Literature DB >> 26214130

Efficient and quantitative high-throughput tRNA sequencing.

Guanqun Zheng1, Yidan Qin2, Wesley C Clark1, Qing Dai3, Chengqi Yi1, Chuan He1,3,4,5, Alan M Lambowitz2, Tao Pan1,4.   

Abstract

Despite its biological importance, tRNA has not been adequately sequenced by standard methods because of its abundant post-transcriptional modifications and stable structure, which interfere with cDNA synthesis. We achieved efficient and quantitative tRNA sequencing in HEK293T cells by using engineered demethylases to remove base methylations and a highly processive thermostable group II intron reverse transcriptase to overcome these obstacles. Our method, DM-tRNA-seq, should be applicable to investigations of tRNA in all organisms.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 26214130      PMCID: PMC4624326          DOI: 10.1038/nmeth.3478

Source DB:  PubMed          Journal:  Nat Methods        ISSN: 1548-7091            Impact factor:   28.547


High-throughput RNA sequencing (RNA-seq) has revolutionized our understanding of gene expression. Widely used RNA-seq methods start with adapter ligation and cDNA synthesis of biological RNA samples followed by PCR amplification to generate sequencing libraries[1]. These standard methods work well for most cellular RNAs, such as mRNA, long ncRNA, miRNA, or fragments derived from rRNA, snRNA, and snoRNA. tRNA is the only class of cellular RNA for which the standard sequencing methods cannot yet be applied efficiently and quantitatively, although attempts have been made (e.g. ref 2). Significant obstacles for the sequencing of tRNA include the presence of numerous post-transcriptional modifications and its stable and extensive secondary structure, which interfere with cDNA synthesis and adapter ligation. tRNAs are essential for cells and their synthesis is under stringent cellular control. Accumulating evidence shows that tRNA expression and mutations are associated with various diseases such as neurological pathologies and cancer development[3,4]. The lack of efficient and quantitative tRNA-seq methods has hindered biological studies of tRNA. We applied two strategies to eliminate or substantially reduce the obstacles of tRNA modification and structure for efficient and quantitative tRNA sequencing (). A DNA and RNA repair protein AlkB-derived enzyme mixture was first used to remove methylations at the Watson-Crick face. Three specific modifications, N1-methyladenosine (m1A), N3-methylcytosine (m3C), and N1-methylguanosine (m1G), are abundant in eukaryotic tRNAs and are particularly problematic for reverse transcriptases (RTs) by causing cDNA synthesis to stop or misincorporate. In mammals, known modifications of these types include m1A present in all tRNAs at position 58, m3C present in five tRNAs at position 32 and the variable loop and m1G present in about half of all tRNAs at positions 37 or 9. We applied two recombinant enzymes as a mixture to remove these three methylations in human tRNAs. The first was the wild-type enzyme AlkB (wtAlkB) from E. coli, which is known to very efficiently demethylate m1A and m3C in single-stranded nucleic acids as its DNA and RNA repair function[5,6]. Wild-type AlkB, however, works very poorly on m1G modification[7]. Based on its known three-dimensional structure complexed with nucleic acids, we engineered AlkB to generate a specific mutant, D135S that efficiently converted m1G to G (). We optimized the reaction conditions and enzyme to RNA ratios using a mixture of the wild-type and the D135S AlkB proteins (). We were able to remove >80% of total m1A, m3C, and ~70% m1G without a noticeable change in tRNA quality (). The remaining m1A or m1G may be more buried in the tRNA tertiary structure (m1A or m1G at position 9 of tRNAs) and thus not easily accessible to demethylase treatment without causing tRNA degradation. We used a thermostable group II intron reverse transcriptase (TGIRT) with high processivity to generate cDNA from highly structured tRNA. The TGIRT reaction does not require adapter ligation; it synthesizes cDNA by template-switching from the adaptor to the 3’ end of the target RNA[8-10]. Importantly, demethylase treatment markedly reduced the amount of RT stops at the m1A58 and m1G37 positions. At the same time, the amount of longer and full-length cDNAs was substantially increased after demethylase treatment of tRNA (). Similar results regarding demethylase treatment were obtained when the RNA template was either total cellular RNA or gel-purified total tRNA (). These results show that the demethylase treatment is effective in producing longer reads; this