Title of Poster or Presentation
Computational Approach to Understanding Canonical Ca2+ Signaling
Submission Type
Oral/Paper Presentation
Degree Type
Masters
Discipline
Sciences
Department
Biology
Access Type
Open Access
Abstract or Description
Introduction: Calcium plays a vital role in the health and functioning of nerves and muscle tissue. Therefore, it is essential to understand the pathology of calcium-dependent intracellular signaling pathways. Through computational modeling, certain pathways in cells can be analyzed to identify patterns among common diseases.
Methods: This study utilizes live human embryonic kidney (HEK) cells tagged with green fluorescent proteins (GFP) to determine model parameters for several canonical Ca2+signaling. When the GFP fluoresces, both cytosolic and endoplasmic reticulum (ER) calcium transients are captured using thresholds and masking to increase accuracy. From there, the calcium transients are fed into a genetic algorithm, which contains a set of ordinary differential equations (ODE), to estimate model parameters.
Results: The parameters identified in the modified cytosolic fitting were VmaxSC (1.51 mol/s ± 0.01), VmaxRyR (1.61 mol/s ± 0.01), KdSC (0.04 mol/L ± 0.001), KdRYR (10.61 mol/L ± 4.44), nSC (1.94 ± 0.11), nRyR (2.79 ± 0.64), Leak Rate (0.49 s-1 ± 0.06), and Ca_0 (0.44 uM ± 0.05). Initial fitting of ER has large residual error as seen in the difference between experimental data from the predicted model.
Conclusion: Modeling fitting is a complex process that takes multiple attempts to determine a precise model that mechanistically consistent with data. The dissociation constant (Kd) for the ryanodine receptor (RyR) for the cytoplasm reveals a possible dose-dependency between extracellular calcium and Ryr receptor. Additionally, the recovery lag of Ca2+ needs to be accounted for when modifying the ER fitting ODE to improve fitness.
Creative Commons License
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Computational Approach to Understanding Canonical Ca2+ Signaling
Introduction: Calcium plays a vital role in the health and functioning of nerves and muscle tissue. Therefore, it is essential to understand the pathology of calcium-dependent intracellular signaling pathways. Through computational modeling, certain pathways in cells can be analyzed to identify patterns among common diseases.
Methods: This study utilizes live human embryonic kidney (HEK) cells tagged with green fluorescent proteins (GFP) to determine model parameters for several canonical Ca2+signaling. When the GFP fluoresces, both cytosolic and endoplasmic reticulum (ER) calcium transients are captured using thresholds and masking to increase accuracy. From there, the calcium transients are fed into a genetic algorithm, which contains a set of ordinary differential equations (ODE), to estimate model parameters.
Results: The parameters identified in the modified cytosolic fitting were VmaxSC (1.51 mol/s ± 0.01), VmaxRyR (1.61 mol/s ± 0.01), KdSC (0.04 mol/L ± 0.001), KdRYR (10.61 mol/L ± 4.44), nSC (1.94 ± 0.11), nRyR (2.79 ± 0.64), Leak Rate (0.49 s-1 ± 0.06), and Ca_0 (0.44 uM ± 0.05). Initial fitting of ER has large residual error as seen in the difference between experimental data from the predicted model.
Conclusion: Modeling fitting is a complex process that takes multiple attempts to determine a precise model that mechanistically consistent with data. The dissociation constant (Kd) for the ryanodine receptor (RyR) for the cytoplasm reveals a possible dose-dependency between extracellular calcium and Ryr receptor. Additionally, the recovery lag of Ca2+ needs to be accounted for when modifying the ER fitting ODE to improve fitness.
