Modeling non-genetic information dynamics in cells using reservoir computing.

Dipesh Niraula, Issam El Naqa, Jack Adam Tuszynski, Robert A Gatenby
Author Information
  1. Dipesh Niraula: Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA.
  2. Issam El Naqa: Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA.
  3. Jack Adam Tuszynski: Departments of Physics and Oncology, University of Alberta, Edmonton, AB, Canada.
  4. Robert A Gatenby: Departments of Radiology and Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL, USA.

Abstract

Virtually all cells use energy-driven, ion-specific membrane pumps to maintain large transmembrane gradients of Na, K, Cl, Mg, and Ca, but the corresponding evolutionary benefit remains unclear. We propose that these gradients enable a dynamic and versatile biological system that acquires, analyzes, and responds to environmental information. We hypothesize that environmental signals are transmitted into the cell by ion fluxes along pre-existing gradients through gated ion-specific membrane channels. The consequent changes in cytoplasmic ion concentration can generate a local response or orchestrate global/regional cellular dynamics through wire-like ion fluxes along pre-existing and self-assembling cytoskeleton to engage the endoplasmic reticulum, mitochondria, and nucleus.

Keywords

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Grants

  1. R01 CA233487/NCI NIH HHS

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