RNA m5C Research Articles

M5CPred-SVM: a novel method for predicting m5C sites of RNA

BackgroundAs one of the most common post-transcriptional modifications (PTCM) in RNA, 5-cytosine-methylation plays important roles in many biological functions such as RNA metabolism and cell fate decision. Through accurate identification of 5-methylcytosine (m5C) sites on RNA, researchers can better understand the exact role of 5-cytosine-methylation in these biological functions. In recent years, computational methods of predicting m5C sites have attracted lots of interests because of its efficiency and low-cost. However, both the accuracy and efficiency of these methods are not satisfactory yet and need further improvement.ResultsIn this work, we have developed a new computational method, m5CPred-SVM, to identify m5C sites in three species, H. sapiens, M. musculus and A. thaliana. To build this model, we first collected benchmark datasets following three recently published methods. Then, six types of sequence-based features were generated based on RNA segments and the sequential forward feature selection strategy was used to obtain the optimal feature subset. After that, the performance of models based on different learning algorithms were compared, and the model based on the support vector machine provided the highest prediction accuracy. Finally, our proposed method, m5CPred-SVM was compared with several existing methods, and the result showed that m5CPred-SVM offered substantially higher prediction accuracy than previously published methods. It is expected that our method, m5CPred-SVM, can become a useful tool for accurate identification of m5C sites.ConclusionIn this study, by introducing position-specific propensity related features, we built a new model, m5CPred-SVM, to predict RNA m5C sites of three different species. The result shows that our model outperformed the existing state-of-art models. Our model is available for users through a web server at https://zhulab.ahu.edu.cn/m5CPred-SVM.

RNA 5-Methylcytosine Controls Plant Development and Environmental Adaptation.

Despite increasing understanding of 5-methylcytosine (m5C) on RNAs in mammals, the function of m5C in plants remains obscure. A dynamic function of m5C in plant development and stress adaptation had been suggested, and Tang et al. have now uncovered a role for RNA m5C methyltransferase in rice adaptation to high temperature.

Prediction of m5C Modifications in RNA Sequences by Combining Multiple Sequence Features

5-Methylcytosine (m5C) is a well-known post-transcriptional modification that plays significant roles in biological processes, such as RNA metabolism, tRNA recognition, and stress responses. Traditional high-throughput techniques on identification of m5C sites are usually time consuming and expensive. In addition, the number of RNA sequences shows explosive growth in the post-genomic era. Thus, machine-learning-based methods are urgently requested to quickly predict RNA m5C modifications with high accuracy. Here, we propose a noval support-vector-machine (SVM)-based tool, called iRNA-m5C_SVM, by combining multiple sequence features to identify m5C sites in Arabidopsis thaliana. Eight kinds of popular feature-extraction methods were first investigated systematically. Then, four well-performing features were incorporated to construct a comprehensive model, including position-specific propensity (PSP) (PSNP, PSDP, and PSTP, associated with frequencies of nucleotides, dinucleotides, and trinucleotides, respectively), nucleotide composition (nucleic acid, di-nucleotide, and tri-nucleotide compositions; NAC, DNC, and TNC, respectively), electron-ion interaction pseudopotentials of trinucleotide (PseEIIPs), and general parallel correlation pseudo-dinucleotide composition (PC-PseDNC-general). Evaluated accuracies over 10-fold cross-validation and independent tests achieved 73.06% and 80.15%, respectively, which showed the best predictive performances in A. thaliana among existing models. It is believed that the proposed model in this work can be a promising alternative for further research on m5C modification sites in plant.

Epitranscriptomic 5-Methylcytosine Profile in PM2.5-induced Mouse Pulmonary Fibrosis

Exposure of airborne particulate matter (PM) with an aerodynamic diameter less than 2.5 μm (PM2.5) is epidemiologically associated with lung dysfunction and respiratory symptoms, including pulmonary fibrosis. However, whether epigenetic mechanisms are involved in PM2.5-induced pulmonary fibrosis is currently poorly understood. Herein, using a PM2.5-induced pulmonary fibrosis mouse model, we found that PM2.5 exposure leads to aberrant mRNA 5-methylcytosine (m5C) gain and loss in fibrotic lung tissues. Moreover, we showed the m5C-mediated regulatory map of gene functions in pulmonary fibrosis after PM2.5 exposure. Several genes act as m5C gain-upregulated factors, probably critical for the development of PM2.5-induced fibrosis in mouse lungs. These genes, including Lcn2, Mmp9, Chi3l1, Adipoq, Atp5j2, Atp5l, Atpif1, Ndufb6, Fgr, Slc11a1, and Tyrobp, are highly related to oxidative stress response, inflammatory responses, and immune system processes. Our study illustrates the first epitranscriptomic RNA m5C profile in PM2.5-induced pulmonary fibrosis and will be valuable in identifying biomarkers for PM2.5 exposure-related lung pathogenesis with translational potential.

