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 multichannel pipette). Calculate the doubling time of HEK293 cells (typically ~20 hr), and seed the appropriate number of cells to obtain at least 9 x 106 cells at the time of transfection. A 145 mm circular culture plate is typically sufficient for 3 96-well transfections when grown to ~90% confluency, with ~10% of cells remaining to reseed a new plate.</li>
</ol>
2. Preparation Prior to Transfection
NOTE: The preparation of the buffers and plasmid DNA in step 2.0-2.2 should be performed in the days prior to transfection since the preparation of these reagents may be time consuming.
<ol>
	<li>Human 3&#39;UTR clones that are compatible with the 3&#39;LIFE assay are available through a public plasmid repository 30. Purify DNA plasmid manually or with liquid handling robots. Use a transfection grade alkaline lysis mini-prep 96-well kit and follow the manufacturer&#8217;s instructions. Resuspend the purified vectors to ~100 ng/&#956;l per well. 
	NOTE: Insufficient luciferase signal will result if plasmid concentration falls below 40 ng/&#956;l.</li>
	<li>Obtain the pLIFE-miRNA vectors 30 or clone using the pipeline in Figure 1B 24. Resuspend the vectors at a concentration of 500 ng/&#956;l for each miRNA and Blank control plasmids.</li>
	<li>Owing to the sensitivity of the nucleofection buffer conditions, ensure that the total volume of transfected materials (including cells and plasmids) does not exceed 10% of the total liquid in each well of the 96-well transfection plate. To achieve this, concentrate the pLIFE-miRNA plasmid stock at a concentration of least 500 ng/&#956;l.</li>
	<li>Prepare 10x firefly luciferase buffer reagents (Table 1), and the 1x Renilla luciferase buffer reagents (Table 2), which can be stored for up to 6 months. 
	NOTE: The DTT in the firefly luciferase buffer must to be stored in solution at -20&#160;oC in single use aliquots.</li>
</ol>
3. Prepare Following Items Immediately Prior to Transfection
<ol>
	<li>Prepare transfection buffer containing PBS, 1.5% HEPES, pH 7.0. Prepare this fresh, although it may be stored for up to 1 month at 4 &#176;C without noticeable decreases in transfection efficiency. In formulating buffer and plasmid DNA volumes, assume 120 reactions for each 96-well plate to sufficiently account for errors in pipetting and volume lost using liquid reservoirs and multichannel pipettes. Aliquot 18 &#956;l per well transfection buffer (120 wells/96-well plate = 2.16 ml per plate), and set aside. 
	NOTE: The cell-electroporation device is extremely sensitive to the buffer conditions used to transfect cells. Accuracy when preparing buffers will ensure consistent performance of the equipment. Extra care must be taken when performing the assay to prevent evaporation of buffers, specifically by minimizing the time that buffer is left uncovered in microcentrifuge tubes, 96-well plates, reservoirs, and electrode plates.</li>
	<li>Reserve four wells for the following controls, no pLIFE-3&#8217;UTR (to measure background of luciferase assay), pLIFE-SV40 3&#8217;UTR (negative target control), positive control for miRNA #1, positive control for miRNA #2. 
	NOTE: These vectors are publically available 30. Alternatively, any previously validated target can be used as a positive control.</li>
	<li>Warm media, trypsin (0.25%) to 37 &#176;C.</li>
	<li>To each well of 96-well cell culture plate, add 200 &#956;l of DMEM supplemented with 10% FBS, 1% Pen/Strep, and placed in a 37 &#176;C incubator for use following transfection.</li>
	<li>Turn on all cell electroporation devices followed by the supporting software. Use Pulse code FF120 for HEK293T cells and PBS/HEPES buffer.</li>
</ol>
4. Preparation of Plasmid DNA and Cell Mixture
NOTE: The following protocol assumes transfecting three 96-well plates in one experiment for a screen with two miRNAs (miRNA-#1 and miRNA-#2). Each plate will correspond to the same 96-well plate of pLIFE-3&#8217;UTR plasmids, and be treated three times with pLIFE-miRNA-blank, pLIFE-miRNA-#1, or pLIFE-miRNA-#2.
<ol>
	<li>Prepare 3 stocks of pLIFE-miRNA + transfection buffer for each miRNA. This stock should account for 50% (10 &#956;l) of total volume of each well, multiplied by 120 wells. Thus, each stock should contain 1.08 ml buffer + 120 &#956;l plasmid DNA (pLIFE-miRNA).</li>
	<li>Remove cells from 145 mm culture plate by eluting media, washing gently with PBS, and treating with ~5 ml 0.25% trypsin for 5 min at 37 &#176;C. Neutralize trypsin with an equal volume of media, and pellet cells at 300 x g for 5 min.</li>
	<li>Remove trypsin/media, and resuspend pellet in ~5-10 ml media (depending on cell density and accurate range of cell counter).</li>
	<li>Count cells using a cell counter. Ensure that cells are &#62;95% viable and within accurate range of machine. 
	NOTE: An inaccurate cell count can result from extremely high cell concentrations (&#62;6.0x&#160; 106/ml). Transfecting too many cells can drastically reduce efficiency of miRNA targeting by reducing plasmid:cell ratio and/or decreasing transfection efficiency.</li>