property will be crucial for the ability to adequately map mammalian tRNA expression where many tRNAs have just one or a handful of differences in their sequences[11,12]. We performed Illumina sequencing using the libraries generated from tRNAs with and without the demethylase treatment. To facilitate our focus on tRNA at this time, the sequencing reads were mapped only to the genomic tRNA database, which contains 515 predicted tRNA genes distributed over 330 unique sequences and 110 predicted tRNA pseudogenes[12]. In all, 6.6–15.7 million and 2.3–4.7 million reads were mapped to the genomic tRNA database when using gel-purified tRNA or total RNA as template, respectively (). These variations in read numbers were derived from sample handling, as similar proportions of reads were obtained for the added internal tRNA standards (). For the biological replicate from HEK293T cells, both untreated and treated samples showed similarly high reproducibility with r2-values from 0.985–0.991 (). As already indicated by the cDNA bands (), the read length and in particular the proportion of reads corresponding to full-length tRNA is increased substantially upon demethylase treatment, as shown by the position plots along individual tRNA genes (). The highest fraction of reads in a LeuAAG tRNA in the untreated samples were RT stops due to the m1G37 modification, whereas all stops at this position were removed with the corresponding increase of full-length tRNA reads upon demethylase treatment (). Similarly, the substantial RT stop at m1G9 of a GlnCTG tRNA was markedly reduced upon demethylase treatment, together with a substantially increased generation of full-length reads (). We still detected a strong stop at the m22G26 (N2,N2-dimethylguanosine) residue in LeuAAG tRNA that remained unchanged upon demethylase treatment. This result indicates that our demethylase mixture is not effective in removing m22G modifications, which are present in ~20% of tRNAs. Nevertheless, our results indicate that the demethylase treatment is very effective in producing longer reads; this property is crucial for the ability to adequately map the mammalian tRNAome at single base resolution. We performed additional analysis to further demonstrate the usefulness of our sequencing method. Plotting each tRNA isoacceptor against their genomic gene copy number showed a poor correlation (), consistent with the known tissue specific tRNA expression in humans[13,14]. We compared the fraction read of the tRNAArg isoacceptors to the fluorescence hybridization signals of the Arg-tRNA probes from tRNA microarrays which were obtained through hybridization without the need for cDNA synthesis[13,15]. The sequencing and array results showed the same trend of isoacceptor abundance, thus validating the quantitative nature of tRNA abundance obtained independently through sequencing and hybridization based approaches (). We also compared RT stops and misincorporations at known modification positions with and without demethylase treatment. In the case of m1A58 in ValCAC and m3C32 in ThrAGT, the demethylases completely removed these modifications as demonstrated by the reversion to cognate sequence at these positions (). In the case of m1G37 in ProTGG and m1G9 in GlnCTG, the demethylase treatment removed a large majority of the modification so the mismatch and stops were substantially reduced (). Therefore, our DM-TGIRT-seq method can determine differences in the modification dynamics of m1A, m1G and m3C at single base resolution, as well as potentially infer positions of non-demethylated modifications. We also examined the expression of unique tRNA genes from chromosome 6. Human chromosome 6 contains approximately one third of all tRNA genes, and over 150 genes are clustered within a 2.7 Mbp region near the class I major histocompatibility (MHC) genes[16]. We found that the tRNA expression levels within the tRNA gene cluster were higher compared to the tRNA genes outside of the cluster (). The expression level of tRNA genes in the cluster was uneven, suggesting that the expression of tRNA genes was not coordinated throughout the entire cluster in HEK293T cells. In summary, despite its biological importance, tRNA has not been adequately studied at the transcriptome level due to its unique characteristics in modification and structure. Our approach described here makes efficient and quantitative tRNA-seq feasible, and has an additional advantage of being able to study modifications in a high throughput manner. Our method is accessible to any lab and offers broad potentials in basic research and diagnostic applications.

