Table of Contents
This work has been put out as a peer reviewed publication that is now live here. | June 19, 2023
You can read the ungated preprint here. | April 2, 2023
Information presented here together suggests that bioelectricity and moreover biochemical and biomechanical gradients may play a causal role in the whole organism aging process.
At present, this is simply a series of block texts copied from various papers and kept here for reference, however in time, I plan to work this into a comprehensive meta analysis making my case for this relationship between aging and bioelectricity. — Completed, see note above.
Definitions / Concepts #
Bioelectrical coupling in multicellular domains regulated by gap junctions: A conceptual approach1 #
Master regulators -> unique control nodes in regulatory processes that can be exploited to trigger coordinated patterning outcomes that are too complex to micromanage bottom-up.
Voltage Membrane (Vmem) -> electrical potential difference between the cell cytoplasm and the extracellular environment.
Statistical Thermodynamics shows that instead of attempting a detailed molecular description of each individuality, a judicious use of average magnitudes can unveil the basic mechanisms characteristic of systems composed by a high number of individualities.
Bioelectricity regulates the transport of signaling ions and molecules crucial to the genetic and epigenetic networks of transcriptional and translational control. It can also act posttranslationally, e.g. by provoking conformational changes in voltage-sensing membrane proteins, activating voltage-gated channels, and blocking the channels with specific ions and molecules. The consequence of this complex interplay is that the kinetic equations for the single-cell genetic regulation should incorporate the cell electric potential together with the mRNA and protein concentrations.
Top-down models in biology: explanation and control of complex living systems above the molecular level2 #
We argue that top-down control models provide a valuable complement to thetoolkit of cell biologists, evolutionary biologists, bioengineersand workers in regenerative medicine because they provide amechanistic roadmap for optimal explanation and control of some complex systems."
For example, the notion of (minimization of)a free energy gradient, which originated in thermodynamics, can be used to study biological systems such as cell movement or brain dynamics.
The free energy principle starts from a simple evolutionary consideration: in order to survive, animals need to occupy a restricted (relatively rare) set of ‘good states’ that essentially define their evolutionary niche (e.g. places wherethey can find food) and avoid the others (e.g. underwaterfor a terrestrial animal). To this aim, animal brains are optimized to process environmental statistics and guide the animal towards these ‘good states’, which is done by using an error-correction mechanism to minimize a distance measure (prediction error or surprise) between the current sensed state and the desired good states.
Remarkably, when crossreferenced with transcriptomes from plant (Arabidopsis) regeneration, one common gene remains: the transmembrane ring protein component of the proton-transporting V-ATPase. This fascinating structure is related to both gap junctions (a.k.a., electrical synapses) and ion pumps that polarize cells, and has already been functionally implicated in embryonic left–right patterning in chick, zebrafish, and frog, zebrafish eye morphogenesis, frog tail regeneration, wound healing in Drosophila, and stem cell regulation in the mouse brain. In some of these cases (e.g., chick and frog), the V-ATPase pump is known to function on the cell surface, generating a significant hyperpolarization of cells by the efflux of positive charges.
Seminal work by Binggeli and Weinstein building on the work of Cone hypothesized that resting membrane potential, Vmem, predictably varied across cell types according to cell type and cell cycle stage. They performed a meta-analysis of literature that reported Vmem in a variety of cell types and stages, showing that proliferative cells and cancer cells both were more depolarized than differentiated cells, and that a boundary existed at around -36 mV that differentiated proliferating and nonproliferating cells.
Cell Membranes are like a GRN’s Markov blanket.
In order toreach the target form, each cell has to move to an appropriatelocation based upon chemotactic concentration gradients. However, these gradients depend upon cell migration. Inother words, self-assembly requires each cell to ‘know itsplace’ so that the population can establish a chemotacticframe of reference that enables each cell to ‘know its place’. This is the problem solved through minimizing free energy,where free energy is minimized when, and only when,every cell has associated itself with a unique target location.Note that, after differentiation, every cell has to infer aunique identity without access to the beliefs of other cells.This hard problem is finessed by the embodied nature ofactive inference: because a cell can only be in one place at atime there is a unique free-energy minimum, where every cell knows its respective place
Cells experience a linear increase in sensitivity to extracellular signals over developmental time.
