CELLoGeNe - An energy landscape framework for logical networks controlling cell decisions

Emil Andersson; Mattias Sjö; Keisuke Kaji; Victor Olariu

doi:10.1016/j.isci.2022.104743

CELLoGeNe - An energy landscape framework for logical networks controlling cell decisions

iScience. 2022 Jul 14;25(8):104743. doi: 10.1016/j.isci.2022.104743. eCollection 2022 Aug 19.

Authors

Emil Andersson¹, Mattias Sjö¹, Keisuke Kaji², Victor Olariu¹

Affiliations

¹ Computational Biology and Biological Physics, Department of Astronomy and Theoretical Physics, Lund University, Sölvegatan 14A, 221 00 Lund, Sweden.
² Centre for Regenerative Medicine, University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh EH16 4UU, UK.

Abstract

Experimental and computational efforts are constantly made to elucidate mechanisms controlling cell fate decisions during development and reprogramming. One powerful computational method is to consider cell commitment and reprogramming as movements in an energy landscape. Here, we develop Computation of Energy Landscapes of Logical Gene Networks (CELLoGeNe), which maps Boolean implementation of gene regulatory networks (GRNs) into energy landscapes. CELLoGeNe removes inadvertent symmetries in the energy landscapes normally arising from standard Boolean operators. Furthermore, CELLoGeNe provides tools to visualize and stochastically analyze the shapes of multi-dimensional energy landscapes corresponding to epigenetic landscapes for development and reprogramming. We demonstrate CELLoGeNe on two GRNs governing different aspects of induced pluripotent stem cells, identifying experimentally validated attractors and revealing potential reprogramming roadblocks. CELLoGeNe is a general framework that can be applied to various biological systems offering a broad picture of intracellular dynamics otherwise inaccessible with existing methods.

Keywords: Bioinformatics; Cell biology; Mathematical biosciences; Stem cells research; Systems biology.