Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

2'-O-ribose methylation of transfer RNA promotes recovery from oxidative stress in Saccharomyces cerevisiae

  • Lauren Endres ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft

    Affiliation College of Arts and Sciences, SUNY Polytechnic Institute, Utica, New York, United States of America

  • Rebecca E. Rose,

    Roles Data curation, Formal analysis, Investigation, Methodology

    Affiliation Metabolomics Core Resource Laboratory, New York University Langone Heath, New York, New York, United States of America

  • Frank Doyle,

    Roles Conceptualization, Data curation, Software

    Affiliation College of Nanoscale Science and Engineering, SUNY Polytechnic Institute, Albany, New York, United States of America

  • Taylor Rahn,

    Roles Conceptualization, Data curation, Investigation, Methodology, Writing – review & editing

    Affiliation College of Arts and Sciences, SUNY Polytechnic Institute, Utica, New York, United States of America

  • Bethany Lee,

    Roles Conceptualization, Data curation, Investigation, Methodology, Writing – review & editing

    Affiliation College of Arts and Sciences, SUNY Polytechnic Institute, Utica, New York, United States of America

  • Jessica Seaman,

    Roles Conceptualization, Writing – original draft, Writing – review & editing

    Affiliation College of Arts and Sciences, SUNY Polytechnic Institute, Utica, New York, United States of America

  • William D. McIntyre,

    Roles Data curation, Methodology, Visualization

    Affiliation Department of Chemistry, University of Connecticut, Storrs, Connecticut, United States of America

  • Daniele Fabris

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Resources, Software, Supervision

    Affiliation Department of Chemistry, University of Connecticut, Storrs, Connecticut, United States of America

2'-O-ribose methylation of transfer RNA promotes recovery from oxidative stress in Saccharomyces cerevisiae

  • Lauren Endres, 
  • Rebecca E. Rose, 
  • Frank Doyle, 
  • Taylor Rahn, 
  • Bethany Lee, 
  • Jessica Seaman, 
  • William D. McIntyre, 
  • Daniele Fabris


Chemical modifications that regulate protein expression at the translational level are emerging as vital components of the cellular stress response. Transfer RNAs (tRNAs) are significant targets for methyl-based modifications, which are catalyzed by tRNA methyltransferases (Trms). Here, Saccharomyces cerevisiae served as a model eukaryote system to investigate the role of 2'-O-ribose tRNA methylation in the cell's response to oxidative stress. Using 2'-O-ribose deletion mutants for trms 3, 7, 13, and 44, in acute and chronic exposure settings, we demonstrate a broad cell sensitivity to oxidative stress-inducing toxicants (i.e., hydrogen peroxide, rotenone, and acetic acid). A global analysis of hydrogen peroxide-induced tRNA modifications shows a complex profile of decreased, or undetectable, 2'-O-ribose modification events in 2’-O-ribose trm mutant strains, providing a critical link between this type of modification event and Trm status post-exposure. Based on the pronounced oxidative stress sensitivity observed for trm7 mutants, we used a bioinformatic tool to identify transcripts as candidates for regulation by Trm7-catalyzed modifications (i.e., enriched in UUC codons decoded by tRNAPheGmAA). This screen identified transcripts linked to diverse biological processes that promote cellular recovery after oxidative stress exposure, including DNA repair, chromatin remodeling, and nutrient acquisition (i.e., CRT10, HIR3, HXT2, and GNP1); moreover, these mutants were also oxidative stress-sensitive. Together, these results solidify a role for TRM3, 7, 13, and 44, in the cellular response to oxidative stress, and implicate 2'-O-ribose tRNA modification as an epitranscriptomic strategy for oxidative stress recovery.


Transfer RNAs are fundamental biological molecules that read cognate codons in mRNA to complete the flow of genetic information from DNA to protein. A ubiquitous feature of tRNAs is chemical modification, the most prominent being methylation (of the base or ribose sugar) as catalyzed by tRNA methyltransferase enzymes (Trms)[1, 2]. Notably, tRNA methylation occurs post-transcriptionally, and can thus be viewed as an epitranscriptomic feature at the molecular level [3]. In general, methyl-based modifications of tRNA function to ensure translational fidelity, although how cells accomplish this depends upon the chemical nature of the modification and its position within the tRNA molecule [4]. For example, modifications within the anticodon stem loop (ASL) at position 34 (decoding the wobble base) and 37 influence both the accuracy and efficiency of translation through degenerate codon selection [57]. Modifications within other loop regions of tRNA can influence base interactions that direct folding, increase stability, or alter the structure of the tRNA molecule in ways that regulate aminoacylation or interactions with the ribosome [812].

This study is motivated by two observations that support a role for tRNA modification systems (i.e., Trm enzymes, their modifications, and target transcripts) in the oxidative stress response. First are studies in several eukaryotic cells demonstrating that deleting Trms results in sensitivity to one or more toxicants that induce oxidative stress, or damage DNA [1316]. Second are observations that tRNA modifications are dynamic, changing in response to various toxicants that induce oxidative stress; moreover, these changes include methylation of the ribose sugar moiety at the 2’-OH position (i.e., 2’-O-ribose methylation) [17, 18]. Collectively, these observations are a good indication that Trms and their corresponding modifications play a role in the cellular response to stress. However, questions remain about how cells engage these tRNA modification systems to survive and recover from oxidative stress after toxicant exposure.

Here we focused on Saccharomyces cerevisiae (budding yeast) 2’-O-ribose methyltransferases because 2’-O-ribose modified bases are known to increase under conditions of oxidative stress. For example, 2’-O-methylcytosine (Cm), 2’-O-methyladenosine (Am), and 5-methoxycarbonylmethyl-2'-O-methyluridine (mcm5Um)[16, 17], and unpublished observations). Furthermore, methylation of tRNA at the 2’-OH position of the ribose sugar is generally thought to increase the stability of tRNA via mechanisms that protect against spontaneous hydrolysis or nuclease digestion (e.g., in non-helical regions) and reinforce intra-loop interactions that stabilize the tertiary structure of the molecule [11, 19]]. Such stabilization strategies are essential for thermophilic organisms where tRNAs must carry out protein translation at denaturing temperatures, an idea supported by observations in diverse archaea that show an abundance of 2’-O-methylated nucleosides among global populations of modified tRNAs [2023]. In mesophilic prokaryotes and eukaryotes, 2’-O-ribose modification also plays a structural role in the non-duplex loop regions of the D- and T-arm [11, 24, 25]. The importance of this type of methylation event in mesophilic eukaryotes is not fully understood, though it seems plausible that it serves a stabilizing function in environments that are destabilizing to tRNA molecules (e.g., increased intracellular reactive oxygen species, or ROS).

S. cerevisiae tRNAs undergo methylation of the 2’-OH position of the ribose sugar at three sites in the body of the tRNA molecule (i.e., 4, 18, and 44), and at two sites within the ASL (i.e., 32 and 34, the latter decoding the wobble base)[26]. At least four Trms are known to carry out these methylation events: Trm3 → Gm18, Trm7 → Cm32 and Nm34, Trm13 → Cm4, and Trm44 → Um44 (Fig 1). To investigate a role for 2’-O-ribose methylation of tRNA in the oxidative stress response, we assessed corresponding trm deletion mutants for their sensitivity to oxidative stress after exposure to hydrogen peroxide, rotenone, and acetic acid. In all assays, hydrogen peroxide was the most potent inducer of oxidative stress sensitivity. Accordingly, we characterized methylation chemistries in 2’-O-ribose mutants after acute exposure to hydrogen peroxide and found a complex profile of methylation events in exposed cells, which included increases in Um, Cm, and Gm in wild type cells. Notably, 2’-O-ribose associated modification chemistries were attenuated in trm3, 13, and 44 mutants. Potential roles for these modifications in the oxidative stress response are discussed further in the context of their position on the tRNA molecule.

