1. Center for Theoretical Problems of Physico-Chemical Pharmacology, Russian Academy of Sciences, Moscow, Russia 2. Center for Theoretical Problems of Physico-Chemical Pharmacology, Russian Academy of Sciences, Moscow, Russia; Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
Anuclear blood cells, platelets, are the basis for the formation of blood clots in human vessels. While antiplatelet therapy is most often used after ischemic events, there is a need for its personalization due to the limited effectiveness and risks of bleeding. Previously, we developed a series of computational models to describe intracellular platelet signaling and a set of experimental methods to characterize the platelets of a given patient. To build a personalized model of platelet signaling, we also conducted research on platelet proteomics. The aim of this study was to personalize the central module of intracellular platelet signaling responsible for the formation of calcium oscillations in response to activation. The model consists of 26 ordinary differential equations. To personalize the model, proteomics data were used and unknown model parameters were selected based on experimental data on the shape and frequency of calcium oscillations in single platelets. As a result of the study, it has been shown that the key personalized parameters of the platelet oscillatory response are the degree of asymmetry of a single calcium spike and the maximum frequency of oscillations. Based on the listed experimentally determined parameters and proteomics data, an algorithm for personalization of the model has been proposed. Here we considered three healthy pediatric donors of different ages. Based on the models, personal curves of platelet calcium response to activation were obtained. The analysis of the models has shown that while there is a large heterogeneity of individual indicators of intracellular signaling, such as the activity of calcium pumps (SERCA) and inositoltriphosphate (IP₃) receptors (IP₃R), these indicators compensate each other in each donors. This observation is confirmed by the analysis of proteomics data from 15 healthy patients: this analysis demonstrates a correlation between the total amount of SERCA and IP₃R. Thus, several new features of human platelet calcium signaling are shown and an algorithm for personalizing its model is proposed.
Balabin F.A., Korobkina J.D.D., Galkina S.V., Panteleev M.A., Sveshnikova A.N. (2024) Personalization of a computational systems biology model of blood platelet calcium signaling. Biomeditsinskaya Khimiya, 70(6), 394-402.
Balabin F.A. et al. Personalization of a computational systems biology model of blood platelet calcium signaling // Biomeditsinskaya Khimiya. - 2024. - V. 70. -N 6. - P. 394-402.
Balabin F.A. et al., "Personalization of a computational systems biology model of blood platelet calcium signaling." Biomeditsinskaya Khimiya 70.6 (2024): 394-402.
Balabin, F. A., Korobkina, J. D. D., Galkina, S. V., Panteleev, M. A., Sveshnikova, A. N. (2024). Personalization of a computational systems biology model of blood platelet calcium signaling. Biomeditsinskaya Khimiya, 70(6), 394-402.
References
Varga-Szabo D., Braun A., Nieswandt B. (2009) Calcium signaling in platelets. J. Thromb. Haemost., 7(7), 1057–1066. CrossRef Scholar google search
Sveshnikova A., Stepanyan M., Panteleev M. (2021) Platelet functional responses and signalling: The molecular relationship. Part 1: responses. Syst. Biol. Physiol. Rep., 1(1), 20. CrossRef Scholar google search
Martyanov A., Panteleev M. (2021) Platelet functional responses and signalling: The molecular relationship. Part 2: receptors. Syst. Biol. Physiol. Rep., 1(3), 13–30. CrossRef Scholar google search
Lian L., Wang Y., Draznin J., Eslin D., Bennett J.S., Poncz M., Wu D., Abrams C.S. (2005) The relative role of PLC and PI3K in platelet activation. Blood, 106(1), 110–117. CrossRef Scholar google search
Sveshnikova A.N., Ataullakhanov F.I., Panteleev M.A. (2015) Compartmentalized calcium signaling triggers subpopulation formation upon platelet activation through PAR1. Mol. Biosyst., 11(1), 1052–1060. CrossRef Scholar google search
Obydennyy S.I., Sveshnikova A.N., Ataullakhanov F.I., Panteleev M.A. (2016) Dynamics of calcium spiking, mitochondrial collapse and phosphatidylserine exposure in platelet subpopulations during activation. J. Thromb. Haemost., 14(9), 1867–1881. CrossRef Scholar google search
