Introduction N6-methyladenosine (m6A) is the most frequent internal modification in eukaryotic mRNAs and is closely related to the occurrence and development of many diseases, especially tumors. However, the relationship between m6A methylation and rheumatoid arthritis (RA) is still a mystery. Methods Two high-throughput sequencing methods, namely, m6A modified RNA immunoprecipitation sequence (m6A-seq) and RNA sequence (RNA-seq) were performed to identify the differentially expressed m6A methylation in human rheumatoid arthritis fibroblast-like synoviocytes cell line MH7A after stimulation with TNF-α. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to obtain enriched GO terms and significant KEGG pathways. Then, four candidate genes, Wilms tumor 1-associating protein (WTAP), receptor-interacting serine/threonine protein kinase 2 (RIPK2), Janus kinase 3 (JAK3) and tumor necrosis factor receptor SF10A (TNFRSF10A) were selected to further validate the m6A methylation, mRNA and protein expression levels in MH7A cells and synovial tissues of adjuvant arthritis (AA) rats by RT-qPCR and Western blot. Results Using m6A-seq, we identified a total of 206 genes with differentially expressed m6A methylation, of which 118 were significantly upregulated and 88 genes were significantly downregulated. Likewise, 1207 differentially mRNA expressed mRNAs were obtained by RNA-seq, of which 793 were upregulated and 414 downregulated. Further joint analysis showed that the m6A methylation and mRNA expression levels of 88 genes changed significantly, of which 30 genes displayed increased m6A methylation and decreased mRNA expression, 57 genes displayed decreased m6A methylation and increased mRNA expression increased, and 1 gene displayed increased m6A methylation and increased mRNA expression. GO and KEGG analyses indicated that these unique genes were mainly enriched in inflammation-related pathways, cell proliferation and apoptosis. In addition, the validations of WTAP, RIPK2, JAK3 and TNFRSF10A were in accordance with the m6A and RNA sequencing results. Conclusion This study established the transcriptional map of m6A in MH7A cells and revealed the potential relationship between RNA methylation modification and RA related genes. The results suggested that m6A modification was associated with the occurrence and course of RA to some extent.

N6-Methyladenosine (m6A), a unique and common mRNA modification method in eukaryotes, is involved in the occurrence and development of many diseases. Liver fibrosis (LF) is a common response to chronic liver injury and may lead to cirrhosis and even liver cancer. However, the involvement of m6A methylation in the development of LF is still unknown. In this study, we performed a systematic evaluation of hepatic genome-wide m6A modification and mRNA expression by m6A-seq and RNA-seq using LF mice. There were 3,315 genes with significant differential m6A levels, of which 2,498 were hypermethylated and 817 hypomethylated. GO and KEGG analyses illustrated that differentially expressed m6A genes were closely correlated with processes such as the endoplasmic reticulum stress response, PPAR signaling pathway and TGF-β signaling pathway. Moreover, a total of 90 genes had both a significant change in the m6A level and mRNA expression shown by joint analysis of m6A-seq and RNA-seq. Hence, the critical elements of m6A modification, including methyltransferase WTAP, demethylases ALKBH5 and binding proteins YTHDF1 were confirmed by RT-qPCR and Western blot. In an additional cell experiment, we also observed that the decreased expression of WTAP induced the development of LF as a result of promoting hepatic stellate cell (HSC) activation. Therefore, this study revealed unique differential m6A methylation patterns in LF mice and suggested that m6A methylation was associated with the occurrence and course of LF to some extent.

