Heterotypic gap junction channels as voltage-sensitive valves for intercellular signaling

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.

Aging as a loss of morphostatic information: A developmental bioelectricity perspective

Maintaining order at the tissue level is crucial throughout the lifespan, as failure can lead to cancer and an accumulation of molecular and cellular disorders. Perhaps, the most consistent and pervasive result of these failures is aging, which is characterized by the progressive loss of function and decline in the ability to maintain anatomical homeostasis and reproduce. This leads to organ malfunction, diseases, and ultimately death. The traditional understanding of aging is that it is caused by the accumulation of molecular and cellular damage. In this article, we propose a complementary view of aging from the perspective of endogenous bioelectricity which has not yet been integrated into aging research. We propose a view of aging as a morphostasis defect, a loss of biophysical prepattern information, encoding anatomical setpoints used for dynamic tissue and organ homeostasis. We hypothesize that this is specifically driven by abrogation of the endogenous bioelectric signaling that normally harnesses individual cell behaviors toward the creation and upkeep of complex multicellular structures in vivo. Herein, we first describe bioelectricity as the physiological software of life, and then identify and discuss the links between bioelectricity and life extension strategies and age-related diseases. We develop a bridge between aging and regeneration via bioelectric signaling that suggests a research program for healthful longevity via morphoceuticals. Finally, we discuss the broader implications of the homologies between development, aging, cancer and regeneration and how morphoceuticals can be developed for aging.

Sustained Extracellular Electrical Stimulation Modulates the Permeability of Gap Junctions in rd1 Mouse Retina with Photoreceptor Degeneration

Neurons build vast gap junction-coupled networks (GJ-nets) that are permeable to ions or small molecules, enabling lateral signaling. Herein, we investigate (1) the effect of blinding diseases on GJ-nets in mouse retinas and (2) the impact of electrical stimulation on GJ permeability. GJ permeability was traced in the acute retinal explants of blind retinal degeneration 1 (rd1) mice using the GJ tracer neurobiotin. The tracer was introduced via the edge cut method into the GJ-net, and its spread was visualized in histological preparations (fluorescent tagged) using microscopy. Sustained stimulation was applied to modulate GJ permeability using a single large electrode. Our findings are: (1) The blind rd1 retinas displayed extensive intercellular coupling via open GJs. Three GJ-nets were identified: horizontal, amacrine, and ganglion cell networks. (2) Sustained stimulation significantly diminished the tracer spread through the GJs in all the cell layers, as occurs with pharmaceutical inhibition with carbenoxolone. We concluded that the GJ-nets of rd1 retinas remain coupled and functional after blinding disease and that their permeability is regulatable by sustained stimulation. These findings are essential for understanding molecular signaling in diseases over coupled networks and therapeutic approaches using electrical implants, such as eliciting visual sensations or suppressing cortical seizures.

Enhanced Methodologies for Investigating the Electrophysiological Characteristics of Endogenous Pannexin 1 Intercellular Cell-Cell Channels

Gap junctions, pivotal intercellular conduits, serve as communication channels between adjacent cells, playing a critical role in modulating membrane potential distribution across cellular networks. The family of Pannexin (Panx) proteins, in particular Pannexin1 (Panx1), are widely expressed in vertebrate cells and exhibit sequence homology with innexins, the invertebrate gap junction channel constituents. Despite being ubiquitously expressed, detailed functional and pharmacological properties of Panx1 intercellular cell-cell channels require further investigation. In this chapter, we introduce optimized cell culture methodologies and electrophysiology protocols to expedite the exploration of endogenous Panx1 cell-cell channels in TC620 cells, a human oligodendroglioma cell line that naturally expresses Panx1. We anticipate these refined protocols will significantly contribute to future characterizations of Panx1-based intercellular cell-cell channels across diverse cell types and offer valuable insights into both normal cellular physiology and pathophysiology.

Dye coupling of horizontal cells in the primate retina

In the monkey retina, there are two distinct types of axon-bearing horizontal cells, known as H1 and H2 horizontal cells (HCs). In this study, cell bodies were prelabled using 4',6-diamidino-2-phenylindole (DAPI), and both H1 and H2 horizontal cells were filled with Neurobiotin™ to reveal their coupling, cellular details, and photoreceptor contacts. The confocal analysis of H1 and H2 HCs was used to assess the colocalization of terminal dendrites with glutamate receptors at cone pedicles. After filling H1 somas, a large coupled mosaic of H1 cells was labeled. The dendritic terminals of H1 cells contacted red/green cone pedicles, with the occasional sparse contact with blue cone pedicles observed. The H2 cells were also dye-coupled. They had larger dendritic fields and lower densities. The dendritic terminals of H2 cells preferentially contacted blue cone pedicles, but additional contacts with nearly all cones within the dendritic field were still observed. The red/green cones constitute 99% of the input to H1 HCs, whereas H2 HCs receive a more balanced input, which is composed of 58% red/green cones and 42% blue cones. These observations confirm those made in earlier studies on primate horizontal cells by Dacey and Goodchild in 1996. Both H1 and H2 HCs were axon-bearing. H1 axon terminals (H1 ATs) were independently coupled and contacted rod spherules exclusively. In contrast, the H2 axon terminals contacted cones, with some preference for blue cone pedicles, as reported by Chan and Grünert in 1998. The primate retina contains three independently coupled HC networks in the outer plexiform layer (OPL), identified as H1 and H2 somatic dendrites, and H1 ATs. At each cone pedicle, the colocalization of both H1 and H2 dendritic tips with GluA4 subunits close to the cone synaptic ribbons indicates that glutamate signaling from the cones to H1 and H2 horizontal cells is mediated by α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors.

Bioelectric networks: the cognitive glue enabling evolutionary scaling from physiology to mind

Each of us made the remarkable journey from mere matter to mind: starting life as a quiescent oocyte ("just chemistry and physics"), and slowly, gradually, becoming an adult human with complex metacognitive processes, hopes, and dreams. In addition, even though we feel ourselves to be a unified, single Self, distinct from the emergent dynamics of termite mounds and other swarms, the reality is that all intelligence is collective intelligence: each of us consists of a huge number of cells working together to generate a coherent cognitive being with goals, preferences, and memories that belong to the whole and not to its parts. Basal cognition is the quest to understand how Mind scales-how large numbers of competent subunits can work together to become intelligences that expand the scale of their possible goals. Crucially, the remarkable trick of turning homeostatic, cell-level physiological competencies into large-scale behavioral intelligences is not limited to the electrical dynamics of the brain. Evolution was using bioelectric signaling long before neurons and muscles appeared, to solve the problem of creating and repairing complex bodies. In this Perspective, I review the deep symmetry between the intelligence of developmental morphogenesis and that of classical behavior. I describe the highly conserved mechanisms that enable the collective intelligence of cells to implement regulative embryogenesis, regeneration, and cancer suppression. I sketch the story of an evolutionary pivot that repurposed the algorithms and cellular machinery that enable navigation of morphospace into the behavioral navigation of the 3D world which we so readily recognize as intelligence. Understanding the bioelectric dynamics that underlie construction of complex bodies and brains provides an essential path to understanding the natural evolution, and bioengineered design, of diverse intelligences within and beyond the phylogenetic history of Earth.

