Name: detection of mirna targets in high-throughput using the 3'life assay
Uploaded: 2015-05-25T13:00:00
Description: Watch this Scientific Journal Video about Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay at JoVE.com

We thank Stephen Blazie, Karen Anderson, Josh LaBaer for advice and discussion. Karen Anderson, John Chaput, and Josh LaBaer for sharing reagents and instrumentation, Michael Gaskin and Andrea Throop for technical advise and protocols. Justin Wolter is a Maher scholar and thanks the Maher family for their generous support.

1. Cell Culture (24-48 hr&#160;prior to transfection)
<ol>
	<li>24-48 hr prior to transfection seed a sufficient quantity of HEK293T cells based on the number of 96-well plates being transfected. 
	NOTE: For consistent transfections, plate cells at a sufficient density to favor rapid division, yet not be at more than 70-90% confluency at the time of transfection.</li>
	<li>Each 96-well plate requires 9 x 106 cells (75,000 cells per well, and 120 wells per plate to account for use of reservoir and multic...

<ol>
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The 3&#8217;LIFE assay identifies functional miRNA targets in 3&#8217;UTRs in high-throughput. This assay is useful for researchers who wish to experimentally identify a large number of putative targets for their miRNA of interest. The 3&#8217;LIFE assay is a powerful approach to query for 3&#8217;UTR driven regulation, in that the assay provides a functional measure of miRNA targeting, and the binary testing of a single reporter::3&#8217;UTR against a single miRNA can confidently address the targeting status of individu...

The overall goal of this method is to detect and precisely map microRNA (miRNA) targets in high-throughput. MiRNAs are endogenous non-coding RNAs ~22 nucleotides in length. Following transcription and processing, mature miRNAs are incorporated in a protein complex called the RNA induced silencing complex (RISC). Each miRNA guides the RISC to target elements located primarily in the 3&#8217;untranslated regions (3&#8217;UTRs) of messenger RNAs (mRNAs), resulting in either translation repression or mRNA cleavage 1. MiRNA recognize target sites based on standard Watson-Crick and G:U wobble base pairing, and are degenerate in nature, containing multiple mismatched base pairs and bulged regions. Many miRNAs are broadly conserved from plants to humans 2,3, where they play a diverse range of biological roles. In metazoans miRNAs can influence multiple biological processes including cell fate decisions 4, developmental timing 5, and frequently exhibit tissue specific expression patterns 6,7. MiRNA misexpression can also result in aberrant gene regulation, which can have substantial influence on cell behaviour based solely on the function of target genes. As such, miRNAs are linked to a wide range of diseases, including neurodegeneration 8,9, diabetes 10 and cancer 11. Bioinformatic and wet-bench approaches suggest that each miRNA may be capable of targeting hundreds to thousands of distinct mRNAs 12-14, indicating that high-throughput or genome wide approaches are required to probe this large pool of potential interactions.
Identifying target genes is a critical component of mechanistically defining miRNA function, and to do so researchers must be able to reveal targets on a large scale. Several approaches have been developed to identify miRNA targets, including bioinformatic prediction algorithms, high-throughput sequencing of targeted mRNAs, and reporter based assays. Each of these approaches has inherent strengths and weaknesses. Given that miRNA targeting is guided by sequence specificity, most notably of nucleotides 2-6 of the miRNA (termed the seed region), several algorithms have been developed to predict miRNA targets throughout the genome of many organisms. These algorithms are trained using the observed base-pairing motifs of validated miRNA targets, and frequently utilize parameters such as stringent seed pairing, site conservation, and/or thermodynamic stability 15. While these filters refine the large number of putative targets with sufficient complementarity to only high confidence targets, they may exclude species specific and non-canonical miRNA target sites, which recent evidence suggests are widespread 16-24. Furthermore, these predictions do not take into account mechanisms of mRNA processing that exclude miRNA target sites, such as alternative polyadenylation 25, RNA editing 26, RNA methylation 27, and cooperative binding. As such, high false positive and false negative rates have been reported for many algorithms 22,24,28. While these algorithms are useful to identify candidate miRNA targets for subsequent experimental validation, these high error rates limit the efficacy of bioinformatic approaches for systematic miRNA target detection.
To systematically probe for interactions between a given miRNA and potentially targeted 3&#8217;UTRs we have developed a high-throughput assay called Luminescent Identification of Functional Elements in 3&#8217;UTRs (3&#8217;LIFE) 24. This assay measures direct interactions and translational repression of the test 3&#8217;UTR by a query miRNA using a dual luciferase reporter system. In this system, the 3&#8217;UTR of a gene of interest is cloned downstream of the firefly luciferase (fluc) reporter reading frame. The reporter construct is cotransfected with a query miRNA in HEK293T cells. MiRNA targeting is determined by measuring the relative change between the test fluc::3&#8217;UTR reporter and a second non-specific Renilla luciferase reporter. Importantly, luciferase assays detect functional miRNA/mRNA interactions that influence the translational output of the reporter. This is a key advantage over traditional methods to detect miRNA regulation, such as RT-qPCR and Western blots, in that this bypasses differences in mRNA degradation and translational repression, as well as changes in protein abundance independent of 3&#8217;UTR based regulation.
Luciferase assays are widely utilized to validate direct miRNA targets because of their relative simplicity and sensitivity, yet their use in high-throughput screens is limited by high costs associated with consumable reagents, the lack of 3&#8217;UTR libraries from public sources, and the absence of standardized luciferase protocols, leading to difficulties in comparing functional repression across multiple datasets. To facilitate the use of the 3&#8217;LIFE assay, we have placed emphasis on simplification of experimental design, utilization of non-commercial transfection 24 and luciferase reagents 29, creating a 3&#8217;UTR library which is regularly updated and expanded, and is available through a public plasmid repository 30.
The scalability of the 3&#8217;LIFE assay allows screening of a large 3&#8217;UTR library for targeting by a given miRNA without biasing the screen towards bioinformatically identified genes. In addition to testing canonical and predicted interactions, this systematic approach allows the identification of novel targets driven via non-canonical and/or species-specific interactions. Importantly, the effect of miRNA targeting on protein production is generally understood to result in modest translational repression 15,31, suggesting that a primary role of miRNA regulation is to fine-tune protein output, protect against aberrant levels of gene expression, and provide robustness to cell specific programs 32,33. The sensitivity of the luciferase assay combined with the inherently large number of negative miRNA/mRNA interactions in the 3&#8217;LIFE screen allows the detection of subtle effects of miRNA targeting on a large number of genes, and the identification of multiple components of gene networks that are regulated by a given miRNA 24.
Here we describe the 3&#39;LIFE protocol, and demonstrate it&#8217;s feasibility by screening two well characterized miRNAs, miR-10b and let-7c against a panel of 275 human 3&#39;UTRs (Figure 1).

