Dynamically regulated miRNA-mRNA networks revealed by exercise

BMC Physiology

Volumn 13, Issue 1, 2013, Pages

  Tonevitsky, Alexander G ^a,b   Maltseva, Diana V ^c   Abbasi, Asghar ^d   Samatov, Timur R ^c   Sakharov, Dmitry A ^c   Shkurnikov, Maxim U ^b   Lebedev, Alexey E ^a   Galatenko, Vladimir V ^a   Grigoriev, Anatoly I ^e   Northoff, Hinnak ^d  

^a MOSCOW STATE UNIVERSITY   (Russian Federation)

^b INSTITUTE OF GENERAL PATHOLOGY AND PATHOPHYSIOLOGY   (Russian Federation)

^c SRC Bioclinicum   (Russian Federation)

^d UNIVERSITY OF TÜBINGEN   (Germany)

^e INSTITUTE OF BIOMEDICAL PROBLEMS   (Russian Federation)

Author keywords

Exercise; miRNA mRNA networks; Regulation

Indexed keywords

MESSENGER RNA; MICRORNA;

ADULT; ARTICLE; BLOOD; EXERCISE; HUMAN; MALE; METABOLISM; PHYSIOLOGY; YOUNG ADULT;

ADULT; EXERCISE; HUMANS; MALE; METABOLIC NETWORKS AND PATHWAYS; MICRORNAS; RNA, MESSENGER; YOUNG ADULT;

EID: 84878628395     PISSN: None     EISSN: 14726793     Source Type: Journal    
DOI: 10.1186/1472-6793-13-9     Document Type: Article

References (60)

