Modified Nucleotides and RNA Structure Prediction

Nucleotide modifications are occurrent in all types of RNA and play an important role in RNA structure formation and stability. Modified bases not only possess the ability to shift the RNA structure ensemble towards desired functional confirmations. By changes in the base pairing partner preference, they may even enlarge or reduce the conformational space, i.e., the number and types of structures the RNA molecule can adopt. However, most methods to predict RNA secondary structure do not provide the means to include the effect of modifications on the result. With the help of a heavily modified transfer RNA (tRNA) molecule, this chapter demonstrates how to include the effect of different base modifications into secondary structure prediction using the ViennaRNA Package. The constructive approach demonstrated here allows for the calculation of minimum free energy structure and suboptimal structures at different levels of modified base support. In particular we, show how to incorporate the isomerization of uridine to pseudouridine ( Ψ ) and the reduction of uridine to dihydrouridine (D).

DPred_3S: identifying dihydrouridine (D) modification on three species epitranscriptome based on multiple sequence-derived features

Introduction: Dihydrouridine (D) is a conserved modification of tRNA among all three life domains. D modification enhances the flexibility of a single nucleotide base in the spatial structure and is disease- and evolution-associated. Recent studies have also suggested the presence of dihydrouridine on mRNA. Methods: To identify D in epitranscriptome, we provided a prediction framework named "DPred_3S" based on the machine learning approach for three species D epitranscriptome, which used epitranscriptome sequencing data as training data for the first time. Results: The optimal features were evaluated by the F-score and integration of different features; our model achieved area under the receiver operating characteristic curve (AUROC) scores 0.955, 0.946, and 0.905 for Saccharomyces cerevisiae, Escherichia coli, and Schizosaccharomyces pombe, respectively. The performances of different machine learning algorithms were also compared in this study. Discussion: The high performances of our model suggest the D sites can be distinguished based on their surrounding sequence, but the lower performance of cross-species prediction may be limited by technique preferences.

Self-attention enabled deep learning of dihydrouridine (D) modification on mRNAs unveiled a distinct sequence signature from tRNAs

Dihydrouridine (D) is a modified pyrimidine nucleotide universally found in viral, prokaryotic, and eukaryotic species. It serves as a metabolic modulator for various pathological conditions, and its elevated levels in tumors are associated with a series of cancers. Precise identification of D sites on RNA is vital for understanding its biological function. A number of computational approaches have been developed for predicting D sites on tRNAs; however, none have considered mRNAs. We present here DPred, the first computational tool for predicting D on mRNAs in yeast from the primary RNA sequences. Built on a local self-attention layer and a convolutional neural network (CNN) layer, the proposed deep learning model outperformed classic machine learning approaches (random forest, support vector machines, etc.) and achieved reasonable accuracy and reliability with areas under the curve of 0.9166 and 0.9027 in jackknife cross-validation and on an independent testing dataset, respectively. Importantly, we showed that distinct sequence signatures are associated with the D sites on mRNAs and tRNAs, implying potentially different formation mechanisms and putative divergent functionality of this modification on the two types of RNA. DPred is available as a user-friendly Web server.

iDHU-Ensem: Identification of dihydrouridine sites through ensemble learning models

Background

Dihydrouridine (D) is one of the most significant uridine modifications that have a prominent occurrence in eukaryotes. The folding and conformational flexibility of transfer RNA (tRNA) can be attained through this modification.

Objective

The modification also triggers lung cancer in humans. The identification of D sites was carried out through conventional laboratory methods; however, those were costly and time-consuming. The readiness of RNA sequences helps in the identification of D sites through computationally intelligent models. However, the most challenging part is turning these biological sequences into distinct vectors.

Methods

The current research proposed novel feature extraction mechanisms and the identification of D sites in tRNA sequences using ensemble models. The ensemble models were then subjected to evaluation using k-fold cross-validation and independent testing.

