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The epitranscriptomic writer ALKBH8 drives tolerance and protects mouse lungs from the environmental pollutant naphthalene
research-article
Author(s):
Andrea Leonardi
a ,
Nataliia Kovalchuk
b ,
Lei Yin
b ,
Lauren Endres
c
,
d ,
Sara Evke
e ,
Steven Nevins
e ,
Samuel Martin
f ,
Peter C. Dedon
g
,
h ,
J. Andres Melendez
d
,
e ,
Laura Van Winkle
i ,
Qing-Yu Zhang
b ,
Xinxin Ding
b ,
Thomas J. Begley
d
,
f
Publication date (Electronic, pub):
17 April 2020
Publication date (Electronic, collection):
2020
Journal:
Epigenetics
Publisher:
Taylor & Francis
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ABSTRACT
The epitranscriptomic writer Alkylation Repair Homolog 8 (ALKBH8) is a transfer RNA (tRNA) methyltransferase that modifies the wobble uridine of selenocysteine tRNA to promote the specialized translation of selenoproteins. Using Alkbh8 deficient ( Alkbh8 def) mice, we have investigated the importance of epitranscriptomic systems in the response to naphthalene, an abundant polycyclic aromatic hydrocarbon and environmental toxicant. We performed basal lung analysis and naphthalene exposure studies using wild type (WT), Alkbh8 de f and Cyp2abfgs-null mice, the latter of which lack the cytochrome P450 enzymes required for naphthalene bioactivation. Under basal conditions, lungs from Alkbh8 def mice have increased markers of oxidative stress and decreased thioredoxin reductase protein levels, and have reprogrammed gene expression to differentially regulate stress response transcripts. Alkbh8 def mice are more sensitive to naphthalene induced death than WT, showing higher susceptibility to lung damage at the cellular and molecular levels. Further, WT mice develop a tolerance to naphthalene after 3 days, defined as resistance to a high challenging dose after repeated exposures, which is absent in Alkbh8 def mice. We conclude that the epitranscriptomic writer ALKBH8 plays a protective role against naphthalene-induced lung dysfunction and promotes naphthalene tolerance. Our work provides an early example of how epitranscriptomic systems can regulate the response to environmental stress in vivo.
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Most cited references78
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The Nrf2-antioxidant response element signaling pathway and its activation by oxidative stress.
Truyen Nguyen, Paul Nioi, Cecil B. Pickett (2009)
A major mechanism in the cellular defense against oxidative or electrophilic stress is activation of the Nrf2-antioxidant response element signaling pathway, which controls the expression of genes whose protein products are involved in the detoxication and elimination of reactive oxidants and electrophilic agents through conjugative reactions and by enhancing cellular antioxidant capacity. At the molecular level, however, the regulatory mechanisms involved in mediating Nrf2 activation are not fully understood. It is well established that Nrf2 activity is controlled, in part, by the cytosolic protein Keap1, but the nature of this pathway and the mechanisms by which Keap1 acts to repress Nrf2 activity remain to be fully characterized and are the topics of discussion in this minireview. In addition, a possible role of the Nrf2-antioxidant response element transcriptional pathway in neuroprotection will also be discussed.
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Reprogramming of tRNA modifications controls the oxidative stress response by codon-biased translation of proteins
Clement Chan, Yan Ling Joy Pang, Wenjun Deng … (2012)
Selective translation of survival proteins is an important facet of the cellular stress response. We recently demonstrated that this translational control involves a stress-specific reprogramming of modified ribonucleosides in tRNA. Here we report the discovery of a step-wise translational control mechanism responsible for survival following oxidative stress. In yeast exposed to hydrogen peroxide, there is a Trm4 methyltransferase-dependent increase in the proportion of tRNALEU( C AA) containing m5C at the wobble position, which causes selective translation of mRNA from genes enriched in the TTG codon. Of these genes, oxidative stress increases protein expression from the TTG-enriched ribosomal protein gene RPL22A, but not its unenriched paralog. Loss of either TRM4 or RPL22A confers hypersensitivity to oxidative stress. Proteomic analysis reveals that oxidative stress causes a significant translational bias toward proteins coded by TTG-enriched genes. These results point to stress-induced reprogramming of tRNA modifications and consequential reprogramming of ribosomes in translational control of cell survival.
