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Том 15   Выпуск 1   Год 2020
Акбердин И.Р.1,2,3, Вертышев А.Ю.4, Пинтус С.С.1,5, Попов Д.В.6, Колпаков Ф.А.1,5

Математическая модель, связывающая Ca2+-зависимый сигнальный путь с регуляцией экспрессии генов в клетках скелетной мышцы человека

Математическая биология и биоинформатика. 2020;15(1):20-39.

doi: 10.17537/2020.15.20.

Список литературы

 

  1. Pedersen B.K., Febbraio M.A. Muscles, exercise and obesity: skeletal muscle as a secretory organ. Nature Reviews Endocrinology. 2012;8(8):457–465. doi: 10.1038/nrendo.2012.49
  2. Hawley J.A., Hargreaves M., Joyne, M.J., Zierath J.R. Integrative biology of exercise. Cell. 2014;159(4):38–749. doi: 10.1016/j.cell.2014.10.029
  3. Koulmann N., Bigard A.X. Interaction between signaling pathways involved in skeletal muscle responses to endurance exercise. Pflügers Archiv. 2006;452(2):125. doi: 10.1007/s00424-005-0030-9
  4. Neubauer O., Sabapathy S., Ashton K.J., Desbrow B., Peake J.M., Lazarus R., Wessner B., Cameron-Smith D., Wagne, K.H., Haseler L.J., Bulmer A.C. Time course-dependent changes in the transcriptome of human skeletal muscle during recovery from endurance exercise: from inflammation to adaptive remodeling. Journal of Applied Physiology. 2013;116(3):274–287. doi: 10.1152/japplphysiol.00909.2013
  5. Vissing K., Schjerling P. Simplified data access on human skeletal muscle transcriptome responses to differentiated exercise. Scientific data. 2014;1:140041. doi: 10.1038/sdata.2014.41
  6. Popov D.V., Makhnovskii P.A., Kurochkina N.S., Lysenko E.A., Vepkhvadze T.F., Vinogradova O.L. Intensity-dependent gene expression after aerobic exercise in endurance-trained skeletal muscle. Biology of sport. 2018;35(3):277. doi: 10.5114/biolsport.2018.77828
  7. Dickinson J.M., D’Lugos A.C., Naymik M.A., Siniard A.L., Wolfe A.J., Curtis D.R., Huentelman M.J., Carroll C.C. Transcriptome response of human skeletal muscle to divergent exercise stimuli. Journal of Applied Physiology. 2018;124(6):1529–1540. doi: 10.1152/japplphysiol.00014.2018
  8. Popov D.V., Makhnovskii P.A., Shagimardanova E.I., Gazizova G.R., Lysenko E.A., Gusev O.A., Vinogradova O.L. Contractile activity-specific transcriptome response to acute endurance exercise and training in human skeletal muscle. American Journal of Physiology-Endocrinology and Metabolism. 2019;316(4):E605–E614. doi: 10.1152/ajpendo.00449.2018
  9. Li Y., Dash R.K., Kim J., Saidel G.M., Cabrera M.E. Role of NADH/NAD+ transport activity and glycogen store on skeletal muscle energy metabolism during exercise: in silico studies. American Journal of Physiology-Cell Physiology. 2009;296(1):25–46. doi: 10.1152/ajpcell.00094.2008
  10. Akberdin I.R., Kazantsev F.V., Ermak T.V., Timonov V.S., Khlebodarova T.M., Likhoshvai V.A. In Silico Cell: Challenges and Perspectives. Mathematical Biology and Bioinformatics. 2013;8(1):295–315. doi: 10.17537/2013.8.295
  11. Kiselev I.N., Akberdin I.R., Vertyshev A.Y., Popov D.V., Kolpakov F.A. A Modular Visual Model of Energy Metabolism in Human Skeletal Muscle. Mathematical Biology and Bioinformatics. 2019;14(2):373–392. doi: 10.17537/2019.14.373
  12. Kolpakov F., Akberdin I., Kashapov T., Kiselev I., Kolmykov S., Kondrakhin Y., Kutumova E., Mandrik N., Pintus S., Ryabova A., Sharipov R., Yevshin I., Kel A. BioUML: an integrated environment for systems biology and collaborative analysis of biomedical data. Nucleic Acids Research. 2019;47(W1):W225–W233. doi: 10.1093/nar/gkz440
  13. Scarpulla R.C. Transcriptional paradigms in mammalian mitochondrial biogenesis and function. Physiological Reviews. 2008;88(2):611–638. doi: 10.1152/physrev.00025.2007
  14. Olesen J., Kiilerich K., Pilegaard H. PGC-1α-mediated adaptations in skeletal muscle. Pflügers Archiv-European Journal of Physiology. 2010;460(1):153–162. doi: 10.1007/s00424-010-0834-0
