The project described was supported by Award Number R01MH079751 (PI: F. Peruzzi) from the National Institute of Mental Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institute of Health.

The following protocol describes the standard procedure to isolate RNA from CSF and profile microRNAs using ready PCR plates. Note that the organic phase extraction is optional, and that a carrier RNA is added to the sample during extraction ensuring maximal recovery of RNA. Consequently, there is no need to quantify the RNA.
Overall, an average of 6-8 plates can be run in one day if the cDNA is synthesized the day before (about 2 hr). Analysis of data is performed when all samples have been profiled and loaded into the software. Depending on the number of samples/groups or their combination for comparison, data analysis may require from one to several hours.
1. RNA Extraction
The RNA extraction was performed from CSF samples, stored frozen at -80 &#176;C in aliquots until analysis. For this procedure the mirVana Paris isolation kit was used, following the manufacturer&#39;s instructions for the total RNA isolation. Please note that, although enrichment for small RNA species is possible with this kit, this step is not done and the RNA extraction procedure is ended after the total RNA isolation step. In addition, although the mirVana Paris isolation kit (like other commercially available RNA isolation kits) does not require organic extraction, a protocol for this procedure can be found below. 
	The protocol for RNA extraction consists of two steps: 
	1.1. Organic Extraction (not required if using mirVana Paris RNA extraction kit) 
	1.2.2. Total RNA isolation
1.1. Organic extraction
1.1.1. Prepare reagents
<ol>
	<li>Add 375 &mu;l of 2-mercaptoethanol to 2x Denaturing solution, and store it at 4 &#176;C.</li>
</ol>
1.1.2. Prepare the CSF
<ol>
	<li>Thaw every aliquot of CSF on ice before the RNA extraction. Add 1 &#181;g of MS2 RNA carrier to 0.5 ml of thawed CSF and gently mix. Note that if the organic extraction is omitted, the MS2 carrier will be added to the sample prior RNA isolation described in 1.2.2.1 below.</li>
	<li>Mix 0.5 ml of 2x Denaturing Solution at room temperature to the CSF.</li>
	<li>Add 1 ml of acid-phenol:chloroform to the CSF plus the 2x Denaturing Solution: be sure to withdrawn the bottom phase containing acid-phenol:chloroform, not the aqueous buffer that lies on top of the mixture. Additionally, note that acid-phenol:chloroform contains phenol, which is a poison and an irritant, use gloves and other personal protection equipment when working with this reagent.</li>
	<li>Vortex for 30-60 sec to mix. For convenience, the 2 ml of sample/denaturing solution/acid-phenol:chloroform mix are divided into two 1.5 ml Eppendorf tubes.</li>
	<li>Centrifuge for 5 min at maximum speed (10,000 x g) at room temperature.</li>
	<li>Carefully remove the aqueous (upper) phase without disturbing the lower phase or the interphase and transfer it to a fresh tube. Note the volume recovered.</li>
</ol>
1.2. RNA isolation
It is recommended to have a dedicated bench, set of pipettes, and racks for handling RNA samples. The working area and tools are decontaminated by using RNase Zap spray and wipes prior each experiment.
1.2.1. Prepare reagents:
<ol>
	<li>Add 21 ml of 100% ethanol to miRNA Wash Solution 1 and 40 ml of 100 % ethanol to Wash Solution 2/3. Please note that miRNA Wash Solution 1 contains guanidium thiocyanate that is a potentially hazardous substance.</li>
</ol>
1.2.2. Total RNA isolation
<ol>
	<li>Add 1.25 volumes of room temperature 100% ethanol to the aqueous phase from the organic extraction and mix thoroughly.</li>
	<li>Place a Filter Cartridge into one of the Collection Tubes.</li>
	<li>Pipette not more than 700 &mu;l of the lysate/ethanol mixture onto the Filter Cartridge.</li>
	<li>Centrifuge for 30 sec at maximum speed. Apply the mixture exceeding 700 &mu;l in successive applications to the same filter. Discard the flow-through after every centrifugation and save the Collection Tube for the washing steps.</li>
	<li>Apply 700 &mu;l miRNA Wash Solution 1 to the Filter Cartridge and centrifuge for 15 sec at maximum speed. Discard the flow through from the Collection Tube and replace the Filter Cartridge into the same Collection Tube.</li>
	<li>Apply 500 &mu;l Wash Solution 2/3 and centrifuge for 15 sec at maximum speed. Discard the flow through from the Collection Tube and replace the Filter Cartridge into the same Collection Tube. Apply a second 500 &mu;l Wash Solution 2/3 and centrifuge for 15 sec at maximum speed. Discard the flow through from the Collection Tube and replace the Filter Cartridge into the same Collection Tube. Spin the assembly for 1 min at maximum speed to remove residual fluid from the filter.</li>
	<li>Transfer the Filter Cartridge into a fresh Collection Tube. Apply 100 &mu;l of preheated (to 95 &#176;C) nuclease-free water to the center of the filter, and close the cap. Centrifuge for 30 sec at maximum speed to recover the RNA.</li>
	<li>Collect the eluate containing RNA and store it at -80 &#176;C for subsequent applications.</li>
	<li>Quantify 1 &#181;l of RNA using the NanoDrop 2000c spectrophotometer. Note that RNA quantification can be skipped if an RNA carrier is added to the sample during RNA extraction. In that case 8 &#181;l of RNA are subjected to cDNA synthesis as detailed below.</li>
</ol>
2. miRNA Profile: qRT-PCR Protocol
The protocol for miRNA profiling consists of two steps:
<ol>
	<li>First-strand cDNA synthesis</li>
	<li>Real-time PCR amplification</li>
</ol>
2.1. First-strand cDNA synthesis
2.1.1. Dilute template RNA
<ol>
	<li>Adjust each of the template RNA samples to a concentration of 5 ng/&#181;l using nuclease free water. If the RNA has not been quantified (see step 1.2.2.9), then 8 &#181;l of RNA are utilized for cDNA synthesis</li>
</ol>
2.1.2. Prepare reagents
<ol>
	<li>Gently thaw the 5x Reaction buffer and nuclease free water, and immediately place on ice.</li>
	<li>Mix by vortexing. Resuspend the RNA spike-in by adding 40 &#181;l nuclease free water to the tube and mix by vortexing; leave it on ice for 15-20 min. Immediately before use, remove the enzyme mix from the freezer, mix by flicking the tubes and place on ice. Spin down all reagents.</li>
</ol>
2.1.3. Reverse transcription reaction setup
<ol>
	<li>Prepare the required amount of RT working solution in a 1.5 ml Eppendorf tube, or equivalent (in the proportions indicated in Table 1, except for the RNA template), mix by vortexing (1-2 sec at max speed), briefly spin down (we use a mini Eppendorf centrifuge with fixed speed, 10 sec) and place it on ice. Note that the UniSp6 RNA spike-in is added to the sample prior the RT reaction (see Table 1).</li>
	<li>Dispense RT working solution into nuclease free PCR tubes.</li>
	<li>Dispense template RNA in each tube. 
		Note: remember to calculate 10% excess volume/each reagent for pipetting and/or robotic dead volume.
		<table border="1" cellpadding="0" cellspacing="0">
			<tbody>
				<tr>
					<td>Reagent</td>
					<td>Panel I Volume (&#181;l)</td>
					<td>Panel I + II Volume (&#181;l)</td>
				</tr>
				<tr>
					<td>5x reaction buffer</td>
					<td>4.4</td>
					<td>8.8</td>
				</tr>
				<tr>
					<td>Nuclease free water</td>
					<td>9.9</td>
					<td>19.8</td>
				</tr>
				<tr>
					<td>Enzyme mix</td>
					<td>2.2</td>
					<td>4.4</td>
				</tr>
				<tr>
					<td>UniSp6 RNA Spike-in template</td>
					<td>1.1</td>
					<td>2.2</td>
				</tr>
				<tr>
					<td>Template total RNA (5 ng/&#181;l)</td>
					<td>4.4</td>
					<td>8.8</td>
				</tr>
				<tr>
					<td>Total Volume</td>
					<td>22</td>
					<td>44</td>
				</tr>
			</tbody>
		</table>
		 