METHODS

Design of the D135S AlkB mutant

The substrates for the wild-type AlkB (wtAlkB), m1A and m3C, are positively charged. A close examination of the structures of substrate-bound AlkB[17] revealed that these positively charged substrates are favorably positioned in the active site by interacting with the negatively charged carboxylic group of Asp135 (D135) (). We reasoned that single mutants at the D135 position might allow better accommodation of m1G in the active site (), thereby enhancing the demethylation efficiency of m1G. Truncated but catalytically active AlkB-ΔN11 was used and mutants with single amino acid replacement at D135 were screened. Of several mutations tested, AlkB D135S gave the best demethylation yields towards m1G (). In the AlkB-m1G structure model constructed by computationally mutating the AlkB structure (), the shorter side chain of S135 seems to allow more room to accommodate m1G while sustaining the crucial hydrogen bond with m1G, which may explain the improvement in activity. We also performed pH-activity profiling for the demethylation of m1A and m1G in tRNA. Decreasing demethylation activity was observed with increasing pH for both m1A and m1G substrates (). Therefore, we chose pH 5.0 for detailed kinetic analysis and subsequent experiments.

Cloning, expression and purification of AlkB and mutant

A truncated AlkB with deletion of the amino (N)-terminal 11 amino acids was cloned into a pET30a vector (Novagen) and overexpressed in E. coli BL21(DE3)[18]. The proteins were purified following procedures published previously[19]. Briefly, cells were grown at 37 °C in the presence of 50 μM kanamycin until the OD600 reached 0.6–0.8. After the addition of IPTG (1 mM) and FeSO4 (5 μM), the cells were incubated for an additional 4 hr at 30 °C. Cells were collected, pelleted and then resuspended in lysis buffer (10 mM Tris pH 7.4, 300 mM NaCl, 5% glycerol, 2 mM CaCl2, 10 mM MgCl2, 10 mM 2-mercaptoethanol). The cells were lysed by sonication and then centrifuged at 17,418 rcf for 20 min. The soluble proteins were first purified using a Ni-NTA superflow cartridge (Qiagen), and then further purified by ion-exchange (Mono S GL, GE Healthcare) and gel-filtration (Superdex-200, Pharmacia) chromatography. All protein purification steps were performed at 4 °C. The Asp135 to Ser mutation was introduced using the QuikChange Site-Directed Mutagenesis Kit (Agilent). The mutant protein was expressed and purified following the same procedure as that of the wild-type protein.

Mammalian cell culture and RNA preparations

Human embryonic kidney cell line HEK293T (CRL-11268) were obtained from American Type Culture Collection (ATCC) and used without further validation. Cells were cultured in DMEM (Thermo) media supplemented with 10% FBS and 1% 100 × Pen Strep (Gibco). Cells were routinely checked for mycoplasma contamination every 3–6 months, using Universal Mycoplasma Detection Kit (ATCC). Total RNA was isolated by using a mirVana miRNA Isolation Kit (Life Technologies). Purified total RNA was premixed with the T7 RNA polymerase transcripts of three tRNA standards[13] (0.01 pmol each standard per μg of total RNA) and deacylated by incubating in 0.1 M Tris-HCl, pH 9 at 37°C for 45 min. Although not necessary for studies of mature tRNAs, which all end with 3’CCA, deacylated RNAs with or without demethylation treatment could be treated with T4 polynucleotide kinase (Epicentre) at 37C° for 30 min to further warrant a free 3’ hydroxyl group for template-switching. When necessary, total tRNA was subsequently isolated using a denaturing 10% polyacrylamide gel followed by passive gel elution and ethanol precipitation.

Demethylation reactions

Demethylation activity assay was performed for either gel purified total tRNA or total cellular RNA. For total tRNA, 100 μl of reaction mixture containing 1 μg of tRNA (~40 pmol) was treated with 2× molar ratio of wtAlkB (80 pmol) and 4× molar ratio of D135S mutant (160 pmol). For total cellular RNA, 5 μg of total RNA (estimated to contain ~40 pmol tRNA) was treated with 4× molar ratio of wtAlkB (160 pmol) and 4× molar ratio of D135S (200 pmol). More demethylases were used for total RNA to alleviate potential interference by rRNA and mRNA in the reaction. The reaction buffer contained 300 mM KCl, 2 mM MgCl2, 50 μM of (NH4)2Fe(SO4)2·6H2O, 300 μM 2-ketoglutarate (2-KG), 2 mM L-ascorbic acid, 50 μg/mL BSA, 50 mM MES buffer (pH 5.0). In both cases, the reaction was incubated for 2 hr at room temperature, and quenched by the addition of 5 mM EDTA. After phenolchloroform extraction, tRNA was recovered by ethanol precipitation.

