Bisulfite Sequencing of RNA for Transcriptome-Wide Detection of 5-Methylcytosine

Transcriptome-wide identification of 5-methylcytosine by deaminase and reader protein-assisted sequencing

5-Methylcytosine (m5C) is one of the posttranscriptional modifications in mRNA and is involved in the pathogenesis of various diseases. However, the capacity of existing assays for accurately and comprehensively transcriptome-wide m5C mapping still needs improvement. Here, we develop a detection method named DRAM (deaminase and reader protein assisted RNA methylation analysis), in which deaminases (APOBEC1 and TadA-8e) are fused with m5C reader proteins (ALYREF and YBX1) to identify the m5C sites through deamination events neighboring the methylation sites. This antibody-free and bisulfite-free approach provides transcriptome-wide editing regions which are highly overlapped with the publicly available bisulfite-sequencing (BS-seq) datasets and allows for a more stable and comprehensive identification of the m5C loci. In addition, DRAM system even supports ultralow input RNA (10 ng). We anticipate that the DRAM system could pave the way for uncovering further biological functions of m5C modifications.

RNA methylation homeostasis in ocular diseases: All eyes on Me

RNA methylation is a pivotal epigenetic modification that adjusts various aspects of RNA biology, including nuclear transport, stability, and the efficiency of translation for specific RNA candidates. The methylation of RNA involves the addition of methyl groups to specific bases and can occur at different sites, resulting in distinct forms, such as N6-methyladenosine (m6A), N1-methyladenosine (m1A), 5-methylcytosine (m5C), and 7-methylguanosine (m7G). Maintaining an optimal equilibrium of RNA methylation is crucial for fundamental cellular activities such as cell survival, proliferation, and migration. The balance of RNA methylation is linked to various pathophysiological conditions, including senescence, cancer development, stress responses, and blood vessel formation, all of which are pivotal for comprehending a spectrum of eye diseases. Recent findings have highlighted the significant role of diverse RNA methylation patterns in ophthalmological conditions such as age-related macular degeneration, diabetic retinopathy, cataracts, glaucoma, uveitis, retinoblastoma, uveal melanoma, thyroid eye disease, and myopia, which are critical for vision health. This thorough review endeavors to dissect the influence of RNA methylation on common and vision-impairing ocular disorders. It explores the nuanced roles that RNA methylation plays in key pathophysiological mechanisms, such as oxidative stress and angiogenesis, which are integral to the onset and progression of these diseases. By synthesizing the latest research, this review offers valuable insights into how RNA methylation could be harnessed for therapeutic interventions in the field of ophthalmology.

NanoMUD: Profiling of pseudouridine and N1-methylpseudouridine using Oxford Nanopore direct RNA sequencing

Nanopore direct RNA sequencing provided a promising solution for unraveling the landscapes of modifications on single RNA molecules. Here, we proposed NanoMUD, a computational framework for predicting the RNA pseudouridine modification (Ψ) and its methylated analog N1-methylpseudouridine (m1Ψ), which have critical application in mRNA vaccination, at single-base and single-molecule resolution from direct RNA sequencing data. Electric signal features were fed into a bidirectional LSTM neural network to achieve improved accuracy and predictive capabilities. Motif-specific models (NNUNN, N = A, C, U or G) were trained based on features extracted from designed dataset and achieved superior performance on molecule-level modification prediction (Ψ models: min AUC = 0.86, max AUC = 0.99; m1Ψ models: min AUC = 0.87, max AUC = 0.99). We then aggregated read-level predictions for site stoichiometry estimation. Given the observed sequence-dependent bias in model performance, we trained regression models based on the distribution of modification probabilities for sites with known stoichiometry. The distribution-based site stoichiometry estimation method allows unbiased comparison between different contexts. To demonstrate the feasibility of our work, three case studies on both in vitro and in vivo transcribed RNAs were presented. NanoMUD will make a powerful tool to facilitate the research on modified therapeutic IVT RNAs and provides useful insight to the landscape and stoichiometry of pseudouridine and N1-pseudouridine on in vivo transcribed RNA species.

