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利用计算机模拟方法的系统发育树来约束代谢基因型-表型关系。

Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods.

机构信息

Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093-0412, USA.

出版信息

Nat Rev Microbiol. 2012 Feb 27;10(4):291-305. doi: 10.1038/nrmicro2737.

Abstract

Reconstructed microbial metabolic networks facilitate a mechanistic description of the genotype-phenotype relationship through the deployment of constraint-based reconstruction and analysis (COBRA) methods. As reconstructed networks leverage genomic data for insight and phenotype prediction, the development of COBRA methods has accelerated following the advent of whole-genome sequencing. Here, we describe a phylogeny of COBRA methods that has rapidly evolved from the few early methods, such as flux balance analysis and elementary flux mode analysis, into a repertoire of more than 100 methods. These methods have enabled genome-scale analysis of microbial metabolism for numerous basic and applied uses, including antibiotic discovery, metabolic engineering and modelling of microbial community behaviour.

摘要

重构的微生物代谢网络通过部署基于约束的重构和分析(COBRA)方法,有助于通过基因型-表型关系的机制描述。由于重构网络利用基因组数据进行洞察和表型预测,因此 COBRA 方法的发展随着全基因组测序的出现而加速。在这里,我们描述了 COBRA 方法的系统发育,它已经从早期的少数几种方法(如通量平衡分析和基本通量模式分析)迅速发展成为 100 多种方法的组合。这些方法使微生物代谢的基因组规模分析成为可能,用于许多基础和应用用途,包括抗生素发现、代谢工程和微生物群落行为建模。

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