The scaling of goals from cellular to anatomical homeostasis: an evolutionary simulation, experiment and analysis

Complex living agents consist of cells, which are themselves competent sub-agents navigating physiological and metabolic spaces. Behaviour science, evolutionary developmental biology and the field of machine intelligence all seek to understand the scaling of biological cognition: what enables individual cells to integrate their activities to result in the emergence of a novel, higher-level intelligence with large-scale goals and competencies that belong to it and not to its parts? Here, we report the results of simulations based on the TAME framework, which proposes that evolution pivoted the collective intelligence of cells during morphogenesis of the body into traditional behavioural intelligence by scaling up homeostatic competencies of cells in metabolic space. In this article, we created a minimal in silico system (two-dimensional neural cellular automata) and tested the hypothesis that evolutionary dynamics are sufficient for low-level setpoints of metabolic homeostasis in individual cells to scale up to tissue-level emergent behaviour. Our system showed the evolution of the much more complex setpoints of cell collectives (tissues) that solve a problem in morphospace: the organization of a body-wide positional information axis (the classic French flag problem in developmental biology). We found that these emergent morphogenetic agents exhibit a number of predicted features, including the use of stress propagation dynamics to achieve the target morphology as well as the ability to recover from perturbation (robustness) and long-term stability (even though neither of these was directly selected for). Moreover, we observed an unexpected behaviour of sudden remodelling long after the system stabilizes. We tested this prediction in a biological system-regenerating planaria-and observed a very similar phenomenon. We propose that this system is a first step towards a quantitative understanding of how evolution scales minimal goal-directed behaviour (homeostatic loops) into higher-level problem-solving agents in morphogenetic and other spaces.

Darwin's agential materials: evolutionary implications of multiscale competency in developmental biology

A critical aspect of evolution is the layer of developmental physiology that operates between the genotype and the anatomical phenotype. While much work has addressed the evolution of developmental mechanisms and the evolvability of specific genetic architectures with emergent complexity, one aspect has not been sufficiently explored: the implications of morphogenetic problem-solving competencies for the evolutionary process itself. The cells that evolution works with are not passive components: rather, they have numerous capabilities for behavior because they derive from ancestral unicellular organisms with rich repertoires. In multicellular organisms, these capabilities must be tamed, and can be exploited, by the evolutionary process. Specifically, biological structures have a multiscale competency architecture where cells, tissues, and organs exhibit regulative plasticity-the ability to adjust to perturbations such as external injury or internal modifications and still accomplish specific adaptive tasks across metabolic, transcriptional, physiological, and anatomical problem spaces. Here, I review examples illustrating how physiological circuits guiding cellular collective behavior impart computational properties to the agential material that serves as substrate for the evolutionary process. I then explore the ways in which the collective intelligence of cells during morphogenesis affect evolution, providing a new perspective on the evolutionary search process. This key feature of the physiological software of life helps explain the remarkable speed and robustness of biological evolution, and sheds new light on the relationship between genomes and functional anatomical phenotypes.

Into the Tissues: Extracellular Matrix and Its Artificial Substitutes: Cell Signalling Mechanisms

The existence of orderly structures, such as tissues and organs is made possible by cell adhesion, i.e., the process by which cells attach to neighbouring cells and a supporting substance in the form of the extracellular matrix. The extracellular matrix is a three-dimensional structure composed of collagens, elastin, and various proteoglycans and glycoproteins. It is a storehouse for multiple signalling factors. Cells are informed of their correct connection to the matrix via receptors. Tissue disruption often prevents the natural reconstitution of the matrix. The use of appropriate implants is then required. This review is a compilation of crucial information on the structural and functional features of the extracellular matrix and the complex mechanisms of cell-cell connectivity. The possibilities of regenerating damaged tissues using an artificial matrix substitute are described, detailing the host response to the implant. An important issue is the surface properties of such an implant and the possibilities of their modification.

Minimal Developmental Computation: A Causal Network Approach to Understand Morphogenetic Pattern Formation

What information-processing strategies and general principles are sufficient to enable self-organized morphogenesis in embryogenesis and regeneration? We designed and analyzed a minimal model of self-scaling axial patterning consisting of a cellular network that develops activity patterns within implicitly set bounds. The properties of the cells are determined by internal 'genetic' networks with an architecture shared across all cells. We used machine-learning to identify models that enable this virtual mini-embryo to pattern a typical axial gradient while simultaneously sensing the set boundaries within which to develop it from homogeneous conditions-a setting that captures the essence of early embryogenesis. Interestingly, the model revealed several features (such as planar polarity and regenerative re-scaling capacity) for which it was not directly selected, showing how these common biological design principles can emerge as a consequence of simple patterning modes. A novel "causal network" analysis of the best model furthermore revealed that the originally symmetric model dynamically integrates into intercellular causal networks characterized by broken-symmetry, long-range influence and modularity, offering an interpretable macroscale-circuit-based explanation for phenotypic patterning. This work shows how computation could occur in biological development and how machine learning approaches can generate hypotheses and deepen our understanding of how featureless tissues might develop sophisticated patterns-an essential step towards predictive control of morphogenesis in regenerative medicine or synthetic bioengineering contexts. The tools developed here also have the potential to benefit machine learning via new forms of backpropagation and by leveraging the novel distributed self-representation mechanisms to improve robustness and generalization.

Beyond Neurons: Long Distance Communication in Development and Cancer

Cellular communication is important in all aspects of tissue and organism functioning, from the level of single cells, two discreet populations, and distant tissues of the body. Long distance communication networks integrate individual cells into tissues to maintain a complex organism during development, but when communication between cells goes awry, disease states such as cancer emerge. Herein we discuss the growing body of evidence suggesting that communication methods known to be employed by neurons, also exist in other cell types. We identify three major areas of long-distance communication: bioelectric signaling, tunneling nanotubes (TNTs), and macrophage modulation of networks, and draw comparisons about how these systems operate in the context of development and cancer. Bioelectric signaling occurs between cells through exchange of ions and tissue-level electric fields, leading to changes in biochemical gradients and molecular signaling pathways to control normal development and tumor growth and invasion in cancer. TNTs transport key morphogens and other cargo long distances, mediating electrical coupling, tissue patterning, and malignancy of cancer cells. Lastly macrophages maintain long distance signaling networks through trafficking of vesicles during development, providing communication relays and priming favorable microenvironments for cancer metastasis. By drawing comparisons between non-neural long distance signaling in the context of development and cancer we aim to encourage crosstalk between the two fields to cultivate new hypotheses and potential therapeutic strategies.

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

Complex anatomical form is regulated in part by endogenous physiological communication between cells; however, the dynamics by which gap junctional (GJ) states across tissues regulate morphology are still poorly understood. We employed a biophysical modeling approach combining different signaling molecules (morphogens) to qualitatively describe the anteroposterior and lateral morphology changes in model multicellular systems due to intercellular GJ blockade. The model is based on two assumptions for blocking-induced patterning: (i) the local concentrations of two small antagonistic morphogens diffusing through the GJs along the axial direction, together with that of an independent, uncoupled morphogen concentration along an orthogonal direction, constitute the instructive patterns that modulate the morphological outcomes, and (ii) the addition of an external agent partially blocks the intercellular GJs between neighboring cells and modifies thus the establishment of these patterns. As an illustrative example, we study how the different connectivity and morphogen patterns obtained in presence of a GJ blocker can give rise to novel head morphologies in regenerating planaria. We note that the ability of GJs to regulate the permeability of morphogens post-translationally suggests a mechanism by which different anatomies can be produced from the same genome without the modification of gene-regulatory networks. Conceptually, our model biosystem constitutes a reaction-diffusion information processing mechanism that allows reprogramming of biological morphologies through the external manipulation of the intercellular GJs and the resulting changes in instructive biochemical signals.

Bioelectric signaling: Reprogrammable circuits underlying embryogenesis, regeneration, and cancer

How are individual cell behaviors coordinated toward invariant large-scale anatomical outcomes in development and regeneration despite unpredictable perturbations? Endogenous distributions of membrane potentials, produced by ion channels and gap junctions, are present across all tissues. These bioelectrical networks process morphogenetic information that controls gene expression, enabling cell collectives to make decisions about large-scale growth and form. Recent progress in the analysis and computational modeling of developmental bioelectric circuits and channelopathies reveals how cellular collectives cooperate toward organ-level structural order. These advances suggest a roadmap for exploiting bioelectric signaling for interventions addressing developmental disorders, regenerative medicine, cancer reprogramming, and synthetic bioengineering.

