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Determining which siderophores siderocalin binds can help elucidate the relevant molecular interactions and the function of the protein as an antagonist for siderophore-mediated iron transport. The specificity of siderocalin for a variety of siderophores and analogs is being probed in this collaboration with the research group of Dr. Roland Strong. Siderocalin binds ferric enterobactin with an affinity close to that of the bacterial outer membrane receptor protein, FepA, however, the binding specificity of siderocalin differs notably from that of FepA. We have determined that the binding of ferric enterobactin by siderocalin is not significantly altered by changing the metal center, the siderophore scaffold or the chirality of the metal complex, but substitution of the 5' position on the catecholate rings can introduce enough steric hindrance to preclude protein binding.

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Despite the great efficiency of these catecholate ligands at chelating iron, independent synthesis of additional stealth siderophores like aerobactin, salmochelin or petrobactin, which can evade siderocalin binding, is necessary to ensure full virulence of the lethal pathogens. The arms race between the mammalian immune system and bacteria in the search for iron: enterobactin removes iron from transferrin a , siderocalin intercepts the ferric complex of enterobactin b , bacteria produce alternative siderophores such as salmochelin S4 c.

Current work in our lab focuses on synthesizing siderophore analogs to further probe the specificity of the protein and to characterize spectroscopically the interactions between the protein and its substrates. We are also investigating the effect of siderocalin and similar proteins on the growth of different human pathogens.

Raymond Group: Coordination Chemistry of Biological Iron Transport Agents

Hoette, T. Goetz, D. Cell , 10 , Cover article.

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Flo, T. Nature , , Fischbach, M. Mammalian Siderophores and Siderocalin. Aside from its bacteriostatic role, siderocalin is upregulated in other mammalian processes such as embryonic kidney development, apoptosis, and ischemia. In cases where non-bacterial stimuli induce the expression of siderocalin, we suspect that an equivalent of a mammalian siderophore exists in order to optimize the role that siderocalin plays in iron regulation. While mammals do not synthesize their own siderophores, bacterial and mammalian catecholate metabolites are often found in the body.

These simple catechols are similar to the binding moieties of natural bacterial siderophores such as enterobactin and bacillibactin. We have shown that simple catechols isolated from human urine exhibit proportional increases in concentration along with siderocalin expression in urine. Ongoing studies are dedicated to finding mammalian siderophores that bind iron and siderocalin, contributing to our understanding of the role of siderocalin in non-bacteriostatic mammalian processes.

Methods Values for all initial model variables and parameters are listed in tables described later in the document. Transferrin binding to transferrin receptor To estimate the differential binding rates of mono- and di-ferric transferrin to transferrin receptor , we used in vitro cell-culture data [ 40 , 65 — 67 ]. Model parameters were estimated using experimental data associated with the following perturbations applied to the basic model: Phlebotomy produces a loss of blood volume that leads to changes in serum hemoglobin and Epo concentrations.

This experiment allows calibration of changes in Epo synthesis and secretion in response to changes in serum hemoglobin. Iron ingestion increases serum iron levels and Hepc synthesis leading to increased serum Hepc. This experiment allows calibration of the dose response of Hepc synthesis and secretion in response to changes in serum iron and the rate of degradation of FPN by Hepc. This experiment performed in mice allows estimation of the half-life of FPN which is crucial for simulation of long-term changes in FPN levels in vivo.

Differences in model parameters between mouse and human are listed in Table 7.

Structure of an iron-transport protein revealed

Anemia of CKD leads to loss of sensitivity of Epo synthesis to changes in serum hemoglobin and decrease in baseline Epo synthesis. Table 7. Parameter values from literature different between human and mouse model. System perturbations for parameter estimation From the transient model, a steady state is reached by simulating the model for a long time. This provides initial conditions for the following perturbations: Phlebotomy. Iron ingestion. Drug injection.

Regulation of cellular iron metabolism

Injection of rhHepc. Injection of rEpo. Table 8. Estimated parameters for pharmacokinetics and pharmacodynamics of rEpo. Results We applied our mechanistic model of iron metabolism to quantitatively analyze differences in the status of iron metabolism in chronic kidney disease CKD with anemia before and after treatment. Phlebotomy responses After phlebotomy, the time course of Epo concentration in plasma and in hematocrit over 60 days has been measured [ 25 ]. For comparison with data, hematocrit was evaluated from model-simulated RBC and plasma volumes: 69 The data for hematocrit and Epo in plasma were normalized to initial values to compensate for differences in steady-state values.

Table 9. Parameter values estimated based on experimental data. Responses to rhHepc injection In a mouse model of iron metabolism [ 71 ], changes of rhHepc and serum iron were measured after injection of 50, Table Estimated parameter for mouse pharmacokinetics of rhHepc. Responses to iron ingestion Simulations of the iron ingestion experiment conducted on healthy human subjects by Girelli et al [ 50 ] incorporate all parameter values estimated via different perturbations and experiments e.

Application and limitations of experimental data With this global model involving a large number of variables and parameters and limited experimental data, the model validation process cannot be exhaustive.


Single vs ensemble predictions In the simulation of CKD with treatments, only the best calibrated model was used for all simulations. Conclusion and future studies This multi-scale, whole-body model of iron metabolism not only simulates data from a wide range of experimental studies, but also predicts novel responses that have not been observed. Supporting information.

S1 Fig. Pharmacokinetic model incorporating absorption, distribution and elimination of rhHepc and rEpo. S2 Fig. S3 Fig. S4 Fig. Comparison of the model output solid line vs. S5 Fig. S6 Fig. S7 Fig. Represents model simulation of development of anemia of chronic kidney disease. S1 Data.

References 1. Brock JH. Iron Metabolism in Health and Disease. London: W. Saunders Company Ltd; Iron metabolism. Curr Opin Chem Biol.

12.72 Iron Transport & Storage

Knutson M, Wessling-Resnick M. Iron metabolism in the reticuloendothelial system. Crit Rev Biochem Mol Biol. Wessling-Resnick M. Biochemistry of iron uptake.

Aisen P, Listowsky I. Iron transport and storage proteins.

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Annu Rev Biochem. Marshall A. Lichtman EB, Thomas J. Prchal Williams Hematology. Epub 7th edition.