MODELING THE CA2+CAMKII NETWORK OF LTP IN THE JIGCELL ENVIRONMENT

Year 2021, Volume: 11 Issue: 1, 71 - 77, 01.06.2021

Onur Alpturk

https://doi.org/10.36222/ejt.962475

Abstract

Since their initial discovery, long-term potentiation (LTP), and long-term depression (LTD) are accepted as the main biomolecular mechanism that controls memory acquisition. In doing this, both mechanisms are fairly complex and involve specific triggers and many cascades reactions that cross-talk and communicate with others. Thus, they are very complex. To reveal how these mechanisms operate and instruct the brain to remember and forget, one judicious approach is developing the mathematical models of processes. However, this notion requires some basic knowledge regarding ordinary differential equations and writing codes. To this respect, it can be postulated that tools, which can be utilized rather by everyone, would certainly expedite and facilitate the formulation of such models. With this rationale in mind, we demonstrate that JigCell offers the perfect platform to develop such models for LTP. Our choice for this tool stems from the fact that it is designed to simulate complex biological systems with ease. Thus, this manuscript is crafted to illustrate how Ca2+/CaMKII network in LTP was constructed in the JigCell environment and to give an idea of how this tool works

Keywords

Memory formation, Long-term potentiation, Mathematical model, JigCell, Calcium, CaMKII