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A Quantitative Systems Approach Reveals Dynamic Control of tRNA Modifications during Cellular Stress
Clement T. Y. Chan, Madhu Dyavaiah, Michael DeMott … (2011)
Introduction The complexity of the transfer RNA (tRNA) system confers great potential for its use in cellular regulatory programs. There are hundreds of tRNA-encoding genes in S. cerevisiae and human genomes, with extensive post-transcriptional processing that includes enzyme-mediated ribonucleoside modifications [1]. Considering both tRNA and ribosomal RNA (rRNA), there are more than 100 known ribonucleoside modifications across all organisms in addition to the canonical adenosine, guanosine, cytidine and uridine [2], [3]. In general, tRNA modifications enhance ribosome binding affinity, reduce misreading and modulate frame-shifting, all of which affect the rate and fidelity of translation [4]–[7]. However, information about the higher-level biological function of ribonucleoside modifications has only recently begun to emerge. We have approached this problem with a systems-level analysis of changes in the spectrum of ribonucleosides in tRNA as a function of cell stress, which has revealed novel insights into the biosynthesis of tRNA modifications and their role in cellular responses. Emerging evidence points to a critical role for tRNA and rRNA modifications in cellular responses to stimuli, with evidence for a role in tRNA stability [8], [9], cellular stress responses [10]–[12] and cell growth [13]. We recently used high-throughput screens and targeted studies to show that the tRNA methyltransferase 9 (Trm9) modulates the toxicity of methylmethanesulfonate (MMS) in S. cerevisiae [11], [14]. This is similar to the observed role of Trm9 in modulating the toxicity of ionizing radiation [15] and of Trm4 in promoting viability after methylation damage [14], [16]. Trm9 catalyzes the methyl esterification of the uracil-based cm5U and cm5s2U to mcm5U and mcm5s2U, respectively, at the wobble bases of tRNAUCU-ARG and tRNACCU-GLU, among others [17]. These wobble base modifications in the tRNA enhance binding of the anticodon with specific codons in mixed codon boxes [18]. Codon-specific reporter assays and genome-wide searches revealed that Trm9-catalyzed tRNA modifications enhanced the translation of AGA- and GAA-rich transcripts that functionally mapped to processes associated with protein synthesis, metabolism and stress signalling [11]. The resulting model proposes that specific codons will be more efficiently translated by anticodons containing the Trm9-modified nucleoside and that tRNA modifications can dynamically change in response to stress. To assess the dynamic nature of tRNA modifications proposed by this model, we developed a systems-oriented approach using liquid chromatography-coupled, tandem quadrupole mass spectrometry (LC-MS/MS) to quantify the full set of tRNA modifications in an organism. Mass spectrometry-based methods have recently emerged as powerful tools for identifying and quantifying RNA modifications [19], [20]. We applied such an approach to quantify changes in the spectrum of tRNA modifications in yeast exposed to four mechanistically dissimilar toxicants. Multivariate statistical analysis of the data reveals dynamic shifts in the population of RNA modifications as part of the response to damage, with signature changes for each agent and dose. Further, analysis of yeast mutants lacking specific modification enzymes revealed novel biosynthetic pathways and compensatory or cooperative shifts in the levels of other modifications. Results/Discussion Development of an LC-MS/MS method to quantify modified ribonucleosides As shown in Figure 1, we developed an LC-MS/MS method capable of quantifying 23 of the ∼25 known ribonucleoside modifications in cytoplasmic tRNA in S. cerevisiae [2], [3]. The method begins with isolation of small RNA species ( 40% in P2 and NaAsO2 contributing 53% in P3. The scores plots (Figure 3A, 3C) clearly distinguish the four agents, with H2O2-induced changes as the major determinant of P1 and with MMS, NaOCl and NaAsO2 distinguished best in P2. While H2O2 and NaOCl are negatively correlated in P1, they are more closely grouped in P2 and P3, which suggests that the changes in tRNA modifications reflect both common and unique facets of the toxic mechanism of each agent. For example, H2O2 and NaOCl are both oxidizing agents, but H2O2 generates hydroxyl radicals by Fenton chemistry while the protonated form of NaOCl yields hydroxyl radicals, chloramines and singlet oxygen [26]–[29]. Similarly, MMS and NaAsO2 are negatively correlated in P3 and more positively correlated in P2, with the latter consistent with recent evidence for alkylation-like adduction of arsenic to DNA and proteins following its metabolism [30], [31]. This would also explain the negative correlation of NaAsO2 and H2O2 in P1, while the recognized oxidative stress caused by arsenite [32] is consistent with a positive correlation between NaAsO2 and H2O2 in P2. 