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Chemical Labels Help Lower RNA Input Requirements for m6A Methylation Sequencing


NEW YORK – A new method for sequencing-based detection of m6A RNA methylation can lower input requirements, eliminating a major bottleneck for profiling studies of this important biomarker.

Developed by researchers led by Lulu Hu of China's Fudan University Cancer Institute and Chuan He of the University of Chicago, m6A-SAC-seq requires ten- to a hundredfold less starting material than existing methods. In a proof-of-concept paper published this week in Nature Biotechnology, the researchers described a chemical labeling-based sequencing protocol that used tens of nanograms of RNA, compared to hundreds or thousands of nanograms required by other methods, which are usually based on immunoprecipitation sequencing. They were able to provide single-base resolution for tens of thousands of sites, as well as modification levels for the sites in different cell lines and cell states.

He said his team has further optimized the protocol to use "single-digit nanograms" of material. "We can actually detect many more sites, something like 50,000 to 100,000 sites in different cell types," he said.

"This new method will likely enable many studies of m6A in tissues or cell types that were not previously possible," Kate Meyer, a researcher at Duke University who has developed methods for m6A sequencing, said in an email. "Additionally, the fact that this method provides site-specific information as well as measurements of m6A abundance opens up new opportunities for investigating how m6A or its levels change across conditions or in different cell or tissue types."

One of many epigenetic modifications, m6A is present in thousands of mRNAs as well as noncoding RNAs and is a critical regulator of gene expression in cells, Meyer explained. "So, determining where m6A is deposited throughout the transcriptome, at what levels, and how that might change across cell types or conditions is incredibly important for understanding how m6A contributes to physiological processes or disease states."

Traditional m6A mapping strategies use antibodies to pull down modified sequences. "But these methods suffer from high input RNA requirements and non-specificity of antibodies," she said.

M6A-SAC-seq, which stands for m6A-selective allyl chemical labeling and sequencing, is one of several antibody-free methods now available — another one is Meyer's Dart-seq. Oxford Nanopore Technologies' platform can also be used to directly detect m6A. He said his lab is working on other methods, as well, but this one seems to be powerful due to its resolution and low input requirements.

Specifically, m6A-SAC-seq uses a dimethyltransferase and an S-adenosyl-methionine analog to allyl-label m6A sites. An iodination treatment generates a cyclic product, causing mutations in cDNA when processed by the HIV-1 reverse transcriptase. These mutations are identified with NGS.

"The use of spike-ins and demethylated control samples using the FTO demethylase further ensure the specificity of the sites being identified," Meyer said.

University of Chicago's He said his team is already applying the method to study stem cell differentiation and early development. "Next, we're going to apply this to study the tumor microenvironment," he said, adding that researchers studying neurons may also find this method useful.

One limitation of the method is that one of the enzymatic steps is biased for m6A in GAC sequences. A September 2021 study in HEK293T and mouse embryonic stem cells suggested that GAC motifs account for approximately 75 percent of m6A. Another 15 percent to 30 percent are found in AAC motifs. "For AAC sequences, our method can detect highly modified bases," He said. "It doesn't detect lowly modified AAC sites." Therefore, it misses approximately 10 to 20 percent of total m6A sites, most of which are in AAC motifs.

"The authors did some analyses related to m6A and RNA binding proteins that are interesting but require further experimental data to validate and more completely understand [this]," Meyer added. "Their study also produces new datasets related to changes in m6A across cell types and during monocytopoiesis, which will hopefully be useful resources for follow-up studies."

He's team is working to get rid of the sequence bias, he said, potentially through directed evolution of the enzyme. Like many in the field, they're also making a push to make the method work in single cells. Meyer, who has also turned her lab's attention to single-cell m6A analysis, said this type of work is leading to new insights that had been missed by bulk profiling approaches.

"The optimized protocol we have now works with hundreds to thousands of cells," He said. "The next goal is single-cell quantitative sequencing. We're getting very close."