Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool

Bibliographic Details
Main Author: Oliveira, Alexandre Rafael Machado
Publication Date: 2022
Other Authors: Cunha, Emanuel, Cruz, Fernando João Pereira, Capela, João, Sequeira, J. C., Sampaio, Marta, Ganâncio, Cláudia, Dias, Oscar
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://hdl.handle.net/1822/80239
Summary: Genome-scale metabolic models (GEMs) are essential tools for in silico phenotype prediction and strain optimisation. The most straightforward GEMs reconstruction approach uses published models as templates to generate theinitial draft, requiring further curation. Such an approachis used by BiGG Integration Tool (BIT), available for merlin users. This tool uses models from BiGG Models database as templates for the draft models. Moreover, BIT allows the selection between different template combinations. The main objective of this study is to assess the draft models generated using this tool and compare them BIT, comparing these to CarveMe models, both of which use the BiGG database, and curated models. For this, three organisms were selected, namely Streptococcus thermophilus, Xylella fastidiosa and Mycobacterium tuberculosis. The models’ variability was assessed using reactions and genes’ metabolic functions. This study concluded that models generated with BIT for each organism were differentiated, despite sharing a significant portion of metabolic functions. Furthermore, the template seems to influence the content of the models, though to a lower extent. When comparing each draft with curated models, BIT had better performances than CarveMe in all metrics. Hence, BIT can be considered a fast and reliable alternative for draft reconstruction for bacteria models.
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spelling Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration ToolBiGG Integration ToolBiGG modelsgenome-scale metabolic modelsmerlinScience & TechnologyGenome-scale metabolic models (GEMs) are essential tools for in silico phenotype prediction and strain optimisation. The most straightforward GEMs reconstruction approach uses published models as templates to generate theinitial draft, requiring further curation. Such an approachis used by BiGG Integration Tool (BIT), available for merlin users. This tool uses models from BiGG Models database as templates for the draft models. Moreover, BIT allows the selection between different template combinations. The main objective of this study is to assess the draft models generated using this tool and compare them BIT, comparing these to CarveMe models, both of which use the BiGG database, and curated models. For this, three organisms were selected, namely Streptococcus thermophilus, Xylella fastidiosa and Mycobacterium tuberculosis. The models’ variability was assessed using reactions and genes’ metabolic functions. This study concluded that models generated with BIT for each organism were differentiated, despite sharing a significant portion of metabolic functions. Furthermore, the template seems to influence the content of the models, though to a lower extent. When comparing each draft with curated models, BIT had better performances than CarveMe in all metrics. Hence, BIT can be considered a fast and reliable alternative for draft reconstruction for bacteria models.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit. A. Oliveira (DFA/BD/10205/2020), E. Cunha (DFA/BD/8076/2020), F. Cruz (SFRH/BD/139198/2018), J. Sequeira (SFRH/BD/147271/2019), and M. Sampaio (SFRH/BD/144643/2019) hold a doctoral fellowship provided by the FCT. J. Ribeiro hold a fellowship provided by the University of Minho (UMI-NHO/BIM/2020/68). Oscar Dias acknowledge FCT for the Assistant Research contract obtained under CEEC Individual 2018.info:eu-repo/semantics/publishedVersionDe GruyterUniversidade do MinhoOliveira, Alexandre Rafael MachadoCunha, EmanuelCruz, Fernando João PereiraCapela, JoãoSequeira, J. C.Sampaio, MartaGanâncio, CláudiaDias, Oscar20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/80239engOliveira, Alexandre; Cunha, Emanuel; Cruz, Fernando; Capela, João; Sequeira, J. C.; Sampaio, Marta; Ganâncio, Cláudia; Dias, Oscar, Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool. Journal of Integrative Bioinformatics, 19(3), 20220014, 20221613-451610.1515/jib-2022-00143605483920220014https://www.degruyter.com/view/j/jibinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T06:12:22Zoai:repositorium.sdum.uminho.pt:1822/80239Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T15:44:39.530458Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool
title Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool
spellingShingle Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool
Oliveira, Alexandre Rafael Machado
BiGG Integration Tool
BiGG models
genome-scale metabolic models
merlin
Science & Technology
title_short Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool
title_full Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool
title_fullStr Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool
title_full_unstemmed Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool
title_sort Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool
author Oliveira, Alexandre Rafael Machado
author_facet Oliveira, Alexandre Rafael Machado
Cunha, Emanuel
Cruz, Fernando João Pereira
Capela, João
Sequeira, J. C.
Sampaio, Marta
Ganâncio, Cláudia
Dias, Oscar
author_role author
author2 Cunha, Emanuel
Cruz, Fernando João Pereira
Capela, João
Sequeira, J. C.
Sampaio, Marta
Ganâncio, Cláudia
Dias, Oscar
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Oliveira, Alexandre Rafael Machado
Cunha, Emanuel
Cruz, Fernando João Pereira
Capela, João
Sequeira, J. C.
Sampaio, Marta
Ganâncio, Cláudia
Dias, Oscar
dc.subject.por.fl_str_mv BiGG Integration Tool
BiGG models
genome-scale metabolic models
merlin
Science & Technology
topic BiGG Integration Tool
BiGG models
genome-scale metabolic models
merlin
Science & Technology
description Genome-scale metabolic models (GEMs) are essential tools for in silico phenotype prediction and strain optimisation. The most straightforward GEMs reconstruction approach uses published models as templates to generate theinitial draft, requiring further curation. Such an approachis used by BiGG Integration Tool (BIT), available for merlin users. This tool uses models from BiGG Models database as templates for the draft models. Moreover, BIT allows the selection between different template combinations. The main objective of this study is to assess the draft models generated using this tool and compare them BIT, comparing these to CarveMe models, both of which use the BiGG database, and curated models. For this, three organisms were selected, namely Streptococcus thermophilus, Xylella fastidiosa and Mycobacterium tuberculosis. The models’ variability was assessed using reactions and genes’ metabolic functions. This study concluded that models generated with BIT for each organism were differentiated, despite sharing a significant portion of metabolic functions. Furthermore, the template seems to influence the content of the models, though to a lower extent. When comparing each draft with curated models, BIT had better performances than CarveMe in all metrics. Hence, BIT can be considered a fast and reliable alternative for draft reconstruction for bacteria models.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-01T00:00:00Z
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 https://hdl.handle.net/1822/80239
url https://hdl.handle.net/1822/80239
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Oliveira, Alexandre; Cunha, Emanuel; Cruz, Fernando; Capela, João; Sequeira, J. C.; Sampaio, Marta; Ganâncio, Cláudia; Dias, Oscar, Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool. Journal of Integrative Bioinformatics, 19(3), 20220014, 2022
1613-4516
10.1515/jib-2022-0014
36054839
20220014
https://www.degruyter.com/view/j/jib
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 De Gruyter
publisher.none.fl_str_mv De Gruyter
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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