Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM
Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM
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DOI：
10.1371/journal.pcbi.1003126
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发表时间：
2013-07-01
影响因子：
4.3
通讯作者：
Galagan, James E.
中科院分区：
文献类型：
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作者：
Dreyfuss, Jonathan M.;Zucker, Jeremy D.;Galagan, James E.
丝状真菌粗糙脉孢菌在二十世纪遗传学、生物化学和分子生物学的发展中发挥了核心作用，并继续作为真核生物学的模式生物。在这里，我们已经重建了其代谢的基因组规模模型。该模型由836个代谢基因，257个通路，6个细胞区室组成，并得到了491篇文献引文的广泛人工整理的支持。为了帮助我们的重建，我们开发了三种基于优化的算法，它们共同组成了代谢快速自动重建（FARM）。这些算法是：LInear代谢物稀释通量平衡分析（limed-FBA），其预测通量，同时线性地解释代谢物稀释;一步功能修剪（OnePrune），其用单个紧凑的线性程序去除阻断的反应;和生长/非生长表型的一致再现（CROP），其比以前的方法更快地协调计算机模拟和实验基因必要性之间的差异。针对300多个未用于训练模型的必需/非必需基因的独立测试集，该模型显示出93%的灵敏度和特异性。我们还使用该模型来模拟最初在脉孢菌上进行的生化遗传学实验，通过全面预测必需基因的营养拯救和合成致死相互作用，我们提供了详细的基于路径的机制解释我们的预测。我们的模型为整合和解释脉孢菌正在进行的实验工作提供了可靠的计算框架，我们预计我们的方法将大大减少为其他生物体开发高质量基因组规模代谢模型所需的手动工作。
The filamentous fungus Neurospora crassa played a central role in the development of twentieth-century genetics, biochemistry and molecular biology, and continues to serve as a model organism for eukaryotic biology. Here, we have reconstructed a genome-scale model of its metabolism. This model consists of 836 metabolic genes, 257 pathways, 6 cellular compartments, and is supported by extensive manual curation of 491 literature citations. To aid our reconstruction, we developed three optimization-based algorithms, which together comprise Fast Automated Reconstruction of Metabolism (FARM). These algorithms are: LInear MEtabolite Dilution Flux Balance Analysis (limed-FBA), which predicts flux while linearly accounting for metabolite dilution; One-step functional Pruning (OnePrune), which removes blocked reactions with a single compact linear program; and Consistent Reproduction Of growth/no-growth Phenotype (CROP), which reconciles differences between in silico and experimental gene essentiality faster than previous approaches. Against an independent test set of more than 300 essential/non-essential genes that were not used to train the model, the model displays 93% sensitivity and specificity. We also used the model to simulate the biochemical genetics experiments originally performed on Neurospora by comprehensively predicting nutrient rescue of essential genes and synthetic lethal interactions, and we provide detailed pathway-based mechanistic explanations of our predictions. Our model provides a reliable computational framework for the integration and interpretation of ongoing experimental efforts in Neurospora, and we anticipate that our methods will substantially reduce the manual effort required to develop high-quality genome-scale metabolic models for other organisms.