We could all use a spa day once in a while, so light some lavender-scented candles, take a deep breath, and let NanoSPA analyze the RNA modifications in your samples. This new nanopore sequencing analysis pipeline provides data on both N6-methyladenosine (m6A) and pseudouridine (Ψ) modifications at the same time, reducing stress and saving time.
Instead of running two separate experiments, NanoSPA (“nanopore simultaneous investigation for pseudouridine and m6A”) analyzes a single set of nanopore sequencing data with two different models. To study Ψ—famous for stabilizing RNA in COVID-19 vaccines—Tao Pan’s lab at the University of Chicago used their NanoPsu model. They didn’t have a model for m6A, though, so the industrious team developed one and trained it with high-quality datasets. Running the complete NanoSPA platform on a mouse embryonic stem cell line showed that the strategy performed similarly to other published m6A methods, achieving a Zen-like balance.
With their holistic perspective, the team suspected that m6A and Ψ might be connected or coordinated in some way. With NanoSPA, they observed that transcripts with lots of Ψ sites had fewer m6A sites, and vice versa, so they aren’t that likely to be on the same transcripts.
Next, they conducted a series of experiments using siRNA knockdown to decrease expression of genes responsible for “writing” these modifications: METTL3 writes m6A, whereas TRUB1 writes Ψ. Here’s what they found:
- Knocking down METTL3 or TRUB1 affects metabolic genes
- METTL3 knockdown (reduced m6A) results in more Ψ in transcripts that usually have lots of m6A, which they say suggests m6A inhibits Ψ
- Unexpectedly, TRUB1 knockdown (reduced Ψ) decreases m6A, which they say could be because TRUB1 promotes m6A, whereas other Ψ writers likely inhibit m6A
The results were complex, so to bring more order to their universe, the researchers looked at how these modifications affect translation, a key process in the life of an RNA. Knocking down both METTL3 and TRUB1 at the same time reduced polysomes in a polysome profiling experiment, and those transcripts that were most reduced were those involved in protein synthesis.
The team calmly reasoned that even though m6A and Ψ slow elongation when they are in coding regions, the modifications could help recruit a ribosome to an mRNA when they are in untranslated regions. Here are the details when the researchers used NanoSPA to look at translation efficiency (TE) in polysomes:
- More m6A means higher TE and the same goes for Ψ
- Not much happens when METTL3 is knocked down—m6A and Ψ levels are about the same in polysomes as in the control condition
- TRUB1 knockdown reduces levels of Ψ in polysomes, but m6A levels are about the same as control
- TE went down in TRUB1 knockdowns
The team concluded that the two modifications are beneficial for translation, but that Ψ has an even larger effect than m6A.
Overall, NanoSPA offers a low-stress, two-in-one solution to investigate m6A and Ψ RNA modifications. As a bonus, because NanoSPA actually extracts information for all of the bases, the approach could generate results for other RNA modifications by plugging in the right models.
So, kick off your shoes, put on some soothing music, and check out the details at Nature Biotechnology, February 2024.