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See detailCreation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0.
Heirendt, Laurent UL; Arreckx, Sylvain; Pfau, Thomas UL et al

in Nature protocols (2019), 14(3), 639-702

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of ... [more ▼]

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods. [less ▲]

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See detailRecon3D enables a three-dimensional view of gene variation in human metabolism.
Brunk, Elizabeth; Sahoo, Swagatika; Zielinski, Daniel C. et al

in Nature biotechnology (2018), 36(3), 272-281

Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein ... [more ▼]

Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life. [less ▲]

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See detailPrediction of intracellular metabolic states from extracellular metabolomic data
Aurich, Maike Kathrin UL; Paglia, Guiseppe; Rolfsson, Ottar et al

in Metabolomics : Official journal of the Metabolomic Society (2015), 11(3), 603-619

Metabolic models can provide a mechanistic framework to analyze information-rich omics data sets, and are increasingly being used to investigate metabolic alternations in human diseases. An expression of ... [more ▼]

Metabolic models can provide a mechanistic framework to analyze information-rich omics data sets, and are increasingly being used to investigate metabolic alternations in human diseases. An expression of the altered metabolic pathway utilization is the selection of metabolites consumed and released by cells. However, methods for the inference of intracellular metabolic states from extracellular measurements in the context of metabolic models remain underdeveloped compared to methods for other omics data. Herein, we describe a workflow for such an integrative analysis emphasizing on extracellular metabolomics data. We demonstrate, using the lymphoblastic leukemia cell lines Molt-4 and CCRF-CEM, how our methods can reveal differences in cell metabolism. Our models explain metabolite uptake and secretion by predicting a more glycolytic phenotype for the CCRFCEM model and a more oxidative phenotype for the Molt-4 model, which was supported by our experimental data. Gene expression analysis revealed altered expression of gene products at key regulatory steps in those central metabolic pathways, and literature query emphasized the role of these genes in cancer metabolism. Moreover, in silico gene knock-outs identified unique control points for each cell line model, e.g., phosphoglycerate dehydrogenase for the Molt-4 model. Thus, our workflow is well-suited to the characterization of cellular metabolic traits based on extracellular metabolomic data, and it allows the integration of multiple omics data sets into a cohesive picture based on a defined model context. [less ▲]

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See detailDo Genome-scale Models Need Exact Solvers or Clearer Standards?
Ebrahim, Ali; Almaas, Eivind; Bauer, Eugen UL et al

in Molecular Systems Biology (2015), 11(10), 1

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See detailInferring the metabolism of human orphan metabolites from their metabolic network context affirms human gluconokinase activity.
Rolfsson, Ottar; Paglia, Giuseppe; Magnusdottir, Manuela et al

in Biochemical Journal (2013), 449(2), 427-435

Metabolic network reconstructions define metabolic information within a target organism and can therefore be used to address incomplete metabolic information. In the present study we used a computational ... [more ▼]

Metabolic network reconstructions define metabolic information within a target organism and can therefore be used to address incomplete metabolic information. In the present study we used a computational approach to identify human metabolites whose metabolism is incomplete on the basis of their detection in humans but exclusion from the human metabolic network reconstruction RECON 1. Candidate solutions, composed of metabolic reactions capable of explaining the metabolism of these compounds, were then identified computationally from a global biochemical reaction database. Solutions were characterized with respect to how metabolites were incorporated into RECON 1 and their biological relevance. Through detailed case studies we show that biologically plausible non-intuitive hypotheses regarding the metabolism of these compounds can be proposed in a semi-automated manner, in an approach that is similar to de novo network reconstruction. We subsequently experimentally validated one of the proposed hypotheses and report that C9orf103, previously identified as a candidate tumour suppressor gene, encodes a functional human gluconokinase. The results of the present study demonstrate how semi-automatic gap filling can be used to refine and extend metabolic reconstructions, thereby increasing their biological scope. Furthermore, we illustrate how incomplete human metabolic knowledge can be coupled with gene annotation in order to prioritize and confirm gene functions. [less ▲]

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See detailDetailing the optimality of photosynthesis in cyanobacteria through systems biology analysis.
Nogales, Juan; Gudmundsson, Steinn; Knight, Eric M. et al

in Proceedings of the National Academy of Sciences of the United States of America (2012), 109(7), 2678-2683

Photosynthesis has recently gained considerable attention for its potential role in the development of renewable energy sources. Optimizing photosynthetic organisms for biomass or biofuel production will ... [more ▼]

