The effects of microRNAs on human neural stem cell differentiation in two- and three-dimensional cultures

Lara Stevanato, John D Sinden, Lara Stevanato, John D Sinden

Abstract

Introduction: Stem cells have the ability to self-renew or to differentiate into numerous cell types; however, our understanding of how to control and exploit this potential is currently limited. An emerging hypothesis is that microRNAs (miRNAs) play a central role in controlling stem cell-fate determination. Herein, we have characterized the effects of miRNAs in differentiated human neural stem cells (hNSCs) by using a cell line currently being tested in clinical trials for stroke disability (NCT01151124, Clinicaltrials.gov).

Methods: HNSCs were differentiated on 2- (2D) and 3-dimensional (3D) cultures for 1 and 3 weeks. Quantification of hNSC differentiation was measured with real-time PCR and axon outgrowth. The miRNA PCR arrays were implemented to investigate differential expression profiles in differentiated hNSCs. Evaluation of miRNA effects on hNSCs was performed by using transfection of miRNA mimics, real-time PCR, Western blot, and immunocytochemistry.

Results: The 3D substrate promoted enhanced hNSC differentiation coupled with a loss of cell proliferation. Differentiated hNSCs exhibited a similar miRNA profiling. However, in 3D samples, the degree and timing of regulation were significantly different in miRNA members of cluster mi-R17 and miR-96-182, and hsa-miR-302a. Overall, hNSC 3D cultures demonstrated differential regulation of miRNAs involved in hNSC stemness, cell proliferation, and differentiation. The miRNA mimic analysis of hsa-miR-146b-5p and hsa-miR-99a confirmed induction of lineage-committed progenitors. Downregulated miRNAs were more abundant; those most significantly downregulated were selected, and their putative target mRNAs analyzed with the aim of unraveling their functionality. In differentiated hNSCs, downregulated hsa-miR-96 correlated with SOX5 upregulation of gene and protein expression; similar results were obtained for hsa-miR-302a, hsa-miR-182, hsa-miR-7, hsa-miR-20a/b, and hsa-miR-17 and their target NR4A3. Moreover, SOX5 was identified as a direct target gene of hsa-miR-96, and NR43A, a direct target of hsa-miR-7 and hsa-mir-17 by luciferase reporter assays. Therefore, the regulatory role of these miRNAs may occur through targeting NR4A3 and SOX5, both reported as modulators of cell-cycle progression and axon length.

Conclusions: The results provide new insight into the identification of specific miRNAs implicated in hNSC differentiation. These strategies may be exploited to optimize in vitro hNSC differentiation potential for use in preclinical studies and future clinical applications.