Fig 1. 2'-O-methylation in Saccharomyces cerevisiae.

2’-O-ribose methyltransferases and target nucleotides (black-filled) in a two-dimensional cloverleaf tRNA structure based on the conventional numbering system (Machnicka, Olchowik et al. 2014). Also shown are other commonly modified nucleotides in tRNAs (dot-filled).

To test the idea that tRNA modification systems targeting the ASL regulate the oxidative stress response, we used Trm7 → tRNAPhe(GmAA) as a model for preferred UUC codon selection [2729]. Using a bioinformatics approach [30], we identified UUC-enriched transcripts in S. cerevisiae as potential Trm7-influenced translational targets and found several with biological functions linked to the oxidative stress response. GNP1 stood out as a UUC-enriched transcript with significant oxidative stress-sensitivity in corresponding gnp1 mutants. In light of recent evidence that trm7 mutants activate the general amino acid control (GAAC) response pathway [31], we propose that attenuated codon-biased translation of GNP1 is a component of this response, contributing to the oxidative stress sensitivity phenotype of the trm7 mutants, which is a focus for future study. Overall, this work solidifies a role for 2’-O-ribose methylation in the oxidative stress response and supports a model in which S. cerevisiae uses this type of modification event in an epitranscriptomic strategy that combines increased tRNA stability and enhanced translational effects post-exposure.

Materials and methods

S. cerevisiae cell culture and transformation

Deletion mutants were retrieved from an S. cerevisiae library (Open Biosystems, Thermo Scientific, Hudson, NH) established by the Saccharomyces Genome Deletion Project and are on a BY4741 background (i.e., haploid genotype: MATa his3Δ1 leu2Δ0 met15Δ0 ura3Δ0)[32]. In this library, ORFs have been replaced by a KanMX cassette, selected for by growth in yeast extract-peptone-dextrose (YPD) broth supplemented with G418 (200 μg/mL) prior to toxicant exposure.

Open reading frames (ORFs) for TRM3, 7, and 13 were obtained in the galactose-inducible BG1805 plasmid vector from the Yeast ORF Collection (DharmaconTM, Horizon Discovery Group, Cambridge, UK)[33]. ORF plasmids were introduced into their respective trm mutant strains by transformation using a one-step buffer containing 40% polyethylene glycol (PEG), 200 mM lithium acetate and 100 mM dimethyl sulphoxide [34]. TRM-ORF transformants were selected by plating on synthetic complete medium: yeast nitrogen base/complete amino acid supplement mixture (YNB/CSM) minus uracil, plus 2% dextrose (SC-Ura, Sunrise Science Products, TN) and growth at 30°C for three days.

For ORF induction, single overnight colonies were initially grown in SC-Ura, and then diluted 1:100 in YNB/CSM minus uracil plus 2% raffinose (ACROS) and allowed to reach stationary phase. These cultures were then diluted three-fold with concentrated media to either induce or repress ORF expression. That is, 3 x YNB/CSM-Ura plus 6% galactose (SIGMA) or 6% dextrose (SIGMA), respectively. After growth to an OD600nm of 2.0, cultures were split into separate tubes for one-hour control (water) or hydrogen peroxide (20 mM) treatments at 30°C, followed by plating on SC-Ura (i.e., 100 μL of a 10−5 dilution) and colony counting after three days of growth at 30°C.

Growth, viability, and colony-forming assays

For the plate-based growth assays, individual mutants were inoculated in liquid, incubated overnight at 30°C with shaking (i.e., 225 rpm), and then diluted in a ten-fold series (i.e., 10−1 to 10−5). Five μL of each dilution was then plated on either YPD, or YPD supplemented with hydrogen peroxide (2 mM), rotenone (400 μM), and acetic acid (20 mM). Plates were incubated at 30°C for 3 days and imaged for growth using a digital camera system (Bio-Rad, CA). Also, quantitative measurements of growth over a twenty hour period were performed on overnight cultures grown from single colonies using an automated microplate reader set at 30°C with orbital shaking (TECAN). To assess viability post-exposure, cultures of trm mutants were grown to log-phase from single colonies in YPD + G418, and then diluted to 3 x 106 cells/mL in YPD or YPD supplemented hydrogen peroxide (40 mM), rotenone (400 mM), and acetic acid (80 mM); BY4741 were similarly treated and served as the control strain. The number of viable cells was determined by staining with trypan blue, four and eight hours post-exposure; cell death was determined by dividing the number of trypan blue positive cells by the total number of cells and is calculated as a percentage.

For the colony-forming assay, similar liquid cultures of mutant single colonies and BY4741 were grown to stationary phase in rich media (i.e., YPD) and diluted to a uniform OD600nm of 2 (~ 6 x 107 cells/mL). Hydrogen peroxide (10 mM), rotenone (100 μM) or acetic acid (20 mM) were added directly to 1 mL of these cultures, with an equivalent volume of water serving as a control. These cultures were incubated for 1 hour at 30°C with shaking, serially diluted to 10−5, and plated on YPD (100 μL). After 3 days of growth at 30°C, the number of colonies was counted. Similar colony forming assays were performed on trm mutants transformed with their respective ORFs, albeit with different growth conditions for ORF selection and expression as described above.

Quantitative real-time reverse-transcription PCR (qRT-PCR)

Total RNA was first isolated from BY4741, and trm3, 7, 13, and 44 mutant strains using TRIzol® reagent (ThermoFisher Scientific) and then 1 μg was converted into complementary DNA (cDNA) using an iScript cDNA synthesis kit (Bio-Rad) according to the manufacturer's instructions. cDNAs were diluted 5 fold and 4 μL was used to detect TRM3, 7, 13, and 44 gene expression with TaqMan® gene-specific expression assays via qRT-PCR on a StepOnePlus real-time PCR system (ThermoFisher Scientific). TRM expression in the trm mutants was determined relative to BY4741 using the delta-delta cycle threshold method (2-ΔΔCt), with actin serving as the internal control.

Transfer RNA modification analysis

Transfer RNA was isolated from yeast spheroplasts generated by digestion with lyticase (from Arthrobacter luteus, Sigma-Aldrich, MO) digestion [35] using a micro RNeasy RNA isolation kit, modified to prevent the loss of covalent modification chemistries. Specifically, at the first step of cell lysis, QIAzol reagent was supplemented with the deaminase inhibitor tertrahydrouridine (0.2 mM, Millipore Sigma, MO), and anti-oxidants deferoxamine and butylhydroxytoluene (both at 0.1 mM, Millipore Sigma, MO). At least 50 μg of total micro RNA was isolated by this method (containing > 85% tRNAs) for subsequent mass spectrometric (MS) analysis of modification chemistries.