Photosynthesis has recently gained considerable attention for its potential role in the development of renewable energy sources. Optimizing photosynthetic organisms for biomass or biofuel production will therefore require a systems understanding of photosynthetic processes. We reconstructed a high-quality genome-scale metabolic network for Synechocystis sp. PCC6803 that describes key photosynthetic processes in mechanistic detail. We performed an exhaustive in silico analysis of the reconstructed photosynthetic process under different light and inorganic carbon (Ci) conditions as well as under genetic perturbations. Our key results include the following. (i) We identified two main states of the photosynthetic apparatus: a Ci-limited state and a light-limited state. (ii) We discovered nine alternative electron flow pathways that assist the photosynthetic linear electron flow in optimizing the photosynthesis performance. (iii) A high degree of cooperativity between alternative pathways was found to be critical for optimal autotrophic metabolism. Although pathways with high photosynthetic yield exist for optimizing growth under suboptimal light conditions, pathways with low photosynthetic yield guarantee optimal growth under excessive light or Ci limitation. (iv) Photorespiration was found to be essential for the optimal photosynthetic process, clarifying its role in high-light acclimation. Finally, (v) an extremely high photosynthetic robustness drives the optimal autotrophic metabolism at the expense of metabolic versatility and robustness. The results and modeling approach presented here may promote a better understanding of the photosynthetic process. They can also guide bioengineering projects toward optimal biofuel production in photosynthetic organisms. [less ▲]

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See detailMultiscale modeling of metabolism and macromolecular synthesis in E. coli and its application to the evolution of codon usage.
Thiele, Ines UL; Fleming, Ronan MT UL; Que, Richard et al

in PLoS ONE (2012), 7(9), 45635

Biological systems are inherently hierarchal and multiscale in time and space. A major challenge of systems biology is to describe biological systems as a computational model, which can be used to derive ... [more ▼]

Biological systems are inherently hierarchal and multiscale in time and space. A major challenge of systems biology is to describe biological systems as a computational model, which can be used to derive novel hypothesis and drive experiments leading to new knowledge. The constraint-based reconstruction and analysis approach has been successfully applied to metabolism and to the macromolecular synthesis machinery assembly. Here, we present the first integrated stoichiometric multiscale model of metabolism and macromolecular synthesis for Escherichia coli K12 MG1655, which describes the sequence-specific synthesis and function of almost 2000 gene products at molecular detail. We added linear constraints, which couple enzyme synthesis and catalysis reactions. Comparison with experimental data showed improvement of growth phenotype prediction with the multiscale model over E. coli's metabolic model alone. Many of the genes covered by this integrated model are well conserved across enterobacters and other, less related bacteria. We addressed the question of whether the bias in synonymous codon usage could affect the growth phenotype and environmental niches that an organism can occupy. We created two classes of in silico strains, one with more biased codon usage and one with more equilibrated codon usage than the wildtype. The reduced growth phenotype in biased strains was caused by tRNA supply shortage, indicating that expansion of tRNA gene content or tRNA codon recognition allow E. coli to respond to changes in codon usage bias. Our analysis suggests that in order to maximize growth and to adapt to new environmental niches, codon usage and tRNA content must co-evolve. These results provide further evidence for the mutation-selection-drift balance theory of codon usage bias. This integrated multiscale reconstruction successfully demonstrates that the constraint-based modeling approach is well suited to whole-cell modeling endeavors. [less ▲]

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See detailIntracellular metabolite profiling of platelets: evaluation of extraction processes and chromatographic strategies.
Paglia, Giuseppe; Magnusdottir, Manuela; Thorlacius, Steinunn et al

in Journal of Chromatography. B : Analytical Technologies in the Biomedical & Life Sciences (2012), 898

An extraction method for intracellular metabolite profiling should ideally be able to recover the broadest possible range of metabolites present in a sample. However, the development of such methods is ... [more ▼]

An extraction method for intracellular metabolite profiling should ideally be able to recover the broadest possible range of metabolites present in a sample. However, the development of such methods is hampered by the diversity of the physico-chemical properties of metabolites as well as by the specific characteristics of samples and cells. In this study, we report the optimization of an UPLC-MS method for the metabolite analysis of platelet samples. The optimal analytical protocol was determined by testing seven different extraction methods as well as by employing two different LC-MS methods, in which the metabolites were separated by using hydrophilic interaction liquid chromatography (HILIC) and reversed phase liquid chromatography (RPLC). The optimal conditions were selected using the coverage of the platelets' metabolome, the response of the identified metabolites, the reproducibility of the analytical method, and the time of the analysis as main evaluation criteria. Our results show that methanol-water (7:3) extraction coupled with HILIC-MS method provides the best compromise, allowing identification of 107 metabolites in a platelet cell extract sample, 91% of them with a RSD% lower than 20. A higher number of metabolites could be detected when analyzing the platelet samples with two different LC-MS methods or when using complementary extraction methods in parallel. [less ▲]

