Article

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

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  • Institute for Problems in Mechanical Engineering of the Russian Academy of Sciences
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Abstract

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

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... The gap junctions between single cells modulate the rules that instruct pattern regulation [38]. Experimentally, the functional inhibition of the gap junctions connecting neighboring cells can be achieved either by injecting a specific factor that targets connexins or by post-translational blocking with an external agent [40]. These processes can be simulated here by weakening the local rules. ...
... However, the outcome to be expected in each experimental case is context-dependent in the sense that it depends not only on the signaling molecule transferred but also on the particular states of the neighboring cells [39]. coupling intensity (e.g., by gap junction blockers [39,40]). ...
... However, the intercellular junctions have context-dependent roles and may show pro-and anti-proliferative effects depending on the particular cell states and the information to be transferred [39,40]. The rich diversity of results obtained with models I and II suggests the difficulty of attempting to normalize domains of abnormal cells by restoring weakened local rules: a detailed knowledge of the dominant local rules is necessary to achieve the desired outcomes. ...
Preprint
We present a weakly coupled map lattice model for patterning that explores the effects exerted by weakening the local dynamic rules on model biological and artificial networks composed of two-state building blocks (cells). To this end, we use two cellular automata models based on: (i) a smooth majority rule (model I) and (ii) a set of rules similar to those of Conway's Game of Life (model II). The normal and abnormal cell states evolve according with local rules that are modulated by a parameter κ\kappa. This parameter quantifies the effective weakening of the prescribed rules due to the limited coupling of each cell to its neighborhood and can be experimentally controlled by appropriate external agents. The emergent spatio-temporal maps of single-cell states should be of significance for positional information processes as well as for intercellular communication in tumorigenesis where the collective normalization of abnormal single-cell states by a predominantly normal neighborhood may be crucial.
... Experimentally, bioelectrical cell states can be instructive for biochemical downstream processes 5,[24][25][26][27][28] . Multicellular potentials convey short-term bioelectrical information to long-term transcriptional processes due to the coupling between the electric potentials and the spatio-temporal distributions of signaling ions (e.g., calcium) and molecules (e.g., serotonin) 5 . ...
... In model animals, voltage-sensitive dyes evidence that distinct anterior-posterior morphologies can be obtained by changing the axial electric potential 24,25 , which is locally regulated by the ion channel conductances. The intercellular gap junctions, which couple cells into electrical networks 29,30 , can also be important for adaptive phenomena: different planarian head morphologies are observed after junction blocking by octanol 26 . Thus, our model must couple the single-cell potentials at the multicellular aggregate level. ...
... In particular, the model explicitly accounts for the coupling between the bioelectricity of three channel families and their respective genetic regulator networks, thus offering new insights into adaptation mechanisms that do not rely on neural networks 13 . Also, we pay attention to the intercellular connectivity because the adaptation involves a community effect at the multicellular scale 4,26 . Scheme 1. Model summary. ...
Article
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Cells can compensate a disruptive change in one ion channel by compensatory changes in other channels. We have simulated the adaptation of a multicellular aggregate of non-excitable cells to the electrophysiological perturbation produced by the external blocking of a cation channel. In the biophysical model employed, we consider that this blocking provokes a cell depolarization that opens a voltage-gated calcium channel, thus allowing toxic Ca²⁺ levels. The cell adaptation to this externally-induced perturbation is ascribed to the multiplicity of channels available to keep the cell membrane potential within a physiological window. We propose that the cell depolarization provokes the upregulated expression of a compensatory channel protein that resets the cell potential to the correct polarized value, which prevents the calcium entry. To this end, we use two different simulation algorithms based on deterministic and stochastic methods. The simulations suggest that because of the local correlations coupling the cell potential to transcription, short-term bioelectrical perturbations can trigger long-term biochemical adaptations to novel stressors in multicellular aggregates. Previous experimental data on planarian flatworms’ adaptation to a barium-containing environment is also discussed.
... Emergence is observed in ant-colonies [73], insect-colonies [31,74], flocks, cells [39][40][41], organs [75], bodies [2,[76][77][78], societies, and ecosystems; see [4,74,79]. Emergent structures operating within MPC systems such as CAs, ABM, and CxN. ...
... Embriogenesis [80], morphological growth [75,[81][82][83], rejuvenation and limb re-growth [71,80,[82][83][84], and cancer treatment [85]. ...
... Chemistry, bio-chemistry, self-replication [75,77], and light-induced bio-chemistry [86][87][88]. ...
Article
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Science is currently becoming aware of the challenges in the understanding of the very root mechanisms of massively parallel computations that are observed in literally all scientific disciplines, ranging from cosmology to physics, chemistry, biochemistry, and biology. This leads us to the main motivation and simultaneously to the central thesis of this review: “Can we design artificial, massively parallel, self-organized, emergent, error-resilient computational environments?” The thesis is solely studied on cellular automata. Initially, an overview of the basic building blocks enabling us to reach this end goal is provided. Important information dealing with this topic is reviewed along with highly expressive animations generated by the open-source, Python, cellular automata software GoL-N24. A large number of simulations along with examples and counter-examples, finalized by a list of the future directions, are giving hints and partial answers to the main thesis. Together, these pose the crucial question of whether there is something deeper beyond the Turing machine theoretical description of massively parallel computing. The perspective, future directions, including applications in robotics and biology of this research, are discussed in the light of known information.
... High and low absolute values of V correspond to the polarized (pol) and depolarized (dep) individual cell states [7,8,12,[25][26][27][28][29], which are regulated by the dynamic balance between channel families whose conductances aim at polarizing or depolarizing the cell, respectively. At the multicellular level, the intercellular junction conductances modulate the system connectivity [7,8,[30][31][32]. ...
... Importantly, Fig. 17 shows that similar bioelectrical patterns can be established by acting at different system levels: the individual cell channel protein transcription (Fig. 17a) and the intercellular junction conductance (Fig. 17b). The first effect can be induced by appropriate transcription factors while the second one is obtained by blocker molecules such as octanol [30]. In this context, general anesthetics are considered junction blockers that disrupt intercellular communication reversibly. ...
... The biophysical simulations presented here can also be extended to other experimental problems where diffusionreaction phenomena coexist with gap junction blocking [22,85]. In particular, the dynamics of the intercellular gap junction network can be associated with the spatial patterning of differentiation and multicellular morphology [30,31]. Fig. 7 for the transcriptional and bioelectrical feedback at the single-cell level in the case of miRNA [44,89]. ...
Article
Cells must coordinate their individual activities toward multicellular goals, which requires efficient information processing mechanisms. Bioelectrical signals encode instructive rules at multiple scales, from the individual cell to the tissue and organ levels, because patterns of cell potentials are locally coupled to transcription and morphogenesis via biochemical downstream processes. We review here biophysical models that suggest how bi-stable and oscillatory bioelectrical memories defined at the single-cell and multicellular scales can constitute pattern memories that are instructive for morphological outcomes. Multicellular aggregates are open to the external microenvironment and typically show spatio-temporal distributions of potassium and calcium ions, neurotransmitters, and specific transcription activators that are correlated with electric potential patterns. This correlation results in patterns composed of dynamic subsystems (modules) with cells that share the same bioelectrical state. The particular integration–segregation topology of the different modules defines a multicellular pattern memory. By acting on these separate modules and their particular integration, pattern memories can be retrieved or externally rewritten, with morphological consequences. Thus, the simulations give further support to recent experimental findings and suggest new opportunities for external actions at the intermediate scale characteristic of endogenous multicellular fields.
... When planarian flatworms are cut into fragments, the resulting pieces can make a complete worm following morphological mechanisms still under discussion (Cebrià et al., 2018, Pezzulo andLevin, 2016). In particular, the number, location, and shape of heads have been experimentally and theoretically studied (Bischof et al., 2020, Cervera et al., 2020a, Cervera et al. 2021a, Durant et al., 2019, Emmons-Bell et al., 2015, Owlarn and Bartscherer, 2016, Pietak and Levin., 2018, Saló et al., 2009. Distinct head-tail, no-head, and doublehead axial morphologies are observed by controlling the electric potential differences across the animal's primary (anterior-posterior) axis as evidenced by voltage-sensitive dyes (Durant et al., 2017, Durant et al., 2019. ...
... The functional importance of this bioelectrical prepattern (Beane et al., 2011, Durant et al., 2017, Durant et al., 2019, Nogi and Levin, 2005, Pezzulo et al., 2021 was shown in experiments in which the number of heads in regenerating fragments was modulated by specifically altering ion channel function or gap junctional connectivity. In addition to the number of heads (and the patterning of the primary axis), different morphologies of planarian heads, the shapes of their brain, and distributions of stem cells are obtained after gap junction (GJ) blocking caused by octanol , Emmons-Bell et al., 2015. In this case, the heads of wild-type, genomically-normal planaria can be remodeled to resemble those of different planaria species by temporarily disturbing the intercellular connectivity during regeneration (Emmons-Bell et al., 2015). ...
... In addition to the number of heads (and the patterning of the primary axis), different morphologies of planarian heads, the shapes of their brain, and distributions of stem cells are obtained after gap junction (GJ) blocking caused by octanol , Emmons-Bell et al., 2015. In this case, the heads of wild-type, genomically-normal planaria can be remodeled to resemble those of different planaria species by temporarily disturbing the intercellular connectivity during regeneration (Emmons-Bell et al., 2015). ...
Article
Head-tail planaria morphologies are influenced by the electric potential differences across the animal’s primary axis, as evidenced e.g. by voltage-sensitive dyes and functional experiments that create permanent lines of 2-headed but genetically wild-type animals. However, bioelectrical and biochemical models that make predictions on what would happen in the case of spatial chimeras made by tissue transplantation from different planaria (different species and head shapes) are lacking. Here, we use a bioelectrical model to qualitatively describe the effects of tissue transplantation on the shape of the r egenerated head. To this end, we assume that the cells may have distinct sets of ion channels and ascribe the system outcome to the axial distributions of average cell potentials over morphologically relevant regions. Our rationale is that the distributions of signaling ions and molecules are spatially coupled with multicellular electric potentials. Thus, long-time downstream transcriptional events should be triggered by short-time bioelectrical processes. We show that relatively small differences between the ion channel characteristics of the cells could eventually give noticeable changes in the electric potential profiles and the expected morphological deviations, which suggests that small but timely bioelectrical actions may have significant morphological effects. Our approach is based on the observed relationships between bioelectrical regionalization and biochemical gradients in body-plan studies. Such models are relevant to regenerative, developmental, and cancer biology in which cells with distinct properties and morphogenetic target states confront each other in the same tissue.
