title: Quantifying Waddington landscapes and paths of non-adiabatic cell fate decisions for differentiation, reprogramming and transdifferentiation.
abstract: Cellular differentiation, reprogramming and transdifferentiation are determined by underlying gene regulatory networks. Non-adiabatic regulation via slow binding/unbinding to the gene can be important in these cell fate decision-making processes. Based on a stem cell core gene network, we uncovered the stem cell developmental landscape. As the binding/unbinding speed decreases, the landscape topography changes from bistable attractors of stem and differentiated states to more attractors of stem and other different cell states as well as substates. Non-adiabaticity leads to more differentiated cell types and provides a natural explanation for the heterogeneity observed in the experiments. We quantified Waddington landscapes with two possible cell fate decision mechanisms by changing the regulation strength or regulation timescale (non-adiabaticity). Transition rates correlate with landscape topography through barrier heights between different states and quantitatively determine global stability. We found the optimal speeds of these cell fate decision-making processes. We quantified biological paths and predict that differentiation and reprogramming go through an intermediate state (IM1), whereas transdifferentiation goes through another intermediate state (IM2). Some predictions are confirmed by recent experimental studies.
authors.affiliation: Department of Chemistry and Physics, State University of New York at Stony Brook, , Stony Brook, NY, USA.
authors.forename: Chunhe
authors.initials: C
authors.lastname: Li
authors.forename: Jin
authors.initials: J
authors.lastname: Wang
mesh_terms: D002454:Cell Differentiation; D019295:Computational Biology; D057890:Epigenomics; D053263:Gene Regulatory Networks; D008957:Models, Genetic; D013234:Stem Cells / Q000166:cytology / Q000502:physiology*
keywords: differentiation and reprogramming; dynamical path; non-adiabatic; potential landscape