  15. Pearen M.A., Eriksson N.A., Fitzsimmons R.L., Goode J.M., Martel N., Andrikopoulos S., Muscat G.E. The nuclear receptor, Nor-1, markedly increases type II oxidative muscle fibers and resistance to fatigue. Molecular Endocrinology. 2012;26(3):372–384. doi: 10.1210/me.2011-1274
  16. Pearen M.A., Goode J.M., Fitzsimmons R.L., Eriksson N.A., Thomas G.P., Cowin G.J., Wang S.C.M., Tuong Z.K., Muscat G.E. Transgenic muscle-specific Nor-1 expression regulates multiple pathways that effect adiposity, metabolism, and endurance. Molecular Endocrinology. 2013;27(11):1897–1917. doi: 10.1210/me.2013-1205
  17. Yoshioka T., Inagaki K., Noguchi T., Sakai M., Ogawa W., Hosooka T., Iguchi H., Watanabe E., Matsuki Y., Hiramatsu R., Kasuga M. Identification and characterization of an alternative promoter of the human PGC-1α gene. Biochemical and Biophysical Research Communications. 2009;381(4):537–543. doi: 10.1016/j.bbrc.2009.02.077
  18. Bruno N.E., Kelly K.A., Hawkins R., Bramah‐Lawani M., Amelio A.L., Nwachukwu J.C., Nettles K.W., Conkright M.D. Creb coactivators direct anabolic responses and enhance performance of skeletal muscle. The EMBO journal. 2014;33(9):1027–1043. doi: 10.1002/embj.201386145
  19. Goode J.M., Pearen M.A., Tuong Z.K., Wang S.C.M., Oh T.G., Shao E.X., Muscat G.E. The nuclear receptor, Nor-1, induces the physiological responses associated with exercise. Molecular Endocrinology. 2016;30(6):660–676. doi: 10.1210/me.2015-1300
  20. Berdeaux R., Hutchins C. Anabolic and pro-metabolic functions of CREB-CRTC in skeletal muscle: advantages and obstacles for type 2 diabetes and cancer cachexia. Frontiers in Endocrinology. 2019;10:535. doi: 10.3389/fendo.2019.00535
  21. Cui J., Kaandorp J.A. Simulating complex calcium-calcineurin signaling network. In: International Conference on Computational Science. Berlin, Heidelberg: Springer; 2008. P. 110–119. doi: 10.1007/978-3-540-69389-5_14
  22. Saucerman J.J., Bers D.M. Calmodulin mediates differential sensitivity of CaMKII and calcineurin to local Ca2+ in cardiac myocytes. Biophysical Journal. 2008;95(10):4597–4612. doi: 10.1529/biophysj.108.128728
  23. Eilers W., Gevers W., Van Overbeek D., De Haan A., Jaspers R.T., Hilbers P.A., Van Riel N., Flück M. Muscle-type specific autophosphorylation of CaMKII isoforms after paced contractions. BioMed Research International. 2014. Article ID 943806. doi: 10.1155/2014/943806
  24. Murgia M., Toniolo L., Nagaraj N., Ciciliot S., Vindigni V., Schiaffino S., Reggiani C., Mann M. Single muscle fiber proteomics reveals fiber-type-specific features of human muscle aging. Cell Reports. 2017;19(11):2396–2409. doi: 10.1016/j.celrep.2017.05.054
  25. Yates L.D., Greaser M.L., Huxley H.E. Quantitative determination of myosin and actin in rabbit skeletal muscle. Journal of Molecular Biology. 1983;168(1):123–141. doi: 10.1016/S0022-2836(83)80326-X
  26. Hasten D.L., Morris G.S., Ramanadham S., Yarasheski K.E. Isolation of human skeletal muscle myosin heavy chain and actin for measurement of fractional synthesis rates. American Journal of Physiology-Endocrinology and Metabolism. 1998;275(6):E1092–E1099. doi: 10.1152/ajpendo.1998.275.6.E1092
  27. Borina E., Pellegrino M.A., D'Antona G., Bottinelli R. Myosin and actin content of human skeletal muscle fibers following 35 days bed rest. Scandinavian Journal of Medicine & Science in Sports. 2010;20(1):65–73. doi: 10.1111/j.1600-0838.2009.01029.x
  28. Carroll C.C., Carrithers J.A., Trappe T.A. Contractile protein concentrations in human single muscle fibers. Journal of Muscle Research and Cell Motility. 2004;25(1):55–59. doi: 10.1023/B:JURE.0000021362.55389.6b
  29. Wilhelm M., Schlegl J., Hahne H., Gholami A.M., Lieberenz M., Savitski M.M., Ziegler E., Butzmann L., Gessulat S., Marx H., Mathieson T. Mass-spectrometry-based draft of the human proteome. Nature. 2014;509(7502):582. doi: 10.1038/nature13319
