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N6-methyladenosine regulates metabolic remodeling in kidney aging through transcriptional regulator GLIS1

BMC Biology volume 22, Article number: 302 (2024) Cite this article

Abstract

Background

Age-related kidney impairment, characterized by tubular epithelial cell senescence and renal fibrosis, poses a significant global public health threat. Although N6-methyladenosine (m6A) methylation is implicated in various pathological processes, its regulatory mechanism in kidney aging remains unclear.

Methods

An m6A-mRNA epitranscriptomic microarray was performed to identify genes with abnormal m6A modifications in aged human kidney tissues. Histological, immunohistochemical, and immunofluorescent staining, western blot, and RT-qPCR were employed to examine the biological functions of targeted genes and m6A methyltransferases both in vivo and in vitro. RNA immunoprecipitation, chromatin immunoprecipitation, ribosomal immunoprecipitation, and luciferase reporter assays were used to investigate the specific interactions between m6A methyltransferases, targeted genes, and their downstream signals.

Results

Significantly lower m6A modification levels were observed in aged human kidney tissues. GLIS1, identified as a “metabolic remodeling factor,” showed significantly reduced protein levels with abnormal m6A modifications. The downregulation of GLIS1 induced cell senescence and renal fibrosis by shifting metabolic remodeling from fatty acid oxidation (FAO) to glycolysis. Additionally, the methylated GLIS1 mRNA was regulated by the abnormal expression of METTL3 and YTHDF1. Silencing METTL3/YTHDF1 weakened the translation of GLIS1 and disrupted the balance between FAO and glycolysis.

Conclusions

Our findings suggest that the m6A modification of GLIS1, activated by METTL3 and reduced in a YTHDF1-dependent manner, leads to kidney aging by regulating the metabolic shift from FAO to glycolysis. This mechanism provides a promising therapeutic target for kidney aging.

Background

Aging has become a critical issue for global public health. In China, the population aged 65 years and older is predicted to reach 400 million by 2050, constituting for 26.9% of the population [1]. Among human organs, the kidney is particularly susceptible to age-related impairment [2, 3]. Natural age-related kidney dysfunctions rarely recover from injury and are predisposed to acute kidney disease (AKI), chronic kidney disease (CKD), and other renal diseases [4]. The tubular epithelial cells (TECs), the primary component of the cortex, play crucial roles in the onset and progression of kidney aging. Senescent TECs lose their self-repair ability and produce proinflammatory cytokines and matrix-synthesizing molecules, leading to renal fibrosis [5,6,7].

Metabolic reprogramming was first reported in tumor development, where energy metabolism in tumor cells shifts from mitochondrial glucose oxidation to inefficient glycolysis, even under normoxic conditions, known as the “Warburg effect” [8]. Recently, the alteration of energy metabolism in the kidney has gained increasing interest as a novel mechanism in kidney diseases [9,10,11]. TECs, especially proximal tubular cells (PTCs), exhibit high baseline energy consumption to maintain kidney metabolic balance [12, 13]. It is confirmed that TECs rely predominantly on fatty acid oxidation (FAO) to produce adenosine triphosphate (ATP) and seldomly engage in glycolysis.

However, the molecular mechanisms and signaling pathways underlying the metabolic reprogramming of PTCs in kidney aging remain unclear. Gli-like transcription factor 1 (GLIS1), a GLI transcription factor, regulates the transcription of various genes in both physiological and pathological conditions and plays a pivotal role in the early development of bovine embryos. Our previous study demonstrated that GLIS1 was highly involved in mitochondrial quality control during cell senescence and age-related renal fibrosis [14]. GLIS1 has emerged as an important upstream modulator of renal fibrosis, highlighting the importance of further elucidating its specific functions and the reprogramming mechanisms.

N6-methyladenosine (m6A) RNA methylation is a prevalent and conserved modification in mammals. The effects of m6A modification on mRNA or noncoding RNAs at the transcription level are mediated by the interaction among m6A methyltransferases (writers), demethylases (erasers), and binding proteins (readers). Specifically, the core heterodimer complex of methyltransferase-like 3 and methyltransferase-like 14 (METTL3-METTL14), along with Wilms’ tumor 1-associating protein (WTAP) as a splicing factor, initiates RNA modification as writers. The primary demethylases include fat mass and obesity-associated protein (FTO) and alkB homolog 5 (ALKBH5) [15, 16]. Reader proteins, including the YT521-B homology domain family 1–3 (YTHDF1-3) and YT521-B homology domain-containing 1–2 (YTHDC1-2), recognize m6A-methylated transcripts to regulate mRNA functions including stability, translation, and degradation [16, 17]. Dysregulation of m6A modification can contribute to various kidney diseases [18,19,20]. However, the relationship between kidney aging and m6A modification remains poorly understood.

In this study, GLIS1 was identified as a target molecule through an m6A-mRNA epitranscriptomic microarray, linked it to cell senescence and renal fibrosis by regulating metabolic remodeling. The dysregulation of m6A-methylated GLIS1 affected the translation of GLIS1 mRNA, contributing to the metabolic shift from FAO to glycolysis in PTCs, thereby accelerating cell senescence and renal fibrosis. This discovery elucidates a novel mechanism and presents a promising therapeutic target for addressing kidney aging.

Results

The downregulated m6A methylation and protein levels of GLIS1 in human aged kidney

To investigate the significant role of m6A modification in aged kidneys, we prepared young and aged human kidney tissues, referred to as the H/control and H/aged groups, respectively. The expression level of γH2AX, a typical senescence-related protein marker, was markedly higher in the H/aged group compared to the H/control group (Additional file 1: Fig. S1B, D) [21]. Notably, the m6A methylation level was significantly reduced in the H/aged group (Fig. 1A). The m6A-mRNA epitranscriptomic microarray revealed 63 hyper-methylated and 297 hypo-methylated m6A peaks in the H/aged group (Fig. 1B, C). Among the hypo-methylated genes, which were primarily related to cellular and metabolic processes (Fig. 1D), GLIS1 was prominently involved in the methylation process of aged kidneys, exhibiting significantly lower m6A modification in the H/aged group (Fig. 1E). As illustrated in Fig. S1A (Additional file 1), the mRNA level of GLIS1 was downregulated in the H/aged group. Additionally, the results of western blot and immunohistochemical (IHC) staining confirmed H/aged group had a lower protein level of GLIS1 compared to the H/control group (Fig. 1F, G and Additional file 1: Fig S1C). Furthermore, we examined the expression of E-cadherin, a PTCs-specific marker that maintained normal epithelial integrity. As shown in Fig S2 (Additional file 1), the simultaneous down-regulation of GLIS1 and E-cadherin suggested that GLIS1 was highly involved in kidney tubule aging.

Fig. 1
figure 1

The abnormal m6A modification and protein levels of GLIS1 in human aged kidney tissues. A Total m6A RNA levels in the H/aged (n = 10) and H/control group (n = 10) detected by m6A methylation quantification kit; B differential methylated mRNA expressions between H/aged (A) and H/control (Y) group by using m6A-mRNA epitranscriptomic microarray analysis (n = 3); C analysis of significant changes in methylated mRNA expression levels between the H/aged and H/control group; D the Gene Ontology (GO) biological process enrichment analysis pathways of predicted mRNA targets; E enriched m6A modification of GLIS1 in the H/aged and H/control group by MeRIP assay (n = 4); F, G protein level of GLIS1 in the H/aged and H/control group by western blot, and its semi-quantitative analyses (n = 6). The data are expressed as the mean ± SD of three independent experiments. ***P < .001 indicates a significant difference versus the H/control group by Student’s t-test

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We previously demonstrated that GLIS1 was primarily localized in the renal tubular epithelium and downregulated both in the 24-month-old group and D-galactose (D-gal) accelerated aging mouse model, and concluding over-expressed GLIS1 reduced renal fibrosis in D-gal mice [14]. In the present study, as shown in Fig. 2A, Oil Red O-positive regions are predominantly located in TECs, indicating lipid accumulation in the 24-month-old group. To specifically investigate GLIS1 and energy metabolism, HK-2 cells were transfected with small interfering RNA (siRNA) targeting GLIS1 (siGLIS1) and analyzed using RNA-sequencing technology (Fig. 4E). Gene Set Enrichment Analysis (GSEA) of the transcriptomic changes in biological functions and pathways indicated a positive correlation between GLIS1 and the FAO pathway (NES =  − 1.89, p < 0.001) (Additional file 1: Fig. S3). Importantly, peroxisome proliferator-activated receptor alpha (PPARα), an upstream regulatory gene in FAO regulation, was implicated in GLIS1-driven kidney aging and exhibited significantly lower levels in the 24-month-old group. Double immunofluorescent (IF) staining for co-expressed GLIS1 and PPARα suggested their potential correlation in the 24-month-old group (Fig. 2D). Additionally, significantly lower levels of ACOX1 and CPT1A, both representative FAO-related proteins, were observed in the 24-month-old group compared to the 6-month-old group (Fig. 2B, C). Similar trends of PPARα, ACOX1, and CPT1A levels in the IHC assay implied reduced energy consumption through the FAO pathway in the 24-month-old group (Fig. 2F).

