Metabolic Model Describing Growth of Substrate Uptake By Idelfonso Arrieta Anant Kumar Upadhyayula

Objectives Explain the Growth of substrate uptake Simulate a range of metabolic responses obtained from Trigonopsis variabilis by simple biochemical reactions produced in a cell 1 of 2

Objectives Understand the behavior of yeast under different growth conditions Simulate the growth of any yeast under discontinuous conditions 1 of 2

Introduction The yeast Trigonopsis variabilis has been reported to be a potent producer of this enzyme. Aerobic metabolism of all yeast is determined by relative sizes of the sugar transport rate into the cell and the Pyruvate transport into the mitochondrion.

Introduction Fermentation models are normally divided into two classes 1. Unstructured models where the biomass is described by one variable 2. Structured models where intracellular metabolic pathways are considered.

Sugar Transport S Generic Yeast cell with Main Metabolic Pathways S’ RI Growth RI’ Cell membrane Mitochondrial membrane Glycolisis Respiratory Intermediate systems TCA Cycle

Description of the model structure The model describes seven major steps in yeast metabolism:  Sugar transport across the plasma membrane.  Sugar conversion to growth macromolecules.  Glycolytic conversion of sugar to pyruvate  Pyruvate conversion to growth macromolecules.

Description of the model structure  Pyruvate conversion to ethanol product  Pyruvate transport across the mithocondrial membrane.  Respiration of pyruvate to carbon dioxide and water.

Assumptions Cell matter and culture medium form a distributed system The limiting substrate is both the carbon and energy source. The composition and metabolic activity assumed constant such that biomass may be described by a single variable X. The redox state of the cell is assumed to be the same as that of the substrate. ATP generation is only a result of fermentation and respiration.

Assumptions All growth yields (g biomass/g substrate) are constant since Y ATP (g biomass/mol ATP), the PO ratio (mol ATP/atom oxygen), and growth stoichiometry. The carbon content of the intermediates for biosynthesis of cell material is provided from both sugar and pyruvate.

Assumptions Saturation of the respiratory capacity is the only controlling factor in fermentation and respiration. ATP is a product of energy-producing reactions and is only a hypothetical value in this model.

Biochemical Reactions Sequence

Rate Equations 1. Balance to S (Glucose in the culture medium) It is consumed through the cellular membrane Maximum Substrate Uptake rate mmol S

Rate Equations 2.Balance to S’(Glucose inside the cell) It is consumed by the transportation of S through the cellular Membrane Kinetic constant in the Growth reactions Kinetic constant of the glycolysis process

Rate Equations 3.Balance to RI (Pyruvate) It is generated through the Glycolysis of S’ and it is consumed toward the interior of the mitochondrion to form the new cell The experimental work with T. variabilis has shown a negligible quantity of Ethanol produced in aerobic growth conditions

Rate Equations 4. Balance to RI ’ (pyruvate inside mithocondrion) It is generated by the transport of RI toward the mithocondrion. Maximum pyruvate transport rate Saturation constant for pyruvate transport across the mithocondrial membrane Oxidation constant

Rate Equations 5. Balance to x New cells are generated in the growth reaction Kinetic constant in the growth reaction.

Rate Equations 6. Balance to oxygen inside the cell It is consumed by the cells during the respiration Maximum specific oxygen uptake rate. Oxidation constant.

Rate Equations 7. Balance to ATP It is generated during the glycolysis and respiration process.It is consumed in the generation reaction of new cells Kinetic constant of the glycolysis process Oxidation constant. Kinetic constant in the growth reaction.

Computation Procedure

COMPUTATION PROCEDURES

Computation procedure The values of the parameters included in are calculated with the following numerical methods: Runge-Kutta (fourth order). Comparation of theoretical data and experimental data and the best values calculated by least squares method.

Results Since the model discussed in this paper can be used to simulate not only an exceptional growth but also a substrate starvation process, so it cave be sued to simulate the growth of any yeast under discontinuous conditions. The maximum specific substrate uptake rate for the rich medium is considerably greater to that of the salts medium. The observed specific oxygen uptake rate k3 does not reach a maximum for higher concentration of of oxygen because the growth is performed under limiting conditions of oxygen(0.5%).

Results The cellular yield concerning the glucose reaches a higher value in the rich medium compared to with the salt medium, since in using the rich medium a large part of the carbonated chains that constitute the cellular matter are formed from the amino acids contained in the medium but while using the salt medium these chains should be synthesized entirely from the main substrate. The energetic yield is much higher in the rich medium with respect to the salts medium since the cellular material synthesis requires a smaller consumption because the rich medium contains several amino acids basic for protein synthesis.

conclusions The chemically structured model is capable of expalining the cellular growth and consumption of sunstrate uptake in the yeast The model may simulate a range of metabolic responses obtained from the T. Variabilis growth in discontinuous culture and can serve to understand the behavior of the yeast under different growth conditions.

Reference Barford, J. P. A general model for aerobic yeast growth. Biotechnol. Bioeng.1990, 35, Montes, F. J., Moreno, J.A., Catalan, J., and Galan, M.A. Oxygen kinetic and metabolic parameters for the yeast Trigonopsis Variabilis. J. Chem. Tech. Biotechnol.1997,68, Montes F.J., Catalan J., and Galan M.A. Barford, J. P. A metabolic model describing growth and substrate uptake of Trigonopsis Variabilis. Enzyme and Microbial Technol. 1998, 22,