The MS analysis was performed on tRNAs isolated from trm mutant strains, before and after acute exposure to hydrogen peroxide (20 mM for 1 hour), as previously described in detail, and for distinct cellular stress responses [3638]. Briefly, isolated tRNAs were digested with select nucleases to obtain analogous mononucleotide mixtures for analysis by direct infusion electrospray ionization (ESI) to detect variable levels of expression in individual modification chemistries. Expression levels were calculated using the Abundance versus Proxy method (AvP), which determines the relative abundance of each post-translational modification (PTM) normalized against the sum of the intensities of the four canonical bases. Statistically significant differences in AvP values (exposed versus unexposed) were determined using an unpaired Student t-test (n = 3), and those with a p-value < 0.05 are shown in Fig 4 and appear in color in S1 and S2 Tables. The same tRNA isolates were also digested with a combination of select nucleases and phosphatases to obtain individual mononucleotides for Tandem MS analysis, carried out in both the positive and negative modes. This approach facilitated the differentiation of isobars detected during PTM analysis, including Am, Um, Cm, and Gm [36, 38].

Intracellular ROS detection

S. cerevisiae trm mutants and BY4741 strains were inoculated into YPD from single colonies. When the culture was at mid-log phase (OD600nm ~ 0.5), cells were pelleted by centrifugation (2500 rpm for 5 min), washed once with phosphate-buffered saline (PBS), and then re-suspended in PBS containing 10 μg/mL 2’,7’-dichlorofluorescin (DCFDA, Molecular Probes-Invitrogen, CA). A stock of DCFDA was prepared fresh on the day of the experiment by dissolving in dimethyl sulfoxide to 10 mg/mL. The cell-DCFDA suspensions were then incubated for 2 hours at 30°C with shaking, washed once with PBS and re-suspended in 1 mL of PBS for direct analysis by flow cytometry using an Image Stream ISX100 (Amnis, WA). The level of reactive oxygen species was measured based on the emission of oxidized DCFDA dye in the green channel (517–527 nm).

Bioinformatics screen of S. cerevisiae ORFs

Whole-genome ORFs of S. cerevisiae were surveyed for UUC codons using the CUT Codon Utilization bioinformatics tool [30]. The CUT tool uses existing genome and transcript data for S. cerevisiae to quantitate the number of times a transcript uses an individual codon or a run of a particular codon (i.e., UUC or UUCUUC). CUT then determines whether or not the codon, or codon run, occurs more or less than the average genome frequency. Statistically significant codon usage was determined by Z-score, with a cutoff of +1.96 representing the 95% confidence level, or an associated P-value of 0.05.


2'-O-ribose trm mutants are sensitive to oxidative stress

Considering the ability of oxidative stress to induce changes in 2’-O-ribose methylation events in S. cerevisiae [17, 18], together with observations of stress sensitivity phenotypes in other S. cerevisiae trm mutants (i.e., Trm9 and Trm4, respectively [13, 15]), we investigated whether 2’-O-ribose trm mutants are also sensitive to oxidative stress. Four 2’-O-ribose methyltransferases were identified in the Saccharomyces Genome Database (SGD), TRM3, 7, 13, and 44 ([39]Fig 1). Quantitative real-time reverse transcription PCR (qRT-PCR) using TRM-specific TaqMan® gene expression assays confirmed that the deletion mutants do not express their respective TRMs (S1 Fig). Interestingly, in the trm3, 7 and 44 mutants, alternate 2'-O-ribose TRMs are up-regulated to varying degrees relative to the BY4741 wild type strain, supporting that compensatory mechanisms may exist at the transcriptional level.

S. cerevisiae strains lacking the above methyltransferases were retrieved from a haploid single-gene deletion library [32] and grown on plates containing hydrogen peroxide, rotenone, and acetic acid to induce oxidative stress. We found that all 2'-O-ribose methyltransferase mutants were sensitive to these toxicants relative to the wild type (control) BY4741 strain (Fig 2A). Notably, this sensitivity phenotype was most apparent on plates supplemented with hydrogen peroxide and was greatest for the trm3 mutant (Fig 2A).

Fig 2. Growth and survival of 2'-O-ribose trm mutants is inhibited in the presence of oxidative stress-inducing agents.

A) Wild type (wt) BY4741 and trm mutant strains were grown from a single colony overnight and then serially diluted in water as indicated. Five μl of each dilution was then plated on YPD agar plates containing acetic acid (20 mM), rotenone (20 μM), and hydrogen peroxide (2 mM), and the cells were grown for 3 days at 30°C. B) Cells were treated with hydrogen peroxide (40 mM), rotenone (400 μM), and acetic acid (80 mM) and non-viable cells were identified by trypan blue staining four and eight hours post-exposure. Untreated cells (i.e., zero hours post-exposure) served as the control. Cell death is shown as the mean number of trypan blue positive cells divided by total cells (i.e., trypan blue positive plus negative), expressed as a percent, with error bars representing the standard deviation of the mean (n = 3). Significant differences in cell death percentages were determined using the t-test: trm mutants versus wild type under the same treatment condition and at the same time post-exposure (n = 3, *P < 0.05, **P < 0.01, ***P < 0.001).

These plate-based assays represent a chronic exposure setting in which it can be challenging to differentiate the effect of the toxicant from the impact of the gene deletion on growth if any. Indeed, a slow-growth phenotype has been reported for trm7 mutants [27, 28], and this phenotype was also detected here for the trm7 mutant strain, while the growth of the trm3, 13, and 44 mutant strains was intermediate between trm7 and wt BY4741 cells (S2 Fig). To further assess the oxidative stress sensitivity of the 2'-O-ribose trm mutants, we performed two acute exposure assays in which cells are normalized with respect to cell number prior to exposure. The resulting data reflect survival and recovery post-exposure rather than continued growth in the presence of the toxicant.

First, the effects of exposure to hydrogen peroxide, acetic acid and rotenone on cell death was determined by trypan blue staining to distinguish non-viable cells (i.e., positive for trypan blue) from viable cells. An eight-hour exposure to hydrogen peroxide produced high percentages of non-viable cells for the trm3 and trm7 mutant strains (Fig 2B, top panel). Exposure to rotenone for eight-hours significantly increased cell death across all strains, with the wild type BY4741 strain being largely refractory to this toxicant, which disrupts mitochondrial function to increase intracellular ROS (Fig 2B, middle panel). A significant increase in cell death was only observed for the trm7 strain after an eight-hour exposure to acetic acid (Fig 2B, bottom panel). Overall, using viability assays as a measure of oxidative stress sensitivity, trm7 mutants were the most sensitive to all toxicants, followed by trm3 mutants (sensitive to hydrogen peroxide and rotenone), whereas trm13 and trm44 mutants were only sensitive to rotenone.

Second, we used colony-forming assays to assess the ability of the 2'-O-ribose trm mutants to recover from an acute toxicant dose, sub-lethal to the wild type BY4741 strain. In this assay, all colonies formed post-exposure were counted, and the data indicate an ability to recover from toxicant exposure. We found that after acute exposure to hydrogen peroxide colony formation was significantly decreased for all 2’-O-ribose trm mutants compared to wild type cells (Fig 3A). Colony formation was similarly decreased after acute exposure to acetic acid and rotenone in trm3 and trm13 mutants (Fig 3A).

Fig 3. Colony survival is decreased in 2'-O-ribose trm mutants after exposure to oxidative stress-inducing agents.

