensation

Engineering of embryonic strategies for tissue-building has extraordinary promise for regenerative medicine. This has led to a resurgence in interest in the relationship between cell biophysical properties and morphological transitions. However, mapping gene or protein expression data to cell biophysical properties to physical morphogenesis remains challenging with current techniques. Here we present MATCHY (multiplexed adhesion and traction of cells at high yield). MATCHY advances the multiplexing and throughput capabilities of existing traction force and cell-cell adhesion assays using microfabrication and an automated computation scheme with machine learning-driven cell segmentation. Both biophysical assays are coupled with serial downstream immunofluorescence to extract cell type/signaling state information. MATCHY is especially suited to complex primary tissue-, organoid-, or biopsy-derived cell mixtures since it does not rely on a priori knowledge of cell surface markers, cell sorting, or use of lineage-specific reporter animals. We first validate MATCHY on canine kidney epithelial cells engineered for RET tyrosine kinase expression and quantify a relationship between downstream signaling and cell traction. We go on to create a biophysical atlas of primary cells dissociated from the mouse embryonic kidney and use MATCHY to identify distinct biophysical states along the nephron differentiation trajectory. Our data complement expression-level knowledge of adhesion molecule changes that accompany nephron differentiation with quantitative biophysical information. These data reveal an 'energetic ratchet' that explains spatial nephron progenitor cell condensation from the niche as they differentiate, which we validate through agent-based computational simulation. MATCHY offers automated cell biophysical characterization at >104-cell throughput, a highly enabling advance for fundamental studies and new synthetic tissue design strategies for regenerative medicine.

From signalling to form: the coordination of neural tube patterning

The development of the vertebrate spinal cord involves the formation of the neural tube and the generation of multiple distinct cell types. The process starts during gastrulation, combining axial elongation with specification of neural cells and the formation of the neuroepithelium. Tissue movements produce the neural tube which is then exposed to signals that provide patterning information to neural progenitors. The intracellular response to these signals, via a gene regulatory network, governs the spatial and temporal differentiation of progenitors into specific cell types, facilitating the assembly of functional neuronal circuits. The interplay between the gene regulatory network, cell movement, and tissue mechanics generates the conserved neural tube pattern observed across species. In this review we offer an overview of the molecular and cellular processes governing the formation and patterning of the neural tube, highlighting how the remarkable complexity and precision of vertebrate nervous system arises. We argue that a multidisciplinary and multiscale understanding of the neural tube development, paired with the study of species-specific strategies, will be crucial to tackle the open questions.

Evolutionary dynamics of whole-body regeneration across planarian flatworms

Regenerative abilities vary dramatically across animals. Even amongst planarian flatworms, well-known for complete regeneration from tiny body fragments, some species have restricted regeneration abilities while others are almost entirely regeneration incompetent. Here, we assemble a diverse live collection of 40 planarian species to probe the evolution of head regeneration in the group. Combining quantification of species-specific head-regeneration abilities with a comprehensive transcriptome-based phylogeny reconstruction, we show multiple independent transitions between robust whole-body regeneration and restricted regeneration in freshwater species. RNA-mediated genetic interference inhibition of canonical Wnt signalling in RNA-mediated genetic interference-sensitive species bypassed all head-regeneration defects, suggesting that the Wnt pathway is linked to the emergence of planarian regeneration defects. Our finding that Wnt signalling has multiple roles in the reproductive system of the model species Schmidtea mediterranea raises the possibility that a trade-off between egg-laying, asexual reproduction by fission/regeneration and Wnt signalling drives regenerative trait evolution. Although quantitative comparisons of Wnt signalling levels, yolk content and reproductive strategy across our species collection remained inconclusive, they revealed divergent Wnt signalling roles in the reproductive system of planarians. Altogether, our study establishes planarians as a model taxon for comparative regeneration research and presents a framework for the mechanistic evolution of regenerative abilities.

