220 Appendices Chapter overview The aim of this thesis was to establish new in vitro and in silico models to study the role of peroxisomes in malnutrition and medium chain acyl-CoA dehydrogenase deficiency and to gain biological insights of both diseases. The thesis includes a general introduction, presented in chapter 1, in which in vitro and in silico models are introduced as well as the different organelles and diseases described in this thesis. Chapter 1 also introduces the different types of in vitro and in silico models and compares the different approaches available at the moment. In chapter 2 of the thesis, I described how I have developed, together with a collaborator, two in vitro models (using primary-tissue derived organoids) of malnutrition in the liver and intestine. These models recapitulated important characteristic events of malnutrition, including the loss of peroxisomes, loss of intestinal barrier function and accumulation of fat in the liver. At the end of the chapter, we demonstrated how loss of peroxisomes could be prevented by cotreatment with fenofibrate (a pharmacological PPAR-α agonist) in the liver and rapamycin (an autophagy inducer) in the intestine. The hepatic organoid model was then further optimized and applied in chapter 4. In this chapter I focused on the degradation of peroxisomes, in a low-amino acid environment, via autophagy, and tried to find different compounds to activate the synthesis of new peroxisomes. I found that DHA (docosahexaenoic acid) (a polyunsaturated fatty acid) prevented the loss of peroxisomes in low-amino acid conditions. While I observed a minor blockage in peroxisomal degradation, I could not fully elucidate the mechanism of action of DHA. Further work is proposed to understand the mechanism of DHA and its role preventing peroxisomal degradation. Chapters 3 and 5 focus on the development of two in silico models. In chapter 3, I supplied data for and validated a deep-learning tool to track and measure organoids in brightfield images. This tool was developed by a colleague from the European PerICo consortium. This tool was applied to the in vitro hepatic malnutrition model to assess the effects of amino acid deprivation on organoid size and number. The deep learning model was able to replicate the manual counting and measuring of organoids presented in chapter 2. Overall, I demonstrated that hepatic organoids exposed to low amino acids were smaller in size (depending on their developmental stage) while intestinal organoids exhibited shorter crypts (key structures in the intestine that play a crucial role in intestinal regeneration).
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