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ABSTRACT: Experimental Evolution of Toxoplasma gondii

PROVIDER: PRJEB34235 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	ERR3505160_1.fastq.gz	Fastqsanger.gz
	ERR3505160_2.fastq.gz	Fastqsanger.gz
	ERR3505170_1.fastq.gz	Fastqsanger.gz
	ERR3505170_2.fastq.gz	Fastqsanger.gz
	ERR3505180_1.fastq.gz	Fastqsanger.gz

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Project description:Tymoshenko2015 - Genome scale metabolic model - ToxoNet1 This model is described in the article: Metabolic Needs and Capabilities of Toxoplasma gondii through Combined Computational and Experimental Analysis. Tymoshenko S, Oppenheim RD, Agren R, Nielsen J, Soldati-Favre D, Hatzimanikatis V. PLoS Comput. Biol. 2015 May; 11(5): e1004261 Abstract: Toxoplasma gondii is a human pathogen prevalent worldwide that poses a challenging and unmet need for novel treatment of toxoplasmosis. Using a semi-automated reconstruction algorithm, we reconstructed a genome-scale metabolic model, ToxoNet1. The reconstruction process and flux-balance analysis of the model offer a systematic overview of the metabolic capabilities of this parasite. Using ToxoNet1 we have identified significant gaps in the current knowledge of Toxoplasma metabolic pathways and have clarified its minimal nutritional requirements for replication. By probing the model via metabolic tasks, we have further defined sets of alternative precursors necessary for parasite growth. Within a human host cell environment, ToxoNet1 predicts a minimal set of 53 enzyme-coding genes and 76 reactions to be essential for parasite replication. Double-gene-essentiality analysis identified 20 pairs of genes for which simultaneous deletion is deleterious. To validate several predictions of ToxoNet1 we have performed experimental analyses of cytosolic acetyl-CoA biosynthesis. ATP-citrate lyase and acetyl-CoA synthase were localised and their corresponding genes disrupted, establishing that each of these enzymes is dispensable for the growth of T. gondii, however together they make a synthetic lethal pair. This model is hosted on BioModels Database and identified by: MODEL1504280000. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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