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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 detailThe intertwined metabolism during symbiotic nitrogen fixation elucidated by metabolic modelling
Pfau, Thomas UL; Christian, Nils UL; Masakapalli, Shyam K. et al

in Scientific Reports (2018), 8

Genome-scale metabolic network models can be used for various analyses including the prediction of metabolic responses to changes in the environment. Legumes are well known for their rhizobial symbiosis ... [more ▼]

Genome-scale metabolic network models can be used for various analyses including the prediction of metabolic responses to changes in the environment. Legumes are well known for their rhizobial symbiosis that introduces nitrogen into the global nutrient cycle. Here, we describe a fully compartmentalised, mass and charge-balanced, genome-scale model of the clover Medicago truncatula, which has been adopted as a model organism for legumes. We employed flux balance analysis to demonstrate that the network is capable of producing biomass components in experimentally observed proportions, during day and night. By connecting the plant model to a model of its rhizobial symbiont, Sinorhizobium meliloti, we were able to investigate the effects of the symbiosis on metabolic fluxes and plant growth and could demonstrate how oxygen availability influences metabolic exchanges between plant and symbiont, thus elucidating potential benefits of inter organism amino acid cycling. We thus provide a modelling framework, in which the interlinked metabolism of plants and nodules can be studied from a theoretical perspective. [less ▲]

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See detailBenchmarking procedures for high-throughput context specific reconstruction algorithms
Pacheco, Maria Irene UL; Pfau, Thomas UL; Sauter, Thomas UL

in Frontiers in Physiology (2016)

Recent progress in high-throughput data acquisition has shifted the focus from data generation to processing and understanding of how to integrate collected information. Context specific reconstruction ... [more ▼]

Recent progress in high-throughput data acquisition has shifted the focus from data generation to processing and understanding of how to integrate collected information. Context specific reconstruction based on generic genome scale models like ReconX or HMR has the potential to become a diagnostic and treatment tool tailored to the analysis of specific individuals. The respective computational algorithms require a high level of predictive power, robustness and sensitivity. Although multiple context specific reconstruction algorithms were published in the last 10 years, only a fraction of them is suitable for model building based on human high-throughput data. Beside other reasons, this might be due to problems arising from the limitation to only one metabolic target function or arbitrary thresholding. This review describes and analyses common validation methods used for testing model building algorithms. Two major methods can be distinguished: consistency testing and comparison based testing. The first is concerned with robustness against noise, e.g., missing data due to the impossibility to distinguish between the signal and the background of non-specific binding of probes in a microarray experiment, and whether distinct sets of input expressed genes corresponding to i.e., different tissues yield distinct models. The latter covers methods comparing sets of functionalities, comparison with existing networks or additional databases. We test those methods on several available algorithms and deduce properties of these algorithms that can be compared with future developments. The set of tests performed, can therefore serve as a benchmarking procedure for future algorithms. [less ▲]

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See detailConstraint based modelling going multicellular
Martins Conde, Patricia UL; Sauter, Thomas UL; Pfau, Thomas UL

in Frontiers in Molecular Biosciences (2016), 3(3),

Constraint based modelling has seen applications in many microorganisms. For example, there are now established methods to determine potential genetic modifications and external interventions to increase ... [more ▼]

Constraint based modelling has seen applications in many microorganisms. For example, there are now established methods to determine potential genetic modifications and external interventions to increase the efficiency of microbial strains in chemical production pipelines. In addition, multiple models of multicellular organisms have been created including plants and humans. While initially the focus here was on modelling individual cell types of the multicellular organism, this focus recently started to switch. Models of microbial communities, as well as multitissue models of higher organisms have been constructed. These models thereby can include different parts of a plant, like root, stem or different tissue types in the same organ. Such models can elucidate details of the interplay between symbiotic organisms, as well as the concerted efforts of multiple tissues and can be applied to analyse the effects of drugs or mutations on a more systemic level. In this review we give an overview of the recent development of multi-tissue models using constraint based techniques and the methods employed when investigating these models. We further highlight advances in combining constraint based models with dynamic and regulatory information and give an overview of these types of hybrid or multi-level approaches. [less ▲]

