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微生物中心代谢的重建与分析

Reconstruction and Analysis of Central Metabolism in Microbes.

作者信息

Edirisinghe Janaka N, Faria José P, Harris Nomi L, Allen Benjamin H, Henry Christopher S

机构信息

Computation Institute, University of Chicago, Chicago, IL, USA.

Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA.

出版信息

Methods Mol Biol. 2018;1716:111-129. doi: 10.1007/978-1-4939-7528-0_5.

Abstract

Genome-scale metabolic models (GEMs) generated from automated reconstruction pipelines often lack accuracy due to the need for extensive gapfilling and the inference of periphery metabolic pathways based on lower-confidence annotations. The central carbon pathways and electron transport chains are among the most well-understood regions of microbial metabolism, and these pathways contribute significantly toward defining cellular behavior and growth conditions. Thus, it is often useful to construct a simplified core metabolic model (CMM) that is comprised of only the high-confidence central pathways. In this chapter, we discuss methods for producing core metabolic models (CMM) based on genome annotations. With its reduced scope compared to GEMs, CMM reconstruction focuses on accurate representation of the central metabolic pathways related to energy biosynthesis and accurate energy yield predictions. We demonstrate the reconstruction and analysis of CMMs using the DOE Systems Biology Knowledgebase (KBase). The complete workflow is available at http://kbase.us/core-models/.

摘要

通过自动化重建流程生成的基因组规模代谢模型(GEMs),由于需要大量的缺口填充以及基于低置信度注释推断外围代谢途径,往往缺乏准确性。中心碳途径和电子传递链是微生物代谢中最被充分理解的区域之一,这些途径对定义细胞行为和生长条件有显著贡献。因此,构建一个仅由高置信度中心途径组成的简化核心代谢模型(CMM)通常很有用。在本章中,我们讨论基于基因组注释生成核心代谢模型(CMM)的方法。与GEMs相比,CMM重建范围缩小,重点在于准确表示与能量生物合成相关的中心代谢途径以及准确预测能量产量。我们展示了使用美国能源部系统生物学知识库(KBase)进行CMMs的重建和分析。完整的工作流程可在http://kbase.us/core-models/获取。

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