IsoSearch: An Untargeted and Unbiased Metabolite and Lipid Isotopomer Tracing Strategy from HR-LC-MS/MS Datasets

Abstract

Stable isotopic tracer analysis is a technique used to determine carbon or nitrogen atom incorporation into biological systems. A number of mass spectrometry based approaches have been developed for this purpose, including high-resolution tandem mass spectrometry (HR-LC-MS/MS), selected reaction monitoring (SRM) and parallel reaction monitoring (PRM). We have developed an approach for analyzing untargeted metabolomic and lipidomic datasets using high-resolution mass spectrometry with polarity switching and implemented our approach in the open-source R script IsoSearch and in Scaffold Elements software. Using our strategy, which requires an unlabeled reference dataset and isotope labeled datasets across various biological conditions, we traced metabolic isotopomer alterations in breast cancer cells (MCF-7) treated with the metabolic drugs 2-deoxy-glucose, 6-aminonicotinamide, compound 968, and rapamycin. Metabolites and lipids were first identified by the commercial software Scaffold Elements and LipidSearch, then IsoSearch successfully profiled the ¹³C-isotopomers extracted metabolites and lipids from ¹³C-glucose labeled MCF-7 cells. The results interpreted known models, such as glycolysis and pentose phosphate pathway inhibition, but also helped to discover new metabolic/lipid flux patterns, including a reactive oxygen species (ROS) defense mechanism induced by 6AN and triglyceride accumulation in rapamycin treated cells. The results suggest the IsoSearch/Scaffold Elements platform is effective for studying metabolic tracer analysis in diseases, drug metabolism, and metabolic engineering for both polar metabolites and non-polar lipids.

Keywords: 13C; 15N; LC-MS/MS; cancer; cell culture; flux; glucose; glutamine; high resolution; isotopic tracer analysis; lipidomics; liquid chromatography; mass spectrometry; metabolism; metabolomics; polarity switching; stable isotope labeling.

Figure 1

The workflow of untargeted fluxomic analysis. Two sets of cells are cultured in ¹²C-glucose or ¹³C[6]-glucose containing media for isotope labeling. Both non-polar lipids and polar metabolites were extracted using MTBE/methanol, and samples were acquired by high resolution LC-MS/MS via data-dependent acquisition (DDA) with polarity switching. The metabolites and lipids of unlabeled samples were then identified using commercial software and serve as references for labeled samples. The isotopically labeled samples were matched against the references using the in-house R script IsoSearch or the commercial software Scaffold Elements.

Figure 2

Validation of untargeted high-resolution fluxomics. (A) Uridine triphosphate (UTP) and its associated isotopomers were detected using both targeted and untargeted metabolomics. The abundant M+5 peak of UTP indicates the ribose ring comes from the ¹³C[6]-glucose. Both the targeted fluxomics via selected reaction monitoring (SRM) (left) and untargeted high-resolution isotopomer tracing (IsoSearch) (right) show a similar isotopomer pattern after ¹³C[6]-glucose tracing for UTP. (B) The phospholipid PC(16:0/16:0) and its associated isotopomers were profiled using untargeted lipid fluxomics. The overlap of lipid isotopomer peaks with high carbon numbers and other lipid peaks are distinguished using the IsoSearch strategy.

Figure 3

An overview of untargeted fluxomics analysis from drug treated MCF-7 breast cancer cells reveals the changes in metabolites and their associated isotopomers. (A) A heat map of untargeted fluxomics results displays various metabolites and their isotopomer alterations after drug treatments with 2DG, Rapa, 6AN and DMSO vehicle control. The MA scatterplot of (B) the top 10 increased (red) and decreased (blue) metabolites induced by 2DG at 24 h; and (C) the top 10 increased (red) and decreased (blue) metabolites induced by 6AN at 24 h; and (D) the top 10 increased (red) and decreased (blue) metabolites induced by rapamycin at 24 h.

Figure 4

The 2DG and 6AN affect metabolic fluxes of ¹³C-glucose in MCF-7 cells differently. The bar graphs indicate the ratio of ¹³C incorporation for the isotopomers of each metabolite via IsoSearch. (A) 2DG inhibits the formation of glucose 6-phosphate and ¹³C flux to glycolysis. The circles represent the carbon atoms of each polar metabolite, and ¹³C-labeled carbons are filled in red. (B) 2DG inhibits ¹³C[6]-glucose metabolic flux and its downstream pathways. The arrow thickness represents the relative flux ratio through the metabolic pathways. (C) The 6AN inhibits 6-phosphogluconate dehydrogenase and ¹³C flux to PPP. (D) The 6AN drives the ¹³C[6]-glucose metabolic flux to aerobic glycolysis and oxidative stress. (E) Glucose, (F) Lactate, (G) Cysteine-glutathione disulfide, (H) carnosine, (I) fumarate, (J) succinate, (K) carnitine, (L) NAD+ isotopomer incorporations are altered by 2DG or 6AN at 2 h, 16 h, and 24 h.

Figure 5

Lipid ¹³C isotopic flux changes are profiled using untargeted LC-MS/MS with polarity switching. (A) The 2DG and Rapa dysregulate various lipid classes compared to the control (DMSO). (B) The 2DG and Rapa alter the phosphatidylcholine (PC), lysophosphatidylcholine (LPC), and triglyceride (TG) lipid classes with various fatty acid chains differently. (C) The 2DG decreases all of the PC(16:0/16:1) isotopomer levels, but Rapa only decreases PC(16:0/16:1) flux through higher ¹³C isotopes (>M+11). (D) Both 2DG and Rapa down-regulated the levels of LPC(16:0) ¹³C isotopomers. (E) TG(16:0/18:1/18:1) isotopomer levels decreased with 2DG treatment, but increased with Rapa.