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NetRed, an algorithm to reduce genome-scale metabolic networks and facilitate the analysis of flux predictions
Metabolic Engineering ( IF 8.4 ) Pub Date : 2020-11-06 , DOI: 10.1016/j.ymben.2020.11.003
Daniel J Lugar 1 , Sean G Mack 1 , Ganesh Sriram 1
Affiliation  

Flux balance analysis (FBA) of large, genome-scale stoichiometric models (GSMs) is a powerful and popular method to predict cell-wide metabolic activity. FBA typically generates a flux vector containing O(1,000) fluxes. The interpretation of such a flux vector is difficult, even for expert users, because of the large size and complex topology of the underlying metabolic network. This interpretation could be simplified by condensing the network to a reduced, yet fully representative version. Toward this goal we report NetRed, an algorithm that systematically reduces a stoichiometric matrix and a corresponding flux vector to a more easily interpretable form. The reduction offered by NetRed is transparent because it relies purely on matrix algebra and not on optimization. Uniquely, it involves zero information loss; therefore, the original unreduced network can be easily recovered from the reduced network. The inputs to NetRed are (i) a stoichiometric matrix, (ii) a flux vector with numerical flux values, and (iii) a list of “protected” metabolites recommended by the user to remain in the reduced network. NetRed outputs a reduced metabolic network containing a reduced number of metabolites, of which the protected metabolites are a subset. The algorithm also generates a corresponding reduced flux vector. Due to its simplified presentation and easier interpretability, the reduced network allows the user to quickly find fluxes through metabolites and reaction modes or pathways of interest. In this manuscript, we first demonstrate NetRed on a simple network consisting of glycolysis and the pentose phosphate pathway (PPP), wherein NetRed reduced the PPP to a single net reaction. We followed this with applications of NetRed to E. coli and yeast GSMs. NetRed reduced the size of an E. coli GSM by 20- to 30-fold and enabled a comprehensive comparison of aerobic and anaerobic metabolism. The application of NetRed to a yeast GSM allowed for easy mechanistic interpretation of a double-gene knockout that rerouted flux toward dihydroartemisinic acid. When applied to an E. coli strain engineered for enhanced valine production, NetRed allowed for a holistic interpretation of the metabolic rerouting resulting from multiple genetic interventions.



中文翻译:

NetRed,一种减少基因组规模代谢网络并促进通量预测分析的算法

大型基因组规模化学计量模型 (GSM) 的通量平衡分析 (FBA) 是一种强大且流行的预测全细胞代谢活动的方法。FBA 通常会生成包含O的通量向量(1,000) 通量。由于基础代谢网络的大尺寸和复杂拓扑结构,即使是专家用户也很难解释这种通量向量。这种解释可以通过将网络压缩为一个简化但完全具有代表性的版本来简化。为了实现这个目标,我们报告了 NetRed,这是一种系统地将化学计量矩阵和相应的通量向量减少到更容易解释的形式的算法。NetRed 提供的归约是透明的,因为它完全依赖于矩阵代数而不是优化。独特的是,它涉及零信息丢失;因此,可以很容易地从减少的网络中恢复原始的未减少的网络。NetRed 的输入是 (i) 化学计量矩阵,(ii) 具有数值通量值的通量向量,(iii) 用户推荐保留在缩减网络中的“受保护”代谢物列表。NetRed 输出包含数量减少的代谢物的减少的代谢网络,其中受保护的代谢物是一个子集。该算法还生成相应的减少通量向量。由于其简化的表示和更容易的解释,简化的网络允许用户通过代谢物和反应模式或感兴趣的途径快速找到通量。在这份手稿中,我们首先在一个由糖酵解和戊糖磷酸途径 (PPP) 组成的简单网络上展示 NetRed,其中 NetRed 将 PPP 还原为单个净反应。我们遵循 NetRed 的应用程序 NetRed 输出包含数量减少的代谢物的减少的代谢网络,其中受保护的代谢物是一个子集。该算法还生成相应的减少通量向量。由于其简化的表示和更容易的解释,简化的网络允许用户通过代谢物和反应模式或感兴趣的途径快速找到通量。在这份手稿中,我们首先在一个由糖酵解和戊糖磷酸途径 (PPP) 组成的简单网络上展示 NetRed,其中 NetRed 将 PPP 还原为单个净反应。我们遵循 NetRed 的应用程序 NetRed 输出包含数量减少的代谢物的减少的代谢网络,其中受保护的代谢物是一个子集。该算法还生成相应的减少通量向量。由于其简化的表示和更容易的解释,简化的网络允许用户通过代谢物和反应模式或感兴趣的途径快速找到通量。在这份手稿中,我们首先在一个由糖酵解和戊糖磷酸途径 (PPP) 组成的简单网络上展示 NetRed,其中 NetRed 将 PPP 还原为单个净反应。我们遵循 NetRed 的应用程序 简化的网络允许用户通过代谢物和反应模式或感兴趣的途径快速找到通量。在这份手稿中,我们首先在一个由糖酵解和戊糖磷酸途径 (PPP) 组成的简单网络上展示 NetRed,其中 NetRed 将 PPP 还原为单个净反应。我们遵循 NetRed 的应用程序 简化的网络允许用户通过代谢物和反应模式或感兴趣的途径快速找到通量。在这份手稿中,我们首先在一个由糖酵解和戊糖磷酸途径 (PPP) 组成的简单网络上展示 NetRed,其中 NetRed 将 PPP 还原为单个净反应。我们遵循 NetRed 的应用程序大肠杆菌和酵母 GSM。NetRed 将大肠杆菌GSM的大小减少了20 到 30 倍,并能够对有氧和无氧代谢进行全面比较。将 NetRed 应用于酵母 GSM 可以轻松解释双基因敲除,该基因敲除将通量重新路由至双氢青蒿酸。当应用于为增强缬氨酸生产而设计的大肠杆菌菌株时,NetRed 允许对多种遗传干预导致的代谢重新路由进行整体解释。

更新日期:2020-11-06
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