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Lab's New Directions
"The so-called 'polarity' exhibited in the regeneration of animals has
suggested the idea to a number of writers that the phenomenon might be related to,
or the outcome of differences in potential in different regions;
or, in other words, of electrical polarity."
Bioelectricity Projects in the Levin Lab
Bioelectrical controls of vertebrate appendage regeneration
Regeneration is a fascinating example of pattern regulation, and has
important biomedical implications. A regenerating system must not only recognize
damage, but also pursue a goal-directed process of restoring the missing structures
(and crucially, know to stop when this process is complete, thus avoiding
cancerous overgrowth). Interestingly, systems with high regenerative ability
have low susceptibility to neoplasm, contrary to the simple view in which
cellular plasticity and propensity for proliferation should go together in
cancer and regeneration. Instead, data suggest that the morphogenetic controls
imposed during regeneration can prevent cells from ignoring the patterning cues
of the host (as occurs in many cancers). What is the mechanistic nature of these
controls? Our lab studies the role of voltage gradients, and how these biophysical
controls couple to genetic and epigenetic pathways in the induction of
regeneration and the imposition of correct morphology on the restored tissue. We
mainly use two model systems to understand these processes: Xenopus laevis
tadpoles and planarian flatworms. An important part of our mission is the
development of molecular reagents, protocols, databases, transgenic animals, and
conceptual (modeling) tools to facilitate others' study of bioelectrical signals
in many aspects of morphogenesis in diverse model systems.
Bioelectrical, non-local controls of regenerative polarity in planaria
Planarian flatworms have an impressive capacity for regeneration. They are able to regenerate large parts of the body, and are continuously maintained by a well-characterized resident population of adult stem cells. Upon cutting, these organisms are able to regenerate the head and tail at their appropriate locations. What mechanisms determine the polarity and allow tissue re-patterning to take place? Consider: after bisection, cells on one side of the cut (in the head fragment's posterior end) will form a tail, while cells which were their immediate neighbors before the cut will make a head (the tail fragment's anterior half). Our data suggest that the mechanism by which blastema cells polls the rest of the host (to determine where the wound is located and what other tissues already exist in the fragment and thus don't need to be recreated) is mediated by physiological signals passing through nerves and long-range gap junctional paths. We have identified endogenous ion fluxes and voltage gradients maintained by specific ion pumps which are crucial for the determination of anterior-posterior polarity during regeneration; manipulating these signals allows us to specify tissue identity and thus control the anatomical structure of regenerating worms. Through studying the roles of electrical polarity (maintained by ion channel and gap junction systems) in planarian regeneration we are gaining insight into the control of regeneration and morphogenesis by endogenous ion fluxes and into the mechanisms by which stem cell differentiation is integrated into functional organ/tissue systems within the organism. Most importantly, we've recently shown that a rapid, transient alteration of the physiological signals underlying morphostasis and regeneration is maintained in perpetuity! That is, worms forming 2 heads (one at each end) because of a 2-day disruption of gap junctional signals will continue to form 2 heads through subsequent months of amputation or fission in normal conditions. These data illustrate how information embedded in physiological networks can be solidified into permanent alteration of the large-scale structure bodyplan. More broadly, this work identifies a molecular glimpse of how the "target morphology" of an animal (the form towards which regeneration regulates) can be permanently reset, and reveals that a drastic change in body structure and behavior can be maintained across a complex metazoan's organism's normal mode of reproduction without any change in DNA sequence.
