Bridging the gap between non-targeted stable isotope labeling and metabolic flux analysis

Abstract

BackgroundMetabolism 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.ResultsWe 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.ConclusionsDifferential 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s40170-016-0150-z) contains supplementary material, which is available to authorized users.

Quantitative metabolic flux analysis reveals an unconventional pathway of fatty acid synthesis in cancer cells deficient for the mitochondrial citrate transport protein

“…NAA is produced and secreted by human non-small cell lung cancer cells, and has shown potential as a plasma biomarker for lung cancer, particularly in young patients (Lou et al, 2016). High levels of NAT8L, the enzyme that generates NAA, is associated with poor prognosis in several cancer types (Zand et al, 2016), and NAT8L silencing reduces cell proliferation (Weindl et al, 2016). These studies raise the possibility that NAA depletion may contribute to the growth suppressive effects of CTP deficiency.…”

MIA: non-targeted mass isotopolome analysis

“…MIA helps the user to quickly visualize and analyze this complex data and to gain new biological insights eventually. A more in-depth description of the implemented workflows and a case study applying the described workflows are available in Weindl et al (2016).…”

“…Such variations are caused by, and are indicative of, altered metabolic fluxes. Therefore, metabolic flux changes are detected in a non-targeted manner (Weindl et al , 2015a, 2016). …”

“…Usually compounds closely connected within the metabolic network show very similar MIDs (Weindl et al , 2016). MIA exploits this fact for the analysis of stable isotope labeling data: Isotopically enriched compounds can be visualized in form of a network with connectivity based on their pairwise similarity.…”

“…However, current approaches are usually highly targeted and only take into account a small set of metabolites. We recently demonstrated the potential of non-targeted stable isotope labeling in the analysis of hypoxic cancer cells to detect hypoxia-induced metabolic flux changes in a non-targeted manner (Weindl et al , 2016). …”