A Meta-Analysis of Bioelectric Data in Cancer, Embryogenesis, and Regeneration

Developmental bioelectricity is the study of the endogenous role of bioelectrical signaling in all cell types. Resting potentials and other aspects of ionic cell physiology are known to be important regulatory parameters in embryogenesis, regeneration, and cancer. However, relevant quantitative measurement and genetic phenotyping data are distributed throughout wide-ranging literature, hampering experimental design and hypothesis generation. Here, we analyze published studies on bioelectrics and transcriptomic and genomic/phenotypic databases to provide a novel synthesis of what is known in three important aspects of bioelectrics research. First, we provide a comprehensive list of channelopathies-ion channel and pump gene mutations-in a range of important model systems with developmental patterning phenotypes, illustrating the breadth of channel types, tissues, and phyla (including man) in which bioelectric signaling is a critical endogenous aspect of embryogenesis. Second, we perform a novel bioinformatic analysis of transcriptomic data during regeneration in diverse taxa that reveals an electrogenic protein to be the one common factor specifically expressed in regeneration blastemas across Kingdoms. Finally, we analyze data on distinct V_mem signatures in normal and cancer cells, revealing a specific bioelectrical signature corresponding to some types of malignancies. These analyses shed light on fundamental questions in developmental bioelectricity and suggest new avenues for research in this exciting field.

Proarrhythmic Electrical Remodeling by Noncardiomyocytes at Interfaces With Cardiomyocytes Under Oxidative Stress

Life-threatening ventricular arrhythmias, typically arising from interfaces between fibrosis and surviving cardiomyocytes, are feared sequelae of structurally remodeled hearts under oxidative stress. Incomplete understanding of the proarrhythmic electrical remodeling by fibrosis limits the development of novel antiarrhythmic strategies. To define the mechanistic determinants of the proarrhythmia in electrical crosstalk between cardiomyocytes and noncardiomyocytes, we developed a novel in vitro model of interface between neonatal rat ventricular cardiomyocytes (NRVMs) and controls [NRVMs or connexin43 (Cx43)-deficient HeLa cells] vs. Cx43⁺ noncardiomyocytes [aged rat ventricular myofibroblasts (ARVFs) or HeLaCx43 cells]. We performed high-speed voltage-sensitive optical imaging at baseline and following acute H₂O₂ exposure. In NRVM-NRVM and NRVM-HeLa controls, no arrhythmias occurred under either experimental condition. In the NRVM-ARVF and NRVM-HeLaCx43 groups, Cx43⁺ noncardiomyocytes enabled passive decremental propagation of electrical impulses and impaired NRVM activation and repolarization, thereby slowing conduction and prolonging action potential duration. Following H₂O₂ exposure, arrhythmia triggers, automaticity, and non-reentrant and reentrant arrhythmias emerged. This study reveals that myofibroblasts (which generate cardiac fibrosis) and other noncardiomyocytes can induce not only structural remodeling but also electrical remodeling and that electrical remodeling by noncardiomyocytes can be particularly arrhythmogenic in the presence of an oxidative burst. Synergistic electrical remodeling between H₂O₂ and noncardiomyocytes may account for the clinical arrhythmogenicity of myofibroblasts at fibrotic interfaces with cardiomyocytes in ischemic/non-ischemic cardiomyopathies. Understanding the enhanced arrhythmogenicity of synergistic electrical remodeling by H₂O₂ and noncardiomyocytes may guide novel safe-by-design antiarrhythmic strategies for next-generation iatrogenic interfaces between surviving native cardiomyocytes and exogenous stem cells or engineered tissues in cardiac regenerative therapies.

Community effects allow bioelectrical reprogramming of cell membrane potentials in multicellular aggregates: Model simulations

Bioelectrical patterns are established by spatiotemporal correlations of cell membrane potentials at the multicellular level, being crucial to development, regeneration, and tumorigenesis. We have conducted multicellular simulations on bioelectrical community effects and intercellular coupling in multicellular aggregates. The simulations aim at establishing under which conditions a local heterogeneity consisting of a small patch of cells can be stabilized against a large aggregate of surrounding identical cells which are in a different bioelectrical state. In this way, instructive bioelectrical information can be persistently encoded in spatiotemporal patterns of separated domains with different cell polarization states. The multicellular community effects obtained are regulated both at the single-cell and intercellular levels, and emerge from a delicate balance between the degrees of intercellular coupling in: (i) the small patch, (ii) the surrounding bulk, and (iii) the interface that separates these two regions. The model is experimentally motivated and consists of two generic voltage-gated ion channels that attempt to establish the depolarized and polarized cell states together with coupling conductances whose individual and intercellular different states permit a dynamic multicellular connectivity. The simulations suggest that community effects may allow the reprogramming of single-cell bioelectrical states, in agreement with recent experimental data. A better understanding of the resulting electrical regionalization can assist the electroceutical correction of abnormally depolarized regions initiated in the bulk of normal tissues as well as suggest new biophysical mechanisms for the establishment of target patterns in multicellular engineering.

Four-State Model for Simulating Kinetic and Steady-State Voltage-Dependent Gating of Gap Junctions

Gap junction (GJ) channels, formed of connexin (Cx) proteins, provide a direct pathway for metabolic and electrical cell-to-cell communication. These specialized channels are not just passive conduits for the passage of ions and metabolites but have been shown to gate robustly in response to transjunctional voltage, V_j, the voltage difference between two coupled cells. Voltage gating of GJs could play a physiological role, particularly in excitable cells, which can generate large transients in membrane potential during the propagation of action potentials. We present a mathematical/computational model of GJ channel voltage gating to assess properties of GJ channels that takes into account contingent gating of two series hemichannels and the distribution of V_j across each hemichannel. From electrophysiological recordings in cell cultures expressing Cx43 or Cx45, the principal isoforms expressed in cardiac tissue, various data sets were fitted simultaneously using global optimization. The results showed that the model is capable of describing both steady-state and kinetic properties of homotypic and heterotypic GJ channels composed of these Cxs. Moreover, mathematical analyses showed that the model can be simplified to a reversible two-state system and solved analytically using a rapid equilibrium assumption. Given that excitable cells are arranged in interconnected networks, the equilibrium assumption allows for a substantial reduction in computation time, which is useful in simulations of large clusters of coupled cells. Overall, this model can serve as a tool for the studying of GJ channel gating and its effects on the spread of excitation in networks of electrically coupled cells.

The Biophysics of Regenerative Repair Suggests New Perspectives on Biological Causation

Evolution exploits the physics of non-neural bioelectricity to implement anatomical homeostasis: a process in which embryonic patterning, remodeling, and regeneration achieve invariant anatomical outcomes despite external interventions. Linear "developmental pathways" are often inadequate explanations for dynamic large-scale pattern regulation, even when they accurately capture relationships between molecular components. Biophysical and computational aspects of collective cell activity toward a target morphology reveal interesting aspects of causation in biology. This is critical not only for unraveling evolutionary and developmental events, but also for the design of effective strategies for biomedical intervention. Bioelectrical controls of growth and form, including stochastic behavior in such circuits, highlight the need for the formulation of nuanced views of pathways, drivers of system-level outcomes, and modularity, borrowing from concepts in related disciplines such as cybernetics, control theory, computational neuroscience, and information theory. This approach has numerous practical implications for basic research and for applications in regenerative medicine and synthetic bioengineering.

Electro-chemo-mechanical model to investigate multi-pulse electric-field-driven integrin clustering

The effect of pulsed electric fields (PEFs) on transmembrane proteins is not fully understood; how do chemo-mechanical cues in the microenvironment mediate the electric field sensing by these proteins? To answer this key gap in knowledge, we have developed a kinetic Monte Carlo statistical model of the integrin proteins that integrates three components of the morphogenetic field (i.e., chemical, mechanical, and electrical cues). Specifically, the model incorporates the mechanical stiffness of the cell membrane, the ligand density of the extracellular environment, the glycocalyx stiffness, thermal Brownian motion, and electric field induced diffusion. The effects of both steady-state electric fields and transient PEF pulse trains on integrin clustering are studied. Our results reveal that electric-field-driven integrin clustering is mediated by membrane stiffness and ligand density. In addition, we explore the effects of PEF pulse-train parameters (amplitude, polarity, and pulse-width) on integrin clustering. In summary, we demonstrate a computational methodology to incorporate experimental data and simulate integrin clustering when exposed to PEFs for time-scales comparable to experiments (seconds-minutes). Thus, we propose a blueprint for understanding PEF/electric field effects on protein induced signaling and highlight key impediments to incorporating experimental values into computational models such as the kinetic Monte Carlo method.