Heemskerk J.W.M., Hoyland J., Masont W.T., Sage S. (1992) Spiking in cytosolic calcium concentration in single fibrinogen-bound fura-2-loaded human platelets. Biochem. J., 283(2), 379–383. CrossRef Scholar google search
Scridon A. (2022) Platelets and their role in hemostasis and thrombosis — From physiology to pathophysiology and therapeutic implications. Int. J. Mol. Sci., 23(21), 12772. CrossRef Scholar google search
Martyanov A.A., Morozova D.S., Sorokina M.A., Filkova A.A., Fedorova D.V., Uzueva S.S., Suntsova E.V., Novichkova G.A., Zharkov P.A., Panteleev M.A., Sveshnikova A.N. (2020) Heterogeneity of integrin αIIbβ3 function in pediatric immune thrombocytopenia revealed by continuous flow cytometry analysis. Int. J. Mol. Sci., 21(9), 3035. CrossRef Scholar google search
Dunster J.L., Panteleev M.A., Gibbins J.M., Sveshnikova A.N. (2018) Mathematical techniques for understanding platelet regulation and the development of new pharmacological approaches. Methods Mol. Biol., 1812, 255–279. CrossRef Scholar google search
Sveshnikova A.N., Balatskiy A.V., Demianova A.S., Shepelyuk T.O., Shakhidzhanov S.S., Balatskaya M.N., Pichugin A.V., Ataullakhanov F.I., Panteleev M.A. (2016) Systems biology insights into the meaning of the platelet's dual-receptor thrombin signaling. J. Thromb. Haemost., 14(10), 2045–2057. CrossRef Scholar google search
Shakhidzhanov S.S., Shaturny V.I., Panteleev M.A., Sveshnikova A.N. (2015) Modulation and pre-amplification of PAR1 signaling by ADP acting via the P2Y12 receptor during platelet subpopulation formation. Biochim. Biophys. Acta, 1850(12), 2518–2529. CrossRef Scholar google search
Martyanov A.A., Balabin F.A., Dunster J.L., Panteleev M.A., Gibbins J.M., Sveshnikova A.N. (2020) Control of platelet CLEC-2-mediated activation by receptor clustering and tyrosine kinase signaling. Biophys. J., 118(11), 2641–2655. CrossRef Scholar google search
Stepanyan M.G., Filkova A.A., Garzon Dasgupta A.G., Martyanov A.A., Sveshnikova A.N. (2021) Platelet activation through GPVI receptor: Variability of the response. Biochem. Moscow Suppl. Ser. A, 15(1), 73–81. CrossRef Scholar google search
Shepelyuk T.O., Panteleev M.A., Sveshnikova A.N. (2016) Computational modeling of quiescent platelet energy metabolism in the context of whole-body glucose turnover. Math. Model. Nat. Phenom., 11(6), 103–113. CrossRef Scholar google search
Obydennyi S.I., Artemenko E.O., Sveshnikova A.N., Ignatova A.A., Varlamova T.V., Gambaryan S., Lomakina G.Y., Ugarova N.N., Kireev I.I., Ataullakhanov F.I., Novichkova G.A., Maschan A.A., Shcherbina A., Panteleev M. (2020) Mechanisms of increased mitochondria-dependent necrosis in Wiskott-Aldrich syndrome platelets. Haematologica, 105(4), 1095–1106. CrossRef Scholar google search
Balabin F., Galkina S., Zhizhaikina I., Panteleev M., Sveshnikova A. (2021) Quantitative assessment of heterogeneity of single platelet calcium responses to activation. Res. Pract. Thromb. Haemost., 5(S2), PB1027. CrossRef Scholar google search
Shakhidzhanov S.S., Balabin F.A., Obydennyi S.I., Ataullakhanov F.I., Sveshnikova A.N. (2019) Calcium oscillations in blood platelets and their possible role in “interpreting” extracellular information by cells. Physics-Uspekhi, 62(7), 660–674. CrossRef Scholar google search
Martyanov A.A., Tesakov I.P., Khachatryan L.A., An O.I., Boldova A.E., Ignatova A.A., Koltsova E.M., Korobkin J.-J.D., Podoplelova N.A., Svidelskaya G.S., Yushkova E., Novichkova G.A., Eble J.A., Panteleev M.A., Kalinin D.V., Sveshnikova A.N. (2023) Platelet functional abnormalities in pediatric patients with kaposiform hemangioendothelioma/ Kasabach-Merritt phenomenon. Blood Adv., 7(17), 4936–4949. CrossRef Scholar google search
Garzon Dasgupta A.K., Martyanov A.A., Ignatova A.A., Zgoda V.G., Novichkova G.A., Panteleev M.A., Sveshnikova A.N. (2024) Comparison of platelet proteomic profiles between children and adults reveals origins of functional differences. Pediatr. Res., 95(4), 966–973. CrossRef Scholar google search
Balabin F.A., Morozova D.S., Mayorov A.S., Martyanov A.A., Panteleev M.A., Sveshnikova A.N. (2018) Clusterization of inositol trisphosphate receptors determines the shape of the calcium oscillation peak in platelet cytosol. Moscow University Physics Bulletin, 73(12), 526–533. CrossRef Scholar google search
Brown P.N., Hindmarsh A.C., Petzold L.R. (1998) Consistent initial condition calculation for differential-algebraic systems. SIAM J. Sci. Comput., 19(5), 1495–1512. CrossRef Scholar google search
Hoops S., Sahle S., Gauges R., Lee C., Pahle J., Simus N., Singhal M., Xu L., Mendes P., Kummer U. (2006) COPASI — a COmplex PAthway SImulator. Bioinformatics, 22(24), 3067-3074. CrossRef Scholar google search