Objective. This study aimed to determine the active components of Zhinao capsule (ZNC) and the targets in treating Alzheimer’s disease (AD) so as to investigate and explore the mechanism of ZNC for AD. Methods. The active components and targets of ZNC were determined from the traditional Chinese medicine systems pharmacology database (TCMSP). The target genes of AD were searched for in GeneCards. Cytoscape was used to construct an herb-component-target-disease network. A protein-protein interaction (PPI) network was constructed by STRING. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the OmicShare. UCSF Chimera and SwissDock were used for molecular docking verification. Finally, four key target genes were validated by Western blotting. Results. In total, 55 active components, 287 targets of active components, 1197 disease genes, and 134 common genes were screened, which were significantly enriched in 3975 terms of biological processes (BP), 284 terms of cellular components (CC), 433 terms of molecular functions (MF), and 245 signaling pathways. Caspase-3 (CASP3) and beta-sitosterol, tumor necrosis factor-alpha (TNF-α) and quercetin, vascular endothelial growth factor A (VEGFA) and baicalein, and mitogen-activated protein kinase 1 (MAPK1) and quercetin showed good-to-better docking. Moreover, ZNC not only downregulated CASP3 and TNF-α protein expression but also upregulated the protein expression of VEGFA and MAPK1. Conclusions. The active components of ZNC, such as beta-sitosterol, quercetin, and baicalein may act on multiple targets like CASP3, VEGFA, MAPK1, and TNF-α to affect T cell receptor (TCR), TNF, and MAPK signaling pathway, thereby achieving the treatment of AD. This study provides a scientific basis for further exploring the potential mechanism of ZNC in the treatment of AD and a reference for its clinical application.

The Jiedu Huazhuo Quyu formula (JHQ) shows significant beneficial effects against liver fibrosis caused by Wilson’s disease (WD). Hence, this study aimed to clarify the mechanisms of the JHQ treatment in WD-associated liver fibrosis. First, we collected 103 active compounds and 527 related targets of JHQ and 1187 targets related to WD-associated liver fibrosis from multiple databases. Next, 113 overlapping genes (OGEs) were obtained. Then, we built a protein-protein interaction (PPI) network with Cytoscape 3.7.2 software and performed the Gene Ontology (GO) term and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analyses with GENE DENOVO online sites. Furthermore, module analysis was performed, and the core target genes in the JHQ treatment of WD-associated liver fibrosis were obtained. Pathway and functional enrichment analyses, molecular docking studies, molecular dynamic (MD) simulation, and Western blot (WB) were then performed. The results indicated that 8 key active compounds including quercetin, luteolin, and obacunone in JHQ might affect the 6 core proteins including CXCL8, MAPK1, and AKT1 and 107 related signaling pathways including EGFR tyrosine kinase inhibitor resistance, Kaposi sarcoma-associated herpesvirus infection, and human cytomegalovirus infection signaling pathways to exhibit curative effects on WD-associated liver fibrosis. Mechanistically, JHQ might inhibit liver inflammatory processes and vascular hyperplasia, regulate the cell cycle, and suppress both the activation and proliferation of hepatic stellate cells (HSCs). This study provides novel insights for researchers to systematically explore the mechanism of JHQ in treating WD-associated liver fibrosis.

Background: N4-acetylcytidine (ac4C), an important posttranscriptional modification, is involved in various disease processes. Long noncoding RNAs (lncRNAs) regulate gene expression mainly through epigenetic modification, transcription, and posttranscriptional modification. Alzheimer’s disease (AD) is a neurodegenerative disease characterized by amyloidosis of the brain. However, the role of lncRNA ac4C modification in AD remains unclear. Objective: In this study, we investigated the association between ac4C modification and AD, and the underlying mechanisms of ac4C modification in AD. Methods: The male 9-month-old APP/PS1 double transgenic mice, age- and sex-matched wild type (WT) mice were used in this study. Then, ac4C-RIP-seq and RNA-seq were used to comprehensively analyze lncRNA ac4C modification in AD mice. The lncRNA-miRNA-mRNA regulatory networks using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed the regulatory relationships among these three lncRNAs and AD. Results: The results showed that there were 120 significantly different ac4C peaks located on 102 lncRNAs in AD, of which 55 were hyperacetylated and 47 were hypoacetylated. Simultaneously, 231 differentially expressed lncRNAs were identified, including 138 upregulated lncRNAs and 93 downregulated lncRNAs. Moreover, 3 lncRNAs, lncRNA Gm26508, lncRNA A430046D13Rik, and lncRNA 9530059O14Rik, showed significant changes in both the ac4C and RNA levels using conjoint analysis. Conclusion: The abundance of lncRNA ac4C modification is significantly different in AD and indicates that lncRNA ac4C is associated with the occurrence and development of AD, which could provide a basis for further exploration of the related regulatory mechanisms.