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Home NEWS Science News Biology

Nanopore Method Maps Active tRNAs During Cellular Stress

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November 7, 2026
in Biology
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Nanopore Method Maps Active tRNAs During Cellular Stress

Nanopore Method Maps Active tRNAs During Cellular Stress

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Researchers have developed a nanopore-based sequencing method called tRIBO-seq that distinguishes between transfer RNAs actively engaged in protein synthesis and the total cellular tRNA pool. Published in Nature Methods, the study demonstrates that this approach reveals distinct abundance, modification, and fragmentation patterns in ribosome-associated tRNAs under various stress conditions. The method addresses a long-standing technical challenge in molecular biology: the difficulty of isolating and characterizing tRNAs directly from actively translating ribosomes without labor-intensive fractionation steps.

During translation, transfer RNAs deliver specific amino acids to the ribosome in coordination with the messenger RNA sequence. Despite their central role in protein synthesis, the precise contribution of tRNAs to the modulation of translation has remained poorly understood. Previous studies have predominantly examined total tRNA populations because isolating ribosome-associated tRNAs typically requires cumbersome sucrose gradient fractionation. This new method allows for the selective capture of native tRNA populations from actively translating ribosomes, providing a more accurate snapshot of the translational status of cells.

The tRIBO-seq workflow involves isolating ribosomes using a puromycin derivative known as the RiboLace smart probe, followed by an antibody-free and tag-free pull-down. This process obtains the ribosome-bound fraction in a single step. The small RNA fraction is then isolated from each pool and used as input for ligation with splint adaptors, which are required for nanopore tRNA library preparation and sequencing. The protocol can be completed within five hours and requires substantially less input material than classical sucrose gradient-based polysome approaches.

To benchmark the method, the researchers applied tRIBO-seq to human embryonic kidney 293T cell cultures grown under standard growth conditions. Principal component analysis of tRNA abundances revealed separate clustering of ribosome-associated tRNAs and total tRNAs, suggesting that even under steady-state conditions, these populations are slightly distinct. The initiator methionine tRNA was found to be the most significantly enriched tRNA in the ribosome-embedded fraction, consistent with its essential role in translation initiation. By contrast, tryptophan and selenocysteine tRNAs appeared significantly decreased from the ribosome-associated pool, aligning with the well-established scarcity of these amino acids in the human proteome.

The study further validated the specificity of tRIBO-seq by testing its performance in cell cultures treated with harringtonine, a translational inhibitor that arrests elongation immediately after translation initiation. Ribosome profiling experiments confirmed that harringtonine exposure led to an accumulation of ribosomes at start codons. Differential expression analysis showed significant enrichment of the initiator tRNA in the ribosome-associated fraction of treated cells, while total tRNAs did not show significant changes. This confirms that tRIBO-seq specifically captures ribosome-embedded tRNAs and reflects the dynamics of translation initiation.

The researchers also investigated whether tRIBO-seq could distinguish cellular responses to distinct forms of translational stress, such as viral infection. In A549 cells infected with vesicular stomatitis virus, principal component analysis revealed a clear separation between infected and uninfected samples in the ribosome-associated tRNA fraction. A significant positive correlation was observed between differential tRNA abundance and viral codon usage, whereas no such correlation was found for total tRNA populations. These results indicate that viral infection selectively alters the composition of ribosome-associated tRNAs to reflect viral codon demand without globally changing total tRNA levels.

Under amino acid deprivation, the method revealed distinct responses in ribosome-associated tRNAs. In HEK293T cells deprived of arginine or leucine, principal component analysis showed clear separation of starved versus control samples in the ribosome-associated tRNA pool. Surprisingly, the study observed an enrichment of cognate tRNAs in the ribosome-associated pool under amino acid starvation, contrasting with the initial expectation of depletion. This trend was most pronounced in leucine starvation, where several leucine tRNA isoacceptors were significantly enriched. Extending arginine deprivation to longer durations revealed a progressive increase in arginine tRNAs, supporting a slower but consistent response to this specific nutrient limitation.

