Sachie Yamaji

Zinc regulates the function and expression of the iron transporters DMT1 and IREG1 in human intestinal Caco-2 cells

Trace metals influence the absorption of each other from the diet and it has been suggested that the divalent metal transporter (DMT1) represents a common uptake pathway for these important micronutrients. However, compelling evidence from our laboratory suggests that DMT1 is predominantly an iron transporter, with lower affinity for other metals. Several studies have shown that increasing dietary iron downregulates DMT1. Interestingly, our current data indicate that zinc upregulates DMT1 protein and mRNA expression and also pH‐dependent iron uptake. Transepithelial flux of iron was also increased and was associated with a rise in IREG1 mRNA expression.

Effects of copper on the expression of metal transporters in human intestinal Caco-2 cells.

Copper is an essential dietary trace metal, however the mechanisms involved in intestinal copper uptake are unclear. Two putative copper transporters are expressed in Caco‐2 cells, the divalent metal transporter (DMT1) and copper transporter (Ctr1). Our data demonstrate that copper could compete with iron for uptake via DMT1 and that DMT1 protein and mRNA expression were decreased following exposure (24 h) to high copper. Expression of Ctr1, which acts as a copper transporter in transfected cell lines, was unaffected by copper treatment. Interestingly, exposure to copper increased iron efflux from Caco‐2 cells and up regulated IREG1 (iron‐regulated mRNA) expression.

Rapid regulation of divalent metal transporter (DMT1) protein but not mRNA expression by non-haem iron in human intestinal Caco-2 cells

A divalent metal transporter, DMT1, located on the apical membrane of intestinal enterocytes is the major pathway for the absorption of dietary non‐haem iron. Using human intestinal Caco‐2 TC7 cells, we have shown that iron uptake and DMT1 protein in the plasma membrane were significantly decreased by exposure to high iron for 24 h, in a concentration‐dependent manner, whereas whole cell DMT1 protein abundance was unaltered. This suggests that part of the response to high iron involved redistribution of DMT1 between the cytosol and cell membrane. These events preceded changes in DMT1 mRNA, which was only decreased following 72 h exposure to high iron.

Regulation of divalent metal transporter expression in human intestinal epithelial cells following exposure to non-haem iron

A number of regulatory factors including dietary iron levels can dramatically alter the expression of the intestinal iron transporter DMT1. Here we show that Caco‐2 cells exposed to iron for 4 h exhibited a significant decrease in plasma membrane DMT1 protein, though total cellular DMT1 levels were unaltered. Following biotinylation of cell surface proteins, there was a significant increase in intracellular biotin‐labelled DMT1 in iron‐exposed cells. Furthermore, iron‐treatment increased levels of DMT1 co‐localised with LAMP1, suggesting that the initial response of intestinal epithelial cells to iron involves internalisation and targeting of DMT1 transporter protein towards a late endosomal/lysosomal compartment.

Addressing the challenges of multiscale model management in systems biology

Mathematical and computational modelling are emerging as important techniques for studying the behaviour of complex biological systems. We argue that two advances are necessary to properly leverage these techniques: firstly, the ability to integrate models developed and executed on separate tools, without the need for substantial translation and secondly, a comprehensive system for storing and man-ageing not only the models themselves but also the parameters and tools used to execute those models and the results they produce. A framework for modelling with these features is described here. We have developed of a suite of XML-based services used for the storing and analysis of models, model parameters and results, and tools for model integration. We present these here, and evaluate their effectiveness using a worked example based on part of the hepatocyte glycogenolysis system.

A composite computational model of liver glucose homeostasis. I. Building the composite model

A computational model of the glucagon/insulin-driven liver glucohomeostasis function, focusing on the buffering of glucose into glycogen, has been developed. The model exemplifies an ‘engineering’ approach to modelling in systems biology, and was produced by linking together seven component models of separate aspects of the physiology. The component models use a variety of modelling paradigms and degrees of simplification. Model parameters were determined by an iterative hybrid of fitting to high-scale physiological data, and determination from small-scale in vitro experiments or molecular biological techniques. The component models were not originally designed for inclusion within such a composite model, but were integrated, with modification, using our published modelling software and computational frameworks. This approach facilitates the development of large and complex composite models, although, inevitably, some compromises must be made when composing the individual models. Composite models of this form have not previously been demonstrated.

A composite computational model of liver glucose homeostasis. II. Exploring system behaviour

Using a composite model of the glucose homeostasis system, consisting of seven interconnected submodels, we enumerate the possible behaviours of the model in response to variation of liver insulin sensitivity and dietary glucose variability. The model can reproduce published experimental manipulations of the glucose homeostasis system and clearly illustrates several important properties of glucose homeostasis—boundedness in model parameters of the region of efficient homeostasis, existence of an insulin sensitivity that allows effective homeostatic control and the importance of transient and oscillatory behaviour in characterizing homeostatic failure. Bifurcation analysis shows that the appearance of a stable limit cycle can be identified.

End-to-end information management for systems biology

Mathematical and computational modelling are research areas with increasing importance in the study of behaviour in complex biological systems. With the increasing breadth and depth of models under consideration, a disciplined approach to managing the diverse data associated with these models is needed. Of particular importance is the issue of provenance, where a model result is linked to information about the generating model, the parameters used in that model and the papers and experiments that were used to derive those parameters. This paper presents an architecture to manage this information along with accompanying tool support and examples of the management system in use at various points in the development of a large model.