		Table 1. Reverse transcription reaction setup.</li>
</ol>
2.1.4. Mix and spin reagents
<ol>
	<li>Mix the reaction by gentle (1-2 sec) vortexing to ensure that all reagents are thoroughly mixed. After mixing, spin down (mini Eppendorf centrifuge with fixed speed, 10 sec).</li>
</ol>
2.1.5. Incubate and heat inactivate
<ol>
	<li>Program a PCR machine as follow:</li>
	<li>Incubate for 60 min at 42 &#176;C</li>
	<li>Heat-inactivate the reverse transcriptase for 5 min at 95 &#176;C</li>
	<li>Immediately cool to 4 &#176;C</li>
	<li>Store at 4 &#176;C or freeze 
		Note: the protocol can be interrupted at this stage. The undiluted cDNA may be kept at -20 &#176;C for up to 5 weeks (optional store at 4 &#176;C for up to 4 days).</li>
</ol>
2.2. Real-time PCR amplification
2.2.1. Prepare reagents for Real-time PCR
<ol>
	<li>Place cDNA (from step 2.1.5) on ice.</li>
	<li>Thaw nuclease free water and PCR Master mix on ice. Protect the PCR Master mix vials from light by covering them with aluminum foil. Immediately before use, mix the PCR Master mix by vortexing 1-2 sec in a mini centrifuge and spin down at 1,500 x g for 1 min.</li>
</ol>
2.2.2. Combine SYBR Green master mix, water, and cDNA and add to PCR plates
The following procedure is recommended to avoid low concentrations of cDNA from adhering to tube surface:
<ol>
	<li>Before removing the plate seal, briefly spin down the plate(s) in a refrigerated centrifuge at 1,500 x g for 1 min.</li>
	<li>In a 15 ml conical tube, combine 2x PCR Master mix and water. Panel I: 2,000 &#181;l 2x master mix and 1,980 &#181;l water; Panel I+II: 4,000 &#181;l 2x master mix and 3,960 &#181;l water.</li>
	<li>Add 20 &#181;l cDNA (panel I) or 40 &#181;l cDNA (panel I+II) and mix.</li>
	<li>Mix gently by vortexing 1-2 sec and spin down in a refrigerated centrifuge at 1,500 x g for 1 min.</li>
	<li>Place the PCR Master mix/cDNA mix in a multichannel pipette reservoir. You may have to identify a reservoir that has the length of the multichannel pipette. This keeps the level of volume high enough allowing for equal volume aliquots throughout the multichannel. This is critical towards the last few aliquots.</li>
	<li>Dispense 10 &#181;l PCR Master mix/cDNA mix to each well of the 384-well plate using a 16-channel pipette.</li>
	<li>Seal the plate with optical sealing.</li>
	<li>Spin plate briefly in a refrigerated centrifuge (1,500 x g for 1 min), to mix the solutions and remove air bubbles. 
		 
