Metabolic modeling and analysis of the metabolic switch in Streptomyces coelicolor

被引:71
作者
Alam, Mohammad T. [1 ]
Merlo, Maria E. [1 ,2 ]
Hodgson, David A. [3 ]
Wellington, Elizabeth M. H. [3 ]
Takano, Eriko [2 ]
Breitling, Rainer [1 ,4 ]
机构
[1] Univ Groningen, Groningen Bioinformat Ctr, Groningen Biomol Sci & Biotechnol Inst, NL-9751 NN Haren, Netherlands
[2] Univ Groningen, Dept Microbial Physiol, Groningen Biomol Sci & Biotechnol Inst, NL-9751 NN Haren, Netherlands
[3] Univ Warwick, Dept Biol Sci, Coventry CV4 7AL, W Midlands, England
[4] Univ Glasgow, Fac Biomed & Life Sci, Glasgow G12 8QQ, Lanark, Scotland
来源
BMC GENOMICS | 2010年 / 11卷
基金
英国生物技术与生命科学研究理事会;
关键词
GENOME-SCALE MODELS; GENE-EXPRESSION; A3(2); CONSTRAINTS; EVOLUTION; RECONSTRUCTION; BIOSYNTHESIS;
D O I
10.1186/1471-2164-11-202
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: The transition from exponential to stationary phase in Streptomyces coelicolor is accompanied by a major metabolic switch and results in a strong activation of secondary metabolism. Here we have explored the underlying reorganization of the metabolome by combining computational predictions based on constraint-based modeling and detailed transcriptomics time course observations. Results: We reconstructed the stoichiometric matrix of S. coelicolor, including the major antibiotic biosynthesis pathways, and performed flux balance analysis to predict flux changes that occur when the cell switches from biomass to antibiotic production. We defined the model input based on observed fermenter culture data and used a dynamically varying objective function to represent the metabolic switch. The predicted fluxes of many genes show highly significant correlation to the time series of the corresponding gene expression data. Individual mispredictions identify novel links between antibiotic production and primary metabolism. Conclusion: Our results show the usefulness of constraint-based modeling for providing a detailed interpretation of time course gene expression data.
引用
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页数:9
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