Housekeeping gene validation for RT-qPCR studies on synovial fibroblasts derived from healthy and osteoarthritic patients with focus on mechanical loading


Autoři: Ute Nazet aff001;  Agnes Schröder aff001;  Susanne Grässel aff002;  Dominique Muschter aff002;  Peter Proff aff001;  Christian Kirschneck aff001
Působiště autorů: Department of Orthodontics, University Medical Centre of Regensburg, Regensburg, Germany aff001;  Department of Orthopaedics, University of Regensburg and Centre for Biomedical Technology, BioPark, Regensburg, Germany aff002
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0225790

Souhrn

Selection of appropriate housekeeping genes is essential for the validity of data normalization in reverse transcription quantitative PCR (RT-qPCR). Synovial fibroblasts (SF) play a mediating role in the development and progression of osteoarthritis (OA) pathogenesis, but there is no information on reliable housekeeping genes available. Therefore the goal of this study was to identify a set of reliable housekeeping genes suitable for studies of mechanical loading on SF from healthy and OA patients. Nine genes were evaluated towards expression stability and ranked according their relative stability determined by four different mathematical procedures (geNorm, NormFinder, BestKeeper and comparative ΔCq). We observed that RPLP0 (ribosomal protein, large, P0) and EEF1A1 (eukaryotic translation elongation factor 1 alpha 1) turned out to be the genes with the most stable expression in SF from non-OA or OA patients treated with or without mechanical loading. According to geNorm two genes are sufficient for normalization throughout. Expression of one tested target gene varied considerably, if normalized to different candidate housekeeping genes. Our study provides a tool for accurate and valid housekeeping gene selection in gene expression experiments on SF from healthy and OA patients with and without mechanical loading in consistent with the MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments) guidelines and additionally demonstrates the impact of proper housekeeping gene selection on the expression of the gene of interest.

Klíčová slova:

Algorithms – Cell cultures – Fibroblasts – Gene expression – Osteoarthritis – Protein translation – RNA synthesis – Elongation factors


Zdroje

1. Chen G, Ning B, Shi T. Single-Cell RNA-Seq Technologies and Related Computational Data Analysis. Front Genet. 2019; 10: 317. doi: 10.3389/fgene.2019.00317 31024627

2. Wang J, Dean DC, Hornicek FJ, Shi H, Duan Z. RNA sequencing (RNA-Seq) and its application in ovarian cancer. Gynecol Oncol. 2019; 152: 194–201. doi: 10.1016/j.ygyno.2018.10.002 30297273

3. Rahmatallah Y, Emmert-Streib F, Glazko G. Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline. Brief Bioinformatics. 2016; 17: 393–407. doi: 10.1093/bib/bbv069 26342128

4. Kierzek R, Turner DH, Kierzek E. Microarrays for identifying binding sites and probing structure of RNAs. Nucleic Acids Res. 2015; 43: 1–12. doi: 10.1093/nar/gku1303 25505162

5. Keen HL, Sigmund CD. Microarray Analysis of Hypertension. Methods Mol Biol. 2017; 1527: 41–52. doi: 10.1007/978-1-4939-6625-7_3 28116705

6. Jacob F, Guertler R, Naim S, Nixdorf S, Fedier A, Hacker NF, et al. Careful selection of housekeeping genes is required for reliable performance of RT-qPCR in human normal and cancer cell lines. PLoS ONE. 2013; 8: e59180. doi: 10.1371/journal.pone.0059180 23554992

7. Kozera B, Rapacz M. Housekeeping genes in real-time PCR. J Appl Genet. 2013; 54: 391–406. doi: 10.1007/s13353-013-0173-x 24078518

8. Kirschneck C, Batschkus S, Proff P, Köstler J, Spanier G, Schröder A. Valid gene expression normalization by RT-qPCR in studies on hPDL fibroblasts with focus on orthodontic tooth movement and periodontitis. Sci Rep. 2017; 7: 14751. doi: 10.1038/s41598-017-15281-0 29116140

9. Kirschneck C, Proff P, Fanghänel J, Wolf M, Roldán JC, Römer P. Housekeeping genes for valid gene expression studies on rat dental, periodontal and alveolar bone tissue by means of RT-qPCR with a focus on orthodontic tooth movement and periodontitis. Ann Anat. 2016; 204: 93–105.

10. Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, et al. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem. 2009; 55: 611–622. doi: 10.1373/clinchem.2008.112797 19246619

11. Tan SC, Carr CA, Yeoh KK, Schofield CJ, Davies KE, Clarke K. Identification of valid housekeeping genes for quantitative RT-PCR analysis of cardiosphere-derived cells preconditioned under hypoxia or with prolyl-4-hydroxylase inhibitors. Mol Biol Rep. 2012; 39: 4857–4867. doi: 10.1007/s11033-011-1281-5 22065248

12. Vandesompele J, de Preter K, Pattyn F, Poppe B, van Roy N, de Paepe A, et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 2002; 3: RESEARCH0034. doi: 10.1186/gb-2002-3-7-research0034 12184808

13. Andersen CL, Jensen JL, Ørntoft TF. Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res. 2004; 64: 5245–5250. doi: 10.1158/0008-5472.CAN-04-0496 15289330

14. Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP. Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper—Excel-based tool using pair-wise correlations. Biotechnol Lett. 2004; 26: 509–515. doi: 10.1023/b:bile.0000019559.84305.47 15127793

15. Silver N, Best S, Jiang J, Thein SL. Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Mol Biol. 2006; 7: 33. doi: 10.1186/1471-2199-7-33 17026756

16. Silver N, Cotroneo E, Proctor G, Osailan S, Paterson KL, Carpenter GH. Selection of housekeeping genes for gene expression studies in the adult rat submandibular gland under normal, inflamed, atrophic and regenerative states. BMC Mol Biol. 2008; 9: 64. doi: 10.1186/1471-2199-9-64 18637167

17. Bhattaram P, Chandrasekharan U. The joint synovium: A critical determinant of articular cartilage fate in inflammatory joint diseases. Semin Cell Dev Biol. 2017; 62: 86–93. doi: 10.1016/j.semcdb.2016.05.009 27212252

18. Wehmeyer C, Pap T, Buckley CD, Naylor AJ. The role of stromal cells in inflammatory bone loss. Clin Exp Immunol. 2017; 189: 1–11. doi: 10.1111/cei.12979 28419440

19. Ospelt C, Brentano F, Rengel Y, Stanczyk J, Kolling C, Tak PP, et al. Overexpression of toll-like receptors 3 and 4 in synovial tissue from patients with early rheumatoid arthritis: toll-like receptor expression in early and longstanding arthritis. Arthritis Rheum. 2008; 58: 3684–3692. doi: 10.1002/art.24140 19035519

20. Carrión M, Juarranz Y, Pérez-García S, Jimeno R, Pablos JL, Gomariz RP, et al. RNA sensors in human osteoarthritis and rheumatoid arthritis synovial fibroblasts: immune regulation by vasoactive intestinal peptide. Arthritis Rheum. 2011; 63: 1626–1636. doi: 10.1002/art.30294 21337319

21. Zarb GA, Carlsson GE. Temporomandibular disorders: osteoarthritis. J Orofac Pain. 1999; 13: 295–306. 10823044

22. Chen Di, Shen J, Zhao W, Wang T, Han L, Hamilton JL, et al. Osteoarthritis: toward a comprehensive understanding of pathological mechanism. Bone Res. 2017; 5: 16044. doi: 10.1038/boneres.2016.44 28149655

23. Herrero-Beaumont G, Roman-Blas JA, Castañeda S, Jimenez SA. Primary osteoarthritis no longer primary: three subsets with distinct etiological, clinical, and therapeutic characteristics. Semin Arthritis Rheum. 2009; 39: 71–80. doi: 10.1016/j.semarthrit.2009.03.006 19589561

24. Chang SH, Mori D, Kobayashi H, Mori Y, Nakamoto H, Okada K, et al. Excessive mechanical loading promotes osteoarthritis through the gremlin-1-NF-κB pathway. Nat Commun. 2019; 10: 1442. doi: 10.1038/s41467-019-09491-5 30926814

25. Tanaka E, Detamore MS, Mercuri LG. Degenerative disorders of the temporomandibular joint: etiology, diagnosis, and treatment. J Dent Res. 2008; 87: 296–307. doi: 10.1177/154405910808700406 18362309

26. Schröder A, Nazet U, Muschter D, Grässel S, Proff P, Kirschneck C. Impact of Mechanical Load on the Expression Profile of Synovial Fibroblasts from Patients with and without Osteoarthritis. Int J Mol Sci. 2019; 20: In press. doi: 10.3390/ijms20030585 30704030

27. Schröder A, Bauer K, Spanier G, Proff P, Wolf M, Kirschneck C. Expression kinetics of human periodontal ligament fibroblasts in the early phases of orthodontic tooth movement. J Orofac Orthop. 2018; 79: 337–351. doi: 10.1007/s00056-018-0145-1 30019109

28. Koretsi V, Kirschneck C, Proff P, Römer P. Expression of glutathione peroxidase 1 in the spheno-occipital synchondrosis and its role in ROS-induced apoptosis. Eur J Orthod. 2015; 37: 308–313. doi: 10.1093/ejo/cju045 25312980

29. Kirschneck C, Meier M, Bauer K, Proff P, Fanghänel J. Meloxicam medication reduces orthodontically induced dental root resorption and tooth movement velocity: a combined in vivo and in vitro study of dental-periodontal cells and tissue. Cell Tissue Res. 2017; 368: 61–78. doi: 10.1007/s00441-016-2553-0 28044198