Figures

Figure 1
Figure 1
Quantification of hNSC differentiation. (A-E) Representative image of (A) undifferentiated, (B) 1 week (1W) 2D differentiated, (C) 3-week (3W) 2D differentiated, (D) 1W 3D differentiated, and (E) 3W 3D differentiated hNSCs; scale bar, 50 μm. (F) Quantification of axon length on 1W and 3W differentiated hNSCs cultured on 2D and 3D substrates. (G) QRT-PCR molecular analysis for neuronal (TUBB3, DCX, and MAP2) and glial (GALC, GFAP, and S100B) markers performed on hNSCs differentiated on 2D and 3D for 1W, and 3W, and expressed as fold change compared with undifferentiated control. Statistical analysis showed significant differences between 2D versus 3D samples at the same time point; ± SDMs. *P < 0.05; **P < 0.001, ***P < 0.005, Student t test.
Figure 2
Figure 2
Evaluation of hNSC proliferation. (A-E) Representative image of (A) undifferentiated, (B) 1W 2D differentiated, (C) 3W 2D differentiated, (D) 1W 3D differentiated, and (E) 3W 3D differentiated hNSCs stained with Ki67, marker of cell proliferation; scale bar, 50 μm; Ki67+ hNSCs (red), nuclear Hoechst counterstain (blue). (F) Quantification of cell proliferation measured as percentage of cells positive for Ki67. Statistical analysis showed a significant reduction in proliferation in 2D and 3D cultures compared with the proliferative control and between 2D and 3D samples at the same time point; ±SDMs. *P < 0.05, **P < 0.001, ***P < 0.005, Student t test.
Figure 3
Figure 3
Human cell differentiation and development miScript miRNA PCR array profiles. Group clustergram analysis of miRNA PCR array profiles analysis of differentially regulated miRNAs identified in control (undifferentiated hNSCs) and hNSCs seeded on 2D and 3D substrates and differentiated for 1W and 3W.
Figure 4
Figure 4
MiRNA mimic transfection analysis. A) hsa-miR-146b-5p, hsa-miR-23b, hsa-miR-99a transfected mimics were measured by real-time RT-PCR, and expressed as fold change compared with GFP transfected hNSCs (control). B) QRT-PCR molecular analysis for neuronal (TUBB3, DCX, and MAP2) and glial (GALC, GFAP, and S100B) markers of 146b-5p, hsa-miR-23b, hsa-miR-99a mimic transfected hNSCs and expressed as fold change compared with GFP transfected hNSCs (control). Statistical analysis was performed against transfected control; ± SDMs, *p < 0.05, **p < 0.001, ***p < 0.005, Student’s t-test.
Figure 5
Figure 5
Validation of miRNA target-predicted genes. (A) qRT-PCR analysis performed on 1W and 3W differentiated hNSCs cultured on 2D and 3D substrates and expressed as fold change compared with proliferative control. Statistical analysis showed significant difference compared with control; ±SDMs, *P < 0.05, **P < 0.001, ***P < 0.005, Student t test. (B) SOX5 and NR4A3 protein quantification performed by Western blot on 1W and 3W differentiated hNSCs cultured on both 2D or 3D substrates and proliferative control. (C) Dual luciferase report assay. Measurement of the relative luciferase activity of SOX5 and NR4A3 3′-UTR constructs transfected with hsa-miR-96, and hsa-miR-7 and 17, respectively. Data are expressed as mean values ± SDMs and are shown as percentage of control (cells transfected with either SOX5 or NR4A3 3′-UTR constructs and control microRNA). Each bar represents values from three independent experiments, measured in triplicate. The relative activity of firefly luciferase expression was normalized to renilla luciferase activity. Data were analyzed with Student t test, ***P < 0.005. (D) MiRNA KEGG pathway analysis results obtained by using DIANA Lab.

