Systems-level physiology of the human red blood cell is computed from metabolic and macromolecular mechanisms

Abstract

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 the full metabolic network, key proteins (>95% of proteome mass fraction), and several macromolecular mechanisms. 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 takes standard hematological variables (e.g., hematocrit, hemoglobin concentration) as input, allowing for personalized physiological predictions. This model is built from first principles and allows for direct computation of physiologically meaningful quantities such as the oxygen dissociation curve and an accurate computation of the flux state of the metabolic network. More broadly, this work represents an important step toward including the proteome and its function in whole-cell models of human cells.