Nervous system and tissue polarity dynamically adapt to new morphologies in planaria

Volume X-Ray Micro-Computed Tomography Analysis of the Early Cephalized Central Nervous System in a Marine Flatworm, Stylochoplana pusilla

Platyhelminthes are a phylum of simple bilaterian invertebrates with prototypic body systems. Compared with non-bilaterians such as cnidarians, the bilaterians are likely to exhibit integrated free-moving behaviors, which require a concentrated nervous system "brain" rather than the distributed nervous system of radiatans. Marine flatworms have an early cephalized 'central' nervous system compared not only with non-bilaterians but also with parasitic flatworms or freshwater planarians. In this study, we used the marine flatworm Stylochoplana pusilla as an excellent model organism in Platyhelminthes because of the early cephalized central nervous system. Here, we investigated the three-dimensional structures of the flatworm central nervous system by the use of X-ray micro-computed tomography (micro-CT) in a synchrotron radiation facility. We found that the obtained tomographic images were sufficient to discriminate some characteristic structures of the nervous system, including nerve cords around the cephalic ganglion, mushroom body-like structures, and putative optic nerves forming an optic commissure-like structure. Through the micro-CT imaging, we could obtain undistorted serial section images, permitting us to visualize precise spatial relationships of neuronal subpopulations and nerve tracts. 3-D micro-CT is very effective in the volume analysis of the nervous system at the cellular level; the methodology is straightforward and could be applied to many other non-model organisms.

Bioelectric networks: the cognitive glue enabling evolutionary scaling from physiology to mind

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.

Closing the loop on morphogenesis: a mathematical model of morphogenesis by closed-loop reaction-diffusion

Morphogenesis, the establishment and repair of emergent complex anatomy by groups of cells, is a fascinating and biomedically-relevant problem. One of its most fascinating aspects is that a developing embryo can reliably recover from disturbances, such as splitting into twins. While this reliability implies some type of goal-seeking error minimization over a morphogenic field, there are many gaps with respect to detailed, constructive models of such a process. A common way to achieve reliability is negative feedback, which requires characterizing the existing body shape to create an error signal-but measuring properties of a shape may not be simple. We show how cells communicating in a wave-like pattern could analyze properties of the current body shape. We then describe a closed-loop negative-feedback system for creating reaction-diffusion (RD) patterns with high reliability. Specifically, we use a wave to count the number of peaks in a RD pattern, letting us use a negative-feedback controller to create a pattern with N repetitions, where N can be altered over a wide range. Furthermore, the individual repetitions of the RD pattern can be easily stretched or shrunk under genetic control to create, e.g., some morphological features larger than others. This work contributes to the exciting effort of understanding design principles of morphological computation, which can be used to understand evolved developmental mechanisms, manipulate them in regenerative-medicine settings, or engineer novel synthetic morphology constructs with desired robust behavior.

Transplantation of fragments from different planaria: A bioelectrical model for head regeneration

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 regenerated 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.

Epigenetics, ovarian cell plasticity, and platelet-rich plasma: Mechanistic theories

Ovarian platelet-rich plasma (PRP) is claimed to restore the fertility potential by improving reserve, an effect perhaps mediated epigenetically by platelet-discharged regulatory elements rather than gonadotropin-activated G-protein coupled receptors, as with stimulated in vitro fertilization (IVF). The finding that fresh activated platelet releasate includes factors able to promote developmental signaling networks necessary to enable cell pluripotency tends to support this theory. The mechanistic uncertainty of intraovarian PRP notwithstanding, at least two other major challenges confront this controversial intervention. The first challenge is to clarify how perimenopausal ovarian function is reset to levels consistent with ovulation. Perhaps a less obvious secondary problem is to confine this renewal such that any induced recalibration of cellular plasticity is kept within acceptable physiologic bounds. Thus, any 'drive' to ovarian rejuvenation must incorporate both accelerator and brake. Ovarian aging may be best viewed as a safeguard against pathologic overgrowth, where senescence operates as an evolved tumor-suppression response. While most ovary cells reach the close of their metabolic life span with low risk for hypertrophy, enhanced lysosomal activity and the proinflammatory 'senescence-associated secretory phenotype' usually offsets this advantage over time. But is recovery of ovarian fitness possible, even if only briefly prior to IVF? Alterations in gap junctions, bio-conductive features, and modulation of gene regulatory networks after PRP use in other tissues are discussed here alongside early data reported from reproductive medicine.