Thermostable group II intron RT template-switching

Template-switching reactions were performed as described[8-10]. Briefly, we used an initial template-primer substrate consisting of a 41-nt RNA oligonucleotide (5’-AGA UCG GAA GAG CAC ACG UCU AGU UCU ACA GUC CGA CGA UC/3SpC3/-3’) that contains Illumina Read1 and Read2 primer-binding sites and a 3’ blocking group (three carbon spacer; Integrated DNA technologies, inc.) annealed to a complementary 32P-labeled DNA primer with a single-nucleotide 3’ overhang, T, which facilitates the template switch to full-length tRNAs that mostly contain a 3’ CCA end. For TGIRT template-switching reactions, typically 100 ng of demethylated tRNAs or 1 μg of demethylated total RNA were mixed with the initial template-primer substrate (100 nM) and 500 nM TGIRT (GsI-IIC MalE rigid fusion RT[10]) in reaction medium containing 450 mM NaCl, 5 mM MgCl2, 20 mM Tris-HCl, pH 7.5, and 5 mM DTT. The reactions were pre-incubated at room temperature for 30 min, initiated by adding 25 mM dNTPs (an equimolar mix of 25 mM dATP, dCTP, dGTP and dTTP) to a final concentration of 1 mM and incubating at 60°C for 30 min. The reactions were terminated by adding 5 M NaOH to a final concentration of 0.25 M, incubating at 95°C for 3 min, and neutralizing with 5 M HCl. The cDNAs resulting from template-switching were analyzed in a denaturing 6% polyacrylamide gel, electroeluted using a D-tube Dialyzer Maxi with MWCO of 6–8 kDa (EMD Millipore), and ethanol precipitated with 0.3 M sodium acetate, pH 5.2, in the presence of 25 μg of linear acrylamide (Life Technologies) carrier. The purified cDNAs were then circularized with CircLigase II (Epicentre) using the manufacturer's protocol with an extended incubation time of 5 hr at 60°C, extracted with phenol-chloroform-isoamyl alcohol (25:24:1), ethanol precipitated and amplified with Phusion-HF (Thermo Scientific) using Illumina multiplex (5’- AAT GAT ACG GCG ACC ACC GAG ATC TAC ACG TTC AGA GTT CTA CAG TCC GAC GAT C -3’) and barcode (5’- CAA GCA GAA GAC GGC ATA CGA GAT BARCODE GTG ACT GGA GTT CAG ACG TGT GCT CTT CCG ATC T -3’) primers for 12 cycles of 98°C for 5 sec, 60°C for 10 sec and 72°C for 10 sec. The PCR products were sequenced on an Illumina HiSeq system.

Quantitative analysis of modification levels using LC-MS/MS

Quantitative analysis of modified nucleotides was done as previously described[20]. Briefly, 100 ng of tRNA was digested by nuclease P1 (2 U) in 30 μl of buffer containing 25 mM NaCl, and 2.5 mM ZnCl2 at 37°C for 1 hr, followed by the addition of NH4HCO3 (100 mM) and alkaline phosphatase (0.5 U). After an additional incubation at 37°C for 1 hr, the solution was diluted to 60 μl, and 10 μl of the solution was injected for LCMS/MS. Nucleosides were separated by reverse phase ultra-performance liquid chromatography on a C18 column with online mass spectrometry detection using an Agilent 6410 QQQ triple-quadruple LC mass spectrometer in positive electrospray ionization mode. The nucleosides were quantified using the nucleoside to base ion mass transitions of 282 to 150 (m1A), 268 to 166 (A), 298 to (m1G), 284 to 152 (G), 258 to 126 (m3C) and 244 to 112 (C). Quantification was performed by comparison with the standard curve obtained from pure nucleoside standards running in the same batch of samples. Modification levels were compared by the ratios of methylated base (m1A, m1G, m3C) over regular base (A, G, C).

tRNA microarrays

The tRNA microarray assay consists of four steps starting from purified tRNA or total RNA without the need of cDNA synthesis: (i) deacylation to remove all 3’ attached amino acids, (ii) selective fluorophore labeling of tRNA using oligonucleotide ligation with T4 DNA ligase to the 3’CCA of all tRNAs, (iii) hybridization, and (iv) data analysis. The reproducibility of the tRNA microarray method and validation of the results have been extensively described previously[13,15].