Results

The results revealed that the stacking ensemble model outperformed all the ensemble models by revealing 0.98 accuracy, 0.98 specificity, 0.97 sensitivity, and 0.92 Matthews Correlation Coefficient. The proposed model, iDHU-Ensem, was also compared with pre-existing predictors using an independent test. The accuracy scores have shown that the proposed model in this research study performed better than the available predictors.

Conclusion

The current research contributed towards the enhancement of D site identification capabilities through computationally intelligent methods. A web-based server, iDHU-Ensem, was also made available for the researchers at https://taseersuleman-idhu-ensem-idhu-ensem.streamlit.app/.

Evolutionary Diversity of Dus2 Enzymes Reveals Novel Structural and Functional Features among Members of the RNA Dihydrouridine Synthases Family

Dihydrouridine (D) is an abundant modified base found in the tRNAs of most living organisms and was recently detected in eukaryotic mRNAs. This base confers significant conformational plasticity to RNA molecules. The dihydrouridine biosynthetic reaction is catalyzed by a large family of flavoenzymes, the dihydrouridine synthases (Dus). So far, only bacterial Dus enzymes and their complexes with tRNAs have been structurally characterized. Understanding the structure-function relationships of eukaryotic Dus proteins has been hampered by the paucity of structural data. Here, we combined extensive phylogenetic analysis with high-precision 3D molecular modeling of more than 30 Dus2 enzymes selected along the tree of life to determine the evolutionary molecular basis of D biosynthesis by these enzymes. Dus2 is the eukaryotic enzyme responsible for the synthesis of D20 in tRNAs and is involved in some human cancers and in the detoxification of β-amyloid peptides in Alzheimer's disease. In addition to the domains forming the canonical structure of all Dus, i.e., the catalytic TIM-barrel domain and the helical domain, both participating in RNA recognition in the bacterial Dus, a majority of Dus2 proteins harbor extensions at both ends. While these are mainly unstructured extensions on the N-terminal side, the C-terminal side extensions can adopt well-defined structures such as helices and beta-sheets or even form additional domains such as zinc finger domains. 3D models of Dus2/tRNA complexes were also generated. This study suggests that eukaryotic Dus2 proteins may have an advantage in tRNA recognition over their bacterial counterparts due to their modularity.

Identification of D Modification Sites Using a Random Forest Model Based on Nucleotide Chemical Properties

Dihydrouridine (D) is an abundant post-transcriptional modification present in transfer RNA from eukaryotes, bacteria, and archaea. D has contributed to treatments for cancerous diseases. Therefore, the precise detection of D modification sites can enable further understanding of its functional roles. Traditional experimental techniques to identify D are laborious and time-consuming. In addition, there are few computational tools for such analysis. In this study, we utilized eleven sequence-derived feature extraction methods and implemented five popular machine algorithms to identify an optimal model. During data preprocessing, data were partitioned for training and testing. Oversampling was also adopted to reduce the effect of the imbalance between positive and negative samples. The best-performing model was obtained through a combination of random forest and nucleotide chemical property modeling. The optimized model presented high sensitivity and specificity values of 0.9688 and 0.9706 in independent tests, respectively. Our proposed model surpassed published tools in independent tests. Furthermore, a series of validations across several aspects was conducted in order to demonstrate the robustness and reliability of our model.

Transcription-wide mapping of dihydrouridine reveals that mRNA dihydrouridylation is required for meiotic chromosome segregation

The epitranscriptome has emerged as a new fundamental layer of control of gene expression. Nevertheless, the determination of the transcriptome-wide occupancy and function of RNA modifications remains challenging. Here we have developed Rho-seq, an integrated pipeline detecting a range of modifications through differential modification-dependent rhodamine labeling. Using Rho-seq, we confirm that the reduction of uridine to dihydrouridine (D) by the Dus reductase enzymes targets tRNAs in E. coli and fission yeast. We find that the D modification is also present on fission yeast mRNAs, particularly those encoding cytoskeleton-related proteins, which is supported by large-scale proteome analyses and ribosome profiling. We show that the α-tubulin encoding mRNA nda2 undergoes Dus3-dependent dihydrouridylation, which affects its translation. The absence of the modification on nda2 mRNA strongly impacts meiotic chromosome segregation, resulting in low gamete viability. Applying Rho-seq to human cells revealed that tubulin mRNA dihydrouridylation is evolutionarily conserved.

