Systems biology study of mucopolysaccharidosis using a human metabolic reconstruction network

Molecular Genetics and Metabolism

Volumn 117, Issue 2, 2016, Pages 129-139

  Salazar, Diego A ^a   Rodríguez López, Alexander ^a   Herreño, Angélica ^a   Barbosa, Hector ^a   Herrera, Juliana ^a   Ardila, Andrea ^a,b   Barreto, George E ^a   González, Janneth ^a   Alméciga Díaz, Carlos J ^a  

^a PONTIFICIA UNIVERSIDAD JAVERIANA   (Colombia)

^b HOSPITAL UNIVERSITARIO SAN IGNACIO   (Colombia)

Author keywords

Diagnostic; Disease biomarkers; Flux balance analysis; Lysosomal storage disease; Systems biology

Indexed keywords

AMINO ACID; BETA GLUCURONIDASE; BETA N ACETYLHEXOSAMINIDASE; BIOLOGICAL MARKER;

ARTICLE; CELL RESPIRATION; GENOMICS; HUMAN; ION EXCHANGE; LIPID METABOLISM; METABOLIC RECONSTRUCTION NETWORK; METABOLISM; MITOCHONDRION; MUCOPOLYSACCHARIDOSIS; PRIORITY JOURNAL; SYSTEMS BIOLOGY; COMPUTER SIMULATION; ENZYMOLOGY; HEK293 CELL LINE; METABOLIC FLUX ANALYSIS; MONONUCLEAR CELL;

BETA-N-ACETYLHEXOSAMINIDASES; BIOMARKERS; COMPUTER SIMULATION; HEK293 CELLS; HUMANS; LEUKOCYTES, MONONUCLEAR; METABOLIC FLUX ANALYSIS; METABOLIC NETWORKS AND PATHWAYS; MUCOPOLYSACCHARIDOSES; SYSTEMS BIOLOGY;

EID: 84957849334     PISSN: 10967192     EISSN: 10967206     Source Type: Journal    
DOI: 10.1016/j.ymgme.2015.08.001     Document Type: Article

References (73)

