Shintaro Iwatani

Metabolic flux analysis in biotechnology processes

Metabolic flux analysis (MFA) has become a fundamental tool of metabolic engineering to elucidate the metabolic state of the cell and has been applied to various biotechnological processes. In recent years, considerable technical advances have been made. Developments of analytical instruments allow us to determine 13C labeling distribution of intracellular metabolites with high accuracy and sensitivity. Moreover, kinetic information of intracellular label distribution during isotopic instationary enables us to calculate metabolic fluxes with shortened experimental time and decreased amount of labeled substrate. The 13C MFA may be one of the most promising approaches for the target estimation to improve strain performances and production processes.

Dynamic modeling of Escherichia coli metabolic and regulatory systems for amino-acid production.

Our aim is to construct a practical dynamic-simulation system that can model the metabolic and regulatory processes involved in the production of primary metabolites, such as amino acids. We have simulated the production of glutamate by transient batch-cultivation using a model of Escherichia coli central metabolism. Kinetic data were used to produce both the metabolic parts of the model, including the phosphotransferase system, glycolysis, the pentose-phosphate pathway, the tricarboxylic acid cycle, the glyoxylate shunt, and the anaplerotic pathways, and the regulatory parts of the model, including regulation by transcription factors, cyclic AMP receptor protein (CRP), making large colonies protein (Mlc), catabolite repressor/activator (Cra), pyruvate dehydrogenase complex repressor (PdhR), and acetate operon repressor (IclR). RNA polymerase and ribosome concentrations were expressed as a function of the specific growth rate, mu, corresponding to the changes in the growth rate during batch cultivation. Parameter fitting was performed using both extracellular concentration measurements and in vivo enzyme activities determined by (13)C flux analysis. By manual adjustment of the parameters, we simulated the batch fermentation of glucose or fructose by a wild-type strain (MG1655) and a glutamate-producing strain (MG1655 Delta sucA). The differences caused by the carbon source, and by wild-type and glutamate-producing strains, were clearly shown by the simulation. A sensitivity analysis revealed the factors that could be altered to improve the production process. Furthermore, an in silico deletion experiments could suggested the existence of uncharacterized regulation. We concluded that our simulation model could function as a new tool for the rational improvement and design of metabolic and regulatory networks.

OpenFLUX2: 13 C-MFA modeling software package adjusted for the comprehensive analysis of single and parallel labeling experiments

BackgroundSteady-state 13C-based metabolic flux analysis (13C-MFA) is the most powerful method available for the quantification of intracellular fluxes. These analyses include concertedly linked experimental and computational stages: (i) assuming the metabolic model and optimizing the experimental design; (ii) feeding the investigated organism using a chosen 13C-labeled substrate (tracer); (iii) measuring the extracellular effluxes and detecting the 13C-patterns of intracellular metabolites; and (iv) computing flux parameters that minimize the differences between observed and simulated measurements, followed by evaluating flux statistics. In its early stages, 13C-MFA was performed on the basis of data obtained in a single labeling experiment (SLE) followed by exploiting the developed high-performance computational software. Recently, the advantages of parallel labeling experiments (PLEs), where several LEs are conducted under the conditions differing only by the tracer(s) choice, were demonstrated, particularly with regard to improving flux precision due to the synergy of complementary information. The availability of an open-source software adjusted for PLE-based 13C-MFA is an important factor for PLE implementation.ResultsThe open-source software OpenFLUX, initially developed for the analysis of SLEs, was extended for the computation of PLE data. Using the OpenFLUX2, in silico simulation confirmed that flux precision is improved when 13C-MFA is implemented by fitting PLE data to the common model compared with SLE-based analysis. Efficient flux resolution could be achieved in the PLE-mediated analysis when the choice of tracer was based on an experimental design computed to minimize the flux variances from different parts of the metabolic network. The analysis provided by OpenFLUX2 mainly includes (i) the optimization of the experimental design, (ii) the computation of the flux parameters from LEs data, (iii) goodness-of-fit testing of the model’s adequacy, (iv) drawing conclusions concerning the identifiability of fluxes and construction of a contribution matrix reflecting the relative contribution of the measurement variances to the flux variances, and (v) precise determination of flux confidence intervals using a fine-tunable and convergence-controlled Monte Carlo-based method.ConclusionsThe developed open-source OpenFLUX2 provides a friendly software environment that facilitates beginners and existing OpenFLUX users to implement LEs for steady-state 13C-MFA including experimental design, quantitative evaluation of flux parameters and statistics.

Mechanical damage to Escherichia coli cells in a model of amino-acid crystal fermentation

We investigated the mechanical damage to the Escherichia coli cell caused by polyvinyl chloride particles as a model of amino-acid crystal fermentation. Our results indicated that the glucose-consumption rate and the intracellular ATP concentration temporarily increased by the mechanical damage, and decreased after considerable damage had occurred on cell membrane.