Systems biology analysis
of iron metabolism

Dissertation

zur Erlangung des akademischen Grades
doctor rerum naturalium
( Dr. rer. nat.)
im Fach Biophysik

eingereicht an der
Mathematisch-Naturwissenschaftlichen Fakultät I
der Humboldt-Universität zu Berlin

von

Herrn Tiago Jose   da Silva Lopes

Präsident der Humboldt-Universität zu Berlin
Prof. Dr. Dr. h.c. Christoph Markschies

Dekan der Mathematisch-Naturwissenschaftlichen Fakultät I
Prof. Dr. Andreas Herrmann

Gutachter:
1. Prof. Edda Klipp
2. Prof. Martina Muckenthaler
3. Prof. Hermann-Georg Holzhutter

Tag der mündlichen Prüfung: 05.December.2010

Widmung:

For my family. For my friends from the past, present and future.

Chapter 1

Inhaltsverzeichnis

• 1 - Introduction
• 2 - Models and Experimental Methods
  • 2.1 General Structure of Iron Metabolism 
  • 2.2 General Flux Network of Iron in the Organism 
  • 2.3 Iron balance: absorption from duodenum and loss from the body 
  • 2.4 Numerical Scales of Pools and Turnover Rates.
    • 2.4.1 Scaling of iron content to the whole mouse organism
    • 2.4.2  Contribution of organs and tissues to whole body mass
    • 2.4.3 Upscaling of iron content to the whole organism  
  • 2.5 Ferrokinetic study of tracer distribution 
    • 2.5.1 Experimental Setting 
    • 2.5.2 Raw data corrected for blood content
    • 2.5.3 Averaged tracer content in the intestine
    • 2.5.4 Normalization of the data set
    • 2.5.5 Mathematical structure of the compartment model of tracer distribution
    • 2.5.6 Clearance mode of model description and derivation of motion equations.
    • 2.5.7 Residence time
  • 2.6 System of Ordinary Differential Equations for Tracer Motion 
  • 2.7 Parameter optimization pipeline 
    • 2.7.1 Parameter Estimation by Convergence from different Starting Points
    • 2.7.2 Quality of final fit 
    • 2.7.3 The problem of interdependence of parameter estimates
  • 2.8 Flux rates and pools sizes derived from clearance parameters
    • 2.8.1 Calculation of absolute flux rates from fractional clearances 
    • 2.8.2 Estimation of peripheral pool size from countercurrent clearance parameters and plasma pool 
    • 2.8.3 Scaling of the system variables and parameters 
  • 2.9 The Cellular Model of Iron Metabolism
    • 2.9.1 Transfer across the cell membrane
    • 2.9.2 Intracellular processes
  • 2.10  Iron flux network
    • 2.10.1 Intracellular and transmembrane iron flux 
  • 2.11 Regulated turnover of iron-processing macromolecules
  • 2.12 Nomenclature: variables and rates
  • 2.13 Balance equations
    • 2.13.1 Balance equations in the plasma compartment
    • 2.13.2 Balance equations in the cell, with cell type parameter specification
  • 2.14 Rate equations of iron transfer between iron-processing proteins 
  • 2.15 Kinetic Description of Iron-Transfer and Regulatory Signals
  • 2.16 Modelling the hepcidin effect on ferroportin expression
  • 2.17 Rate equations of iron uptake and iron release by the cell
  • 2.18 Rate equations of internal transfer
  • 2.19 Rate equations of combined transcription/translation (protein biosynthesis)
  • 2.20 Rate equations of protein degradation
  • 2.21 Kinetics expressions for autocrine and endocrine signalling
  • 2.22 Parameter portrait to simulate physiological or pathological deviation
  • 2.23 Numerical solution of dynamic systems (ordinary differential equations)