1. Muenzer J. Overview of the mucopolysaccharidoses. Rheumatology (Oxford) 2011, 50(Suppl. 5):v4-v12. 10.1093/rheumatology/ker394.
2. Coutinho M.F., Lacerda L., Alves S. Glycosaminoglycan storage disorders: a review. Biochem. Res. Int. 2012, 2012:471325. 10.1155/2012/471325.
3. Lampe C., Bellettato C.M., Karabul N., Scarpa M. Mucopolysaccharidoses and other lysosomal storage diseases. Rheum. Dis. Clin. North Am. 2013, 39:431-455. 10.1016/j.rdc.2013.03.004.
4. Giugliani R. Mucopolysacccharidoses: from understanding to treatment, a century of discoveries. Genet. Mol. Biol. 2012, 35:924-931.
5. Lehman T.J.A., Miller N., Norquist B., Underhill L., Keutzer J. Diagnosis of the mucopolysaccharidoses. Rheumatology (Oxford) 2011, 50(Suppl. 5):v41-v48. 10.1093/rheumatology/ker390.
6. Tomatsu S., Shimada T., Mason R.W., Montaño A.M., Kelly J., LaMarr W.A., et al. Establishment of glycosaminoglycan assays for mucopolysaccharidoses. Metabolites 2014, 4:655-679. 10.3390/metabo4030655.
7. Lawrence R., Brown J.R., Lorey F., Dickson P.I., Crawford B.E., Esko J.D. Glycan-based biomarkers for mucopolysaccharidoses. Mol. Genet. Metab. 2014, 111:73-83. 10.1016/j.ymgme.2013.07.016.
8. Beck M., Muenzer J., Scarpa M. Evaluation of disease severity in mucopolysaccharidoses. J. Pediatr. Rehabil. Med. 2010, 3:39-46. 10.3233/PRM-2010-0100.
9. Clarke L.A. The mucopolysaccharidoses: a success of molecular medicine. Expert Rev. Mol. Med. 2008, 10:e1. 10.1017/S1462399408000550.
10. Clarke L.A., Winchester B., Giugliani R., Tylki-Szymańska A., Amartino H. Biomarkers for the mucopolysaccharidoses: discovery and clinical utility. Mol. Genet. Metab. 2012, 106:395-402. 10.1016/j.ymgme.2012.05.003.
11. Valayannopoulos V., Wijburg F.A. Therapy for the mucopolysaccharidoses. Rheumatology (Oxford) 2011, 50(Suppl. 5):v49-v59. 10.1093/rheumatology/ker396.
12. Boya P. Lysosomal function and dysfunction: mechanism and disease. Antioxid. Redox Signal. 2012, 17:766-774. 10.1089/ars.2011.4405.
13. Klionsky D., Emr S. Autophagy as a regulated pathway of cellular degradation. Science 2000, 290(80):1717-1721.
14. Walkley S. Pathogenic cascades in lysosomal disease-why so complex?. J. Inherit. Metab. Dis. 2009, 32:181-189. 10.1007/s10545-008-1040-5.Pathogenic.
15. Tomita M., Kami K. Systems biology, metabolomics, and cancer metabolism. Science 2012, 336(80):990-991. 10.1126/science.1223066.
16. Xie L., Ge X., Tan H., Xie L., Zhang Y., Hart T., et al. Towards structural systems pharmacology to study complex diseases and personalized medicine. PLoS Comput. Biol. 2014, 10. 10.1371/journal.pcbi.1003554.
17. Cardoso J. Analysis of genetic variation and potential applications in genome-scale metabolic modeling. Front. Bioeng. Biotechnol. 2015, 3. 10.3389/fbioe.2015.00013.
18. Kulasingam V., Diamandis E.P. Tissue culture-based breast cancer biomarker discovery platform. Int. J. Cancer 2008, 123:2007-2012. 10.1002/ijc.23844.
19. Kulasingam V., Pavlou M.P., Diamandis E.P. Integrating high-throughput technologies in the quest for effective biomarkers for ovarian cancer. Nat. Rev. Cancer 2010, 10:371-378. 10.1038/nrc2831.
20. Avila J.L., Convit J. Inhibition of leucocytic lysosomal enzymes by glycosaminoglycans in vitro. Biochem. J. 1975, 152:57-64.
21. Kell D.B., Goodacre R. Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery. Drug Discov. Today 2014, 19:171-182. 10.1016/j.drudis.2013.07.014.
