Modification Of Ribonucleic Acid Research Articles

Mapping m6A Sites on HIV-1 RNA Using Oligonucleotide LC-MS/MS.

The biological significance of chemical modifications to the ribonucleic acid (RNA) of human immunodeficiency virus type-1 (HIV-1) has been recognized. However, our understanding of the site-specific and context-dependent roles of these chemical modifications remains limited, primarily due to the absence of nucleotide-resolution mapping of modification sites. In this study, we present a method for achieving nucleotide-resolution mapping of chemical modification sites on HIV-1 RNA using liquid chromatography and tandem mass spectrometry (LC-MS/MS). LC-MS/MS, a powerful tool capable of directly analyzing native RNAs, has proven effective for mapping RNA modifications in small RNA molecules, including ribosomal RNA and transfer RNA. However, longer RNAs have posed challenges, such as the 9 Kb HIV-1 virion RNA, due to the complexity of and ambiguity in mass differences among RNase T1-cleaved RNA fragments in LC-MS/MS data. Here, we introduce a new target RNA enrichment method to isolate small local RNA fragments of HIV-1 RNA that potentially harbor site-specific N6-methyladenosine (m6A) modifications. In our initial trial, we used target-specific DNA probes only and encountered insufficient RNA fragmentation due to inefficient S1 digestion near the target site. Recognizing that inefficient S1 digestion by HIV-1 RNA is likely due to the formation of secondary structures in proximity to the target site, we designed multiple DNA probes annealing to various sites of HIV-1 RNA to better control the structures of RNA substrates for S1 digestion. The use of these non-target DNA probes significantly improved the isolation of more homogeneous target RNA fragments of approximately 50 bases in length. Oligonucleotide LC-MS/MS analysis of these isolated target RNA fragments successfully separated and detected both m6A-methylated and non-methylated oligomers at the two m6A-predicted sites. The principle of this new target enrichment strategy holds promise and should be broadly applicable to the analysis of any lengthy RNA that was previously deemed infeasible for investigation using oligonucleotide LC-MS/MS.

Bioinspired Spatiotemporal Management toward RNA Therapies.

Ribonucleic acid (RNA)-based therapies have become an attractive topic in disease intervention, especially with some that have been approved by the FDA such as the mRNA COVID-19 vaccine (Comirnaty, Pfizer-BioNTech, and Spikevax, Moderna) and Patisiran (siRNA-based drug for liver delivery). However, extensive applications are still facing challenges in delivering highly negatively charged RNA to the targeted site. Therapeutic delivery strategies including RNA modifications, RNA conjugates, and RNA polyplexes and delivery platforms such as viral vectors, nanoparticle-based delivery platforms, and hydrogel-based delivery platforms as potential nucleic acid-releasing depots have been developed to enhance their cellular uptake and protect nucleic acid from being degraded by immune systems. Here, we review the growing number of viral vectors, nanoparticles, and hydrogel-based RNA delivery systems; describe RNA loading/release mechanism induced by environmental stimulations including light, heat, pH, or enzyme; discuss their physical or chemical interactions; and summarize the RNA therapeutics release period (temporal) and their target cells/organs (spatial). Finally, we describe current concerns, highlight current challenges and future perspectives of RNA-based delivery systems, and provide some possible research areas that provide opportunities for clinical translation of RNA delivery carriers.

Recent Advances in RNA-Targeted Cancer Therapy.

Ribonucleic acid (RNA) plays a pivotal role in gene regulation and protein biosynthesis. Interfering the physiological function of key RNAs to induce cell apoptosis holds great promise for cancer treatment. Many RNA-targeted anti-cancer strategies have emerged continuously. Among them, RNA interference (RNAi) has been recognized as a promising therapeutic modality for various disease treatments. Nevertheless, the primary obstacle in siRNA delivery-escaping the endosome and crossing the plasma membrane severely impedes its therapeutic potential. Thus far, a variety of nanosystems as well as carrier-free bioconjugation for siRNA delivery have been developed and employed to enhance the drug delivery and anti-tumor efficiency. Besides, the use of small molecules to target specific RNA structures and disrupt their function, along with the covalent modification of RNA, has also drawn tremendous attention recently owing to high therapeutic efficacy. In this review, we will provide an overview of recent progress in RNA-targeted cancer therapy including various siRNA delivery strategies, RNA-targeting small molecules, and newly emerged covalent RNA modification. Finally, challenges and future perspectives faced in this research field will be discussed.