A) Wild type (BY4741), trm3, trm7, trm13, and trm44 mutant strains were grown to stationary-phase and exposed to acetic acid (20 mM), rotenone (100 μM), and hydrogen peroxide (10 mM). One hour post-exposure, the cultures were serially by a factor of 10−5, plated (100 μl), and the number of colonies was recorded after growth at 30°C for three days. Percent colony survival is shown as the mean for the toxicant relative to each individual strain under untreated conditions; error bars are standard deviations (n = 6 for wild type and n = 3 for trm mutants). Significant differences in colony formation and survival were determined using the t-test: trm mutants versus wild type under the same treatment condition (*P < 0.05, **P < 0.01, ***P < 0.001). B) trm mutants strains (as indicated) were transformed with their corresponding galactose (Gal)-inducible open reading frames (+ TRM-ORF). Cells grown to stationary phase in selection media (-Ura) + raffinose (carbon source) were diluted (3 fold) in media (-Ura) containing either galactose (+ Gal) or dextrose (+ Dex), and allowed further growth to stationary phase. Then, cells were split into separate tubes for one-hour control (water) or hydrogen peroxide (20 mM) treatments at 30°C, and similarly diluted (i.e., 10−5), plated, with colonies recorded three days later. Percent colony survival is shown as the mean ± standard deviations (TRM3 and TRM13, n = 3; TRM7, n = 4). Significant differences in colony survival were determined using a Student t-test: cells exposed to hydrogen peroxide, +Gal (TRM "on") versus +Dex (TRM "off", *P < 0.005, **P <0.001).

Reintroduction of 2’-O-ribose methyltransferases attenuates sensitivity to oxidative stress

Since the 2’-O-ribose trm mutants were most sensitive to hydrogen peroxide, we used this toxicant to assess colony formation after introducing the open reading frames (ORFs) of the TRM genes under the control of a galactose (GAL) inducible promoter (i.e., trm-Δ + TRM-ORF). ORF constructs were available from a yeast open reading frame collection [33] for TRM3, 7, and 13, and their expression was selected for by initial growth in the absence of uracil. Under non-inducible growth conditions for ORF gene expression (i.e., + Dex: TRM “off”) the colony-forming ability of the 2’-O-ribose mutants was reduced after exposure to hydrogen peroxide as expected. However, under growth conditions that induce ORF gene expression (i.e., + Gal: TRM “on”) the number of colonies that survived hydrogen peroxide exposure significantly increased (Fig 3B). Although glucose is the preferred carbon source for S. cerevisiae, under +Gal-untreated conditions, the trm3 and trm7 mutants produced more colonies relative to the +Dex-untreated (results not shown), suggesting that some reprogramming occurs during the carbon source switch; thus, the data is presented relative to the same growth conditions concerning the carbon source. These results demonstrate some degree of rescue of oxidative stress sensitivity phenotypes by introducing 2’-O-ribose methyltransferase genes into their respective deletion mutants.

Oxidative stress-induced nucleoside modification profiles in 2’-O-ribose trm mutants

We used direct infusion electrospray ionization mass spectrometry (ESI-MS) to quantitate the levels of ribonucleoside modifications in wild type BY4741 cells and 2’-O-ribose trm mutants before and after exposure to hydrogen peroxide, focusing on Am, Um, Cm and Gm. Exposure-induced changes are shown relative to unexposed wild type cells (Fig 4), which were calculated from discrete values determined using the abundance versus proxy method. This method measures the absolute signal intensity of the modified ribonucleoside over the sum of the absolute intensities of the canonical bases, taking into account any changes unmodified nucleosides [36].

Fig 4. Analysis of 2'-O-ribose methylation in S. cerevisiae exposed to hydrogen peroxide.

Wild type (wt) BY4741 and trm strains were cultured to log-phase growth (OD600nm = 0.6) and either left untreated (open bars) or exposed to hydrogen peroxide (20 mM for 1 hour, grey-filled bars). Ribonucleoside modifications were identified by direct infusion electrospray ionization mass spectrometry (ESI-MS). Quantitative measurements of 2'-O-methyladenosine (Am, panel A), 2'-O-methyluridine (Um, panel B), 2'-O-methylcytidine (Cm, panel C), and 2'-O-methylguanosine (Gm, panel D) were made using the abundance versus proxy method (AvP), defined as the absolute signal intensity over the sum of the absolute intensities of the canonical bases. Fold changes represent increases or decreases in AvP values relative to wt untreated cells and were calculated using the AvP values from S1 and S2 Tables, with error bars indicating the standard error of the mean change (n = 3).

We detected increases in Um, Cm, and Gm in wild type cells after exposure to hydrogen peroxide. These toxicant-induced increases in Um, Cm, and Gm were attenuated across all 2’-O-ribose trm mutants. Notably, in the cases of trm3, and 13, this lack of induction occurred on a background of higher levels of Um, Cm and Gm, relative to wild type cells. Am was also higher in trm13 mutants. These interesting (and unexpected) results lead us to question whether there is an oxidative stress phenotype in 2’-O-ribose trm mutants prior to exposure. We investigated this possibility by staining cells with the 2’,7’-dichlorofluorescein (DCFDA), a dye that oxidizes in the presence of intracellular reactive oxygen species (ROS), emitting fluorescence that is detected in the “green” channel using flow cytometry. The mean DCFDA intensity was significantly increased in all 2’-O-ribose trm mutants, with the trm3 and trm13 strains showing the most substantial increases compared to wild type cells (Fig 5). These preliminary results support that some redox mechanism(s) is deregulated in the trm mutants and are not indicative of the type of reactive oxygen species elevated, or hydrogen peroxide levels, which will be determined in future.

Fig 5. 2'-O-ribose trm mutants have elevated levels of intracellular reactive oxygen species (ROS).

The indicated trm mutant strains were cultured to log-phase growth (OD600nm = 0.6) and stained with 2',7'-dichlorofluorescin (DCFDA) to measure intracellular ROS. The fluorescence intensity emitted by oxidized DCFDA at 517–527 nm was determined by flow cytometry (≥ 4000 cells per population), and is shown as the mean ± standard deviation (n = 4). Significant differences in mean fluorescence intensities were determined using the t-test: trm mutants versus wild type under similar treatment conditions (**P < 0.01, ***P < 0.001).

In the case of trm7 mutants, 2’-O-ribonucleosides were not induced by exposure to hydrogen peroxide (Fig 4). In fact, in cells treated with hydrogen peroxide, Um, Cm and Gm were decreased, and Am was undetectable. Overall, these results show a complex profile of 2’-O-ribose methylation events in S. cerevisiae exposed to hydrogen peroxide and suggest that some of these modifications act as part of both the oxidative stress response and in ROS maintenance under normal growth conditions. This complexity is further reflected in our global analysis of ribonucleotide modifications that are changed in the 2’-O-ribose trm mutants under both normal growth conditions and in response to hydrogen peroxide treatment (S1 and S2 Tables).

Identification of candidate transcripts influenced by 2’-O-ribose methylation

Considering the oxidative stress sensitivity of the 2'-O-ribose trm mutants, we were interested in identifying transcripts that are translationally regulated by this type of methylation event. Based on previous work, we expect that stress-associated methylation of tRNAs enhances the translation of stress-responsive gene transcripts [40]. If this is true, then genes involved in the stress response will use codons whose translation is influenced by methylated tRNAs, including those methylated at the 2'-O-ribose position. We tested this idea using tRNAPhe(GAA) as a model since it is a biologically relevant target of Trm7, [27, 28] and is methylated at the wobble position (underlined), a site that is known to influence codon selection (reviewed in)[5]. In addition, phenylalanine decoding represents a straightforward "two-choice" decision compared to other degenerate codons since it is decoded by either UUU or UUC, and S. cerevisiae Trm7-modified tRNAPhe(GmAA) is thought to promote cognate UUC base-pairing interactions that favor the translation of UUC over UUU [41].