22. Vandamme D., Fitzmaurice W., Kholodenko B., Kolch W. Systems medicine: helping us understand the complexity of disease. QJM 2013, 106:891-895. 10.1093/qjmed/hct163.
23. Eddy D.M., Schlessinger L. Archimedes: a trial-validated model of diabetes. Diabetes Care 2003, 26:3093-3101. 10.2337/diacare.26.11.3093.
24. Shoaie S., Nielsen J. Elucidating the interactions between the human gut microbiota and its host through metabolic modeling. Front. Genet. 2014, 5. 10.3389/fgene.2014.00086.
25. Iyengar R., Zhao S., Chung S.-W., Mager D.E., Gallo J.M. Merging systems biology with pharmacodynamics. Sci. Transl. Med. 2012, 4. (126ps7-126ps7). 10.1126/scitranslmed.3003563.
26. Mast F.D., Ratushny A.V., Aitchison J.D. Systems cell biology. J. Cell Biol. 2014, 206:695-706. 10.1083/jcb.201405027.
27. Finley S.D., Chu L.-H., Popel A.S. Computational systems biology approaches to anti-angiogenic cancer therapeutics. Drug Discov. Today 2014, 10.1016/j.drudis.2014.09.026.
28. Hwang D., Lee I.Y., Yoo H., Gehlenborg N., Cho J.-H., Petritis B., et al. A systems approach to prion disease. Mol. Syst. Biol. 2009, 5:252. 10.1038/msb.2009.10.
29. Jegga A.G., Schneider L., Ouyang X., Zhang J. Systems biology of the autophagy-lysosomal pathway. Autophagy 2011, 7:477-489.
30. Bordbar A., Monk J.M., King Z.A., Palsson B.O. Constraint-based models predict metabolic and associated cellular functions. Nat. Rev. Genet. 2014, 15:107-120. 10.1038/nrg3643.
31. Thiele I., Palsson B.Ø. A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat. Protoc. 2010, 5:93-121. 10.1038/nprot.2009.203.
32. Sigurdsson M.I., Jamshidi N., Steingrimsson E., Thiele I., Palsson B.Ø. A detailed genome-wide reconstruction of mouse metabolism based on human Recon 1. BMC Syst. Biol. 2010, 4:140. 10.1186/1752-0509-4-140.
33. Dumas M.E., Kinross J., Nicholson J.K. Metabolic phenotyping and systems biology approaches to understanding metabolic syndrome and fatty liver disease. Gastroenterology 2014, 146:46-62. 10.1053/j.gastro.2013.11.001.
34. Shahzad K., Loor J.J. Application of top-down and bottom-up systems approaches in ruminant physiology and metabolism. Curr. Genomics 2012, 13:379-394. 10.2174/138920212801619269.
35. Jing L.S., Shah F.F.M., Mohamad M.S., Hamran N.L., Salleh A.H.M., Deris S., et al. Database and tools for metabolic network analysis. Biotechnol. Bioprocess Eng. 2014, 19:568-585. 10.1007/s12257-014-0172-8.
36. Duarte N.C., Becker S.A., Jamshidi N., Thiele I., Mo M.L., Vo T.D., et al. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc. Natl. Acad. Sci. U. S. A. 2007, 104:1777-1782. 10.1073/pnas.0610772104.
37. Thiele I., Swainston N., Fleming R.M.T., Hoppe A., Sahoo S., Aurich M.K., et al. A community-driven global reconstruction of human metabolism. Nat. Biotechnol. 2013, 31:419-425. 10.1038/nbt.2488.
38. Shlomi T., Cabili M.N., Ruppin E. Predicting metabolic biomarkers of human inborn errors of metabolism. Mol. Syst. Biol. 2009, 5:263. 10.1038/msb.2009.22.
39. Becker S.A., Feist A.M., Mo M.L., Hannum G., Palsson B.Ø., Herrgard M.J. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nat. Protoc. 2007, 2:727-738. 10.1038/nprot.2007.99.
40. Orth J.D., Thiele I., Palsson B.Ø. What is flux balance analysis?. Nat. Biotechnol. 2010, 28:245-248. 10.1038/nbt.1614.
41. Raman K., Chandra N. Flux balance analysis of biological systems: applications and challenges. Brief. Bioinform. 2009, 10:435-449. 10.1093/bib/bbp011.