The Diversity and Functions of Plant RNA Modifications: What We Know and Where We Go from Here.

Since the discovery of the first ribonucleic acid (RNA) modifications in transfer RNAs (tRNAs) and ribosomal RNAs (rRNAs), scientists have been on a quest to decipher the identities and functions of RNA modifications in biological systems. The last decade has seen monumental growth in the number of studies that have characterized and assessed the functionalities of RNA modifications in the field of plant biology. Owing to these studies, we now categorize RNA modifications based on their chemical nature and the RNA on which they are found, as well as the array of proteins that are involved in the processes that add, read, and remove them from an RNA molecule. Beyond their identity, another key piece of the puzzle is the functional significance of the various types of RNA modifications. Here, we shed light on recent studies that help establish our current understanding of the diversity of RNA modifications found in plant transcriptomes and the functions they play at both the molecular (e.g., RNA stability, translation, and transport) and organismal (e.g., stress response and development) levels. Finally, we consider the key research questions related to plant gene expression and biology in general and highlight developments in various technologies that are driving our insights forward in this research area. Expected final online publication date for the Annual Review of Plant Biology, Volume 74 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Overexpression of TMEM150A in glioblastoma multiforme patients correlated with dismal prognoses and compromised immune statuses.

Transmembrane proteins have exhibited a significant correlation with glioblastoma multiforme (GBM). The current study elucidates the roles of transmembrane protein 150A (TMEM150A) in GBM. Data on patients with GBM were collected from The Cancer Genome Atlas and Xena databases. The objective was to identify the expression levels of TMEM150A in patients with GBM, and evaluate its diagnostic and prognostic values, accomplished using the receiver operating characteristic and survival analyses. On a cellular level, Cell Counting Kit-8, Wound healing, and Transwell experiments were performed to gauge the impact of TMEM150A on cell growth and migration. The study further investigated the correlation between TMEM150A expression and immune status, along with ribonucleic acid (RNA) modifications in GBM. The findings demonstrated TMEM150A overexpression in the cancerous tissues of patients with GBM, with an area under the curve value of 0.95. TMEM150A overexpression was significantly correlated with poor prognostic indicators. TMEM150A overexpression and isocitrate dehydrogenase (IDH) mutation status were predictive of poor survival time among patients with GBM. In vitro experiments indicated that suppressing TMEM150A expression could inhibit GBM cell proliferation, migration, and invasion. Moreover, TMEM150A overexpression was associated with stromal, immune, and estimate scores, immune cells (such as the T helper (Th) 17 cells, Th2 cells, and regulatory T cells), cell markers, and RNA modifications. Therefore, TMEM150A overexpression might serve as a promising biomarker for predicting poor prognosis in patients with GBM. Inhibiting TMEM150A expression holds the potential for improving the survival time of patients with GBM.

Molecular Characterization and Clinical Characteristics of m5C-Based RNA Methylation in Spinal Cord Injury: Validated by qPCR.

