Cause and Necessity of Metabolic Adaptations in Human Epidermis

The epidermis is the outermost layer of human skin, and acts as primary barrier to physical, chemical, infective, and ultra-violet light insults. It is a rapidly self-renewing organ, composed primarily by keratinocytes that proliferate continuously in deeper layers and differentiate during their movement towards the surface undergoing morphological changes which are critical for skin homeostasis. This process is enabled by a dynamic metabolic activity, which is fine-tuned during the course of differentiation to fulfill the diverging demands of different layers. To date, however, we lack a precise and formal description of the intracellular metabolic and regulatory transients necessary to support epidermal function. Such a model constitutes a pivotal cornerstone towards understanding epidermal conditions and devising rational therapeutic strategies.

In this interdisciplinary PhD project at the interface between cellular and computational biology we aim at producing a holistic and systematic analysis of the metabolic adaptation in human keratinocytes. We use non-targeted mass spectrometry-based metabolomics to thoroughly characterize the activity in keratinocyte metabolism with unprecedented coverage and temporal resolution. A novel computational analysis based on Markov Random Fields will be used to build a model that describes the time-dependent metabolic pathway utilization to support the four critical functions of (i) proliferation, (ii) construction of the impermeable, extracellular lipid/protein layer, (iii) anti-oxidative response, and (iv) energy generation. Integration with matched gene expression data will inform on the transcriptional control of critical pathways.  Finally, we will seek in expression data from skin samples collected from young and elder humans for putative causes for the reduced metabolic capacity coupled to skin aging. Our model will be used to formulate compensatory strategies.

Keywords: Human skin, keratinocyte differentiation, metabolism, probabilistic graphical modeling