Author: Levin M1, Martyniuk CJ2
Affiliation: <sup>1</sup>Allen Discovery Center at Tufts University, Center for Regenerative and Developmental Biology, Biology Department, Tufts University, 200 Boston Avenue, Suite 4600 Medford, MA 02155, USA. Electronic address: michael.levin@tufts.edu.
<sup>2</sup>Department of Physiological Sciences and Center for Environmental and Human Toxicology, University of Florida Genetics Institute, Interdisciplinary Program in Biomedical Sciences Neuroscience, College of Veterinary Medicine, University of Florida, Gainesville, FL, 32611, USA.
Conference/Journal: Biosystems.
Date published: 2017 Aug 27
Other:
Pages: S0303-2647(17)30284-8 , Special Notes: doi: 10.1016/j.biosystems.2017.08.009. [Epub ahead of print] , Word Count: 194
What determines large-scale anatomy? DNA does not directly specify geometrical arrangements of tissues and organs, and a process of encoding and decoding for morphogenesis is required. Moreover, many species can regenerate and remodel their structure despite drastic injury. The ability to obtain the correct target morphology from a diversity of initial conditions reveals that the morphogenetic code implements a rich system of pattern-homeostatic processes. Here, we describe an important mechanism by which cellular networks implement pattern regulation and plasticity: bioelectricity. All cells, not only nerves and muscles, produce and sense electrical signals; in vivo, these processes form bioelectric circuits that harness individual cell behaviors toward specific anatomical endpoints. We review emerging progress in reading and re-writing anatomical information encoded in bioelectrical states, and discuss the approaches to this problem from the perspectives of information theory, dynamical systems, and computational neuroscience. Cracking the bioelectric code will enable much-improved control over biological patterning, advancing basic evolutionary developmental biology as well as enabling numerous applications in regenerative medicine and synthetic bioengineering.
Copyright © 2017 Elsevier B.V. All rights reserved.
KEYWORDS: Bayesian inference; Bioelectricity; Dynamical system theory; Embryogenesis; Ion channels; Morphogenesis; Patterning; Primitive cognition; Regeneration
PMID: 28855098 DOI: 10.1016/j.biosystems.2017.08.009