Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
FEMS Yeast Res. 2020 Mar 1;20(2). doi: 10.1093/femsyr/foaa006.
Over the last decades, yeast has become a key model organism for the study of lipid biochemistry. Because the regulation of lipids has been closely linked to various physiopathologies, the study of these biomolecules could lead to new diagnostics and treatments. Before the field can reach this point, however, sufficient tools for integrating and analyzing the ever-growing availability of lipidomics data will need to be developed. To this end, genome-scale models (GEMs) of metabolic networks are useful tools, though their large size and complexity introduces too much uncertainty in the accuracy of predicted outcomes. Ideally, therefore, a model for studying lipids would contain only the pathways required for the proper analysis of these biomolecules, but would not be an ad hoc reduction. We hereby present a metabolic model that focuses on lipid metabolism constructed through the integration of detailed lipid pathways into an already existing GEM of Saccharomyces cerevisiae. Our model was then systematically reduced around the subsystems defined by these pathways to provide a more manageable model size for complex studies. We show that this model is as consistent and inclusive as other yeast GEMs regarding the focus and detail on the lipid metabolism, and can be used as a scaffold for integrating lipidomics data to improve predictions in studies of lipid-related biological functions.
在过去的几十年中，酵母已成为研究脂质生物化学的重要模式生物。由于脂质的调节与各种生理病理学密切相关，因此对这些生物分子的研究可能会带来新的诊断和治疗方法。然而，在该领域能够达到这一目标之前，需要开发足够的工具来整合和分析脂质组学数据的不断增长的可用性。为此，代谢网络的基因组规模模型（GEM）是有用的工具，尽管其庞大的规模和复杂性给预测结果的准确性带来了太多的不确定性。因此，理想情况下，用于研究脂质的模型应该只包含适当分析这些生物分子所需的途径，但不能是专门的简化。在此，我们提出了一种通过将详细的脂质途径整合到已有的酿酒酵母 GEM 中构建的代谢模型，该模型专注于脂质代谢。然后，我们围绕这些途径定义的子系统对模型进行了系统地简化，为复杂研究提供了更易于管理的模型规模。我们表明，该模型在脂质代谢方面与其他酵母 GEM 一样具有一致性和包容性，并且可以用作整合脂质组学数据的支架，以改善与脂质相关的生物学功能研究中的预测。
