MSCs can alleviate ferroptosis and improve DKD through the Smad2/3/METTL3/S1PR1 axis.

Diabetic kidney disease (DKD) is a significant cause of end-stage renal disease (ESRD), markedly increasing the risk of cardiovascular disease and all-cause mortality. Although mesenchymal stem cells (MSCs) have demonstrated potential in mitigating DKD through various pathways, their specific mechanisms remain unclear. In this study, we observed increased Smad2 phosphorylation and ferroptosis in DKD models, which were alleviated by MSC intervention. Dot blot analysis and the EpiQuik M6A RNA Methylation Quantification Kit revealed elevated m6A modification levels in DKD. Bioinformatics analysis, receiver operating characteristic (ROC) curves, and Western blot (WB) assays indicated a correlation between METTL3 expression and changes in m6A modification in DKD. Knockdown of METTL3 and Smad2 reduced m6A modification and ferroptosis levels. Furthermore, knockdown of METTL3 reversed the increase in m6A modification caused by Smad2 overexpression. Notably, transcriptome and m6A-seq analysis identified S1pr1 as a target gene. Using the GEPIA database, we found a close association between S1pr1 expression and both Smad2 and METTL3 in kidney tissues. The SRAMP tool predicted nine m6A modification sites on S1pr1 mRNA, eight with over 95% credibility and one at position 688 with over 90% credibility. Knockdown of S1pr1 reversed the protective effect of METTL3 knockdown against ferroptosis in DKD, increasing Fe2+, ROS, and ACSL4 levels while decreasing GPX4 and SLC7A11 expression. Finally, MSC intervention and shRNA-mediated METTL3 knockdown increased the reduced S1pr1 levels in DKD kidney tissue. Our findings suggest that upon nuclear translocation, Smad2 promotes S1pr1 gene m6A modification by binding to METTL3, thereby affecting S1pr1 expression and positively regulating cellular ferroptosis in DKD models. MSC intervention can reduce this process, further elucidating the mechanism by which MSCs regulate podocyte ferroptosis in DKD. This study employed m6A-seq technology to identify relevant m6A methylated differential genes through a comprehensive series of data processing and screening steps. Specifically, cellular samples from three groups—the MPC5 group (MPC5 cells cultured in regular medium), the MPC5sh_METTL3 group (MPC5 cells transfected with sh-METTL3 virus), and the MPC5sh_METTL3_G group (MPC5 cells transfected with sh-METTL3 virus and subsequently treated with 25 µmol/L glucose for 72 hours in the culture medium)—were subjected to Total RNA extraction and quality control. Following this, sequence analysis libraries were constructed and evaluated, and the samples were sequenced and screened. The sequencing data were then aligned to the reference sequence for comparative analysis. Peak calling and differential peak (diff Peak) analysis were conducted to identify changes in m6A methylation sites between the groups. Additionally, transcriptome sequencing analysis was performed, and an integrated analysis of the transcriptome and m6A-seq data was carried out to identify genes with differential m6A methylation that may be associated with alterations in gene expression.