<table border="0" cellpadding="0" cellspacing="0" width="406">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Reagents</td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">glycylglycine</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">G1127-25G</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Kx PO4</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">P2222</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">EGTA</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">E3889</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">ATP</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">FLAAS</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">DTT</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">D0632</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MgSO4</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">M7506</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">CoA</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">C4282</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">luciferin</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">L9504</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">NaCl</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">S7653</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Na2EDTA</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">E0399</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">K H2 P O4</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">1551139</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">BSA</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">A2153</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">NaN3</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">S2002</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Coelenterazine</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">C3230</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">PBS/HEPES</td>
			<td style="width:71px;">Corning</td>
			<td style="width:119px;">21-040-CV</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">DMEM</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">D5546</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">FBS</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">F2442</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Pennicilin/Streptomicin</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">P4333</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Trypsin</td>
			<td style="width:71px;"></td>
			<td style="width:119px;">T2600000</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;"></td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Consumables</td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">MaxiPrep Kit</td>
			<td style="width:71px;">Promega</td>
			<td style="width:119px;">A2392</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">96-well miniprep plate</td>
			<td style="width:71px;">Pall</td>
			<td>8032</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">96-well shuttle plates</td>
			<td style="width:71px;">Lonza</td>
			<td style="width:119px;">V4SP-2096</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">5x Lysis Buffer</td>
			<td style="width:71px;">Promega</td>
			<td>E1941&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;"></td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Instruments</td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">96-well GloMax Plate Reader</td>
			<td style="width:71px;">Promega</td>
			<td style="width:119px;">E9032</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Biomech FX Liquid Handler Robot</td>
			<td style="width:71px;">Beckmann</td>
			<td style="width:119px;">A31842</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">4D-Nucleofector Core Unit</td>
			<td style="width:71px;">Lonza</td>
			<td style="width:119px;">AAF-1001</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">96-well Shuttle System</td>
			<td style="width:71px;">Lonza</td>
			<td style="width:119px;">AAM-1001</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Cell Counter Countess</td>
			<td style="width:71px;">Invitrogen</td>
			<td style="width:119px;">C10227</td>
		</tr>
	</tbody>
</table>