RNA m5C methylation: a potential modulator of innate immune pathways in hepatocellular carcinoma

RNA 5-methylcytosine (m5C) methylation plays a crucial role in hepatocellular carcinoma (HCC). As reported, aberrant m5C methylation is closely associated with the progression, therapeutic efficacy, and prognosis of HCC. The innate immune system functions as the primary defense mechanism in the body against pathogenic infections and tumors since it can activate innate immune pathways through pattern recognition receptors to exert anti-infection and anti-tumor effects. Recently, m5C methylation has been demonstrated to affect the activation of innate immune pathways including TLR, cGAS-STING, and RIG-I pathways by modulating RNA function, unveiling new mechanisms underlying the regulation of innate immune responses by tumor cells. However, research on m5C methylation and its interplay with innate immune pathways is still in its infancy. Therefore, this review details the biological significance of RNA m5C methylation in HCC and discusses its potential regulatory relationship with TLR, cGAS-STING, and RIG-I pathways, thereby providing fresh insights into the role of RNA methylation in the innate immune mechanisms and treatment of HCC.

MePMe-seq: antibody-free simultaneous m6A and m5C mapping in mRNA by metabolic propargyl labeling and sequencing

Internal modifications of mRNA have emerged as widespread and versatile regulatory mechanism to control gene expression at the post-transcriptional level. Most of these modifications are methyl groups, making S-adenosyl-L-methionine (SAM) a central metabolic hub. Here we show that metabolic labeling with a clickable metabolic precursor of SAM, propargyl-selenohomocysteine (PSH), enables detection and identification of various methylation sites. Propargylated A, C, and G nucleosides form at detectable amounts via intracellular generation of the corresponding SAM analogue. Integration into next generation sequencing enables mapping of N6-methyladenosine (m6A) and 5-methylcytidine (m5C) sites in mRNA with single nucleotide precision (MePMe-seq). Analysis of the termination profiles can be used to distinguish m6A from 2'-O-methyladenosine (Am) and N1-methyladenosine (m1A) sites. MePMe-seq overcomes the problems of antibodies for enrichment and sequence-motifs for evaluation, which was limiting previous methodologies. Metabolic labeling via clickable SAM facilitates the joint evaluation of methylation sites in RNA and potentially DNA and proteins.

The potential role of RNA modification in skin diseases, as well as the recent advances in its detection methods and therapeutic agents

RNA modification is considered as an epigenetic modification that plays an indispensable role in biological processes such as gene expression and genome editing without altering nucleotide sequence, but the molecular mechanism of RNA modification has not been discussed systematically in the development of skin diseases. This article mainly presents the whole picture of theoretical achievements on the potential role of RNA modification in dermatology. Furthermore, this article summarizes the latest advances in clinical practice related with RNA modification, including its detection methods and drug development. Based on this comprehensive review, we aim to illustrate the current blind spots and future directions of RNA modification, which may provide new insights for researchers in this field.

No evidence for epitranscriptomic m5C modification of SARS-CoV-2, HIV and MLV viral RNA

The addition of chemical groups to cellular RNA to modulate RNA fate and/or function is summarized under the term epitranscriptomic modification. More than 170 different modifications have been identified on cellular RNA, such as tRNA, rRNA and, to a lesser extent, on other RNA types. Recently, epitranscriptomic modification of viral RNA has received considerable attention as a possible additional mechanism regulating virus infection and replication. N6-methyladenosine (m6A) and C5-methylcytosine (m5C) have been most broadly studied in different RNA viruses. Various studies, however, reported varying results with regard to number and extent of the modification. Here we investigated the m5C methylome of SARS-CoV-2, and we reexamined reported m5C sites in HIV and MLV. Using a rigorous bisulfite-sequencing protocol and stringent data analysis, we found no evidence for the presence of m5C in these viruses. The data emphasize the necessity for optimizing experimental conditions and bioinformatic data analysis.

Navigating the pitfalls of mapping DNA and RNA modifications

Chemical modifications to nucleic acids occur across the kingdoms of life and carry important regulatory information. Reliable high-resolution mapping of these modifications is the foundation of functional and mechanistic studies, and recent methodological advances based on next-generation sequencing and long-read sequencing platforms are critical to achieving this aim. However, mapping technologies may have limitations that sometimes lead to inconsistent results. Some of these limitations are technical in nature and specific to certain types of technology. Here, however, we focus on common (yet not always widely recognized) pitfalls that are shared among frequently used mapping technologies and discuss strategies to help technology developers and users mitigate their effects. Although the emphasis is primarily on DNA modifications, RNA modifications are also discussed.

