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An experimentally validated genome-scale metabolic reconstruction of Klebsiella pneumoniae MGH 78578, iYL1228.

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.

SUBMITTER: Liao YC

PROVIDER: S-EPMC3067640 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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An experimentally validated genome-scale metabolic reconstruction of Klebsiella pneumoniae MGH 78578, iYL1228.

Liao Yu-Chieh YC Huang Tzu-Wen TW Chen Feng-Chi FC Charusanti Pep P Hong Jay S J JS Chang Hwan-You HY Tsai Shih-Feng SF Palsson Bernhard O BO Hsiung Chao A CA

Journal of bacteriology 20110204 7

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 compos ...[more]

PMID: 21296962

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Project description:The screening of a cDNA derived expression library of Klebsiella pneumoniae MGH 78578 expressed in E.coli using a fusion construct and specific HaloTag interaction to a modified surface is shown. Thus, 1536 different clones were screened including positive (ompA, mdh) and negative (pyrC, gapA) reference proteins. The goal of the screening was to identify potential novel immunogenic proteins from K. pneumoniae by selecting clones showing a high signal intensity in comparison to the known antigens used as positve markers. Afterwards, the most promising clones were sequenced to identify the gene and corresponding protein and these proteins were then investigated further. Consequently, 14 novel immunogenic proteins could be identified. In total 1536 (4 x 384) different lysates were spotted on different microarray slides. Each slides contained 3600 distinct spots, seperated into two compartments of 1800 spots each. Each compartment comprised quadruplicate replicates of each sample lysate with controls being analysed with more replicates. As controls we used: ompA1, ompA2 and mdh (3 x 40 replicates) as positive reference proteins, as they have been described as immunogenic before. gapA and pyrC (2 x 40 replicates) as negative reference proteins, additionally two sets of E.coli cell lysates without fusionprotein expressed, namely Acella electrocompetent cells (40 replicates) and KRX (32 replicates). Last but not least a buffer control (24 replicates) was included. Therefore, each set of replicate slides contained 376 different samples and 8 controls. Each screening was performed with three replicate slides. Consequently, a total number of 12 slides were screened (4 sets of samples x 3 replicates). For identification rabbit polyclonal antibody to K. pneumoniae (Acris AP00792PU-N) as primary and Goat polyclonal to Rabbit IgG conjugated with ChromeoTM-546 (Abcam ab60317) as secondary antibody were used. The top compartment was incubated first with primary antibody, while the bottom compartment was incubated with PBS at the same time. Afterwards both compartments were incubated with secondary antibody.

Project description:Anaerobic gut fungi in the phylum Neocallimastigomycota typically inhabit the digestive tracts of large mammalian herbivores, where they play an integral role in the decomposition of raw lignocellulose into its constitutive sugar monomers. However, quantitative tools to study their physiology are lacking, partially due to their complex and unresolved metabolism that includes the largely uncharacterized fungal hydrogenosome. Modern omics approaches combined with metabolic modeling can be used to establish an understanding of gut fungal metabolism and develop targeted engineering strategies to harness their degradation capabilities for lignocellulosic bioprocessing. Here, we introduce a high-quality genome of the anaerobic fungus Neocallimastix lanati from which we constructed the first genome-scale metabolic model of an anaerobic fungus. Relative to its size (200 Mbp, sequenced at 62× depth), it is the least fragmented publicly available gut fungal genome to date. Of the 1,788 lignocellulolytic enzymes annotated in the genome, 585 are associated with the fungal cellulosome, underscoring the powerful lignocellulolytic potential of N. lanati The genome-scale metabolic model captures the primary metabolism of N. lanati and accurately predicts experimentally validated substrate utilization requirements. Additionally, metabolic flux predictions are verified by 13C metabolic flux analysis, demonstrating that the model faithfully describes the underlying fungal metabolism. Furthermore, the model clarifies key aspects of the hydrogenosomal metabolism and can be used as a platform to quantitatively study these biotechnologically important yet poorly understood early-branching fungi.IMPORTANCE Recent genomic analyses have revealed that anaerobic gut fungi possess both the largest number and highest diversity of lignocellulolytic enzymes of all sequenced fungi, explaining their ability to decompose lignocellulosic substrates, e.g., agricultural waste, into fermentable sugars. Despite their potential, the development of engineering methods for these organisms has been slow due to their complex life cycle, understudied metabolism, and challenging anaerobic culture requirements. Currently, there is no framework that can be used to combine multi-omic data sets to understand their physiology. Here, we introduce a high-quality PacBio-sequenced genome of the anaerobic gut fungus Neocallimastix lanati Beyond identifying a trove of lignocellulolytic enzymes, we use this genome to construct the first genome-scale metabolic model of an anaerobic gut fungus. The model is experimentally validated and sheds light on unresolved metabolic features common to gut fungi. Model-guided analysis will pave the way for deepening our understanding of anaerobic gut fungi and provides a systematic framework to guide strain engineering efforts of these organisms for biotechnological use.

Dataset Information

An experimentally validated genome-scale metabolic reconstruction of Klebsiella pneumoniae MGH 78578, iYL1228.

Publications

An experimentally validated genome-scale metabolic reconstruction of Klebsiella pneumoniae MGH 78578, iYL1228.

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