iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological and patho-physiological states
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  • 作者:Aarash Bordbar (1)
    Neema Jamshidi (1)
    Bernhard O Palsson (1)
  • 刊名:BMC Systems Biology
  • 出版年:2011
  • 出版时间:December 2011
  • 年:2011
  • 卷:5
  • 期:1
  • 全文大小:1843KB
  • 参考文献:1. Oberhardt MA, Palsson BO, Papin JA: Applications of genome-scale metabolic reconstructions. / Mol Syst Biol 2009, 5:320. CrossRef
    2. Feist AM, Palsson BO: The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli. / Nat Biotech 2008,26(6):659鈥?67. CrossRef
    3. Thiele I, Palsson BO: A protocol for generating a high-quality genome-scale metabolic reconstruction. / Nat Protoc 2010,5(1):93鈥?21. CrossRef
    4. Edwards JS, Palsson BO: Systems properties of the Haemophilus influenzae Rd metabolic genotype. / Journal of Biological Chemistry 1999,274(25):17410鈥?. CrossRef
    5. Reed JL, Vo TD, Schilling CH, Palsson BO: An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). / Genome Biology 2003,4(9):R54.1-R54.12. CrossRef
    6. Forster J, Famili I, Fu PC, Palsson BO, Nielsen J: Genome-Scale Reconstruction of the Saccharomyces cerevisiae Metabolic Network. / Genome Research 2003,13(2):244鈥?3. CrossRef
    7. Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO: Global reconstruction of the human metabolic network based on genomic and bibliomic data. / Proc Natl Acad Sci USA 2007,104(6):1777鈥?2. CrossRef
    8. Lewis NE, Schramm G, Bordbar A, Schellenberger J, Andersen MP, Cheng JK, Patel N, Yee A, Lewis RA, Eils R, Konig R, Palsson BO: Large-scale in silico modeling of metabolic interactions between cell types in the human brain. / Nat Biotechnol 2010,28(12):1279鈥?5. CrossRef
    9. Gille C, Bolling C, Hoppe A, Bulik S, Hoffmann S, Hubner K, Karlstadt A, Ganeshan R, Konig M, Rother K, Weidlich M, Behre J, Holzhutter HG: HepatoNet1: a comprehensive metabolic reconstruction of the human hepatocyte for the analysis of liver physiology. / Mol Syst Biol 2010, 6:411. CrossRef
    10. Jerby L, Shlomi T, Ruppin E: Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism. / Mol Syst Biol 2010, 6:401. CrossRef
    11. Chang RL, Xie L, Bourne PE, Palsson BO: Drug off-target effects predicted using structural analysis in the context of a metabolic network model. / PLoS Comput Biol 2010,6(9):e1000938. CrossRef
    12. Bordbar A, Lewis NE, Schellenberger J, Palsson BO, Jamshidi N: Insight into human alveolar macrophage and M. tuberculosis interactions via metabolic reconstructions. / Mol Syst Biol 2010, 6:422. CrossRef
    13. Rapoport TA, Heinrich R, Jacobasch G, Rapoport S: A linear steady-state treatment of enzymatic chains. A mathematical model of glycolysis of human erythrocytes. / Eur J Biochem 1974,42(1):107鈥?0. CrossRef
    14. Brumen M, Heinrich R: A metabolic osmotic model of human erythrocytes. / Biosystems 1984,17(2):155鈥?9. CrossRef
    15. Joshi A, Palsson BO: Metabolic dynamics in the human red cell. Part I--A comprehensive kinetic model. / Journal of Theoretical Biology 1989,141(4):515鈥?8. CrossRef
    16. Mulquiney PJ, Bubb WA, Kuchel PW: Model of 2,3-bisphosphoglycerate metabolism in the human erythrocyte based on detailed enzyme kinetic equations: in vivo kinetic characterization of 2,3-bisphosphoglycerate synthase/phosphatase using 13C and 31P NMR. / Biochem J 1999,342(Pt 3):567鈥?0. CrossRef
    17. Schauer M, Heinrich R, Rapoport SM: Mathematische Modellierung der Glykolyse und des Adeninnukleotidstoffwechsels menschlicher Erythrozyten. / Acta Biological er Medica Germanica 1981, 40:1659鈥?682.
