Genome-scale modeling of Chinese hamster ovary cells by hybrid semi-parametric flux balance analysis

Detalhes bibliográficos
Autor(a) principal: Ramos, João R. C.
Data de Publicação: 2022
Outros Autores: Oliveira, Gil P., Dumas, Patrick, Oliveira, Rui
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/146029
Resumo: Funding Information: This work was sponsored by GlaxoSmithKline Biologicals SA whereby the NOVA University Lisbon was engaged under an Agreement for R and D Services. All authors were involved in the conception and design of the study. PD’s lab performed the experiments/acquired the data. JR, GO, RO analyzed and interpreted the data. All authors were involved in drafting the manuscript or critically revising it for important intellectual content. All authors had full access to the data and approved the manuscript before it was submitted by the corresponding author. Publisher Copyright: © 2022, The Author(s).
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spelling Genome-scale modeling of Chinese hamster ovary cells by hybrid semi-parametric flux balance analysisCHO-K1 cellsCulture media designFlux balance analysisGenome-scale modelingHybrid semi-parametric systemsMachine learningBiotechnologyBioengineeringFunding Information: This work was sponsored by GlaxoSmithKline Biologicals SA whereby the NOVA University Lisbon was engaged under an Agreement for R and D Services. All authors were involved in the conception and design of the study. PD’s lab performed the experiments/acquired the data. JR, GO, RO analyzed and interpreted the data. All authors were involved in drafting the manuscript or critically revising it for important intellectual content. All authors had full access to the data and approved the manuscript before it was submitted by the corresponding author. Publisher Copyright: © 2022, The Author(s).Flux balance analysis (FBA) is currently the standard method to compute metabolic fluxes in genome-scale networks. Several FBA extensions employing diverse objective functions and/or constraints have been published. Here we propose a hybrid semi-parametric FBA extension that combines mechanistic-level constraints (parametric) with empirical constraints (non-parametric) in the same linear program. A CHO dataset with 27 measured exchange fluxes obtained from 21 reactor experiments served to evaluate the method. The mechanistic constraints were deduced from a reduced CHO-K1 genome-scale network with 686 metabolites, 788 reactions and 210 degrees of freedom. The non-parametric constraints were obtained by principal component analysis of the flux dataset. The two types of constraints were integrated in the same linear program showing comparable computational cost to standard FBA. The hybrid FBA is shown to significantly improve the specific growth rate prediction under different constraints scenarios. A metabolically efficient cell growth feed targeting minimal byproducts accumulation was designed by hybrid FBA. It is concluded that integrating parametric and nonparametric constraints in the same linear program may be an efficient approach to reduce the solution space and to improve the predictive power of FBA methods when critical mechanistic information is missing.LAQV@REQUIMTEDQ - Departamento de QuímicaRUNRamos, João R. C.Oliveira, Gil P.Dumas, PatrickOliveira, Rui2022-12-06T22:14:31Z2022-112022-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article16application/pdfhttp://hdl.handle.net/10362/146029eng1615-7591PURE: 47595431https://doi.org/10.1007/s00449-022-02795-9info: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:RCAAP2024-03-11T05:26:55Zoai:run.unl.pt:10362/146029Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:52:26.076436Repositório 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 Genome-scale modeling of Chinese hamster ovary cells by hybrid semi-parametric flux balance analysis
title Genome-scale modeling of Chinese hamster ovary cells by hybrid semi-parametric flux balance analysis
spellingShingle Genome-scale modeling of Chinese hamster ovary cells by hybrid semi-parametric flux balance analysis
Ramos, João R. C.
CHO-K1 cells
Culture media design
Flux balance analysis
Genome-scale modeling
Hybrid semi-parametric systems
Machine learning
Biotechnology
Bioengineering
title_short Genome-scale modeling of Chinese hamster ovary cells by hybrid semi-parametric flux balance analysis
title_full Genome-scale modeling of Chinese hamster ovary cells by hybrid semi-parametric flux balance analysis
title_fullStr Genome-scale modeling of Chinese hamster ovary cells by hybrid semi-parametric flux balance analysis
title_full_unstemmed Genome-scale modeling of Chinese hamster ovary cells by hybrid semi-parametric flux balance analysis
title_sort Genome-scale modeling of Chinese hamster ovary cells by hybrid semi-parametric flux balance analysis
author Ramos, João R. C.
author_facet Ramos, João R. C.
Oliveira, Gil P.
Dumas, Patrick
Oliveira, Rui
author_role author
author2 Oliveira, Gil P.
Dumas, Patrick
Oliveira, Rui
author2_role author
author
author
dc.contributor.none.fl_str_mv LAQV@REQUIMTE
DQ - Departamento de Química
RUN
dc.contributor.author.fl_str_mv Ramos, João R. C.
Oliveira, Gil P.
Dumas, Patrick
Oliveira, Rui
dc.subject.por.fl_str_mv CHO-K1 cells
Culture media design
Flux balance analysis
Genome-scale modeling
Hybrid semi-parametric systems
Machine learning
Biotechnology
Bioengineering
topic CHO-K1 cells
Culture media design
Flux balance analysis
Genome-scale modeling
Hybrid semi-parametric systems
Machine learning
Biotechnology
Bioengineering
description Funding Information: This work was sponsored by GlaxoSmithKline Biologicals SA whereby the NOVA University Lisbon was engaged under an Agreement for R and D Services. All authors were involved in the conception and design of the study. PD’s lab performed the experiments/acquired the data. JR, GO, RO analyzed and interpreted the data. All authors were involved in drafting the manuscript or critically revising it for important intellectual content. All authors had full access to the data and approved the manuscript before it was submitted by the corresponding author. Publisher Copyright: © 2022, The Author(s).
publishDate 2022
dc.date.none.fl_str_mv 2022-12-06T22:14:31Z
2022-11
2022-11-01T00:00:00Z
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/10362/146029
url http://hdl.handle.net/10362/146029
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1615-7591
PURE: 47595431
https://doi.org/10.1007/s00449-022-02795-9
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 16
application/pdf
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
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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