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m6A modification-tuned sphingolipid metabolism regulates postnatal liver development in male mice

Nature Metabolism volume 5, pages 842–860 (2023)Cite this article

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Abstract

Different organs undergo distinct transcriptional, epigenetic and physiological alterations that guarantee their functional maturation after birth. However, the roles of epitranscriptomic machineries in these processes have remained elusive. Here we demonstrate that expression of RNA methyltransferase enzymes Mettl3 and Mettl14 gradually declines during postnatal liver development in male mice. Liver-specific Mettl3 deficiency causes hepatocyte hypertrophy, liver injury and growth retardation. Transcriptomic and N6-methyl-adenosine (m6A) profiling identify the neutral sphingomyelinase, Smpd3, as a target of Mettl3. Decreased decay of Smpd3 transcripts due to Mettl3 deficiency results in sphingolipid metabolism rewiring, characterized by toxic ceramide accumulation and leading to mitochondrial damage and elevated endoplasmic reticulum stress. Pharmacological Smpd3 inhibition, Smpd3 knockdown or Sgms1 overexpression that counteracts Smpd3 can ameliorate the abnormality of Mettl3-deficent liver. Our findings demonstrate that Mettl3–N6-methyl-adenosine fine-tunes sphingolipid metabolism, highlighting the pivotal role of an epitranscriptomic machinery in coordination of organ growth and the timing of functional maturation during postnatal liver development.

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Fig. 1: Mettl3 is highly expressed in embryonic and neonatal livers and declines during postnatal liver development.
Fig. 2: Hepatic Mettl3 deficiency induces hepatocyte hypertrophy, liver injury and growth retardation during postnatal development.
Fig. 3: Postnatal-onset hepatocyte-specific deletion of Mettl3 did not cause liver injury.
Fig. 4: Mettl3 deficiency leads to sphingolipid metabolic reprogramming in Mettl3ΔHep liver.
Fig. 5: Mettl3 regulates Smpd3 mRNA decay through m6A modification.
Fig. 6: Hepatic ceramide, mitochondrial damage and endoplasmic reticulum levels are increased in Mettl3ΔHep liver.
Fig. 7: Pharmacological inhibition of Smpd3 attenuates Mettl3 deficiency-induced ceramide accumulation and liver injury.
Fig. 8: Smpd3 knockdown alleviates ceramide accumulation and liver injury caused by liver Mettl3 deficiency.

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Data availability

The transcriptomic dataset of livers from C57BL/6J mice across 12 time points, from late embryonic stage (E17.5) to adulthood (day 60), were obtained from the National Center for Biotechnology Information GEO database (accession no. GSE103322). RNA-seq and Me–RIP–seq data reported in this study have been deposited in the GEO database under accession no. GSE197799. Source data are provided with this paper.

Code availability

All codes and scripts used for association studies are available on request.

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Acknowledgements

This study was supported by the National Key Research and Development Program of China to S.L. and D.Y. (no. 2020YFA0804400); the National Natural Science Foundation of China (nos. 82270621, 81802799, 82071854, 81971936, 32100590, 32270820 and 32000857); Shandong Provincial Natural Science Foundation, China (nos. ZR2019BH002, ZR2020QH038, ZR2020MH269, ZR2021QB012 and ZR2022MH150); Jiangsu Provincial Natural Science Foundation, China (no. BK20180222); Funds for Youth Interdisciplinary and Innovation Research Groups of Shandong University (nos. 2020QNQT003 and 2020QNQT009); The Fundamental Research Funds for the Central Universities (nos. 2022JC008 and 2042021gf0013); Hubei Province’s Outstanding Medical Academic Leader Program; Basic and Clinical Medical Research Joint Fund of Zhongnan Hospital, Wuhan University; and Taishan Scholars Programme of Shandong Province. M.H. was supported by an ERC consolidator grant and Rainer Hoenig Stiftung. We thank S. Huang (Center for Reproductive Medicine, Shandong University) and the Core Facility of Advanced Medical Research Institute of Shandong University for technical support.