1. MicroRNAs: genomics, biogenesis, mechanism, and function. Bartel DP, Cell 2004 116 281 297 10.1016/S0092-8674(04)00045-5 14744438
2. MicroRNAs of the immune system: roles in inflammation and cancer. Davidson-Moncada J, Papavasiliou FN, Tam W, Ann N Y Acad Sci 2010 1183 183 194 10.1111/j.1749-6632.2009.05121.x 20146715
3. MicroRNAs in vascular biology and vascular disease. Zhang C, J Cardiovasc Transl Res 2010 3 235 240 10.1007/s12265-010-9164-z 20560045
4. Rethinking the Warburg effect with Myc micromanaging glutamine metabolism. Dang CV, Cancer Res 2010 70 859 862 10.1158/0008-5472.CAN-09-3556 20086171
5. High responders to resistance exercise training demonstrate differential regulation of skeletal muscle microRNA expression. Davidsen PK, Gallagher IJ, Hartman JW, Tarnopolsky MA, Dela F, Helge JW, Timmons JA, Phillips SM, J Appl Physiol 2011 110 309 317 10.1152/japplphysiol.00901.2010 21030674
6. Dynamic regulation of circulating microRNA during acute exhaustive exercise and sustained aerobic exercise training. Baggish AL, Hale A, Weiner RB, Lewis GD, Systrom D, Wang F, Wang TJ, Chan SY, J Physiol 2011 589 3983 3994 10.1113/jphysiol.2011.213363 21690193
7. Evidence for microRNA involvement in exercise-associated neutrophil gene expression changes. Radom-Aizik S, Zaldivar F Jr, Oliver S, Galassetti P, Cooper DM, J Appl Physiol 2010 109 252 261 10.1152/japplphysiol.01291.2009 20110541
8. Effects of exercise on microRNA expression in young males peripheral blood mononuclear cells. Radom-Aizik S, Zaldivar F Jr, Leu SY, Adams GR, Oliver S, Cooper DM, Clin Transl Sci 2012 5 32 38 10.1111/j.1752-8062.2011.00384.x 22376254
9. Exercise training prevents the microvascular rarefaction in hypertension balancing angiogenic and apoptotic factors: role of microRNAs-16, -21, and -126. Fernandes T, Magalhães FC, Roque FR, Phillips MI, Oliveira EM, Hypertension 2012 59 513 520 10.1161/HYPERTENSIONAHA.111.185801 22215713
10. Impact of brief exercise on peripheral blood NK cell gene and microRNA expression in young adults. Radom-Aizik S, Zaldivar FP, Haddad F, Cooper DM, J Appl Physiol 2013 114 628 636 10.1152/japplphysiol.01341.2012 23288554
11. Circulating microRNA-126 increases after different forms of endurance exercise in healthy adults. Uhlemann M, Möbius-Winkler S, Fikenzer S, Adam J, Redlich M, Möhlenkamp S, Hilberg T, Schuler GC, Adams V, Eur J Prev Cardiol 2012 10.1177/2047487312467902
12. Circulating MicroRNAs and Aerobic Fitness-The HUNT-Study. Bye A, Røsjø H, Aspenes ST, Condorelli G, Omland T, Wisløff U, PLoS One 2013 8 57496 10.1371/journal.pone.0057496 23469005
13. Endurance exercise training attenuates leucine oxidation and BCOAD activation during exercise in humans. McKenzie S, Phillips SM, Carter SL, Lowther S, Gibala MJ, Tarnopolsky MA, Am J Physiol Endocrinol Metab 2000 278 580 587 10751189
14. Metabolomics investigation of exercise-modulated changes in metabolism in rat liver after exhaustive and endurance exercises. Huang CC, Lin WT, Hsu FL, Tsai PW, Hou CC, Eur J Appl Physiol 2010 108 557 566 10.1007/s00421-009-1247-7 19865828
15. Oxidative stress in phenylketonuria: what is the evidence? Ribas GS, Sitta A, Wajner M, Vargas CR, Cell Mol Neurobiol 2011 31 653 662 10.1007/s10571-011-9693-2 21516352
16. Simultaneous determination of methionine sulfoxide and methionine in blood plasma using gas chromatography-mass spectrometry. Mashima R, Nakanishi-Ueda T, Yamamoto Y, Anal Biochem 2003 313 28 33 10.1016/S0003-2697(02) 00537-7 12576054
17. Protein metabolism and endurance exercise. Gibala MJ, Sports Med 2007 37 337 340 10.2165/00007256-200737040-00016 17465602
18. Exercise-recruited NK cells display exercise-associated eHSP-70. Horn P, Kalz A, Lim CL, Pyne D, Saunders P, Mackinnon L, Peake J, Suzuki K, Exerc Immunol Rev 2007 13 100 111 18198664
19. Whole blood and leukocyte RNA isolation for gene expression analyses. Feezor RJ, Baker HV, Mindrinos M, Hayden D, Tannahill CL, Brownstein BH, Fay A, MacMillan S, Laramie J, Xiao W, Moldawer LL, Cobb JP, Laudanski K, Miller-Graziano CL, Maier RV, Schoenfeld D, Davis RW, Tompkins RG, Inflammation and Host Response to Injury, Large-Scale Collaborative Research Program, Physiol Genomics 2004 19 247 254 10.1152/physiolgenomics.00020.2004 15548831
