MetaboTools: A Comprehensive Toolbox for Analysis of Genome-Scale Metabolic Models

Abstract

Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration, and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorials explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. This computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.

The Virtual Metabolic Human database: integrating human and gut microbiome metabolism with nutrition and disease

“…These reconstructions are provided in multiple standard formats (e.g., SBML) for download and allow for access to the entire knowledge base via the API and enable the in silico formulation of personalized diets via the "Diet designer", which can then directly be integrated with the human or microbial metabolic reconstructions using the COBRA Toolbox 13 . Simulation results based on these diets 36,62,63 or based on the integration of omics data, e.g., metabolomics 12 and transcriptomics 64 , can then be visualized and interpreted in the context of human metabolic and disease-specific maps, thus providing a more comprehensive, systems-level understanding of the modeled system.…”

“…Genome-scale metabolic reconstructions have been generated for representatives of all domains of life, including humans 5 and gut microbes [6][7][8][9] . Importantly, these metabolic reconstructions can be converted into computational models using condition-specific information, e.g., transcriptomic 10 or metabolomic data 11,12 . Open-access, community-developed toolboxes, such as the Constraint-Based Reconstruction and Analysis (COBRA) Toolbox 13 , facilitate simulations with metabolic models that permit us to address a variety of biomedical and biotechnological questions in silico 14,15 .…”

Systematic interrogation of the distinct metabolic potential in gut microbiomes of inflammatory bowel disease patients with dysbiosis

“…This will enable the prediction of microbial species contributing to the human blood, urine, and tissue metabolome. Additionally, metabolomic measurements can serve as constraints for the further contextualization of personalized models (Aurich et al, 2016) allowing further insight into the mechanisms behind host-microbe co-metabolism.…”

Seeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling

“…Therefore, extracellular metabolomic measurements can help to predict intracellular flux states by integrating these data into a constraint-based framework using a sampling-based network approach [49,50]. The MetaboTools toolbox provides a workflow for integrating metabolomic data into multi-omic models and predicting metabolic phenotypes through analysing how metabolite uptake and secretion differ between conditions [48].…”