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) |
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Pages (from-to) | S37-S43 |
Journal | Journal of Infectious Diseases |
Volume | 215 |
DOIs | |
State | Published - 2017 |
Keywords
- Bacteria
- Biolog
- Flux balance analysis
- Gap filling
- Klebsiella pneumoniae KPPR1
- Metabolic model
- Resistance
- Transposon insertion sequencing
ASJC Scopus subject areas
- Immunology and Allergy
- Infectious Diseases