10.1371/journal.pgen.1001247.g003 Figure 3 Principal component analysis (PCA) of changes in the levels of tRNA modifications caused by exposure to MMS, H2O2, NaOCl, and NaAsO2. Toxicant-induced changes in the relative quantities of 23 tRNA ribonucleoside modifications (Table S2) were subjected to PCA following mean centering and normalization of the fold-change data. Both PCA (Figure 3B, 3D) and cluster analysis (Figure 2) revealed that m5C, m2 2G, Cm and t6A are major features of the H2O2 response, while m1A, m3C and m7G were associated with MMS. Increases in Gm, Um, I and Am were responsible for the variance induced by NaOCl, which is consistent with the inversely related doses and levels for Am and Um observed in cluster analysis. NaAsO2 was poorly distinguished in P2, with only m2G accounting for variance only at the highest concentrations (Figure 2). tRNA modification biosynthetic pathways are critical to the stress response The observation of toxicant- and dose-dependent changes in the levels of the 23 tRNA modifications is consistent with a model in which cells respond to toxicant exposure by modifying tRNA structure to enhance the synthesis of proteins critical to cell survival, as has been proposed in our earlier work with yeast exposure to MMS [11]. In this case, the conversion of cm5U to mcm5U by Trm9 was found to be critical for surviving MMS exposure [11]. To define the roles of specific tRNA modifications in the toxicant response, cytotoxicity phenotypic analyses were performed with yeast mutants lacking each of 13 trm tRNA methyltransferase genes and 3 other types of RNA modification biosynthetic genes. As shown in Figure 4, heightened sensitivity to H2O2 was observed in mutants lacking Trm4 and Trm7, which catalyze formation of two modifications elevated by H2O2 exposure: m5C and Cm, respectively [33], [34]. The simple explanation is that the increase in a specific tRNA modification is needed to promote an efficient stress response. However, m2 2G was also elevated by H2O2 (Figure 2, Figure 3), yet loss of an enzyme involved in its biosynthesis, Trm1 [35], [36], did not confer H2O2 sensitivity (Figure 4). This behavior draws a comparison to mRNA, as it has been reported that many of the transcripts induced in response to a stress are not essential for viability during a challenge from that stress [37], [38]. MMS sensitivity was identified in trm1, trm4 and trm9 mutants, the latter as shown previously [11], whose corresponding proteins synthesize m2 2G, m5C and mcm5U/mcm5s2U, respectively. However, these modifications were not strongly associated with MMS exposure in PCA (Figure 2, Figure 3). Somewhat surprisingly, loss of Trm1, Trm4, Trm7 and Trm9 conferred NaAsO2 sensitivity. These methyltransferases are responsible for m2 2G, m5C, m1G (position 37) and mcm5u/mcm5s2U, respectively, of which only m2G was found to vary significantly in PCA (Figure 3). For NaOCl, only trm4 was sensitive to exposure and the m5C product of Trm4 was not associated with NaOCl exposure (Figure 3). Again, this behavior parallels that of mRNA transcripts the levels of which do not change after exposure but that encode proteins important for viability after exposure [37], [38]. 10.1371/journal.pgen.1001247.g004 Figure 4 Phenotypic analysis of cytotoxicity induced by MMS, NaOCl, H2O2, and NaAsO2 in yeast mutants lacking trm tRNA methyltransferase and other modification genes. Data represent mean ± SD for three biological replicates. Asterisks denote values statistically different from unexposed controls by Student's t-test, p 1.5-fold increase in m3C, mcm5U, m1G, m2G, t6A, mcm5s2U and m2 2G (Figure 5), which raises the possibility that Trm82 itself or m7G inhibits other tRNA modifying enzymes. With the caveat of possible increases in tRNA copy number, the ∼50% increase in these modifications suggests a pool of unmodified tRNA molecules, an observation supported by increases in m3C after exposure to MMS, mcm5U after exposure to NaOCl, and both t6A and m2 2G after exposure to H2O2 (Figure 2, Figure 3). 