... More recently, the capacities of humans and other animals to navigate and behave in complex social environments has also been intensively investigated, as has the ability of humans (infants and adults) and other animals to detect intelligent agents in their environments and form a theory of mind [3]. Subcellular systems (molecular networks) navigate the transcriptional space (B), while collections of cells navigate the anatomical morphospace, such as planarian tissues that can be pushed into regions of the space corresponding to diverse species' head shapes without genomic editing (C) (image by Alexis Pietak [31]). Higher-order systems distort the energy landscapes for their subsystems (via virtual "objects" in that space) to enable their components' local homeostatic mechanisms to achieve goals that are adaptive at the higher level systems' space. ...
... The philosophical basis of our perspective has been described previously; it dates back at least to Ashby [39] and was featured prominently in the work of Maturana and Subcellular systems (molecular networks) navigate the transcriptional space (B), while collections of cells navigate the anatomical morphospace, such as planarian tissues that can be pushed into regions of the space corresponding to diverse species' head shapes without genomic editing (C) (image by Alexis Pietak [31]). Higher-order systems distort the energy landscapes for their subsystems (via virtual "objects" in that space) to enable their components' local homeostatic mechanisms to achieve goals that are adaptive at the higher level systems' space. ...
... By perturbing this system, not only can the pattern memories of the collective intelligence be altered (for example, permanently changing the number of heads that genetically wild-type planarian tissues consider to be their correct target morphology) [116,117], but they can be pushed into the regions of an anatomical state space belonging to other species. In planaria, temporary disruption of bioelectrical connectivity among cells (with no genomic editing) leads to the regeneration of heads (including brain shape and stem cell distribution) appropriate to other extant species of planaria [31,118], which are 100-150 million years apart phylogenetically. ...
Article
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One of the most salient features of life is its capacity to handle novelty and namely to thrive and adapt to new circumstances and changes in both the environment and internal components. An understanding of this capacity is central to several fields: the evolution of form and function, the design of effective strategies for biomedicine, and the creation of novel life forms via chimeric and bioengineering technologies. Here, we review instructive examples of living organisms solving diverse problems and propose competent navigation in arbitrary spaces as an invariant for thinking about the scaling of cognition during evolution. We argue that our innate capacity to recognize agency and intelligence in unfamiliar guises lags far behind our ability to detect it in familiar behavioral contexts. The multi-scale competency of life is essential to adaptive function, potentiating evolution and providing strategies for top-down control (not micromanagement) to address complex disease and injury. We propose an observer-focused viewpoint that is agnostic about scale and implementation, illustrating how evolution pivoted similar strategies to explore and exploit metabolic, transcriptional, morphological, and finally 3D motion spaces. By generalizing the concept of behavior, we gain novel perspectives on evolution, strategies for system-level biomedical interventions, and the construction of bioengineered intelligences. This framework is a first step toward relating to intelligence in highly unfamiliar embodiments, which will be essential for progress in artificial intelligence and regenerative medicine and for thriving in a world increasingly populated by synthetic, bio-robotic, and hybrid beings.
... Recent data have identified one set of mechanisms mediating the ability of the cells to make, for example, the correct number of heads: a standing bioelectrical distribution across the tissue, generated by ion channels and propagated by electrical synapses known as gap junctions (Figures 7A-D). Manipulation of the normal voltage pattern by targeting the gap junctions (Sordillo and Bargmann, 2021) or ion channels can give rise to planaria with one, two, or 0 heads, or heads with shape (and brain shape) resembling other extant species of planaria (Emmons-Bell et al., 2015;Sullivan et al., 2016). Remarkably, the worms with abnormal head number are permanently altered to this pattern, despite their wild-type genetics: cut into pieces with no further manipulations, the pieces continue to regenerate with abnormal head number (Oviedo et al., 2010;Durant et al., 2017). ...
... The process of completing a correct planarian pattern from a simple fragment can be modeled in this way, perhaps with overall stress levels instantiating the free energy that the system is trying to minimize (Kuchling et al., 2020b). Such attractors correspond to different possible morphologies, and indeed the normally robust regeneration toward a single pattern (D) can be modified in planaria by temporarily disrupting their gap junctional network, which causes genetically un-modified worms to nevertheless build heads appropriate to other species' attractors in morphospace (E) (Emmons-Bell et al., 2015;Sullivan et al., 2016). Images in panels (A,B) courtesy of Jeremy Guay of Peregrine Creative. ...
... Of course, the Self does not return immediately, as shown by the many hallucinatory (Saniova et al., 2009;Kelz et al., 2019) experiences of people coming out of general anesthesia-it takes some time for the brain to return to the correct global bioelectric state once the network connections are allowed again (meta-stability) (Rabinovich et al., 2008). Interestingly, and in line with the proposed isomorphism between cognition and morphogenesis, gap junction blockade has exactly this effect in regeneration: planaria briefly treated with GJ blocker regenerate heads of other species, but eventually snap out of it and remodel back to their correct target morphology (Emmons-Bell et al., 2015). It is no accident that the same reagents cause drastic changes in the high-level Selves in both behavioral and morphogenetic contexts: evolution uses the same scheme (GJ-mediated bioelectrical networks) to implement both. ...
Article
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Synthetic biology and bioengineering provide the opportunity to create novel embodied cognitive systems (otherwise known as minds) in a very wide variety of chimeric architectures combining evolved and designed material and software. These advances are disrupting familiar concepts in the philosophy of mind, and require new ways of thinking about and comparing truly diverse intelligences, whose composition and origin are not like any of the available natural model species. In this Perspective, I introduce TAME—Technological Approach to Mind Everywhere—a framework for understanding and manipulating cognition in unconventional substrates. TAME formalizes a non-binary (continuous), empirically-based approach to strongly embodied agency. TAME provides a natural way to think about animal sentience as an instance of collective intelligence of cell groups, arising from dynamics that manifest in similar ways in numerous other substrates. When applied to regenerating/developmental systems, TAME suggests a perspective on morphogenesis as an example of basal cognition. The deep symmetry between problem-solving in anatomical, physiological, transcriptional, and 3D (traditional behavioral) spaces drives specific hypotheses by which cognitive capacities can increase during evolution. An important medium exploited by evolution for joining active subunits into greater agents is developmental bioelectricity, implemented by pre-neural use of ion channels and gap junctions to scale up cell-level feedback loops into anatomical homeostasis. This architecture of multi-scale competency of biological systems has important implications for plasticity of bodies and minds, greatly potentiating evolvability. Considering classical and recent data from the perspectives of computational science, evolutionary biology, and basal cognition, reveals a rich research program with many implications for cognitive science, evolutionary biology, regenerative medicine, and artificial intelligence.
... Theoretical approaches to morphogenesis are usually based on the pattern formation resulting from the reaction-diffusion of instructive signals (Ibañes and Izpisúa Belmonte, 2007;Lewis, 2008;Kondo and Miura, 2010;Green and Sharpe, 2015). While the propagation of these signals may involve the cellular uptake of specific molecules from the external microenvironment, it can also occur through intercellular mechanisms, e.g. using gap junctions (GJs) between adjacent cells (Mathews and Levin, 2017;Emmons-Bell et al., 2015;Glen et al., 2018). Gap junctions are versatile signaling gates that enable many cell types to form communicating networks with complex signaling and computational capacities (Palacios-Prado and Bukauskas, 2009;Li et al., 2018;Seki et al., 2014;Cervera et al., 2019;Bhattacharya et al., 2020). ...
... Since junctional blocking can lead to changes in the permeability of GJs to different types of small signaling molecules that impact morphogenesis, we propose a simple framework for understanding how GJ manipulation gives rise to diverse morphotypes of complex anatomical features. As an illustrative case, we focus on the ability of exposure to octanol (Fig. 1), a gap junction blocker, to induce head shapes in planarian flatworms that belong to other species of planaria (Emmons-Bell et al., 2015). ...
... While significant insight exists into the determinants of the number and location(s) of heads (Petersen and Reddien, 2007;Iglesias et al., 2008;Umesono et al., 2013;Owlarn and Bartscherer, 2016;Durant et al., 2019;Pietak et al., 2019;Bischof et al., 2020), less information is available about what factors determine the shape of the heads observed in different species of planaria. Interestingly, experiments revealed that wild-type (genomically-normal) planarian cells can be induced to build heads appropriate to other species of planaria (Emmons-Bell et al., 2015). Using octanol, a blocker of electrical synapses known as GJs (Adler and Woodruff, 2000) that reduces physiological connectivity during regeneration, it was observed that head shapes (including characteristic brain shape and distributions of stem cells) were produced that closely resemble those of other extant planarian species. ...
Article
Complex anatomical form is regulated in part by endogenous physiological communication between cells; however, the dynamics by which gap junctional (GJ) states across tissues regulate morphology are still poorly understood. We employed a biophysical modeling approach combining different signaling molecules (morphogens) to qualitatively describe the anteroposterior and lateral morphology changes in model multicellular systems due to intercellular GJ blockade. The model is based on two assumptions for blocking-induced patterning: (i) the local concentrations of two small antagonistic morphogens diffusing through the GJs along the axial direction, together with that of an independent, uncoupled morphogen concentration along an orthogonal direction, constitute the instructive patterns that modulate the morphological outcomes, and (ii) the addition of an external agent partially blocks the intercellular GJs between neighboring cells and modifies thus the establishment of these patterns. As an illustrative example, we study how the different connectivity and morphogen patterns obtained in presence of a GJ blocker can give rise to novel head morphologies in regenerating planaria. We note that the ability of GJs to regulate the permeability of morphogens post-translationally suggests a mechanism by which different anatomies can be produced from the same genome without the modification of gene-regulatory networks. Conceptually, our model biosystem constitutes a reaction-diffusion information processing mechanism that allows reprogramming of biological morphologies through the external manipulation of the intercellular GJs and the resulting changes in instructive biochemical signals.
... Then, decreasing the intercellular connectivity from the synchronization regime immediately causes a phase shift in these cell potentials and a strong decrease can inhibit the wave propagation. The external blocking of the junction conductance can be realized by specific ions and molecules, producing changes in the instructive patterns that eventually result in significant morphological alterations [69,70]. ...
... Note that, from an operational viewpoint, it should be feasible to control electric potentials and currents at a limited number of physical locations [40]. In particular, bioelectric networks can be manipulated by changes in the regulation of target channel proteins (the case of the pol channel transcription rate r o m,pol here), the microenvironmental ionic concentrations [16], and the blocking of specific channels [13,40,56] and intercellular junctions (the case of the conductance G o here) [16,69]. Also, charged nanoparticles can be used in external actions on cell potentials, as observed by flux cytometry, dyes, and fluorescence microscopy techniques. ...
... In related work, computational simulations of non-excitable cells highlighted the critical role gap junctions hold in intercellular coupling and suggested potential mechanisms by which bioelectric state information propagates from the single-to multicellular scale [4,15,16]. The disruption of intercellular communication has been shown to disrupt morphological outcomes in various multicellular systems [5,17] and this perspective of gap junctions as information processing conduits has received experimental support [18]. While the aforementioned studies were instrumental in setting a precedent for studying bioelectric signaling in multicellular modeling, subsequent extension to the human developmental processes has not been performed due to the challenges of parameterizing human iPSC ionic flux regulation on more than one level of spatial scale (cellular or subcellular); therefore, previous characterizations of human electrophysiology have either focused on the molecular scale of ion channel or cellular scale of whole cell ionic current [19,20]. ...
