Purpose of the Experiment Fluxes in central carbon metabolism of a genetically engineered,...

Purpose of the Experiment

Fluxes in central carbon metabolism of a genetically engineered, riboflavin-producing Bacillus subtilis strain were investigated in glucose-limited chemostat cultures at low (0.11 h -1 ) and high (0.44 h -1 ) dilution rates.

Introduction

A metabolic network could be defined as a set of enzymatic reactions that biochemically process metabolites within the cell and transport processes that convert extra-cellular metabolites to intracellular metabolites and vice versa.

E. Coli Metabolic Network

The E.Coli metabolic network.

Ultimate Goal

Development of complete models simulating every aspect of cellular metabolism Absence of kinetic information on some of the reactions and the dynamics and regulation of metabolic reactions is the major hindrance.Many researchers have tried various approaches towards the ultimate goal with varying degrees of success. Some of them are :

Simulation Models

Biochemical systems theory (Savageau, 1969a, 1969b, 1970),

Metabolic control analysis (Kacser and Burns, 1973),

Temporal decomposition (Palsson et al., 1987). Pathway analysis (Clark, 1988), Flux balance analysis (Varma and Palsson,

1994b), Cybernetic modeling (Ramakrishna et al., 1996;),

Flux Balance Analysis

Flux balance analysis has gained a greater degree of acceptance with researchers.

It describes the metabolic physiology in a quantitative manner

It is based on the fundamental law of mass conservation. It is based on the fundamental physicochemical

constraints on metabolic networks. It only requires information about the stoichiometry of

metabolic pathways and on metabolic demands.  

Flux Balance Analysis (contd.)

Metabolic Flux Analysis

Metabolic flux analysis(MFA) is similar to flux balance analysis (FBA) but instead of the optimization techniques used in FBA experimentally measured/estimated fluxes are used to reduce the underdetermined nature of a metabolic system.

Modeling through MFA

• A model was developed through metabolic flux analysis to comprehensively describe the central metabolism of Bacillus subtilis

• The model was based on previously developed exhaustive biochemical reactions models developed by Dauner and Sauer

Problems with MFA

A typical problem of metabolic flux analysis using such metabolite balances are underdetermined equation systems.

These are caused by alternative pathways and redundant reactions in central metabolism, an inherent feature of biological systems.

MFA Process

Metabolic net fluxes are determined from an initial, randomly chosen set of parameters, and the corresponding isotopomer balances are calculated.

From this isotopomer distribution, synthetic NMR signals are simulated and compared to the experimentally determined 13C-13C scalar coupling fine structures in cellular amino acids.

Flow chart of flux estimation procedure

M in (X ^ 2 ) - so lu tion fou n d

N ew E s tim ate F lu x S o lu tion

C a lcu la te X ^ 2 c rite rion

S im u la te S yn th e tic N M R S ig n a ls

S o lve iso top om er b a lan ces

C a lcu la te F lu xes

System Trying to Model

Model Estimation

Net and exchange fluxes were estimated on the basis of the physiological data from Dauner and Sauer

Initial Basis Fluxes

D=0.11 h-1 D=0.44 h-1Units

cell dry weight: 1.54 ±0.07 1.73 ±0.09 (g L-1)

q(riboflavin): 0.02 ±0.00 0.03 ±0.00 (mmol g-1 h-1)

q(glucose): 1.98 ±0.13 7.05 ±0.40 (mmol g-1 h-1)

q(acetate): 0.01 ±0.01 0.09 ±0.10 (mmol g-1 h-1)

q(citrate): 0.03 ±0.01 0.06 ±0.02 (mmol g-1 h-1)

q(protein): 2.51 ±0.38 10.06 ±1.53 (mg g-1 h-1)

q(cell wall): 10.85 ±0.06 11.77 ±1.46 (mg g-1 h-1)

q(PEP): 0.01 ±0.00 0.01 ±0.00 (mmol g-1 h-1)

q(pyruvate): 0.01 ±0.00 0.01 ±0.00 (mmol g-1 h-1)

q(formate): 0.03 ±0.02 0.04 ±0.05 (mmol g-1 h-1)

q(diacetyl): 0.09 ±0.03 0.17 ±0.06 (mmol g-1 h-1)

q(succinate): 0.00 ±0.01 0.01 ±0.01 (mmol g-1 h-1)

q(CO2): 6.69 ±0.44 19.75 ±0.99 (mmol g-1 h-1)

q(O2): 6.71 ±0.28 19.71 ±0.90 (mmol g-1 h-1)Note. Data taken from (Dauner and Sauer, 2001).

Appendix A. Major extracellular fluxes used for metabolic flux analysis.

Determined Exchange Fluxes

Exchange reaction

D=0.11 h-1 D=0.44 h-1

G6P F6P 0.21 4.08P5P + E4P F6P + T3P 7.82 02 P5P S7P + T3P 0 4.39S7P + T3P E4P + F6P 31.28 1.24T3P PGA 0.76 9.38PGA PEP 1.03 0.59FUM MAL 1.24 1.37MAL OAA 3.48 2.5OAA PEP 0.21 1.45PGA SER 1.98 0SER GLY + C1 4.98 0.25

Fraction

Table II. Determined exchange fluxes.

References

Metabolic Flux Analysis with a Comprehensive Isotopomer Model in Bacillus subtillis. Michael Dauner, James E. Bailey, Uwe Sauer.Institute of Biotechnology, ETH Zurich, CH 8093 Zurich, Switzerland.

References

Robustness Analysis of the Escherichia coli Metabolic Network. Jeremy S. Edwards and Bernhard O. Palsson. 927 Biotechnol. Prog. 2000, 16, 92-939

Combining Pathway Analysis with Flux Balance Analysis for the Comprehensive Study of Metabolic Systems. Christopher H. Schilling, Jeremy S. Edwards, David Letscher, Bernhard Ø. Palsson