Fig. 2
figure 2

The metabolic remodeling process in natural kidney aging. A Representative images of Oil Red O staining in the 24-month-old and 6-month-old group (n = 6), scale bar = 50 μm; B, C the downregulated protein levels of FAO markers (i.e., PPARα, ACOX1, and CPT1A) and upregulated protein levels of glycolysis markers (i.e., HK2 and PDK1) by western blot, and their semi-quantitative analyses (n = 6); D immunostaining for GLIS1 (red) and PPARα (green), with DAPI (blue) counterstaining by IF staining in the 24-month-old and 6-month-old group (n = 6), scale bar = 50 μm; E lactate levels in the 24-month-old and 6-month-old group (n = 6); F the downregulated protein levels of PPARα, ACOX1, and CPT1A, and up-regulated protein levels of HK2 and PDK1 in the 24-month-old group by IHC assay and their semi-quantitative analyses (n = 6), scale bar = 50 μm. The data are expressed as the mean ± SD of three independent experiments. **P < .01 or ***P < .001 versus the 6-month-old group by Student’s t-test

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Conversely, hexokinase 2 (HK2) and pyruvate dehydrogenase lipoamide kinase isozyme 1 (PDK1), key glycolytic rate-limiting enzymes, were significantly elevated in the 24-month-old group (Fig. 2B, C), as further confirmed by IHC staining (Fig. 2F). The elevated lactate levels in the 24-month-old group confirmed that glucose, rather than fatty acids (FAs), was the primary source of energy in kidney aging (Fig. 2E). These findings demonstrated that kidney aging involved a metabolic shift from the FAO to the glycolysis.

The protective function of GLIS1 in metabolic remodeling from FAO to glycolysis in mouse kidney aging

We further explored whether GLIS1 activation could influence metabolic remodeling in response to kidney aging. Over-expressed GLIS1 was achieved in an accelerated aging mouse model via the injection of AAV-GLIS1. As shown in Fig. 3A, lipid accumulation in the D-gal-treated group was significantly reduced with the introduction of AAV-GLIS1. Furthermore, levels of PPARα, CPT1A, and ACOX1 were markedly reduced in the D-gal-treated group, but significantly increased with AAV-GLIS1 treatment, suggesting that over-expressed GLIS1 enhanced the FAO pathway (Fig. 3B, C, E, F). In terms of glucose utilization, the AAV-GLIS1 group exhibited lower levels of HK2 and PDK1, along with reduced lactate levels in the D-gal-treated group (Fig. 3D). These findings indicated that over-expressed GLIS1 altered metabolic remodeling in kidney aging.

Fig. 3
figure 3

The over-expressed GLIS1 suppressed metabolic remodeling from FAO to glycolysis in the accelerated aging mouse model. A The representative images of mouse kidney tissue in the control, AAV-Vector and AAV-GLIS1 group stained with Oil Red O (n = 6), scale bar = 50 μm; B, C downregulated protein levels of PPARα, ACOX1, and CPT1A in the accelerated aging mouse model were reversed in the presence of AAV-GLIS1, while upregulated protein levels of HK2 and PKD1 in the accelerated aging mouse model were reduced by introducing AAV-GLIS1 (n = 6); D lactate levels in the control, AAV-Vector and AAV-GLIS1 group (n = 6); E the reversed effect of PPARα, ACOX1 and CPT1A levels, as well as HK2 and PDK1 levels in the presence of AAV-GLIS1 by IHC assay, and their semi-quantitative analyses (n = 6), scale bar = 50 μm; F immunostaining for PPARα, ACOX1, CPTA1, HK2, and PDK1 (green), with DAPI (blue) counterstaining by IF staining in accelerated aging mouse model (n = 6), scale bar = 50 μm. The data are expressed as the mean ± SD of three independent experiments. **P < .01 or ***P < .001 versus the AAV-vector group by one-way ANOVA

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The regulatory mechanism of GLIS1 in metabolic remodeling in mouse kidney aging

As depicted in Fig. 4A, lipid accumulation was evident in the siGLIS1 group. The elevated ECAR levels in the siGLIS1 group indicated a preference for glycolysis over FAO in these cells (Fig. 4B, C). Consistently, TG and FFA levels decreased in HK-2 cells with siGLIS1 (Fig. 4G–I). Analysis of the metabolic components in the culture medium revealed significantly higher lactate production and glucose consumption in the siGLIS1 group (Fig. 4D), implying enhanced glycolysis. This was further supported by the reduction of PPARα, CPT1A, and ACOX1, along with the upregulation of HK2 and PDK1 (Fig. 4E, F). Similar trends in GLIS1-driven metabolic remodeling were observed by immunofluorescent (IF) staining (Fig. 4J).

Fig. 4
figure 4

GLIS1 regulated metabolic remodeling from FAO to glycolysis pathway by binding to the PPARα promoter. A Representative images of Oil Red O staining in the control vector and siGLIS1 group (n = 3), scale bar = 50 μm; B, C the ECAR levels after culturing with glucose followed by oligomycin and 2-DG in the control vector and siGLIS1 group, and its semi-quantitative analysis (n = 3); D metabolic component analysis in control and siGLIS1 group (n = 3); E, F downregulated protein levels of GLIS1, PPARα, ACOX1, and CPTA1, and upregulated protein levels of HK2 and PDK1 in siGLIS1 group by western blot, and their semi-quantitative analyses (n = 3); G–I cellular free fatty acid (FFA), triglyceride (TG) and total cholesterol (TC) levels in HK-2 cells in control and siGLIS1 group (n = 3); J immunostaining for PPARα, ACOX1, CPT1A, HK2, and PDK1 (green), with DAPI (blue) counterstaining by IF staining (n = 3), scale bar = 50 μm; K the interaction of PPARα and GLIS1 confirmed by ChIP and PCR assay (n = 3); L the protein levels of FN and HK2 by western blot in HK-2 cells treated with D-gal in the presence of OE-GLIS1, OE-GLIS1 + CPTA1 inhibitor (etomoxir), OE-GLIS1 + PPARα (MK886), and OE-GLIS1 + siACOX1(n = 3). The data are expressed as the mean ± SD of three independent experiments. **P < .01 or ***P < .001 versus the vector group (C, D, F, H, and I), or IgG group (K) by Student’s t-test

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Chromatin immunoprecipitation (ChIP)-PCR assay demonstrated that GLIS1 specifically bound to the promoter region of PPARα in HK-2 cells (Fig. 4K). We also established HK-2 cells with over-expressed GLIS1 in D-gal medium (GLIS1-OE). In D-gal-treated HK-2 cells, HK2 and FN levels significantly decreased in the GLIS1-OE group compared to the control group (vector only) (Fig. 4L). In contrast, the GLIS1-OE group exhibited opposite results, with inhibition of PPARα, ACOX1, and CPT1A, suggesting that the protective effects of GLIS1 were suppressed through FAO inhibition. These findings demonstrated that GLIS1 could regulate PPARα expression by binding to its promoter region, and alleviated cell senescence and renal fibrosis by modulating the balance of FAO and glycolysis.

The downregulated expression of METTL3 in GLIS1 m6A modification

m6A modification levels were found to be downregulated in both natural and accelerated aging models (Additional file 1: Fig. S4A, B). Consequently, the expression levels of m6A-regulated proteins (i.e., METTL3, METTL14, WTAP, FTO, and ALKBH5) were measured in the 24-month-old group. Compared to the 6-month-old group, both mRNA and protein expressions of METTL3 and METTL14 were reduced, while WTAP and FTO expressions were elevated. ALKBH5 showed significantly lower mRNA levels with no effect on its protein level (Fig. 5D and Additional file 1: Fig. S4C–H). Among these, METTL3 and FTO exhibited the most significant differences, but the protein level of GLIS1 was notably reduced in the presence of siMETTL3 (Additional file 1: Fig. S4K and Fig. 5A–C), whereas siFTO had no such effect (Additional file 1: Fig. S5I, J). METTL3 and FTO exhibited the most significant differences, but the protein level of GLIS1 was notably reduced in the presence of siMETTL3 (Additional file 1: Fig. S4K and Fig. 5A–C), not siFTO (Additional file 1: Fig. S5I, J). Additionally, METTL3 protein expression was lower in the 24-month-old group (Fig. 5D). IHC and IF staining confirmed that METTL3 was mainly localized in the cell nucleus and weakly expressed in the 24-month-old group (Fig. 5E–G). Both GLIS1 and METTL3 levels were lower in D-gal-treated HK-2 cells, suggesting a potential correlation in kidney aging (Fig. 5H). Furthermore, the RNA immunoprecipitation PCR (RIP-PCR) assay confirmed the direct interaction between GLIS1 mRNA and METTL3 (Fig. 5I, J). Interestingly, the m6A level of GLIS1 was significantly lower in the presence of siMETTL3, although siMETTL3 did not affect the mRNA level of GLIS1 (Fig. 5K, L). It was demonstrated that the dysregulation of m6A modification of GLIS1 was attributed to the abnormal expression of METTL3 in kidney aging.

