Team:Valencia/OurModel

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Detailed model description


We have based our Project on the budding yeast Saccharomyces cerevisiae. Although it is a model organism for the study of many biological processes, there are only a few reports on yeast electrophysiology. That’s why we began to work with a model built up for excitable cells (neurons and cardiomyocites) in which several parts can be distinguished:


  • Modelling Ionic Current Flow through VDCCs

If we assume that the whole calcium currents occur through this calcium channels and that the instantaneous current-voltage relation is linear, we can describe the ionic current ICa by the Ohm's law:

Eq1.jpg

Where g is the conductance associated with the channel, V is the transmembrane potential and ECa is the Nerst potential, related to the different ionic concentration inside and outside the cell.
Considering that these channels are only permeable to calcium and have two states -open or closed-, the total conductance associated with the population of VDCCs can be expressed as the maximal conductance Gbarra.jpg times the fraction of all channels that are open. This fraction is determined by hypothetical activation and inactivation variables m and h, which depend on voltage and time:

Eq2.jpg
2.1.jpg

Minf.jpg is the steady-state value of m and Taum.jpg is the time constant. They are defined functions of voltage:

2.1.1.jpg
2.1.2.jpg



2.2.jpg
2.3.jpg

K is the halfway inactivation concentration and [Ca2+]o is the constant extracellular calcium concentration.

Now, we have to model how transmembrane potential changes in time. To do this, we can consider the following membrane-equivalent electrial circuit, where all ionic currents involved in initiation and propagation of the action potential are represented:

V circuit.gif

We can know the transmembrane potential at any time after applying an electrical input by solving this equation:

Eq3.jpg

However, we have assumed that our stimulus triggers the excitatory post-synaptic potential (EPSP), so it's not necessary to solve the previous equation. But modelling the calcium influx is only the first step...

  • Modelling Free Intracellular Calcium Concentration

The change in free intracellular calcium concentration is mostly due to the influx of calcium ions described above, but there are several factors which also contribute. For instance, we have considered calcium buffers and calcium remove by membrane pumps.


Calcium current
The relation between the calcium inward current ICa and the change in intracellular calcium concentration is given by:

Eq4.jpg

F is the Faraday's constant, [Ca2+] is the calcium concentration just below the plasma membrane and Vol is the cell volume considered.

V CaCurrent.jpg



V Buffer2.jpg

Calcium buffers
At this point we have taken into account the presence of calcium buffers such as calmodulin, calcineurin, calbindin, and other ones in the cell. To make the model easier, we have assumed that calcium binds to a single binding site on a single buffer as it is expressed here:

V Buffer.jpg

f and b are the forward and backward rates of the binding reaction:

Eq5.jpg


Calcium pumps
Once the buffering system has reduced the amount of free intracellular calcium, the remaining calcium ions must be removed from the cell in order to maintain calcium homeostasis. We have described the behaviour of calcium pumps by the following first-order equation:

Eq6.jpg

Where [Ca2+]eq is the equilibrium concentration of the pump, [Ca2+] is the calcium concentration in the shell just below the membrane and tpump is the pump's time constant, which depends on voltage:

6.1.jpg
V Pump.jpg



We have neglected the intracellular diffusion of calcium due to the different concentrations between the inner perimembranal area and deeper areas of the citoplasm, we have considered that the calcium release from intracellular organelles (for instance, endoplasmic reticulum and mitochondria) may reduce these concentration differences. Thus, we assume the calcium concentration just below the plasma membrane as whole intracellular calcium.


In our project, the mechanism for the production of light through a yeast-based system is similar to the one described by the previous model. Therefore, after determining experimentally yeasts’ response to this type of input, we decided to fit the model to our experimental results and determine the differences between neurons and yeasts’ VDCCs (Voltage-Dependent Calcium Channels). In particular, this fitting allowed us to determine the conductance (g) of yeasts’ calcium channels:

Eq llevat.jpg

It has to be noted that we took into account some particular properties of yeasts’ plasma membrane, for instance, its transmembrane potential, which is so much lower than in neurons.

The following figure shows our experimental data (dotted line) and the theoretical results predicted by our model considering the determined conductance of 21,386 µS:

Fitting.jpg