Bandodkar P., Shaikh R., Reeves G.T. (2023) ISRES+: An improved evolutionary strategy for function minimization to estimate the free parameters of systems biology models. Bioinformatics, 39(7), btad403. CrossRef Scholar google search
Moein M., Grzyb K., Goncalves Martins T., Komoto S., Peri F., Crawford A.D., Fouquier d'Herouel A., Skupin A. (2018) CaSiAn: A calcium signaling analyzer tool. Bioinformatics, 34(17), 3052–3054. CrossRef Scholar google search
Skupin A., Falcke M. (2009) From puffs to global Ca2+ signals: How molecular properties shape global signals. Chaos Interdiscip. J. Nonlinear Sci., 19(3), 037111. CrossRef Scholar google search
Bezprozvanny L., Watras J., Ehrlich B.E. (1991) Bell-shaped calcium-response curves of lns(l,4,5)P3- and calcium-gated channels from endoplasmic reticulum of cerebellum. Nature, 351(6329), 751-754. CrossRef Scholar google search
Wagner J., Keizer J. (1994) Effects of rapid buffers on Ca2+ diffusion and Ca2+ oscillations. Biophys. J., 67(1), 447–456. CrossRef Scholar google search
Chin D., Means A.R. (2000) Calmodulin: A prototypical calcium sensor. Trends Cell Biol., 10(8), 322–328. CrossRef Scholar google search
Nash P.D., Opas M., Michalak M. (1994) Calreticulin: Not just another calcium-binding protein. Mol. Cell Biochem., 135(6), 71–78. CrossRef Scholar google search
Biswas C., Ostrovsky O., Makarewich C.A., Wanderling S., Gidalevitz T., Argon Y. (2007) The peptide-binding activity of GRP94 is regulated by calcium. Biochem. J., 405(2), 233–241. CrossRef Scholar google search
Schorr S., Klein M.-C., Gamayun I., Melnyk A., Jung M., Schäuble N., Wang Q., Hemmis B., Bochen F., Greiner M., Lampel P., Urban S.K., Hassdenteufel S., Dudek J., Chen X.-Z., Wagner R., Cavalié A., Zimmermann R. (2015) Co-chaperone specificity in gating of the polypeptide conducting channel in the membrane of the human endoplasmic reticulum. J. Biol. Chem., 290(30), 18621–18635. CrossRef Scholar google search
Hajnóczky G., Booth D., Csordás G., Debattisti V., Golenár T., Naghdi S., Niknejad N., Paillard M., Seifert E.L., Weaver D. (2014) Reliance of ER-mitochondrial calcium signaling on mitochondrial EF-hand Ca2+ binding proteins: Miros, MICUs, LETM1 and solute carriers. Curr. Opin. Cell Biol., 29(8), 133–141. CrossRef Scholar google search
Laker R.C., Taddeo E.P., Akhtar Y.N., Zhang M., Hoehn K.L., Yan Z. (2016) The mitochondrial permeability transition pore regulator cyclophilin D exhibits tissue-specific control of metabolic homeostasis. PLoS ONE, 11, e0167910. CrossRef Scholar google search
Burkhart J.M., Vaudel M., Gambaryan S., Radau S., Walter U., Martens L., Geiger J., Sickmann A., Zahedi R.P. (2012) The first comprehensive and quantitative analysis of human platelet protein composition allows the comparative analysis of structural and functional pathways. Blood, 120(15), e73–e82. CrossRef Scholar google search
Lee M.Y., Diamond S.L. (2015) A human platelet calcium calculator trained by pairwise agonist scanning. PLoS Comput. Biol., 11(2), e1004118. CrossRef Scholar google search
Shankar K.N., Zhang Y., Sinno T., Diamond S.L. (2022) A three-dimensional multiscale model for the prediction of thrombus growth under flow with single-platelet resolution. PLoS Comput. Biol., 18(1), e1009850. CrossRef Scholar google search
Brummel-Ziedins K.E. (2014) Developing individualized coagulation profiling of disease risk: Thrombin generation dynamic models of the pro and anticoagulant balance. Thromb. Res., 133(Suppl. 1), S9–S11. CrossRef Scholar google search
Undas A., Gissel M., Kwasny-Krochin B., Gluszko P., Mann K., Brummel-Ziedins K. (2010) Thrombin generation in rheumatoid arthritis: Dependence on plasma factor composition. Thromb. Haemost., 104(2), 224–230. CrossRef Scholar google search
Brummel-Ziedins K.E., Orfeo T., Callas P.W., Gissel M., Mann K.G., Bovill E.G. (2012) The prothrombotic phenotypes in familial protein C deficiency are differentiated by computational modeling of thrombin generation. PloS ONE, 7(9), e44378. CrossRef Scholar google search
Sage S.O., Pugh N., Mason M.J., Harper A.G.S. (2011) Monitoring the intracellular store Ca2+ concentration in agonist-stimulated, intact human platelets by using Fluo-5N. J. Thromb. Haemost., 9(3), 540–551. CrossRef Scholar google search
Mak D.-O.D., Foskett J.K. (2015) Inositol 1,4,5-trisphosphate receptors in the endoplasmic reticulum: A single-channel point of view. Cell Calcium, 58(1), 67–78. CrossRef Scholar google search
