T-psi-C: user friendly database of tRNA sequences and structures

Progress in Tandem Mass Spectrometry Data Analysis for Nucleic Acids

Mass spectrometry (MS) has become a critical tool in the characterization of covalently modified nucleic acids. Well-developed bottom-up approaches, where nucleic acids are digested with an endonuclease and the resulting oligonucleotides are separated before MS and MS/MS analysis, provide substantial insight into modified nucleotides in biological and synthetic nucleic. Top-down MS presents an alternative approach where the entire nucleic acid molecule is introduced to the mass spectrometer intact and then fragmented by MS/MS. Current top-down MS workflows have incorporated automated, on-line HPLC workflows to enable rapid desalting of nucleic acid samples for facile mass analysis without complication from adduction. Furthermore, optimization of MS/MS parameters utilizing collision, electron, or photon-based activation methods have enabled effective bond cleavage throughout the phosphodiester backbone while limiting secondary fragmentation, allowing characterization of progressively larger (~100 nt) nucleic acids and localization of covalent modifications. Development of software applications to perform automated identification of fragment ions has accelerated the broader adoption of mass spectrometry for analysis of nucleic acids. This review focuses on progress in tandem mass spectrometry for characterization of nucleic acids with particular emphasis on the software tools that have proven critical for advancing the field.

Quantitative detection of pseudouridine in RNA by mass spectrometry

Pseudouridine (Ψ) is one of the most prevalent and dynamic modification in RNA, and was shown to evade the host immune response in mRNA vaccines. Despite its significance, the biological role of Ψ remains poorly understood as certain key limitations and challenges in the detection of Ψ are yet to be overcome. In account of this, we report the usage of a chemical labelling strategy for the first quantitative detection of Ψ by mass spectrometry. We demonstrate a labelling efficiency exceeding 99% in isolated yeast tRNAs hosting multiple Ψs. LC-MS/MS analysis enables precise mapping of Ψ at single-base resolution, while simultaneously capturing a wide array of additional post-transcriptional modifications, which is not achieved with current sequencing technologies. This advancement may help unravel the dynamics and biological implications of Ψ, shedding light on its interplay with other modifications and deepening our understanding of its functional role.

Quantitative analysis of tRNA abundance and modifications by nanopore RNA sequencing

Transfer RNAs (tRNAs) play a central role in protein translation. Studying them has been difficult in part because a simple method to simultaneously quantify their abundance and chemical modifications is lacking. Here we introduce Nano-tRNAseq, a nanopore-based approach to sequence native tRNA populations that provides quantitative estimates of both tRNA abundances and modification dynamics in a single experiment. We show that default nanopore sequencing settings discard the vast majority of tRNA reads, leading to poor sequencing yields and biased representations of tRNA abundances based on their transcript length. Re-processing of raw nanopore current intensity signals leads to a 12-fold increase in the number of recovered tRNA reads and enables recapitulation of accurate tRNA abundances. We then apply Nano-tRNAseq to Saccharomyces cerevisiae tRNA populations, revealing crosstalks and interdependencies between different tRNA modification types within the same molecule and changes in tRNA populations in response to oxidative stress.

A selective and sensitive detection system for 4-thiouridine modification in RNA

4-Thiouridine (s4U) is a modified nucleoside, found at positions 8 and 9 in tRNA from eubacteria and archaea. Studies of the biosynthetic pathway and physiological role of s4U in tRNA are ongoing in the tRNA modification field. s4U has also recently been utilized as a biotechnological tool for analysis of RNAs. Therefore, a selective and sensitive system for the detection of s4U is essential for progress in the fields of RNA technologies and tRNA modification. Here, we report the use of biotin-coupled 2-aminoethyl-methanethiosulfonate (MTSEA biotin-XX) for labeling of s4U and demonstrate that the system is sensitive and quantitative. This technique can be used without denaturation; however, addition of a denaturation step improves the limit of detection. Thermus thermophilus tRNAs, which abundantly contain 5-methyl-2-thiouridine, were tested to investigate the selectivity of the MTSEA biotin-XX s4U detection system. The system did not react with 5-methyl-2-thiouridine in tRNAs from a T. thermophilus tRNA 4-thiouridine synthetase (thiI) gene deletion strain. Thus, the most useful advantage of the MTSEA biotin-XX s4U detection system is that MTSEA biotin-XX reacts only with s4U and not with other sulfur-containing modified nucleosides such as s2U derivatives in tRNAs. Furthermore, the MTSEA biotin-XX s4U detection system can analyze multiple samples in a short time span. The MTSEA biotin-XX s4U detection system can also be used for the analysis of s4U formation in tRNA. Finally, we demonstrate that the MTSEA biotin-XX system can be used to visualize newly transcribed tRNAs in S. cerevisiae cells.