20. Argonaute protein identity and pairing geometry determine cooperativity in mammalian RNA silencing. Broderick JA, Salomon WE, Ryder SP, Aronin N, Zamore PD, RNA 2011 17 1858 1869 10.1261/rna.2778911 21878547
21. Mammalian GW182 contains multiple Argonaute-binding sites and functions in microRNA-mediated translational repression. Takimoto K, Wakiyama M, Yokoyama S, RNA 2009 15 1078 1089 10.1261/rna.1363109 19398495
22. D-Serine exposure resulted in gene expression changes implicated in neurodegenerative disorders and neuronal dysfunction in male Fischer 344 rats. Davidson ME, Kerepesi LA, Soto A, Chan VT, Arch Toxicol 2009 83 747 762 10.1007/s00204-009-0405-3 19212759
23. Bcl2 suppresses DNA repair by enhancing c-Myc transcriptional activity. Jin Z, May WS, Gao F, Flagg T, Deng X, J Biol Chem 2006 281 14446 14456 10.1074/jbc.M511914200 16554306
24. MYC in breast tumor progression. Chen Y, Olopade OI, Expert Rev Anticancer Ther 2008 8 1689 1698 10.1586/14737140.8.10.1689 18925859
25. Akt activation emulates Chk1 inhibition and Bcl2 overexpression and abrogates G2 cell cycle checkpoint by inhibiting BRCA1 foci. Tonic I, Yu WN, Park Y, Chen CC, Hay N, J Biol Chem 2010 285 23790 23798 10.1074/jbc.M110.104372 20495005
26. Transcriptional autoregulation by BRCA1. De Siervi A, De Luca P, Byun JS, Di LJ, Fufa T, Haggerty CM, Vazquez E, Moiola C, Longo DL, Gardner K, Cancer Res 2010 70 532 542 10.1158/0008-5472.CAN-09-1477 20068145
27. Prediction of plant microRNA targets. Rhoades MW, Reinhart BJ, Lim LP, Burge CB, Bartel B, Bartel DP, Cell 2002 110 513 520 10.1016/S0092-8674(02) 00863-2 12202040
28. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Lewis BP, Burge CB, Bartel DP, Cell 2005 120 15 20 10.1016/j.cell.2004.12.035 15652477
29. MicroRNA-21 contributes to myocardial disease by stimulating MAP kinase signalling in fibroblasts. Thum T, Gross C, Fiedler J, Fischer T, Kissler S, Bussen M, Galuppo P, Just S, Rottbauer W, Frantz S, Castoldi M, Soutschek J, Koteliansky V, Rosenwald A, Basson MA, Licht JD, Pena JT, Rouhanifard SH, Muckenthaler MU, Tuschl T, Martin GR, Bauersachs J, Engelhardt S, Nature 2008 456 980 984 10.1038/nature07511 19043405
30. Identification of a microRNA signature of renal ischemia reperfusion injury. Godwin JG, Ge X, Stephan K, Jurisch A, Tullius SG, Iacomini J, Proc Natl Acad Sci USA 2010 107 14339 14344 10.1073/pnas.0912701107 20651252
31. MicroRNAs: the fine-tuners of Toll-like receptor signalling. O'Neill LA, Sheedy FJ, McCoy CE, Nat Rev Immunol 2011 11 163 175 10.1038/nri2957 21331081
32. Increased expression of peripheral blood leukocyte genes implicate CD14+ tissue macrophages in cellular intestine allograft rejection. Ashokkumar C, Ningappa M, Ranganathan S, Higgs BW, Sun Q, Schmitt L, Snyder S, Dobberstein J, Branca M, Jaffe R, Zeevi A, Squires R, Alissa F, Shneider B, Soltys K, Bond G, Abu-Elmagd K, Humar A, Mazariegos G, Hakonarson H, Sindhi R, Am J Pathol 2011 179 1929 1938 10.1016/j.ajpath.2011.06.040 21854741
33. MicroRNA 21 promotes glioma invasion by targeting matrix metalloproteinase regulators. Gabriely G, Wurdinger T, Kesari S, Esau CC, Burchard J, Linsley PS, Krichevsky AM, Mol Cell Biol 2008 28 5369 5380 10.1128/MCB.00479-08 18591254
34. Emerging roles of PDGF-D signaling pathway in tumor development and progression. Wang Z, Ahmad A, Li Y, Kong D, Azmi AS, Banerjee S, Sarkar FH, Biochim Biophys Acta 1806 2010 122 130
35. Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Hafner M, Landthaler M, Burger L, Khorshid M, Hausser J, Berninger P, Rothballer A, Ascano M Jr, Jungkamp AC, Munschauer M, Ulrich A, Wardle GS, Dewell S, Zavolan M, Tuschl T, Cell 2010 141 129 141 10.1016/j.cell.2010.03.009 20371350
36. Regulation of apoptosis signal-regulating kinase 1 by protein phosphatase 2Cepsilon. Saito J, Toriumi S, Awano K, Ichijo H, Sasaki K, Kobayashi T, Tamura S, Biochem J 2007 405 591 596 10.1042/BJ20070231 17456047
37. RhoBTB3: a Rho GTPase-family ATPase required for endosome to Golgi transport. Espinosa EJ, Calero M, Sridevi K, Pfeffer SR, Cell 2009 137 938 948 10.1016/j.cell.2009.03.043 19490898
38. Identification of blood biomarkers for psychosis using convergent functional genomics. Kurian SM, Le-Niculescu H, Patel SD, Bertram D, Davis J, Dike C, Yehyawi N, Lysaker P, Dustin J, Caligiuri M, Lohr J, Lahiri DK, Nurnberger JI Jr, Faraone SV, Geyer MA, Tsuang MT, Schork NJ, Salomon DR, Niculescu AB, Mol Psychiatry 2011 16 37 58 10.1038/mp.2009.117 19935739