Fig. 5
figure 5

METTL3 directly interacted with GLIS1 in kidney aging. A The mRNA level of METTL3 in the vector and siMETTL3 group in HK-2 cells by RT-qPCR (n = 3); B, C protein level of GLIS1 by western blot in the vector and siMETTL3 group in HK-2 cells, and its semi-quantitative analysis (n = 3); D protein levels of METTL3, METTL14, and WTAP by western blot in the 24-month-old and 6-month-old group (n = 6); E, F the expression of METTL3 in the 24-month-old and 6-month-old group by IHC assay, and its semi-quantitative analysis (n = 6), scale bar = 50 μm; G immunostaining for METTL3 (green), with DAPI (blue) counterstaining by IF staining in the 24-month-old and 6-month-old group (n = 6), scale bar = 50 μm; H immunostaining for METTL3 (green), GLIS1 (red), with DAPI (blue) counterstaining by IF staining in HK-2 cells (n = 3), scale bar = 50 μm; I, J METTL3 RIP and RT-PCR confirmed the interaction between METTL3 and GLIS1 mRNA, and its semi-quantitative analysis (n = 3); K the lower m6A level of GLIS1 in siMETTL3 group compared with the vector group in HK-2 cells by using MeRIP-qPCR (n = 3); L the mRNA level of GLIS1 in the vector and siMETTL3 group in HK-2 cells by RT-qPCR (n = 3); M mutations at the two putative m6A sites in GLIS1 (A to G); N m6A level of GLIS1 in HK-2 cells with co-expression of siMETTL3 and GLIS1-WT/Muts by MeRIP-qPCR (n = 3); O the mRNA level of GLIS1 in the vector and GLIS1-Mut3 group by RT-qPCR (n = 3). The data are expressed as the mean ± SD of three independent experiments. **P < .01 or ***P < .001 versus the vector group (A, C, K) or 6-month-old group (E) or IgG group (J) by Student’s t-test; ##P < .01, ###P < .001 versus the vector-WT group, ++P < .01, +++P < .001 versus the siMETTL3-WT group, **P < .01 versus vector group by two way-ANOVA (N)

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Based on the enriched and specific m6A peaks of GLIS1 identified in SRAMP (Fig. 5M, upper panel), two putative m6A sites of GLIS1 were mutated from A to G, referred to as: GLIS1-Mut1, GLIS1-Mut2 (one potential m6A site), and GLIS1-Mut3 (two potential m6A sites) (Fig. 5M, lower panel). The levels of GLIS1 m6A modification in HK-2 cells with siMETTL3 and/or GLIS1-mutant genes were investigated using MeRIP-qPCR. As hypothesized, down-regulation of METTL3 reduced the m6A modifications of GLIS1-WT, GLIS1-Mut1, and GLIS1-Mut2 in HK-2 cells compared to the control group. However, the m6A modification and mRNA levels of GLIS1-Mut3, containing two m6A site mutations, did not show significant changes with siMETTL3 (Fig. 5N, O). This indicated that the m6A site mutation reduced the binding efficacy between GLIS1 mRNA and METTL3.

METTL3 alleviated cell senescence and renal fibrosis in mouse kidney aging

Considering the direct interaction between METTL3 and GLIS1, we examined the regulatory function of METTL3 in accelerated aged mouse models by administering AAV-METTL3. Over-expressed METTL3 increased the protein level of GLIS1 without affecting its mRNA level. Furthermore, the enrichment of GLIS1 m6A modification was enhanced by over-expressed METTL3 (Fig. 6A–D). Consistent with results from 24-month-old mice, the expression of METTL14 increased with METTL3 over-expression, although this increase was less pronounced compared to that of METTL3 (Fig. 6A, B). the downregulation of FN and P16INK4A, confirmed by western blot, IHC, and Masson staining (Fig. 6A, B, E), demonstrated that METTL3 affected cell senescence and renal fibrotic lesions by the regulation of GLIS1. To assess FAO and glycolysis levels, quadruple staining of PPARα (Red), CPT1A (Green), HK2 (Pink), and PDK1 (Yellow) was performed (Fig. 6F). The AAV-METTL3 group exhibited significantly higher fluorescent intensities of PPARα and CPT1A, whereas the levels of HK2 and PDK1 were down-regulated.

Fig. 6
figure 6

METTL3 ameliorated age-related renal fibrosis in accelerated aging mouse model. A, B Downregulated protein levels of METTL3, METTL14, and GLIS1 in an accelerated aging mouse model were reversed in the presence of AAV-METTL3, and the upregulated protein levels of P16INK4A and FN by western blot in the accelerated aging mouse model were reduced by introducing AAV-METTL3 (n = 6); C the enriched m6A modification of GLIS1 in the control, AAV-Vector and AAV-METTL3 group by MeRIP-qPCR assay (n = 6); D GLIS1 mRNA levels in the control, AAV-Vector, and AAV-METTL3 group detected by RT-qPCR (n = 5); E protein levels of GLIS1, P16INK4A, and FN in the control, AAV-Vector and AAV-METTL3 group by Masson staining and IHC assay and their semi-quantitative analyses (n = 6), scale bar = 50 μm; F immunostaining for PPARα (red) and CPT1A (green), HK2 (pink), and PDK1 (yellow), with DAPI (blue) counterstaining by IF staining in the control, AAV-Vector, and AAV-METTL3 group (n = 6), scale bar = 50 μm. The data are expressed as the mean ± SD of three independent experiments. **P < .01 or ***P < .001 versus the AAV-vector group by one-way ANOVA

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Moreover, the ablation of METTL3 resulted in significantly lower levels of GLIS1 and FAO-related proteins. In contrast, higher protein levels of HK2 and PDK1 indicated the enhanced glycolysis in HK-2 cells with siMETTL3 (Fig. 7A). Similar findings were confirmed by double IF staining of GLIS1 and the associated metabolic remodeling markers (Fig. 7C). In HK2 cells with siMETTL3, increased levels of FN, α-SMA, and P16 INK4A, along with more lipid accumulation, were observed (Fig. 7A, B). In summary, the m6A modification of GLIS1 via METTL3 regulation was essential for the down-regulation of GLIS1, thereby accelerating cell senescence and renal fibrosis in kidney aging.

Fig. 7
figure 7

The ablation of METTL3 triggered metabolic remodeling and aggravated cell senescence renal fibrosis. A Protein levels of GLIS1, PPARα, ACOX1, CPT1A, HK2, PDK1, FN, α-SMA, and P16INK4A by western blot in the vector and siMETTL3 group, and their semi-quantitative analyses (n = 3); B representative images of Oil Red O staining in the vector and siMETTL3 group (n = 3), scale bar = 50 μm; C double immunostaining for GLS1 and PPARα, ACOX1, CPT1A, HK2, PDK1, and α-SMA by IF staining (n = 3) scale bar = 50 μm. The data are expressed as the mean ± SD of three independent experiments. **P < .01 or ***P < .001 versus the vector group by Student’s t-test

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The translation effect of YTHDF1 by binding GLIS1 mRNA in mouse kidney aging

The m6A-modified RNA is recognized by “reader” proteins, which influence downstream biological functions. As shown in Fig. S4L (Additional file 1), when RNA synthesis was inhibited by actinomycin D in HK-2 cells, no differences in GLIS1 mRNA levels were observed between the siMETTL3 and control groups, suggesting that METTL3 regulated GLIS1 protein expression without affecting its mRNA. YTHDF1 and YTHDF3, two of the most well-characterized m6A readers, can modulate mRNA stability, translation, and degradation [22, 23]. No significant differences on YTHDF3 levels were observed between the 6-month-old and 24-month-old groups (Additional file 1: Fig. S5A), while YTHDF1 was primarily localized in the cell cytoplasm and weakly expressed in the 24-month-old group (Fig. 8A, G). IF staining and western blot assays further confirmed the significantly lower expression of YTHDF1 in the 24-month-old group (Fig. 8B–D).