When the sensitivity to exogenous gradients is suppressed, the cells think they have not migrated sufficiently to differentiate and remain confused about theiridentity. Conversely, if we increase the sensitivity to the vertical gradient, the cells migrate over smaller vertical distances resulting in a vertical compression of the final form. Doubling the sensitivity to intracellular signals causes a failure of migration and differentiation and generalized atrophy.
Intracellular signalling-dependent transcription -> multicellular gradient states anchored to create transcription predictions that can be associated with epigenetic processes.
Intervention & Recording Methodology #
In Vitro / In Vivo #
Defined extracellular ionic solutions to study and manipulate the cellular resting membrane potential5 #
The resting membrane potential (RMP) represents the voltage at which the net ionic currents across the membrane are zero. When the membrane potential becomes more negative or positive than the RMP, the cell is said to be hyperpolarized or depolarized, respectively. The RMP is recognized as a key regulator of many cellular phenomena, such as proliferation, morphogenesis, migration and differentiation, as well as morphogenesis in development and regeneration.
The RMP is determined by two main factors: (1) the membrane permeability and (2) concentration gradient of the most abundant permeable ions, Na+, K+, and Cl−. The voltage Goldman Hodgkin Katz (GHK) equation is the simplest and most widely used method to calculate the RMP. The GHK equation describes the relationship between the RMP of a cell and variables such as temperature, ionic permeability and composition of the dominant monovalent ions of a cell: K+, Na+ and Cl−. Quantifying the contribution of each ion to the RMP can reveal insights into the cell biological mechanisms driving the RMP and the effects of changes in RMP within the cell. The RMP is set and controlled by a repertoire of ion channels, pumps, transporters and junction proteins, whose activities are usually regulated by voltage, ligands, or both. The multifaceted time-, voltage-, spatial- and ligand-dependent activity and localization of these proteins allows the selective movement of ions across the membrane. As a consequence, the RMP itself varies in a cell specific, time- and context-dependent fashion, as previously summarized elsewhere, making it difficult to accurately capture using the GHK equation alone.
The first step in the proposed method is the generation of a calibration curve to characterize the relationship between the optical reading from the voltage dye with the voltage reading by patch clamp within a cell line of interest. The goal is to then use the change in fluorescence relative to the change in voltage obtained with the calibration curve measure the voltage difference between two conditions without the need for patch clamping for subsequent experiments. We used the DiBAC voltage-sensitive dye (whose signal is stable while recording; ) and quantified fluorescent signal for a field of view and patch clamp electrophysiology to measure the RMP of individual cells.
Potassium and sodium are two of the most abundant ions in the extracellular milieu and therefore were chosen to elicit a change in RMP.
We designed a simple methodology to identify the role of a given ion in setting the RMP by substituting each permeable ion with a cell membrane-impermeable ion and measuring the effect on the RMP.
In Silico #
- Currently Exploring BETSE
Corrolation Questions #
How does steady-state Vmem change over time in correlation to mitotic division? #
These ideas were formally tested in a series of groundbreaking experiments by Clarence D. Cone, Jr. throughout the late 1960’s. He first observed that Vmem varied through the cell cycle and postulated that the variations were directly related to progression through G1 /S and G2 /M transitions in proliferating cells. In a follow up study to explicitly test causation, he altered the intracellular ionic concentration of cells and was able to induce a reversible mitotic block by mimicking Vmem to levels observed in neurons.8 Even more impressively, it was shown that sustained depolarization was able to induce DNA synthesis and mitosis in mature neurons.
Membrane potential has been examined as a key regulator of proliferation in a number of cell types, suggesting that modulation of Vmem is required for both G1 /S phase and G2 /M phase transitions. Depolarization of membrane through changes in extracellular ion concentration inhibits G1 /S progression of lymphocytes, astrocytes, fibroblasts and Schwann cells suggesting hyper-polarization is a required step for S phase initation.
