MAP‑1B, PACS‑2 and AHCYL1 are regulated by miR‑34A/B/C and miR‑449 in neuroplasticity following traumatic spinal cord injury in rats: Preliminary explorative results from microarray data

Cao,Hongshi; Zhang,Yu; Chu,Zhe; Zhao,Bolun; Wang,Haiyan; An,Libin

doi:10.3892/mmr.2019.10538

MAP‑1B, PACS‑2 and AHCYL1 are regulated by miR‑34A/B/C and miR‑449 in neuroplasticity following traumatic spinal cord injury in rats: Preliminary explorative results from microarray data

Authors:
- Hongshi Cao
- Yu Zhang
- Zhe Chu
- Bolun Zhao
- Haiyan Wang
- Libin An
View Affiliations

Affiliations: School of Nursing, Jilin University, Jilin 130021, P.R. China, Department of Neurovascular Disease, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China, Department of Emergency, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China, School of Nursing, Dalian University, Dalian, Liaoning 116000, P.R. China, Department of Neurotrauma Surgery, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China
Published online on: July 30, 2019 https://doi.org/10.3892/mmr.2019.10538
Pages: 3011-3018
Copyright: © Cao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

Abstract

Spinal cord injury (SCI) is a specific type of damage to the central nervous system causing temporary or permanent changes in its function. The present aimed to identify the genetic changes in neuroplasticity following SCI in rats. The GSE52763 microarray dataset, which included 15 samples [3 sham (1 week), 4 injury only (1 week), 4 injury only (3 weeks), 4 injury + treadmill (3 weeks)] was downloaded from the Gene Expression Omnibus database. An empirical Bayes linear regression model in limma package was used to identify the differentially expressed genes (DEGs) in injury vs. sham and treadmill vs. non‑treadmill comparison groups. Subsequently, time series and enrichment analyses were performed using pheatmap and clusterProfile packages, respectively. Additionally, protein‑protein interaction (PPI) and transcription factor (TF)‑microRNA (miRNA)‑target regulatory networks were constructed using Cytoscape software. In total, 159 and 105 DEGs were identified in injury vs. sham groups and treadmill vs. non‑treadmill groups, respectively. There were 40 genes in cluster 1 that presented increased expression levels in the injury (1 week/3 weeks) groups compared with the sham group, and decreased expression levels in the injury + treadmill group compared with the injury only groups; conversely, 52 genes in cluster 2 exhibited decreased expression levels in the injury (1 week/3 weeks) groups compared with the sham group, and increased expression levels in the injury + treadmill group compared with the injury only groups. Enrichment analysis indicated that clusters 1 and 2 were associated with immune response and signal transduction, respectively. Furthermore, microtubule associated protein 1B, phosphofurin acidic cluster sorting protein 2 and adenosylhomocysteinase‑like 1 exhibited the highest degrees in the regulatory network, and were regulated by miRNAs including miR‑34A, miR‑34B, miR‑34C and miR‑449. These miRNAs and their target genes may serve important roles in neuroplasticity following traumatic SCI in rats. Nevertheless, additional in‑depth studies are required to confirm these data.