To identify transcripts that may be influenced by Trm7-mediated tRNAPhe(GmAA) modifications, we took a bioinformatics approach using the gene-specific Codon UTilization (CUT) tool [30]. This tool identified a set of transcripts that use UUC to decode phenylalanine at a higher frequency when compared to all other transcripts of the S. cerevisiae genome. Moreover, these UUC-enriched transcripts correspond to genes that are involved biological processes associated with the oxidative stress response, as well as others that are involved in processes that regulate cell growth and metabolism (Table 1). Interestingly, these transcripts not only use UUC at a higher frequency compared to other transcripts, they also have UUC in duplicate or triplicate codon "runs", which is a rare event considering that there are only 24 reported open reading frames in S. cerevisiae that contain a UUCUUCUUC run, representing only 0.36% of the coding genome for this organism (S3 Table) [30].

Table 1. Transcript open reading frames enriched in UUC codons for phenylalanine decoding.

2'-O-ribose translational targets are oxidative stress-sensitive

Our bioinformatics approach identified transcripts that are potential targets of Trm7-mediated 2’-O-ribose methylation, providing support for the idea that UUC-enriched transcripts rely on 2'-O-ribose methylation to enhance their translation in response to stress. As a first step towards testing this theory, we retrieved S. cerevisiae strains deficient for a subset of UUC-enriched genes (i.e., CRT10, FRE5, HXT2, HIR3, and GNP1) from our library of deletion strain mutants, and assessed colony survival after exposure hydrogen peroxide. We found significant sensitivity, to varying degrees, across all of the UUC-enriched gene mutants investigated thus far (Fig 6). These findings support that UUC-enriched gene transcripts encode proteins that play a functional role in recovering from oxidative stress and point to a potential role for Trm7-mediated regulatory effects at the translational level, which fits into our broader hypothetical model of how 2'-O-ribose methylation contributes to the oxidative stress response (Fig 7).

Fig 6. Colony survival is decreased in UUC-enriched deletion mutants after exposure to oxidative stress-inducing agents.

Wild type (BY4741), crt10, fre5, hxt2, hir3, and gnp1 mutant strains were grown to stationary-phase (i.e., OD600 = 3.0) and exposed to hydrogen peroxide (10 mM) to induce oxidative stress. After 1 hour of exposure, the cultures were serially diluted to 9 x 102 cells per ml, plated (100 μl), and the number of colonies was recorded after growth at 30°C for three days. In the central figure, percent survival is shown relative to untreated wt. The inset shows the magnitude of the decrease in survival (i.e., percent survival untreated minus treated conditions for individual strains). Significant differences in colony formation and survival were determined using a Student t-test: UUC-enriched mutants versus wild type under similar treatment conditions (n = 5, *P < 0.002, **P < 0.001).

Fig 7. A hypothetical model for how 2'-O-ribose tRNA methylation promotes oxidative stress recovery.

In this model, 2'-O-ribose Trms are responsive to oxidative stress exposure by unknown signaling events or pathways as indicated by the question mark. Trms then target various tRNAs for 2'-O-ribose methylation at positions that have previously been implicated in increased tRNA stability, amino acid charging, and enhanced translation of transcripts enriched in certain codons. Possible biological processes that may be involved in oxidative stress recovery via this type of translational regulation were identified at a bioinformatic level. The precise role of Trm-dependent 2'-O-ribose methylation for enhanced decoding of transcripts associated with these biological processes has yet to be determined.


Here we have shown that the deletion of 2’-O-ribose methyltransferase genes in S. cerevisiae leads to sensitivity to oxidative stress-inducing toxicants. The degree of individual 2’-O-ribose trm mutant sensitivity was dependent upon assay endpoint (i.e., cell viability or cell survival to colony formation), and hydrogen peroxide produced the highest degree of oxidative stress sensitivity by colony assay across all trm mutants. Notably, although rotenone significantly increased cell death across all trm mutants, mitochondrial dysfunction may also be a contributing factor to a decrease in viability.

Our analysis of oxidative stress-induced nucleoside modifications in the trm mutants revealed a complex profile of 2’-O-ribose methylation events, raising new questions. For example, why do cells deficient in TRMs 3 and 13 increase overall levels of 2’-O-ribose modified nucleosides while exhibiting no observable growth impairment? Alone, these mutants were not deficient in any single 2’-O-ribose methylation event, arguing for compensatory mechanisms of 2’-O-ribose methylation that are sufficient for growth, but insufficient to overcome oxidative stress. Compensatory mechanisms further suggest an underlying stress phenotype, which included elevated levels of intracellular ROS in the trm mutants. We postulate that to offset the destabilizing effects of this ROS on tRNA molecules, 2’-O-ribose trm mutants undergo widespread increases in 2’-O-ribose methylation. Further research is required to define the molecular mechanisms behind this ROS-associated phenotype.

The trm3 mutant strain showed a high degree of sensitivity across all toxicants relative to other 2’-O-ribose mutants. Trm3 is responsible for the formation of 2’-O-methylguanosine (Gm) at position 18, which occurs in several tRNA species including isotypes of tRNALeu, tRNAHis, tRNATyr, tRNASer, and tRNATrp; in these isotypes, Gm18 is adjacent to guanosine at position 19 [26, 42]. Our modification analysis shows an increase in Gm after exposure to hydrogen peroxide that was absent in the trm3 mutants, raising the possibility that Trm3-mediated Gm18 formation may be a component of the oxidative stress response. A caveat to this interpretation is that our modification data is not positional, and so we cannot attribute exposure-induced Gm solely to the activity of Trm3 at position 18. A likely role for Trm3-mediated Gm modification in response to oxidative stress is to enhance the stability of tRNA molecules after exposure to toxicants that elevate ROS. Gm at position 18 of the D loop interacts with Ψ at position 55 and, together with other D- and TΨ-loop interactions (i.e., G19-C56 and G53-m1A), acts to stabilize the three-dimensional core of the tRNA molecule [11, 24, 25]. A parallel for this exists in thermophilic organisms where 2’-O-ribose methylation and 2-thiolation of t54, acts as a thermal adaptation to increase tRNA stability [2023, 43]. In either environment—oxidative stress or extreme temperature—tRNA molecules would be susceptible to denaturation, particularly in non-duplex regions, such as the D-loop where G18 resides. It follows that Trm3-mediated Gm modification could represent an oxidative stress adaption of protein synthesis.

Trm7 interacts with Trm732 and Trm734 for respective 2’-O-ribose methylations of C32 and N34 to form Cm32, and Gm34 in tRNAPhe, Cm32 and Cm34 for tRNATrp, and ncm5Um for tRNALeu(UAA) [27, 28, 44]. As these Trm7-dependent modifications occur in the anticodon stem loop (ASL), they can influence anticodon: codon interactions [57]. By extension, the oxidative stress sensitivity seen here for the trm7 mutants may be due to impaired codon selection, which negatively impacts the translation of stress-responsive transcripts (modeled in Fig 7). Reports of tRNAPhe genomic sequences with an AAA anticodon are rare, and whether or not these tRNAPheAAA genes are transcribed is not clear [45]. So, eukaryotes seem to rely upon a single anticodon in tRNAPhe, GAA, to decode both UUC (cognate at the wobble) and UUU (non-cognate at the wobble). Thus, Gm methylation as a mechanism for promoting cognate codon recognition could represent a critical mechanism for degenerate codon selection in certain cellular contexts, including oxidative stress.