References

    1. Falanga V. Stem cells in tissue repair and regeneration. J Invest Dermatol. 2012;132:1538–1541. doi: 10.1038/jid.2012.77.
    1. Pollock K, Stroemer P, Patel S, Stevanato L, Hope A, Miljan E, Dong Z, Hodges H, Price J, Sinden JD. A conditionally immortal clonal stem cell line from human cortical neuroepithelium for the treatment of ischemic stroke. Exp Neurol. 2006;199:143–155. doi: 10.1016/j.expneurol.2005.12.011.
    1. Hodges H, Pollock K, Stroemer P, Patel S, Stevanato L, Reuter I, Sinden J. Making stem cell lines suitable for transplantation. Cell Transplant. 2007;16:101–115.
    1. Smith EJ, Stroemer RP, Gorenkova N, Nakajima M, Crum WR, Tang E, Stevanato L, Sinden JD, Modo M. Implantation site and lesion topology determine efficacy of a human neural stem cell line in a rat model of chronic stroke. Stem Cells. 2012;30:785–796. doi: 10.1002/stem.1024.
    1. Stroemer P, Patel S, Hope A, Oliveira C, Pollock K, Sinden J. The neural stem cell line CTX0E03 promotes behavioral recovery and endogenous neurogenesis after experimental stroke in a dose-dependent fashion. Neurorehabil Neural Repair. 2009;23:895–909. doi: 10.1177/1545968309335978.
    1. Fire A, Xu S, Montgomery MK, Kostas SA, Driver SE, Mello CC. Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature. 1998;391:806–811. doi: 10.1038/35888.
    1. Anokye-Danso F, Trivedi CM, Juhr D, Gupta M, Cui Z, Tian Y, Zhang Y, Yang W, Gruber PJ, Epstein JA, Morrisey EE. Highly efficient miRNA-mediated reprogramming of mouse and human somatic cells to pluripotency. Cell Stem Cell. 2011;8:376–388. doi: 10.1016/j.stem.2011.03.001.
    1. Spivakov M, Fisher AG. Epigenetic signatures of stem-cell identity. Nat Rev Genet. 2007;8:263–271. doi: 10.1038/nrg2046.
    1. Gangaraju VK, Lin H. MicroRNAs: key regulators of stem cells. Nat Rev Mol Cell Biol. 2009;10:116–125. doi: 10.1038/nrm2621.
    1. Saba R, Schratt GM. MicroRNAs in neuronal development, function and dysfunction. Brain Res. 2010;1338:3–13.
    1. Li X, Jin P. Roles of small regulatory RNAs in determining neuronal identity. Nat Rev Neurosci. 2010;11:329–338. doi: 10.1038/nrn2739.
    1. Badylak SF. The extracellular matrix as a scaffold for tissue reconstruction. Semin Cell Dev Biol. 2002;13:377–383. doi: 10.1016/S1084952102000940.
    1. Buxboim A, Discher DE. Stem cells feel the difference. Nat Methods. 2010;7:695–697. doi: 10.1038/nmeth0910-695.
    1. Gelain F, Bottai D, Vescovi A, Zhang S. Designer self-assembling peptide nanofiber scaffolds for adult mouse neural stem cell 3-dimensional cultures. PLoS One. 2006;1:e119. doi: 10.1371/journal.pone.0000119.
    1. Li WJ, Tuli R, Okafor C, Derfoul A, Danielson KG, Hall DJ, Tuan RS. A three-dimensional nanofibrous scaffold for cartilage tissue engineering using human mesenchymal stem cells. Biomaterials. 2005;26:599–609. doi: 10.1016/j.biomaterials.2004.03.005.
    1. Lutolf MP, Gilbert PM, Blau HM. Designing materials to direct stem-cell fate. Nature. 2009;462:433–441. doi: 10.1038/nature08602.
    1. Nur EKA, Ahmed I, Kamal J, Schindler M, Meiners S. Three-dimensional nanofibrillar surfaces promote self-renewal in mouse embryonic stem cells. Stem Cells. 2006;24:426–433. doi: 10.1634/stemcells.2005-0170.
    1. Ortinau S, Schmich J, Block S, Liedmann A, Jonas L, Weiss DG, Helm CA, Rolfs A, Frech MJ. Effect of 3D-scaffold formation on differentiation and survival in human neural progenitor cells. Biomed Eng Online. 2010;9:70. doi: 10.1186/1475-925X-9-70.
