Cancer as a disorder of patterning information: computational and biophysical perspectives on the cancer problem

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.

Collective intelligence: A unifying concept for integrating biology across scales and substrates

A defining feature of biology is the use of a multiscale architecture, ranging from molecular networks to cells, tissues, organs, whole bodies, and swarms. Crucially however, biology is not only nested structurally, but also functionally: each level is able to solve problems in distinct problem spaces, such as physiological, morphological, and behavioral state space. Percolating adaptive functionality from one level of competent subunits to a higher functional level of organization requires collective dynamics: multiple components must work together to achieve specific outcomes. Here we overview a number of biological examples at different scales which highlight the ability of cellular material to make decisions that implement cooperation toward specific homeodynamic endpoints, and implement collective intelligence by solving problems at the cell, tissue, and whole-organism levels. We explore the hypothesis that collective intelligence is not only the province of groups of animals, and that an important symmetry exists between the behavioral science of swarms and the competencies of cells and other biological systems at different scales. We then briefly outline the implications of this approach, and the possible impact of tools from the field of diverse intelligence for regenerative medicine and synthetic bioengineering.

Biophysical control of plasticity and patterning in regeneration and cancer

Cells and tissues display a remarkable range of plasticity and tissue-patterning activities that are emergent of complex signaling dynamics within their microenvironments. These properties, which when operating normally guide embryogenesis and regeneration, become highly disordered in diseases such as cancer. While morphogens and other molecular factors help determine the shapes of tissues and their patterned cellular organization, the parallel contributions of biophysical control mechanisms must be considered to accurately predict and model important processes such as growth, maturation, injury, repair, and senescence. We now know that mechanical, optical, electric, and electromagnetic signals are integral to cellular plasticity and tissue patterning. Because biophysical modalities underly interactions between cells and their extracellular matrices, including cell cycle, metabolism, migration, and differentiation, their applications as tuning dials for regenerative and anti-cancer therapies are being rapidly exploited. Despite this, the importance of cellular communication through biophysical signaling remains disproportionately underrepresented in the literature. Here, we provide a review of biophysical signaling modalities and known mechanisms that initiate, modulate, or inhibit plasticity and tissue patterning in models of regeneration and cancer. We also discuss current approaches in biomedical engineering that harness biophysical control mechanisms to model, characterize, diagnose, and treat disease states.

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

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

Cellular signaling pathways as plastic, proto-cognitive systems: Implications for biomedicine

Many aspects of health and disease are modeled using the abstraction of a "pathway"-a set of protein or other subcellular activities with specified functional linkages between them. This metaphor is a paradigmatic case of a deterministic, mechanistic framework that focuses biomedical intervention strategies on altering the members of this network or the up-/down-regulation links between them-rewiring the molecular hardware. However, protein pathways and transcriptional networks exhibit interesting and unexpected capabilities such as trainability (memory) and information processing in a context-sensitive manner. Specifically, they may be amenable to manipulation via their history of stimuli (equivalent to experiences in behavioral science). If true, this would enable a new class of biomedical interventions that target aspects of the dynamic physiological "software" implemented by pathways and gene-regulatory networks. Here, we briefly review clinical and laboratory data that show how high-level cognitive inputs and mechanistic pathway modulation interact to determine outcomes in vivo. Further, we propose an expanded view of pathways from the perspective of basal cognition and argue that a broader understanding of pathways and how they process contextual information across scales will catalyze progress in many areas of physiology and neurobiology. We argue that this fuller understanding of the functionality and tractability of pathways must go beyond a focus on the mechanistic details of protein and drug structure to encompass their physiological history as well as their embedding within higher levels of organization in the organism, with numerous implications for data science addressing health and disease. Exploiting tools and concepts from behavioral and cognitive sciences to explore a proto-cognitive metaphor for the pathways underlying health and disease is more than a philosophical stance on biochemical processes; at stake is a new roadmap for overcoming the limitations of today's pharmacological strategies and for inferring future therapeutic interventions for a wide range of disease states.

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.