Several UUC-biased genes were identified here, and their corresponding trm mutants were sensitive to oxidative stress. gnp1 mutants were the most sensitive relative to other UUC-biased mutants—a notable result since GNP1 encodes an amino acid transmembrane transport protein, and trm7 mutants have recently been shown to activate the general amino acid control (GAAC) response pathway [31]. These observations suggest that impaired translation of GNP1 in trm7 mutants is a component of the GAAC response and contributes to the pronounced oxidative stress sensitivity phenotype of these mutants.

Trm13 is responsible 2’-O-ribose methylation of position 4 in at least three species of S. cerevisiae tRNAs: tRNAGly(GCC)-Cm4, tRNAPro-Cm4, and tRNAHis-Am4 [26, 42, 46]. Despite the overall elevated levels of Am in the trm13 mutants, we detected a small but significant attenuation of the Am signal as induced by hydrogen peroxide. Together with the trm13 mutant stress sensitivity phenotype, this suggests that there may be a Trm13 → Am4 component to the oxidative stress response. Position 4 resides within an acceptor stem region that is engaged base-pairing interactions with residue 69 to form a stable duplex region; thus, a role in structural stability is not predicted for 2’-O-methylation at this site [46]. Another possibility is that Trm3-mediated position 4 methylation influences other processes of translation, such as translocation or aminoacylation. Indeed, in E. coli, 2’-O-ribose methylation within the acceptor stem can negatively influence translation [47], and some aminoacyl tRNA synthetases rely on tRNA features within the acceptor stem or variable loop region to determine tRNA identity for charging [4851].

trm44 mutants demonstrated the least amount of oxidative stress-sensitivity relative to the other 2’-O-ribose trm mutants studied herein. Trm44 is responsible for Um 2’-O ribose methylation at position 44 [52], and although U occurs at position 44 in isotypes of tRNACys, tRNATyr, and tRNALeu, to date, the only tRNA species targeted by Trm44 identified in S. cerevisiae is cytoplasmic tRNASer [26, 53, 54]. Attenuated increases in Um modifications in response to hydrogen peroxide treatment were detected in the trm44 mutants, suggesting a Trm44 → Um component to the oxidative stress response. Um44 modification is thought to increase tRNA stability by maximizing base stacking and base interactions that promote the C3’-endo form (preferred for stability in thermophiles) of RNA [55]. Another role for Trm44-mediated Um44 modification could be linked to charging of tRNASer by seryl-tRNA synthetases, which rely on features within the acceptor stem and variable loop regions for recognition [4851]. Thus, both stability and accurate tRNASer charging could be affected in trm44 mutants, producing sensitivity to oxidative stress.

While this study substantiates a role for 2'-O-ribose tRNA methylation in the oxidative stress response, the question of how oxidative stress induces trms to methylate tRNAs remains. At least one eukaryote Trm, human TRM9L, is targeted for serine phosphorylation by the ERK-RSK pathway, as induced by hydrogen peroxide [56]; thus, 2'-O-ribose Trms may be similarly targeted for activating phosphorylation events, either by this or other stress-responsive kinase pathways. This effect could be further augmented by the oxidative inactivation of dual-specificity phosphatases, which dephosphorylate protein phospho-serine -threonine, and -tyrosine, effects that are known to be induced by ROS [57]. It is also possible that some increases in 2'-O-ribose methylation events do not come from an increase in trm activity per se, but are the result of changes in the pools of tRNAs available for trm-specific methylation (e.g., through transcriptional up-regulation or increased turn-over of unmethylated tRNA species). Overall, the toxicants used in this study generate diverse intracellular ROS, capable of damaging tRNAs as well as other biomolecules. The non-helical regions of tRNAs may be particularly susceptible to ROS since they are more likely to undergo spontaneous hydrolysis relative to double-stranded helical regions due to the “in-line” geometry of the phosphate and adjacent 2’-OH moiety, which can act as an attacking nucleophile [58]. This type of geometry does not occur in double-stranded helical regions, which are well-conserved among tRNAs and rarely methylated [58, 59]. Further, methylation of the 2’-OH sugar favors a 3’-endo sugar pucker in the helical region of tRNAs, which prevents the type of in-line geometry that is susceptible to spontaneous hydrolysis [11, 19, 60]. Thus, we propose that oxidative stress-associated 2’-OH ribose methylation represents a dual strategy that both maintains the structural stability of tRNAs and exerts translational effects post-exposure. In some instances, this strategy may involve promoting the translation of stress-responsive transcripts with a codon-bias (e.g., Trm7 → tRNAPhe), while in other instances, it promotes accuracy in charging (e.g., Trm44 → tRNASer). Both situations represent combined epitranscriptomic strategies for oxidative stress recovery.

Supporting information

S1 Fig. TRM expression in wildtype and mutant strains.


S2 Fig. Unchallenged growth of 2’-O-ribose trm mutants.


S1 Table. Post-transcriptional RNA modifications, unchallenged.


S2 Table. Hydrogen peroxide-induced post-transcriptional modifications.


S3 Table. UUC-enriched open reading frames (ORFs).



First we would like to thank all members of the Department of Biology and Chemistry at SUNY Polytechnic Institute for their support in enabling this research. In addition, we are grateful to Dr. E. Phizicky (University of Rochester) for providing an independent trm7 mutant strain with an inducible Trm7 ORF to validate our observations. Also, we thank Dr. T.J. Begley (University at Albany) for providing access to his Open Biosystems deletion strain library. Dr. M. Fasullo provided advice on general techniques and specific protocols for S. cerevisiae growth and transformation, and generously offered his time to critically review this manuscript.


