Weindl Daniel, Cordes Thekla, Battello Nadia, Sapcariu Sean C, Dong Xiangyi, Wegner Andre, Hiller Karsten
Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, Avenue des Hauts Fourneaux, Esch-sur-Alzette, 4362 Luxembourg.
Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, Avenue des Hauts Fourneaux, Esch-sur-Alzette, 4362 Luxembourg ; Department of Bioengineering, University of California, Gilman Drive, San Diego, La Jolla, 92037 USA.
Cancer Metab. 2016 Apr 23;4:10. doi: 10.1186/s40170-016-0150-z. eCollection 2016.
Metabolism gained increasing interest for the understanding of diseases and to pinpoint therapeutic intervention points. However, classical metabolomics techniques only provide a very static view on metabolism. Metabolic flux analysis methods, on the other hand, are highly targeted and require detailed knowledge on metabolism beforehand.
We present a novel workflow to analyze non-targeted metabolome-wide stable isotope labeling data to detect metabolic flux changes in a non-targeted manner. Furthermore, we show how similarity-analysis of isotopic enrichment patterns can be used for pathway contextualization of unidentified compounds. We illustrate our approach with the analysis of changes in cellular metabolism of human adenocarcinoma cells in response to decreased oxygen availability. Starting without a priori knowledge, we detect metabolic flux changes, leading to an increased glutamine contribution to acetyl-CoA production, reveal biosynthesis of N-acetylaspartate by N-acetyltransferase 8-like (NAT8L) in lung cancer cells and show that NAT8L silencing inhibits proliferation of A549, JHH-4, PH5CH8, and BEAS-2B cells.
Differential stable isotope labeling analysis provides qualitative metabolic flux information in a non-targeted manner. Furthermore, similarity analysis of enrichment patterns provides information on metabolically closely related compounds. N-acetylaspartate and NAT8L are important players in cancer cell metabolism, a context in which they have not received much attention yet.
代谢对于理解疾病和确定治疗干预点越来越受到关注。然而,经典的代谢组学技术仅提供了关于代谢的非常静态的观点。另一方面,代谢通量分析方法具有高度针对性,并且事先需要对代谢有详细的了解。
我们提出了一种新颖的工作流程,用于分析非靶向全代谢组稳定同位素标记数据,以非靶向方式检测代谢通量变化。此外,我们展示了如何将同位素富集模式的相似性分析用于未鉴定化合物的途径背景分析。我们通过分析人腺癌细胞在氧供应减少时细胞代谢的变化来说明我们的方法。在没有先验知识的情况下开始,我们检测到代谢通量变化,导致谷氨酰胺对乙酰辅酶A产生的贡献增加,揭示了肺癌细胞中N-乙酰天冬氨酸通过N-乙酰转移酶8样(NAT8L)的生物合成,并表明NAT8L沉默抑制了A549、JHH-4、PH5CH8和BEAS-2B细胞的增殖。
差异稳定同位素标记分析以非靶向方式提供定性代谢通量信息。此外,富集模式的相似性分析提供了关于代谢密切相关化合物的信息。N-乙酰天冬氨酸和NAT8L是癌细胞代谢中的重要参与者,在这方面它们尚未受到太多关注。