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See detailMonitoring metabolites consumption and secretion in cultured cells using ultra-performance liquid chromatography quadrupole-time of flight mass spectrometry (UPLC-Q-ToF-MS).
Paglia, Giuseppe; Hrafnsdottir, Sigrun; Magnusdottir, Manuela et al

in Analytical and Bioanalytical Chemistry (2012), 402(3), 1183-98

Here we present an ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) method for extracellular measurements of known and unexpected metabolites in parallel. The method was developed by ... [more ▼]

Here we present an ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) method for extracellular measurements of known and unexpected metabolites in parallel. The method was developed by testing 86 metabolites, including amino acids, organic acids, sugars, purines, pyrimidines, vitamins, and nucleosides, that can be resolved by combining chromatographic and m/z dimensions. Subsequently, a targeted quantitative method was developed for 80 metabolites. The presented method combines a UPLC approach using hydrophilic interaction liquid chromatography (HILIC) and MS detection achieved by a hybrid quadrupole-time of flight (Q-ToF) mass spectrometer. The optimal setup was achieved by evaluating reproducibility and repeatability of the analytical platforms using pooled quality control samples to minimize the drift in instrumental performance over time. Then, the method was validated by analyzing extracellular metabolites from acute lymphoblastic leukemia cell lines (MOLT-4 and CCRF-CEM) treated with direct (A-769662) and indirect (AICAR) AMP activated kinase (AMPK) activators, monitoring uptake and secretion of the targeted compound over time. This analysis pointed towards a perturbed purine and pyrimidine catabolism upon AICAR treatment. Our data suggest that the method presented can be used for qualitative and quantitative analysis of extracellular metabolites and it is suitable for routine applications such as in vitro drug screening. [less ▲]

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See detailQuantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0.
Schellenberger, Jan; Que, Richard; Fleming, Ronan MT UL et al

in Nature Protocols (2011), 6(9), 1290-1307

Over the past decade, a growing community of researchers has emerged around the use of constraint-based reconstruction and analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic ... [more ▼]

Over the past decade, a growing community of researchers has emerged around the use of constraint-based reconstruction and analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a substantial update of this in silico toolbox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include (i) network gap filling, (ii) (13)C analysis, (iii) metabolic engineering, (iv) omics-guided analysis and (v) visualization. As with the first version, the COBRA Toolbox reads and writes systems biology markup language-formatted models. In version 2.0, we improved performance, usability and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the toolbox and validate results. This toolbox lowers the barrier of entry to use powerful COBRA methods. [less ▲]

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See detailThe human metabolic reconstruction Recon 1 directs hypotheses of novel human metabolic functions.
Rolfsson, Ottar; Palsson, Bernhard O.; Thiele, Ines UL

in BMC Systems Biology (2011), 5

BACKGROUND: Metabolic network reconstructions formalize our knowledge of metabolism. Gaps in these networks pinpoint regions of metabolism where biological components and functions are "missing." At the ... [more ▼]

BACKGROUND: Metabolic network reconstructions formalize our knowledge of metabolism. Gaps in these networks pinpoint regions of metabolism where biological components and functions are "missing." At the same time, a major challenge in the post genomic era involves characterisation of missing biological components to complete genome annotation. RESULTS: We used the human metabolic network reconstruction RECON 1 and established constraint-based modelling tools to uncover novel functions associated with human metabolism. Flux variability analysis identified 175 gaps in RECON 1 in the form of blocked reactions. These gaps were unevenly distributed within metabolic pathways but primarily found in the cytosol and often caused by compounds whose metabolic fate, rather than production, is unknown. Using a published algorithm, we computed gap-filling solutions comprised of non-organism specific metabolic reactions capable of bridging the identified gaps. These candidate solutions were found to be dependent upon the reaction environment of the blocked reaction. Importantly, we showed that automatically generated solutions could produce biologically realistic hypotheses of novel human metabolic reactions such as of the fate of iduronic acid following glycan degradation and of N-acetylglutamate in amino acid metabolism. CONCLUSIONS: The results demonstrate how metabolic models can be utilised to direct hypotheses of novel metabolic functions in human metabolism; a process that we find is heavily reliant upon manual curation and biochemical insight. The effectiveness of a systems approach for novel biochemical pathway discovery in mammals is demonstrated and steps required to tailor future gap filling algorithms to mammalian metabolic networks are proposed. [less ▲]

