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

Bischof, Johanna; Miller, Kelsie A.; LaPalme, Jennifer V.; Levin, Michael

doi:10.1016/j.ydbio.2020.08.009

Cited by 9 publications

(6 citation statements)

References 48 publications

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“…In this regard, the boundary-marker represents the antagonistic version of “growth factors” that biological cells signal to neighboring cells to divide [ 64 ]. Another important feature of the model is that the intrinsic controller is designed to support the implementation of planar cell polarity (PCP) that gives the cell a sense of polarity, a feature that is known to play an important role in the development of organism-level axial polarity [ 65 , 66 ]. In the model, specifically, the anterior (left) column of the intrinsic controller influences the anterior gap-junction weight, whereas the posterior (right) column influences the posterior gap-junction weight ( Figure 2 ).…”

Section: Model and Methodsmentioning

confidence: 99%

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

Manicka

Levin

2022

Entropy

Self Cite

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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.

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Section: Model and Methodsmentioning

confidence: 99%

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

Manicka

Levin

2022

Entropy

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“…This shift in the target morphology for regeneration is permanent (unless the animal’s bioelectric pattern memory is reset back to a one-headed state by an experimental manipulation). Thus, much like in nervous systems, the architecture underlying memory in this space consists of electrophysiological hardware with a highly reliable default behavior (guiding to the one-head region of morphospace) but also the capacity to be re-written toward other states, which ultimately feed into changes in gene expression and long-term changes in cell properties (Bischof et al 2020 ; Pai et al 2016 ; Pietak et al 2019 ). The standing pattern of resting potential differences which instructively determines the number of heads that will be built is quite literally the memory of the collective intelligence of the body—a bioelectric state that guides its behavior in anatomical morphospace and can be modified by experience in physiological space.…”

Section: Basal Cognition Without Neurons: What Dynamic Bodies Think A...mentioning

confidence: 99%

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

Levin

2023

Anim Cogn

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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.

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“…By visualizing the orientation of cilia beat and cilia-driven flow in living planarians, they found that ciliary beat reorientated within several weeks to match the new axial body plan, and the progresses is independent from cilia beating. 38 Calcium (Ca 2+ ) channel play an important role in depolarizationinduced contractions of muscle, 39 which is indispensable to flatworm neuromuscular physiology. Knockdown of the subunit of Ca 2+ channel will lead to loss of mobility.…”

Section: Impacts Of Physiological Factors On Regenerationmentioning

confidence: 99%

“…Levin et al created double head planarians to demonstrate the flexibility of the body polarity. By visualizing the orientation of cilia beat and cilia‐driven flow in living planarians, they found that ciliary beat reorientated within several weeks to match the new axial body plan, and the progresses is independent from cilia beating 38 …”

Section: Impacts Of Physiological Factors On Regenerationmentioning

confidence: 99%

An insight into planarian regeneration

Han

Zhao

et al. 2022

Cell Proliferation

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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.

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

Cited by 9 publications

References 48 publications

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

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

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

An insight into planarian regeneration

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