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ABSTRACT: Adaptive introgression and cryptic population structure of Cryptosporidium hominis in Africa revealed by comparative genomics

PROVIDER: PRJNA634705 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR11843800_1.fastq.gz	Fastqsanger.gz
	SRR11843800_2.fastq.gz	Fastqsanger.gz
	SRR11843801_1.fastq.gz	Fastqsanger.gz
	SRR11843801_2.fastq.gz	Fastqsanger.gz
	SRR11843802_1.fastq.gz	Fastqsanger.gz

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Project description:Vanee2010 - Genome-scale metabolic model of Cryptosporidium hominis (iNV213) This model is described in the article: A genome-scale metabolic model of Cryptosporidium hominis. Vanee N, Roberts SB, Fong SS, Manque P, Buck GA. Chem. Biodivers. 2010 May; 7(5): 1026-1039 Abstract: The apicomplexan Cryptosporidium is a protozoan parasite of humans and other mammals. Cryptosporidium species cause acute gastroenteritis and diarrheal disease in healthy humans and animals, and cause life-threatening infection in immunocompromised individuals such as people with AIDS. The parasite has a one-host life cycle and commonly invades intestinal epithelial cells. The current genome annotation of C. hominis, the most serious human pathogen, predicts 3884 genes of which ca. 1581 have predicted functional annotations. Using a combination of bioinformatics analysis, biochemical evidence, and high-throughput data, we have constructed a genome-scale metabolic model of C. hominis. The model is comprised of 213 gene-associated enzymes involved in 540 reactions among the major metabolic pathways and provides a link between the genotype and the phenotype of the organism, making it possible to study and predict behavior based upon genome content. This model was also used to analyze the two life stages of the parasite by integrating the stage-specific proteomic data for oocyst and sporozoite stages. Overall, this model provides a computational framework to systematically study and analyze various functional behaviors of C. hominis with respect to its life cycle and pathogenicity. This model is hosted on BioModels Database and identified by: MODEL1507180071. 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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