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See detailA community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2.
Thiele, Ines UL; Hyduke, Daniel R.; Steeb, Benjamin et al

in BMC Systems Biology (2011), 5

BACKGROUND: Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently ... [more ▼]

BACKGROUND: Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. RESULTS: Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. CONCLUSION: Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation. [less ▲]

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See detailFunctional characterization of alternate optimal solutions of Escherichia coli's transcriptional and translational machinery.
Thiele, Ines UL; Fleming, Ronan MT UL; Bordbar, Aarash et al

in Biophysical Journal (2010), 98(10), 2072-81

The constraint-based reconstruction and analysis approach has recently been extended to describe Escherichia coli's transcriptional and translational machinery. Here, we introduce the concept of reaction ... [more ▼]

The constraint-based reconstruction and analysis approach has recently been extended to describe Escherichia coli's transcriptional and translational machinery. Here, we introduce the concept of reaction coupling to represent the dependency between protein synthesis and utilization. These coupling constraints lead to a significant contraction of the feasible set of steady-state fluxes. The subset of alternate optimal solutions (AOS) consistent with maximal ribosome production was calculated. The majority of transcriptional and translational reactions were active for all of these AOS, showing that the network has a low degree of redundancy. Furthermore, all calculated AOS contained the qualitative expression of at least 92% of the known essential genes. Principal component analysis of AOS demonstrated that energy currencies (ATP, GTP, and phosphate) dominate the network's capability to produce ribosomes. Additionally, we identified regulatory control points of the network, which include the transcription reactions of sigma70 (RpoD) as well as that of a degradosome component (Rne) and of tRNA charging (ValS). These reactions contribute significant variance among AOS. These results show that constraint-based modeling can be applied to gain insight into the systemic properties of E. coli's transcriptional and translational machinery. [less ▲]

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See detailA detailed genome-wide reconstruction of mouse metabolism based on human Recon 1
Sigurdsson, Martin I.; Jamshidi, Neema; Steingrimsson, Eirikur et al

in BMC Systems Biology (2010), 4

BACKGROUND: Well-curated and validated network reconstructions are extremely valuable tools in systems biology. Detailed metabolic reconstructions of mammals have recently emerged, including human ... [more ▼]

BACKGROUND: Well-curated and validated network reconstructions are extremely valuable tools in systems biology. Detailed metabolic reconstructions of mammals have recently emerged, including human reconstructions. They raise the question if the various successful applications of microbial reconstructions can be replicated in complex organisms. RESULTS: We mapped the published, detailed reconstruction of human metabolism (Recon 1) to other mammals. By searching for genes homologous to Recon 1 genes within mammalian genomes, we were able to create draft metabolic reconstructions of five mammals, including the mouse. Each draft reconstruction was created in compartmentalized and non-compartmentalized version via two different approaches. Using gap-filling algorithms, we were able to produce all cellular components with three out of four versions of the mouse metabolic reconstruction. We finalized a functional model by iterative testing until it passed a predefined set of 260 validation tests. The reconstruction is the largest, most comprehensive mouse reconstruction to-date, accounting for 1,415 genes coding for 2,212 gene-associated reactions and 1,514 non-gene-associated reactions.We tested the mouse model for phenotype prediction capabilities. The majority of predicted essential genes were also essential in vivo. However, our non-tissue specific model was unable to predict gene essentiality for many of the metabolic genes shown to be essential in vivo. Our knockout simulation of the lipoprotein lipase gene correlated well with experimental results, suggesting that softer phenotypes can also be simulated. CONCLUSIONS: We have created a high-quality mouse genome-scale metabolic reconstruction, iMM1415 (Mus Musculus, 1415 genes). We demonstrate that the mouse model can be used to perform phenotype simulations, similar to models of microbe metabolism. Since the mouse is an important experimental organism, this model should become an essential tool for studying metabolic phenotypes in mice, including outcomes from drug screening. [less ▲]

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See detailA protocol for generating a high-quality genome-scale metabolic reconstruction.
Thiele, Ines UL; Palsson, Bernhard O.

in Nature Protocols (2010), 5(1), 93-121

Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured ... [more ▼]

Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process. [less ▲]