Dihydrouridine synthesis in tRNAs is under reductive evolution in Mollicutes

Dihydrouridine (D) is a tRNA-modified base conserved throughout all kingdoms of life and assuming an important structural role. The conserved dihydrouridine synthases (Dus) carries out D-synthesis. DusA, DusB and DusC are bacterial members, and their substrate specificity has been determined in Escherichia coli. DusA synthesizes D20/D20a while DusB and DusC are responsible for the synthesis of D17 and D16, respectively. Here, we characterize the function of the unique dus gene encoding a DusB detected in Mollicutes, which are bacteria that evolved from a common Firmicute ancestor via massive genome reduction. Using in vitro activity tests as well as in vivo E. coli complementation assays with the enzyme from Mycoplasma capricolum (DusB_MCap), a model organism for the study of these parasitic bacteria, we show that, as expected for a DusB homolog, DusB_MCap modifies U17 to D17 but also synthetizes D20/D20a combining therefore both E. coli DusA and DusB activities. Hence, this is the first case of a Dus enzyme able to modify up to three different sites as well as the first example of a tRNA-modifying enzyme that can modify bases present on the two opposite sides of an RNA-loop structure. Comparative analysis of the distribution of DusB homologs in Firmicutes revealed the existence of three DusB subgroups namely DusB1, DusB2 and DusB3. The first two subgroups were likely present in the Firmicute ancestor, and Mollicutes have retained DusB1 and lost DusB2. Altogether, our results suggest that the multisite specificity of the M. capricolum DusB enzyme could be an ancestral property.

Identification of D Modification Sites by Integrating Heterogeneous Features in Saccharomyces cerevisiae

As an abundant post-transcriptional modification, dihydrouridine (D) has been found in transfer RNA (tRNA) from bacteria, eukaryotes, and archaea. Nonetheless, knowledge of the exact biochemical roles of dihydrouridine in mediating tRNA function is still limited. Accurate identification of the position of D sites is essential for understanding their functions. Therefore, it is desirable to develop novel methods to identify D sites. In this study, an ensemble classifier was proposed for the detection of D modification sites in the Saccharomyces cerevisiae transcriptome by using heterogeneous features. The jackknife test results demonstrate that the proposed predictor is promising for the identification of D modification sites. It is anticipated that the proposed method can be widely used for identifying D modification sites in tRNA.

Mapping of ribosomal 23S ribosomal RNA modifications in Clostridium sporogenes

All organisms contain RNA modifications in their ribosomal RNA (rRNA), but the importance, positions and exact function of these are still not fully elucidated. Various functions such as stabilizing structures, controlling ribosome assembly and facilitating interactions have been suggested and in some cases substantiated. Bacterial rRNA contains much fewer modifications than eukaryotic rRNA. The rRNA modification patterns in bacteria differ from each other, but too few organisms have been mapped to draw general conclusions. This study maps 23S ribosomal RNA modifications in Clostridium sporogenes that can be characterized as a non-toxin producing Clostridium botulinum. Clostridia are able to sporulate and thereby survive harsh conditions, and are in general considered to be resilient to antibiotics. Selected regions of the 23S rRNA were investigated by mass spectrometry and by primer extension analysis to pinpoint modified sites and the nature of the modifications. Apparently, C. sporogenes 23S rRNA contains few modifications compared to other investigated bacteria. No modifications were identified in domain II and III of 23S rRNA. Three modifications were identified in domain IV, all of which have also been found in other organisms. Two unusual modifications were identified in domain V, methylated dihydrouridine at position U2449 and dihydrouridine at position U2500 (Escherichia coli numbering), in addition to four previously known modified positions. The enzymes responsible for the modifications were searched for in the C. sporogenes genome using BLAST with characterized enzymes as query. The search identified genes potentially coding for RNA modifying enzymes responsible for most of the found modifications.

