MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models

TL;DR

MetaboTools provides a comprehensive MATLAB-based toolbox and protocol for integrating and analyzing extracellular metabolomic data within genome-scale metabolic models, facilitating phenotype stratification and broader biological insights.

Contribution

This work introduces a complete workflow, toolbox, and tutorials for the computational analysis of metabolomic data in the context of metabolic models, accessible to the scientific community.

Findings

Supports integrative analysis of multiple omics datasets

Enables phenotype stratification based on metabolomic data

Provides tools applicable without full workflow execution

Abstract

Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Our previous work revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. Through this work, which consists of a protocol, a toolbox, and tutorials of two use cases, we make our methods available to the broader scientific community. 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, this protocol constitutes a comprehensive guide to the intra-model analysis of extracellular metabolomic data and a resource offering a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.