RNAWRE: a resource of writers, readers and erasers of RNA modifications.

RNA modifications are involved in various kinds of cellular biological processes. Accumulated evidences have demonstrated that the functions of RNA modifications are determined by the effectors that can catalyze, recognize and remove RNA modifications. They are called ‘writers’, ‘readers’ and ‘erasers’. The identification of RNA modification effectors will be helpful for understanding the regulatory mechanisms and biological functions of RNA modifications. In this work, we developed a database called RNAWRE that specially deposits RNA modification effectors. The current version of RNAWRE stored 2045 manually curated writers, readers and erasers for the six major kinds of RNA modifications, namely Cap, m1A, m6A, m5C, ψ and Poly A. The main modules of RNAWRE not only allow browsing and downloading the RNA modification effectors but also support the BLAST search of the potential RNA modification effectors in other species. We hope that RNAWRE will be helpful for the researches on RNA modifications.Database URL: http://rnawre.bio2db.com

A Mini-review of the Computational Methods Used in Identifying RNA 5-Methylcytosine Sites.

RNA 5-methylcytosine (m5C) is one of the pillars of post-transcriptional modification (PTCM). A growing body of evidence suggests that m5C plays a vital role in RNA metabolism. Accurate localization of RNA m5C sites in tissue cells is the premise and basis for the in-depth understanding of the functions of m5C. However, the main experimental methods of detecting m5C sites are limited to varying degrees. Establishing a computational model to predict modification sites is an excellent complement to wet experiments for identifying m5C sites. In this review, we summarized some available m5C predictors and discussed the characteristics of these methods.

Episo: quantitative estimation of RNA 5-methylcytosine at isoform level by high-throughput sequencing of RNA treated with bisulfite

MotivationRNA 5-methylcytosine (m5C) is a type of post-transcriptional modification that may be involved in numerous biological processes and tumorigenesis. RNA m5C can be profiled at single-nucleotide resolution by high-throughput sequencing of RNA treated with bisulfite (RNA-BisSeq). However, the exploration of transcriptome-wide profile and potential function of m5C in splicing remains to be elucidated due to lack of isoform level m5C quantification tool.ResultsWe developed a computational package to quantify Epitranscriptomal RNA m5C at the transcript isoform level (named Episo). Episo consists of three tools: mapper, quant and Bisulfitefq, for mapping, quantifying and simulating RNA-BisSeq data, respectively. The high accuracy of Episo was validated using an improved m5C-specific methylated RNA immunoprecipitation (meRIP) protocol, as well as a set of in silico experiments. By applying Episo to public human and mouse RNA-BisSeq data, we found that the RNA m5C is not evenly distributed among the transcript isoforms, implying the m5C may subject to be regulated at isoform level.Availability and implementationEpiso is released under the GNU GPLv3+ license. The resource code Episo is freely accessible from https://github.com/liujunfengtop/Episo (with Tophat/cufflink) and https://github.com/liujunfengtop/Episo/tree/master/Episo_Kallisto (with Kallisto).Supplementary information Supplementary data are available at Bioinformatics online.

A general strategy exploiting m5C duplex-remodelling effect for selective detection of RNA and DNA m5C methyltransferase activity in cells.