    18. Jamshidi N, Edwards JS, Fahland T, Church GM, Palsson BO: Dynamic simulation of the human red blood cell metabolic network. / Bioinformatics 2001,17(3):286鈥?. CrossRef
    19. Kinoshita A, Tsukada K, Soga T, Hishiki T, Ueno Y, Nakayama Y, Tomita M, Suematsu M: Roles of hemoglobin Allostery in hypoxia-induced metabolic alterations in erythrocytes: simulation and its verification by metabolome analysis. / J Biol Chem 2007,282(14):10731鈥?1. CrossRef
    20. Raftos JE, Whillier S, Kuchel PW: Glutathione synthesis and turnover in the human erythrocyte: alignment of a model based on detailed enzyme kinetics with experimental data. / J Biol Chem 2010,285(31):23557鈥?7. CrossRef
    21. Roux-Dalvai F, Gonzalez de Peredo A, Simo C, Guerrier L, Bouyssie D, Zanella A, Citterio A, Burlet-Schiltz O, Boschetti E, Righetti PG, Monsarrat B: Extensive analysis of the cytoplasmic proteome of human erythrocytes using the peptide ligand library technology and advanced mass spectrometry. / Mol Cell Proteomics 2008,7(11):2254鈥?9. CrossRef
    22. Pasini EM, Kirkegaard M, Mortensen P, Lutz HU, Thomas AW, Mann M: In-depth analysis of the membrane and cytosolic proteome of red blood cells. / Blood 2006,108(3):791鈥?01. CrossRef
    23. Low TY, Seow TK, Chung MC: Separation of human erythrocyte membrane associated proteins with one-dimensional and two-dimensional gel electrophoresis followed by identification with matrix-assisted laser desorption/ionization-time of flight mass spectrometry. / Proteomics 2002,2(9):1229鈥?9. CrossRef
    24. Goodman SR, Kurdia A, Ammann L, Kakhniashvili D, Daescu O: The human red blood cell proteome and interactome. / Exp Biol Med (Maywood) 2007,232(11):1391鈥?08. CrossRef
    25. Zhang Y, Thiele I, Weekes D, Li Z, Jaroszewski L, Ginalski K, Deacon AM, Wooley J, Lesley SA, Wilson IA, Palsson B, Osterman A, Godzik A: Three-dimensional structural view of the central metabolic network of Thermotoga maritima. / Science 2009,325(5947):1544鈥?. CrossRef
    26. Vo TD, Greenberg HJ, Palsson BO: Reconstruction and functional characterization of the human mitochondrial metabolic network based on proteomic and biochemical data. / J Biol Chem 2004,279(38):39532鈥?0. CrossRef
    27. Wiback SJ, Palsson BO: Extreme pathway analysis of human red blood cell metabolism. / Biophysical Journal 2002,83(2):808鈥?18. CrossRef
    28. Mahadevan R, Schilling CH: The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. / Metab Eng 2003,5(4):264鈥?6. CrossRef
    29. Lou LL, Clarke S: Enzymatic methylation of band 3 anion transporter in intact human erythrocytes. / Biochemistry 1987,26(1):52鈥?. CrossRef
    30. Allan D, Michell RH: Production of 1,2-diacylglycerol in human erythrocyte membranes exposed to low concentrations of calcium ions. / Biochim Biophys Acta 1976,455(3):824鈥?0. CrossRef
    31. Arduini A, Mancinelli G, Radatti GL, Dottori S, Molajoni F, Ramsay RR: Role of carnitine and carnitine palmitoyltransferase as integral components of the pathway for membrane phospholipid fatty acid turnover in intact human erythrocytes. / J Biol Chem 1992,267(18):12673鈥?1.
