Bioelectrical control of positional information in development and regeneration: A review of conceptual and computational advances.

Positional information describes pre-patterns of morphogenetic substances that alter spatio-temporal gene expression to instruct development of growth and form. A wealth of recent data indicate bioelectrical properties, such as the transmembrane potential (Vmem), are involved as instructive signals in the spatiotemporal regulation of morphogenesis. However, the mechanistic relationships between Vmem and molecular positional information are only beginning to be understood. Recent advances in computational modeling are assisting in the development of comprehensive frameworks for mechanistically understanding how endogenous bioelectricity can guide anatomy in a broad range of systems. Vmem represents an extraordinarily strong electric field (∼1.0 × 106 V/m) active over the thin expanse of the plasma membrane, with the capacity to influence a variety of downstream molecular signaling cascades. Moreover, in multicellular networks, intercellular coupling facilitated by gap junction channels may induce directed, electrodiffusive transport of charged molecules between cells of the network to generate new positional information patterning possibilities and characteristics. Given the demonstrated role of Vmem in morphogenesis, here we review current understanding of how Vmem can integrate with molecular regulatory networks to control single cell state, and the unique properties bioelectricity adds to transport phenomena in gap junction-coupled cell networks to facilitate self-assembly of morphogen gradients and other patterns. Understanding how Vmem integrates with biochemical regulatory networks at the level of a single cell, and mechanisms through which Vmem shapes molecular positional information in multicellular networks, are essential for a deep understanding of body plan control in development, regeneration and disease.

• Publication year

  2018

• Venue

  Progress in Biophysics and Molecular Biology

• Publication date

  2018-04-05

• Fields of study

  Biology, Physics, Computer Science, Engineering, Medicine

• Identifiers
  DOI 10.1016/j.pbiomolbio.2018.03.008PMID 29626560PMCID PMC10464501
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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