Fig. 8
figure 8

YTHDF1 identified with m6A-meditated GLIS1 mRNA and participated the translation process of GLIS1 protein. A The expression of YTHDF1 in the 24-month-old and 6-month-old group by IHC assay, and its semi-quantitative analysis (n = 6), scale bar = 50 μm; B immunostaining for YTHDF1 (green), with DAPI (blue) counterstaining by IF staining in the 24-month-old and 6-month-old group (n = 6), scale bar = 50 μm; C, D protein level of YTHDF1 in the 24-month-old and 6-month-old group by western blot, and its semi-quantitative analysis (n = 6); E mRNA level of YTHDF1 by RT-qPCR in HK-2 cells within vector or siYTHDF1 (n = 3); F protein level of GLIS1 in HK-2 cells within vector or siYTHDF1, and its semi-quantitative analysis (n = 3); G double immunostaining for GLIS1 (red) and YTHDF1 (green) by IF staining in HK-2 cells (n = 3), scale bar = 50 μm; H, I RIP and RT-PCR assays confirmed the interaction between YTHDF1 and GLIS1 mRNA, and its semi-quantitative analysis (n = 3); J the expression of GLIS1 with RPL22-FLAG label by ribosomal immunoprecipitation in HK-2 cells (n = 3); K the mRNA level of GLIS1 by RT-qPCR in HK-2 cells within vector or siYTHDF1 (n = 3); L, M relative luciferase activity of the GLIS1-WT or GLIS1-Mut 3′UTR luciferase reporter in the vector and siMETTL3 group, n = 3. The data are expressed as the mean ± SD of three independent experiments. **P < .01 or ***P < .001 versus the 6-month-old group, or vector group, or IgG group by Student’s t-test

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To assess the stability of METTL3-induced GLIS1 mRNA in the presence of YTHDF1, no significant differences in GLIS1 mRNA levels were found at any time point between the siYTHDF1 and vector groups, indicating that YTHDF1 did not affect GLIS1 mRNA stability (Additional file 1: Fig. S5B, C). However, the protein level of GLIS1 was significantly lower in the siYTHDF1 group (Additional file 1: Fig. S5B, Fig. 8E, F), suggesting that altered m6A methylation via YTHDF1 reduced GLIS1 protein expression without affecting its mRNA. To investigate whether protein degradation contributed to the downregulation of GLIS1, we treated cells with MG132, a proteasome inhibitor, in the presence of siYTHDF1. Both vector and siYTHDF1 groups exhibited the same GLIS1 protein levels, regardless of MG132 treatment, indicating YTHDF1 regulated GLIS1 protein independently of the protein degradation pathway (Additional file 1: Fig. S5D).

Furthermore, silencing YTHDF1 resulted in decreased GLIS1 expression in the presence of METTL3 overexpression in HK-2 cells (Additional file 1: Fig. S5E). This suggested that YTHDF1 might regulate protein translation rather than its stability or post-translation modification through a METTL3-dependent pathway. The specific interaction between YTHDF1 and GLIS1 mRNA was confirmed by RIP-PCR assay (Fig. 8H, I). A ribosome immunoprecipitation assay using HK-2 cells expressing Flag-tagged RPL22 under YTHDF1 modulation revealed significantly lower GLIS1 mRNA ribosome occupancy in the siYTHDF1 group compared to the vector group (Fig. 8J, K), indicating that YTHDF1 promoted the translation process of GLIS1. To further verify whether YTHDF1 could directly bind to the m6A modification sites of GLIS1 mRNA, a luciferase reporter assay was conducted (Fig. 8L, M). Our results demonstrated that YTHDF1 directly recognized the methylated GLIS1 transcripts, promoting the translation of methylated GLIS1 mRNA in HK-2 cells via an m6A-YTHDF1-dependent mechanism.

Discussion

The age-related decline in renal mass is primarily attributed to changes in the tubule-interstitial compartment rather than glomerular alterations. This is because the capillaries surrounding the renal tubules are less dense than those around the glomeruli, limiting oxygen supply to the tubules and making them more susceptible to pathological stimuli (27, 28). Age-related tubular dysfunction may offer potential diagnostic and therapeutic targets for elderly patients at risk of AKI and CKD. Our study demonstrated that GLIS1, a protective gene regulated by abnormal m6A modification, was closely associated with kidney aging, and could reduce renal fibrosis by regulating energy metabolism.

Under physiological conditions, TECs primarily rely on the FAO pathway for energy supply by transporting extracellular FAs into cells. Lipid metabolism is essential for PTCs, as FAO generates a large amount of ATP to support cell metabolism. However, inflammation and lipid accumulation resulting from FAO disorders are commonly observed in kidney-related diseases [24,25,26]. Our findings indicated that the downregulation of FAO-related proteins led to abnormal lipid accumulation in the renal tubular epithelial region during aging, resulting in severe fibrosis. Glycolysis, another key metabolic pathway, involves increased glucose uptake and preferential lactate production, and it is primarily involved in regulating the tumor microenvironment. The shift in fuel-source preference from FAs to glucose impairs FAO in PTCs, as observed in diabetes or sustained hyperglycemia [26,27,28,29]. Our research demonstrated that FAO deficiency led to excessive lipid droplet accumulation inside PTCs, triggering lipotoxicity and renal fibrosis, which were hallmarks of kidney aging. Additionally, the preference of glycolysis not only directly affects ECM synthesis, including amino acid synthesis, hydroxylation, glycosylation, and ECM secretion, but also enhances the activation of fibroblasts that primarily produce ECM, exacerbating renal fibrosis [30,31,32]. Thus, it can be concluded that impaired FAO pathways and increased glucose utilization contributed to age-related renal fibrosis.

The upstream genetic mutations or signaling mechanisms related to changes in energy substrate preference likely contribute to metabolic remodeling [33, 34]. We previously demonstrated that GLIS1 was primarily located but weakly expressed in renal tubules during aging. Over-expression of GLIS1 suppressed senescence-associated proteins, reduced β-galactosidase deposition, and alleviated renal fibrosis. This study demonstrated a positive correlation between GLIS1 and the FAO pathway, suggesting that energy metabolism was highly involved in GLIS1-driven kidney aging, consistent with the potential reprogramming effect of GLIS1 in somatic cells. Additionally, PPARα, a target gene, was down-regulated in HK-2 cells with siGLIS1. ChIP-PCR assay identified that GLIS1 could directly bind to the PPARα regulatory region. PPARα, which is highly expressed in TECs, is a ligand-activated nuclear transcription factor regulating the expression of proteins involved in FA uptake and oxidation [35,36,37,38]. Both natural and accelerated aging models exhibited down-regulation of GLIS1, accompanied by lower levels of FAO markers. Apart from PPARα, the downstream genes CPT1A and ACOX1, which are rate-limiting enzymes in the peroxisomal and mitochondrial FAO pathways, promote inflammatory reactions [39,40,41]. A significantly lower level of FN was observed with over-expressed GLIS1. However, the inhibition of PPARα increased FN level even with over-expressed GLIS1, suggesting PPARα was a key regulatory factor in GLIS1-driven kidney aging. Furthermore, the downregulation of FN upon inhibition of CPT1A and ACOX1 indicated that the GLIS1-driven PPARα-dependent pathway induced renal fibrosis through the peroxisomal and mitochondrial FAO pathways.

Methylation of m6A is the most important modification of eukaryotic mRNA, playing crucial roles in numerous diseases [42, 43]. METTL3, a key component of the m6A methyltransferase complex, is responsible for catalyzing the methylation reaction and has been reported in kidney diseases [44, 45]. For example, METTL3 enhances the m6A methylation of TAB3 mRNA in an IGF2BP2-dependent manner, preventing mRNA degradation and accelerating AKI progression [44]. METTL3 also interacts with DGCR8, positively affecting the maturation of miR-873-5p, acting as a protective role against colistin-induced oxidative stress and apoptosis [46]. Given the abnormal expression of methylated GLIS1 in aging kidneys, our findings suggested that the downregulation of METTL3 reduced m6A methylation of GLIS1 during kidney aging. Due to the specific interaction between METTL3 and GLIS1, the ablation of METTL3 simultaneously decreased both the methylation and protein levels of GLIS1, accelerating cell senescence and renal fibrosis through metabolic remodeling from the FAO to glycolysis. Thus, we concluded that METTL3-induced GLIS1 m6A modification was essential for regulating GLIS1 protein expression in kidney aging. METTL3 is the only catalytic component, while METTL14 primarily maintains the integrity of the complex and facilitates substrate RNA binding. Our results showed the decreased level of METTL14 in D-gal mice was reversed by over-expressed METTL3, indicating the biological functions of the METTL3-METTL14 complex in kidney aging. Future studies will focus on the roles of METTL3 and/or METTL14 during kidney aging.

The YTH family, acting as "reader proteins," consists of three members (YTHDF1-3) that recognize methylated mRNA and affect its functions. We demonstrated that YTHDF1 was weakly expressed in aged kidneys and specifically interacted with GLIS1 mRNA. According to research by Xiong et al., the YTHDF1 recognizes the abnormal m6A modification of JAK1 mediated by METTL3, enhances JAK1 protein translation efficiency and subsequent phosphorylation of STAT3 in tumor-infiltrating myeloid cells [47, 48]. Similarly, the translation function of YTHDF1 in our study was identified in m6A-regulated GLIS1 mRNA. siYTHDF1 suppressed GLIS1 expression in the ribosome, without affecting mRNA stability or post-translation modification. It can be concluded that METTL3/YTHDF1-induced GLIS1 m6A modification regulated the protein level of GLIS1, rather than its mRNA level.

Conclusion

We proposed the significant role of the METTL3/YTHDF1-GLIS1 axis in kidney aging and explored the mechanism of GLIS1-driven metabolic remodeling. Abnormal methylation of GLIS1, regulated by METTL3, reduced its protein expression by impairing the translation process in a YTHDF1-dependent manner. GLIS1-driven metabolic remodeling inhibited the FAO pathway by targeting PPARα and promoted the glycolysis pathway, leading to cell senescence and renal fibrosis.

