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Prospecting hydrogen production of Escherichia coli by metabolic network modeling

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Prospecting hydrogen production of Escherichia coli by metabolic network modeling. / Seppälä, Jenni J.; Larjo, Antti; Aho, Tommi; Yli-Harja, Olli; Karp, Matti T.; Santala, Ville.

In: International Journal of Hydrogen Energy, Vol. 38, No. 27, 10.09.2013, p. 11780-11789.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Seppälä, JJ, Larjo, A, Aho, T, Yli-Harja, O, Karp, MT & Santala, V 2013, 'Prospecting hydrogen production of Escherichia coli by metabolic network modeling', International Journal of Hydrogen Energy, vol. 38, no. 27, pp. 11780-11789. https://doi.org/10.1016/j.ijhydene.2013.07.002

APA

Seppälä, J. J., Larjo, A., Aho, T., Yli-Harja, O., Karp, M. T., & Santala, V. (2013). Prospecting hydrogen production of Escherichia coli by metabolic network modeling. International Journal of Hydrogen Energy, 38(27), 11780-11789. https://doi.org/10.1016/j.ijhydene.2013.07.002

Vancouver

Seppälä JJ, Larjo A, Aho T, Yli-Harja O, Karp MT, Santala V. Prospecting hydrogen production of Escherichia coli by metabolic network modeling. International Journal of Hydrogen Energy. 2013 Sep 10;38(27):11780-11789. https://doi.org/10.1016/j.ijhydene.2013.07.002

Author

Seppälä, Jenni J. ; Larjo, Antti ; Aho, Tommi ; Yli-Harja, Olli ; Karp, Matti T. ; Santala, Ville. / Prospecting hydrogen production of Escherichia coli by metabolic network modeling. In: International Journal of Hydrogen Energy. 2013 ; Vol. 38, No. 27. pp. 11780-11789.

Bibtex - Download

@article{aff8b574034f44078b1c59d614326dc5,
title = "Prospecting hydrogen production of Escherichia coli by metabolic network modeling",
abstract = "Genome-scale model was applied to analyze the anaerobic metabolism of Escherichia coli. Three different methods were used to find deletions affecting fermentative hydrogen production: flux balance analysis (FBA), algorithm for blocking competing pathways (ABCP), and manual selection. Based on these methods, 81 E. coli mutants possessing one gene deletion were selected and cultivated in batch experiments. Experimental results of H2 and biomass production were compared against the results of FBA. Several gene deletions enhancing H2 production were found. Correctness of gene essentiality predictions of FBA for the selected genes was 78{\%} and 77{\%} in glucose and galactose media, respectively. 33{\%} of the mutations that were predicted by FBA to increase H2 production had a positive effect in experiments. Batch cultivation is a simple and straightforward experimental way to screen improvements in H2 production. However, the ability of FBA to predict the H2 production rate cannot be evaluated by batch experiments. Metabolic network models provide a method for gaining broader understanding of the complicated metabolic system of a cell and can aid in prospecting suitable gene deletions for enhancing H2 production. {\circledC} 2013, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights.",
keywords = "Escherichia coli, Flux balance analysis, Hydrogen production, Metabolic engineering, Metabolic network modeling",
author = "Sepp{\"a}l{\"a}, {Jenni J.} and Antti Larjo and Tommi Aho and Olli Yli-Harja and Karp, {Matti T.} and Ville Santala",
note = "Contribution: organisation=keb,FACT1=0.5<br/>Contribution: organisation=sgn,FACT2=0.5<br/>Portfolio EDEND: 2013-09-29<br/>Publisher name: Elsevier Ltd",
year = "2013",
month = "9",
day = "10",
doi = "10.1016/j.ijhydene.2013.07.002",
language = "English",
volume = "38",
pages = "11780--11789",
journal = "International Journal of Hydrogen Energy",
issn = "0360-3199",
publisher = "Elsevier",
number = "27",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Prospecting hydrogen production of Escherichia coli by metabolic network modeling

AU - Seppälä, Jenni J.

AU - Larjo, Antti

AU - Aho, Tommi

AU - Yli-Harja, Olli

AU - Karp, Matti T.

AU - Santala, Ville

N1 - Contribution: organisation=keb,FACT1=0.5<br/>Contribution: organisation=sgn,FACT2=0.5<br/>Portfolio EDEND: 2013-09-29<br/>Publisher name: Elsevier Ltd

PY - 2013/9/10

Y1 - 2013/9/10

N2 - Genome-scale model was applied to analyze the anaerobic metabolism of Escherichia coli. Three different methods were used to find deletions affecting fermentative hydrogen production: flux balance analysis (FBA), algorithm for blocking competing pathways (ABCP), and manual selection. Based on these methods, 81 E. coli mutants possessing one gene deletion were selected and cultivated in batch experiments. Experimental results of H2 and biomass production were compared against the results of FBA. Several gene deletions enhancing H2 production were found. Correctness of gene essentiality predictions of FBA for the selected genes was 78% and 77% in glucose and galactose media, respectively. 33% of the mutations that were predicted by FBA to increase H2 production had a positive effect in experiments. Batch cultivation is a simple and straightforward experimental way to screen improvements in H2 production. However, the ability of FBA to predict the H2 production rate cannot be evaluated by batch experiments. Metabolic network models provide a method for gaining broader understanding of the complicated metabolic system of a cell and can aid in prospecting suitable gene deletions for enhancing H2 production. © 2013, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights.

AB - Genome-scale model was applied to analyze the anaerobic metabolism of Escherichia coli. Three different methods were used to find deletions affecting fermentative hydrogen production: flux balance analysis (FBA), algorithm for blocking competing pathways (ABCP), and manual selection. Based on these methods, 81 E. coli mutants possessing one gene deletion were selected and cultivated in batch experiments. Experimental results of H2 and biomass production were compared against the results of FBA. Several gene deletions enhancing H2 production were found. Correctness of gene essentiality predictions of FBA for the selected genes was 78% and 77% in glucose and galactose media, respectively. 33% of the mutations that were predicted by FBA to increase H2 production had a positive effect in experiments. Batch cultivation is a simple and straightforward experimental way to screen improvements in H2 production. However, the ability of FBA to predict the H2 production rate cannot be evaluated by batch experiments. Metabolic network models provide a method for gaining broader understanding of the complicated metabolic system of a cell and can aid in prospecting suitable gene deletions for enhancing H2 production. © 2013, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights.

KW - Escherichia coli

KW - Flux balance analysis

KW - Hydrogen production

KW - Metabolic engineering

KW - Metabolic network modeling

UR - http://www.scopus.com/inward/record.url?scp=84882724445&partnerID=8YFLogxK

U2 - 10.1016/j.ijhydene.2013.07.002

DO - 10.1016/j.ijhydene.2013.07.002

M3 - Article

VL - 38

SP - 11780

EP - 11789

JO - International Journal of Hydrogen Energy

JF - International Journal of Hydrogen Energy

SN - 0360-3199

IS - 27

ER -