  30. Edfors F., Danielsson F., Hallström B.M., Käll L., Lundberg E., Pontén F., Forsström B., Uhlén M. Gene‐specific correlation of RNA and protein levels in human cells and tissues. Molecular systems biology. 2016;12(10). doi: 10.15252/msb.20167144
  31. Fortelny N., Overall C.M., Pavlidis P., Freue G.V.C. Can we predict protein from mRNA levels? Nature. 2017;547(7664):E19. doi: 10.1038/nature22293
  32. Wang D., Eraslan B., Wieland T., Hallström B., Hopf T., Zolg D.P., Zecha J., Asplund A., Li L.H., Meng C., Frejno M. A deep proteome and transcriptome abundance atlas of 29 healthy human tissues. Molecular systems biology. 2019;15(2). doi: 10.15252/msb.20188503
  33. Le Novere N., Hucka M., Mi H., Moodie S., Schreiber F., Sorokin A., Demir E., Wegner K., Aladjem M.I., Wimalaratne S.M., Bergman F.T. The systems biology graphical notation. Nature Biotechnology. 2009;27(8):735. doi: 10.1038/nbt.1558
  34. Likhoshvai V., Ratushny A. Generalized Hill function method for modeling molecular processes. Journal of Bioinformatics and Computational Biology. 2007;5(02b):521–531. doi: 10.1142/S0219720007002837
  35. Sonntag A.G., Dalle Pezze P., Shanley D.P., Thedieck K. A modelling–experimental approach reveals insulin receptor substrate (IRS)‐dependent regulation of adenosine monosphosphate‐dependent kinase (AMPK) by insulin. The FEBS Journal. 2012;279(18):3314–3328. doi: 10.1111/j.1742-4658.2012.08582.x
  36. Brown P.N., Byrne G.D., Hindmarsh A.C. VODE: A variable-coefficient ODE solver. SIAM Journal on Scientific and Statistical Computing. 1989;10(5):1038–1051. doi: 10.1137/0910062
  37. Benders A.A., Oosterhof A., Wevers R.A., Veerkamp J.H. Excitation-contraction coupling of cultured human skeletal muscle cells and the relation between basal cytosolic Ca2+ and excitability. Cell calcium. 1997;21(1):81–91. doi: 10.1016/S0143-4160(97)90099-3
  38. Koopman W.J., Willems P.H., Oosterhof A., van Kuppevelt T.H., Gielen S.C. Amplitude modulation of nuclear Ca2+ signals in human skeletal myotubes: a possible role for nuclear Ca2+ buffering. Cell calcium. 2005;38(2):141–152. doi: 10.1016/j.ceca.2005.06.003
  39. Gejl K.D., Hvid L.G., Willis S.J., Andersson E., Holmberg H.C., Jensen R., Frandsen U., Hansen J., Plomgaard P., Ørtenblad N. Repeated high‐intensity exercise modulates Ca2+ sensitivity of human skeletal muscle fibers. Scandinavian Journal of Medicine & Science in Sports. 2016;26(5):488–497. doi: 10.1111/sms.12483
  40. Rabitz H., Kramer M., Dacol D. Sensitivity analysis in chemical kinetics. Annual Review of Physical Chemistry. 1983;34(1):419–461. doi: 10.1146/annurev.pc.34.100183.002223
  41. Jensen T.E., Rose A.J., Jørgens S.B., Brandt N., Schjerling P., Wojtaszewski J.F., Richter E.A. Possible CaMKK-dependent regulation of AMPK phosphorylation and glucose uptake at the onset of mild tetanic skeletal muscle contraction. American Journal of Physiology-Endocrinology and Metabolism. 2007;292(5):E1308–E1317. doi: 10.1152/ajpendo.00456.2006
  42. Abbott M.J., Edelman A.M., Turcotte L.P. CaMKK is an upstream signal of AMP-activated protein kinase in regulation of substrate metabolism in contracting skeletal muscle. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology. 2009;297(6):R1724–R1732. doi: 10.1152/ajpregu.00179.2009
  43. Gehlert S., Bloch W., Suhr F. Ca2+-dependent regulations and signaling in skeletal muscle: from electro-mechanical coupling to adaptation. International Journal of Molecular Sciences. 2015;16(1):1066–1095. doi: 10.3390/ijms16011066
  44. Egan B., Zierath J.R. Exercise metabolism and the molecular regulation of skeletal muscle adaptation. Cell Metabolism. 2013;17(2):162–184. doi: 10.1016/j.cmet.2012.12.012
  45. Popov D.V. Adaptation of skeletal muscle to contractile activity of various duration and intensity: role of PGC-1a. Biochemistry (Moscow). 2018;83(6):781–799.