	<li>Aliquot three tubes each containing 9 x 106 cells, corresponding to the cells required for transfection of one 96-well plate. Spin cells at 300 x g for 3 min.</li>
	<li>Remove media. Be sure to remove as much media as possible with minimal disturbance of the pellet as excess media can impact transfection efficiency.</li>
	<li>Resuspend cells in 1.2 ml transfection buffer/miRNA plasmid mixture, and set aside.</li>
	<li>The following steps detail resuspension of pLIFE-3&#8217;UTR plasmid in transfection buffer. As this occurs in 96 well plates, take care to avoid evaporation of buffer by covering plates at all times.
	<ol>
		<li>Using a multichannel pipette, move 32.4 &#956;l transfection buffer into each well of a 96 well PCR plate (9 &#956;l [per transfection] * 3 [plates] * 1.2 [to account for pipette error]).</li>
		<li>Add 3.6 &#956;l (~100 ng/&#956;l) of mini-prepped pLIFE-3&#8217;UTR plasmid to each well and mix thoroughly.</li>
		<li>Pipette 10 &#956;l of this mixture into each well of the 96-well transfection plate and cover.</li>
	</ol>
	</li>
</ol>
5. Transfection
<ol>
	<li>Move 1.2 ml of the first cell/buffer/pLIFE-miRNA plasmid mixture into reservoir. Mix well.</li>
	<li>Add 10 &#956;l of this mixture into the first 96-well transfection plate already containing 10 &#956;l transfection buffer/pLIFE-3&#8217;UTR. Mix well by pipetting up and down several times. 
	NOTE: Equal suspension of cells in the buffer will ensure even and thorough passage of the electrical current through the cuvette and maximize transfection efficiency.</li>
	<li>Place 96-well transfection plate on the cell electroporation device and initiate transfection.</li>
	<li>Once transfection is complete, add 100 &#956;l of pre-warmed media from 96-well culture plate to each well of the 96-well transfection plate and mix well. Move 100 &#956;l from each well into the 96-well culture plate.</li>
	<li>Mix cells in culture plate with pipette positioned vertically in the center of the well, as cells will tend to aggregate on the sides of the well unless mixed properly.</li>
	<li>Repeat 5.1-5.5 for the remaining two plates.</li>
	<li>Cleaning 96-well transfection plate
	<ol>
		<li>The 96-well transfection plates can be recycled by washing with 70% EtOH to ensure no carry over of nucleic acids between experiments. Perform two 70% EtOH washes using a spray bottle to completely fill each well, followed by wiping down excess EtOH on the electrode strips (bottom side) and allowing the transfection plates to completely dry in the culture hood. 
		NOTE: We have tested for carry-over DNA contamination by transfecting 12 wells with 2 &#956;g pmaxGFP plasmid each into HEK293T cells, followed by a single wash with 70% EtOH, and a second transfection with no plasmid DNA. With this extremely high plasmid concentration, extremely bright reporter, and a single wash, there was no observable fluorescence in any of the 12 replicate transfections.</li>
	</ol>
	</li>
	<li>Culture cells for 48-72 hr at 37 &#176;C, followed by the dual luciferase assay.</li>
</ol>
6. Cell Lysate Preparation for Luciferase Assay
<ol>
	<li>Dilute lysis buffer with 4 parts water, 1 part 5x passive lysis buffer in a reservoir. Calculate 26 &#956;l/well, adding ~20 extra volumes to account for loss in the reservoir. 
	NOTE: Buffer is stored at -20 &#186;C and can be extremely viscous, thus prior to allowing the 5x buffer to approach room temperature will improve pipetting accuracy.</li>
	<li>Analyze each well for transfection efficiency using fluorescence microscopy. Note any inconsistencies in wells that did not transfect efficiently (&#62;90% transfection efficiency), or are expressing low levels of RFP indicative of overcrowding or media exhaustion. Remove these wells from the analysis.</li>
	<li>Completely remove the media from the cells, being careful not to elute too quickly which will cause cells to detach. 
	NOTE: Remaining media will dilute the lysate and cause fluctuations in values across experiments.</li>
	<li>Add 26 &#956;l of lysis buffer to each well, and place on a plate shaker/rocker at low/moderate speed for ~20-30 min. Use this time to prepare luciferase buffers, wash and prime the luminometer(s), and transfer lysate to opaque measurement plates.</li>
</ol>
7. Dual Luciferase Assay
NOTE: If multiple plates are being measured sequentially on one luminometer, create buffer master mixes with everything except ATP and substrates, adding these reagents followed by pH adjustment immediately before use with each plate. ATP and substrates may degrade over time; consistency in the amount of time these reagents are in the buffer will improve consistency across multiple plates.
<ol>
	<li>Prepare 1x luciferase buffers (Table 1):
	<ol>
		<li>Wrap two tubes (typically 15/50 ml centrifuge tubes) containing the firefly and Renilla buffers with aluminum foil, as substrates may be light sensitive.</li>
