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Glycerol metabolic conversion to succinic acid using Actinobacillus succinogenes. a metabolic network-based analysis

Binns, M; Vlysidis, A; Webb, C; Theodoropoulos, C; de Atauri, P; Cascante, M

In: Computer Aided Chemical Engineering. 2011. p. 1421-1425.

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Abstract

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. ?? 2011 Elsevier B.V.

Bibliographic metadata

Content type:
Type of book contribution:
Publication date:
Contribution start page:
1421
Contribution end page:
1425
Contribution pagination:
1421-1425
Contribution total pages:
5
Abstract:
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. ?? 2011 Elsevier B.V.
Digtial Object Identifier:
10.1016/B978-0-444-54298-4.50063-5
Related website(s):
  • Related website http://www.scopus.com/inward/record.url?eid=2-s2.0-79958807410&partnerID=40&md5=42b12e0b8f1d933bffb933d8e05679d2
General notes:
  • cited By (since 1996) 0

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:142886
Created by:
Webb, Colin
Created:
28th December, 2011, 15:43:34
Last modified by:
Webb, Colin
Last modified:
28th December, 2011, 16:42:47

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