  46. Amoasii L., Holland W., Sanchez-Ortiz E., Baskin K.K., Pearson M., Burgess S.C., Nelson B.R., Bassel-Duby R., Olson E.N. A MED13-dependent skeletal muscle gene program controls systemic glucose homeostasis and hepatic metabolism. Genes & development. 2016;30(4):434–446. doi: 10.1101/gad.273128.115
  47. Amoasii L., Sanchez-Ortiz E., Fujikawa T., Elmquist J.K., Bassel-Duby R., Olson E.N. NURR1 activation in skeletal muscle controls systemic energy homeostasis. PNAS. 2019;116(23):11299–11308. doi: 10.1073/pnas.1902490116
  48. Chao L.C., Wroblewski K., Ilkayeva O.R., Stevens R.D., Bain J., Meyer G.A., Schenk S., Martinez L., Vergnes L., Narkar V.A., Drew B.G. Skeletal muscle Nur77 expression enhances oxidative metabolism and substrate utilization. Journal of Lipid Research. 2012;53(12):2610–2619. doi: 10.1194/jlr.M029355
  49. Hai T., Curran T. Crossfamily dimerization of transcription factors Fos/Jun and ATF/CREB alters DNA binding specificity. PNAS. 1991;88:3720–3724. doi: 10.1073/pnas.88.9.3720
  50. Newman J.R., Keating A.E. Comprehensive identification of human bZIP interactions with coiled-coil arrays. Science. 2003;300(5628):2097–2101. doi: 10.1126/science.1084648
  51. Matys V., Fricke E., Geffers R., Gobling E., Haubrock M., Hehl R., Hornischer K., Karas D., Kel A.E., Kel-Margoulis O.V., Kloos D.U. TRANSFAC®: transcriptional regulation, from patterns to profiles. NAR. 2003;31(1):374–378. doi: 10.1093/nar/gkg108
  52. Yevshin I., Sharipov R., Kolmykov S., Kondrakhin Y., Kolpakov F. GTRD: a database on gene transcription regulation – 2019 update. NAR. 2018;47(D1):D100–D105. doi: 10.1093/nar/gky1128
  53. Zhang X., Odom D.T., Koo S.H., Conkright M.D., Canettieri G., Best J., Chen H., Jenner R., Herbolsheimer E., Jacobsen E., Kadam S. Genome-wide analysis of cAMP-response element binding protein occupancy, phosphorylation, and target gene activation in human tissues. PNAS. 2005;102(12):4459–4464. doi: 10.1073/pnas.0501076102
  54. Pattamaprapanont P., Garde C., Fabre O., Barrès R. Muscle contraction induces acute hydroxymethylation of the exercise-responsive gene Nr4a3. Frontiers in Endocrinology. 2016;7:165. doi: 10.3389/fendo.2016.00165
  55. Foteinou P.T., Venkataraman A., Francey L.J., Anafi R.C., Hogenesch J.B., Doyle F.J. Computational and experimental insights into the circadian effects of SIRT1. PNAS. 2018;115(45):11643–11648. doi: 10.1073/pnas.1803410115
  56. Catoire M., Mensink M., Boekschoten M.V., Hangelbroek R., Müller M., Schrauwen P., Kersten S. Pronounced effects of acute endurance exercise on gene expression in resting and exercising human skeletal muscle. PloS One. 2012;7(11):e51066. doi: 10.1371/journal.pone.0051066
  57. Fu M., Zhang J., Lin Y., Zhu X., Ehrengruber M.U., Chen Y.E. Early growth response factor-1 is a critical transcriptional mediator of peroxisome proliferator-activated receptor-γ1 gene expression in human aortic smooth muscle cells. Journal of Biological Chemistry. 2002;277(30):26808–26814. doi: 10.1074/jbc.M203748200
  58. Mingui F.U., Zhang J., Yimin L.I.N., Xiaojun Z.H.U., Luning Z.H.A.O., Ahmad M., Ehrengruber M.U. Early stimulation and late inhibition of peroxisome proliferator-activated receptor gamma (PPARgamma) gene expression by transforming growth factor beta in human aortic smooth muscle cells: role of early growth-response factor-1 (Egr-1), activator protein 1 (AP1) and Smads. Biochemical Journal. 2003;370(3):1019–1025. doi: 10.1042/bj20021503