Bioelectrical Coupling of Single-Cell States in Multicellular Systems

The spatiotemporal distributions of signaling ions and molecules that modulate biochemical pathways in nonexcitable cells are influenced by multicellular electric potentials. These potentials act as distributed controllers encoding instructive spatial patterns in development and regeneration. We review experimental facts and discuss recent bioelectrical models that provide new physical insights and complement biochemical approaches. Single-cell states are modulated at the multicellular level because of the coupling between neighboring cells, thus allowing memories and multicellular patterns. The model is based on (i) two generic voltage-gated ion channels that promote the polarized and depolarized cell states, (ii) a feedback mechanism for the transcriptional and bioelectrical regulations, and (iii) voltage-gated intercellular conductances that allow a dynamic intercellular connectivity. The simulations provide steady-state and oscillatory multicellular states that help explain aspects of development and guide experimental procedures attempting to establish instructive bioelectrical patterns based on electric potentials and currents to regulate cell behavior and morphogenesis.

Endogenous Bioelectrics in Development, Cancer, and Regeneration: Drugs and Bioelectronic Devices as Electroceuticals for Regenerative Medicine

A major frontier in the post-genomic era is the investigation of the control of coordinated growth and three-dimensional form. Dynamic remodeling of complex organs in regulative embryogenesis, regeneration, and cancer reveals that cells and tissues make decisions that implement complex anatomical outcomes. It is now essential to understand not only the genetics that specifies cellular hardware but also the physiological software that implements tissue-level plasticity and robust morphogenesis. Here, we review recent discoveries about the endogenous mechanisms of bioelectrical communication among non-neural cells that enables them to cooperate in vivo. We discuss important advances in bioelectronics, as well as computational and pharmacological tools that are enabling the taming of biophysical controls toward applications in regenerative medicine and synthetic bioengineering.

The Computational Boundary of a "Self": Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

All epistemic agents physically consist of parts that must somehow comprise an integrated cognitive self. Biological individuals consist of subunits (organs, cells, and molecular networks) that are themselves complex and competent in their own native contexts. How do coherent biological Individuals result from the activity of smaller sub-agents? To understand the evolution and function of metazoan creatures' bodies and minds, it is essential to conceptually explore the origin of multicellularity and the scaling of the basal cognition of individual cells into a coherent larger organism. In this article, I synthesize ideas in cognitive science, evolutionary biology, and developmental physiology toward a hypothesis about the origin of Individuality: "Scale-Free Cognition." I propose a fundamental definition of an Individual based on the ability to pursue goals at an appropriate level of scale and organization and suggest a formalism for defining and comparing the cognitive capacities of highly diverse types of agents. Any Self is demarcated by a computational surface - the spatio-temporal boundary of events that it can measure, model, and try to affect. This surface sets a functional boundary - a cognitive "light cone" which defines the scale and limits of its cognition. I hypothesize that higher level goal-directed activity and agency, resulting in larger cognitive boundaries, evolve from the primal homeostatic drive of living things to reduce stress - the difference between current conditions and life-optimal conditions. The mechanisms of developmental bioelectricity - the ability of all cells to form electrical networks that process information - suggest a plausible set of gradual evolutionary steps that naturally lead from physiological homeostasis in single cells to memory, prediction, and ultimately complex cognitive agents, via scale-up of the basic drive of infotaxis. Recent data on the molecular mechanisms of pre-neural bioelectricity suggest a model of how increasingly sophisticated cognitive functions emerge smoothly from cell-cell communication used to guide embryogenesis and regeneration. This set of hypotheses provides a novel perspective on numerous phenomena, such as cancer, and makes several unique, testable predictions for interdisciplinary research that have implications not only for evolutionary developmental biology but also for biomedicine and perhaps artificial intelligence and exobiology.

Modeling somatic computation with non-neural bioelectric networks

The field of basal cognition seeks to understand how adaptive, context-specific behavior occurs in non-neural biological systems. Embryogenesis and regeneration require plasticity in many tissue types to achieve structural and functional goals in diverse circumstances. Thus, advances in both evolutionary cell biology and regenerative medicine require an understanding of how non-neural tissues could process information. Neurons evolved from ancient cell types that used bioelectric signaling to perform computation. However, it has not been shown whether or how non-neural bioelectric cell networks can support computation. We generalize connectionist methods to non-neural tissue architectures, showing that a minimal non-neural Bio-Electric Network (BEN) model that utilizes the general principles of bioelectricity (electrodiffusion and gating) can compute. We characterize BEN behaviors ranging from elementary logic gates to pattern detectors, using both fixed and transient inputs to recapitulate various biological scenarios. We characterize the mechanisms of such networks using dynamical-systems and information-theory tools, demonstrating that logic can manifest in bidirectional, continuous, and relatively slow bioelectrical systems, complementing conventional neural-centric architectures. Our results reveal a variety of non-neural decision-making processes as manifestations of general cellular biophysical mechanisms and suggest novel bioengineering approaches to construct functional tissues for regenerative medicine and synthetic biology as well as new machine learning architectures.

From non-excitable single-cell to multicellular bioelectrical states supported by ion channels and gap junction proteins: Electrical potentials as distributed controllers

Endogenous bioelectric patterns within tissues are an important driver of morphogenesis and a tractable component of a number of disease states. Developing system-level understanding of the dynamics by which non-neural bioelectric circuits regulate complex downstream cascades is a key step towards both, an evolutionary understanding of ion channel genes, and novel strategies in regenerative medicine. An important capability gap is deriving rational modulation strategies targeting individual cells' bioelectric states to achieve global (tissue- or organ-level) outcomes. Here, we develop an ion channel-based model that describes multicellular states on the basis of spatio-temporal patterns of electrical potentials in aggregates of non-excitable cells. The model is of biological interest because modern techniques allow to associate bioelectrical signals with specific ion channel proteins in the cell membrane that are central to embryogenesis, regeneration, and tumorigenesis. As a complementary approach to the usual biochemical description, we have studied four biophysical questions: (i) how can single-cell bioelectrical states be established; (ii) how can a change in the cell potential caused by a transient perturbation of the cell state be maintained after the stimulus is gone (bioelectrical memory); (iii) how can a single-cell contribute to the control of multicellular ensembles based on the spatio-temporal pattern of electrical potentials; and (iv) how can oscillatory patterns arise from the single-cell bioelectrical dynamics. Experimentally, endogenous bioelectric gradients have emerged as instructive agents for morphogenetic processes. In this context, the simulations can guide new procedures that may allow a distributed control of the multicellular ensemble.

Planarian regeneration as a model of anatomical homeostasis: Recent progress in biophysical and computational approaches

Planarian behavior, physiology, and pattern control offer profound lessons for regenerative medicine, evolutionary biology, morphogenetic engineering, robotics, and unconventional computation. Despite recent advances in the molecular genetics of stem cell differentiation, this model organism's remarkable anatomical homeostasis provokes us with truly fundamental puzzles about the origin of large-scale shape and its relationship to the genome. In this review article, we first highlight several deep mysteries about planarian regeneration in the context of the current paradigm in this field. We then review recent progress in understanding of the physiological control of an endogenous, bioelectric pattern memory that guides regeneration, and how modulating this memory can permanently alter the flatworm's target morphology. Finally, we focus on computational approaches that complement reductive pathway analysis with synthetic, systems-level understanding of morphological decision-making. We analyze existing models of planarian pattern control and highlight recent successes and remaining knowledge gaps in this interdisciplinary frontier field.

