147 5 Establishing a peroxisomal β-oxidation computational kinetic model to understand the effects of amino-acid restriction of the peroxisomal β-oxidation. The model predicts metabolite concentrations and pathway fluxes under different conditions. This study also highlights the potential to integrate proteomics data obtained into a kinetic model to understand metabolic regulation in peroxisomal diseases. Future studies are required to extend the model with the metabolism of branched-chain fatty acids. Detailed kinetic studies will be needed to incorporate the import and export of fatty acids into the peroxisome. METHODS Computational methods The computational model was coded in Python. It consists of 24 ordinary differential equations and 6 rate equations for a total of 6 enzymes. Steady state fluxes and concentrations were calculated with the odeint function and by setting all the time derivatives to zero. The (fixed) C18-acylCoA concentration was 150 µM, unless stated differently. A detailed description of the model and equations can be found in Supplementary Text 1. The model script can be found in https://colab.research.google.com/drive/1raOWdS341mwhoR4kVe1_vayT0AEyzp. Access can be granted upon request. Experimental methods All the experimental procedures using murine liver organoids are described in chapter 4. Statistical Analysis Results are expressed as mean ± standard error of the mean (SEM). Biological replicates are considered as independent experiments, since they were done with independent organoid lines. Analyses were performed using GraphPad Prism Software Version 9.02 (Graphpad Software). Statistical significance between comparisons is provided in figure legends. No indication means no significant changes (ns).
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