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Upon Accounting for the Impact of Isoenzyme Loss Gene Deletion Costs Anticorrelate with Their Evolutionary Rates

机译:考虑到同工酶损失的影响后基因删除的成本与其进化速度成反比。

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摘要

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.
机译:系统级的代谢网络模型可以计算生物体基因组的生长和代谢表型。特别是,通量平衡方法已用于估计单个代谢基因对机体适应性的贡献,从而提供了机会来测试这种贡献是否携带有关相应基因进化压力的信息。先前未能确定酿酒酵母中这种计算的基因损失成本与序列衍生的进化速率之间的预期负相关性,已被归因于基因对生物体的适应性贡献“此刻即刻”与同一个基因的历史之间存在真正的生物学鸿沟。它在数百万年的进化过程中积累的突变证明了这一点。在这里,我们表明这种负相关性确实存在,并且可以通过回顾广泛使用的通量平衡模型假设来暴露。特别是,我们引入了一种称为“功能损失成本”的新指标,该指标将基因损失事件的成本估算为由该损失引起的总潜在功能损害。在数千个最小环境中,这一新指标显示出与进化速率显着负相关。我们证明,通过用同功酶完全非冗余的假设代替同工酶为备份提供无限容量的基本假设,可以解释使用功能损失成本相对于基因损失成本所获得的改进。我们进一步表明,关于同工酶的假设的这种变化增加了通量平衡模型预测的上位相互作用的回忆,但以降低预测精度为代价。除了建议谨慎使用基因组规模通量平衡模型中的基因反应图谱外,我们的分析还提供了新的证据,证明进化基因的重要性远远超过了严格的本质。

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