30. Kirschneck C, Fanghänel J, Wahlmann U, Wolf M, Roldán JC, Proff P. Interactive effects of periodontitis and orthodontic tooth movement on dental root resorption, tooth movement velocity and alveolar bone loss in a rat model. Ann Anat. 2017; 210: 32–43. doi: 10.1016/j.aanat.2016.10.004 27838559

31. Kirschneck C, Maurer M, Wolf M, Reicheneder C, Proff P. Regular nicotine intake increased tooth movement velocity, osteoclastogenesis and orthodontically induced dental root resorptions in a rat model. Int J Oral Sci. 2017; 9: 174–184. doi: 10.1038/ijos.2017.34 28960194

32. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001; 25: 402–408. doi: 10.1006/meth.2001.1262 11846609

33. Schroeder A, Mueller O, Stocker S, Salowsky R, Leiber M, Gassmann M, et al. The RIN: an RNA integrity number for assigning integrity values to RNA measurements. BMC Mol Biol. 2006; 7: 3. doi: 10.1186/1471-2199-7-3 16448564

34. Kenmochi N, Kawaguchi T, Rozen S, Davis E, Goodman N, Hudson TJ, et al. A map of 75 human ribosomal protein genes. Genome Res. 1998; 8: 509–523. doi: 10.1101/gr.8.5.509 9582194

35. Lund A, Knudsen SM, Vissing H, Clark B, Tommerup N. Assignment of human elongation factor 1alpha genes: EEF1A maps to chromosome 6q14 and EEF1A2 to 20q13.3. Genomics. 1996; 36: 359–361. doi: 10.1006/geno.1996.0475 8812466

36. Becker M, Kuhse J, Kirsch J. Effects of two elongation factor 1A isoforms on the formation of gephyrin clusters at inhibitory synapses in hippocampal neurons. Histochem Cell Biol. 2013; 140: 603–609. doi: 10.1007/s00418-013-1122-9 23839781

37. Hoffmann H, Schiene-Fischer C. Functional aspects of extracellular cyclophilins. Biol Chem. 2014; 395: 721–735. doi: 10.1515/hsz-2014-0125 24713575

38. Gagliardi A, Besio R, Carnemolla C, Landi C, Armini A, Aglan M, et al. Cytoskeleton and nuclear lamina affection in recessive osteogenesis imperfecta: A functional proteomics perspective. J Proteomics. 2017; 167: 46–59. doi: 10.1016/j.jprot.2017.08.007 28802583

39. Savinkova L, Drachkova I, Arshinova T, Ponomarenko P, Ponomarenko M, Kolchanov N. An experimental verification of the predicted effects of promoter TATA-box polymorphisms associated with human diseases on interactions between the TATA boxes and TATA-binding protein. PLoS ONE. 2013; 8: e54626. doi: 10.1371/journal.pone.0054626 23424617

40. Taylor S, Wakem M, Dijkman G, Alsarraj M, Nguyen M. A practical approach to RT-qPCR-Publishing data that conform to the MIQE guidelines. Methods. 2010; 50: S1–5. doi: 10.1016/j.ymeth.2010.01.005 20215014

41. Taylor SC, Mrkusich EM. The state of RT-quantitative PCR: firsthand observations of implementation of minimum information for the publication of quantitative real-time PCR experiments (MIQE). J Mol Microbiol Biotechnol. 2014; 24: 46–52. doi: 10.1159/000356189 24296827

42. Taki FA, Abdel-Rahman AA, Zhang B. A comprehensive approach to identify reliable housekeeping gene candidates to investigate the link between alcoholism and endocrinology in Sprague-Dawley rats. PLoS ONE. 2014; 9: e94311. doi: 10.1371/journal.pone.0094311 24824616

43. Robledo D, Ronza P, Harrison PW, Losada AP, Bermúdez R, Pardo BG, et al. RNA-seq analysis reveals significant transcriptome changes in turbot (Scophthalmus maximus) suffering severe enteromyxosis. BMC Genomics. 2014; 15: 1149. doi: 10.1186/1471-2164-15-1149 25526753

44. Mahanty A, Purohit GK, Mohanty S, Nayak NR, Mohanty BP. Suitable housekeeping gene for quantitative real-time PCR analysis of gene expression in gonadal tissues of minnow Puntius sophore under high-temperature stress. BMC Genomics. 2017; 18: 617. doi: 10.1186/s12864-017-3974-1 28810828

45. Reuther S, Reiter M, Raabe A, Dikomey E. Effect of irradiation on the expression of DNA repair genes studied in human fibroblasts by real-time qPCR using three methods of housekeeping gene validation. Radiat Environ Biophys. 2013; 52: 463–469. doi: 10.1007/s00411-013-0482-9 23884658


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