Dynamic regulation and key roles of ribonucleic acid methylation

Ribonucleic acid (RNA) methylation is the most abundant modification in biological systems, accounting for 60% of all RNA modifications, and affects multiple aspects of RNA (including mRNAs, tRNAs, rRNAs, microRNAs, and long non-coding RNAs). Dysregulation of RNA methylation causes many developmental diseases through various mechanisms mediated by N ⁶-methyladenosine (m⁶A), 5-methylcytosine (m⁵C), N ¹-methyladenosine (m¹A), 5-hydroxymethylcytosine (hm⁵C), and pseudouridine (Ψ). The emerging tools of RNA methylation can be used as diagnostic, preventive, and therapeutic markers. Here, we review the accumulated discoveries to date regarding the biological function and dynamic regulation of RNA methylation/modification, as well as the most popularly used techniques applied for profiling RNA epitranscriptome, to provide new ideas for growth and development.

Required Elements in tRNA for Methylation by the Eukaryotic tRNA (Guanine-N2-) Methyltransferase (Trm11-Trm112 Complex)

The Saccharomyces cerevisiae Trm11 and Trm112 complex (Trm11-Trm112) methylates the 2-amino group of guanosine at position 10 in tRNA and forms N²-methylguanosine. To determine the elements required in tRNA for methylation by Trm11-Trm112, we prepared 60 tRNA transcript variants and tested them for methylation by Trm11-Trm112. The results show that the precursor tRNA is not a substrate for Trm11-Trm112. Furthermore, the CCA terminus is essential for methylation by Trm11-Trm112, and Trm11-Trm112 also only methylates tRNAs with a regular-size variable region. In addition, the G10-C25 base pair is required for methylation by Trm11-Trm112. The data also demonstrated that Trm11-Trm112 recognizes the anticodon-loop and that U38 in tRNA^Ala acts negatively in terms of methylation. Likewise, the U32-A38 base pair in tRNA^Cys negatively affects methylation. The only exception in our in vitro study was tRNA^Val_AAC1. Our experiments showed that the tRNA^Val_AAC1 transcript was slowly methylated by Trm11-Trm112. However, position 10 in this tRNA was reported to be unmodified G. We purified tRNA^Val_AAC1 from wild-type and trm11 gene deletion strains and confirmed that a portion of tRNA^Val_AAC1 is methylated by Trm11-Trm112 in S. cerevisiae. Thus, our study explains the m²G10 modification pattern of all S. cerevisiae class I tRNAs and elucidates the Trm11-Trm112 binding sites.

“Superwobbling” and tRNA-34 Wobble and tRNA-37 Anticodon Loop Modifications in Evolution and Devolution of the Genetic Code

The genetic code evolved around the reading of the tRNA anticodon on the primitive ribosome, and tRNA-34 wobble and tRNA-37 modifications coevolved with the code. We posit that EF-Tu, the closing mechanism of the 30S ribosomal subunit, methylation of wobble U34 at the 5-carbon and suppression of wobbling at the tRNA-36 position were partly redundant and overlapping functions that coevolved to establish the code. The genetic code devolved in evolution of mitochondria to reduce the size of the tRNAome (all of the tRNAs of an organism or organelle). “Superwobbling” or four-way wobbling describes a major mechanism for shrinking the mitochondrial tRNAome. In superwobbling, unmodified wobble tRNA-U34 can recognize all four codon wobble bases (A, G, C and U), allowing a single unmodified tRNA-U34 to read a 4-codon box. During code evolution, to suppress superwobbling in 2-codon sectors, U34 modification by methylation at the 5-carbon position appears essential. As expected, at the base of code evolution, tRNA-37 modifications mostly related to the identity of the adjacent tRNA-36 base. TRNA-37 modifications help maintain the translation frame during elongation.

Non-Redundant tRNA Reference Sequences for Deep Sequencing Analysis of tRNA Abundance and Epitranscriptomic RNA Modifications

Analysis of RNA by deep-sequencing approaches has found widespread application in modern biology. In addition to measurements of RNA abundance under various physiological conditions, such techniques are now widely used for mapping and quantification of RNA modifications. Transfer RNA (tRNA) molecules are among the frequent targets of such investigation, since they contain multiple modified residues. However, the major challenge in tRNA examination is related to a large number of duplicated and point-mutated genes encoding those RNA molecules. Moreover, the existence of multiple isoacceptors/isodecoders complicates both the analysis and read mapping. Existing databases for tRNA sequencing provide near exhaustive listings of tRNA genes, but the use of such highly redundant reference sequences in RNA-seq analyses leads to a large number of ambiguously mapped sequencing reads. Here we describe a relatively simple computational strategy for semi-automatic collapsing of highly redundant tRNA datasets into a non-redundant collection of reference tRNA sequences. The relevance of the approach was validated by analysis of experimentally obtained tRNA-sequencing datasets for different prokaryotic and eukaryotic model organisms. The data demonstrate that non-redundant tRNA reference sequences allow improving unambiguous mapping of deep sequencing data.

