Fucosidosis in Tunisian patients: mutational analysis and homology-based modeling of FUCA1 enzyme.
Alpha-L-fucosidase (FUCA1)
Angiokeratoma
Bioinformatics tool
Fucosidosis
Mutations
Journal
BMC medical genomics
ISSN: 1755-8794
Titre abrégé: BMC Med Genomics
Pays: England
ID NLM: 101319628
Informations de publication
Date de publication:
23 08 2021
23 08 2021
Historique:
received:
09
02
2021
accepted:
23
07
2021
entrez:
24
8
2021
pubmed:
25
8
2021
medline:
21
1
2022
Statut:
epublish
Résumé
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. 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. 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. 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.
Sections du résumé
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.
Identifiants
pubmed: 34425818
doi: 10.1186/s12920-021-01061-3
pii: 10.1186/s12920-021-01061-3
pmc: PMC8383439
doi:
Substances chimiques
alpha-L-Fucosidase
EC 3.2.1.51
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
208Commentaires et corrections
Type : ErratumIn
Informations de copyright
© 2021. The Author(s).
Références
Endreffy I, Bjørklund G, Szerafin L, Chirumbolo S, Urbina MA, Endreffy E. Plasma alpha-L-fucosidase activity in chronic inflammation and autoimmune disorders in a pediatric cohort of hospitalized patients. Immunol Res. 2017;65(5):1025–30.
doi: 10.1007/s12026-017-8943-x
Fukushima H, de Wet JR, O’Brien JS. Molecular cloning of a cDNA for human alpha-L-fucosidase. Proc Natl Acad Sci U S A. 1985;82(4):1262–5.
doi: 10.1073/pnas.82.4.1262
Occhiodoro T, Beckmann KR, Morris CP, Hopwood JJ. Human alpha-L-fucosidase: complete coding sequence from cDNA clones. BiochemBiophys Res Commun. 1989;164(1):439–45.
doi: 10.1016/0006-291X(89)91739-7
Miano M, Lanino E, Gatti R, Morreale G, Fondelli P, Celle ME, Stroppiano M, Crescenzi F, Dini G. Four year follow-up of a case of fucosidosis treated with unrelated donor bone marrow transplantation. Bone Marrow Transplant. 2001;27(7):747–51.
doi: 10.1038/sj.bmt.1702994
Abdallah C, Hannallah R, McGill W. Anesthesia for fucosidosis. Paediatr Anaesth. 2007;17(10):994–7.
doi: 10.1111/j.1460-9592.2007.02269.x
Panmontha W, Amarinthnukrowh P, Damrongphol P, Desudchit T, Suphapeetiporn K, Shotelersuk V. Novel mutations in the FUCA1 gene that cause fucosidosis. Genet Mol Res. 2016;15(3). https://doi.org/10.4238/gmr.15038733 .
Willems PJ, Seo HC, Coucke P, Tonlorenzi R, O’brien JS. Spectrum of mutations in fucosidosis. Eur J Hum Genet. 1999;7(1):60–7.
doi: 10.1038/sj.ejhg.5200272
Cragg H, Williamson M, Young E, O’Brien J, Alhadeff J, Fang-Kircher S, Paschke E, Winchester B. Fucosidosis: genetic and biochemical analysis of eight cases. J Med Genet. 1997;34(2):105–10.
doi: 10.1136/jmg.34.2.105
Miller SA, Dykes DD, Polesky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res. 1988;16(3):1215.
doi: 10.1093/nar/16.3.1215
Adzhubei IA, Schmidt S, Peshkin L, et al. A method and server for predicting damaging missense mutations. Nat Methods. 2010;7(4):248–9.
doi: 10.1038/nmeth0410-248
López-Ferrando V, Gazzo A, de la Cruz X, Orozco M, Gelpí JL. PMut: a web-based tool for the annotation of pathological variants on proteins, 2017 update. Nucleic Acids Res. 2017;45(W1):W222–8.
doi: 10.1093/nar/gkx313
Kumar P, Henikoff S, Ng PC. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc. 2009;4(7):1073–81.
doi: 10.1038/nprot.2009.86
Rodrigues CH, Pires DE, Ascher DB. DynaMut: predicting the impact of mutations on protein conformation, flexibility and stability. Nucleic Acids Res. 2018;46(W1):W350–5.
doi: 10.1093/nar/gky300
Desmet FO, Hamroun D, Lalande M, Collod-Béroud G, Claustres M, Béroud C. Human Splicing Finder: an online bioinformatics tool to predict splicing signals. Nucleic Acids Res. 2009;37(9):e67.
doi: 10.1093/nar/gkp215
Wu HJ, Ho CW, Ko TP, Popat SD, Lin CH, Wang AH. Structural basis of alpha-fucosidase inhibition by iminocyclitols with K(i) values in the micro- to picomolar range. Angew Chem Int Ed Engl. 2010;49(2):337–40.