The rod synapse in aging wildtype and Dscaml1 mutant mice

The retina is an intricately organized neural tissue built on cone and rod pathways for color and night vision. Genetic mutations that disrupt the proper function of the rod circuit contribute to blinding diseases including retinitis pigmentosa and congenital stationary night blindness (CSNB). Down Syndrome cell adhesion molecule like 1 (Dscaml1) is expressed by rods, rod bipolar cells (RBCs), and sub-populations of amacrine cells, and has been linked to a middle age onset of CSNB in humans. However, how Dscaml1 contributes to this visual deficit remains unexplored. Here, we probed Dscaml1's role in the maintenance of the rod-to-RBC synapse using a loss of function mouse model. We used immunohistochemistry to investigate the anatomical formation and maintenance of the rod-to-RBC synapse in the young, adult, and aging retina. We generated 3D reconstructions, using serial electron micrographs, of rod spherules and RBCs to measure the number of invaginating neurites, RBC dendritic tip number, and RBC mitochondrial morphology. We find that while rod-to-RBC synapses form and are maintained, similar to wildtype, that there is an increase in the number of invaginating neurites in rod spherules, a reduction in RBC dendritic tips, and reduced mitochondrial volume and complexity in the Dscaml1 mutant retina compared to controls. We also observed precocious sprouting of RBC dendrites into the outer nuclear layer (ONL) of the Dscaml1 mutant retina compared to controls. These results contribute to our knowledge of Dscaml1's role in rod circuit development and maintenance and give additional insight into possible genetic therapy targets for blinding diseases and disorders like CSNB.

Molecular mechanisms of catch bonds and their implications for platelet hemostasis

Adhesive molecular bonds between blood cells are essential for thrombosis and hemostasis as they provide means for platelet adhesion, aggregation, and signaling in flowing blood. According to the nowadays conventional definition, a "catch" bond is a type of non-covalent bio-molecular bridge, whose dissociation lifetime counter-intuitively increases with applied tensile force. Following recent experimental findings, such receptor-ligand protein bonds are vital to the blood cells involved in the prevention of bleeding (hemostatic response) and infection (immunity). In this review, we examine the up-to-date experimental discoveries and theoretical insights about catch bonds between the blood cells, their biomechanical principles at the molecular level, and their role in platelet thrombosis and hemostasis.

Topological data analysis of spatial patterning in heterogeneous cell populations: clustering and sorting with varying cell-cell adhesion

Different cell types aggregate and sort into hierarchical architectures during the formation of animal tissues. The resulting spatial organization depends (in part) on the strength of adhesion of one cell type to itself relative to other cell types. However, automated and unsupervised classification of these multicellular spatial patterns remains challenging, particularly given their structural diversity and biological variability. Recent developments based on topological data analysis are intriguing to reveal similarities in tissue architecture, but these methods remain computationally expensive. In this article, we show that multicellular patterns organized from two interacting cell types can be efficiently represented through persistence images. Our optimized combination of dimensionality reduction via autoencoders, combined with hierarchical clustering, achieved high classification accuracy for simulations with constant cell numbers. We further demonstrate that persistence images can be normalized to improve classification for simulations with varying cell numbers due to proliferation. Finally, we systematically consider the importance of incorporating different topological features as well as information about each cell type to improve classification accuracy. We envision that topological machine learning based on persistence images will enable versatile and robust classification of complex tissue architectures that occur in development and disease.

Configurational entropy is an intrinsic driver of tissue structural heterogeneity

Tissues comprise ordered arrangements of cells that can be surprisingly disordered in their details. How the properties of single cells and their microenvironment contribute to the balance between order and disorder at the tissue-scale remains poorly understood. Here, we address this question using the self-organization of human mammary organoids as a model. We find that organoids behave like a dynamic structural ensemble at the steady state. We apply a maximum entropy formalism to derive the ensemble distribution from three measurable parameters - the degeneracy of structural states, interfacial energy, and tissue activity (the energy associated with positional fluctuations). We link these parameters with the molecular and microenvironmental factors that control them to precisely engineer the ensemble across multiple conditions. Our analysis reveals that the entropy associated with structural degeneracy sets a theoretical limit to tissue order and provides new insight for tissue engineering, development, and our understanding of disease progression.

Physical interactions in non-ideal fluids promote Turing patterns

Turing's mechanism is often invoked to explain periodic patterns in nature, although direct experimental support is scarce. Turing patterns form in reaction-diffusion systems when the activating species diffuse much slower than the inhibiting species, and the involved reactions are highly nonlinear. Such reactions can originate from cooperativity, whose physical interactions should also affect diffusion. We here take direct interactions into account and show that they strongly affect Turing patterns. We find that weak repulsion between the activator and inhibitor can substantially lower the required differential diffusivity and reaction nonlinearity. By contrast, strong interactions can induce phase separation, but the resulting length scale is still typically governed by the fundamental reaction-diffusion length scale. Taken together, our theory connects traditional Turing patterns with chemically active phase separation, thus describing a wider range of systems. Moreover, we demonstrate that even weak interactions affect patterns substantially, so they should be incorporated when modelling realistic systems.

