References of "Palsson, Bernhard O"
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See detailA genome-scale metabolic reconstruction of Pseudomonas putida KT2440: iJN746 as a cell factory.
Nogales, Juan; Palsson, Bernhard O.; Thiele, Ines UL

in BMC Systems Biology (2008), 2

BACKGROUND: Pseudomonas putida is the best studied pollutant degradative bacteria and is harnessed by industrial biotechnology to synthesize fine chemicals. Since the publication of P. putida KT2440's ... [more ▼]

BACKGROUND: Pseudomonas putida is the best studied pollutant degradative bacteria and is harnessed by industrial biotechnology to synthesize fine chemicals. Since the publication of P. putida KT2440's genome, some in silico analyses of its metabolic and biotechnology capacities have been published. However, global understanding of the capabilities of P. putida KT2440 requires the construction of a metabolic model that enables the integration of classical experimental data along with genomic and high-throughput data. The constraint-based reconstruction and analysis (COBRA) approach has been successfully used to build and analyze in silico genome-scale metabolic reconstructions. RESULTS: We present a genome-scale reconstruction of P. putida KT2440's metabolism, iJN746, which was constructed based on genomic, biochemical, and physiological information. This manually-curated reconstruction accounts for 746 genes, 950 reactions, and 911 metabolites. iJN746 captures biotechnologically relevant pathways, including polyhydroxyalkanoate synthesis and catabolic pathways of aromatic compounds (e.g., toluene, benzoate, phenylacetate, nicotinate), not described in other metabolic reconstructions or biochemical databases. The predictive potential of iJN746 was validated using experimental data including growth performance and gene deletion studies. Furthermore, in silico growth on toluene was found to be oxygen-limited, suggesting the existence of oxygen-efficient pathways not yet annotated in P. putida's genome. Moreover, we evaluated the production efficiency of polyhydroxyalkanoates from various carbon sources and found fatty acids as the most prominent candidates, as expected. CONCLUSION: Here we presented the first genome-scale reconstruction of P. putida, a biotechnologically interesting all-surrounder. Taken together, this work illustrates the utility of iJN746 as i) a knowledge-base, ii) a discovery tool, and iii) an engineering platform to explore P. putida's potential in bioremediation and bioplastic production. [less ▲]

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See detailGlobal reconstruction of the human metabolic network based on genomic and bibliomic data.
Duarte, Natalie C.; Becker, Scott A.; Jamshidi, Neema et al

in Proceedings of the National Academy of Sciences of the United States of America (2007), 104(6), 1777-82

Metabolism is a vital cellular process, and its malfunction is a major contributor to human disease. Metabolic networks are complex and highly interconnected, and thus systems-level computational ... [more ▼]

Metabolism is a vital cellular process, and its malfunction is a major contributor to human disease. Metabolic networks are complex and highly interconnected, and thus systems-level computational approaches are required to elucidate and understand metabolic genotype-phenotype relationships. We have manually reconstructed the global human metabolic network based on Build 35 of the genome annotation and a comprehensive evaluation of >50 years of legacy data (i.e., bibliomic data). Herein we describe the reconstruction process and demonstrate how the resulting genome-scale (or global) network can be used (i) for the discovery of missing information, (ii) for the formulation of an in silico model, and (iii) as a structured context for analyzing high-throughput biological data sets. Our comprehensive evaluation of the literature revealed many gaps in the current understanding of human metabolism that require future experimental investigation. Mathematical analysis of network structure elucidated the implications of intracellular compartmentalization and the potential use of correlated reaction sets for alternative drug target identification. Integrated analysis of high-throughput data sets within the context of the reconstruction enabled a global assessment of functional metabolic states. These results highlight some of the applications enabled by the reconstructed human metabolic network. The establishment of this network represents an important step toward genome-scale human systems biology. [less ▲]

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See detailCandidate states of Helicobacter pylori's genome-scale metabolic network upon application of "loop law" thermodynamic constraints.
Price, Nathan D.; Thiele, Ines UL; Palsson, Bernhard O.

in Biophysical Journal (2006), 90(11), 3919-28

Constraint-based modeling has proven to be a useful tool in the analysis of biochemical networks. To date, most studies in this field have focused on the use of linear constraints, resulting from mass ... [more ▼]

Constraint-based modeling has proven to be a useful tool in the analysis of biochemical networks. To date, most studies in this field have focused on the use of linear constraints, resulting from mass balance and capacity constraints, which lead to the definition of convex solution spaces. One additional constraint arising out of thermodynamics is known as the "loop law" for reaction fluxes, which states that the net flux around a closed biochemical loop must be zero because no net thermodynamic driving force exists. The imposition of the loop-law can lead to nonconvex solution spaces making the analysis of the consequences of its imposition challenging. A four-step approach is developed here to apply the loop-law to study metabolic network properties: 1), determine linear equality constraints that are necessary (but not necessarily sufficient) for thermodynamic feasibility; 2), tighten V(max) and V(min) constraints to enclose the remaining nonconvex space; 3), uniformly sample the convex space that encloses the nonconvex space using standard Monte Carlo techniques; and 4), eliminate from the resulting set all solutions that violate the loop-law, leaving a subset of steady-state solutions. This subset of solutions represents a uniform random sample of the space that is defined by the additional imposition of the loop-law. This approach is used to evaluate the effect of imposing the loop-law on predicted candidate states of the genome-scale metabolic network of Helicobacter pylori. [less ▲]

