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ABSTRACT: A Single-Center Retrospective Study on the Molecular Epidemiological Characteristics of different Klebsiella pneumoniae infections in Northern China

PROVIDER: PRJNA1102315 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR28743700_1.fastq.gz	Fastqsanger.gz
	SRR28743700_2.fastq.gz	Fastqsanger.gz
	SRR28743701_1.fastq.gz	Fastqsanger.gz
	SRR28743701_2.fastq.gz	Fastqsanger.gz
	SRR28743702_1.fastq.gz	Fastqsanger.gz

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Project description:Liao2011 - Genome-scale metabolic reconstruction of Klebsiella pneumoniae (iYL1228) This model is described in the article: An experimentally validated genome-scale metabolic reconstruction of Klebsiella pneumoniae MGH 78578, iYL1228. Liao YC, Huang TW, Chen FC, Charusanti P, Hong JS, Chang HY, Tsai SF, Palsson BO, Hsiung CA. J. Bacteriol. 2011 Apr; 193(7): 1710-1717 Abstract: Klebsiella pneumoniae is a Gram-negative bacterium of the family Enterobacteriaceae that possesses diverse metabolic capabilities: many strains are leading causes of hospital-acquired infections that are often refractory to multiple antibiotics, yet other strains are metabolically engineered and used for production of commercially valuable chemicals. To study its metabolism, we constructed a genome-scale metabolic model (iYL1228) for strain MGH 78578, experimentally determined its biomass composition, experimentally determined its ability to grow on a broad range of carbon, nitrogen, phosphorus and sulfur sources, and assessed the ability of the model to accurately simulate growth versus no growth on these substrates. The model contains 1,228 genes encoding 1,188 enzymes that catalyze 1,970 reactions and accurately simulates growth on 84% of the substrates tested. Furthermore, quantitative comparison of growth rates between the model and experimental data for nine of the substrates also showed good agreement. The genome-scale metabolic reconstruction for K. pneumoniae presented here thus provides an experimentally validated in silico platform for further studies of this important industrial and biomedical organism. This model is hosted on BioModels Database and identified by: MODEL1507180054. 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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