Recording morphogen signals reveals origins of gastruloid symmetry breaking

When cultured in three dimensional spheroids, mammalian stem cells can reproducibly self-organize a single anterior-posterior axis and sequentially differentiate into structures resembling the primitive streak and tailbud. Whereas the embryo's body axes are instructed by spatially patterned extra-embryonic cues, it is unknown how these stem cell gastruloids break symmetry to reproducibly define a single anterior-posterior (A-P) axis. Here, we use synthetic gene circuits to trace how early intracellular signals predict cells' future anterior-posterior position in the gastruloid. We show that Wnt signaling evolves from a homogeneous state to a polarized state, and identify a critical 6-hour time period when single-cell Wnt activity predicts future cellular position, prior to the appearance of polarized signaling patterns or morphology. Single-cell RNA sequencing and live-imaging reveal that early Wnt-high and Wnt-low cells contribute to distinct cell types and suggest that axial symmetry breaking is driven by sorting rearrangements involving differential cell adhesion. We further extend our approach to other canonical embryonic signaling pathways, revealing that even earlier heterogeneity in TGFβ signaling predicts A-P position and modulates Wnt signaling during the critical time period. Our study reveals a sequence of dynamic cellular processes that transform a uniform cell aggregate into a polarized structure and demonstrates that a morphological axis can emerge out of signaling heterogeneity and cell movements even in the absence of exogenous patterning cues.

Mechanochemical feedback loops in contact-dependent fate patterning

To reliably form and maintain structures with specific functions, many multicellular systems evolved to leverage the interplay between biochemical signaling, mechanics, and morphology. We review mechanochemical feedback loops in cases where cell-cell contact-based Notch signaling drives fate decisions, and the corresponding differentiation process leads to contact remodeling. We compare different mechanisms for initial symmetry breaking and subsequent pattern refinement, as well as discuss how patterning outcomes depend on the relationship between biochemical and mechanical timescales. We conclude with an overview of new approaches, including the study of synthetic circuits, and give an outlook on future experimental and theoretical developments toward dissecting and harnessing mechanochemical feedback.

Programming multicellular assembly with synthetic cell adhesion molecules

Cell adhesion molecules are ubiquitous in multicellular organisms, specifying precise cell-cell interactions in processes as diverse as tissue development, immune cell trafficking and the wiring of the nervous system^1-4. Here we show that a wide array of synthetic cell adhesion molecules can be generated by combining orthogonal extracellular interactions with intracellular domains from native adhesion molecules, such as cadherins and integrins. The resulting molecules yield customized cell-cell interactions with adhesion properties that are similar to native interactions. The identity of the intracellular domain of the synthetic cell adhesion molecules specifies interface morphology and mechanics, whereas diverse homotypic or heterotypic extracellular interaction domains independently specify the connectivity between cells. This toolkit of orthogonal adhesion molecules enables the rationally programmed assembly of multicellular architectures, as well as systematic remodelling of native tissues. The modularity of synthetic cell adhesion molecules provides fundamental insights into how distinct classes of cell-cell interfaces may have evolved. Overall, these tools offer powerful abilities for cell and tissue engineering and for systematically studying multicellular organization.

Eya-controlled affinity between cell lineages drives tissue self-organization during Drosophila oogenesis

Cooperative morphogenesis of cell lineages underlies the development of functional units and organs. To study mechanisms driving the coordination of lineages, we investigated soma-germline interactions during oogenesis. From invertebrates to vertebrates, oocytes develop as part of a germline cyst that consists of the oocyte itself and so-called nurse cells, which feed the oocyte and are eventually removed. The enveloping somatic cells specialize to facilitate either oocyte maturation or nurse cell removal, which makes it essential to establish the right match between germline and somatic cells. We uncover that the transcriptional regulator Eya, expressed in the somatic lineage, controls bilateral cell-cell affinity between germline and somatic cells in Drosophila oogenesis. Employing functional studies and mathematical modelling, we show that differential affinity and the resulting forces drive somatic cell redistribution over the germline surface and control oocyte growth to match oocyte and nurse cells with their respective somatic cells. Thus, our data demonstrate that differential affinity between cell lineages is sufficient to drive the complex assembly of inter-lineage functional units and underlies tissue self-organization during Drosophila oogenesis.