Cerebrospinal Fluid MicroRNA Profiling Using Quantitative Real Time PCR

The overall goal of this procedure is to profile microRNAs in cerebral spinal fluids by quantitative PCR and to analyze the data using Gen X professional software. This is accomplished by first isolating total RNA from cerebral spinal fluid samples. The second step is to perform reverse transcription in order to transcribe the RNAs into CDNAs.

Next, the CDNAs are mixed with a cyber green master mix loaded into 384 well plates containing primers for 742 unique sequences and amplified using real-time PCR. The final step is to analyze the data acquired from the real-time amplification. Ultimately, the results can be expressed as a fold change, increase or decrease over a control, and visualized in various graphic representations.

So the main advantage of our technique over existing methods like chip arrays is that our method is highly sensitive and requires minimal amount of RNAs. Generally, individuals new to this method will struggle because of the high amount of data generated and the use of the software for data analysis. First, spray the working area and pipettes with RNA Zap.

To begin, CDNA synthesis dilute the template RNA samples to a concentration of five nanograms per microliter with nuclease free water. Next, gently place the five x reaction buffer on ice to thaw. Then add 40 microliters of nuclease free water to the RNA spike in to resuspend the reagent, vortex the tube and leave it on ice for 15 to 20 minutes.

Next, remove the enzymes from the freezer, flick the tubes and place them on ice. Also, once all the reagents have thawed, quickly spin them down. Prepare reverse transcriptase working solution in a 1.5 milliliter eph tube by adding the five x reaction buffer enzyme.

Mix nuclease free water and RNA spike in template using the proportions indicated in table one. Next, mix the working solution by vortexing it for one to two seconds at maximum speed. Briefly spin down the solution for 10 seconds, and then dispense the working solution into nuclease free PCR tubes.

Then add the template RNA directly into the PCR tubes. Gently vortex the reaction for one to two seconds to ensure that all of the reagents are thoroughly mixed and spin down the tubes for 10 seconds. Place the sample in the PCR machine and enter the settings shown here.

Then start the program following retro transcription. The CDNA is ready for real-time PCR amplification and can be stored at negative 20 degrees Celsius for up to five weeks. To begin real-time PCR amplification, first place the CDNA and the PCR master mix on ice.

To thaw protect the PCR master mix vials from light by covering them with aluminum foil while they thaw. Once thawed vortex, the PCR master mix for one to two seconds. Next, combine 2000 microliters of two XPCR master mix and 1, 980 microliters of water in a 15 milliliter conical tube.

Add 20 microliters of the CDNA to the mixture and gently vortex the solutions for one to two seconds. Then spin the solutions down in a refrigerated centrifuge at 1, 500 times G for one minute at four degrees Celsius. Next place the PCR reaction mix into a multi-channel pipette reservoir.

Briefly spin down the ready-to-use plates in a refrigerated centrifuge at 1, 500 times G before removing the plate seal. Then dispense 10 microliters of the PCR master mix containing CD NA to each well of a 384 well plate. Using a 16 channel pipette and seal the plate with an optical sealing film.

After adding the master mix, briefly spin the plate in a refrigerated centrifuge at 1, 500 times G to pull the solution to the bottom of the wells. Mix the samples and remove air bubbles to pause the experiment. At this point, store the reactions in an area protected from light at four degrees Celsius for up to 24 hours.

Next, perform real-time PCR amplification and melting curve analysis following the parameters detailed in table two. To begin analysis, select the second derivative analysis method in the Roche light cycler. Then calculate the quantification cycle or CQ values.

Export the data as a table and save it as a text file. Next, import the data into Gen X by first clicking on the gon import wizard button and then clicking start at the next window, select the format instrument and plate layout files. Plate layout Excel files can be downloaded from the GON website.

Then import panel one and click next. The table generated after the file import contains predefined columns, edit sample names, and add or remove classification columns at this step. Click next when you’re done and save the data.

Then load it to the data editor First, calibrate the data between the plates by choosing INTERPLATE calibration from the pre-processing menu to ensure all of the plates are calculated using the same parameters. Next, define a cutoff value that will discard data higher than the threshold cycle or ct. If a micro RNA has a CT that is greater for one replica out of three, that reading will be replaced with the average of the CT from the two other probes.

Define reference genes by selecting a list of microRNAs that have similar CQ values across all samples and run gene norm. Next, normalize the data using the obtained reference genes. The resulting values will correspond to the delta ct.

Remove empty and almost empty columns by opening the pre-processing window and selecting validate sheet, and then selecting Apply on the remove empty columns line in the line below. Choose the desired percentage of valid data and click apply. Select 100%if you wish to compare only microRNAs common to all samples.

Load the final MDF file into Gen X and open the data manager to classify cluster and visualize microRNAs and samples on heat maps and dendro grams. Then select and create groups of samples and click apply when you’re done. Next in the control panel window, click run.

Save the heat map in the desired format such as TIFF or bitmap, and then copy and modify the heat map as needed. This graphic bar was obtained from the G norm application within Gen X to analyze 10 possible micro RNA reference genes. These results indicate that MIR 622 and MI 1, 266 are the most stably expressed microRNAs.

The box plot displayed here shows the distribution of data for each of 11 statistically significant microRNAs within the groups of HIVE and HIV plus without encephalitis. In each column, the plot indicates the median and first and third quartiles, along with the maximum and minimum values. Following this procedure, mineral profiling can be performed on any body fluids, tissue samples, and cultured cells.