Identification of key genes and construction of microRNA–mRNA regulatory networks in bladder smooth muscle cell response to mechanical stimuli using microarray expression profiles and bioinformatics analysis
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To identify keys genes and elucidate miRNA–mRNA regulatory networks in Bladder smooth muscle cell (BSMC) response to mechanical stimuli.
Human BSMCs, seeded on a silicone membrane, were subjected to mechanical stretch or without stretch. Microarray was used to analyze the differential expression of mRNAs and miRNAs between human BSMCs under mechanical stretch and control static control group. Differentially expressed genes(DEGs) and miRNAs (DEMs) in these two groups were identified. Subsequently, differentially expressed DEGs were conducted with functional analysis, and then PPI network was constructed. Finally, miRNA–mRNA regulatory network was visualized using Cytoscape.
1639 significant DEGs and three DEMs were identified between the stretch group and control static group. The PPI network of DEGs was constructed by STRING, which was composed of 1459 nodes and 1481 edges, including 188 upregulated genes and 255 downregulated genes. Moreover, 36 genes in the PPI network were identified as hub genes in BSMCs response to mechanical stretch, e.g. CCNH, CPSF2, TSNAX, ARPC5 and PSMD3 genes. Subsequently, 39 clusters were selected from PPI network using MCODE, and it was shown that the most significant cluster consisted of 14 nodes and 91 edges. Besides, miR-503HG was the most significantly downregulated miRNA and was predicted to target five upregulated genes, including SMAD7, CCND3, WIPI2, NYNRIN and PVRL1.
Our data mining and integration help reveal the mechanotransduction mechanism of BSMCs’ response to mechanical stimulation and contribute to the early diagnosis of bladder outlet obstruction (BOO) as well as the improvement of pathogenesis of BOO treatment.
KeywordsBladder smooth muscle cell Mechanical stimulation Microarray expression profiles Bioinformatics analysis
LP, D-YL: Protocol/project development. D-YL: Data collection or management. LP, D-YL: Data analysis. D-YL: Manuscript writing/editing.
This study was funded by Grant No. 81770673, No. 31170907, No. 31370951, and No. 81470927 from the National Natural Science Foundation of China, Grant No. JH2015017 from Application-oriented Foundation of Committee Organization Department of Sichuan Provincial Party and 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University.
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
- 7.Chen S, Peng C, Wei X, Luo D, Lin Y, Yang T, Jin X, Gong L, Li H, Wang K (2017) Simulated physiological stretch increases expression of extracellular matrix proteins in human bladder smooth muscle cells via integrin α4/αv-FAK-ERK1/2 signaling pathway. World J Urol 35(8):1247–1254CrossRefPubMedGoogle Scholar
- 15.Wang KC, Nguyen P, Weiss A, Yeh YT, Chien HS, Lee A, Teng D, Subramaniam S, Li YS, Chien S (2014) MicroRNA-23b regulates cyclin-dependent kinase-activating kinase complex through cyclin H repression to modulate endothelial transcription and growth under flow. Arterioscler Thromb Vasc Biol 34(7):1437–1445CrossRefPubMedPubMedCentralGoogle Scholar
- 19.Kinoshita T, Nohata N, Watanabe-Takano H, Yoshino H, Hidaka H, Fujimura L, Fuse M, Yamasaki T, Enokida H, Nakagawa M, Hanazawa T, Okamoto Y, Seki N (2012) Actin-related protein 2/3 complex subunit 5 (ARPC5) contributes to cell migration and invasion and is directly regulated by tumor-suppressive microRNA-133a in head and neck squamous cell carcinoma. Int J Oncol 40(6):1770–1778PubMedGoogle Scholar
- 27.Muys BR, Lorenzi JC, Zanette DL, Lima e Bueno Rde B, de Araújo LF, Dinarte-Santos AR, Alves CP, Ramão A, de Molfetta GA, Vidal DO, Silva WA Jr (2016) Placenta-Enriched LincRNAs MIR503HG and LINC00629 Decrease migration and invasion potential of JEG-3 cell line. PLoS One 11(3):e0151560CrossRefPubMedPubMedCentralGoogle Scholar
- 28.Brandenberger R, Wei H, Zhang S, Lei S, Murage J, Fisk GJ, Li Y, Xu C, Fang R, Guegler K, Rao MS, Mandalam R, Lebkowski J, Stanton LW (2004) Transcriptome characterization elucidates signaling networks that control human ES cell growth and differentiation. Nat Biotechnol 22(6):707–716CrossRefPubMedGoogle Scholar