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

Abstract

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.

Keywords: bioelectricity; gap junction; ion channel; morphological computation; regeneration; synthetic morphology.

Figure 1

Shape homeostasis in biological systems. (a) Early embryos give rise to two complete bodies when split in half. (b) Conversely, when mixed, embryos remodel to form a normal single animal. (c) Salamanders regenerate whole limbs when amputated. (d) Deer regenerate large amounts of bone and nerve during antler regrowth; the phenomenon of trophic memory in some species results in ectopic growths at sites of damage done in previous cycles to a structure that falls off completely and is rebuilt from scratch each year. Photograph of human twins in panel a reproduced with permission from Wikimedia Commons (Oudeschool; https://commons.wikimedia.org/wiki/File:Power20302.jpg; licensed under the Creative Commons Attribution 3.0 Unported license). Panels b and c drawn by Jeremy Guay, Peregrine Creative. Panel d reproduced with permission from Reference .

Figure 2

Endogenous bioelectric properties. (a) Subcellular organelles (such as the nuclear envelope) maintain voltage potentials across their membranes. (b) Cell plasma membranes likewise maintain a V_mem as a function of the ion channels and pumps in their membranes. (c) Cells organized into tissues drive a transepithelial potential, which gives rise to electric fields that provide a vector to points of damage. (d) Combinations of these local and long-range properties result in gradients across entire anatomical body axes. Abbreviation: V_TEP, transepithelial electrical potential. Modified with permission from Maria Lobikin.

Figure 3

Cell-level events in bioelectrical signaling. (a) The resting potential of terminally differentiated, quiescent cells tends to be hyperpolarized, whereas that of embryonic, stem, or tumor cells tends to be depolarized. This is a functional relationship, as artificial regulation of the V_mem instructively sets cell proliferative capacity and plasticity. The resting potential of single cells is set by the function of ion channels and pumps in their membranes (b); changes in this voltage are transduced (c) by a set of membrane mechanisms (voltage-gated calcium channels, voltage-powered transporters of serotonin and butyrate, voltage-regulated phosphatases, and others) into second-messenger cascades that impinge on transcription, thus regulating single-cell behaviors (d) such as proliferation, migration, cell shape, and programmed cell death. Abbreviations: 5-HT, 5-hydroxytryptamine, also known as serotonin; HDAC, histone deacetylase; hMSC, human mesenchymal stem cell; MAD3, Max-interacting transcriptional repressor; MAP kinase, mitogen-activated protein kinase; mESC, mouse embryonic stem cell. Panel a modified with permission from Reference and drawn by Jeremy Guay, Peregrine Creative. Panel b modified with permission from Maria Lobikin. Panel c modified with permission from Reference .

Figure 4

Manipulation of the bioelectric control layer. (a) The feedback between ion channels’ determination of V_mem and their own sensitivity to V_mem results in a layer of feedback that functions in parallel to canonical signaling via transcriptional circuits. These two layers are coupled but have their own intrinsic dynamics and play distinct roles in regulating patterning processes. (b) Simulation environments for physiological signaling are used to guide interventions in guided self-assembly of bioelectrical patterns. (c) Investigation of the functions of the bioelectric layer is performed via altering the network connectivity (via genetic or pharmacological change of gap junctions—synaptic plasticity) or by altering individual cellular activation levels (via genetic or pharmacological control of ion channels and pumps—intrinsic plasticity). (d) Optogenetic and microfluidic technologies are beginning to be developed to hold embryos (such as the frog embryo shown here) and apply patterned light that differentially triggers hyperpolarizing and depolarizing channels. Panels a, b, and c modified with permission from Alexis Pietak. Panel d reproduced with permission from Dany Spencer Adams, Jin Akagi, and Sebastien Uzel (83).

Figure 5

Large-scale bioelectric patterns are instructive for shape. (a) Limb regeneration does not normally occur in froglets. (Inset) There is no blue stain for MSX1, a blastema marker, indicating that it is absent from the tissue sample. (b) A mixture of ionophores designed to specifically alter the bioelectric state of the blastema, after only 24 h of exposure, triggers the presence of an MSX1-positive blastema. (Inset) The growth of an entire limb (arrowhead). (c) Spatial distributions of resting potential revealed by voltage-sensitive fluorescent dyes, such as this image of a craniofacial voltage prepattern in Xenopus, determine downstream gene expression and anatomical outcomes. (d) Manipulation of these endogenous patterns by misexpression of ion channels can result in organ-level reprogramming, such as turning a portion of the gut into a complete eye. (e) Understanding of the bioelectric circuit that controls, for example, anterior–posterior specification in a fragment of regenerating Planaria can be used to design drug cocktails that (f) alter the anatomical structure thus produced, such as inducing the posterior-facing blastema to build a secondary head in Planaria. (g) Depolarization of host tissues in the context of an eye transplant induces drastic overproliferation of nerve emerging from the implanted organ in comparison to a control host. (h) This technique can be used to pattern the ectopic nerve, inducing it to connect to specific regions by patterning the activation of ion channels in the surrounding tissue. Abbreviations: dpa, days postamputation; hpa, hours postamputation; IVM, ivermectin; mRNA, messenger RNA; SCH, SCH-28080. Panels a and b reproduced with permission from Reference . Panel c modified with permission from Reference . Panel d modified with permission from Reference . Panel e modified with permission from Reference . Panel f modified with permission from Reference . Panel g reproduced with permission from References and and from Douglas J. Blackiston. Panel h reproduced with permission from Douglas J. Blackiston.

