Reconstruction and analysis of human heart-specific metabolic network based on transcriptome and proteome data

Biochemical and Biophysical Research Communications

Volumn 415, Issue 3, 2011, Pages 450-454

  Zhao, Yuqi ^a,b   Huang, Jingfei ^a,c  

^a KUNMING INSTITUTE OF ZOOLOGY   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Biomarkers for cardiovascular disease; Flux balance analysis; Heart specific model; Metabolic network; Selective drug targets

Indexed keywords

ADENYLYLSULFATE KINASE; BIOLOGICAL MARKER; HYDROLASE; PHOSPHOGLUCOMUTASE; PROTEOME; SODIUM GLUCOSE COTRANSPORTER 1; TRANSCRIPTOME;

ALGORITHM; ARTICLE; CARDIOVASCULAR DISEASE; CARDIOVASCULAR FUNCTION; ENZYME ACTIVITY; GENE DELETION; GENE EXPRESSION; GENE INTERACTION; GENETIC ASSOCIATION; GENETIC TRANSFECTION; HEART MUSCLE METABOLISM; HOUSEKEEPING GENE; HUMAN; NONHUMAN; PRIORITY JOURNAL; PROTEIN TARGETING;

BIOLOGICAL MARKERS; CARDIOVASCULAR DISEASES; DRUG DELIVERY SYSTEMS; EPISTASIS, GENETIC; HUMANS; METABOLIC NETWORKS AND PATHWAYS; MODELS, BIOLOGICAL; MYOCARDIUM; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PROTEIN ARRAY ANALYSIS; PROTEOME; TRANSCRIPTOME;

EID: 82355175105     PISSN: 0006291X     EISSN: 10902104     Source Type: Journal    
DOI: 10.1016/j.bbrc.2011.10.090     Document Type: Article

References (31)