RNA:5-methylcytosine (m5C) methyltransferases are currently the focus of intense research following a series of high-profile reports documenting their physiological links to several diseases. However, no methods exist which permit the specific analysis of RNA:m5C methyltransferases in cells. Herein, we described how a combination of biophysical studies led us to identify distinct duplex-remodelling effects of m5C on RNA and DNA duplexes. Specifically, m5C induces a C3′-endo to C2′-endo sugar-pucker switch in CpG RNA duplex but triggers a B-to-Z transformation in CpG DNA duplex. Inspired by these different ‘structural signatures’, we developed a m5C-sensitive probe which fluoresces spontaneously in response to m5C-induced sugar-pucker switch, hence useful for sensing RNA:m5C methyltransferase activity. Through the use of this probe, we achieved real-time imaging and flow cytometry analysis of NOP2/Sun RNA methyltransferase 2 (NSUN2) activity in HeLa cells. We further applied the probe to the cell-based screening of NSUN2 inhibitors. The developed strategy could also be adapted for the detection of DNA:m5C methyltransferases. This was demonstrated by the development of DNA m5C-probe which permits the screening of DNA methyltransferase 3A inhibitors. To our knowledge, this study represents not only the first examples of m5C-responsive probes, but also a new strategy for discriminating RNA and DNA m5C methyltransferase activity in cells.

Depletion of TRDMT1 affects 5-methylcytosine modification of mRNA and inhibits HEK293 cell proliferation and migration

Human TRDMT1 is a transfer RNA (tRNA) methyltransferase for cytosine-5 methylation and has been suggested to be involved in the regulation of numerous developmental processes. However, little is known about the molecular mechanisms or their biological significance. In this study, we investigated the effects of CRISPR-based TRDMT1 knockdown on phenotypes, mRNA m5C modifications and gene expression changes in HEK293 cells. We found that knockdown of TRDMT1 significantly inhibited cell proliferation and migration but had no effect on clonogenic potential. The inhibitory effects could be attenuated by re-expression of TRDMT1 in HEK293 cells. RNA sequencing (RNA-Seq) and RNA bisulfite sequencing (RNA-BisSeq) were performed in TRDMT1 knockdown and wild-type HEK293 cells. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that the differentially expressed genes were associated with the cell cycle, RNA transport, and RNA degradation and were enriched in cancer and Notch signaling pathways. We also found that TRDMT1 knockdown could change mRNA methylation levels. For the first time, these findings clarify the role of TRDMT1 in regulating mRNA methylation and inhibiting the proliferation and migration of HEK293 cells. These results provide new insights into a new function of TRDMT1 and elucidate the molecular mechanisms of aberrant RNA m5C during tumorigenesis.

5-methylcytosine promotes pathogenesis of bladder cancer through stabilizing mRNAs.

Although 5-methylcytosine (m5C) is a widespread modification in RNAs, its regulation and biological role in pathological conditions (such as cancer) remain unknown. Here, we provide the single-nucleotide resolution landscape of messenger RNA m5C modifications in human urothelial carcinoma of the bladder (UCB). We identify numerous oncogene RNAs with hypermethylated m5C sites causally linked to their upregulation in UCBs and further demonstrate YBX1 as an m5C 'reader' recognizing m5C-modified mRNAs through the indole ring of W65 in its cold-shock domain. YBX1 maintains the stability of its target mRNA by recruiting ELAVL1. Moreover, NSUN2 and YBX1 are demonstrated to drive UCB pathogenesis by targeting the m5C methylation site in the HDGF 3' untranslated region. Clinically, a high coexpression of NUSN2, YBX1 and HDGF predicts the poorest survival. Our findings reveal an unprecedented mechanism of RNA m5C-regulated oncogene activation, providing a potential therapeutic strategy for UCB.

Genome-wide identification of mRNA 5-methylcytosine in mammals.

Accurate and systematic transcriptome-wide detection of 5-methylcytosine (m5C) has proved challenging, and there are conflicting views about the prevalence of this modification in mRNAs. Here we report an experimental and computational framework that robustly identified mRNA m5C sites and determined sequence motifs and structural features associated with the modification using a set of high-confidence sites. We developed a quantitative atlas of RNA m5C sites in human and mouse tissues based on our framework. In a given tissue, we typically identified several hundred exonic m5C sites. About 62-70% of the sites had low methylation levels (<20% methylation), while 8-10% of the sites were moderately or highly methylated (>40% methylation). Cross-species analysis revealed that species, rather than tissue type, was the primary determinant of methylation levels, indicating strong cis-directed regulation of RNA methylation. Combined, these data provide a valuable resource for identifying the regulation and functions of RNA methylation.