Sequencing read mapping

Sequencing reads were aligned using Bowtie to a modified hg19 genomic tRNA database[12]. A single mismatch was allowed in order to identify potential modification misincorporations at a modification site. Briefly, a tRNA library was adapted from the tRNAScan-SE library by appending CCA to tRNAs from the genomic tRNA database (http://gtrnadb.ucsc.edu/Hsapi19/). Isodecoders with identical scores were consolidated for ease of identity assignment, decreasing the number of reference genes and pseudogenes from 625 to 462. Prior to mapping, reads were processed using Trimmomatic v0.32. Sequences greater than 15 bp were then aligned to the aforementioned culled tRNA library using Bowtie2 with sensitive options. Reads mapping to multiple isodecoders due to length of fragment were discarded. Modification fractions were determined by analyzing at a putative position ‘n’ the number of correct reads, the number of misincorporations, as well as the number of reads stopped at the n+1 position.
  19 in total

Review 1.  Emerging roles of tRNA in adaptive translation, signalling dynamics and disease.

Authors:  Sebastian Kirchner; Zoya Ignatova
Journal:  Nat Rev Genet       Date:  2014-12-23       Impact factor: 53.242

2.  A dual program for translation regulation in cellular proliferation and differentiation.

Authors:  Hila Gingold; Disa Tehler; Nanna R Christoffersen; Morten M Nielsen; Fazila Asmar; Susanne M Kooistra; Nicolaj S Christophersen; Lise Lotte Christensen; Michael Borre; Karina D Sørensen; Lars D Andersen; Claus L Andersen; Esther Hulleman; Tom Wurdinger; Elisabeth Ralfkiær; Kristian Helin; Kirsten Grønbæk; Torben Ørntoft; Sebastian M Waszak; Orna Dahan; Jakob Skou Pedersen; Anders H Lund; Yitzhak Pilpel
Journal:  Cell       Date:  2014-09-11       Impact factor: 41.582

3.  Oxidative demethylation by Escherichia coli AlkB directly reverts DNA base damage.

Authors:  Sarah C Trewick; Timothy F Henshaw; Robert P Hausinger; Tomas Lindahl; Barbara Sedgwick
Journal:  Nature       Date:  2002-09-12       Impact factor: 49.962

Review 4.  RNA-Seq: a revolutionary tool for transcriptomics.

Authors:  Zhong Wang; Mark Gerstein; Michael Snyder
Journal:  Nat Rev Genet       Date:  2009-01       Impact factor: 53.242

5.  ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility.

Authors:  Guanqun Zheng; John Arne Dahl; Yamei Niu; Peter Fedorcsak; Chun-Min Huang; Charles J Li; Cathrine B Vågbø; Yue Shi; Wen-Ling Wang; Shu-Hui Song; Zhike Lu; Ralph P G Bosmans; Qing Dai; Ya-Juan Hao; Xin Yang; Wen-Ming Zhao; Wei-Min Tong; Xiu-Jie Wang; Florian Bogdan; Kari Furu; Ye Fu; Guifang Jia; Xu Zhao; Jun Liu; Hans E Krokan; Arne Klungland; Yun-Gui Yang; Chuan He
Journal:  Mol Cell       Date:  2012-11-21       Impact factor: 17.970

Review 6.  Gene map of the extended human MHC.

Authors:  Roger Horton; Laurens Wilming; Vikki Rand; Ruth C Lovering; Elspeth A Bruford; Varsha K Khodiyar; Michael J Lush; Sue Povey; C Conover Talbot; Mathew W Wright; Hester M Wain; John Trowsdale; Andreas Ziegler; Stephan Beck
Journal:  Nat Rev Genet       Date:  2004-12       Impact factor: 53.242

7.  Thermostable group II intron reverse transcriptase fusion proteins and their use in cDNA synthesis and next-generation RNA sequencing.

