Metadag: a web tool to generate and analyse metabolic networks

Abstract

[eng] Background: MetaDAG is a web-based tool developed to address challenges posedby big data from omics technologies, particularly in metabolic network reconstructionand analysis. The tool is capable of constructing metabolic networks for specificorganisms, sets of organisms, reactions, enzymes, or KEGG Orthology (KO) identifiers.By retrieving data from the KEGG database, MetaDAG helps users visualize and analyzecomplex metabolic interactions efficiently.Results: MetaDAG computes two models: a reaction graph and a metabolic directedacyclic graph (m-DAG). The reaction graph represents reactions as nodes and metaboliteflow between them as edges. The m-DAG simplifies the reaction graph by collapsingstrongly connected components, significantly reducing the number of nodeswhile maintaining connectivity. MetaDAG can generate metabolic networks from variousinputs, including KEGG organisms or custom data (e.g., reactions, enzymes, KOs).The tool displays these models on an interactive web page and provides downloadablefiles, including network visualizations. MetaDAG was tested using two datasets.In an eukaryotic analysis, it successfully classified organisms from the KEGG databaseat the kingdom and phylum levels. In a microbiome study, MetaDAG accurately distinguishedbetween Western and Korean diets and categorized individuals by weight lossoutcomes based on dietary interventions.Conclusion: MetaDAG offers an effective and versatile solution for metabolic networkreconstruction from diverse data sources, enabling large-scale biological comparisons.Its ability to generate synthetic metabolisms and its broad application, from taxonomyclassification to diet analysis, make it a valuable tool for biological research. MetaDAGis available online, with user support provided via a comprehensive guide. MetaDAG:https:// bioin fo. uib. es/ metad ag/ User guide: https:// biocom-​uib. github. io/ MetaD ag/