XomicsToModel: Multiomics data integration and generation of thermodynamically consistent metabolic models

Abstract

AbstractConstraint-based modelling can mechanistically simulate the behaviour of a biochemical system, permitting hypotheses generation, experimental design and interpretation of experimental data, with numerous applications, including modelling of metabolism. Given a generic model, several methods have been developed to extract a context-specific, genome-scale metabolic model by incorporating information used to identify metabolic processes and gene activities in a given context. However, existing model extraction algorithms are unable to ensure that the context-specific model is thermodynamically feasible. This protocol introduces XomicsToModel, a semi-automated pipeline that integrates bibliomic, transcriptomic, proteomic, and metabolomic data with a generic genome-scale metabolic reconstruction, or model, to extract a context-specific, genome-scale metabolic model that is stoichiometrically, thermodynamically and flux consistent. The XomicsToModel pipeline is exemplified for extraction of a specific metabolic model from a generic metabolic model, but it enables multi-omic data integration and extraction of physicochemically consistent mechanistic models from any generic biochemical network. With all input data fully prepared, algorithmic completion of the pipeline takes ~10 min, however manual review of intermediate results may also be required, e.g., when inconsistent input data lead to an infeasible model.