		<li>Prepare 1x Firefly luciferase buffer. Add 1 ml of each the five 10x firefly luciferase reagents, adding EGTA last, to 5 ml H20 to a final 1x concentration.
		<ol>
			<li>Add 0.025 g ATP to 10 ml 1x firefly buffer. Mix by inverting several times. Keep ATP on ice at all times. ATP will degrade, so if measuring more than one plate sequentially, buffer must be made fresh beginning at this step for each additional plate.</li>
			<li>Add 100 &#956;l of 100 beetle luciferin (substrate) (Table 1) Buffer should change to yellowish color based on pH.</li>
		</ol>
		</li>
		<li>1x Renilla luciferase buffer reconstitution: Per 96-well plate, aliquot 10 ml of 1 &#8220;Renilla buffer&#8221;.
		<ol>
			<li>Add 100 &#956;l of BSA (44 mg/ml stock).</li>
			<li>If screening more than one plate, separate master mix into 10 ml &#160;aliquots.</li>
			<li>Add 100 &#956;l of coelenterazine to buffer (previously aliquoted and stored at 100x conc.)</li>
		</ol>
		</li>
		<li>Adjust pH of 1x firefly buffer to 8.0, followed by the 1x Renilla buffer to 5.0 using NaOH and HCl. 
		NOTE: The activity of each buffer, and the ability of the Renilla buffer to quench the Firefly luciferase activity is highly dependent on pH. For consistent results be extremely accurate in this step.</li>
		<li>Bring volume of each buffer (corresponding to 1 96-well plate) to 10.5 ml to accommodate for luminometer priming.</li>
	</ol>
	</li>
	<li>Transfer lysate to opaque white plates: At this point the cells should be in lysis buffer for ~20 min. Take 25 &#956;l from each well using a multichannel pipette, be sure to pipet up and down thoroughly to break up the clumps of cells and homogenize the lysate.</li>
	<li>Prepare the luminometer. Turn on the luminometer and select the protocol in the DLR folder, called &#8220;DLR with two injections&#8221;. Other formats are not compatible with the data analysis pipeline (below).
	<ol>
		<li>Select the wells to be tested (all wells is the default).</li>
		<li>Extend the &#39;Delay before measurement&#39; setting to 5 seconds, with a 10 sec measurement time (see 29 for explanation).</li>
		<li>Capillary wash steps: water 3x, EtOH 3x, water 3x, dry 3x. Prime buffers once into the waste, and then prime a second time back into the buffer tubes to ensure mixing. Inject the firefly buffer first and prime it in the left capillary, followed by Renilla in the right capillary.</li>
	</ol>
	</li>
	<li>Initiate the luciferase assay. Each plate should take ~48 min to read. After completion save the file first, and then repeat the wash steps and shut off the luminometer. 
	NOTE: Multiple plates can be read and data stored on the same excel file, however issues may be encountered with multiple plate reads where the luminometer program will crash. Be sure to save all data between measurements and take screenshots if program crashes before save is possible.
	<ol>
		<li>Replace old buffers with new, being sure to prime at least twice with new buffers before starting the new plate.</li>
	</ol>
	</li>
</ol>
8. Data Analysis
<ol>
	<li>Utilize excel tables &#8220;3&#8217;LIFE - single plate analysis&#8221; and &#8220;3&#8217;LIFE &#8211; multiplate analysis&#8221; available from <a href="http://www.mangonelab.com">www.mangonelab.com</a>. Copy raw data for firefly and Renilla luciferase measurements from luminometer output file into locations corresponding to the negative condition, miRNA #1, and miRNA #2 into the &#8220;3&#8217;LIFE &#8211; single plate analysis&#8221; spreadsheet.</li>
	<li>The spreadsheet will automatically calculate firefly/Renilla ratio and normalize each miRNA to the appropriate negative control, and normalize repression values across each plate. 
	NOTE: This spreadsheet will automatically identify wells with low luciferase signal, highlight significantly repressed wells, and provide measures of repression across the entire plate. See 24 for detailed explanation of statistical analysis.
	<ol>
		<li>Copy the values from the &#8220;Normalized RI Index&#8221; box, into corresponding cells in the &#8220;3&#8217;LIFE &#8211; multiplate analysis&#8221; spreadsheet at the position corresponding to replicate #1 for each miRNA tested. Repeat for all biological replicates performed on different days.</li>
	</ol>
	</li>
	<li>If desired, insert the gene names and target prediction status in columns B and D, respectively.
	<ol>
		<li>Allow the spreadsheet to automatically calculate the average of all plate. Observe the data in 96 well format as a heat map (Figure 2). The file also arranges the data in list format (Figure 2). 
		NOTE: The repression index is the measure used to identify putative miRNA targets. Different stringency parameters can be used, based on individual preferences. On average we consider likely hits below repression index of 0.8 and statistically significant by t test (p-value &#60;0.05). As shown in Figure 3 potential targets based on these criteria will be highlighted in red.</li>
	</ol>
	</li>
</ol>