Methionine starvation induced a different type of tRNA dynamic. In MCF-7 cells subjected to methionine deprivation, the abundance of tRNAs remained relatively stable, but prolonged deprivation led to a strong and widespread hypomethylation of tRNAs, particularly in the total tRNA pool. This loss of methyl-based modifications was validated using liquid chromatography-tandem mass spectrometry, which showed that most methylation marks were reduced, with m1A being significantly decreased at 16 hours. The hypomethylated positions overlapped with known methylation sites, suggesting a coordinated cellular response to preserve translational fidelity by preferentially loading modified tRNAs onto ribosomes.

Oxidative stress triggered a distinct fragmentation response in ribosome-associated tRNAs. When MCF-7 cells were treated with sodium arsenite, a well-characterized inducer of oxidative stress, the method detected a drastic increase in tRNA fragments in the ribosome-associated fraction. Differential expression analysis revealed that 14 ribosome-associated tRNAs were significantly altered, in contrast to only two changing in the total tRNA pool. Fragmentation analysis identified specific cleavage sites around position 49 of several tRNAs, suggesting a nonrandom, site-specific degradation pattern. This result aligns with previous studies reporting that angiogenin activation occurs in the ribosome, likely preferentially degrading tRNAs in that location.

The study acknowledges several limitations in the application of tRIBO-seq. The performance of the method may vary depending on the translational activity of the cell type, with neuronal progenitors potentially requiring higher amounts of input material compared to cancerous cell lines. The protocol has so far been tested only in mammalian cell lines, and its extension to nonmammalian eukaryotic samples has not been evaluated. Additionally, because the current workflow deacylates tRNAs before library preparation, it cannot distinguish between charged and uncharged ribosome-associated tRNAs, a distinction that may be important under amino acid starvation conditions.

Despite these limitations, tRIBO-seq offers a robust and reproducible approach to map the full tRNA landscape, capturing abundance, modification, and fragmentation patterns across both total and actively translating tRNA populations. The method provides a focused snapshot of the tRNA pool actively engaged in translation, thereby increasing data granularity, particularly under stress conditions. By enabling integrated analysis of codon-anticodon interactions with minimal batch effects, tRIBO-seq offers a versatile tool for dissecting tRNA-mediated regulatory mechanisms across diverse biological contexts.

The findings highlight the importance of examining both ribosome-embedded and total tRNA populations to comprehensively understand how the tRNAome is used in translation and rewired by environmental cues. The ability to quantify tRNA abundances, modification landscapes, and fragmentation patterns from a single experiment using a single sequencing platform represents a significant advancement in the study of translational dynamics. This technology provides an opportunity to explore both canonical and noncanonical roles of tRNA, including ribosome engagement, modification dynamics, and fragmentation activities, contributing to the broader understanding of cellular adaptation to stress.

Subject of Research: Development and application of tRIBO-seq for profiling translationally active tRNAs under stress

Article Title: Selective profiling of translationally active tRNAs and their dynamics under stress

Article References: Monti, M., Yilmaz, H., Del Piano, A., Arnoldi, M., Bonomo, I., Llovera, L., Sarabando, J., Ribeiro, D., Soares, A. R., Clamer, M., & Novoa, E. M. (2026). Selective profiling of translationally active tRNAs and their dynamics under stress. Nature Methods. https://doi.org/10.1038/s41592-026-03277-6

Image Credits: AI Generated

DOI: 10.1038/s41592-026-03277-6

Keywords: tRIBO-seq, nanopore sequencing, transfer RNA, ribosome profiling, cellular stress, translation, tRNA modification, viral infection, amino acid starvation, oxidative stress, Selective, profiling

News Source: Kristina Jarvis. (November 7, 2026). Nanopore Method Maps Active tRNAs During Cellular Stress. Scienmag.

Tags: amino acid starvationcellular stressNanopore Sequencingoxidative stressprofilingribosome profilingselectivetransfer RNAtranslationtRIBO-seqtRNA modificationviral infection
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