The Role of Early Bioelectric Signals in the Regeneration of Planarian Anterior/Posterior Polarity

Axial patterning during planarian regeneration relies on a transcriptional circuit that confers distinct positional information on the two ends of an amputated fragment. The earliest known elements of this system begin demarcating differences between anterior and posterior wounds by 6 h postamputation. However, it is still unknown what upstream events break the axial symmetry, allowing a mutual repressor system to establish invariant, distinct biochemical states at the anterior and posterior ends. Here, we show that bioelectric signaling at 3 h is crucial for the formation of proper anterior-posterior polarity in planaria. Briefly manipulating the endogenous bioelectric state by depolarizing the injured tissue during the first 3 h of regeneration alters gene expression by 6 h postamputation and leads to a double-headed phenotype upon regeneration despite confirmed washout of ionophores from tissue. These data reveal a primary functional role for resting membrane potential taking place within the first 3 h after injury and kick-starting the downstream pattern of events that elaborate anatomy over the following 10 days. We propose a simple model of molecular-genetic mechanisms to explain how physiological events taking place immediately after injury regulate the spatial distribution of downstream gene expression and anatomy of regenerating planaria.

Transcription factor Tbx18 induces the differentiation of c-kit+ canine mesenchymal stem cells (cMSCs) into SAN-like pacemaker cells in a co-culture model in vitro

Bone mesenchymal stem cells (MSCs), as well as cardiomyocytes, are derived from early mesoderm, becoming committed to their fate under the influence of different differentiation factors. We examined whether the overexpression of Tbx18 can induce the differentiation of c-kit⁺ cMSCs into a phenotype similar to that of native pacemaker cells and whether these transfected cells can couple to adjacent atrial cells with functional consequences. The c-kit⁺ cMSCs were first sorted, then transfected with different lentiviral vectors. Tbx18-c-kit⁺ cMSCs represented the experimental group, while EYFP-c-kit⁺ cMSCs and canine sinoatrial node (SAN) cells were used as controls. Within days of transfection, the hyperpolarization-activated cyclic nucleotide-gated (HCN) channel HCN4 protein and gap junction protein Connexin 45 (Cx45) expression in Tbx18-c-kit⁺ cMSCs were 12-fold and 5.6-fold higher, respectively, than that in EYFP-c-kit⁺ cMSCs. After co-culture with canine atrial cells in vitro for three days, the funny currents (I_f) were recorded in the Tbx18-c-kit⁺ cMSCs, but not in EYFP-c-kit⁺ cMSCs. The trend of these I_f currents was highly similar to that of SAN cells, although the current density was smaller. The Tbx18-EYFP-c-kit⁺ cMSCs showed responsiveness to β-adrenergic stimulation, and the intracellular cyclic adenosine monophosphate (cAMP) level was higher than that in EYFP-c-kit⁺ cMSCs. The Tbx18-EYFP-c-kit⁺ cMSCs delivered fluorescent dye to neighboring atrial cells via gap junctions, thus these cell pairs could communicate as a pacemaker unit. We propose that the overexpression of Tbx18 in c-kit⁺ cMSCs induces their differentiation to SAN-like pacemaker cells.

Electrical Communication in Lymphangions

Contractions of lymphangions, i.e., the segment between two one-way lymphatic valves, generate the pressure gradients that propel lymph back to the circulation. Each lymphangion is comprised of an inner sheet of lymphatic endothelial cells circumscribed by one or more layers of lymphatic muscle cells (LMCs). Each contraction is produced by an LMC action potential (AP) that propagates via gap junctions along the lymphangion. Yet, electrical coupling within and between cell layers and the impact on AP waves is poorly understood. Here, we combine studies in rat and mouse lymphatic vessels with mathematical modeling to show that initiation of AP waves depends on high input resistance (low current drain), whereas propagation depends on morphology and sufficient LMC:LMC coupling. Simulations show that 1) myoendothelial coupling is insignificant to facilitate AP generation and sustain an experimentally measured cross-junctional potential difference of 25 mV, i.e., AP waves propagate along the LMC layer only; 2) LMC:LMC resistance is estimated around 2-10 MΩ but depends on vessel structure and cell-cell coupling, e.g., some degree of LMC overlap protects AP waves against LMC decoupling; 3) the propensity of AP wave initiation is highest around the valves, where the density of LMCs is low; and 4) a single pacemaker cell embedded in the LMC layer must be able to generate very large currents to overcome the current drain from the layer. However, the required current generation to initiate an AP wave is reduced upon stimulation of multiple adjacent LMCs. With stimulation of all LMCs, AP waves can also arise from heterogeneity in the electrical activity of LMCs. The findings advance our understanding of the electrical constraints that underlie initiation of APs in the LMC layer and make testable predictions about how morphology, LMC excitability, and LMC:LMC electrical coupling interact to determine the ability to initiate and propagate AP waves in small lymphatic vessels.

The bioelectric code: An ancient computational medium for dynamic control of growth and form

What determines large-scale anatomy? DNA does not directly specify geometrical arrangements of tissues and organs, and a process of encoding and decoding for morphogenesis is required. Moreover, many species can regenerate and remodel their structure despite drastic injury. The ability to obtain the correct target morphology from a diversity of initial conditions reveals that the morphogenetic code implements a rich system of pattern-homeostatic processes. Here, we describe an important mechanism by which cellular networks implement pattern regulation and plasticity: bioelectricity. All cells, not only nerves and muscles, produce and sense electrical signals; in vivo, these processes form bioelectric circuits that harness individual cell behaviors toward specific anatomical endpoints. We review emerging progress in reading and re-writing anatomical information encoded in bioelectrical states, and discuss the approaches to this problem from the perspectives of information theory, dynamical systems, and computational neuroscience. Cracking the bioelectric code will enable much-improved control over biological patterning, advancing basic evolutionary developmental biology as well as enabling numerous applications in regenerative medicine and synthetic bioengineering.

Top-down models in biology: explanation and control of complex living systems above the molecular level

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering.

Endogenous Bioelectric Signaling Networks: Exploiting Voltage Gradients for Control of Growth and Form

Living systems exhibit remarkable abilities to self-assemble, regenerate, and remodel complex shapes. How cellular networks construct and repair specific anatomical outcomes is an open question at the heart of the next-generation science of bioengineering. Developmental bioelectricity is an exciting emerging discipline that exploits endogenous bioelectric signaling among many cell types to regulate pattern formation. We provide a brief overview of this field, review recent data in which bioelectricity is used to control patterning in a range of model systems, and describe the molecular tools being used to probe the role of bioelectrics in the dynamic control of complex anatomy. We suggest that quantitative strategies recently developed to infer semantic content and information processing from ionic activity in the brain might provide important clues to cracking the bioelectric code. Gaining control of the mechanisms by which large-scale shape is regulated in vivo will drive transformative advances in bioengineering, regenerative medicine, and synthetic morphology, and could be used to therapeutically address birth defects, traumatic injury, and cancer.

Gap junctional signaling in pattern regulation: Physiological network connectivity instructs growth and form

Gap junctions (GJs) are aqueous channels that allow cells to communicate via physiological signals directly. The role of gap junctional connectivity in determining single-cell functions has long been recognized. However, GJs have another important role: the regulation of large-scale anatomical pattern. GJs are not only versatile computational elements that allow cells to control which small molecule signals they receive and emit, but also establish connectivity patterns within large groups of cells. By dynamically regulating the topology of bioelectric networks in vivo, GJs underlie the ability of many tissues to implement complex morphogenesis. Here, a review of recent data on patterning roles of GJs in growth of the zebrafish fin, the establishment of left-right patterning, the developmental dysregulation known as cancer, and the control of large-scale head-tail polarity, and head shape in planarian regeneration has been reported. A perspective in which GJs are not only molecular features functioning in single cells, but also enable global neural-like dynamics in non-neural somatic tissues has been proposed. This view suggests a rich program of future work which capitalizes on the rapid advances in the biophysics of GJs to exploit GJ-mediated global dynamics for applications in birth defects, regenerative medicine, and morphogenetic bioengineering. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 643-673, 2017.