    32. Berridge MJ, Irvine RF: Inositol trisphosphate, a novel second messenger in cellular signal transduction. / Nature 1984,312(5992):315鈥?1. CrossRef
    33. Tsukamoto T, Sonenberg M: Catecholamine regulation of human erythrocyte membrane protein kinase. / J Clin Invest 1979,64(2):534鈥?0. CrossRef
    34. McGee JE, Fitzpatrick FA: Erythrocyte-neutrophil interactions: formation of leukotriene B4 by transcellular biosynthesis. / Proc Natl Acad Sci USA 1986,83(5):1349鈥?3. CrossRef
    35. Inoue K, Ohbora Y, Yamasawa K: Metabolism of acetaldehyde by human erythrocytes. / Life Sci 1978,23(2):179鈥?3. CrossRef
    36. Becker SA, Price ND, Palsson BO: Metabolite coupling in genome-scale metabolic networks. / BMC Bioinformatics 2006.,7(111):
    37. Palsson BO: / Systems biology: properties of reconstructed networks. New York: Cambridge University Press; 2006. CrossRef
    38. Graham JM, Peerson JM, Haskell MJ, Shrestha RK, Brown KH, Allen LH: Erythrocyte riboflavin for the detection of riboflavin deficiency in pregnant Nepali women. / Clin Chem 2005,51(11):2162鈥?. CrossRef
    39. Baines M, Davies G: The evaluation of erythrocyte thiamin diphosphate as an indicator of thiamin status in man, and its comparison with erythrocyte transketolase activity measurements. / Ann Clin Biochem 1988,25(Pt 6):698鈥?05.
    40. Agarwal DP, Tobar-Rojas L, Harada S, Goedde HW: Comparative study of erythrocyte aldehyde dehydrogenase in alcoholics and control subjects. / Pharmacol Biochem Behav 1983,18(Suppl 1):89鈥?5. CrossRef
    41. Murakami K, Kondo T, Ohtsuka Y, Fujiwara Y, Shimada M, Kawakami Y: Impairment of glutathione metabolism in erythrocytes from patients with diabetes mellitus. / Metabolism 1989,38(8):753鈥?. CrossRef
    42. Prabakaran S, Wengenroth M, Lockstone HE, Lilley K, Leweke FM, Bahn S: 2-D DIGE analysis of liver and red blood cells provides further evidence for oxidative stress in schizophrenia. / J Proteome Res 2007,6(1):141鈥?. CrossRef
    43. Dadoly J: The Merck Manual. / Medical Reference Services Quarterly 18th edition. 2007,26(2):113鈥?14. CrossRef
    44. Shifman S, Bronstein M, Sternfeld M, Pisante-Shalom A, Lev-Lehman E, Weizman A, Reznik I, Spivak B, Grisaru N, Karp L, Schiffer R, Kotler M, Strous RD, Swartz-Vanetik M, Knobler HY, Shinar E, Beckmann JS, Yakir B, Risch N, Zak NB, Darvasi A: A highly significant association between a COMT haplotype and schizophrenia. / Am J Hum Genet 2002,71(6):1296鈥?02. CrossRef
    45. Usaite R, Patil KR, Grotkjaer T, Nielsen J, Regenberg B: Global transcriptional and physiological responses of Saccharomyces cerevisiae to ammonium, L-alanine, or L-glutamine limitation. / Appl Environ Microbiol 2006,72(9):6194鈥?03. CrossRef
    46. Herrgard MJ, Lee BS, Portnoy V, Palsson BO: Integrated analysis of regulatory and metabolic networks reveals novel regulatory mechanisms in Saccharomyces cerevisiae. / Genome Research 2006,16(5):627鈥?35. CrossRef
    47. Wishart DS, Knox C, Guo AC, Eisner R, Young N, Gautam B, Hau DD, Psychogios N, Dong E, Bouatra S, Mandal R, Sinelnikov I, Xia J, Jia L, Cruz JA, Lim E, Sobsey CA, Shrivastava S, Huang P, Liu P, Fang L, Peng J, Fradette R, Cheng D, Tzur D, Clements M, Lewis A, De Souza A, Zuniga A, Dawe M, / et al.: HMDB: a knowledgebase for the human metabolome. / Nucleic Acids Res 2009, (37 Database):D603鈥?0.