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Author notes

  1. These authors contributed equally: Shiguan Wang, Shanze Chen, Jianfeng Sun, Pan Han.

Authors and Affiliations

  1. Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China

    Shiguan Wang, Jianfeng Sun, Pan Han, Bowen Xu, Xinying Li, Peng Zhang, Ping Mi & Detian Yuan

  2. Department of Pulmonary and Critical Care Medicine, Shenzhen Institute of Respiratory Diseases, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, China

    Shanze Chen

  3. State Key Laboratory of Virology and Hubei Province Key Laboratory of Allergy and Immunology, Hubei Jiangxia Laboratory, Institute of Medical Virology, TaiKang Center for Life and Medical Sciences, TaiKang Medical School, Wuhan University, Wuhan, China

    Youquan Zhong, Zaichao Xu & Yuchen Xia

  4. Institute of Pathology and Pathophysiology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China

    Cuijuan Zhang

  5. Department of Gastroenterology, Qilu Hospital, Shandong University, Jinan, China

    Lixiang Li & Shiyang Li

  6. Shandong Provincial Clinical Research Center for Digestive Disease, Jinan, China

    Lixiang Li & Detian Yuan

  7. Pediatric Research Institute, Children’s Hospital Affiliated to Shandong University, Jinan, China

    Haiyan Zhang

  8. Advanced Medical Research Institute, Shandong University, Jinan, China

    Shiyang Li

  9. Division of Chronic Inflammation and Cancer, German Cancer Research Center, Heidelberg, Germany

    Mathias Heikenwalder

  10. The M3 Research Institute, Eberhard Karls University Tübingen, Tübingen, Germany

    Mathias Heikenwalder

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Contributions

D.Y., M.H., S.L. and Y.X. designed experiments, interpreted data and wrote the manuscript. S.W. and S.C. contributed to experimental design and performed in vivo animal studies. S.W., P.H., J.S., B.X., X.L., L.L. and H.Z. performed in vitro experiments. Y.Z. and Z.X. performed AAV8 packaging. P.Z., P.M. and C.Z. contributed to histological analysis. All authors provided input and reviewed the manuscript.

Corresponding authors

Correspondence to Yuchen Xia, Shiyang Li, Mathias Heikenwalder or Detian Yuan.

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Nature Metabolism thanks B. Finck, W. Holland and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Isabella Samuelson, in collaboration with the Nature Metabolism team.

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Extended data

Extended Data Fig. 1 Gene expression patterns in mouse liver development.

a, Eight k-means clusters showing different expression trends in murine livers at different stages of development determined by the normalized gene expression using the Z-score transformation method. b, The average temporal expression patterns of genes in the eight clusters. c, Heatmap of enriched GO and KEGG terms colored by p-values.

Extended Data Fig. 2 Dynamic changes of Mettl3 expression during postnatal liver development.

a, qRT-PCR of livers from WT C57BL/6J mice at different ages for indicated genes (n = 4 for Afp, Apoe, Fabp1, Fasn, Ppara, Fbp1 and Pck1; n = 6 for Ythdf2, Ythdf3, Alkbh5 and Ythdf1). Data are shown in mean ± SEM. b, IHC of Mettl3 in livers from WT C57BL/6J mice at different ages as indicated. Scale bar, 20 μm.

Source data

Extended Data Fig. 3 Hepatic Mettl3 deficiency induces hepatocyte hypertrophy and liver injury during postnatal development.