Cellular Vmem levels vary widely among different cell types (-10 to -90 mV) and this parameter generally corresponds to proliferative potential. This trend is thought to be functional since mitotically active cells such as embryonic, cancer, and stem cells have shown to be more depolarized (0 to -30 mV) than terminally differentiated cells (-50 to -100 mV) that no longer proliferate. Mammalian liver cells reside more toward the middle of the scale and it has been suggested that this is correlated with the extraordinary regenerative capacity of this organ.
Genome-wide analysis reveals conserved transcriptional responses downstream of resting potential change in Xenopus embryos, axolotl regeneration, and human mesenchymal cell differentiation8 #
No systematic analysis has been performed to identify and integrate genome-wide transcriptional changes following steady-state depolarization in vivo, or to suggest novel biomedical endpoints for Vmem modulation.
In order to understand the role of bioelectricity in pattern formation, and to harness this signaling modality for biomedicine, it is important to understand the transcriptional networks downstream of specific Vmem change.
Our analysis identified putative transcriptional targets by which Vmem regulates apoptosis, and also identified other cell death mechanisms like anoikis that are regulated by Vmem. Our analysis also identified, for the first time, fate specification genes regulated by Vmem for tissues from all three germ layers.
mTOR signalling increases with age. Inverse correlation with steady-state Vmem? #
mTORC1 Is a Local, Postsynaptic Voltage Sensor Regulated by Positive and Negative Feedback Pathways9 #
Our subsequent study revealed that acute reduction of mTORC1 activity by rapamycin in vivo preferentially alters the expression of proteins involved in ion homeostasis and regulation of the membrane potential.
It has been suggested that overactive mTORC1 in epilepsy promotes excessive protein synthesis that engenders neuronal hyperexcitability. Equally as important, overactive mTORC1 represses several ion channels that reduces excitability.
Considering the presence of mTORC1 in the postsynaptic region and its ability to regulate the levels of ion channels, ionotropic receptors, and their associated proteins that determine conductance and trafficking, it is germane to define the link between dysregulated mTORC1 activity and abnormal membrane excitability. While it may be that the proposed positive and negative feedback mechanisms governing mTORC1-dependent regulation of membrane potential may be simple as presented, consideration and refinement of this hypothesis is an important step that will have broad implications not only in neurological disorders but in other fields that investigate excitable membranes.
Information Processing #
Synchronization of Bioelectric Oscillations in Networks of Nonexcitable Cells: From Single-Cell to Multicellular States10 #
Therefore, the ensemble synchronization of electric potentials should also have feedback effects concerning the collective regulation of individual cell cycles.
In our case, however, we have focused on bioelectrical phenomena, where oscillatory collective communication across different scales arise in aggregates of glioma cells, bacterial communities, pancreatic islets, and the possible coupling between the expression of plasticity-related proteins and oscillating brain states. In all these cases, specific ion channel proteins contribute to the coordination of large cell populations by regulating endogenous electric pulses. The potential maps of Figures 6−8 can be seen as bioelectrical templates for the spatiotemporal distributions of signaling ions and molecules that influence downstream biochemical pathways. It is then conceivable that ensemble-averaged bioelectric magnitudes may assist in the control of single-cell characteristics by improving the system reliability at the multicellular level, which suggests that efforts to control the system-level activity of cellular ensembles can target specific electric potentials and currents.
Magnetic field treatments #
The biological activity of magnetic fields is a consequence of the effect those fields have on ion currents, as well as upon particles having a specific magnetic moment. This interaction causes certain orientations of physical stimuli, which influence the properties of cell membranes, electrolyte systems, sensitivity threshold for free nerve endings or cell capable of contracting.
