Untargeted metabolomics approaches aim at the global probing of the metabolic space of a biological system. LC-ESI-HRMS has become a key technique for this purpose. However, the application of LC-HRMS gives rise to several new challenges such as the correct recognition of biologically derived features, ion suppression caused by matrix effects and the most prevalent problem of identification of unknown compounds. Stable isotopic labeling (SIL) assisted approaches offer new possibilities to overcome these limitations. Within the presented thesis, two LC-HRMS based untargeted metabolomics workflows have been developed for the analysis of uniformly 13C labeled metabolites with a high isotopic enrichment degree (i.e. >97%). Both workflows have been realized in close cooperation with bioinformaticians and comprise all steps beginning from cultivation, sample preparation, LC-HRMS analysis to data processing and statistical evaluation. The first workflow facilitates the unbiased annotation of the global metabolome and LC-HRMS/MS analysis for structure elucidation. The workflow was exemplified with various U-13C labeled organisms and resulted in the comprehensive detection of truly biology derived compounds. The second workflow has been developed for the study of the metabolic fate of exogenous and endogenous tracer substances in biological systems. To this end, the detoxification of the mycotoxin deoxynivalenol in planta as an exogenous tracer and U-13C labeled phenylalanine (>99%) as an endogenous tracer have been studied separately. For both studies, only tracer derived biotransformation products many of which not known before have been found, demonstrating the advantages of this approach. The concepts of both presented SIL assisted workflows can be easily adopted for a wide range of different applications and therefore show a high potential to be used in various other research fields.