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Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection
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 knockou...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5697012/ https://www.ncbi.nlm.nih.gov/pubmed/29157227 http://dx.doi.org/10.1186/s12918-017-0496-z |
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author | López-Agudelo, Víctor A. Baena, Andres Ramirez-Malule, Howard Ochoa, Silvia Barrera, Luis F. Ríos-Estepa, Rigoberto |
author_facet | López-Agudelo, Víctor A. Baena, Andres Ramirez-Malule, Howard Ochoa, Silvia Barrera, Luis F. Ríos-Estepa, Rigoberto |
author_sort | López-Agudelo, Víctor A. |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-017-0496-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5697012 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-56970122017-12-01 Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection López-Agudelo, Víctor A. Baena, Andres Ramirez-Malule, Howard Ochoa, Silvia Barrera, Luis F. Ríos-Estepa, Rigoberto BMC Syst Biol Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-017-0496-z) contains supplementary material, which is available to authorized users. BioMed Central 2017-11-21 /pmc/articles/PMC5697012/ /pubmed/29157227 http://dx.doi.org/10.1186/s12918-017-0496-z Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article López-Agudelo, Víctor A. Baena, Andres Ramirez-Malule, Howard Ochoa, Silvia Barrera, Luis F. Ríos-Estepa, Rigoberto 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 |
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_short | 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 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5697012/ https://www.ncbi.nlm.nih.gov/pubmed/29157227 http://dx.doi.org/10.1186/s12918-017-0496-z |
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