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Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNASU+plasmid+and+PSI:Biology-Materials+repositories:+resources+to+accelerate+biological+research.">DNASU plasmid and PSI:Biology-Materials repositories: resources to accelerate biological research.</a> Nucleic Acids Res. , (2013).</li><li>Baek, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+impact+of+microRNAs+on+protein+output.">The impact of microRNAs on protein output.</a> Nature. 455 (7209), 64-71 (2008).</li><li>Ebert, M. S., Sharp, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Roles+for+MicroRNAs+in+Conferring+Robustness+to+Biological+Processes.">Roles for MicroRNAs in Conferring Robustness to Biological Processes.</a> Cell. 149 (3), 515-524 (2012).</li><li>Pelaez, N., Carthew, R. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biological+robustness+and+the+role+of+microRNAs:+a+network+perspective.">Biological robustness and the role of microRNAs: a network perspective.</a> Current Topics in Developmental Biology. 99, 237-255 (2012).</li></ol>

This work is supported by funds from the College of Liberal Arts and Science and the Biodesign Institute at Arizona State University and NIH Exploratory/Developmental Research Grant 1R21CA179144-01A1.

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

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

Research

JoVE Journal

Biology

10.0K Views.  Arizona State University. Luminescent identification of functional elements in 3’ untranslated regions (3’UTRs) (3’LIFE) is a technique to identify functional regulation in 3’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.