Cancer as a problem of morphogenetic disorganization
One view of cancer (distinct from the current paradigm of intrinsically "cancerous" cells resulting from specific DNA modifications) is as a problem of organization within a "society of cells". Cancer is, in some sense, a disease of geometry - a failure of cells to attend to the signals that normally organize their behavior towards the patterning needs of the host. This view is supported by classical and recent data showing that aggressive cancer cells can be normalized by regenerative and embryonic environments - context is crucial, and environments in which tight morphogenetic cues are being imposed have the ability to reverse or reboot cancer phenotypes. The converse is also true: we have found a bioelectrical property that imposes a neoplastic-like phenotype upon pigment cells in vivo. This is not surprising, given that a significant component of morphogenetic cues are ionic in nature. Remarkably however, this effect is non-local in nature - it is the transmembrane potential of other, quite distant cells that determines the metastasis-like effect. We are pursuing several lines of inquiry including 1) developing methods for tracking bioelectrical signatures of pre-tumor cells as a non-invasive diagnostic modality, 2) understanding how voltage properties of distant cells can be a cancer-triggering event in the body, and 3) learning to control transmembrane potential of key cell types to normalize existing tumors.
Gap Junctions in Pattern Formation:
Bioelectric Aspects of Very Early Left-Right Patterning
The Role of Serotonin in Embryogenesis:
Mathematical Modeling and Physiomics:
Molecular biology and genomics are revealing a constantly expanding amount of information about genes, their products, and the way they interact. It is notoriously difficult to control or make predictions about systems involving mutual interactions of even a few components because of feedback loops and the basic results of dynamical systems theory. Indeed, looking at a high-resolution mechanistic pathway, such as painstakingly elucidated in many recent studies, is insufficient for knowing what biological pattern this transcriptional network results in. It is essential to develop constructive, synthetic models of morphogenesis which integrate 3-dimensional shape from the function of molecular components and pathways. To fully understand the implications of information coming from genome projects and biochemical analyses of gene activities for morphogenesis, a synthesis is needed. We are attempting to use the mathematical and computer modeling tools of chaos, information, and complexity theories to understand large-scale patterning and control properties of bioelectrical mechanisms and small molecule transport among cell groups. Our main efforts along these lines are directed towards (1) development of a formalization for morphogenetic processes (bioinformatics of shape, beyond gene/protein sequence, and automated model discovery), (2) testing the hypothesis that cell behavior can be understood as the segregation and movement of cell states through a multi-dimensional state space with axes defined by bioelectrical parameters such as membrane voltage, K+ content, pH, nuclear membrane potential, etc., and (3) developing quantitative models integrating physiology and genetics of ion transporter function during early left-right asymmetry.
Computational Approaches to Pattern Formation:
Bioinformatics has revolutionized molecular biology, but the field still largely lacks necessary computational tools to crack the problem of pattern regulation and control. With each new functional or high-resolution genomic dataset, it becomes ever more difficult to come up with constructive models that explain how complex pattern arises, and what steps could be taken to induce the kinds of patterning changes required for regenerative medicine and the repair of birth defects. Thus, we are working towards a set of software tools that utilize the principles of machine learning and artificial intelligence to establish a bioinformatics of shape. Our goal is to understand the fundamental rules that allow complex patterns to be formed and to repair themselves after damage, and to discover models of these processes that are not merely lists of necessary gene products but algorithms that clearly reveal the regulation of shape, size, topology, and anatomical arrangement. To this end, we have produced novel formalisms for describing functional experiments and resulting anatomical outcomes, and a genetic algorithm-based platform for discovery of mechanistic models that explain complex patterning results in the published literature. This resulted in the first quantitative model of planarian regeneration explaining numerous experimental datasets, and the first regenerative model discovered by a non-human intelligence (a machine learning platform). Importantly, our goal is not only to understand specifics of real model organisms (e.g., planarian regeneration) but to uncover broad general principles useful for synthetic morphology applications - an Artificial Life perspective. Another aspect of this work is the study of computation in biological tissues (which process information in order to regulate and remodel their shape). Thus for example, we are not simply trying to make computational models to explain planarian regeneration, but rather, we see the planarian itself as a model of the kind of computation we want to understand. Additional projects include computational models of emergent signaling dynamics that explain stochastic behavior and pattern dysregulation in cancer.
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