TY - JOUR
T1 - Glycerol metabolic conversion to succinic acid using Actinobacillus succinogenes. a metabolic network-based analysis
AU - Binns, Michael
AU - Vlysidis, Anestis
AU - Webb, Colin
AU - Theodoropoulos, Constantinos
AU - de Atauri, Pedro
AU - Cascante, Marta
PY - 2011
Y1 - 2011
N2 - Glycerol is produced in large quantities by the growing biodiesel industry (approximately 100kg per ton of biodiesel). Hence there is a growing demand for processes converting glycerol into useful valuable chemicals. Here we consider the conversion of glycerol into the commodity chemical succinic acid (SA) throughfermentation with the organism Actinobacillus succinogenes. Metabolic control analysis is applied, using knowledge of the structure, the fluxes generated through flux balance analysis and elasticities, which are modelled using random sampling to account for their uncertainty. The results of this analysis give ranges of control coefficients, summarised with a novel parameter we have called the control bias. We have found that the step having the greatest positive effect on SA production is the glycerol uptake and that the enzymes from malate to SA, and from pyruvate to malate are important steps with positive control. A less obvious step identified is the uptake of CO2. Steps having negative control are the ones leading to byproducts such as formic acid.
AB - Glycerol is produced in large quantities by the growing biodiesel industry (approximately 100kg per ton of biodiesel). Hence there is a growing demand for processes converting glycerol into useful valuable chemicals. Here we consider the conversion of glycerol into the commodity chemical succinic acid (SA) throughfermentation with the organism Actinobacillus succinogenes. Metabolic control analysis is applied, using knowledge of the structure, the fluxes generated through flux balance analysis and elasticities, which are modelled using random sampling to account for their uncertainty. The results of this analysis give ranges of control coefficients, summarised with a novel parameter we have called the control bias. We have found that the step having the greatest positive effect on SA production is the glycerol uptake and that the enzymes from malate to SA, and from pyruvate to malate are important steps with positive control. A less obvious step identified is the uptake of CO2. Steps having negative control are the ones leading to byproducts such as formic acid.
KW - Flux analysis
KW - Metabolic control analysis
KW - Thermodynamic constraints
UR - http://www.scopus.com/inward/record.url?scp=79958807410&partnerID=8YFLogxK
U2 - 10.1016/B978-0-444-54298-4.50063-5
DO - 10.1016/B978-0-444-54298-4.50063-5
M3 - Article
AN - SCOPUS:79958807410
SN - 1570-7946
VL - 29
SP - 1421
EP - 1425
JO - Computer Aided Chemical Engineering
JF - Computer Aided Chemical Engineering
ER -