Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0.

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 ▲]

DEVELOPMENT OF A COMPUTATIONAL RESOURCE FOR PERSONALIZED DIETARY RECOMMENDATIONS

Doctoral thesis (2018)

There is a global increase in the incidence of non-communicable diseases associated with unhealthy food intakes. Conditions such as diabetes, heart disease, high blood pressure, and strokes represent a ... [more ▼]

There is a global increase in the incidence of non-communicable diseases associated with unhealthy food intakes. Conditions such as diabetes, heart disease, high blood pressure, and strokes represent a high societal impact and an economic burden for health-care systems around the world. To understand these diseases, one needs to account the several factors that influence how the human body processes food, some of which are determined by the genome and patterns of gene expression that translate to the ability - or lack of - to degrade and absorb certain nutrients. Other factors, like the gut microbiota, are more volatile because its composition is highly moldable by diet and lifestyle. Multi-omics technologies can support the comprehensive collection of dietary intake data and monitoring of the health status of individuals. Also, a correct analysis of this data could lead to new insights about the complex processes involved in the digestion of dietary components and their involvement in the prevention or the appearance of health problems, but its integration and interpretation are still problematic. Thus, in this thesis, we propose the utilization of Constraint-Based Reconstruction and Analysis (COBRA) methods as a framework for the integration of this complex data. To achieve this goal, we have created a knowledge-base, the Virtual Metabolic Human (VMH), that combines information from large-scale models of metabolism from the human organism and typical gut microbes, with food composition information, and a disease compendium. VMH’s unique combination of resources leverages the exploration of metabolic pathways from different organisms, the inclusion of dietary information into in-silico experiments through its own diet designer tool, visualization and analysis of experimental and simulation data, and exploring disease mechanisms and potential treatment strategies. VMH is a step forward in providing the necessary tools to investigate the mechanisms behind the influence of diet in health and disease. Tools such as the diet designer can be used as a basis for diet optimization by predicting combinations of foods that can contribute to specific metabolic outcomes, which has the potential to be integrated and translated into treatment development and dietary recommendations in the foreseeable future. [less ▲]

Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D

in Journal of Cheminformatics (2017)

The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a ... [more ▼]

The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, many algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice. [less ▲]

Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota

in Nature Biotechnology (2016)

Genome-scale metabolic models derived from human gut metagenomic data can be used as a framework to elucidate how microbial communities modulate human metabolism and health. We present AGORA (assembly of ... [more ▼]

Genome-scale metabolic models derived from human gut metagenomic data can be used as a framework to elucidate how microbial communities modulate human metabolism and health. We present AGORA (assembly of gut organisms through reconstruction and analysis), a resource of genome-scale metabolic reconstructions semi-automatically generated for 773 human gut bacteria. Using this resource, we identified a defined growth medium for Bacteroides caccae ATCC 34185. We also showed that interactions among modeled species depend on both the metabolic potential of each species and the nutrients available. AGORA reconstructions can integrate either metagenomic or 16S rRNA sequencing data sets to infer the metabolic diversity of microbial communities. AGORA reconstructions could provide a starting point for the generation of high-quality, manually curated metabolic reconstructions. AGORA is fully compatible with Recon 2, a comprehensive metabolic reconstruction of human metabolism, which will facilitate studies of host–microbiome interactions. [less ▲]

Do Genome-scale Models Need Exact Solvers or Clearer Standards?

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

Network Visualization Tools to Enhance Metabolic Engineering Platforms

in 7th International Conference on Practical Applications of Computational Biology & Bioinformatics (2013)

In this work, we present a software platform for the visualization of metabolic models, which is implemented as a plug-in for the open-source metabolic engineering (ME) platform OptFlux. The tools ... [more ▼]

In this work, we present a software platform for the visualization of metabolic models, which is implemented as a plug-in for the open-source metabolic engineering (ME) platform OptFlux. The tools provided by this plug-in allow the visualization of the models (or parts of the models) combined with the results from operations applied over these models, mainly regarding phenotype simulation, strain optimization and pathway analysis. The tool provides a generic input/ output framework that can import/ export layouts from different formats used by other tools, namely XGMML and SBML. Thus, this work provides a bridge between network visualization and ME. [less ▲]