10.1371/journal.pgen.1001247.g005 Figure 5 Cluster analysis visualization of changes in the relative levels of tRNA ribonucleoside modifications in mutants lacking ribonucleoside-modifying enzymes. The ratios of ribonucleoside levels from Table S5 were subjected to hierarchical cluster analysis. Red – increases; green – decreases. The top-left color bar indicates the range of fold-change values. Cooperativity could also explain the case in which the level of a modification changes significantly following exposure yet the mutant strain is not sensitive to the exposure. For example, loss of trm1 did not confer sensitivity to H2O2 but its product, m2 2G, rose significantly with H2O2 exposure (Figure 2, Figure 3, Figure 4). The stress-induced change in m2 2G may be a response to a change occurring with another modification for which the mutant strain might be sensitive to the exposure. In support of this argument, m5C modifications increase along with m2 2G after H2O2 exposure and deficiencies in the m5C-producing methyltransferase Trm4 confer sensitivity to H2O2. Wohlgamuth-Benedum et al. have also demonstrated such cooperativity among RNA modifications in their observation of the negative regulation of wobble position C-to-U editing by thiolation of a U at position 33 outside the anticodon in T. brucei [39]. Finally, there is the case in which a modification decreases with exposure to a stressor and a deficiency in the enzyme responsible for that modification confers sensitivity, as in the case of m5C, trm4 and NaOCl (Figure 2, Figure 3, Figure 4). The population level of m5C may decrease with NaOCl exposure in spite of a protective increase in the level of m5C at some critical tRNA location. This may reflect a decrease in the transcription of tRNA substrates of Trm4 or the targeted degradation of specific tRNA species. It is important to note that biosynthetic redundancy, as in the case of Gm with Trm3 and Trm7, could mask any major changes in tRNA modification levels that are associated with mutational loss of one enzyme (Figure 5), yet loss of one of the redundant enzymes can induce sensitivity, such as the case of H2O2 and trm7 (Figure 2, Figure 3, Figure 4). These observations lead to many questions that obviously require more mechanistic study to define the precise role of tRNA modifications in cellular responses to stress. One consistent feature that arose from our studies of modifications affected by or protecting against toxicant exposure was the frequent involvement of the wobble position, 34 (Tables S4, S6). The correlation between the wobble modification and the importance of a corresponding enzyme after toxicant exposure is not surprising in light of recent observations of the critical role played by these modifications and anticodon loop ribonucleosides in translational fidelity and efficiency [4]. Controlled alteration of ribonucleoside structure at position 34, and that at the conserved purine at position 37, is proposed to allow reading of degenerate codons by modulating the structure of the anticodon domain to facilitate correct codon binding [4]. As the most frequently modified ribonucleosides, positions 34 and 37 also have the largest variety of modifications [40], [41], so it is reasonable that they would be extensively involved in translational control of the survival response. This is also consistent with our previous observation that mcm5U at the wobble position was critical to the translation of key protein synthesis and DNA damage response genes [11]. Perhaps more interesting is a potential role for putative non-anticodon loop ribonucleoside modifications in the survival response. For example, Trm44 is the 2′-O-methyltransferase in yeast responsible for formation of 2′-O-methyl-U (Um), which occurs only at position 44 in yeast tRNA [42], [43]. Loss of Trm44 conferred sensitivity to NaAsO2 exposure. This observation suggests three possibilities: (1) that Trm44 synthesizes or influences the synthesis of modifications at other positions in tRNA; (2) that Um occurs in positions other than 44 (e.g., anticodon loop); or (3) that Um(44) plays a role in modulating translation in response to NaAsO2 exposure. Another example involves Trm1 and m2 2G at position 26. Current evidence