The body electric 2.0: recent advances in developmental bioelectricity for regenerative and synthetic bioengineering

Abstract

Breakthroughs in biomedicine and synthetic bioengineering require predictive, rational control over anatomical structure and function. Recent successes in manipulating cellular and molecular hardware have not been matched by progress in understanding the patterning software implemented during embryogenesis and regeneration. A fundamental capability gap is driving desired changes in growth and form to address birth defects and traumatic injury. Here we review new tools, results, and conceptual advances in an exciting emerging field: endogenous non-neural bioelectric signaling, which enables cellular collectives to make global decisions and implement large-scale pattern homeostasis. Spatially distributed electric circuits regulate gene expression, organ morphogenesis, and body-wide axial patterning. Developmental bioelectricity facilitates the interface to organ-level modular control points that direct patterning in vivo. Cracking the bioelectric code will enable transformative progress in bioengineering and regenerative medicine.

Figure 1

Bioelectric signaling outside the nervous system. (a) The information-processing functions of the brain derive from electric dynamics implemented by ion channels, which set cell resting potentials, and gap junction synapses, which allow voltage states to selectively propagate to neighboring cells. (b) The same components are expressed in most somatic cells, outside the nervous system, allowing them to set up distinct bioelectric states across tissues. (c) On a single-cell level, voltage states are transduced by a variety of mechanisms, including KRAS clustering, cytoskeletal changes, and transporters of small signaling molecules such as calcium, serotonin, and butyrate. (d) Such transduction mechanisms convert bioelectric states produced by channel and pump activity to second-messenger events that regulate numerous downstream genes. Even more important than individual cell potentials (e) are the spatio-temporal patterns of bioelectrical state across tissue, seen in the mid-flank of a tadpole soaked in fluorescent voltage-reporter dye (e′). Such distributions include both endogenous prepatterns for organ morphogenesis, such as the ‘electric face’ pattern that determines gene expression and anatomy of the Xenopus face (f) (red arrow points to a hyperpolarized spot that determines location of the right eye), and of pathological states corresponding to sites of tumor formation (g) that are detectable by aberrant depolarization signals (h). Credits: a, b — Jeremy Guay of Peregrine Creative; e′ — Douglas Blackiston; f — Dany S. Adams; g — Brook Chernet.

Figure 2

Manipulation of bioelectric networks result in patterning changes in vivo. (a) Networks of electrically connected cells can be manipulated in several fundamental ways: altering the electrical connectivity (network topology) via dominant-negative, mutant, or wild-type connexin proteins (synaptic plasticity), altering the resting potential of individual cell groups by introducing new channels or modifying existing channels pharmacologically (intrinsic plasticity), or directly altering the normally voltage-guided movement and signaling of small molecules (such as neurotransmitters) through the network. Altering V_mem in vivo (regardless which ion movement is used to achieve it) predictably induces changes such as increasing the innervation from eye transplants in frog embryos (b), which normally grows out one new nerve bundle (b′), but exhibits extensive new innervation when the surrounding host tissue is depolarized (b″); the same method can be used to target innervation growth to regions of specific V_mem (b‴) shows neuronal targeting of a region expressing the hyperpolarizing Kir4.1 channel). On an organ level, inducing eye-specific bioelectric patterns by ion channel mRNA misexpression can induce eye formation anywhere in the body, even outside the anterior neural field, such as on the gut ((c) red arrowhead indicates ectopic eye made in endoderm), or ectopic limbs (red arrow in (d), induced in a frog overexpressing an optogenetic activator). Credits: a – Jeremy Guay of Peregrine Creative; b-b‴ – Douglas Blackiston; d – EnPAC transgenic frog made by Gufa Lin. Photos by Dany S. Adams and Erin Switzer.

Figure 3

Bioelectric prepatterns store target morphology memories. Planaria that have normal anatomy (one head, one tail (a)) and normal molecular histology (head marker expressed only in the head end (b)), but are transiently modified (using pharmacological targeting of bioelectric circuit) to have depolarized (green) regions in both ends versus the normal unilateral pattern (c) will regenerate from middle third fragments as one or two-headed (bipolar heteromorphosis) forms respectively (d). Recent computational modeling of the bioelectric circuit (the state space of which is schematized in (e)) reveals how its attractors encode stable (permanent) pattern memories that guide future rounds of regeneration toward distinct anatomical outcomes. Credits: a-d from [77^••]; e – Jeremy Guay of Peregrine Creative.

Figure 4

Predictive computational platforms for biomedical applications: a possible roadmap. Existing bioinformatics resources, including databases of known ion channel drugs (a), expression profiles of channels and pumps in various healthy and diseased human tissues (a′), and known correct bioelectric prepatterns for specific cellular tissues and structures (a″), are inputs into expert systems being developed in our center (b). These machine-learning platforms invert bioelectric modeling tools [79] to infer what interventions can be performed (which ion channels, pumps, or gap junctions need to be activated or deactivated) to induce desired bioelectric states. Using systemic application or bioreactor-based delivery in model systems (c) or human patients (c′), these will someday be able to address bioelectric circuit disorders that comprise many degenerative, birth defect, or carcinogenic conditions, as well as induce regenerative repair. The ultimate goal of this research program is a ‘biological compiler’ that can convert anatomical specifications (d) into biophysical signals that modify target morphology encodings causing cells to build to the spec (illustrated via planarian bodyplan (d′)). Credits: a, a′ – Jeremy Guay of Peregrine Creative; a″ – Dany S. Adams; b – Alexis Pietak; c – Jay Dubb; c′ – Jeremy Guay of Peregrine Creative; d – Daniel Lobo; d′ – Junji Morokuma.