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

High Throughput MicroRNA Profiling: Optimized Multiplex qRT-PCR at Nanoliter Scale on the Fluidigm Dynamic ArrayTM IFCs

The broad involvement of miRNAs in critical processes underlying development, tissue homoeostasis and disease has led to a surging interest among the research and pharmaceutical communities. To study miRNAs, it is essential that the quantification of microRNA levels is accurate and robust. By comparing wild-type to small RNA deficient mouse embryonic stem cells (mESC), we revealed a lack of accuracy and robustness in previous published multiplex qRT-PCR techniques. Here, we describe an optimized method, including purifying away excessive primers from previous multiplex steps before singleplex real time detection, which dramatically increases the accuracy and robustness of the technique. Furthermore, we explain how performing the technique on a microfluidic chip at nanoliter volumes significantly reduces reagent costs and permits time effective high throughput miRNA expression profiling.

Here we describe an optimized multiplex reverse transcriptase quantitative PCR (qRT-PCR) protocol in combination with a microfluidic platform as a cost and time effective high-throughput screening tool for microRNA (miRNA) expression levels, especially when working with limited amounts of sample.

The broad involvement of miRNAs in critical processes underlying development, tissue homoeostasis and disease has led to a surging interest among the ...

Bioengineering

Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform

The gene expression platform assay allows for robust and highly reproducible quantification of the expression of up to 800 transcripts (mRNA or miRNAs) in a single reaction. The miRNA assay counts transcripts by directly imaging and digitally counting miRNA molecules that are labeled with color-coded fluorescent barcoded probe sets (a reporter probe and a capture probe). Barcodes are hybridized directly to mature miRNAs that have been elongated by ligating a unique oligonucleotide tag (miRtag) to the 3&#39; end. Reverse transcription and amplification of the transcripts are not required. Reporter probes contain a sequence of six color positions populated using a combination of four fluorescent colors. The four colors over six positions are used to construct a gene-specific color barcode sequence. Post-hybridization processing is automated on a robotic prep station. After hybridization, the excess probes are washed away, and the tripartite structures (capture probe-miRNA-reporter probe) are fixed to a streptavidin-coated slide via the biotin-labeled capture probe. Imaging and barcode counting is done using a digital analyzer. The immobilized barcoded miRNAs are visualized and imaged using a microscope and camera, and the unique barcodes are decoded and counted. Data quality control (QC), normalization, and analysis are facilitated by a custom-designed data processing and analysis software that accompanies the assay software. The assay demonstrates high linearity over a broad range of expression, as well as high sensitivity. Sample and assay preparation does not involve enzymatic reactions, reverse transcription, or amplification; has few steps; and is largely automated, reducing investigator effects and resulting in high consistency and technical reproducibility. Here, we describe the application of this technology to identifying circulating miRNA perturbations in irritable bowel syndrome.

We describe the use of a multiplexed high-throughput gene expression platform that quantitates gene expression by barcoding and counting molecules in biological substrates without the need for amplification. We used the platform to quantitate microRNA (miRNA) expression in whole blood in subjects with and without irritable bowel syndrome.

The gene expression platform assay allows for robust and highly reproducible quantification of the expression of up to 800 transcripts (mRNA or miRNAs) in ...

Genetics

Differentiation of a Human Neural Stem Cell Line on Three Dimensional Cultures, Analysis of MicroRNA and Putative Target Genes

Neural stem cells (NSCs) are capable of self-renewal and differentiation into neurons, astrocytes and oligodendrocytes under specific local microenvironments. In here, we present a set of methods used for three dimensional (3D) differentiation and miRNA analysis of a clonal human neural stem cell (hNSC) line, currently in clinical trials for stroke disability (NCT01151124 and NCT02117635, Clinicaltrials.gov). HNSCs were derived from an ethical approved first trimester human fetal cortex and conditionally immortalized using retroviral integration of a single copy of the c-mycERTAMconstruct. We describe how to measure axon process outgrowth of hNSCs differentiated on 3D scaffolds and how to quantify associated changes in miRNA expression using PCR array. Furthermore we exemplify computational analysis with the aim of selecting miRNA putative targets. SOX5 and NR4A3 were identified as suitable miRNA putative target of selected significantly down-regulated miRNAs in differentiated hNSC. MiRNA target validation was performed on SOX5 and NR4A3 3&#8217;UTRs by dual reporter plasmid transfection and dual luciferase assay.

