Toward a Proteome-Complete Computational Model of the Human Red Blood Cell

The human red blood cell has served as a starting point for the application and development of systems biology approaches due to its simplicity, intrinsic experimental accessibility, and importance in human health applications. Here, we present a multi-scale computational model of the human red blood cell that accounts for metabolism and macromolecules. Proteomics data are used to place quantitative constraints on individual protein complexes that catalyze metabolic reactions, as well as a total proteome capacity constraint. We explicitly describe molecular mechanisms-such as hemoglobin binding and the formation and detoxification of reactive oxygen species-and account for sequence variations between individuals, allowing for personalized physiological predictions. This model allows for direct computation of the oxyhemoglobin curve as a function of model species and a more accurate computation of the flux state of the metabolic network. More broadly, this work represents another step toward building increasingly more complete systems biology whole-cell models.