Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool
| Main Author: | |
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| Publication Date: | 2022 |
| Other Authors: | , , , , , , |
| 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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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 |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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publishedVersion |
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https://hdl.handle.net/1822/80239 |
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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 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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De Gruyter |
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De Gruyter |
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