With the intent of characterizing changes in miRNAs on differentiated human neural stem cells (hNSCs) we describe hNSC differentiation on a three dimensional system,the evaluation of changes in microRNA expression by miRNA PCR array, and computational analysis for miRNA target prediction and its validation by dual luciferase assay.

Neural stem cells (NSCs) are capable of self-renewal and differentiation into neurons, astrocytes and oligodendrocytes under specific local ...

Developmental Biology

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally regulate cellular gene expression. MiRNAs bind to the 3&#39; untranslated region (UTR) of target mRNA to inhibit protein translation or in some instances cause mRNA degradation. The binding of the miRNA to the 3&#39; UTR of the target mRNA is mediated by a 2&#8211;8 nucleotide seed sequence at the 5&#39; end of miRNA. While the role of miRNAs as cellular regulatory molecules is well established, identification of the target mRNAs with functional relevance remains a challenge. Bioinformatic tools have been employed to predict sequences within the 3&#39; UTR of mRNAs as potential targets for miRNA binding. These tools have also been utilized to determine the evolutionary conservation of such sequences among related species in an attempt to predict functional role. However, these computational methods often generate false positive results and are limited to predicting canonical interaction between miRNA and mRNA. Therefore, experimental procedures that measure direct binding of miRNA to its mRNA target are necessary to establish functional interaction. In this report, we describe a sensitive method for validating direct interaction between the cellular miRNA miR-125b and the 3&#39; UTR of PARP-1 mRNA. We elaborate a protocol in which synthetic biotinylated-miRNA mimics were transfected into mammalian cells and the miRNA-mRNA complex in the cellular lysate was pulled down with streptavidin-coated magnetic beads. Finally, the target mRNA in the pulled-down nucleic acid complex was quantified using a qPCR-based strategy.

This report describes a fast and reliable method for validating mRNA targets of cellular miRNAs. The method uses synthetic biotinylated Locked Nucleic Acid (LNA)-based miRNA mimics to capture target mRNA. Subsequently, streptavidin-coated magnetic beads are employed to pulldown the target mRNA for quantification by qPCR polymerase chain reaction.

MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally regulate cellular gene expression. MiRNAs bind to the 3&#39; ...

Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer

There is increasing interest in liquid biopsy for cancer diagnosis, prognosis and therapeutic monitoring, creating the need for reliable and useful biomarkers for clinical practice. Here, we present a protocol to extract, reverse transcribe and evaluate the expression levels of circulating miRNAs from plasma samples of patients with colorectal cancer (CRC). microRNAs (miRNAs) are a class of non-coding RNAs of 18-25 nucleotides in length that regulate the expression of target genes at the translational level and play an important role, including that of pro- and anti-angiogenic function, in the physiopathology of various organs. miRNAs are stable in biological fluids such as serum and plasma, which renders them ideal circulating biomarkers for cancer diagnosis, prognosis and treatment decision-making and monitoring. Circulating miRNA extraction was performed using a rapid and effective method that involves both organic and column-based methodologies. For miRNA retrotranscription, we used a multi-step procedure that considers polyadenylation at 3&#39; and the ligation of an adapter at 5&#39; of the mature miRNAs, followed by random miRNA pre-amplification. We selected a 24-miRNA custom panel to be tested by quantitative real-time polymerase chain reaction (qRT-PCR) and spotted the miRNA probes on array custom plates. We performed qRT-PCR plate runs on a real-time PCR System. Housekeeping miRNAs for normalization were selected using GeNorm software (v. 3.2). Data were analyzed using Expression suite software (v 1.1) and statistical analyses were performed. The method proved to be reliable and technically robust and could be useful to evaluate biomarker levels in liquid samples such as plasma and/or serum.