		Note: the experiment can be paused at this point. Store the reactions protected from light at 4 &#176;C for up to 24 hr.</li>
</ol>
2.2.3. Real-Time PCR
Perform real-time PCR amplification and melting curve analysis following the parameters detailed in Table 2.
<table border="1" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>Process Step</td>
			<td>Settings, Roche LC480</td>
		</tr>
		<tr>
			<td>Polymerase Activation/Denaturation</td>
			<td>95 &#176;C, 10 min</td>
		</tr>
		<tr>
			<td>Amplification</td>
			<td>45 Amplification cycles at 
				95 &#176;C, 10 sec 
				60 &#176;C, 1 min 
				Ramp-rate 
				1.6 &#176;C/sec 
				Optical read</td>
		</tr>
		<tr>
			<td>Melting curve analysis</td>
			<td>Yes</td>
		</tr>
	</tbody>
</table>
Table 2. Real-time PCR cycle conditions using the Roche LightCycler 480.
2.3. Real-time PCR data analysis
Real time PCR data analysis is done with the Exiqon GenEx Professional 5.0, following the recommended instructions. The GenEx step-by-step manual can be downloaded at <a href="http://www.exiqon.com/ls/Documents/Scientific/Exiqon-data-analysis-guide.pdf">http://www.exiqon.com/ls/Documents/Scientific/Exiqon-data-analysis-guide.pdf</a> 
	Data analysis consists of three steps:
<ol>
	<li>Import of data</li>
	<li>Preprocessing of data</li>
	<li>Statistical analysis</li>
</ol>
2.3.1. Import of data
<ol>
	<li>In the Roche LightCycler 480 select the 2nd derivative analysis method and calculate the Cq values. Data are exported as a table and saved as text files.</li>
	<li>To import the data, open GenEx and click on the Exiqon import wizard button and click "Start". Follow the instructions to select format, instrument and plate layout file(s). Note that plate layout files (excel files) are downloaded from the Exiqon web site (<a href="http://www.exiqon.com/plate-layout-files">http://www.exiqon.com/plate-layout-files</a>).</li>
	<li>Import Panels I and II and click "Next".</li>
	<li>The table generated after file import contains predefined columns. Samples names can be edited and classification columns can be added or removed at this step. Click "Next" when you are done.</li>
	<li>Save data and load to Data Editor.</li>
</ol>
2.3.2. Preprocessing of data
<ol>
	<li>As recommended by Exiqon and GenEx, when comparing multiple plates the first thing to do is to calibrate the data between the plates by choosing inter-plate calibration from the preprocessing menu.</li>
	<li>It is recommended to run miRNA arrays in triplicate runs. If a miRNA is not present in at least two out of three replicas it will be set as nonexpressed.</li>
	<li>In the next step in the preprocessing, set a cut off. Defining a cut off value indicates that data with a threshold cycle (Ct) higher than this value are discarded. In the present experiments using cerebrospinal fluid specimen, the cut off was set at 39. Therefore, all samples with a Ct higher than 39 in the three replicas will be discarded. If a miRNA has a Ct &#62; 39 for one probe (one replica out of three), that reading will be replaced with the average of the Ct for the other two probes, provided they are both below 39.</li>
	<li>Define reference genes. GenEx Professional has the option to utilize geNorm and/or NormFinder to identify reference genes. Select a list of miRNAs that have similar Cq values across all sample and run geNorm and/or NormFinder. According to this analysis, in the example provided here, miR-622 and miR-1266 had the most uniform values across the samples and were chosen as reference genes (Figure 1).</li>
	<li>Next, data are normalized using the reference genes and the values obtained correspond to the &#916;Ct</li>
	<li>If cDNA synthesis reactions were performed in triplicates, at this point the values should be averaged.</li>
	<li>Validate sheet to remove empty and almost empty columns. In the preprocessing window select "Validate sheet" and than apply on the Remove empty columns line. In the line below, chose the desired percentage of valid data and click apply. For instance, select 100% if you wish to compare only miRNAs common to all samples.</li>
	<li>Handle missing data. 
		Select &#8220;Missing data&#8221; from the Preprocessing menu and chose one of the options to handle missing data. This step is required. Note that GenEx will give you error if you try to load files that contain unhandled missing data.</li>
	<li>Determine relative quantification between groups of samples (i.e. experiment versus control). Relative quantification among groups is calculated using the &#916;&#916; Ct method. In GenEx, click the preprocessing tab and select relative quantification. In the window select the reference group and hit apply. Note that for graphical representations and/or for further statistical analyses, expression data should be converted to a logarithmic scale. In the preprocessing menu, select Log2.</li>
</ol>
2.3.3. Statistical Analysis
GenEx software allows a wide range of statistical analyses, including T-test and ANOVA.
<ol>
	<li>Load the final mdf file into GenEx and open data manager. It is critical to select the correct samples or groups of samples for which statistical analysis is performed.</li>
	<li>Select "Statistics" and chose the icon corresponding to the desired test.</li>
	<li>Click "Run" in the control panel window. Save results as excel or mdf files.</li>
</ol>
2.3.4. Expression profiling
MicroRNAs and samples can be classified, clustered, and visualized on heat-maps and dendrograms, as follows
<ol>
	<li>Load the final mdf file into GenEx and open data manager. Use this window to select and create groups of samples or miRNAs. Click "Apply" when you are done.</li>
	<li>In the upper left corner select cluster and click on the heatmap icon</li>
	<li>In the control panel window click "Run". The heatmap can be saved in various formats such as tiff or bmp; it can also be copied and modified as needed.</li>
</ol>