doi: 10.1002/anie.200905597
Studer G, Rempfer C, Waterhouse AM, Gumienny R, Haas J, Schwede T. QMEANDisCo-distance constraints applied on model quality estimation. Bioinformatics. 2020;36(6):1765–71.
doi: 10.1093/bioinformatics/btz828
Guex N, Peitsch MC. SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling. Electrophoresis. 1997;18:2714–23.
doi: 10.1002/elps.1150181505
Sulzenbacher G, Bignon C, Nishimura T, Tarling CA, Withers SG, Henrissat B, Bourne Y. Crystal structure of Thermotoga maritima alpha-L-fucosidase. Insights into the catalytic mechanism and the molecular basis for fucosidosis. J Biol Chem. 2004;279(13):13119–28.
doi: 10.1074/jbc.M313783200
Ben Turkia H, Tebib N, Azzouz H, Abdelmoula MS, Bouguila J, Sanhaji H, Miladi N, Maire I, Caillaud C, Kaabachi N, Ben Dridi MF. Phenotypic spectrum of fucosidosis in Tunisia. J Inherit Metab Dis. 2008;31(2):S313–6.
doi: 10.1007/s10545-008-0891-0
Willems PJ, Gatti R, Darby JK, Romeo G, Durand P, Dumon JE, O’Brien JS. Fucosidosis revisited: a review of 77 patients. Am J Med Genet. 1991;38(1):111–31.
doi: 10.1002/ajmg.1320380125
Boggio P, Luna PC, Abad ME, Larralde M. Doença de Fabry [Fabry disease]. An Bras Dermatol. 2009;84(4):367–76.
doi: 10.1590/S0365-05962009000400008
Bruggink C, Poorthuis BJ, Deelder AM, Wuhrer M. Analysis of urinary oligosaccharides in lysosomal storage disorders by capillary high-performance anion-exchange chromatography-mass spectrometry. Anal Bioanal Chem. 2012;403(6):1671–83.
doi: 10.1007/s00216-012-5968-9
Tomatsu S, Dieter T, Schwartz IV, Sarmient P, Giugliani R, Barrera LA, et al. Identification of a common mutation in mucopolysaccharidosis IVA: correlation among genotype, phenotype, and keratan sulfate. J Hum Genet. 2004;49(9):490–4.
doi: 10.1007/s10038-004-0178-8
Sakurama H, Tsutsumi E, Ashida H, Katayama T, Yamamoto K, Kumagai H. Differences in the substrate specificities and active-site structures of two α-L-fucosidases (glycoside hydrolase family 29) from Bacteroides thetaiotaomicron. Biosci Biotechnol Biochem. 2012;76(5):1022–4.
doi: 10.1271/bbb.111004
Cao H, Walton JD, Brumm P, Phillips GN Jr. Structure and substrate specificity of a eukaryotic fucosidase from Fusarium graminearum. J Biol Chem. 2014;289(37):25624–38.
doi: 10.1074/jbc.M114.583286
Williamson M, Cragg H, Grant J, Kretz K, O’Brien J, Willems PJ, Young E, Winchester B. A 5’ splice site mutation in fucosidosis. J Med Genet. 1993;30(3):218–23.
doi: 10.1136/jmg.30.3.218
Krawczak M, Thomas NS, Hundrieser B, Mort M, Wittig M, Hampe J, Cooper DN. Single base-pair substitutions in exon-intron junctions of human genes: nature, distribution, and consequences for mRNA splicing. Hum Mutat. 2007;28(2):150–8.
doi: 10.1002/humu.20400
Braliou GG, Kontou PI, Boleti H, Pantelis BG. Susceptibility to leishmaniasis is affected by host SLC11A1 gene polymorphisms: a systematic review and meta-analysis. Parasitol Res. 2019;118:2329–42.
doi: 10.1007/s00436-019-06374-y
Opdal SH. IL-10 gene polymorphisms in infectious disease and SIDS. FEMS Immunol Med Microbiol. 2004;42(1):48–52.
doi: 10.1016/j.femsim.2004.06.006
Witka BZ, Oktaviani DJ, Marcellino M, Barliana MI, Abdulah R. Type 2 diabetes-associated genetic polymorphisms as potential disease predictors. Diabetes Metab Syndr Obes. 2019;12:2689–706.
doi: 10.2147/DMSO.S230061
Sophie M, Hameed A, Muneer A, Samdani AJ, Saleem S, Azhar A. SLC11A1 polymorphisms and host susceptibility to cutaneous leishmaniasis in Pakistan. Parasit Vectors. 2017;10:12.
doi: 10.1186/s13071-016-1934-2