detection of mirna targets in high-throughput using the 3'life assay

Luminescent Identification of Functional Elements in 3&#8217;UTRs (3&#8217;LIFE) allows the rapid identification of targets of specific miRNAs within an array of hundreds of queried 3&#8217;UTRs. Target identification is based on the dual-luciferase assay, which detects binding at the mRNA level by measuring translational output, giving a functional readout of miRNA targeting. 3&#8217;LIFE uses non-proprietary buffers and reagents, and publically available reporter libraries, making genome-wide screens feasible and cost-effective. 3&#8217;LIFE can be performed either in a standard lab setting or scaled up using liquid handling robots and other high-throughput instrumentation. We illustrate the approach using a dataset of human 3&#8217;UTRs cloned in 96-well plates, and two test miRNAs, let-7c and miR-10b. We demonstrate how to perform DNA preparation, transfection, cell culture and luciferase assays in 96-well format, and provide tools for data analysis. In conclusion 3&#39;LIFE is highly reproducible, rapid, systematic, and identifies high confidence targets.

The luminometer output file contains raw measurements for both firefly and Renilla luciferase proteins. This raw format is compatible with the &#8220;3&#8217;LIFE &#8211; single plate analysis&#8221; and &#8220;3&#8217;LIFE &#8211; multiplate analysis&#8221; spreadsheets available from the Mangone lab website (<a href="http://www.mangonelab.com">www.mangonelab.com</a>). The single plate analysis spreadsheet automatically calculates firefly/Renilla ratio, normalizes each miRNA to the appropriate negativ...

Watch this Scientific Journal Video about Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay at JoVE.com

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Luminescent identification of functional elements in 3&#8217; untranslated regions (3&#8217;UTRs) (3&#8217;LIFE) is a technique to identify functional regulation in 3&#8217;UTRs by miRNAs or other regulatory factors. This protocol utilizes high-throughput methodology such as 96-well transfection and luciferase assays to screen hundreds of putative interactions for functional repression.

Luminescent Identification of Functional Elements in 3&#8217;UTRs (3&#8217;LIFE) allows the rapid identification of targets of specific miRNAs within an ...

Research

JoVE Journal

Biology

High-throughput Saccharification Assay for Lignocellulosic Materials

Polysaccharides that make up plant lignocellulosic biomass can be broken down to produce a range of sugars that subsequently can be 
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The Target ID Library is designed to assist in discovery and identification of microRNA (miRNA) targets. The Target ID Library is a plasmid-based, ...

High-throughput Crystallization of Membrane Proteins Using the Lipidic Bicelle Method

Membrane proteins (MPs) play a critical role in many physiological processes such as pumping specific molecules across the otherwise impermeable membrane ...

High-throughput Physical Mapping of Chromosomes using Automated in situ Hybridization

High-throughput Physical Mapping of Chromosomes using Automated in situ Hybridization

Projects to obtain whole-genome sequences for 10,000 vertebrate species1 and for 5,000 insect and related arthropod species2 are expected to take place ...

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

Transposon  mutagenesis and single-gene deletion are two methods applied in genome-wide  gene knockout in bacteria 1,2. Although transposon mutagenesis is ...

RNA Secondary Structure Prediction Using High-throughput SHAPE

Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed ...

High-throughput Functional Screening using a Homemade Dual-glow Luciferase Assay

We present a rapid and inexpensive high-throughput screening protocol to identify transcriptional regulators of alpha-synuclein, a gene associated with ...

High-throughput Screening for Chemical Modulators of Post-transcriptionally Regulated Genes

Both transcriptional and post-transcriptional regulation have a profound impact on genes expression. However, commonly adopted cell-based screening assays ...

Identification of Kinase-substrate Pairs Using High Throughput Screening


We have developed a screening platform to identify dedicated human protein kinases for phosphorylated substrates which can be used to elucidate novel ...

High Throughput Danio Rerio Energy Expenditure Assay

High Throughput Danio Rerio Energy Expenditure Assay

Zebrafish are an important model organism with inherent advantages that have the potential to make zebrafish a widely applied model for the study of ...