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arXiv 2406.16596q-bio.MNq-bio.QM
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大肠杆菌核心与生物合成代谢的紧凑模型

A compact model of Escherichia coli core and biosynthetic metabolism

Marco Corrao, Hai He, Wolfram Liebermeister, Elad Noor, Arren Bar-Even

AI总结:

本文提出了针对大肠杆菌K-12 MG1655的手动精选中等规模代谢模型iCH360,聚焦核心能量与生物合成代谢,克服了基因组规模模型难分析的问题,并展示了其在多种分析场景中的实用潜力。

摘要:

代谢模型以结构化和标准化的方式浓缩了关于生物体的生化知识。由于许多生物体的大规模网络重建易于获取,基因组规模模型在建模者和工程师中被广泛使用。然而,这些大型模型可能难以分析和可视化,有时会生成难以解释甚至生物学上不切实际的预测。在典型细菌代谢的数千个酶促反应中,只有几百个构成了产生能量载体和生物合成前体所必需的代谢途径。这些途径具有相对较高的通量,是维持和繁殖细胞的核心,并为工程代谢途径提供前体和能量。聚焦于这些核心代谢子系统,我们提出了 iCH360,一个针对研究充分的大肠杆菌(Escherichia coli)K-12 MG1655 的能量与生物合成代谢的手动精选中等规模模型。该模型是最新基因组规模重建模型 iML1515 的子网络,并带有更新的数据库注释层和一系列用于可视化的代谢图谱。我们用广泛的生物学信息和定量数据丰富了化学计量网络,增强了模型的范围和适用性。此外,我们评估了该模型与其基因组规模母模型相比的特性,并展示了该网络及支持数据在各种场景中的使用,包括酶约束通量平衡分析、基本通量模式分析和热力学分析。总体而言,我们相信该模型有潜力成为大肠杆菌的参考中等规模代谢模型。

英文摘要:

Metabolic models condense biochemical knowledge about organisms in a structured and standardised way. As large-scale network reconstructions are readily available for many organisms, genome-scale models are being widely used among modellers and engineers. However, these large models can be difficult to analyse and visualise and occasionally generate predictions that are hard to interpret or even biologically unrealistic. Of the thousands of enzymatic reactions in a typical bacterial metabolism, only a few hundred form the metabolic pathways essential to produce energy carriers and biosynthetic precursors. These pathways carry relatively high flux, are central to maintaining and reproducing the cell, and provide precursors and energy to engineered metabolic pathways. Focusing on these central metabolic subsystems, we present iCH360, a manually curated medium-scale model of energy and biosynthesis metabolism for the well-studied bacterium Escherichia coli K-12 MG1655. The model is a sub-network of the most recent genome-scale reconstruction, iML1515, and comes with an updated layer of database annotations and with a range of metabolic maps for visualisation. We enriched the stoichiometric network with extensive biological information and quantitative data, enhancing the scope and applicability of the model. In addition, we assess the properties of this model in comparison to its genome-scale parent and demonstrate the use of the network and supporting data in various scenarios, including enzyme-constrained flux balance analysis, elementary flux mode analysis, and thermodynamic analysis. Overall, we believe this model holds the potential to become a reference medium-scale metabolic model for E. coli.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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