    1. Saha K, Pollock JF, Schaffer DV, Healy KE. Designing synthetic materials to control stem cell phenotype. Curr Opin Chem Biol. 2007;11:381–387. doi: 10.1016/j.cbpa.2007.05.030.
    1. Knight E, Murray B, Carnachan R, Przyborski S. Alvetex(R): polystyrene scaffold technology for routine three dimensional cell culture. Methods Mol Biol. 2011;695:323–340. doi: 10.1007/978-1-60761-984-0_20.
    1. Bokhari M, Carnachan RJ, Przyborski SA, Cameron NR. Emulsion-templated porous polymers as scaffolds for three dimensional cell culture: effect of synthesis parameters on scaffold formation and homogeneity. J Mater Chem. 2007;17:4088–4094. doi: 10.1039/b707499a.
    1. Bokhari M, Carnachan RJ, Cameron NR, Przyborski SA. Novel cell culture device enabling three-dimensional cell growth and improved cell function. Biochem Biophys Res Commun. 2007;354:1095–1100. doi: 10.1016/j.bbrc.2007.01.105.
    1. Burgoyne RD, Cambray-Deakin MA, Lewis SA, Sarkar S, Cowan NJ. Differential distribution of beta-tubulin isotypes in cerebellum. EMBO J. 1988;7:2311–2319.
    1. Gleeson JG, Lin PT, Flanagan LA, Walsh CA. Doublecortin is a microtubule-associated protein and is expressed widely by migrating neurons. Neuron. 1999;23:257–271. doi: 10.1016/S0896-6273(00)80778-3.
    1. Zhang J, Dong XP. Dysfunction of microtubule-associated proteins of MAP2/tau family in prion disease. Prion. 2012;6:334–338. doi: 10.4161/pri.20677.
    1. Wolswijk G. Chronic stage multiple sclerosis lesions contain a relatively quiescent population of oligodendrocyte precursor cells. J Neurosci. 1998;18:601–609.
    1. Schmittgen TD, Livak KJ. Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc. 2008;3:1101–1108. doi: 10.1038/nprot.2008.73.
    1. miScript miRNA PCR Array Data Analysis. .
    1. DIANA LAB - DNA Intelligent Analysis MICROT.
    1. Maragkakis M, Alexiou P, Papadopoulos GL, Reczko M, Dalamagas T, Giannopoulos G, Goumas G, Koukis E, Kourtis K, Simossis VA, Sethupathy P, Vergoulis T, Koziris N, Sellis T, Tsanakas P, Hatzigeorgiou AG. Accurate microRNA target prediction correlates with protein repression levels. BMC Bioinformatics. 2009;10:295. doi: 10.1186/1471-2105-10-295.
    1. Chen K, Rajewsky N. Natural selection on human microRNA binding sites inferred from SNP data. Nat Genet. 2006;38:1452–1456. doi: 10.1038/ng1910.
    1. PicTar – MDC.
    1. TargetScan.
    1. Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005;120:15–20. doi: 10.1016/j.cell.2004.12.035.
    1. DIANA LAB - DNA Intelligent Analysis MIRPATH.
    1. Scholzen T, Gerdes J. The Ki-67 protein: from the known and the unknown. J Cell Physiol. 2000;182:311–322. doi: 10.1002/(SICI)1097-4652(200003)182:3<311::AID-JCP1>;2-9.
    1. Wulczyn FG, Smirnova L, Rybak A, Brandt C, Kwidzinski E, Ninnemann O, Strehle M, Seiler A, Schumacher S, Nitsch R. Post-transcriptional regulation of the let-7 microRNA during neural cell specification. FASEB J. 2007;21:415–426. doi: 10.1096/fj.06-6130com.
    1. Smith B, Treadwell J, Zhang D, Ly D, McKinnell I, Walker PR, Sikorska M. Large-scale expression analysis reveals distinct microRNA profiles at different stages of human neurodevelopment. PLoS One. 2010;5:e11109. doi: 10.1371/journal.pone.0011109.
    1. Katakowski M, Zheng X, Jiang F, Rogers T, Szalad A, Chopp M. MiR-146b-5p suppresses EGFR expression and reduces in vitro migration and invasion of glioma. Cancer Invest. 2010;28:1024–1030. doi: 10.3109/07357907.2010.512596.
