X¹³CMS: Global Tracking of Isotopic Labels in Untargeted Metabolomics

Abstract

Studies of isotopically labeled compounds have been fundamental to understanding metabolic pathways and fluxes. They have traditionally, however, been used in conjunction with targeted analyses that identify and quantify a limited number of labeled downstream metabolites. Here we describe an alternative workflow that leverages recent advances in untargeted metabolomic technologies to track the fates of isotopically labeled metabolites in a global, unbiased manner. This untargeted approach can be applied to discover novel biochemical pathways and characterize changes in the fates of labeled metabolites as a function of altered biological conditions such as disease. To facilitate the data analysis, we introduce X13CMS, an extension of the widely used mass spectrometry-based metabolomic software package XCMS. X13CMS uses the XCMS platform to detect metabolite peaks and perform retention-time alignment in liquid chromatography/mass spectrometry (LC/MS) data. With the use of the XCMS output, the program then identifies isotopologue groups that correspond to isotopically labeled compounds. The retrieval of these groups is done without any a priori knowledge besides the following input parameters: (i) the mass difference between the unlabeled and labeled isotopes, (ii) the mass accuracy of the instrument used in the analysis, and (iii) the estimated retention-time reproducibility of the chromatographic method. Despite its name, X13CMS can be used to track any isotopic label. Additionally, it detects differential labeling patterns in biological samples collected from parallel control and experimental conditions. We validated the ability of X13CMS to accurately retrieve labeled metabolites from complex biological matrices both with targeted LC/MS/MS analysis of a subset of the hits identified by the program and with labeled standards spiked into cell extracts. We demonstrate the full functionality of X13CMS with an analysis of cultured rat astrocytes treated with uniformly labeled (U-)13C-glucose during lipopolysaccharide (LPS) challenge. Our results show that out of 223 isotopologue groups enriched from U-13C-glucose, 95 have statistically significant differential labeling patterns in astrocytes challenged with LPS compared to unchallenged control cells. Only two of these groups overlap with the 32 differentially regulated peaks identified by XCMS, indicating that X13CMS uncovers different and complementary information from untargeted metabolomic studies. Like XCMS, X13CMS is implemented in R. It is available from our laboratory website at .

Ketogenesis prevents diet-induced fatty liver injury and hyperglycemia

“…The summed ion count of each of these acyl-CoA groups, representing the total abundance of a species in all of its observed labeled forms, was markedly increased in HMGCS2-deficient livers, suggesting increased flux through the DNL pathway ( Figure 5, C and D). To confirm that these identified acyl-CoA species were not differentially labeled by [ 13 C]pyruvate, bioinformatics analysis using software that we recently developed (40) revealed that these compounds were not labeled differently in ketogenesis-insufficient animals compared with those in controls, again supporting that augmented acyl-CoA pools cannot simply be attributed to increased labeling, but instead indicate increased pool sizes. Moreover, terminal oxidation of [ (41).…”

Effective Use of Mass Spectrometry in the Clinical Laboratory

“…Once molecules that differentiate the 2 populations have been identified, a targeted approach can be used to further characterize the utility of monitoring changes in the putative biomarkers. One particularly novel approach to metabolomics is the use of stable isotopes to trace metabolic fate of energy sources in diseased and healthy cells (24 ).…”

Non-targeted Tracer Fate Detection

“…Such information can also be ob-tained from NTFD by analyzing specific mass spectrometric fragments [9] or combinations thereof [25]. MzMatch-ISO [18] and X 13 CMS [14] are both R packages that allow for the non-targeted determination of MIDs and can be regarded as the LC-MS equivalents of NTFD.…”

“…Although many metabolic pathways are well described and known since many years, new reactions are continuously being identified, [10,11] underlining the necessity for a global detection of isotopic enrichment. Recently, several tools for the non-targeted detection of isotopic enrichment in mass spectrometric data have been developed [12][13][14][15][16][17][18].…”