... We initiated our model development by focusing on the lowest-scale components of the multicellular bioelectric system individually ( Figure 1). In non-excitable stem cells, the critical determinants of cellular resting V mem are ion channels, gap junctions, and ion pumps; multiple studies [32][33][34] have proven that these core bioelectric system components must coordinate activities to create and maintain cell resting V mem state [30,35] and multicellular bioelectric patterns profiles during organogenesis [14,35] and embryogenesis [17,36,37]. Therefore, we hypothesized that this conserved single-cell bioelectric system relationship would also extend to multicellular system dynamics in a multiscale manner via intercellular conduits. ...
Article
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Bioelectric signals possess the ability to robustly control and manipulate patterning during embryogenesis and tissue-level regeneration. Endogenous local and global electric fields function as a spatial ‘pre-pattern’, controlling cell fates and tissue-scale anatomical boundaries; however, the mechanisms facilitating these robust multiscale outcomes are poorly characterized. Computational modeling addresses the need to predict in vitro patterning behavior and further elucidate the roles of cellular bioelectric signaling components in patterning outcomes. Here, we modified a previously designed image pattern recognition algorithm to distinguish unique spatial features of simulated non-excitable bioelectric patterns under distinct cell culture conditions. This algorithm was applied to comparisons between simulated patterns and experimental microscopy images of membrane potential (Vmem) across cultured human iPSC colonies. Furthermore, we extended the prediction to a novel co-culture condition in which cell sub-populations possessing different ionic fluxes were simulated; the defining spatial features were recapitulated in vitro with genetically modified colonies. These results collectively inform strategies for modeling multiscale spatial characteristics that emerge in multicellular systems, characterizing the molecular contributions to heterogeneity of membrane potential in non-excitable cells, and enabling downstream engineered bioelectrical tissue design.
... Genet ically wild-type planaria can be induced to form two heads instead of a head and tail, and this pattern is then permanently propagated in the animals regenerating from subsequent cuts in plain water with no further manipulation (Oviedo et al., 2010). Planarian fragments can also be induced to form heads appropriate to other species, with no genomic editing (Emmons-Bell et al., 2015). Voltage-sensitive fluorescent dyes now allow the visualization of these pattern memories; for example, showing a two-headed bioelectric prepattern induced in a transcriptionally and anatomically normal one-head worm. ...
... More generally, can we develop a science of prediction of collective systems' goals from a knowledge of their parts? Where else do goals come from, in cases where evolutionary history and genomic information is not a plausible origin, such as Xenobots made from wild-type Xenopus laevis skin cells, or wild-type planaria bioelectrically induced to create head shapes of other species (Emmons-Bell et al., 2015;Kriegman et al., 2021;Sullivan, Emmons-Bell, & Levin, 2016)? ...
Chapter
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A unique exploration of teleonomy—also known as “evolved purposiveness”—as a major influence in evolution by a broad range of specialists in biology and the philosophy of science. The evolved purposiveness of living systems, termed “teleonomy” by chronobiologist Colin Pittendrigh, has been both a major outcome and causal factor in the history of life on Earth. Many theorists have appreciated this over the years, going back to Lamarck and even Darwin in the nineteenth century. In the mid-twentieth century, however, the complex, dynamic process of evolution was simplified into the one-way, bottom-up, single gene-centered paradigm widely known as the modern synthesis. In Evolution “On Purpose,” edited by Peter A. Corning, Stuart A. Kauffman, Denis Noble, James A. Shapiro, Richard I. Vane-Wright, and Addy Pross, some twenty theorists attempt to modify this reductive approach by exploring in depth the different ways in which living systems have themselves shaped the course of evolution. Evolution “On Purpose” puts forward a more inclusive theoretical synthesis that goes far beyond the underlying principles and assumptions of the modern synthesis to accommodate work since the 1950s in molecular genetics, developmental biology, epigenetic inheritance, genomics, multilevel selection, niche construction, physiology, behavior, biosemiotics, chemical reaction theory, and other fields. In the view of the authors, active biological processes are responsible for the direction and the rate of evolution. Essays in this collection grapple with topics from the two-way “read-write” genome to cognition and decision-making in plants to the niche-construction activities of many organisms to the self-making evolution of humankind. As this collection compellingly shows, and as bacterial geneticist James Shapiro emphasizes, “The capacity of living organisms to alter their own heredity is undeniable.”
... F The bioelectric prepattern is a true memory because, despite the wild-type genetic sequence, fragments from two-headed animals continue to generate two-headed animals in perpetuity (with no more treatments) [195]-this is an example of the software layer that is reprogrammable and enabled by the genetically specified ion channel hardware, which does not need to change to be shifted to an entirely different large-scale target morphology. G Not only can head number be reprogrammed by a brief physiological stimulus to the morphogenetic agent, but also head shape: an animal with a triangular head shape can be shifted toward morphologies (including brain shape and stem cell distribution) [197,198] of other species with round or flat heads. This enables the cellular collective to explore attractors in morphospace (G'), using the exact same genome, which eventually could become canalized into genetically distinct species. ...
... Evolution could make use of this in precisely the same way as it exploits classical learning (brain bioelectric dynamics), via genetic assimilation and Baldwin effects [29,196] that can later canalize adaptive outcomes of morphogenetic and physiological plasticity. Indeed, it has been shown that existing planarian species' head shapes are readily recapitulated by a genetically wild-type animal experiencing changes to its bioelectric circuit during regeneration-100-150 million years of evolutionary distance in morphospace can be crossed in a few days because of the dynamics of bioelectric pattern memories [197,198]. If proven advantageous, this could eventually be transferred into the genome by ion channel mutations that produce the same bioelectric circuitdriven developmental behavior (assimilation of physiological plasticity into the hardware [199]). ...
Article
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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.
... For example, in planaria, the number of heads can be specified by transiently manipulating the endogenous bioelectric circuit that stores the anatomy toward which cells work: once set to a different layout, this "pattern memory" is stored by the tissue and used to guide the location of heads in cut fragments. Not only head number, but also head shape can be controlled [231]: brief interruption of bioelectrical communication among cells in a planarian fragment results in the regeneration of heads (and brain shapes) appropriate to other species of planaria, in the absence of genetic change (but in a stochastic manner with ratios proportional to evolutionary distance between the species). This has been modeled via dynamical systems concepts as the cellular network being pushed out of its usual, default attractor state (by the injury), and sometimes settling down into the wrong attractor if the normal cell:cell communication is inhibited [166]. ...
... The remarkable fact is that the reagent used to achieve this is a gap junction blocker, which breaks the bioelectric gestalt between the cells [232,233] in precisely the same way as general anesthetics interfere with gap junctions in the brain to cause a loss of high-level integration (consciousness). Much as patients coming out of general anesthesia that often have brief but significant hallucinations (visit incorrect regions of the brain state space), planaria exposed to an uncoupler of electrical synapses inhabit an incorrect region of morphospace for about 3 weeks, but then remodel back to the much deeper default attractor [231]. ...
Article
Central to the study of cognition is being able to specify the Subject that is making decisions and owning memories and preferences. However, all real cognitive agents are made of parts (such as brains made of cells). The integration of many active subunits into a coherent Self appearing at a larger scale of organization is one of the fundamental questions of evolutionary cognitive science. Typical biological model systems, whether basal or advanced, have a static anatomical structure which obscures important aspects of the mind-body relationship. Recent advances in bioengineering now make it possible to assemble, disassemble, and recombine biological structures at the cell, organ, and whole organism levels. Regenerative biology and controlled chimerism reveal that studies of cognition in intact, “standard”, evolved animal bodies are just a narrow slice of a much bigger and as-yet largely unexplored reality: the incredible plasticity of dynamic morphogenesis of biological forms that house and support diverse types of cognition. The ability to produce living organisms in novel configurations makes clear that traditional concepts, such as body, organism, genetic lineage, death, and memory are not as well-defined as commonly thought, and need considerable revision to account for the possible spectrum of living entities. Here, I review fascinating examples of experimental biology illustrating that the boundaries demarcating somatic and cognitive Selves are fluid, providing an opportunity to sharpen inquiries about how evolution exploits physical forces for multi-scale cognition. Developmental (pre-neural) bioelectricity contributes a novel perspective on how the dynamic control of growth and form of the body evolved into sophisticated cognitive capabilities. Most importantly, the development of functional biobots – synthetic living machines with behavioral capacity – provides a roadmap for greatly expanding our understanding of the origin and capacities of cognition in all of its possible material implementations, especially those that emerge de novo, with no lengthy evolutionary history of matching behavioral programs to bodyplan. Viewing fundamental questions through the lens of new, constructed living forms will have diverse impacts, not only in basic evolutionary biology and cognitive science, but also in regenerative medicine of the brain and in artificial intelligence.
... In planarian flatworms, disruption of gap junction communication during regeneration can lead to double-headed specimens or even worms with characteristics of different planarian species. 9,10 The importance of gap junction connectivity to developmental biology suggests potent applications in synthetic morphology and tissue engineering. ...
Article
Full-text available
Gap junction connectivity is crucial to intercellular communication and plays a key role in many critical processes in developmental biology. However, direct analysis of gap junction connectivity in populations of developing cells has proven difficult due to the limitations of patch clamp and dye diffusion based technologies. We re-examine a microfluidic technique based on the principle of laminar flow, which aims to electrically measure gap junction connectivity. In the device, the trilaminar flow of a saline sheathed sucrose solution establishes distinct regions of electrical conductivity in the extracellular fluid spanning an NRK-49F cell monolayer. In theory, the sucrose gap created by laminar flow provides sufficient electrical isolation to detect electrical current flows through the gap junctional network. A novel calibration approach is introduced to account for stream width variation in the device, and elastomeric valves are integrated to improve the performance of gap junction blocker assays. Ultimately, however, this approach is shown to be ineffective in detecting changes in gap junction impedance due to the gap junction blocker, 2-APB. A number of challenges associated with the technique are identified and analyzed in depth and important improvements are described for future iterations.
... Specifically, for example, no existing model makes a prediction on what will happen if 50% of the neoblasts of a given planarian are replaced with those of a different species and the head is cut off (Fig. 5c). Whether the head will be of the right shape for one of the two species (dominant), or an in-between hybrid form, or in fact continuously cycle between shapes (as each set of neoblasts works to remodel toward the shape they normally make with great fidelity), cannot yet be derived from the properties of single cell regulatory pathwaysit is a collective decision about navigating the space of possible head shapes 128,129 (Fig. 5d). ...
Article
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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.
