Transfer RNAs (tRNAs) ship particular amino acids to ribosomes throughout translation of messenger RNA into proteins. The abundance of tRNAs can due to this fact have a profound affect on cell physiology, however measuring the quantity of every tRNA in cells has been restricted by technical challenges. Researchers on the Max Planck Institute of Biochemistry have now overcome these limitations with mim-tRNAseq, a technique that can be utilized to quantify tRNAs in any organism and can assist enhance our understanding of tRNA regulation in well being and illness.
A cell accommodates a number of hundred thousand tRNA molecules, every of which consists of solely 70 to 90 nucleotides folded right into a cloverleaf-like sample. At one finish, tRNAs carry one of many twenty amino acids that function protein constructing blocks, whereas the alternative finish pairs with the codon specifying this amino acid in messenger RNA throughout translation. Although there are solely 61 codons for the twenty amino acids, cells from totally different organisms can include tons of of distinctive tRNA molecules, a few of which differ from one another by solely a single nucleotide. Many nucleotides in tRNAs are additionally embellished with chemical modifications, which assist tRNAs fold or bind the proper codon.
The ranges of particular person tRNAs are dynamically regulated in several tissues and through improvement, and tRNA defects are linked to neurogical illnesses and most cancers. The molecular origins of those hyperlinks stay unclear, as a result of quantifying the abundance and modifications of tRNAs in cells has lengthy remained a problem. The crew of Danny Nedialkova on the MPI of Biochemistry has now developed mim-tRNAseq, a technique that precisely measures the abundance and modification standing of various tRNAs in cells.
Modification roadblocks and resolutions
To measure the degrees of a number of RNAs concurrently, scientists use an enzyme known as reverse transcriptase to first rewrite RNA into DNA. Millions of those DNA copies can then be quantified in parallel by high-throughput sequencing. Rewriting tRNAs into DNA has been tremendously onerous since many tRNA modifications block the reverse transcriptase, inflicting it to cease synthesizing DNA.
“Many researches have proposed elegant solutions to this problem, but all of them relieve only a fraction of the modification roadblocks in tRNAs,” explains Danny Nedialkova, Max Planck Research Group Leader on the Max Planck Institute of Biochemistry. “We noticed that one specific reverse transcriptase seemed to be much better at reading through modified tRNA sites. By optimizing the reaction conditions, we could significantly improve the enzyme’s efficiency, enabling it to read through nearly all tRNA modification roadblocks,” provides Nedialkova. This made it attainable to assemble DNA libraries from full-length tRNA copies and use them for high-throughput sequencing.
The mim-tRNAseq computational toolkit
The evaluation of the ensuing sequencing information additionally introduced important challenges. “We identified two major issues: the first one is the extensive sequence similarity between different tRNA transcripts,” explains Andrew Behrens, PhD pupil in Nedialkova’s group and first writer of the paper. “The second one comes from the fact that an incorrect nucleotide (a misincorporation) is introduced at many modified sites during reverse transcription. Both make it extremely challenging to assign each DNA read to the tRNA molecule it originated from,” provides Behrens.
The crew tackled these points with novel computational approaches, together with the usage of modification annotation to information correct learn alignment. The ensuing complete toolkit is packaged right into a freely obtainable pipeline for alignment, evaluation and visualization of tRNA-derived sequencing information . Researchers can use mim-tRNAseq to not solely measure tRNA abundance, but additionally to map and quantify tRNA modifications that induce nucleotide misincorporations by the reverse transcriptase. “mim-tRNAseq opens up myriad possibilities moving forward,” says Nedialkova. “We expect it will help us and others to tackle many outstanding questions about tRNA biology in health and disease.”