DMS-MaP is a sequencing-based method that allows us to get a snapshot of RNA structure, and learn how it changes under different conditions. In contrast to conventional structure determination methods, like crystallography and electron microscopy, DMS-MaP can be used in cells and deconvolute RNA structure ensembles. As RNA structure has implications in a multitude of biological phenomena, our method could provide mechanistic insights into almost any field of biological research.
Begin by transferring 89 microliters of the refolding buffer into a designated 1.5-milliliter tube for each reaction having a final volume of 100 microliters. Prewarm the tube at 37 degrees Celsius in a thermoshaker placed underneath a chemical hood. Add 10 microliters of nuclease-free water into a PCR tube, and transfer one to 10 picomoles of RNA in it.
Incubate it in a thermocycler at 95 degrees Celsius for one minute to denature the RNA. And then immediately place the tube on an ice block to avoid RNA misfolding. Now, to refold the RNA, add the sample to the designated tube containing the refolding buffer at 37 degrees Celsius and mix it well before incubating it for 10 to 20 minutes.
Next, add one microliter of 100%Dimethyl Sulfate, or DMS, having a concentration of 10.5 molar into the tube containing the RNA sample, and incubate the reaction mixture for five minutes while shaking it at 800 to 1, 400 rotations per minute. After the five-minute reaction, quench it with 60 microliters of 100%beta-mercaptoethanol, and mix it well before vortexing and immediately placing the RNA on ice. Then clean up the RNA and elute it in 10 microliters of nuclease-free water.
Quantify the RNA using a spectrophotometer. Finally, store the modified RNA at minus 80 degrees Celsius. After adding the reaction mixture into the PCR tube, transfer at least 100 nanograms of the eluted modified RNA in 10 microliters of nuclease-free water to the PCR tube.
Incubate the mixture at 57 degrees Celsius for 30 minutes to 1.5 hours in a thermocycler. 30 minutes is sufficient to make a product containing 500 nucleotides. Next, add one microliter of four molar sodium hydroxide to it, mix well by pipette, and incubate at 95 degrees Celsius for three minutes to degrade the RNA, and release TGIRT from the complementary DNA.
Using a column-based approach to remove the primers, clean up the complementary DNA. And perform PCR to amplify it. Verify the PCR success by running two microliters of the PCR product on an agarose gel before proceeding to the library preparation.
Then quantify the extracted fragments using a spectrophotometer before indexing the fragments for sequencing. Transfer the virus-infected cells grown to the desired stage of infection into a dedicated and appropriate fume hood having the required biosafety level. Add 2.5%volume of DMS to the culture medium containing the cells, and seal the container with parafilm.
Immediately incubate the container at 37 degrees Celsius for five minutes. After incubation, carefully pipette out and discard the DMS-containing medium into appropriate chemical waste. Then gently add 10 milliliters of stop buffer into the cells, scrape the cells, and transfer them to a 15-milliliter conical tube.
Pellet down the cells by centrifuging the tube for three minutes at 3, 000 g. Remove the supernatant, and wash the cell pellet two times with 10 milliliters of PBS. Carefully remove residual PBS as much as possible after the wash.
Dissolve the pellet in an appropriate amount of RNA isolation reagent to perform RNA extraction. Next, add 200 microliters of chloroform to one milliliter of homogenized cells in the RNA isolation reagent, and vortex it for 15 to 20 seconds until the cell solution turns bright pink. Wait until phase separation has occurred, which is indicated by the pink lipid phase settling at the bottom.
Spin the tube at a speed of around 20, 000 g for 15 minutes at four degrees Celsius before transferring the upper aqueous phase to a new tube. Clean up the RNA and elute in a sufficient volume of nuclease-free water. Then after performing ribosomal RNA depletion using the preferred approach, elute the RNA in an adequate volume of nuclease-free water, and quantify it using a spectrophotometer.
The purified RNA can be used again in RT-PCR. Using the mentioned web server, the DMS-MaP data can be conveniently analyzed. The reads are mapped to a reference, and the per base mutations are counted.
The resulting population average files can be used as constraints in well-known RNA structure prediction software. The resulting minimum free energy structures can be visualized using software like VARNA. As of now, only the stable version of DREAM can deconvolute RNA structure ensembles.
However, work to make this feature more accessible to the whole community is under progress. In vitro transcription of the gBlock fragment elongated by attachment of a T7 polymerase promoter generated the RNA of interest, appearing as a single band at 300 nucleotides on a 1%agarose gel. Success of the gene-specific RT-PCR performed on the DMS modified RNA was indicated by a single band at 300 base pairs on a 2%agarose gel.
The indexed fragment appeared approximately 150 base pairs higher as expected. DMS treatment was performed on HCT-8 cells displaying cytopathic effect four days post-infection with the virus. The extracted total RNA appeared on the agarose gel as two bright bands, accounting for the 40S and 60S subunits.
After ribosomal RNA depletion, the two bright bands disappeared, leaving a smear in the corresponding lane. After library preparation, samples had varying size distributions and appeared as a smear. The band was excised between 200 and 500 nucleotides, and the adapter dimers were separated out.
The structure model of the SARS-CoV-2 genome showed that bases with open conformation have higher reactivity as compared to those engaged in base pairing. The reactivity profile of the bases indicated that uracil and guanine had low reactivity values and were not modified by DMS. With our method, we are able to predict structures in cells in a high-throughput manner without size constraints.
Control metrics are very important, because they provide insight into the accuracy of the structure predictions. To further verify the accuracy of the prediction, more experiments that disturb, or alter the structure should be conducted.