Quantification of substoichiometric modification reveals global tsRNA hypomodification, preferences for angiogenin-mediated tRNA cleavage, and idiosyncratic epitranscriptomes of human neuronal cell-lines

Modification of tRNA is an integral part of the epitranscriptome with a particularly pronounced potential to generate diversity in RNA expression. Eukaryotic tRNA contains modifications in up to 20% of their nucleotides, but not all sites are always fully modified. Combinations and permutations of partially modified sites in tRNAs can generate a plethora of tRNA isoforms, termed modivariants. Here, we investigate the stoichiometry of incompletely modified sites in tRNAs from human cell lines for their information content. Using a panel of RNA modification mapping methods, we assess the stoichiometry of sites that contain the modifications 5-methylcytidine (m5C), 2'-O-ribose methylation (Nm), 3-methylcytidine (m3C), 7-methylguanosine (m7G), and Dihydrouridine (D). We discovered that up to 75% of sites can be incompletely modified and that the differential modification status of a cellular tRNA population holds information that allows to discriminate e.g. different cell lines. As a further aspect, we investigated potential causal connectivity between tRNA modification and its processing into tRNA fragments (tiRNAs and tRFs). Upon exposure of cultured living cells to cell-penetrating angiogenin, the modification patterns of the corresponding RNA populations was changed. Importantly, we also found that tsRNAs were significantly less modified than their parent tRNAs at numerous sites, suggesting that tsRNAs might derive chiefly from hypomodified tRNAs.

Advances in mRNA 5-methylcytosine modifications: Detection, effectors, biological functions, and clinical relevance

5-methylcytosine (m⁵C) post-transcriptional modifications affect the maturation, stability, and translation of the mRNA molecule. These modifications play an important role in many physiological and pathological processes, including stress response, tumorigenesis, tumor cell migration, embryogenesis, and viral replication. Recently, there has been a better understanding of the biological implications of m⁵C modification owing to the rapid development and optimization of detection technologies, including liquid chromatography-tandem mass spectrometry (LC-MS/MS) and RNA-BisSeq. Further, predictive models (such as PEA-m⁵C, m⁵C-PseDNC, and DeepMRMP) for the identification of potential m⁵C modification sites have also emerged. In this review, we summarize the current experimental detection methods and predictive models for mRNA m⁵C modifications, focusing on their advantages and limitations. We systematically surveyed the latest research on the effectors related to mRNA m⁵C modifications and their biological functions in multiple species. Finally, we discuss the physiological effects and pathological significance of m⁵C modifications in multiple diseases, as well as their therapeutic potential, thereby providing new perspectives for disease treatment and prognosis.

Agnostic Framework for the Classification/Identification of Organisms Based on RNA Post-Transcriptional Modifications

We propose a novel approach for building a classification/identification framework based on the full complement of RNA post-transcriptional modifications (rPTMs) expressed by an organism at basal conditions. The approach relies on advanced mass spectrometry techniques to characterize the products of exonuclease digestion of total RNA extracts. Sample profiles comprising identities and relative abundances of all detected rPTM were used to train and test the capabilities of different machine learning (ML) algorithms. Each algorithm proved capable of identifying rigorous decision rules for differentiating closely related classes and correctly assigning unlabeled samples. The ML classifiers resolved different members of the Enterobacteriaceae family, alternative Escherichia coli serotypes, a series of Saccharomyces cerevisiae knockout mutants, and primary cells of the Homo sapiens central nervous system, which shared very similar genetic backgrounds. The excellent levels of accuracy and resolving power achieved by training on a limited number of classes were successfully replicated when the number of classes was significantly increased to escalate complexity. A dendrogram generated from ML-curated data exhibited a hierarchical organization that closely resembled those afforded by established taxonomic systems. Finer clustering patterns revealed the extensive effects induced by the deletion of a single pivotal gene. This information provided a putative roadmap for exploring the roles of rPTMs in their respective regulatory networks, which will be essential to decipher the epitranscriptomics code. The ubiquitous presence of RNA in virtually all living organisms promises to enable the broadest possible range of applications, with significant implications in the diagnosis of RNA-related diseases.