INTRODUCTION To interpret metabolomic and lipidomic profiles, it is necessary to identify the metabolic reactions that connect the measured molecules. This can be achieved by putting them in the context of genome-scale metabolic network reconstructions. However, mapping experimentally measured molecules onto metabolic networks is challenging due to differences in identifiers and level of annotation between data and metabolic networks, especially for lipids. OBJECTIVES To help linking lipids from lipidomics datasets with lipids in metabolic networks, we developed a new matching method based on the ChEBI ontology. The implementation is freely available as a python library and in MetExplore webserver. METHODS Our matching method is more flexible than an exact identifier-based correspondence since it allows establishing a link between molecules even if a different level of precision is provided in the dataset and in the metabolic network. For instance, it can associate a generic class of lipids present in the network with the molecular species detailed in the lipidomics dataset. This mapping is based on the computation of a distance between molecules in ChEBI ontology. RESULTS We applied our method to a chemical library (968 lipids) and an experimental dataset (32 modulated lipids) and showed that using ontology-based mapping improves and facilitates the link with genome scale metabolic networks. Beyond network mapping, the results provide ways for improvements in terms of network curation and lipidomics data annotation. CONCLUSION This new method being generic, it can be applied to any metabolomics data and therefore improve our comprehension of metabolic modulations.

中文翻译：

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使用本体论改善基因组规模代谢网络中的脂质定位。

简介为了解释代谢组学和脂质组学概况，有必要确定连接被测分子的代谢反应。可以通过将它们置于基因组规模的代谢网络重建环境中来实现。但是，由于数据和代谢网络之间的标识符和注释级别不同，尤其是对于脂质，将实验测量的分子映射到代谢网络上具有挑战性。目的为了帮助将脂质组学数据集的脂质与代谢网络中的脂质连接起来，我们基于ChEBI本体开发了一种新的匹配方法。该实现可作为python库和MetExplore Web服务器免费提供。方法我们的匹配方法比基于精确标识符的对应方法更加灵活，因为即使在数据集和代谢网络中提供了不同级别的精度，它也可以在分子之间建立链接。例如，它可以将网络中存在的一类脂质与脂质组学数据集中详述的分子种类相关联。此映射基于ChEBI本体中分子之间的距离的计算。结果我们将我们的方法应用于化学文库（968种脂质）和实验数据集（32种经调制的脂质），并表明使用基于本体的作图可以改善并促进与基因组规模代谢网络的联系。除网络映射外，结果还提供了改进网络管理和脂质组学数据注释的方法。