Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus <i>Neurospora crassa</i> Using FARM

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.丝状真菌粗糙脉孢菌（Neurospora crassa）在20世纪遗传学、生物化学与分子生物学的发展历程中发挥了核心作用，至今仍作为真核生物研究的模式生物。本研究构建了该菌的基因组尺度代谢模型，该模型涵盖836个代谢基因、257条代谢通路与6个细胞区室，且依托对491篇文献的全面人工整理与注释得以构建。为辅助模型构建，本研究开发了三类基于优化算法的工具，共同构成代谢快速自动重构工具（Fast Automated Reconstruction of Metabolism，FARM）。这三类算法分别为：线性代谢物稀释通量平衡分析（LInear MEtabolite Dilution Flux Balance Analysis，limed-FBA），该算法在通量预测中以线性方式考量代谢物稀释效应；单步功能剪枝算法（One-step functional Pruning，OnePrune），通过单个紧凑线性规划程序移除阻塞反应；生长/无生长表型一致性重现算法（Consistent Reproduction Of growth/no-growth Phenotype，CROP），相较于此前方法，可更快解决虚拟预测与实验测得的基因必需性之间的差异。针对未用于模型训练的300余个必需/非必需基因组成的独立测试集，该模型的灵敏度与特异性均达到93%。本研究还利用该模型模拟了最初在粗糙脉孢菌上开展的生化遗传学实验：全面预测了必需基因的营养拯救效应与合成致死相互作用，并针对预测结果提供了基于代谢通路的详细机理解释。本模型为整合与解析当前粗糙脉孢菌的相关实验研究提供了可靠的计算框架，同时我们预期，本研究开发的方法将大幅降低为其他物种构建高质量基因组尺度代谢模型所需的人工工作量。