Epigenetic modifications play an important role in central nervous system disorders. As a widespread posttranscriptional RNA modification, the role of the m5C modification in cerebral ischemia-reperfusion injury (IRI) remains poorly defined. Here, we successfully constructed a neuronal oxygen-glucose deprivation/reoxygenation (OGD/R) model and obtained an overview of the transcriptome-wide m5C profiles using RNA-BS-seq. We discovered that the distribution of neuronal m5C modifications was highly conserved, significantly enriched in CG-rich regions and concentrated in the mRNA translation initiation regions. After OGD/R, modification level of m5C increased, whereas the number of methylated mRNA genes decreased. The amount of overlap of m5C sites with the binding sites of most RNA-binding proteins increased significantly, except for that of the RBM3-binding protein. Moreover, hypermethylated genes in neurons were significantly enriched in pathological processes, and the hub hypermethylated genes RPL8 and RPS9 identified by the protein-protein interaction network were significantly related to cerebral injury. Furthermore, the upregulated transcripts with hypermethylated modification were enriched in the processes involved in response to stress and regulation of apoptosis, and these processes were not identified in hypomethylated transcripts. In final, we verified that OGD/R induced neuronal apoptosis in vitro using TUNEL and western blot assays. Our study identified novel m5C mRNAs associated with ischemia-reperfusion in neurons, providing valuable perspectives for future studies on the role of the RNA methylation in cerebral IRI.

BackgroundAging is an influential risk factor for progression of both degenerative and oncological diseases of the bone. Osteosarcoma, considered the most common primary mesenchymal tumor of the bone, is a worldwide disease with poor 5-year survival. This study investigated the role of aging-/senescence-induced genes (ASIGs) in contributing to osteosarcoma diagnosis, prognosis, and therapeutic agent prediction.MethodsTherapeutically Applicable Research to Generate Effective Treatments (TARGET), Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA) were used to collect relevant gene expression and clinical data of osteosarcoma and paracancerous tissues. Patients were clustered by consensus using prognosis-related ASIGs. ssGSEA, ESTIMATE, and TIMER were used to determine the tumor immune microenvironment (TIME) of subgroups. Functional analysis of differentially expressed genes between subgroups, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set variation analyses (GSVAs), was performed to clarify functional status. Prognostic risk models were constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. SCISSOR was used to identify relevant cells in osteosarcoma single-cell data for different risk groups. The effect of immunotherapy was predicted based on TIDE scores and chemotherapy drug sensitivity using CTRP and PRISM.ResultsThree molecular subgroups were identified based on prognostic differentially expressed ASIGs. Immunological infiltration levels of the three groups differed significantly. Based on GO and KEGG analyses, differentially expressed genes between the three subgroups mainly relate to immune and aging regulation pathways; GSVA showed substantial variations in multiple Hallmark pathways among the subgroups. The ASIG risk score built based on differentially expressed genes can predict patient survival and immune status. We also developed a nomogram graph to accurately predict prognosis in combination with clinical characteristics. The correlation between the immune activation profile of patients and the risk score is discussed. Through single-cell analysis of the tumor microenvironment, we identified distinct risk-group-associated cells with significant differences in immune signaling pathways. Immunotherapeutic efficacy and chemotherapeutic agent screening were evaluated based on risk score.ConclusionAging-related prognostic genes can distinguish osteosarcoma molecular subgroups. Our novel aging-associated gene signature risk score can be used to predict the osteosarcoma immune landscape and prognosis. Moreover, the risk score correlates with the TIME and provides a reference for immunotherapy and chemotherapy in terms of osteosarcoma.