RNAm5Cfinder: A Web-server for Predicting RNA 5-methylcytosine (m5C) Sites Based on Random Forest

5-methylcytosine (m5C) is a common nucleobase modification, and recent investigations have indicated its prevalence in cellular RNAs including mRNA, tRNA and rRNA. With the rapid accumulation of m5C sites data, it becomes not only feasible but also important to build an accurate model to predict m5C sites in silico. For this purpose, here, we developed a web-server named RNAm5Cfinder based on RNA sequence features and machine learning method to predict RNA m5C sites in eight tissue/cell types from mouse and human. We confirmed the accuracy and usefulness of RNAm5Cfinder by independent tests, and the results show that the comprehensive and cell-specific predictors could pinpoint the generic or tissue-specific m5C sites with the Area Under Curve (AUC) no less than 0.77 and 0.87, respectively. RNAm5Cfinder web-server is freely available at http://www.rnanut.net/rnam5cfinder.

BisAMP: A web-based pipeline for targeted RNA cytosine-5 methylation analysis.

RNA cytosine-5 methylation (m5C) has emerged as a key epitranscriptomic mark, which fulfills multiple roles in structural modulation, stress signaling and the regulation of protein translation. Bisulfite sequencing is currently the most accurate and reliable method to detect m5C marks at nucleotide resolution. Targeted bisulfite sequencing allows m5C detection at single base resolution, by combining the use of tailored primers with bisulfite treatment. A number of computational tools currently exist to analyse m5C marks in DNA bisulfite sequencing. However, these methods are not directly applicable to the analysis of RNA m5C marks, because DNA analysis focuses on CpG methylation, and because artifactual unconversion and misamplification in RNA can obscure actual methylation signals. We describe a pipeline designed specifically for RNA cytosine-5 methylation analysis in targeted bisulfite sequencing experiments. The pipeline is directly applicable to Illumina MiSeq (or equivalent) sequencing datasets using a web interface (https://bisamp.dkfz.de), and is defined by optimized mapping parameters and the application of tailored filters for the removal of artifacts. We provide examples for the application of this pipeline in the unambiguous detection of m5C marks in tRNAs from mouse embryonic stem cells and neuron-differentiated stem cells as well as in 28S rRNA from human fibroblasts. Finally, we also discuss the adaptability of BisAMP to the analysis of DNA methylation. Our pipeline provides an accurate, fast and user-friendly framework for the analysis of cytosine-5 methylation in amplicons from bisulfite-treated RNA.

Catalytic crosslinking-based methods for enzyme-specified profiling of RNA ribonucleotide modifications.

Well over a hundred types of naturally occurring covalent modifications can be made to ribonucleotides in RNA molecules. Moreover, several types of such modifications are each known to be catalysed by multiple enzymes which largely appear to modify distinct sites within the cellular RNA. In order to aid functional investigations of such multi-enzyme RNA modification types in particular, it is important to determine which enzyme is responsible for catalysing modification at each site. Two methods, Aza-IP and methylation-iCLIP, were developed and used to map genome-wide locations of methyl-5-cytosine (m5C) RNA modifications inherently in an enzyme specific context. Though the methods are quite distinct, both rely on capturing catalytic intermediates of RNA m5C methyltransferases in a state where the cytosine undergoing methylation is covalently crosslinked to the enzyme. More recently the fundamental methylation-iCLIP principle has also been applied to map methyl-2-adenosine sites catalysed by the E. coli RlmN methylsynthase. Here I describe the ideas on which the two basic methods hinge, and summarise what has been achieved by them thus far. I also discuss whether and how such principles may be further exploited for profiling of other RNA modification types, such as methyl-5-uridine and pseudouridine.

Topological Characterization of Human and Mouse m5C Epitranscriptome Revealed by Bisulfite Sequencing.

Background Compared with the well-studied 5-methylcytosine (m5C) in DNA, the role and topology of epitranscriptome m5C remain insufficiently characterized. Results Through analyzing transcriptome-wide m5C distribution in human and mouse, we show that the m5C modification is significantly enriched at 5′ untranslated regions (5′UTRs) of mRNA in human and mouse. With a comparative analysis of the mRNA and DNA methylome, we demonstrate that, like DNA methylation, transcriptome m5C methylation exhibits a strong clustering effect. Surprisingly, an inverse correlation between mRNA and DNA m5C methylation is observed at CpG sites. Further analysis reveals that RNA m5C methylation level is positively correlated with both RNA expression and RNA half-life. We also observed that the methylation level of mitochondrial RNAs is significantly higher than RNAs transcribed from the nuclear genome. Conclusions This study provides an in-depth topological characterization of transcriptome-wide m5C modification by associating RNA m5C methylation patterns with transcriptional expression, DNA methylations, RNA stabilities, and mitochondrial genome.

