Team:ETH Zurich/Modeling/Genome-Scale Model
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(1) ''"Thirteen Years of Building Constraint-Based In Silico Models of Escherichia coli"'' ,Jennifer L. Reed and Bernhard Ø. Palsson, ''Journal of Bacteriology'', May 2003, p. 2692-2699, Vol. 185, No. 9 <br> | (1) ''"Thirteen Years of Building Constraint-Based In Silico Models of Escherichia coli"'' ,Jennifer L. Reed and Bernhard Ø. Palsson, ''Journal of Bacteriology'', May 2003, p. 2692-2699, Vol. 185, No. 9 <br> | ||
(2) ''"A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information"'', A.M. Feist et al., ''Molecular Systems Biology'' 3:121<br> | (2) ''"A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information"'', A.M. Feist et al., ''Molecular Systems Biology'' 3:121<br> | ||
- | (3) ''"Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox"'', S.A. Becker et al., ''Nature Protocols'', 2007 | + | (3) ''"Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox"'', S.A. Becker et al., ''Nature Protocols'', 2007<br> |
(4) ''"In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data."'', Edwards JS, Ibarra RU, Palsson BO (2001), ''Nat Biotechnol'', 19: 125–130. | (4) ''"In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data."'', Edwards JS, Ibarra RU, Palsson BO (2001), ''Nat Biotechnol'', 19: 125–130. | ||
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Revision as of 15:12, 26 October 2008
Genome Scale AnalysisIn the Restriction Enzymes Analysis modeling section we deal with the analysis of restriction enzymes effects on the genome from the simple point of view of nucleotide sequences and cutting patterns. This is not informative enough when we try to understand if the key principles of reduction and selection at the base of our minimal genome approach are valid in the context of the whole cell response. It is evident that our selection method for smaller genome size strains is based on the assumption that is possible to control growth rate as a function of its genome size. As explained in the Project Overview, we put a selective pressure on the genome size by combining two effects together: the random reduction of the genome size by restriction enzymes cutting and the feeding of a limited amount of thymidine nucleotides on the background of a thymidine auxotrophic strain. In this context, one should also consider the effects that the lost of chromosomal coding regions may have on the physiology of the cell. This scenario needs to be validate using modeling techniques that relate genome content and substrates avaiability with cell physiology, on a system level fashion. Fortunately, in the last ten year huge progress have been achieved in coding our understanding of biological networks into whole cell comprehensive stochiometric models. This model typology is called genome scale modeling and we use the most update genome scale model for our working strain (E.Coli K12 MG1655) in order to answer the following questions:
These questions are answered below, in the respective sections. As first we introduce the genome scale model concepts, the Flux Balance Analysis theory and in particular the iAF1260 E.Coli Genome Scale Model developed by [http://gcrg.ucsd.edu/|the Palsson's Group at UCSD], that we modified and used. In the following sections we show the results of simulations for the different questions to be answered. Genome Scale Models and E.Coli K12 MG1655Genome scale models are biological network reconstructions that effectively represent genome annotations defining the metabolic network that is specific to a particular organism. Thymidine limitation effects on growth ratesGenome size effects on growth ratesDifferent mediumsGrowth rates as output of whole cell system behaviourComparing different approaches to minimal genomeReferences(1) "Thirteen Years of Building Constraint-Based In Silico Models of Escherichia coli" ,Jennifer L. Reed and Bernhard Ø. Palsson, Journal of Bacteriology, May 2003, p. 2692-2699, Vol. 185, No. 9 |