  1. 1. Svensson I, Bjork G, Bjork W, Johansson KE, Johansson A. Evidence for enzymatic methylation in vitro of the ribose moiety of RNA. Biochem Biophys Res Commun. 1968;31(2):216–21. pmid:5656069.
  2. 2. Towns WL, Begley TJ. Transfer RNA methytransferases and their corresponding modifications in budding yeast and humans: activities, predications, and potential roles in human health. DNA Cell Biol. 2012;31(4):434–54. pmid:22191691; PubMed Central PMCID: PMC3322404.
  3. 3. Chan C, Pham P, Dedon PC, Begley TJ. Lifestyle modifications: coordinating the tRNA epitranscriptome with codon bias to adapt translation during stress responses. Genome Biol. 2018;19(1):228. pmid:30587213; PubMed Central PMCID: PMC6307160.
  4. 4. Agris PF, Narendran A, Sarachan K, Vare VYP, Eruysal E. The Importance of Being Modified: The Role of RNA Modifications in Translational Fidelity. Enzymes. 2017;41:1–50. pmid:28601219.
  5. 5. Agris PF. Bringing order to translation: the contributions of transfer RNA anticodon-domain modifications. EMBO Rep. 2008;9(7):629–35. pmid:18552770; PubMed Central PMCID: PMC2475317.
  6. 6. Capra JD, Peterkofsky A. Effect on in vitro methylation on the chromatographic and coding properties of methyl-deficient leucine transfer RNA. J Mol Biol. 1968;33(3):591–607. pmid:4882614.
  7. 7. Karlsborn T, Tukenmez H, Mahmud AK, Xu F, Xu H, Bystrom AS. Elongator, a conserved complex required for wobble uridine modifications in eukaryotes. RNA Biol. 2014;11(12):1519–28. pmid:25607684; PubMed Central PMCID: PMC4615193.
  8. 8. Shugart L, Chastain BH, Novelli GD, Stulberg MP. Restoration of aminoacylation activity of undermethylated transfer RNA by in vitro methylation. Biochem Biophys Res Commun. 1968;31(3):404–9. pmid:4871328.
  9. 9. Gefter ML, Russell RL. Role modifications in tyrosine transfer RNA: a modified base affecting ribosome binding. J Mol Biol. 1969;39(1):145–57. pmid:4938812.
  10. 10. Phizicky EM, Hopper AK. tRNA biology charges to the front. Genes Dev. 2010;24(17):1832–60. pmid:20810645; PubMed Central PMCID: PMC2932967.
  11. 11. Motorin Y, Helm M. tRNA stabilization by modified nucleotides. Biochemistry. 2010;49(24):4934–44. pmid:20459084.
  12. 12. Alexandrov A, Chernyakov I, Gu W, Hiley SL, Hughes TR, Grayhack EJ, et al. Rapid tRNA decay can result from lack of nonessential modifications. Mol Cell. 2006;21(1):87–96. pmid:16387656.
  13. 13. Begley U, Dyavaiah M, Patil A, Rooney JP, DiRenzo D, Young CM, et al. Trm9-catalyzed tRNA modifications link translation to the DNA damage response. Mol Cell. 2007;28(5):860–70. pmid:18082610; PubMed Central PMCID: PMC2211415.
  14. 14. Fu D, Brophy JA, Chan CT, Atmore KA, Begley U, Paules RS, et al. Human AlkB homolog ABH8 Is a tRNA methyltransferase required for wobble uridine modification and DNA damage survival. Mol Cell Biol. 2010;30(10):2449–59. pmid:20308323; PubMed Central PMCID: PMC2863699.
  15. 15. Chan CT, Pang YL, Deng W, Babu IR, Dyavaiah M, Begley TJ, et al. Reprogramming of tRNA modifications controls the oxidative stress response by codon-biased translation of proteins. Nat Commun. 2012;3:937. pmid:22760636; PubMed Central PMCID: PMC3535174.
  16. 16. Endres L, Begley U, Clark R, Gu C, Dziergowska A, Malkiewicz A, et al. Alkbh8 Regulates Selenocysteine-Protein Expression to Protect against Reactive Oxygen Species Damage. PLoS One. 2015;10(7):e0131335. pmid:26147969; PubMed Central PMCID: PMC4492958.
  17. 17. Chan CT, Dyavaiah M, DeMott MS, Taghizadeh K, Dedon PC, Begley TJ. A quantitative systems approach reveals dynamic control of tRNA modifications during cellular stress. PLoS Genet. 2010;6(12):e1001247. pmid:21187895; PubMed Central PMCID: PMC3002981.
  18. 18. Su D, Chan CT, Gu C, Lim KS, Chionh YH, McBee ME, et al. Quantitative analysis of ribonucleoside modifications in tRNA by HPLC-coupled mass spectrometry. Nat Protoc. 2014;9(4):828–41. pmid:24625781; PubMed Central PMCID: PMC4313537.
  19. 19. Davis DR. Biophysical and Conformational Properties of Modified Nucleosides in RNA (Nuclear Magnetic Resonance Studies). In: Grosjean R. Benne H, editor. Modification and Editing of RNA. Washington DC: American Society for Microbiology; 1998. p. 85–102.
  20. 20. Edmonds CG, Crain PF, Gupta R, Hashizume T, Hocart CH, Kowalak JA, et al. Posttranscriptional modification of tRNA in thermophilic archaea (Archaebacteria). J Bacteriol. 1991;173(10):3138–48. pmid:1708763; PubMed Central PMCID: PMC207908.
  21. 21. Kowalak JA, Dalluge JJ, McCloskey JA, Stetter KO. The role of posttranscriptional modification in stabilization of transfer RNA from hyperthermophiles. Biochemistry. 1994;33(25):7869–76. pmid:7516708.
  22. 22. Grosjean H, Gupta R., Maxwell S. Modified nucleotides in archaeal RNAs. In: Blum P, editor. Archaea, New Models for Prokaryotic Biology: Norwich Horizon Press; 2008. p. 164–96.
  23. 23. Agris PF, Koh H, Soll D. The effect of growth temperatures on the in vivo ribose methylation of Bacillus stearothermophilus transfer RNA. Arch Biochem Biophys. 1973;154(1):277–82. pmid:4689778.
  24. 24. Ladner JE, Jack A, Robertus JD, Brown RS, Rhodes D, Clark BF, et al. Structure of yeast phenylalanine transfer RNA at 2.5 A resolution. Proc Natl Acad Sci U S A. 1975;72(11):4414–8. pmid:1105583; PubMed Central PMCID: PMC388732.
  25. 25. Grosjean H. Nucleic Acids Are Not Boring Long Polymers of Only Four Types of Nucleotides: A Guided Tour. In: Grosjean H, editor. DNA and RNA Modification Enzymes: Structure, Mechanism, Function and Evolution. Austin, Texas: Landes Bioscience; 2009. p. 1–18.
  26. 26. Boccaletto P, Machnicka MA, Purta E, Piątkowski P, Bagiński B, Wirecki TK, et al. MODOMICS: a database of RNA modification pathways. 2017 update. Nucleic Acids Research. 2017;46(D1):D303–D7. pmid:29106616
  27. 27. Pintard L, Lecointe F, Bujnicki JM, Bonnerot C, Grosjean H, Lapeyre B. Trm7p catalyses the formation of two 2'-O-methylriboses in yeast tRNA anticodon loop. EMBO J. 2002;21(7):1811–20. pmid:11927565; PubMed Central PMCID: PMC125368.
  28. 28. Guy MP, Podyma BM, Preston MA, Shaheen HH, Krivos KL, Limbach PA, et al. Yeast Trm7 interacts with distinct proteins for critical modifications of the tRNAPhe anticodon loop. RNA. 2012;18(10):1921–33. pmid:22912484; PubMed Central PMCID: PMC3446714.
  29. 29. Guy MP, Phizicky EM. Conservation of an intricate circuit for crucial modifications of the tRNAPhe anticodon loop in eukaryotes. RNA. 2015;21(1):61–74. pmid:25404562; PubMed Central PMCID: PMC4274638.
  30. 30. Doyle F, Leonardi A, Endres L, Tenenbaum SA, Dedon PC, Begley TJ. Gene- and genome-based analysis of significant codon patterns in yeast, rat and mice genomes with the CUT Codon UTilization tool. Methods. 2016;107:98–109. pmid:27245397; PubMed Central PMCID: PMC5014648.
