Unveiling new features of the human pathogen Cryptococcus neoformans through the reconstruction and exploitation of a dedicated genome-scale metabolic model
Cryptococcus neoformans is notorious for causing severe pulmonary and central nervous system infections, particularly in immunocompromised patients. High mortality rates, associated with its tropism and adaptation to the brain microenvironment and its drug resistance profile, make this pathogen a pu...
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Elsevier
2025-01-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037025001989 |
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| author | Romeu Viana Diogo Couceiro William Newton Luís Coutinho Oscar Dias Carolina Coelho Miguel Cacho Teixeira |
| author_facet | Romeu Viana Diogo Couceiro William Newton Luís Coutinho Oscar Dias Carolina Coelho Miguel Cacho Teixeira |
| author_sort | Romeu Viana |
| collection | DOAJ |
| description | Cryptococcus neoformans is notorious for causing severe pulmonary and central nervous system infections, particularly in immunocompromised patients. High mortality rates, associated with its tropism and adaptation to the brain microenvironment and its drug resistance profile, make this pathogen a public health threat and a World Health Organization (WHO) priority. This study presents the first reconstructed genome-scale metabolic model (GSMM), iRV890, for C. neoformans var. grubii, which comprises 890 genes, 2598 reactions, and 2047 metabolites across four compartments. The GSMM iRV890 model was reconstructed using the open-source software tool merlin 4.0.2, is openly available in the well-established systems biology markup language (SBML) format and underwent validation using experimental data for specific growth and glucose consumption rates, and 222 nitrogen and carbon assimilation sources, with a 85 % prediction rate. Based on the comparison with GSMMs available for other pathogenic yeasts, unique metabolic features were predicted for C. neoformans, including key pathways shaping dynamics between C. neoformans and human host, as well as its underlying adaptions to the brain environment. Finally, the 96 predicted essential genes from the validated model are investigated as potential novel antifungal drug targets—including Erg4, Chs1, Fol1, and Fas1—which represent promising candidates for targeted drug development due to their absence in human cells. |
| format | Article |
| id | doaj-art-5aa1ff1baa9248ee8f528f74dcf1d847 |
| institution | DOAJ |
| issn | 2001-0370 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj-art-5aa1ff1baa9248ee8f528f74dcf1d8472025-08-20T03:07:24ZengElsevierComputational and Structural Biotechnology Journal2001-03702025-01-01272336234610.1016/j.csbj.2025.05.034Unveiling new features of the human pathogen Cryptococcus neoformans through the reconstruction and exploitation of a dedicated genome-scale metabolic modelRomeu Viana0Diogo Couceiro1William Newton2Luís Coutinho3Oscar Dias4Carolina Coelho5Miguel Cacho Teixeira6Department of Bioengineering, Instituto Superior Técnico, University of Lisbon, Lisboa 1049-001, Portugal; iBB - Institute for Bioengineering and Biosciences, Associate Laboratory Institute for Health and Bioeconomy - i4HB, Lisboa 1049-001, PortugalDepartment of Bioengineering, Instituto Superior Técnico, University of Lisbon, Lisboa 1049-001, Portugal; iBB - Institute for Bioengineering and Biosciences, Associate Laboratory Institute for Health and Bioeconomy - i4HB, Lisboa 1049-001, Portugal; INESC-ID, R. Alves Redol, 9, Lisbon 1000-029, PortugalMRC Centre for Medical Mycology at University of Exeter, University of Exeter, Exeter, United KingdomDepartment of Bioengineering, Instituto Superior Técnico, University of Lisbon, Lisboa 1049-001, Portugal; iBB - Institute for Bioengineering and Biosciences, Associate Laboratory Institute for Health and Bioeconomy - i4HB, Lisboa 1049-001, PortugalCEB - Centre of Biological Engineering, Universidade do Minho, Braga 4710-057, PortugalMRC Centre for Medical Mycology at University of Exeter, University of Exeter, Exeter, United KingdomDepartment of Bioengineering, Instituto Superior Técnico, University of Lisbon, Lisboa 1049-001, Portugal; iBB - Institute for Bioengineering and Biosciences, Associate Laboratory Institute for Health and Bioeconomy - i4HB, Lisboa 1049-001, Portugal; Corresponding author at: Department of Bioengineering, Instituto Superior Técnico, University of Lisbon, Lisboa 1049-001, Portugal.Cryptococcus neoformans is notorious for causing severe pulmonary and central nervous system infections, particularly in immunocompromised patients. High mortality rates, associated with its tropism and adaptation to the brain microenvironment and its drug resistance profile, make this pathogen a public health threat and a World Health Organization (WHO) priority. This study presents the first reconstructed genome-scale metabolic model (GSMM), iRV890, for C. neoformans var. grubii, which comprises 890 genes, 2598 reactions, and 2047 metabolites across four compartments. The GSMM iRV890 model was reconstructed using the open-source software tool merlin 4.0.2, is openly available in the well-established systems biology markup language (SBML) format and underwent validation using experimental data for specific growth and glucose consumption rates, and 222 nitrogen and carbon assimilation sources, with a 85 % prediction rate. Based on the comparison with GSMMs available for other pathogenic yeasts, unique metabolic features were predicted for C. neoformans, including key pathways shaping dynamics between C. neoformans and human host, as well as its underlying adaptions to the brain environment. Finally, the 96 predicted essential genes from the validated model are investigated as potential novel antifungal drug targets—including Erg4, Chs1, Fol1, and Fas1—which represent promising candidates for targeted drug development due to their absence in human cells.http://www.sciencedirect.com/science/article/pii/S2001037025001989C. neoformansGlobal stoichiometric modelDrug targetsMetabolic featuresNeurotropism |
| spellingShingle | Romeu Viana Diogo Couceiro William Newton Luís Coutinho Oscar Dias Carolina Coelho Miguel Cacho Teixeira Unveiling new features of the human pathogen Cryptococcus neoformans through the reconstruction and exploitation of a dedicated genome-scale metabolic model Computational and Structural Biotechnology Journal C. neoformans Global stoichiometric model Drug targets Metabolic features Neurotropism |
| title | Unveiling new features of the human pathogen Cryptococcus neoformans through the reconstruction and exploitation of a dedicated genome-scale metabolic model |
| title_full | Unveiling new features of the human pathogen Cryptococcus neoformans through the reconstruction and exploitation of a dedicated genome-scale metabolic model |
| title_fullStr | Unveiling new features of the human pathogen Cryptococcus neoformans through the reconstruction and exploitation of a dedicated genome-scale metabolic model |
| title_full_unstemmed | Unveiling new features of the human pathogen Cryptococcus neoformans through the reconstruction and exploitation of a dedicated genome-scale metabolic model |
| title_short | Unveiling new features of the human pathogen Cryptococcus neoformans through the reconstruction and exploitation of a dedicated genome-scale metabolic model |
| title_sort | unveiling new features of the human pathogen cryptococcus neoformans through the reconstruction and exploitation of a dedicated genome scale metabolic model |
| topic | C. neoformans Global stoichiometric model Drug targets Metabolic features Neurotropism |
| url | http://www.sciencedirect.com/science/article/pii/S2001037025001989 |
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