Background: Injuries to the central nervous system (CNS), such as spinal cord injury (SCI), may devastate families and society. Subacute SCI may majorly impact secondary damage during the transitional period between the acute and subacute phases. A range of CNS illnesses has been linked to changes in the level of protein expression. However, the importance of proteins during the early subacute stage of SCI remains unknown. The role of proteins in the early subacute phase of SCI has not been established yet. Methods: SCI-induced damage in rats was studied using isobaric tagging for relative and absolute protein quantification (iTRAQ) to identify proteins that differed in expression 3 days after the injury, as well as proteins that did not alter in expression. Differentially expressed proteins (DEPs) were analyzed employing Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to discover the biological processes, cell components, and molecular functions of the proteins. We also performed Gene Set Enrichment Analysis （GSEA） software BP pathway and KEGG analysis on all proteins to further identify their functions. In addition, the first 15 key nodes of a protein-protein interaction (PPI) system were found. Results: During the early subacute stage of SCI, we identified 176 DEPs in total between the control and damage groups, with 114 (64.77%) being up-regulated and 62 (35.23%) being down-regulated. As a result of this study, we discovered the most important cellular components and molecular activities, as well as biological processes and pathways, in the early subacute phase of SCI. The top 15 high-degree core nodes were Alb, Plg, F2, Serpina1, Fgg, Apoa1, Vim, Hpx, Apoe, Agt, Ambp, Pcna, Gc, F12， and Gfap. Conclusion: Our study could provide new views on regulating the pathogenesis of proteins in the early subacute phase after SCI, which provides a theoretical basis for exploring more effective therapeutic targets for SCI in the future.

Background Spinal cord injury (SCI) is a devastating trauma of the central nervous system (CNS), with high levels of morbidity, disability, and mortality. One week after SCI may be a critical time for treatment. Changes in protein expression have crucial functions in nervous system diseases, although the effects of changes occurring 1 week after SCI on patient outcomes are unclear. Material/Methods Protein expression was examined in a rat contusive SCI model 1 week after SCI. Differentially expressed proteins (DEPs) were identified by isobaric tagging for relative and absolute protein quantification (iTRAQ)-coupled liquid chromatography tandem-mass spectrometry (LC-MS/MS) proteomics analysis. Gene Ontology (GO) analysis was performed to identify the biological processes, molecular functions, and cellular component terms of the identified DEPs, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) was used to identify key enriched pathways. Protein–protein interaction (PPI) networks were analyzed to identify the top 10 high-degree core proteins. Results Of the 295 DEPs identified, 204 (69.15%) were upregulated and 91 (30.85%) were downregulated 1 week after injury. The main cellular components, molecular functions, biological processes, and pathways identified may be crucial mechanisms involved in SCI. The top 10 high-degree core proteins were complement component C3 (C3), alpha-2-HS-glycoprotein (Ahsg), T-kininogen 1 (Kng1), Serpinc1 protein (Serpinc1), apolipoprotein A-I (Apoa1), serum albumin (Alb), disulfide-isomerase protein (P4hb), transport protein Sec61 subunit alpha isoform 1 (Sec61a1), serotransferrin (Tf), and 60S ribosomal protein L15 (Rpl15). Conclusions The proteins identified in this study may provide potential targets for diagnosis and treatment 1 week after SCI.

Cerebral ischaemia‒reperfusion injury (IRI), during which neurons undergo oxygen-glucose deprivation/reoxygenation (OGD/R), is a notable pathological process in many neurological diseases. N1-methyladenosine (m1A) is an RNA modification that can affect gene expression and RNA stability. The m1A landscape and potential functions of m1A modification in neurons remain poorly understood. We explored RNA (mRNA, lncRNA, and circRNA) m1A modification in normal and OGD/R-treated mouse neurons and the effect of m1A on diverse RNAs. We investigated the m1A landscape in primary neurons, identified m1A-modified RNAs, and found that OGD/R increased the number of m1A RNAs. m1A modification might also affect the regulatory mechanisms of noncoding RNAs, e.g., lncRNA–RNA binding proteins (RBPs) interactions and circRNA translation. We showed that m1A modification mediates the circRNA/lncRNA‒miRNA–mRNA competing endogenous RNA (ceRNA) mechanism and that 3' untranslated region (3’UTR) modification of mRNAs can hinder miRNA–mRNA binding. Three modification patterns were identified, and genes with different patterns had intrinsic mechanisms with potential m1A-regulatory specificity. Systematic analysis of the m1A landscape in normal and OGD/R neurons lays a critical foundation for understanding RNA modification and provides new perspectives and a theoretical basis for treating and developing drugs for OGD/R pathology-related diseases.