... Indeed, specific manipulation of ion channel and pump function has been shown to induce ectopic organs, 13 duplicate the primary body axis, 14,15 repair defects of the brain, 16 trigger regeneration of appendages under non-regenerative conditions, 17 prevent oncogene-driven tumorigenesis, 18,19 and induce morphologies appropriate to other species without genomic editing or transgenes. 20 While the molecular components necessary for development and regeneration are increasingly characterized, [21][22][23][24][25] many deep problems (such as the expected morphology of chimeric organisms) remain, 26 because we do not yet understand the algorithms that are sufficient for cells to collaborate toward complex anatomical outcomes. It is necessary to design and test models of minimal circuits that would recapitulate system-level morphogenetic repair processes. ...
... This spatial regionalization can be due to different junction expression over distinct modules. It can also be induced by junction blocking [45], using specific molecules in each multicellular module. ...
Article
Background: Transmembrane electrical potential differences in cells modulate the spatio-temporal distribution of signaling ions and molecules that are instructive for downstream signaling pathways in multicellular systems. The local coupling between bioelectricity and protein transcription patterns allows dynamic subsystems (modules) of cells that share the same bioelectrical state to show similar biochemical downstream processes. Methods: We simulate theoretically how the integration-segregation pattern formed by the different multicellular modules that define a biosystem can be controlled by multicellular potentials. To this end, we couple together the model equations of the bioelectrical network to those of the genetic network. Results: The coupling provided by the intercellular junctions and the external microenvironment allows the restoration of the target bioelectrical pattern by changing the transcription rate of specific ion channels, the post-translational blocking of these channels, and changes in the environmental ionic concentrations. Conclusions: The simulations show that the single-cell feedback between bioelectrical and transcriptional processes, together with the coupling provided by the intercellular junctions and the environment, can correct large-scale patterns by means of suitable external actions. General significance: This study provides a theoretical advancement in the understanding of how the multicellular bioelectric coupling may guide repolarizing interventions for regenerating a tissue, with potential implications in biomedicine.
... In development, these bioelectric fields regulate the expression of genes that establish organs and limbs; they also create gradients of morphogens to align anterior-posterior and left-right axes [2,[8][9][10]. Additional examples in Drosophila, Zebrafish, frog, Planaria, chick, and mouse demonstrate that perturbing the normal bioelectric field regulates organ and organism size [10][11][12][13][14]. ...
Article
Full-text available
In healthy skin, vectorial ion transport gives rise to a transepithelial potential which directly impacts many physiological aspects of skin function. A wound is a physical defect that breaches the epithelial barrier and changes the electrochemical environment of skin. Electroceutical dressings are devices that manipulate the electrochemical environment, host as well as microbial, of a wound. In this review, electroceuticals are organized into three mechanistic classes: ionic, wireless, and battery powered. All three classes of electroceutical dressing show encouraging effects on infection management and wound healing with evidence of favorable impact on keratinocyte migration and disruption of wound biofilm infection. This foundation sets the stage for further mechanistic as well as interventional studies. Successful conduct of such studies will determine the best dosage, timing, and class of stimulus necessary to maximize therapeutic efficacy.
... By manipulating the ion conductances responsible for these gradients through pharmacological or RNAi methods, researchers can induce predictable changes in the anatomical structure of the regenerated planaria, resulting in forms with two heads or no heads that are still viable [16]. This works because the bioelectric pattern is natively used by cells to store the large-scale target morphology information about the number of heads [73,223] ; moreover, it also stores information about the shape of the heads -manipulation can force a genetically wild-type worm to make head and brain shapes belonging to other species of flatworm 100-150 million years in evolutionary distance [77,278]. The anatomical setpoint for the regenerative process is stored bioelectrically, and is a true memory because it persists -2-headed animals that are re-cut in plain water continue to demonstrate the 2-headed phenotype in perpetuity [204]. ...
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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. We argue here that the most consistent and pervasive result of these failures is aging, which is characterized by the progressive loss of function and decline in the abilityn 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 accumulation of molecular and cellular damage resulting from energy metabolism and mitochondrial function, and that cell growth and lifespan are limited by replicative senescence due to shortening of telomeres. In this article, we propose a complementary view of aging as a morphostasis defect, specifically driven by abrogation of the endogenous bioelectric signaling that normally harness individual cell behaviors toward the creation and upkeep of complex multicellular structures in vivo. We first present bioelectricity as the software of life, then in a second part we identify and discuss the links between bioelectricity and rejuvenation strategies and age-related diseases, and develop a bridge between aging and regeneration via bioelectric signaling that suggests a research program for addressing aging. In a third part, we discuss the broader implications of the homologies between development, aging, cancer and regeneration. In a fourth part, we present the morphoceuticals for aging and we conclude.
... One example of this plasticity of morphogenetic behavior (expanding on the default genetically encoded repertoire) is the fact that temporary exposure to a blocker of electrical synapses (i.e., an anesthetic) causes planarian fragments to create the heads of other species, with no genetic change required (Emmons-Bell et al. 2015;Sullivan et al. 2016). The bioelectric network incorrectly navigates to additional attractors in morphogenetic space that are normally used by species 100-150 million years of evolutionary distance-all without any genetic change needed (much like nervous systems allow an animal to dynamically remember or envision novel, distant scenarios without the need for genetic change to its brain hardware to enable each new thought). ...
Article
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Each of us made the remarkable journey from mere matter to mind: starting life as a quiescent oocyte (“just chemistry and physics”), and slowly, gradually, becoming an adult human with complex metacognitive processes, hopes, and dreams. In addition, even though we feel ourselves to be a unified, single Self, distinct from the emergent dynamics of termite mounds and other swarms, the reality is that all intelligence is collective intelligence: each of us consists of a huge number of cells working together to generate a coherent cognitive being with goals, preferences, and memories that belong to the whole and not to its parts. Basal cognition is the quest to understand how Mind scales—how large numbers of competent subunits can work together to become intelligences that expand the scale of their possible goals. Crucially, the remarkable trick of turning homeostatic, cell-level physiological competencies into large-scale behavioral intelligences is not limited to the electrical dynamics of the brain. Evolution was using bioelectric signaling long before neurons and muscles appeared, to solve the problem of creating and repairing complex bodies. In this Perspective, I review the deep symmetry between the intelligence of developmental morphogenesis and that of classical behavior. I describe the highly conserved mechanisms that enable the collective intelligence of cells to implement regulative embryogenesis, regeneration, and cancer suppression. I sketch the story of an evolutionary pivot that repurposed the algorithms and cellular machinery that enable navigation of morphospace into the behavioral navigation of the 3D world which we so readily recognize as intelligence. Understanding the bioelectric dynamics that underlie construction of complex bodies and brains provides an essential path to understanding the natural evolution, and bioengineered design, of diverse intelligences within and beyond the phylogenetic history of Earth.
... The presence of very high energetic barriers can render such a GM effectively oneway, as seen in the context-dependent switches between signal transduction pathways and GRNs that characterize cellular differentiation during morphogenesis. Biological examples of these include modications of bioelectric pattern memories in planaria, which can create alternative-species head shapes that eventually remodel back to normal [83], or produce 2-headed worms which are permanent, and regenerate as 2-headed in perpetuity [84]. ...
Article
Living systems face both environmental complexity and limited access to free-energy resources. Survival under these conditions requires a control system that can activate, or deploy, available perception and action resources in a context specific way. In this Part I, we introduce the free-energy principle (FEP) and the idea of active inference as Bayesian prediction-error minimization, and show how the control problem arises in active inference systems. We then review classical and quantum formulations of the FEP, with the former being the classical limit of the latter. In the accompanying Part II, we show that when systems are described as executing active inference driven by the FEP, their control flow systems can always be represented as tensor networks (TNs). We show how TNs as control systems can be implemented within the general framework of quantum topological neural networks, and discuss the implications of these results for modeling biological systems at multiple scales.
... 174 They can also dictate species-specific structural variations in anatomical features. 175 Moreover, in a set of recent studies, 149,150,159,160,176 a computational platform for simulating endogenous bioelectrical control mechanisms identified human-approved ion channel-targeting drugs that could repair drastic brain defects in a tadpole model by enforcing the appropriate bioelectric prepattern despite the action of powerful teratogens. The most remarkable aspect of these is that heart, gut, and brain defects induced by a mutation of the important neurogenesis gene NOTCH could be repaired by transient exposure to pharmacological electroceuticals (specifically HCN2-opener drugs) without repairing the mutation. ...
Article
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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.
... This capacity to do things that were not specifically selected for [221] and do not exist elsewhere in their (or others') phylogenetic history reveals that evolution can not only create seeds for cellular machines that do multiple things, but for ones that can do novel things. This is because genomic information is overloaded by physiological interpretation machinery (internal observer modules): the exact same DNA sequence can be used by cells to build a tadpole or a Xenobot (and the same planarian genome can build the heads of several different species [222,223]). Thus, evolution teaches us about powerful polycomputing strategies because it does not make solutions for specific problems-it creates generic problem solving machines, in which the competition and cooperation of overlapping, nested computational agents at all levels exploit the ability of existing hardware to carry out numerous functions simultaneously. ...
Article
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The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., a tendency to oversimplify) and prior technological limitations in favor of a more continuous view, necessitated by the study of evolution, developmental biology, and intelligent machines. Form and function are tightly entwined in nature, and in some cases, in robotics as well. Thus, efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as “polycomputing”—the ability of the same substrate to simultaneously compute different things, and make those computational results available to different observers. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of their computational materials, as reported in the rapidly growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of mesoscale events, as it has already done at quantum and relativistic scales. To develop our understanding of how life performs polycomputing, and how it can be convinced to alter one or more of those functions, we can first create technologies that polycompute and learn how to alter their functions. Here, we review examples of biological and technological polycomputing, and develop the idea that the overloading of different functions on the same hardware is an important design principle that helps to understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as to evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering.
... The presence of very high energetic barriers can render such a GM effectively one-way, as seen in the context-dependent switches between signal transduction pathways and GRNs that characterize cellular differentiation during morphogenesis. Biological examples of these include modifications of bioelectric pattern memories in planaria, which can create alternative-species head shapes that eventually remodel back to normal [83], or produce 2-headed worms which are permanent, and regenerate as 2headed in perpetuity [84]. ...
Preprint
Full-text available
Living systems face both environmental complexity and limited access to free-energy resources. Survival under these conditions requires a control system that can activate, or deploy, available perception and action resources in a context specific way. We show here that when systems are described as executing active inference driven by the free-energy principle (and hence can be considered Bayesian prediction-error minimizers), their control flow systems can always be represented as tensor networks (TNs). We show how TNs as control systems can be implmented within the general framework of quantum topological neural networks, and discuss the implications of these results for modeling biological systems at multiple scales.
... d, The genomically specified cellular hardware sets parameters that describe positions and trajectories through morphospace 99,100 , such as that formed by axes defining possible planarian head shapes 101 . The same, genetically wild-type cells can be induced to find and build attractors that belong to various species 102 . The computational machinery within cell collectives enables living systems to navigate morphospace to reach the anatomical goal configuration. ...