An insight into planarian regeneration

Background

Planarian has attracted increasing attentions in the regeneration field for its usefulness as an important biological model organism attributing to its strong regeneration ability. Both the complexity of multiple regulatory networks and their coordinate functions contribute to the maintenance of normal cellular homeostasis and the process of regeneration in planarian. The polarity, size, location and number of regeneration tissues are regulated by diverse mechanisms. In this review we summarize the recent advances about the importance genetic and molecular mechanisms for regeneration control on various tissues in planarian.

Methods

A comprehensive literature search of original articles published in recent years was performed in regards to the molecular mechanism of each cell types during the planarian regeneration, including neoblast, nerve system, eye spot, excretory system and epidermal.

Results

Available molecular mechanisms gave us an overview of regeneration process in every tissue. The sense of injuries and initiation of regeneration is regulated by diverse genes like follistatin and ERK signaling. The Neoblasts differentiate into tissue progenitors under the regulation of genes such as egfr‐3. The regeneration polarity is controlled by Wnt pathway, BMP pathway and bioelectric signals. The neoblast within the blastema differentiate into desired cell types and regenerate the missing tissues. Those tissue specific genes regulate the tissue progenitor cells to differentiate into desired cell types to complete the regeneration process.

Conclusion

All tissue types in planarian participate in the regeneration process regulated by distinct molecular factors and cellular signaling pathways. The neoblasts play vital roles in tissue regeneration and morphology maintenance. These studies provide new insights into the molecular mechanisms for regulating planarian regeneration.

A Computational Approach to Explaining Bioelectrically Induced Persistent, Stochastic Changes of Axial Polarity in Planarian Regeneration

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.

Minimal Developmental Computation: A Causal Network Approach to Understand Morphogenetic Pattern Formation

What information-processing strategies and general principles are sufficient to enable self-organized morphogenesis in embryogenesis and regeneration? We designed and analyzed a minimal model of self-scaling axial patterning consisting of a cellular network that develops activity patterns within implicitly set bounds. The properties of the cells are determined by internal 'genetic' networks with an architecture shared across all cells. We used machine-learning to identify models that enable this virtual mini-embryo to pattern a typical axial gradient while simultaneously sensing the set boundaries within which to develop it from homogeneous conditions-a setting that captures the essence of early embryogenesis. Interestingly, the model revealed several features (such as planar polarity and regenerative re-scaling capacity) for which it was not directly selected, showing how these common biological design principles can emerge as a consequence of simple patterning modes. A novel "causal network" analysis of the best model furthermore revealed that the originally symmetric model dynamically integrates into intercellular causal networks characterized by broken-symmetry, long-range influence and modularity, offering an interpretable macroscale-circuit-based explanation for phenotypic patterning. This work shows how computation could occur in biological development and how machine learning approaches can generate hypotheses and deepen our understanding of how featureless tissues might develop sophisticated patterns-an essential step towards predictive control of morphogenesis in regenerative medicine or synthetic bioengineering contexts. The tools developed here also have the potential to benefit machine learning via new forms of backpropagation and by leveraging the novel distributed self-representation mechanisms to improve robustness and generalization.

Morphology changes induced by intercellular gap junction blocking: A reaction-diffusion mechanism

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.

Does regeneration recapitulate phylogeny? Planaria as a model of body-axis specification in ancestral eumetazoa

Metazoan body plans combine well-defined primary, secondary, and in many bilaterians, tertiary body axes with structural asymmetries at multiple scales. Despite decades of study, how axis-defining symmetries and system-defining asymmetries co-emerge during both evolution and development remain open questions. Regeneration studies in asexual planaria have demonstrated an array of viable forms with symmetrized and, in some cases, duplicated body axes. We suggest that such forms may point toward an ancestral eumetazoan form with characteristics of both cnidarians and placazoa.