  31. 31. Han L, Guy MP, Kon Y, Phizicky EM. Lack of 2'-O-methylation in the tRNA anticodon loop of two phylogenetically distant yeast species activates the general amino acid control pathway. PLoS Genet. 2018;14(3):e1007288. pmid:29596413; PubMed Central PMCID: PMC5892943.
  32. 32. Winzeler EA, Shoemaker DD, Astromoff A, Liang H, Anderson K, Andre B, et al. Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science. 1999;285(5429):901–6. pmid:10436161.
  33. 33. Gelperin DM, White MA, Wilkinson ML, Kon Y, Kung LA, Wise KJ, et al. Biochemical and genetic analysis of the yeast proteome with a movable ORF collection. Genes Dev. 2005;19(23):2816–26. pmid:16322557; PubMed Central PMCID: PMC1315389.
  34. 34. Tripp JD, Lilley JL, Wood WN, Lewis LK. Enhancement of plasmid DNA transformation efficiencies in early stationary-phase yeast cell cultures. Yeast. 2013;30(5):191–200. pmid:23483586; PubMed Central PMCID: PMC3656150.
  35. 35. Scott JH, Schekman R. Lyticase: endoglucanase and protease activities that act together in yeast cell lysis. J Bacteriol. 1980;142(2):414–23. pmid:6991473; PubMed Central PMCID: PMC293993.
  36. 36. Rose RE, Quinn R, Sayre JL, Fabris D. Profiling ribonucleotide modifications at full-transcriptome level: a step toward MS-based epitranscriptomics. RNA. 2015;21(7):1361–74. pmid:25995446; PubMed Central PMCID: PMC4478354.
  37. 37. Rose RE, Pazos MA 2nd, Curcio MJ, Fabris D. Global Epitranscriptomics Profiling of RNA Post-Transcriptional Modifications as an Effective Tool for Investigating the Epitranscriptomics of Stress Response. Mol Cell Proteomics. 2016;15(3):932–44. pmid:26733207; PubMed Central PMCID: PMC4813711.
  38. 38. McIntyre W, Netzband R, Bonenfant G, Biegel JM, Miller C, Fuchs G, et al. Positive-sense RNA viruses reveal the complexity and dynamics of the cellular and viral epitranscriptomes during infection. Nucleic Acids Res. 2018;46(11):5776–91. pmid:29373715; PubMed Central PMCID: PMC6009648.
  39. 39. Cherry JM, Hong EL, Amundsen C, Balakrishnan R, Binkley G, Chan ET, et al. Saccharomyces Genome Database: the genomics resource of budding yeast. Nucleic Acids Res. 2012;40(Database issue):D700–5. pmid:22110037; PubMed Central PMCID: PMC3245034.
  40. 40. Endres L, Dedon PC, Begley TJ. Codon-biased translation can be regulated by wobble-base tRNA modification systems during cellular stress responses. RNA Biol. 2015;12(6):603–14. pmid:25892531; PubMed Central PMCID: PMC4615639.
  41. 41. Ogle JM, Brodersen DE, Clemons WM Jr., Tarry MJ, Carter AP, Ramakrishnan V. Recognition of cognate transfer RNA by the 30S ribosomal subunit. Science. 2001;292(5518):897–902. pmid:11340196.
  42. 42. Sprinzl M, Horn C, Brown M, Ioudovitch A, Steinberg S. Compilation of tRNA sequences and sequences of tRNA genes. Nucleic Acids Res. 1998;26(1):148–53. pmid:9399820; PubMed Central PMCID: PMC147216.
  43. 43. Shigi N, Sakaguchi Y, Asai S, Suzuki T, Watanabe K. Common thiolation mechanism in the biosynthesis of tRNA thiouridine and sulphur-containing cofactors. EMBO J. 2008;27(24):3267–78. pmid:19037260; PubMed Central PMCID: PMC2609741.
  44. 44. Juhling F, Morl M, Hartmann RK, Sprinzl M, Stadler PF, Putz J. tRNAdb 2009: compilation of tRNA sequences and tRNA genes. Nucleic Acids Res. 2009;37(Database issue):D159–62. pmid:18957446; PubMed Central PMCID: PMC2686557.
  45. 45. Chan PP, Lowe TM. GtRNAdb 2.0: an expanded database of transfer RNA genes identified in complete and draft genomes. Nucleic Acids Res. 2016;44(D1):D184–9. pmid:26673694; PubMed Central PMCID: PMC4702915.
  46. 46. Wilkinson ML, Crary SM, Jackman JE, Grayhack EJ, Phizicky EM. The 2'-O-methyltransferase responsible for modification of yeast tRNA at position 4. RNA. 2007;13(3):404–13. pmid:17242307; PubMed Central PMCID: PMC1800514.
  47. 47. Feinberg JS, Joseph S. Identification of molecular interactions between P-site tRNA and the ribosome essential for translocation. Proc Natl Acad Sci U S A. 2001;98(20):11120–5. pmid:11562497; PubMed Central PMCID: PMC58693.
  48. 48. Giege R, Eriani G. Transfer RNA Recognition and Aminoacylation by Synthetases. eLS. Chichester: John Wiley & Sons; 2014. p. 1–18.
  49. 49. McClain WH, Foss K. Changing the identity of a tRNA by introducing a G-U wobble pair near the 3' acceptor end. Science. 1988;240(4853):793–6. pmid:2452483.
  50. 50. Hou YM, Schimmel P. A simple structural feature is a major determinant of the identity of a transfer RNA. Nature. 1988;333(6169):140–5. pmid:3285220.
  51. 51. Berg MD, Genereaux J, Zhu Y, Mian S, Gloor GB, Brandl CJ. Acceptor Stem Differences Contribute to Species-Specific Use of Yeast and Human tRNA(Ser). Genes (Basel). 2018;9(12). pmid:30544642; PubMed Central PMCID: PMC6316282.
  52. 52. Kotelawala L, Grayhack EJ, Phizicky EM. Identification of yeast tRNA Um(44) 2'-O-methyltransferase (Trm44) and demonstration of a Trm44 role in sustaining levels of specific tRNA(Ser) species. RNA. 2008;14(1):158–69. pmid:18025252; PubMed Central PMCID: PMC2151035.
  53. 53. Zachau HG, Dutting D, Feldmann H. The structures of two serine transfer ribonucleic acids. Hoppe Seylers Z Physiol Chem. 1966;347(4):212–35. pmid:5991670.
  54. 54. Olson MV, Page GS, Sentenac A, Piper PW, Worthington M, Weiss RB, et al. Only one of two closely related yeast suppressor tRNA genes contains an intervening sequence. Nature. 1981;291(5815):464–9. pmid:6262655.
  55. 55. Kawai G, Yamamoto Y, Kamimura T, Masegi T, Sekine M, Hata T, et al. Conformational rigidity of specific pyrimidine residues in tRNA arises from posttranscriptional modifications that enhance steric interaction between the base and the 2'-hydroxyl group. Biochemistry. 1992;31(4):1040–6. pmid:1310418.
  56. 56. Gu C, Ramos J, Begley U, Dedon PC, Fu D, Begley TJ. Phosphorylation of human TRM9L integrates multiple stress-signaling pathways for tumor growth suppression. Sci Adv. 2018;4(7):eaas9184. pmid:30009260; PubMed Central PMCID: PMC6040840.
  57. 57. Ostman A, Frijhoff J, Sandin A, Bohmer FD. Regulation of protein tyrosine phosphatases by reversible oxidation. J Biochem. 2011;150(4):345–56. pmid:21856739.
  58. 58. Wakeman CA, Winkler WC. Analysis of the RNA backbone: structural analysis of riboswitches by in-line probing and selective 2'-hydroxyl acylation and primer extension. Methods Mol Biol. 2009;540:173–91. pmid:19381560.
  59. 59. Machnicka MA, Olchowik A, Grosjean H, Bujnicki JM. Distribution and frequencies of post-transcriptional modifications in tRNAs. RNA Biol. 2014;11(12):1619–29. pmid:25611331; PubMed Central PMCID: PMC4615829.
  60. 60. Yokoyama S, Watanabe K, Miyazawa T. Dynamic structures and functions of transfer ribonucleic acids from extreme thermophiles. Adv Biophys. 1987;23:115–47. pmid:2449804.