Research Article

Identification of Expressed miRNAs in Human Rheumatoid Arthritis Using Computational Approach – Discovery of a New miR-7167 from Human

Author(s): Simon Durai Raj Christian, Krishnaraj Thirugnanasambantham, Mohamed Ibrahim Hairul Islam, Mathan Kumar Sudalaimuthu, Sandhya Sundaram, Ganapathy Ashok, Venugopal Senthilkumar, Senguttuvan Muralidaran and Saravanan Subramanian*

Volume 8, Issue 2, 2019

Page: [147 - 154] Pages: 8

DOI: 10.2174/2211536608666181204111438

Abstract

Background: Rheumatoid Arthritis (RA) is a chronic inflammatory and autoimmune disease leading to bones and joints destruction. It is one of the major causes of lifetime disability and mortality among humans in the developing and developed countries. It was evident that epigenetic dysregulation is related to the pathogenesis of RA. MicroRNAs (miRNAs) are small non-coding RNAs that are epigenetic regulators for diverse biological processes and also provided novel molecular insights in the formation of arthritis.

Objective: The influences of miRNAs in the alteration of gene regulation during the pathogenesis of arthritis were exposed in recent years.

Method: The computational approach to identify miRNA through EST-based homology is more powerful, economical and time-efficient. In this study, we applied EST-based homology search to identify miRNAs responsible for the development of arthritis in human beings.

Results: Our study on 36519 ESTs in human RA condition revealed the expression of four miRNAs, HSA-miR-198, HSA-miR-4647, has-miR-7167-5p and has-miR-7167-3p. The present study is the first report about has-miR-7167 that was homologous to Macaca mulatta.

Conclusion: The predicted targets of these identified miRNAs revealed many biological functions in the pathogenesis of RA. Further elaborated studies on these miRNAs will help to understand their function in the development of RA and the use of miRNAs as therapeutic targets in the future.

Keywords: Arthritis, EST, human, miRNA target, autoimmune, joints.