Morphoceuticals: perspectives for discovery of drugs targeting anatomical control mechanisms in regenerative medicine, cancer and aging

Morphoceuticals are a new class of interventions that target the setpoints of anatomical homeostasis for efficient, modular control of growth and form. Here, we focus on a subclass: electroceuticals, which specifically target the cellular bioelectrical interface. Cellular collectives in all tissues form bioelectrical networks via ion channels and gap junctions that process morphogenetic information, controlling gene expression and allowing cell networks to adaptively and dynamically control growth and pattern formation. Recent progress in understanding this physiological control system, including predictive computational models, suggests that targeting bioelectrical interfaces can control embryogenesis and maintain shape against injury, senescence and tumorigenesis. We propose a roadmap for drug discovery focused on manipulating endogenous bioelectric signaling for regenerative medicine, cancer suppression and antiaging therapeutics. Teaser: By taking advantage of the native problem-solving competencies of cells and tissues, a new kind of top-down approach to biomedicine becomes possible. Bioelectricity offers an especially tractable interface for interventions targeting the software of life for regenerative medicine applications.

Information Theory as an Experimental Tool for Integrating Disparate Biophysical Signaling Modules

There is a growing appreciation in the fields of cell biology and developmental biology that cells collectively process information in time and space. While many powerful molecular tools exist to observe biophysical dynamics, biologists must find ways to quantitatively understand these phenomena at the systems level. Here, we present a guide for the application of well-established information theory metrics to biological datasets and explain these metrics using examples from cell, developmental and regenerative biology. We introduce a novel computational tool named after its intended purpose, calcium imaging, (CAIM) for simple, rigorous application of these metrics to time series datasets. Finally, we use CAIM to study calcium and cytoskeletal actin information flow patterns between Xenopus laevis embryonic animal cap stem cells. The tools that we present here should enable biologists to apply information theory to develop a systems-level understanding of information processing across a diverse array of experimental systems.

A computational model of organism development and carcinogenesis resulting from cells' bioelectric properties and communication

A sound theory of biological organization is clearly missing for a better interpretation of observational results and faster progress in understanding life complexity. The availability of such a theory represents a fundamental progress in explaining both normal and pathological organism development. The present work introduces a computational implementation of some principles of a theory of organism development, namely that the default state of cells is proliferation and motility, and includes the principle of variation and organization by closure of constraints. In the present model, the bioelectric context of cells and tissue is the field responsible for organization, as it regulates cell proliferation and the level of communication driving the system’s evolution. Starting from a depolarized (proliferative) cell, the organism grows to a certain size, limited by the increasingly polarized state after successive proliferation events. The system reaches homeostasis, with a depolarized core (proliferative cells) surrounded by a rim of polarized cells (non-proliferative in this condition). This state is resilient to cell death (random or due to injure) and to limited depolarization (potentially carcinogenic) events. Carcinogenesis is introduced through a localized event (a spot of depolarized cells) or by random depolarization of cells in the tissue, which returns cells to their initial proliferative state. The normalization of the bioelectric condition can reverse this out-of-equilibrium state to a new homeostatic one. This simplified model of embryogenesis, tissue organization and carcinogenesis, based on non-excitable cells’ bioelectric properties, can be made more realistic with the introduction of other components, like biochemical fields and mechanical interactions, which are fundamental for a more faithful representation of reality. However, even a simple model can give insight for new approaches in complex systems and suggest new experimental tests, focused in its predictions and interpreted under a new paradigm.

Multi-scale Chimerism: An experimental window on the algorithms of anatomical control

Despite the immense progress in genetics and cell biology, major knowledge gaps remain with respect to prediction and control of the global morphologies that will result from the cooperation of cells with known genomes. The understanding of cooperativity, competition, and synergy across diverse biological scales has been obscured by a focus on standard model systems that exhibit invariant species-specific anatomies. Morphogenesis of chimeric biological material is an especially instructive window on the control of biological growth and form because it emphasizes the need for prediction without reliance on familiar, standard outcomes. Here, we review an important and fascinating body of data from experiments utilizing DNA transfer, cell transplantation, organ grafting, and parabiosis. We suggest that these are all instances (at different levels of organization) of one general phenomenon: chimerism. Multi-scale chimeras are a powerful conceptual and experimental tool with which to probe the mapping between properties of components and large-scale anatomy: the laws of morphogenesis. The existing data and future advances in this field will impact not only the understanding of cooperation and the evolution of body forms, but also the design of strategies for system-level outcomes in regenerative medicine and swarm robotics.

