Development and application of efficient pathway enumeration algorithms for metabolic engineering applications
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/33091 |
Resumo: | Metabolic Engineering (ME) aims to design microbial cell factories towards the production of valuable compounds. In this endeavor, one important task relates to the search for the most suitable heterologous pathway(s) to add to the selected host. Different algorithms have been developed in the past towards this goal, following distinct approaches spanning constraint-based modelling, graph-based methods and knowledge-based systems based on chemical rules. While some of these methods search for pathways optimizing specific objective functions, here the focus will be on methods that address the enumeration of pathways that are able to convert a set of source compounds into desired targets and their posterior evaluation according to different criteria. Two pathway enumeration algorithms based on (hyper)graph-based representations are selected as the most promising ones and are analyzed in more detail: the Solution Structure Generation and the Find Path algorithms. Their capabilities and limitations are evaluated when designing novel heterologous pathways, by applying these methods on three case studies of synthetic ME related to the production of non-native compounds in E. coli and S. cerevisiae: 1-butanol, curcumin and vanillin. Some targeted improvements are implemented, extending both methods to address limitations identified that impair their scalability, improving their ability to extract potential pathways over large-scale databases. In all case-studies, the algorithms were able to find already described pathways for the production of the target compounds, but also alternative pathways that can represent novel ME solutions after further evaluation. |
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Development and application of efficient pathway enumeration algorithms for metabolic engineering applicationsSynthetic biologyOptimal pathway designPathway optimizationPathway enumerationHypergraphsConstraint-based modelingFlux balance analysisMetabolic engineeringScience & TechnologyMetabolic Engineering (ME) aims to design microbial cell factories towards the production of valuable compounds. In this endeavor, one important task relates to the search for the most suitable heterologous pathway(s) to add to the selected host. Different algorithms have been developed in the past towards this goal, following distinct approaches spanning constraint-based modelling, graph-based methods and knowledge-based systems based on chemical rules. While some of these methods search for pathways optimizing specific objective functions, here the focus will be on methods that address the enumeration of pathways that are able to convert a set of source compounds into desired targets and their posterior evaluation according to different criteria. Two pathway enumeration algorithms based on (hyper)graph-based representations are selected as the most promising ones and are analyzed in more detail: the Solution Structure Generation and the Find Path algorithms. Their capabilities and limitations are evaluated when designing novel heterologous pathways, by applying these methods on three case studies of synthetic ME related to the production of non-native compounds in E. coli and S. cerevisiae: 1-butanol, curcumin and vanillin. Some targeted improvements are implemented, extending both methods to address limitations identified that impair their scalability, improving their ability to extract potential pathways over large-scale databases. In all case-studies, the algorithms were able to find already described pathways for the production of the target compounds, but also alternative pathways that can represent novel ME solutions after further evaluation.The work is partially funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within projects ref. COMPETE FCOMP-01-0124-FEDER-015079 and Strategic Project PEst-OE/EQB/LA0023/2013, and also by Project 23060, PEM - Technological Support Platform for Metabolic Engineering, co-funded by FEDER through Portuguese QREN under the scope of the Technological Research and Development Incentive system, North Operational.ElsevierUniversidade do MinhoLiu, FilipeVilaça, PauloRocha, I.Rocha, Miguel2015-022015-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/33091engLiu, F.; Vilaça, P.; Rocha, I.; Rocha, Miguel, Development and application of efficient pathway enumeration algorithms for metabolic engineering applications. Computer Methods and Programs in Biomedicine, 118(2), 134-146, 20150169-260710.1016/j.cmpb.2014.11.01025580014info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:19:29Zoai:repositorium.sdum.uminho.pt:1822/33091Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:12:26.337141Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Development and application of efficient pathway enumeration algorithms for metabolic engineering applications |
title |
Development and application of efficient pathway enumeration algorithms for metabolic engineering applications |
spellingShingle |
Development and application of efficient pathway enumeration algorithms for metabolic engineering applications Liu, Filipe Synthetic biology Optimal pathway design Pathway optimization Pathway enumeration Hypergraphs Constraint-based modeling Flux balance analysis Metabolic engineering Science & Technology |
title_short |
Development and application of efficient pathway enumeration algorithms for metabolic engineering applications |
title_full |
Development and application of efficient pathway enumeration algorithms for metabolic engineering applications |
title_fullStr |
Development and application of efficient pathway enumeration algorithms for metabolic engineering applications |
title_full_unstemmed |
Development and application of efficient pathway enumeration algorithms for metabolic engineering applications |
title_sort |
Development and application of efficient pathway enumeration algorithms for metabolic engineering applications |
author |
Liu, Filipe |
author_facet |
Liu, Filipe Vilaça, Paulo Rocha, I. Rocha, Miguel |
author_role |
author |
author2 |
Vilaça, Paulo Rocha, I. Rocha, Miguel |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Liu, Filipe Vilaça, Paulo Rocha, I. Rocha, Miguel |
dc.subject.por.fl_str_mv |
Synthetic biology Optimal pathway design Pathway optimization Pathway enumeration Hypergraphs Constraint-based modeling Flux balance analysis Metabolic engineering Science & Technology |
topic |
Synthetic biology Optimal pathway design Pathway optimization Pathway enumeration Hypergraphs Constraint-based modeling Flux balance analysis Metabolic engineering Science & Technology |
description |
Metabolic Engineering (ME) aims to design microbial cell factories towards the production of valuable compounds. In this endeavor, one important task relates to the search for the most suitable heterologous pathway(s) to add to the selected host. Different algorithms have been developed in the past towards this goal, following distinct approaches spanning constraint-based modelling, graph-based methods and knowledge-based systems based on chemical rules. While some of these methods search for pathways optimizing specific objective functions, here the focus will be on methods that address the enumeration of pathways that are able to convert a set of source compounds into desired targets and their posterior evaluation according to different criteria. Two pathway enumeration algorithms based on (hyper)graph-based representations are selected as the most promising ones and are analyzed in more detail: the Solution Structure Generation and the Find Path algorithms. Their capabilities and limitations are evaluated when designing novel heterologous pathways, by applying these methods on three case studies of synthetic ME related to the production of non-native compounds in E. coli and S. cerevisiae: 1-butanol, curcumin and vanillin. Some targeted improvements are implemented, extending both methods to address limitations identified that impair their scalability, improving their ability to extract potential pathways over large-scale databases. In all case-studies, the algorithms were able to find already described pathways for the production of the target compounds, but also alternative pathways that can represent novel ME solutions after further evaluation. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-02 2015-02-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/33091 |
url |
http://hdl.handle.net/1822/33091 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Liu, F.; Vilaça, P.; Rocha, I.; Rocha, Miguel, Development and application of efficient pathway enumeration algorithms for metabolic engineering applications. Computer Methods and Programs in Biomedicine, 118(2), 134-146, 2015 0169-2607 10.1016/j.cmpb.2014.11.010 25580014 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799132559803678720 |