<ol>
	<li>Pacifici, M., 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=Cerebrospinal+fluid+miRNA+profile+in+HIV-encephalitis.">Cerebrospinal fluid miRNA profile in HIV-encephalitis.</a> J. Cell. Physiol. 10, (2012).</li><li>Krol, J., Loedige, I., Filipowicz, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+widespread+regulation+of+microRNA+biogenesis,+function+and+decay.">The widespread regulation of microRNA biogenesis, function and decay.</a> Nat. Rev. Genet.. 11, 597-610 (2010).</li><li>Calin, G. A., Croce, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNA+signatures+in+human+cancers.">MicroRNA signatures in human cancers.</a> Nat. Rev. Cancer. 6, 857-866 (2006).</li><li>Chen, X., 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=Characterization+of+microRNAs+in+serum:+a+novel+class+of+biomarkers+for+diagnosis+of+cancer+and+other+diseases.">Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases.</a> Cell Res. 18, 997-1006 (2008).</li><li>De Smaele, E., Ferretti, E., Gulino, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs+as+biomarkers+for+CNS+cancer+and+other+disorders.">MicroRNAs as biomarkers for CNS cancer and other disorders.</a> Brain Res. 1338, 100-111 (2010).</li><li>Heneghan, H. M., Miller, N., Kerin, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MiRNAs+as+biomarkers+and+therapeutic+targets+in+cancer.">MiRNAs as biomarkers and therapeutic targets in cancer.</a> Curr. Opin. Pharmacol. 10, 543-550 (2010).</li><li>Kosaka, N., Iguchi, H., Ochiya, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Circulating+microRNA+in+body+fluid:+a+new+potential+biomarker+for+cancer+diagnosis+and+prognosis.">Circulating microRNA in body fluid: a new potential biomarker for cancer diagnosis and prognosis.</a> Cancer Sci. 101, 2087-2092 (2010).</li><li>Lu, J., 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=MicroRNA+expression+profiles+classify+human+cancers.">MicroRNA expression profiles classify human cancers.</a> Nature. 435, 834-838 (2005).</li><li>Shah, A. A., Leidinger, P., Blin, N., Meese, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=miRNA:+small+molecules+as+potential+novel+biomarkers+in+cancer.">miRNA: small molecules as potential novel biomarkers in cancer.</a> Curr. Med. Chem. 17, 4427-4432 (2010).</li><li>Blondal, T., 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=Assessing+sample+and+miRNA+profile+quality+in+serum+and+plasma+or+other+biofluids.">Assessing sample and miRNA profile quality in serum and plasma or other biofluids.</a> Methods. 59, 1-6 (2013).</li><li>Jensen, S. G., 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=Evaluation+of+two+commercial+global+miRNA+expression+profiling+platforms+for+detection+of+less+abundant+miRNAs.">Evaluation of two commercial global miRNA expression profiling platforms for detection of less abundant miRNAs.</a> BMC Genomics. 12, 435 (2011).</li></ol>

The authors have nothing to disclose.

MicroRNAs are small noncoding RNAs that regulate gene expression by inhibiting translation and/or promoting mRNA degradation2. Due to their high stability in cell-free conditions, microRNAs have been detected in many body fluids. Furthermore, distinct expression profile of microRNAs has been correlated with stage and/or progression in a variety of human cancers3-9.
There are several tools available to profile microRNAs, including classical chip arrays or the latest deep s...

MicroRNAs belong to the family of small (21-23 nt in length) noncoding RNAs that regulate gene expression post-transcriptionally. microRNAs can be secreted in the extracellular space where they appear to be relatively stable. While determining changes in miRNA expression can be an important step toward identification of biomarkers, performing miRNA profiles and handling a large amount of data may be intimidating.
Here, we describe a protocol to determine changes in miRNA expression in the cerebrospinal fluid (applicable to other body fluids) by a sensitive real time PCR. We also describe the use of software for data analysis, including statistical analysis and graphical representation of results. The entire procedure is relatively easy and straightforward and, depending on the number of samples to be profiled and the number of real time PCR machines available, also relatively quick. The experimental part requires accuracy in handling RNA and pipetting into 384-well plates, while the data analysis section using GenEx requires some basic knowledge in informatics and statistics.

