title: Construction and analysis of the model of energy metabolism in E. coli.
abstract: Genome-scale models of metabolism have only been analyzed with the constraint-based modelling philosophy and there have been several genome-scale gene-protein-reaction models. But research on the modelling for energy metabolism of organisms just began in recent years and research on metabolic weighted complex network are rare in literature. We have made three research based on the complete model of E. coli's energy metabolism. We first constructed a metabolic weighted network using the rates of free energy consumption within metabolic reactions as the weights. We then analyzed some structural characters of the metabolic weighted network that we constructed. We found that the distribution of the weight values was uneven, that most of the weight values were zero while reactions with abstract large weight values were rare and that the relationship between w (weight values) and v (flux values) was not of linear correlation. At last, we have done some research on the equilibrium of free energy for the energy metabolism system of E. coli. We found that E(out) (free energy rate input from the environment) can meet the demand of E(ch)(in) (free energy rate dissipated by chemical process) and that chemical process plays a great role in the dissipation of free energy in cells. By these research and to a certain extend, we can understand more about the energy metabolism of E. coli.
authors: Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.
authors: Zixiang
authors: Z
authors: Xu
authors: Xiao
authors: X
authors: Sun
authors: Jibin
authors: J
authors: Sun
mesh_terms: D004734:Energy Metabolism; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism*; D005798:Genes, Bacterial / Q000235:genetics; D008954:Models, Biological; D013816:Thermodynamics
references: J Theor Biol. 2004 Jun 7;228(3):327-33
references: 15135031
references: Nat Rev Microbiol. 2004 Nov;2(11):886-97
references: 15494745
references: Nature. 2004 Feb 26;427(6977):839-43
references: 14985762
references: PLoS Comput Biol. 2008 Feb;4(2):e36
references: 18266464
references: Trends Biotechnol. 2003 Apr;21(4):162-9
references: 12679064
references: BMC Microbiol. 2005 Mar 07;5:8
references: 15752426
references: Mol Syst Biol. 2006;2:2006.0004
references: 16738551
references: Nat Biotechnol. 2008 Jun;26(6):659-67
references: 18536691
references: Biotechnol Bioeng. 2013 Mar;110(3):914-23
references: 23042478
references: J Bacteriol. 2005 Aug;187(16):5818-30
references: 16077130
references: Nature. 2006 Oct 5;443(7111):527-33
references: 17024084
references: Biophys J. 2007 Mar 1;92(5):1792-805
references: 17172310
references: Genome Biol. 2003;4(9):R54
references: 12952533
references: Metab Eng. 2003 Oct;5(4):264-76
references: 14642354
references: Biophys J. 2008 Aug;95(3):1487-99
references: 18645197
references: Mol Syst Biol. 2007;3:121
references: 17593909
references: Nat Protoc. 2007;2(3):727-38
references: 17406635
references: J Biol Chem. 2007 Sep 28;282(39):28791-28799
references: 17573341
references: Biophys J. 2006 Feb 15;90(4):1453-61
references: 16299075
references: Genome Res. 2004 Jul;14(7):1298-309
references: 15197165
references: Metab Eng. 2005 Jul;7(4):251-9
references: 16140239
references: Biophys J. 2002 Jul;83(1):79-86
references: 12080101
references: Bioinformatics. 2005 Apr 15;21(8):1603-9
references: 15613400
references: Mol Syst Biol. 2005;1:2005.0012
references: 16729047