Data from: Upon accounting for the impact of isoenzyme loss, gene deletion costs anticorrelate with their evolutionary rates

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.系统级代谢网络模型（system-level metabolic network models）可通过生物体的基因组计算其生长与代谢表型。尤为关键的是，通量平衡（flux balance）方法已被用于估算单个代谢基因对生物体适应度的贡献，借此得以检验这些贡献是否蕴含对应基因所受进化压力的相关信息。此前，在酿酒酵母（Saccharomyces cerevisiae）中，研究者未能在计算得到的基因缺失成本与基于序列推导的进化速率之间发现预期的负相关关系，这一现象曾被归因于基因在“当下”对生物体的适应度贡献，与其经数百万年进化积累的突变所体现的历史重要性之间，存在真实的生物学差距。本研究证实，该负相关关系确实存在，且可通过重新审视通量平衡模型中一项被广泛采用的核心假设加以揭示。具体而言，我们提出一种名为“功能缺失成本（function-loss cost）”的全新量化指标，该指标将基因缺失事件的成本估算为该缺失所引发的整体潜在功能损伤。在数千种最小培养环境中，这一新指标与进化速率呈现显著的负相关关系。我们证实，相较于传统的基因缺失成本指标，使用功能缺失成本所带来的性能提升，源于将“同工酶具备无限备份代偿能力”这一基础假设，替换为“同工酶完全不具备功能冗余性”的假设。进一步研究表明，这一关于同工酶的假设变更，虽提升了通量平衡模型所预测的上位相互作用（epistatic interactions）的召回率，但也以降低预测精度为代价。本研究除了提醒研究者需谨慎应用基因组规模通量平衡模型（genome-scale flux balance models）中的基因-反应映射关系外，还提供了新证据，表明进化层面的基因重要性所涵盖的范畴远不止严格的必需性。