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 N-methyladenosine (mA) and 5-methylcytidine (mC) sites in mRNA with single nucleotide precision (MePMe-seq). Analysis of the termination profiles can be used to distinguish mA from 2'-O-methyladenosine (A) and N1-methyladenosine (mA) 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.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630376 | PMC |
http://dx.doi.org/10.1038/s41467-023-42832-z | DOI Listing |
Mikrochim Acta
January 2025
College of Geography and Environmental Sciences, College of Chemistry and Materials Science, Zhejiang Normal University, Jinhua, 321004, China.
Myoglobin (Mb), an important cardiac marker, plays a crucial role in diagnosing, monitoring, and evaluating the condition of patients with cardiovascular diseases. Here, we propose a label-free photoelectrochemical (PEC) sensor for the detection of Mb through target regulated the photoactivity of AgS/FeOOH heterojunction. The AgS/FeOOH nanospindles were synthesized and served as a sensing platform for the fabrication of bio-recognized process for Mb.
View Article and Find Full Text PDFJ Neurochem
January 2025
Center for Protein Diagnostics (PRODI) Biospectroscopy, Ruhr University Bochum, Bochum, Germany.
Alzheimer's disease (AD) is characterized by the accumulation of amyloid-beta (Aβ) plaques in the brain, contributing to neurodegeneration. This study investigates lipid alterations within these plaques using a novel, label-free, multimodal approach. Combining infrared (IR) imaging, machine learning, laser microdissection (LMD), and flow injection analysis mass spectrometry (FIA-MS), we provide the first comprehensive lipidomic analysis of chemically unaltered Aβ plaques in post-mortem human AD brain tissue.
View Article and Find Full Text PDFSci Rep
January 2025
Fischell Department of Bioengineering, University of Maryland, College Park, USA.
The development of optical sensors for label-free quantification of cell parameters has numerous uses in the biomedical arena. However, using current optical probes requires the laborious collection of sufficiently large datasets that can be used to calibrate optical probe signals to true metabolite concentrations. Further, most practitioners find it difficult to confidently adapt black box chemometric models that are difficult to troubleshoot in high-stakes applications such as biopharmaceutical manufacturing.
View Article and Find Full Text PDFNat Commun
January 2025
National-Local Joint Engineering Laboratory of Druggability and New Drug Evaluation, National Engineering Research Center for New Drug and Druggability (cultivation), Guangdong Province Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Epitranscriptomic modifications, particularly N6-methyladenosine (mA), are crucial regulators of gene expression, influencing processes such as RNA stability, splicing, and translation. Traditional computational methods for detecting mA from Nanopore direct RNA sequencing (DRS) data are constrained by their reliance on experimentally validated labels, often resulting in the underestimation of modification sites. Here, we introduce pum6a, an innovative attention-based framework that integrates positive and unlabeled multi-instance learning (MIL) to address the challenges of incomplete labeling and missing read-level annotations.
View Article and Find Full Text PDFPLoS One
January 2025
Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Endometriosis is a chronic inflammatory disorder characterized by presence of endometrial tissue outside the uterine cavity. Immunohistochemical analysis (IHC) revealed markedly elevated expression of IL6ST in endometrial tissue of patients with ovarian endometriosis. Level of methylation of IL6ST is diminished in patients with endometriosis, whereas level of mRNA expression is markedly elevated by RT-PCR.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!