    48. Surgenor DM, Bishop CW: / The red blood cell. / Volume 2. 2nd edition. New York: Academic Press; 1974.
    49. Orth JD, Thiele I, Palsson BO: What is flux balance analysis? / Nat Biotechnol 2010,28(3):245鈥?. CrossRef
    50. Becker SA, Feist AM, Mo ML, Hannum G, Palsson BO, Herrgard MJ: Quantitative prediction of cellular metabolism with constraint-based models: The COBRA Toolbox. / Nat Protocols 2007,2(3):727鈥?38. CrossRef
    51. Amberger J, Bocchini CA, Scott AF, Hamosh A: McKusick's Online Mendelian Inheritance in Man (OMIM). / Nucleic Acids Res 2009, (37 Database):D793鈥?.
    52. Wishart DS, Knox C, Guo AC, Cheng D, Shrivastava S, Tzur D, Gautam B, Hassanali M: DrugBank: a knowledgebase for drugs, drug actions and drug targets. / Nucleic Acids Res 2008, (36 Database):D901鈥?.
    53. Sigurdsson MI, Jamshidi N, Jonsson JJ, Palsson BO: Genome-scale network analysis of imprinted human metabolic genes. / Epigenetics 2009,4(1):43鈥?. CrossRef
    54. Shlomi T, Cabili MN, Ruppin E: Predicting metabolic biomarkers of human inborn errors of metabolism. / Mol Syst Biol 2009, 5:263. CrossRef
  • 作者单位:Aarash Bordbar (1)
    Neema Jamshidi (1)
    Bernhard O Palsson (1)

    1. Department of Bioengineering, University of California San Diego, 417 Powell-Focht Bioengineering Hall, 9500 Gilman Drive, La Jolla, CA, 92093-0412, USA
文摘
Background The development of high-throughput technologies capable of whole cell measurements of genes, proteins, and metabolites has led to the emergence of systems biology. Integrated analysis of the resulting omic data sets has proved to be hard to achieve. Metabolic network reconstructions enable complex relationships amongst molecular components to be represented formally in a biologically relevant manner while respecting physical constraints. In silico models derived from such reconstructions can then be queried or interrogated through mathematical simulations. Proteomic profiling studies of the mature human erythrocyte have shown more proteins present related to metabolic function than previously thought; however the significance and the causal consequences of these findings have not been explored. Results Erythrocyte proteomic data was used to reconstruct the most expansive description of erythrocyte metabolism to date, following extensive manual curation, assessment of the literature, and functional testing. The reconstruction contains 281 enzymes representing functions from glycolysis to cofactor and amino acid metabolism. Such a comprehensive view of erythrocyte metabolism implicates the erythrocyte as a potential biomarker for different diseases as well as a 'cell-based' drug-screening tool. The analysis shows that 94 erythrocyte enzymes are implicated in morbid single nucleotide polymorphisms, representing 142 pathologies. In addition, over 230 FDA-approved and experimental pharmaceuticals have enzymatic targets in the erythrocyte. Conclusion The advancement of proteomic technologies and increased generation of high-throughput proteomic data have created the need for a means to analyze these data in a coherent manner. Network reconstructions provide a systematic means to integrate and analyze proteomic data in a biologically meaning manner. Analysis of the red cell proteome has revealed an unexpected level of complexity in the functional capabilities of human erythrocyte metabolism.

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