39. Role of microRNAs in the reperfused myocardium towards post-infarct remodelling. Zhu H, Fan GC, Cardiovasc Res 2012 94 284 292 10.1093/cvr/cvr291 22038740
40. miR-24 Inhibits cell proliferation by targeting E2F2, MYC, and other cell-cycle genes via binding to "seedless" 3'UTR microRNA recognition elements. Lal A, Navarro F, Maher CA, Maliszewski LE, Yan N, O'Day E, Chowdhury D, Dykxhoorn DM, Tsai P, Hofmann O, Becker KG, Gorospe M, Hide W, Lieberman J, Mol Cell 2009 35 610 625 10.1016/j.molcel.2009.08.020 19748357
41. Novel insights into the pathomechanisms of skeletal muscle channelopathies. Burge JA, Hanna MG, Curr Neurol Neurosci Rep 2012 12 62 69 10.1007/s11910-011-0238-3 22083238
42. Verification of expressions of Kir2 as potential peripheral biomarkers in lymphocytes from patients with Parkinson's disease. Gui YX, Wan Y, Xiao Q, Wang Y, Wang G, Chen SD, Neurosci Lett 2011 505 104 108 10.1016/j.neulet.2011.09.070 22001575
43. MicroRNA-27a promotes myoblast proliferation by targeting myostatin. Huang Z, Chen X, Yu B, He J, Chen D, Biochem Biophys Res Commun 2012 423 265 269 10.1016/j.bbrc.2012.05.106 22640741
44. Coordinated roles of ST3Gal-VI and ST3Gal-IV sialyltransferases in the synthesis of selectin ligands. Yang WH, Nussbaum C, Grewal PK, Marth JD, Sperandio M, Blood 2012 120 1015 1026 10.1182/blood-2012-04-424366 22700726
45. MicroRNAs modulate hematopoietic lineage differentiation. Chen CZ, Li L, Lodish HF, Bartel DP, Science 2004 303 83 86 10.1126/science.1091903 14657504
46. miR-181a is an intrinsic modulator of T cell sensitivity and selection. Li QJ, Chau J, Ebert PJ, Sylvester G, Min H, Liu G, Braich R, Manoharan M, Soutschek J, Skare P, Klein LO, Davis MM, Chen CZ, Cell 2007 129 147 161 10.1016/j.cell.2007.03.008 17382377
47. A-kinase anchoring proteins: different partners, different dance. Chen L, Kass RS, Nat Cell Biol 2005 7 1050 1051 16385733
48. The human sugar-phosphate/phosphate exchanger family SLC37. Bartoloni L, Antonarakis SE, Pflugers Arch 2004 447 780 783 10.1007/s00424-003-1105-0 12811562
49. Aerobic parameters of exercise as a function of body size during growth in children. Cooper DM, Weiler-Ravell D, Whipp BJ, Wasserman K, J Appl Physiol 1984 56 628 634 6706770
50. A new method for detecting anaerobic threshold by gas exchange. Beaver WL, Wasserman K, Whipp BJ, J Appl Physiol 1986 60 2020 2027 3087938
51. Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach. Floegel A, Stefan N, Yu Z, Mühlenbruch K, Drogan D, Joost HG, Fritsche A, Häring HU, Hrabe de Angelis M, Peters A, Roden M, Prehn C, Wang-Sattler R, Illig T, Schulze MB, Adamski J, Boeing H, Pischon T, Diabetes 2013 62 639 648 10.2337/db12-0495 23043162
52. Passing the anaerobic threshold is associated with substantial changes in the gene expression profile in white blood cells. Sakharov DA, Maltseva DV, Riabenko EA, Shkurnikov MU, Northoff H, Tonevitsky AG, Grigoriev AI, Eur J Appl Physiol 2012 112 963 972 10.1007/s00421-011-2048-3 21717121
53. Bioconductor: open software development for computational biology and bioinformatics. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J, Genome Biol 2004 5 80 10.1186/gb-2004-5-10-r80 15461798
54. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, Speed TP, Biostatistics 2003 4 249 264 10.1093/biostatistics/4.2.249 12925520
55. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bolstad BM, Irizarry RA, Astrand M, Speed TP, Bioinformatics 2003 19 185 193 10.1093/bioinformatics/19.2.185 12538238
56. Tukey JW, Exploratory data analysis Reading: Addison-Wesley 1977
57. Limma: linear models for microarray data. Smyth GK, Bioinformatics and computational biology solutions using R and bioconductor New York: Springer, Gentleman R, Carey V, Dudoit S, Irizarry R, Huber W, 2005 397 420
58. Yang YH, Speed TP, Design and analysis of comparative microarray experiments In: Statistical analysis of gene expression microarray data. Edited by Speed TP. Chapman and Hall/CRC Press 2003 35 93
59. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Benjamini Y, Hochberg Y, J R Statist Soc B (Methodological) 1995 57 289 300
60. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. da Huang W, Sherman BT, Lempicki RA, Nat Protoc 2009 4 44 57 19131956