Article
Bioengineering can address many important needs, from transformative biomedicine to environmental remediation. In addition to practical applications, the construction of new living systems will increase our understanding of biology and will nurture emerging intersections between biological and computational sciences. In this Review, we discuss the transition from cell-level synthetic biology to multicellular synthetic morphology. We highlight experimental embryology studies, including organoids and xenobots, that go beyond the familiar, default outcomes of embryogenesis, revealing the plasticity, interoperability and problem-solving capacities of life. In addition to traditional bottom-up engineering of genes and proteins, design strategies can be pursued based on modelling cell collectives as agential materials, with their own goals, agendas and powers of problem-solving. Such an agential bioengineering approach could transform developmental biology, regenerative medicine and robotics, building on frameworks that include active, computational and agential matter. Synthetic morphogenesis is limited by knowledge gaps about the competencies of cells and cell groups. This Review discusses a synthetic bioengineering framework based on empirically determined properties of cells, including goal-seeking and agential behaviours, which will allow the creation of complex devices that cannot be built using bottom-up approaches. Synthetic bioengineering allows the construction of new arrangements of living material.Synthetic morphology aims at creating an ‘anatomical compiler’ that writes DNA instructions based on a specific design goal.Bottom-up bioengineering approaches are limited by knowledge gaps in developmental biology, thus relying on the micromanagement of passive materials.Cells and tissues are effectively manipulated as agential materials, by targeting their pattern memory and homeostatic capabilities.Extending bottom-up approaches by adding empirically and computationally characterized agential materials (cells and tissues) will greatly improve the rational creation and repair of complex morphologies. Synthetic bioengineering allows the construction of new arrangements of living material. Synthetic morphology aims at creating an ‘anatomical compiler’ that writes DNA instructions based on a specific design goal. Bottom-up bioengineering approaches are limited by knowledge gaps in developmental biology, thus relying on the micromanagement of passive materials. Cells and tissues are effectively manipulated as agential materials, by targeting their pattern memory and homeostatic capabilities. Extending bottom-up approaches by adding empirically and computationally characterized agential materials (cells and tissues) will greatly improve the rational creation and repair of complex morphologies.
... In fact, the only available abnormal line of planaria is a permanently two-headed form [96][97][98], which was produced not genetically but by manipulating bioelectrical signaling-the modality that is used to coordinate cellular competency [99][100][101], as is predicted by our model for species like planaria. Given their resistance to mutation, it's unclear how speciation in planaria happens, but it should be noted that the same bioelectrical strategy that controls computation and cognition (i.e., behavioral competencies) in brains has been shown to coax genetically wild-type planaria to grow the heads appropriate to other species [102,103]. ...
Article
Full-text available
Biological genotypes do not code directly for phenotypes; developmental physiology is the control layer that separates genomes from capacities ascertained by selection. A key aspect is cellular competency, since cells are not passive materials but descendants of unicellular organisms with complex context-sensitive behavioral capabilities. To probe the effects of different degrees of cellular competency on evolutionary dynamics, we used an evolutionary simulation in the context of minimal artificial embryogeny. Virtual embryos consisted of a single axis of positional information values provided by cells’ ‘structural genes’, operated upon by an evolutionary cycle in which embryos’ fitness was proportional to monotonicity of the axial gradient. Evolutionary dynamics were evaluated in two modes: hardwired development (genotype directly encodes phenotype), and a more realistic mode in which cells interact prior to evaluation by the fitness function (“regulative” development). We find that even minimal ability of cells with to improve their position in the embryo results in better performance of the evolutionary search. Crucially, we observed that increasing the behavioral competency masks the raw fitness encoded by structural genes, with selection favoring improvements to its developmental problem-solving capacities over improvements to its structural genome. This suggests the existence of a powerful ratchet mechanism: evolution progressively becomes locked in to improvements in the intelligence of its agential substrate, with reduced pressure on the structural genome. This kind of feedback loop in which evolution increasingly puts more effort into the developmental software than perfecting the hardware explains the very puzzling divergence of genome from anatomy in species like planaria. In addition, it identifies a possible driver for scaling intelligence over evolutionary time, and suggests strategies for engineering novel systems in silico and in bioengineering.
... 20,21 Importantly, modulation of bioelectric signaling via drugs, channel misexpression, or optogenetics has been shown to be able to induce whole organ (e.g., eye 22 ) formation, regeneration of appendages under normally nonregenerative conditions, 23 and even the formation of head structures belonging to other species. 24 It is clear that bioelectric computations within cell groups are an important and increasingly tractable interface through which to control large-scale growth and form. 25 One example of this kind of approach is the repair of brain defects in an amphibian model. ...
Article
Characteristic spatial differences of cellular resting potential across tissues have been shown to act as instructive bioelectric prepatterns regulating embryonic and regenerative morphogenesis, as well as cancer suppression. Indeed, modulation of bioelectric patterns via specific ion channel-targeting drugs, channel misexpression, or optogenetics has been used to control growth and form in vitro, showing promise in regenerative medicine and synthetic bioengineering. Repair of defects, injury, and transformation requires quantitative understanding of bioelectric dynamics within tissues so that these can be modulated toward desired outcomes in organ patterning or the creation of entirely novel synthetic constructs. The major gap in the discovery of interventions for rational control of organ-level outcomes is the inability to predict large-scale bioelectric patterns—their emergence from symmetry breaking (given a set of channels expressed on the tissue) and their change as a function of time under specific bioelectrical interventions. It is thus essential to develop machine learning and other computational tools to help human scientists identify bioelectric states with desirable properties. In this study, we tested the ability of a heuristic search algorithm to explore the parameter space of bioelectrical circuits by adjusting the parameters of simulated cells. We show that while bioelectrical space is not easy to search, it does contain parameter sets that encode rich and interesting patterning behaviors. We demonstrate proof of principle of using a computational search platform to identify circuits with desired properties, as a first step toward the design of machine learning tools for improved bioelectric control of growth and form.
... This capacity to do things that were not specifically selected for [209] and do not exist elsewhere in their (or others') phylogenetic history reveals that evolution can not only create seeds for machines that do multiple things, but ones that can do novel things. This is because genomic information is overloaded by physiological interpretation machinery (internal observer modules): the exact same DNA sequence can be used to build a tadpole or a Xenobot (and the same planarian genome can build the heads of several different species [210,211]). Thus, evolution teaches us about powerful polycomputing strategies because it does not make solutions for specific problems -it creates generic problem-solving machines, in which the competition and cooperation of overlapping, nested computational agents at all levels exploit the ability of existing hardware to carry out numerous functions simultaneously. ...
Preprint
Full-text available
The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., tendency to oversimplify) and prior technological limitations in favor of a more continuous, gradualist view necessitated by the study of evolution, developmental biology, and intelligent machines. Efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as "polycomputing" - the ability of the same substrate to simultaneously compute different things. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of computational materials as reported in the rapidly-growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of meso-scale events, as it has already done at quantum and relativistic scales. Here, we review examples of biological and technological polycomputing, and develop the idea that overloading of different functions on the same hardware is an important design principle that helps understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering.
... In fact the only available abnormal line of planaria is a permanently two-headed form [109][110][111], which was produced not genetically but by manipulating bioelectrical signalingthe modality that is used to coordinate cellular competency [112][113][114], as is predicted by our model for species like planaria. Given their resistance to mutation, it's unclear how speciation in planaria happens, but it should be noted that the same bioelectrical strategy that controls computation and cognition (i.e., behavioral competencies) in brains has been shown to coax genetically wildtype planaria to grow the heads appropriate to other species [115,116]. ...
Preprint
Full-text available
Biological genotypes do not code directly for phenotypes; developmental physiology is the control layer that separates genomes from capacities ascertained by selection. A key aspect is competency, as cells are not a passive material but descendants of unicellular organisms with complex context-sensitive capabilities. We used an evolutionary simulation in the context of minimal artificial embryogeny to probe the effects of different degrees of cellular competency on evolutionary dynamics. Virtual embryos consisted of a single axis of positional information values provided by cells' genomes, operated upon by an evolutionary cycle in which embryos' fitness was proportional to monotonicity of the axial gradient. Evolutionary dynamics were evaluated in two modes: hardwired "mosaic" development (genotype directly encodes phenotype), and a more realistic mode in which cells interact prior to evaluation by the fitness function ("regulative" development). Even minimal competency with respect to improving their position in the embryo results in better performance of the evolutionary search. Crucially, we observed that as competency of cells masks the raw fitness of the genomes, the phenotypic fitness gains are then mostly due to improvements of cells' developmental problem-solving capacities, not the structural genome. This suggests the existence of a powerful ratchet mechanism: evolution progressively becomes locked in to improvements in the intelligence of its agential substrate, with reduced pressure on the structural genome. A feedback loop in which evolution increasingly puts more effort into the developmental software than perfecting the hardware explains the very puzzling divergence of genome from anatomy in species like planaria, identifies a possible drive for scaling intelligence over time, and suggests strategies for engineering novel systems in silico and in bioengineering.
... The first is the hardware/software distinction: genomes do not encode final outcomes, they encode the structure of a system with plasticity, context-sensitivity, and the flexibility to produce different outcomes from the exact same hardware. This is why genetically wild-type flatworm cells can generate head structures appropriate to other species when their bioelectric signaling is shifted to different attractors (Emmons-Bell et al., 2015), why normal skin cells liberated from frogs spontaneously self-assemble into different, motile proto-organisms (''Xenobots'') without any genomic editing (Kriegman et al., 2020;Blackiston et al., 2021), and why embryos with severe genetic defects can be bioelectrically coaxed to normal brain morphogenesis by reinforcing specific voltage patterns (Pai et al., 2018(Pai et al., , 2015. Developmental bioelectric circuits also feature a kind of re-writable memory. ...
Article
Conceptual and mathematical models of neurons have lagged behind empirical understanding for decades. Here we extend previous work in modeling biological systems with fully scale-independent quantum information-theoretic tools to develop a uniform, scalable representation of synapses, dendritic and axonal processes, neurons, and local networks of neurons. In this representation, hierarchies of quantum reference frames act as hierarchical active-inference systems. The resulting model enables specific predictions of correlations between synaptic activity, dendritic remodeling, and trophic reward. We summarize how the model may be generalized to nonneural cells and tissues in developmental and regenerative contexts.
... However, how exactly could octanol generate this mismatched state? Grodstein and Levin 42 showed that an electrodiffusion model predicts that decreasing GJ connectivity naturally induces multiple swings between hyperpolarized and depolarized (Fig. 6), essentially dividing the worm into voltage islands (as also shown experimentally in Emmons-Bell et al. 64 ). Octanol is a GJ blocker-its main effect is precisely to decrease GJ connectivity. ...
