Inherited Metabolic Diseases

Computational modelling of cell-type specific metabolism in Gaucher disease

To model personalised and cell-type specific features of GD, we will develop a suite of metabolic models using data from macrophages differentiated from iPSCs generated from GD patient fibroblasts. We will leverage XomicsToModel, our recently established semi-automated pipeline that integrates transcriptomic, proteomic, and metabolomic data, as well as the results of biochemical literature curation, with a generic

genome-scale metabolic reconstruction (e.g., Recon4) to extract a context-specific, genome-scale metabolic model that is stoichiometrically, thermodynamically and flux consistent. Transcriptomic data on patient-derived fibroblast and macrophage cell lines will be leveraged to develop draft metabolic models to predict system-level metabolic responses to experimental perturbations. These predictions will be used to identify metabolites to target for quantitative analysis and thereby test the ability of the model to predict metabolic responses to pharmacological perturbations, e.g., by way of substrate reduction therapy. Refined models, constrained with targeted metabolomic data, will be used to design isotope labelling experiments and subsequently infer metabolic fluxes from mass isotopologue distribution data acquired from stable isotope labelling experiments.