42. Huang D.W., Sherman B.T., Lempicki R.A. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009, 37:1-13. 10.1093/nar/gkn923.
43. Gudmundsson S., Thiele I. Computationally efficient flux variability analysis. BMC Bioinformatics 2010, 11:489. 10.1186/1471-2105-11-489.
44. Wendeler M., Sandhoff K. Hexosaminidase assays. Glycoconj. J. 2009, 26:945-952. 10.1007/s10719-008-9137-5.
45. Kutner R.H., Zhang X.-Y., Reiser J. Production, concentration and titration of pseudotyped HIV-1-based lentiviral vectors. Nat. Protoc. 2009, 4:495-505. 10.1038/nprot.2009.22.
46. Alméciga-Díaz C.J., Montaño A.M., Tomatsu S., Barrera L.A. Adeno-associated virus gene transfer in Morquio A disease-effect of promoters and sulfatase-modifying factor 1. FEBS J. 2010, 277:3608-3619. 10.1111/j.1742-4658.2010.07769.x.
47. van Diggelen O.P., Zhao H., Kleijer W.J., Janse H.C., Poorthuis B.J., van Pelt J., et al. A fluorimetric enzyme assay for the diagnosis of Morquio disease type A (MPS IV A). Clin. Chim. Acta 1990, 187:131-139.
48. Shapira Emmanuel, Blitzer Miriam, Miller James, Africk Diane Biochemical Genetics. A Laboratory Manual 1989, Oxford University Press, New York.
49. Woloszynek J.C., Coleman T., Semenkovich C.F., Sands M.S. Lysosomal dysfunction results in altered energy balance. J. Biol. Chem. 2007, 282:35765-35771. 10.1074/jbc.M705124200.
50. Woloszynek J.C., Kovacs A., Ohlemiller K.K., Roberts M., Sands M.S. Metabolic adaptations to interrupted glycosaminoglycan recycling. J. Biol. Chem. 2009, 284:29684-29691. 10.1074/jbc.M109.020818.
51. Folger O., Jerby L., Frezza C., Gottlieb E., Ruppin E., Shlomi T. Predicting selective drug targets in cancer through metabolic networks. Mol. Syst. Biol. 2011, 7:501. 10.1038/msb.2011.35.
52. Herreño A.M., Barbosa H.M., Herrera J., Cuaspa R., Almeciga-Díaz C.J., Barrera L. In-vitro evaluation of adenoassociated and lentiviral vectors for Morquio A. J. Inborn Errors Metab. Screen. 2014, 2:84.
53. Resendis-Antonio O., González-Torres C., Jaime-Muñoz G., Hernandez-Patiño C.E., Salgado-Muñoz C.F. Modeling metabolism: a window toward a comprehensive interpretation of networks in cancer. Semin. Cancer Biol. 2014, 10.1016/j.semcancer.2014.04.003.
54. Vitner E.B., Platt F.M., Futerman A.H. Common and uncommon pathogenic cascades in lysosomal storage diseases. J. Biol. Chem. 2010, 285:20423-20427. 10.1074/jbc.R110.134452.
55. Simonaro C.M., D'Angelo M., He X., Eliyahu E., Shtraizent N., Haskins M.E., et al. Mechanism of glycosaminoglycan-mediated bone and joint disease: implications for the mucopolysaccharidoses and other connective tissue diseases. Am. J. Pathol. 2008, 172:112-122. 10.2353/ajpath.2008.070564.
56. Pereira V.G., Gazarini M.L., Rodrigues L.C., da Silva F.H., Han S.W., Martins A.M., et al. Evidence of lysosomal membrane permeabilization in mucopolysaccharidosis type I: rupture of calcium and proton homeostasis. J. Cell. Physiol. 2010, 223:335-342. 10.1002/jcp.22039.
57. Ballabio A., Gieselmann V. Lysosomal disorders: from storage to cellular damage. Biochim. Biophys. Acta 2009, 1793:684-696. 10.1016/j.bbamcr.2008.12.001.
58. Settembre C., Zoncu R., Medina D.L., Vetrini F., Erdin S., Erdin S., et al. A lysosome-to-nucleus signalling mechanism senses and regulates the lysosome via mTOR and TFEB. EMBO J. 2012, 31:1095-1108. 10.1038/emboj.2012.32.