5-Methylcytosine RNA Methylation in Arabidopsis Thaliana

5-Methylcytosine (m5C) is a well-characterized DNA modification, and is also predominantly reported in abundant non-coding RNAs in both prokaryotes and eukaryotes. However, the distribution and biological functions of m5C in plant mRNAs remain largely unknown. Here, we report transcriptome-wide profiling of RNA m5C in Arabidopsis thaliana by applying m5C RNA immunoprecipitation followed by a deep-sequencing approach (m5C-RIP-seq). LC–MS/MS and dot blot analyses reveal a dynamic pattern of m5C mRNA modification in various tissues and at different developmental stages. m5C-RIP-seq analysis identified 6045 m5C peaks in 4465 expressed genes in young seedlings. We found that m5C is enriched in coding sequences with two peaks located immediately after start codons and before stop codons, and is associated with mRNAs with low translation activity. We further demonstrated that an RNA (cytosine-5)-methyltransferase, tRNA-specific methyltransferase 4B (TRM4B), exhibits m5C RNA methyltransferase activity. Mutations in TRM4B display defects in root development and decreased m5C peaks. TRM4B affects the transcript levels of the genes involved in root development, which is positively correlated with their mRNA stability and m5C levels. Our results suggest that m5C in mRNA is a new epitranscriptome marker inArabidopsis, and that regulation of this modification is an integral part of gene regulatory networks underlying plant development.

Abstract 4470: RNA m5C methyltransferases and hnRNPK mediate disease-associated chromatin structure and drug resistance in leukemia

Abstract The mechanisms governing disease-associated chromatin organization and drug selectivity are poorly understood. Our epigenetic drug screening experiments identify two distinct lineage-specific drug-responsive patterns in myeloid leukemia (MDS/AML) cells. We have established multiple MDS/AML cell lines resistant to nucleic acid analogues with different chemical backbones and have demonstrated a clear relationship between drug-resistance and sugar-phosphate backbone. Based on these results, we used various experimental approaches to elucidate leukemia-associated, drug-responsive chromatin structural changes and their underlying mechanisms. Our data demonstrate that hnRNPK, a conserved factor in heterogeneous nuclear RNA-binding protein (hnRNP) complexes, directly interacts with RNA m5C methyltransferases NSUNs/DMNT2 and RNA-polymerase II (pol-II)/CTD9 as well as erythroid vs myeloid lineage-determining transcription factors (TFs) GATA1 and SPI1/PU.1 to form distinct drug-responsive chromatin structures in MDS/AML cells. hnRNP preferentially binds to methylated polypyrimidine RNA sequences to facilitate transcription elongation. Compared to azacitidine-sensitive MDS/AML cells, there is a marked increase in azacitidine-resistant MDS/AML cells in RNA m5C and NUSNs/ DNMT2 associated with a marked increase in the interaction between hnRNPK and active pol-II/CDK9. By employing a newly-developed nascent RNA capturing technology coupled with super-resolution stimulated-emission depletion confocal microscopy, we demonstrate co-localization of hnRNPK with the TFs and active pol-II at nascent RNA sites in MDS/AML cells, further supporting the existence of hnRNPK-mediated drug-responsive transcription and lineage-specific chromatin structures in MDS/AML cells. Our experiments using clinical specimens demonstrate a positive correlation between MDS/AML progression and increase in expression of hnRNPK and RNA m5C methyltransferases, supporting their importance and clinical relevance. Furthermore, knockdown of hnRNPK and RNA 5mC methyltransferases effectively inhibited the growth of MDS/AML cells. In conclusion, our data demonstrate distinct RNA m5C methyltransferases/hnRNPK-mediated chromatin structures that control the growth and drug sensitivity of MDS/AML cells. Based on our data, we propose a novel working model of RNA m5C methyltransferase/hnRNPK-mediated drug-responsive chromatin structure in MDS/AML cells, in which RNA m5C methyltransferases function as the writers of m5C on nascent RNA, and hnRNPK functions as a reader of the RNA m5C and an operator to regulate transcription elongation and gene activation. Such novel chromatin structure-based drug action models and mechanisms may identify new diagnostic and prognostic biomarkers and therapeutic approaches. Note: This abstract was not presented at the meeting. Citation Format: Jason X. Cheng, Li Cheng, Adam Cloe, Yuan Li, Ming Yue, Michelle M. Le Beau, Richard A. Larson, James W. Vardiman. RNA m5C methyltransferases and hnRNPK mediate disease-associated chromatin structure and drug resistance in leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4470. doi:10.1158/1538-7445.AM2017-4470