Gap junction proteins and the wiring (Rewiring) of neuronal circuits

The unique morphology and pattern of synaptic connections made by a neuron during development arise in part by an extended period of growth in which cell-cell interactions help to sculpt the arbor into its final shape, size, and participation in different synaptic networks. Recent experiments highlight a guiding role played by gap junction proteins in controlling this process. Ectopic and overexpression studies in invertebrates have revealed that the selective expression of distinct gap junction genes in neurons and glial cells is sufficient to establish selective new connections in the central nervous systems of the leech (Firme et al. [2012]: J Neurosci 32:14265-14270), the nematode (Rabinowitch et al. [2014]: Nat Commun 5:4442), and the fruit fly (Pézier et al., 2016: PLoS One 11:e0152211). We present here an overview of this work and suggest that gap junction proteins, in addition to their synaptic/communicative functions, have an instructive role as recognition and adhesion factors. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 575-586, 2017.

Vertically- and horizontally-transmitted memories - the fading boundaries between regeneration and inheritance in planaria

The Weismann barrier postulates that genetic information passes only from the germline to the soma and not in reverse, thus providing an obstacle to the inheritance of acquired traits. Certain organisms such as planaria – flatworms that can reproduce through asymmetric fission – avoid the limitations of this barrier, thus blurring the distinction between the processes of inheritance and development. In this paper, we re-evaluate canonical ideas about the interaction between developmental, genetic and evolutionary processes through the lens of planaria. Biased distribution of epigenetic effects in asymmetrically produced parts of a regenerating organism could increase variation and therefore affect the species' evolution. The maintenance and fixing of somatic experiences, encoded via stable biochemical or physiological states, may contribute to evolutionary processes in the absence of classically defined generations. We discuss different mechanisms that could induce asymmetry between the two organisms that eventually develop from the regenerating parts, including one particularly fascinating source – the potential capacity of the brain to produce long-lasting epigenetic changes.

Summary: In this hypothesis paper we re-evaluate canonical ideas about the interaction between developmental, genetic and evolutionary processes through the lens of planaria, an invertebrate model organism which challenges fundamental assumptions regarding reproduction.

Physiological inputs regulate species-specific anatomy during embryogenesis and regeneration

A key problem in evolutionary developmental biology is identifying the sources of instructive information that determine species-specific anatomical pattern. Understanding the inputs to large-scale morphology is also crucial for efforts to manipulate pattern formation in regenerative medicine and synthetic bioengineering. Recent studies have revealed a physiological system of communication among cells that regulates pattern during embryogenesis and regeneration in vertebrate and invertebrate models. Somatic tissues form networks using the same ion channels, electrical synapses, and neurotransmitter mechanisms exploited by the brain for information-processing. Experimental manipulation of these circuits was recently shown to override genome default patterning outcomes, resulting in head shapes resembling those of other species in planaria and Xenopus. The ability to drastically alter macroscopic anatomy to that of other extant species, despite a wild-type genomic sequence, suggests exciting new approaches to the understanding and control of patterning. Here, we review these results and discuss hypotheses regarding non-genomic systems of instructive information that determine biological growth and form.

Exploring Instructive Physiological Signaling with the Bioelectric Tissue Simulation Engine

Bioelectric cell properties have been revealed as powerful targets for modulating stem cell function, regenerative response, developmental patterning, and tumor reprograming. Spatio-temporal distributions of endogenous resting potential, ion flows, and electric fields are influenced not only by the genome and external signals but also by their own intrinsic dynamics. Ion channels and electrical synapses (gap junctions) both determine, and are themselves gated by, cellular resting potential. Thus, the origin and progression of bioelectric patterns in multicellular tissues is complex, which hampers the rational control of voltage distributions for biomedical interventions. To improve understanding of these dynamics and facilitate the development of bioelectric pattern control strategies, we developed the BioElectric Tissue Simulation Engine (BETSE), a finite volume method multiphysics simulator, which predicts bioelectric patterns and their spatio-temporal dynamics by modeling ion channel and gap junction activity and tracking changes to the fundamental property of ion concentration. We validate performance of the simulator by matching experimentally obtained data on membrane permeability, ion concentration and resting potential to simulated values, and by demonstrating the expected outcomes for a range of well-known cases, such as predicting the correct transmembrane voltage changes for perturbation of single cell membrane states and environmental ion concentrations, in addition to the development of realistic transepithelial potentials and bioelectric wounding signals. In silico experiments reveal factors influencing transmembrane potential are significantly different in gap junction-networked cell clusters with tight junctions, and identify non-linear feedback mechanisms capable of generating strong, emergent, cluster-wide resting potential gradients. The BETSE platform will enable a deep understanding of local and long-range bioelectrical dynamics in tissues, and assist the development of specific interventions to achieve greater control of pattern during morphogenesis and remodeling.

On Having No Head: Cognition throughout Biological Systems

The central nervous system (CNS) underlies memory, perception, decision-making, and behavior in numerous organisms. However, neural networks have no monopoly on the signaling functions that implement these remarkable algorithms. It is often forgotten that neurons optimized cellular signaling modes that existed long before the CNS appeared during evolution, and were used by somatic cellular networks to orchestrate physiology, embryonic development, and behavior. Many of the key dynamics that enable information processing can, in fact, be implemented by different biological hardware. This is widely exploited by organisms throughout the tree of life. Here, we review data on memory, learning, and other aspects of cognition in a range of models, including single celled organisms, plants, and tissues in animal bodies. We discuss current knowledge of the molecular mechanisms at work in these systems, and suggest several hypotheses for future investigation. The study of cognitive processes implemented in aneural contexts is a fascinating, highly interdisciplinary topic that has many implications for evolution, cell biology, regenerative medicine, computer science, and synthetic bioengineering.

Charged Residues at the First Transmembrane Region Contribute to the Voltage Dependence of the Slow Gate of Connexins

Connexins (Cxs) are a family of membrane-spanning proteins that form gap junction channels and hemichannels. Connexin-based channels exhibit two distinct voltage-dependent gating mechanisms termed slow and fast gating. Residues located at the C terminus of the first transmembrane segment (TM-1) are important structural components of the slow gate. Here, we determined the role of the charged residues at the end of TM-1 in voltage sensing in Cx26, Cx46, and Cx50. Conductance/voltage curves obtained from tail currents together with kinetics analysis reveal that the fast and slow gates of Cx26 involves the movement of two and four charges across the electric field, respectively. Primary sequence alignment of different Cxs shows the presence of well conserved glutamate residues in the C terminus of TM-1; only Cx26 contains a lysine in that position (lysine 41). Neutralization of lysine 41 in Cx26 increases the voltage dependence of the slow gate. Swapping of lysine 41 with glutamate 42 maintains the voltage dependence. In Cx46, neutralization of negative charges or addition of a positive charge in the Cx26 equivalent region reduced the slow gate voltage dependence. In Cx50, the addition of a glutamate in the same region decreased the voltage dependence, and the neutralization of a negative charge increased it. These results indicate that the charges at the end of TM-1 are part of the slow gate voltage sensor in Cxs. The fact that Cx42, which has no charge in this region, still presents voltage-dependent slow gating suggests that charges still unidentified also contribute to the slow gate voltage sensitivity.