View Figures

View References

1	Chen Y, He Y and DeVivo MJ: Changing demographics and injury profile of new traumatic spinal cord injuries in the United States, 1972–2014. Arch Phys Med Rehabil. 97:1610–1619. 2016. View Article : Google Scholar : PubMed/NCBI
2	Lenehan B, Street J, Kwon BK, Noonan V, Zhang H, Fisher CG and Dvorak MF: The epidemiology of traumatic spinal cord injury in British Columbia, Canada. Spine (Phila Pa 1976). 37:321–329. 2012. View Article : Google Scholar : PubMed/NCBI
3	DeVivo MJ and Chen Y: Trends in new injuries, prevalent cases, and aging with spinal cord injury. Arch Phys Med Rehabil. 92:332–338. 2011. View Article : Google Scholar : PubMed/NCBI
4	Hurlbert RJ, Hadley MN, Walters BC, Aarabi B, Dhall SS, Gelb DE, Rozzelle CJ, Ryken TC and Theodore N: Pharmacological therapy for acute spinal cord injury. Neurosurgery. 76 (Suppl 1):S71–S83. 2015. View Article : Google Scholar : PubMed/NCBI
5	Scarisbrick IA, Sabharwal P, Cruz H, Larsen N, Vandell AG, Blaber SI, Ameenuddin S, Papke LM, Fehlings MG, Reeves RK, et al: Dynamic role of kallikrein 6 in traumatic spinal cord injury. Eur J Neurosci. 24:1457–1469. 2010. View Article : Google Scholar
6	Lemarchant S, Pruvost M, Hébert M, Gauberti M, Hommet Y, Briens A, Maubert E, Gueye Y, Féron F, Petite D, et al: tPA promotes ADAMTS-4-induced CSPG degradation, thereby enhancing neuroplasticity following spinal cord injury. Neurobiol Dis. 66:28–42. 2014. View Article : Google Scholar : PubMed/NCBI
7	Koehn LM, Noor NM, Dong Q, Er SY, Rash LD, King GF, Dziegielewska KM, Saunders NR and Habgood MD: Selective inhibition of ASIC1a confers functional and morphological neuroprotection following traumatic spinal cord injury. Version 2. F1000Res. 5:18222016. View Article : Google Scholar : PubMed/NCBI
8	Liu NK, Wang XF, Lu QB and Xu XM: Altered microRNA expression following traumatic spinal cord injury. Exp Neurol. 219:424–429. 2009. View Article : Google Scholar : PubMed/NCBI
9	Ning B, Gao L, Liu RH, Liu Y, Zhang NS and Chen ZY: microRNAs in spinal cord injury: Potential roles and therapeutic implications. Int J Biol Sci. 10:997–1006. 2014. View Article : Google Scholar : PubMed/NCBI
10	Shin HY, Kim H, Kwon MJ, Hwang DH, Lee K and Kim BG: Molecular and cellular changes in the lumbar spinal cord following thoracic injury: Regulation by treadmill locomotor training. PLoS One. 9:e882152014. View Article : Google Scholar : PubMed/NCBI
11	Yang Z, Lv Q, Wang Z, Dong X, Yang R and Zhao W: Identification of crucial genes associated with rat traumatic spinal cord injury. Mol Med Rep. 15:1997–2006. 2017. View Article : Google Scholar : PubMed/NCBI
12	Liu Q, Zhang B, Liu C and Zhao D: Molecular mechanisms underlying the positive role of treadmill training in locomotor recovery after spinal cord injury. Spinal Cord. 55:441–446. 2017. View Article : Google Scholar : PubMed/NCBI
13	Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Holko M, et al: NCBI GEO: Archive for functional genomics data sets-update. Nucleic Acids Res. 41:D991–D995. 2013. View Article : Google Scholar : PubMed/NCBI
14	Carvalho BS and Irizarry RA: A framework for oligonucleotide microarray preprocessing. Bioinformatics. 26:2363–2367. 2010. View Article : Google Scholar : PubMed/NCBI
15	Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W and Smyth GK: Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43:e472015. View Article : Google Scholar : PubMed/NCBI
16	Kolde R: pheatmap: Pretty Heatmaps. R package version 0.6.1. 2013. http://CRAN.R-project.org/packageepheatmapOct 12–2015
17	Yu G, Wang LG, Han Y and He QY: clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS. 16:284–287. 2012. View Article : Google Scholar : PubMed/NCBI
18	The Gene Ontology Consortium, . Expansion of the gene ontology knowledgebase and resources. Nucleic Acids Research. 45:D331–D338. 2017. View Article : Google Scholar : PubMed/NCBI
19	Mi H, Huang X, Muruganujan A, Tang H, Mills C, Kang D and Thomas PD: PANTHER version 11: Expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements. Nucleic Acids Res. 45:D183–D189. 2017. View Article : Google Scholar : PubMed/NCBI
20	Kanehisa M and Goto S: KEGG: Kyoto encyclopaedia of genes and genomes. Nucleic Acids Res. 28:27–30. 2000. View Article : Google Scholar : PubMed/NCBI