When left does not seem right: epigenetic and bioelectric differences between left- and right-sided breast cancer

Background

During embryogenesis lateral symmetry is broken, giving rise to Left/Right (L/R) breast tissues with distinct identity. L/R-sided breast tumors exhibit consistently-biased incidence, gene expression, and DNA methylation. We postulate that a differential L/R tumor-microenvironment crosstalk generates different tumorigenesis mechanisms.

Methods

We performed in-silico analyses on breast tumors of public datasets, developed xenografted tumors, and conditioned MDA-MB-231 cells with L/R mammary extracts.

Results

We found L/R differential DNA methylation involved in embryogenic and neuron-like functions. Focusing on ion-channels, we discovered significant L/R epigenetic and bioelectric differences. Specifically, L-sided cells presented increased methylation of hyperpolarizing ion channel genes and increased Ca²⁺ concentration and depolarized membrane potential, compared to R-ones. Functional consequences were associated with increased proliferation in left tumors, assessed by KI67 expression and mitotic count.

Conclusions

Our findings reveal considerable L/R asymmetry in cancer processes, and suggest specific L/R epigenetic and bioelectric differences as future targets for cancer therapeutic approaches in the breast and many other paired organs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00440-5.

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.

Close to Optimal Cell Sensing Ensures the Robustness of Tissue Differentiation Process: The Avian Photoreceptor Mosaic Case

The way that progenitor cell fate decisions and the associated environmental sensing are regulated to ensure the robustness of the spatial and temporal order in which cells are generated towards a fully differentiating tissue still remains elusive. Here, we investigate how cells regulate their sensing intensity and radius to guarantee the required thermodynamic robustness of a differentiated tissue. In particular, we are interested in finding the conditions where dedifferentiation at cell level is possible (microscopic reversibility), but tissue maintains its spatial order and differentiation integrity (macroscopic irreversibility). In order to tackle this, we exploit the recently postulated Least microEnvironmental Uncertainty Principle (LEUP) to develop a theory of stochastic thermodynamics for cell differentiation. To assess the predictive and explanatory power of our theory, we challenge it against the avian photoreceptor mosaic data. By calibrating a single parameter, the LEUP can predict the cone color spatial distribution in the avian retina and, at the same time, suggest that such a spatial pattern is associated with quasi-optimal cell sensing. By means of the stochastic thermodynamics formalism, we find out that thermodynamic robustness of differentiated tissues depends on cell metabolism and cell sensing properties. In turn, we calculate the limits of the cell sensing radius that ensure the robustness of differentiated tissue spatial order. Finally, we further constrain our model predictions to the avian photoreceptor mosaic.

A bioelectric model of carcinogenesis, including propagation of cell membrane depolarization and reversal therapies

As the main theory of carcinogenesis, the Somatic Mutation Theory, increasingly presents difficulties to explain some experimental observations, different theories are being proposed. A major alternative approach is the Tissue Organization Field Theory, which explains cancer origin as a tissue regulation disease instead of having a mainly cellular origin. This work fits in the latter hypothesis, proposing the bioelectric field, in particular the cell membrane polarization state, and ionic exchange through ion channels and gap junctions, as an important mechanism of cell communication and tissue organization and regulation. Taking into account recent experimental results and proposed bioelectric models, a computational model of cancer initiation was developed, including the propagation of a cell depolarization wave in the tissue under consideration. Cell depolarization leads to a change in its state, with the activation and deactivation of several regulation pathways, increasing cell proliferation and motility, changing its epigenetic state to a more stem cell-like behavior without the requirement of genomic mutation. The intercellular communication via gap junctions leads, in certain circumstances, to a bioelectric state propagation to neighbor cells, in a chain-like reaction, till an electric discontinuity is reached. However, this is a reversible process, and it was shown experimentally that, by implementing a therapy targeted on cell ion exchange channels, it is possible to reverse the state and repolarize cells. This mechanism can be an important alternative way in cancer prevention, diagnosis and therapy, and new experiments are proposed to test the presented hypothesis.