Graphical Abstract
[1]
Saravanan S, Islam VI, Babu NP, et al. Swertiamarin attenuates inflammation mediators via modulating NF- κB/I κB and JAK2/STAT3 transcription factors in adjuvant induced arthritis. Eur J Pharm Sci 2014; 56: 70-86.
[2]
Firestein GS. Invasive fibroblast-like synoviocytes in rheumatoid arthritis. Passive responders or transformed aggressors? Arthritis Rheumatol 1996; 39: 1781-90.
[3]
Hairul-Islam MI, Saravanan S, Thirugnanasambantham K, et al. Swertiamarin, a natural steroid, prevent bone erosion by modulating rankl/rank/opg signaling. Int Immunopharmacol 2017; 53: 114-24.
[4]
Saravanan S, Babu NP, Pandikumar P, et al. Therapeutic effect of Saraca asoca (roxb.) wilde on lysosomal enzymes and collagen metabolism in adjuvant induced arthritis. Inflammopharmacology 2011; 19: 317-25.
[5]
Yang M, Xiao C, Wu Q, et al. Anti-inflammatory effect of sanshuibaihu decoction may be associated with nuclear factor-kappa B and p38 MAPK alpha in collagen-induced arthritis in rat. J Ethnopharmacol 2010; 127: 264-73.
[6]
Generali E, Ceribelli A, Stazi MA, et al. Lessons learned from twins in autoimmune and chronic inflammatory diseases. J Autoimmun 2017; 83: 51-61.
[7]
Kato M, Yasuda S, Atsumi T. The role of genetics and epigenetics in rheumatic diseases: are they really a target to be aimed at? Rheumatol Int 2018; 38(8): 1333-8.
[8]
Zhang M, Lygrisse K, Wang J. Role of microRNA in osteoarthritis. J Arthritis 2017; 6: 239.
[9]
Alivernini S, Gremese E, McSharry C, et al. MicroRNA-155-at the critical interface of innate and adaptive immunity in arthritis. Front Immunol 2018; 8: 1932.
[10]
Huang Y, Shen XJ, Zou Q, et al. Biological functions of micrornas: a review. J Physiol Biochem 2011; 67: 129-39.
[11]
Ono K, Horie T, Nishino T, et al. MicroRNAs and high-density lipoprotein cholesterol metabolism. Int Heart J 2015; 56: 365-71.
[12]
Zhang B, Pan X, Wang Q, et al. Computational identification of microRNAs and their targets. Comput Biol Chem 2006; 30: 395-407.
[13]
Parkinson J, Blaxter M. Expressed sequence tags: an overview. Methods Mol Biol 2009; 533: 1-12.
[14]
Altschul SF, Gish W, Miller W, et al. Basic local alignment search tool. J Mol Biol 1990; 215: 403-10.
[15]
Griffiths-Jones S. The microRNA registry. Nucleic Acids Res 2004; 32: D109-11.
[16]
Griffiths-Jones S, Saini HK, van Dongen S, et al. Mirbase: Tools for microrna genomics. Nucleic Acids Res 2008; 36: D154-8.
[17]
Camacho C, Coulouris G, Avagyan V, et al. Blast+: architecture and applications. BMC Bioinformatics 2009; 10: 421.
[18]
Altschul SF, Madden TL, Schaffer AA, et al. Gapped blast and psi-blast: A new generation of protein database search programs. Nucleic Acids Res 1997; 25: 3389-402.
[19]
Zuker M. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 2003; 31: 3406-15.
[20]
Agarwal V, Bell GW, Nam JW, et al. Predicting effective microRNA target sites in mammalian mRNAs. eLife 2015; 12: 4.
[21]
Krek A, Grun D, Poy MN, et al. Combinatorial microRNA target predictions. Nat Genet 2005; 37: 495-500.
[22]
Wong N, Wang X. Mirdb: an online resource for microrna target prediction and functional annotations. Nucleic Acids Res 2015; 43: D146-52.
[23]
Wang X. Improving microrna target prediction by modeling with unambiguously identified microRNA-target pairs from clip-ligation studies. Bioinformatics 2016; 32: 1316-22.
[24]
Rehmsmeier M, Steffen P, Hochsmann M, et al. Fast and effective prediction of microRNA/target duplexes. RNA 2004; 10: 1507-17.
[25]
Thompson JD, Higgins DG, Gibson TJ. Clustal W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 1994; 22: 4673-80.
[26]
Kumar S, Stecher G, Tamura K. Mega7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol 2016; 33: 1870-4.
[27]
Ceribelli A, Nahid MA, Satoh M, et al. MicroRNAs in rheumatoid arthritis. FEBS Lett 2011; 585: 3667-74.
[28]
Lagos-Quintana M, Rauhut R, Lendeckel W, et al. Identification of novel genes coding for small expressed RNAs. Science 2001; 294: 853-8.
[29]
Kwak PB, Wang QQ, Chen XS, et al. Enrichment of a set of microRNAs during the cotton fiber development. BMC Genomics 2009; 10: 457.
