title: Epithelial topology.
abstract: It is universally accepted that genetic control over basic aspects of cell and molecular biology is the primary organizing principle in development and homeostasis of living systems. However, instances do exist where important aspects of biological order arise without explicit genetic instruction, emerging instead from simple physical principles, stochastic processes, or the complex self-organizing interaction between random and seemingly unrelated parts. Being mostly resistant to direct genetic dissection, the analysis of such emergent processes falls into a grey area between mathematics, physics and molecular cell biology and therefore remains very poorly understood. We recently proposed a mathematical model predicting the emergence of a specific non-Gaussian distribution of polygonal cell shapes from the stochastic cell division process in epithelial cell sheets; this cell shape distribution appears to be conserved across a diverse set of animals and plants.1 The use of such topological models to study the process of cellular morphogenesis has a long history, starting almost a century ago, and many insights from those original works influence current experimental studies. Here we review current and past literature on this topic while exploring some new ideas on the origins and implications of topological order in proliferating epithelia.
authors.affiliation: School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA.
authors.forename: Radhika
authors.initials: R
authors.lastname: Nagpal
authors.forename: Ankit
authors.initials: A
authors.lastname: Patel
authors.forename: Matthew C
authors.initials: MC
authors.lastname: Gibson
mesh_terms: D000818:Animals; D002468:Cell Physiological Phenomena; D049109:Cell Proliferation; D048430:Cell Shape; D004331:Drosophila melanogaster / Q000502:physiology*; D004847:Epithelial Cells / Q000166:cytology*; D004848:Epithelium / Q000033:anatomy & histology* / Q000473:pathology*; D018613:Microscopy, Confocal; D008953:Models, Anatomic; D008954:Models, Biological; D008957:Models, Genetic; D015233:Models, Statistical; D008962:Models, Theoretical; D016011:Normal Distribution; D013269:Stochastic Processes