Cancer progression as a sequence of atavistic reversions

It has long been recognized that cancer onset and progression represent a type of reversion to an ancestral quasi-unicellular phenotype. This general concept has been refined into the atavistic model of cancer that attempts to provide a quantitative analysis and testable predictions based on genomic data. Over the past decade, support for the multicellular-to-unicellular reversion predicted by the atavism model has come from phylostratigraphy. Here, we propose that cancer onset and progression involve more than a one-off multicellular-to-unicellular reversion, and are better described as a series of reversionary transitions. We make new predictions based on the chronology of the unicellular-eukaryote-to-multicellular-eukaryote transition. We also make new predictions based on three other evolutionary transitions that occurred in our lineage: eukaryogenesis, oxidative phosphorylation and the transition to adaptive immunity. We propose several modifications to current phylostratigraphy to improve age resolution to test these predictions. Also see the video abstract here: https://youtu.be/3unEu5JYJrQ.

Biology transcends the limits of computation

Cognition-sensing and responding to the environment-is the unifying principle behind the genetic code, origin of life, evolution, consciousness, artificial intelligence, and cancer. However, the conventional model of biology seems to mistake cause and effect. According to the reductionist view, the causal chain in biology is chemicals → code → cognition. Despite this prevailing view, there are no examples in the literature to show that the laws of physics and chemistry can produce codes, or that codes produce cognition. Chemicals are just the physical layer of any information system. In contrast, although examples of cognition generating codes and codes controlling chemicals are ubiquitous in biology and technology, cognition remains a mystery. Thus, the central question in biology is: What is the nature and origin of cognition? In order to elucidate this pivotal question, we must cultivate a deeper understanding of information flows. Through this lens, we see that biological cognition is volitional (i.e., deliberate, intentional, or knowing), and while technology is constrained by deductive logic, living things make choices and generate novel information using inductive logic. Information has been called "the hard problem of life' and cannot be fully explained by known physical principles (Walker et al., 2017). The present paper uses information theory (the mathematical foundation of our digital age) and Turing machines (computers) to highlight inaccuracies in prevailing reductionist models of biology, and proposes that the correct causation sequence is cognition → code → chemicals.

Bioelectrical approaches to cancer as a problem of the scaling of the cellular self

One lens with which to understand the complex phenomenon of cancer is that of developmental biology. Cancer is the inevitable consequence of a breakdown of the communication that enables individual cells to join into computational networks that work towards large-scale, morphogenetic goals instead of more primitive, unicellular objectives. This perspective suggests that cancer may be a physiological disorder, not necessarily due to problems with the genetically-specified protein hardware. One aspect of morphogenetic coordination is bioelectric signaling, and indeed an abnormal bioelectric signature non-invasively reveals the site of incipient tumors in amphibian models. Functionally, a disruption of resting potential states triggers metastatic melanoma phenotypes in embryos with no genetic defects or carcinogen exposure. Conversely, optogenetic or molecular-biological modulation of bioelectric states can override powerful oncogenic mutations and prevent or normalize tumors. The bioelectrically-mediated information flows that harness cells toward body-level anatomical outcomes represent a very attractive and tractable endogenous control system, which is being targeted by emerging approaches to cancer.

