Morphology changes induced by intercellular gap junction blocking: A reaction-diffusion mechanism

The indispensable role of time in autonomous development

Advances in single-cell analysis have led to a picture of development largely in agreement with Waddington's eponymous epigenetic landscape, in which a cell's fate is determined by its basin of attraction in a high-dimensional gene-expression space. Yet conceptual gaps remain as to how a single progenitor can simultaneously generate multiple endpoints, and why time should be required of the process at all. We propose a theoretical model based on the Hamiltonian mechanics of n-dimensional rotational motion, which resolves these paradoxes. We derive the result that systems which become different from themselves over time must initially move in a direction not towards their ultimate endpoints, and propose that this process of resolving ambiguity can be quantified (in an information-theoretic sense) by the volume subtended in gene-expression space by the trajectories taken by the system towards its endpoints. We discuss the implications of this theory for the analysis of single-cell gene-expression data in studies of development.

Oscillatory phenomena in electrophysiological networks: The coupling between cell bioelectricity and transcription

Morphogenetic regulation during embryogenesis and regeneration rely on information transfer and coordination between different regions. Here, we explore theoretically the coupling between bioelectrical and transcriptional oscillations at the individual cell and multicellular levels. The simulations, based on a set of ion channels and intercellular gap junctions, show that bioelectrical and transcriptional waves can electrophysiologically couple distant regions of a model network in phase and antiphase oscillatory states that include synchronization phenomena. In this way, different multicellular regionalizations can be encoded by cell potentials that oscillate between depolarized and polarized states, thus allowing a spatio-temporal coding. Because the electric potential patterns characteristic of development and regeneration are correlated with the spatial distributions of signaling ions and molecules, bioelectricity can act as a template for slow biochemical signals following a hierarchy of experimental times. In particular, bioelectrical gradients that couple cell potentials to transcription rates give to each single cell a rough idea of its location in the multicellular ensemble, thus controlling local differentiation processes that switch on and off crucial parts of the genome.

Identification of Distinct, Quantitative Pattern Classes from Emergent Tissue-Scale hiPSC Bioelectric Properties

Bioelectric signals possess the ability to robustly control and manipulate patterning during embryogenesis and tissue-level regeneration. Endogenous local and global electric fields function as a spatial 'pre-pattern', controlling cell fates and tissue-scale anatomical boundaries; however, the mechanisms facilitating these robust multiscale outcomes are poorly characterized. Computational modeling addresses the need to predict in vitro patterning behavior and further elucidate the roles of cellular bioelectric signaling components in patterning outcomes. Here, we modified a previously designed image pattern recognition algorithm to distinguish unique spatial features of simulated non-excitable bioelectric patterns under distinct cell culture conditions. This algorithm was applied to comparisons between simulated patterns and experimental microscopy images of membrane potential (Vmem) across cultured human iPSC colonies. Furthermore, we extended the prediction to a novel co-culture condition in which cell sub-populations possessing different ionic fluxes were simulated; the defining spatial features were recapitulated in vitro with genetically modified colonies. These results collectively inform strategies for modeling multiscale spatial characteristics that emerge in multicellular systems, characterizing the molecular contributions to heterogeneity of membrane potential in non-excitable cells, and enabling downstream engineered bioelectrical tissue design.

Information integration during bioelectric regulation of morphogenesis of the embryonic frog brain

Spatiotemporal patterns of cellular resting potential regulate several aspects of development. One key aspect of the bioelectric code is that transcriptional and morphogenetic states are determined not by local, single-cell, voltage levels but by specific distributions of voltage across cell sheets. We constructed and analyzed a minimal dynamical model of collective gene expression in cells based on inputs of multicellular voltage patterns. Causal integration analysis revealed a higher-order mechanism by which information about the voltage pattern was spatiotemporally integrated into gene activity, as well as a division of labor among and between the bioelectric and genetic components. We tested and confirmed predictions of this model in a system in which bioelectric control of morphogenesis regulates gene expression and organogenesis: the embryonic brain of the frog Xenopus laevis. This study demonstrates that machine learning and computational integration approaches can advance our understanding of the information-processing underlying morphogenetic decision-making, with a potential for other applications in developmental biology and regenerative medicine.

Transplantation of fragments from different planaria: A bioelectrical model for head regeneration

Head-tail planaria morphologies are influenced by the electric potential differences across the animal's primary axis, as evidenced e.g. by voltage-sensitive dyes and functional experiments that create permanent lines of 2-headed but genetically wild-type animals. However, bioelectrical and biochemical models that make predictions on what would happen in the case of spatial chimeras made by tissue transplantation from different planaria (different species and head shapes) are lacking. Here, we use a bioelectrical model to qualitatively describe the effects of tissue transplantation on the shape of the regenerated head. To this end, we assume that the cells may have distinct sets of ion channels and ascribe the system outcome to the axial distributions of average cell potentials over morphologically relevant regions. Our rationale is that the distributions of signaling ions and molecules are spatially coupled with multicellular electric potentials. Thus, long-time downstream transcriptional events should be triggered by short-time bioelectrical processes. We show that relatively small differences between the ion channel characteristics of the cells could eventually give noticeable changes in the electric potential profiles and the expected morphological deviations, which suggests that small but timely bioelectrical actions may have significant morphological effects. Our approach is based on the observed relationships between bioelectrical regionalization and biochemical gradients in body-plan studies. Such models are relevant to regenerative, developmental, and cancer biology in which cells with distinct properties and morphogenetic target states confront each other in the same tissue.

Competency in Navigating Arbitrary Spaces as an Invariant for Analyzing Cognition in Diverse Embodiments

One of the most salient features of life is its capacity to handle novelty and namely to thrive and adapt to new circumstances and changes in both the environment and internal components. An understanding of this capacity is central to several fields: the evolution of form and function, the design of effective strategies for biomedicine, and the creation of novel life forms via chimeric and bioengineering technologies. Here, we review instructive examples of living organisms solving diverse problems and propose competent navigation in arbitrary spaces as an invariant for thinking about the scaling of cognition during evolution. We argue that our innate capacity to recognize agency and intelligence in unfamiliar guises lags far behind our ability to detect it in familiar behavioral contexts. The multi-scale competency of life is essential to adaptive function, potentiating evolution and providing strategies for top-down control (not micromanagement) to address complex disease and injury. We propose an observer-focused viewpoint that is agnostic about scale and implementation, illustrating how evolution pivoted similar strategies to explore and exploit metabolic, transcriptional, morphological, and finally 3D motion spaces. By generalizing the concept of behavior, we gain novel perspectives on evolution, strategies for system-level biomedical interventions, and the construction of bioengineered intelligences. This framework is a first step toward relating to intelligence in highly unfamiliar embodiments, which will be essential for progress in artificial intelligence and regenerative medicine and for thriving in a world increasingly populated by synthetic, bio-robotic, and hybrid beings.