Institute of Bioanalytical Chemistry, Faculty of Chemistry and Mineralogy, University of Leipzig, Germany; Center for Biotechnology and Biomedicine, University of Leipzig, Deutscher Platz 5, Leipzig, Germany.
Department of Chemistry, Biology and Biotechnology, University of Perugia, via Elce di Sotto 8, 06123 Perugia, Italy; Consortium for Computational Molecular and Materials Sciences (CMS), via Elce di Sotto 8, 06123 Perugia, Italy.
Free Radic Biol Med. 2019 Nov 20;144:110-123. doi: 10.1016/j.freeradbiomed.2019.04.027. Epub 2019 Apr 26.
The high chemical diversity of lipids allows them to perform multiple biological functions ranging from serving as structural building blocks of biological membranes to regulation of metabolism and signal transduction. In addition to the native lipidome, lipid species derived from enzymatic and non-enzymatic modifications (the epilipidome) make the overall picture even more complex, as their functions are still largely unknown. Oxidized lipids represent the fraction of epilipidome which has attracted high scientific attention due to their apparent involvement in the onset and development of numerous human disorders. Development of high-throughput analytical methods such as liquid chromatography coupled on-line to mass spectrometry provides the possibility to address epilipidome diversity in complex biological samples. However, the main bottleneck of redox lipidomics, the branch of lipidomics dealing with the characterization of oxidized lipids, remains the lack of optimal computational tools for robust, accurate and specific identification of already discovered and yet unknown modified lipids. Here we discuss the main principles of high-throughput identification of lipids and their modified forms and review the main software tools currently available in redox lipidomics. Different levels of confidence for software assisted identification of redox lipidome are defined and necessary steps toward optimal computational solutions are proposed.
脂质具有很高的化学多样性，能够执行多种生物学功能，从作为生物膜的结构构建块到调节代谢和信号转导。除了天然脂质组外，酶促和非酶促修饰衍生的脂质种类（外脂质组）使整体情况更加复杂，因为它们的功能在很大程度上仍不清楚。氧化脂质代表了外脂质组的一个部分，由于它们明显参与了许多人类疾病的发生和发展，因此引起了科学界的高度关注。高通量分析方法的发展，如液相色谱在线耦合质谱，为解决复杂生物样本中外脂质组的多样性提供了可能性。然而，氧化脂质组学（脂质组学的一个分支，涉及氧化脂质的特征描述）的主要瓶颈仍然是缺乏用于稳健、准确和特异性鉴定已发现和未知修饰脂质的最佳计算工具。本文讨论了高通量鉴定脂质及其修饰形式的主要原则，并综述了氧化脂质组学中目前可用的主要软件工具。定义了软件辅助鉴定氧化脂质组的不同置信度水平，并提出了实现最佳计算解决方案的必要步骤。