tRNA Modifications: Impact on Structure and Thermal Adaptation

Transfer RNAs (tRNAs) are central players in translation, functioning as adapter molecules between the informational level of nucleic acids and the functional level of proteins. They show a highly conserved secondary and tertiary structure and the highest density of post-transcriptional modifications among all RNAs. These modifications concentrate in two hotspots-the anticodon loop and the tRNA core region, where the D- and T-loop interact with each other, stabilizing the overall structure of the molecule. These modifications can cause large rearrangements as well as local fine-tuning in the 3D structure of a tRNA. The highly conserved tRNA shape is crucial for the interaction with a variety of proteins and other RNA molecules, but also needs a certain flexibility for a correct interplay. In this context, it was shown that tRNA modifications are important for temperature adaptation in thermophilic as well as psychrophilic organisms, as they modulate rigidity and flexibility of the transcripts, respectively. Here, we give an overview on the impact of modifications on tRNA structure and their importance in thermal adaptation.

The complete mitochondrial genome sequence of Sogatella furcifera (Horváth) and a comparative mitogenomic analysis of three predominant rice planthoppers

The white-backed planthopper (WBPH), Sogatella furcifera (Horváth), is one of the most destructive pests of rice crops in many Asian countries. Using long-PCR and shotgun library methods, we sequenced the entire mitochondrial genomes (mt-genomes) of two WBPH individuals. Total lengths of the mt-genome of the two WBPH individuals were 16,612 bp and 16,654 bp with an identical AT content of 76.19%. Among the 13 protein coding genes (PCGs), only nad5 used an atypical initiation codon GTG. Most of the tRNA genes had the typical cloverleaf secondary structure except that the dihydrouridine (DHU) arms in two trnS genes and the TΨC arm of trnG gene did not form a stable stem-loop structure. Similar to the brown planthopper (BPH), Nilaparvata lugens (Stål), and the small brown planthopper (SBPH), Laodelphax striatellus (Fallén), some extraordinary features were observed in the WBPH mt-genome. These include similar gene rearrangement pattern, unusually short length of the atp8 gene and variable numbers of tandem repeat (VNTR) structure in control region. Interestingly, the same tandem repeat unit with stable secondary structure appeared in two different planthoppers, WBPH and SBPH, which belong to two different genera of the Delphacidae. This peculiar feature provides a direct evidence for the close relationship between the two planthoppers and updates our understanding of the evolutionary characteristics of mitochondrial control region. Comparison with two other predominant rice planthoppers (BPH and SBPH) revealed that different PCGs of mitochondria exhibit different evolutionary patterns.

Structure of dihydrouridine synthase C (DusC) from Escherichia coli

Dihydrouridine (D) is one of the most widely conserved tRNA modifications. Dihydrouridine synthase (Dus) is responsible for introducing D modifications into RNA by the reduction of uridine. Recently, a unique substrate-recognition mechanism using a small adapter molecule has been proposed for Thermus thermophilus Dus (TthDusC). To acquire insight regarding its substrate-recognition mechanism, the crystal structure of DusC from Escherichia coli (EcoDusC) was determined at 2.1 Å resolution. EcoDusC was shown to be composed of two domains: an N-terminal catalytic domain and a C-terminal tRNA-binding domain. An L-shaped electron density surrounded by highly conserved residues was found in the active site, as observed for TthDus. Structure comparison with TthDus indicated that the N-terminal region has a similar structure, whereas the C-terminal domain has marked differences in its relative orientation to the N-terminal domain as well as in its own structure. These observations suggested that Dus proteins adopt a common substrate-recognition mechanism using an adapter molecule, whereas the manner of tRNA binding is diverse.

