Transfer-RNA-derived fragments (tRFs) are a class of small non-coding RNAs that are functionally different from their parental transfer RNAs (tRNAs). tRFs can regulate gene expression by several mechanisms, and are involved in a variety of pathological processes. Here, we aimed at understanding the composition and abundance of tRFs in squamous cell carcinoma of the head and neck (SCCHN), and evaluated the potential of tRFs as prognostic markers in this cancer type. We obtained tRF expression data from The Cancer Genome Atlas (TCGA) HNSC cohort (523 patients) using MINTbase v2.0, and correlated to available TCGA clinical data. RNA-binding proteins were predicted according to the calculated Position Weight Matrix (PWM) score from the RNA-Binding Protein DataBase (RBPDB). A total of 10,158 tRFs were retrieved and a high diversity in expression levels was seen. Fifteen tRFs were found to be significantly associated with overall survival (Kaplan-Meier survival analysis, log rank test p-value < 0.01). The top prognostic marker, tRF-20-S998LO9D (p < 0.001), was further measured in tumor and tumor-free samples from 16 patients with squamous cell carcinoma of the oral tongue and 12 healthy controls, and was significantly upregulated in tumor compared to matched tumor-free tongue (p < 0.001). Results suggest that tRFs are useful prognostic markers in SCCHN.
- Keywords
- SCCHN, prognostic marker, tRNA-derived fragment,
- MeSH
- Databases, Factual MeSH
- Squamous Cell Carcinoma of Head and Neck genetics mortality MeSH
- Kaplan-Meier Estimate MeSH
- Humans MeSH
- Biomarkers, Tumor genetics MeSH
- Head and Neck Neoplasms genetics mortality MeSH
- Prognosis MeSH
- RNA-Binding Proteins genetics MeSH
- RNA, Transfer genetics MeSH
- Case-Control Studies MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Biomarkers, Tumor MeSH
- RNA-Binding Proteins MeSH
- RNA, Transfer MeSH
In the modern era, molecular genetic techniques are crucial in ecological studies, as well as in the classification, typing, and phylogenetic analysis of prokaryotes. These techniques are mainly aimed at whole genome comparisons and PCR-derived experiments, including amplifying the 16S rRNA and other various housekeeping genes used in taxonomy, as well as MLST (multilocus sequence typing) and MLSA (multilocus sequence analysis) of different taxonomic bacterial groups. The gene encoding threonine-tRNA ligase (thrS) is a gene potentially applicable as an identification and phylogenetic marker in bacteria. It is widely distributed in bacterial genomes and is subject to evolutionary selection pressure due to its important function in protein synthesis. In this study, specific primers were used to amplify a thrS gene fragment (~740 bp) in 36 type and 30 wild strains classified under family Bifidobacteriaceae. The full-length gene has not yet been considered as a possible identification, classification, and phylogenetic marker in bifidobacteria. The thrS sequences revealed higher sequence variability (82.7% of pairwise identities) among members of the family than that shown by 16S rRNA gene sequences (96.0%). Although discrepancies were found between the thrS-derived and previously reported whole genome phylogenetic analyses, the main phylogenetic groups of bifidobacteria were properly assigned. Most wild strains of bifidobacteria were better differentiated based on their thrS sequences than on their 16S rRNA gene identities. Phylogenetic confidence of the evaluated gene with respect to other alternative genetic markers widely used in taxonomy of bifidobacteria (fusA, GroELhsp60, pyrG, and rplB genes) was confirmed using the localized incongruence difference - Templeton analysis.
