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.Klebsiella pneumoniae, a Gram-negative bacterium of the family Enterobacteriaceae, is a microorganism with significance in both medicine and biotechnology. K. pneumoniae is a common opportunistic human pathogen, causing pneumonia, urinary tract infections, and bacteremia (25). Most clinical K. pneumoniae isolates are multidrug resistant, and up to 20% of them are extended-spectrum beta-lactamase-producing strains. The situation is worsened by the recent spreading of carbapenem-resistant NDM-1 strains, which leave very few antibiotics effective and therefore pose a serious threat to human health (23). In biotechnology, K. pneumoniae is capable of metabolizing glycerol as a sole source of carbon to produce 1,3-propanediol, a chemical that has many industrial applications (16,51). Proper functioning of the metabolic network in K. pneumoniae underlies its ability both to cause disease and to serve as a useful platform strain for metabolic engineering.The study of metabolism in many organisms has greatly benefitted from in silico genome-scale reconstruction of their metabolic networks combined with flux balance analysis (FBA), a computational technique that incorporates many different components of metabolism and their couplings to provide insight into steady-state flux distributions among the different pathways. Such system level analyses are critical since they can reveal emergent, network level properties not readily apparent from more-focused investigation of individual genes or pathways.The metabolic network reconstruction of Escherichia coli K-12 represents the best-developed genome-scale network to date because E. coli is arguably the most studied and best characterized microorganism in terms of genome annotation, functional characterization, and knowledge of growth behavior (11). Metabolic network r...