Methods

Sample preparation

Human specimens

A total of 20 kidney tissue samples were collected from participants diagnosed with renal tumors at the First Affiliated Hospital of China Medical University. Exclusion criteria included the absence of prior radiotherapy or chemotherapy before nephrectomy, as well as the presence of systemic dysfunctions [49]. Informed consent was obtained from all participants prior to the study commenced. Given the increased risk of end-stage renal disease and drug-induced nephrotoxicity in individuals over 65 years old [50], participants were divided into two groups based on age (young: < 65 years old; aged: ≥ 65 years old). The clinical characteristics of the participants are presented in Additional file 2: Table S1.

Animal experimental design

All animal experiments were conducted in the SPF (Specific Pathogen-Free) animal laboratory of China Medical University following Guidelines outlined in the NIH guide for the Care and Use of Laboratory Animals. C57BL/6 J male mice were sourced from Charles River Laboratories and housed in a controlled environment with a standard light/dark cycle, along with unrestricted access to water and a chow diet. Tissue samples from the natural aging model were collected at 6 months (n = 8) and 24 months (n = 8), referred to as the 6-month-old and 24-month-old groups, respectively.

The accelerated aging model was developed by administrating D-gal into C57BL/6 mice, thereby simulating the natural aging process in rodents. D-gal activates senescence-related signal pathways by reacting with free amines of amino acids, forming advanced glycation end products and resulting in the formation of advanced glycation end products and the subsequent induction of oxidative stress and inflammation. The experimental strategy was illustrated in Fig. 2A. Briefly, mice received subcutaneous injections of D-gal at 500 mg kg − 1 day − 1 from 8 to 16 weeks. At 9 weeks, adeno-associated viruses (Syngentech, Beijing, China) containing GLIS1 expression vector (AAV2/9-GLIS1) or METTL3 expression vector (AAV2/9-METTL3) were injected into the renal pelvis of D-gal-treated mice. A total volume of 100 μL pAAV2/9-GLIS1-FLAG (NM_147221.2) or pAAV2/9-METTL3-FLAG and an empty vector (1 × 1012 virus genome/ml) were injected into the renal pelvis of mice. Three groups were established as follows: (1) control group (n = 8); (2) D-gal treated group with AAV-GLIS1/AAV-METTL3 (n = 8); (3) D-gal treated group with AAV-vector (n = 8).

Cell culture and treatment

The human kidney TEC line (HK-2) was obtained from the American Type Culture Collection and cultured in DMEM/F12 medium supplemented with 10% fetal bovine serum (FBS) and 1% antibiotic–antimycotic at 37 °C. The culture medium was replaced every three days until the cells reached 90% confluence. To simulate kidney aging, HK-2 cells were treated with D-gal (100 mM) for 72 h, creating the D-gal-treated HK-2 group. Alternatively, HK-2 cells were treated with 25 μM MK-886 or 40 μM etomoxir for 24 h to investigate the roles of peroxisome proliferator-activated receptor alpha (PPARα) and carnitine palmitoyltransferase 1A (CPT1A).

The human over-expressed GLIS1 gene was amplified and subcloned into the eukaryotic expression vector pcDNA3.1. Specific target sequences for GLIS1 siRNA, siFTO, siMETTL3, siYTHDF1, and siACOX1 (Syngentech, China) were transfected into target cells using Lipofectamine 3000 (Invitrogen) according to the manufacturer’s instructions. A scrambled sequence served as the control. The siRNA sequences are listed in Additional file 2: Table S2.

Histological and immunohistochemical (IHC) staining

Human and mouse kidney tissues were cut into 3 μm-thick sections. These samples were stained with Masson and periodic acid-Schiff (PAS) staining and observed under a microscope. For semi-quantitative analysis, the glomerulosclerosis index (GSI) was recorded on a scale from 0 to 4 (0: no lesion; 1: mild sclerosis, 0–25% of the glomerulus affected; 2: moderate sclerosis, 25–50% of the glomerulus affected; 3: severe sclerosis, 50–75% of the glomerulus affected) [1, 2]. Masson staining was used to assess interstitial fibrosis in kidney tissues, with morphometric analysis with scores as follows: 0: < 5% affected interstitial area; 1: 5–25% affected interstitial area; 2: 25–50% affected interstitial area; 3: > 50% affected interstitial area.

IHC was performed according to the manufacturer’s instructions. Specific primary antibodies targeting GLIS1 (Proteintech 23,138–1-AP), P16INK4A (Thermo Fisher Scientific Cat# MA5-17,142), γ-H2AX (Proteintech 10,856–1-AP), FN (Abcam ab2413), α-SMA (Abcam ab5694), PPARα (Novus NB300-537), ACOX1 (Novus NBP1-80950), CPT1A (Abcam ab234111), HK2 (Sigma SAB2108077), PDK1 (Sigma SAB4502160), METTL3 (Abcam ab195352), and YTHDF1 (Abcam ab252346) were incubated overnight at 4 °C. The sections were then incubated with secondary antibodies for 1 h at room temperature. Afterward, the samples were stained with diaminobenzidine (DAB) and counterstained with hematoxylin, followed by visualization using a microscope.

Transmission electron microscope (TEM) observation

Serial Sects. (80 nm) of the samples were prepared using an ultramicrotome and stained with uranyl acetate and lead citrate. After rinsing and vacuum-drying at room temperature, the ultrastructure of the samples, particularly foot process effacement and GBM, were observed using TEM. For semi-quantitative analysis, ImageJ software was employed to measure the thickness of GBM.

Quantification of m6A modifications

m6A modification was quantified using the EpiQuik m6A RNA Methylation Quantification Kit (Colorimetric). Total RNA was isolated from human kidney tissues using TRIzol solution, and the concentration was determined with a spectrophotometer. A total of 200 ng of RNA was coated on the assay well at 37 °C for 90 min, followed by the addition of capture antibody solution and detection antibody solution. m6A methylation levels were quantified at a wavelength of 450 nm.

Western blot

Protein lysates from kidney tissues and cultured cells were prepared, electrophoresed, and transferred to PVDF membranes. The membranes were blocked with 5% non-fat milk for 1 h at room temperature, followed by overnight incubation with primary antibodies: GLIS1 (Proteintech 23,138–1-AP), P16INK4A (Thermo Fisher Scientific MA5-17,142), γ-H2AX (Proteintech 10,856–1-AP), FN (Abcam ab2413), α-SMA (Abcam ab5694), collagen type I (COL I) (Abcam ab260043), PPARα (Novus NB300-537), ACOX1 (Abcam ab184032), CPT1A (Abcam ab234111), HK2 (Abcam ab209847), PDK1 (Abcam ab110025), METTL3 (Abcam ab195352), METTL14 (Sigma HPA038002), WTAP (Proteintech 10,200–1-AP), FTO (Proteintech 27,226–1-AP), ALKBH5 (Proteintech 16,837–1-AP), YTHDF3 (Proteintech 25,537–1-AP), and YTHDF1 (Abcam ab252346) overnight at 4 °C. Afterward, a secondary antibody was applied for 1 h at room temperature, and the blots were visualized using enhanced chemiluminescence (ECL).

m6A-mRNA epitranscriptomic microarray analysis

Human m6A epitranscriptomic microarray and mRNA microarray analyses were performed based on Arraystar’s standard protocols. Total RNA was immunoprecipitated with an anti-m6A antibody. The immunoprecipitated (IP) and supernatant (Sup) RNA were labeled with Cy5 and Cy3, respectively. The RNAs were then hybridized to the Arraystar Human mRNA Epitranscriptomic Microarray (8 × 60 K, Arraystar). Raw intensities of IP and Sup were normalized using the average of log2-scaled Spike-in RNA intensities. The raw data have been uploaded to the Gene Expression Omnibus database under the accession number GSE232249.

RT-qPCR

The extracted RNAs from kidney tissues or cultured cells were reversely transcribed, and RT-qPCR was performed using Takara TB Green® Premix Ex TaqTM II (Takara, RR820). The primers are listed in Additional file 2: Table S3.

RNA-sequencing and analysis for differentially expressed transcripts

Total RNA was extracted using TRIzol (Invitrogen, Carlsbad, CA, USA). RNA sequencing analysis was technically supported by Aksomics Biotech CO. LTD (Shanghai, China). Differentially expressed genes were identified based on raw p values and fold change. Genes were considered significantly differentially expressed if the corrected p value was < 0.05 and the absolute fold change was > 2 in multiple tests.

Renal senescence-associated β-galactosidase (SA-β-gal) staining

Frozen Sects. (8 μm) were prepared for SA-β-Gal staining using the Senescence β-Galactosidase Staining Kit (Cell Signaling Technology, 9860).

Immunofluorescent (IF) staining

Paraffin-embedded kidney sections were deparaffinized and rehydrated. HK-2 cells cultured on coverslips were fixed with cold methanol/acetone for 10 min at room temperature. After blocking with 10% donkey serum for 60 min, the slides were immunostained overnight at 4 °C with primary antibodies: GLIS1 (Active Motif, 61,801), α-SMA (Proteintech, 67,735–1-Ig), COL I (Novus, NB600-408), FN (Abcam, ab2413), PPARα (Novus, NB300-537), ACOX1 (Abcam, ab184032), CPT1A (Proteintech, 15,184–1-AP), HK2 (Abcam, ab209847), PDK1 (Abcam, ab110025), METTL3 (Abcam, ab195352), and YTHDF1 (Abcam, ab252346), then incubated with a secondary antibody for 2 h. Cell nuclei were counterstained with DAPI (Sigma-Aldrich) for 10 min. Images were obtained using a confocal microscope.