Aberrant patterns of 5-methylcytosine (m5C)-based ribonucleic acid (RNA) methylation have critical roles in various human diseases, but their importance in spinal cord injury (SCI) is largely unknown. We explore the expression patterns and potential roles of m5C-based regulators of RNA modification after SCI. We analyzed 16 m5C-based regulators of RNA modification in tissues with SCI and normal rats from the Gene Expression Omnibus database. We constructed a "gene signature" of m5C-based regulators of RNA modification to predict the prognosis of SCI using least absolute shrinkage and selection operator regression and random-forest strategy. We found that the m5C-related genes, deoxyribonucleic acid (DNA) methyltransferase1 (Dnmt1), methyl-CpG binding domain protein 2 (Mbd2), ubiquitin-like with PHD and ring finger domains 1 (Uhrf1), uracil-N-glycosylase (Ung), and zinc finger and BTB(brica-brac, tramtrack, and broad) domain containing 38 (Zbtb38) had high expression, and zinc finger and BTB domain containing 4 (Zbtb4) had low expression in SCI. Analysis of the correlation between the gene sets of m5C-based regulators of RNA modification and immune-cell infiltration and immune response revealed Dnmt1, DNA methyltransferases 3A (Dnmt3a), Mbd2, and Ung to be positive regulators of the immune microenvironment, and Zbtb4 may negatively regulate the immune environment. Then, two molecular subtypes were identified based on 16 m5C-regulated genes. Functional-enrichment analysis of differentially expressed genes between different patterns of m5C-based modification was undertaken. Through the creation of a protein-protein interaction network, we screened 11 hub genes. We demonstrated their importance between SCI group and sham group using real-time reverse transcription-quantitative polymerase chain reaction in rat model. Expression of hub genes did not correlate with mitophagy but was positively correlated with endoplasmic reticulum stress (ERS), which suggested that there may be differences in ERS between different patterns of m5C-based modification. This present study explored and discovered the close link between m5C regulators-related genes and SCI. We also hope our findings may contribute to further mechanistic and therapeutic research on the role of key m5C regulators after SCI.

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.

Mixed-Weight Neural Bagging for Detecting m6A Modifications in SARS-CoV-2 RNA Sequencing.

The m6A modification is the most common ribonucleic acid (RNA) modification, playing a role in prompting the virus's gene mutation and protein structure changes in the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Nanopore single-molecule direct RNA sequencing (DRS) provides data support for RNA modification detection, which can preserve the potential m6A signature compared to second-generation sequencing. However, due to insufficient DRS data, there is a lack of methods to find m6A RNA modifications in DRS. Our purpose is to identify m6A modifications in DRS precisely. We present a methodology for identifying m6A modifications that incorporated mapping and extracted features from DRS data. To detect m6A modifications, we introduce an ensemble method called mixed-weight neural bagging (MWNB), trained with 5-base RNA synthetic DRS containing modified and unmodified m6A. Our MWNB model achieved the highest classification accuracy of 97.85% and AUC of 0.9968. Additionally, we applied the MWNB model to the COVID-19 dataset; the experiment results reveal a strong association with biomedical experiments. Our strategy enables the prediction of m6A modifications using DRS data and completes the identification of m6A modifications on the SARS-CoV-2. The Corona Virus Disease 2019 (COVID-19) outbreak has significantly influence, caused by the SARS-CoV-2. An RNA modification called m6A is connected with viral infections. The appearance of m6A modifications related to several essential proteins affects proteins' structure and function. Therefore, finding the location and number of m6A RNA modifications is crucial for subsequent analysis of the protein expression profile.

Non-Coding RNA m6A Modification in Cancer: Mechanisms and Therapeutic Targets.

Recently, N6-methyl-adenosine (m6A) ribonucleic acid (RNA) modification, a critical and common internal RNA modification in higher eukaryotes, has generated considerable research interests. Extensive studies have revealed that non-coding RNA m6A modifications (e.g. microRNAs, long non-coding RNAs, and circular RNAs) are associated with tumorigenesis, metastasis, and other tumour characteristics; in addition, they are crucial molecular regulators of cancer progression. In this review, we discuss the relationship between non-coding RNA m6A modification and cancer progression from the perspective of various cancers. In particular, we focus on important mechanisms in tumour progression such as proliferation, apoptosis, invasion and metastasis, tumour angiogenesis. In addition, we introduce clinical applications to illustrate more vividly that non-coding RNA m6A modification has broad research prospects. With this review, we aim to summarize the latest insights and ideas into non-coding RNA m6A modification in cancer progression and targeted therapy, facilitating further research.

Identification of an eight-m6A RNA methylation regulator prognostic signature of uterine corpus endometrial carcinoma based on bioinformatics analysis.