Article
Morphogenesis results when cells cooperate to construct a specific anatomical structure. The behavior of such cell swarms exhibits not only robustness but also plasticity with respect to what specific anatomies will be built. Important aspects of evolutionary biology, regenerative medicine, and cancer are impacted by the algorithms by which instructive information guides invariant or stochastic outcomes of such collective activity. Planarian flatworms are an important model system in this field, as flatworms reliably regenerate a primary body axis after diverse kinds of injury. Importantly, the number of heads to which they regenerate is not determined genetically: lines of worms can be produced, which, with no further manipulation, regenerate as two-headed (2H) worms, or as "Cryptic"worms. When cut into pieces, Cryptic worms produce one-headed (1H) and 2H regenerates stochastically. Neural and bioelectric mechanisms have been proposed to explain aspects of the regenerative dataset. However, these models have not been unified and do not explain all of the Cryptic worm data. In this study, we propose a model in which two separate systems (a bioelectric circuit and a neural polarity mechanism) compete to determine the anatomical structure of a regenerate. We show how our model accounts for existing data and provides a consistent synthesis of mechanisms that explain both the robustness of planarian regeneration and its remarkable re-writability toward novel stable and stochastic anatomical states.
... The first is the hardware/software distinction: genomes do not encode final outcomes, they encode the structure of a system with plasticity, context-sensitivity, and the flexibility to produce different outcomes from the exact same hardware. This is why genetically wild-type flatworm cells can generate head structures appropriate to other species when their bioelectric signaling is shifted to different attractors [148], why normal skin cells liberated from frogs spontaneously selfassemble into different, motile proto-organisms ("Xenobots") without any genomic editing [149,150], and why embryos with severe genetic defects can be bioelectrically coaxed to normal brain morphogenesis by reinforcing specific voltage patterns [151,152]. Developmental bioelectric circuits also feature a kind of re-writable memory. ...
Preprint
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Conceptual and mathematical models of neurons have lagged behind empirical understanding for decades. Here we extend previous work in modeling biological systems with fully scale-independent quantum information-theoretic tools to develop a uniform, scalable representation of synapses, dendritic and axonal processes, neurons, and local networks of neurons. In this representation, hierarchies of quantum reference frames act as hierarchical active-inference systems. The resulting model enables specific predictions of correlations between synaptic activity, dendritic remodeling, and trophic reward. We summarize how the model may be generalized to nonneural cells and tissues in developmental and regenerative contexts.
... Of course, the Self does not return immediately, as shown by the many hallucinatory [312; 313] experiences of people coming out of general anesthesiait takes some time for the brain to return to the correct global bioelectric state once the network connections are allowed again (meta-stability) [314]. Interestingly, and in line with the proposed isomorphism between cognition and morphogenesis, gap junction blockade has exactly this effect in regeneration: planaria briefly treated with GJ blocker regenerate heads of other species, but eventually snap out of it and remodel back to their correct target morphology [183]. It is no accident that the same reagents cause drastic changes in the high-level Selves in both behavioral and morphogenetic contexts: evolution uses the same scheme (GJ-mediated bioelectrical networks) to implement both. ...
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Synthetic biology and bioengineering provide the opportunity to create novel embodied cognitive systems (otherwise known as minds) in a very wide variety of chimeric architectures combining evolved and designed material and software. These advances are disrupting familiar concepts in the philosophy of mind, and require new ways of thinking about and comparing truly diverse intelligences, whose composition and origin are not like any of the available natural model species. In this Perspective, I introduce TAME - Technological Approach to Mind Everywhere - a framework for understanding and manipulating cognition in unconventional substrates. TAME formalizes a non-binary (continuous), empirically-based approach to strongly embodied agency. When applied to regenerating/developmental systems, TAME suggests a perspective on morphogenesis as an example of basal cognition. The deep symmetry between problem-solving in anatomical, physiological, transcriptional, and 3D (traditional behavioral) spaces drives specific hypotheses by which cognitive capacities can scale during evolution. An important medium exploited by evolution for joining active subunits into greater agents is developmental bioelectricity, implemented by pre-neural use of ion channels and gap junctions to scale cell-level feedback loops into anatomical homeostasis. This architecture of multi-scale competency of biological systems has important implications for plasticity of bodies and minds, greatly potentiating evolvability. Considering classical and recent data from the perspectives of computational science, evolutionary biology, and basal cognition, reveals a rich research program with many implications for cognitive science, evolutionary biology, regenerative medicine, and artificial intelligence.
... In this scenario, Equations (1)-(4) constitute a minimum model based on conductances ultimately related to specific proteins. In principle, the transcription, translation, and post-translational gating of these ion channel and junction proteins are amenable to external modulation and future therapeutic strategies [3,12,13,15,45,56,[62][63][64][65][66][67][68][69][70][71]. Consequently, the bioelectrical patterns and their encoded information could be externally regulated by acting on multicellular mean field phenomena such as electrical potential, potassium, and calcium waves [3][4][5]9,72,73] as a complementary procedure to addressing individual cell characteristics. ...
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Electric potential distributions can act as instructive pre-patterns for development, regeneration, and tumorigenesis in cell systems. The biophysical states influence transcription, proliferation, cell shape, migration, and differentiation through biochemical and biomechanical downstream transduction processes. A major knowledge gap is the origin of spatial patterns in vivo, and their relationship to the ion channels and the electrical synapses known as gap junctions. Understanding this is critical for basic evolutionary developmental biology as well as for regenerative medicine. We computationally show that cells may express connexin proteins with different voltage-gated gap junction conductances as a way to maintain multicellular regions at distinct membrane potentials. We show that increasing the multicellular connectivity via enhanced junction function does not always contribute to the bioelectrical normalization of abnormally depolarized multicellular patches. From a purely electrical junction view, this result suggests that the reduction rather than the increase of specific connexin levels can also be a suitable bioelectrical approach in some cases and time stages. We offer a minimum model that incorporates effective conductances ultimately related to specific ion channel and junction proteins that are amenable to external regulation. We suggest that the bioelectrical patterns and their encoded instructive information can be externally modulated by acting on the mean fields of cell systems, a complementary approach to that of acting on the molecular characteristics of individual cells. We believe that despite the limitations of a biophysically focused model, our approach can offer useful qualitative insights into the collective dynamics of cell system bioelectricity.
... In further experiments, we demonstrated that briefly reducing gap junction-mediated connectivity between adjacent cells in the bioelectric network that guides regeneration led worms to regenerate head and brain shapes appropriate to other worm species whose lineages split more than 100 million years ago. 12 My group has developed the use of voltage-sensitive dyes to visualize the bioelectric pattern memory that guides gene expression and cell behavior toward morphogenetic outcomes. 13 Meanwhile, my Allen Center colleagues are using synthetic artificial electric tissues made of human cells and computer models of ion channel activity to understand how electrical dynamics across groups of non-neural cells can set up the voltage patterns that control downstream gene expression, distribution of morphogen molecules, and cell behaviors to orchestrate morphogenesis. ...
... Furthermore, it is now possible to induce regenerative repair of complex appendages in non-regenerative conditions [45,46], and even reprogramme tumours into normal tissue [47][48][49][50], by specific manipulation of ion channels that implement bioelectric state transitions in vivo. Beyond recreating the genome-default anatomical features, it was recently found that genomically wild-type animals (with no DNA editing) could be made to build heads belonging to other living species ∼150 million years distant, simply by manipulating the bioelectric network during regeneration [51,52]. ...
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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’.
... These patterns are important not only for the understanding of development and regeneration but also for replicating morphogenic processes in engineered multicellular systems [3,35]. Note in this context that the building blocks used in the model simulations are amenable to external modulation: the proteins forming the single-cell ion channels and the intercellular gap junctions can be regulated at the transcription, translation, and post-translational levels, e.g., by mRNA microinjection, blocking by specific ions and molecules, and optical pulses [3,[12][13][14]34,42,45,54,60]. On the basis of these experimental facts, we believe that bioelectrical patterns should be good candidates for operational control because in addition to encode instructive information that is eventually decoded as biological outcomes [3][4][5]12,20], they involve multicellular potentials rather than molecular characteristics of the individual cell. ...
Article
Bioelectrical patterns are established by spatiotemporal correlations of cell membrane potentials at the multicellular level, being crucial to development, regeneration, and tumorigenesis. We have conducted multicellular simulations on bioelectrical community effects and intercellular coupling in multicellular aggregates. The simulations aim at establishing under which conditions a local heterogeneity consisting of a small patch of cells can be stabilized against a large aggregate of surrounding identical cells which are in a different bioelectrical state. In this way, instructive bioelectrical information can be persistently encoded in spatiotemporal patterns of separated domains with different cell polarization states. The multicellular community effects obtained are regulated both at the single-cell and intercellular levels, and emerge from a delicate balance between the degrees of intercellular coupling in: (i) the small patch, (ii) the surrounding bulk, and (iii) the interface that separates these two regions. The model is experimentally motivated and consists of two generic voltage-gated ion channels that attempt to establish the depolarized and polarized cell states together with coupling conductances whose individual and intercellular different states permit a dynamic multicellular connectivity. The simulations suggest that community effects may allow the reprogramming of single-cell bioelectrical states, in agreement with recent experimental data. A better understanding of the resulting electrical regionalization can assist the electroceutical correction of abnormally depolarized regions initiated in the bulk of normal tissues as well as suggest new biophysical mechanisms for the establishment of target patterns in multicellular engineering.
... In further experiments, we demonstrated that briefly reducing gap junction-mediated connectivity between adjacent cells in the bioelectric network that guides regeneration led worms to regenerate head and brain shapes appropriate to other worm species whose lineages split more than 100 million years ago. 12 My group has developed the use of voltage-sensitive dyes to visualize the bioelectric pattern memory that guides gene expression and cell behavior toward morphogenetic outcomes. 13 Meanwhile, my Allen Center colleagues are using synthetic artificial electric tissues made of human cells and computer models of ion channel activity to understand how electrical dynamics across groups of non-neural cells can set up the voltage patterns that control downstream gene expression, distribution of morphogen molecules, and cell behaviors to orchestrate morphogenesis. ...
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A microfluidic device has been designed to electrically measure average intercellular connectivity in a cell monolayer. This proof-of-concept design uses elastomeric microvalves to isolate cells across three microfluidic chambers, creating a direct microscale analog of benchtop sucrose gap physiology rigs. The device operation has been verified for normal rat kidney cells (NRK-49F) using a chemical gap junction blocker, 2-aminoethoxydiphenyl borate (2-APB). At 410 Hz, the system measured an averaged network impedance magnitude between 730 and 930 kΩ and demonstrated the ability to distinguish a significant increase of 6.51 kΩ and 0.464° due to 2-APB perfusion.
