摘要
Background: Patients with diabetes mellitus (DM) have higher incidence and more severe urinary tract infections (UTIs) for longer duration than those of the patients without DM. It causes more complicated etiologies during uropathogenic Escherichia coli (UPEC) infection. However, studies regarding the molecular mechanism are scarce. Methods: The present study (1) aimed to verify if sugar influences the process of UPEC-induced cystitis and invasion into the uroepithelial cells and (2) illustrated the mechanism of effects for sugar enhanced the UPEC infection into uroepithelial cells is related to TLR-4-mediated and JAK/STAT1-dependent pathway. Results: The results of the present study indicated that sugar can enhance UPEC infection in uroepithelial cells by up-regulating the transduced circuit between TLR-4-mediated UPEC interaction and JAK/STAT-1 signal pathways. The results of the inhibitor-co-incubating experiments demonstrated that the mechanism involved in the synergistic amplification of TLR-4-mediated UPEC interaction and JAK/STAT1 signaling pathways is responsible for the increased UPEC infection in uroepithelial cells. Conclusion: The results also proved that STAT-1 plays a critical role in the regulation of UPEC invasion and infection in the uroepithelial cells, especially those pretreated with glucose. The present study suggests a possible therapeutic approach to preferentially suppress UPEC infection during UTIs in the patients with diabetes.
原文 | 英語 |
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頁(從 - 到) | 193-205 |
頁數 | 13 |
期刊 | Journal of Microbiology, Immunology and Infection |
卷 | 54 |
發行號 | 2 |
DOIs | |
出版狀態 | 已發佈 - 1月 1 2019 |
ASJC Scopus subject areas
- 免疫學和過敏
- 一般免疫學和微生物學
- 微生物學(醫學)
- 傳染性疾病
指紋
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Data for: Enhanced uropathogenic Escherichia coli-induced infection in uroepithelial cells by sugar through TLR-4 and JAK/STAT1 signaling pathways
Ho, C.-H. (Contributor), Fan, C.-K. (Contributor), Wu, C.-C. (Contributor), Yu, H.-J. (Contributor), Liu, H.-T. (Contributor), Chen, K.-C. (Contributor), Liu, S.-P. (Contributor) & Cheng, P.-C. (Creator), Mendeley Data, 2019
DOI: 10.17632/n25dwn3zjj.1, https://data.mendeley.com/datasets/n25dwn3zjj
資料集: Dataset