N6-methyladenosine (m6A) methylation is proved to play a significant role in human cancers. This study aimed to explore the association between m6A ribonucleic acid (RNA) methylation regulators and uterine corpus endometrial carcinoma (UCEC), and build a prognostic signature of m6A regulators for UCEC.RNA-seq transcriptome data and clinicopathological data of UCEC were downloaded from the Cancer Genome Atlas database. We compared the expression of 23 m6A-regulators in tumor tissues and nontumor tissues. Then we classified the data into 3 clusters by consensus clustering analysis. Several regulators were picked out as the prognostic signature of patients with UCEC based on least absolute shrinkage and selection operator Cox regression analysis. Additionally, we established a predictive nomogram to calculate survival times. Finally, we used receiver operating characteristic curve, univariate Cox regression analysis, and multivariate Cox regression analysis to further verify the prognostic value of the risk signature consisting of m6A regulators.The expression of 18/23 m6A regulators was significantly different in UCEC compared with normal samples. Gene ontology functional analysis of these regulators revealed that they were mainly participated in RNA splicing, stabilization, modification, and degradation. LRPPRC, IGFBP2, KIAA1429, IGFBP3, FMR1, YTHDF1, METTL14, and YTHDF2 were selected to construct the risk signature and predictive nomogram. The results of receiver operating characteristic curve, univariate Cox regression analysis, and multivariate Cox regression analysis for the risk signature showed a good predictive performance for UCEC.The risk signature of 8-m6A regulators has potential prognostic value for patients with UCEC.

Weakly supervised learning of RNA modifications from low-resolution epitranscriptome data.

MotivationIncreasing evidence suggests that post-transcriptional ribonucleic acid (RNA) modifications regulate essential biomolecular functions and are related to the pathogenesis of various diseases. Precise identification of RNA modification sites is essential for understanding the regulatory mechanisms of RNAs. To date, many computational approaches for predicting RNA modifications have been developed, most of which were based on strong supervision enabled by base-resolution epitranscriptome data. However, high-resolution data may not be available.ResultsWe propose WeakRM, the first weakly supervised learning framework for predicting RNA modifications from low-resolution epitranscriptome datasets, such as those generated from acRIP-seq and hMeRIP-seq. Evaluations on three independent datasets (corresponding to three different RNA modification types and their respective sequencing technologies) demonstrated the effectiveness of our approach in predicting RNA modifications from low-resolution data. WeakRM outperformed state-of-the-art multi-instance learning methods for genomic sequences, such as WSCNN, which was originally designed for transcription factor binding site prediction. Additionally, our approach captured motifs that are consistent with existing knowledge, and visualization of the predicted modification-containing regions unveiled the potentials of detecting RNA modifications with improved resolution.Availability implementationThe source code for the WeakRM algorithm, along with the datasets used, are freely accessible at: https://github.com/daiyun02211/WeakRMSupplementary information Supplementary data are available at Bioinformatics online.

Machine learning applications in RNA modification sites prediction.

Ribonucleic acid (RNA) modifications are post-transcriptional chemical composition changes that have a fundamental role in regulating the main aspect of RNA function. Recently, large datasets have become available thanks to the recent development in deep sequencing and large-scale profiling. This availability of transcriptomic datasets has led to increased use of machine learning based approaches in epitranscriptomics, particularly in identifying RNA modifications. In this review, we comprehensively explore machine learning based approaches used for the prediction of 11 RNA modification types, namely, , , , , , , , , , , and . This review covers the life cycle of machine learning methods to predict RNA modification sites including available benchmark datasets, feature extraction, and classification algorithms. We compare available methods in terms of datasets, target species, approach, and accuracy for each RNA modification type. Finally, we discuss the advantages and limitations of the reviewed approaches and suggest future perspectives.

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.

Characterization of Post-Transcriptional RNA Modifications by Sheathless Capillary Electrophoresis-High Resolution Mass Spectrometry.

Over the past decade there has been a growing interest in RNA modification analysis. High performance liquid chromatography-tandem mass spectrometry coupling (HPLC-MS/MS) is classically used to characterize post-transcriptional modifications of ribonucleic acids (RNAs). Here we propose a novel and simple workflow based on capillary zone electrophoresis-tandem mass spectrometry (CE-MS/MS), in positive mode, to characterize RNA modifications at nucleoside and oligonucleotide levels. By first totally digesting the purified RNA, prior to CE-MS/MS analysis, we were able to identify the nucleoside modifications. Then, using a bottom-up approach, sequencing of the RNAs and mapping of the modifications were performed. Sequence coverages from 68% to 97% were obtained for four tRNAs. Furthermore, unambiguous identification and mapping of several modifications were achieved.