Bistability of somatic pattern memories: stochastic outcomes in bioelectric circuits underlying regeneration

Nervous systems' computational abilities are an evolutionary innovation, specializing and speed-optimizing ancient biophysical dynamics. Bioelectric signalling originated in cells' communication with the outside world and with each other, enabling cooperation towards adaptive construction and repair of multicellular bodies. Here, we review the emerging field of developmental bioelectricity, which links the field of basal cognition to state-of-the-art questions in regenerative medicine, synthetic bioengineering and even artificial intelligence. One of the predictions of this view is that regeneration and regulative development can restore correct large-scale anatomies from diverse starting states because, like the brain, they exploit bioelectric encoding of distributed goal states-in this case, pattern memories. We propose a new interpretation of recent stochastic regenerative phenotypes in planaria, by appealing to computational models of memory representation and processing in the brain. Moreover, we discuss novel findings showing that bioelectric changes induced in planaria can be stored in tissue for over a week, thus revealing that somatic bioelectric circuits in vivo can implement a long-term, re-writable memory medium. A consideration of the mechanisms, evolution and functionality of basal cognition makes novel predictions and provides an integrative perspective on the evolution, physiology and biomedicine of information processing in vivo. This article is part of the theme issue 'Basal cognition: multicellularity, neurons and the cognitive lens'.

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.

Science-Driven Societal Transformation, Part III: Design

Climate change, biodiversity loss, and other major social and environmental problems pose severe risks. Progress has been inadequate and scientists, global policy experts, and the general public increasingly conclude that transformational change is needed across all sectors of society in order to improve and maintain social and ecological wellbeing. At least two paths to transformation are conceivable: (1) reform of and innovation within existing societal systems (e.g., economic, legal, and governance systems); and (2) the de novo development of and migration to new and improved societal systems. This paper is the final in a three-part series of concept papers that together outline a novel science-driven research and development program aimed at the second path. It summarizes literature to build a narrative on the topic of de novo design of societal systems. The purpose is to raise issues, suggest design possibilities, and highlight directions and questions that could be explored in the context of this or any R&D program aimed at new system design. This paper does not present original research, but rather provides a synthesis of selected ideas from the literature. Following other papers in the series, a society is viewed as a superorganism and its societal systems as a cognitive architecture. Accordingly, a central goal of design is to improve the collective cognitive capacity of a society, rendering it more capable of achieving and sustainably maintaining vitality. Topics of attention, communication, self-identity, power, and influence are discussed in relation to societal cognition and system design. A prototypical societal system is described, and some design considerations are highlighted.

Emergence of informative higher scales in biological systems: a computational toolkit for optimal prediction and control

The biological sciences span many spatial and temporal scales in attempts to understand the function and evolution of complex systems-level processes, such as embryogenesis. It is generally assumed that the most effective description of these processes is in terms of molecular interactions. However, recent developments in information theory and causal analysis now allow for the quantitative resolution of this question. In some cases, macro-scale models can minimize noise and increase the amount of information an experimenter or modeler has about "what does what." This result has numerous implications for evolution, pattern regulation, and biomedical strategies. Here, we provide an introduction to these quantitative techniques, and use them to show how informative macro-scales are common across biology. Our goal is to give biologists the tools to identify the maximally-informative scale at which to model, experiment on, predict, control, and understand complex biological systems.

Scale-Free Biology: Integrating Evolutionary and Developmental Thinking

When the history of life on earth is viewed as a history of cell division, all of life becomes a single cell lineage. The growth and differentiation of this lineage in reciprocal interaction with its environment can be viewed as a developmental process; hence the evolution of life on earth can also be seen as the development of life on earth. Here, in reviewing this field, some potentially fruitful research directions suggested by this change in perspective are highlighted. Variation and selection become, for example, bidirectional information flows between scales, while the notions of "cooperation" and "competition" become scale relative. The language of communication, inference, and information processing becomes more useful than the language of causation to describe the interactions of both homogeneous and heterogeneous living systems at any scale. Emerging scale-free theoretical frameworks such as predictive coding and active inference provide conceptual tools for reconceptualizing biology as the study of a unified, multiscale dynamical system.

Post-SSRI Sexual Dysfunction: A Bioelectric Mechanism?

