Liao Peng1, De-Yi Luo2. 1. Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China. 2. Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China. luodeyi1985@163.com.
Abstract
PURPOSE: To identify keys genes and elucidate miRNA-mRNA regulatory networks in Bladder smooth muscle cell (BSMC) response to mechanical stimuli. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
PURPOSE: To identify keys genes and elucidate miRNA-mRNA regulatory networks in Bladder smooth muscle cell (BSMC) response to mechanical stimuli. METHODS: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. RESULTS: 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. CONCLUSIONS: 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.
Authors: G Andersen; D Busso; A Poterszman; J R Hwang; J M Wurtz; R Ripp; J C Thierry; J M Egly; D Moras Journal: EMBO J Date: 1997-03-03 Impact factor: 11.598
Authors: Ettickan Boopathi; Cristiano Gomes; Stephen A Zderic; Bruce Malkowicz; Ranjita Chakrabarti; Darshan P Patel; Alan J Wein; Samuel Chacko Journal: Am J Physiol Cell Physiol Date: 2014-07-16 Impact factor: 4.249
Authors: Shazia Mahamdallie; Shawn Yost; Emma Poyastro-Pearson; Esty Holt; Anna Zachariou; Sheila Seal; Anna Elliott; Matthew Clarke; Margaret Warren-Perry; Sandra Hanks; John Anderson; Simon Bomken; Trevor Cole; Roula Farah; Rhoikos Furtwaengler; Adam Glaser; Richard Grundy; James Hayden; Steve Lowis; Frédéric Millot; James Nicholson; Milind Ronghe; Jane Skeen; Denise Williams; Daniel Yeomanson; Elise Ruark; Nazneen Rahman Journal: Lancet Child Adolesc Health Date: 2019-03-16