The Emerging Roles of RNA Modifications in Glioblastoma.

Glioblastoma (GBM) is a grade IV glioma that is the most malignant brain tumor type. Currently, there are no effective and sufficient therapeutic strategies for its treatment because its pathological mechanism is not fully characterized. With the fast development of the Next Generation Sequencing (NGS) technology, more than 170 kinds of covalent ribonucleic acid (RNA) modifications are found to be extensively present in almost all living organisms and all kinds of RNAs, including ribosomal RNAs (rRNAs), transfer RNAs (tRNAs) and messenger RNAs (mRNAs). RNA modifications are also emerging as important modulators in the regulation of biological processes and pathological progression, and study of the epi-transcriptome has been a new area for researchers to explore their connections with the initiation and progression of cancers. Recently, RNA modifications, especially m6A, and their RNA-modifying proteins (RMPs) such as methyltransferase like 3 (METTL3) and α-ketoglutarate-dependent dioxygenase alkB homolog 5 (ALKBH5), have also emerged as important epigenetic mechanisms for the aggressiveness and malignancy of GBM, especially the pluripotency of glioma stem-like cells (GSCs). Although the current study is just the tip of an iceberg, these new evidences will provide new insights for possible GBM treatments. In this review, we summarize the recent studies about RNA modifications, such as N6-methyladenosine (m6A), N6,2′O-dimethyladenosine (m6Am), 5-methylcytosine (m5C), N1-methyladenosine (m1A), inosine (I) and pseudouridine (ψ) as well as the corresponding RMPs including the writers, erasers and readers that participate in the tumorigenesis and development of GBM, so as to provide some clues for GBM treatment.

RNA modifications and the link to human disease.

Ribonucleic acid (RNA) is involved in translation and transcription, which are the mechanisms in which cells express genes (Alberts et al., 2002). The three classes of RNA discussed are transfer RNA (tRNA), messenger RNA (mRNA), and ribosomal RNA (rRNA). mRNA is the transcript encoded from DNA, rRNA is associated with ribosomes, and tRNA is associated with amino acids and is used to read mRNA transcripts to make proteins (Lodish, Berk, Zipursky, et al., 2000). Interestingly, the function of tRNA, rRNA, and mRNA can be significantly altered by chemical modifications at the co-transcriptional and post-transcriptional levels, and there are over 171 of these modifications identified thus far (Boccaletto et al., 2018; Modomics-Modified bases, 2017). Several of these modifications are linked to diseases such as cancer, diabetes, and neurological disorders. In this review, we will introduce a few RNA modifications with biological functions and how dysregulation of these RNA modifications is linked to human disease.

Surpassing limits of static RNA modification analysis with dynamic NAIL-MS.

Ribonucleic acids (RNA) are extensively modified. These modifications are quantified by mass spectrometry (LC-MS/MS) to determine the abundance of a modification under certain conditions or in various genetic backgrounds. With LC-MS/MS the steady state of modifications is determined, and thus we only have a static view of the dynamics of RNA modifications. With nucleic acid isotope labeling coupled mass spectrometry (NAIL-MS) we overcome this limitation and get access to the dynamics of RNA modifications. We describe labeling techniques for E. coli, S. cerevisiae and human cell culture and the current instrumental limitations. We present the power of NAIL-MS but we also outline validation experiments, which are necessary for correct data interpretation. As an example, we apply NAIL-MS to study the demethylation of adenine and cytidine, which are methylated by the damaging agent methyl-methanesulfonate in E. coli. With NAIL-MS we exclude the concurrent processes for removal of RNA methylation, namely RNA degradation, turnover and dilution. We use our tool to study the speed and efficiency of 1-methyladenosine and 3-methylcytidine demethylation. We further outline current limitations of NAIL-MS but also potential future uses for e.g. relative quantification of tRNA isoacceptor abundances.