Selective serotonin reuptake inhibitor (SSRI) drugs, targeting serotonin transport, are widely used. A puzzling and biomedically important phenomenon concerns the persistent sexual dysfunction following SSRI use seen in some patients. What could be the mechanism of a persistent physiological state brought on by a transient exposure to serotonin transport blockers? In this study, we briefly review the clinical facts concerning this side effect of serotonin reuptake inhibitors and suggest a possible mechanism. Bioelectric circuits (among neural or non-neural cells) could persistently maintain alterations of bioelectric cell properties (resting potential), resulting in long-term changes in electrophysiology and signaling. We present new data revealing this phenomenon in planarian flatworms, in which brief SSRI exposures induce long-lasting changes in resting potential profile. We also briefly review recent data linking neurotransmitter signaling to developmental bioelectrics. Further study of tissue bioelectric memory could enable the design of ionoceutical interventions to counteract side effects of SSRIs and similar drugs.

Morphological Coordination: A Common Ancestral Function Unifying Neural and Non-Neural Signaling

Nervous systems are traditionally thought of as providing sensing and behavioral coordination functions at the level of the whole organism. What is the evolutionary origin of the mechanisms enabling the nervous systems’ information processing ability? Here, we review evidence from evolutionary, developmental, and regenerative biology suggesting a deeper, ancestral function of both pre-neural and neural cell-cell communication systems: the long-distance coordination of cell division and differentiation required to create and maintain body-axis symmetries. This conceptualization of the function of nervous system activity sheds new light on the evolutionary transition from the morphologically rudimentary, non-neural Porifera and Placazoa to the complex morphologies of Ctenophores, Cnidarians, and Bilaterians. It further allows a sharp formulation of the distinction between long-distance axis-symmetry coordination based on external coordinates, e.g., by whole-organism scale trophisms as employed by plants and sessile animals, and coordination based on body-centered coordinates as employed by motile animals. Thus we suggest that the systems that control animal behavior evolved from ancient mechanisms adapting preexisting ionic and neurotransmitter mechanisms to regulate individual cell behaviors during morphogenesis. An appreciation of the ancient, non-neural origins of bioelectrically mediated computation suggests new approaches to the study of embryological development, including embryological dysregulation, cancer, regenerative medicine, and synthetic bioengineering.

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.

Bioelectric Control of Metastasis in Solid Tumors

As the leading cause of death in cancer, there is an urgent need to develop treatments to target the dissemination of primary tumor cells to secondary organs, known as metastasis. Bioelectric signaling has emerged in the last century as an important controller of cell growth, and with the development of current molecular tools we are now beginning to identify its role in driving cell migration and metastasis in a variety of cancer types. This review summarizes the currently available research for bioelectric signaling in solid tumor metastasis. We review the steps of metastasis and discuss how these can be controlled by bioelectric cues at the level of a cell, a population of cells, and the tissue. The role of ion channel, pump, and exchanger activity and ion flux is discussed, along with the importance of the membrane potential and the relationship between ion flux and membrane potential. We also provide an overview of the evidence for control of metastasis by external electric fields (EFs) and draw from examples in embryogenesis and regeneration to discuss the implications for endogenous EFs. By increasing our understanding of the dynamic properties of bioelectric signaling, we can develop new strategies that target metastasis to be translated into the clinic.

Somatic multicellularity as a satisficing solution to the prediction-error minimization problem

Adaptive success in the biosphere requires the dynamic ability to adjust physiological, transcriptional, and behavioral responses to environmental conditions. From chemical networks to organisms to whole communities, biological entities at all levels of organization seek to optimize their predictive power. Here, we argue that this fundamental drive provides a novel perspective on the origin of multicellularity. One way for unicellular organisms to minimize surprise with respect to external inputs is to be surrounded by reproductively-disabled, i.e. somatic copies of themselves – highly predictable agents which in effect reduce uncertainty in their microenvironments. We show that the transition to multicellularity can be modeled as a phase transition driven by environmental threats. We present modeling results showing how multicellular bodies can arise if non-reproductive somatic cells protect their reproductive parents from environmental lethality. We discuss how a somatic body can be interpreted as a Markov blanket around one or more reproductive cells, and how the transition to somatic multicellularity can be represented as a transition from exposure of reproductive cells to a high-uncertainty environment to their protection from environmental uncertainty by this Markov blanket. This is, effectively, a transition by the Markov blanket from transparency to opacity for the variational free energy of the environment. We suggest that the ability to arrest the cell cycle of daughter cells and redirect their resource utilization from division to environmental threat amelioration is the key innovation of obligate multicellular eukaryotes, that the nervous system evolved to exercise this control over long distances, and that cancer is an escape by somatic cells from the control of reproductive cells. Our quantitative model illustrates the evolutionary dynamics of this system, provides a novel hypothesis for the origin of multicellular animal bodies, and suggests a fundamental link between the architectures of complex organisms and information processing in proto-cognitive cellular agents.