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See detailReconstruction annotation jamborees: a community approach to systems biology.
Thiele, Ines UL; Palsson, Bernhard O.

in Molecular Systems Biology (2010), 6

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See detailWhat is flux balance analysis?
Orth, Jeffrey D.; Thiele, Ines UL; Palsson, Bernhard O.

in Nature Biotechnology (2010), 28(3), 245-8

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See detailGenome-scale reconstruction of Escherichia coli's transcriptional and translational machinery: a knowledge base, its mathematical formulation, and its functional characterization.
Thiele, Ines UL; Jamshidi, Neema; Fleming, Ronan MT UL et al

in PLoS Computational Biology (2009), 5(3), 1000312

Metabolic network reconstructions represent valuable scaffolds for '-omics' data integration and are used to computationally interrogate network properties. However, they do not explicitly account for the ... [more ▼]

Metabolic network reconstructions represent valuable scaffolds for '-omics' data integration and are used to computationally interrogate network properties. However, they do not explicitly account for the synthesis of macromolecules (i.e., proteins and RNA). Here, we present the first genome-scale, fine-grained reconstruction of Escherichia coli's transcriptional and translational machinery, which produces 423 functional gene products in a sequence-specific manner and accounts for all necessary chemical transformations. Legacy data from over 500 publications and three databases were reviewed, and many pathways were considered, including stable RNA maturation and modification, protein complex formation, and iron-sulfur cluster biogenesis. This reconstruction represents the most comprehensive knowledge base for these important cellular functions in E. coli and is unique in its scope. Furthermore, it was converted into a mathematical model and used to: (1) quantitatively integrate gene expression data as reaction constraints and (2) compute functional network states, which were compared to reported experimental data. For example, the model predicted accurately the ribosome production, without any parameterization. Also, in silico rRNA operon deletion suggested that a high RNA polymerase density on the remaining rRNA operons is needed to reproduce the reported experimental ribosome numbers. Moreover, functional protein modules were determined, and many were found to contain gene products from multiple subsystems, highlighting the functional interaction of these proteins. This genome-scale reconstruction of E. coli's transcriptional and translational machinery presents a milestone in systems biology because it will enable quantitative integration of '-omics' datasets and thus the study of the mechanistic principles underlying the genotype-phenotype relationship. [less ▲]

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See detailReconstruction of biochemical networks in microorganisms.
Feist, Adam M.; Herrgard, Markus J.; Thiele, Ines UL et al

in Nature Reviews. Microbiology (2009), 7(2), 129-43

Systems analysis of metabolic and growth functions in microbial organisms is rapidly developing and maturing. Such studies are enabled by reconstruction, at the genomic scale, of the biochemical reaction ... [more ▼]

Systems analysis of metabolic and growth functions in microbial organisms is rapidly developing and maturing. Such studies are enabled by reconstruction, at the genomic scale, of the biochemical reaction networks that underlie cellular processes. The network reconstruction process is organism specific and is based on an annotated genome sequence, high-throughput network-wide data sets and bibliomic data on the detailed properties of individual network components. Here we describe the process that is currently used to achieve comprehensive network reconstructions and discuss how these reconstructions are curated and validated. This review should aid the growing number of researchers who are carrying out reconstructions for particular target organisms. [less ▲]

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See detailIdentification of potential pathway mediation targets in Toll-like receptor signaling.
Li, Fan; Thiele, Ines UL; Jamshidi, Neema et al

in PLoS Computational Biology (2009), 5(2), 1000292

Recent advances in reconstruction and analytical methods for signaling networks have spurred the development of large-scale models that incorporate fully functional and biologically relevant features. An ... [more ▼]

Recent advances in reconstruction and analytical methods for signaling networks have spurred the development of large-scale models that incorporate fully functional and biologically relevant features. An extended reconstruction of the human Toll-like receptor signaling network is presented herein. This reconstruction contains an extensive complement of kinases, phosphatases, and other associated proteins that mediate the signaling cascade along with a delineation of their associated chemical reactions. A computational framework based on the methods of large-scale convex analysis was developed and applied to this network to characterize input-output relationships. The input-output relationships enabled significant modularization of the network into ten pathways. The analysis identified potential candidates for inhibitory mediation of TLR signaling with respect to their specificity and potency. Subsequently, we were able to identify eight novel inhibition targets through constraint-based modeling methods. The results of this study are expected to yield meaningful avenues for further research in the task of mediating the Toll-like receptor signaling network and its effects. [less ▲]

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