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The dominant paradigm in biomedicine focuses on genetically‐specified components of cells and their biochemical dynamics, emphasizing bottom‐up emergence of complexity. Here, I explore the biomedical implications of a complementary emerging field: diverse intelligence. Using tools from behavioral science and multiscale neuroscience, we can study development, regenerative repair, and cancer suppression as behaviors of a collective intelligence of cells navigating the spaces of possible morphologies and transcriptional and physiological states. A focus on the competencies of living material—from molecular to organismal scales—reveals a new landscape for interventions. Such top‐down approaches take advantage of the memories and homeodynamic goal‐seeking behavior of cells and tissues, offering the same massive advantages in biomedicine and bioengineering that reprogrammable hardware has provided information technologies. The bioelectric networks that bind individual cells toward large‐scale anatomical goals are an especially tractable interface to organ‐level plasticity, and tools to modulate them already exist. This suggests a research program to understand and tame the software of life for therapeutic gain by understanding the many examples of basal cognition that operate throughout living bodies.
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Collective intelligence and individual intelligence are usually considered to be fundamentally different. Individual intelligence is uncontroversial. It occurs in organisms with special neural machinery, evolved by natural selection to enable cognitive and learning functions that serve the fitness benefit of the organism, and then trained through lifetime experience to maximise individual rewards. Whilst the mechanisms of individual intelligence are not fully understood, good models exist for many aspects of individual cognition and learning. Collective intelligence, in contrast, is a much more ambiguous idea. What exactly constitutes collective intelligence is often vague, and the mechanisms that might enable it are frequently domain-specific. These cannot be mechanisms selected specifically for the purpose of collective intelligence because collectives are not (except in special circumstances) evolutionary units, and it is not clear that collectives can learn the way individual intelligences do since they are not a singular locus of rewards and benefits. Here, we use examples from evolution and developmental morphogenesis to argue that these apparent distinctions are not as categorical as they appear. Breaking down such distinctions enables us to borrow from and expand existing models of individual cognition and learning as a framework for collective intelligence, in particular connectionist models familiar in the context of neural networks. We discuss how specific features of these models inform the necessary and sufficient conditions for collective intelligence, and identify current knowledge gaps as opportunities for future research.
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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.
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Traditional mammalian testing is too time‐ and cost‐intensive to keep up with the large number of environmental chemicals needing assessment. This has led to a dearth of information about the potential adverse effects of these chemicals, especially on the developing brain. Thus, there is an urgent need for rapid and cost‐effective neurotoxicity and developmental neurotoxicity testing. Because of the complexity of the brain, metabolically competent organismal models are necessary to understand the effects of chemicals on nervous system development and function on a systems level. In this overview, we showcase asexual freshwater planarians as an alternative invertebrate (“non‐animal”) organismal model for neurotoxicology research. Planarians have long been used to study the effects of chemicals on regeneration and behavior. But they have only recently moved back into the spotlight because modern molecular and computational approaches now enable quantitative high‐content and high‐throughput toxicity studies. Here, we present a short history of the use of planarians in toxicology research, highlight current techniques to measure toxicity qualitatively and quantitatively in planarians, and discuss how to further promote this non‐animal organismal system into mainstream toxicology research. The articles in this collection will help work towards this goal by providing detailed protocols that can be adopted by the community to standardize planarian toxicity testing.
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Characteristic spatial differences of cellular resting potential across tissues have been shown to act as instructive bioelectric prepatterns regulating embryonic and regenerative morphogenesis, as well as cancer suppression. Indeed, modulation of bioelectric patterns via specific ion channel-targeting drugs, channel misexpression, or optogenetics has been used to control growth and form in vitro, showing promise in regenerative medicine and synthetic bioengineering. Repair of defects, injury, and transformation requires quantitative understanding of bioelectric dynamics within tissues so that these can be modulated toward desired outcomes in organ patterning or the creation of entirely novel synthetic constructs. The major gap in the discovery of interventions for rational control of organ-level outcomes is the inability to predict large-scale bioelectric patterns - their emergence from symmetry breaking (given a set of channels expressed on the tissue) and their change as a function of time under specific bioelectrical interventions. It is thus essential to develop machine learning and other computational tools to help human scientists identify bioelectric states with desirable properties. Here, we tested the ability of a heuristic search algorithm to explore the parameter space of bio-electrical circuits by adjusting the parameters of simulated cells. We show that while bioelectrical space is not easy to search, it does contain parameter sets that encode rich and interesting patterning behaviors. We demonstrate proof of principle of using a computational search platform to identify circuits with desired properties, as a first step toward the design of machine learning tools for improved bioelectric control of growth and form.
Chapter
Extracting mechanistic knowledge from the spatial and temporal phenotypes of morphogenesis is a current challenge due to the complexity of biological regulation and their feedback loops. Furthermore, these regulatory interactions are also linked to the biophysical forces that shape a developing tissue, creating complex interactions responsible for emergent patterns and forms. Here we show how a computational systems biology approach can aid in the understanding of morphogenesis from a mechanistic perspective. This methodology integrates the modeling of tissues and whole-embryos with dynamical systems, the reverse engineering of parameters or even whole equations with machine learning, and the generation of precise computational predictions that can be tested at the bench. To implement and perform the computational steps in the methodology, we present user-friendly tools, computer code, and guidelines. The principles of this methodology are general and can be adapted to other model organisms to extract mechanistic knowledge of their morphogenesis.
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How are individual cell behaviors coordinated toward invariant large-scale anatomical outcomes in development and regeneration despite unpredictable perturbations? Endogenous distributions of membrane potentials, produced by ion channels and gap junctions, are present across all tissues. These bioelectrical networks process morphogenetic information that controls gene expression, enabling cell collectives to make decisions about large-scale growth and form. Recent progress in the analysis and computational modeling of developmental bioelectric circuits and channelopathies reveals how cellular collectives cooperate toward organ-level structural order. These advances suggest a roadmap for exploiting bioelectric signaling for interventions addressing developmental disorders, regenerative medicine, cancer reprogramming, and synthetic bioengineering.
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Development of the body plan is controlled by large networks of regulatory genes. A gene regulatory network that controls the specification of endoderm and mesoderm in the sea urchin embryo is summarized here. The network was derived from large-scale perturbation analyses, in combination with computational methodologies, genomic data, cis-regulatory analysis, and molecular embryology. The network contains over 40 genes at present, and each node can be directly verified at the DNA sequence level by cis-regulatory analysis. Its architecture reveals specific and general aspects of development, such as how given cells generate their ordained fates in the embryo and why the process moves inexorably forward in developmental time.
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Background Bioelectric gradients among all cells, not just within excitable nerve and muscle, play instructive roles in developmental and regenerative pattern formation. Plasma membrane resting potential gradients regulate cell behaviors by regulating downstream transcriptional and epigenetic events. Unlike neurons, which fire rapidly and typically return to the same polarized state, developmental bioelectric signaling involves many cell types stably maintaining various levels of resting potential during morphogenetic events. It is important to begin to quantitatively model the stability of bioelectric states in cells, to understand computation and pattern maintenance during regeneration and remodeling. Method To facilitate the analysis of endogenous bioelectric signaling and the exploitation of voltage-based cellular controls in synthetic bioengineering applications, we sought to understand the conditions under which somatic cells can stably maintain distinct resting potential values (a type of state memory). Using the Channelpedia ion channel database, we generated an array of amphibian oocyte and mammalian membrane models for voltage evolution. These models were analyzed and searched, by simulation, for a simple dynamical property, multistability, which forms a type of voltage memory. Results We find that typical mammalian models and amphibian oocyte models exhibit bistability when expressing different ion channel subsets, with either persistent sodium or inward-rectifying potassium, respectively, playing a facilitative role in bistable memory formation. We illustrate this difference using fast sodium channel dynamics for which a comprehensive theory exists, where the same model exhibits bistability under mammalian conditions but not amphibian conditions. In amphibians, potassium channels from the Kv1.x and Kv2.x families tend to disrupt this bistable memory formation. We also identify some common principles under which physiological memory emerges, which suggest specific strategies for implementing memories in bioengineering contexts. Conclusion Our results reveal conditions under which cells can stably maintain one of several resting voltage potential values. These models suggest testable predictions for experiments in developmental bioelectricity, and illustrate how cells can be used as versatile physiological memory elements in synthetic biology, and unconventional computation contexts.
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Locomotion in vertebrates and invertebrates has a long history in research as the most prominent example of interlimb coordination. However, the evolution towards upright stance and gait has paved the way for a bewildering variety of functions in which the upper limbs interact with each other in a context-specific manner. The neural basis of these bimanual interactions has been investigated in recent years on different scales, ranging from the single-cell level to the analysis of neuronal assemblies. Although the prevailing viewpoint has been to assign bimanual coordination to a single brain locus, more recent evidence points to a distributed network that governs the processes of neural synchronization and desynchronization that underlie the rich variety of coordinated functions. The distributed nature of this network accounts for disruptions of interlimb coordination across various movement disorders.
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The integumentary system comprises the skin and its appendages, which includes hair, nails, feathers, sebaceous and eccrine glands. In this review, we focus on the expression profile of connexins and pannexins throughout the integumentary system in mammals, birds and fish. We provide a picture of the complexity of the connexin/pannexin network illustrating functional importance of these proteins in maintaining the integrity of the epidermal barrier. The differential regulation and expression of connexins and pannexins during skin renewal, together with a number of epidermal, hair and nail abnormalities associated with mutations in connexins, emphasize that the correct balance of connexin and pannexin expression is critical for maintenance of the skin and its appendages with both channel and non-channel functions playing profound roles. Changes in connexin expression during both hair and feather regeneration provide suggestions of specialized communication compartments. Finally, we discuss the potential use of zebrafish as a model for connexin skin biology, where evidence mounts that differential connexin expression is involved in skin patterning and pigmentation.
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Transformative applications in biomedicine require the discovery of complex regulatory networks that explain the development and regeneration of anatomical structures, and reveal what external signals will trigger desired changes of large-scale pattern. Despite recent advances in bioinformatics, extracting mechanistic pathway models from experimental morphological data is a key open challenge that has resisted automation. The fundamental difficulty of manually predicting emergent behavior of even simple networks has limited the models invented by human scientists to pathway diagrams that show necessary subunit interactions but do not reveal the dynamics that are sufficient for complex, self-regulating pattern to emerge. To finally bridge the gap between high-resolution genetic data and the ability to understand and control patterning, it is critical to develop computational tools to efficiently extract regulatory pathways from the resultant experimental shape phenotypes. For example, planarian regeneration has been studied for over a century, but despite increasing insight into the pathways that control its stem cells, no constructive, mechanistic model has yet been found by human scientists that explains more than one or two key features of its remarkable ability to regenerate its correct anatomical pattern after drastic perturbations. We present a method to infer the molecular products, topology, and spatial and temporal non-linear dynamics of regulatory networks recapitulating in silico the rich dataset of morphological phenotypes resulting from genetic, surgical, and pharmacological experiments. We demonstrated our approach by inferring complete regulatory networks explaining the outcomes of the main functional regeneration experiments in the planarian literature; By analyzing all the datasets together, our system inferred the first systems-biology comprehensive dynamical model explaining patterning in planarian regeneration. This method provides an automated, highly generalizable framework for identifying the underlying control mechanisms responsible for the dynamic regulation of growth and form.
