Application of circuit simulation method for differential modeling of TIM-2 iron uptake and metabolism in mouse kidney cells - Xie, Zhijian; Harrison, Scott H.; Torti, Suzy V.; Torti, Frank M.; Han, Jian (Frontiers in Physiology, 2013)
Circuit simulation is a powerful methodology to generate differential mathematical models. Due to its highly accurate modelling capability, circuit simulation can be used to investigate interactions between the parts and processes of a cellular system. Circuit simulation has become a core technology for the field of electrical engineering, but its application in biology has not yet been fully realized. As a case study for evaluating the more advanced features of a circuit simulation tool called Advanced Design System (ADS), we collected and modeled laboratory data for iron metabolism in mouse kidney cells for a H ferritin (HFt) receptor, T cell immunoglobulin and mucin domain-2 (TIM-2). The internal controlling parameters of TIM-2 associated iron metabolism were extracted and the ratios of iron movement among cellular compartments were quantified by ADS. The differential model processed by circuit simulation demonstrated a capability to identify variables and predict outcomes that could not be readily measured by in vitro experiments. For example, an initial rate of uptake of iron-loaded HFt was 2.17 pmol per million cells. TIM-2 binding probability with iron-loaded HFt was 16.6%. An average of 8.5 minutes was required for the complex of TIM-2 and iron-loaded HFt to form an endosome. The endosome containing HFt lasted roughly 2 hours. At the end of endocytosis, about 28% HFt remained intact and the rest was degraded. Iron released from degraded HFt was in the labile iron pool (LIP) and stimulated the generation of endogenous HFt for new storage. Both experimental data and the model showed that TIM-2 was not involved in the process of iron export. The extracted internal controlling parameters successfully captured the complexity of TIM-2 pathway and the use of circuit simulation-based modeling across a wider range of cellular systems is the next step for validating the significance and utility of this method.