Reconstruction and validation of a constraint-based metabolic network model for bone marrow-derived mesenchymal stem cells

Abstract

Objectives: In recent years, constraint-based modeling of metabolic networks has become increasingly popular. These metabolic network models are suitable for systems-level modeling of cell physiology. The goal of the present work is to reconstruct a constraint-based metabolic network model of bone marrow-derived mesenchymal stem cells (BMMSCs). Materials and methods: In order to reconstruct a BMMSC-specific metabolic model, transcriptomic data of BMMSCs, and additionally, the human generic metabolic network model (Recon1) were used. Then, using mCADRE algorithm, a draft metabolic network of BMMSC was reconstructed. Literature and proteomic data were subsequently used to refine and improve the draft. From this, iMSC1255 was derived as the metabolic network model of BMMSCs. Results: iMSC1255 includes 1255 genes, 1850 metabolites and 2288 reactions. After including additional constraints based on previously reported experimental results, our model successfully predicted the BMMSC growth rate and metabolic phenotypes. Conclusions: In conclusion, in this work iMSC1255 is introduced as the metabolic network model of mesenchymal stem cells. Based on current knowledge, this work is the first report on genome-scale reconstruction and validation of a stem cell metabolic network model.