Fucosidosis in Tunisian patients: mutational analysis and homology-based modeling of FUCA1 enzyme.

ABSTRACT

BACKGROUND: Fucosidosis is an autosomal recessive lysosomal storage disease caused by defective alpha-L-fucosidase (FUCA1) activity, leading to the accumulation of fucose-containing glycolipids and glycoproteins in various tissues. Clinical features include angiokeratoma, progressive psychomotor retardation, neurologic signs, coarse facial features, and dysostosis multiplex. METHODS: All exons and flanking intron regions of FUCA1 were screened by direct sequencing to identify mutations and polymorphisms in three unrelated families with fucosidosis. Bioinformatics tools were then used to predict the impacts of novel alterations on the structure and function of proteins. Furthermore, the identified mutations were localized onto a 3D structure model using the DeepView Swiss-PdbViewer 4.1 software, which established a function-structure relationship of the FUCA1 proteins. RESULTS: Four novel mutations were identified in this study. Two patients (P1 and P2) in Families 1 and 2 who had the severe phenotype were homoallelic for the two identified frameshift mutations p.K57Sfs*75 and p.F77Sfs*55, respectively. The affected patient (P3) from Family 3, who had the milder phenotype, was heterozygous for the novel missense mutation p.G332E and the novel splice site mutation c.662+5g>c. We verified that this sequence variation did not correspond to a polymorphism by testing 50 unrelated individuals. Additionally, 16 FUCA1 polymorphisms were identified. The structure prediction analysis showed that the missense mutation p.G332E would probably lead to a significant conformational change, thereby preventing the expression of the FUCA1 protein indeed; the 3D structural model of the FUCA1 protein reveals that the glycine at position 332 is located near a catalytic nucleophilic residue. This makes it likely that the enzymatic function of the protein with p.G332E is severely impaired. CONCLUSION: These are the first FUCA1 mutations identified in Tunisia that cause the fucosidosis disease. Bioinformatics analysis allowed us to establish an approximate structure-function relationship for the FUCA1 protein, thereby providing better genotype/phenotype correlation knowledge.