KV1 channels identified in rodent myelinated axons, linked to Cx29 in innermost myelin: support for electrically active myelin in mammalian saltatory conduction

Saltatory conduction in mammalian myelinated axons was thought to be well understood before recent discoveries revealed unexpected subcellular distributions and molecular identities of the K(+)-conductance pathways that provide for rapid axonal repolarization. In this study, we visualize, identify, localize, quantify, and ultrastructurally characterize axonal KV1.1/KV1.2 channels in sciatic nerves of rodents. With the use of light microscopic immunocytochemistry and freeze-fracture replica immunogold labeling electron microscopy, KV1.1/KV1.2 channels are localized to three anatomically and compositionally distinct domains in the internodal axolemmas of large myelinated axons, where they form densely packed "rosettes" of 9-nm intramembrane particles. These axolemmal KV1.1/KV1.2 rosettes are precisely aligned with and ultrastructurally coupled to connexin29 (Cx29) channels, also in matching rosettes, in the surrounding juxtaparanodal myelin collars and along the inner mesaxon. As >98% of transmembrane proteins large enough to represent ion channels in these specialized domains, ∼500,000 KV1.1/KV1.2 channels define the paired juxtaparanodal regions as exclusive membrane domains for the voltage-gated K(+)conductance that underlies rapid axonal repolarization in mammals. The 1:1 molecular linkage of KV1 channels to Cx29 channels in the apposed juxtaparanodal collars, plus their linkage to an additional 250,000-400,000 Cx29 channels along each inner mesaxon in every large-diameter myelinated axon examined, supports previously proposed K(+)conductance directly from juxtaparanodal axoplasm into juxtaparanodal myeloplasm in mammalian axons. With neither Cx29 protein nor myelin rosettes detectable in frog myelinated axons, these data showing axon-to-myelin linkage by abundant KV1/Cx29 channels in rodent axons support renewed consideration of an electrically active role for myelin in increasing both saltatory conduction velocity and maximum propagation frequency in mammalian myelinated axons.

Physiological controls of large-scale patterning in planarian regeneration: a molecular and computational perspective on growth and form

Planaria are complex metazoans that repair damage to their bodies and cease remodeling when a correct anatomy has been achieved. This model system offers a unique opportunity to understand how large-scale anatomical homeostasis emerges from the activities of individual cells. Much progress has been made on the molecular genetics of stem cell activity in planaria. However, recent data also indicate that the global pattern is regulated by physiological circuits composed of ionic and neurotransmitter signaling. Here, we overview the multi-scale problem of understanding pattern regulation in planaria, with specific focus on bioelectric signaling via ion channels and gap junctions (electrical synapses), and computational efforts to extract explanatory models from functional and molecular data on regeneration. We present a perspective that interprets results in this fascinating field using concepts from dynamical systems theory and computational neuroscience. Serving as a tractable nexus between genetic, physiological, and computational approaches to pattern regulation, planarian pattern homeostasis harbors many deep insights for regenerative medicine, evolutionary biology, and engineering.

Telocytes in their context with other intercellular communication agents

The past decade has borne witness to an explosion in our understanding of the fundamental complexities of intercellular communication. Previously, the field was solely defined by the simple exchange of endocrine, autocrine and epicrine agents. Then it was discovered that cells possess an elaborate system of extracellular vesicles, including exosomes, which carry a vast array of small and large molecules (including many epigenetic agents such as a variety RNAs and DNA), as well as large organelles that modulate almost every aspect of cellular function. In addition, it was thought that electrical communication between cells was limited mainly to neurotransmitters and neuromodulators in the nervous system. Also within the past decade, it was found that - in addition to neurons - most cells (both mammalian and non-mammalian) communicate via elaborate bioelectric systems which modulate many fundamental cellular processes including growth, differentiation, morphogenesis and repair. In the nervous system, volume transmission via the extracellular matrix has been added to the list. Lastly, it was discovered that what had previously been regarded as simple connective cells in most tissues proved to be miniature communication devices now known as telocytes. These unusually long, tenuous and sinuous cells utilize elaborate electrical, chemical and epigenetic mechanisms, including the exchange of exosomes, to integrate many activities within and between nearly all types of cells in tissues and organs. Their interrelationship with neural stem cells and neurogenesis in the context of neurodegenerative disease is just beginning to be explored. This review presents an account of precisely how each of these varied mechanisms are relevant and critical to the understanding of what telocytes are and how they function.

Target morphology and cell memory: a model of regenerative pattern formation

Despite the growing body of work on molecular components required for regenerative repair, we still lack a deep understanding of the ability of some animal species to regenerate their appropriate complex anatomical structure following damage. A key question is how regenerating systems know when to stop growth and remodeling – what mechanisms implement recognition of correct morphology that signals a stop condition? In this work, we review two conceptual models of pattern regeneration that implement a kind of pattern memory. In the first one, all cells communicate with each other and keep the value of the total signal received from the other cells. If a part of the pattern is amputated, the signal distribution changes. The difference fromthe original signal distribution stimulates cell proliferation and leads to pattern regeneration, in effect implementing an error minimization process that uses signaling memory to achieve pattern correction. In the second model, we consider a more complex pattern organization with different cell types. Each tissue contains a central (coordinator) cell that controls the tissue and communicates with the other central cells. Each of them keeps memory about the signals received from other central cells. The values of these signals depend on the mutual cell location, and the memory allows regeneration of the structure when it is modified. The purpose of these models is to suggest possible mechanisms of pattern regeneration operating on the basis of cell memory which are compatible with diverse molecular implementation mechanisms within specific organisms.

Reverberation of excitation in neuronal networks interconnected through voltage-gated gap junction channels

Voltage-dependent gap junction gating contributes to reverberation in neuronal circuits.

We combined Hodgkin–Huxley equations and gating models of gap junction (GJ) channels to simulate the spread of excitation in two-dimensional networks composed of neurons interconnected by voltage-gated GJs. Each GJ channel contains two fast and slow gates, each exhibiting current–voltage (I-V) rectification and gating properties that depend on transjunctional voltage (V_j). The data obtained show how junctional conductance (g_j), which is necessary for synchronization of the neuronal network, depends on its size and the intrinsic firing rate of neurons. A phase shift between action potentials (APs) of neighboring neurons creates bipolar, short-lasting V_j spikes of approximately ±100 mV that induce V_j gating, leading to a small decay of g_j, which can accumulate into larger decays during bursting activity of neurons. We show that I-V rectification of GJs in local regions of the two-dimensional network of neurons can lead to unidirectional AP transfer and consequently to reverberation of excitation. This reverberation can be initiated by a single electrical pulse and terminated by a low-amplitude pulse applied in a specific window of reverberation cycle. Thus, the model accounts for the influence of dynamically modulatable electrical synapses in shaping the function of a neuronal network and the formation of reverberation, which, as proposed earlier, may be important for the development of short-term memory and its consolidation into long-term memory.

Towards a Physarum learning chip

Networks of protoplasmic tubes of organism Physarum polycehpalum are macro-scale structures which optimally span multiple food sources to avoid repellents yet maximize coverage of attractants. When data are presented by configurations of attractants and behaviour of the slime mould is tuned by a range of repellents, the organism preforms computation. It maps given data configuration into a protoplasmic network. To discover physical means of programming the slime mould computers we explore conductivity of the protoplasmic tubes; proposing that the network connectivity of protoplasmic tubes shows pathway-dependent plasticity. To demonstrate this we encourage the slime mould to span a grid of electrodes and apply AC stimuli to the network. Learning and weighted connections within a grid of electrodes is produced using negative and positive voltage stimulation of the network at desired nodes; low frequency (10 Hz) sinusoidal (0.5 V peak-to-peak) voltage increases connectivity between stimulated electrodes while decreasing connectivity elsewhere, high frequency (1000 Hz) sinusoidal (2.5 V peak-to-peak) voltage stimulation decreases network connectivity between stimulated electrodes. We corroborate in a particle model. This phenomenon may be used for computation in the same way that neural networks process information and has the potential to shed light on the dynamics of learning and information processing in non-neural metazoan somatic cell networks.