<table><tbody><tr><td colspan="4">&lt;p&gt;&lt;strong&gt;Table 3. List of equipment.&lt;/strong&gt;&lt;/p&gt;</td></tr><tr><td> &lt;p&gt;Finnpipette Novus Multichannel Pipetter&lt;/p&gt; </td><td>Thermo Scientific</td><td>&lt;p&gt;HH05279&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;Finntip Pipette Tips&lt;/p&gt; </td><td>Thermo Scientific</td><td>&lt;p&gt;9400613&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;Thermal Cycler C1000&lt;/p&gt; </td><td>Biorad</td><td></td><td></td></tr><tr><td> &lt;p&gt;0.2 ml Low Profile, Clear PCR tubes&lt;/p&gt; </td><td>Biorad</td><td>&lt;p&gt;TLS0801&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;Flat Cap Strips&lt;/p&gt; </td><td>Biorad</td><td>&lt;p&gt;TLS0803&lt;/p&gt;</td><td></td></tr><tr><td>&lt;p&gt;LightCycler 480 Real-Time PCR System&lt;/p&gt;</td><td>Roche</td><td></td><td></td></tr><tr><td>&lt;p&gt;LightCycler 480 Sealing Foil&lt;/p&gt;</td><td>Roche</td><td>&lt;p&gt;04 729 757 001&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;Refrigerated Centrifuge 5804R&lt;/p&gt; </td><td>Eppendorf</td><td></td><td></td></tr><tr><td> &lt;p&gt;Swing-bucket Rotor, 4-place&lt;/p&gt; </td><td>Eppendorf</td><td>&lt;p&gt;A-4-44&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;Bench-Top Mini Centrifuge&lt;/p&gt; </td><td>Fisher</td><td>&lt;p&gt;05-090-100&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;Bench-Top Vortex&lt;/p&gt; </td><td>Fisher</td><td></td><td></td></tr><tr><td> &lt;p&gt;1.5 ml Microcentrifuge Tubes, Sterilized&lt;/p&gt; </td><td>Fisher</td><td>&lt;p&gt;02-681-5&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;Matrix Reagent Reservoir, 25 ml&lt;/p&gt; </td><td>Thermo Scientific</td><td>&lt;p&gt;8093&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;Thermomixer Confort&lt;/p&gt; </td><td>Eppendorf</td><td></td><td></td></tr><tr><td>&lt;p&gt;Bench-Top Mini Centrifuge Sigma 1-15&lt;/p&gt;</td><td>Sigma</td><td></td><td></td></tr><tr><td> &lt;p&gt;Bench-Top Vortex&lt;/p&gt; </td><td>Velp Scientifica</td><td>&lt;p&gt;F202A0173&lt;/p&gt;</td><td></td></tr><tr><td colspan="4">&lt;p&gt;&lt;strong&gt;Table 4. List of reagents.&lt;/strong&gt;&lt;/p&gt;</td></tr><tr><td> &lt;p&gt;Universal c-DNA synthesis kit, 16-32 rxns&lt;/p&gt; </td><td>Exiqon</td><td>&lt;p&gt;203300&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;SYBR Green master mix, Universal RT, 25 ml&lt;/p&gt; </td><td>Exiqon</td><td>&lt;p&gt;203400&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;Ultrapure Distilled Water Dnase, Rnase free&lt;/p&gt; </td><td>Invitrogen</td><td>&lt;p&gt;10977-015&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;MicroRNA Ready to use PCR Human Panels (I+II) V2.R&lt;/p&gt; </td><td>Exiqon</td><td>&lt;p&gt;203608&lt;/p&gt;</td><td></td></tr><tr><td>&lt;p&gt;mirVana miRNA isolation Kit, 40 isolations&lt;/p&gt;</td><td>Ambion</td><td>&lt;p&gt;AM1556&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;MS2 RNA carrier&lt;/p&gt; </td><td>Roche Applied Science</td><td>&lt;p&gt;10165948001&lt;/p&gt;</td><td></td></tr><tr><td>&lt;p&gt;2-mercaptoethanol 98%&lt;/p&gt;</td><td>Sigma Aldrich</td><td>&lt;p&gt;M3148-25ml&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;Ethanol 100%&lt;/p&gt; </td><td>Carlo Erba</td><td>&lt;p&gt;64-17-5&lt;/p&gt;</td><td></td></tr><tr><td> &lt;p&gt;Nuclease free water&lt;/p&gt; </td><td>Qiagen</td><td>&lt;p&gt;1039480&lt;/p&gt;</td><td></td></tr><tr><td>&lt;p&gt;RNAse Zap&lt;/p&gt;</td><td>Ambion</td><td>&lt;p&gt;AM9780&lt;/p&gt;</td><td></td></tr></tbody></table>

cerebrospinal fluid microrna profiling using quantitative real time pcr

MicroRNAs (miRNAs) constitute a potent layer of gene regulation by guiding RISC to target sites located on mRNAs and, consequently, by modulating their translational repression. Changes in miRNA expression have been shown to be involved in the development of all major complex diseases. Furthermore, recent findings showed that miRNAs can be secreted to the extracellular environment and enter the bloodstream and other body fluids where they can circulate with high stability. The function of such circulating miRNAs remains largely elusive, but systematic high throughput approaches, such as miRNA profiling arrays, have lead to the identification of miRNA signatures in several pathological conditions, including neurodegenerative disorders and several types of cancers. In this context, the identification of miRNA expression profile in the cerebrospinal fluid, as reported in our recent study, makes miRNAs attractive candidates for biomarker analysis.
There are several tools available for profiling microRNAs, such as microarrays, quantitative real-time PCR (qPCR), and deep sequencing. Here, we describe a sensitive method to profile microRNAs in cerebrospinal fluids by quantitative real-time PCR. We used the Exiqon microRNA ready-to-use PCR human panels I and II V2.R, which allows detection of 742 unique human microRNAs. We performed the arrays in triplicate runs and we processed and analyzed data using the GenEx Professional 5 software.
Using this protocol, we have successfully profiled microRNAs in various types of cell lines and primary cells, CSF, plasma, and formalin-fixed paraffin-embedded tissues.