Figure 6

Bioelectric states that can override genome defaults. (a) Brief pharmacological manipulation of connectivity within the bioelectric network that guides planarian regeneration results in two-headed forms that regenerate this new body plan in perpetuity: Long after the original reagent is gone, regeneration of a middle fragment in plain water reveals an altered pattern memory despite an unchanged genomic sequence and removal of ectopic tissue. (b) Oncogenes injected into frog embryos (with red fluorescent tracer) induce tumorous growths. (c) If their resting potential is forced into the normal state by coinjection with a GlyR chloride channel mutant, tumors do not form (iii) even though the oncogene is still present (iv). Panel a reproduced with permission from Reference . Panels b and c modified with permission from Reference .

Figure 7

Decoding content from neural data: two examples. (a) Place cell decoding: trajectory events (e.g., sequences of place cells forming a trajectory) in an open arena reconstructed from single-cell recordings in the rat hippocampus while the rat was at rest. These trajectory events may support navigational planning, in this example, potential plans toward the next goal site located at the center of the arena. Event duration (in milliseconds) is shown in the right corner. (b) Reconstructions of movies from functional magnetic resonance imaging blood oxygenation level–dependent signals in the occipitotemporal visual cortex of human subjects who watched movies. (Top) Frames of three movies presented to participants. (Bottom) The averaged high posterior (AHP) reconstruction of the same frames. Panel a modified with permission from Reference . Panel b modified with permission from Reference .

Figure 8

Concepts from computational neuroscience applied to pattern regulation. Significant functional isomorphism exists between developmental bioelectricity and information processing in the brain and in artificial systems. Geometric memory (e.g., of a path through a maze) in the brain (a) is implemented by memory encoded as stable bioelectrical states (b), which are maintained by connectivity and electrical communication among brain cells (c). The electric states, in turn, are generated by ion channel and gap junctional proteins (d). Pattern memory (the shape that is regenerated after a salamander’s limb is amputated and that serves as a stop condition for further growth) (e) is likewise implemented by information encoded in gradients of electrical potential in the tissue (f), which are maintained by V_mem potentials of specific cells throughout the body (g) that, in turn, are generated by ion channel and gap junctional proteins (h). In artificial cybernetic systems, specific patterns (i) can be remembered and processed by artificial neural net representations (j), which are built up from electrical circuits consisting of transistors (k); interestingly, gap junctions act much like transistors (l) because they regulate their permeability (current) on the basis of the voltage applied across them. A prediction and an implication of this view of bioelectric networks are that nonneural cells and tissues ought to be trainable for specific patterning topologies and computations. (m) In this example, the goal is to control the state of electric synapses (gap junctions) among specific regions, and force it to make one side of the network (e.g., the left half) well coupled while another side (the right half) stays uncoupled. Cells would be grown on a penetrating electrode array and assayed for gap junctional connectivity as a resistance measurement. The training paradigm would be a closed-loop system as follows: Every few seconds (over a period of days in culture), it would measure the coupling (resistance) of cells. To force the network to arrange its topology such that R2 is high and R1 is low (at first, they would be roughly equal), the system would mesofluidically deliver an amount of something the cells like (nutrients, opioids, endorphins, other addictive substances, etc.) proportional to the ratio R2/R1. We conjecture that, with time, the network would establish the needed connectivity pattern to maximize R2/R1 to optimize its receipt of the drug. (n) In this example, the goal is to train the tissue to perform a specific computation [an arbitrary function f(x) that maps inputs to outputs]. Over a period of days, the system applies stimuli to E1 and E2 and measures activity on E3. The reward in each cycle of the loop is proportional to the inverse of the error between E3 and the desired f(E1,E2). The tissue may learn to act as needed, revealing the ability to program physiological responses from the top down. Abbreviation: 5-HT, 5-hydroxytryptamine, also known as serotonin. Panels a, b, e, and f drawn by Alexis Pietak. Panels c, d, and g–n modified with permission from Alexis Pietak.