Standardization of Human Metabolic Stoichiometric Models: Challenges and Directions

Abstract

Genome-scale metabolic network models are of great importance in systems biology research, as they are used in metabolic activity dynamics studies and provide the metabolic level representation in multi-omic investigations. Especially for human, accurate metabolic network reconstruction is important in biomedical research and drug discovery. Today, there exist many instances of the human metabolic network as a whole and in its tissue-specific versions. Some are improved updates of models reconstructed from the same research team, while others are combinations of models from various teams, in an effort to include all available information from genome annotation and omic datasets. A major challenge regarding the human stoichiometric models in particular is the standardization of the reconstruction methods, representation formats and model repositories. Stoichiometric model standardization will enable the educated selection of the model that better fits the goals of a study, the direct comparison of results from various flux analysis studies and the identification of model sections that require reconsideration and updating with respect to the annotation of the human genome and proteome. Standardized human metabolic models aligned to the human genome will be a very useful tool in multi-omic studies, enabling the direct and consistent integration of the metabolic with the gene regulation and protein interaction networks. In this work, we provide a thorough overview of the current collection of human metabolic stoichiometric models, describe the current issues regarding their direct comparison and alignment in the context of the various model repositories, exposing the standardization needs, and propose potential solutions.