suggests that m2 2G occurs only at position 26 in yeast tRNA [43] and that Trm1 is the methyltransferase responsible for its formation [44]. The fact that loss of Trm1 conferred sensitivity to MMS and NaAsO2 exposure and that H2O2 exposure increased the level of m2 2G again suggest the three possibilities analogous to those for Trm44 and Um. Similar arguments can be made for Trm3 and Gm at position 18 with NaOCl exposure, for Trm11 and m2G at position 10 with NaOCl and NaAsO2 exposure, and for Trm8/82 and m7G at position 46 with MMS exposure. All of these observations point to participation of wobble and non-wobble RNA modifications in a complex and dynamic network of translational mechanisms in cellular responses. This expands the repertoire of translational control mechanisms, which includes recent discoveries about the effect of ribonucleoside modifications on tRNA stability [8], [9]. In this model, cell stress leads to rapid degradation of specific tRNAs and subsequent effects on translational efficiency. Another similar stress response involves cleavage of cytoplasmic transfer RNAs by ribonucleases released during the stress [10]. One consequence of these degradation pathways would be to decrease the amount of modified ribonucleoside detected in our assay, which may explain some of our observations with the toxicant stresses. Our approach to quantifying tRNA modifications provides information only about population-level changes, so the observed changes could result from modification of existing tRNA molecules or changes in the number of tRNA copies. Of particular importance here is the observation by Phizicky and coworkers that loss of m7G at position 46 leads to degradation of specific tRNAs [9], which suggests that our observation of changes in the levels of RNA modifications could be amplified by both reduction in the activity of modifying enzymes and by tRNA degradation. On the other hand, one argument against large increases in tRNA copy number arises from recent observations of repressed tRNA transcription during S-phase and, of direct relevance to the present studies, during replication stress induced by MMS, hydroxyurea and likely other toxicants [45]. Finally, our findings may also parallel recent work on tRNA charging. Reactive oxygen species have been implicated as a methionine misacylation trigger and modification status could help promote these programmed changes to the genetic code [12]. As we are beginning to appreciate the precision and coordinated nature by which cells mount a regulated stress-response, it is most likely the observed changes in tRNA modification levels promote multiple biological responses. Novel biosynthetic pathways for tRNA modifications As recognized by several groups [19], [20], the LC-MS/MS platform facilitates definition of biosynthetic pathways for RNA modifications. This is illustrated in Table S5, which contains ratios of the basal levels of tRNA modifications in yeast mutants lacking various tRNA modification enzymes compared to wild type yeast, and in a heat map visual depiction of these ratios in Figure 5. These data corroborate known substrate/enzyme pairs [43] and further demonstrate the highly quantitative nature of our approach. For example, the level of m1I drops to nearly undetectable levels with loss of Tad1, the adenosine deaminase producing the inosine precursor to m1I [46]. That a diploid heterozygous mutant of trm5, the product of which catalyzes N-methylation of I [47], caused a ∼40% reduction in total m1I attests to the accuracy of our assay and demonstrate that gene dosage effects alter the level of tRNA modification. A similar ∼50% reduction in yW occurred in the trm5 mutant due to the absence of the m1G(37) precursor to yW [47], while complete loss of Trm12, which methylates the 4-demethylwyosine precursor of yW, made yW undetectable. Other pathways critical to yW are apparent in the smaller decreases in yW (0.3– to 0.5-fold) occurred in cells deficient in other enzymes (Trm8, Trm82, Tad1, Mod5, Tan1, Trm11, Trm5; Figure 5, Table S5). The data in Figure 5 also reveal several novel observations. Pintard et al. observed that Trm7 catalyzes 2′-O-methylation of G and C nucleosides at positions 32 and 34, but they could not detect the ncm5Um product of 2′-O-methylation of ncm5U [34]. While we could only tentatively identify ncm5Um, we observed a quantifiable signal for a species with the correct molecular transition for