• 3 - Results
  • 3.1 Plasma Iron Pool
    • 3.1.1 Tracer uptake into murine Organs
    • 3.1.2 The Erythropoietic System
    • 3.1.3 Compartment size of Tracer-Accessible Peripheral Pools
    • 3.1.4 Hierarchy of Iron Residence Times in Different Organs
    • 3.1.5 Comparison of Tracer-accessible pools with unlabelled non-heme
    • 3.1.6 Iron Excretion from the body 
  • 3.2 Simulation Studies with the Cellular Model
    • 3.2.1 Simulation of Chronic Blood Loss
    • 3.2.2 Erythropoiesis
    • 3.2.3 Recycling of iron
    • 3.2.4 Storage
    • 3.2.5 Absorption
    • 3.2.6 Excretion
    • 3.2.7 The new steady state
  • 3.3 Analysis of changes in dietary iron supply
    • 3.3.1 Absorption
    • 3.3.2 Erythropoiesis
    • 3.3.3 Recycling
    • 3.3.4 Storage
    • 3.3.5 Excretion
  • 3.4 Hepcidin Studies
    • 3.4.1 Hepcidin seems not to be active in Liver Hepatocytes
    • 3.4.2 DMT1 and ferroportin expression changes
    • 3.4.3 Iron in Spleen
    • 3.4.4 Transferrin Saturation and Erythropoiesis
  • 3.5 IRP Studies
    • 3.5.1 Transferrin Saturation and Erythropoiesis
    • 3.5.2 Duodenum
    • 3.5.3 Liver
    • 3.5.4 Spleen
    • 3.5.5 Bone marrow
  • 3.6 IRP and Hemochromatosis
• 4 - Discussion
  • 4.1 Mathematical Model of Iron Metabolism – General Structure
  • 4.2 Structural and Kinetic Hierarchy of the Model
  • 4.3 Model Parameterization from Experimental Data: Iron Status and Fluxes
  • 4.4 Iron status of the adult mice on different dietary regimes
  • 4.5 Modelling iron fluxes by the Fe⁵⁹ tracer method
  • 4.6 Iron status
  • 4.7 Dynamic fluxes
  • 4.8 Kinematic model of iron flux steady-state
  • 4.9 Inhomogeneity of compartments
  • 4.10 Numerical parameter estimation
  • 4.11 Interdependence (correlation) of parameter estimates
  • 4.12 Further parameters of the model
  • 4.13 Physiological interpretation of the flux model
  • 4.14 Systemic iron metabolism can be described as a closed compartment system.
  • 4.15 Iron metabolism is organized as temporal hierarchy on five time scales
  • 4.16 Iron turnover in the plasma compartment depends on the iron status
  • 4.17 Iron distribution into body periphery is a three-level hierarchy of flux rates
  • 4.18 Share of flux into tissues mirrors transferrin receptor expression
  • 4.19 Tracer distribution iron-rich condition reflects the switch-over to the storage mode
  • 4.20 Tissue cells equilibrate influx and reflux of iron to maintain the iron pool
  • 4.21 Intracellular residence time of iron is longer than the life time of its protein “carriers"
  • 4.22 Readily accessible tissue iron pools are a fraction of the non-heme iron
  • 4.23 There are two kinetically distinct major iron pools in the mouse body
  • 4.24 Iron turnover occurs at similar rate in intestine and skin, but assignment to iron loss vs. iron reflux is only indirectly estimable
  • 4.25 Murine erythrocyte iron turnover has a random elimination component together with a lifespan-determined removal component
  • 4.26 The spleen is a mixed indicator of erythropoiesis and RES activity
  • 4.27 Experimental design for characterizing the iron status and the dynamic turnover of the C57BL6 mouse strain.
  • 4.28 Simulated Experiments – Perturbation and Transgenic Reconstruction
  • 4.29 Conclusion and Outlook
• Appendix A
• References
• Acknowledgements