We present a protocol to evaluate the expression levels of circulating microRNA (miRNAs) in plasma samples from cancer patients. In particular, we used a commercially available kit for circulating miRNA extraction and reverse transcription. Finally, we analyzed a panel of 24 selected miRNAs using real-time pre-spotted probe custom plates.

There is increasing interest in liquid biopsy for cancer diagnosis, prognosis and therapeutic monitoring, creating the need for reliable and useful ...

Cancer Research

An In Vitro Protocol for Evaluating MicroRNA Levels, Functions, and Associated Target Genes in Tumor Cells

MicroRNAs (miRNAs) are small regulatory RNAs which are recognized to modulate numerous intracellular signaling pathways in several diseases including cancers. These small regulatory RNAs mainly interact with the 3&#8217; untranslated regions (3&#8217; UTR) of their target messenger RNAs (mRNAs) ultimately resulting in the inhibition of decoding processes of mRNAs and the augmentation of target mRNA degradations. Based on the expression levels and intracellular functions, miRNAs are able to serve as regulatory factors of oncogenic and tumor-suppressive mRNAs. Identification of bona fide target genes of a miRNA among hundreds or even thousands of computationally predicted targets is a crucial step to discern the roles and basic molecular mechanisms of a miRNA of interest. Various miRNA target prediction programs are available to search possible miRNA-mRNA interactions. However, the most challenging question is how to validate direct target genes of a miRNA of interest. This protocol describes a reproducible strategy of key methods on how to identify miRNA targets related to the function of a miRNA. This protocol presents a practical guide on step-by-step procedures to uncover miRNA levels, functions, and related target mRNAs using the probe-based real-time polymerase chain reaction (PCR), sulforhodamine B (SRB) assay following a miRNA mimic transfection, dose-response curve generation, and luciferase assay along with the cloning of 3&#8217; UTR of a gene, which is necessary for proper understanding of the roles of individual miRNAs.

This protocol uses a probe-based real-time polymerase chain reaction (PCR), a sulforhodamine B (SRB) assay, 3&#8217; untranslated regions (3&#8217; UTR) cloning, and a luciferase assay to verify the target genes of a miRNA of interest and to understand the functions of miRNAs.

MicroRNAs (miRNAs) are small regulatory RNAs which are recognized to modulate numerous intracellular signaling pathways in several diseases including ...

RNA Blot Analysis for the Detection and Quantification of Plant MicroRNAs

MicroRNAs (miRNAs) are a class of endogenously expressed non-coding, ~21 nt small RNAs involved in the regulation of gene expression in both plants and animals. Most miRNAs act as negative switches of gene expression targeting key genes. In plants, primary miRNAs (pri-miRNAs) transcripts are generated by RNA polymerase II, and they form varying lengths of stable stem-loop structures called pre-miRNAs. An endonuclease, Dicer-like1, processes the pre-miRNAs into miRNA-miRNA* duplexes. One of the strands from miRNA-miRNA* duplex is selected and loaded onto Argonaute 1 protein or its homologs to mediate the cleavage of target mRNAs. Although miRNAs are key signaling molecules, their detection is often carried out by less than optimal PCR-based methods instead of a sensitive northern blot analysis. We describe a simple, reliable, and extremely sensitive northern method that is ideal for the quantification of miRNA levels with very high sensitivity, literally from any plant tissue. Additionally, this method can be used to confirm the size, stability and the abundance of miRNAs and their precursors.

This method demonstrates use of the northern hybridization technique to detect miRNAs from total RNA extract.

MicroRNAs (miRNAs) are a class of endogenously expressed non-coding, ~21 nt small RNAs involved in the regulation of gene expression in both plants and ...