ncm5Um and observed that loss of Trm7 led to a lowering of putative ncm5Um to undetectable levels (Figure 5, Table S5). This supports their prediction that Trm7 catalyzes formation of ncm5Um in yeast. Another example involves the formation of Um. While Trm44 catalyzes synthesis of Um at position 44 in tRNA(ser) [42], analysis of trm mutants in Figure 5 and Table S5 suggests a redundancy in methyltransferase activity capable of 2′-O-methylation of U(44), including Trm7, which methylates U at positions 32 and 34 [34], and Trm13 methylation of C and A at position 4 in several yeast tRNAs. Cells lacking Trm44, Trm7 or Trm13 have 53%, 50% and 76% of wild type levels of Um, respectively. More striking evidence for this redundancy arises in correlation analysis that revealed a strong covariance in the levels of tRNA modifications in cells lacking either Trm 44 or Trm 13 (Table S7; C = 0.87). This correlation ranks second highest in our analysis behind the two subunits of the m7G methyltransferase (Trm8 and Trm82; C = 0.95), which suggests possible functional redundancy for Trm44 and Trm13, with broader substrate specificities for either or both enzymes. In summary, a quantitative bioanalytical approach to the study of tRNA modifications has revealed several novel biosynthetic pathways for RNA modifications and has led to the discovery of signature changes in the spectrum of tRNA modifications in the damage response to different toxicant exposures. The results support a general model of dynamic control of tRNA modifications in cellular response pathways and add to the growing repertoire of mechanisms controlling translational responses in cells [8]–[10], [13]. Further, these cellular response mechanisms almost certainly involve parallel changes in spectrum of ribonucleoside modifications in rRNA and perhaps other RNA species. Materials and Methods Materials All chemicals and reagents were of the highest purity available and were used without further purification. 2′-O-Methyluridine (Um), pseudouridine (Y), N1-methyladenosine (m1A), N2,N2-dimethylguanosine (m2 2G), and 2′-O-methylguanosine (Gm) were purchased from Berry and Associates (Dexter, MI). N6-Threonylcarbamoyladenosine (t6A) was purchased from Biolog (Bremen, Germany). N6-Isopentenyladenosine (i6A) was purchased from International Laboratory LLC (San Bruno, CA). 2′-O-Methyladenosine (Am), N4-acetylcytidine (ac4C), 5-methyluridine (m5U), inosine (I), 2-methylguanosine (m2G), N7-methylguanosine (m7G), 2′-O-methylcytidine (Cm), 3-methylcytidine (m3C), 5-methylcytidine (m5C), alkaline phosphatase, lyticase, RNase A, ammonium acetate, geneticine and desferrioxamine were purchased from Sigma Chemical Co. (St. Louis, MO). Nuclease P1 was purchased from Roche Diagnostic Corp. (Indianapolis, IN). Phosphodiesterase I was purchased from USB (Cleveland, OH). PureLink miRNA Isolation Kits were purchased from Invitrogen (Carlsbad, CA). Acetonitrile and HPLC-grade water were purchased from Mallinckrodt Baker (Phillipsburg, NJ). All strains of S. cerevisiae BY4741 were purchased from American Type Culture Collections (Manassas, VA). Exposure of S. cerevisiae Cultures of S. cerevisiae BY4741 were grown to mid-log phase followed by addition of toxicants to the noted final concentrations (cytotoxicity of ∼20%, 50% and 80%): H2O2, 2, 5 or 12 mM; MMS, 6, 12 or 24 mM; NaAsO2, 20, 40 or 60 mM; NaOCl, 3.2, 4.0 or 4.8 mM. The sensitivity of the following mutant strains to toxicant exposure was also determined (doses producing ∼80% cytotoxicity in wild-type: 12 mM H2O2, 24 mM MMS, 60 mM NaAsO2, or 4.8 mM NaOCl): trm1, trm2, trm3, trm4, trm7, trm8, trm9, trm10, trm11, trm12, trm13, trm44, trm82, tad1, mod5, and tan1. Since trm5 is essential, a diploid strain (GBY1) lacking one copy of trm5 was used. After a 1 h, cells were collected and viability determined by plating. tRNA isolation Following lyticase treatment (50 units) in the presence of deaminase inhibitors (5 µg/ml coformycin, 50 µg/ml tetrahydrouridine) and antioxidants (0.1 mM desferrioxamine, 0.1 mM butylated hydroxytoluene), tRNA-containing small RNA species were isolated (Invitrogen PureLink miRNA kit) and the tRNA quantified (Agilent Series 2100 Bioanalyzer). Quantification of cytoplasmic tRNA modifications Following addition of deaminase inhibitors, antioxidants and [15N]5-2-deoxyadenosine internal standard (6 pmol), tRNA (6 µg) in 30 mM sodium acetate and 2 mM ZnCl2 (pH 6.8) was hydrolyzed with