a, Schematic representation of genomic Mettl3 (top), floxed Mettl3 and deleted Mettl3 (bottom) alleles. b, H&E staining of liver sections from 5-week-old WT and Mettl3ΔHep mice (n = 3 biological independent samples). Scale bar, 50 μm. c, H&E staining of liver sections from 4-week-old WT and Mettl3ΔHep mice (n = 3 biological independent samples). Scale bar, 100 μm. d, p-Akt levels in livers from WT and Mettl3ΔHep mice in response to fasting and refeeding (n = 3 biological independent samples). e, IHC of CD45, CD3 and B220 in livers from WT and Mettl3ΔHep mice. Scale bar, 20 μm. (n = 3 biological independent samples). f, qRT-PCR of livers from WT (n = 5) and Mettl3ΔHep (n = 5) mice for indicated genes. g, Timeline of AAV8-induced Cre expression in adult Mettl3fl/fl mice and immunoblotting for Mettl3 showing the Knock-out effect. h, IHC of Mettl3 in livers from AAV8-Mock and AAV8-Cre Mettl3fl/fl mice. Black arrowheads, hepatocytes; Red arrowheads, non-parenchymal cells. n = 3 biological independent samples. Scale bar, 50 μm. i, Representative picture of AAV8-Mock and AAV8-Cre Mettl3fl/fl mice 2 months after i.v. injection (n = 3 biological independent samples). Scale bar, 5cm. j, Serum ALT and AST in AAV8-Mock (n = 3) and AAV8-Cre Mettl3fl/fl mice (n = 3). k, Gross appearance of livers in AAV8-Mock and AAV8-Cre Mettl3fl/fl mice 2 months after i.v. injection (n = 3 biological independent samples). The scale bar represents 1 cm. l, Representative H&E staining of livers from AAV8-Mock and AAV8-Cre Mettl3fl/fl mice (n = 3 biological independent samples). Scale bar, 50 μm. Data are shown in mean ± SEM; ns, not significant, *p < 0.05, **p < 0.01, ***p < 0.001 by unpaired two-tailed Student’s t test.

Source data

Extended Data Fig. 4 Livers of AAV8-Cre mice show no signs of damage.

Representative H&E staining of livers from AAV8-Mock, AAV8-Cre and Mettl3ΔHep mice at different time points (n = 3 biological independent samples). Scale bar, 20 μm.

Extended Data Fig. 5 meRIP and mRNA stability assay for sphingolipid metabolism-related genes.

a, The m6A motif and m6A modification for sphingolipid metabolism-related genes. b, mRNA stability analysis in primary hepatocytes isolated from Mettl3ΔHep (n = 3) versus WT (n = 3) mice treated with actinomycin D (5 μg/mL) for the indicated times. The residual RNAs were normalized to the value of time 0. Data are shown in mean ± SEM; ns, not significant, *p < 0.05, **p < 0.01 by two-way ANOVA statistics (b).

Source data

Extended Data Fig. 6 METTL3 regulates SMPD3 expression in HEK293T cells and H1 ESCs.

a, The GGAC motif for human SMPD3. b, Immunoblotting for METTL3 and SMPD3 in HEK293T cells. c, Immunoblotting for METTL3 and SMPD3 in H1 ESCs. d, m6A enrichment of the SMPD3 mRNAs in sgREN (n = 4) versus sgMETTL3 clone #1 (n = 4) and clone #5 (n = 4) in H1 cells by m6A-RIP-qPCR. Data are shown in mean ± SEM; ****p < 0.0001 by unpaired two-tailed Student’s t test.

Source data

Extended Data Fig. 7 Mettl3 deficiency in hepatocytes causes mitochondrial damage and ER stress.

a, Membrane fluidity of primary hepatocytes from WT and Mettl3ΔHep mice determined by TMA-DPH (n = 7 biological independent samples). b, Electron microscopy of WT and Mettl3ΔHep livers. Arrowheads indicate the perinuclear space. Scale bar, 5 μm. c, Mitochondrial membrane potential assessment of primiary hepatocytes from WT and Mettl3ΔHep mice 24 hours after isolation with the mitochondria-specific probe JC-1. Red and green fluorescence indicate J-aggregates and JC-1 monomers, respectively (n = 3 biological independent samples). Scale bar, 100 μm. d, Mitochondrial membrane potential assessment of primiary hepatocytes from WT and Mettl3ΔHep mice 48 hours after isolation with the mitochondria-specific probe JC-1. Red and green fluorescence indicate J-aggregates and JC-1 monomers, respectively (n = 3 biological independent samples). Scale bar, 100 μm. **p < 0.01 by unpaired two-tailed Student’s t test.