Building a tRNA thermometer to estimate microbial adaptation to temperature

Because ambient temperature affects biochemical reactions, organisms living in extreme temperature conditions adapt protein composition and structure to maintain biochemical functions. While it is not feasible to experimentally determine optimal growth temperature (OGT) for every known microbial species, organisms adapted to different temperatures have measurable differences in DNA, RNA and protein composition that allow OGT prediction from genome sequence alone. In this study, we built a 'tRNA thermometer' model using tRNA sequence to predict OGT. We used sequences from 100 archaea and 683 bacteria species as input to train two Convolutional Neural Network models. The first pairs individual tRNA sequences from different species to predict which comes from a more thermophilic organism, with accuracy ranging from 0.538 to 0.992. The second uses the complete set of tRNAs in a species to predict optimal growth temperature, achieving a maximum ${r^2}$ of 0.86; comparable with other prediction accuracies in the literature despite a significant reduction in the quantity of input data. This model improves on previous OGT prediction models by providing a model with minimum input data requirements, removing laborious feature extraction and data preprocessing steps and widening the scope of valid downstream analyses.

Systematics for types and effects of RNA variations

Systematics is described for annotation of variations in RNA molecules. The conceptual framework is part of Variation Ontology (VariO) and facilitates depiction of types of variations, their functional and structural effects and other consequences in any RNA molecule in any organism. There are more than 150 RNA related VariO terms in seven levels, which can be further combined to generate even more complicated and detailed annotations. The terms are described together with examples, usually for variations and effects in human and in diseases. RNA variation type has two subcategories: variation classification and origin with subterms. Altogether six terms are available for function description. Several terms are available for affected RNA properties. The ontology contains also terms for structural description for affected RNA type, post-transcriptional RNA modifications, secondary and tertiary structure effects and RNA sugar variations. Together with the DNA and protein concepts and annotations, RNA terms allow comprehensive description of variations of genetic and non-genetic origin at all possible levels. The VariO annotations are readable both for humans and computer programs for advanced data integration and mining.

A Census and Categorization Method of Epitranscriptomic Marks

In the past few years, thorough investigation of chemical modifications operated in the cells on ribonucleic acid (RNA) molecules is gaining momentum. This new field of research has been dubbed “epitranscriptomics”, in analogy to best-known epigenomics, to stress the potential of ensembles of RNA modifications to constitute a post-transcriptional regulatory layer of gene expression orchestrated by writer, reader, and eraser RNA-binding proteins (RBPs). In fact, epitranscriptomics aims at identifying and characterizing all functionally relevant changes involving both non-substitutional chemical modifications and editing events made to the transcriptome. Indeed, several types of RNA modifications that impact gene expression have been reported so far in different species of cellular RNAs, including ribosomal RNAs, transfer RNAs, small nuclear RNAs, messenger RNAs, and long non-coding RNAs. Supporting functional relevance of this largely unknown regulatory mechanism, several human diseases have been associated directly to RNA modifications or to RBPs that may play as effectors of epitranscriptomic marks. However, an exhaustive epitranscriptome’s characterization, aimed to systematically classify all RNA modifications and clarify rules, actors, and outcomes of this promising regulatory code, is currently not available, mainly hampered by lack of suitable detecting technologies. This is an unfortunate limitation that, thanks to an unprecedented pace of technological advancements especially in the sequencing technology field, is likely to be overcome soon. Here, we review the current knowledge on epitranscriptomic marks and propose a categorization method based on the reference ribonucleotide and its rounds of modifications (“stages”) until reaching the given modified form. We believe that this classification scheme can be useful to coherently organize the expanding number of discovered RNA modifications.

Survey and Validation of tRNA Modifications and Their Corresponding Genes in Bacillus subtilis sp Subtilis Strain 168

Extensive knowledge of both the nature and position of tRNA modifications in all cellular tRNAs has been limited to two bacteria, Escherichia coli and Mycoplasma capricolum. Bacillus subtilis sp subtilis strain 168 is the model Gram-positive bacteria and the list of the genes involved in tRNA modifications in this organism is far from complete. Mass spectrometry analysis of bulk tRNA extracted from B. subtilis, combined with next generation sequencing technologies and comparative genomic analyses, led to the identification of 41 tRNA modification genes with associated confidence scores. Many differences were found in this model Gram-positive bacteria when compared to E. coli. In general, B. subtilis tRNAs are less modified than those in E. coli, even if some modifications, such as m1A22 or ms2t6A, are only found in the model Gram-positive bacteria. Many examples of non-orthologous displacements and of variations in the most complex pathways are described. Paralog issues make uncertain direct annotation transfer from E. coli to B. subtilis based on homology only without further experimental validation. This difficulty was shown with the identification of the B. subtilis enzyme that introduces ψ at positions 31/32 of the tRNAs. This work presents the most up to date list of tRNA modification genes in B. subtilis, identifies the gaps in knowledge, and lays the foundation for further work to decipher the physiological role of tRNA modifications in this important model organism and other bacteria.