- Keywords
- Bifidobacterium, classification, genetic marker, phylogenetics, thrS gene,
- MeSH
- Genes, Bacterial MeSH
- Bacterial Proteins genetics MeSH
- Bifidobacterium classification enzymology genetics MeSH
- DNA, Bacterial genetics MeSH
- Phylogeny * MeSH
- Multilocus Sequence Typing MeSH
- DNA, Ribosomal genetics MeSH
- RNA, Ribosomal, 16S genetics MeSH
- Sequence Analysis, DNA MeSH
- Bacterial Typing Techniques MeSH
- Threonine-tRNA Ligase genetics MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Bacterial Proteins MeSH
- DNA, Bacterial MeSH
- DNA, Ribosomal MeSH
- RNA, Ribosomal, 16S MeSH
- Threonine-tRNA Ligase MeSH
Human cytosolic prolyl-tRNA synthetase (HcProRS) catalyses the formation of the prolyl-tRNAPro, playing an important role in protein synthesis. Inhibition of HcProRS activity has been shown to have potential benefits in the treatment of fibrosis, autoimmune diseases and cancer. Recently, potent pyrazinamide-based inhibitors were identified by a high-throughput screening (HTS) method, but no further elaboration was reported. The pyrazinamide core is a bioactive fragment found in numerous clinically validated drugs and has been subjected to various modifications. Therefore, we applied a virtual screening protocol to our in-house library of pyrazinamide-containing small molecules, searching for potential novel HcProRS inhibitors. We identified a series of 3-benzylaminopyrazine-2-carboxamide derivatives as positive hits. Five of them were confirmed by a thermal shift assay (TSA) with the best compounds 3b and 3c showing EC50 values of 3.77 and 7.34 µM, respectively, in the presence of 1 mM of proline (Pro) and 3.45 µM enzyme concentration. Co-crystal structures of HcProRS in complex with these compounds and Pro confirmed the initial docking studies and show how the Pro facilitates binding of the ligands that compete with ATP substrate. Modelling 3b into other human class II aminoacyl-tRNA synthetases (aaRSs) indicated that the subtle differences in the ATP binding site of these enzymes likely contribute to its potential selective binding of HcProRS. Taken together, this study successfully identified novel HcProRS binders from our anti-tuberculosis in-house compound library, displaying opportunities for repurposing old drug candidates for new applications such as therapeutics in HcProRS-related diseases.
- Keywords
- X-ray crystallographic studies, in silico modelling, inhibitor, prolyl-tRNA synthetase, thermal shift assay,
- MeSH
- Adenosine Triphosphate metabolism MeSH
- Amino Acyl-tRNA Synthetases antagonists & inhibitors MeSH
- Biological Assay methods MeSH
- Enzyme Inhibitors chemistry isolation & purification pharmacology MeSH
- Protein Conformation MeSH
- Crystallography, X-Ray MeSH
- Humans MeSH
- Ligands MeSH
- Models, Molecular MeSH
- Computer Simulation * MeSH
- Pyrazinamide chemistry MeSH
- Binding Sites MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Adenosine Triphosphate MeSH
- Amino Acyl-tRNA Synthetases MeSH
- Enzyme Inhibitors MeSH
- Ligands MeSH
- prolyl T RNA synthetase MeSH Browser
- Pyrazinamide MeSH
Argonaute proteins are instrumental in regulating RNA stability and translation. AGO2, the major mammalian Argonaute protein, is known to primarily associate with microRNAs, a family of small RNA 'guide' sequences, and identifies its targets primarily via a 'seed' mediated partial complementarity process. Despite numerous studies, a definitive experimental dataset of AGO2 'guide'-'target' interactions remains elusive. Our study employs two experimental methods-AGO2 CLASH and AGO2 eCLIP, to generate thousands of AGO2 target sites verified by chimeric reads. These chimeric reads contain both the AGO2 loaded small RNA 'guide' and the target sequence, providing a robust resource for modeling AGO2 binding preferences. Our novel analysis pipeline reveals thousands of AGO2 target sites driven by microRNAs and a significant number of AGO2 'guides' derived from fragments of other small RNAs such as tRNAs, YRNAs, snoRNAs, rRNAs, and more. We utilize convolutional neural networks to train machine learning models that accurately predict the binding potential for each 'guide' class and experimentally validate several interactions. In conclusion, our comprehensive analysis of the AGO2 targetome broadens our understanding of its 'guide' repertoire and potential function in development and disease. Moreover, we offer practical bioinformatic tools for future experiments and the prediction of AGO2 targets. All data and code from this study are freely available at https://github.com/ML-Bioinfo-CEITEC/HybriDetector/ .
- MeSH
- Argonaute Proteins genetics metabolism MeSH
- MicroRNAs * genetics metabolism MeSH
- RNA, Ribosomal MeSH
- RNA, Transfer MeSH
- Mammals metabolism MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Argonaute Proteins MeSH
- MicroRNAs * MeSH
- RNA, Ribosomal MeSH
- RNA, Transfer MeSH