Oil Red O staining

Oil Red O staining was performed on frozen kidney tissue Sects. (8 μm) and HK-2 cells cultured on coverslips (Sigma, O0625). The prepared samples were rinsed with distilled water and isopropanol, stained in Oil Red O working solution for 15 min, rinsed with 60% isopropanol and distilled water, and then counterstained with hematoxylin. Images were captured using a microscope.

Lactate and glucose measurement

Lactate concentration in kidney tissue and cell supernatant was measured using the Lactate Colorimetric Assay Kit (Biovision, K627-100) at a wavelength of 450 nm. Glucose concentration in the cell supernatant was detected using the Glucose Colorimetric/Fluorometric Assay Kit (Biovision, K606-100) at a wavelength of 450 nm.

Extracellular acidification rate (ECAR) measurement

The ECAR, representing the glycolysis ratio, was measured using a Seahorse Bioscience extracellular flux analyzer. Cells were cultured in XF24 V7 cell culture microplates (Seahorse Bioscience) with 10 mM glucose for 2 h at 37 °C, followed by the addition of the ATP synthase inhibitor oligomycin or the glycolysis inhibitor 2-deoxyglucose (2-DG). The results were analyzed using Wave software.

Assessment of cellular lipids

The levels of triglycerides (TG) (Cayman Chemical, 10,010,303), cholesterol (TC) (Cayman Chemical, 10,009,779), and free fatty acids (FFA) (Cayman Chemical, CAC-700310–96) in HK-2 cells were measured using commercial kits according to the manufacturer’s instructions.

Chromatin immunoprecipitation (ChIP) assay

ChIP was performed using the Chromatin Immunoprecipitation Kit (Millipore, 17–371). Fragmented chromatin from fixed cells was incubated with a GLIS1 antibody (Santa, Sc-365857) and protein G magnetic beads. DNA released from the precipitates was analyzed by PCR. The primer sequences specific to the GLIS1 binding region within the PPARα promoter region were as follows: PPARα promoter forward: 5′- TACGTGACCACTCTGCACAC-3′ and reverse: 5′- CCTCCGGGCTCAAAGACATT-3′. IgG and ddH2O served as negative controls, while RNA polymerase II and GAPDH were used as positive controls.

RNA immunoprecipitation (RIP) assay

RIP was conducted using the Magna RIP™ RNA-Binding Protein Immunoprecipitation Kit (Millipore, 17–701). Magnetic beads coated with 5 mg of specific antibodies against METTL3 (Proteintech, 10,573–1-AP), YTHDF1 (Proteintech, 17,479–1-AP), or rabbit IgG (Millipore) were incubated with cell lysates overnight. RNA–protein complexes were treated with proteinase K digestion buffer to isolate the immunoprecipitated RNA. The relative interaction between GLIS1 mRNA and METTL3/YTHDF1 was determined by PCR. The Primers for RIP-PCR were listed in Additional file 2: Table S4.

Methylated RNA immunoprecipitation (MeRIP)-qPCR

Poly(A) RNA was purified and fragmented using RNA fragmentation reagents (Thermo, AM8740). A fraction (1/10) of the RNA was reserved as the input control. Anti-m6A antibody (Abcam, ab151230) or mouse IgG was incubated with Protein A/G magnetic Beads, mixed with fragmented poly(A) RNA and 1 × poly(A) RNA RNase inhibitor-supplemented IP buffer, and rotated at 4 °C for 2 h. The m6A-containing RNAs were eluted and purified using an RNA purification column. RT-qPCR was then used to determine the enrichment of methylated mRNAs.

Luciferase reporter and mutation assay

GLIS1 mutants were generated using the Mut Express II Fast Mutagenesis Kit V2 (Vazyme). HK-2 cells were transfected with 250 ng of the 3′ UTR luciferase reporter plasmid (Promega). Luciferase activity was measured using the Dual Glo Luciferase Assay kit (Promega) as previously described [51].

RNA stability and protein decay assays

HK-2 cells, with or without siMETTL3 and siYTHDF1, were treated with 5 μg/mL actinomycin D (MedChemExpress, HY-17559). Total RNA was isolated at specified time points (0, 1, 2, 4, and 6 h), and the mRNA levels of GLIS1 were measured using RT-qPCR. To inhibit the proteasome, HK-2 cells, with or without siYTHDF1, were treated with 1.25 μM MG132 for 24 h, and GLIS1 protein levels were detected by western blot.

Ribosomal immunoprecipitation

The RPL22-Flag construct (Sino Biological, HG16861-NF) was transfected into HK-2 cells with vector or siYTHDF1. Protein lysates from vector control and siYTHDF1 cells were incubated overnight with 5 μg anti-FLAG antibody or IgG (control). RT-qPCR analysis was performed to determine the transcriptional changes of GLIS1.

Statistical analysis

All quantitative data were obtained from independent experiments with triplicate repeats and expressed as the mean ± SD. Statistical analysis was performed using SPSS 15.0 software, with two-tailed unpaired Student’s t-tests for comparisons between two groups and one-way ANOVA followed by Bonferroni test for multiple comparisons. A P value of less than 0.05 was considered statistically significant: *P < 0.05, ** P < 0.01, *** P < 0.001; NS indicates no significance.

Data availability

All data generated or analyzed during this study are included in this published article, its supplementary information files, and publicly available repositories. Sequencing datasets are available in the NCBI Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/). The epitranscriptomic data are uploaded to the Gene Expression Omnibus database under accession number: GSE232249 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE232249). RNA-sequence datasets are available according to accession number: GSE237055 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE237055).

Abbreviations

m6A:

N6-methyladenosine

FAO:

Fatty acid oxidation

AKI:

Acute kidney disease

CKD:

Chronic kidney disease

TECs:

Tubular epithelial cells

ATP:

Adenosine triphosphate

GLIS1:

Gli-like transcription factor 1

METTL3-METTL14:

Methyltransferase-like 3-methyltransferase-like 14

FTO:

Fat mass and obesity-associated protein

ALKBH5:

AlkB homolog 5

PAS:

Periodic acid Schiff

ECM:

Extracellular matrix

GESA:

Gene set enrichment analysis

PPARα:

Peroxisome proliferator-activated receptor alpha

HK2:

Hexokinase 2

PDK1:

Pyruvate dehydrogenase lipoamide kinase isozyme 1

References

  1. Fang EF, Scheibye-Knudsen M, Jahn HJ, Li J, Ling L, Guo H, Zhu X, Preedy V, Lu H, Bohr VA, et al. A research agenda for aging in China in the 21st century. Ageing Res Rev. 2015;24(Pt B):197–205.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Chen Y, Yang Y, Liu Z, He L. Adiponectin promotes repair of renal tubular epithelial cells by regulating mitochondrial biogenesis and function. Metabolism. 2022;128: 154959.

    Article  PubMed  Google Scholar 

  3. Lausecker F, Lennon R, Randles MJ. The kidney matrisome in health, aging, and disease. Kidney Int. 2022;102(5):1000–12.

    Article  PubMed  Google Scholar 

  4. Fang Y, Gong AY, Haller ST, Dworkin LD, Liu Z, Gong R. The ageing kidney: molecular mechanisms and clinical implications. Ageing Res Rev. 2020;63: 101151.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Franzin R, Stasi A, Sallustio F, Bruno S, Merlotti G, Quaglia M, Grandaliano G, Pontrelli P, Thurman JM, Camussi G, et al. Extracellular vesicles derived from patients with antibody-mediated rejection induce tubular senescence and endothelial to mesenchymal transition in renal cells. Am J Transplant. 2022;22(9):2139–57.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Li L, Xiang T, Guo J, Guo F, Wu Y, Feng H, Liu J, Tao S, Fu P, Ma L. Inhibition of ACSS2-mediated histone crotonylation alleviates kidney fibrosis via IL-1β-dependent macrophage activation and tubular cell senescence. Nat Commun. 2024;15(1):3200.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Liu X, Zhan P, Zhang Y, Jin H, Wang Y, Yang Y, Wang Z, Wang X, Xu Q, Zhen J, et al. Lysosomal-Associated Protein Transmembrane 5, Tubular Senescence, and Progression of CKD. J Am Soc Nephrol. 2024;35(12):1655–70.

    Article  PubMed  Google Scholar 

  8. Hsu PP, Sabatini DM. Cancer cell metabolism: Warburg and beyond. Cell. 2008;134(5):703–7.

    Article  PubMed  Google Scholar 

  9. Zhu Z, Hu J, Chen Z, Feng J, Yang X, Liang W, Ding G. Transition of acute kidney injury to chronic kidney disease: role of metabolic reprogramming. Metabolism. 2022;131: 155194.

