Between the first-round of journal club talks and the paper that we all discussed on day three of the module, you have begun to learn a lot about the usefulness of RNA aptamers and of SELEX.
One particularly compelling type of aptamer is that which not only binds to a target, but in doing so reproducibly effects a particular function. An example is riboswitches consisting of an aptamer domain and an expression platform; these are common in nature, particularly in bacteria. The aptamer domain typically recognizes a small molecule metabolite. Due to a resulting conformational change in the expression platform, transcription of a gene (or translation of its associated protein) may subsequently be turned on or off. For example, target binding may alter premature transcript termination via terminator/anti-terminator pairing. Engineers can mimic nature’s designs to create riboswitches with arbitrary desired functions. Ribozymes, or RNA with cleaving activity, may be incorporated in engineered riboswitches for additional utility.
The specificity and affinity exhibited by aptamers is well-suited to several therapeutic uses. You have now seen examples of aptamers acting as drugs, drug antidotes, and potentially as targeted drug carriers that hone in on disease sites. You can start to appreciate the trade-offs inherent in experimental design for human health applications. For example, is the greater cost and labor of in vivo experiments offset by increased likelihood that the aptamer actually works in the required environment?
While RNA aptamers theoretically present infinite engineering possibilities, in reality researchers are limited by time and resources. Thus, improving SELEX efficiency is an important research topic in its own right. Two examples of modified SELEX that you saw in the journal club papers were use of microfluidics with magnetic beads and dual selection. Other modifications to SELEX are particular to specific applications, such as preparing aptamers to complex targets (e.g., tumors).
In this module, we have investigated SELEX efficiency at the column selection step, using known RNA sequences (one that binds to heme and one that doesn’t) as a model system. We varied stringency in two ways: number of washes, and amount of target aptamer present. After today’s experiment, you should be able to discover some trends in SELEX efficiency. Consider how applicable your results are to an arbitrary SELEX system, and what further experiments you might suggest doing in the future.
Part 1: Purify, quantify, and prepare RNA
Repeat the Day 4 protocol, parts 1 through 3. That is, briefly:
- Digest the completed IVT reactions with DNase, then purify on a Micro Bio-Spin column.
- Quantify the RNA by spectrophotometry.
- If you have less than 1.4 nmol of either "post" sample, let one of the teaching faculty know.
- Dilute each sample to 8 μM in the selection buffer (SB).
- Note that to dilute your post-column sample, you will have to make an educated assumption about the ratio of 6-5 to 8-12, because they do not have the same molecular weight. What do you expect to have happened on the column? For your report, you may want to consider how substantially your final result could be affected if your assumption is wrong.
- Finally, denature not only your "post" samples, but also your four "pre" samples, at 70 °C (5 minutes) and then let them cool for at least 10 minutes.
- If you are missing some "pre" samples due to low RNA yields, let the teaching faculty know; we have extra 6-5 and 8-12 to give you.
Part 2: Binding assay
- Retrieve some 6 μM heme from the teaching faculty. Why might you use 6 μM instead of 8 μM, if we want 1:1 molar RNA:heme? Hint: Which concentration are you more certain of, the heme or the RNA?
- A 1M stock solution of heme was originally prepared in DMSO, then diluted in multiple steps to 6 μM. Note that the stock solution is prepared by dabbing a little (solid) hemin into DMSO, and then testing the concentration on a spectrophotometer. The extinction coefficient of heme at 405 nm is 180 mM-1cm-1.
- For each sample in the table below, add 175 μL of heme solution to either an empty eppendorf tube or to the exactly 1.4 nmol "pre" samples you previously set aside.
- Now add 175 μL of selection buffer to the first tube. To the remaining tubes, add 175 μL of the appropriate aptamer solution if it's not already in there (i.e., your "post" samples).
- Incubate for a minimum of five minutes at room temperature.
- Meanwhile, unwrap some microcuvettes, one for each sample. Add 350 μL of selection buffer to the first cuvette.
- Remember that SB has soap in it. If you form bubbles as you are pipetting, these may interfere with the absorbance measurement. Thus, as you pipet each sample into its cuvette, do not expel the final drop of SB.
- If a bubble forms anyway, ask the teaching faculty to help you pop it with a needle.
- When your samples are completely ready, sign up for your spectrophotometry slot up front. When your team name is called, head up to 56-670 (Essigman lab) to meet Jacob. You must bring safety glasses with you and wear them at all times in the lab.
Jacob will help each team run the spectrophotometer.
- Under the "Cary" tab in Setup, confirm that you will be measuring from 350 to 425 nm in 0.5 nm steps.
- Under the Baseline tab in Setup, confirm that the "Baseline correction" option is selected, which corrects your spectra according to the blank.
