Jacobs Christopher, Lambourne Luke, Xia Yu, Segrè Daniel
Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America.
Department of Bioengineering, Faculty of Engineering, McGill University, Montreal, Quebec, Canada.
PLoS One. 2017 Jan 20;12(1):e0170164. doi: 10.1371/journal.pone.0170164. eCollection 2017.
System-level metabolic network models enable the computation of growth and metabolic phenotypes from an organism's genome. In particular, flux balance approaches have been used to estimate the contribution of individual metabolic genes to organismal fitness, offering the opportunity to test whether such contributions carry information about the evolutionary pressure on the corresponding genes. Previous failure to identify the expected negative correlation between such computed gene-loss cost and sequence-derived evolutionary rates in Saccharomyces cerevisiae has been ascribed to a real biological gap between a gene's fitness contribution to an organism "here and now" and the same gene's historical importance as evidenced by its accumulated mutations over millions of years of evolution. Here we show that this negative correlation does exist, and can be exposed by revisiting a broadly employed assumption of flux balance models. In particular, we introduce a new metric that we call "function-loss cost", which estimates the cost of a gene loss event as the total potential functional impairment caused by that loss. This new metric displays significant negative correlation with evolutionary rate, across several thousand minimal environments. We demonstrate that the improvement gained using function-loss cost over gene-loss cost is explained by replacing the base assumption that isoenzymes provide unlimited capacity for backup with the assumption that isoenzymes are completely non-redundant. We further show that this change of the assumption regarding isoenzymes increases the recall of epistatic interactions predicted by the flux balance model at the cost of a reduction in the precision of the predictions. In addition to suggesting that the gene-to-reaction mapping in genome-scale flux balance models should be used with caution, our analysis provides new evidence that evolutionary gene importance captures much more than strict essentiality.
系统水平的代谢网络模型能够根据生物体的基因组计算其生长和代谢表型。特别是,通量平衡方法已被用于估计单个代谢基因对生物体适应性的贡献,从而有机会检验这些贡献是否携带有关相应基因进化压力的信息。先前在酿酒酵母中未能识别出这种计算出的基因缺失成本与序列衍生的进化速率之间预期的负相关,被归因于基因在“此时此地”对生物体适应性的贡献与其在数百万年进化过程中积累的突变所证明的历史重要性之间存在真实的生物学差距。在这里,我们表明这种负相关确实存在,并且可以通过重新审视通量平衡模型的一个广泛采用的假设来揭示。具体而言,我们引入了一种新的指标,我们称之为“功能丧失成本”,它将基因缺失事件的成本估计为由该缺失导致的总潜在功能损害。在数千种最小环境中,这种新指标与进化速率呈现出显著的负相关。我们证明,使用功能丧失成本相对于基因缺失成本所获得的改进,是通过将同工酶提供无限备份能力的基本假设替换为同工酶完全非冗余的假设来解释的。我们进一步表明,关于同工酶的这一假设变化增加了通量平衡模型预测的上位相互作用的召回率,但代价是预测精度的降低。除了表明在基因组规模的通量平衡模型中基因到反应的映射应谨慎使用外,我们的分析还提供了新的证据,即进化基因重要性所涵盖的远不止严格的必需性。