MicroRNAs (miRNAs) are endogenous 22-nt long non-coding RNAs that regulate gene expression post-transcriptionally in a diversity of organisms (Bartel, 2004). Although the understanding of miRNA biological functions is progressing remarkably, the exact mechanisms by which miRNAs regulate gene expression are still not unambiguously defined. However, it is commonly believed that miRNAs trigger target mRNA regulation by binding to 3’UTRs (Chekulaeva & Filipowicz, 2009). The discovery of the first miRNA (lin-4) revealed sequence complementarity to multiple conserved sites in the 3’UTR of the lin-14 mRNA (Lee et al., 1993; Wightman et al., 1993). Exact principles of gene expression knockdown mediated by miRNA are still in debate (Eulalio et al., 2008).
Binding site properties have an essential impact on miRNA-mRNA interaction [figure, short explanations on seed regions, flanking regions, spacers, mismatches and resulting bulges]. Some functionally important parts of miRNAs have been described in literature, such as the seed region (Grimson et al., 2007; Bartel, 2009). It is defined as a region of seven nucleotides length that shows perfect pairing between the miRNA and its target sequence. The seed usually consists of the nucleotides on position 2-8 of a miRNA binding sites in the 5'UTR of the mRNA. Based on this simple principle, we randomized our miRNA binding sites between nucleotide 9 - 12 or 9 - 22 in the so called flanking region. Alternatively, we tried rational exchanges of nucleotides to see how they effect binding of the miRNA to its target mRNA. A combination of random and rational design of binding sites could thereby help to achieve a narrow range of resulting knockdown. Hence, we wrote a programm - the miBS designer - for in silico construction of synthetic miRNA binding sites. The experimental applicability is still limited by redundant target sites and various miRNA expression patterns within the cells. This hampers distinct expression levels of the gene of interest (GOI) fused to the miRNA binding site. We (want to overcome) these limitations in vitro and in vivo with our synthetic miRNA Kit.
Results
After creating a binding site library and testing the miRNA-binding site interaction in vitro, we were able to compute an in silico model based on a machine learning approach to predict knockdown efficiencies. Thereby, we created an integrative feedback loop between experiments and simulation. A more detailed description of the different binding sites, we characterized can be found in our measurements page.
The basic set-up of our fine tuning construct, miTuner, allows on the simultaneous expression of a synthetic miRNA and a gene of interest (GOI) that is fused with a binding site for this specific miRNA.
Our kit comes with different parts that can be combined by choice, e. g. different mammalian promoters and characterized binding sites of specific properties. By choosing a certain binding site to tag the GOI, one can adjust the level of expression of this gene. In a proof-of-principle approach, we show the fine-tuning capability of our setup using a Dual Luciferase Assay. Here, firefly luciferase acts as the GOI targeted by a synthetic miRNA, while Renilla is used to normalize measurements. FIGURES
Another application of our synthetic miRNA Kit profits of tissue specific endogenous miRNAs expression. These can be exploited for On and Off-Targeting. On targeting in this case would mean that the presence of a certain miRNA in a cell switches on expression of the GOI. This can be accomplished by using a repressor that is targeted by an endogenously expressed miRNA. We exemplified this scenario by using a Tet Repressor fused with a perfect binding site for miRNA 122, a liver-specific miRNA (REF!). At the same time, the promoter expressing the GOI would be under control of a Tet Operator. Upon presence of the miRNA 122, the Tet Repressor would be knocked down, release the promoter and expression of the GOI could be established.
(YOUC AN CHANGE THIS INTO PAST TENSE IF IT WORKED. AND ADD THE OFF SWITCHE; I AM NOT CERTAIN OF WHAT WE DID THERE, AND FIGURES!)
We further tested our kit using a gene that is an interesting candidate for gene therapy, human alpha-1-antitrypsin (haat) (ref, description). In this approach, we tagged haat, that we used as our GOI, with binding sites that we measured and characterized with our miMeasure construct beforehand. This was a first potential therapeutic approach applying ELISA for measurements.
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