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Project

Modelling of gene networks for steering of biomimetic production processes in tissue engineering.

The specialization of cartilage cells, or chondrogenic differentiation, is an intricate and meticulously regulated process that plays a vital role in both bone formation and cartilage regeneration. This PhD work centers on the development of computational models to study the molecular regulation of this process. First, we investigate how individual genes and their defects contribute to the overall change in functionality of the growth plate, where chondrogenic differentiation fuels bone growth. As each gene is influenced by a myriad of feedback mechanisms that keep its expression in a desirable range, predicting what will happen if one of these genes defaults is challenging. Therefore, we constructed a qualitative model, focusing on the process of bone formation, that simulates how the intricate interplay between the genes results in a functional growth plate morphology. This model allows the effect of gene knockouts or overexpression to be evaluated from a network perspective, and hence relates this genetic deficiency to the impairment of the gross bone formation on a tissue level. This knowledge can be of great assistance in the design and control of \textit{in vitro} bone tissue engineering processes.

A framework with increased temporal and quantitative resolution is then used to study chondrocyte hypertrophy in an expanded network. Chondrocyte hypertrophy, a process in which cartilage cells enlarge and change their secretion profile to attract bone forming cells and blood vessels, is orchestrated on a molecular level by a switch between two ‘genetic programs’. In this switch, one set of transcription factors that represents chondrocyte proliferation competes with, and is ultimately replaced by, another set that represents hypertrophy. Since hypertrophy plays a vital role not only in the development the skeleton, but is also thought to be involved in several bone-related diseases, it has been studied extensively. We combine information of how individual factors that prevent or contribute to the hypertrophic switch interact in a computational model to develop a more global view of the regulatory network underlying hypertrophy. Through simulations of this regulatory network model we can perform an in silico screening for factors that greatly impact, positively or negatively, the decision to undergo hypertrophy.

The results of this screening are checked for consistency using an ensemble approach. Specifically, a genetic algorithm is used to generate an ensemble of models, differing only in parameter values, whose qualitative dynamics match those observed in the growth plate. The range of behaviour exhibited by individual factors throughout this ensemble is mostly consistent. Additionally, a subset of the network topology is compared to that obtained by inference from growth plate expression profiles. Understanding how individual factors contribute to the hypertrophic switch in the context of the regulatory network has important repercussions in both cartilage and bone tissue engineering. Our approach further suggests several putative targets for intervention in disease processes where hypertrophy plays a role. In summary, this PhD offers and explores a series of tools that form a first step to a rigorous and systems-level understanding of chondrogenic differentiation.

Date:4 Oct 2010  →  30 Sep 2015
Keywords:Gene network, Biomimetics, Boolean, Tissue engineering
Disciplines:Orthopaedics, Surgery, Nursing, Biomechanics, Biological system engineering, Biomaterials engineering, Biomechanical engineering, Medical biotechnology, Other (bio)medical engineering
Project type:PhD project