[30]
Weber MJ. New human and mouse microrna genes found by homology search. FEBS J 2005; 272: 59-73.
[31]
Nam JW, Lee WJ, Zhang BT. 2004. Computational methods for identification of human microRNA precursors.Trends in Artificial Intelligence of the 8th Pacific Rim, August 9-13, 2004, Auckland, New Zealand, 2004.
[32]
Bentwich I, Avniel A, Karov Y, et al. Identification of hundreds of conserved and nonconserved human microRNAs. Nat Genet 2005; 37: 766-70.
[33]
Chan EKL, Satoh M, Pauley KM. Contrast in aberrant microRNA expression in systemic lupus erythematosus and rheumatoid arthritis: is microRNA-146 all we need? Arthritis Rheum 2009; 60(4): 912-5.
[34]
Brenner M, Gulko PS. The arthritis severity locus Cia5a regulates the expression of inflammatory mediators including Syk pathway genes and proteases in pristane-induced arthritis. BMC Genomics 2012; 13: 710.
[35]
Cavaillès V, Dauvois S, L’Horset F, et al. Nuclear factor rip140 modulates transcriptional activation by the estrogen receptor. EMBO J 1995; 14: 3741-51.
[36]
Cutolo M, Capellino S, Montagna P, et al. New roles for estrogens in rheumatoid arthritis. Clin Exp Rheumatol 2003; 21: 687-90.
[37]
Chen H, Zhu H, Zhang K, et al. Estrogen deficiency accelerates lumbar facet joints arthritis. Sci Rep 2017; 7: 1379.
[38]
Bhattacharjee M, Balakrishnan L, Renuse S, et al. Synovial fluid proteome in rheumatoid arthritis. Clin Proteomics 2016; 13: 12.
[39]
Lorenz HM. T-cell-activation inhibitors in rheumatoid arthritis. BioDrugs 2003; 17: 263-70.
[40]
Lee SH, Park JS, Byun JK, et al. PTEN ameliorates autoimmune arthritis through down-regulating STAT3 activation with reciprocal balance of Th17 and tregs. Sci Rep 2016; 6: 34617.
[41]
Nohr E, Lee LH, Cates JM, et al. Diagnostic value of histone 3 mutations in osteoclast-rich bone tumors. Hum Pathol 2017; 68: 119-27.
[42]
Wang F, Chen FF, Gao WB, et al. Identification of citrullinated peptides in the synovial fluid of patients with rheumatoid arthritis using LC-MALDI-TOF/TOF. Clin Rheumatol 2016; 35: 2185-94.
[43]
Lenert A, Fardo DW. Novel non-coding RNAs associated with rheumatoid arthritis in Asians by gene-based testingArthritis Rheumatol 2017; 69 (suppl 10), Abstract no 1009
[44]
Gebauer M, Saas J, Haag J, et al. Repression of anti-proliferative factor tob1in osteoarthritic cartilage. Arthritis Res Ther 2005; 7: R274.
[45]
Alam I, Koller DL, Canete T, et al. Fine mapping of bone structure and strength QTLs in heterogeneous stock rat. Bone 2015; 81: 417-26.
[46]
Muslin AJ. MAPK signalling in cardiovascular health and disease: molecular mechanisms and therapeutic targets. Clin Sci (Lond) 2008; 115(7): 203-18.
[47]
Schon S, Huep G, Prante C, et al. Mutational and functional analyses of xylosyltransferases and their implication in osteoarthritis. Osteoarthritis Cartilage 2006; 14: 442-8.
[48]
Lopez-Serra P, Marcilla M, Villanueva A, et al. A DERL3-associated defect in the degradation of SLC2A1 mediates the Warburg effect. Nat Commun 2014; 5: 3608.
[49]
Macintyre AN, Gerriets VA, Nichols AG, et al. The glucose transporter Glut1 is selectively essential for CD4 T cell activation and effector function. Cell Metab 2014; 20(1): 61-72.
[50]
Freudenberg J, Lee HS, Han BG, et al. Genome-wide association study of rheumatoid arthritis in Koreans: population-specific loci as well as overlap with european susceptibility loci. Arthritis Rheum 2011; 63: 884-93.
[51]
Arias de la Rosa I, Escudero-Contreras A, Rodriguez-Cuenca S, et al. Defective glucose and lipid metabolism in rheumatoid arthritis is determined by chronic inflammation in metabolic tissues. J Intern Med 2018; 284(1): 61-77.
[52]
Park R, Kim TH, Ji JD. Gene expression profile in patients with axial spondyloarthritis: meta-analysis of publicly accessible microarray datasets. J Rheum Dis 2016; 23(6): 363-72.
[53]
Reimann F, Cox JJ, Belfer I, et al. Pain perception is altered by a nucleotide polymorphism in SCN9A. Proc Natl Acad Sci USA 2010; 107: 5148-53.

© 2024 Bentham Science Publishers | Privacy Policy