PubMed 19136465
Referenced in: none
Automatically associated channels: Cav1.2 , HCN2
Title: A single anti-microRNA antisense oligodeoxyribonucleotide (AMO) targeting multiple microRNAs offers an improved approach for microRNA interference.
Authors: Yanjie Lu, Jiening Xiao, Huixian Lin, Yunlong Bai, Xiaobin Luo, Zhiguo Wang, Baofeng Yang
Journal, date & volume: Nucleic Acids Res., 2009 Feb , 37, e24
PubMed link: http://www.ncbi.nlm.nih.gov/pubmed/19136465
Abstract
Anti-miRNA antisense inhibitors (AMOs) have demonstrated their utility in miRNA research and potential in miRNA therapy. Here we report a modified AMO approach in which multiple antisense units are engineered into a single unit that is able to simultaneously silence multiple-target miRNAs, the multiple-target AMO or MTg-AMO. We validated the technique with two separate MTg-AMOs: anti-miR-21/anti-miR-155/anti-miR-17-5p and anti-miR-1/anti-miR-133. We first verified the ability of the MTg-AMOs to antagonize the repressive actions of their target miRNAs using luciferase reporter activity assays and to specifically knock down the levels of their target miRNAs using real-time RT-PCR methods. We then used the MTg-AMO approach to identify several tumor suppressors-TGFBI, APC and BCL2L11 as the target genes for oncogenic miR-21, miR-155 and miR-17-5p, respectively, and two cardiac ion channel genes HCN2 (encoding a subunit of cardiac pacemaker channel) and CACNA1C (encoding the alpha-subunit of cardiac L-type Ca(2+) channel) for the muscle-specific miR-1 and miR-133. We further demonstrated that the MTg-AMO targeting miR-21, miR-155 and miR-17-5p produced a greater inhibitory effect on cancer cell growth, compared with the regular single-target AMOs. Moreover, while using the regular single-target AMOs excluded HCN2 as a target gene for either miR-1 or miR-133, the MTg-AMO approach is able to reveal HCN2 as the target for both miR-1 and miR-133. Our findings suggest the MTg-AMO as an improved approach for miRNA target finding and for studying function of miRNAs. This approach may find its broad application for exploring biological processes involving multiple miRNAs and multiple genes.