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Modelling Calcium Dynamics Basic reference: Keener and Sneyd, Mathematical Physiology.

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Presentation on theme: "Modelling Calcium Dynamics Basic reference: Keener and Sneyd, Mathematical Physiology."— Presentation transcript:

1 Modelling Calcium Dynamics Basic reference: Keener and Sneyd, Mathematical Physiology

2 So far we concentrated on Na + (and K + ), as those are the ions that are most important for the control of cell volume and the membrane potential. So far we concentrated on Na + (and K + ), as those are the ions that are most important for the control of cell volume and the membrane potential. But Ca 2+ plays an equally important role in practically every cell type. But Ca 2+ plays an equally important role in practically every cell type. Ca 2+ controls secretion, cell movement, muscular contraction, cell differentiation, ciliary beating and many other essential cellular processes. Ca 2+ controls secretion, cell movement, muscular contraction, cell differentiation, ciliary beating and many other essential cellular processes. Important in both excitable and non-excitable cells. Important in both excitable and non-excitable cells. Calcium is a vital second messenger

3 Whole-body control they really mean response Maintained high levels of calcium in the blood

4 Calcium in muscle

5 Calcium in phototransduction

6 Calcium in taste receptors

7 Calcium and synapses Derkach et al. Nature Reviews Neuroscience 8, 101–113 (February 2007) | doi:10.1038/nrn2055

8 Cezar Tigaret Jack Mellor University of Bristol

9 Inward flux of calcium through voltage-gated calcium channels. Dependent on fluctuations of the membrane potential. Often seen in electrically excitable cells such as neurosecretory cells Not dependent on membrane potential. Oscillations arise from recycling of calcium to and from internal stores (ER and mitochondria) Ryanodinereceptors IP 3 receptors Muscle cells and many neurons Electrically non- excitable cells. Smooth muscle Three principal mechanisms

10 Calcium and auditory system Inner hair cells are excitable sensory cells in the inner ear that encode acoustic information

11 Voltage gated Ca 2+ channels [Ca 2+ ] i C ALCIUM - BASED ELECTRICAL ACTIVITY Ca 2+ dependent K + channel K Ca K+K+ I K(v) Voltage gated Ca 2+ channels Ca 2+ I K(V) During prolonged APs, Ca 2+ spreads further into the cell Courtesy of H. Kennedy University of Bristol

12 Time scale is of order of milliseconds Time scale is of order of seconds Typically found in endocrine cells and only some types of neurons

13 Fig. 5. Mixed [Ca 2+ ] c oscillations trigger synchronous oscillations of insulin secretion Fig. 2. Temporal correlation between membrane potential (MP) and [Ca 2+ ] c oscillations FIG. 2. Simultaneous measurements of Vm and [Ca 2+ ] i oscillations in spontaneously firing somatotrophs

14 Time scale is of order of milliseconds Time scale is of order of seconds

15 Fold-Homoclinic Chay-Keizer Model Morris-Lecar  -cell Model Fold-subHopf Pituitary Cells Model Inner Hair Cells Model Bursting Mechanism

16 I I K (V) I Ca (V) V I SK (Ca) Patch clamp amplifier (current clamp) V Computer DigitizerIBTX Original concept : Sharp et al, 1993 Implementation : QuB (Milescu et al, 2008) Adding BK current with Dynamic Clamp read V I BK compute df/dt = (f  (V)-V)/  BK write I BK I BK = g BK × f × (V-V K ) I BK Courtesy of J. Tabak Florida State University, US

17 Adding I BK (fast) back with dynamic clamp restores bursting -40 -20 0 -40 -20 0 -40 -20 0 1 sec V (mV) Control BK block + g BK = 0.5 nS

18 Subtracting I BK converts bursting into spiking -40 -20 0 -40 -20 0 1 sec V (mV) Control - g BK = 1 nS V (mV) Courtesy of J. Tabak Florida State University, US

19 The challenge

20 Calcium buffering Over 99% of all calcium in the cytoplasm is bound to large proteins, called calcium buffers Over 99% of all calcium in the cytoplasm is bound to large proteins, called calcium buffers In other words, if 100 calcium ions enter the cell, less than 1, on average, ends up as a free ion in solution. The others all get bound to the buffers In other words, if 100 calcium ions enter the cell, less than 1, on average, ends up as a free ion in solution. The others all get bound to the buffers It’s very important to understand how such buffers get included in models. It’s very important to understand how such buffers get included in models.