nuclease P1 (1 U) and RNase A (5 U) for 3 h at 37°C and dephosphorylated with alkaline phosphatase (10 U) and phosphodiesterase I (0.5 U) for 1 h at 37°C following addition of acetate buffer to 30 mM, pH 7.8. Proteins were removed by filtration (Microcon YM-10). Ribonucleosides were resolved with a Thermo Scientific Hypersil GOLD aQ reverse-phase column (150×2.1 mm, 3 µm particle size) eluted with the following gradient of acetonitrile in 8 mM ammonium acetate at a flow rate of 0.3 ml/min and 36°C: 0–18 min, 1–2%; 18–23 min, 2%; 23–28 min, 2–7%; 28–30 min, 7%; 30–31 min, 7–100%; 31–41 min, 100%. The HPLC column was coupled to an Agilent 6410 Triple Quadrupole LC/MS mass spectrometer with an electrospray ionization source where it was operated in positive ion mode with the following parameters for voltages and source gas: gas temperature, 350°C; gas flow, 10 l/min; nebulizer, 20 psi; and capillary voltage, 3500 V. The first and third quadrupoles (Q1 and Q3) were fixed to unit resolution and the modifications were quantified by pre-determined molecular transitions. Q1 was set to transmit the parent ribonucleoside ions and Q3 was set to monitor the deglycosylated product ions, except for Y for which the stable C-C glycosidic bond led to fragmentation of the ribose ring; we used the m/z 125 ion for quantification [48], [49]. The dwell time for each ribonucleoside was 200 ms. The retention time, m/z of the transmitted parent ion, m/z of the monitored product ion, fragmentor voltage, and collision energy of each modified nucleoside and 15N-labeled internal standard are as follow: D, 1.9 min, m/z 247→115, 80 V, 5 V; Y, 2.5 min, m/z 245→125, 80 V, 10 V; m5C, 3.3 min, m/z 258→126, 80 V, 8 V; Cm, 3.6 min, m/z 258→112, 80 V, 8 V; m5U, 4.2 min, m/z 259→127, 80 V, 7 V; ncm5U, 4.3 min, m/z 302→170, 90 V, 7 V; ac4C, 4.4 min, m/z 286→154, 80 V, 6 V; m3C, 4.4 min, m/z 258→126, 80 V, 8 V; ncm5Um, 5.5 min, m/z 316→170, 90 V, 7 V; Um, 5.1 min, m/z 259→113, 80 V, 7 V; m7G, 5.1 min, m/z 298→166, 90 V, 10 V; m1A, 5.7 min, m/z 282→150, 100 V, 16 V; mcm5U, 6.4 min, m/z 317→185, 90 V, 7 V; m1I, 7.3 min, m/z 283→151, 80 V, 10 V; Gm, 8.0 min, m/z 298→152, 80 V, 7 V; m1G, 8.3 min, m/z 298→166, 90 V, 10 V; m2G, 9.4 min, m/z 298→166, 90 V, 10 V; I, 10.9 min, m/z 269→137, 80 V, 10 V; mcm5s2U, 14.2 min, m/z 333→201, 90 V, 7 V; [15N]5-dA, 14.4 min, m/z 257→141, 90 V, 10 V; m2 2G, 15.9 min, m/z 312→180, 100 V, 8 V; t6A, 17.2 min, m/z 413→281, 100 V, 8 V; Am, 19 min, m/z 282→136, 100 V, 15 V; yW, 34.2 min, m/z 509→377, 80 V, 5 V, and i6A, 34.4 min, m/z 336→204, 100 V, 17 V. The mass spectrometer monitored ions with the molecular transitions of D, Y, m5C, and Cm from 1 to 4 min; molecular transitions of m5U, ncm5U, ac4C, m3C, ncm5Um, Um, m7G, m1A, and mcm5U from 4 to 7 min; molecular transitions of m1I, Gm, m1G, and m2G from 7 to 10 min; molecular transitions of I, mcm5s2U, [15N]5-dA, m2 2G, t6A, and Am from 10 to 30 min; molecular transitions of yW and i6A from 30 to 40 min. The identities of individual ribonucleosides were established by comparison to commercially available synthetic standards, high mass accuracy mass spectrometry, fragmentation patterns generated by collision-induced dissociation (CID) in a quadrupole time-of-flight mass spectrometer (QTOF) or MSn analysis by ion trap mass spectrometry, with comparison to literature data (e.g., ref. [48]). Quantification of m7G in control and MMS-treated yeast To assess the direct and indirect effects of MMS on levels of methylated ribonucleosides, the absolute levels of m7G were quantified in small RNA hydrolysates isolated from MMS-exposed and unexposed mutant and wild type strains of yeast by the LC-MS/MS method described above. Calibration curves were generated by mixing variable amounts of m7G (final concentrations of 0, 5, 50, 300, 600, 1000, and 2000 nM) with a fixed concentration of [15N]5-dA (40 nM). A volume of 10 µl of each solution was analyzed with the LC-MS/MS system described earlier. Statistical analysis of changes in the levels of tRNA modifications Differences in the levels of ribonucleosides in exposed versus unexposed and in mutant versus wild-type yeast were analyzed by Student's t-test. Hierarchical clustering analyses were performed using Cluster 3.0. Data were transformed to log2 ratios of modification levels in treated cells relative to unexposed controls. Clustering was carried out using the centroid linkage algorithm based on the distance