Morphogenesis as Bayesian inference: A variational approach to pattern formation and control in complex biological systems

Recent advances in molecular biology such as gene editing [1], bioelectric recording and manipulation [2] and live cell microscopy using fluorescent reporters [3], [4] - especially with the advent of light-controlled protein activation through optogenetics [5] - have provided the tools to measure and manipulate molecular signaling pathways with unprecedented spatiotemporal precision. This has produced ever increasing detail about the molecular mechanisms underlying development and regeneration in biological organisms. However, an overarching concept - that can predict the emergence of form and the robust maintenance of complex anatomy - is largely missing in the field. Classic (i.e., dynamic systems and analytical mechanics) approaches such as least action principles are difficult to use when characterizing open, far-from equilibrium systems that predominate in Biology. Similar issues arise in neuroscience when trying to understand neuronal dynamics from first principles. In this (neurobiology) setting, a variational free energy principle has emerged based upon a formulation of self-organization in terms of (active) Bayesian inference. The free energy principle has recently been applied to biological self-organization beyond the neurosciences [6], [7]. For biological processes that underwrite development or regeneration, the Bayesian inference framework treats cells as information processing agents, where the driving force behind morphogenesis is the maximization of a cell's model evidence. This is realized by the appropriate expression of receptors and other signals that correspond to the cell's internal (i.e., generative) model of what type of receptors and other signals it should express. The emerging field of the free energy principle in pattern formation provides an essential quantitative formalism for understanding cellular decision-making in the context of embryogenesis, regeneration, and cancer suppression. In this paper, we derive the mathematics behind Bayesian inference - as understood in this framework - and use simulations to show that the formalism can reproduce experimental, top-down manipulations of complex morphogenesis. First, we illustrate this 'first principle' approach to morphogenesis through simulated alterations of anterior-posterior axial polarity (i.e., the induction of two heads or two tails) as in planarian regeneration. Then, we consider aberrant signaling and functional behavior of a single cell within a cellular ensemble - as a first step in carcinogenesis as false 'beliefs' about what a cell should 'sense' and 'do'. We further show that simple modifications of the inference process can cause - and rescue - mis-patterning of developmental and regenerative events without changing the implicit generative model of a cell as specified, for example, by its DNA. This formalism offers a new road map for understanding developmental change in evolution and for designing new interventions in regenerative medicine settings.

The Cognitive Lens: a primer on conceptual tools for analysing information processing in developmental and regenerative morphogenesis

Brains exhibit plasticity, multi-scale integration of information, computation and memory, having evolved by specialization of non-neural cells that already possessed many of the same molecular components and functions. The emerging field of basal cognition provides many examples of decision-making throughout a wide range of non-neural systems. How can biological information processing across scales of size and complexity be quantitatively characterized and exploited in biomedical settings? We use pattern regulation as a context in which to introduce the Cognitive Lens-a strategy using well-established concepts from cognitive and computer science to complement mechanistic investigation in biology. To facilitate the assimilation and application of these approaches across biology, we review tools from various quantitative disciplines, including dynamical systems, information theory and least-action principles. We propose that these tools can be extended beyond neural settings to predict and control systems-level outcomes, and to understand biological patterning as a form of primitive cognition. We hypothesize that a cognitive-level information-processing view of the functions of living systems can complement reductive perspectives, improving efficient top-down control of organism-level outcomes. Exploration of the deep parallels across diverse quantitative paradigms will drive integrative advances in evolutionary biology, regenerative medicine, synthetic bioengineering, cognitive neuroscience and artificial intelligence. This article is part of the theme issue 'Liquid brains, solid brains: How distributed cognitive architectures process information'.

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

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.

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.