The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
miR-375 Targets 3′-Phosphoinositide–Dependent Protein Kinase-1 and Regulates Glucose-Induced Biological Responses in Pancreatic β-Cells
Open accessAbstract
OBJECTIVE—MicroRNAs are short, noncoding RNAs that regulate gene expression. We hypothesized that the phosphatidylinositol 3-kinase (PI 3-kinase) cascade known to be important in β-cell physiology could be regulated by microRNAs. Here, we focused on the pancreas-specific miR-375 as a potential regulator of its predicted target 3′-phosphoinositide–dependent protein kinase-1 (PDK1), and we analyzed its implication in the response of insulin-producing cells to elevation of glucose levels. RESEARCH DESIGN AND METHODS—We used insulinoma-1E cells to analyze the effects of miR-375 on PDK1 protein level and downstream signaling using Western blotting, glucose-induced insulin gene expression using quantitative RT-PCR, and DNA synthesis by measuring thymidine incorporation. Moreover, we analyzed the effect of glucose on miR-375 expression in both INS-1E cells and primary rat islets. Finally, miR-375 expression in isolated islets was analyzed in diabetic Goto-Kakizaki (GK) rats. RESULTS—We found that miR-375 directly targets PDK1 and reduces its protein level, resulting in decreased glucose-stimulatory action on insulin gene expression and DNA synthesis. Furthermore, glucose leads to a decrease in miR-375 precursor level and a concomitant increase in PDK1 protein. Importantly, regulation of miR-375 expression by glucose occurs in primary rat islets as well. Finally, miR-375 expression was found to be decreased in fed diabetic GK rat islets. CONCLUSIONS—Our findings provide evidence for a role of a pancreatic-specific microRNA, miR-375, in the regulation of PDK1, a key molecule in PI 3-kinase signaling in pancreatic β-cells. The effects of glucose on miR-375 are compatible with the idea that miR-375 is involved in glucose regulation of insulin gene expression and β-cell growth.
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Bartel (2004) · doi:10.1016/s0092-8674(04)00045-5 · Cited by 34,714
The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14
Lee, R. C., Feinbaum, R. L., & Ambros, V. (1993) · Cell · doi:10.1016/0092-8674(93)90529-y · Cited by 12,948
Silencing of microRNAs in vivo with ‘antagomirs’
Krützfeldt, J., Rajewsky, N., Braich, R., Rajeev, K. G., Tuschl, T., Manoharan, M., & Stoffel, M. (2005) · Nature · doi:10.1038/nature04303 · Cited by 3,949
Critical nodes in signalling pathways: insights into insulin action
Taniguchi, C. M., Emanuelli, B., & Kahn, C. R. (2006) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1837 · Cited by 2,760
A pancreatic islet-specific microRNA regulates insulin secretion
Poy, M. N., Eliasson, L., Krutzfeldt, J., Kuwajima, S., Ma, X., MacDonald, P. E., Pfeffer, S., Tuschl, T., Rajewsky, N., Rorsman, P., et al. (2004) · Nature · doi:10.1038/nature03076 · Cited by 2,102
miR-122 regulation of lipid metabolism revealed by in vivo antisense targeting
Esau, C., Davis, S., Murray, S. F., Yu, X. X., Pandey, S. K., Pear, M., Watts, L., Booten, S. L., Graham, M., McKay, R., et al. (2006) · Cell Metabolism · doi:10.1016/j.cmet.2006.01.005 · Cited by 2,082
Makeyev, E. V., Zhang, J., Carrasco, M. A., & Maniatis, T. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.07.015 · Cited by 1,395
Five stages of evolving beta-cell dysfunction during progression to diabetes
Weir, G. C., & Bonner-Weir, S. (2004) · Diabetes · doi:10.2337/diabetes.53.suppl_3.s16 · Cited by 1,126
Plaisance, V., Abderrahmani, A., Perret-Menoud, V., Jacquemin, P., Lemaigre, F., & Regazzi, R. (2006) · Journal of Biological Chemistry · doi:10.1074/jbc.m601225200 · Cited by 350
MicroRNA-124a Regulates Foxa2 Expression and Intracellular Signaling in Pancreatic β-Cell Lines*
Baroukh, N., Ravier, M. A., Loder, M. K., Hill, E. V., Bounacer, A., Scharfmann, R., Rutter, G. A., & Van Obberghen, E. (2007) · Journal of Biological Chemistry · doi:10.1074/jbc.m611841200 · Cited by 326
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Rottiers, V., & Näär, A. M. (2012) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3313 · Cited by 1,156
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Metadata
- Authors
- El Ouaamari, A., Baroukh, N., Martens, G. A., Lebrun, P., Pipeleers, D., & van Obberghen, E.
- Venue
- Diabetes
- Publisher
- American Diabetes Association
- Published
- 2008-10-01
- Volume
- 57
- Issue
- 10
- Pages
- 2708-2717
- ISSN
- 0012-1797 (ISSN-L)
- 1939-327X
- OpenAlex
- W2151428158
- Cited by
- 430
- References
- 10
- FWCI
- 18.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
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