    1. Lindsay MA. microRNAs and the immune response. Trends Immunol. 2008;29:343–351. doi: 10.1016/j.it.2008.04.004.
    1. Chen H, Shalom-Feuerstein R, Riley J, Zhang SD, Tucci P, Agostini M, Aberdam D, Knight RA, Genchi G, Nicotera P, Melino G. Vasa-Nicotera M: miR-7 and miR-214 are specifically expressed during neuroblastoma differentiation, cortical development and embryonic stem cells differentiation, and control neurite outgrowth in vitro. Biochem Biophys Res Commun. 2010;394:921–927. doi: 10.1016/j.bbrc.2010.03.076.
    1. Cioffi JA, Yue WY, Mendolia-Loffredo S, Hansen KR, Wackym PA, Hansen MR. MicroRNA-21 overexpression contributes to vestibular schwannoma cell proliferation and survival. Otol Neurotol. 2010;31:1455–1462.
    1. Cirera-Salinas D, Pauta M, Allen RM, Salerno AG, Ramirez CM, Chamorro-Jorganes A, Wanschel AC, Lasuncion MA, Morales-Ruiz M, Suarez Y, Baldan Á, Esplugues E, Fernández-Hernando C. Mir-33 regulates cell proliferation and cell cycle progression. Cell Cycle. 2012;11:922–933. doi: 10.4161/cc.11.5.19421.
    1. Liu XS, Chopp M, Wang XL, Zhang L, Hozeska-Solgot A, Tang T, Kassis H, Zhang RL, Chen C, Xu J, Zhang ZG. MicroRNA-17-92 cluster mediates the proliferation and survival of neural progenitor cells after stroke. J Biol Chem. 2013;288:12478–12488. doi: 10.1074/jbc.M112.449025.
    1. Porrello ER, Johnson BA, Aurora AB, Simpson E, Nam YJ, Matkovich SJ, Dorn GW 2nd, van Rooij E, Olson EN. MiR-15 family regulates postnatal mitotic arrest of cardiomyocytes. Circ Res. 2011;109:670–679. doi: 10.1161/CIRCRESAHA.111.248880.
    1. Trompeter HI, Abbad H, Iwaniuk KM, Hafner M, Renwick N, Tuschl T, Schira J, Muller HW, Wernet P. MicroRNAs MiR-17, MiR-20a, and MiR-106b act in concert to modulate E2F activity on cell cycle arrest during neuronal lineage differentiation of USSC. PLoS One. 2011;6:e16138. doi: 10.1371/journal.pone.0016138.
    1. Weeraratne SD, Amani V, Teider N, Pierre-Francois J, Winter D, Kye MJ, Sengupta S, Archer T, Remke M, Bai AH, Warren P, Pfister SM, Steen JA, Pomeroy SL, Cho YJ. Pleiotropic effects of miR-183 96 182 converge to regulate cell survival, proliferation and migration in medulloblastoma. Acta Neuropathol. 2012;123:539–552. doi: 10.1007/s00401-012-0969-5.
    1. Parsons XH, Parsons JF, Moore DA. Genome-scale mapping of microRNA signatures in human embryonic stem cell neurogenesis. Mol Med Ther. 2012;1 doi:10.4172/2324-8769.1000105.
    1. Wang Y, Keys DN, Au-Young JK, Chen C. MicroRNAs in embryonic stem cells. J Cell Physiol. 2009;218:251–255. doi: 10.1002/jcp.21607.
    1. Ponnio T, Conneely OM. Nor-1 regulates hippocampal axon guidance, pyramidal cell survival, and seizure susceptibility. Mol Cell Biol. 2004;24:9070–9078. doi: 10.1128/MCB.24.20.9070-9078.2004.
    1. Martinez-Morales PL, Quiroga AC, Barbas JA, Morales AV. SOX5 controls cell cycle progression in neural progenitors by interfering with the WNT-beta-catenin pathway. EMBO Rep. 2010;11:466–472. doi: 10.1038/embor.2010.61.
    1. Kwan KY, Lam MM, Krsnik Z, Kawasawa YI, Lefebvre V, Sestan N. SOX5 postmitotically regulates migration, postmigratory differentiation, and projections of subplate and deep-layer neocortical neurons. Proc Natl Acad Sci U S A. 2008;105:16021–16026. doi: 10.1073/pnas.0806791105.
    1. Lai T, Jabaudon D, Molyneaux BJ, Azim E, Arlotta P, Menezes JR, Macklis JD. SOX5 controls the sequential generation of distinct corticofugal neuron subtypes. Neuron. 2008;57:232–247. doi: 10.1016/j.neuron.2007.12.023.

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