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See detailInsight into metabolic pathways of the potential biofuel producer, Paenibacillus polymyxa ICGEB2008
Adlakha, Nidhi; Pfau, Thomas UL; Ebenhöh, Oliver et al

in Biotechnology for Biofuels (2015), 8(159),

Background Paenibacillus polymyxa is a facultative anaerobe known for production of hydrolytic enzymes and various important biofuel molecules. Despite its wide industrial use and the availability of its ... [more ▼]

Background Paenibacillus polymyxa is a facultative anaerobe known for production of hydrolytic enzymes and various important biofuel molecules. Despite its wide industrial use and the availability of its genome sequence, very little is known about metabolic pathways operative in the Paenibacillus system. Here, we report metabolic insights of an insect gut symbiont, Paenibacillus polymyxa ICGEB2008, and reveal pathways playing an important role in the production of 2,3-butanediol and ethanol. Result We developed a metabolic network model of P. polymyxa ICGEB2008 with 133 metabolites and 158 reactions. Flux balance analysis was employed to investigate the importance of redox balance in ICGEB2008. This led to the detection of the Bifid shunt, a pathway previously not described in Paenibacillus, which can uncouple the production of ATP from the generation of reducing equivalents. Using a combined experimental and modeling approach, we further studied pathways involved in 2,3-butanediol and ethanol production and also demonstrated the production of hydrogen by the organism. We could further show that the nitrogen source is critical for metabolite production by Paenibacillus, and correctly quantify the influence on the by-product metabolite profile of ICGEB2008. Both simulations and experiments showed that metabolic flux is diverted from ethanol to acetate production when an oxidized nitrogen source is utilized. Conclusion We have created a predictive model of the central carbon metabolism of P. polymyxa ICGEB2008 and could show the presence of the Bifid shunt and explain its role in ICGEB2008. An in-depth study has been performed to understand the metabolic pathways involved in ethanol, 2,3-butanediol and hydrogen production, which can be utilized as a basis for further metabolic engineering efforts to improve the efficiency of biofuel production by this P. polymyxa strain. [less ▲]

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See detailTowards improved genome-scale metabolic network reconstructions: unification, transcript specificity and beyond.
Pfau, Thomas UL; Pacheco, Maria Irene UL; Sauter, Thomas UL

in Briefings in bioinformatics (2015)

Genome-scale metabolic network reconstructions provide a basis for the investigation of the metabolic properties of an organism. There are reconstructions available for multiple organisms, from ... [more ▼]

Genome-scale metabolic network reconstructions provide a basis for the investigation of the metabolic properties of an organism. There are reconstructions available for multiple organisms, from prokaryotes to higher organisms and methods for the analysis of a reconstruction. One example is the use of flux balance analysis to improve the yields of a target chemical, which has been applied successfully. However, comparison of results between existing reconstructions and models presents a challenge because of the heterogeneity of the available reconstructions, for example, of standards for presenting gene-protein-reaction associations, nomenclature of metabolites and reactions or selection of protonation states. The lack of comparability for gene identifiers or model-specific reactions without annotated evidence often leads to the creation of a new model from scratch, as data cannot be properly matched otherwise. In this contribution, we propose to improve the predictive power of metabolic models by switching from gene-protein-reaction associations to transcript-isoform-reaction associations, thus taking advantage of the improvement of precision in gene expression measurements. To achieve this precision, we discuss available databases that can be used to retrieve this type of information and point at issues that can arise from their neglect. Further, we stress issues that arise from non-standardized building pipelines, like inconsistencies in protonation states. In addition, problems arising from the use of non-specific cofactors, e.g. artificial futile cycles, are discussed, and finally efforts of the metabolic modelling community to unify model reconstructions are highlighted. [less ▲]