Results from this study have been previously published1. Figure 1 shows results from the analysis of candidate reference microRNAs using geNorm application. Accordingly, two microRNAs, miR-622 and miR-1266, were identified as reference genes and were used to normalize miRNA values.
For the CSF study we had three groups of samples: HIV- (n=10), HIVE (n=4), and HIV+ without Encephalitis (HIV+, n=5). The two groups, HIVE and HIV+, were compar...

Watch this Scientific Journal Video about Cerebrospinal Fluid MicroRNA Profiling Using Quantitative Real Time PCR at JoVE.com

Cerebrospinal Fluid MicroRNA Profiling Using Quantitative Real Time PCR

We describe a protocol of real time PCR to profile microRNAs in the cerebrospinal fluid (CSF). With the exception of RNA extraction protocols, the procedure can be extended to RNA extracted from other body fluids, cultured cells, or tissue specimens.

MicroRNAs (miRNAs) constitute a potent layer of gene regulation by guiding RISC to target sites located on mRNAs and, consequently, by modulating their ...

cerebrospinal-fluid-microrna-profiling-using-quantitative-real-time

Universidad de Cartagena UDEC

Research

JoVE Journal

Medicine

15.3K Views.  LSU Health Sciences Center. We describe a protocol of real time PCR to profile microRNAs in the cerebrospinal fluid (CSF). With the exception of RNA extraction protocols, the procedure can be extended to RNA extracted from other body fluids, cultured cells, or tissue specimens.

Video: Cerebrospinal Fluid MicroRNA Profiling Using Quantitative Real Time PCR

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

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

Detection of microRNA Expression in Peritoneal Membrane of Rats Using Quantitative Real-time PCR

MicroRNAs (miRNAs) are small noncoding RNAs that regulate messenger RNA expression post-transcriptionally. The miRNA expression profile has been investigated in various organs and tissues in rat. However, standard methods for the purification of miRNAs and detection of their expression in rat peritoneal membrane have not been well established. We have developed an effective and reliable method to purify and quantify miRNAs using quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) in rat peritoneal membrane. This protocol consists of four steps: 1) purification of peritoneal membrane sample; 2) purification of total RNA including miRNA from peritoneal membrane sample; 3) reverse transcription of miRNA to produce cDNA; and 4) qRT-PCR to detect miRNA expression. Using this protocol, we successfully determined that the expression of six miRNAs (miRNA-142-3p, miRNA-21-5p, miRNA-221-3p, miRNA-223-3p, miRNA-327, and miRNA-34a-5p) increased significantly in the peritoneal membrane of a rat peritoneal fibrosis model compared with those in control groups. This protocol can be used to study the profile of miRNA expression in the peritoneal membrane of rats in many pathological conditions.

Here we present a protocol for the detection of microRNA expression in rat peritoneal membrane using quantitative real-time reverse-transcription polymerase chain reaction. This method is suitable for studying the microRNA expression profile in rat peritoneal membrane in several pathological conditions.

MicroRNAs (miRNAs) are small noncoding RNAs that regulate messenger RNA expression post-transcriptionally. The miRNA expression profile has been ...

Genetics

MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR (qPCR)