Improved RNA‐modification mapping through employment of novel ribonucleases and LC‐MS

More than 150 different chemical modifications have been documented in various types of ribonucleic acids (RNA) [1]. They play key roles in translation, cellular fate, and stabilization of RNA structure [2]. While majority of these modifications are catalyzed by cellular enzymes, others are generated by xenobiotic stress exposure. RNA modifications have been linked to human diseases [3] such as neurological disorders and cancer.Understanding the role of these modifications in human disorders requires precise identification and location of the site in the overall RNA sequence. Nucleobase specific ribonuclease (RNase) enzymes are useful in mapping the location of chemical modification. Here the RNA is digested with a nucleobase‐specific enzyme and the resulting digestion products are subjected to liquid chromatography coupled with mass spectrometry (LC‐MS) ‐based sequencing, a method widely referred to as RNA modification mapping [4].Commercially available RNase T1 (G‐specific) and RNase A (pyrimidine‐specific) have been widely used in RNA modification mapping procedures. To augment the limitations of these enzymes, additional nucleobase‐specific enzymes, RNase MC1 (U‐specific) [5] and cusativin (C‐specific) [6] have been developed that could complement the existing enzymes. Thus, the digestion products generated by multiple enzymes can complement each other thereby improving the sequence coverage and generation of overlapping digestion products of substrate RNA. In the current investigation, we will present reconstruction of modified tRNA sequences from the digestion products generated by digestion of Escherichia coli tRNA by multiple nucleobase‐specific enzymes. We will also demonstrate the utility of this technology to map the stress‐induced damage in the ribosomal RNA. The advantage of such a multi‐pronged approach as opposed to the single enzyme usage in reconstruction of modified RNA sequences will be discussed.Support or Funding InformationFinancial support for this work was provided by the National Institutes of Health (GM058843) and the University of Cincinnati.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

RNAModMapper: RNA Modification Mapping Software for Analysis of Liquid Chromatography Tandem Mass Spectrometry Data.

Liquid chromatography tandem mass spectrometry (LC-MS/MS) has proven to be a powerful analytical tool for the characterization of modified ribonucleic acids (RNAs). The typical approach for analyzing modified nucleosides within RNA sequences by mass spectrometry involves ribonuclease digestion followed by LC-MS/MS analysis and data interpretation. Here we describe a new software tool, RNAModMapper (RAMM), to assist in the interpretation of LC-MS/MS data. RAMM is a stand-alone package that requires user-submitted DNA or RNA sequences to create a local database against which collision-induced dissociation (CID) data of modified oligonucleotides can be compared. RAMM can interpret MS/MS data containing modified nucleosides in two modes: fixed and variable. In addition, RAMM can also utilize interpreted MS/MS data for RNA modification mapping back against the input sequence(s). The applicability of RAMM was first tested using total tRNA isolated from Escherichia coli. It was then applied to map modifications found in 16S and 23S rRNA from Streptomyces griseus.

Stable Isotope Labeling for Improved Comparative Analysis of RNA Digests by Mass Spectrometry

Even with the advent of high throughput methods to detect modified ribonucleic acids (RNAs), mass spectrometry remains a reliable method to detect, characterize, and place post-transcriptional modifications within an RNA sequence. Here we have developed a stable isotope labeling comparative analysis of RNA digests (SIL-CARD) approach, which improves upon the original 18O/16O labeling CARD method. Like the original, SIL-CARD allows sequence or modification information from a previously uncharacterized in vivo RNA sample to be obtained by direct comparison with a reference RNA, the sequence of which is known. This reference is in vitro transcribed using a 13C/15N isotopically enriched nucleoside triphosphate (NTP). The two RNAs are digested with an endonuclease, the specificity of which matches the labeled NTP used for transcription. As proof of concept, several transfer RNAs (tRNAs) were characterized by SIL-CARD, where labeled guanosine triphosphate was used for the reference in vitro transcription. RNase T1 digestion products from the in vitro transcript will be 15Da higher in mass than the same digestion products from the in vivo tRNA that are unmodified, leading to a doublet in the mass spectrum. Singlets, rather than doublets, arise if a sequence variation or a post-transcriptional modification is present that results in a relative mass shift different from 15Da. Moreover, the use of the in vitro synthesized tRNA transcript allows for quantitative measurement of RNA abundance. Overall, SIL-CARD simplifies data analysis and enhances quantitative RNA modification mapping by mass spectrometry. Graphical Abstract ᅟ.