    Article  PubMed  Google Scholar 

  10. Chen H, You R, Guo J, Zhou W, Chew G, Devapragash N, Loh JZ, Gesualdo L, Li Y, Jiang Y, et al. WWP2 regulates renal fibrosis and the metabolic reprogramming of profibrotic myofibroblasts. J Am Soc Nephrol. 2024;35(6):696–718.

    Article  PubMed  Google Scholar 

  11. Abbad L, Détrait M, Kavvadas P, Bergonnier D, Melis L, Laudette M, Migeon T, Verpont MC, Lucas A, Chatziantoniou C, et al. Signaling through cAMP-Epac1 induces metabolic reprogramming to protect podocytes in glomerulonephritis. Kidney Int. 2024;106(3):450–69.

    Article  PubMed  Google Scholar 

  12. Molitoris BA, Sandoval RM, Yadav SPS, Wagner MC. Albumin uptake and processing by the proximal tubule: physiological, pathological, and therapeutic implications. Physiol Rev. 2022;102(4):1625–67.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Nakagawa T, Johnson RJ, Andres-Hernando A, Roncal-Jimenez C, Sanchez-Lozada LG, Tolan DR, Lanaspa MA. Fructose production and metabolism in the kidney. J Am Soc Nephrol. 2020;31(5):898–906.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Xu L, Wang J, Yu H, Mei H, He P, Wang M, Liu Y, Fan Q, Chen Y, Li Y, et al. GLIS1 alleviates cell senescence and renal fibrosis through PGC1-α mediated mitochondrial quality control in kidney aging. Free Radic Biol Med. 2023;209(Pt 1):171–84.

    PubMed  Google Scholar 

  15. Oerum S, Meynier V, Catala M, Tisné C. A comprehensive review of m6A/m6Am RNA methyltransferase structures. Nucleic Acids Res. 2021;49(13):7239–55.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Jiang X, Liu B, Nie Z, Duan L, Xiong Q, Jin Z, Yang C, Chen Y. The role of m6A modification in the biological functions and diseases. Signal Transduct Target Ther. 2021;6(1):74.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Wang Y, Wang Y, Patel H, Chen J, Wang J, Chen ZS, Wang H. Epigenetic modification of m(6)A regulator proteins in cancer. Mol Cancer. 2023;22(1):102.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Chen J, Xu C, Yang K, Gao R, Cao Y, Liang L, Chen S, Xu S, Rong R, Wang J, et al. Inhibition of ALKBH5 attenuates I/R-induced renal injury in male mice by promoting Ccl28 m6A modification and increasing Treg recruitment. Nat Commun. 2023;14(1):1161.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Qu H, Liu X, Zhu J, Xiong X, Li L, He Q, Wang Y, Yang G, Zhang L, Yang Q, et al. Dock5 deficiency promotes proteinuric kidney diseases via modulating podocyte lipid metabolism. Adv Sci (Weinh). 2024;11(11): e2306365.

    Article  PubMed  Google Scholar 

  20. Tsai YC, Hsieh TH, Liao YR, Tsai MT, Lin TP, Lee DY, Park J, Kim D, Susztak K, Yang SF, et al. METTL3-mediated N 6 -methyladenosine mRNA modification and cGAS-STING pathway activity in kidney fibrosis. J Am Soc Nephrol. 2024;35(10):1312–29.

    Article  PubMed  Google Scholar 

  21. Wagner KD, Wagner N. The senescence markers p16INK4A, p14ARF/p19ARF, and p21 in organ development and homeostasis. Cells. 2022;11(12):1966.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Zou Z, Sepich-Poore C, Zhou X, Wei J, He C. The mechanism underlying redundant functions of the YTHDF proteins. Genome Biol. 2023;24(1):17.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Burns MWN, Kohler JJ. O-GlcNAc regulates YTHDF1 and YTHDF3 activity. Nat Cell Biol. 2023;25(11):1570–2.

    Article  PubMed  Google Scholar 

  24. Onodera T, Wang MY, Rutkowski JM, Deja S, Chen S, Balzer MS, Kim DS, Sun X, An YA, Field BC, et al. Endogenous renal adiponectin drives gluconeogenesis through enhancing pyruvate and fatty acid utilization. Nat Commun. 2023;14(1):6531.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Hammoud S, Ivanova A, Osaki Y, Funk S, Yang H, Viquez O, Delgado R, Lu D, Phillips Mignemi M, Tonello J, et al. Tubular CPT1A deletion minimally affects aging and chronic kidney injury. JCI Insight. 2024;9(6):e171961.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Guo X, Wen S, Wang J, Zeng X, Yu H, Chen Y, Zhu X, Xu L. Senolytic combination of dasatinib and quercetin attenuates renal damage in diabetic kidney disease. Phytomedicine. 2024;130: 155705.

    Article  PubMed  Google Scholar 

  27. Hou Y, Tan E, Shi H, Ren X, Wan X, Wu W, Chen Y, Niu H, Zhu G, Li J, et al. Mitochondrial oxidative damage reprograms lipid metabolism of renal tubular epithelial cells in the diabetic kidney. Cell Mol Life Sci. 2024;81(1):23.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Hu H, Li W, Hao Y, Peng Z, Zou Z, Liang W. Baicalin ameliorates renal fibrosis by upregulating CPT1α-mediated fatty acid oxidation in diabetic kidney disease. Phytomedicine. 2024;122: 155162.

    Article  PubMed  Google Scholar 

  29. Lin S, Wang L, Jia Y, Sun Y, Qiao P, Quan Y, Liu J, Hu H, Yang B, Zhou H. Lipin-1 deficiency deteriorates defect of fatty acid β-oxidation and lipid-related kidney damage in diabetic kidney disease. Transl Res. 2024;266:1–15.

    Article  PubMed  Google Scholar 

  30. Jiang A, Liu J, Wang Y, Zhang C. cGAS-STING signaling pathway promotes hypoxia-induced renal fibrosis by regulating PFKFB3-mediated glycolysis. Free Radic Biol Med. 2023;208:516–29.

    Article  PubMed  Google Scholar 

  31. Chen Y, Bai X, Chen J, Huang M, Hong Q, Ouyang Q, Sun X, Zhang Y, Liu J, Wang X, et al. Pyruvate kinase M2 regulates kidney fibrosis through pericyte glycolysis during the progression from acute kidney injury to chronic kidney disease. Cell Prolif. 2024;57(2): e13548.

    Article  PubMed  Google Scholar 

  32. Wang Y, Li H, Jiang S, Fu D, Lu X, Lu M, Li Y, Luo D, Wu K, Xu Y, et al. The glycolytic enzyme PFKFB3 drives kidney fibrosis through promoting histone lactylation-mediated NF-κB family activation. Kidney Int. 2024;106(2):226–40.

    Article  PubMed  Google Scholar 

  33. Liu C, Xiong Q, Li Q, Lin W, Jiang S, Zhang D, Wang Y, Duan X, Gong P, Kang N. CHD7 regulates bone-fat balance by suppressing PPAR-γ signaling. Nat Commun. 2022;13(1):1989.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Qiang L, Wang L, Kon N, Zhao W, Lee S, Zhang Y, Rosenbaum M, Zhao Y, Gu W, Farmer SR, et al. Brown remodeling of white adipose tissue by SirT1-dependent deacetylation of Pparγ. Cell. 2012;150(3):620–32.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Liu L, Ning X, Wei L, Zhou Y, Zhao L, Ma F, Bai M, Yang X, Wang D, Sun S. Twist1 downregulation of PGC-1α decreases fatty acid oxidation in tubular epithelial cells, leading to kidney fibrosis. Theranostics. 2022;12(8):3758–75.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Chung KW, Lee EK, Lee MK, Oh GT, Yu BP, Chung HY. Impairment of PPARα and the fatty acid oxidation pathway aggravates renal fibrosis during aging. J Am Soc Nephrol. 2018;29(4):1223–37.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Li Y, Xiong Z, Yan W, Gao E, Cheng H, Wu G, Liu Y, Zhang L, Li C, Wang S, et al. Branched chain amino acids exacerbate myocardial ischemia/reperfusion vulnerability via enhancing GCN2/ATF6/PPAR-α pathway-dependent fatty acid oxidation. Theranostics. 2020;10(12):5623–40.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Zheng ZY, Jiang T, Huang ZF, Chu B, Gu J, Zhao X, Liu H, Fan J, Yu LP, Jiang SH, et al. Fatty acids derived from apoptotic chondrocytes fuel macrophages FAO through MSR1 for facilitating BMSCs osteogenic differentiation. Redox Biol. 2022;53: 102326.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Yin X, Zeng W, Wu B, Wang L, Wang Z, Tian H, Wang L, Jiang Y, Clay R, Wei X, et al. PPARα inhibition overcomes tumor-derived exosomal lipid-induced dendritic cell dysfunction. Cell Rep. 2020;33(3): 108278.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Wagner N, Wagner KD. Recent Insights into the Role of PPARs in Disease. Cells. 2023;12(12):1572.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Shen S, Faouzi S, Souquere S, Roy S, Routier E, Libenciuc C, André F, Pierron G, Scoazec JY, Robert C. Melanoma persister cells are tolerant to BRAF/MEK inhibitors via ACOX1-mediated fatty acid oxidation. Cell Rep. 2020;33(8): 108421.