MicroRNAs (miRNAs) are single-stranded, 18&#x2013;24 nucleotide long, non-coding RNA molecules. They are involved in virtually every cellular process including development1, apoptosis2, and cell cycle regulation3. MiRNAs are estimated to regulate the expression of 30% to 90% of human genes4 by binding to their target messenger RNAs (mRNAs)5. Widespread dysregulation of miRNAs has been reported in various diseases and cancer subtypes6. Due to their prevalence and unique structure, these small molecules are likely to be the next generation of biomarkers, therapeutic agents and/or targets.
Methods used to investigate miRNA expression include SYBR green I dye- based as well as Taqman-probe based qPCR. If miRNAs are to be effectively used in the clinical setting, it is imperative that their detection in fresh and/or archived clinical samples be accurate, reproducible, and specific. qPCR has been widely used for validating expression of miRNAs in whole genome analyses such as microarray studies7. The samples used in this protocol were from patients who underwent radical prostatectomy for clinically localized prostate cancer; however other tissues and cell lines can be substituted in. Prostate specimens were snap-frozen in liquid nitrogen after resection. Clinical variables and follow-up information for each patient were collected for subsequent analysis8.
Quantification of miRNA levels in prostate tumor samples. The main steps in qPCR analysis of tumors are: Total RNA extraction, cDNA synthesis, and detection of qPCR products using miRNA-specific primers. Total RNA, which includes mRNA, miRNA, and other small RNAs were extracted from specimens using TRIzol reagent. Qiagen's miScript System was used to synthesize cDNA and perform qPCR (Figure 1). Endogenous miRNAs are not polyadenylated, therefore during the reverse transcription process, a poly(A) polymerase polyadenylates the miRNA. The miRNA is used as a template to synthesize cDNA using oligo-dT and Reverse Transcriptase. A universal tag sequence on the 5' end of oligo-dT primers facilitates the amplification of cDNA in the PCR step. PCR product amplification is detected by the level of fluorescence emitted by SYBR Green, a dye which intercalates into double stranded DNA. Specific miRNA primers, along with a Universal Primer that binds to the universal tag sequence will amplify specific miRNA sequences. 
The miScript Primer Assays are available for over a thousand human-specific miRNAs, and hundreds of murine-specific miRNAs. Relative quantification method was used here to quantify the expression of miRNAs. To correct for variability amongst different samples, expression levels of a target miRNA is normalized to the expression levels of a reference gene. The choice of a gene on which to normalize the expression of targets is critical in relative quantification method of analysis. Examples of reference genes typically used in this capacity are the small RNAs RNU6B, RNU44, and RNU48 as they are considered to be stably expressed across most samples. In this protocol, RNU6B is used as the reference gene.

MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR qPCR

Quantitative Real Time polymerase chain reaction (qPCR) is a rapid and sensitive method to investigate the expression levels of various microRNA (miRNA) molecules in tumor samples. Using this method expression of hundreds of different miRNA molecules can be amplified, quantified, and analyzed from the same cDNA template.

MicroRNAs (miRNAs) are single-stranded, 18&#x2013;24 nucleotide long, non-coding RNA molecules. They are involved in virtually every cellular process ...

Dynamic Proteomic and miRNA Analysis of Polysomes from Isolated Mouse Heart After Langendorff Perfusion

Studies in dynamic changes in protein translation require specialized methods. Here we examined changes in newly-synthesized proteins in response to ischemia and reperfusion using the isolated perfused mouse heart coupled with polysome profiling. To further understand the dynamic changes in protein translation, we characterized the mRNAs that were loaded with cytosolic ribosomes (polyribosomes or polysomes) and also recovered mitochondrial polysomes and compared mRNA and protein distribution in the high-efficiency fractions (numerous ribosomes attached to mRNA), low-efficiency (fewer ribosomes attached) which also included mitochondrial polysomes, and the non-translating fractions. miRNAs can also associate with mRNAs that are being translated, thereby reducing the efficiency of translation, we examined the distribution of miRNAs across the fractions. The distribution of mRNAs, miRNAs, and proteins was examined under basal perfused conditions, at the end of 30 min of global no-flow ischemia, and after 30 min of reperfusion. Here we present the methods used to accomplish this analysis&#8212;in particular, the approach to optimization of protein extraction from the sucrose gradient, as this has not been described before&#8212;and provide some representative results.

Here we present a protocol to perform polysome profiling on the isolated perfused mouse heart. We describe methods for heart perfusion, polysome profiling, and analysis of the polysome fractions with respect to mRNAs, miRNAs, and the polysome proteome.

Studies in dynamic changes in protein translation require specialized methods. Here we examined changes in newly-synthesized proteins in response to ...

Biochemistry

Detection of MicroRNAs in Microglia by Real-time PCR in Normal CNS and During Neuroinflammation

Microglia are cells of the myeloid lineage that reside in the central nervous system (CNS)1. These cells play an important role in pathologies of many diseases associated with neuroinflammation such as multiple sclerosis (MS)2. Microglia in a normal CNS express macrophage marker CD11b and exhibit a resting phenotype by expressing low levels of activation markers such as CD45. During pathological events in the CNS, microglia become activated as determined by upregulation of CD45 and other markers3. The factors that affect microglia phenotype and functions in the CNS are not well studied. MicroRNAs (miRNAs) are a growing family of conserved molecules (~22 nucleotides long) that are involved in many normal physiological processes such as cell growth and differentiation4 and pathologies such as inflammation5. MiRNAs downregulate the expression of certain target genes by binding complementary sequences of their mRNAs and play an important role in the activation of innate immune cells including macrophages6 and microglia7. In order to investigate miRNA-mediated pathways that define the microglial phenotype, biological function, and to distinguish microglia from other types of macrophages, it is important to quantitatively assess the expression of particular microRNAs in distinct subsets of CNS-resident microglia. Common methods for measuring the expression of miRNAs in the CNS include quantitative PCR from whole neuronal tissue and in situ hybridization. However, quantitative PCR from whole tissue homogenate does not allow the assessment of the expression of miRNA in microglia, which represent only 5-15% of the cells of neuronal tissue. Hybridization in situ allows the assessment of the expression of microRNA in specific cell types in the tissue sections, but this method is not entirely quantitative. In this report we describe a quantitative and sensitive method for the detection of miRNA by real-time PCR in microglia isolated from normal CNS or during neuroinflammation using experimental autoimmune encephalomyelitis (EAE), a mouse model for MS. The described method will be useful to measure the level of expression of microRNAs in microglia in normal CNS or during neuroinflammation associated with various pathologies including MS, stroke, traumatic injury, Alzheimer's disease and brain tumors.