Source data

Extended Data Fig. 8 Inhibition of ceramide synthesis by GW4869 ameliorated mitochondrial dysfunction, apoptosis and hepatocyte injury in Mettl3ΔHep mice.

a, H&E of WT and Mettl3ΔHep livers treated with vehicle or different inhibitors as indicated (n = 3 biological independent samples). Scale bar, 100 μm. b, MDA, Cyt-c, BIP and p-eIF2α IHC in Mettl3ΔHep livers treated with vehicle versus GW4869 (n = 4 biological independent samples). Scale bar, 50 μm. c-g, IHC of cl-Casp3 (c), TUNEL (d), CD45 (e), F480 (f) and Ki67 (g) in Mettl3ΔHep livers treated with vehicle versus GW4869 (n = 4 biological independent samples). Scale bar, 50 μm. h, qRT-PCR of Mettl3ΔHep livers treated with vehicle versus GW4869 for indicated genes (n = 4 biological independent samples). Data are shown in mean ± SEM; ns, not significant, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by unpaired two-tailed Student’s t test.

Source data

Extended Data Fig. 9 The liver damage in Mettl3ΔHep mice were reduced by Smpd3 knockdown.

a,b, Silencing efficiency of siRNAs targeting Smpd3 was detected by qRT-PCR (n = 4) (a) and immunoblotting (b) in mouse liver cell line AML12. c, qRT-PCR detection of sphingolipid metabolism-related genes in livers from WT (n = 4) and Mettl3ΔHep mice treated with (n = 4) or siSmpd3 (n = 5). d, IHC of MDA, p-eIF2α, CD45 and Epcam from siNC- or siSmpd3-treated livers. (n = 3 biological independent samples). e, Quantification for Atf3, Bax, Mettl3, cl-Casp3 and PCNA proteins in Fig. 8k (n = 3). f, qRT-PCR of livers from WT (n = 4) and Mettl3ΔHep mice treated with siNC (n = 4) or siSmpd3 (n = 5) for indicated genes. Data are shown in mean ± SEM; ns, not significant, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by unpaired two-tailed Student’s t test.

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Extended Data Fig. 10 Sgms1 overexpression attenuated liver injury in Mettl3ΔHep mice.

a, Timeline of AAV8-Sgms1 and AAV8-EGFP treatment in Mettl3ΔHep mice. b, qRT-PCR was used to detect the expression of Sgms1 in AAV-EGFP (n = 5) and AAV-Sgms1 (n = 4) livers. c, Representative IHC of Sgms1 in AAV-EGFP and AAV-Sgms1 livers. Scale bar, 20 μm. d, Mouse body weight gain over time post AAV8 injection (n = 4 for each group). e, Liver injury was assessed by serum AST and ALT from mice in (b) (n = 4/5/4). f, Representative liver macroscopy. Scale bar, 1 cm. g, Representative H&E staining of livers from mice in (f). Scale bar, 50 μm. h, Western blot of liver lysates from mice in (b) for indicated proteins. i, Quantification for the indicated proteins in (h) (n = 3). j, qRT-PCR of livers from mice in (b) for indicated genes (n = 4/5/4). k, IHC of cl-Casp3, Cyt-c, CD45 and Ki67 from AAV-EGFP and AAV-Sgms1 livers, and quantification for cl-Casp3 and Ki67 staining (n = 5/4). Scale bar, 20 μm. l, p-eIF2a, MDA, BIP, Epcam and CK19 IHC in livers from Mettl3ΔHep mice injected with AAV-EGFP or AAV-Sgms1. Data are shown in mean ± SEM; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by unpaired two-tailed Student’s t test (b, d, e, I, j and k) or by two-way ANOVA statistics (d).

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Supplementary information

Reporting Summary

Supplementary Table 1

Downregulating genes for functional enrichment analysis and network construction.

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Upregulating genes for functional enrichment analysis and network construction.

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Neonatal-enriched genes for functional enrichment analysis and network construction.

Supplementary Table 4

Primers for qPCR.

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Wang, S., Chen, S., Sun, J. et al. m6A modification-tuned sphingolipid metabolism regulates postnatal liver development in male mice. Nat Metab 5, 842–860 (2023). https://doi.org/10.1038/s42255-023-00808-9

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