    Article  PubMed  Google Scholar 

  42. Wang C, Hou X, Guan Q, Zhou H, Zhou L, Liu L, Liu J, Li F, Li W, Liu H. RNA modification in cardiovascular disease: implications for therapeutic interventions. Signal Transduct Target Ther. 2023;8(1):412.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Liu WW, Zheng SQ, Li T, Fei YF, Wang C, Zhang S, Wang F, Jiang GM, Wang H. RNA modifications in cellular metabolism: implications for metabolism-targeted therapy and immunotherapy. Signal Transduct Target Ther. 2024;9(1):70.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Wang JN, Wang F, Ke J, Li Z, Xu CH, Yang Q, Chen X, He XY, He Y, Suo XG, et al. Inhibition of METTL3 attenuates renal injury and inflammation by alleviating TAB3 m6A modifications via IGF2BP2-dependent mechanisms. Sci Transl Med. 2022;14(640):eabk270.

    Article  Google Scholar 

  45. Jiang L, Liu X, Hu X, Gao L, Zeng H, Wang X, Huang Y, Zhu W, Wang J, Wen J, et al. METTL3-mediated m(6)A modification of TIMP2 mRNA promotes podocyte injury in diabetic nephropathy. Mol Ther. 2022;30(4):1721–40.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Wang J, Ishfaq M, Xu L, Xia C, Chen C, Li J. METTL3/m(6)A/miRNA-873-5p attenuated oxidative stress and apoptosis in colistin-induced kidney injury by modulating Keap1/Nrf2 pathway. Front Pharmacol. 2019;10:517.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Xiong J, He J, Zhu J, Pan J, Liao W, Ye H, Wang H, Song Y, Du Y, Cui B, et al. Lactylation-driven METTL3-mediated RNA m(6)A modification promotes immunosuppression of tumor-infiltrating myeloid cells. Mol Cell. 2022;82(9):1660-1677.e1610.

    Article  PubMed  Google Scholar 

  48. Sun Y, Gong W, Zhang S. METTL3 promotes colorectal cancer progression through activating JAK1/STAT3 signaling pathway. Cell Death Dis. 2023;14(11):765.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Shi M, Yang S, Zhu X, Sun D, Sun D, Jiang X, Zhang C, Wang L. The RAGE/STAT5/autophagy axis regulates senescence in mesangial cells. Cell Signal. 2019;62: 109334.

    Article  PubMed  Google Scholar 

  50. Hommos MS, Glassock RJ, Rule AD. Structural and functional changes in human kidneys with healthy aging. J Am Soc Nephrol. 2017;28(10):2838–44.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Yang Z, Cai Z, Yang C, Luo Z, Bao X. ALKBH5 regulates STAT3 activity to affect the proliferation and tumorigenicity of osteosarcoma via an m6A-YTHDF2-dependent manner. EBioMedicine. 2022;80: 104019.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank Aksomics Biotech Co., Ltd. (Shanghai, China) that technically support the epitranscriptomic data analysis.

Funding

This research was supported partly by the National Natural Science Foundation of China (No.81800642), partly by the China Postdoctoral Science Foundation (2021M703608), and partly by Doctoral Scientific Research Foundation of Liaoning Province (20180540113).

Author information

Author notes

  1. Li Xu, Shuo Chen, and Qiuling Fan contributed equally to this work.

Authors and Affiliations

  1. Department of Laboratory Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524003, China

    Li Xu

  2. Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China

    Shuo Chen

  3. Department of Gynecologic Oncology Research Office, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangzhou, 510150, China

    Shuo Chen

  4. Department of Nephrology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China

    Qiuling Fan

  5. Department of Nephrology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510245, Guangdong, China

    Yonghong Zhu

  6. Department of Nephrology, The First Hospital of China Medical University, Shenyang, 110001, China

    Hang Mei & Ying Chen

  7. Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, 110004, China

    Jiao Wang

  8. Department of Urology, The First Hospital of China Medical University, Shenyang, 110001, China

    Hongyuan Yu

  9. Department of Orthodontics, School and Hospital of Stomatology, Liaoning Provincial Key Laboratory of Oral Diseases, China Medical University, Shenyang, 110001, China

    Fan Liu

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  1. Li Xu
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Contributions

L.F., C.S., and X.L. led the project. F.Q.L. and L.F. designed and conceived the study. Y.H.Y, W.J., and C.S. drafted the manuscript. X.L. and M.H. performed data analysis. X.L. and L.F. revised the manuscript. C.Y., Z.Y.H., and Y.H.Y performed the functional experiments. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Hongyuan Yu, Ying Chen or Fan Liu.

Ethics declarations

Ethics approval and consent to participate

The protocols for this research involving human tissues and animal tissues were approved by the Research Ethics Committee of China Medical University (Reference number: [2020] 120 and KT2020024, respectively).

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Not applicable.

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The authors declare that they have no competing interests.

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Supplementary Information

12915_2024_2100_MOESM1_ESM.docx

Additional file 1: Fig. S1. The GSI and interstitial fibrosis score in the H/control and H/aged group. (A) mRNA level of GLIS1 in the H/aged and H/control group by RT-qPCR, (n = 10); (B-D) Protein levels of γH2AX and GLIS1 in the H/aged and H/control group by IHC assay, and their semi-quantitative analyses (n = 6); The data are expressed as the mean ± SD of three independent experiments. *P < 0.05, ***P < 0.001 versus the H/control group by Student’s t-test. Fig. S2. The simultaneous down-regulation of GLIS1 and E-cadherin in mouse kidney aging. (Immunostaining for GLIS1 (red) and PGC1-α (green), with DAPI (blue) counterstaining by IF staining in the 24-month-old and 6-month-old group (n = 6), scale bar = 50 μm). Fig. S3. FAO pathway was correlated to GLIS1 by RNA sequence analysis. (A) The annotation of FAO pathway via gene set enrichment analysis (GSEA); (B) Differentially expressed genes for FAO regulation in Heap map. Fig. S4. The mRNA levels of m6A-regulated proteins in mouse kidney aging. (A) The enriched m6A modification of GLIS1 in the 24-month-old and 6-month-old group by MeRIP-qPCR assay (n = 5); (B) The enriched m6A modification of GLIS1 in the control and D-gal-treated group by MeRIP-qPCR assay (n = 5); (C) Protein level of FTO and ALKBH5 by western blot in the 24-month-old and 6-month-old group (n = 6); (D-H) mRNA levels of METTL3, METTL14, WTAP, FTO and ALKBH5 using RT-qPCR in the 24-month-old and 6-month-old group (n = 5); (I) mRNA level of FTO using RT-qPCR in HK-2 cells within vector or siFTO (n = 3); (J) Protein level of GLIS1 by western blot in HK-2 cells within vector or siFTO, and its semi-quantitative analysis (n = 3); (K) Protein level of METTL3 by western blot in HK-2 cells treated with control (vector only) or siMETTL3, and its semi-quantitative analysis (n = 3); (L) mRNA level of GLIS1 in control (vector only) and siMETTL3 groups treated with actinomycin D by RT-qPCR, (n = 3). The data are expressed as the mean ± SD of three independent experiments. *P < 0.05, **P < 0.01, ***P < 0.001 versus the 6-month-old group (A, D-H), or **P < 0.01 versus control group (B), or vector group (I and K) by Student’s t-test. Fig. S5. YTHDF1 regulated m6A modification of GLIS1 without affecting mRNA stability and protein degradation. (A) Protein level of YTHDF1 by western blot in the 24-month-old and 6-month-old group (n = 6); (B) Protein level of YTHDF1 by western blot in HK-2 cells treated with control (vector only) and siYTHDF1, and its semi-quantitative analysis (n = 3); (C) mRNA levels of GLIS1 in HK-2 cells treated with actinomycin D and vector or siYTHDF1 by RT-qPCR (n = 5); (D) Protein levels of GLIS1 in HK-2 cells (vector or siYTHDF1) treated with or without MG132 by western blot, and their semi-quantitative analyses (n = 3); (E) Protein level of GLIS1 by western blot in HK-2 cells treated with D-gal with over-expressed METTL3 (METTL3 OE) or siYTHDF1, and its semi-quantitative analysis, (n = 3). The data are expressed as the mean ± SD of three independent experiments. ***P < 0.001 versus the vector group by Student’s t-test.

12915_2024_2100_MOESM2_ESM.docx

Additional file 2: Table S1 Clinical characteristics of participants. Table S2 The sequences of siRNA. Table S3 Primers for RT-qPCR. Table S4 Primers for RIP-PCR.

Additional file 3. Unedited gel.

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Xu, L., Chen, S., Fan, Q. et al. N6-methyladenosine regulates metabolic remodeling in kidney aging through transcriptional regulator GLIS1. BMC Biol 22, 302 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12915-024-02100-y

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BMC Biology

ISSN: 1741-7007

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