Gap Junctional Blockade Stochastically Induces Different Species-Specific Head Anatomies in Genetically Wild-Type Girardia dorotocephala Flatworms

The shape of an animal body plan is constructed from protein components encoded by the genome. However, bioelectric networks composed of many cell types have their own intrinsic dynamics, and can drive distinct morphological outcomes during embryogenesis and regeneration. Planarian flatworms are a popular system for exploring body plan patterning due to their regenerative capacity, but despite considerable molecular information regarding stem cell differentiation and basic axial patterning, very little is known about how distinct head shapes are produced. Here, we show that after decapitation in G. dorotocephala, a transient perturbation of physiological connectivity among cells (using the gap junction blocker octanol) can result in regenerated heads with quite different shapes, stochastically matching other known species of planaria (S. mediterranea, D. japonica, and P. felina). We use morphometric analysis to quantify the ability of physiological network perturbations to induce different species-specific head shapes from the same genome. Moreover, we present a computational agent-based model of cell and physical dynamics during regeneration that quantitatively reproduces the observed shape changes. Morphological alterations induced in a genomically wild-type G. dorotocephala during regeneration include not only the shape of the head but also the morphology of the brain, the characteristic distribution of adult stem cells (neoblasts), and the bioelectric gradients of resting potential within the anterior tissues. Interestingly, the shape change is not permanent; after regeneration is complete, intact animals remodel back to G. dorotocephala-appropriate head shape within several weeks in a secondary phase of remodeling following initial complete regeneration. We present a conceptual model to guide future work to delineate the molecular mechanisms by which bioelectric networks stochastically select among a small set of discrete head morphologies. Taken together, these data and analyses shed light on important physiological modifiers of morphological information in dictating species-specific shape, and reveal them to be a novel instructive input into head patterning in regenerating planaria.

Re-membering the body: applications of computational neuroscience to the top-down control of regeneration of limbs and other complex organs

A major goal of regenerative medicine and bioengineering is the regeneration of complex organs, such as limbs, and the capability to create artificial constructs (so-called biobots) with defined morphologies and robust self-repair capabilities. Developmental biology presents remarkable examples of systems that self-assemble and regenerate complex structures toward their correct shape despite significant perturbations. A fundamental challenge is to translate progress in molecular genetics into control of large-scale organismal anatomy, and the field is still searching for an appropriate theoretical paradigm for facilitating control of pattern homeostasis. However, computational neuroscience provides many examples in which cell networks - brains - store memories (e.g., of geometric configurations, rules, and patterns) and coordinate their activity towards proximal and distant goals. In this Perspective, we propose that programming large-scale morphogenesis requires exploiting the information processing by which cellular structures work toward specific shapes. In non-neural cells, as in the brain, bioelectric signaling implements information processing, decision-making, and memory in regulating pattern and its remodeling. Thus, approaches used in computational neuroscience to understand goal-seeking neural systems offer a toolbox of techniques to model and control regenerative pattern formation. Here, we review recent data on developmental bioelectricity as a regulator of patterning, and propose that target morphology could be encoded within tissues as a kind of memory, using the same molecular mechanisms and algorithms so successfully exploited by the brain. We highlight the next steps of an unconventional research program, which may allow top-down control of growth and form for numerous applications in regenerative medicine and synthetic bioengineering.

Bioelectric memory: modeling resting potential bistability in amphibian embryos and mammalian cells

Background

Bioelectric gradients among all cells, not just within excitable nerve and muscle, play instructive roles in developmental and regenerative pattern formation. Plasma membrane resting potential gradients regulate cell behaviors by regulating downstream transcriptional and epigenetic events. Unlike neurons, which fire rapidly and typically return to the same polarized state, developmental bioelectric signaling involves many cell types stably maintaining various levels of resting potential during morphogenetic events. It is important to begin to quantitatively model the stability of bioelectric states in cells, to understand computation and pattern maintenance during regeneration and remodeling.

Method

To facilitate the analysis of endogenous bioelectric signaling and the exploitation of voltage-based cellular controls in synthetic bioengineering applications, we sought to understand the conditions under which somatic cells can stably maintain distinct resting potential values (a type of state memory). Using the Channelpedia ion channel database, we generated an array of amphibian oocyte and mammalian membrane models for voltage evolution. These models were analyzed and searched, by simulation, for a simple dynamical property, multistability, which forms a type of voltage memory.

Results

We find that typical mammalian models and amphibian oocyte models exhibit bistability when expressing different ion channel subsets, with either persistent sodium or inward-rectifying potassium, respectively, playing a facilitative role in bistable memory formation. We illustrate this difference using fast sodium channel dynamics for which a comprehensive theory exists, where the same model exhibits bistability under mammalian conditions but not amphibian conditions. In amphibians, potassium channels from the Kv1.x and Kv2.x families tend to disrupt this bistable memory formation. We also identify some common principles under which physiological memory emerges, which suggest specific strategies for implementing memories in bioengineering contexts.

Conclusion

Our results reveal conditions under which cells can stably maintain one of several resting voltage potential values. These models suggest testable predictions for experiments in developmental bioelectricity, and illustrate how cells can be used as versatile physiological memory elements in synthetic biology, and unconventional computation contexts.

Electronic supplementary material

The online version of this article (doi:10.1186/s12976-015-0019-9) contains supplementary material, which is available to authorized users.

Molecular bioelectricity: how endogenous voltage potentials control cell behavior and instruct pattern regulation in vivo

In addition to biochemical gradients and transcriptional networks, cell behavior is regulated by endogenous bioelectrical cues originating in the activity of ion channels and pumps, operating in a wide variety of cell types. Instructive signals mediated by changes in resting potential control proliferation, differentiation, cell shape, and apoptosis of stem, progenitor, and somatic cells. Of importance, however, cells are regulated not only by their own V_mem but also by the V_mem of their neighbors, forming networks via electrical synapses known as gap junctions. Spatiotemporal changes in V_mem distribution among nonneural somatic tissues regulate pattern formation and serve as signals that trigger limb regeneration, induce eye formation, set polarity of whole-body anatomical axes, and orchestrate craniofacial patterning. New tools for tracking and functionally altering V_mem gradients in vivo have identified novel roles for bioelectrical signaling and revealed the molecular pathways by which V_mem changes are transduced into cascades of downstream gene expression. Because channels and gap junctions are gated posttranslationally, bioelectrical networks have their own characteristic dynamics that do not reduce to molecular profiling of channel expression (although they couple functionally to transcriptional networks). The recent data provide an exciting opportunity to crack the bioelectric code, and learn to program cellular activity at the level of organs, not only cell types. The understanding of how patterning information is encoded in bioelectrical networks, which may require concepts from computational neuroscience, will have transformative implications for embryogenesis, regeneration, cancer, and synthetic bioengineering.

Endogenous gradients of resting potential instructively pattern embryonic neural tissue via Notch signaling and regulation of proliferation

Biophysical forces play important roles throughout embryogenesis, but the roles of spatial differences in cellular resting potentials during large-scale brain morphogenesis remain unknown. Here, we implicate endogenous bioelectricity as an instructive factor during brain patterning in Xenopus laevis. Early frog embryos exhibit a characteristic hyperpolarization of cells lining the neural tube; disruption of this spatial gradient of the transmembrane potential (Vmem) diminishes or eliminates the expression of early brain markers, and causes anatomical mispatterning of the brain, including absent or malformed regions. This effect is mediated by voltage-gated calcium signaling and gap-junctional communication. In addition to cell-autonomous effects, we show that hyperpolarization of transmembrane potential (Vmem) in ventral cells outside the brain induces upregulation of neural cell proliferation at long range. Misexpression of the constitutively active form of Notch, a suppressor of neural induction, impairs the normal hyperpolarization pattern and neural patterning; forced hyperpolarization by misexpression of specific ion channels rescues brain defects induced by activated Notch signaling. Strikingly, hyperpolarizing posterior or ventral cells induces the production of ectopic neural tissue considerably outside the neural field. The hyperpolarization signal also synergizes with canonical reprogramming factors (POU and HB4), directing undifferentiated cells toward neural fate in vivo. These data identify a new functional role for bioelectric signaling in brain patterning, reveal interactions between Vmem and key biochemical pathways (Notch and Ca(2+) signaling) as the molecular mechanism by which spatial differences of Vmem regulate organogenesis of the vertebrate brain, and suggest voltage modulation as a tractable strategy for intervention in certain classes of birth defects.