References

• [1] Hebb, D. O. (1949). The Organization of Behavior. New York, NY: Wiley & Sons.
• [2] Hughes, J. R. (1958). Post-tetanic potentiation. Physiological Reviews. 38 (1): 91–113.
• [3] Bliss, T. V., & Lømo, T. (1973). Long‐lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. The Journal of Physiology, 232(2), 331-356.Baltaci, S. B., Mogulkoc, R., & Baltaci, A. K. (2019). Molecular mechanisms of early and late LTP. Neurochemical Research, 44(2), 281-296.
• [4] Baltaci, S. B., Mogulkoc, R., & Baltaci, A. K. (2019). Molecular mechanisms of early and late LTP. Neurochemical Research, 44(2), 281-296.
• [5] He, Y., Kulasiri, D., & Samarasinghe, S. (2016). Modelling bidirectional modulations in synaptic plasticity: A biochemical pathway model to understand the emergence of long term potentiation (LTP) and long term depression (LTD). Journal of Theoretical Biology, 403, 159-177.
• [6] Alptürk, O., & Şengör, N. S. (2019). A Model for the Effect of Glia on the Communication Amongst Neurons. 2019 27th Signal Processing and Communications Applications Conference (SIU), pp. 1-4.
• [7] Lisman, J. E., & Zhabotinsky, A. M. (2001). A model of synaptic memory: a CaMKII/PP1 switch that potentiates transmission by organizing an AMPA receptor anchoring assembly. Neuron, 31(2), 191-201.
• [8] Tewari, S., & Majumdar, K. (2012). A mathematical model for astrocytes mediated LTP at single hippocampal synapses. Journal of Computational Neuroscience, 33(2), 341-370.
• [9] Ohadi, D., Schmitt, D. L., Calabrese, B., Halpain, S., Zhang, J., & Rangamani, P. (2019). Computational modeling reveals frequency modulation of calcium-cAMP/PKA pathway in dendritic spines. Biophysical Journal, 117(10), 1963-1980.
• [10] Smolen, P., Baxter, D. A., & Byrne, J. H. (2006). A model of the roles of essential kinases in the induction and expression of late long-term potentiation. Biophysical Journal, 90(8), 2760-2775.
• [11] Jones Jr, T. C., Hoops, S., Watson, L. T., Palmisano, A., Tyson, J. J., & Shaffer, C. A. (2018). JigCell Model Connector: building large molecular network models from components. Simulation, 94(11), 993-1008.
• [12] http://copasi.org/Projects/JigCell_Model_Connector/
• [13] The files can be downloaded from https://github.com/oalptu1/Cerebra.git
• [14] He, Y., Kulasiri, D., & Samarasinghe, S. (2016). Modelling bidirectional modulations in synaptic plasticity: A biochemical pathway model to understand the emergence of long term potentiation (LTP) and long term depression (LTD). Journal of Theoretical Biology, 403, 159-177.
• [15] Zalcman, G., Federman, N., & Romano, A. (2018). CaMKII isoforms in learning and memory: localization and function. Frontiers in Molecular Neuroscience, 11, 445.
• [16] Kennedy, M. B. (2016). Synaptic signaling in learning and memory. Cold Spring Harbor perspectives in Biology, 8(2), a016824.
• [17] Citri, A., & Malenka, R. C. (2008). Synaptic plasticity: multiple forms, functions, and mechanisms. Neuropsychopharmacology, 33(1), 18-41.
• [18] Hoelz, A., Nairn, A. C., & Kuriyan, J. (2003). Crystal structure of a tetradecameric assembly of the association domain of Ca2+/calmodulin-dependent kinase II. Molecular Cell, 11(5), 1241-1251.
• [19] Magupalli, V. G., Mochida, S., Yan, J., Jiang, X., Westenbroek, R. E., Nairn, A. C., Scheuer, T., & Catterall, W. A. (2013). Ca2+-independent activation of Ca2+/calmodulin-dependent protein kinase II bound to the C-terminal domain of CaV2. 1 calcium channels. Journal of Biological Chemistry, 288(7), 4637-4648.
• [20] Zhabotinsky, A. M. (2000). Bistability in the Ca2+/calmodulin-dependent protein kinase-phosphatase system. Biophysical Journal, 79(5), 2211-2221.
• [21] Pharris, M. C., Patel, N. M., VanDyk, T. G., Bartol, T. M., Sejnowski, T. J., Kennedy, M. B., Stefan, M. I., & Kinzer-Ursem, T. L. (2019). A multi-state model of the CaMKII dodecamer suggests a role for calmodulin in maintenance of autophosphorylation. PLoS Computational Biology, 15(12), e1006941.
• [22] Lisman, J. E., & Goldring, M. A. (1988). Feasibility of long-term storage of graded information by the Ca2+/calmodulin-dependent protein kinase molecules of the postsynaptic density. Proceedings of the National Academy of Sciences, 85(14), 5320-5324.
• [23] Michelson, S., & Schulman, H. (1994). CaM kinase: a model for its activation and dynamics. Journal of Theoretical Biology, 171(3), 281-290.
• [24] Hanson, P. I., & Schulman, H. (1992). Neuronal Ca2+/calmodulin-dependent protein kinases. Annual Review of Biochemistry, 61(1), 559-601.
• [25] Strack, S., Choi, S., Lovinger, D. M., & Colbran, R. J. (1997). Translocation of autophosphorylated calcium/calmodulin-dependent protein kinase II to the postsynaptic density. Journal of Biological Chemistry, 272(21), 13467-13470.
• [26] Yoshimura, Y., Sogawa, Y., & Yamauchi, T. (1999). Protein phosphatase 1 is involved in the dissociation of Ca2+/calmodulin-dependent protein kinase II from postsynaptic densities. FEBS Letters, 446(2-3), 239-242.
• [27] Shenolikar, S., & Nairn, A. C. (1991). Protein phosphatases—recent progress. Adv. Sec. Mess. Phosphoprot. Res. 23:1–121.
• [28] Endo, S., Zhou, X., Connor, J., Wang, B., & Shenolikar, S. (1996). Multiple structural elements define the specificity of recombinant human inhibitor-1 as a protein phosphatase-1 inhibitor. Biochemistry, 35(16), 5220-5228.
• [29] Allen, P. B., Hvalby, Ø., Jensen, V., Errington, M. L., Ramsay, M., Chaudhry, F. A., Bliss, T. V. P., Storm-Mathisen, J., Morris, R. G. M., Andersen, P., & Greengard, P. (2000). Protein phosphatase-1 regulation in the induction of long-term potentiation: heterogeneous molecular mechanisms. Journal of Neuroscience, 20(10), 3537-3543.
• [30] Fährmann, M., Möhlig, M., Schatz, H., & Pfeiffer, A. (1998). Purification and characterization of a Ca2+/calmodulin‐dependent protein kinase II from hog gastric mucosa using a protein‐protein affinity chromatographic technique. European Journal of Biochemistry, 255(2), 516-525.
• [31] De Koninck, P., & Schulman, H. (1998). Sensitivity of CaM kinase II to the frequency of Ca2+ oscillations. Science, 279(5348), 227-230.
• [32] Stemmer, P. M., & Klee, C. B. (1994). Dual calcium ion regulation of calcineurin by calmodulin and calcineurin B. Biochemistry, 33(22), 6859-6866.
• [33] Hanson, P. I., Meyer, T., Stryer, L., & Schulman, H. (1994). Dual role of calmodulin in autophosphorylation of multifunctional CaM kinase may underlie decoding of calcium signals. Neuron, 12(5), 943-956.
• [34] The list of publications regarding the use of COPASI could be accessed from http://copasi.org/Research/