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Understanding how organisms establish their form during embryogenesis and regeneration represents a major knowledge gap in biological pattern formation. It has been recently suggested that morphogenesis could be understood in terms of cellular information processing and the ability of cell groups to model shape. Here, we offer a proof of principle that self-assembly is an emergent property of cells that share a common (genetic and epigenetic) model of organismal form. This behaviour is formulated in terms of variational free-energy minimization-of the sort that has been used to explain action and perception in neuroscience. In brief, casting the minimization of thermodynamic free energy in terms of variational free energy allows one to interpret (the dynamics of) a system as inferring the causes of its inputs-and acting to resolve uncertainty about those causes. This novel perspective on the coordination of migration and differentiation of cells suggests an interpretation of genetic codes as parametrizing a generative model-predicting the signals sensed by cells in the target morphology-and epigenetic processes as the subsequent inversion of that model. This theoretical formulation may complement bottom-up strategies-that currently focus on molecular pathways-with (constructivist) top-down approaches that have proved themselves in neuroscience and cybernetics.
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Biophysical forces play important roles throughout embryogenesis, but the roles of spatial differences in cellular resting potentials during large-scale brain morphogenesis remain unknown. Here, we implicate endogenous bioelectricity as an instructive factor during brain patterning in Xenopus laevis. Early frog embryos exhibit a characteristic hyperpolarization of cells lining the neural tube; disruption of this spatial gradient of the transmembrane potential (Vmem) diminishes or eliminates the expression of early brain markers, and causes anatomical mispatterning of the brain, including absent or malformed regions. This effect is mediated by voltage-gated calcium signaling and gap-junctional communication. In addition to cell-autonomous effects, we show that hyperpolarization of transmembrane potential (Vmem) in ventral cells outside the brain induces upregulation of neural cell proliferation at long range. Misexpression of the constitutively active form of Notch, a suppressor of neural induction, impairs the normal hyperpolarization pattern and neural patterning; forced hyperpolarization by misexpression of specific ion channels rescues brain defects induced by activated Notch signaling. Strikingly, hyperpolarizing posterior or ventral cells induces the production of ectopic neural tissue considerably outside the neural field. The hyperpolarization signal also synergizes with canonical reprogramming factors (POU and HB4), directing undifferentiated cells toward neural fate in vivo. These data identify a new functional role for bioelectric signaling in brain patterning, reveal interactions between Vmem and key biochemical pathways (Notch and Ca(2+) signaling) as the molecular mechanism by which spatial differences of Vmem regulate organogenesis of the vertebrate brain, and suggest voltage modulation as a tractable strategy for intervention in certain classes of birth defects. Copyright © 2015 the authors 0270-6474/15/354366-20$15.00/0.
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We present here a new model of the cellular dynamics that enable regeneration of complex biological morphologies. Biological cell structures are considered as an ensemble of mathematical points on the plane. Each cell produces a signal which propagates in space and is received by other cells. The total signal received by each cell forms a signal distribution defined on the cell structure. This distribution characterizes the geometry of the cell structure. If a part of this structure is removed, the remaining cells have two signals. They keep the value of the signal which they had before the amputation (memory), and they receive a new signal produced after the amputation. Regeneration of the cell structure is stimulated by the difference between the old and the new signals. It is stopped when the two signals coincide. The algorithm of regeneration contains certain rules which are essential for its functioning, being the first quantitative model of cellular memory that implements regeneration of complex patterns to a specific target morphology. Correct regeneration depends on the form and the size of the cell structure, as well as on some parameters of regeneration.
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How periodic patterns are generated is an open question. A number of mechanisms have been proposed - most famously, Turing's reaction-diffusion model. However, many theoretical and experimental studies focus on the Turing mechanism while ignoring other possible mechanisms. Here, we use a general model of periodic patterning to show that different types of mechanism (molecular, cellular, mechanical) can generate qualitatively similar final patterns. Observation of final patterns is therefore not sufficient to favour one mechanism over others. However, we propose that a mathematical approach can help to guide the design of experiments that can distinguish between different mechanisms, and illustrate the potential value of this approach with specific biological examples. © 2015. Published by The Company of Biologists Ltd.
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In addition to the immediate microenvironment, long-range signaling may be an important component of cancer. Molecular-genetic analyses have implicated gap junctions—key mediators of cell-cell communication—in carcinogenesis. We recently showed that the resting voltage potential of distant cell groups is a key determinant of metastatic transformation and tumor induction. Here, we show in the Xenopus laevis model that gap junctional communication (GJC) is a modulator of the long-range bioelectric signaling that regulates tumor formation. Genetic disruption of GJC taking place within tumors, within remote host tissues, or between the host and tumors significantly lowers the incidence of tumors induced by KRAS mutations. The most pronounced suppression of tumor incidence was observed upon GJC disruption taking place farther away from oncogene-expressing cells, revealing a role for GJC in distant cells in the control of tumor growth. In contrast, enhanced GJC communication through the overexpression of wild-type connexin Cx26 increased tumor incidence. Our data confirm a role for GJC in tumorigenesis, and reveal that this effect is non-local. Based on these results and on published data on movement of ions through GJs, we present a quantitative model linking the GJC coupling and bioelectrical state of cells to the ability of oncogenes to initiate tumorigenesis. When integrated with data on endogenous bioelectric signaling during left-right patterning, the model predicts differential tumor incidence outcomes depending on the spatial configurations of gap junction paths relative to tumor location and major anatomical body axes. Testing these predictions, we found that the strongest influence of GJ modulation on tumor suppression by hyperpolarization occurred along the embryonic left-right axis. Together, these data reveal new, long-range aspects of cancer control by the host's physiological parameters.
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Planarians are an important model organism for regeneration and stem cell research. A complete understanding of stem cell and regeneration dynamics in these animals requires time-lapse imaging in vivo, which has been difficult to achieve due to a lack of tissue-specific markers and the strong negative phototaxis of planarians. We have developed the Planarian Immobilization Chip (PIC) for rapid, stable immobilization of planarians for in vivo imaging without injury or biochemical alteration. The chip is easy and inexpensive to fabricate, and worms can be mounted for and removed after imaging within minutes. We show that the PIC enables significantly higher-stability immobilization than can be achieved with standard techniques, allowing for imaging of planarians at sub-cellular resolution in vivo using brightfield and fluorescence microscopy. We validate the performance of the PIC by performing time-lapse imaging of planarian wound closure and sequential imaging over days of head regeneration. We further show that the device can be used to immobilize Hydra, another photophobic regenerative model organism. The simple fabrication, low cost, ease of use, and enhanced specimen stability of the PIC should enable its broad application to in vivo studies of stem cell and regeneration dynamics in planarians and Hydra.
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We illustrate shape mode analysis as a simple, yet powerful technique to concisely describe complex biological shapes and their dynamics. We analyze two typical examples featuring (i) the bend centerline of beating flagella, and (ii) the closed boundary outline of gliding flatworms. Here, shape mode analysis is based on the mathematical technique of principal component analysis and allows to project a multi-feature data set on a small set of empirical shape modes, which are directly inferred from the data itself. Complex shape dynamics are thus characterized by a small number of shape scores that change in time. We present this method using descriptive examples, explaining abstract mathematics in a graphic way.
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The microenvironment is increasingly recognized as a crucial aspect of cancer. In contrast and complement to the field's focus on biochemical factors and extracellular matrix, we characterize a novel aspect of host:tumor interaction - endogenous bioelectric signals among non-excitable somatic cells. Extending prior work focused on the bioelectric state of cancer cells themselves, we show for the first time that the resting potentials of distant cells are critical for oncogene-dependent tumorigenesis. In the Xenopus laevis tadpole model, we used human oncogenes such as mutant KRAS to drive formation of tumor-like structures that exhibited overproliferation, increased nuclear size, hypoxia, acidity, and leukocyte attraction. Remarkably, misexpression of hyperpolarizing ion channels at distant sites within the tadpole significantly reduced the incidence of these tumors. The suppression of tumorigenesis could also be achieved by hyperpolarization using native CLIC1 chloride channels, suggesting a treatment modality not requiring gene therapy. Using a dominant negative approach, we implicate HDAC1 as the mechanism by which resting potential changes affect downstream cell behaviors. Based on published data on the voltage-mediated changes of butyrate flux through the SLC5A8 transporter, we present a model linking resting potentials of host cells to the ability of oncogenes to initiate tumorigenesis. Antibiotic data suggest that the relevant butyrate is generated by a native bacterial species, identifying a novel link between the microbiome and cancer that is mediated by alterations in bioelectric signaling.
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The systems movement is made up of many systems societies as well as of disciplinary researchers and researches, explicitly or implicitly focusing on the subject of systemics, officially introduced in the scientific community fifty years ago. Many researches in different fields have been and continue to be sources of new ideas and challenges for the systems community. To this regard, a very important topic is the one of EMERGENCE. Between the goals for the actual and future systems scientists there is certainly the definition of a general theory of emergence and the building of a general model of it. The Italian Systems Society, Associazione Italiana per la Ricerca sui Sistemi (AIRS), decided to devote its Second National Conference to this subject. Because AIRS is organized under the form of a network of researchers, institutions, scholars, professionals, and teachers, its research activity has an impact at different levels and in different ways. Thus the topic of emergence was not only the focus of this conference but it is actually the main subject of many AIRS activities.
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A major goal of regenerative medicine and bioengineering is the regeneration of complex organs, such as limbs, and the capability to create artificial constructs (so-called biobots) with defined morphologies and robust self-repair capabilities. Developmental biology presents remarkable examples of systems that self-assemble and regenerate complex structures toward their correct shape despite significant perturbations. A fundamental challenge is to translate progress in molecular genetics into control of large-scale organismal anatomy, and the field is still searching for an appropriate theoretical paradigm for facilitating control of pattern homeostasis. However, computational neuroscience provides many examples in which cell networks - brains - store memories (e.g., of geometric configurations, rules, and patterns) and coordinate their activity towards proximal and distant goals. In this Perspective, we propose that programming large-scale morphogenesis requires exploiting the information processing by which cellular structures work toward specific shapes. In non-neural cells, as in the brain, bioelectric signaling implements information processing, decision-making, and memory in regulating pattern and its remodeling. Thus, approaches used in computational neuroscience to understand goal-seeking neural systems offer a toolbox of techniques to model and control regenerative pattern formation. Here, we review recent data on developmental bioelectricity as a regulator of patterning, and propose that target morphology could be encoded within tissues as a kind of memory, using the same molecular mechanisms and algorithms so successfully exploited by the brain. We highlight the next steps of an unconventional research program, which may allow top-down control of growth and form for numerous applications in regenerative medicine and synthetic bioengineering.