TY - JOUR
T1 - Comprehensive genome-scale metabolic model of the human pathogen Cryptococcus neoformans
T2 - A platform for understanding pathogen metabolism and identifying new drug targets
AU - Tezcan, Enes Fahri
AU - Demirtas, Yigit
AU - Cakar, Zeynep Petek
AU - Ulgen, Kutlu O.
N1 - Publisher Copyright:
Copyright © 2023 Tezcan, Demirtas, Cakar and Ulgen.
PY - 2023
Y1 - 2023
N2 - Introduction: The fungal priority pathogen Cryptococcus neoformans causes cryptococcal meningoencephalitis in immunocompromised individuals and leads to hundreds of thousands of deaths per year. The undesirable side effects of existing treatments, the need for long application times to prevent the disease from recurring, the lack of resources for these treatment methods to spread over all continents necessitate the search for new treatment methods. Methods: Genome-scale models have been shown to be valuable in studying the metabolism of many organisms. Here we present the first genome-scale metabolic model for C. neoformans, iCryptococcus. This comprehensive model consists of 1,270 reactions, 1,143 metabolites, 649 genes, and eight compartments. The model was validated, proving accurate when predicting the capability of utilizing different carbon and nitrogen sources and growth rate in comparison to experimental data. Results and Discussion: The compatibility of the in silico Cryptococcus metabolism under infection conditions was assessed. The steroid and amino acid metabolisms found in the essentiality analyses have the potential to be drug targets for the therapeutic strategies to be developed against Cryptococcus species. iCryptococcus model can be applied to explore new targets for antifungal drugs along with essential gene, metabolite and reaction analyses and provides a promising platform for elucidation of pathogen metabolism.
AB - Introduction: The fungal priority pathogen Cryptococcus neoformans causes cryptococcal meningoencephalitis in immunocompromised individuals and leads to hundreds of thousands of deaths per year. The undesirable side effects of existing treatments, the need for long application times to prevent the disease from recurring, the lack of resources for these treatment methods to spread over all continents necessitate the search for new treatment methods. Methods: Genome-scale models have been shown to be valuable in studying the metabolism of many organisms. Here we present the first genome-scale metabolic model for C. neoformans, iCryptococcus. This comprehensive model consists of 1,270 reactions, 1,143 metabolites, 649 genes, and eight compartments. The model was validated, proving accurate when predicting the capability of utilizing different carbon and nitrogen sources and growth rate in comparison to experimental data. Results and Discussion: The compatibility of the in silico Cryptococcus metabolism under infection conditions was assessed. The steroid and amino acid metabolisms found in the essentiality analyses have the potential to be drug targets for the therapeutic strategies to be developed against Cryptococcus species. iCryptococcus model can be applied to explore new targets for antifungal drugs along with essential gene, metabolite and reaction analyses and provides a promising platform for elucidation of pathogen metabolism.
KW - cryptococcus neoformans
KW - drug target
KW - gene essentiality
KW - genome scale metabolic model
KW - metabolic reconstruction
UR - http://www.scopus.com/inward/record.url?scp=85174398469&partnerID=8YFLogxK
U2 - 10.3389/fbinf.2023.1121409
DO - 10.3389/fbinf.2023.1121409
M3 - Article
AN - SCOPUS:85174398469
SN - 2673-7647
VL - 3
JO - Frontiers in Bioinformatics
JF - Frontiers in Bioinformatics
M1 - 1121409
ER -