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Article

A Genome-Scale Metabolic Model for the Human Pathogen Candida Parapsilosis and Early Identification of Putative Novel Antifungal Drug Targets

by 1,2,3,†, 1,2,3,†, 1,2,3, 4, 5 and 1,2,3,*
1
Department of Bioengineering, Instituto Superior Técnico, University of Lisbon, 1049-001 Lisboa, Portugal
2
iBB—Institute for Bioengineering and Biosciences, 1049-001 Lisboa, Portugal
3
Associate Laboratory Institute for Health and Bioeconomy—i4HB, 1049-001 Lisboa, Portugal
4
CEB—Centre of Biological Engineering, Universidade do Minho, 4710-057 Braga, Portugal
5
ITQB Nova—Instituto de Tecnologia Química e Biológica António Xavier, 1049-001 Lisboa, Portugal
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Fernando Leal
Genes 2022, 13(2), 303; https://doi.org/10.3390/genes13020303
Received: 21 December 2021 / Accepted: 2 February 2022 / Published: 5 February 2022
(This article belongs to the Section Microbial Genetics and Genomics)
Candida parapsilosis is an emerging human pathogen whose incidence is rising worldwide, while an increasing number of clinical isolates display resistance to first-line antifungals, demanding alternative therapeutics. Genome-Scale Metabolic Models (GSMMs) have emerged as a powerful in silico tool for understanding pathogenesis due to their systems view of metabolism, but also to their drug target predictive capacity. This study presents the construction of the first validated GSMM for C. parapsilosis—iDC1003—comprising 1003 genes, 1804 reactions, and 1278 metabolites across four compartments and an intercompartment. In silico growth parameters, as well as predicted utilisation of several metabolites as sole carbon or nitrogen sources, were experimentally validated. Finally, iDC1003 was exploited as a platform for predicting 147 essential enzymes in mimicked host conditions, in which 56 are also predicted to be essential in C. albicans and C. glabrata. These promising drug targets include, besides those already used as targets for clinical antifungals, several others that seem to be entirely new and worthy of further scrutiny. The obtained results strengthen the notion that GSMMs are promising platforms for drug target discovery and guide the design of novel antifungal therapies. View Full-Text
Keywords: C. parapsilosis; genome-scale metabolic model; drug target; drug discovery C. parapsilosis; genome-scale metabolic model; drug target; drug discovery
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MDPI and ACS Style

Viana, R.; Couceiro, D.; Carreiro, T.; Dias, O.; Rocha, I.; Teixeira, M.C. A Genome-Scale Metabolic Model for the Human Pathogen Candida Parapsilosis and Early Identification of Putative Novel Antifungal Drug Targets. Genes 2022, 13, 303. https://doi.org/10.3390/genes13020303

AMA Style

Viana R, Couceiro D, Carreiro T, Dias O, Rocha I, Teixeira MC. A Genome-Scale Metabolic Model for the Human Pathogen Candida Parapsilosis and Early Identification of Putative Novel Antifungal Drug Targets. Genes. 2022; 13(2):303. https://doi.org/10.3390/genes13020303

Chicago/Turabian Style

Viana, Romeu, Diogo Couceiro, Tiago Carreiro, Oscar Dias, Isabel Rocha, and Miguel C. Teixeira. 2022. "A Genome-Scale Metabolic Model for the Human Pathogen Candida Parapsilosis and Early Identification of Putative Novel Antifungal Drug Targets" Genes 13, no. 2: 303. https://doi.org/10.3390/genes13020303

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