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See detailTowards multidimensional genome annotation.
Reed, Jennifer L.; Famili, Iman; Thiele, Ines UL et al

in Nature Reviews. Genetics (2006), 7(2), 130-41

Our information about the gene content of organisms continues to grow as more genomes are sequenced and gene products are characterized. Sequence-based annotation efforts have led to a list of cellular ... [more ▼]

Our information about the gene content of organisms continues to grow as more genomes are sequenced and gene products are characterized. Sequence-based annotation efforts have led to a list of cellular components, which can be thought of as a one-dimensional annotation. With growing information about component interactions, facilitated by the advancement of various high-throughput technologies, systemic, or two-dimensional, annotations can be generated. Knowledge about the physical arrangement of chromosomes will lead to a three-dimensional spatial annotation of the genome and a fourth dimension of annotation will arise from the study of changes in genome sequences that occur during adaptive evolution. Here we discuss all four levels of genome annotation, with specific emphasis on two-dimensional annotation methods. [less ▲]

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See detailCandidate metabolic network states in human mitochondria. Impact of diabetes, ischemia, and diet.
Thiele, Ines UL; Price, Nathan D.; Vo, Thuy D. et al

in Journal of Biological Chemistry (2005), 280(12), 11683-95

The human mitochondrial metabolic network was recently reconstructed based on proteomic and biochemical data. Linear programming and uniform random sampling were applied herein to identify candidate ... [more ▼]

The human mitochondrial metabolic network was recently reconstructed based on proteomic and biochemical data. Linear programming and uniform random sampling were applied herein to identify candidate steady states of the metabolic network that were consistent with the imposed physico-chemical constraints and available experimental data. The activity of the mitochondrion was studied under four metabolic conditions: normal physiologic, diabetic, ischemic, and dietetic. Pairwise correlations between steady-state reaction fluxes were calculated in each condition to evaluate the dependence among the reactions in the network. Applying constraints on exchange fluxes resulted in predictions for intracellular fluxes that agreed with experimental data. Analyses of the steady-state flux distributions showed that the experimentally observed reduced activity of pyruvate dehydrogenase in vivo could be a result of stoichiometric constraints and therefore would not necessarily require enzymatic inhibition. The observed changes in the energy metabolism of the mitochondrion under diabetic conditions were used to evaluate the impact of previously suggested treatments. The results showed that neither normalized glucose uptake nor decreased ketone body uptake have a positive effect on the mitochondrial energy metabolism or network flexibility. Taken together, this study showed that sampling of the steady-state flux space is a powerful method to investigate network properties under different conditions and provides a basis for in silico evaluations of effects of potential disease treatments. [less ▲]

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See detailExpanded metabolic reconstruction of Helicobacter pylori (iIT341 GSM/GPR): an in silico genome-scale characterization of single- and double-deletion mutants.
Thiele, Ines UL; Vo, Thuy D.; Price, Nathan D. et al

in Journal of Bacteriology (2005), 187(16), 5818-30

Helicobacter pylori is a human gastric pathogen infecting almost half of the world population. Herein, we present an updated version of the metabolic reconstruction of H. pylori strain 26695 based on the ... [more ▼]

Helicobacter pylori is a human gastric pathogen infecting almost half of the world population. Herein, we present an updated version of the metabolic reconstruction of H. pylori strain 26695 based on the revised genome annotation and new experimental data. This reconstruction, iIT341 GSM/GPR, represents a detailed review of the current literature about H. pylori as it integrates biochemical and genomic data in a comprehensive framework. In total, it accounts for 341 metabolic genes, 476 intracellular reactions, 78 exchange reactions, and 485 metabolites. Novel features of iIT341 GSM/GPR include (i) gene-protein-reaction associations, (ii) elementally and charge-balanced reactions, (iii) more accurate descriptions of isoprenoid and lipopolysaccharide metabolism, and (iv) quantitative assessments of the supporting data for each reaction. This metabolic reconstruction was used to carry out in silico deletion studies to identify essential and conditionally essential genes in H. pylori. A total of 128 essential and 75 conditionally essential metabolic genes were identified. Predicted growth phenotypes of single knockouts were validated using published experimental data. In addition, in silico double-deletion studies identified a total of 47 synthetic lethal mutants involving 67 different metabolic genes in rich medium. [less ▲]

Detailed reference viewed: 107 (2 UL)