To reduce the demand for fossil resources, biotechnological processes are increasingly applied. Therefore, the biological hosts used for manufacturing of products of interest have to be optimized in order to achieve the highest possible yield. For this optimization, which is usually carried out by means of metabolic engineering strategies, the intracellular processes need to be investigated in advance by methods such as ¹³C-Metabolic Flux Analysis (MFA).

The present thesis focused on improving analytical techniques for the measurement of ¹³C-labeling patterns of metabolites. Parameters influencing the data quality of existing analytical techniques based on gas chromatography-mass spectrometry (GC-MS) for the classic ¹³C-MFA, were investigated. Focusing on the analysis of proteinogenic amino acids, a detailed protocol for sample preparation and GC-MS analysis was established to enable scientists to easily produce high quality labeling data for ¹³C-MFA.

Additionally, sample preparation and measurement methods for labeling determination of intracellular metabolites were implemented and further developed. The application of the developed methods facilitates an in-depth analysis of the glucose uptake in Pseudomonas and the examination of cyclic Entner-Doudoroff-Pathway fluxes. Compared to classic ¹³C-MFA, the use of intracellular metabolites increased the information content and therefore additional fluxes could be resolved.

Furthermore, the potential of GC-MS/MS analyses was investigated to increase the positional ¹³C-label information of the MS data by introducing a second fragmentation step. This positional information on ¹³C-isotopes can be exploited to resolve additional metabolic fluxes. Leucine and lysine were found to be promising amino acids in terms of acetyl-CoA labeling determination when analyzed in tandem MS. Labeling experiments with Saccharomyces cerevisiae revealed differences in the labeling of cytosolic and mitochondrial acetyl-CoA, indicating that there is no significant exchange of these two compartmental pools.

The methods presented in this study are highly sophisticated and are suited for determination of the labeling of various metabolites. The information gained by the application of these methods is suitable for use in¹³C-MFA and thus enables a deeper insight into the metabolic activity inside the cell