Biochemistry

Identifying Targets of Human microRNAs with the LightSwitch Luciferase Assay System using 3'UTR-reporter Constructs and a microRNA Mimic in Adherent Cells

MicroRNAs (miRNAs) are important regulators of gene expression and play a role in many biological processes. More than 700 human miRNAs have been identified so far with each having up to hundreds of unique target mRNAs. Computational tools, expression and proteomics assays, and chromatin-immunoprecipitation-based techniques provide important clues for identifying mRNAs that are direct targets of a particular miRNA. In addition, 3'UTR-reporter assays have become an important component of thorough miRNA target studies because they provide functional evidence for and quantitate the effects of specific miRNA-3'UTR interactions in a cell-based system. To enable more researchers to leverage 3'UTR-reporter assays and to support the scale-up of such assays to high-throughput levels, we have created a genome-wide collection of human 3'UTR luciferase reporters in the highly-optimized LightSwitch Luciferase Assay System. The system also includes synthetic miRNA target reporter constructs for use as positive controls, various endogenous 3'UTR reporter constructs, and a series of standardized experimental protocols.
Here we describe a method for co-transfection of individual 3'UTR-reporter constructs along with a miRNA mimic that is efficient, reproducible, and amenable to high-throughput analysis.

MicroRNAs (miRNAs) are important regulators of gene expression and have been shown to play a role in numerous biological processes. To better understand miRNA-UTR interactions, we have created a genome-wide collection of 3 UTR luciferase reporters paired with a novel luciferase gene and assay reagent, the LightSwitch system.

MicroRNAs (miRNAs) are important regulators of gene expression and play a role in many biological processes.  More than 700 human miRNAs have been ...

Highly Efficient Ligation of Small RNA Molecules for MicroRNA Quantitation by High-Throughput Sequencing

MiRNA cloning and high-throughput sequencing, termed miR-Seq, stands alone as a transcriptome-wide approach to quantify miRNAs with single nucleotide resolution. This technique captures miRNAs by attaching 3&#8217; and 5&#8217; oligonucleotide adapters to miRNA molecules and allows de novo miRNA discovery. Coupling with powerful next-generation sequencing platforms, miR-Seq has been instrumental in the study of miRNA biology. However, significant biases introduced by oligonucleotide ligation steps have prevented miR-Seq from being employed as an accurate quantitation tool. Previous studies demonstrate that biases in current miR-Seq methods often lead to inaccurate miRNA quantification with errors up to 1,000-fold for some miRNAs1,2. To resolve these biases imparted by RNA ligation, we have developed a small RNA ligation method that results in ligation efficiencies of over 95% for both 3&#8217; and 5&#8242; ligation steps. Benchmarking this improved library construction method using equimolar or differentially mixed synthetic miRNAs, consistently yields reads numbers with less than two-fold deviation from the expected value. Furthermore, this high-efficiency miR-Seq method permits accurate genome-wide miRNA profiling from in vivo total RNA samples2.

MicroRNAs (miRNAs) are a widely conserved class of regulatory molecules. Here we describe a miRNA cloning method that relies upon two potent ligation steps followed by high-throughput sequencing. Our method permits accurate genome-wide quantitation of miRNAs.

MiRNA cloning and high-throughput sequencing, termed miR-Seq, stands alone as a transcriptome-wide approach to quantify miRNAs with single nucleotide ...

Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs

Probe-based quantitative PCR (qPCR) is a favoured method for measuring transcript abundance, since it is one of the most sensitive detection methods that provides an accurate and reproducible analysis. Probe-based chemistry offers the least background fluorescence as compared to other (dye-based) chemistries. Presently, there are several platforms available that use probe-based chemistry to quantitate transcript abundance. qPCR in a 96 well plate is the most routinely used method, however only a maximum of 96 samples or miRNAs can be tested in a single run. This is time-consuming and tedious if a large number of samples/miRNAs are to be analyzed. High-throughput probe-based platforms such as microfluidics (e.g. TaqMan Array Card) and nanofluidics arrays (e.g. OpenArray) offer ease to reproducibly and efficiently detect the abundance of multiple microRNAs in a large number of samples in a short time. Here, we demonstrate the experimental setup and protocol for miRNA quantitation from serum or plasma-EDTA samples, using probe-based chemistry and three different platforms (96 well plate, microfluidics and nanofluidics arrays) offering increasing levels of throughput.

Circulating microRNAs have recently emerged as promising and novel biomarkers for various cancers and other diseases. The goal of this article is to discuss three different probe-based real-time PCR platforms and methods that are available to quantify and determine the abundance of circulating microRNAs.

Probe-based quantitative PCR (qPCR) is a favoured method for measuring transcript abundance, since it is one of the most sensitive detection methods that ...