Transcriptome-Wide Mapping of RNA 5-Methylcytosine in Arabidopsis mRNAs and Noncoding RNAs.

Posttranscriptional methylation of RNA cytosine residues to 5-methylcytosine (m5C) is an important modification with diverse roles, such as regulating stress responses, stem cell proliferation, and RNA metabolism. Here, we used RNA bisulfite sequencing for transcriptome-wide quantitative mapping of m5C in the model plant Arabidopsis thaliana We discovered more than a thousand m5C sites in Arabidopsis mRNAs, long noncoding RNAs, and other noncoding RNAs across three tissue types (siliques, seedling shoots, and roots) and validated a number of these sites. Quantitative differences in methylated sites between these three tissues suggest tissue-specific regulation of m5C. Perturbing the RNA m5C methyltransferase TRM4B resulted in the loss of m5C sites on mRNAs and noncoding RNAs and reduced the stability of tRNAAsp(GTC) We also demonstrate the importance of m5C in plant development, as trm4b mutants have shorter primary roots than the wild type due to reduced cell division in the root apical meristem. In addition, trm4b mutants show increased sensitivity to oxidative stress. Finally, we provide insights into the targeting mechanism of TRM4B by demonstrating that a 50-nucleotide sequence flanking m5C C3349 in MAIGO5 mRNA is sufficient to confer methylation of a transgene reporter in Nicotiana benthamiana.

The Carboxyl-terminal Extension of Yeast tRNA m5C Methyltransferase Enhances the Catalytic Efficiency of the Amino-terminal Domain

The human tRNA m(5)C methyltransferase is a potential target for anticancer drugs because it is a novel downstream target of the proto-oncogene myc, mediating Myc-induced cell proliferation. Sequence comparisons of RNA m(5)C methyltransferases indicate that the eukaryotic enzymes possess, in addition to a conserved catalytic domain, a large characteristic carboxyl-terminal extension. To gain insight into the function of this additional domain, the modular architecture of the yeast tRNA m(5)C methyltransferase orthologue, Trm4p, was studied. The yeast enzyme catalyzes the transfer of a methyl group from S-adenosyl-L-methionine to carbon 5 of cytosine at different positions depending on the tRNAs. By limited proteolysis, Trm4p was shown to be composed of two domains that have been separately produced and purified. Here we demonstrate that the aminoterminal domain, encompassing the active site, binds tRNA with similar affinity as the whole enzyme but shows low catalytic efficiency. The carboxyl-terminal domain displays only weak affinity for tRNA. It is not required for m(5)C formation and does not appear to contribute to substrate specificity. However, it enhances considerably the catalytic efficiency of the amino-terminal domain.

Cysteine of sequence motif VI is essential for nucleophilic catalysis by yeast tRNA m5C methyltransferase

Sequence comparison of several RNA m(5)C methyltransferases identifies two conserved cysteine residues that belong to signature motifs IV and VI of RNA and DNA methyltransferases. While the cysteine of motif IV is used as the nucleophilic catalyst by DNA m(5)C methyltransferases, this role is fulfilled by the cysteine of motif VI in Escherichia coli 16S rRNA m(5)C967 methyltransferase, but whether this conclusion applies to other RNA m(5)C methyltransferases remains to be verified. Yeast tRNA m(5)C methyltransferase Trm4p is a multisite-specific S-adenosyl-L-methionine-dependent enzyme that catalyzes the methylation of cytosine at C5 in several positions of tRNA. Here, we confirm that Cys310 of motif VI in Trm4p is essential for nucleophilic catalysis, presumably by forming a covalent link with carbon 6 of cytosine. Indeed, the enzyme is able to form a stable covalent adduct with the 5-fluorocytosine-containing RNA substrate analog, whereas the C310A mutant protein is inactive and unable to form the covalent complex.