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Titolo:
In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data
Autore:
Edwards, JS; Ibarra, RU; Palsson, BO;
Indirizzi:
Univ Calif San Diego, Dept Bioengn, La Jolla, CA 92093 USA Univ Calif San Diego La Jolla CA USA 92093 ioengn, La Jolla, CA 92093 USA Univ Delaware, Dept Chem Engn, Newark, DE 19716 USA Univ Delaware Newark DE USA 19716 e, Dept Chem Engn, Newark, DE 19716 USA
Titolo Testata:
NATURE BIOTECHNOLOGY
fascicolo: 2, volume: 19, anno: 2001,
pagine: 125 - 130
SICI:
1087-0156(200102)19:2<125:ISPOEC>2.0.ZU;2-N
Fonte:
ISI
Lingua:
ENG
Soggetto:
BASIC CONCEPTS; GROWTH; MODEL; CELL; SIMULATION; NETWORKS; GENOME; CONSTRAINTS; EXPRESSION; COMPLEXITY;
Keywords:
Escherichia coli; genome analysis; metabolic reconstruction; computer simulation;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Agriculture,Biology & Environmental Sciences
Life Sciences
Citazioni:
49
Recensione:
Indirizzi per estratti:
Indirizzo: Palsson, BO Univ Calif San Diego, Dept Bioengn, 9500 Gilman Dr, La Jolla, CA 92093 USA Univ Calif San Diego 9500 Gilman Dr La Jolla CA USA 92093 USA
Citazione:
J.S. Edwards et al., "In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data", NAT BIOTECH, 19(2), 2001, pp. 125-130

Abstract

A significant goal in the post-genome era is to relate the annotated genome sequence to the physiological functions of a cell. Working from the annotated genome sequence, as well as biochemical and physiological information,it is possible to reconstruct complete metabolic networks. Furthermore, computational methods have been developed to interpret and predict the optimal performance of a metabolic network under a range of growth conditions. Wehave tested the hypothesis that Escherichia coil uses its metabolism to grow at a maximal rate using the E. coil MG1655 metabolic reconstruction. Based an this hypothesis, we formulated experiments that describe the quantitative relationship between a primary carbon source (acetate or succinate) uptake rate, oxygen uptake rate, and maximal cellular growth rate. We found that the experimental data were consistent with the stated hypothesis, namely that the E. coil metabolic network is optimized to maximize growth under the experimental conditions considered. This study thus demonstrates how the combination of in silico and experimental biology can be used to obtain aquantitative genotype-phenotype relationship for metabolism in bacterial cells.

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Documento generato il 19/01/20 alle ore 09:01:51