PUB - Publikationen an der Universität Bielefeld

Metabolic fluxes (i.e. in vivo reaction rates) represent the properties of cellular regulation and are most suitable for characterizing specific phenotypes of microorganisms. As intracellular fluxes are not directly measurable they have to be estimated from measured quantities through model-based evaluation with the aid of computational routines based on13C labeling experiments (13C-MFA). However, the question might be raised about the biological significance and statistical reliability of those flux estimations based on single experiments. In addition the medium throughput approach of13C-MFA leads to a multiplied amount of data, so the used algorithms for data pre-processing and evaluation of results has to be optimized to increase the efficiency. Seeking to answer the question and to adopt the challenge of medium throughput13C-MFA a se- ries of standardized13C-labeling experiments with the model organism Corynebacterium glutami- cum wildtype (WT) and a lysine producer (LP) was carried out under well-controlled conditions: continuous cultivation mode with dilution rates of 0.20h−1, 0.15h−1, 0.10h−1and 0.05h−1was chosen to ensure metabolic and isotopic stationarity. For increasing throughput and minimizing 13C labeling costs a parallel bioreactor setup at small scale (300mL working volume) was uti- lized. Hence, all experiments were performed in fourfold biological replicates for calculation of extracellular rates, i.e. substrate uptake and (by-) product formation, including corresponding stan- dard error. By online FT-IR spectrometry discrimination between13C and12C carbon dioxide was realized. From each single experiment six technical samples were taken and labeling patterns of intracellular metabolites were analyzed by LC-MS/MS technology. To realise data evaluation, processing and storage of such experiments an application-oriented software package 13CFLUX2-Essentials was developed. The package offers an environment to handle the huge amount of data, e.g. the graphically aided adjustment and management of analytical raw data or different functions for comparing results. Calculation of extracellular rates as well as carbon balances, network modeling, parallel multi-start simulations, evaluation and visualization of results is automatically performed. Thus,13C-MFA in a medium throughput is possible now and was developed and used in this work. From the 20 datasets intracellular fluxes were estimated using the 13CFLUX2 software package. Comprehensive statistical analysis of error propagation was performed to investigate the influence of analytical and experimental errors on the determinacy of all fluxes. Label measurements of intracellular metabolites showed different reproducibility between technical and biological repli- cations. Carbon balances were closed between 73–102% with an average about 86%. Beside the extracellulare rates ~66 labeling fragments were included for parameter fitting. 5–7 metabolites were rejected due to analytical errors. With each dataset 10000 single fittings were performed in an multi start optimization (MSO). Differences between biological replicas were caused by va- riations in the fractional labeling of intermediates. 12 out of 20 datasets showed unique global optimal solutions in the MSO results. The studies in a small-scale system discover bottle necks and points for improvement for further investigations. It is demonstrated that multiple experimental runs distinctively increases reliability and, in turn, the potential to generate meaningful fluxome data. Hence, these results strengthen the position of metabolic flux analysis to be an effective diagnostic tool for metabolic engineering.