1. Mishra P.K., Givvimani S., Metreveli N., Tyagi S.C. Attenuation of beta2-adrenergic receptors and homocysteine metabolic enzymes cause diabetic cardiomyopathy. Biochem. Biophys. Res. Commun. 2010, 401:175-181.
2. Niculescu L.S., Vladica M., Sima A.V. Association of APOA5 and APOC3 gene polymorphisms with plasma apolipoprotein A5 level in patients with metabolic syndrome. Biochem. Biophys. Res. Commun. 2010, 391:587-591.
3. Arnolov J., Ingelsson E., Sundstrom J., Lind L. Impact of body mass index and the metabolic syndrome on the risk of cardiovascular disease and death in middle-aged men. Circulation 2010, 121:230-U88.
4. Ho J.S., Cannaday J.J., Barlow C.E., Mitchell T.L., Cooper K.H., FitzGerald S.J. Relation of the number of metabolic syndrome risk factors with all-cause and cardiovascular mortality. Am. J. Cardiol. 2008, 102:689-692.
5. Lusis A.J., Attie A.D., Reue K. Metabolic syndrome: from epidemiology to systems biology. Nat. Rev. Genet. 2008, 9:819-830.
6. Hanash S. Progress in mining the human proteome for disease applications. Omics - J. Integr. Biol. 2011, 15:133-139.
7. Goryanin I., Ma H.W., Sorokin A., Mazein A., Selkov A., Selkov E., Demin O. The Edinburgh human metabolic network reconstruction and its functional analysis. Mol. Syst. Biol. 2007, 3.
8. Xiong M.A., Feghali-Bostwick C.A., Arnett F.C., Zhou X.D. A systems biology approach to genetic studies of complex diseases. FEBS Lett. 2005, 579:5325-5332.
9. Becker S.A., Palsson B.O. Context-specific metabolic networks are consistent with experiments. PLoS Comput. Biol. 2008, 4.
10. Oberhardt M.A., Palsson B.O., Papin J.A. Applications of genome-scale metabolic reconstructions. Mol. Syst. Biol. 2009, 5.
11. Duarte N.C., Becker S.A., Jamshidi N., Thiele I., Mo M.L., Vo T.D., Srivas R., Palsson B.O. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc. Natl. Acad. Sci. USA 2007, 104:1777-1782.
12. Shlomi T., Cabili M.N., Ruppin E. Predicting metabolic biomarkers of human inborn errors of metabolism. Mol. Syst. Biol. 2009, 5.
13. Jerby L., Shlomi T., Ruppin E. Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism. Mol. Syst. Biol. 2010, 6.
14. Blekhman R., Oshlack A., Chabot A.E., Smyth G.K., Gilad Y. Gene regulation in primates evolves under tissue-specific selection pressures. PLoS Genet. 2008, 4.
15. Heck A.J.R., Aye T.T., Scholten A., Taouatas N., Varro A., Van Veen T.A.B., Vos M.A. Proteome-wide protein concentrations in the human heart. Mol. BioSyst. 2010, 6:1917-1927.
16. Herrgard M.J., Becker S.A., Feist A.M., Mo M.L., Hannum G., Palsson B.O. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nat. Protoc. 2007, 2:727-738.
17. Orth J.D., Thiele I., Palsson B.O. What is flux balance analysis?. Nat. Biotechnol. 2010, 28:245-248.
18. Church G.M., Segre D., Vitkup D. Analysis of optimality in natural and perturbed metabolic networks. Proc. Natl. Acad. Sci. USA 2002, 99:15112-15117.
19. Chang C.W., Cheng W.C., Chen C.R., Shu W.Y., Tsai M.L., Huang C.L., Hsu I.C. Identification of human housekeeping genes and tissue-selective genes by microarray meta-analysis. PLoS ONE 2011, 6.
20. Mahadevan R., Schilling C.H. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab. Eng. 2003, 5:264-276.
21. Apweiler R., Wu C.H., Bairoch A., Natale D.A., Barker W.C., Boeckmann B., Ferro S., Gasteiger E., Huang H.Z., Lopez R., Magrane M., Martin M.J., Mazumder R., O'Donovan C., Redaschi N., Suzek B. The universal protein resource (UniProt): an expanding universe of protein information. Nucleic Acids Res. 2006, 34:D187-D191.
22. Bindea G., Mlecnik B., Hackl H., Charoentong P., Tosolini M., Kirilovsky A., Fridman W.H., Pages F., Trajanoski Z., Galon J. ClueGO: a cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 2009, 25:1091-1093.
23. Overall C.M., Lopez-Otin C. Protease degradomics: a new challenge for proteomics. Nat. Rev. Mol. Cell Biol. 2002, 3:509-519.
24. Pucci P., Monti M., Cozzolino M., Cozzolino F., Vitiello G., Tedesco R., Flagiello A. Puzzle of protein complexes in vivo: a present and future challenge for functional proteomics. Expert Rev. Proteomics 2009, 6:159-169.
25. Ideker T., Cline M.S., Smoot M., Cerami E., Kuchinsky A., Landys N., Workman C., Christmas R., Avila-Campilo I., Creech M., Gross B., Hanspers K., Isserlin R., Kelley R., Killcoyne S., Lotia S., Maere S., Morris J., Ono K., Pavlovic V., Pico A.R., Vailaya A., Wang P.L., Adler A., Conklin B.R., Hood L., Kuiper M., Sander C., Schmulevich I., Schwikowski B., Warner G.J., Bader G.D. Integration of biological networks and gene expression data using Cytoscape. Nat. Protoc. 2007, 2:2366-2382.
26. Palsson B.O., Duarte N.C., Herrgard M.J. Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model. Genome Res. 2004, 14:1298-1309.
27. Yaffe M.B., Reinhardt H.C., Jiang H., Hemann M.T. Exploiting synthetic lethal interactions for targeted cancer therapy. Cell Cycle 2009, 8:3112-3119.
28. Hamosh A., Scott A.F., Amberger J.S., Bocchini C.A., McKusick V.A. Online Mendelian inheritance in man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 2005, 33:D514-D517.
29. Gerszten R.E., Wang T.J. The search for new cardiovascular biomarkers. Nature 2008, 451:949-952.
30. Baxter J.D., Webb P., Grover G., Scanlan T.S. Selective activation of thyroid hormone signaling pathways by GC-1: a new approach to controlling cholesterol and body weight. Trends Endocrinol. Metab. 2004, 15:154-157.
31. Anders M.W. Putting bioactivation reactions to work: targeting antioxidants to mitochondria. Chem. Biol. Interact. 2011, 192:8-13.