Metabolic capabilities of Actinobacillus succinogenes for succinic acid production
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Journal of Chemical Engineering |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322014000400004 |
Resumo: | Attention has been focused on microbial succinic acid production as an alternative for conventional chemical synthesis that is associated with environmental pollution. A metabolic model for Actinobacillus succinogenes 130Z was developed with a mixture of glucose and xylose as substrate. The metabolic fluxes during succinicate production were determined using flux balance analysis by linear programming optimization in the MATLAB environment. Different glucose ratios (0.3, 0.4 and 0.7 mol.mol-1substrate) were used as model assumptions to calculate optimal fluxes, maximum growth and succinate production. The model revealed that higher growth rates and product yields were correlated with higher glucose content in the substrate mixture. When glucose constituted 0.5 mol.mol-1 substrate, a lower succinate yield (0.64 mol.mol-1 substrate) was obtained, compared to 0.73 mol.mol-1 substrate when glucose was used individually. Deletion of different unessential reactions in the model showed that a knockout of the acetate formation pathway would increase the succinate yield by 21% when glucose and xylose were used in equal molar ratios. |
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Brazilian Journal of Chemical Engineering |
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Metabolic capabilities of Actinobacillus succinogenes for succinic acid productionSuccinic AcidActinobacillus succinogenesXyloseMetabolic ModelAttention has been focused on microbial succinic acid production as an alternative for conventional chemical synthesis that is associated with environmental pollution. A metabolic model for Actinobacillus succinogenes 130Z was developed with a mixture of glucose and xylose as substrate. The metabolic fluxes during succinicate production were determined using flux balance analysis by linear programming optimization in the MATLAB environment. Different glucose ratios (0.3, 0.4 and 0.7 mol.mol-1substrate) were used as model assumptions to calculate optimal fluxes, maximum growth and succinate production. The model revealed that higher growth rates and product yields were correlated with higher glucose content in the substrate mixture. When glucose constituted 0.5 mol.mol-1 substrate, a lower succinate yield (0.64 mol.mol-1 substrate) was obtained, compared to 0.73 mol.mol-1 substrate when glucose was used individually. Deletion of different unessential reactions in the model showed that a knockout of the acetate formation pathway would increase the succinate yield by 21% when glucose and xylose were used in equal molar ratios.Brazilian Society of Chemical Engineering2014-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322014000400004Brazilian Journal of Chemical Engineering v.31 n.4 2014reponame:Brazilian Journal of Chemical Engineeringinstname:Associação Brasileira de Engenharia Química (ABEQ)instacron:ABEQ10.1590/0104-6632.20140314s00002997info:eu-repo/semantics/openAccessRafieenia,R.eng2014-11-14T00:00:00Zoai:scielo:S0104-66322014000400004Revistahttps://www.scielo.br/j/bjce/https://old.scielo.br/oai/scielo-oai.phprgiudici@usp.br||rgiudici@usp.br1678-43830104-6632opendoar:2014-11-14T00:00Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ)false |
dc.title.none.fl_str_mv |
Metabolic capabilities of Actinobacillus succinogenes for succinic acid production |
title |
Metabolic capabilities of Actinobacillus succinogenes for succinic acid production |
spellingShingle |
Metabolic capabilities of Actinobacillus succinogenes for succinic acid production Rafieenia,R. Succinic Acid Actinobacillus succinogenes Xylose Metabolic Model |
title_short |
Metabolic capabilities of Actinobacillus succinogenes for succinic acid production |
title_full |
Metabolic capabilities of Actinobacillus succinogenes for succinic acid production |
title_fullStr |
Metabolic capabilities of Actinobacillus succinogenes for succinic acid production |
title_full_unstemmed |
Metabolic capabilities of Actinobacillus succinogenes for succinic acid production |
title_sort |
Metabolic capabilities of Actinobacillus succinogenes for succinic acid production |
author |
Rafieenia,R. |
author_facet |
Rafieenia,R. |
author_role |
author |
dc.contributor.author.fl_str_mv |
Rafieenia,R. |
dc.subject.por.fl_str_mv |
Succinic Acid Actinobacillus succinogenes Xylose Metabolic Model |
topic |
Succinic Acid Actinobacillus succinogenes Xylose Metabolic Model |
description |
Attention has been focused on microbial succinic acid production as an alternative for conventional chemical synthesis that is associated with environmental pollution. A metabolic model for Actinobacillus succinogenes 130Z was developed with a mixture of glucose and xylose as substrate. The metabolic fluxes during succinicate production were determined using flux balance analysis by linear programming optimization in the MATLAB environment. Different glucose ratios (0.3, 0.4 and 0.7 mol.mol-1substrate) were used as model assumptions to calculate optimal fluxes, maximum growth and succinate production. The model revealed that higher growth rates and product yields were correlated with higher glucose content in the substrate mixture. When glucose constituted 0.5 mol.mol-1 substrate, a lower succinate yield (0.64 mol.mol-1 substrate) was obtained, compared to 0.73 mol.mol-1 substrate when glucose was used individually. Deletion of different unessential reactions in the model showed that a knockout of the acetate formation pathway would increase the succinate yield by 21% when glucose and xylose were used in equal molar ratios. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-12-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322014000400004 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66322014000400004 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0104-6632.20140314s00002997 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Brazilian Society of Chemical Engineering |
publisher.none.fl_str_mv |
Brazilian Society of Chemical Engineering |
dc.source.none.fl_str_mv |
Brazilian Journal of Chemical Engineering v.31 n.4 2014 reponame:Brazilian Journal of Chemical Engineering instname:Associação Brasileira de Engenharia Química (ABEQ) instacron:ABEQ |
instname_str |
Associação Brasileira de Engenharia Química (ABEQ) |
instacron_str |
ABEQ |
institution |
ABEQ |
reponame_str |
Brazilian Journal of Chemical Engineering |
collection |
Brazilian Journal of Chemical Engineering |
repository.name.fl_str_mv |
Brazilian Journal of Chemical Engineering - Associação Brasileira de Engenharia Química (ABEQ) |
repository.mail.fl_str_mv |
rgiudici@usp.br||rgiudici@usp.br |
_version_ |
1754213174608920576 |