Information integration during bioelectric regulation of morphogenesis of the embryonic frog brain

Santosh Manicka; Vaibhav P Pai; Michael Levin

doi:10.1016/j.isci.2023.108398

Information integration during bioelectric regulation of morphogenesis of the embryonic frog brain

iScience. 2023 Nov 4;26(12):108398. doi: 10.1016/j.isci.2023.108398. eCollection 2023 Dec 15.

Authors

Santosh Manicka¹, Vaibhav P Pai¹, Michael Levin^{1

2}

Affiliations

¹ Allen Discovery Center at Tufts University, Medford, MA 02155, USA.
² Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA.

Abstract

Spatiotemporal patterns of cellular resting potential regulate several aspects of development. One key aspect of the bioelectric code is that transcriptional and morphogenetic states are determined not by local, single-cell, voltage levels but by specific distributions of voltage across cell sheets. We constructed and analyzed a minimal dynamical model of collective gene expression in cells based on inputs of multicellular voltage patterns. Causal integration analysis revealed a higher-order mechanism by which information about the voltage pattern was spatiotemporally integrated into gene activity, as well as a division of labor among and between the bioelectric and genetic components. We tested and confirmed predictions of this model in a system in which bioelectric control of morphogenesis regulates gene expression and organogenesis: the embryonic brain of the frog Xenopus laevis. This study demonstrates that machine learning and computational integration approaches can advance our understanding of the information-processing underlying morphogenetic decision-making, with a potential for other applications in developmental biology and regenerative medicine.

Keywords: Biomimetics; Complex system biology; Embryology; In silico biology; Model organism.