Biomedical subjects

Tae Hoon Yang

Publications and source records attributed to Tae Hoon Yang.

5 recordsLinked to original sources

PubMed2006

Respirometric 13C flux analysis, Part I: design, construction and validation of a novel multiple reactor system using on-line membrane inlet mass spectrometry.

A novel method for (13)C flux analysis based on on-line CO(2) labeling measurements is presented. This so-called respirometric (13)C flux analysis requires multiple parallel (13)C labeling experiments using differently labeled tracer substrates. In Part I of the work, a membrane-inlet mass spectrometry-based measurement system with 6 parallel reactors with each 12 ml liquid volume and associated experimental and computational methods for the respirometric (13)C data acquisition and evaluation are described. Signal dynamics after switching between membrane probes follow exactly first-order allowing extrapolation to steady state. Each measurement cycle involving 3 reactors takes about 2 min. After development of a dynamic calibration method, the suitability and reliability of the analysis was examined with a lysine-producing mutant of Corynebacterium glutamicum using [1-(13)C(1)], [6-(13)C(1)], [1,6-(13)C(2)] glucose. Specific rates of oxygen uptake and CO(2) production were estimated with an error less than +/-0.3 mmol g(-1) h(-1) and had +/-3% to +/-10% deviations between parallel reactors which is primarily caused by inaccuracies in initial biomass concentration. The respiratory quotient could be determined with an uncertainty less than +/-0.02 and varied only +/-3% between reactors. Fractional labeling of CO(2) was estimated with much higher precision of about +/-0.001 to +/-0.005. The detailed statistical analysis suggested that these data should be of sufficient quality to allow physiological interpretation and metabolic flux estimation. The obtained data were applied for the respirometric (13)C metabolic flux analysis in Part II.

Bioreactors↗

PubMed2006

Respirometric 13C flux analysis--Part II: in vivo flux estimation of lysine-producing Corynebacterium glutamicum.

A novel method for metabolic flux studies of central metabolism which is based on respirometric (13)C flux analysis, i.e., parallel (13)C tracer studies with online CO(2) labeling measurements is applied to flux quantification of a lysine-producing mutant of Corynebacterium glutamicum. For this purpose, 3 respirometric (13)C labeling experiments with [1-(13)C(1)], [6-(13)C(1)] and [1,6-(13)C(2)] glucose were carried out in parallel. All fluxes comprising the reactions of glycolysis, of TCA cycle, of C3- and C4-metabolite interconversion and of lysine biosynthesis as well as the net reactions in the pentose phosphate pathway could be quantified solely using experimental data obtained from CO(2) labeling and extracellular rate measurements. At key branch points, 68+/-5% of glucose 6-phosphate were observed to be metabolized into pentose phosphate pathway and 48+/-1% of pyruvate into TCA cycle via pyruvate dehydrogenase. The results showed a good agreement with the previous studies using (13)C tracer cultivation and GC/MS analysis of proteinogenic amino acids. Also, respiratory quotient calculated from flux estimates using redox balance showed a high accordance with the value determined directly from the measured specific rates of O(2) consumption and CO(2) production. The results strongly support that the respirometric (13)C metabolic flux analysis is suited as an alternative to the conventional methods to study functional and regulatory activities of cells. The developed method is applicable to study growing or non-growing cells, primary and secondary metabolism and immobilized cells. Due to the non-accumulating nature of CO(2) labeling and instantaneous nature of the resulting fluxes, the method can also be used for dynamic profiling of metabolic activities. Therefore, it is complementary to conventional methods for metabolic flux analysis.

Bioreactors↗

PubMed2005

Theoretical aspects of 13C metabolic flux analysis with sole quantification of carbon dioxide labeling.