21	Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, et al: STRING v10: Protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 43:D447–D452. 2015. View Article : Google Scholar : PubMed/NCBI
22	Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B and Ideker T: Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 13:2498–2504. 2003. View Article : Google Scholar : PubMed/NCBI
23	Tang Y, Li M, Wang J, Pan Y and Wu FX: CytoNCA: A cytoscape plugin for centrality analysis and evaluation of protein interaction networks. Biosystems. 127:67–72. 2015. View Article : Google Scholar : PubMed/NCBI
24	He X and Zhang J: Why do hubs tend to be essential in protein networks? PLoS Genet. 2:e882006. View Article : Google Scholar : PubMed/NCBI
25	Wang J, Duncan D, Shi Z and Zhang B: WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): Update 2013. Nucleic Acids Res. 41:W77–W83. 2013. View Article : Google Scholar : PubMed/NCBI
26	Gonzalez-Billault C, Jimenez-Mateos EM, Caceres A, Diaz-Nido J, Wandosell F and Avila J: Microtubule-associated protein 1B function during normal development, regeneration, and pathological conditions in the nervous system. J Neurobiol. 58:48–59. 2004. View Article : Google Scholar : PubMed/NCBI
27	Ma D, Nothias F, Boyne LJ and Fischer I: Differential regulation of microtubule-associated protein 1B (MAP1B) in rat CNS and PNS during development. J Neurosci Res. 49:319–332. 1997. View Article : Google Scholar : PubMed/NCBI
28	Gödel M, Temerinac D, Grahammer F, Hartleben B, Kretz O, Riederer BM, Propst F, Kohl S and Huber TB: Microtubule associated protein 1b (MAP1B) is a marker of the microtubular cytoskeleton in podocytes but is not essential for the function of the kidney filtration barrier in mice. PLoS One. 10:e01401162015. View Article : Google Scholar : PubMed/NCBI
29	Tortosa E, Montenegro-Venegas C, Benoist M, Härtel S, González-Billault C, Esteban JA and Avila J: Microtubule-associated protein 1B (MAP1B) is required for dendritic spine development and synaptic maturation. J Biol Chem. 286:40638–40648. 2011. View Article : Google Scholar : PubMed/NCBI
30	Köttgen M, Benzing T, Simmen T, Tauber R, Buchholz B, Feliciangeli S, Huber TB, Schermer B, Kramer-Zucker A, Höpker K, et al: Trafficking of TRPP2 by PACS proteins represents a novel mechanism of ion channel regulation. EMBO J. 24:705–716. 2005. View Article : Google Scholar : PubMed/NCBI
31	Liu WM, Wu JY, Li FC and Chen QX: Ion channel blockers and spinal cord injury. J Neurosci Res. 89:791–801. 2011. View Article : Google Scholar : PubMed/NCBI
32	Kawaai K, Mizutani A, Shoji H, Ogawa N, Ebisui E, Kuroda Y, Wakana S, Miyakawa T, Hisatsune C and Mikoshiba K: IRBIT regulates CaMKIIα activity and contributes to catecholamine homeostasis through tyrosine hydroxylase phosphorylation. Proc Natl Acad Sci USA. 112:5515–5520. 2015. View Article : Google Scholar : PubMed/NCBI
33	Jauhari A, Singh T, Singh P, Parmar D and Yadav S: Regulation of miR-34 family in neuronal development. Mol Neurobiol. 55:936–945. 2018. View Article : Google Scholar : PubMed/NCBI
34	Aranha MM, Santos DM, Solá S, Steer CJ and Rodrigues CM: miR-34a regulates mouse neural stem cell differentiation. PLoS One. 6:e213962011. View Article : Google Scholar : PubMed/NCBI
35	Rokavec M, Li H, Jiang L and Hermeking H: The p53/miR-34 axis in development and disease. J Mol Cell Biol. 6:214–230. 2014. View Article : Google Scholar : PubMed/NCBI
36	Zhu Y, Wu Y and Zhang R: Electro-acupuncture promotes the proliferation of neural stem cells and the survival of neurons by downregulating miR-449a in rat with spinal cord injury. EXCLI J. 16:363–374. 2017.PubMed/NCBI
37	Han R, Ji X, Rong R, Li Y, Yao W, Yuan J, Wu Q, Yang J, Yan W, Han L, et al: MiR-449a regulates autophagy to inhibit silica-induced pulmonary fibrosis through targeting Bcl2. J Mol Med (Berl). 94:1267–1279. 2016. View Article : Google Scholar : PubMed/NCBI
38	Kanno H, Ozawa H, Sekiguchi A and Itoi E: The role of autophagy in spinal cord injury. Autophagy. 5:390–392. 2009. View Article : Google Scholar : PubMed/NCBI
39	Li H, Zhang Q, Yang X and Wang L: PPAR-γ agonist rosiglitazone reduces autophagy and promotes functional recovery in experimental traumaticspinal cord injury. Neurosci Lett. 650:89–96. 2017. View Article : Google Scholar : PubMed/NCBI