ABSTRACT
The nervous system is responsible for the communication between the organism and its environment. This task is possible by the presence of the myelin sheath, which is a double membrane formed by about 75% lipids and 25% proteins. The sulfatide represents one of the main lipids of the myelin band; its degradation is catabolized by the enzyme Arylsulfatase A (ARSA), to generated galactosylceramide. Mutations affecting ARSA function lead to the neurodegenerative disease Metachromatic Leukodystrophy. This disease is characterized by accumulation of sulfatide within the band of myelin affecting its functionality. The biochemical consequences of ARSA deficiency are not well understood yet. In this paper, we used an in-silico systems-biology approach to model the biochemical consequences of ARSA deficiency within a general human metabolic network (Recon2) and a glia cellular model. We expected that ARSA deficiency mainly affected the glycosphingolipid pathways. However, the results suggest that mitochondrial metabolism and amino acid transport were the main reactions affected within both cellular models. In the glia cell model, it was highlighted the high number of affected reactions of neurotransmitters metabolism, while only a reduced effect was observed in reactions involved in glycosphingolipids metabolism. We hypothesize that ARSA deficiency might lead to metabolic consequences that not only compromise the myelin band or the glycosphingolipids metabolism but also the overall metabolic function of the nervous system. Furthermore, these results offer the bases for the design of in-vitro and in-vivo experiments that allow generating new knowledge of MLD pathophysiology and other neurodegenerative diseases.
ABSTRACT
Mucopolysaccharidosis (MPS) is a group of lysosomal storage diseases (LSD), characterized by the deficiency of a lysosomal enzyme responsible for the degradation of glycosaminoglycans (GAG). This deficiency leads to the lysosomal accumulation of partially degraded GAG. Nevertheless, deficiency of a single lysosomal enzyme has been associated with impairment in other cell mechanism, such as apoptosis and redox balance. Although GAG analysis represents the main biomarker for MPS diagnosis, it has several limitations that can lead to a misdiagnosis, whereby the identification of new biomarkers represents an important issue for MPS. In this study, we used a system biology approach, through the use of a genome-scale human metabolic reconstruction to understand the effect of metabolism alterations in cell homeostasis and to identify potential new biomarkers in MPS. In-silico MPS models were generated by silencing of MPS-related enzymes, and were analyzed through a flux balance and variability analysis. We found that MPS models used approximately 2286 reactions to satisfy the objective function. Impaired reactions were mainly involved in cellular respiration, mitochondrial process, amino acid and lipid metabolism, and ion exchange. Metabolic changes were similar for MPS I and II, and MPS III A to C; while the remaining MPS showed unique metabolic profiles. Eight and thirteen potential high-confidence biomarkers were identified for MPS IVB and VII, respectively, which were associated with the secondary pathologic process of LSD. In vivo evaluation of predicted intermediate confidence biomarkers (ß-hexosaminidase and ß-glucoronidase) for MPS IVA and VI correlated with the in-silico prediction. These results show the potential of a computational human metabolic reconstruction to understand the molecular mechanisms this group of diseases, which can be used to identify new biomarkers for MPS.
