ABSTRACT
The investigation of epidermal homeostasis and differentiation is ideal for developing systems biological models linking the molecular to the cellular and further on to the tissue level. There to a certain extent literature on in silico models of human epidermis and of course more of epithelia in general. Early models date back to the 1980s when epidermal tissue formation has been simulated with vertical stacks of flattened tetrakaidecahedral cells [1,2]. Mitrani used a lattice-based model to show that upward migration of keratinocytes within the epidermis is a passively driven process. Passive migration results from the extrusion of basal cells due to forces exerted by dividing cells [3]. The first spatial simulation of an epidermis using a lattice-free (off-lattice) model was
developed in 1995. This mode mainly focused on cell proliferation and differentiation [4]. More recently, off-lattice models of epithelial monolayers [5,6] and three-dimensional epithelial cell populations [7] were developed. In 2005, Grabe et al. presented a two-dimensional model of human epidermis that includes not only cell proliferation and differentiation but also the essential process of epidermal barrier formation [8]. Moreover, the transepidermal water flux and the associated flow of Ca2+ ions leading to the characteristic transepidermal Ca2+ gradient was part of this model. Terminal differentiation is controlled by this Ca2+ gradient. Simulation showed a horizontally layered in silico tissue morphology as a result of the Ca2+ differentiation program. An application with clinical relevance of this human epidermal homeostasis model was developed by reproducing main pathological characteristics of psoriatic skin [9]. One of the first three-dimensional epidermal homeostasis models also considering in silico melanoma development was published in the same year [10]. Finally, Adra et al. presented a multi-scaled three-dimensional in silico model of human epidermis linking keratinocyte behavior and transforming growth factor (TGF-β1) signaling [11].