Authors:  Sabine Mohr; Eman Ghanem; Whitney Smith; Dennis Sheeter; Yidan Qin; Olga King; Damon Polioudakis; Vishwanath R Iyer; Scott Hunicke-Smith; Sajani Swamy; Scott Kuersten; Alan M Lambowitz
Journal:  RNA       Date:  2013-05-22       Impact factor: 4.942

8.  Diversity of tRNA genes in eukaryotes.

Authors:  Jeffrey M Goodenbour; Tao Pan
Journal:  Nucleic Acids Res       Date:  2006-11-06       Impact factor: 16.971

9.  Diverse cell stresses induce unique patterns of tRNA up- and down-regulation: tRNA-seq for quantifying changes in tRNA copy number.

Authors:  Yan Ling Joy Pang; Ryan Abo; Stuart S Levine; Peter C Dedon
Journal:  Nucleic Acids Res       Date:  2014-10-27       Impact factor: 16.971

10.  tRNA over-expression in breast cancer and functional consequences.

Authors:  Mariana Pavon-Eternod; Suzanna Gomes; Renaud Geslain; Qing Dai; Marsha Rich Rosner; Tao Pan
Journal:  Nucleic Acids Res       Date:  2009-11       Impact factor: 16.971

View more
  198 in total

1.  Selective amplification and sequencing of cyclic phosphate-containing RNAs by the cP-RNA-seq method.

Authors:  Shozo Honda; Keisuke Morichika; Yohei Kirino
Journal:  Nat Protoc       Date:  2016-02-11       Impact factor: 13.491

2.  Removing roadblocks to deep sequencing of modified RNAs.

Authors:  Jeremy E Wilusz
Journal:  Nat Methods       Date:  2015-09       Impact factor: 28.547

3.  Transcriptome-wide mapping reveals reversible and dynamic N(1)-methyladenosine methylome.

Authors:  Xiaoyu Li; Xushen Xiong; Kun Wang; Lixia Wang; Xiaoting Shu; Shiqing Ma; Chengqi Yi
Journal:  Nat Chem Biol       Date:  2016-02-10       Impact factor: 15.040

Review 4.  Role of tRNAs in Breast Cancer Regulation.

Authors:  Nam Hoon Kwon; Jin Young Lee; Sunghoon Kim
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

5.  The RNA landscape of the human placenta in health and disease.

Authors:  Gordon C S Smith; D Stephen Charnock-Jones; Sungsam Gong; Francesca Gaccioli; Justyna Dopierala; Ulla Sovio; Emma Cook; Pieter-Jan Volders; Lennart Martens; Paul D W Kirk; Sylvia Richardson
Journal:  Nat Commun       Date:  2021-05-11       Impact factor: 14.919

Review 6.  Discovering and Mapping the Modified Nucleotides That Comprise the Epitranscriptome of mRNA.

Authors:  Bastian Linder; Samie R Jaffrey
Journal:  Cold Spring Harb Perspect Biol       Date:  2019-06-03       Impact factor: 10.005

7.  Senataxin homologue Sen1 is required for efficient termination of RNA polymerase III transcription.

Authors:  Julieta Rivosecchi; Marc Larochelle; Camille Teste; Frédéric Grenier; Amélie Malapert; Emiliano P Ricci; Pascal Bernard; François Bachand; Vincent Vanoosthuyse
Journal:  EMBO J       Date:  2019-07-11       Impact factor: 11.598

8.  Gene-Specific Control of tRNA Expression by RNA Polymerase II.

Authors:  Alan Gerber; Keiichi Ito; Chi-Shuen Chu; Robert G Roeder
Journal:  Mol Cell       Date:  2020-04-15       Impact factor: 17.970

Review 9.  Epigenetic inheritance of acquired traits through sperm RNAs and sperm RNA modifications.

Authors:  Qi Chen; Wei Yan; Enkui Duan
Journal:  Nat Rev Genet       Date:  2016-10-03       Impact factor: 53.242

10.  Universally high transcript error rates in bacteria.

Authors:  Weiyi Li; Michael Lynch
Journal:  Elife       Date:  2020-05-29       Impact factor: 8.140

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.