Magnetic fields, influencing the ions moving within the body by means of Lorentz forces, applied perpendicularly to the direction of ion streams and the direction of magnetic field forces’ lines, cause deflexion of the ion stream, as well as the direction of lines of magnetic field forces, thus causing the phenomenon of deflexion of paths along which negative and positive ions move, in opposite directions. Moreover, ions gather in the vicinity of biological barriers, e.g. cell membranes in magnetic field, as a result of which ion polarization occurs (in accordance with the phenomenon of ion cyclotrone resonance – ICR) and change in the ion diffusion rate between the inside area of the cell and the intercellular space. A consequence of the above-mentioned phenomena is a change in intercellular concentration of ion, sodium, and potassium ions, among others, which has significant influence upon the intensity of numerous metabolic processes and the speed of nerve conductivity.
Other published studies indicate that the application of low-frequency magnetic fields is conducive to the regeneration of tissues damaged in accidents, thermal traumas, or due to other factors that impair the continuity of the tissues.
One of the most fruitful contexts in which to study electric phenomena in regeneration is that of the vertebrate limb. When a limb is amputated, an injury current appears, which is thought to induce dedifferentiation into or activation of blastema cells. It further serves to pattern the limb forming from these cells by attracting neuronal growth and providing spatial information for cells migrating into the new limb.
It is necessary to determine to what extent it is profitable to understand EM field interactions with organisms as information, rather than mechanical influence. A related issue is the possible interaction between the level of complexity of a given biosystem and the degree of involvement of bioelectromagnetic phenomena. This is hinted at, for example, by the observation that to achieve the same effects, greater magnetic fields must be used on individual cells and tissues than on the whole organism.
What is the effect of epigenetic markers on redundancy in GRNs? #
The available evidence suggests that DNA methylation may tip the balance to favor the expression of plasticity-associated genes by inhibiting the activity of memory-suppressor genes.
Overall, these findings indicate that a precise pattern of chromatin modifications in the nucleus is established in response to upstream signaling cascades, although the role of specific enzymes and modifications of specific sites in learning and memory need to be better elucidated. Based on their position downstream of environmental stimuli and the associated signaling cascades, epigenetic mechanisms are well suited to integrate the upstream signaling information and translate it into gene-specific transcriptional regulation.
It is now evident that integration and regulation of epigenetic modifications allows for complex control of gene expression necessary for long-term memory formation and maintenance. Dynamic changes in DNA methylation and chromatin structure are the result of well-established intracellular signaling cascades that converge on the nucleus to adjust the precise equilibrium of gene repression and activation.
Presumably, regulation of certain genes will lead to consolidation of synaptic plasticity via the regulation of synaptic effector molecules, whereas other genes might be better positioned to regulate the intrinsic excitability of a cell via modulation of Na+ and K+ channel functions.
Is the buildup of epigenetic markers downstream of intercellular communication mechanisms? #
It has become clear that in various biological processes, connexin transcription network is modulated by a combination of multiple transcription factors, histone modifications, and microRNAs. However, how the interaction between these regulatory mechanisms takes place is still an open question.
- Connexin is the protein that codes for gap junctions in cells. The fact that it’s production is modulated by GRN layer transcription is an example of the multi-scale feedback loop at work between that happens at the individual cell level and the multicellular level.
Long-Term, Stochastic Editing of Regenerative Anatomy via Targeting Endogenous Bioelectric Gradients15 #
DH regenerative target morphology could be stored via a change in the bodywide distribution of cellular resting potentials, especially because 8-OH has been shown to alter bioelectric prepatterns by generating more isopotential regions of Vmem patterning in planaria.
The altered regenerative anatomical pattern encoded in the planarian body can be forced back to a WT state by resetting the bioelectrical circuit—the stable voltage prepattern is functionally determinative of regeneration outcome.
Given that the voltage change induces complete second heads and resets the DH phenotype to produce tails, it is very likely that these instructive voltage changes lie upstream of the endogenous gene networks that are needed to build a head (86). Bioelectric signaling operates in concert with downstream target genes and chromatin modifications. Thus, it is likely that additional components of the DH effect may include other epigenetic mechanisms that integrate with bioelectrics to define outcomes above the cell level.
As recognized from Turing onward, the implementation of memory signals such as postulated here requires dynamic interaction, either in the form of competition between short- and long-range signals, resonance as implemented in many neural network models, enzymatic amplification of reaction rates, or some other energy-consuming process.
