Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection

ABSTRACT: Background: Up to date, Mycobacterium tuberculosis (Mtb) remains as the worst intracellular killer pathogen. To establish infection, inside the granuloma, Mtb reprograms its metabolism to support both growth and survival, keeping a balance between catabolism, anabolism and energy supply. M...

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Autores:
López Agudelo, Víctor Alonso
Baena García, Andrés
Ramírez Malule, Howard
Ochoa Cáceres, Silvia Mercedes
Barrera Robledo, Luis Fernando
Ríos Estepa, Rigoberto
Tipo de recurso:
Article of investigation
Fecha de publicación:
2017
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/12825
Acceso en línea:
http://hdl.handle.net/10495/12825
Palabra clave:
Mycobacterium tuberculosis
Análisis del plano de fase fenotípica
Modelado metabólico a escala del genoma
Reprogramación metabólica
Rights
openAccess
License
Atribución 2.5 Colombia (CC BY 2.5 CO)
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oai_identifier_str oai:bibliotecadigital.udea.edu.co:10495/12825
network_acronym_str UDEA2
network_name_str Repositorio UdeA
repository_id_str
dc.title.spa.fl_str_mv Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection
title Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection
spellingShingle Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection
Mycobacterium tuberculosis
Análisis del plano de fase fenotípica
Modelado metabólico a escala del genoma
Reprogramación metabólica
title_short Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection
title_full Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection
title_fullStr Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection
title_full_unstemmed Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection
title_sort Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection
dc.creator.fl_str_mv López Agudelo, Víctor Alonso
Baena García, Andrés
Ramírez Malule, Howard
Ochoa Cáceres, Silvia Mercedes
Barrera Robledo, Luis Fernando
Ríos Estepa, Rigoberto
dc.contributor.author.none.fl_str_mv López Agudelo, Víctor Alonso
Baena García, Andrés
Ramírez Malule, Howard
Ochoa Cáceres, Silvia Mercedes
Barrera Robledo, Luis Fernando
Ríos Estepa, Rigoberto
dc.subject.none.fl_str_mv Mycobacterium tuberculosis
Análisis del plano de fase fenotípica
Modelado metabólico a escala del genoma
Reprogramación metabólica
topic Mycobacterium tuberculosis
Análisis del plano de fase fenotípica
Modelado metabólico a escala del genoma
Reprogramación metabólica
description ABSTRACT: Background: Up to date, Mycobacterium tuberculosis (Mtb) remains as the worst intracellular killer pathogen. To establish infection, inside the granuloma, Mtb reprograms its metabolism to support both growth and survival, keeping a balance between catabolism, anabolism and energy supply. Mtb knockouts with the faculty of being essential on a wide range of nutritional conditions are deemed as target candidates for tuberculosis (TB) treatment. Constraint-based genome-scale modeling is considered as a promising tool for evaluating genetic and nutritional perturbations on Mtb metabolic reprogramming. Nonetheless, few in silico assessments of the effect of nutritional conditions on Mtb’s vulnerability and metabolic adaptation have been carried out. Results: A genome-scale model (GEM) of Mtb, modified from the H37Rv iOSDD890, was used to explore the metabolic reprogramming of two Mtb knockout mutants (pfkA- and icl-mutants), lacking key enzymes of central carbon metabolism, while exposed to changing nutritional conditions (oxygen, and carbon and nitrogen sources). A combination of shadow pricing, sensitivity analysis, and flux distributions patterns allowed us to identify metabolic behaviors that are in agreement with phenotypes reported in the literature. During hypoxia, at high glucose consumption, the Mtb pfkA-mutant showed a detrimental growth effect derived from the accumulation of toxic sugar phosphate intermediates (glucose-6-phosphate and fructose-6-phosphate) along with an increment of carbon fluxes towards the reductive direction of the tricarboxylic acid cycle (TCA). Furthermore, metabolic reprogramming of the icl-mutant (icl1&icl2) showed the importance of the methylmalonyl pathway for the detoxification of propionyl-CoA, during growth at high fatty acid consumption rates and aerobic conditions. At elevated levels of fatty acid uptake and hypoxia, we found a drop in TCA cycle intermediate accumulation that might create redox imbalance. Finally, findings regarding Mtb-mutant metabolic adaptation associated with asparagine consumption and acetate, succinate and alanine production, were in agreement with literature reports. Conclusions: This study demonstrates the potential application of genome-scale modeling, flux balance analysis (FBA), phenotypic phase plane (PhPP) analysis and shadow pricing to generate valuable insights about Mtb metabolic reprogramming in the context of human granulomas.
