Generation and validation of the iKp1289 Metabolic model for klebsiella pneumoniae KPPR1

Christopher S. Henry; Ella Rotman; Wyndham W. Lathem; Keith E.J. Tyo; Alan R. Hauser; Mark J. Mandel

doi:10.1093/infdis/jiw465

Generation and validation of the iKp1289 Metabolic model for klebsiella pneumoniae KPPR1

Christopher S. Henry^*, Ella Rotman, Wyndham W. Lathem, Keith E.J. Tyo, Alan R. Hauser, Mark J. Mandel

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

Klebsiella pneumoniae has a reputation for causing a wide range of infectious conditions, with numerous highly virulent and antibioticresistant strains. Metabolic models have the potential to provide insights into the growth behavior, nutrient requirements, essential genes, and candidate drug targets in these strains. Here we develop a metabolic model for KPPR1, a highly virulent strain of K. Pneumoniae. We apply a combination of Biolog phenotype data and fitness data to validate and refine our KPPR1 model. The final model displays a predictive accuracy of 75% in identifying potential carbon and nitrogen sources for K. Pneumoniae and of 99% in predicting nonessential genes in rich media.We demonstrate how this model is useful in studying the differences in the metabolic capabilities of the low-virulence MGH 78578 strain and the highly virulent KPPR1 strain. For example, we demonstrate that these strains differ in carbohydrate metabolism, including the ability to metabolize dulcitol as a primary carbon source. Our model makes numerous other predictions for follow-up verification and analysis.

Original language	English (US)
Pages (from-to)	S37-S43
Journal	Journal of Infectious Diseases
Volume	215
DOIs	https://doi.org/10.1093/infdis/jiw465
State	Published - 2017

Funding

Financial support. This work was supported by the National Institute of Allergy and Infectious Diseases (to C. S. H. PATRIC Bioinformatics Resource Center to C. S. H.; grants AI053674, AI04831, and AI118257 to A. R. H.; and grant R21AI117262 to M. J. M.); the Office of Biological and Environmental Research, Department of Energy (contract DE-AC02-06CH11357 to C. S. H. via the DOE Knowledgebase project); the National Science Foundation (grant 1452549 to K. E. J. T. and grant IOS-1456963 to M. J. M.); the Chicago Biomedical Consortium, with support from the Searle Funds at The Chicago Community Trust (funding to M. J. M.); the National Institute of General Medical Sciences (R35GM119627 to M. J. M.); and the Northwestern University Feinberg School of Medicine (seed grant to W. W. L., A. R. H., and M. J. M.).

Keywords

Bacteria
Biolog
Flux balance analysis
Gap filling
Klebsiella pneumoniae KPPR1
Metabolic model
Resistance
Transposon insertion sequencing

ASJC Scopus subject areas

General Medicine

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1093/infdis/jiw465

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title = "Generation and validation of the iKp1289 Metabolic model for klebsiella pneumoniae KPPR1",

abstract = "Klebsiella pneumoniae has a reputation for causing a wide range of infectious conditions, with numerous highly virulent and antibioticresistant strains. Metabolic models have the potential to provide insights into the growth behavior, nutrient requirements, essential genes, and candidate drug targets in these strains. Here we develop a metabolic model for KPPR1, a highly virulent strain of K. Pneumoniae. We apply a combination of Biolog phenotype data and fitness data to validate and refine our KPPR1 model. The final model displays a predictive accuracy of 75% in identifying potential carbon and nitrogen sources for K. Pneumoniae and of 99% in predicting nonessential genes in rich media.We demonstrate how this model is useful in studying the differences in the metabolic capabilities of the low-virulence MGH 78578 strain and the highly virulent KPPR1 strain. For example, we demonstrate that these strains differ in carbohydrate metabolism, including the ability to metabolize dulcitol as a primary carbon source. Our model makes numerous other predictions for follow-up verification and analysis.",

keywords = "Bacteria, Biolog, Flux balance analysis, Gap filling, Klebsiella pneumoniae KPPR1, Metabolic model, Resistance, Transposon insertion sequencing",

author = "Henry, {Christopher S.} and Ella Rotman and Lathem, {Wyndham W.} and Tyo, {Keith E.J.} and Hauser, {Alan R.} and Mandel, {Mark J.}",

note = "Publisher Copyright: {\textcopyright} The Author 2016.",

year = "2017",

doi = "10.1093/infdis/jiw465",

language = "English (US)",

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pages = "S37--S43",

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AU - Rotman, Ella

AU - Lathem, Wyndham W.

AU - Tyo, Keith E.J.

AU - Hauser, Alan R.

AU - Mandel, Mark J.

N1 - Publisher Copyright: © The Author 2016.

PY - 2017

Y1 - 2017

N2 - Klebsiella pneumoniae has a reputation for causing a wide range of infectious conditions, with numerous highly virulent and antibioticresistant strains. Metabolic models have the potential to provide insights into the growth behavior, nutrient requirements, essential genes, and candidate drug targets in these strains. Here we develop a metabolic model for KPPR1, a highly virulent strain of K. Pneumoniae. We apply a combination of Biolog phenotype data and fitness data to validate and refine our KPPR1 model. The final model displays a predictive accuracy of 75% in identifying potential carbon and nitrogen sources for K. Pneumoniae and of 99% in predicting nonessential genes in rich media.We demonstrate how this model is useful in studying the differences in the metabolic capabilities of the low-virulence MGH 78578 strain and the highly virulent KPPR1 strain. For example, we demonstrate that these strains differ in carbohydrate metabolism, including the ability to metabolize dulcitol as a primary carbon source. Our model makes numerous other predictions for follow-up verification and analysis.

AB - Klebsiella pneumoniae has a reputation for causing a wide range of infectious conditions, with numerous highly virulent and antibioticresistant strains. Metabolic models have the potential to provide insights into the growth behavior, nutrient requirements, essential genes, and candidate drug targets in these strains. Here we develop a metabolic model for KPPR1, a highly virulent strain of K. Pneumoniae. We apply a combination of Biolog phenotype data and fitness data to validate and refine our KPPR1 model. The final model displays a predictive accuracy of 75% in identifying potential carbon and nitrogen sources for K. Pneumoniae and of 99% in predicting nonessential genes in rich media.We demonstrate how this model is useful in studying the differences in the metabolic capabilities of the low-virulence MGH 78578 strain and the highly virulent KPPR1 strain. For example, we demonstrate that these strains differ in carbohydrate metabolism, including the ability to metabolize dulcitol as a primary carbon source. Our model makes numerous other predictions for follow-up verification and analysis.

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KW - Flux balance analysis

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KW - Metabolic model

KW - Resistance

KW - Transposon insertion sequencing

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ER -

Generation and validation of the iKp1289 Metabolic model for klebsiella pneumoniae KPPR1

Abstract

Funding

Keywords

ASJC Scopus subject areas

UN SDGs

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