between each dataset measured using the Pearson correlation, with heat map representations produced using Java Treeview. Principal component analysis was performed using XLStat (Addinsoft SARL, Paris, France), with a Pearson correlation matrix consisting of data that were mean-centered and normalized to the standard deviation. Correlation analysis was used to assess the degree of covariance among the various sets of fold-change values for each mutant (Table S5), with correlation coefficients calculated using Excel (Microsoft). Supporting Information Figure S1 Mass spectrometer signal intensities for tRNA ribonucleoside modifications. Small RNA isolates containing tRNA (85%) were enzymatically hydrolyzed and quantities ranging from 0.1 to 2 μg were analyzed by LC-MS/MS. Mass spectrometer signal intensities were determined for 23 of 25 modified ribonucleosides from yeast tRNA and plotted against total tRNA. Data represent mean ± SD for three analyses of the same sample. (1.76 MB TIF) Click here for additional data file. Figure S2 Cytotoxicity dose-response studies with S. cerevisiae exposed to MMS, H2O2, NaAsO2 and NaOCl. Data represent mean ±SD for three biological replicates. The dotted line marks the 80% survival level. (1.18 MB TIF) Click here for additional data file. Figure S3 Quantification of absolute level of m7G in different strains of yeast with or without MMS-exposure. Data represent mean ± SD for three biological replicates. (2.88 MB TIF) Click here for additional data file. Table S1 Normalized mass spectrometer signal intensities for tRNA modifications in S. cerevisiae treated with four toxicants. Data represent mean ± SD for N = 3, with Student's t-test relative to control values. (0.99 MB PDF) Click here for additional data file. Table S2 Fold-change values for S. cerevisiae tRNA modifications in treated cells relative to untreated controls. * Based on data from Table S1. (0.07 MB PDF) Click here for additional data file. Table S3 Contribution of each agent to variance in principal component analysis. (0.03 MB PDF) Click here for additional data file. Table S4 Relationships between conserved locations of tRNA ribonucleosides that are altered by exposure or that confer resistance to cytotoxicity in S. cerevisiae. (0.09 MB PDF) Click here for additional data file. Table S5 Ratios of the levels of tRNA modifications in mutant strains relative to wild type S. cerevisiae. Underlined: Mutant was determined to be significantly different from wild type by Student's t-test with P 1.5. (0.65 MB PDF) Click here for additional data file. Table S6 Locations of tRNA ribonucleosides affected by exposure to toxicants and critical to surviving toxicant exposure. (0.04 MB PDF) Click here for additional data file. Table S7 Correlation coefficients between tRNA modification profiles for each mutant. Coefficients above 0.8 are shaded red and those between 0.5 and 0.8 are shaded pink. (0.67 MB PDF) Click here for additional data file.
Author and article information
Journal
Journal ID (nlm-ta): Epigenetics
Journal ID (iso-abbrev): Epigenetics
Title:
Epigenetics
Publisher:
Taylor & Francis
ISSN
(Print):
1559-2294
ISSN
(Electronic):
1559-2308
Publication date
(Electronic, pub):
17
April
2020
Publication date
(Electronic, collection):
2020
Publication date PMC-release: 17
April
2020
Volume: 15
Issue: 10
Pages: 1121-1138
Affiliations
[b
]College of Pharmacy, Department of Toxicology and Pharmacology, University of Arizona; , Tucson, AZ, USA
[g
]Department of Biological Engineering, Massachusetts Institute of Technology; , Cambridge, MA, USA
Author notes
CONTACT Thomas J. Begley
tbegley@
123456albany.edu
University at Albany; , 1400 Washington Ave, LSRB 1003K, Albany, NY12222, USA
Author information
Lauren Endres
https://orcid.org/0000-0002-7989-8671
Peter C. Dedon
https://orcid.org/0000-0003-0011-3067
Thomas J. Begley
https://orcid.org/0000-0002-5641-7644
Article
Publisher ID: 1750213DOI: 10.1080/15592294.2020.1750213
PMC ID: 7518688
PubMed ID: 32303148
SO-VID: 32612b8e-b93e-457e-a193-ac32a24e93a7
Copyright © © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis
Group.
License:
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License ( http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
History
Page count
Figures: 7,
References: 87,
Pages: 18
Categories
Subject:
Research Article
Subject:
Research Paper
ScienceOpen disciplines: Genetics
Data availability:
ScienceOpen disciplines: Genetics