publishDate 2017
dc.date.issued.none.fl_str_mv 2017
dc.date.accessioned.none.fl_str_mv 2020-01-04T22:19:27Z
dc.date.available.none.fl_str_mv 2020-01-04T22:19:27Z
dc.type.spa.fl_str_mv info:eu-repo/semantics/article
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http://purl.org/coar/version/c_970fb48d4fbd8a85
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dc.identifier.citation.spa.fl_str_mv López Agudelo, V. A., Baena García, A., Ramírez Malule, H., Ochoa Cáceres, S. M., Barrera Robledo, L. F., & Ríos Estepa, R. (2017). Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection. BMC Systems. Biology, 11(107), 1-18. https://doi.org/10.1186/s12918-017-0496-z
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10495/12825
dc.identifier.doi.none.fl_str_mv 10.1186/s12918-017-0496-z
dc.identifier.eissn.none.fl_str_mv 1752-0509
identifier_str_mv López Agudelo, V. A., Baena García, A., Ramírez Malule, H., Ochoa Cáceres, S. M., Barrera Robledo, L. F., & Ríos Estepa, R. (2017). Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection. BMC Systems. Biology, 11(107), 1-18. https://doi.org/10.1186/s12918-017-0496-z
10.1186/s12918-017-0496-z
1752-0509
url http://hdl.handle.net/10495/12825
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.ispartofjournalabbrev.spa.fl_str_mv BMC Syst. Biol.
dc.rights.*.fl_str_mv Atribución 2.5 Colombia (CC BY 2.5 CO)
dc.rights.spa.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.uri.*.fl_str_mv https://creativecommons.org/licenses/by/2.5/co/
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dc.rights.creativecommons.spa.fl_str_mv https://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv Atribución 2.5 Colombia (CC BY 2.5 CO)
https://creativecommons.org/licenses/by/2.5/co/
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eu_rights_str_mv openAccess
dc.format.extent.spa.fl_str_mv 17
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv BMC
dc.publisher.group.spa.fl_str_mv Bioprocesos
Grupo de Inmunología Celular e Inmunogenética
Simulación, Diseño, Control y Optimización de Procesos (SIDCOP)
dc.publisher.place.spa.fl_str_mv Londres, Inglaterra
institution Universidad de Antioquia
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spelling López Agudelo, Víctor AlonsoBaena García, AndrésRamírez Malule, HowardOchoa Cáceres, Silvia MercedesBarrera Robledo, Luis FernandoRíos Estepa, Rigoberto2020-01-04T22:19:27Z2020-01-04T22:19:27Z2017López Agudelo, V. A., Baena García, A., Ramírez Malule, H., Ochoa Cáceres, S. M., Barrera Robledo, L. F., & Ríos Estepa, R. (2017). Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection. BMC Systems. Biology, 11(107), 1-18. https://doi.org/10.1186/s12918-017-0496-zhttp://hdl.handle.net/10495/1282510.1186/s12918-017-0496-z1752-0509ABSTRACT: Background: Up to date, Mycobacterium tuberculosis (Mtb) remains as the worst intracellular killer pathogen. To establish infection, inside the granuloma, Mtb reprograms its metabolism to support both growth and survival, keeping a balance between catabolism, anabolism and energy supply. Mtb knockouts with the faculty of being essential on a wide range of nutritional conditions are deemed as target candidates for tuberculosis (TB) treatment. Constraint-based genome-scale modeling is considered as a promising tool for evaluating genetic and nutritional perturbations on Mtb metabolic reprogramming. Nonetheless, few in silico assessments of the effect of nutritional conditions on Mtb’s vulnerability and metabolic adaptation have been carried out. Results: A genome-scale model (GEM) of Mtb, modified from the H37Rv iOSDD890, was used to explore the metabolic reprogramming of two Mtb knockout mutants (pfkA- and icl-mutants), lacking key enzymes of central carbon metabolism, while exposed to changing nutritional conditions (oxygen, and carbon and nitrogen sources). A combination of shadow pricing, sensitivity analysis, and flux distributions patterns allowed us to identify metabolic behaviors that are in agreement with phenotypes reported in the literature. During hypoxia, at high glucose consumption, the Mtb pfkA-mutant showed a detrimental growth effect derived from the accumulation of toxic sugar phosphate intermediates (glucose-6-phosphate and fructose-6-phosphate) along with an increment of carbon fluxes towards the reductive direction of the tricarboxylic acid cycle (TCA). Furthermore, metabolic reprogramming of the icl-mutant (icl1&icl2) showed the importance of the methylmalonyl pathway for the detoxification of propionyl-CoA, during growth at high fatty acid consumption rates and aerobic conditions. At elevated levels of fatty acid uptake and hypoxia, we found a drop in TCA cycle intermediate accumulation that might create redox imbalance. Finally, findings regarding Mtb-mutant metabolic adaptation associated with asparagine consumption and acetate, succinate and alanine production, were in agreement with literature reports. Conclusions: This study demonstrates the potential application of genome-scale modeling, flux balance analysis (FBA), phenotypic phase plane (PhPP) analysis and shadow pricing to generate valuable insights about Mtb metabolic reprogramming in the context of human granulomas.COL0008639COL0023715COL005657417application/pdfengBMCBioprocesosGrupo de Inmunología Celular e InmunogenéticaSimulación, Diseño, Control y Optimización de Procesos (SIDCOP)Londres, Inglaterrainfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARTArtículo de investigaciónhttp://purl.org/coar/version/c_970fb48d4fbd8a86http://purl.org/coar/version/c_970fb48d4fbd8a85Atribución 2.5 Colombia (CC BY 2.5 CO)info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/co/http://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by/4.0/Mycobacterium tuberculosisAnálisis del plano de fase fenotípicaModelado metabólico a escala del genomaReprogramación metabólicaMetabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infectionBMC Syst. Biol.BMC Systems Biology11811107ORIGINALLopezVictor_2017_Metabolicadaptationtwo.pdfLopezVictor_2017_Metabolicadaptationtwo.pdfArtículo de investigaciónapplication/pdf3319526http://bibliotecadigital.udea.edu.co/bitstream/10495/12825/1/LopezVictor_2017_Metabolicadaptationtwo.pdf4b86690803600340bcc0ba431b577bb1MD51CC-LICENSElicense_urllicense_urltext/plain; charset=utf-849http://bibliotecadigital.udea.edu.co/bitstream/10495/12825/2/license_url4afdbb8c545fd630ea7db775da747b2fMD52license_textlicense_texttext/html; charset=utf-80http://bibliotecadigital.udea.edu.co/bitstream/10495/12825/3/license_textd41d8cd98f00b204e9800998ecf8427eMD53license_rdflicense_rdfapplication/rdf+xml; charset=utf-80http://bibliotecadigital.udea.edu.co/bitstream/10495/12825/4/license_rdfd41d8cd98f00b204e9800998ecf8427eMD54LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://bibliotecadigital.udea.edu.co/bitstream/10495/12825/5/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5510495/12825oai:bibliotecadigital.udea.edu.co:10495/128252022-02-07 09:35:31.631Repositorio Institucional Universidad de Antioquiaandres.perez@udea.edu.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