- Blank on selection buffer alone. Press Baseline to take the reference spectrum.
- Then, beginning with the heme sample, press Start to measure each sample. You will be prompted to give each sample an informative name.
- From the C directory, go to the folder named Agi and 20.109, then create a folder called "YourDay_YourColor", for example TR_Pink.
- You can briefly zoom in on each spectrum to note down the approximate absorbance value at 405 nm, and also observe whether the peak appears to have shifted away from 396 to 405-410 nm.
- Finally, display each of your absorbance measurements on the chart simultaneously by clicking on the "Trace Preferences" button in the upper left side of the screen. Export your data by clicking "Save Data As..." under File. Save your data as a .CSV file titled "YourDay_YourColor" in the USB drive (removable D drive).
|| Abs at 405 nm
|| Peak seems shifted?
| Heme alone
| 6-5 "pre"
| 8-12 "pre"
| Mixture "pre"
| Mixture "post," fewer washes = ____
| Mixture "post," more washes = ____
Part 3: Begin analysis
You may want to start your analysis in lab, or wait until later. The directions below provide an outline of the steps you need to take.
- Retrieve your .csv file from today's Talk page once the teaching faculty have put them up.
- Open the file in Excel (or similar spreadsheet program) and save it with a .xls (or similar) extension and a new, informative name.
- Deleted the unneeded information (collection time, etc.) from the bottom of the spreadsheet.
- Delete all but the first (identical) wavelength columns, but be sure to retain sample names, moving them above the absorbance column if necessary.
- Select all of the columns, and in Excel's menu choose Data → Sort. Choose Sort by Ascending according to Column A.
- Following these instructions exactly will flip the wavelengths from descending to ascending while retaining the correct associations between wavelength and sample absorbance. If all of your absorbances are suddenly monotonically increasing, go back to the original file and start again.
- Move sample names back to the top if they have shifted to the bottom.
- Quickly plot absorbance vs. wavelength for each sample, all on the same chart. Re-scale as necessary to get a good look.
- Making the symbols a small point size will help you better see the individual curves.
- Do the sample curves all overlap pretty well at 375-380 nm? If so, move to step 12. Otherwise, proceed with the next step.
- Choose one sample - for example, the 6-5 or 8-12 "pre" sample - as a standard. Find the average difference between each sample and your standard sample in the entire 375-380 nm range.
- For example, set up a new column - perhaps on a new sheet - that takes the difference of the absorbance at a given wavelength in each column from the standard column. Hint: inserting a "$" sign before a column name, such as "$J," will tell Excel to use column J as the standard for each subtraction.
- The two "pre" aptamers should have a difference quite near zero, perhaps 0.0004. Other samples may have differences closer to 0.01 or even 0.1.
- For each sample, subtract the average difference in the (supposed-to-)overlap region from the entire absorbance spectrum. This part is best done on a new worksheet.
- Plot the subtracted samples and confirm that they now overlap where expected.
- Insert a few rows at the top of your sheet. In one row, select the A405 value for each sample. In the next row, write the % 8-12 for each "pre" sample.
- For the "pre" and "post" mixtures, linearly interpolate between the 6-5 and 8-12 A405 values to estimate the % 8-12.
- How well does the "pre" value match what you thought you put in? How might you account for any observed difference?
- How does your "post" value compare with what you expected, given the % 8-12 you started with, and relatively speaking for your and your partner's wash number?
- Do the horizontal peak shifts seem consistent with your findings based on the vertical shifts?
- Post a summary of your findings on today's Talk page ASAP, but by 48 hrs after Day 8 (by 5 pm Sat or Sun, depending on your section). That way the entire class can look for trends while writing their respective lab reports.
For next time
Some of you will be presenting during journal club next time. No other homework is due on day 8. Several assignments are due in one week.
Please remember to send all major assignments to the 20109.submit AT gmail DOT com address.
- Your first draft of the laboratory report is due by 11 a.m. on Day 1 of Module 3, i.e., next time.
- Your computational assignment is due by 11 a.m. on Day 1 of Module 2, i.e., a week from today.
- If you presented for journal club today, your first short reflective assignment is also due, both by email and as a hardcopy at the beginning of lab next time. Please remember to use the 20109.submit AT gmail DOT com address.
- An awareness of your own strengths and weaknesses can often help you improve your future work. After you give your presentation, write a brief self-evaluation (200 words is plenty). Specifically, describe at least two things that you thought you did well, and at least two that could use improvement; a short paragraph will suffice for each of the two sections. Feel free to include both big-picture and detail-oriented comments.
Primarily same as Day 4, plus heme solution described in Protocol section above.