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NIHBA: a network interdiction approach for metabolic engineering design

MOTIVATION: Flux balance analysis (FBA) based bilevel optimization has been a great success in redesigning metabolic networks for biochemical overproduction. To date, many computational approaches have been developed to solve the resulting bilevel optimization problems. However, most of them are of...

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Autores principales: Jiang, Shouyong, Wang, Yong, Kaiser, Marcus, Krasnogor, Natalio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267835/
https://www.ncbi.nlm.nih.gov/pubmed/32167529
http://dx.doi.org/10.1093/bioinformatics/btaa163
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author Jiang, Shouyong
Wang, Yong
Kaiser, Marcus
Krasnogor, Natalio
author_facet Jiang, Shouyong
Wang, Yong
Kaiser, Marcus
Krasnogor, Natalio
author_sort Jiang, Shouyong
collection PubMed
description MOTIVATION: Flux balance analysis (FBA) based bilevel optimization has been a great success in redesigning metabolic networks for biochemical overproduction. To date, many computational approaches have been developed to solve the resulting bilevel optimization problems. However, most of them are of limited use due to biased optimality principle, poor scalability with the size of metabolic networks, potential numeric issues or low quantity of design solutions in a single run. RESULTS: Here, we have employed a network interdiction model free of growth optimality assumptions, a special case of bilevel optimization, for computational strain design and have developed a hybrid Benders algorithm (HBA) that deals with complicating binary variables in the model, thereby achieving high efficiency without numeric issues in search of best design strategies. More importantly, HBA can list solutions that meet users’ production requirements during the search, making it possible to obtain numerous design strategies at a small runtime overhead (typically ∼1 h, e.g. studied in this article). AVAILABILITY AND IMPLEMENTATION: Source code implemented in the MATALAB Cobratoolbox is freely available at https://github.com/chang88ye/NIHBA. CONTACT: math4neu@gmail.com or natalio.krasnogor@ncl.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-72678352020-06-09 NIHBA: a network interdiction approach for metabolic engineering design Jiang, Shouyong Wang, Yong Kaiser, Marcus Krasnogor, Natalio Bioinformatics Original Papers MOTIVATION: Flux balance analysis (FBA) based bilevel optimization has been a great success in redesigning metabolic networks for biochemical overproduction. To date, many computational approaches have been developed to solve the resulting bilevel optimization problems. However, most of them are of limited use due to biased optimality principle, poor scalability with the size of metabolic networks, potential numeric issues or low quantity of design solutions in a single run. RESULTS: Here, we have employed a network interdiction model free of growth optimality assumptions, a special case of bilevel optimization, for computational strain design and have developed a hybrid Benders algorithm (HBA) that deals with complicating binary variables in the model, thereby achieving high efficiency without numeric issues in search of best design strategies. More importantly, HBA can list solutions that meet users’ production requirements during the search, making it possible to obtain numerous design strategies at a small runtime overhead (typically ∼1 h, e.g. studied in this article). AVAILABILITY AND IMPLEMENTATION: Source code implemented in the MATALAB Cobratoolbox is freely available at https://github.com/chang88ye/NIHBA. CONTACT: math4neu@gmail.com or natalio.krasnogor@ncl.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-06 2020-03-13 /pmc/articles/PMC7267835/ /pubmed/32167529 http://dx.doi.org/10.1093/bioinformatics/btaa163 Text en © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Jiang, Shouyong
Wang, Yong
Kaiser, Marcus
Krasnogor, Natalio
NIHBA: a network interdiction approach for metabolic engineering design
title NIHBA: a network interdiction approach for metabolic engineering design
title_full NIHBA: a network interdiction approach for metabolic engineering design
title_fullStr NIHBA: a network interdiction approach for metabolic engineering design
title_full_unstemmed NIHBA: a network interdiction approach for metabolic engineering design
title_short NIHBA: a network interdiction approach for metabolic engineering design
title_sort nihba: a network interdiction approach for metabolic engineering design
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267835/
https://www.ncbi.nlm.nih.gov/pubmed/32167529
http://dx.doi.org/10.1093/bioinformatics/btaa163
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