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See detailModelling Metabolic Interactions in the Legume-Rhizobia Symbiosis
Pfau, Thomas UL

Doctoral thesis (2013)

With the emergence of “omics” techniques, it has become essential to develop tools to utilise the vast amount of data produced by these methods. Genome-scale metabolic models represent the mathematical ... [more ▼]

With the emergence of “omics” techniques, it has become essential to develop tools to utilise the vast amount of data produced by these methods. Genome-scale metabolic models represent the mathematical essence of metabolism and can easily be linked to the data from omics sources. Such models can be used for various analyses, including the investigation of metabolic responses to changing environmental conditions. Legumes are known for their ability to form a nitrogen-fixing symbiosis with rhizobia, a vital process that provides the biosphere with the majority of its nitrogen content. In the present thesis, a genome-scale metabolic model for the legume Medicago truncatula was reconstructed, based on the annotated genome sequence and the MedicCyc database. A novel approach was employed to define the compartmentalisation of the plant’s metabolism. The model was used to calculate the biosynthetic costs of biomass precursors (e.g. amino acids, sugars, fatty acids, nucleotides), and its capability to produce biomass in experimentally observed ratios was demonstrated using flux balance analysis. Further investigation was carried out into how the biosynthesis fluxes and costs change with respect to different nitrogen sources. The precise charge balancing of all reactions in the model allowed the investigation of the effects of charge transport over the cellular membrane. The simulations showed a good agreement with experimental data in using different sources of nitrogen (ammonium and nitrate) to minimise the charge transport of the membrane. To allow the investigation of the symbiotic relationship, two rhizobial models were used. The first model, for Sinorhizobium meliloti, was reconstructed from the MetaCyc database (MC-model); the second model was a recently published model for S. meliloti specialised for symbiotic nitrogen fixation (SNF-model). Combined models were created for both rhizobial networks using a specialised nodule submodel of the plant model. Potential interactions were extracted from the literature and investigated, with the analysis suggesting that oxygen availability is the main limitation factor in symbiotic nitrogen fixation. Within the analysis the SNF-model appeared to be too restricted and lacking the potential for sufficient nitrogen fixation; therefore, further analysis was carried out using the MC-model, upon which it was observed that the availability of oxygen can also influence how nitrogen is supplied to the plant. At high oxygen concentrations ammonia is the primary form of nitrogen supplied by the rhizobium. However, the simulations, in accordance with experimental data, show that at lower concentrations of oxygen, alanine takes precedence. The findings also support the concept of amino acid cycling as a potential way to improve nitrogen fixation. The more flexible MetaCyc based model has allowed other potential genetic engineering approaches for higher nitrogen fixation yields to be proposed. [less ▲]

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See detailSystems approaches to modelling pathways and networks
Pfau, Thomas UL; Christian, Nils UL; Ebenhöh, Oliver

in Briefings in Functional Genomics (2011), 10(5), 266-279

It has become commonly accepted that systems approaches to biology are of outstanding importance to gain understanding from the vast amount of data which is presently being generated by advancing high ... [more ▼]

It has become commonly accepted that systems approaches to biology are of outstanding importance to gain understanding from the vast amount of data which is presently being generated by advancing high-throughput technologies. The diversity of methods to model pathways and networks has significantly expanded over the past two decades. Modern and traditional approaches are equally important and recent activities aim at integrating the advantages of both. While traditional methods, based on differential equations, are useful to study the dynamics of small systems, modern constraint-based models can be applied to genome-scale systems, but are not able to capture dynamic features. Integrating different approaches is important to develop consistent theoretical descriptions encompassing various scales of biological information. The rapid progress of the field of theoretical systems biology, however, demonstrates how our fundamental theoretical understanding of biology is gaining momentum. The scientific community has apparently accepted the challenge to truly understand the principles of life. [less ▲]

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