59. Kurz T., Terman A., Gustafsson B., Brunk U.T. Lysosomes in iron metabolism, ageing and apoptosis. Histochem. Cell Biol. 2008, 129:389-406. 10.1007/s00418-008-0394-y.
60. Settembre C., Ballabio A. Lysosome: regulator of lipid degradation pathways. Trends Cell Biol. 2014, 24:743-750. 10.1016/j.tcb.2014.06.006.
61. Tessitore A., Pirozzi M., Auricchio A. Abnormal autophagy, ubiquitination, inflammation and apoptosis are dependent upon lysosomal storage and are useful biomarkers of mucopolysaccharidosis VI. Pathogenetics 2009, 2:4. 10.1186/1755-8417-2-4.
62. Aronovich E.L., Hackett P.B. Lysosomal storage disease: gene therapy on both sides of the blood-brain barrier. Mol. Genet. Metab. 2015, 114:83-93. 10.1016/j.ymgme.2014.09.011.
63. Hassiotis S., Jolly R.D., Hemsley K.M. Development of cerebellar pathology in the canine model of mucopolysaccharidosis type IIIA (MPS IIIA). Mol. Genet. Metab. 2014, 113:283-293. 10.1016/j.ymgme.2014.10.008.
64. Martins C., Hůlková H., Dridi L., Dormoy-Raclet V., Grigoryeva L., Choi Y., et al. Neuroinflammation, mitochondrial defects and neurodegeneration in mucopolysaccharidosis III type C mouse model. Brain 2015, 138:336-355. 10.1093/brain/awu355.
65. Haskins M. Animal models for mucopolysaccharidosis disorders and their clinical relevance. Acta Paediatr. 2007, 96:56-62. 10.1111/j.1651-2227.2007.00211.x.Animal.
66. Donida B., Marchetti D.P., Biancini G.B., Deon M., Manini P.R., da Rosa H.T., et al. Oxidative stress and inflammation in mucopolysaccharidosis type IVA patients treated with enzyme replacement therapy. Biochim. Biophys. Acta Mol. Basis Dis. 2015, 1852:1012-1019. 10.1016/j.bbadis.2015.02.004.
67. Trudel S., Trécherel E., Gomila C., Peltier M., Aubignat M., Gubler B., et al. Oxidative stress is independent of inflammation in the neurodegenerative sanfilippo syndrome type B. J. Neurosci. Res. 2015, 93:424-432. 10.1002/jnr.23497.
68. Haimovitz-Friedman A., Kolesnick R.N., Fuks Z. Ceramide signaling in apoptosis. Br. Med. Bull. 1997, 53:539-553.
69. Cutler R.G., Kelly J., Storie K., Pedersen W.A., Tammara A., Hatanpaa K., et al. Involvement of oxidative stress-induced abnormalities in ceramide and cholesterol metabolism in brain aging and Alzheimer's disease. Proc. Natl. Acad. Sci. U. S. A. 2004, 101:2070-2075. 10.1073/pnas.0305799101.
70. Kalvodova L., Kahya N., Schwille P., Ehehalt R., Verkade P., Drechsel D., et al. Lipids as modulators of proteolytic activity of BACE: involvement of cholesterol, glycosphingolipids, and anionic phospholipids in vitro. J. Biol. Chem. 2005, 280:36815-36823. 10.1074/jbc.M504484200.
71. Kan S.-H., Aoyagi-Scharber M., Le S.Q., Vincelette J., Ohmi K., Bullens S., et al. Delivery of an enzyme-IGFII fusion protein to the mouse brain is therapeutic for mucopolysaccharidosis type IIIB. Proc. Natl. Acad. Sci. 2014, 111:14870-14875. 10.1073/pnas.1416660111.
72. Tomatsu S., Orii K.O., Vogler C., Nakayama J., Levy B., Grubb J.H., et al. Mouse model on N-acetylgalactosamine-6-sulfate sulfatase deficiency (Galns-/-produced by targeted disruption of the gene defective in Morquio A disease. Hum. Mol. Genet. 2003, 12:3349-3358. 10.1093/hmg/ddg366.
73. Crawley A.C., Yogalingam G., Muller V.J., Hopwood J.J. Two mutations within a feline mucopolysaccharidosis type VI colony cause three different clinical phenotypes. J. Clin. Invest. 1998, 101:109-119. 10.1172/JCI935.