Tabellen

• Table 2.1: The values were taken from [27 ].
• Table 2.1: Species shared by all cell-types in the model.
• Table 2.2: Model fluxes.
• Table 2.3 summarizes the turnover rates of macromolecules (synthesis and degradation).
• TABLE 3.1: 1) Molecular weight of iron 55.847 2) 1.36 ml plasma per 25 mg mouse (see table 2.1) 3) Rounded value of row 4 * 55.847 / 1000 *1.36 ml (body plasma volume)
• TABLE 3.2: Clearance parameter rates for the best fit and also the upper and lower limits obtained after Monte Carlo perturbations of the measurement values followed by the curve-fit procedure.
• Table 3.3. The calculations were done for the “best-fit” parameters.
• TABLE 3.4: The calculated pool sizes for the three dietary regimes.
• Table 3.5: The calculated residence time that iron molecules spend in the organs of mice held under different diets.
• Table 3.6: Non-heme iron content of mouse (C57B6/L) organs in different dietary regimes. 
• Table 3.7: Tracer-accessible Iron Pools compared with non-heme Iron in different dietary Regimes.
• Table 1: Iron-adequate Diet in healthy Mice - Tracer Iron Content of Body Organs after intravenous Injection
• Table 2: Iron-deficient Diet in healthy Mice - Tracer Iron Content of Body Organs after intravenous Injection
• Table 3: Iron-loaded Diet in healthy Mice - Tracer Iron Content of Body Organs after intravenous Injection

Bilder

• Figure 2.1: Global flux model layout.
• Figure 2.2: Optimization pipeline developed in this study.
• Figure 2.3: The figure shows the general cellular model shared by all organs in the model.
• Fig. 2.4:
• Fig. 2.5: This is a simplified scheme of the turnover of the iron-processing proteins in the generic cell.
• Fig. 6: Hepcidin increases degradation of ferroportin protein by binding and internalizing.
• Figure 3.1: distribution of radioactive plasma iron between organs.
• Figure 3.2: The best fit of our model to the measured data of mice held under iron adequate diet.
• Figure 3.3: The best fit of our model to the measured data of mice held under iron deficient diet.
• Figure 3.4: The best fit of our model to the measured data of mice held under iron loaded diet.
• Figure 3.5: The calculated radioiron fluxes from plasma into organs. Data obtained from
• Figure 3.6: The calculated pool sizes for the different organs under three diets.
• Figure 3.7: Blood loss and its relation to body iron status indicators.
• Figure 3.8: The reserves of iron are linearly depleted with increases in the daily loss of iron.
• Figure 3.9: Time necessary for the model to establish a new steady state with a daily loss of iron.
• Figure 3.10: Relation of changes in the dietary iron supply (flux v5, controlles by parameter K5) and iron fluxes/storage/regulation.
• Figure 3.11: With increases in duodenal iron supply, there is an increase in the iron absorption in the bone marrow through TfR1, its ferritin stores also increases and consequently the RBC levels are also increased.
• Figure 3.12: With increased duodenal absorption there is an increase in the iron supply in the RES, due ineffective erythropoiesis.
• Figure 3.13: The reserved in the liver and muscles are increased with higher duodenal iron absorption.
• Figure 3.14: With increased iron levels in the body, the excretion level through skin desquamation and mucosal exfoliation are also raised.
• Figure 3.15: Comparison of different model configurations.
• Figure 3.16: the increase and decrease in hepcidin expression is inversely followed by expression levels of DMT1 and ferroportin in duodenum.
• Figure 3.17: with lack of hepcidin there is an increase in the levels of the membrane iron transporter ferroportin.
• Figure 3.18: at very low values of hepcidin expression we can observe an increase in the erythrocytes and in the transferrin saturation.
• Figure 3.19: with lack of IRP2 expression in tissues there is a decrease of RBC despite the fact that no change can be observed in the transferrin saturation.
• Figure 3.20: with lack of IRP2 expression there is a decrease in ferroportin and DMT1, however, there is an increase in the level of ferritin iron which corresponds to the observations of [83 ]. Note that the normal level of IRP2 expression is at U2=1.0.
• Figure 3.21: with lack of IRP2 expression there is a decrease in ferroportin and TfR1, since the IRP system provides protection of the mRNA of those genes against degradation. However, just the decrease of TfR1 is in accordance with [83 ].
• Figure 3.22: with lack of IRP2 expression there is a decrease in ferroportin and in the iron acquisition.
• Figure 3.23: In IRP 2 knock-out mice there is no change in the level of ferritin iron in the bone marrow.
• Figure 3.24: In the duodenum of hereditary hemochromatosis or anemic patients there is increased activity of IRP activity.