Fibroblast‐specific genome‐scale modelling predicts an imbalance in amino acid metabolism in Refsum disease. (31st March 2020)

• Record Type: Journal Article
• Authors: Wegrzyn, Agnieszka B.; Herzog, Katharina; Gerding, Albert; Kwiatkowski, Marcel; Wolters, Justina C.; Dolga, Amalia M.; van Lint, Alida E. M.; Wanders, Ronald J. A.; Waterham, Hans R.; Bakker, Barbara M.
• Is Part Of: FEBS journal. Volume 287:Number 23(2020)
• Page Start: 5096
• Page End: 5113
• Publication Date: 2020-03-31
• Subjects: amino acids -- fibroblast -- genome‐scale modelling -- metabolism -- Refsum disease; Biochemistry -- Periodicals; Molecular biology -- Periodicals; Pathology, Molecular -- Periodicals; 572
• DOI: 10.1111/febs.15292
• Languages: English
• ISSNs: 1742-464X

Abstract

Abstract : Refsum disease (RD) is an inborn error of metabolism that is characterised by a defect in peroxisomal α‐oxidation of the branched‐chain fatty acid phytanic acid. The disorder presents with late‐onset progressive retinitis pigmentosa and polyneuropathy and can be diagnosed biochemically by elevated levels of phytanate in plasma and tissues of patients. To date, no cure exists for RD, but phytanate levels in patients can be reduced by plasmapheresis and a strict diet. In this study, we reconstructed a fibroblast‐specific genome‐scale model based on the recently published, FAD‐curated model, based on Recon3D reconstruction. We used transcriptomics (available via GEO database with identifier GSE138379 ), metabolomics and proteomics (available via ProteomeXchange with identifier PXD015518 ) data, which we obtained from healthy controls and RD patient fibroblasts incubated with phytol, a precursor of phytanic acid. Our model correctly represents the metabolism of phytanate and displays fibroblast‐specific metabolic functions. Using this model, we investigated the metabolic phenotype of RD at the genome scale, and we studied the effect of phytanate on cell metabolism. We identified 53 metabolites that were predicted to discriminate between healthy and RD patients, several of which with a link to amino acid metabolism. Ultimately, these insights in metabolic changes may provide leads for pathophysiology and therapy. Databases: Transcriptomics data are available via GEO database with identifier GSE138379, and proteomics data are available via ProteomeXchange with identifier PXD015518 . Abstract : Refsum disease (RD) is an inborn error of metabolism that is characterised by a defect in peroxisomal α‐oxidation of the branched‐chain fatty acid phytanic acid. In this study, we used various omics obtained from healthy controls and RD patient fibroblasts to reconstruct a fibroblast‐specific genome‐scale model. Using this model, we identified 53 metabolites that discriminated between healthy and RD patients, several of which with a link to amino acid metabolism.