21 Slow buffering Ca 2+ + P B k on k off b t is total buffer If buffering is slow, this is just included as an extra term in the equation for c, as well as an additional equation for b. Thus

22 Fast buffering If the buffer is assumed to be at pseudo-steady state (i.e., k on and k off are large) then Hence But if we add the two PDEs in the previous slide, we get

23 Hence, it follows that Oh dear. Buffers give a nasty nonlinear transport equation for calcium.

24 Simple case If the buffer doesn’t diffuse, and K>>c, then things simplify well. Then the previous nasty equation just becomes Buffering is now a simple scale factor, and all fluxes must be interpreted as effective fluxes. Often called fast, linear, buffering.

25 Travelling wave equation The U-shaped curve is a curve of Hopf bifurcations, the C-shaped curve is a curve of homoclinic bifurcations.

26 Generic modelling Set up a typical reaction diffusion equation for calcium: ER fluxes PM fluxes mitochondrialfluxes buffering This reaction-diffusion equation is coupled to a system of o.d.e.s (or p.d.e.s), describing the various receptor states, IP 3, the reaction and diffusion of the buffers, calcium inside the ER or mitochondria, or any other important species. This reaction-diffusion equation is coupled to a system of o.d.e.s (or p.d.e.s), describing the various receptor states, IP 3, the reaction and diffusion of the buffers, calcium inside the ER or mitochondria, or any other important species. The specifics of the coupled o.d.e.s depend on which particular model is being used. The specifics of the coupled o.d.e.s depend on which particular model is being used. Sometimes the PM fluxes appear only as boundary conditions, sometimes not, depending on the exact assumptions made about the spatial properties of the cell. Sometimes the PM fluxes appear only as boundary conditions, sometimes not, depending on the exact assumptions made about the spatial properties of the cell. In general the buffering flux is a sum of terms, describing buffering by multiple diffusing buffers. In general the buffering flux is a sum of terms, describing buffering by multiple diffusing buffers. Total buffer

27 Ca 2+ dependent K + channels are responsible for APs repolarisation (Marcotti et. al. J. Physiol. 2004) Time (ms) Helen Kennedy, University of Bristol

28 Boundary Conditions:

29

30 Ca 2+ channelK Ca channel

31 An intercellular wave of calcium in pancreatic acinar cell cluster. From David Yule. Calcium in pancreatic acinar cells

32 A typical example

33 Question: coupled calcium oscillators a b c Real image Apical Region Mitochondrial buffer Basal Region Two dimensional model; no flux boundary conditions are applied on the external borders of each cell and the cells are connected by flux BC applied on the internal borders. Two dimensional model; no flux boundary conditions are applied on the external borders of each cell and the cells are connected by flux BC applied on the internal borders. Question: How important is intercellular diffusion of Ca 2+ and IP 3 for the coordination (or lack thereof) of the intercellular waves? Question: How important is intercellular diffusion of Ca 2+ and IP 3 for the coordination (or lack thereof) of the intercellular waves? FEM mesh Three spatially distributed coupled oscillators

34 Identical cells Falls into the 2/1 pattern, where two go together with the third slightly out of phase. This seems to be a lot more stable. Cell Movie Cell Movie

35 Insights from a point model 1 23

36 Ca 2+ Coupling Can Kill the Oscillations pancreatic islets

37 Oscillator Death in Coupled System of Identical  -cells

38 Glycolytic Oscillator Pathway of glycolysis from glucose to pyruvate. Substrates and products are in blue, enzymes are in green. The two high energy intermediates whose oxidations are coupled to ATP synthesis are shown in red (1,3-bisphosphoglycerate and phosphoenol-pyruvate). Pathway of glycolysis from glucose to pyruvate. Substrates and products are in blue, enzymes are in green. The two high energy intermediates whose oxidations are coupled to ATP synthesis are shown in red (1,3-bisphosphoglycerate and phosphoenol-pyruvate). (G6P) (FBP)

39 Coupled Glycolytic Oscillators

40


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