“It is crucial to pursue the understanding of stable physiological circuits with developmental endpoints, which may provide important sources of epigenetic plasticity and interact with biochemical properties encoded by the genome.
Mechanisms for transduction of voltage gradients and ion flows into second-messenger cascades and changes of gene expression include: conformational changes in integrin signaling, activation of calcium influx through voltage gated calcium channels, regulation of small morphogen movement in and out of cells by voltage-powered transporters, and voltage regulation of phosphatase activity.
Such permanent resetting of anatomical structure from a transient, physiological (not genomic)perturbation suggests the possibility that epigenetic modification may be involved in control of regenerative pattern formation.
If epigenetic mechanisms are important for guiding regeneration, how might these mechanisms link to upstream bioelectric controls? One system in which such a pathway has been elucidated is the orientation of the early embryonic left-right axis by an endogenous Left to Right voltage gradient. Recent work demonstrated that a histone de-acetylation mechanism converts the very early voltage gradient into asymmetric gene expression at much later stages by rightward electrophoretic transport of serotonin—a cofactor for a histone deacetylase.
sirtuins are HDACs #
Sir2, an HDAC known to promote longevity, deacetylates H4K16Ac and increases yeast lifespan.
Sodium butyrate and suberanilohydroxamic acid, HDAC inhibitors that increase global H3K27ac, downregulated age-upregulated genes and upregulated age-downregulated genes, restoring homeostasis in the mouse brain.
Given the large number of biological substrates affected by sirtuins, the identification of precise and disease-relevant molecular targets is a challenging goal. Multiple HDACs have been shown to influence the course of diseases; however, the degree to which their molecular activities can be coordinated has not been fully characterized. Evaluating the safety and efficacy of small molecules that can modulate sirtuin activity will be important elements in the development of new therapies to treat neurodegenerative diseases.
Moreover, pharmacological reduction of HDAC activity using the inhibitor, sodium butyrate, also induced heterotaxia, characterized by increased histoneacetylation and aberrant expression of the conservedleft-right asymmetry marker, Nodal related 1 (Xnr-1) gene.
Transmembrane voltage potential of somatic cells controls oncogene-mediated tumorigenesis at long-range19 #
These data suggest that the control of tumorigenesis by Vmem is mediated by HDAC1, via butyrate derived from gram-positive bacteria.
In academic work, please cite this essay as:
Anderson, Benjamin, “Bioelectricity as a Causal Factor in Aging”, TheBenjam.in (2022-07-23), available at https://www.thebenjam.in/research/.
Javier Cervera, Alexis Pietak, Michael Levin, Salvador Mafe, Bioelectrical coupling in multicellular domains regulated by gap junctions: A conceptual approach, Bioelectrochemistry, Volume 123, 2018, Pages 45-61, ISSN 1567-5394, https://doi.org/10.1016/j.bioelechem.2018.04.013 ↩︎
Pezzulo Giovanni and Levin Michael 2016 Top-down models in biology: explanation and control of complex living systems above the molecular levelJ. R. Soc. Interface.132016055520160555. https://doi.org/10.1098/rsif.2016.0555 ↩︎
A Meta-Analysis of Bioelectric Data in Cancer, Embryogenesis, and Regeneration Pranjal Srivastava, Anna Kane, Christina Harrison, and Michael Levin Bioelectricity 2021 3:1, 42-67 https://doi.org/10.1089/bioe.2019.0034 ↩︎
Friston Karl, Levin Michael, Sengupta Biswa and Pezzulo Giovanni 2015Knowing one’s place: a free-energy approach to pattern regulationJ. R. Soc. Interface.122014138320141383. http://doi.org/10.1098/rsif.2014.1383 ↩︎
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Jarosław Pasek, Tomasz Pasek, Karolina Sieroń-Stołtny, Grzegorz Cieślar & Aleksander Sieroń (2016) Electromagnetic fields in medicine – The state of art, Electromagnetic Biology and Medicine, 35:2, 170-175, DOI: 10.3109/15368378.2015.1048549 ↩︎
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