  59. Pardo P.S., Mohamed J.S., Lopez M.A., Boriek A.M. Induction of Sirt1 by mechanical stretch of skeletal muscle through the early response factor EGR1 triggers an antioxidative response. Journal of Biological Chemistry. 2011;286(4):2559–2566. doi: 10.1074/jbc.M110.149153
  60. Lin C.Y., Lovén J., Rahl P.B., Paranal R.M., Burge C.B., Bradner J.E., Lee T.I., Young R.A. Transcriptional amplification in tumor cells with elevated c-Myc. Cell. 2012;151(1):56–67. doi: 10.1016/j.cell.2012.08.026
  61. Nie Z., Hu G., Wei G., Cui K., Yamane A., Resch W., Wang R., Green D.R., Tessarollo L., Casellas R., Zhao K. c-Myc is a universal amplifier of expressed genes in lymphocytes and embryonic stem cells. Cell. 2012;151(1):68–79. doi: 10.1016/j.cell.2012.08.033
  62. Rahl P.B., Young R.A. MYC and transcription elongation. Cold Spring Harbor Perspectives in Medicine. 2014;4(1):a020990. doi: 10.1101/cshperspect.a020990
  63. Frank S.R., Parisi T., Taubert S., Fernandez P., Fuchs M., Chan H.M., Livingston D.M., Amati B. MYC recruits the TIP60 histone acetyltransferase complex to chromatin. EMBO reports. 2003;4(6):575–580. doi: 10.1038/sj.embor.embor861
  64. Faiola F., Liu X., Lo S., Pan S., Zhang K., Lymar E., Farina A., Martinez E. Dual regulation of c-Myc by p300 via acetylation-dependent control of Myc protein turnover and coactivation of Myc-induced transcription. Molecular and Cellular Biology. 2005;25(23):10220–10234. doi: 10.1128/MCB.25.23.10220-10234.2005
  65. Guccione E., Martinato F., Finocchiaro G., Luzi L., Tizzoni L., Dall'Olio V., Zardo G., Nervi C., Bernard L., Amati B. Myc-binding-site recognition in the human genome is determined by chromatin context. Nature Cell Biology. 2006;8(7):764. doi: 10.1038/ncb1434
  66. Knoepfler P.S., Zhang X.Y., Cheng P.F., Gafken P.R., McMahon S.B., Eisenman R.N. Myc influences global chromatin structure. The EMBO Journal. 2006;25(12):2723–2734. doi: 10.1038/sj.emboj.7601152
  67. Mastropasqua F., Girolimetti G. and Shoshan M. PGC1α: friend or foe in cancer? Genes. 2018;9(1):48. doi: 10.3390/genes9010048
  68. Tan Z., Luo X., Xiao L., Tang M., Bode A.M., Dong Z., Cao Y. The role of PGC1α in cancer metabolism and its therapeutic implications. Molecular Cancer Therapeutics. 2016;15(5):774–782. doi: 10.1158/1535-7163.MCT-15-0621
  69. Ahuja P., Zhao P., Angelis E., Ruan H., Korge P., Olson A., Wang Y., Jin E.S., Jeffrey F.M., Portman M., MacLellan W.R. Myc controls transcriptional regulation of cardiac metabolism and mitochondrial biogenesis in response to pathological stress in mice. The Journal of Clinical Investigation. 2010;120(5):1494–1505. doi: 10.1172/JCI38331
  70. Sancho P., Burgos-Ramos E., Tavera A., Kheir T.B., Jagust P., Schoenhals M., Barneda D., Sellers K., Campos-Olivas R., Graña O., Viera C.R. MYC/PGC-1α balance determines the metabolic phenotype and plasticity of pancreatic cancer stem cells. Cell Metabolism. 2015;22(4):590–605. doi: 10.1016/j.cmet.2015.08.015
Содержание
Оригинальная статья
Мат. биол. и биоинф.
2020;15(1):20-39
doi: 10.17537/2020.15.20
опубликована на рус. яз.

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