miMeasure

Abstract

With the rising importance of small RNA molecules in gene therapy the identification and characterization of miRNAs and their binding sites become crucial for innovative applications. In order to exploit the miRNA ability to target and regulate specific genes, we constructed a measurement standard (see sidebar) not only to characterize existing miRNAs but also to validate potential synthetic miRNAs for a new therapeutic approach. The synthetic miRNAs we created lack endogenous targets and are thus applicable for gene regulation without any side effects. This openes new possiblities of precise expression tuning. Our miMeasure constructs plasmid normalizes knockdown of the green fluorescent protein (EGFP) to the blue fluorescent protein (EBFP2). This allows an accurate study of binding site properties, since both fluorescent proteins are combined in the same construct and driven by the same bidirectional promoter. Another advantage is, that any desired binding site can be cloned easily into the miMeasure plasmid with the BB_2 standard. As the binding site is inserted downstream of EGFP, a regulation of EGFP expression is to be expected. The percentage of knockdown of each modified binding site can be determined by the comparison of the ratio of EGFP to EBFP2 ratio compared to the ratio of the perfect binding site caused knock-down. The ratio is derived from a linear regression curve. Therefore the knock-down efficiency can be conducted by various basic methods e.g. plate reading, flow cytometry or microscopy.

Introduction

Micro RNAs regulate the translation of their target genes by preferably binding to regions in the 3’ UTR which are called miRNA binding sites (BS)(ref). This miRNA BS consists of a bp seed region at the 3'UTR that is perfectly matched to the miRNA, and surrounding regions that matched partially. The seed region is defined as being the minimal required basepairing at the 3’ end of the miRNA that can regulate the mRNA. Apart from the seed region, binding can be unspecific, creating bulges between miRNA and mRNA (fig). The position and properties of the bulges seem to play a role in miRNA binding and therefore knockdown efficiency (reviewed in Bartel et al., 2009).

Since we were going to use synthetic miRNA BS in our genetherapeutic approach, we had to find a way to study their effects in a standardized manner that would be comparable and reproducible.

One goal of the iGEM Team Heidelberg 2010 was to test the effects of changes in BS sequence and thereby characterize miRNA BS. To standardize our measurements of knockdown according to BS specificity, we had to come up with a new standard that is independent from the endogenous cell machinery. We decided to bring in synthetic miRNAs and engineer BS for them, simulating naturally occurring miRNAs and miRNA BS without having to worry about the effect of endogenous targets. Of course there are also differences that arise through the availability of the enzymes involved in the miRNA pathway that may differ slightly from cell to cell. Therefore, we also measured the knockdown achieved by the perfect binding site and set this as 100% knockdown efficiency. Ideally, the shRNA would be expressed stably in the cell line, but a uniform co-transfection also leads to an even distribution of shRNA into each cell.

The main idea of our measurement standard, miMeasure, was to express two nearly identical but discernable proteins, one of them tagged with a BS, the other one unregulated. These two reporters were expressed by a bidirectional CMV promoter to make sure their expression rate is identical. We used a destablilized version of GFP, dsEGFP by Clontech (ref) and a dsEBFP2 that was derived from the same sequence. Thus, we could make sure that both proteins exhibit the same synthesis and degradation properties, making them directly comparable. Hereby we can also neglect the difference between mRNA and protein knockdown and can take the fluorescence of the marker protein as a direct, linear output of mRNA knockdown. We included a BBB standard site into our plasmid, which allows to clone BS behind the GFP. If co-transfected with the corresponding shRNA, GFP will be downregulated, while BFP expression is maintained. The ratio of GFP to BFP expression can be used to conclude the knockdown efficiency (in percent, compared to perfect binding site=100% and no binding site=0%) of the BS. Having destabilized marker proteins with a turnover time of two hours enables us not only to avoid accumulation of marker proteins, which would make the knockdown harder to observe, but also to conduct time-lapse experiments. In the future, this could be for example a way to observe the activity patterns of endogenous miRNAs.

Results

Analysis of Randomized Binding Sites Against Synthetic miRNA

We used microscopy analysis to determine the EGFP expression in relation to EBFP2. EBFP2 serves as a normalization for transfection efficiency. Nine miMeasure constructs with different binding sites were designed. The binding sites are either mutated at one site, or they contain randomly changed sites within a certain range. If the GFP is down-knocked by the construct carrying a perfect binding site (which is complementary to the synthetic miRNA miRsAg) we set percentage of knock-down to 100%. The negative control represents 0% knock-down, since there is no binding site cloned into this miMeasure construct. So all the modified binding sites lie in between. The GFP/BFP-ratio stand for the level of GFP-expression normalized to on copy per cell. We modified binding sites for the synthetic miRNA by introducing random basepairs surrounding the seed region as described above, thereby changing the knockdown efficiency. In figure 1 we plotted the knockdown percentage of our constructs. The miMeasure construct and negative control were co-transfected with either shRNA miRsAg expressed from a CMV promoter on pcDNA5 or an inert synthetic RNA as control in 1:4 ratio, respectively.

GFP/BFP ratio normalized by the negative control The data are generated by confocal microscopy of Hela cells, which were transfected with different miMeasure constructs M12-M22 including the negative control (miMeasure construct without binding site). The negative control equals to 1.

Comparing the GFP/BFP-ratio between the constructs, we can see a significant difference of GFP expression in between the negative control and the construct containing the perfect binding site. Since the control is not downregulated due to lack of binding sites, we set it as 100% expression on this chart. It can be seen that the perfect binding sites effects the lowest GFP expression, approximately 50%, while other binding sites range in between 55% and 100% of expression.

Flow cytometry measurements

GFP/BFP ratio of single cells according to flow cytometry analysis

Analysis of miRaPCR Generated Binding Sites Against a Natural miRNA

The miRaPCR generates binding sites out of rationally designed fragments. These are aligned with each other by chance, whereby different spacer regions are inserted randomly in between. It has been suggested that having more than one binding site of for the same miRNA behind each other can lead to stronger down-regulation than a single one. If imperfect binding sites are aligned, it is also supposed to be stronger than a single one. This is what we tested using MiRaPCR for effortless assembly of binding site fragments. For our experiments, we took advantage of the high abundance of miRNA 122 in liver cells and tested different combinations of binding sites created by miRaPCR. We transfected HeLa and HuH7 cells with the constructs described in table 2. Since HuH7 cells express miR-122, the constructs will be affected in the HuH7 cells without cotransfecting any miRNAs, whereas miR-122 were cotransfected for the HeLa cells in 2:1 ratio. The result shows the ratio between GFP and BFP normalized to the negative control (miMeasure constructs without binding sites). The miMeasure constructs where also compared to the expression of miMeasure containing one perfect binding site for miRNA 122.

Discussion

Methods

The fluorescence of GFP and BFP can be compared using different methods, for example automated fluorescence plate reader systems, flow cytometry or manual and automated fluorescence microscopy.

References