The potential of using sole respirometric CO2 labeling measurement for 13C metabolic flux analysis was investigated by metabolic simulations. For this purpose a model was created, considering all CO2 forming and consuming reactions in the central catabolic and anabolic pathways. To facilitate the interpretation of the simulation results, the underlying metabolic network was parameterized by physiologically meaningful flux parameters such as flux partitioning ratios at metabolic branch points and reaction reversibilities. For real case flux scenarios of the industrial amino acid producer Corynebacterium glutamicum and different commercially available (13)C-labeled tracer substrates, observability and output sensitivity towards key flux parameters was investigated. Metabolic net fluxes in the central metabolism, involving, e.g. glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, anaplerotic carboxylation, and glyoxylate pathway were found to be determinable by the respirometric approach using a combination of [1-13C] and [6-13C] glucose in two parallel studies. The reversibilities of bidirectional reactions influence the isotopic labeling of CO2 only to a negligible degree. On one hand, they therefore cannot be determined. On the other hand, their precise values are not required for the quantification of net fluxes. Computer-aided optimal experimental design was carried out to predict the quality of the information from the respirometric tracer experiments and identify suitable tracer substrates. A combination of [1-13C] and [6-13C] glucose in two parallel studies was found to yield a similar quality of information as compared to an approach with mass spectrometric labeling analysis of secreted products. The quality of information can be further increased by additional studies with [1,2-13C2] or [1,6-13C2] glucose. Respirometric tracer studies with sole labeling analysis of CO2 are therefore promising for 13C metabolic flux analysis.

Carbon Dioxide↗

PubMed2004

Metabolic network simulation using logical loop algorithm and Jacobian matrix.

A novel method to accomplish efficient numerical simulation of metabolic networks for flux analysis was developed. The only inputs required are the set of stoichiometric balances and the atom mapping matrices of all components of the reaction network. The latter are used to automatically calculate isotopomer mapping matrices. Using the symbolic toolbox of MATLAB the analytical solution of the stoichiometric balance equation system, isotopomer balances and the analytical Jacobian matrix of the total set of stoichiometric and isotopomer balances are created automatically. The number of variables in the isotopomer distribution equation system is significantly reduced applying modified isotopomer mapping matrices. These allow lumping of several consecutive isotopomer reactions into a single one. The solution of the complete system of equations is improved by implementing an iterative logical loop algorithm and using the analytical Jacobian matrix. This new method provided quick and robust convergence to the root of such equation systems in all cases tested. The method was applied to a network of lysine producing Corynebacterium glutamicum. The resulting equation system with the dimension of 546 x 546 was directly derived from 12 isotopomer balance equations. The results obtained yielded identical labeling patterns for metabolites as compared to the relaxation method.

Algorithms↗

PubMed2003

Dynamic calibration and dissolved gas analysis using membrane inlet mass spectrometry for the quantification of cell respiration.

A membrane inlet mass spectrometer connected to a miniaturized reactor was applied for dynamic dissolved gas analysis. Cell samples were taken from 7 mL shake flask cultures of Corynebacterium glutamicum ATCC 13032, and transferred to the 12 mL miniaturized reactor. There, oxygen uptake and carbon dioxide and its mass isotopomer production rates were determined using a new experimental procedure and applying nonlinear model equations. A novel dynamic method for the calibration of the membrane inlet mass spectrometer using first-order dynamics was developed. To derive total dissolved concentration of all carbon dioxide species (C(T)) from dissolved carbon dioxide concentration ([CO(2)](aq)), the ratio of C(T) to [CO(2)](aq) was determined by nonlinear parameter estimation, whereas the mass transfer coefficient of CO(2) was determined by the Wilke-Chang correlation. Subsequently, the suitability of the model equations for respiration measurements was examined using residual analysis and the Jarque-Bera hypothesis test. The resulting residuals were found to be random with normal distribution, which proved the adequacy of the application of the model for cell respiration analysis. Hence, dynamic changes in respiration activities could be accurately analyzed using membrane inlet mass spectrometry with the novel calibration method.

Algorithms↗