Microglia are resident macrophages that provide the first line of defense and immune surveillance of the central nervous system. MicroRNAs are regulatory molecules that play an important role in many physiological processes including activation and differentiation of macrophages. In this article, we describe the method for measurement of microRNAs in microglia.

Microglia are cells of the myeloid lineage that reside in the central nervous system (CNS)1. These cells play an important role in pathologies of many ...

Immunology and Infection

Circulating MicroRNA Quantification Using DNA-binding Dye Chemistry and Droplet Digital PCR

Circulating (of cell-free) microRNAs (miRNAs) are released from cells into the blood stream. The amount of specific microRNAs in the circulation has been linked to a disease state and has the potential to be used as disease biomarker. A sensitive and accurate method for circulating microRNA quantification using a dye-based chemistry and droplet digital PCR technology has been recently developed. Specifically, using Locked Nucleic Acid (LNA)-based miRNA-specific primers with a green fluorescent DNA-binding dye in a compatible droplet digital PCR system it is possible to obtain the absolute quantification of specific miRNAs. Here, we describe how performing this technique to assess miRNA amount in biological fluids, such as plasma and serum, is both feasible and effective.

A sensitive and accurate method for cell-free microRNAs quantification using a dye-based chemistry and droplet digital PCR technology is described.

Circulating (of cell-free) microRNAs (miRNAs) are released from cells into the blood stream. The amount of specific microRNAs in the circulation has been ...

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays

Quantitative real-time PCR (QPCR) has emerged as an accurate and valuable tool in profiling gene expression levels.  One of its many advantages is a lower detection limit compared to other methods of gene expression profiling while using smaller amounts of input for each assay.  Automated qPCR setup has improved this field by allowing for greater reproducibility.  Its convenient and rapid setup allows for high-throughput experiments, enabling the profiling of many different genes simultaneously in each experiment.  This method along with internal plate controls also reduces experimental variables common to other techniques.  
We recently developed a qPCR assay for profiling of pre-microRNAs  (pre-miRNAs) using a set of 186 primer pairs.  MicroRNAs have emerged as a novel class of small, non-coding RNAs with the ability to regulate many mRNA targets at the post-transcriptional level.  These small RNAs are first transcribed by RNA polymerase II as a primary miRNA (pri-miRNA) transcript, which is then cleaved into the precursor miRNA (pre-miRNA).  Pre-miRNAs are exported to the cytoplasm where Dicer cleaves the hairpin loop to yield mature miRNAs.  Increases in miRNA levels can be observed at both the precursor and mature miRNA levels and profiling of both of these forms can be useful.  There are several commercially available assays for mature miRNAs; however, their high cost may deter researchers from this profiling technique.  Here, we discuss a cost-effective, reliable, SYBR-based qPCR method of profiling pre-miRNAs.  Changes in pre-miRNA levels often reflect mature miRNA changes and can be a useful indicator of mature miRNA expression.  However, simultaneous profiling of both pre-miRNAs and mature miRNAs may be optimal as they can contribute nonredundant information and provide insight into microRNA processing.  Furthermore, the technique described here can be expanded to encompass the profiling of other library sets for specific pathways or pathogens.

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR qPCR Arrays

We will demonstrate the setup and analysis of pre-microRNA 96-well arrays for QPCR using a robot as well as by hand with a Thermo Scientific Matrix multichannel pipette.

Quantitative real-time PCR (QPCR) has emerged as an accurate and valuable tool in profiling gene expression levels.  One of its many advantages is a lower ...

Biology

Isolation of Small Noncoding RNAs from Human Serum

The analysis of RNA and its expression is a common feature in many laboratories. Of significance is the emergence of small RNAs like microRNAs, which are found in mammalian cells. These small RNAs are potent gene regulators controlling vital pathways such as growth, development and death and much interest has been directed at their expression in bodily fluids. This is due to their dysregulation in human diseases such as cancer and their potential application as serum biomarkers. However, the analysis of miRNA expression in serum may be problematic. In most cases the amount of serum is limiting and serum contains low amounts of total RNA, of which small RNAs only constitute 0.4-0.5%1. Thus the isolation of sufficient amounts of quality RNA from serum is a major challenge to researchers today. In this technical paper, we demonstrate a method which uses only 400 &#181;l of human serum to obtain sufficient RNA for either DNA arrays or qPCR analysis. The advantages of this method are its simplicity and ability to yield high quality RNA. It requires no specialized columns for purification of small RNAs and utilizes general reagents and hardware found in common laboratories. Our method utilizes a Phase Lock Gel to eliminate phenol contamination while at the same time yielding high quality RNA. We also introduce an additional step to further remove all contaminants during the isolation step. This protocol is very effective in isolating yields of total RNA of up to 100 ng/&#181;l from serum but can also be adapted for other biological tissues.

This protocol describes a method for extracting small RNAs from human serum. We have used this method to isolate microRNAs from cancer serum for use in DNA arrays and also singleplex quantitative PCR. The protocol utilizes phenol and guanidinium thiocyanate reagents with modifications to yield high quality RNA.

The analysis of RNA and its expression is a common feature in many laboratories. Of significance is the emergence of small RNAs like microRNAs, which are ...

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 ...