Fluorescent labeling of tRNA dihydrouridine residues: Mechanism and distribution

Dihydrouridine (DHU) positions within tRNAs have long been used as sites to covalently attach fluorophores, by virtue of their unique chemical reactivity toward reduction by NaBH(4), their abundance within prokaryotic and eukaryotic tRNAs, and the biochemical functionality of the labeled tRNAs so produced. Interpretation of experiments employing labeled tRNAs can depend on knowing the distribution of dye among the DHU positions present in a labeled tRNA. Here we combine matrix-assisted laser desorption/ionization mass spectroscopy (MALDI-MS) analysis of oligonucleotide fragments and thin layer chromatography to resolve and quantify sites of DHU labeling by the fluorophores Cy3, Cy5, and proflavin in Escherichia coli tRNA(Phe) and E. coli tRNA(Arg). The MALDI-MS results led us to re-examine the precise chemistry of the reactions that result in fluorophore introduction into tRNA. We demonstrate that, in contrast to an earlier suggestion that has long been unchallenged in the literature, such introduction proceeds via a substitution reaction on tetrahydrouridine, the product of NaBH(4) reduction of DHU, resulting in formation of substituted tetrahydrocytidines within tRNA.

Synthesis and functional activity of tRNAs labeled with fluorescent hydrazides in the D-loop

We describe an optimized procedure for replacing the dihydrouridine residues of charged tRNAs with Cy3 and Cy5 dyes linked to a hydrazide group, and demonstrate that the labeled molecules are functional in ribosomal activities including 30S initiation complex formation, EF-Tu-dependent binding to the ribosome, translocation, and polypeptide synthesis. This procedure should be straightforwardly generalizable to the incorporation of other hydrazide-linked fluorophores into tRNA or other dihydrouridine-containing RNAs. In addition, we use a rapid turnover FRET experiment, measuring energy transfer between Cy5-labeled tRNA(fMet) and Cy3-labeled fMetPhe-tRNA(Phe), to obtain direct evidence supporting the hypothesis that the early steps of translocation involve movements of the flexible 3'-single-stranded regions of the tRNAs, with the considerable increase in the distance separating the two tRNA tertiary cores occurring later in the process.

Fluorescent labeling of tRNAs for dynamics experiments

Transfer RNAs (tRNAs) are substrates for complex enzymes, such as aminoacyl-tRNA synthetases and ribosomes, and play an essential role in translation of genetic information into protein sequences. Here we describe a general method for labeling tRNAs with fluorescent dyes, so that the activities and dynamics of the labeled tRNAs can be directly monitored by fluorescence during the ribosomal decoding process. This method makes use of the previously reported fluorescent labeling of natural tRNAs at dihydrouridine (D) positions, but extends the previous method to synthetic tRNAs by preparing tRNA transcripts and introducing D residues into transcripts with the yeast enzyme Dus1p dihydrouridine synthase. Using the unmodified transcript of Escherichia coli tRNAPro as an example, which has U17 and U17a in the D loop, we show that Dus1p catalyzes conversion of one of these Us (mostly U17a) to D, and that the modified tRNA can be labeled with the fluorophores proflavin and rhodamine 110, with overall labeling yields comparable to those obtained with the native yeast tRNAPhe. Further, the transcript of yeast tRNAPhe, modified by Dus1p and labeled with proflavin, translocates on the ribosome at a rate similar to that of the proflavin-labeled native yeast tRNAPhe. These results demonstrate that synthetic tRNA transcripts, which may be designed to contain mutations not found in nature, can be labeled and studied. Such labeled tRNAs should have broad utility in research that involves studies of tRNA maturation, aminoacylation, and tRNA-ribosome interactions.